rfq number 04-02 (c19) · site #4 s.r. 0040, segment 0260 & 0261 (both directions): five-lane...

FIN 05-0599766SAP #200063

Prepared for Pennsylvania Department of Transportation Bureau of Planning and Research 400 North Street 6th Floor East Harrisburg, PA 17120

RFQ Number 04-02 (C19) Traffic Data Collection Methodologies

Final Report

April 2006

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EXECUTIVE SUMMARY

The purpose of this research was to field-test portable and permanently-installed non-intrusivetraffic data collection equipment.

Field Testing of Equipment in a Portable Setup

As specified by the Department, the four non-intrusive traffic counters tested in a portable setupwere as follows:

! RTMS by EIS (Microwave)! SAS-1 by Smartek (Acoustic)! Smart Sensor by Wavetronix (Microwave)! TIRTL by Control Specialists (Infrared)

Four sites were selected in the Uniontown, Pennsylvania area. The primary objective of the siteselection was to provide a cross-section of roadside environments for equipment setup. Asecondary objective was to select sites near in-pavement traffic counting stations operated byPennDOT. PennDOT operates in-pavement counting stations that are both short-term (STIP),and permanent (ATR). The four sites were as follows:

Site #1: S.R. 0119, Segment 0470 (Northbound Only): Freeway - Single Direction (STIPSite)

Site #2: S.R. 0040, Segment 0160 (Both Directions): Two-Lane Highway - ATR Site

Site #3: S.R. 0119, Segment 0470 & 0471 (Both Directions): Freeway - Both Directions(STIP Site)

Site #4 S.R. 0040, Segment 0260 & 0261 (Both Directions): Five-Lane Suburban Arterial

Note that Site #1 and Site #3 are in the same location, however, Site #1 testing included only thenorthbound lanes, while Site #3 testing included the monitoring of both directions simultaneouslywith a single sensor.

The test was conducted over the course of two days, September 14 and 15, 2005. The equipmentwas set up at each site by vendor representatives. Vendors were given approximately two hoursto set up, and data collection at each site was four hours in duration. The following tableprovides a summary of the results for each sensor.

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Summary of Field Testing

Site #(Dir)

Smart Sensor SAS-1 TIRTL RTMS

APD % 4-Hr % APD % 4-Hr % APD % 4-Hr % APD % 4-Hr %

1 (NB) 6% 5.8% 1% 1.0% 1% 0.2% 6% 4.1%

2 (EB) 4% 3.7% 2% 0.7% 1% 0.0% 3% 1.3%

2 (WB) 2% 0.5% 20% 20.4% 1% 0.2% 25% 24.9%

3 (NB) 2% 1.4% 1% 0.8% 19% 18.5% 2% 1.5%

3 (SB) 2% 0.9% 3% 1.0% 26% 26.0% 1% 0.1%

4 (EB) 2% 1.2% 3% 1.1% 25% 25.7% 2% 0.2%

4 (WB) 3% 1.1% 5% 5.0% 15% 14.9% 43% 40.6%

Average 3% 2.1% 5% 4.3% 13% 12.2% 12% 10.4%

Note that APD = Absolute Percent Difference, which is computed as follows:

|Vs - Vm|APD = ------------ x 100%

Vm

where:

APD = Absolute Percent Difference (%)Vs = Volume from the sensor or ATR / STIP (vehicles)Vm = Volume from the manual count (vehicles)

APD was computed for the total volume for each 15-minute interval and averaged across the 16time periods in each four-hour test. These data are presented in the columns labeled “APD %.” It was also computed for the total volume in the four-hour test period. These data are presentedin the columns labeled “4-Hr %.”

Additionally, the ATR at S.R. 0040 and the STIP at S.R. 0119 provided counts that consistentlymatched the manual counts. The highest mean APD for either was 4.9%, which wasencountered at S.R. 0040, where some error was expected due to the distance between the ATRand the test site. Truck classification data were not provided for the STIP, however, at the ATR,only the TIRTL was in closer agreement with the manually-determined traffic composition.

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Compared to the Minnesota Guidestar research, the microwave sensors performed about thesame in the freeway environments, while the acoustic sensor matched the manual counts at thePennsylvania freeway sites at a higher rate than it did in Minnesota.

In the non-freeway environments, the Smart Sensor performed about the same as it did in thePennsylvania and Minnesota freeway environments, while the RTMS and SAS-1 did not matchthe manual counts as closely in non-freeway environments.

The results for the TIRTL matched the Minnesota research relatively closely when spanning two-lanes, however, its rate of matching the manual counts in the four and five-lane test sections wasmuch lower than the Minnesota research.

Field Testing of Equipment in a Permanent Setup

For testing the non-intrusive technologies in a permanent setup, six Mobility Technologies(traffic.com) sites in the Pittsburgh and Philadelphia area were selected for a quality assurancecheck. The sample was comprised of two microwave (RTMS X2) sensors each in thePhiladelphia and Pittsburgh areas, and two acoustic (SAS-1) sensors in the Philadelphia area. Ateach site, three hours of traffic volume and classification data were manually collected forcomparison to the sensor data. At the microwave sensor sites, the classification scheme wassimply to differentiate between trucks and passenger vehicles. At the acoustic sensor sites, theclassification scheme was to differentiate between passenger vehicles, single-unit trucks, andtractor-trailer trucks.

The six sites were as follows:

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Traffic.comStation ID

Sensor Location Direction Sensor Type

Philadelphia Sites

7188* S.R. 0422, across from the WB Off-Ramp toTrooper Road

EB microwave

7128 S.R. 0202, 0.5 miles north of S.R. 0029interchange

NB microwave

7193 S.R. 0476, 0.2 miles south of Exit 19 (ChemicalRoad)

SB acoustic

7124 S.R. 0476, 0.6 miles north of S.R. 0076 SB acoustic

Pittsburgh Sites

7089 S.R. 0279, 1.25 miles south of the GreentreeInterchange

NB microwave

7087 S.R. 0376, 345-ft west of the Squirrel HillTunnels

EB microwave

*Indicates site was next to a PennDOT STIP site.

Both the microwave and acoustic sensors demonstrated the ability to provide accurate trafficvolume counts. The acoustic sensor performed very well at the S.R. 0476 site near ChemicalRoad, having differed from the manual counts by less than 1% on the three-hour volume, andreporting a vehicle composition that matched the manual counts very closely. The microwavesensors at S.R. 0376, S.R. 0422 and S.R. 0202 demonstrated conformance with the manualcounts to within 5%, although the under-classifying of trucks was prevalent throughout all of themicrowave sites. Of the six sites, four provided good counts. The S.R. 0279 site was rejected asan outlier because the sensor was not set up to monitor all of the lanes. The S.R. 0476 site nearS.R. 0076 was rejected because of an extreme unexplained disparity between the manual countsand the sensor counts.

At the S.R. 0422 Eastbound site, the microwave sensor matched the manual counts closer thanthe PennDOT STIP by a margin of 2.2%. This was sufficient to detect a statistically significantdifference between the STIP and the microwave sensor in matching the manual counts.

There was no statistically significant difference between the best performing acoustic sensor andbest performing microwave sensor. Similarly, there was no statistically significant differencebetween volumes collected by microwave sensors from the near and far side lanes. This may bean indication that there was no difference in reality.

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Conclusion

In short, there appears to be good potential for using portable non-intrusive traffic data collectionequipment in Pennsylvania. PennDOT should make use of all three technologies since each hascircumstances in which it is likely to perform the best. Acoustic sensors might be mostappropriate in areas where an overhead sensor is needed but the right-of-way is limited andoverhead utilities are not an issue. Microwave sensors might be most appropriate in areas wherethe right-of-way is not an issue and it is desired to move the sensor as far as possible from thetraveling lanes. The TIRTL might be most appropriate in instances where truck classification isimportant and roadway geometry allows the device to be set up to manufacturer’s specifications. Both trailer-mounting telescoping poles and temporary poles have the potential for use inPennsylvania, however, the persons responsible for the devices should exercise engineeringjudgement to ensure that the safety of the motoring public or capacity of the roadway is notjeopardized.

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TABLE OF CONTENTS

1.0 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

2.0 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

3.0 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

4.0 Tasks 1 and 2 Portable Installation Research Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

5.0 Task 3 Permanent Installation Research Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

6.0 Summary and Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47

APPENDIX A - Tasks 1 and 2 Test Site Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A-1

APPENDIX B - Tasks 1 and 2 Excerpts from Sensor Set Up Requirements . . . . . . . . . . . . . . B-1

APPENDIX C - Tasks 1 and 2 Site #1: S.R. 0119 Northbound Test Results . . . . . . . . . . . . . . C-1

APPENDIX D - Tasks 1 and 2 Site #2: S.R. 0040 Westbound Test Results . . . . . . . . . . . . . D-1

APPENDIX E - Tasks 1 and 2 Site #2: S.R. 0040 Eastbound Test Results . . . . . . . . . . . . . . . E-1

APPENDIX F - Tasks 1 and 2 Site #3: S.R. 0119 Northbound Test Results . . . . . . . . . . . . . . F-1

APPENDIX G - Tasks 1 and 2 Site #3: S.R. 0119 Southbound Test Results . . . . . . . . . . . . . G-1

APPENDIX H - Tasks 1 and 2 Site #4: S.R. 0040 Westbound Test Results . . . . . . . . . . . . . H-1

APPENDIX I - Tasks 1 and 2 Site #4: S.R. 0040 Eastbound Test Results . . . . . . . . . . . . . . . . I-1

APPENDIX J - Task 3 Testing Details . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J-1

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LIST OF TABLES

Table 1 - Summary of Test Results from Minnesota GuideStar . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Table 2 - Field Test Schedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Table 3 - FHWA Classification Scheme F . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

Table 4 - Sites Selected for Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Table 5 - Dates and Times of Manual Traffic Counts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Table 6 - Summary of Results - Site #1: S.R. 0119 Northbound . . . . . . . . . . . . . . . . . . . . . . . . 16

Table 7 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #1 16

Table 8 - Summary of Statistical Significance Tests - Site #1: S.R. 0119 Northbound . . . . . . . 17

Table 9 - Summary of Results - Site #2: S.R. 0040 Westbound . . . . . . . . . . . . . . . . . . . . . . . . . 20

Table 10 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #2 WB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20

Table 11 - Summary of Statistical Significance Tests - Site #2: S.R. 0040 Westbound . . . . . . . 21

Table 12 - Summary of Results - Site #2: S.R. 0040 Eastbound . . . . . . . . . . . . . . . . . . . . . . . . 22

Table 13 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #2 EB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

Table 14 - Summary of Statistical Significance Tests - Site #2: S.R. 0040 Eastbound . . . . . . . 23

Table 15 - Summary of Results - Site #3: S.R. 0119 Northbound . . . . . . . . . . . . . . . . . . . . . . . 26

Table 16 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #3 NB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

Table 17 - Summary of Statistical Significance Tests - Site #3: S.R. 0119 Northbound . . . . . . 27

Table 18 - Summary of Results - Site #3: S.R. 0119 Southbound . . . . . . . . . . . . . . . . . . . . . . . 28

Table 19 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #3 SB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28

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Table 20 - Summary of Statistical Significance Tests - Site #3: S.R. 0119 Southbound . . . . . . 29

Table 21 - Summary of Results - Site #4: S.R. 0040 Westbound . . . . . . . . . . . . . . . . . . . . . . . . 32

Table 22 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #4 WB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Table 23 - Summary of Results - Site #4: S.R. 0040 Eastbound . . . . . . . . . . . . . . . . . . . . . . . . 34

Table 24 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #4 EB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34

Table 25 - Summary of Results - S.R. 0422 Eastbound (Microwave Sensor and STIP) . . . . . . 36

Table 26 - Summary of Results - S.R. 0422 Westbound (Microwave Sensor and STIP) . . . . . . 37

Table 27 - Summary of Results - S.R. 0202 Northbound (Microwave Sensor) . . . . . . . . . . . . . 38

Table 28 - Summary of Results - S.R. 0476 Southbound near Chemical Road (Acoustic Sensor) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40

Table 29 - Summary of Results - S.R. 0476 Southbound near S.R.0076 (Acoustic Sensor) . . . 41



Table 32 - STIP vs Microwave Sensor Absolute Percent Difference Data at S.R. 0422 . . . . . . 46

Table 33 - S.R. 0376 vs S.R. 0422 Absolute Percent Difference Data . . . . . . . . . . . . . . . . . . . . 46

Table 34 - S.R. 0476 vs S.R. 0376 Absolute Percent Difference Data . . . . . . . . . . . . . . . . . . . . 47

Table 35 - Summary of Portable Setup Field Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49

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LIST OF FIGURES

Figure 1 - Tasks 1 and 2 Site Location Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Figure 2 - Temporary Pole . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Figure 3 - Task 3 Sites Location Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Figure 4 - Site #2: S.R. 0040 Two-Lane Section Looking West . . . . . . . . . . . . . . . . . . . . . . . . . 18

Figure 5 - Setup for Site #3: S.R. 0119 (Both Directions Monitored) . . . . . . . . . . . . . . . . . . . . . 24

Figure 6 - S.R. 0040 Five-Lane Section Test Site . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30

Figure 7 - S.R. 0422 Site (Looking East) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35

Figure 8 - S.R. 0202 Site (Looking South) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38

Figure 9 - S.R. 0476 at Chemical Road Site (Looking South) . . . . . . . . . . . . . . . . . . . . . . . . . . 39

Figure 10 - S.R. 0476 at S.R. 0076 Site (Looking South) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

Figure 11 - I-279 Site (Looking North) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

Figure 12 - S.R. 0376 Site (Looking West Just Upstream of Site) . . . . . . . . . . . . . . . . . . . . . . . 44

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1.0 Introduction

PennDOT has the need to perform short-term traffic volume and classification counts on high-traffic-volume-routes in the state. Most current methods of counting involve placing hardwaresuch as road tubes or credit card-sized counters in the traveling lanes. This presents both safetyand operational problems since placing equipment in the roadway is difficult to accomplishwithout disturbing traffic flow. To alleviate this concern, PennDOT is investigating theeffectiveness of non-intrusive traffic data collection equipment. The overall goal of this researchproject is to field evaluate various non-intrusive data collection technologies and provide theDepartment with the necessary information and tools to enable them to make the mostappropriate use of these technologies.

One objective in pursuit of this goal was to field-evaluate non-intrusive data collectiontechnologies provided by four different vendors in a short-term installation. These technologiesincluded microwave, acoustic, and infrared. This objective was accomplished through theresearch outlined in Tasks 1 and 2, which included a comparison of the results from the non-intrusive traffic data collection equipment to in-pavement sensors operated by PennDOT. Asecond objective included the field evaluation of permanent microwave and acoustic installationsin the Philadelphia and Pittsburgh areas. This objective was accomplished through the researchoutlined in Task 3. The final objective was to provide the Department with the tools andinformation necessary to make the most appropriate use of these non-intrusive countingtechnologies, which is the purpose of this report.

This report is outlined in the following manner. First, Section 2.0 provides some backgroundmaterial on non-intrusive traffic data collection equipment, including research conducted as partof the Minnesota Guidestar project, which has generated a substantial body of knowledge in thisarea. Next, the research methodology is outlined in Section 3.0. The research project wasgenerally divided into two distinct efforts: (1) the field test of these devices in a portable setup,as described in Tasks 1 and 2; and (2) the evaluation of devices in a permanent setup, asdescribed in Task 3. Section 4.0 presents the results of the field testing of the portable setups,while Section 5.0 presents the results of evaluation of the permanent setups. Section 6.0concludes the report with a summary of the research results.

2.0 Background

Most of the documented research performed with these devices has been conducted as part ofthe Minnesota GuideStar program. Early research tested a wide variety of non-intrusive trafficcounters, including the microwave and acoustic sensors, as well as many others. More recentresearch has focused on the portability of the microwave and acoustic sensors, and hasspecifically focused on the development of temporary poles to mount these overhead counters. Current research is expanding to include the infrared “TIRTL” device, which is mounted nearthe road surface and performs the traffic data collection based on axle observation rather thanvehicle observation like the acoustic and microwave sensors. These more recent efforts with themicrowave and acoustic sensors on temporary poles and the TIRTL are summarized below.

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The primary source of information on this research is an interim report submitted to the 2004North American Travel Monitoring Exhibition & Conference (NATMEC) in June of 2004. Afollow-up telephone discussion was also held with lead researcher Eric Minge of SRF ConsultingGroup, Inc in 2005. In summary, their testing relative to the temporary poles was conducted inthe freeway environment of I-394 near Minneapolis. The SmartSensor and RTMS microwavesensors and SAS-1 acoustic sensors were placed on temporary poles for the purpose of trafficcounting, classification, and speed measurement. The temporary poles that were recommendedas a result of the research were 16-ft and 24-ft in height. The maximum sensor mounting heighttested was 25-ft, and the offsets from the nearest lanes ranged from 20-ft to 50-ft. As will beseen in Section 3.0, even the 24-ft high pole results in a mounting height for the acoustic sensorthat is lower than manufacturer installation guidelines. This was reflected in the accuracy results,which are presented in Table 1. Note that all three sensors were to perform a length-basedvehicle classification.

Table 1 - Summary of Test Results from Minnesota GuideStar

RTMS by EIS SmartSensor byWavetronix

SAS-1 by SmartekSystems

Error in OverallCount

2.4% - 8.6% 1.4% - 4.9% 9.9% - 11.8%

Stop-and-Go TrafficPerformance

Under-Counts Over-Counts Under-Counts

Vehicle Classification Reasonable measureof vehicle lengthswhen optimally

calibrated

Reasonable measureof vehicle lengthswhen optimally

calibrated

Distribution ofmedium and largevehicles was not

accurate

Other Concrete barrierspresent a challenging

data collectionlocation for this

sensor

Echo from concretemedian barrier had

slight impact onaccuracy

Significant error incounting whenspeeds droppedbelow 30 mph.

These tests generally proved that the sensors perform well when they can be installed tomanufacturers’ guidelines. However, even in a freeway environment, which is typicallycharacterized by wide shoulders and right-of-way, clear roadside areas, and limited overheadinterference from utility lines, the installation geometry for these sensors was not always met. One example is the acoustic sensor, which needed to be mounted higher than the temporary poleheight would allow. It is hypothesized that the counter performance in non-freewayenvironments may be significantly different than that obtained in the freeway environmentbecause of the constraints presented in the roadside. The right-of-way tends to be narrower, sothe counters cannot be mounted as far from the road; overhead interference from utilities tendsto be greater, potentially restricting the height that the devices can be mounted; and the physical

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space to set up the sensors is much more restricted and closer to the driver, which might cause additional roadside hazards or erratic driving. One purpose of the proposed research is to examine these issues in pursuit of the overall goal of evaluating the potential for these devices to implemented in Pennsylvania. More recent research performed in conjunction with the Minnesota GuideStar program has focused on the TIRTL by Control Specialists. Research results related to the TIRTL sensor were provided in the final report for the project, entitled, Evaluation of Portable Non-Intrusive Traffic Detection System (Kotzenmacher, Minge, and Hao, September 2005). This report indicates that the TIRTL provided accurate results for axle-based vehicle classification detection, with the overall accuracy ranging from 94% to 97%. However, severe weather, such as heavy precipitation or snow, affected the TIRTL sensor’s performance and caused traffic to be undercounted. System security was a concern when the TIRTL units were used for the portable application without having a permanent enclosure to protect them. It was also conveyed to the researcher in a phone interview that, much like the overhead sensors, the TIRTL is not accurate in stop-and-go traffic. They also noted that the TIRTL was highly sensitive to the crown in the roadway and any protrusions from the pavement. Another purpose of the proposed research is to test the TIRTL device in a variety of environments. 3.0 Methodology As noted earlier, the research had three tasks, which were divided into two main efforts: evaluation of these devices in a portable setup, which was accomplished through the work of Tasks 1 and 2, and evaluation of the devices in a permanent setup, which was accomplished through the work of Task 3. The tasks are presented in this chapter according to these two main efforts. 3.1 Tasks 1 and 2: Evaluation of Non-Intrusive Traffic Data Collection Equipment in a

Portable Setup In the initial Request for Quotation, the first two tasks were identified as follows: Task 1: Field Evaluations of Four (4) Non-Intrusive Technologies Task 2: Quality Assurance Comparison to the PennDOT Automated Traffic Recorders and Short-Term In-Pavement Traffic Data Collection Methods and BPR Manual Count In short, the purpose of Task 1 was to evaluate the non-intrusive traffic data collection equipment in a portable setup. The purpose of Task 2 was to ensure that the evaluation would take place near a permanent or short-term in-pavement count station operated by PennDOT so that comparisons could be made between the non-intrusive equipment and the PennDOT equipment. As such, it was one effort, which is described below.

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3.1.1 Non-Intrusive Data Collection Equipment Tested

As specified by the Department, the four non-intrusive traffic counters tested were as follows:

! RTMS by EIS (Microwave)! SAS-1 by Smartek (Acoustic)! Smart Sensor by Wavetronix (Microwave)! TIRTL by Control Specialists (Infrared)

3.1.2 Site Selection

Four sites were selected in the Uniontown, Pennsylvania area. The primary objective of the siteselection was to provide a cross-section of roadside environments for equipment setup. It wasnoted from previous research and the users’ manuals from the various sensors that each sensorhas recommended requirements for where they are placed in the roadside relative to theroadway. Microwave and acoustic sensors are placed high above the elevation of the roadway,at various setbacks and heights. The TIRTL is placed in the roadside at an elevation that iswithin a few inches of the roadway surface. In this research, the selected roadside environmentsprovided opportunities for the equipment to be set up in nearly ideal locations in some instances,but forced set up in less than ideal locations in others. Understanding that limited right-of-way,roadside safety, and utility conflicts are important considerations, it was crucial to select sitesthat forced the equipment to be set up in less than ideal locations to gauge any resulting drop-offin performance. While some environments forced the equipment into less than ideal positions, inno case was it impossible to set up the equipment.

A second objective of the site selection was that at least one site be located at a PennDOTpermanent Automatic Traffic Recorder (ATR) and that at least one site be located at a PennDOTShort-Term In-Pavement sensor (STIP).

The four sites were as follows:

Site #1: S.R. 0119, Segment 0470 (Northbound Only): Freeway - Single Direction (STIPSite)

Site #2: S.R. 0040, Segment 0160 (Both Directions): Two-Lane Highway - ATR Site

Site #3: S.R. 0119, Segment 0470 & 0471 (Both Directions): Freeway - Both Directions(STIP Site)

Site #4: S.R. 0040, Segment 0260& 0261 (Both Directions): Five-Lane Suburban Arterial

Note that Site #1 and Site #3 are in the same location, however, Site #1 testing included only thenorthbound lanes, while Site #3 testing included the monitoring of both directions simultaneously

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Figure 1 - Tasks 1 and 2 Site Location Map

with a single sensor. Additional details on the sites are provided in Appendix A. See Figure 1 fora Location Map.

