analysis of active transportation and demand management strategies workshop 1 richard dowling,...

Analysis of Active Transportation and

Demand Management Strategies

Workshop

1

Richard Dowling, Kittelson & AssociatesRichard Margiotta, Cambridge Systematics

James Colyar & Chung Tran, Federal Highway Administration

Purpose of Workshop

To introduce: The draft ATDM HCM Analysis Guide for

analyzing investment strategies

Updated draft chapter 35 for the HCM.

Computational engines to assist ATDM analysis.

To illustrate application of ATDM analysis framework and the HCM to ATDM investment decision making.

2

Agenda (morning)

09:00 – Introductions, Purpose, Agenda09:15 – ATDM Overview10:00 – The ATDM Analysis Framework10:30 – Break10:45 – The ATDM Analysis Framework

(cont)11:45 – Lunch (on your own)

3

Agenda (afternoon)12:45 – Computational Engines 1:45 – Example #0 – Before ATDM2:30 – Example #1 – HOV to HOT Convert3:00 – Break3:15 – Example #2 – Dynamic Metering3:45 – Example #3 - TDM4:15 – Wrap Up4:30 – Done

4

Workshop Objectives

Inform you about new method to better account for the operational benefits of Active Transportation and Demand Management programs

◦Improve competitiveness of operational improvements for long range funding.

5

Key Concepts for Today

Evaluating facility operations under a variety of demand, incident, weather, and work zone conditions

◦Creation of event scenarios

◦Evaluation of performance under each scenario.

◦Aggregation of results into meaningful performance measures.

6

Active Management

1. Overview of ATDM

7

TopicsATDM Defined

FHWA ATDM Program Elements

How This Project (Capacity and Operational Analysis Methods) Fits In

8

Active Management

9

Active Management

Active Management is the fundamental concept of taking a dynamic approach to a performance based process

ATDM Definition

10

ATDM is the dynamic management, control, and influence of travel demand, traffic demand, and travel flow of transportation facilities.

The Balance between Static and Dynamic

Static Dynamic

E.g., static signs, fixed-time signal

operations, time-of-day shoulder use)

E.g., adaptive signal timings, congestion-

triggered hard shoulder running,

fully-variable speed limits)

11

ATDM Can Be Applied Throughout the Trip Chain

Lane / facilityUse/Choice

Time of day choice

Route Choice

Mode choice

Destination choice

12

Moving Towards Active Management

Fully dynamic operations

24/7 current / predicted levels of traffic and incidents

Adjust supply based on demand

Responsive shoulder use based on demand

Adjust supply by time of dayTemporary shoulder use during peak periods

Manage flow by time of day

Monitor and manage existing lanes

13

ATDM Categories

14

•Management of system capacity and traffic volumes

Active Traffic Management

•Influence and control of time, route, and mode shifts

Active Demand Management

•Management of circulation and parking capacity

Active Parking Management

Active Demand Management: Dynamic Ridesharing

Avego Real-time Ridesharing Demo http://www.youtube.com/watch?v=P58Ug6JpdRU

15

http://www.youtube.com/watch?v=P58Ug6JpdRU

Active Traffic Management: VDOT I-66

VDOT: I-66 Active Traffic Management System in Northern Virginia: http://www.youtube.com/watch?v=x-ZZKhaLRzI

16

http://www.youtube.com/watch?v=x-ZZKhaLRzI

Active Parking Management: SF Park

SFPark: Know Where the Parking is Video: http://youtu.be/9JVepZcA-GI

17

http://youtu.be/9JVepZcA-GI

Evolution Towards Next Generation of Operations

ATDM approaches help agencies to evolve towards the use of real-time decision support systems, predicted information, and have a focus on both supply and demand.

19

Challenges and Barriers to ATDM

Institutional CapabilitiesBenefits and Costs UnclearTransferability Limited Design and Planning GuidanceData NeedsModeling InvestmentLimited Public Outreach, Communications,

and Public Relations Examples

20

FHWA ATDM Program Goal

Enable agencies to improve trip reliability, safety, and throughput of the surface transportation systems by dynamically managing and controlling travel and traffic demand, and available capacity, based on prevailing and anticipated conditions, using one or a combination of real-time operational strategies.

21

ATDM Program Objectives

Increase awareness and understanding of ATDMDevelop, test, and evaluate strategiesProvide tools and methods for performance

analyses Provide tools and methods for benefit/cost

analysesTrain agencies to deploy effective ATDM systemsProvide guidance to FHWA Division Offices

22

ATDM Program Components

Research

Tool Development

And Guidance

Outreachand

Training

Stakeholder Engagement

Program Management

23

http://www.ops.fhwa.dot.gov/atdm/index.htm

http://www.ops.fhwa.dot.gov/atdm/index.htm

ATDM Analysis Guide Project Purpose

Develop improved methods to analyze the capacity and operations impacts of ATDM

Respond to need for “HCM-level” analysisProvide basis for content for HCM Chapter

35

◦Analysis framework + specifics where available

◦Leverage SHRP 2 L08 (Reliability in the HCM)

24

Project Products and VettingFHWA Guide on Ops Analysis of ATDMUpdated Chapter 35 on ATDM for HCMComputational engine (software)Workshops to get feedback on methodsWorkshops to teach the methods

Dallas, TX – April 9, 2013Seattle, WA – April 23, 2013Baltimore, MD – May 2, 2013

Final Guidebook – June 2013HCQS Workshop HCM Chapter 35 – July 2013

25

Future Efforts - FHWA or others

Respond to comments

◦HCQS Committee and others

Additional validationIncorporate on-going related HCM

research

◦E.g. Reliability, managed lanes, incident management

Software

26

Active Management

3. ATDM Analysis Framework

27

Active Management

3. ATDM Analysis Framework

28

Purpose of ATDM Analysis

To evaluate the performance of a facility, with and without ATDM deployed, in terms of:

◦Productivity

◦Efficiency

◦Reliability

29

ATDM Analysis is Not Traditional HCM Analysis

HCM

◦Static: ideal weather, fixed demand, non-incident conditions

◦Single analysis run

ATDM

◦Dynamic: variable demand, weather, incidents

◦Multiple analysis runs

30

Why Are We Doing This?Need to capture how a facility actually

operates, accounting for periodic disruptions (incidents, weather, work zones) and variable demand

ATDM strategies primarily affect disruptions and variable demand, not capacity

Reliability estimation requires that we assess all the potential sources of congestion

31

Measures of Effectiveness (MOEs) for ATDM

Traditional HCM freeway facility measures:

◦Number of vehicles served

◦Density

◦Average speed

◦Queue Length

Need to be expanded to account for reliability and sources of congestion

Note: “Measures of Effectiveness” and “Performance Measures” are terms that are used interchangeably 32

MOEs for ATDM (cont.)

Congestion and Reliability

◦Useful to normalize travel time to the Travel Time Index:

TTI = Actual Travel Time

Ideal Travel Time

◦Delay is important because it can be monetized in benefit/cost studies

33

Travel Time Reliability

Measured by how travel time of a trip (or facility) varies from one time period to another

In other words, reliability is measured as the variability of travel times◦“How long will my trip take today compared to

the same trip at the same time on any average day?”

◦The travel time distribution is used to describe reliability

Effects of Demand, Incidents, and Weather

WeekdayTravel Times5:00-6:00 P.M., on State Route 520 Eastbound,Seattle, WA

2 Incidents with Rain

3 Incidents

Presidents Day

1 Incident with Rain

Martin Luther King Day

Rain

1 Incident

4 Incidents

0

5

10

15

20

25

30

Jan 3 Feb 2 Mar 4 Apr 3

Travel Time (in Minutes)

Number of Incidents

2003

Understanding Reliability

0

50

100

150

200

250

300

350

10 15 20 25 30 35

Travel time (minutes)

Num

ber

of tr

ips

95th percentile =22.7 minutes

Avg. =15.9 minutes

Free-flow = 11.5 minutes

Buffer

Planning time index = 22.7 / 11.5 = 1.97

Buffer time = 22.7 – 15.9 = 6.8 min.

Buffer time index =(22.7 – 15.9)/15.9 = 43%

Planning time index = 22.7 / 11.5 = 1.97

Buffer time = 22.7 – 15.9 = 6.8 min.

Buffer time index =(22.7 – 15.9)/15.9 = 43%

SR 520 EastboundSeattle, 4-7pm weekdays

I-75 NB, Atlanta, GeorgiaP.M. Peak

37

6 11 16 21 26 31 360

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

500,000

Percent on-time@ 45 mph (14%)

Planning Time

Mean (10.7 minutes)

80th Percentile (13.3 minutes)

95th Percentile (16.5 minutes)

Travel Time (Minutes)

Number of Trips

A Full Suite of Travel Time-Based Measures Is Used for ATDM

Vehicle-hours of delay Maximum d/c ratio Maximum queue length Average speed VMT demanded VMT serviced

38

ATDM Measures (cont.)

95th %ile TTI (“Planning Time Index”) 80th %ile TTI Standard deviation Semi-Standard Deviation

◦ One-sided; deviations from free flow

“Reliability Rating”

◦ % trips that are occur at a TTI = 1.33 or less

Misery Index (average of worse 5% TTIs)

39

Why So Many Measures?Reliability is complex – need multiple metrics

to characterize the distributionDifferent applications require different

measures

◦Economic analysis of projects

◦Compatibility with field measurements (ongoing monitoring)Will be important for MAP-21’s “Performance

Management” requirements

40

ATDM Evaluation: What Do We Need?Analytical engine to estimate traffic

impacts

◦We use FREEVAL, software built around HCM Chapter 10 (“Freeway Facilities”)

◦Other methods could be used (e.g., simulation)

41

What Do We Need (cont.)?

Way to vary the inputs so that the full range of conditions is replicated

◦All possible combinations just too numerous to handle

◦Find 30 combinations (scenarios) of traffic level, incident characteristics, weather, and/or work zones that are of interest for our analysis

42

Assess “After”Performance

Assess “Before”Performance

ATD

M

Evalu

ati

on

Ap

pro

ach

43

5. Design ATDM Strategy

4. ComputeMOE’s

2. Generate Scenarios

3. Apply Ops Tool to Scenarios

6. Convert ATDM Into Ops Inputs

8. ComputeMOE’s

7. Apply Ops Tool to Scenarios

1. Preparation(Data, Study Area)

Step 1 – Preparation

Define purpose and scope of ATDM analysis.

Assemble Data

◦Conventional HCM data for facility

◦Historic data on demand variability, weather, incidents, work zones.

44

Scope of Analysis

Decisions:

◦Objectives of ATDM investments.

◦Thresholds of acceptable performance.