3.1.3 Test Procedure

The equipment was set up at each site by vendor representatives. This was to ensure that the installation adhered to the manufacturers’ guidelines as closely as possible. It was also to ensurethat inexperience in setting up the equipment was not an issue in the final results of the research. Pertinent excerpts from the manufacturers’ guidelines for equipment set up are provided inAppendix B.

The test was conducted over the course of two days, September 14 and 15, 2005. Table 2provides the testing schedule. As can be seen, vendors were given approximately two hours toset up, and data collection at each site was four-hours in duration. Sunrise was at approximately7:00 am, therefore it was dark during set up and the first hour of data collection at Sites #1 and#3.

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A temporary pole similar to that used in the Minnesota Guidestar research was constructed bythe researchers and brought to Site #1 on the evening of September 13, 2005. This pole was 26feet in height and was designed to be attached to an I-beam traffic sign support at Site #1. TheSmart Sensor by Wavetronix was attached to this temporary pole for data collection at Site #1 todemonstrate the usage of the pole. This pole used in the testing is shown attached to the signpost in Figure 2. In the photo in Figure 2, a five-pound weight is attached to the pole in lieu of asensor. This photo was taken during a field trial in which the difficulty in raising and loweringthe pole was gauged.

Figure 2- Temporary Pole

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Table 2 - Field Test Schedule

Time Event

Wednesday, September 14, 2005

4:00 am to 6:00 am Set Up Equipment at Site #1

6:00 am to 10:00 am Collect Data at Site #1

10:00 am to 2:00 pm Move Equipment to Site #2 and Set Up

2:00 pm to 6:00 pm Collect Data at Site #2, Breakdown and Adjourn for the Day at 6:00 pm

Thursday, September 15, 2005

4:00 am to 6:00 am Set Up Equipment at Site #3

6:00 am to 10:00 am Collect Data at Site #3

10:00 am to 1:00 pm Move Equipment to Site #4 and Set Up

1:00 pm to 5:00 pm Collect Data at Site #4

5:00 pm Breakdown Equipment, Vendors Provide Data to Researcher

Light towers with the lights removed were provided to the vendors of the acoustic andmicrowave sensors for mounting and elevating their sensors. These were Nighthawk LT 12 unitsmanufactured by Multiquip. According to the manufacturer’s specifications, the pole containedon these units telescoped to a height of approximately 30 feet. Each vendor was provided withtheir own light tower unit, which was placed and leveled with the assistance of the researcher. Each vendor then banded their sensor onto the light tower pole and raised the pole to the desiredheight. Vendors of the TIRTL sensor set up on tripods that they supplied.

The researcher provided each vendor with the time of day to which to synchronize for equipmentsetup. It was each vendor’s responsibility to synchronize the sensor data collection to this time.

The data were collected in 15-minute intervals and, depending on the sensor, classified accordingto length or the FHWA Scheme F classification scheme. The length-based classification schemewas as follows: 0 to 22-ft (passenger vehicles), 22 to 40-ft (single unit trucks), and longer than40-ft (multi-unit trucks). The microwave and acoustic sensors used the length-basedclassification scheme. The TIRTL collected data according to the FHWA scheme. The FHWAScheme, along with its relationship to the length-based system, is detailed in Table 3.

For comparison to the vendor data, the research team had two teams classifying and countingtraffic in the field. The first team counted and classified traffic according to the length-basedscheme. The second team counted and classified traffic according to the FHWA scheme. Traffic was also video-recorded during the test to provide a backup for the manual counts.

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Table 3 - FHWA Classification Scheme F

VehicleClass

Description Axles Relation to Length ClassificationScheme

1 Motorcycles 2 0 to 21-ft (passenger cars)

2 Passenger Cars 2 0 to 21-ft (passenger cars)

3 4-Tire Single Unit Vehicle 2 0 to 21-ft (passenger cars)

4 Buses 2 22 to 40-ft (single unit trucks)

5 2-Axle, 6-Tire Single Unit Truck 2 22 to 40-ft (single unit trucks)

6 3-Axle Single Unit Truck 3 22 to 40-ft (single unit trucks)

7 4+ Axle Single Unit Truck 4 22 to 40-ft (single unit trucks)

8 4 or Less Single Trailer Truck 4 40-ft + (multi-unit trucks)

9 5-Axle Single Trailer Truck 5 40-ft + (multi-unit trucks)

10 6+ Axle Single-Trailer Truck 6 40-ft + (multi-unit trucks)

11 5 or Less Axle Multi-TrailerTruck

5 40-ft + (multi-unit trucks)

12 6-Axle Multi-Trailer Truck 6 40-ft + (multi-unit trucks)

13 7+ Axle Multi-Trailer Truck 7 40-ft + (multi-unit trucks)

3.1.4 Data Analysis

For each traffic counter, including the PennDOT counters near the sites, the traffic data from thesensor were compared to the manual counts and classification data. The comparison was madefor the total volume (unclassified) in each 15-minute period, and for the total four-hour period,by computing the Absolute Percent Difference, which is defined as follows:

|Vs - Vm|APD = ------------ x 100%

Vm

where:

APD = Absolute Percent Difference (%)Vs = Volume from the sensor or ATR / STIP (vehicles)Vm = Volume from the manual count (vehicles)

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The classification data was assessed through a comparison of the percentage of trucks over thefour-hour period reported by each sensor against that from the manual counts.

Additionally, for each of the test sites, a series of tests for detecting statistically significantdifferences between the mean values of the Absolute Percent Difference (APD) data from thevarious sensors were conducted. These were not conducted for all possible pairs, but insteadwere custom-selected based upon the results at each site. The analyses are based on finding thestandard error of the mean for the comparison and comparing this to the actual differences in themeans. The equation for standard error of the mean is provided below:

s = [(s12 / n1) + (s2

2 / n2)] 0.5

where:s = standard error of the means1

& n1 = standard deviation and sample size for technology 1s2

& n2 = standard deviation and sample size for technology 2

Assuming a 95% confidence interval, if the difference between the average APD for twocompeting technologies was greater than 2.131 (t-value with 15 degrees of freedom) times the“standard error of the mean”, then it was concluded that the difference was statisticallysignificant. If the difference was less than 2.131 times the “standard error of the mean,” it wasconcluded that the variation detected could be due to random error. The results of the Task 1and 2 tested are found in Section 4.0.

3.2 Task 3: Evaluation of Non-Intrusive Traffic Data Collection Equipment in aPermanent Setup

The purpose of this task was to perform a quality assurance check on a sample of permanentlyinstalled non-intrusive traffic counters in the Pittsburgh and Philadelphia areas. Themethodology is described below.

3.2.1 Site Selection

There are over 250 microwave and acoustic non-intrusive traffic sensors in operation in thePittsburgh and Philadelphia areas. These are owned and operated by Mobility Technologies(traffic.com) in the course of providing internet-based Advanced Traveler Information tomotorists in these areas. Note that these sensors provide data in addition to traffic volume,however, only total traffic volume and vehicle classification were of interest in this research.

Of the hundreds of sensors in the operation, a screening process was in place that eliminatedmany from consideration for inclusion in the research. First, PennDOT was not interested in anysensors that were monitoring ramps. Second, Mobility Technologies narrowed down theavailable pool to those that appeared to be operating properly. These were identified through aquality control process that is unknown to the researcher.

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Once these two criteria were applied, the available pool of test sites were reduced to 12 in thePittsburgh area and 82 in the Philadelphia area. Note that of the 12 test sites in the Pittsburgharea, there were only eight unique sensors, as four of the sensors monitored two sites. Thisoccurred when a single sensor was used to monitor both directions of a roadway. In thePhiladelphia area, there were 68 unique locations, as there were 28 instances of both directionsof a roadway being included in the pool. Of these 28 instances, the same sensor was used tomonitor both directions 13 times, and the opposing directions were monitored by differentsensors 15 times.

All of the sites in the Pittsburgh area were on urban freeways, as were nearly all of the sites inthe Philadelphia area. It was decided that in order to increase safety and avoid occupying theshoulders of these high volume roadways during the manual data collection, the counting wouldbe performed via the surveillance cameras the Department had in operation in each area. Therefore, the managers at the traffic operations centers in both Philadelphia and Pittsburghwere contacted to determine the coverage provide by their video surveillance system. Sensorlocations outside the coverage areas were eliminated from consideration as well. This eliminated43 of the 82 candidates in the Philadelphia area. In Pittsburgh, since the pool was so small, thesites were ranked and eliminated if they were outside the coverage area. The first three locationsproposed were outside the coverage area, however, the next two were inside and eventuallyincluded in the study.

The final consideration in the selection of sites was the Department’s preference to use siteslocated next to PennDOT Automated Traffic Recorder (ATR) or Short-Term In-Pavement(STIP) sensor sites. After all of the aforementioned criteria were applied, there was one sitelocated next to a STIP in the Philadelphia area, and no such sites in the Pittsburgh area.

The scope of work called for six sites to be included in the research, with four sites in thePhiladelphia area and two in Pittsburgh. In addition, four of the sites were to be microwave sitesand two were to be acoustic. The microwave sensors were X2 RTMS sensors manufactured byElectronic Integrated Systems (EIS). The acoustic sensors were SAS-1 sensors manufactured bySmartek Systems. Note that EIS has since developed an improved X3 sensor, however, none ofthese improved sensors were in the pool of potential sites.

In the Philadelphia area, the four sites were selected as follows. First, the site that was locatednear a STIP was selected due to Department preferences. This site used a microwave sensor,thus fulfilling one of these four slots. Review of the Pittsburgh sites revealed no acoustic sensorsites, creating the need to select both acoustic sensor sites from the Philadelphia area. Therewere four candidate sites with acoustic sensors, of which two were randomly selected. The finalPhiladelphia site was to be a microwave site, of which there were 34 candidate sites. One sitewas randomly selected from this pool of 34.

In the Pittsburgh area, three of the 12 sites were located near PennDOT ATR / STIP sites,however, none of these were inside the area of video surveillance coverage. Therefore, the

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remaining sites were randomly ranked and presented to the manager of the traffic operationscenter until two were found that were inside the video surveillance coverage.

Table 4 provides the sites that were included in this study. Figure 3 provides a location mapshowing the sites.

3.2.2 Data Collection

Task 3 called for three hours of manual counts to be performed at each site. These three hourswere to be during the am or pm peak periods. At all of the sites except S.R. 0376 in Pittsburgh,the sites were counted during the pm peak. S.R. 0376 was counted during the am peak. Theexact times of data collection were not always continuous because of activities in the trafficcontrol center that interfered with data collection. The exact days and times of data collectionare provided in Table 5.

Table 4 - Sites Selected for Study

Traffic.comStation ID

Sensor Location Direction Sensor Type

Philadelphia Sites

7188* S.R. 0422, across from the WB Off-Ramp toTrooper Road

EB microwave

7128 S.R. 0202, 0.5 miles north of S.R. 0029interchange

NB microwave

7193 S.R. 0476, 0.2 miles south of Exit 19 (ChemicalRoad)

SB acoustic

7124 S.R. 0476, 0.6 miles north of S.R. 0076 SB acoustic

Pittsburgh Sites

7089 S.R. 0279, 1.25 miles south of the GreentreeInterchange

NB microwave

7087 S.R. 0376, 345-ft west of the Squirrel HillTunnels

EB microwave

*Indicates site was next to a PennDOT STIP site.

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Figure 3 - Task 3 Sites Location Map

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Table 5 - Dates and Times of Manual Traffic Counts

Site Day Times

S.R. 0422 Sept. 7, 2005 2:00 to 5:00 pm

S.R. 0202 Sept. 8, 2005 2:00 to 3:30 pm, 3:45 to 5:15 pm

S.R. 0476 (Chemical Rd) Sept. 7, 2005 2:00 to 3:45 pm, 4:15 to 5:30 pm

S.R. 0476 (I-76) Sept. 8, 2005 1:15 to 1:45 pm, 2:00 to 3:00 pm, 3:30 to4:30 pm, 4:45 to 5:15 pm

S.R. 0279 Sept. 21, 2005 2:00 to 5:00 pm

S.R. 0376 Sept. 28, 2005 7:00 to 10:00 am

At the sites in Philadelphia, video recordings were made of the traffic during the times of datacollection. These video tapes were then watched and counted manually using JAMAR TurningMovement Count boards. In Pittsburgh, the facilities to record video were not available,therefore the traffic was counted and classified in real-time using the same JAMAR equipment. 15-minute intervals were used at all sites.

According to personnel at Mobility Technologies, the sensors were synchronized to NetworkProtocol Time (NTP), to which the researcher was also synchronized.

The counts were to include classification of vehicles according to the same scheme used by thesensor. The classification scheme was discussed with personnel from Mobility Technologies. They indicated that for the microwave sites, the classification scheme was simply to differentiatethe passenger vehicles from the trucks. At the acoustic sensor sites, the scheme used threeclasses: passenger vehicles, single unit trucks, and tractor-trailer trucks.

The Department provided the researcher with the data from the Mobility Technologies database. It was available in 15-minute intervals according to the classification schemes discussed above. The data were not available on a per lane basis, but were instead totaled by direction. TheDepartment also provided data from the STIP sensor for the S.R. 0422 site. Both directions ofSTIP data were provided at this location. The westbound direction was not manually counted,but the STIP data can be compared to data from the Mobility Technologies database. The clockat the STIP was also synchronized to NTP time.

3.2.3 Data Analysis

Similar to the Task 1 / Task 2 research, the analysis consisted of comparing the manual counts tothe data from the Mobility Technologies sensors or PennDOT STIP by computing the APD forthe total volume for each 15-minute period.

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Three statistical analyses were also conducted, each intended to answer a different question. First, the APD from the STIP data collected at S.R. 0422 was compared to the average APDfrom the microwave sensor data collected at this location to determine if there was a statisticallysignificant difference between the STIP and the sensor. Next, the average APD at S.R. 0422 wascompared to the average APD from S.R. 0376 to determine if there was a statistically significantdifference between a microwave sensor monitoring the lanes nearest to it as opposed to onemonitoring the lanes of the “far side” of the roadway. Lastly, the average APD at S.R. 0476(Chemical Road) was compared to the average APD from S.R. 0376 data to see if there was astatistically significant difference between the best performing microwave sensor and the bestperforming acoustic sensor.

Note that all of the comparisons are between single sites. This was because in each case, therewas only a single site for at least one of the types of sensors to be compared. In the firstcomparison, there was only one site located next to a STIP. In the second comparison, there wasonly one microwave sensor monitoring “near side” lanes. In the final comparison, there was onlyone acoustic sensor.

As with the Task 1 / Task 2 research, the tests of statistical difference in the means were basedon finding the standard error of the mean for the comparison and comparing this to the actualdifferences in the means. Assuming a 95% confidence interval, if the difference between theaverage APD for two competing technologies was greater than 2.201 (t-value with 11 degrees offreedom) times the “standard error of the mean”, then it was concluded that the difference wasstatistically significant. If the difference was less than 2.201 times the “standard error of themean,” it was concluded that the variation detected could be due to random error.

4.0 Tasks 1 and 2 Portable Installation Research Results

The results of the comparison of the manual counts to the data from the non-intrusive traffic datacollection equipment are provided in this section. Each subsection is devoted to a single site,presented in the order in which they were tested in the field. In instances where two directionswere monitored at a single site, which was the case at Sites #2, 3, and 4, each direction ispresented separately.

4.1 Site #1: S.R.0119 Northbound Lanes

At this site, S.R. 0119 was two lanes in each direction separated by a grass median. Theequipment was set up in the roadside area behind the northbound shoulder. The following is adescription of the site layout from south to north. Note that horizontal distances were measuredusing a measuring wheel. Vertical heights were estimated by the vendor representatives.

The Smart Sensor was on the temporary pole which was attached to an I-beam sign post. Thepole placed the sensor approximately 23 feet from the lane edge of the northbound lanes. Thebottom of the pole was lower than the elevation of the roadway by approximately two feet,placing the sensor approximately 24 feet above the roadway. It was noted by the vendor that

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this was higher than the optimal placement of the sensor. However, during the initial set up, thisdid not appear to be causing problems with the sensor operation, so it was not lowered. By thetime it was identified as a problem, the test was underway and it was too late to lower the sensor.

The TIRTL was set up directly in front of the Smart Sensor. It was placed on both sides of thenorthbound lanes on vendor-supplied tripods that placed it a couple of inches off the roadwaysurface. The tripod setback was 15.6 feet from the lane edge on the right side and 12 feet fromthe lane edge on the median side. In both instances, the tripods were completely outside of theshoulders.

The SAS-1 was set up approximately 26 feet north of the Smart Sensor and TIRTL. It was setback approximately 20 feet from the lane edge on the right side of the northbound lanes and wasat the full height of the light tower, which was approximately 28 feet above the surface of theroad.

The RTMS was set up approximately 141 feet north of the Smart Sensor and TIRTL, andapproximately 115 feet north of the SAS-1. It was set back 18.7 feet from the lane edge on theright side of the northbound lanes and was approximately 17 feet above the surface of the road. At least 100 feet of separation was provided at every site between the two microwave sensors toeliminate interference.

Table 6 provides a summary of the comparison of the sensor traffic counts and classification tothe manual traffic counts and classification. Full details are provided in Appendix C. Note thatthe average APD and standard deviation for the STIP were 2% and 2% respectively. The APDfor the 3.5 hours for which STIP counts were provided was 1.5%, or a total of 31 vehicles.

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Table 6 - Summary of Results - Site #1: S.R. 0119 Northbound

Performance Measure SAS-1* SS RTMS TIRTL

Total Four-Hour Volume (Manual) 1,961 2,242 2,242 2,242

Total Four-Hour Volume (Sensor) 1,981 2,371 2,333 2,247

Percent Difference, Sensor vs Manual 1.0% 5.8% 4.1% 0.2%

Percent Single Unit Trucks fromSensor (Manual Counts = 6.3%)

56.5% 24.5% 3.1% 6.4%

Percent Tractor-Trailer Trucks fromSensor (Manual Counts = 3.5%)

42.4% 4.8% 1.3% 3.9%

Absolute Percent Difference Statistics Computed Over the 12 15-minute Intervals

Average 1% 6% 6% 1%

Standard Deviation 1% 4% 5% 1%

Minimum and Maximum, Range 0 to 4%,4%

1 to 11%,10%

1 to 17%,16%

0 to 3%,3%

Median 1% 6% 4% 1%

Mode (1% interval with mostobservations)

1% 3% 1% 1%

*Data from 9:30 to 10:00 am were not available for SAS-1. Statistics were queried for the 3.5hour period between 6:00 am and 9:30 am. Percent Single Unit Trucks from manual counts forthis time period was 6.2%. Percent Tractor-Trailer Trucks was 3.5%.

Additionally, the performance of the TIRTL relative to the FHWA Classification scheme issummarized in Table 7. Note, there were no vehicles in Classes 11 through 13. Classes 2 and 3were combined since automated traffic recorders typically have trouble differentiating betweenthese passenger vehicle classes. Values shown in the table are the number of vehicles in eachclass.

Table 7 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #1

Class # 1 2+3 4 5 6 7 8 9 10

TIRTL 11 2004 16 83 22 23 17 65 6

Manual 9 2013 8 84 28 21 11 62 6

As can be seen, the TIRTL matched the manual counts closely, both in terms of total volume andtruck classification. The counts match so closely, particularly for total volume, that they are

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generally considered within the margin of error for the test considering the human elementsinvolved, the spatial distribution of the test site, clock synchronization, etc.

The SAS-1 also matched the total volume very closely, however, there were major problems withthe truck classification. With the exception of 22 vehicles, every vehicle was classified as eithera single unit or tractor trailer truck, which is clearly erroneous.

The microwave sensors matched the manual counts the least closely at this site. All of intervalsfor the RTMS are offset from the manual counts by 155 seconds due to the vendor’s inability tosynchronize the sensor to provide 15-minute volumes beginning at exactly 6:00 am. As notedpreviously, the vendors of the Smart Sensor indicated that their unit was mounted too high. Theyindicated that the extra height caused false detections in the passing lane when pickup truckswent by in the slow lane. They hypothesized that the signal was reflecting off the inside of thetruck bed for a short duration before being sent back to the sensor. This time delay made itappear to the sensor that another vehicle was traveling in the passing lane.

Tests of statistical significance were conducted using the APD data to determine if the differencein APD for total volume for each of the sensors was statistically different. The following six testswere conducted:

! SAS-1 vs TIRTL - Was conducted since these both had an average APD of 1%.! RTMS vs Smart Sensor - Was conducted since these both had an average APD of 6%.! RTMS vs TIRTL and SAS-1 vs Smart Sensor - Were conducted to determine if the two

that closely matched the manual counts were statistically different than the two thatmatched less closely.

! STIP vs SAS-1 and STIP vs RTMS - Were conducted to determine if the STIP matchedthe manual counts less closely than a sensor with an average of 1% and / or more closelythan a sensor with an average APD of 6%.

The test results are summarized in Table 8.

Table 8 - Summary of Statistical Significance Tests - Site #1: S.R. 0119 Northbound

Technology #1 Technology #2 Statistical Significant Difference?

SAS-1 (1.1%) TIRTL (1.3%) No

RTMS (6.1%) Smart Sensor (6.1%) No

SAS-1 (1.1%) Smart Sensor (6.1%) Yes

TIRTL (1.3%) RTMS (6.1%) Yes

SAS-1 (1.1%) STIP (2.0%) No

STIP (2.0%) RTMS (6.1%) Yes

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Figure 4 - Site #2: S.R. 0040 Two-Lane Section Looking West

The actual difference between the SAS-1 and the TIRTL was only 0.1%, which was too small tobe statistically significant. Likewise, the RTMS and Smart Sensor had the same average APD toa tenth of a percent, which was also too small of a difference to be statistically significant. Therewas a statistically significant difference between the RTMS and the TIRTL, and between theSAS-1 and the Smart Sensor at 99% confidence. Additional tests between the pairs would haverevealed similar results. There was no statistically significant difference between the averageAPD of the STIP and the SAS-1. There was, however, a statistically significant differencebetween the average APD of the STIP and the RTMS.

4.2 Site #2: S.R.0040 Westbound

At the site, S.R. 0040 had one lane in each direction, both of which were monitored with thesame unit for each vendor. The equipment was set up on the north side of S.R. 0040, therefore itwas directly adjacent to the westbound lane. Vendors were permitted to set up outside of thePennDOT right-of-way due to safety concerns with occupying the shoulder. All but the TIRTLwere set up outside the right-of-way. Figure 4 shows the site during the test. The following is adescription of the site layout from east to west. Note that horizontal distances were measuredusing a measuring wheel. Vertical heights were estimated by the vendor representatives.

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The RTMS was set up approximately 18 feet from the lane edge on a light tower. The height ofthe pole placed it approximately 17 feet above the roadway.

The SAS-1 was set up approximately 48 feet to the west, next to a utility pole. It wasapproximately 17 feet from the lane edge and was at the full height of the light tower, which wasapproximately 30 feet.

The TIRTL was 10 feet west of the SAS-1 and was located on the opposite side of the utilitypole. It was installed on both sides of the roadway on the manufacturer’s tripods approximately11 feet from the lane edge. Both units were clear of the shoulder.

Finally, the Smart Sensor was located approximately 100-ft to the west of the RTMS, and 50 feetto the west of the area with the SAS-1 and TIRTL. It was approximately 16.5 feet from the laneedge with the light tower telescoped to a height that placed the unit approximately 17 feet abovethe roadway.

Table 9 provides a summary of the comparison of the equipment traffic counts and classificationto the manual traffic counts and classification. Table 10 provides a class-by-class comparison ofthe TIRTL counts to the manual counts for the FHWA classification scheme. Full details areprovided in Appendix D. The four-hour volume for the ATR at this location was 1,756, which isa difference of 0.7%. The average APD and standard deviation were 5% and 3%, however, theATR was located approximately 0.5 miles from the test site, so some error was introduced by theover 30-second travel time from the test site to the ATR. However, very little traffic wasexpected to have turned off or on between the ATR and the test site since there were only a fewresidential driveways. The traffic composition reported by the ATR was 96.5% passengervehicles, 2.5% single unit trucks, and 1.0% tractor-trailer trucks. The only sensor in closeragreement with the manual classification was the TIRTL.

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Table 9 - Summary of Results - Site #2: S.R. 0040 Westbound






83.0% 4.3% 1.4% 2.8%


3.2% 0.8% 0.6% 1.5%


Average 20% 2% 25% 1%



0 to 4%,4%

17 to 33%,16%

0 to 6%,6%

Median 19% 2% 26% 1%


18% 2%, 3% 26%, 28% 1%

*Data from 5:15 to 6:00 pm were not available for SAS-1. Statistics were queried for the 3.25hour period between 2:00 pm and 5:15 pm. Percent Single Unit Trucks from manual counts forthis time period was 3.4%. Percent Tractor-Trailer Trucks was 1.6%.

Table 10 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #2WB

Class # 1 2+3 4 5 6 7 8 9 10

TIRTL 13 1676 9 20 4 16 11 14 2

Manual 13 1678 11 21 6 16 7 15 1

The RTMS and SAS-1 had high variations from the manual counts at the 15-minute interval leveland overall. The TIRTL and Smart Sensor matched the manual counts much more closely. TheTIRTL also matched the truck percentages closely. As can be seen in Table 10, the TIRTLclassification was extremely close to that performed manually. The RTMS and Smart Sensormatched the manual classifications reasonably well, while the SAS-1 did poorly.

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Test of statistical significance between means were conducted using the absolute percentdifference (APD) data to determine if the difference in APD for total volume for each of thesensors was statistically different. The following six tests were conducted:

! Smart Sensor vs TIRTL - Was conducted since these both matched the manual countsclosely.

! RTMS vs SAS-1 - Was conducted since these did not match the manual counts so closely.! RTMS vs TIRTL and SAS-1 vs Smart Sensor - Was conducted to determine if the two

that closely matched the manual counts were statistically different than the two thatmatched less closely.

! ATR vs TIRTL and ATR vs Smart Sensor - Was conducted to determine if the ATRmatched the manual counts less closely than the two sensors that matched the manualcounts the most closely.

The test results are summarized in Table 11.

Table 11 - Summary of Statistical Significance Tests - Site #2: S.R. 0040 Westbound


TIRTL (1.3%) Smart Sensor (1.9%) No

SAS-1 (20%) RTMS (25%) Yes

TIRTL (1.3%) RTMS (25%) Yes

Smart Sensor (1.9%) SAS-1 (20%) Yes

TIRTL (1.3%) ATR (4.9%) Yes

Smart Sensor (1.9%) ATR (4.9%) Yes

The actual difference between the Smart Sensor and the TIRTL was only 0.6%, which was toosmall to be statistically significant. There was a statistically significant difference between theRTMS and the SAS-1, the RTMS and the TIRTL, and between the SAS-1 and the Smart Sensorat 99% confidence. Additional tests between the pairs would have revealed similar results. Withrespect to the ATR, there was a statistically significant difference between the average APDs ofboth the TIRTL and the Smart Sensor and the ATR.

4.3 Site #2: S.R. 0040 Eastbound

This was simply the opposite direction of traffic for the S.R. 0040 test described in Section 4.2. For each sensor, the traffic data were collected in both directions simultaneously using a singleunit. Refer to Section 4.2 for a description and photo of the site layout. Note that the eastboundlane was on the far side of the roadway relative to where the equipment was set up.

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Table 12 provides a summary of the comparison of the sensor traffic counts and classification tothe manual traffic counts and classification. Table 13 provides a class-by-class comparison ofthe TIRTL counts to the manual counts for the FHWA classification scheme. Full details areprovided in Appendix E. The four-hour volume for the ATR at this location was 1,791, which isa difference of four vehicles or 0.2%. The average APD and standard deviation for the ATRwere 3% and 2% respectively. As noted in the previous section, some of this deviation wasintroduced by the half-mile spacing between the test site and the ATR. The traffic compositionreported by the ATR was 95.8% passenger vehicles, 3.1% single unit trucks, and 1.1% tractor-trailer trucks. As was the case with the westbound direction, the only sensor in closer agreementwith the manual classification was the TIRTL. The TIRTL, SAS-1, and RTMS all had an averageAPD that was less than this ATR.

Table 12 - Summary of Results - Site #2: S.R. 0040 Eastbound






86.7% 17.0% 2.6% 4.5%


7.7% 2.1% 0.5% 1.4%


Average 2% 4% 3% 1%



0 to 19%,19%

0 to 10%,10%

0 to 2%,2%

Median 2% 4% 2% 1%


1% 4% 3% 1%

*Data from 5:15 to 6:00 pm were not available for SAS-1. Statistics are queried for the 3.25 hourperiod between 2:00 pm and 5:15 pm.

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Table 13 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #2 EB

Class # 1 2+3 4 5 6 7 8 9 10

TIRTL 18 1663 8 31 42 0 6 18 1

Manual 19 1658 10 38 40 1 3 18 0

All four sensors matched the manual counts very closely. For the RTMS and SAS-1, this wasmuch different than the results from the westbound side, where they deviated significantly fromthe manual counts. The Smart Sensor matched the manual counts a little more closely on thewestbound side (near side), whereas the TIRTL matched the manual counts a little more closelyon the eastbound side (far side). The TIRTL actually matched the four-hour volume down to thevehicle, and matched the FHWA truck classifications recorded manually very closely.

For the Smart Sensor, one notable difference between the two directions is that the percentage ofsingle unit trucks was much closer to the manual counts for the westbound side (near side) than itwas for the eastbound side (far side). It should be noted that there was an intersection just to theeast of the site, and that traffic in the eastbound direction slowed for short durations while trafficturned right into the side road.

Again, as with the westbound direction, tests of statistical significance between means wereconducted between the Smart Sensor and TIRTL; RTMS and SAS-1; RTMS and TIRTL; SAS-1and Smart Sensor; ATR and TIRTL; and ATR and Smart Sensor. The test results are summarizedin Table 14.

Table 14 - Summary of Statistical Significance Tests - Site #2: S.R. 0040 Eastbound


TIRTL (0.9%) Smart Sensor (4.2%) Yes

SAS-1 (1.6%) RTMS (2.7%) No

TIRTL (0.9%) RTMS (2.7%) Yes

Smart Sensor (4.2%) SAS-1 (1.6%) Yes

TIRTL (0.9%) ATR (3.4%) Yes

ATR (3.4%) Smart Sensor (4.2%) No

Like the westbound side, there was a statistically significant difference between the RTMS andTIRTL, the SAS-1 and Smart Sensor, and the ATR and TIRTL. However, unlike the westbounddirection, a statistically significant difference was detected between the TIRTL and Smart Sensor at 95% confidence, but was not detected between the ATR and the Smart Sensor or the SAS-1and the RTMS..

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Figure 5- Setup for Site #3: S.R. 0119 (Both Directions Monitored)

4.4 Site #3: S.R. 0119 Both Sides - Northbound Direction

This site was at the exact location of Site #1, however, for Site #3 testing, each vendor set uptheir equipment to count both directions (four lanes) of S.R. 0119. Like the Site #1 testing, theequipment was set up on the northbound side of S.R. 0119 in the roadside behind the shoulder. Therefore, it was directly adjacent to the northbound lanes. Figure 5 shows the site. Thefollowing is a description of the site layout from south to north. Note that horizontal distanceswere measured using a measuring wheel. Vertical heights were estimated by the vendorrepresentatives.

On the northbound side, the TIRTL was set up in almost the identical location as it was for Site#1. The primary difference was that for the Site #1 testing, the receiver was placed in themedian just off the northbound inside shoulder, whereas for the Site #3 testing, the receiver was

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placed in the roadside behind the southbound outside shoulder. As such, it spanned bothdirections of the freeway as well as the median. For both sides, the TIRTL unit was set up on themanufacturer’s tripods approximately 11 feet from the lane edge. Consequently, it was clear ofthe shoulder on both sides.

The Smart Sensor was set up approximately 19 feet north of the TIRTL on a light tower. It wastelescoped to a height that placed it approximately 22 feet above the roadway. It was 28 feetfrom the lane edge.

The SAS-1 was set up approximately 72 feet north of the Smart Sensor on a light towertelescoped to full height (approximately 30 feet). It was nine feet from the lane edge, andoccupied part of the shoulder.

The RTMS was setup 25 feet north of the SAS-1 and approximately 100 feet north of the SmartSensor. It was 29 feet from the lane edge and placed on a light tower approximately 15 feetabove the roadway.

Table 15 provides a summary of the comparison of the sensor traffic counts and classification tothe manual traffic counts and classification. Table 16 provides a class-by-class comparison ofthe TIRTL counts to the manual counts for the FHWA classification scheme. Full details areprovided in Appendix F. Only the final hour of STIP data was available for this test, and itsdeviation from the manual counts was much greater than the previous day. The average APDand standard deviation for the single hour were 15% and 10% respectively, which were in starkcontrast to the average APD of 2% measured for this same STIP just one day previously. Thesedata were disregarded as outliers and no further analysis of them was performed.

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Table 15 - Summary of Results - Site #3: S.R. 0119 Northbound






64.5% 42.7% 3.3% 8.4%


35.0% 6.1% 0.5% 5.0%


Average 1% 2% 2% 19%



1 to 4%,3%

0 to 4%,4%

11 to 36%,25%

Median 1% 2% 1% 18%


1% 2% 1% 17%, 18%


Table 16 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #3 NB

Class # 1 2+3 4 5 6 7 8 9 10

TIRTL 15 1546 22 81 25 24 22 63 5

Manual 10 1968 13 87 25 24 14 69 3

All of the overhead sensors matched the manual counts closely for volume. Both the SmartSensor and RTMS matched the manual counts more closely during this second setup. None ofthe sensors matched the manual classification that well. The SAS-1 over-classified both singleunit and tractor-trailer trucks, as it classified very few vehicles as passenger vehicles. The SmartSensor also over-classified both types of trucks, identifying nearly half of the traffic stream astrucks. The RTMS was the only overhead sensor to report reasonable numbers for the truckpercentages, however, these still differed quite a bit from the manual counts.

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The TIRTL had a passenger vehicle count that was much less than the manual count. For thatreason, its percentage difference was much higher than the other counters, and its performanceduring the Site 1 testing. It also had a percentage of trucks which was higher than the manualcounts, likely due to the undercounting of passenger vehicles. It was noted during the set up thatit was a difficult site for this equipment due to differences in the roadway geometry between thenorthbound and southbound lanes. Even with this complication, it still performed well atidentifying trucks in the traffic stream.

Tests of statistical significance between means were conducted using the average APD data. Thetest results are summarized in Table 17.

Table 17 - Summary of Statistical Significance Tests - Site #3: S.R. 0119 Northbound


SAS-1 (1.4%) Smart Sensor (2.2%) Yes

RTMS (1.8%) Smart Sensor (2.2%) No

SAS-1 (1.4%) RTMS (1.8%) No

Smart Sensor (2.2%) TIRTL (19%) Yes

The average APD for the SAS-1, RTMS, and Smart Sensor were 1.4%, 1.8%, and 2.2%respectively. The tests of statistical significance revealed a statistically significant differencebetween the SAS-1 (1.4%) and Smart Sensor (2.2%) at 95% confidence, but not between any ofthe other pairs. A test of statistical significance between the Smart Sensor (2.2%) and the TIRTL(19%) confirmed the difference was statistically significant at 99%. It would have also beenstatistically significant with other pairings involving the TIRTL.

4.5 Site #3: S.R. 0119 Both Sides - Southbound Direction

This was simply the opposite direction of traffic for the S.R. 0119 test described in Section 4.4. For each sensor, the traffic data were collected in both directions simultaneously using a singleunit. Refer to Section 4.4 for a description of the site layout. Note that the southbound laneswere on the far side of the roadway relative to where the equipment was set up.

Table 18 provides a summary of the comparison of the sensor traffic counts and classification tothe manual traffic counts and classification. Table 19 provides a class-by-class comparison ofthe TIRTL counts to the manual counts for the FHWA classification scheme. Full details areprovided in Appendix G. The four-hour volume for the STIP at this location was 2,769, which isa difference of 43 vehicles or 1.5%. The average APD and standard deviation were 3% and 4%respectively. In general, the counter matched the manual counts closely in all periods but one, inwhich the deviation was 15%. This was unexplained, as none of the other sensors had deviationsthat would be considered outliers during this same 15-minute interval. At this location, theperformance of this STIP was comparable to the overhead sensors in matching the manual

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manual counts. All of the overhead sensors matched the manual counts more closely than theSTIP. However, the difference was so slight that a test of statistical significance between theSTIP and RTMS, which matched the manual counts the most closely, revealed no statisticallysignificant differences at 95%.

Table 18 - Summary of Results - Site #3: S.R. 0119 Southbound






11.3% 75.4% 3.5% 10.7%


74.0% 9.1% 0.1% 5.0%


Average 3% 2% 1% 26%



1 to 3%,3%

0 to 4%,4%

5 to 36%,31%

Median 2% 2% 1% 25%


1%, 2% 2% 1% 25%


Table 19 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #3 SB

Class # 1 2+3 4 5 6 7 8 9 10

TIRTL 162 1592 34 96 73 19 24 73 6

Manual 5 2508 14 127 42 14 19 77 6

Like the northbound (near side), the overhead sensors produced traffic volumes that were theclosest to the manual counts. The Smart Sensor and RTMS matched the manual counts moreclosely on the southbound (far side), while SAS-1 matched the northbound (near side) more

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closely. Again, none of the overhead sensors matched the manual truck classifications veryclosely, although the RTMS at least provided reasonable numbers.

The TIRTL matched the manual counts even less closely on the southbound (far side) than it didon the northbound side (near side). Again, the main issue appeared to have been theundercounting of passenger vehicles, as the truck classification appeared to be in relativeagreement with the manual counts.

The same tests of statistical significance between means that were conducted with thenorthbound (near side) data were conducted with the southbound (far side) data. The testresults are summarized in Table 20.

Table 20 - Summary of Statistical Significance Tests - Site #3: S.R. 0119 Southbound


Smart Sensor (1.6%) SAS-1 (2.5%) No

SAS-1 (2.5%) RTMS (1.4%) No

Smart Sensor (1.6%) RTMS (1.4%) No

Smart Sensor (1.6%) TIRTL (26%) Yes

Smart Sensor (1.6%) STIP (2.9%) No

STIP (2.9%) RTMS (1.4%) No

The average APD for the Smart Sensor, SAS-1, RTMS, and were 1.6%, 2.5%, and 1.4%respectively. The tests of statistical significance did not reveal a statistically significantdifference between any of the overhead sensors or the STIP. A statistically significant differencewas revealed between the TIRTL and the Smart Sensor (1.6%) at 95% confidence.

4.6 Site #4: S.R. 0040 Five-Lane Cross Section - Westbound Direction

This site was located in the commercial area of Uniontown. S.R. 0040 had two lanes in eachdirection plus a two-way left-turn lane (TWLTL). Vendors were asked to omit the traffic usingthe TWLTL. Due to the driveway activity in the area, it was understood that there would bedifferences in the traffic passing each sensor. However, the differences should have been minorcompared to the overall traffic volume.

The equipment was set up on the westbound side of S.R. 0040 on the paved shoulder. Allequipment was set up inside of the PennDOT right-of-way. Figure 6 shows the site. Thefollowing is a description of the site layout from east to west. Note that horizontal distances weremeasured using a measuring wheel. Vertical heights were estimated by the vendorrepresentatives.

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Figure 6- S.R. 0040 Five-Lane Section Test Site

The TIRTL was set up on the manufacturer’s tripods approximately 6 feet from the lane edge onthe westbound side, and just behind a depressed curb on the eastbound side. This depressed curbwas separated from the nearest eastbound traveling lane by only a short gutter, placing the unitwithin a few feet of the travel lanes.

The Smart Sensor was set up on a light tower approximately 10 feet from the lane edge. It wasapproximately 50 feet west of the TIRTL, and was telescoped to a height of approximately 15feet, which placed it under the overhead utility lines in the area.

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The SAS-1 was set up on a light tower approximately 7 feet from the lane edge. It was 17 feetwest of the Smart Sensor and was telescoped to a height of 30 feet. It was two to three feet infront of existing utility lines in the area. Note that the electric company expressed concern withthe location of the pole / sensor relative to their electric lines, and indicated that it should havebeen lowered by “a few feet.”

The RTMS was approximately 100 feet west of the SAS-1 and nearly 120 feet from the SmartSensor. It was 7 feet from the lane edge and was on a light tower telescoped to a height of 17feet, placing it under the existing overhead utility lines. At this location, the vendor indicatedthat the sensor was too close to the westbound right-most lane (near lane) to monitor it, andomitted it from the traffic count.

Table 21 provides a summary of the comparison of the sensor traffic counts and classification tothe manual traffic counts and classification. Table 22 provides a class-by-class comparison ofthe TIRTL counts to the manual counts for the FHWA classification scheme. Full details areprovided in Appendix H.

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Table 21 - Summary of Results - Site #4: S.R. 0040 Westbound


Total Four-Hour Volume (Manual) 2,697 2,864 1,260** 2,864




0.0% 3.7% 2.0%** 5.7%


0.0% 0.9% 0.5%** 1.1%


Average 5% 3% 43% 15%



0 to 6%,6%

9 to 65%,56%

2 to 21%,19%

Median 6% 2% 44% 15%


6% 1%, 2%,4%

40 to 50% 15%

*Data from 4:45 to 5:00 pm were not available for SAS-1. Statistics were queried for the 3.75hour period between 1:00 pm and 4:45 pm. Percent Single Unit Trucks from manual counts forthis time period was 4.9%. Percent Tractor-Trailer Trucks was 0.7%.**Statistics were queried for the passing lane only since the curb lane was omitted. PercentSingle Unit Trucks from manual counts for this lane was 7.1%. Percent Tractor-Trailer Truckswas 1.3%.

Table 22 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #4 WB

Class # 1 2+3 4 5 6 7 8 9 10

TIRTL 55 2215 21 61 15 42 10 16 2

Manual 32 2676 19 55 14 46 4 16 2

Due to the turning activity in the area, the margin of error for this test was relatively high. Consequently, the analysis did not dwell on small differences in the numbers. Tests of statisticalsignificance were omitted because even if a statistically significant difference can be detectedbased on sample size and standard deviations, engineering judgement dictates that small

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differences are not effectively significant due to the margin of error caused by the turningactivity.

Clearly, the SAS-1 and Smart Sensor matched the manual counts the closest. The RTMS mayhave been detecting some of the traffic in the curb lane as it attempted to only count the passinglane. None of these overhead sensors matched the truck classification very closely. Like theSite #3 testing, the TIRTL matched the manually-counted truck classes closely but had asignificant deviation from the manually-counted passenger vehicle classes.

4.7 Site #4: S.R. 0040 Five-Lane Cross Section - Eastbound Direction

This was simply the opposite direction of traffic for the test described in Section 4.6. For eachsensor, the traffic data were collected in both directions simultaneously using a single unit. Referto Section 4.6 for a description of the site layout. Note that the eastbound lanes were on the farside of the roadway relative to where the equipment was set up.

Table 23 provides a summary of the comparison of the sensor traffic counts and classification tothe manual traffic counts and classification. Table 24 provides a class-by-class comparison ofthe TIRTL counts to the manual counts for the FHWA classification scheme. Full details areprovided in Appendix I.

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Table 23 - Summary of Results - Site #4: S.R. 0040 Eastbound






0.0% 9.3% 2.3% 7.9%


0.0% 2.1% 0.7% 1.6%


Average 3% 2% 2% 25%



0 to 5%,5%

0 to 6%,6%

8 to 30%,22%

Median 2% 2% 2% 27%


2% 1% 1%, 2% 28%, 30%

*Data from 4:45 to 5:00 pm were not available for SAS-1. Statistics were queried for the 3.75hour period between 1:00 pm and 4:45 pm. Percent Single Unit Trucks from manual counts forthis time period was 4.8%. Percent Tractor-Trailer Trucks was 1.1%.

Table 24 - Comparison of TIRTL versus Manual in the FHWA Classification Scheme - Site #4 EB

Class # 1 2+3 4 5 6 7 8 9 10

TIRTL 61 1920 23 79 66 5 15 17 2

Manual 27 2750 22 74 39 1 9 22 2

Again, considering the margin of error for this test, only the significant differences and trendsshould be highlighted. The overhead sensors were all in close agreement with the manual countsrelative to volume. The RTMS matched the eastbound (far side) manual count much closer thanit did the westbound (near side) manual count. The SAS and Smart Sensor performed about thesame relative to the manual count. Again, the TIRTL identified trucks consistently with manualcounts while struggling to do the same with the passenger vehicles.