◦Temporal and spatial limitsConventional + reliability reporting period (new)

◦Traffic operations analysis tool (HCM, microsim)

45

Set Time and Space Limits

46

StudyPeriod

Study Section

18:00 66 66 69 70 63 66 66 6617:45 66 68 68 65 69 63 63 6317:30 68 66 60 67 63 39 64 6417:15 64 70 70 65 38 39 67 6717:00 62 64 68 40 18 37 69 6916:45 64 70 37 14 14 40 65 6516:30 69 39 25 21 16 37 69 6916:15 66 65 38 13 11 37 70 7016:00 68 63 62 40 18 38 67 6715:45 63 63 62 68 40 37 68 6815:30 64 61 65 62 61 39 61 6115:15 63 63 60 65 67 63 63 6315:00 65 70 64 63 67 64 64 64

18:00 66 66 69 70 63 66 66 6617:45 66 68 68 65 69 63 63 6317:30 68 66 60 67 63 39 64 6417:15 64 70 70 65 38 39 67 6717:00 62 64 68 40 18 37 69 6916:45 64 70 37 14 14 40 65 6516:30 69 39 25 21 16 37 69 6916:15 66 65 38 13 11 37 70 7016:00 68 63 62 40 18 38 67 6715:45 63 63 62 68 40 37 68 6815:30 64 61 65 62 61 39 61 6115:15 63 63 60 65 67 63 63 6315:00 65 70 64 63 67 64 64 64

18:00 66 66 69 70 63 66 66 6617:45 66 68 68 65 69 63 63 6317:30 68 66 60 67 63 39 64 6417:15 64 70 70 65 38 39 67 6717:00 62 64 68 40 18 37 69 6916:45 64 70 37 14 14 40 65 6516:30 69 39 25 21 16 37 69 6916:15 66 65 38 13 11 37 70 7016:00 68 63 62 40 18 38 67 6715:45 63 63 62 68 40 37 68 6815:30 64 61 65 62 61 39 61 6115:15 63 63 60 65 67 63 63 6315:00 65 70 64 63 67 64 64 64

18:00 66 66 69 70 63 66 66 6617:45 66 68 68 65 69 63 63 6317:30 68 66 60 67 63 39 64 6417:15 64 70 70 65 38 39 67 6717:00 62 64 68 40 18 37 69 6916:45 64 70 37 14 14 40 65 6516:30 69 39 25 21 16 37 69 6916:15 66 65 38 13 11 37 70 7016:00 68 63 62 40 18 38 67 6715:45 63 63 62 68 40 37 68 6815:30 64 61 65 62 61 39 61 6115:15 63 63 60 65 67 63 63 6315:00 65 70 64 63 67 64 64 64

18:00 66 66 69 70 63 66 66 6617:45 66 68 68 65 69 63 63 6317:30 68 66 60 67 63 39 64 6417:15 64 70 70 65 38 39 67 6717:00 62 64 68 40 18 37 69 6916:45 64 70 37 14 14 40 65 6516:30 69 39 25 21 16 37 69 6916:15 66 65 38 13 11 37 70 7016:00 68 63 62 40 18 38 67 6715:45 63 63 62 68 40 37 68 6815:30 64 61 65 62 61 39 61 6115:15 63 63 60 65 67 63 63 6315:00 65 70 64 63 67 64 64 6415:00

18:00

Each cell is one analysis period of an analysis segment.

Days of Year

Reliability

Dimension

TemporalDimension

SpatialDimension

Reliability Reporting Period

Step 2: Generate Scenarios

A Scenario is a set of Challenges to Facility Operation

◦A specified combination of:Demand, Weather, Incident, and Work Zone

Specify their probabilities

◦P(scenario) = P(d) * P(w) * P(i) * P(wz)

Identify effects on demand, capacity, speed

47

Identify Factors and Determine Probabilities

48

Demand Level (Percentiles)

5th 25th 50th 75th 95th Row Totals

No lane-blocking incident 0.65

1 lane blocked, 15 minutes 0.11

1 lane blocked, 30 minutes 0.08

2+ lanes blocked, 15 minutes 0.07



Column Totals 0.15 0.23 0.25 0.23 0.15 1.00

Demand Variability

Need continuous counts from

◦Permanent traffic counters (ATRs)

◦ITS equipment

Develop the demand distribution for the analysis period (e.g. peak period)

Ideally for facility in question

◦Data from similar roadways

◦Systemwide defaults (see handout)

49

I-95 SB, Pompano Beach, Florida4:00-6:00 p.m., Weekdays

50

11,000 11,500 12,000 12,500 13,000 13,500 14,000 14,500 15,000 15,500 16,0000

10

20

30

40

50

60

70

5th Percentile

25th Percentile

50th Percentile

75th Percentile

95th Percentile

Peak-Period Volume

Incident Characteristics

Requires incident logs or default valuesIf a sufficiently long history exists for a

facility, use data specific to it

◦Be careful of low sample sizes

◦Probably best to develop areawide numbers, once every 1-3 years

51

Incident Characteristics (cont.)

Determine % of days with no incident for the year

E(incidents) = (Period VMT) x (IncRate)

IncRate ~ 4 x CrashRateRemove shoulder-only incident days, if

desired

52

Incident Characteristics (cont.)

Peak Period Weekday = 30 MVMTCrashRate = 1.1/MVMTE(incidents) = 30 * 1.1 * 4

= 132 incidents/yearShoulder-only incidents = 33% of total inc.88 incident days, or 35% of weekdays

53

Compute Probabilities for Weighting Results

54

Demand Level (Percentiles)

5th 25th 50th 75th 95th Row Totals

No lane-blocking incident 0.098 0.146 0.163 0.146 0.098 0.65

1 lane blocked, 15 minutes 0.017 0.025 0.028 0.025 0.017 0.11

1 lane blocked, 30 minutes 0.012 0.018 0.020 0.018 0.012 0.08

2+ lanes blocked, 15 minutes 0.011 0.016 0.018 0.016 0.011 0.07



Column Totals 0.15 0.23 0.25 0.23 0.15 1.00

Other Factors: Weather

55

Weather Type Range

SpeedAdjustmen

tFactor

CapacityAdjustmen

tFactor

Probability

Clear 1.00 1.00 50.0%Light Rain > 0.00 <= 0.10 in/hr 0.98 0.98 8.0%Medium Rain > 0.10 <= 0.25 in/hr 0.94 0.93 4.0%Heavy Rain > 0.25 in/hr 0.93 0.86 2.0%Very Light Snow > 0.00 <= 0.05 in/hr 0.89 0.96 6.0%Light Snow > 0.05 <= 0.10 in/hr 0.88 0.91 3.0%Medium Snow > 0.10 <= 0.50 in/hr 0.86 0.89 2.0%Heavy Snow > 0.50 in/hr 0.85 0.76 2.0%Low Wind > 10 <= 20 mph 0.99 0.99 4.0%High Wind > 20 mph 0.98 0.98 2.0%Cool < 50 >= 340 F 0.99 0.99 2.0%Cold < 34 >= -40 F 0.98 0.98 2.0%Very Cold < -4.00 F 0.94 0.91 3.0%Medium Visibility < 1.00 >= 0.50 miles 0.94 0.90 2.0%Low Visibility < 0.50 >= 0.25 miles 0.93 0.88 2.0%Very Low Visibility < 0.25 miles 0.93 0.88 6.0%Total 100.0%

Other Factors: Work Zones

56

Type Lanes Open Duration (min) Cap/Lane Spd.Adj. Prob.

None All n/a 2000 1.00 70.0%

Short Term(1 day or less)

1 240 1600 0.80 5.0%

2 240 1600 0.80 5.0%

3 240 1600 0.80 5.0%

Long Term(>1day)

1 240 1400 0.70 5.0%

2 240 1450 0.73 5.0%

3 240 1500 0.75 5.0%

Total 100.0%

Step 3: Apply HCM Analysis Tool

FREEVAL-ATDM

◦Expanded to:Accept inputs for 30 scenariosCompute reliability MOE’s

◦It is both a simpler and a more complex version of SHRP2-L08 FREEVALSimpler scenario generatorAutomates ATDM adjustment process

57

HCM Adjustments for Scenarios

Capacity and Speed Adjustments

◦generally follows HCM 2010 and SHRP2- LO8Weather = HCM 2010 Freeway + SHRP2-L08 Incident = HCM 2010 FreewayWork Zone = HCM 2010 Freeway

Demand Adjustments

◦Computed off-line and input by analyst

Not currently set up for arterials

58

Step 4: Compute MOE’s

Vehicle-Miles Traveled - Demand (VMT-D)

Vehicle-Miles Traveled - Served (VMT-S)

Vehicle-Hours Traveled (VHT)

Vehicle-Hours Delay (VHD)

Average System Speed (MPH)

Delay Per Mile (VHD/VMT-D)

The Planning Time Index (PTI)

59

Step 5: Design ATDM Plan

Travel Demand Management Strategies

◦Travel Information, Employer Based TDM

Weather Traffic Management Plan

Traffic Incident Management Plan

Work Zone Traffic Management Plan

Variable Speed Limits

HOV/HOT Lane Management Strategies

Shoulder/Median Lane Strategies

Truck Controls

Ramp Metering

60

Step 6: Convert to HCM Inputs

Strategies must be converted to effect on:

DemandCapacityFree-Flow SpeedOpen LanesRamp Metering Rates

Must be computed and input by analyst

◦Weather, incident, work zone, demand specific.

SHRP2-L08 formula used to predict speed61

Step 7 – Apply Ops Tool

Same as Step 3

◦FREEVAL-ATDM

◦But with ATDM speed, capacity, demand, lanes, ramp metering factors and values.

62

Step 8: Compute MOE’s

63

MOE Before After Diff %

VMT Demand 25,847,488 25,847,488 0 0.0%

VMT Served 25,847,198 25,847,488 290 0.0%

VHT 603,529 561,258 -42,271 -7.5%

VHD 234,285 192,009 -42,276 -22.0%

MPH 42.83 46.05 3.23 7.0%

Ave. Delay 32.63 26.74 -5.89 -22.0%

PTI 3.92 3.36 -0.56 -16.5%

Comments/Questions?

64

Active Management

Example Applications

65

The Software

ATDM Analyzer (Kittelson)

◦Generates Scenarios

◦Generates demand, capacity, speed adjustment factors for HCM analysis

FREEVAL-ATDM (ITRE)

◦Expanded version of HCM 2010 FREEVAL

◦Reads scenario adjustment factors

◦Applies HCM analysis 30 times

◦Compiles results66

The ATDM Analyzer

Master TabBasic info6 macros25 steps

67

FHWA ATDM AnalyzerCreated By: R.Dowling Kittelson & Associates, Inc.Create Date: 12/1/2012Version: 1.07gLast Update: 3/3/2013

Project Title: This is Test 1 Project Title Data Entry CellsAnalyst Name: R.DowlingSeed File Comments: These are the Seed File Adjustment Factor Comments Select Analysis Approach (future implementation)Before Comments: These are the Before comments PlanningAfter ATDM Comments: These are the After ATDM comments Operations

File Names No MessagesAll files must be in same directorySeed File: FREEVAL-ATDM-(March 5).xlsm filename format: "xxxxxx.xlsm" FREEVAL-ATDM-(March 5).xlsmBefore Adjust Factors File: BeforeAdjust.xlsx filename format: "xxxxxx.xlsx" BeforeAdjust.xlsxAfter ATDM Factors File: AfterAdjust.xlsx filename format: "xxxxxx.xlsx" AfterAdjust.xlsx

Note: when running macros, this software turns off Excel's screen update. So look at bottom bar for messages about run status.