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5.0 Task 3 Permanent Installation Research Results

The results of the comparison of the manual counts to the data from the Mobility Technologiessensors are provided in this section. Each subsection is devoted to a single site. First, themicrowave sensors from Philadelphia are presented. These are followed by the acoustic sensors,both of which were in Philadelphia. The Pittsburgh sites, both of which were microwave, follow. The section is concluded with statistical analysis of the Absolute Percent Difference data (APD)from the various sites.

5.1 S.R. 0422 Eastbound at the Westbound Off-Ramp to Trooper Road

At the sensor location, S.R. 0422 was two lanes in each direction with a narrow median thatincluded safety-shaped concrete median barrier. See Figure 7. This microwave sensor waslocated adjacent to the eastbound lanes of S.R. 0422 and was set up to monitor both directions ofS.R. 0422. In the eastbound direction, it was located at the end of an on-ramp, as such, lanechanging and merging activity was higher than normal in the vicinity of the counter. It isimportant to note that in some instances, there was not sufficient space in the traffic stream fortraffic entering from the ramp. Consequently, some of the traffic traveled on the shoulder oncethe ramp ended, and some traveled side-by-side sharing the right-lane with another vehicle untilthey were able to merge properly. The STIP was not located directly adjacent to the sensor, asjust downstream of the sensor was a bridge carrying S.R. 0422 over the Schuylkill River. ThePennDOT STIP was located just downstream of this bridge.

Figure 7 - S.R. 0422 Site (Looking East)

The details of the results are contained in Appendix J. A summary of the results is provided inTable 25.

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Table 25 - Summary of Results - S.R. 0422 Eastbound (Microwave Sensor and STIP)

Performance Measure Value

Total Three-Hour Volume (Manual) 8,970

Total Three-Hour Volume (Sensor) 8,824

Percent Difference, Sensor vs Manual 1.6%

Percent Trucks from Manual Counts / Sensor 6.3% / 4.1%

Total Three-Hour Volume (STIP) 9,341

Percent Difference, STIP vs Manual 4.1%


Average 2.2%

Standard Deviation 0.9%

Minimum and Maximum, Range 0.4% to 3.6%, 3.2%

Median 2.4%

Mode (1% interval with most observations) 2.2% to 3.2%

In general, the microwave sensor performed very well, matching the manual counts to within 1 to2%, which matched even more closely than the PennDOT STIP. The sensor had an overallvolume that was less than the manual count, which may be partially explained by the mergingactivity and travel on the shoulder / traveling side-by-side in the right-lane. However, at adifference in total volume of less than 2%, the difference was likely close to the typical margin oferror for manual counts.

Trucks were under-classified by the microwave sensor. The sensor classifies vehicles based onits rough estimates of length, whereas the researcher classified consistent with FHWAClassification Scheme F, which bases the classification on axle configuration and number of tiresin contact with the pavement. It is possible that the sensor identified some of the shorter trucksas passenger vehicles. Only total volume was provided for the STIP, therefore, no evaluation ofits classification abilities were made.

5.2 S.R. 0422 Westbound at the Westbound Off-Ramp to Trooper Road

This site was located directly across the median from the previous site and was in fact counted bythe same sensor. Since this was not one of the selected sites, manual counts were not collected atthis site, however, data were available from both the PennDOT STIP and sensor for comparison. The details of the analysis are contained in Appendix J. Table 26 provides a summary of thecomparison of these traffic volumes.

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Table 26 - Summary of Results - S.R. 0422 Westbound (Microwave Sensor and STIP)


Total Three-Hour Volume (STIP) 12,475


Percent Difference, Sensor vs STIP 37.7%


Average 38.4%



Median 37.5%


As can be seen, there was a great disparity between the traffic volume counted by the STIP andthe count from the sensor. Without manual counts, it could not be determined for certain whichcount was correct. However, since this direction of S.R. 0422 would be considered “outbound”,it should have likely had higher volumes than the eastbound side during the pm peak, whichwould have been “inbound.” Since the eastbound three-hour volume was just under 9,000, it islikely that the sensor volume of 7,768 for the westbound direction was too low.

It should be noted that this site was not one in the available pool provided by MobilityTechnologies. As such, it was eliminated from consideration by them either because theysuspected it was not counting properly, or because the count was some how complicated by theTrooper Road off-ramp, which was very close to the sensor location. The sensor may have beenomitting some exiting traffic. For certain, the STIP was counting the full traffic volumeapproaching the interchange since its location on the opposite side of the bridge over theSchuykill River was a considerable distance from the interchange.

5.3 S.R. 0202 Northbound, 0.5 Miles North of S.R. 0029 Interchange

At the sensor location, S.R. 0202 was two lanes in each direction with a grass median, visuallyestimated at approximately 40-ft. See Figure 8. This microwave sensor was located adjacent tothe southbound lanes of S.R. 0202 and was set up to monitor both directions of S.R. 0202. Assuch, these lanes were the farthest from the sensor, which was different from the S.R. 0422Eastbound site in which the lanes monitored were the closest to the sensor. The details of theresults are contained in Appendix J. A summary of the results is provided in Table 27.

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Figure 8 - S.R. 0202 Site (Looking South)

Table 27 - Summary of Results - S.R. 0202 Northbound (Microwave Sensor)







Average 5.0%



Median 4.4%

Mode (1% interval with most observations) 4% to 5%

The disparity between the manual counts and sensor counts for this microwave sensor wasgreater than that measured with the other the microwave sensor at S.R. 0422 Eastbound. Similarto the sensor at S.R. 0422 Eastbound, the manual traffic volume was greater than that measuredby the sensor. In fact, at these two sensors, there was only one 15-minute period where thesensor count was higher than the manual count. That occurred at the S.R. 0422 site, and thedifference was only three vehicles. It is possible that the sensor accuracy at this site was lessthan that at the S.R. 0422 site because of the distance from the sensor since the lanes tested were

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on the “far side” of the roadway relative to the sensor location. In addition, the median on S.R.0202 at this site was relatively wide, adding even more distance between the sensor and lanes. However, at a difference of approximately 5%, the microwave sensor provided a relativelyaccurate traffic volume count. Like the sensor at S.R. 0422 Eastbound, trucks appeared to havebeen under-classified by the sensor, likely due in part to the classification of shorter trucks aspassenger vehicles.

5.4 S.R. 0476 Southbound, 0.2 Miles South of Exit 19 (Chemical Road)

At the sensor location, S.R. 0476 was three lanes in the southbound direction with a grassmedian. See Figure 9. This acoustic sensor was located in the median and only monitored thesouthbound lanes. The count location was at the beginning of a weaving section in which afourth lane was added at an on-ramp and then dropped after a few hundred feet at an off-ramp. As such, a significant amount of lane changing occurred in this area. Additionally, it was notedfrom a test query of traffic volumes from the Mobility Technologies database provided by theDepartment that this weaving lane was not monitored by the sensor. When vehicles crossed goremarkings while traveling between the right-most through lane and this weaving lane, there wassome uncertainty by the researcher regarding whether to include them in the traffic volume.


Figure 9 - S.R. 0476 at Chemical Road Site(Looking South)

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Table 28 - Summary of Results - S.R. 0476 Southbound near Chemical Road (Acoustic Sensor)





Percent Single Unit Trucks from ManualCounts / Sensor

4.0% / 4.5%

Percent Tractor Trailer Trucks from ManualCounts / Sensor

3.5% / 3.2%


Average 1.2%



Median 1.0%


This acoustic sensor provided an extremely accurate count. Given the uncertainty regardingcertain entering / exiting vehicles, and allowing for some error in the manual counts, it is possiblethat the sensor counted with little to no errors. Even the truck classification was extremelyaccurate, deviating from the manual truck classification by less than 0.5% for both the singleunits and the tractor-trailers.

5.5 S.R. 0476 Southbound, 0.6 Miles North of S.R. 0076

At the sensor location, S.R. 0476 was three lanes in the southbound direction. See Figure 10. This acoustic sensor was located on the southbound side of S.R. 0476 and only monitored thesouthbound lanes. Incidently, a microwave sensor was also located on this side of S.R. 0476 andwas used to monitor the northbound lanes. Analysis of the performance of the microwave sensoris not included since it was not a selected site. This acoustic sensor was a few hundred feetdownstream of an on-ramp, however, the activity at this ramp should have had little influence onthe traffic count at the sensor location.


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Figure 10 - S.R. 0476 at S.R. 0076 Site (Looking South)

Table 29 - Summary of Results - S.R. 0476 Southbound near S.R.0076 (Acoustic Sensor)





Percent Single Unit Trucks from ManualCounts / Sensor

3.5% / 4.6%

Percent Tractor Trailer Trucks from ManualCounts / Sensor

3.3% / 0.3%


Average 25.0%



Median 26.2%


As can be seen, there were some extreme disparities between the manual count and the acousticsensor count. The Mobility Technologies sensor reported a lesser volume than the manual count

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in every 15-minute time interval, and reported a total volume that was over 3,400 vehicles lessthan the manual count. Clearly, there were either serious problems with the sensor or there wasa major blunder in the test methodology. The data sets from each count were checked to ensurethat proper data from Mobility Technologies were queried, and that time periods were beingconsistently compared. Given the quality control checks that the counters were subject to priorto being submitted for consideration in this research, it was unexpected that a counter would bein error by that margin. The results at this site were considered outliers, and were omitted fromany further analysis.

5.6 S.R. 0279 Northbound, 1.25 Miles South of the Greentree Interchange

At the sensor location, S.R. 0279 was three lanes in the northbound direction with a median thatincluded a safety shaped concrete median barrier. See Figure 11. This microwave sensor waslocated on the southbound side of S.R. 0279, and as such, the lanes monitored were on the “farside” of the roadway relative to the counter location.

Figure 11 - I-279 Site (Looking North)

One problem with this location is that the third lane on S.R. 0279 northbound is a truck climbinglane, and the sensor is positioned in the area where the lane is added. The manual counts wereperformed just upstream of the taper to avoid confusion caused by the lane changing in the taperof the truck climbing lane and because the surveillance camera provided a better vantage pointfor counting. Therefore, the manual counts included the entire traffic volume on this section offreeway, and do not omit the traffic volume in the climbing lane. Consequently, the manualcounts are expected to be higher than the sensor counts.

A video recording was not made of this location due to the lack of required equipment in thetraffic control center. Furthermore, the vantage point from the camera to the section of S.R.0279 with the truck climbing lane was partially obscured by branches, and likely would not haveprovided an acceptable view. The details of the results are contained in Appendix J. Asummary of the results is provided in Table 30.

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Average 12.2%



Median 14.8%


Given the special considerations caused by the omission of the truck climbing lane, the countsprovided by the microwave sensor appeared reasonable. It was interesting to note in the reviewof the 15-minute interval data (see Appendix J) that the agreement between the manual countsand the sensor counts steadily improved from the beginning of the test to the end. This may havebeen due in part to the number of trucks declining over time and decreasing as a percentage ofoverall traffic as the peak period traffic grew. Whatever the reason, the difference between thesensor and manual counts was less than 5% in each of 15-minute intervals between 4:00 pm and5:00 pm, with a minimum difference of 1.8% occurring between 4:15 and 4:30 pm. Likewise,the average APD between 2 and 3 pm was 19.5%, compared to 14.4% between 3 and 4 pm, and2.9% between 4 and 5 pm. Also noteworthy was that even though the truck climbing lane wasomitted, the percentage of trucks measured by the sensor was still lower than the manual count. The results at this site were considered outliers and were omitted from any further analysis.

Perhaps the most important thing to be learned from this site is that the Department shouldensure that all lanes of a facility are being counted before using Mobility Technologies data. TheMobility Technologies records indicated that the stations in which the number of lanes countedwas less than the number of lanes present were as follows:

Pittsburgh Sites: Station ID# 7019 (I-79), Station ID# 7031 (I-79), Station ID# 7033 (I-279),Station ID# 7061 (I-279), Station ID# 7068 (I-279), Station ID# 7089 (I-279), Station ID# 7096(I-376 WB), Station ID# 7108 (Freeport Road NB), Station ID# 7114 (I-279), and Station ID#7120 (S.R. 3069)

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Philadelphia Sites: Station ID# 7141 (I-95), Station ID# 7150 (I-476 SB), Station ID# 7164 (I-95SB), Station ID# 7169 (I-76 EB), Station ID# 7176 (I-95), Station ID# 7182 (S.R.0309 SB),Station ID# 7190 (I-76 WB), Station ID# 7198 (I-76 WB), Station ID# 7203 (I-76 EB), StationID# 7207 (I-76 EB), Station ID# 7243 (I-76 EB), and Station ID# 7255 (I-76)

5.7 S.R. 0376 Eastbound, 345-ft West of the Squirrel Hill Tunnels

At the sensor location, S.R. 0376 was two lanes in the eastbound direction with a median thatincluded a safety shaped concrete median barrier. See Figure 12. This microwave sensor waslocated on the westbound side of S.R. 0376, and as such, the lanes monitored were on the “farside” of the roadway relative to the counter location. Note that the direction counted was“entering” the tunnel, however, stop-and-go traffic was not experienced. A lane drop justupstream of the sensor location metered flow to the sensor site. In addition, at the time of thecount, the peak commuter traffic was flowing in the westbound direction. The details of theresults are contained in Appendix J. A summary of the results is provided in Table 31.

Figure 12 - S.R. 0376 Site (Looking West Just Upstream of Site)

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Average 1.9%



Median 1.9%


This site represented the best performance of the microwave X2 sensor in matching the manualcounts. The total three-hour volume only differed by four vehicles, and the average APD was1.9%, better by 0.3% than the next closest match exhibited at S.R. 0422. As was the case withthe other microwave sensors, the number of trucks was under-classified relative to the manualcounts.

5.8 Statistical Analysis

Three statistical analyses were conducted, each intended to answer a different question. First,the average Absolute Percent Difference (APD) from the STIP data collected at S.R. 0422 wascompared to the average APD from the microwave sensor data collected at this location todetermine if there was a statistically significant difference between the STIP and the sensor. Next, the average APD at S.R. 0422 was compared to the average APD from S.R. 0376 todetermine if there was a statistically significant difference between a microwave sensormonitoring the lanes nearest to it as opposed to one monitoring the lanes of the “far side” of theroadway. Lastly, the average APD at S.R. 0476 (Chemical Road) was compared to the averageAPD from S.R. 0376 data to see if there was a statistically significant difference between the bestperforming microwave sensor and the best performing acoustic sensor.

Note that all of the comparisons are between single sites. This was because in each case, therewas only a single site for at least one of the types of sensors to be compared. In the firstcomparison, there was only one site located next to a STIP. In the second comparison, there wasonly one microwave sensor monitoring “near side” lanes. In the final comparison, there was onlyone acoustic sensor.

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Each of these analyses is presented below.

5.8.1 STIP vs Microwave Sensor at S.R. 0422

The key parameters used in the test of significant difference between means are provided inTable 32.

Table 32 - STIP vs Microwave Sensor Absolute Percent Difference Data at S.R. 0422

Measure STIP Sensor

Mean 4.4% 2.2%

Standard Deviation 2.0% 0.9%

Sample Size 12 12 In this comparison, the actual difference in the means was 2.2%, which was 3.4 times thestandard error of the mean, which was computed as 0.6%. Therefore, it was concluded with99% confidence that there was a statistically significant difference in the mean APDs betweenthe STIP and the microwave sensor at the S.R. 0422 site.

5.8.2 S.R 0376 vs S.R. 0422, Near Lane Monitoring vs Far Lane Monitoring

The key parameters used in the test of significant difference between means are provided inTable 33. S.R. 0376 was monitored from a microwave sensor in the roadside on the opposite sideof the roadway. In other words, these lanes were the “far lanes” relative to the sensor location. S.R. 0422 was monitored from a microwave sensor in the roadside directly adjacent to it. Thesetwo sites were selected for comparison because they both were monitored by microwave sensorsthat were monitoring both directions of a four-lane divided highway from a single unit. Inaddition, the average APDs with the respective manual counts collected at their location werethe least of the “near” and “far” side lanes monitored by microwave sensors. A similarcomparison cannot be made between the acoustic sensor sites since they were both monitored bysensors directly adjacent to the lanes.

Table 33 - S.R. 0376 vs S.R. 0422 Absolute Percent Difference Data

Measure S.R. 0376 S.R. 0422

Mean 1.9% 2.2%


Sample Size 12 12 In this comparison, the actual difference in the means was 0.3%, which was only 0.7 times thestandard error of the mean, which was 0.5%. Therefore, it was concluded that there was no

47

statistically significant difference in the average APDs between the S.R. 0376 (far lane) and S.R.0422 (near lane) sites at 95% confidence.

5.8.3 S.R. 0476 (Chemical Road) vs S.R. 0376, Acoustic vs Microwave Sensors

The key parameters used in the test of significant difference between means are provided inTable 34. S.R. 0476 and S.R. 0376 were selected because their average APDs with therespective manual counts collected at their location were the least of the acoustic and microwavesensors respectively.

Table 34 - S.R. 0476 vs S.R. 0376 Absolute Percent Difference Data

Measure S.R. 0476(Acoustic)

S.R. 0376(Microwave)

Mean 1.2% 1.9%


Sample Size 12 12 In this comparison, the actual difference in the means was 0.7%, which was only 1.5 times thestandard error of the mean, which was 0.5%. Therefore, it was concluded that there was nostatistically significant difference in the average APDs between the S.R. 0476 (acoustic) and S.R.0376 (microwave) sites at 95% confidence.

6.0 Summary and Conclusions

The conclusions of the study are focused in four areas. First, a summary of the performance ofeach sensor is provided. This is followed by a comparison of the results of this research tosimilar research conducted in the field. A discussion of issues related to the temporary poles andtrailer-mounted telescoping poles is then provided. This section is then wrapped up with someconcluding remarks.

6.1 Summary of Sensor Performance

6.1.1 TIRTL

The TIRTL, which was only tested in a portable setup, matched the manual traffic data veryclosely when spanning the two-lane sections. Relative to the manual traffic data at the four- andfive-lane sections, it undercounted passenger vehicles, but still did well with truck identification.

6.1.2 SAS-1

The SAS-1 provided traffic volumes that closely matched the manual counts at all of the portablesites except the two-lane S.R. 0040 site. Its closest matches occurred at the S.R. 0119

48

northbound lanes, both during Site #1 and Site #3 testing. It was generally within 5% of themanual counts, with the lone exception being the near side (westbound) direction at Site #2. Thetruck classification was poor, as the sensor typically either identified every vehicle in the sampleas a passenger car or identified every vehicle as a truck. In the permanent setup, the acousticsensor performed very well at the S.R. 0476 site near Chemical Road, having differed from themanual counts by less than 1% on the three-hour volume, and reporting a vehicle compositionthat matched the manual counts very closely.

6.1.3 RTMS

In a portable setup, the RTMS provided traffic volumes that most closely matched the manualcounts at Site #3 and the S.R. 0040 Site #2 and #4 far side lanes. Due to the vendor’s inability tosynchronize the counter, this counter was consistently out of time synchronization with the clockmaintained by the researcher, which caused some error. The truck classification always providedreasonable numbers, and in an overall sense, it was likely the overhead sensor that matched themanual classification the closest during the portable testing. In the permanent installation testing,the RTMS units at S.R. 0376, S.R. 0422 and S.R. 0202 demonstrated conformance with themanual counts to within 5%, although the under-classifying of trucks was prevalent throughoutall of the microwave sites. At the S.R. 0422 Eastbound site, the permanently-installed RTMSmatched the manual counts closer than the PennDOT STIP by a margin of 2.2%. This wassufficient to detect a statistically significant difference between the STIP and the microwavesensor in matching the manual counts.

6.1.4 Smart Sensor

The Smart Sensor, which was only tested in a portable setup, matched the manual trafficvolumes the most consistently of all the sensors testing during the Task 1 / Task 2 research. Itwas noted by the vendors at the time of the testing that the Site #1 volumes were over-countingpickup trucks due to the height of the sensor. When the northbound S.R. 0119 lanes werecounted again during the Site #3 testing, they matched the manual counts much more closely. Infact, the 6% deviation from the manual counts measured during the Site #1 testing was thehighest overall for the Smart Sensor, with the remainders all being within 4%. Truckclassification by the Smart Sensor exhibited a tendency to over-classify trucks, sometimesdramatically. However, there were two instances where the vehicle composition matched themanual counts reasonably well, those being the near side lane(s) at the two S.R. 0040 sites.

6.1.5 ATR / STIP

In the Task 1 / Task 2 testing, the ATR at S.R. 0040 and the STIP at S.R. 0119 provided countsthat consistently matched the manual counts. The highest mean APD for either was 4.9%, whichwas encountered at S.R. 0040, where some error was expected due to the distance between theATR and the test site. Truck classification data were not provided for the STIP, however, at theATR, only the TIRTL was in closer agreement with the manually-determined traffic composition.

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6.1.6 Summary of Traffic Volume Results

Table 35 provides a summary of the traffic volume results from the portable testing across allsites by vendor. For each vendor, the average APD data across the 16 15-minute time intervalsis provided, along with the APD between the sensor and manual count in the total four-hourvolume. As can be seen, the sensor matching the manual counts the most closely over all of thesites is the Smart Sensor.

Table 35 - Summary of Portable Setup Field Testing

Site #(Dir)

Smart Sensor SAS-1 TIRTL RTMS

APD % 4-Hr % APD % 4-Hr % APD % 4-Hr % APD % 4-Hr %

1 (NB) 6% 5.8% 1% 1.0% 1% 0.2% 6% 4.1%

2 (EB) 4% 3.7% 2% 0.7% 1% 0.0% 3% 1.3%

2 (WB) 2% 0.5% 20% 20.4% 1% 0.2% 25% 24.9%

3 (NB) 2% 1.4% 1% 0.8% 19% 18.5% 2% 1.5%

3 (SB) 2% 0.9% 3% 1.0% 26% 26.0% 1% 0.1%

4 (EB) 2% 1.2% 3% 1.1% 25% 25.7% 2% 0.2%

4 (WB) 3% 1.1% 5% 5.0% 15% 14.9% 43% 40.6%

Average 3% 2.1% 5% 4.3% 13% 12.2% 12% 10.4%

At the permanent installations, there was no statistically significant difference between the bestperforming acoustic sensor and best performing microwave sensor. Similarly, there was nostatistically significant difference between volumes collected by microwave sensors from thenear and far side lanes. The inability to prove statistically significant differences in both instanceswas attributed more to the small differences in the average APD than it was to the variability ofthe APD over time at the respective sites. This may be indication that there was no difference inreality.