This is the Master Input and Control Worksheet

Tasks (Work from left tab to right tab for worksheets) Sheets to Check, edit. Macro Buttons0 Fill in identifying data, file names, and comments in cells above.1 Review/Edit probabilities, demand adjustment and capacity adjustment factors in "demand" worksheet Go to "demand" sheet2 Review/Edit probabilities, demand adjustment and capacity adjustment factors in "weather" worksheet Go to "weather" sheet3 Review/Edit probabilities, demand adjustment and capacity adjustment factors in "incident" worksheet Go to "incidents" sheet4 Review/Edit probabilities, demand adjustment and capacity adjustment factors in "workzone" worksheet Go to "workzones" sheet5 Examine "scenarios" worksheet to see range of adjustment factors. Edit earlier sheets to get desired range. Go to "scenarios" sheet6 Copy and sort scenarios from lowest to highest d/c adjustments using buttons on "sorted" worksheet Go to "sorted" sheet7 Select 30 scenarios for FREEVAL analysis using "30scen" worksheet. Go to "30scen" sheet

8 Code the basic freeway geometry and demand data into the FREEVAL Seed File Go to FREEVAL-ATDM.XLSM File

9 Copy adjustment factors, lanes, metering rates from FREEVAL (seed) file -->

10 Copy scenario descriptions to Seed File (For later use in FREEVAL)---->

11 Compute "before" demand, capacity, speed, lanes, ramp metering rate adjustment factors by scenario.

Check "messages" sheet for warnings and information. message count: 0

12 Export "Before ATDM" adjustment factor file for FREEVAL

13 Run FREEVAL for "Before ATDM" case. Switch to FREEVAL workbook14 Review Results, copy FREEVAL and "before" adjustments files to own subdirectory. Review FREEVAL ATDM Output Sheet

15 Enter TDM plan in TDM worksheet Go to "TDM" worksheet16 Enter Weather Traffi c Management Plan in W-TMP worksheet. Go to "W-TMP" worksheet17 Enter Traffi c Incident Management Plan in TIM worksheet. Go to "TIM" worksheet18 Enter Work Zone Traffi c Management Plan in WZ-TMP worksheet. Go to "WZ-TMP" worksheet19 Select Lane, Truck, Metering strategies for each scenario Go to "30Lanes" worksheet

20 Compute "after" demand, capacity, speed, lanes, ramp metering rate adjustment factors by scenario.21 Check "messages" sheet for warnings. message count: 0

22 export "After ATDM" adjustment factor file for FREEVAL

23 Copy FREEVAL and After ATDM factors file to new directory (folder) Switch to Windows, create folder24 Run FREEVAL for "After ATDM" case. Switch to FREEVAL workbook25 Review Results Review FREEVAL ATDM Output Sheet

9. Copy Seed File Factors to Workbook

10. Copy scenario names to Seed

11. Compute: Before Factors

12. Export Before Factors

20. Compute After ATDM Factors

22. Export After ATDM Factors

Yellow cells are User Input Fields

Step 0 – Basic Info

68

FHWA ATDM AnalyzerCreated By: R.Dowling Kittelson & Associates, Inc.Create Date: 12/1/2012Version: 1.07gLast Update: 3/3/2013

Project Title: This is Test 1 Project Title Data Entry CellsAnalyst Name: R.DowlingSeed File Comments: These are the Seed File Adjustment Factor Comments Select Analysis Approach (future implementation)Before Comments: These are the Before comments PlanningAfter ATDM Comments: These are the After ATDM comments Operations

File Names No MessagesAll files must be in same directorySeed File: FREEVAL-ATDM-(March 5).xlsm filename format: "xxxxxx.xlsm" FREEVAL-ATDM-(March 5).xlsmBefore Adjust Factors File: BeforeAdjust.xlsx filename format: "xxxxxx.xlsx" BeforeAdjust.xlsxAfter ATDM Factors File: AfterAdjust.xlsx filename format: "xxxxxx.xlsx" AfterAdjust.xlsx

Note: when running macros, this software turns off Excel's screen update. So look at bottom bar for messages about run status.

This is the Master Input and Control Worksheet

Tasks (Work from left tab to right tab for worksheets) Sheets to Check, edit. Macro Buttons0 Fill in identifying data, file names, and comments in cells above.1 Review/Edit probabilities, demand adjustment and capacity adjustment factors in "demand" worksheet Go to "demand" sheet2 Review/Edit probabilities, demand adjustment and capacity adjustment factors in "weather" worksheet Go to "weather" sheet3 Review/Edit probabilities, demand adjustment and capacity adjustment factors in "incident" worksheet Go to "incidents" sheet4 Review/Edit probabilities, demand adjustment and capacity adjustment factors in "workzone" worksheet Go to "workzones" sheet5 Examine "scenarios" worksheet to see range of adjustment factors. Edit earlier sheets to get desired range. Go to "scenarios" sheet6 Copy and sort scenarios from lowest to highest d/c adjustments using buttons on "sorted" worksheet Go to "sorted" sheet7 Select 30 scenarios for FREEVAL analysis using "30scen" worksheet. Go to "30scen" sheet

8 Code the basic freeway geometry and demand data into the FREEVAL Seed File Go to FREEVAL-ATDM.XLSM File

9 Copy adjustment factors, lanes, metering rates from FREEVAL (seed) file -->

10 Copy scenario descriptions to Seed File (For later use in FREEVAL)---->

11 Compute "before" demand, capacity, speed, lanes, ramp metering rate adjustment factors by scenario.

Check "messages" sheet for warnings and information. message count: 0

12 Export "Before ATDM" adjustment factor file for FREEVAL

13 Run FREEVAL for "Before ATDM" case. Switch to FREEVAL workbook14 Review Results, copy FREEVAL and "before" adjustments files to own subdirectory. Review FREEVAL ATDM Output Sheet

15 Enter TDM plan in TDM worksheet Go to "TDM" worksheet16 Enter Weather Traffi c Management Plan in W-TMP worksheet. Go to "W-TMP" worksheet17 Enter Traffi c Incident Management Plan in TIM worksheet. Go to "TIM" worksheet18 Enter Work Zone Traffi c Management Plan in WZ-TMP worksheet. Go to "WZ-TMP" worksheet19 Select Lane, Truck, Metering strategies for each scenario Go to "30Lanes" worksheet

20 Compute "after" demand, capacity, speed, lanes, ramp metering rate adjustment factors by scenario.21 Check "messages" sheet for warnings. message count: 0

22 export "After ATDM" adjustment factor file for FREEVAL

23 Copy FREEVAL and After ATDM factors file to new directory (folder) Switch to Windows, create folder24 Run FREEVAL for "After ATDM" case. Switch to FREEVAL workbook25 Review Results Review FREEVAL ATDM Output Sheet

9. Copy Seed File Factors to Workbook

10. Copy scenario names to Seed

11. Compute: Before Factors

12. Export Before Factors

20. Compute After ATDM Factors

22. Export After ATDM Factors

Demand Adjustments Concept

69

HCM Count Day

Step 1Demand Adjustments Tab

70

Name Dem.Adj. Prob.V.Low 5th Percentile Highest Demand 0.77 10.0%

Low 15th Percentile Highest Demand 0.93 10.0%Low-Med 30th Percentile Highest Demand 0.97 20.0%

Med 50th Percentile Highest Demand 1.00 20.0%Med-Hi 70th Percentile Highest Demand 1.02 20.0%

High 85th Percentile Highest Demand 1.04 10.0%V.High 95th Percentile Highest Demand 1.05 10.0%

Ave./Tot 0.977 100%

Step 2 - Weather Adjust

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Name > And <= units Start Dur (min) Spd.Adj. Cap.Adj. Dem.Adj. ProbClear 1 240 1.00 1.00 1.00 50.0%Lt.Rain 0.00 0.10 in/hr 1 240 0.98 0.98 1.00 8.0%Med.Rain 0.10 0.25 in/hr 1 240 0.94 0.93 1.00 4.0%Hvy.Rain 0.25 n/a in/hr 1 240 0.93 0.86 1.00 2.0%V.Lt.Snow 0.00 0.05 in/hr 1 240 0.89 0.96 1.00 6.0%Lt.Snow 0.05 0.10 in/hr 1 240 0.88 0.91 1.00 3.0%Med.Snw 0.10 0.50 in/hr 1 240 0.86 0.89 1.00 2.0%Hvy.Snw 0.50 n/a in/hr 1 240 0.85 0.76 1.00 2.0%Lo.Wind 10.00 20.00 mph 1 240 0.99 0.99 1.00 4.0%Hi.Wind 20.00 n/a mph 1 240 0.98 0.98 1.00 2.0%

< And >= unitsCool 50.00 34.00 deg. F 1 240 0.99 0.99 1.00 2.0%Below 34 34.00 -4.00 deg. F 1 240 0.98 0.98 1.00 2.0%Below -4 -4.00 n/a deg. F 1 240 0.94 0.91 1.00 3.0%Med.Vis. 1.00 0.50 miles 1 240 0.94 0.90 1.00 2.0%Lo.Visib. 0.50 0.25 miles 1 240 0.93 0.88 1.00 2.0%V.Lo.Vis. 0.25 n/a miles 1 240 0.93 0.88 1.00 6.0%

0.9686 0.965 1.00 100.0%

Step 3 –Incidents Adjusts Tab

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Lanes Dur. Sect Start Speed Cap DemType Blocked (min) # Period Adj. Adj. Adj. Prob.No 0 240 20 1 1.00 1.00 1.00 50.0%Non- shldr 30 17 2 0.99 0.99 1.00 10.0%Crash 1 30 17 2 0.79 0.79 1.00 7.0%

2+ 60 17 2 0.61 0.61 1.00 6.0%PDO shldr 45 17 2 0.86 0.86 1.00 5.0%

1 45 17 2 0.79 0.79 1.00 4.0%2+ 60 17 2 0.61 0.61 1.00 4.0%

Injury shldr 60 17 2 0.86 0.86 1.00 3.0%1 60 17 2 0.79 0.79 1.00 3.0%2+ 60 17 2 0.61 0.61 1.00 3.0%

Fatal shldr 150 17 2 0.86 0.86 1.00 1.0%1 150 17 2 0.79 0.79 1.00 2.0%2+ 150 17 2 0.61 0.61 1.00 2.0%

Average or Total: 0.894 0.894 1.00 100.0%

Step 4 – Work Zones Adjust

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Work Zone Lanes Dur. Sect. Start Cap/ Spd. Cap. Dem.Type Open (min) # Period Lane Adj. Adj. Adj. Prob.None 2000 1.00 1.00 1.00 70.0%Short Term 1 240 17 2 1600 0.80 0.80 1.00 5.0%Short Term 2 240 17 2 1600 0.80 0.80 1.00 5.0%Short Term 3 240 17 2 1600 0.80 0.80 1.00 5.0%Long Term 1 240 17 2 1400 0.70 0.70 1.00 5.0%Long Term 2 240 17 2 1450 0.73 0.73 1.00 5.0%Long Term 3 240 17 2 1500 0.75 0.75 1.00 5.0%Ave/Tot 0.93 0.93 1.00 100.0%

Steps 5, 6 & 7 – Select 30 Scenarios

Step 5 – Examine 10,192 Scenarios.Step 6 – Sort scenarios from best to worstStep 7 – Select the 30 you want.