6.2 Comparison of Results from the Permanent and Temporary Installations

In the Task 3 research, four RTMS sites and two SAS-1 sites were evaluated, although one ofeach was omitted from the analysis as an outlier. The remaining four sensors matched themanual counts within 5%. Note that the X2 version of the RTMS was evaluated in the Task 3research while the more advanced X3 version was used for Task 1 / Task 2 research. Withrespect to truck classification, the SAS-1 matched the manually-measured traffic compositionparticularly closely, while the RTMS sensors under-classified trucks relative to the manualclassification.

50

Like the Task 3 research, the Task 1 / Task 2 research also found the RTMS and SAS-1 sensorsto match manual counts within 5%, but not consistently across all sites, as both sensors deviatedfrom the manual counts by a substantial margin at the S.R. 0040 two-lane site in the westbound(near side) direction. Another difference was noted between the SAS-1 performance in matchingthe manual truck classification at the permanent site and the portable sites. At the portable sites,the traffic composition was reported as nearly all passenger vehicles or nearly all trucks. At thepermanent site, the manual classification yielded a truck composition of 4.0% single unit trucksand 3.5% tractor-trailers on approximately 10,000 vehicles. The SAS-1 reported 4.5% singleunits and 3.2% tractor-trailers, which was relatively close to the manual classification results.

6.3 Comparison of Results to the Minnesota Guidestar Research

The Minnesota Guidestar research focused on using these devices in the portable setup, so itsresults will be compared to the results of the Task 1 / Task 2 research. The first comparison thatwas made was between the freeway installations at Site #1 and Site #3 and the Minnesotaresearch. Comparing the Minnesota result “error in overall count” to the “average APD fromthe manual counts” resulting from this study, the following can be seen. First, the RTMSperformed about the same, ranging from 2% to 9% in the Minnesota study, and 1% to 6% in thisresearch. Similarly, the Smart Sensor ranged from 1% to 5% in Minnesota and 2% to 6% in thisresearch. The TIRTL matched the manual counts to within 1% when spanning two-lanes in theTask 1 / Task 2 research, which is closer than the 93 to 97% reported in Minnesota. However,when spanning the four- and five-lane sections, the TIRTL deviated significantly from theMinnesota results. Note that the Minnesota testing associated with these results was conductedon a two-way two-lane highway.

The SAS-1 ranged from 9% to 11% in Minnesota, but 1% to 3% in this research, which was asubstantial improvement. This might be attributable to the sensor mounting height, which wasbelieved to be higher in the Pennsylvania research. Another factor to consider in comparingthese studies is that the sensors were set up by the vendors in the Pennsylvania research, whereasthe vendors were not involved in the equipment set up in the Minnesota research.

A second comparison of these parameters can be made between the freeway sites in Minnesotaand Pennsylvania and the non-freeway sites at Sites #2 and #4. The Smart Sensor ranged from 2to 4% at the non-freeway sites, which was comparable to those measured at the freeway sites. The SAS-1 had mixed results, having ranged from 2% to 20% at the non-freeway sites. At thefive-lane arterial (Site #4), the SAS-1 matched the manual counts closely, having an averageAPD of 3% in the eastbound direction and 5% in the westbound direction. This was comparableto the freeways in Pennsylvania and better than those in Minnesota. However, at the two-lanehighway (Site #2), the average APDs were 2% and 20% respectively, which were much differentfrom one another, and in the case of the westbound (near side) direction, was higher than eitherthe Pennsylvania or Minnesota freeway sites. The RTMS matched the manual counts closely forthe far side lanes of both the two-lane highway site and the five-lane arterial, which wascomparable to the freeway results. However, at 25% and 43%, its results for the near side(westbound) lanes were much higher than the freeway results.

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6.4 Temporary Poles and Trailer-Mounted Telescoping Poles

Roadside presence and safety is an important issue that the Department must consider duringdeployment of these devices. Both a temporary pole and light tower were used for the sensors,while the TIRTL was set up on the manufacturer-supplied tripods. Each is discussed below.

The temporary pole that was placed on the I-beam sign post had a minimal presence in theroadside, however, it could have reached the traveling lanes from where it was set up had itfallen towards the road. It was also quite heavy to lift into place. The potential for one person tolift the pole into place while maintaining full control over it to minimize the potential of it fallinginto traffic is questionable. In addition, the temporary pole installation is likely not suitable forsmaller sign posts and those not securely planted in the ground because of its size and weight.

The light towers were much easier to control and their potential to fall into traffic was less,assuming they were properly leveled and the outriggers were extended. According to themanufacturer specifications, the particular light towers that were used are stable in gusty windsup to 65 mph. However, these took up significant space in the roadside. They could not be setup within the PennDOT right-of-way at the S.R. 0040 two-lane section and consumed the entire8-foot shoulder at the S.R. 0040 five-lane section. At a weight of over 0.75 tons, they alsopresent a formidable roadside hazard if struck by a vehicle. However, they may be appropriatefor the freeway environment if the roadside has sufficient cross-section to place them outside theclear zone. Portable non-intrusive traffic counters mounted on trailer-mounted telescoping poleshave been observed in use in Pennsylvania on both the Pennsylvania Turnpike and I-79 inDistrict 11-0. They were also recently observed on I-70 to the west of Baltimore, Marylandupstream of a major work zone. These devices were mounted on trailer-mounted telescopingpoles. They were equipped with rather large solar panels and some had dome cameras as well. Itwas interesting to note that all of the trailers were protected from traffic with temporary barrier.

The tripods used to mount the TIRTL are likely not appropriate for most installations becausethey leave the device open to vandalism and tampering. It was encouraging that the TIRTL didnot have to occupy the shoulder during the testing at the S.R. 0119 sites, however, the roadsidewas lower in elevation than the traveling lanes and shoulder. During their presentation, thevendor noted enclosures that might be used to secure and protect the TIRTL during temporaryinstallations. Ideas used elsewhere included placing a construction barrel over the tripod-mounted TIRTL with holes cut in the barrel to maintain line-of-sight between the transmitter andreceiver.

6.5 Implementation Plan

The Department will likely use these devices as part of work zones, as they have already beenobserved, and also for counting in the PennDOT traffic volume monitoring program. To be usedin work zones, they will need to be specified properly in contract documents. Therefore, anawareness is required among the Department personnel, design consultants, contractors, andconstruction inspection forces. The Department should work within their own training

52

infrastructure and the Local Technical Assistance Program (LTAP) center to bring about thisawareness. Additionally, standard special specifications can be developed. It is likely that somespecifications for these devices already exist since these devices have been observed in use inexisting projects. These specifications may need to be expanded or eliminated if they areproprietary in nature. The ideal special provision would include the following provisions:

(1) It should provide the contractor with a choice of either a trailer-mounted telescoping poleor a temporary pole. However, the special provision should note that the temporary polespecified in the Minnesota Guidestar research is too short for the acoustic sensor, and islikely more expensive and heavier than is required. If the acoustic sensor is to bespecified, the pole upon which it will be placed must be of sufficient height to place thedevice at least 30-ft above the road surface. In addition, the temporary pole used in thisresearch was constructed of 10-foot Electric Metallic Tubing (EMT) in lieu of 10-footSchedule 40 Aluminum pipe, and EMT sleeves secured with muffler brackets in lieu ofthe Schedule 40 steel couplers between the sections of pole. This provided a pole thatwas sufficiently sturdy to hold the sensor in place during the raising and lowering of thepole as well as during the testing, at a fraction of the weight and cost.

(2) The special provision should include protection for the mounting system when placed inthe roadside, particularly if the trailer-mounted telescoping pole is used.

(3) It can include a power source of either solar or deep-cycle marine battery. Based on theresults of other research in this area, the battery appears to be the better option, however,it will require a tamper-proof enclosure.

(4) The sensor to be specified should include consideration of the roadside environment,including overhead utilities and available right-of-way. If the device must be placedwithin 10-ft of the roadway and overhead utilities are not a concern, then the acousticsensor may be the most appropriate choice. If the device can be placed further than 10-ftfrom the roadway, or if overhead utilities are a concern, then the microwave devices maybe the most appropriate choice. The manufacturer guidelines for each device should bemade available to the engineer(s) making the selection.

For the purposes of collecting short-term traffic counts, it must be decided if the Departmentdesires to have detailed truck classification data collected as well. If so, then the TIRTL shouldbe specified if the device can be installed to manufacturer guidelines. This includes a roadsurface that is relatively flat with no protrusions such as barriers and islands, as well as a roadsidearea that is no higher than the road surface for at least 5-feet where the device can be placed. The Department should also include the enclosure intended for temporary installations that ismade by the sensor manufacturer. If detailed classification data are not to be collected, then aspecial provision similar to that drafted for the work zone installation can be used.

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6.6 Concluding Remarks

In summary, there appears to be good potential for using portable non-intrusive traffic datacollection equipment in Pennsylvania. PennDOT should make use of all three technologies sinceeach has circumstances in which it is likely to perform the best. Acoustic sensors might be mostappropriate in areas where an overhead sensor is needed but the right-of-way is limited andoverhead utilities are not an issue. Microwave sensors might be most appropriate in areas wherelimited right-of-way is not an issue and it is desired to move the sensor as far as possible from thetraveling lanes. The TIRTL might be most appropriate in instances where truck classification isimportant and roadway geometry allows the device to be set up to manufacturer’s specifications. Both trailer-mounting telescoping poles and temporary poles have the potential for use inPennsylvania, however, the persons responsible for the devices should exercise engineeringjudgement to ensure that the safety of the motoring public or capacity of the roadway is notjeopardized.

With respect to the traffic volume data available to the Department from Mobility Technologies,the Department should be cautious when using these data. If the sensors are in proper workingorder and are monitoring all of the lanes, then there is a good chance that quality of the data ishigh. However, in light of the fact that (1) many of the sensors were eliminated from thisresearch due to quality-related concerns, (2) that two of the six sites that were selected did notprovide counts that matched the manual counts, and (3) that many of the sensors appear to notbe monitoring all of the lanes, the Department should review any data from these sensors toensure that they are reasonable before use.

A-1

APPENDIX A - Tasks 1 and 2 Test Site Details

A-2

Site #1

S.R.: 0119Segment: 0470Direction(s): NorthboundATR or STIP Site: STIPNumber of Lanes Tested: 2Speed Limit: 55 mphMunicipality: North Union TownshipAADT: 8,654Percent Trucks: 4%Area Type: SuburbanFunctional Classification: Urban Principal Arterial - Other FreewaysRoadside Description: limited access freeway, large shoulders with backup area, grass medianOther Factors: rumble strips on both shouldersTypical Section: (2) 12-ft lanes with 10-ft paved outside shoulder and 4.5-ft inside shoulder. 30-ft grass median with sizable mound near overpass. 17-ft of graded shoulder backup area tooutside into roadside ditch.

Site #2

S.R.: 0040Segment: 0160Direction(s): BothATR or STIP Site: ATR SiteNumber of Lanes Tested: 2Speed Limit: 45 mphMunicipality: Redstone TownshipAADT: 10,832Percent Trucks: 5%Area Type: Suburban / ResidentialFunctional Classification: Rural Principal Arterial - OtherRoadside Description: small paved shoulders, guiderail and embankments in the area, utility polesboth sides, adjacent developed properties with drivewaysTypical Section: (2) 11-ft lanes with 4-ft shoulder EB and 2-ft paved shoulder WB. Guiderail ison EB side 5.5-ft from lane edge. Utility poles are 14-ft from lanes on WB side and 17-ft fromlanes on EB side. On utility poles, lowest lines are approximately 15-ft to 20-ft above the road.Other Factors: Centerline Rumble Strips

A-3

Site #3

Same location as Site #1, however, both directions will be monitored. Information is providedunder the description of Site #1 with the following exceptions:

Direction(s): BothNumber of Lanes Tested: 4AADT: 17,137Percent Trucks: 4%

Site #4

S.R.: 0040Segment: 0260 / 0261Direction(s): BothATR or STIP Site: NoneNumber of Lanes Tested: 4Speed Limit: 35 mphMunicipality: South Union TownshipAADT: 18,684Percent Trucks: 5%Area Type: Suburban / Strip DevelopmentFunctional Classification: Urban Other Principal ArterialRoadside Description: five-lane arterial with a two-way left-turn lane. Most of it is curbed butthere is a small area with shoulder on one side and parking lot on the other. Existing utility poles,private poles, and mast arms in the area.Typical Section: 58-ft cartway with 8-ft shoulder WB and 2-ft gutter and 8" high curb EB. Utility poles on WB side 12.5-ft from lane edge, approximately 20-ft clear to lowest lines.

B-1

APPENDIX B - Tasks 1 and 2 Excerpts from Sensor Set Up Requirements

B-2

SAS -1 by Smartek (Acoustic)

! Practical limit for furthest lane to be monitored is 90 to 100-ft from the sensor.

! The maximum distance from the nearest lane is 40-ft. The normal distance is 10 to 20-ft.

The Recommended Install Height (in feet) of SAS-1 for Multi-Lane Monitoring:

Distance fromNearest Lane

Number of Lanes Monitored

5 4 3 2 1

6-ft 34 30 26 24 20

12-ft 36 32 28 26 22

18-ft 38 34 30 28 24

24-ft 40 36 32 28 24

30-ft 44 38 34 30 24

TIRTL by Control Systems (Infrared)

! The beams between the transmitter and receiver should be 90 degrees to the roadside.

! For optimal operation, the distance between the transmitter and receiver should be keptto a minimum. The maximum distance is 328-ft (656-ft with long-range optic).

! The height of the beams above the peak of the road surface must be no more than 5 cm (2inches).

! The height of the beams above the edges of the road must be equal, this is important forroads with large camber.

! The angle of inclination of the TIRTL receiver and transmitter must be equal to that ofthe road surface.

SmartSensor by WaveTronix (Microwave)

! Maximum distance from furthest lane monitored to the nearest lane is 200-ft.

! The recommend offset from the nearest lane is 25 to 35-ft. The recommended heights atthose offsets range from 20-ft to 23-ft.

B-3

Mounting Height Guidelines (All Units in Feet)Offset from first detection

laneRecommended Mounting

HeightMinimum Mounting

HeightMaximum Mounting

Height10 12 9 1511 12 9 1612 13 10 1613 13 11 1714 14 11 1715 15 12 1816 15 12 1817 16 13 1818 17 14 1919 17 14 1920 18 15 2021 18 15 2122 18 16 2223 19 16 2324 19 16 2425 20 17 2526 20 17 2627 21 18 2728 21 18 2829 21 18 2930 22 19 3031 22 19 3132 22 19 3233 23 19 3334 23 19 3435 23 20 3536 23 20 3637 23 20 3738 24 21 3839 24 21 3940 25 22 4041 25 22 4142 26 22 4243 26 22 4344 27 23 4445 27 23 4546 28 23 4647 28 24 4748 29 24 4849 29 24 49

50 to 180-ft 30 25 height must be less thanthe offset

B-4

RTMS by EIS (Microwave)

! The ideal mounting location for most highway applications is 30-ft from the first lane anda height of 23-ft.

! For setbacks that are less than 20-ft, a mounting height of 17-ft is recommended.

! For setbacks that are more than 20-ft, the height may be increased approximately 3-ft per5-ft increase in setback to a maximum of 30-ft.

! When deploying RTMS on heavy structures such as overpasses and some sign-bridges,mount them so that the microwave beam clears the structures to avoid multi-pathdistortion of the beam. Do not mount directly on perpendicular overpasses.

! The number of lanes that can be monitored is a function of the setback from the first lane,as is shown in the following table.

Setback vs Lanes Monitored

Setback (ft) Lanes Monitored

8 3

10 4

12 5

14 6

16 8

18 10

20 11

22 12

25 or more 13 (eight lanes + 5 lane equivalent median)

C-1

APPENDIX C - Tasks 1 and 2 Site #1: S.R. 0119 Northbound Test Results

C-2

Manual CountPC SU TT Total

6:00 AM 6:15 AM 73 2 3 786:15 AM 6:30 AM 94 9 2 1056:30 AM 6:45 AM 104 14 4 1226:45 AM 7:00 AM 128 6 1 1357:00 AM 7:15 AM 121 2 5 1287:15 AM 7:30 AM 120 12 7 1397:30 AM 7:45 AM 159 10 4 1737:45 AM 8:00 AM 187 7 7 2018:00 AM 8:15 AM 141 15 2 1588:15 AM 8:30 AM 127 11 12 1508:30 AM 8:45 AM 139 9 2 1508:45 AM 9:00 AM 139 8 3 1509:00 AM 9:15 AM 120 6 8 1349:15 AM 9:30 AM 119 10 9 1389:30 AM 9:45 AM 110 8 4 1229:45 AM 10:00 AM 141 12 6 159

TOTAL 2022 141 79 2242Composition 90.2% 6.3% 3.5%

Manual FHWA ClassClass 1 Class 2+3 Class 4 Class 5 Class 6 Class 7 Class 8 Class 9 Class 10

0 73 0 1 1 0 0 3 00 94 1 7 0 1 0 2 00 104 2 11 1 0 0 3 10 128 0 3 3 0 0 1 01 120 0 1 1 0 1 4 00 120 4 2 2 4 2 5 02 157 0 5 4 1 1 3 00 187 1 5 0 1 0 7 00 141 0 9 3 3 0 2 00 127 0 6 3 2 2 9 11 138 0 8 0 1 1 1 01 138 0 5 1 2 0 3 01 119 0 2 1 3 2 5 10 119 0 7 2 1 1 7 13 107 0 5 2 1 1 2 10 141 0 7 4 1 0 5 19 2013 8 84 28 21 11 62 6

C-3

SAS-1 by Smartek APD inPC SU TT TOTAL Total Vol APD in Total Volume

6:00 AM 6:15 AM 3 34 42 79 1% Average 1%6:15 AM 6:30 AM 0 57 48 105 0% StDev 1%6:30 AM 6:45 AM 1 68 54 123 1%6:45 AM 7:00 AM 3 85 50 138 2% Traffic Composition7:00 AM 7:15 AM 0 72 57 129 1% SAS-1 Manual7:15 AM 7:30 AM 1 86 53 140 1% PC 1.1% 90.3%7:30 AM 7:45 AM 6 116 54 176 2% SU 56.5% 6.2%7:45 AM 8:00 AM 2 131 70 203 1% TT 42.4% 3.5%8:00 AM 8:15 AM 1 90 68 159 1%8:15 AM 8:30 AM 1 82 68 151 1% 3.5-Hour Volume Difference8:30 AM 8:45 AM 0 98 51 149 1% 20 vehicles8:45 AM 9:00 AM 0 100 50 150 0%9:00 AM 9:15 AM 2 40 98 140 4% 3.5 Hour Volume Difference (%)9:15 AM 9:30 AM 2 61 76 139 1% 1.0%9:30 AM 9:45 AM DATA NOT AVAILABLE FROM VENDOR9:45 AM 10:00 AM DATA NOT AVAILABLE FROM VENDOR

Smart Sensor by WavetronixTotal APD inPC SU TT TOTAL Total Vol APD in Total Volume

6:00 AM 6:15 AM 63 18 4 85 9% Average 6%6:15 AM 6:30 AM 76 38 3 117 11% StDev 4%6:30 AM 6:45 AM 100 29 7 136 11%6:45 AM 7:00 AM 98 38 5 141 4% Traffic Composition7:00 AM 7:15 AM 87 37 5 129 1% SS Manual7:15 AM 7:30 AM 104 31 11 146 5% PC 70.7% 90.2%7:30 AM 7:45 AM 130 42 6 178 3% SU 24.5% 6.3%7:45 AM 8:00 AM 147 50 11 208 3% TT 4.8% 3.5%8:00 AM 8:15 AM 112 44 5 161 2%8:15 AM 8:30 AM 116 33 11 160 7% 4-Hour Volume Difference8:30 AM 8:45 AM 123 30 2 155 3% 129 vehicles8:45 AM 9:00 AM 111 36 6 153 2%9:00 AM 9:15 AM 93 43 10 146 9% 4-Hour Volume Difference (%)9:15 AM 9:30 AM 96 46 11 153 11% 5.8%9:30 AM 9:45 AM 95 28 8 131 7%9:45 AM 10:00 AM 126 37 9 172 8%

C-4

RTMS by EISTotal APD inPC SU TT TOTAL Total Vol APD in Total Volume

6:00 AM 6:15 AM 74 4 1 79 1% Average 6%6:15 AM 6:30 AM 107 2 0 109 4% StDev 5%6:30 AM 6:45 AM 126 4 2 132 8%6:45 AM 7:00 AM 132 0 1 133 1% Traffic Composition7:00 AM 7:15 AM 116 3 3 122 5% RTMS Manual7:15 AM 7:30 AM 149 10 3 162 17% PC 95.6% 90.2%7:30 AM 7:45 AM 171 5 0 176 2% SU 3.1% 6.3%7:45 AM 8:00 AM 210 6 3 219 9% TT 1.3% 3.5%8:00 AM 8:15 AM 143 4 0 147 7%8:15 AM 8:30 AM 156 8 6 170 13% 4-Hour Volume Difference8:30 AM 8:45 AM 145 2 0 147 2% 91 vehicles8:45 AM 9:00 AM 151 3 2 156 4%9:00 AM 9:15 AM 136 8 2 146 9% 4-Hour Volume Difference (%)9:15 AM 9:30 AM 127 6 3 136 1% 4.1%9:30 AM 9:45 AM 131 4 1 136 11%9:45 AM 10:00 AM 157 3 3 163 3%

TIRTL by Control Specialists APD inTotalVol

FHWA Classes1 2+3 4 5 6 7 8 9 10 PC SU TT Total

6:00 AM 6:15 AM 0 70 0 3 0 1 0 2 0 70 4 2 76 3%6:15 AM 6:30 AM 0 98 1 3 0 1 0 2 0 98 5 2 105 0%6:30 AM 6:45 AM 0 105 2 7 1 0 2 3 1 105 10 6 121 1%6:45 AM 7:00 AM 0 128 2 6 1 0 0 1 0 128 9 1 138 2%7:00 AM 7:15 AM 1 116 1 3 1 0 0 5 0 117 5 5 127 1%7:15 AM 7:30 AM 2 120 4 2 2 4 1 6 0 122 12 7 141 1%7:30 AM 7:45 AM 2 154 0 7 3 1 1 4 0 156 11 5 172 1%7:45 AM 8:00 AM 0 187 1 7 0 1 0 7 0 187 9 7 203 1%8:00 AM 8:15 AM 0 141 1 6 3 3 0 4 0 141 13 4 158 0%8:15 AM 8:30 AM 0 132 0 5 3 2 2 7 1 132 10 10 152 1%8:30 AM 8:45 AM 1 136 1 6 0 1 1 1 0 137 8 2 147 2%8:45 AM 9:00 AM 1 134 0 6 0 2 3 3 0 135 8 6 149 1%9:00 AM 9:15 AM 1 120 0 3 1 3 3 5 1 121 7 9 137 2%9:15 AM 9:30 AM 0 120 1 7 2 1 3 7 1 120 11 11 142 3%9:30 AM 9:45 AM 3 102 1 6 2 1 1 3 1 105 10 5 120 2%9:45 AM 10:00 AM 0 141 1 6 3 2 0 5 1 141 12 6 159 0%