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Step 7 - Select 30 Scenarios

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Scen Adj. Prob. Demand Weather Incident workzone Orig.Prob1 19.48% Low Clear No None 1.750%2 1.39% Low Clear No Lng.Trm 3 0.125%3 1.56% Low Clear PDO-1 None 0.140%4 0.11% Low Clear PDO-1 Lng.Trm 3 0.010%5 1.56% Low Med.Rain No None 0.140%6 0.11% Low Med.Rain No Lng.Trm 3 0.010%7 0.12% Low Med.Rain PDO-1 None 0.011%8 0.01% Low Med.Rain PDO-1 Lng.Trm 3 0.001%9 1.17% Low Lt.Snow No None 0.105%

10 0.08% Low Lt.Snow No Lng.Trm 3 0.008%11 3.12% Med Clear PDO-1 None 0.280%12 0.22% Med Clear PDO-1 Lng.Trm 3 0.020%13 38.96% Med Clear No None 3.500%14 2.78% Med Clear No Lng.Trm 3 0.250%15 0.25% Med Med.Rain PDO-1 None 0.022%16 0.02% Med Med.Rain PDO-1 Lng.Trm 3 0.002%17 3.12% Med Med.Rain No None 0.280%18 0.22% Med Med.Rain No Lng.Trm 3 0.020%19 0.19% Med Lt.Snow PDO-1 None 0.017%20 0.01% Med Lt.Snow PDO-1 Lng.Trm 3 0.001%21 19.48% High Clear No None 1.750%22 1.39% High Clear No Lng.Trm 3 0.125%23 1.56% High Clear PDO-1 None 0.140%24 0.11% High Clear PDO-1 Lng.Trm 3 0.010%25 1.56% High Med.Rain No None 0.140%26 0.11% High Med.Rain No Lng.Trm 3 0.010%27 0.12% High Med.Rain PDO-1 None 0.011%28 0.01% High Med.Rain PDO-1 Lng.Trm 3 0.001%29 1.17% High Lt.Snow No None 0.105%30 0.01% High Lt.Snow PDO-1 Lng.Trm 3 0.001%

Total 100.00% 8.984%

Step 7 – Medium Demand Scenarios

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Total 100.00% 8.984%

Steps 7 – High Demand Scenarios

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Total 100.00% 8.984%

Steps 8-10Set up FREEVAL

Step 8 - Code Conventional HCM data into FREEVAL

Step 9 – Get Freeway data from FREEVAL.Step 10 – Copy Scenario names into

FREEVAL.

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Steps 11- 14Run Before ATDM Analysis

11. Compute “before” Factors (Macro)12. Export factors to file (Macro)13. Run Freeval

◦Import factors from file

◦Run ATDM analysis

14. Review Results

◦Freeval output

◦Process in spreadsheet.

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ATDM Analysis Scenarios Configuration

Following file is selected:

C:\work\proj\proj2009\p09058 fhwa atm hcm\phase3\final report\example\hov\hovAfterAdjust.xlsx

First Select your ATDM Adjustment Factors file, and then press "Insert Adjustment Factors File" to proceed.

Step 1 : Seed File Data Entry1. Go to "t=1" sheet and put geometrical and seed scenario's demand information of the facility you would like to analyze

Step 2 : Identify the Adjustment Factors File

The adjustment factors file should located in the same folder as current Excel file.

2. Come back to "ATDM Input" sheet for continuing scenario configuration. Yellow background cells needs to be edited and data entered by user.

3. If user wants, he can import all geometric and demand information from another FREEVAL-ATDM coded seed file by pressing "Import From Another FREEVAL-ATDM Seed File" button.

Take me to t=1

Insert Adjustment Factors File

Select ATDM Adjustment Factors File

Import From Another FREEVAL-ATDM Seed File

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Scenario Number

Scenario DescriptionScenario

ProbabilitySave File?

1 D= Low, W= Clear, I= No, Wz= None 0.001 No2 D= Low, W= Clear, I= No, Wz= Lng.Trm 3 0.086 No3 D= Low, W= Clear, I= PDO-1, Wz= None 0.011 No4 D= Low, W= Clear, I= PDO-1, Wz= Lng.Trm 3 0.011 No5 D= Low, W= Med.Rain, I= No, Wz= None 0.043 No6 D= Low, W= Med.Rain, I= No, Wz= Lng.Trm 3 0.172 No7 D= Low, W= Med.Rain, I= PDO-1, Wz= None 0.086 No8 D= Low, W= Med.Rain, I= PDO-1, Wz= Lng.Trm 3 0.001 No9 D= Low, W= Lt.Snow, I= No, Wz= None 0.057 No10 D= Low, W= Lt.Snow, I= No, Wz= Lng.Trm 3 0.102 No11 D= Med, W= Clear, I= PDO-1, Wz= None 0.000 No12 D= Med, W= Clear, I= PDO-1, Wz= Lng.Trm 3 0.086 No13 D= Med, W= Clear, I= No, Wz= None 0.057 No14 D= Med, W= Clear, I= No, Wz= Lng.Trm 3 0.006 No15 D= Med, W= Med.Rain, I= PDO-1, Wz= None 0.004 No16 D= Med, W= Med.Rain, I= PDO-1, Wz= Lng.Trm 3 0.004 No17 D= Med, W= Med.Rain, I= No, Wz= None 0.007 No18 D= Med, W= Med.Rain, I= No, Wz= Lng.Trm 3 0.172 No19 D= Med, W= Lt.Snow, I= PDO-1, Wz= None 0.002 No20 D= Med, W= Lt.Snow, I= PDO-1, Wz= Lng.Trm 3 0.057 No21 D= High, W= Clear, I= No, Wz= None 0.000 No22 D= High, W= Clear, I= No, Wz= Lng.Trm 3 0.001 No23 D= High, W= Clear, I= PDO-1, Wz= None 0.000 No24 D= High, W= Clear, I= PDO-1, Wz= Lng.Trm 3 0.021 No25 D= High, W= Med.Rain, I= No, Wz= None 0.000 No26 D= High, W= Med.Rain, I= No, Wz= Lng.Trm 3 0.002 No27 D= High, W= Med.Rain, I= PDO-1, Wz= None 0.000 No28 D= High, W= Med.Rain, I= PDO-1, Wz= Lng.Trm 3 0.004 No29 D= High, W= Lt.Snow, I= No, Wz= None 0.006 No30 D= High, W= Lt.Snow, I= PDO-1, Wz= Lng.Trm 3 0.000 No

Sum=1

Step 4: Batch Processing ATDM Scenarios

Please press "Batch Process All ATDM Scenarios" to start batch processing.

Please Enter "Scenario Description" and "Scenario Probability"

Step 3 : FREEVAL-RL-ATDM Scenario Configuration

Batch Process All Scenarios

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After ATDM AnalysisSteps 15-19

15 - TDM worksheet16 - Weather TMP worksheet17 - Traffic incident management sheet18 - Work zone traffic management plan19 - Other strategies

◦Managed lanes, VSL, Truck Ban, Metering

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Step 15 – TDM Plan Calculator

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1. Combined Effects Calculator TDM Plan For Recurrent CongestionTDM TDM TDM

Spd Cap Dem #1 #2 #3A. Control Strategies

Base (same as in seed file) 1.00 1.00 1.00 - - -HOT Lane – Static Toll 1.00 1.00 0.90 Yes Yes YesHOT Lane – Congestion Price 1.00 1.00 0.90 - Yes YesFull Facility Static Toll 1.00 1.00 0.90 - - YesFull Facility Dynamic Pricing 1.00 1.00 0.90 - - Yes

B. Advisory StrategiesBase (same as in seed file) 1.00 1.00 1.00 - - -Pre-Trip Traveler Info 1.00 1.00 0.90 Yes Yes YesChangeable Message Signs 1.00 1.00 0.90 - Yes YesEmployer TDM 1.00 1.00 0.90 - - Yes

2. Suggested Combined Effects for Consideration in TDM Effects MatrixPlan Spd Cap DemTDM #1 1.00 1.00 0.81TDM #2 1.00 1.00 0.66TDM #3 1.00 1.00 0.48

Performance Effects

TDM Plan Inputs

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Name Spd Cap DemVery Low Demand 1.00 1.00 1.00Low Demand 1.00 1.00 0.90Low-Med Demand 1.00 1.00 0.81Medium Demand 1.00 1.00 0.70Medium-High Demand 1.00 1.00 0.66High Demand 1.00 1.00 0.55Very High Demand 1.00 1.00 0.48

3. Adjustments to account for effect of Recurrent Congestion TDM Plan (1.00 means no change)

This is what really counts. Previous results were a suggestion.