APD in Total Volume Class by Class ComparisonAverage 1% 1 2+3 4 5 6 7 8 9 10StDev 1% TIRTL 11 2004 16 83 22 23 17 65 6

Manual 9 2013 8 84 28 21 11 62 6Traffic Composition

TIRTL ManualPC 89.7% 90.2% 4-Hour Volume DifferenceSU 6.4% 6.3% 5 vehiclesTT 3.9% 3.5% 4-Hour Volume Difference (%)

0.2%

C-5

STIP APD inTotal VolTotal APD in Total Volume

6:00 AM 6:15 AM Average 2%6:15 AM 6:30 AM StDev 2%6:30 AM 6:45 AM 122 0%6:45 AM 7:00 AM 135 0%7:00 AM 7:15 AM 127 1%7:15 AM 7:30 AM 142 2%7:30 AM 7:45 AM 172 1%7:45 AM 8:00 AM 206 2%8:00 AM 8:15 AM 162 3%8:15 AM 8:30 AM 151 1% 3.5-Hour Volume Difference8:30 AM 8:45 AM 150 0% 31 vehicles8:45 AM 9:00 AM 154 3%9:00 AM 9:15 AM 138 3% 3.5-Hour Volume Diff (%)9:15 AM 9:30 AM 144 4% 1.5%9:30 AM 9:45 AM 119 2%9:45 AM 10:00 AM 168 6%

Summary Site #1 - US 119 NB Day 1

Abs % Difference Traffic Composition 4-Hour VolumeAverage Stdev PC SU TT Difference %

TIRTL 1.3% 1% 89.7% 6.4% 3.9% 5 0.2%SAS-1 1.1% 1% 1.1% 56.5% 42.4% 20 1.0%RTMS 6.1% 5% 95.6% 3.1% 1.3% 91 4.1%SmartSen 6.1% 4% 70.7% 24.5% 4.8% 129 5.8%STIP 2.0% 2% --- --- --- 31 1.5%Manual --- --- 90.2% 6.3% 3.5% --- ---

Statistically Significant Difference in Total Volume based on 15-minuteaverage APD data

sem actual diff ad/sem sig diffTIRTL vs SAS-1 0.4% 0.1% 0.36 NoRTMS vs SS 1.5% 0.0% 0.02 NoRTMS vs TIRTL 1.2% 4.8% 3.99 YesSS vs SAS-1 0.9% 5.0% 5.26 YesSTIP vs TIRTL 0.5% 0.7% 1.39 NoSTIP vs RTMS 1.3% 4.1% 3.09 YesSTIP vs SAS-1 0.5% 0.8% 1.58 Nosem = standard error of the mean

D-1

APPENDIX D - Tasks 1 and 2 Site #2: S.R. 0040 Westbound Test Results

D-2


2:00 PM 2:15 PM 86 2 3 912:15 PM 2:30 PM 103 6 6 1152:30 PM 2:45 PM 105 7 1 1132:45 PM 3:00 PM 72 4 4 803:00 PM 3:15 PM 104 8 0 1123:15 PM 3:30 PM 90 4 0 943:30 PM 3:45 PM 111 8 1 1203:45 PM 4:00 PM 123 2 1 1264:00 PM 4:15 PM 126 2 1 1294:15 PM 4:30 PM 102 3 2 1074:30 PM 4:45 PM 121 2 2 1254:45 PM 5:00 PM 118 1 1 1205:00 PM 5:15 PM 125 1 1 1275:15 PM 5:30 PM 129 4 0 1335:30 PM 5:45 PM 106 0 0 1065:45 PM 6:00 PM 70 0 0 70


Manual FHWA ClassClass 1 Class 2+3 Class 4 Class 5 Class 6 Class 7 Class 8 Class 9 Class 10

1 85 0 2 0 0 0 3 01 102 1 3 0 2 2 3 12 103 2 3 1 1 0 1 00 72 0 1 0 3 1 3 00 104 1 3 1 3 0 0 01 89 0 1 0 3 0 0 02 109 2 2 2 2 0 1 00 123 0 0 0 2 0 1 01 125 1 1 0 0 1 0 00 102 0 2 1 0 1 1 01 120 1 1 0 0 1 1 00 118 1 0 0 0 0 1 01 124 1 0 0 0 1 0 01 128 1 2 1 0 0 0 01 105 0 0 0 0 0 0 01 69 0 0 0 0 0 0 013 1678 11 21 6 16 7 15 1

D-3

SAS-1 by Smartek APD inPC SU TT TOTAL Total Vol APD in Total Volume

2:00 PM 2:15 PM 13 57 1 71 22% Average 20%2:15 PM 2:30 PM 16 74 4 94 18% StDev 4%2:30 PM 2:45 PM 10 81 5 96 15%2:45 PM 3:00 PM 7 54 3 64 20% Traffic Composition3:00 PM 3:15 PM 16 71 4 91 19% SAS-1 Manual3:15 PM 3:30 PM 8 66 3 77 18% PC 13.9% 95.0%3:30 PM 3:45 PM 10 82 7 99 18% SU 83.0% 3.4%3:45 PM 4:00 PM 11 92 1 104 17% TT 3.2% 1.6%4:00 PM 4:15 PM 18 86 2 106 18%4:15 PM 4:30 PM 8 66 1 75 30% 3.25-Hour Volume Difference4:30 PM 4:45 PM 14 82 3 99 21% -297 vehicles4:45 PM 5:00 PM 17 72 1 90 25%5:00 PM 5:15 PM 13 81 2 96 24% 3.25-Hour Volume Difference %5:15 PM 5:30 PM DATA NOT AVAILABLE FROM VENDOR -20.4%5:30 PM 5:45 PM DATA NOT AVAILABLE FROM VENDOR5:45 PM 6:00 PM DATA NOT AVAILABLE FROM VENDOR


2:00 PM 2:15 PM 88 1 2 91 0% Average 2%2:15 PM 2:30 PM 103 8 3 114 1% StDev 1%2:30 PM 2:45 PM 109 5 1 115 2%2:45 PM 3:00 PM 70 3 3 76 5% Traffic Composition3:00 PM 3:15 PM 99 10 1 110 2% SS Manual3:15 PM 3:30 PM 87 7 0 94 0% PC 94.8% 95.6%3:30 PM 3:45 PM 117 7 0 124 3% SU 4.3% 3.1%3:45 PM 4:00 PM 125 4 0 129 2% TT 0.8% 1.3%4:00 PM 4:15 PM 117 11 0 128 1%4:15 PM 4:30 PM 108 1 1 110 3% 4-Hour Volume Difference4:30 PM 4:45 PM 118 1 2 121 3% 8 vehicles4:45 PM 5:00 PM 121 2 0 123 3%5:00 PM 5:15 PM 119 6 1 126 1% 4-Hour Volume Difference (%)5:15 PM 5:30 PM 128 6 1 135 2% 0.5%5:30 PM 5:45 PM 107 3 0 110 4%5:45 PM 6:00 PM 67 3 0 70 0%

D-4


2:00 PM 2:15 PM 72 1 1 74 19% Average 25%2:15 PM 2:30 PM 80 4 1 85 26% StDev 5%2:30 PM 2:45 PM 89 0 2 91 19%2:45 PM 3:00 PM 60 1 1 62 23% Traffic Composition3:00 PM 3:15 PM 80 1 2 83 26% RTMS Manual3:15 PM 3:30 PM 68 2 0 70 26% PC 98.0% 95.6%3:30 PM 3:45 PM 96 3 1 100 17% SU 1.4% 3.1%3:45 PM 4:00 PM 91 0 0 91 28% TT 0.6% 1.3%4:00 PM 4:15 PM 95 1 0 96 26%4:15 PM 4:30 PM 80 2 0 82 23% 4-Hour Volume Difference4:30 PM 4:45 PM 89 1 0 90 28% -440 vehicles4:45 PM 5:00 PM 86 0 0 86 28%5:00 PM 5:15 PM 89 2 0 91 28% 4-Hour Volume Difference (%)5:15 PM 5:30 PM 92 1 0 93 30% -24.9%5:30 PM 5:45 PM 87 0 0 87 18%5:45 PM 6:00 PM 47 0 0 47 33%

TIRTL by Control SpecialistsFHWA Classes APD in

1 2+3 4 5 6 7 8 9 10 PC SU TT Total Total Vol6:00 AM 6:15 AM 1 87 1 0 0 0 0 2 1 88 1 3 92 1%6:15 AM 6:30 AM 1 103 1 2 0 2 2 4 0 104 5 6 115 0%6:30 AM 6:45 AM 2 108 1 0 0 1 1 1 0 110 2 2 114 1%6:45 AM 7:00 AM 0 69 1 1 0 4 1 2 1 69 6 4 79 1%7:00 AM 7:15 AM 0 104 2 2 1 2 0 0 0 104 7 0 111 1%7:15 AM 7:30 AM 1 90 0 0 0 3 0 1 0 91 3 1 95 1%7:30 AM 7:45 AM 2 111 1 2 2 2 0 1 0 113 7 1 121 1%7:45 AM 8:00 AM 0 123 0 1 0 2 0 1 0 123 3 1 127 1%8:00 AM 8:15 AM 1 124 0 2 0 0 1 0 0 125 2 1 128 1%8:15 AM 8:30 AM 0 101 0 2 0 0 2 0 0 101 2 2 105 2%8:30 AM 8:45 AM 1 113 1 1 0 0 1 1 0 114 2 2 118 6%8:45 AM 9:00 AM 0 117 0 2 0 0 0 1 0 117 2 1 120 0%9:00 AM 9:15 AM 1 121 0 3 0 0 1 0 0 122 3 1 126 1%9:15 AM 9:30 AM 1 132 1 1 1 0 1 0 0 133 3 1 137 3%9:30 AM 9:45 AM 1 104 0 0 0 0 1 0 0 105 0 1 106 0%9:45 AM 10:00 AM 1 69 0 1 0 0 0 0 0 70 1 0 71 1%



TIRTL Manual 4-Hour Volume DifferencePC 95.7% 95.6% -3 vehiclesSU 2.8% 3.1%TT 1.5% 1.3% 4-Hour Volume Difference (%)

-0.2%

D-5

ATR APD inTotal VolPC SU TT Total APD in Total Volume

2:00 PM 2:15 PM 91 1 3 95 4% Average 5%2:15 PM 2:30 PM 95 7 2 104 10% StDev 3%2:30 PM 2:45 PM 114 4 2 120 6%2:45 PM 3:00 PM 74 5 3 82 3% Traffic Composition3:00 PM 3:15 PM 98 4 0 102 9% ATR Manual3:15 PM 3:30 PM 93 1 0 94 0% PC 96.5% 95.6%3:30 PM 3:45 PM 114 8 1 123 3% SU 2.5% 3.1%3:45 PM 4:00 PM 121 1 1 123 2% TT 1.0% 1.3%4:00 PM 4:15 PM 122 2 0 124 4%4:15 PM 4:30 PM 110 2 2 114 7% 4-Hour Volume Difference4:30 PM 4:45 PM 113 2 1 116 7% -12 vehicles4:45 PM 5:00 PM 123 0 1 124 3%5:00 PM 5:15 PM 121 2 1 124 2% 4-Hour Volume Diff (%)5:15 PM 5:30 PM 124 3 0 127 5% -0.7%5:30 PM 5:45 PM 115 2 0 117 10%5:45 PM 6:00 PM 67 0 0 67 4%


Summary: Site #2 - US 40 WB Day 1


TIRTL 1% 1% 95.7% 2.8% 1.5% -3 -0.2%SmartSen 2% 1% 94.8% 4.3% 0.8% 8 0.5%RTMS 25% 5% 98.0% 1.4% 0.6% -440 -24.9%SAS-1 20% 4% 13.9% 83.0% 3.2% -297 -20.4%ATR 5% 3% 96.5% 2.5% 1.0% -12 -0.7%Manual --- --- 95.6% 3.1% 1.3% --- ---

Statistically Significant Difference in Total Volume based on 15-minuteAPD data

sem actual diff ad/sem sig diffTIRTL vs SS 0.5% 0.6% 1.22 NoRTMS vs SAS-1 1.5% 4.4% 2.87 YesRTMS vs TIRTL 1.2% 23.6% 19.34 YesSS vs SAS-1 1.2% 18.5% 15.68 YesATR vs TIRTL 0.8% 3.7% 4.51 YesATR vs SS 0.8% 3.0% 3.67 Yessem = standard error of the mean

E-1

APPENDIX E - Tasks 1 and 2 Site #2: S.R. 0040 Eastbound Test Results

E-2




Manual FHWA ClassificationClass 1 Class 2+3 Class 4 Class 5 Class 6 Class 7 Class 8 Class 9 Class 10

0 78 1 4 1 0 0 1 01 76 1 1 1 0 0 1 01 91 0 1 3 0 1 1 04 99 1 3 2 0 0 1 01 110 2 2 1 1 1 0 00 131 0 2 5 0 0 0 00 114 1 3 1 0 0 1 03 91 0 1 3 0 0 0 02 107 2 1 2 0 0 1 00 125 0 2 3 0 1 5 03 126 1 3 3 0 0 2 00 113 0 2 4 0 0 0 02 112 0 7 3 0 0 1 02 100 0 0 1 0 0 1 00 100 0 3 2 0 0 3 00 85 1 3 5 0 0 0 019 1658 10 38 40 1 3 18 0

E-3

SAS-1 by Smartek APD inTotal VolPC SU TT TOTAL APD in Total Volume

2:00 PM 2:15 PM 3 73 10 86 1% Average 2%2:15 PM 2:30 PM 5 66 12 83 2% StDev 1%2:30 PM 2:45 PM 5 81 14 100 2%2:45 PM 3:00 PM 4 102 3 109 1% Traffic Composition3:00 PM 3:15 PM 8 85 21 114 3% SAS-1 Manual3:15 PM 3:30 PM 4 128 5 137 1% PC 5.6% 93.9%3:30 PM 3:45 PM 7 112 3 122 2% SU 86.7% 5.0%3:45 PM 4:00 PM 10 85 2 97 1% TT 7.7% 1.2%4:00 PM 4:15 PM 4 106 8 118 3%4:15 PM 4:30 PM 11 116 12 139 2% 3.25-Hour Volume Difference4:30 PM 4:45 PM 11 119 9 139 1% 10 vehicles4:45 PM 5:00 PM 7 111 3 121 2%5:00 PM 5:15 PM 5 108 13 126 1% 3.25-Hour Volume Difference %5:15 PM 5:30 PM DATA NOT AVAILABLE FROM VENDOR 0.7%5:30 PM 5:45 PM DATA NOT AVAILABLE FROM VENDOR5:45 PM 6:00 PM DATA NOT AVAILABLE FROM VENDOR

Smart Sensor by WavetronixTotal APD in

PC SU TT TOTAL Total Vol APD in Total Volume2:00 PM 2:15 PM 73 12 3 88 4% Average 4%2:15 PM 2:30 PM 79 15 2 96 19% StDev 4%2:30 PM 2:45 PM 78 23 0 101 3%2:45 PM 3:00 PM 101 13 4 118 7% Traffic Composition3:00 PM 3:15 PM 93 24 3 120 2% SS Manual3:15 PM 3:30 PM 104 36 0 140 1% PC 80.8% 93.8%3:30 PM 3:45 PM 107 14 3 124 3% SU 17.0% 5.0%3:45 PM 4:00 PM 78 25 0 103 5% TT 2.1% 1.2%4:00 PM 4:15 PM 105 14 2 121 5%4:15 PM 4:30 PM 115 19 7 141 4% 4-Hour Volume Difference4:30 PM 4:45 PM 112 24 2 138 0% 66 vehicles4:45 PM 5:00 PM 110 13 1 124 4%5:00 PM 5:15 PM 105 19 2 126 1% 4-Hour Volume Difference (%)5:15 PM 5:30 PM 84 22 4 110 6% 3.7%5:30 PM 5:45 PM 87 18 5 110 2%5:45 PM 6:00 PM 65 26 2 93 1%

E-4


2:00 PM 2:15 PM 83 3 0 86 1% Average 3%2:15 PM 2:30 PM 83 2 0 85 5% StDev 2%2:30 PM 2:45 PM 98 0 2 100 2%2:45 PM 3:00 PM 105 3 0 108 2% Traffic Composition3:00 PM 3:15 PM 115 4 0 119 1% RTMS Manual3:15 PM 3:30 PM 142 0 0 142 3% PC 96.9% 93.8%3:30 PM 3:45 PM 120 2 1 123 3% SU 2.6% 5.0%3:45 PM 4:00 PM 96 2 0 98 0% TT 0.5% 1.2%4:00 PM 4:15 PM 120 0 0 120 4%4:15 PM 4:30 PM 124 8 4 136 0% 4-Hour Volume Difference4:30 PM 4:45 PM 129 4 0 133 4% 24 vehicles4:45 PM 5:00 PM 127 4 0 131 10%5:00 PM 5:15 PM 118 3 0 121 3% 4-Hour Volume Difference (%)5:15 PM 5:30 PM 100 4 1 105 1% 1.3%5:30 PM 5:45 PM 102 4 1 107 1%5:45 PM 6:00 PM 93 4 0 97 3%

TIRTL by Control Specialists APD inTotal VolFHWA Classes

1 2+3 4 5 6 7 8 9 10 PC SU TT Total6:00 AM 6:15 AM 0 80 2 1 1 0 0 1 0 80 4 1 85 0%6:15 AM 6:30 AM 1 75 0 1 1 0 0 1 0 76 2 1 79 2%6:30 AM 6:45 AM 1 91 1 0 4 0 0 1 0 92 5 1 98 0%6:45 AM 7:00 AM 4 100 0 2 2 0 0 1 0 104 4 1 109 1%7:00 AM 7:15 AM 1 111 2 2 1 0 1 1 0 112 5 2 119 1%7:15 AM 7:30 AM 0 128 1 1 5 0 0 0 0 128 7 0 135 2%7:30 AM 7:45 AM 0 116 1 1 1 0 0 1 0 116 3 1 120 0%7:45 AM 8:00 AM 2 90 0 3 3 0 0 0 0 92 6 0 98 0%8:00 AM 8:15 AM 2 110 1 0 2 0 0 1 0 112 3 1 116 1%8:15 AM 8:30 AM 0 126 0 2 3 0 1 5 0 126 5 6 137 1%8:30 AM 8:45 AM 3 129 0 3 3 0 0 1 1 132 6 2 140 1%8:45 AM 9:00 AM 0 112 0 2 4 0 0 0 0 112 6 0 118 1%9:00 AM 9:15 AM 2 112 0 6 3 0 1 1 0 114 9 2 125 0%9:15 AM 9:30 AM 2 98 0 1 2 0 2 1 0 100 3 3 106 2%9:30 AM 9:45 AM 0 100 0 3 2 0 1 3 0 100 5 4 109 1%9:45 AM 10:00 AM 0 85 0 3 5 0 0 0 0 85 8 0 93 1%



TIRTL Manual 4-Hour Volume DifferencePC 94.1% 93.8% 0 vehiclesSU 4.5% 5.0%TT 1.4% 1.2% 4-Hour Volume Difference (%)

0.0%

E-5

ATR APD inPC SU TT Total Total Vol APD in Total Volume

2:00 PM 2:15 PM 82 3 1 86 1% Average 3%2:15 PM 2:30 PM 76 1 1 78 4% StDev 2%2:30 PM 2:45 PM 97 4 1 102 4%2:45 PM 3:00 PM 103 3 1 107 3% Traffic Composition3:00 PM 3:15 PM 116 3 0 119 1% ATR Actual3:15 PM 3:30 PM 127 8 0 135 2% PC 95.8% 93.8%3:30 PM 3:45 PM 112 3 1 116 3% SU 3.1% 5.0%3:45 PM 4:00 PM 96 2 0 98 0% TT 1.1% 1.2%4:00 PM 4:15 PM 118 3 1 122 6%4:15 PM 4:30 PM 124 2 5 131 4% 4-Hour Volume Difference4:30 PM 4:45 PM 139 5 2 146 6% 4 vehicles4:45 PM 5:00 PM 112 4 0 116 3%5:00 PM 5:15 PM 113 4 2 119 5% 4-Hour Volume Error (%)5:15 PM 5:30 PM 110 2 2 114 10% 0.2%5:30 PM 5:45 PM 104 3 3 110 2%5:45 PM 6:00 PM 86 6 0 92 2%


Summary: Site #2 - US 40 EB Day 1


TIRTL 1% 1% 94.1% 4.5% 1.4% 0 0.0%SmartSen 4% 4% 80.8% 17.0% 2.1% 66 3.7%SAS-1 2% 2% 5.6% 86.7% 7.7% 10 0.7%RTMS 3% 2% 96.9% 2.6% 0.5% 24 1.3%ATR 3% 2% 95.8% 3.1% 1.1% 4 0.2%Manual --- --- 93.8% 5.0% 1.2% --- ---


sem actual diff ad/sem sig diffTIRTL vs SS 1.2% 3.3% 2.79 YesRTMS vs SAS-1 0.7% 1.0% 1.55 NoRTMS vs TIRTL 0.6% 1.8% 2.73 YesSS vs SAS-1 1.1% 2.5% 2.27 YesATR vs TIRTL 0.6% 2.5% 4.04 YesATR vs SS 1.2% 0.8% 0.61 Nosem = standard error of the mean

F-1

APPENDIX F - Tasks 1 and 2 Site #3: S.R. 0119 Northbound Test Results

F-2





0 77 0 1 2 0 0 0 00 82 2 2 1 0 0 3 00 97 1 5 1 1 0 3 00 116 2 2 0 1 0 2 01 114 0 6 5 2 0 2 10 115 3 4 1 1 1 4 00 165 1 10 0 3 1 5 01 203 2 5 4 4 0 6 10 144 0 8 0 1 1 6 00 136 0 8 1 1 0 4 03 115 0 2 2 1 0 4 01 122 2 7 3 0 1 1 01 140 0 7 1 2 2 6 00 127 0 8 1 0 3 10 12 98 0 7 1 4 2 9 01 117 0 5 2 3 3 4 010 1968 13 87 25 24 14 69 3