Step 16 – Weather TMP Calculator

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1. Combined Effects Calculator Weather TMP Plan For Recurrent CongestionW-TMP W-TMP W-TMP

Spd Cap Dem #1 #2 #31 Control Strategies

Base (same as in seed file) 1.00 1.00 1.00 - - -Vehice Restrictions (chain controls) 1.00 1.05 0.90 Yes Yes Yes

2 Advisory StrategiesBase (same as in seed file) 1.00 1.00 1.00 - - -Pre-Trip Traveler Info 1.00 1.00 0.80 Yes Yes YesChangeable Message Signs 1.00 1.00 0.80 - Yes YesEmployer TDM 1.00 1.00 0.80 - - Yes

3 Treatment StrategiesBase (same as in seed file) 1.00 1.00 1.00 - - -Snow removal 1.10 1.10 1.00 Yes Yes YesAnti-Icing 1.10 1.10 1.00 - Yes YesFog Dispersion 1.10 1.10 1.00 - - Yes

2. Suggested Combined Effects for Consideration in Weather TMP Effects MatrixCombined Effects Spd Cap DemW-TMP #1 1.10 1.16 0.72W-TMP #2 1.21 1.27 0.58W-TMP #3 1.33 1.40 0.46

Performance Effects

Step 17 – TIM Calculator (1)

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1. Combined Effects CalculatorTIMP TIMP TIMP

Detect Respond Clear Spd Cap Dem #1 #2 #31 Site Management & Traffi c Control

Base (No new strategies not already in seed file) 1.00 1.00 1.00 1.00 1.00 1.00 - - -Incident Command System 1.00 0.90 1.00 1.00 1.00 1.00 Yes Yes YesTraffi c Control With On-Site Traffi c Manage Teams 1.00 1.00 1.00 1.10 1.10 1.00 - Yes YesEnd-of-Queue Advance Warning Systems 1.00 1.00 1.00 1.00 1.00 1.00 - - Yes

2 Advisory (Traveler Information) Strategies Detect Respond Clear Spd Cap DemBase (No new strategies not already in seed file) 1.00 1.00 1.00 1.00 1.00 1.00 - - -Pre-Trip Traveler Info 1.00 1.00 1.00 1.00 1.00 0.90 Yes Yes YesChangeable Message Signs 1.00 1.00 1.00 1.00 1.00 0.90 - Yes YesPortable Message Signs 1.00 1.00 1.00 1.00 1.00 0.90 - - YesEmployer TDM 1.00 1.00 1.00 1.00 1.00 0.90 - - Yes

3 Detection & Verification Strategies Detect Respond Clear Spd Cap DemBase (No new strategies not already in seed file) 1.00 1.00 1.00 1.00 1.00 1.00 - - -Field Verification by On-Site Responders 0.90 1.00 1.00 1.00 1.00 1.00 Yes Yes YesClosed-Circuit Television Cameras 0.90 1.00 1.00 1.00 1.00 1.00 - Yes YesFrequent/Enhanced Roadway Reference Markers 0.90 1.00 1.00 1.00 1.00 1.00 - Yes YesEnhanced 9-1-1/Automated Positioning Systems 0.90 1.00 1.00 1.00 1.00 1.00 - - YesMotorist Aid Call Boxes 0.90 1.00 1.00 1.00 1.00 1.00 - - YesAutomated Collision Notification Systems 0.90 1.00 1.00 1.00 1.00 1.00 - - Yes

Traffi c Incident Management Plan Elements (1.00 means no change from "Before ATDM" condition)

Incident Duration FactorsTraffi c Incident Management Strategies Performance Effects

TIM Calculator (2)

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1. Combined Effects CalculatorTIMP TIMP TIMP

Detect Respond Clear Spd Cap Dem #1 #2 #34 Response

Base (No new strategies not already in seed file) 1.00 1.00 1.00 1.00 1.00 1.00 - - -Personnel/Equipment Resource Lists 1.00 0.90 1.00 1.00 1.00 1.00 Yes Yes YesTowing and Recovery Vehicle Identification Guide 1.00 0.90 1.00 1.00 1.00 1.00 Yes Yes YesInstant Tow Dispatch Procedures 1.00 0.90 1.00 1.00 1.00 1.00 - Yes YesTowing and Recovery Zone-Based Contracts 1.00 0.90 1.00 1.00 1.00 1.00 - Yes YesEnhanced Computer-Aided Dispatch 1.00 0.90 1.00 1.00 1.00 1.00 - - YesDual/Optimized Dispatch Procedures 1.00 0.90 1.00 1.00 1.00 1.00 - - YesMotorcycle Patrols 1.00 0.90 1.00 1.00 1.00 1.00 - - YesEquipment Staging Areas/Pre-positioned Equipment 1.00 0.90 1.00 1.00 1.00 1.00 - - Yes

5 Quick Clearance & Recovery Detect Respond Clear Spd Cap DemBase (No new strategies not already in seed file) 1.00 1.00 1.00 1.00 1.00 1.00 - - -Incident Investigation Sites 1.00 1.00 0.90 1.00 1.00 1.00 Yes Yes YesQuick Clearance Laws 1.00 1.00 0.90 1.00 1.00 1.00 Yes Yes YesQuick Clearance Policies 1.00 1.00 0.90 1.00 1.00 1.00 - Yes YesQuick Clearance Incentives 1.00 1.00 0.90 1.00 1.00 1.00 - Yes YesExpedited Crash Investigations 1.00 1.00 0.90 1.00 1.00 1.00 - - YesService Patrols 1.00 1.00 0.90 1.00 1.00 1.00 - - YesEnhanced Capability Service Patrols 1.00 1.00 0.90 1.00 1.00 1.00 - - YesMajor Incident Response Teams 1.00 1.00 0.90 1.00 1.00 1.00 - - Yes

2. Suggested Combined Effects for Consideration in TIM Effects MatrixCombined Effects Detect Respond Clear Spd Cap DemW-TMP #1 0.90 0.73 0.81 1.00 1.00 0.90W-TMP #2 0.73 0.59 0.66 1.10 1.10 0.81W-TMP #3 0.53 0.39 0.43 1.10 1.10 0.66

Traffi c Incident Management Plan Elements (1.00 means no change from "Before ATDM" condition)

Incident Duration FactorsTraffi c Incident Management Strategies Performance Effects

Step 18 – Work Zone TMP Calculator

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1. Combined Effects CalculatorWZ-TMP WZ-TMP WZ-TMP

Spd Cap Dem #1 #2 #31 Site Management & Traffi c Control

Base (No new strategies not already in seed file) 1.00 1.00 1.00 Yes Yes YesEnd-of-Queue Advance Warning Systems 1.00 1.05 1.00 - Yes YesSpeed Feedback Signs (User specified effect) 0.90 1.00 1.00 - - YesAutomated Speed Enforcement (User specified effect) 0.90 1.00 1.00 - - Yes

2 Traveler Information Advisory StrategiesBase (No new strategies not already in seed file) 1.00 1.00 1.00 - - -Pre-Trip Traveler Info (User specifies effectiveness) 1.00 1.00 0.90 Yes Yes YesChangeable Message Signs (User specifies effectiveness) 1.00 1.00 0.90 - Yes YesPortable Message Signs (User specified effectiveness) 1.00 1.00 0.90 - - YesEmployer TDM (User specifies effectiveness) 1.00 1.00 0.90 - - YesDetours 1.00 1.00 0.80 - - Yes

2. Suggested Combined Effects for Consideration in TIM Effects MatrixCombined Effects Spd Cap DemWZ-TMP #1 1.00 1.00 0.90WZ-TMP #2 1.00 1.05 0.81WZ-TMP #3 0.81 1.05 0.52

Traffi c Work Zone Management Strategies Performance Effects

Work Zone Traffi c Management Plan Elements (1.00 means no change from "Before ATDM" condition)

Variable Speed Limits

Set on TIM worksheet

◦Specify mph reduction per half mile upstream of incident.

◦Same reduction rate applies to work zones.

Specify VSL in terms of expected reduction in free-flow speeds

◦Embed an estimate of compliance.

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Step 19 - Lane Management, Truck Bans, & Meters (1)

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Scen Prob Demand Weather Incident workzone HOV/HOT Shoulder Median Truck Controls Meter

1 19.48% Low Clear No None Base Base Base Base Base

2 1.39% Low Clear No Lng.Trm 3 HOV Shldr-Aux Med-Bus Base Base

3 1.56% Low Clear PDO-1 None HOV Shldr-Aux Med-Bus Base Meter On - Static

4 0.11% Low Clear PDO-1 Lng.Trm 3 HOV-All Shldr-Bus Med-HOV Base Meter On - Static

5 1.56% Low Med.Rain No None HOV-All Shldr-Bus Med-HOV Truck Ban Dynamic-Local

6 0.11% Low Med.Rain No Lng.Trm 3 HOT Shldr-HOV Med-All Truck Ban Dynamic-Local

7 0.12% Low Med.Rain PDO-1 None HOT Shldr-HOV Med-All Truck Ban Meter Off

8 0.01% Low Med.Rain PDO-1 Lng.Trm 3 HOT-Free Shldr-All Base Truck Ban Meter Off

9 1.17% Low Lt.Snow No None HOT-Free Shldr-All Base Truck Ban Base

10 0.08% Low Lt.Snow No Lng.Trm 3 Base Base Base Base Base

11 3.12% Med Clear PDO-1 None Base Base Base Base Base

12 0.22% Med Clear PDO-1 Lng.Trm 3 HOV Shldr-Aux Med-Bus Base Base

13 38.96% Med Clear No None HOV Shldr-Aux Med-Bus Base Meter On - Static

14 2.78% Med Clear No Lng.Trm 3 HOV-All Shldr-Bus Med-HOV Base Meter On - Static

15 0.25% Med Med.Rain PDO-1 None HOV-All Shldr-Bus Med-HOV Truck Ban Dynamic-Local

16 0.02% Med Med.Rain PDO-1 Lng.Trm 3 HOT Shldr-HOV Med-All Truck Ban Dynamic-Local

17 3.12% Med Med.Rain No None HOT Shldr-HOV Med-All Truck Ban Meter Off

18 0.22% Med Med.Rain No Lng.Trm 3 HOT-Free Shldr-All Base Truck Ban Meter Off

19 0.19% Med Lt.Snow PDO-1 None HOT-Free Shldr-All Base Truck Ban Base

20 0.01% Med Lt.Snow PDO-1 Lng.Trm 3 Base Base Base Base Base

21 19.48% High Clear No None Base Base Base Base Base

22 1.39% High Clear No Lng.Trm 3 HOV Shldr-Aux Med-Bus Base Base

23 1.56% High Clear PDO-1 None HOV Shldr-Aux Med-Bus Base Meter On - Static

24 0.11% High Clear PDO-1 Lng.Trm 3 HOV-All Shldr-Bus Med-HOV Base Meter On - Static

25 1.56% High Med.Rain No None HOV-All Shldr-Bus Med-HOV Truck Ban Dynamic-Local

26 0.11% High Med.Rain No Lng.Trm 3 HOT Shldr-HOV Med-All Truck Ban Dynamic-Local

27 0.12% High Med.Rain PDO-1 None HOT Shldr-HOV Med-All Truck Ban Meter Off

28 0.01% High Med.Rain PDO-1 Lng.Trm 3 HOT-Free Shldr-All Base Truck Ban Meter Off

29 1.17% High Lt.Snow No None HOT-Free Shldr-All Base Truck Ban Base

30 0.01% High Lt.Snow PDO-1 Lng.Trm 3 Base Base Base Base Base

Step 19 - Lane Management, Truck Bans, & Meters (2)