F-3

SAS-1 by Smartek Total APD inPC SU TT TOTAL Total Vol APD in Total Volume

6:00 AM 6:15 AM 0 76 2 78 3% Average 1%6:15 AM 6:30 AM 0 72 20 92 2% StDev 1%6:30 AM 6:45 AM 0 63 44 107 1%6:45 AM 7:00 AM 1 78 46 125 2% Traffic Composition7:00 AM 7:15 AM 1 88 43 132 1% SAS-1 Manual7:15 AM 7:30 AM 0 85 44 129 0% PC 0.6% 89.5%7:30 AM 7:45 AM 2 99 86 187 1% SU 64.5% 6.7%7:45 AM 8:00 AM 1 127 97 225 0% TT 35.0% 3.8%8:00 AM 8:15 AM 5 71 86 162 1%8:15 AM 8:30 AM 0 79 74 153 2% 3.75-Hour Volume Difference8:30 AM 8:45 AM 0 86 40 126 1% 16 vehicles8:45 AM 9:00 AM 0 95 44 139 1%9:00 AM 9:15 AM 1 139 20 160 1% 3.75 Hour Volume Difference (%)9:15 AM 9:30 AM 0 110 42 152 1% 0.8%9:30 AM 9:45 AM 1 67 59 127 3%9:45 AM 10:00 AM DATA NOT AVAILABLE FROM VENDOR


PC SU TT TOTAL Total Vol APD in Total Volume6:00 AM 6:15 AM 32 44 2 78 3% Average 2%6:15 AM 6:30 AM 50 38 5 93 3% StDev 1%6:30 AM 6:45 AM 59 43 7 109 1%6:45 AM 7:00 AM 56 66 4 126 2% Traffic Composition7:00 AM 7:15 AM 70 53 10 133 2% SS Manual7:15 AM 7:30 AM 59 64 9 132 2% PC 51.2% 89.4%7:30 AM 7:45 AM 102 77 9 188 2% SU 42.7% 6.7%7:45 AM 8:00 AM 115 98 15 228 1% TT 6.1% 3.9%8:00 AM 8:15 AM 100 51 8 159 1%8:15 AM 8:30 AM 91 61 4 156 4% 4-Hour Volume Difference8:30 AM 8:45 AM 74 51 4 129 2% 32 vehicles8:45 AM 9:00 AM 56 77 7 140 2%9:00 AM 9:15 AM 86 58 11 155 3% 4-Hour Volume Difference (%)9:15 AM 9:30 AM 80 60 15 155 3% 1.4%9:30 AM 9:45 AM 59 50 18 127 3%9:45 AM 10:00 AM 61 68 8 137 1%

F-4


6:00 AM 6:15 AM 82 0 0 82 3% Average 2%6:15 AM 6:30 AM 92 2 0 94 4% StDev 1%6:30 AM 6:45 AM 103 4 0 107 1%6:45 AM 7:00 AM 122 0 1 123 0% Traffic Composition7:00 AM 7:15 AM 124 7 1 132 1% RTMS Manual7:15 AM 7:30 AM 126 7 1 134 4% PC 96.1% 89.4%7:30 AM 7:45 AM 181 5 1 187 1% SU 3.3% 6.7%7:45 AM 8:00 AM 222 4 3 229 1% TT 0.5% 3.9%8:00 AM 8:15 AM 155 7 0 162 1%8:15 AM 8:30 AM 148 4 0 152 1% 4-Hour Volume Difference8:30 AM 8:45 AM 125 5 1 131 3% 34 vehicles8:45 AM 9:00 AM 134 2 0 136 1%9:00 AM 9:15 AM 157 8 0 165 4% 4-Hour Volume Difference (%)9:15 AM 9:30 AM 139 8 3 150 0% 1.5%9:30 AM 9:45 AM 117 8 1 126 2%9:45 AM 10:00 AM 133 4 0 137 1%

TIRTL by Control Specialists APD inTotalVol

FHWA Classes1 2+3 4 5 6 7 8 9 10 PC SU TT Total

6:00 AM 6:15 AM 1 67 0 2 1 0 0 0 0 68 3 0 71 11%6:15 AM 6:30 AM 0 51 0 1 1 1 1 2 1 51 3 4 58 36%6:30 AM 6:45 AM 0 76 1 7 1 1 0 3 0 76 10 3 89 18%6:45 AM 7:00 AM 0 86 2 2 0 1 0 2 0 86 5 2 93 24%7:00 AM 7:15 AM 1 87 2 3 5 2 2 2 2 88 12 6 106 19%7:15 AM 7:30 AM 0 81 2 7 1 2 1 4 0 81 12 5 98 24%7:30 AM 7:45 AM 2 142 3 7 0 3 0 4 0 144 13 4 161 13%7:45 AM 8:00 AM 1 162 2 6 5 4 3 5 1 163 17 9 189 16%8:00 AM 8:15 AM 1 119 1 2 1 0 3 6 0 120 4 9 133 17%8:15 AM 8:30 AM 1 105 0 8 1 1 0 3 0 106 10 3 119 21%8:30 AM 8:45 AM 0 96 2 2 2 1 0 5 0 96 7 5 108 15%8:45 AM 9:00 AM 3 97 2 7 3 0 0 0 0 100 12 0 112 18%9:00 AM 9:15 AM 1 110 1 4 1 1 3 6 0 111 7 9 127 20%9:15 AM 9:30 AM 0 105 2 9 1 0 3 9 1 105 12 13 130 13%9:30 AM 9:45 AM 3 73 1 10 0 4 3 8 0 76 15 11 102 17%9:45 AM 10:00 AM 1 89 1 4 2 3 3 4 0 90 10 7 107 21%




-18.5%

F-5

STIP APD inTotal Total Vol APD in Total Volume

6:00 AM 6:15 AM Average 15%6:15 AM 6:30 AM StDev 10%6:30 AM 6:45 AM6:45 AM 7:00 AM7:00 AM 7:15 AM7:15 AM 7:30 AM7:30 AM 7:45 AM7:45 AM 8:00 AM8:00 AM 8:15 AM8:15 AM 8:30 AM 1-Hour Volume Difference8:30 AM 8:45 AM 17 vehicles8:45 AM 9:00 AM9:00 AM 9:15 AM 165 30% 1-Hour Volume Difference (%)9:15 AM 9:30 AM 147 7% 3.0%9:30 AM 9:45 AM 136 14%9:45 AM 10:00 AM 136 9%

Summary: Site #3 - US 119 NB Day 2


SAS-1 1.4% 1% 0.6% 64.5% 35.0% 16 0.8%SmartSen 2.2% 1% 51.2% 42.7% 6.1% 32 1.4%RTMS 1.8% 1% 96.1% 3.3% 0.5% 34 1.5%TIRTL 19% 6% 86.6% 8.4% 5.0% -410 -18.5%

Manual --- --- 89.4% 6.7% 3.9% --- ---


sem actual diff ad/sem sig diffSAS-1 vs SS 0.3% 0.8% 2.43 YesSS vs RTMS 0.4% 0.3% 0.80 NoRTMS vs SAS-1 0.4% 0.5% 1.13 NoSS vs TIRTL 1.5% 16.8% 11.49 Yessem = standard error of the mean

G-1

APPENDIX G - Tasks 1 and 2 Site #3: S.R. 0119 Southbound Test Results

G-2





0 114 0 1 3 0 0 1 00 109 1 2 1 0 0 3 10 160 3 9 4 0 0 7 11 176 0 9 3 0 1 2 00 145 0 7 4 2 1 4 10 168 2 15 3 2 1 6 10 187 0 9 2 4 1 5 01 196 0 11 2 0 1 2 10 153 1 6 6 0 0 6 01 158 2 7 3 0 2 9 00 177 0 8 4 1 2 5 01 141 1 6 2 0 2 5 01 139 2 10 1 1 2 4 00 152 0 10 0 3 3 2 00 168 2 8 1 1 0 10 00 165 0 9 3 0 3 6 15 2508 14 127 42 14 19 77 6

G-3


6:00 AM 6:15 AM 16 10 93 119 0% Average 3%6:15 AM 6:30 AM 23 13 93 129 10% StDev 3%6:30 AM 6:45 AM 34 11 144 189 3%6:45 AM 7:00 AM 20 22 146 188 2% Traffic Composition7:00 AM 7:15 AM 22 28 118 168 2% SAS-1 Manual7:15 AM 7:30 AM 44 36 130 210 6% PC 14.7% 89.4%7:30 AM 7:45 AM 26 21 159 206 1% SU 11.3% 7.0%7:45 AM 8:00 AM 21 28 161 210 2% TT 74.0% 3.5%8:00 AM 8:15 AM 24 12 138 174 1%8:15 AM 8:30 AM 36 26 129 191 5% 3.75-Hour Volume Difference8:30 AM 8:45 AM 26 19 153 198 1% 27 vehicles8:45 AM 9:00 AM 21 19 115 155 2%9:00 AM 9:15 AM 23 16 117 156 3% 3.75 Hour Volume Difference (%)9:15 AM 9:30 AM 26 17 126 169 1% 1.0%9:30 AM 9:45 AM 24 14 152 190 0%9:45 AM 10:00 AM DATA NOT AVAILABLE FROM VENDOR


6:00 AM 6:15 AM 21 97 5 123 3% Average 2%6:15 AM 6:30 AM 14 98 8 120 3% StDev 1%6:30 AM 6:45 AM 38 130 19 187 2%6:45 AM 7:00 AM 26 156 12 194 1% Traffic Composition7:00 AM 7:15 AM 16 134 15 165 1% SS Manual7:15 AM 7:30 AM 36 144 22 202 2% PC 15.5% 89.4%7:30 AM 7:45 AM 31 159 17 207 0% SU 75.4% 7.0%7:45 AM 8:00 AM 40 158 15 213 0% TT 9.1% 3.6%8:00 AM 8:15 AM 26 131 18 175 2%8:15 AM 8:30 AM 40 127 21 188 3% 4-Hour Volume Difference8:30 AM 8:45 AM 26 153 18 197 0% 24 vehicles8:45 AM 9:00 AM 20 120 14 154 3%9:00 AM 9:15 AM 13 125 19 157 2% 4-Hour Volume Difference (%)9:15 AM 9:30 AM 36 119 18 173 2% 0.9%9:30 AM 9:45 AM 33 137 20 190 0%9:45 AM 10:00 AM 24 150 17 191 2%

G-4


6:00 AM 6:15 AM 119 2 0 121 2% Average 1%6:15 AM 6:30 AM 116 3 0 119 2% StDev 1%6:30 AM 6:45 AM 178 8 0 186 1%6:45 AM 7:00 AM 184 3 0 187 3% Traffic Composition7:00 AM 7:15 AM 159 7 0 166 1% RTMS Manual7:15 AM 7:30 AM 192 8 0 200 1% PC 96.5% 89.4%7:30 AM 7:45 AM 201 4 1 206 1% SU 3.5% 7.0%7:45 AM 8:00 AM 207 4 0 211 1% TT 0.1% 3.6%8:00 AM 8:15 AM 167 7 0 174 1%8:15 AM 8:30 AM 173 8 1 182 0% 4-Hour Volume Difference8:30 AM 8:45 AM 190 8 0 198 1% -4 vehicles8:45 AM 9:00 AM 151 5 0 156 1%9:00 AM 9:15 AM 149 5 0 154 4% 4-Hour Volume Difference (%)9:15 AM 9:30 AM 167 3 0 170 0% -0.1%9:30 AM 9:45 AM 173 13 0 186 2%9:45 AM 10:00 AM 183 9 0 192 3%


1 2+3 4 5 6 7 8 9 10 PC SU TT Total6:00 AM 6:15 AM 9 95 0 4 2 0 2 1 0 104 6 3 113 5%6:15 AM 6:30 AM 4 59 1 3 4 0 0 2 2 63 8 4 75 36%6:30 AM 6:45 AM 7 108 2 11 4 1 2 6 1 115 18 9 142 23%6:45 AM 7:00 AM 12 110 0 10 4 2 1 3 0 122 16 4 142 26%7:00 AM 7:15 AM 10 86 2 4 6 1 0 4 0 96 13 4 113 31%7:15 AM 7:30 AM 7 103 4 12 5 2 2 6 0 110 23 8 141 29%7:30 AM 7:45 AM 14 120 1 5 6 4 1 5 0 134 16 6 156 25%7:45 AM 8:00 AM 12 130 1 9 5 0 2 2 0 142 15 4 161 25%8:00 AM 8:15 AM 10 103 1 4 5 2 1 5 0 113 12 6 131 24%8:15 AM 8:30 AM 14 100 1 7 7 0 2 9 0 114 15 11 140 23%8:30 AM 8:45 AM 10 112 1 4 4 2 3 4 1 122 11 8 141 28%8:45 AM 9:00 AM 13 87 3 5 4 0 2 5 0 100 12 7 119 25%9:00 AM 9:15 AM 15 77 4 9 5 1 1 3 1 92 19 5 116 28%9:15 AM 9:30 AM 10 93 3 3 3 3 3 2 0 103 12 5 120 29%9:30 AM 9:45 AM 4 102 7 2 2 1 0 10 0 106 12 10 128 33%9:45 AM 10:00 AM 11 107 3 4 7 0 2 6 1 118 14 9 141 25%




-26.0%

G-5

STIP APD inTotal Total Vol APD in Total Volume

6:00 AM 6:15 AM 120 1% Average 3%6:15 AM 6:30 AM 121 3% StDev 4%6:30 AM 6:45 AM 185 1%6:45 AM 7:00 AM 190 1%7:00 AM 7:15 AM 164 0%7:15 AM 7:30 AM 168 15%7:30 AM 7:45 AM 214 3%7:45 AM 8:00 AM 215 0%8:00 AM 8:15 AM 174 1%8:15 AM 8:30 AM 173 5% 4-Hour Volume Difference8:30 AM 8:45 AM 200 2% -43 vehicles8:45 AM 9:00 AM 143 9%9:00 AM 9:15 AM 156 3% 4-Hour Volume Difference (%)9:15 AM 9:30 AM 171 1% -1.5%9:30 AM 9:45 AM 187 2%9:45 AM 10:00 AM 188 1%

Summary: Site #3 - US 119 SB Day 2


SmartSen 1.6% 1% 15.5% 75.4% 9.1% 24 0.9%SAS-1 2.5% 3% 14.7% 11.3% 74.0% 27 1.0%RTMS 1.4% 1% 96.5% 3.5% 0.1% -4 -0.1%TIRTL 26% 7% 84.3% 10.7% 5.0% -731 -26.0%STIP 2.9% 4% --- --- --- -43 -1.5%Manual --- --- 89.4% 7.0% 3.6% --- ---


sem actual diff ad/sem sig diffSAS-1 vs SS 0.8% 0.9% 1.24 NoSAS-1 vs RTMS 0.7% 1.1% 1.46 NoRTMS vs SS 0.4% 0.1% 0.41 NoSS vs TIRTL 1.7% 24.3% 14.40 YesSTIP vs SS 1.0% 1.3% 1.27 NoSTIP vs RTMS 1.0% 1.5% 1.42 No

H-1

APPENDIX H - Tasks 1 and 2 Site #4: S.R. 0040 Westbound Test Results

H-2





3 154 0 3 0 4 0 0 03 166 1 7 0 6 1 2 00 162 0 3 1 2 0 0 15 138 0 5 5 5 0 0 04 146 0 3 1 4 0 2 02 144 2 4 2 4 0 1 11 168 4 5 0 3 0 1 03 177 8 5 0 1 0 1 01 151 1 3 0 3 1 0 02 137 1 4 1 3 0 1 01 169 1 2 1 5 0 3 02 179 0 3 1 2 0 0 01 212 1 2 1 1 0 4 02 192 0 2 0 1 0 0 01 218 0 3 1 2 1 0 01 163 0 1 0 0 1 1 032 2676 19 55 14 46 4 16 2

H-3


1:00 PM 1:15 PM 160 0 0 160 2% Average 5%1:15 PM 1:30 PM 175 0 0 175 6% StDev 2%1:30 PM 1:45 PM 171 0 0 171 1%1:45 PM 2:00 PM 143 0 0 143 9% Traffic Composition2:00 PM 2:15 PM 155 0 0 155 3% SAS-1 Manual2:15 PM 2:30 PM 149 0 0 149 7% PC 100.0% 94.3%2:30 PM 2:45 PM 171 0 0 171 6% SU 0.0% 4.9%2:45 PM 3:00 PM 184 0 0 184 6% TT 0.0% 0.7%3:00 PM 3:15 PM 156 0 0 156 3%3:15 PM 3:30 PM 140 0 0 140 6% 3.75-Hour Volume Difference3:30 PM 3:45 PM 173 0 0 173 5% -136 vehicles3:45 PM 4:00 PM 177 0 0 177 5%4:00 PM 4:15 PM 205 0 0 205 8% 3.75 Hour Volume Difference (%)4:15 PM 4:30 PM 193 0 0 193 2% -5.0%4:30 PM 4:45 PM 209 0 0 209 8%4:45 PM 5:00 PM DATA NOT AVAILABLE FROM VENDOR


1:00 PM 1:15 PM 158 6 0 164 0% Average 3%1:15 PM 1:30 PM 170 7 1 178 4% StDev 2%1:30 PM 1:45 PM 168 7 2 177 5%1:45 PM 2:00 PM 140 10 0 150 5% Traffic Composition2:00 PM 2:15 PM 149 7 1 157 2% SS Manual2:15 PM 2:30 PM 150 7 2 159 1% PC 95.4% 94.6%2:30 PM 2:45 PM 169 9 2 180 1% SU 3.7% 4.7%2:45 PM 3:00 PM 173 9 6 188 4% TT 0.9% 0.8%3:00 PM 3:15 PM 156 6 0 162 1%3:15 PM 3:30 PM 139 2 2 143 4% 4-Hour Volume Difference3:30 PM 3:45 PM 174 9 3 186 2% -31 vehicles3:45 PM 4:00 PM 176 8 2 186 1%4:00 PM 4:15 PM 210 5 3 218 2% 4-Hour Volume Difference (%)4:15 PM 4:30 PM 196 4 0 200 2% -1.1%4:30 PM 4:45 PM 206 5 1 212 6%4:45 PM 5:00 PM 168 5 0 173 4%

H-4

RTMS by EIS (Slow lane was not counted due to setup geometry. Only passing lane was counted.)Total APD inPC SU TT TOTAL Total Vol APD in Total Volume

1:00 PM 1:15 PM 109 0 0 109 42% Average 43%1:15 PM 1:30 PM 117 2 1 120 54% StDev 16%1:30 PM 1:45 PM 108 2 1 111 50%1:45 PM 2:00 PM 93 3 0 96 25% Traffic Composition2:00 PM 2:15 PM 101 2 1 104 63% RTMS Manual2:15 PM 2:30 PM 101 0 1 102 62% PC 97.5% 91.6%2:30 PM 2:45 PM 115 2 0 117 48% SU 2.0% 7.1%2:45 PM 3:00 PM 109 3 0 112 20% TT 0.5% 1.3%3:00 PM 3:15 PM 91 3 0 94 38%3:15 PM 3:30 PM 89 3 1 93 55% 4-Hour Volume Difference3:30 PM 3:45 PM 115 6 1 122 65% 512 vehicles3:45 PM 4:00 PM 105 2 1 108 30%4:00 PM 4:15 PM 116 3 2 121 9% 4-Hour Volume Difference (%)4:15 PM 4:30 PM 117 1 0 118 34% 40.6%4:30 PM 4:45 PM 135 4 0 139 45%4:45 PM 5:00 PM 106 0 0 106 41%


1 2+3 4 5 6 7 8 9 10 PC SU TT Total1:00 PM 1:15 PM 9 154 0 1 0 2 0 2 0 163 3 2 168 2%1:15 PM 1:30 PM 4 137 0 7 0 5 1 3 0 141 12 4 157 16%1:30 PM 1:45 PM 0 139 0 2 3 3 0 0 0 139 8 0 147 13%1:45 PM 2:00 PM 4 114 0 5 5 5 0 1 0 118 15 1 134 15%2:00 PM 2:15 PM 6 112 0 5 1 3 0 1 0 118 9 1 128 20%2:15 PM 2:30 PM 2 121 2 5 0 5 0 1 1 123 12 2 137 14%2:30 PM 2:45 PM 1 139 1 8 0 3 1 1 0 140 12 2 154 15%2:45 PM 3:00 PM 4 146 8 6 0 1 1 0 0 150 15 1 166 15%3:00 PM 3:15 PM 2 127 2 3 0 2 0 1 0 129 7 1 137 14%3:15 PM 3:30 PM 4 103 1 4 1 3 0 0 1 107 9 1 117 21%3:30 PM 3:45 PM 2 135 2 2 2 5 1 2 0 137 11 3 151 17%3:45 PM 4:00 PM 4 144 3 4 1 2 1 0 0 148 10 1 159 15%4:00 PM 4:15 PM 3 173 1 2 0 1 0 3 0 176 4 3 183 18%4:15 PM 4:30 PM 3 151 0 5 1 1 1 0 0 154 7 1 162 18%4:30 PM 4:45 PM 3 177 1 1 1 1 2 0 0 180 4 2 186 18%4:45 PM 5:00 PM 4 143 0 1 0 0 2 1 0 147 1 3 151 10%




-14.9%

H-5

Summary: Site #4 - US 40 WB Day 2


SmartSen 3% 2% 95.4% 3.7% 0.9% -31 -1.1%SAS-1 5% 2% 100.0% 0.0% 0.0% -136 -5.0%TIRTL 15% 4% 93.1% 5.7% 1.1% -427 -14.9%RTMS 43% 16% 97.5% 2.0% 0.5% 512 40.6%

Manual --- --- 94.6% 4.7% 0.8% --- ---

I-1

APPENDIX I - Tasks 1 and 2 Site #4: S.R. 0040 Eastbound Test Results

I-2





0 134 1 1 3 0 1 1 04 160 1 5 2 0 0 2 02 158 3 8 4 0 0 1 06 164 10 5 2 0 0 0 00 155 2 2 3 0 1 0 02 174 0 5 0 0 1 1 03 174 1 2 7 0 1 1 01 146 1 4 3 0 1 3 01 168 2 7 3 0 0 0 11 179 0 5 0 0 2 1 00 219 1 10 6 0 0 0 02 177 0 4 0 0 0 0 02 189 0 2 2 0 1 4 00 165 0 4 2 0 1 4 13 194 0 6 2 0 0 0 00 194 0 4 0 1 0 4 027 2750 22 74 39 1 9 22 2