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1 19.48% Low Clear No None Base Base Base Base Base

2 1.39% Low Clear No Lng.Trm 3 HOV Shldr-Aux Med-Bus Base Base

3 1.56% Low Clear PDO-1 None HOV Shldr-Aux Med-Bus Base Meter On - Static

4 0.11% Low Clear PDO-1 Lng.Trm 3 HOV-All Shldr-Bus Med-HOV Base Meter On - Static

5 1.56% Low Med.Rain No None HOV-All Shldr-Bus Med-HOV Truck Ban Dynamic-Local

6 0.11% Low Med.Rain No Lng.Trm 3 HOT Shldr-HOV Med-All Truck Ban Dynamic-Local

7 0.12% Low Med.Rain PDO-1 None HOT Shldr-HOV Med-All Truck Ban Meter Off

8 0.01% Low Med.Rain PDO-1 Lng.Trm 3 HOT-Free Shldr-All Base Truck Ban Meter Off

9 1.17% Low Lt.Snow No None HOT-Free Shldr-All Base Truck Ban Base

10 0.08% Low Lt.Snow No Lng.Trm 3 Base Base Base Base Base

11 3.12% Med Clear PDO-1 None Base Base Base Base Base

12 0.22% Med Clear PDO-1 Lng.Trm 3 HOV Shldr-Aux Med-Bus Base Base

13 38.96% Med Clear No None HOV Shldr-Aux Med-Bus Base Meter On - Static

14 2.78% Med Clear No Lng.Trm 3 HOV-All Shldr-Bus Med-HOV Base Meter On - Static

15 0.25% Med Med.Rain PDO-1 None HOV-All Shldr-Bus Med-HOV Truck Ban Dynamic-Local

16 0.02% Med Med.Rain PDO-1 Lng.Trm 3 HOT Shldr-HOV Med-All Truck Ban Dynamic-Local

17 3.12% Med Med.Rain No None HOT Shldr-HOV Med-All Truck Ban Meter Off

18 0.22% Med Med.Rain No Lng.Trm 3 HOT-Free Shldr-All Base Truck Ban Meter Off

19 0.19% Med Lt.Snow PDO-1 None HOT-Free Shldr-All Base Truck Ban Base

20 0.01% Med Lt.Snow PDO-1 Lng.Trm 3 Base Base Base Base Base

21 19.48% High Clear No None Base Base Base Base Base

22 1.39% High Clear No Lng.Trm 3 HOV Shldr-Aux Med-Bus Base Base

23 1.56% High Clear PDO-1 None HOV Shldr-Aux Med-Bus Base Meter On - Static

24 0.11% High Clear PDO-1 Lng.Trm 3 HOV-All Shldr-Bus Med-HOV Base Meter On - Static

25 1.56% High Med.Rain No None HOV-All Shldr-Bus Med-HOV Truck Ban Dynamic-Local

26 0.11% High Med.Rain No Lng.Trm 3 HOT Shldr-HOV Med-All Truck Ban Dynamic-Local

27 0.12% High Med.Rain PDO-1 None HOT Shldr-HOV Med-All Truck Ban Meter Off

28 0.01% High Med.Rain PDO-1 Lng.Trm 3 HOT-Free Shldr-All Base Truck Ban Meter Off

29 1.17% High Lt.Snow No None HOT-Free Shldr-All Base Truck Ban Base

30 0.01% High Lt.Snow PDO-1 Lng.Trm 3 Base Base Base Base Base

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Managed Lanes Response - HOV/HOT

Code # Shrt.Name Description Parameter 1 Parameter 2 Parameter 3 Calculated Parameters

1.00 Base Leaves lanes as coded in seed file Number HOV Lanes 0 Mixed Flow Cap (vph/ln) 2100 HOV/HOT Cap/Mixed Flow Cap 1.00

2.00 HOV Convert Left most coded lanes to HOV Number HOV Lanes 1 Mainline HOV's (vph) 450 HOV/HOT Cap (vph/ln) 1800 HOV/HOT Cap/Mixed Flow Cap 0.21

3.00 HOV-All Throws open HOV Lanes to all traffi c Number HOV Lanes 1 HOV/HOT Cap (vph/ln) 2100 HOV/HOT Cap/Mixed Flow Cap 1.00

4.00 HOT Convert Left most coded lanes to HOT Number HOT Lanes 1 Actual HOT use (vph) 1500 HOV/HOT Cap (vph/ln) 1600 HOV/HOT Cap/Mixed Flow Cap 0.71

5.00 HOT-Free Throws open HOT lanes to all traffi c, zero tollNumber HOT Lanes 1 HOV/HOT Cap (vph/ln) 2100 HOV/HOT Cap/Mixed Flow Cap 1.00

Managed Lanes Response - Shoulder


1.00 Base Leaves lanes as coded in seed file Number of Shldr Lanes 0 Mixed Flow Cap (vph/ln) 2100 Shldr Cap/Mixed Flow Cap 1.00

2.00 Shldr-Aux Opens Shoulder as Aux. Lane between on/off rampsNumber of Shldr Lanes 1 Actual Shlder use (vph) 1050 Shoulder Cap (vph/ln) 1250 Shldr Cap/Mixed Flow Cap 0.50

3.00 Shldr-Bus Opens Shoulder to buses only. Number of Shldr Lanes 1 Buses/Hour 12 Shoulder Cap (vph/ln) 1250 Shldr Cap/Mixed Flow Cap 0.01

4.00 Shldr-HOV Shoulder for HOV's + Entry/Exit Number of Shldr Lanes 1 Mainline HOV's (vph) 450 Shoulder Cap (vph/ln) 1250 Shldr Cap/Mixed Flow Cap 0.21

5.00 Shldr-All Opens Shoulder to All traffi c Number of Shldr Lanes 1 Shoulder Cap (vph/ln) 1250 Shldr Cap/Mixed Flow Cap 0.60

Managed Lanes Response - Median


1.00 Base Leaves lanes as coded in seed file Number of Median Lanes 0 Mixed Flow Cap (vph/ln) 2100 Med Cap/Mixed Flow Cap 1.00

2.00 Med-Bus Opens median to buses Number of Median Lanes 1 Buses/Hour 12 Median Cap (vph/ln) 1300 Med Cap/Mixed Flow Cap 0.01

3.00 Med-HOV Opens median to HOV's Number of Median Lanes 1 Mainline HOV's (vph) 450 Median Cap (vph/ln) 1300 Med Cap/Mixed Flow Cap 0.21

4.00 Med-All Opens median to all traffi c Number of Median Lanes 1 Median Cap (vph/ln) 1300 Med Cap/Mixed Flow Cap 0.62

5.00 Other Do Not Use - Not Activated Number of Median Lanes 0 Median Cap (vph/ln) 1300 Med Cap/Mixed Flow Cap 1.00

Managed Lanes Response - Truck Controls


1.00 Base No change from seed file Mixed Flow Cap (vph/ln) 2100

2.00 Truck Ban No trucks allowed Percent Heavy Vehicles 5.00% Percent of HVs Banned 80.00% PCE/truck 2 Cap Adj. Fac. 1.10

3.00 Other Do Not Use - Not Activated



Ramp Metering ResponseCode # Shrt.Name Description Parameter 1 Parameter 2 Parameter 3 Parameter 4

1.00 Base Leaves meter rates as coded in seed file.2.00 Meter On - Static Sets Meters to Static Rates Merge Capacity Adjust 1.03 Not Used Max. Meter Rate (vph/Ln) 900 Demand Adj. for Divert 1.003.00 Dynamic-Local Dynamically adjust rates - local optimaMerge Capacity Adjust 1.03 Min. Meter Rate (vph/Ln) 240 Max. Meter Rate (vph/Ln) 900 Targer VPH/Lane 21004.00 Meter Off Turn off all meters Merge Capacity Adjust 0.97 Ramp capacity (vph/Ln) 2100 Demand Adj. for Divert 1.005.00 Other Do Not Use - Not Activated

3.00 For Dynamic-Local Meters: Max. Ramp Storage(veh) 40 Demand Adj. for Divert 1.00Ste

p 1

9 -

Para

mete

rs

Steps 20-25Run After ATDM Analysis

Step 20 – Compute ATDM factors (macro)Step 21 – Review warning messagesStep 22 – Export factors to file (macro)Step 23 – Copy files to new directoryStep 24 – Run Freeval

◦Import factors file

◦Run ATDM analysis

Step 25 - Review Results93

Ste

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FR

EEV

AL-A

TD

MIm

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Facto

rs

94

ATDM Analysis Scenarios Configuration

Following file is selected:

C:\work\proj\proj2009\p09058 fhwa atm hcm\phase3\final report\example\hov\hovAfterAdjust.xlsx

First Select your ATDM Adjustment Factors file, and then press "Insert Adjustment Factors File" to proceed.

Step 1 : Seed File Data Entry1. Go to "t=1" sheet and put geometrical and seed scenario's demand information of the facility you would like to analyze

Step 2 : Identify the Adjustment Factors File

The adjustment factors file should located in the same folder as current Excel file.

2. Come back to "ATDM Input" sheet for continuing scenario configuration. Yellow background cells needs to be edited and data entered by user.

3. If user wants, he can import all geometric and demand information from another FREEVAL-ATDM coded seed file by pressing "Import From Another FREEVAL-ATDM Seed File" button.

Take me to t=1

Insert Adjustment Factors File

Select ATDM Adjustment Factors File

Import From Another FREEVAL-ATDM Seed File

95

Scenario Number

Scenario DescriptionScenario

ProbabilitySave File?

1 D= Low, W= Clear, I= No, Wz= None 0.001 No2 D= Low, W= Clear, I= No, Wz= Lng.Trm 3 0.086 No3 D= Low, W= Clear, I= PDO-1, Wz= None 0.011 No4 D= Low, W= Clear, I= PDO-1, Wz= Lng.Trm 3 0.011 No5 D= Low, W= Med.Rain, I= No, Wz= None 0.043 No6 D= Low, W= Med.Rain, I= No, Wz= Lng.Trm 3 0.172 No7 D= Low, W= Med.Rain, I= PDO-1, Wz= None 0.086 No8 D= Low, W= Med.Rain, I= PDO-1, Wz= Lng.Trm 3 0.001 No9 D= Low, W= Lt.Snow, I= No, Wz= None 0.057 No10 D= Low, W= Lt.Snow, I= No, Wz= Lng.Trm 3 0.102 No11 D= Med, W= Clear, I= PDO-1, Wz= None 0.000 No12 D= Med, W= Clear, I= PDO-1, Wz= Lng.Trm 3 0.086 No13 D= Med, W= Clear, I= No, Wz= None 0.057 No14 D= Med, W= Clear, I= No, Wz= Lng.Trm 3 0.006 No15 D= Med, W= Med.Rain, I= PDO-1, Wz= None 0.004 No16 D= Med, W= Med.Rain, I= PDO-1, Wz= Lng.Trm 3 0.004 No17 D= Med, W= Med.Rain, I= No, Wz= None 0.007 No18 D= Med, W= Med.Rain, I= No, Wz= Lng.Trm 3 0.172 No19 D= Med, W= Lt.Snow, I= PDO-1, Wz= None 0.002 No20 D= Med, W= Lt.Snow, I= PDO-1, Wz= Lng.Trm 3 0.057 No21 D= High, W= Clear, I= No, Wz= None 0.000 No22 D= High, W= Clear, I= No, Wz= Lng.Trm 3 0.001 No23 D= High, W= Clear, I= PDO-1, Wz= None 0.000 No24 D= High, W= Clear, I= PDO-1, Wz= Lng.Trm 3 0.021 No25 D= High, W= Med.Rain, I= No, Wz= None 0.000 No26 D= High, W= Med.Rain, I= No, Wz= Lng.Trm 3 0.002 No27 D= High, W= Med.Rain, I= PDO-1, Wz= None 0.000 No28 D= High, W= Med.Rain, I= PDO-1, Wz= Lng.Trm 3 0.004 No29 D= High, W= Lt.Snow, I= No, Wz= None 0.006 No30 D= High, W= Lt.Snow, I= PDO-1, Wz= Lng.Trm 3 0.000 No

Sum=1

Step 4: Batch Processing ATDM Scenarios

Please press "Batch Process All ATDM Scenarios" to start batch processing.

Please Enter "Scenario Description" and "Scenario Probability"

Step 3 : FREEVAL-RL-ATDM Scenario Configuration

Batch Process All Scenarios

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Step 25 –Results (1)

96

20 97.6 630 9

1.68 Misery Index 5.451.23 3.371.99 66.17%3.82 18.58%

Recurring 1.8 0.1 15.1%Non-Recurring 56.8 3.6 84.9%Total 58.6 3.7 100.0%

1.1 4.02.0 12.91% 35%

99% 65%100.0% 100.0%

0.00% 0.00%

Facility DescriptionNumber of Segments Number of Weather ScenariosFacility Length (miles) Number of Incident ScenariosNumber of Total Scenarios Numb. of Incident + Weather Scenarios

% Time with Queues on the Facility % Time with Queues on the Facility

80th Percentile TTI Reliability Rating95th Percentile TTI (PTI) Percent of VMT at TTI > 2

Probability Density Function (480 Obs.) Cumulative Distribution Function (480 Obs.)

Mean TTI

% VMT Served in the Study Period % VMT Served in the Study Period% VMT Unserved in the Study Period % VMT Unserved in the Study Period

(VMT and Probability Weighted)

VHD Under Condition (Veh. Hrs)

Total During RRP

Average in 15 min

% Time in Condition

Percent Contribution to Total Vehicular Hours of Delay (VHD)

(VMT and Probability Weighted)

Maximum 15-min Facility TTI Maximum 15-min Facility TTI

50th Percentile TTI Semi-Standard Deviation

% Time without Queues on the Facility % Time without Queues on the Facility

Analysis Details for Reliability Reporting Period by Congestion Status and Scenarios

Scenarios with Recurring Congestion All ScenariosMaximum 15-min Segment D/C Ratio Maximum 15-min Segment D/C Ratio

Facility Reliability Performance Measures

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

[1,1

.2)

[1.4

,1.6

)

[1.8

,2)

[2.2

,2.4

)

[2.6

,2.8

)

[3,3

.2)

[3.4

,3.6

)

[3.8

,4)

[4.2

,4.4

)

[4.6

,4.8

)

5+

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

11.

31.

61.

92.

22.

52.

83.

13.

43.

7 44.

34.

64.

9

3%

97%

Recurring

Non-Recurring

97

1 0.1% 100,002 100,002 140 1,569 0.86 7.6 1.1 63.7 59.8 0.00 0.0%

2 8.6% 100,002 100,002 184 1,613 1.02 8.2 1.1 62.0 55.5 0.38 12.5%

3 1.1% I 100,002 100,002 143 1,571 0.96 7.6 1.1 63.6 59.8 0.00 0.0%

4 1.1% I 100,002 100,002 1,207 2,635 3.27 61.5 2.2 37.9 15.0 2.15 62.5%

5 4.3% W 100,002 100,002 262 1,690 0.93 8.4 1.2 59.2 54.4 0.00 0.0%

6 17.2% W 100,002 100,002 389 1,818 1.09 10.6 1.2 55.0 43.3 1.08 25.0%

7 8.6% WI 100,002 100,002 270 1,699 1.03 8.4 1.2 58.9 54.4 0.17 0.0%

8 0.1% WI 100,002 100,002 2,205 3,634 3.51 68.3 2.9 27.5 14.2 3.41 75.0%

9 5.7% W 100,002 100,002 374 1,803 0.95 8.9 1.3 55.5 51.0 0.00 0.0%

10 10.2% W 100,002 100,002 623 2,051 1.12 12.7 1.4 48.8 36.3 1.79 31.3%

11 0.0% I 107,529 107,529 182 1,718 1.03 7.8 1.1 62.6 58.0 0.19 0.0%

12 8.6% I 107,529 107,529 2,295 3,831 3.51 68.9 2.8 28.1 14.0 3.64 75.0%

13 5.7% 107,529 107,529 172 1,708 0.93 7.8 1.1 63.0 58.0 0.00 0.0%

14 0.6% 107,529 107,529 313 1,849 1.09 10.2 1.2 58.2 45.1 1.20 25.0%

15 0.4% WI 107,529 107,529 347 1,883 1.11 9.8 1.2 57.1 48.0 0.47 6.3%

16 0.4% WI 107,529 107,529 3,833 5,370 3.78 77.0 3.8 20.0 13.2 6.06 87.5%

17 0.7% W 107,529 107,529 312 1,848 1.00 8.7 1.2 58.2 52.1 0.00 0.0%

18 17.2% W 107,529 107,529 849 2,385 1.17 15.1 1.5 45.1 30.0 3.19 43.8%

19 0.2% WI 107,529 107,529 504 2,040 1.13 10.9 1.3 52.7 43.8 0.98 18.8%

20 5.7% WI 107,529 107,526 4,350 5,886 3.86 79.9 4.2 18.3 12.9 6.06 93.8%M

ean

TTI

Scenario Details

% 1

5-m

ins

with

LOS=

F

Scen

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N

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r

Scen

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Pr

obab

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VMTD

Veh-

mile

s (D

eman

d)

VMTV

Veh-

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s (V

olum

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Type

VHD

dela

y (h

rs)

Max

D/C

VHT

Mea

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eed

(mph

)

Max

Tra

vel

Tim

e (m

in)

Min

Spe

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(mph

)

Max

Q

Leng

th (m

i)

Step 25 - Results (3)

98

MOE Before After Diff %

VMT Demand 25,847,488 25,847,488 0 0.0%

VMT Served 25,847,198 25,847,488 290 0.0%

VHT 603,529 561,258 -42,271 -7.5%

VHD 234,285 192,009 -42,276 -22.0%

MPH 42.83 46.05 3.23 7.0%

Ave. Delay 32.63 26.74 -5.89 -22.0%

PTI 3.92 3.36 -0.56 -16.5%

Example Applications

1. Before Conditions2. ATDM1 – Convert HOV to HOT3. ATDM2 – Add Dynamic Metering4. ATDM3 – Add Incident/Employer TDM

99

The Site

EB Freeway - 4-Hour PM Peak, 70 mph FFS, HOV Lane

Required Data

◦Conventional HCM analysis data (seed file)

◦Demand variability (permanent count station) data

◦Collision records, Weather records, Work Zone records

100

Conventional HCM Inputs

101

SEGMENT: 1 2 3 4 5 6 7 8 9 10Type B B OFR B ONR B OFR B ONR BLength (ft) 2000 2000 2000 2000 2000 2000 2000 2000 2000 2000Lanes 3 3 3 3 3 3 3 3 3 3Free-Flow Speed (mph) 70 70 70 70 70 70 70 70 70 70

Demand (vph) 2700 2700 2700 2500 2700 2700 2700 2500 2700 2700Capacity Adj. 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Origin Demand Adj. 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Destination Demand Adj. 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

Speed Adjust. 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00% Trucks 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0 5.0% RV's 0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0On-Ramp Demand (vph) 200 200 On-Ramp % Trucks 5 5 On-Ramp % RV's 0 0 Off-Ramp Demand(vph) 200 200 Off-Ramp % Trucks 5 5 Off-Ramp % RV's 0 0 Acc/ Dec Lane Length (ft) 300 300 300 300 Lanes on Ramp 1 1 1 1 Ramp Side Right Right Right Right Ramp FFS (mph) 45 45 45 45 Ramp Meter Rate (vph) 2100 2100 Ramp-to-Ramp Demand (vph)

Active Management

Application 1 – “Before” Analysis

102

Demand Variability Data

103

Level of DemandRatio of Demand to Seed File Demand

Probability

5th Percentile Highest Demand 0.77 10.0%







Average or Total 0.977 100.0%

Weather Data

104

Weather RangeFree-Flow Speed.Adj.

Capacity Adjust.

Demand Adjust.

Probability

Clear n/a 1.00 1.00 1.00 50.0%Light Rain >0.00 and <=0.10 in/hr 0.98 0.98 1.00 8.0%Medium Rain >0.10 and <=0.25 in/hr 0.94 0.93 1.00 4.0%Heavy Rain >0.25 in/hr 0.93 0.86 1.00 2.0%Very Light Snow >0.00 and <=0.05 in/hr 0.89 0.96 1.00 6.0%Light Snow >0.05 and <=0.10 in/hr 0.88 0.91 1.00 3.0%Medium Snow >0.10 and <=0.50 in/hr 0.86 0.89 1.00 2.0%Heavy Snow >0.50 in/hr 0.85 0.76 1.00 2.0%Moderate Wind >10 and <=20 mph 0.99 0.99 1.00 4.0%High Wind >20 mph 0.98 0.98 1.00 2.0%Cool <50 and >=340 F 0.99 0.99 1.00 2.0%Cold <34 and >=-40 F 0.98 0.98 1.00 2.0%Very Cold <-40 F 0.94 0.91 1.00 3.0%Medium Visibility <1.00 and >=0.50 miles 0.94 0.90 1.00 2.0%Low Visibility <0.50 and >=0.25 miles 0.93 0.88 1.00 2.0%Very Low Visibility <0.25 miles 0.93 0.88 1.00 6.0%

Average or Total 0.97 0.97 1.00 100.0%

Incident Data

105

IncidentType

Max. Lanes Blocked

Free-FlowSpeed Adjust.