I-3


1:00 PM 1:15 PM 139 0 0 139 1% Average 3%1:15 PM 1:30 PM 169 0 0 169 3% StDev 3%1:30 PM 1:45 PM 176 0 0 176 0%1:45 PM 2:00 PM 183 0 0 183 2% Traffic Composition2:00 PM 2:15 PM 160 0 0 160 2% SAS-1 Manual2:15 PM 2:30 PM 181 0 0 181 1% PC 100.0% 94.2%2:30 PM 2:45 PM 178 0 0 178 6% SU 0.0% 4.8%2:45 PM 3:00 PM 162 0 0 162 2% TT 0.0% 1.1%3:00 PM 3:15 PM 182 0 0 182 0%3:15 PM 3:30 PM 184 0 0 184 2% 3.75-Hour Volume Difference3:30 PM 3:45 PM 224 0 0 224 5% -31 vehicles3:45 PM 4:00 PM 180 0 0 180 2%4:00 PM 4:15 PM 220 0 0 220 10% 3.75 Hour Volume Difference (%)4:15 PM 4:30 PM 178 0 0 178 1% -1.1%4:30 PM 4:45 PM 196 0 0 196 4%4:45 PM 5:00 PM DATA NOT AVAILABLE FROM VENDOR


PC SU TT TOTAL Total Vol APD in Total Volume1:00 PM 1:15 PM 126 15 1 142 1% Average 2%1:15 PM 1:30 PM 161 13 3 177 2% StDev 1%1:30 PM 1:45 PM 148 25 5 178 1%1:45 PM 2:00 PM 168 22 6 196 5% Traffic Composition2:00 PM 2:15 PM 150 13 2 165 1% SS Manual2:15 PM 2:30 PM 172 13 1 186 2% PC 88.6% 94.3%2:30 PM 2:45 PM 164 22 3 189 0% SU 9.3% 4.6%2:45 PM 3:00 PM 141 18 6 165 4% TT 2.1% 1.1%3:00 PM 3:15 PM 165 13 1 179 2%3:15 PM 3:30 PM 172 12 5 189 1% 4-Hour Volume Difference3:30 PM 3:45 PM 200 27 7 234 1% 36 vehicles3:45 PM 4:00 PM 165 17 0 182 1%4:00 PM 4:15 PM 179 16 9 204 2% 4-Hour Volume Difference (%)4:15 PM 4:30 PM 163 12 6 181 2% 1.2%4:30 PM 4:45 PM 184 22 2 208 1%4:45 PM 5:00 PM 185 16 6 207 2%

I-4


1:00 PM 1:15 PM 139 2 1 142 1% Average 2%1:15 PM 1:30 PM 171 2 1 174 0% StDev 2%1:30 PM 1:45 PM 156 8 4 168 5%1:45 PM 2:00 PM 169 7 0 176 6% Traffic Composition2:00 PM 2:15 PM 157 5 0 162 1% RTMS Manual2:15 PM 2:30 PM 179 0 0 179 2% PC 97.0% 94.3%2:30 PM 2:45 PM 190 3 1 194 3% SU 2.3% 4.6%2:45 PM 3:00 PM 161 6 1 168 6% TT 0.7% 1.1%3:00 PM 3:15 PM 182 3 1 186 2%3:15 PM 3:30 PM 173 5 1 179 5% 4-Hour Volume Difference3:30 PM 3:45 PM 227 13 0 240 2% -6 vehicles3:45 PM 4:00 PM 181 2 0 183 0%4:00 PM 4:15 PM 196 2 3 201 1% 4-Hour Volume Difference (%)4:15 PM 4:30 PM 176 5 2 183 1% -0.2%4:30 PM 4:45 PM 204 2 1 207 1%4:45 PM 5:00 PM 190 4 4 198 2%

TIRTL by Control SpecialistsAPD in

Total VolFHWA Classes1 2+3 4 5 6 7 8 9 10 PC SU TT Total

1:00 PM 1:15 PM 1 117 2 2 6 0 1 1 0 118 10 2 130 8%1:15 PM 1:30 PM 8 112 0 6 4 0 1 1 0 120 10 2 132 24%1:30 PM 1:45 PM 4 104 2 7 4 0 1 2 0 108 13 3 124 30%1:45 PM 2:00 PM 4 110 6 8 1 1 4 0 0 114 16 4 134 28%2:00 PM 2:15 PM 3 101 2 5 5 0 1 0 0 104 12 1 117 28%2:15 PM 2:30 PM 6 122 1 5 3 0 2 1 0 128 9 3 140 23%2:30 PM 2:45 PM 2 127 0 6 7 3 2 0 0 129 16 2 147 22%2:45 PM 3:00 PM 3 99 1 3 5 0 0 0 2 102 9 2 113 29%3:00 PM 3:15 PM 7 112 2 3 3 0 0 0 0 119 8 0 127 30%3:15 PM 3:30 PM 1 136 0 2 4 0 1 0 0 137 6 1 144 23%3:30 PM 3:45 PM 3 146 3 10 8 0 0 0 0 149 21 0 170 28%3:45 PM 4:00 PM 4 116 1 5 3 0 0 0 0 120 9 0 129 30%4:00 PM 4:15 PM 6 125 0 6 4 0 1 4 0 131 10 5 146 27%4:15 PM 4:30 PM 3 117 1 3 3 0 0 5 0 120 7 5 132 25%4:30 PM 4:45 PM 6 139 1 4 2 0 0 0 0 145 7 0 152 26%4:45 PM 5:00 PM 0 137 1 4 4 1 1 3 0 137 10 4 151 26%




-25.7%

I-5

Summary: Site #4 - US 40 EB Day 2


SAS-1 3% 3% 100% 0% 0% -31 -1.1%SmartSen 2% 1% 88.6% 9.3% 2.1% 36 1.2%RTMS 2% 2% 97.0% 2.3% 0.7% -6 -0.2%TIRTL 25% 5% 90.5% 7.9% 1.6% -756 -25.7%

Manual --- --- 94.3% 4.6% 1.1% --- ---

J-1

APPENDIX J - Task 3 Testing Details

J-2

S.R. 0422 Eastbound Data (Microwave Sensor and STIP)

Manual Count (9-7-05)Left Lane Right Lane Total

From To Cars Trucks Total Cars Trucks Total Cars Trucks Total2:00 PM 2:15 PM 228 17 245 288 44 332 516 61 5772:15 PM 2:30 PM 228 23 251 298 43 341 526 66 5922:30 PM 2:45 PM 266 20 286 346 38 384 612 58 6702:45 PM 3:00 PM 242 19 261 363 31 394 605 50 6553:00 PM 3:15 PM 267 12 279 349 38 387 616 50 6663:15 PM 3:30 PM 333 18 351 409 34 443 742 52 7943:30 PM 3:45 PM 355 15 370 435 37 472 790 52 8423:45 PM 4:00 PM 333 11 344 399 31 430 732 42 7744:00 PM 4:15 PM 353 10 363 441 30 471 794 40 8344:15 PM 4:30 PM 369 9 378 421 22 443 790 31 8214:30 PM 4:45 PM 389 15 404 428 18 446 817 33 8504:45 PM 5:00 PM 399 8 407 466 22 488 865 30 895

Composition 93.7% 6.3%

STIP Count (9-7-05)Lane ABS Diff APD

From To Left Right Total From Man2:00 PM 2:15 PM 267 325 592 15 2.6%2:15 PM 2:30 PM 294 338 632 40 6.8%2:30 PM 2:45 PM 343 365 708 38 5.7%2:45 PM 3:00 PM 316 380 696 41 6.3%3:00 PM 3:15 PM 341 369 710 44 6.6%3:15 PM 3:30 PM 393 394 787 7 0.9%3:30 PM 3:45 PM 454 434 888 46 5.5%3:45 PM 4:00 PM 400 401 801 27 3.5%4:00 PM 4:15 PM 449 416 865 31 3.7%4:15 PM 4:30 PM 452 404 856 35 4.3%4:30 PM 4:45 PM 466 434 900 50 5.9%4:45 PM 5:00 PM 445 461 906 11 1.2%

478 483 average 4.4%stdev 2.0%max 6.8%

3-Hour Analysis min 0.9%Manual Total 8970 range 5.9%

STIP Total 9341 median 4.9%APD on Total 4.1% mode 5.5% to 6.5%

J-3

Sensor Count (9-7-05)From To Cars Trucks Total APD

2:00 PM 2:15 PM 534 29 563 2.4%2:15 PM 2:30 PM 545 31 576 2.7%2:30 PM 2:45 PM 645 28 673 0.4%2:45 PM 3:00 PM 598 36 634 3.2%3:00 PM 3:15 PM 633 26 659 1.1%3:15 PM 3:30 PM 750 26 776 2.3%3:30 PM 3:45 PM 791 40 831 1.3%3:45 PM 4:00 PM 720 32 752 2.8%4:00 PM 4:15 PM 778 26 804 3.6%4:15 PM 4:30 PM 766 35 801 2.4%4:30 PM 4:45 PM 814 23 837 1.5%4:45 PM 5:00 PM 889 29 918 2.6%

95.9% 4.1% average 2.2%stdev 0.9%

3-Hour Analysis max 3.6%Manual Total 8970 min 0.4%Sensor Total 8824 range 3.1%

Difference 146 median 2.4%APD on Total 1.6% mode 2.2% to 3.2%

S.R. 0422 Westbound Data (Microwave Sensor and STIP)

STIP Count (9-7-05) Sensor Count (9-7-05)Lane

From To Left Right Total Total APD2:00 PM 2:15 PM 327 420 747 414 44.6%2:15 PM 2:30 PM 352 403 755 444 41.2%2:30 PM 2:45 PM 378 443 821 448 45.4%2:45 PM 3:00 PM 406 462 868 496 42.9%3:00 PM 3:15 PM 509 507 1016 614 39.6%3:15 PM 3:30 PM 562 525 1087 670 38.4%3:30 PM 3:45 PM 600 605 1205 784 34.9%3:45 PM 4:00 PM 604 578 1182 770 34.9%4:00 PM 4:15 PM 612 595 1207 776 35.7%4:15 PM 4:30 PM 622 574 1196 758 36.6%4:30 PM 4:45 PM 598 569 1167 742 36.4%4:45 PM 5:00 PM 639 585 1224 852 30.4%

619 574 1193 average 38.4%stdev 4.5%

3-Hour Analysis max 45.4%STIP Total 12475 min 30.4%

Sensor Total 7768 range 15.0%Difference 4707 median 37.5%

APD on Total 37.7% mode 34.9% to 35.9%

J-4

S.R. 0202 Northbound Data (Microwave Sensor)

Manual Count (9-8-05)Lane

Left Right TotalFrom To Cars Trucks Total Cars Trucks Total Cars Trucks Total

2:00 PM 2:15 PM 293 19 312 220 47 267 513 66 5792:15 PM 2:30 PM 292 24 316 233 52 285 525 76 6012:30 PM 2:45 PM 302 21 323 234 40 274 536 61 5972:45 PM 3:00 PM 352 17 369 264 43 307 616 60 6763:00 PM 3:15 PM 398 11 409 266 49 315 664 60 7243:15 PM 3:30 PM 415 23 438 267 46 313 682 69 7513:45 PM 4:00 PM 483 14 497 310 32 342 793 46 8394:00 PM 4:15 PM 555 18 573 357 36 393 912 54 9664:15 PM 4:30 PM 548 12 560 344 30 374 892 42 9344:30 PM 4:45 PM 579 13 592 381 26 407 960 39 9994:45 PM 5:00 PM 592 6 598 400 16 416 992 22 10145:00 PM 5:15 PM 584 8 592 416 18 434 1000 26 1026

Composition 93.6% 6.4%

Sensor Count (9-8-05)Total

From To Cars Trucks Total Ab Diff APD2:00 PM 2:15 PM 524 31 555 24 4.1%2:15 PM 2:30 PM 551 36 587 14 2.3%2:30 PM 2:45 PM 549 28 577 20 3.4%2:45 PM 3:00 PM 626 21 647 29 4.3%3:00 PM 3:15 PM 665 25 690 34 4.7%3:15 PM 3:30 PM 678 39 717 34 4.5%3:45 PM 4:00 PM 781 25 806 33 3.9%4:00 PM 4:15 PM 865 27 892 74 7.7%4:15 PM 4:30 PM 887 20 907 27 2.9%4:30 PM 4:45 PM 900 17 917 82 8.2%4:45 PM 5:00 PM 921 19 940 74 7.3%5:00 PM 5:15 PM 934 23 957 69 6.7%

96.6% 3.4% average 5.0%3-Hour Analysis stdev 2.0%

Manual Total 9706 max 8.2%Sensor Total 9192 min 2.3%

Difference 514 range 5.9%APD on Total 5.3% median 4.4%

mode 4 to 5%

J-5

S.R. 0476 Southbound (Chemical Road) Data (Acoustic Sensor)

Manual Count (9-7-05)Left Lane Middle Lane Right Lane Total

From To Cars SU TT Total Cars SU TT Total Cars SU TT Total Cars SU TT Total2:00 PM 2:15 PM 247 4 3 254 261 20 36 317 142 25 15 182 650 49 54 7532:15 PM 2:30 PM 226 2 2 230 255 28 22 305 145 20 6 171 626 50 30 7062:30 PM 2:45 PM 232 6 1 239 273 20 23 316 149 27 4 180 654 53 28 7352:45 PM 3:00 PM 241 2 0 243 233 22 23 278 121 22 8 151 595 46 31 6723:00 PM 3:15 PM 308 3 1 312 286 21 30 337 183 20 9 212 777 44 40 8613:15 PM 3:30 PM 312 4 0 316 302 19 25 346 170 25 8 203 784 48 33 8653:30 PM 3:45 PM 330 1 1 332 300 15 26 341 202 10 5 217 832 26 32 8904:15 PM 4:30 PM 376 4 3 383 335 15 21 371 223 17 7 247 934 36 31 10014:30 PM 4:45 PM 410 2 1 413 339 15 29 383 234 9 7 250 983 26 37 10464:45 PM 5:00 PM 393 3 0 396 357 6 15 378 235 11 8 254 985 20 23 10285:00 PM 5:15 PM 411 0 1 412 401 9 16 426 237 7 5 249 1049 16 22 10875:15 PM 5:30 PM 485 0 2 487 396 6 18 420 277 11 2 290 1158 17 22 1197

Composition 92.5% 4.0% 3.5%


From To Cars SU Truck TT Truck Total Ab Diff APD2:00 PM 2:15 PM 658 39 47 744 9 1.2%2:15 PM 2:30 PM 639 38 25 702 4 0.6%2:30 PM 2:45 PM 650 53 26 729 6 0.8%2:45 PM 3:00 PM 606 42 24 672 0 0.0%3:00 PM 3:15 PM 809 39 30 878 17 2.0%3:15 PM 3:30 PM 758 47 28 833 32 3.7%3:30 PM 3:45 PM 814 41 29 884 6 0.7%4:15 PM 4:30 PM 911 48 29 988 13 1.3%4:30 PM 4:45 PM 986 25 35 1046 0 0.0%4:45 PM 5:00 PM 955 35 22 1012 16 1.6%5:00 PM 5:15 PM 1019 28 24 1071 16 1.5%5:15 PM 5:30 PM 1123 44 23 1190 7 0.6%

Composition 92.4% 4.5% 3.2% average 1.2%stdev 1.0%


Difference 92 median 1.0%APD on Total 0.8% mode 0% to 1%

J-6

S.R. 0476 Southbound (I-76) Data (Acoustic Sensor)

Manual Count (9-8-05)Left Lane Middle Lane Right Lane Total

From To Cars SU TT Total Cars SU TT Total Cars SU TT Total Cars SU TT Total1:15 PM 1:30 PM 209 3 1 213 283 24 22 329 207 19 21 247 699 46 44 7891:30 PM 1:45 PM 223 2 0 225 283 19 27 329 238 23 18 279 744 44 45 8332:00 PM 2:15 PM 224 1 0 225 299 18 17 334 227 29 17 273 750 48 34 8322:15 PM 2:30 PM 239 1 1 241 293 15 13 321 226 28 17 271 758 44 31 8332:30 PM 2:45 PM 226 3 1 230 280 11 15 306 229 18 24 271 735 32 40 8072:45 PM 3:00 PM 350 3 2 355 333 26 20 379 278 30 11 319 961 59 33 10533:30 PM 3:45 PM 416 2 1 419 370 18 23 411 346 21 9 376 1132 41 33 12063:45 PM 4:00 PM 447 6 2 455 400 19 16 435 341 14 20 375 1188 39 38 12654:00 PM 4:15 PM 445 0 0 445 415 14 24 453 323 13 20 356 1183 27 44 12544:15 PM 4:30 PM 483 4 0 487 379 18 27 424 378 6 5 389 1240 28 32 13004:45 PM 5:00 PM 531 3 1 535 435 17 15 467 410 8 11 429 1376 28 27 14315:00 PM 5:15 PM 490 0 0 490 422 12 15 449 373 9 11 393 1285 21 26 1332

Composition 93.2% 3.5% 3.3%


From To Cars SU Truck TT Truck Total Ab Diff APD1:15 PM 1:30 PM 641 34 1 676 113 14.3%1:30 PM 1:45 PM 679 36 4 719 114 13.7%2:00 PM 2:15 PM 665 47 1 713 119 14.3%2:15 PM 2:30 PM 637 49 1 687 146 17.5%2:30 PM 2:45 PM 554 55 4 613 194 24.0%2:45 PM 3:00 PM 738 37 5 780 273 25.9%3:30 PM 3:45 PM 807 33 2 842 364 30.2%3:45 PM 4:00 PM 873 34 3 910 355 28.1%4:00 PM 4:15 PM 805 26 1 832 422 33.7%4:15 PM 4:30 PM 869 23 1 893 407 31.3%4:45 PM 5:00 PM 805 35 4 844 587 41.0%5:00 PM 5:15 PM 952 25 2 979 353 26.5%

Composition 95.1% 4.6% 0.3% average 25.0%stdev 8.7%


Difference 3447 median 26.2%APD on Total 26.6% mode 25.5% to 26.5%

J-7

S.R. 0279 Northbound Data (Microwave Sensor)


From To Cars Trucks Total Cars Trucks Total Cars Trucks Total2:00 PM 2:15 PM 396 14 410 271 43 314 667 57 7242:15 PM 2:30 PM 382 15 397 281 42 323 663 57 7202:30 PM 2:45 PM 400 8 408 279 40 319 679 48 7272:45 PM 3:00 PM 385 20 405 282 43 325 667 63 7303:00 PM 3:15 PM 458 9 467 303 40 343 761 49 8103:15 PM 3:30 PM 454 15 469 294 53 347 748 68 8163:30 PM 3:45 PM 501 15 516 337 46 383 838 61 8993:45 PM 4:00 PM 501 10 511 359 29 388 860 39 8994:00 PM 4:15 PM 474 12 486 354 33 387 828 45 8734:15 PM 4:30 PM 530 5 535 349 36 385 879 41 9204:30 PM 4:45 PM 507 9 516 345 35 380 852 44 8964:45 PM 5:00 PM 549 10 559 382 26 408 931 36 967

93.9% 6.1%


From To Cars Trucks Total Ab Diff APD2:00 PM 2:15 PM 524 32 556 168 23.2%2:15 PM 2:30 PM 564 40 604 116 16.1%2:30 PM 2:45 PM 539 35 574 153 21.0%2:45 PM 3:00 PM 570 32 602 128 17.5%3:00 PM 3:15 PM 623 43 666 144 17.8%3:15 PM 3:30 PM 646 41 687 129 15.8%3:30 PM 3:45 PM 734 41 775 124 13.8%3:45 PM 4:00 PM 768 40 808 91 10.1%4:00 PM 4:15 PM 795 42 837 36 4.1%4:15 PM 4:30 PM 864 39 903 17 1.8%4:30 PM 4:45 PM 837 36 873 23 2.6%4:45 PM 5:00 PM 882 56 938 29 3.0%

94.6% 5.4% average 12.2%stdev 7.7%


Difference 1158 median 14.8%APD on Total 11.6% mode 17%

J-8

S.R. 0376 Eastbound Data (Microwave Sensor)


From To Cars Trucks Total Cars Trucks Total Cars Trucks Total7:00 AM 7:15 AM 418 5 423 234 51 285 652 56 7087:15 AM 7:30 AM 431 10 441 258 34 292 689 44 7337:30 AM 7:45 AM 456 3 459 283 36 319 739 39 7787:45 AM 8:00 AM 433 5 438 296 30 326 729 35 7648:00 AM 8:15 AM 408 3 411 264 37 301 672 40 7128:15 AM 8:30 AM 385 14 399 241 43 284 626 57 6838:30 AM 8:45 AM 363 9 372 243 43 286 606 52 6588:45 AM 9:00 AM 421 17 438 234 70 304 655 87 7429:00 AM 9:15 AM 304 15 319 201 54 255 505 69 5749:15 AM 9:30 AM 319 14 333 232 58 290 551 72 6239:30 AM 9:45 AM 334 10 344 251 49 300 585 59 6449:45 AM 10:00 AM 293 11 304 221 52 273 514 63 577

91.8% 8.2%


From To Cars Trucks Total Ab Diff APD7:00 AM 7:15 AM 692 35 727 19 2.7%7:15 AM 7:30 AM 700 28 728 5 0.7%7:30 AM 7:45 AM 765 32 797 19 2.4%7:45 AM 8:00 AM 751 23 774 10 1.3%8:00 AM 8:15 AM 707 32 739 27 3.8%8:15 AM 8:30 AM 653 30 683 0 0.0%8:30 AM 8:45 AM 633 16 649 9 1.4%8:45 AM 9:00 AM 674 39 713 29 3.9%9:00 AM 9:15 AM 551 28 579 5 0.9%9:15 AM 9:30 AM 564 43 607 16 2.6%9:30 AM 9:45 AM 612 31 643 1 0.2%9:45 AM 10:00 AM 525 36 561 16 2.8%

95.5% 4.5% average 1.9%stdev 1.3%

3-Hour Analysis max 3.9%Manual Total 8196 min 0.0%Sensor Total

Difference8200 range 3.9%

-4 median 1.9%APD on Total 0.0% mode 0 to 1 %

rfq number 04-02 (c19) · site #4 s.r. 0040, segment 0260 & 0261 (both directions): five-lane...

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