CapacityAdjust

DemandAdjust

Probability

No Incident Present n/a 1.00 1.00 1.00 50.0%

Non-Crashes Shoulder 0.99 0.99 1.00 10.0%

1 0.79 0.79 1.00 7.0%

2+ 0.61 0.61 1.00 6.0%

Property Damage Only Crashes Shoulder 0.86 0.86 1.00 5.0%

1 0.79 0.79 1.00 4.0%

2+ 0.61 0.61 1.00 4.0%

Injury Crashes Shoulder 0.86 0.86 1.00 3.0%

1 0.79 0.79 1.00 3.0%

2+ 0.61 0.61 1.00 3.0%

Fatal Crashes Shoulder 0.86 0.86 1.00 1.0%

1 0.79 0.79 1.00 2.0%

2+ 0.61 0.61 1.00 2.0%

Average or Total: 0.89 0.89 1.00 100.0%

Work Zone Data

106

Work Zone Type Lanes Open Capacity/LaneFree-Flow

Speed Adjust

Demand Adjust

Probability

No Work Zone All 2000 1.00 1.00 70.0%

Short Term

1 1600 0.80 1.00 5.0%

2 1600 0.80 1.00 5.0%

3 1600 0.80 1.00 5.0%

Long Term

1 1400 0.70 1.00 5.0%

2 1450 0.73 1.00 5.0%

3 1500 0.75 1.00 5.0%

Average or Total 0.93 1.00 100.0%

Select 30 Scenarios

107

Number Demand Weather Incident Work ZonesInitial

ProbabilityFinal

Probability1 Low Clear No None 1.7500% 19.48%2 Low Clear No Lng.Trm 3 0.1250% 1.39%3 Low Clear PDO-1 None 0.1400% 1.56%4 Low Clear PDO-1 Lng.Trm 3 0.0100% 0.11%5 Low Med.Rain No None 0.1400% 1.56%6 Low Med.Rain No Lng.Trm 3 0.0100% 0.11%7 Low Med.Rain PDO-1 None 0.0112% 0.12%8 Low Med.Rain PDO-1 Lng.Trm 3 0.0008% 0.01%9 Low Lt.Snow No None 0.1050% 1.17%10 Low Lt.Snow No Lng.Trm 3 0.0075% 0.08%11 Med Clear PDO-1 None 0.2800% 3.12%12 Med Clear PDO-1 Lng.Trm 3 0.0200% 0.22%13 Med Clear No None 3.5000% 38.96%14 Med Clear No Lng.Trm 3 0.2500% 2.78%15 Med Med.Rain PDO-1 None 0.0224% 0.25%16 Med Med.Rain PDO-1 Lng.Trm 3 0.0016% 0.02%17 Med Med.Rain No None 0.2800% 3.12%18 Med Med.Rain No Lng.Trm 3 0.0200% 0.22%19 Med Lt.Snow PDO-1 None 0.0168% 0.19%20 Med Lt.Snow PDO-1 Lng.Trm 3 0.0012% 0.01%21 High Clear No None 1.7500% 19.48%22 High Clear No Lng.Trm 3 0.1250% 1.39%23 High Clear PDO-1 None 0.1400% 1.56%24 High Clear PDO-1 Lng.Trm 3 0.0100% 0.11%25 High Med.Rain No None 0.1400% 1.56%26 High Med.Rain No Lng.Trm 3 0.0100% 0.11%27 High Med.Rain PDO-1 None 0.0112% 0.12%28 High Med.Rain PDO-1 Lng.Trm 3 0.0008% 0.01%29 High Lt.Snow No None 0.1050% 1.17%30 High Lt.Snow PDO-1 Lng.Trm 3 0.0006% 0.01%

Total 8.9841% 100.00%

Results – Before ATDM

108

Scenario Number

Scenario Probability

Max D/CMean TTI

Mean Speed (mph)

Max Q Length

(mi)

% 15-mins with LOS=F

1 19.5% 0.86 1.09 63.7 0.00 0.0%

2 1.4% 1.02 1.12 62.0 0.38 12.5%

3 1.6% 1.05 1.10 63.2 0.24 6.3%

4 0.1% 3.59 4.19 21.1 4.08 75.0%

5 1.6% 0.93 1.17 59.2 0.00 0.0%

6 0.1% 1.09 1.25 55.0 1.08 25.0%

7 0.1% 1.13 1.21 57.5 0.58 6.3%

8 0.0% 3.86 5.28 16.4 5.91 87.5%

9 1.2% 0.95 1.25 55.5 0.00 0.0%

10 0.1% 1.12 1.40 48.8 1.79 31.3%

Reliability “Before” ATDM

109

20 97.6 630 9

1.15 Misery Index 1.881.11 13.981.17 96.63%1.27 0.54%

50th Percentile TTI Semi-Standard Deviation

Facility Reliability Performance MeasuresMean TTI


Number of Incident ScenariosNumber of Total Scenarios Numb. of Incident + Weather Scenarios

Facility DescriptionNumber of Segments Number of Weather ScenariosFacility Length (miles)


1.1 4.42.0 27.90% 4%

100% 96%100.0% 100.0%

0.00% 0.00%






Total During RRP

Average in 15 min

% Time in Condition


Maximum 15-min Facility TTI Maximum 15-min Facility TTI% Time with Queues on the Facility % Time with Queues on the Facility

67%

33% Recurring

Non-Recurring

Active Management

Example #1 – Convert HOV To HOT

110

Capacity Adjustment

HOV Capacity = 1800 vph/ln

◦But max HOV’s = 1350 vph

Target HOT Vol = 1600 vph/ln

◦Allow for latency in tolls

◦Achievable HOT vol = 1500 vph

111

Results: Convert HOV to HOT

112

MOEBeforew. HOV

Afterw. HOT

Difference % Diff

VMT Demanded 26,674,965 26,674,965 0 0.0%

VMT Served 26,674,714 26,674,872 158 0.0%

VHT 438,126 432,492 -5,633 -1.3%

VHD 57,879 52,080 -5,799 -11.1%

Average Speed 60.88 61.68 0.79 1.3%

Average Delay (secs/mi) 7.81 7.03 -0.78 -11.1%

PTI 1.25 1.23 -0.02 -1.5%

Active Management

Example #2 – Add Dynamic Meter

113

Local Dynamic Metering

Set target max. merge volumeSubtract out upstream mainline demandRemainder is ramp metering rate

◦Subject to max and min rates

◦Subject to ramp storage

Make sure you are testing a “Good” Metering Plan

114

Results: HOT+Meter

115

HOT HOT + Meter Diff %

Annual VMT Demanded 26,674,965 26,674,965 0 0.0%

Annual VMT Served 26,674,872 26,674,943 71 0.0%

VHT 432,492 430,764 -1,728 -0.4%

VHD 52,080 50,305 -1,775 -3.5%

Average Speed 61.68 61.92 0.25 0.4%

Average Delay 7.03 6.79 -0.24 -3.5%

PTI 1.23 1.19 -0.04 -3.8%

Active Management

ATDM #3 – Add Incident TDM

116

Incident and Regular TDM

TDM for Recurring Congestion

◦Kick in major employer TDM on high demand days

TDM for Incidents

◦Kick in more intensive major employer TDM on days with major incidentsAdd in participation from smaller employers

117

Results: HOT+Meter+TDM

118

HOT + Meter

HOT + Meter + TDM

Difference % Diff

Annual VMT Demanded 26,674,965 26,062,769 -612,196 -2.3%

Annual VMT Served 26,674,943 26,062,769 -612,174 -2.3%

VHT 430,764 418,028 -12,737 -3.0%

VHD 50,305 46,241 -4,065 -8.8%

Average Speed 61.92 62.35 0.42 0.7%

Average Delay 6.79 6.39 -0.40 -6.3%

PTI 1.19 1.18 -0.01 -0.8%

Combined ATDM Program Results

119

Measure of Effectiveness

Before ATDM ATDM Plan Difference % Diff

Annual VMT Demanded 26,674,965 26,062,769 -612,196 -2.3%

Annual VMT Served 26,674,714 26,062,769 -611,945 -2.3%

Vehicle-Hours Traveled 438,126 418,028 -20,098 -4.6%

Vehicle-Hours Delay 57,879 46,241 -11,639 -20.1%

Average Speed (mph) 60.88 62.35 1.46 2.4%

Average Delay (secs/mi) 7.81 6.39 -1.42 -18.2%

PTI (Planning Time Index) 1.25 1.18 -0.07 -5.8%

HOT + Dynamic Metering + TDM

Results with ATDM Plan

120


1.0 3.71.3 20.10% 2%

100% 98%100.0% 100.0%

0.00% 0.00%

% Time with Queues on the Facility % Time with Queues on the Facility



Total During RRP

Average in 15 min

% Time in Condition


Maximum 15-min Facility TTI Maximum 15-min Facility TTI




69%

31% Recurring

Non-Recurring

1.12 Misery Index 1.541.10 7.631.14 99.10%1.22 0.35%


Mean TTI50th Percentile TTI Semi-Standard Deviation

Facility Reliability Performance Measures

121

Before ATDM HOT HOT+Dynamic Meter

HOT+Dynamic Meter+TDM

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

Increase in Average SpeedReduction in Average DelayReduction in PTI

Ch

an

ge in

Perf

orm

an

ce M

easu

re

122

0 10 20 30 40 50 60 700%

5%

10%

15%

20%

25%

Effects on Cumulative Speed Profiles

BeforeHOTMeterTDM

Average MPH

Biggest Im-provement at

Lower Percentiles

Modest Improve-ment at Higher Per-

centiles

Ne

glig

ible

Im

pro

ve

me

nt

123

HOV to HOT55%

Dynamic Me-tering17%

Travel Demand Management

28%

Relative Contributions of ATDM Plan Components to Delay Savings

(for I-580 Example Problem)

Comments/Questions?

124

Active Management

Next Steps

125

Next Steps

Upcoming workshopsDallas, TX – April 9, 2013Seattle, WA – April 23, 2013Baltimore, MD – May 2, 2013

Final Guidebook – June 2013HCQS Workshop HCM Chapter 35 – July 2013

126

Comments/Questions to:

◦James Colyar, FHWA, [email protected]

◦Jim Hunt, FHWA, [email protected]

◦Rick Dowling, [email protected]

◦Richard Margiotta, [email protected]

127

Acknowledgements

FHWA Review Team:

◦James Colyar, Jim Hunt, Jim Sturrock, Jim McCarthy, Chung Tran, John Halkias, Wayne Berman, Ralph Volpe, Robert Sheehan.

Consultant Team:

◦Erin Flanigan, Rick Dowling, Richard Margiotta, Harry Cohen, Seyed Aghdashi, Nagui Rouphail, Bastian Schroeder.

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analysis of active transportation and demand management strategies workshop 1 richard dowling,...

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