assessment and refinement of real-time travel time algorithms for use in practice
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Assessment and Refinement of Real-Time Travel Time Algorithms for Use in Practice. Nov 8, 2006. Outline. Ramp Meter Data Fidelity Assessment Inrix Data Update Data Collection Plan Travel Time Best Practices Results Schedule update. Ramp Meter Data Fidelity Assessment. - PowerPoint PPT PresentationTRANSCRIPT
Assessment and Refinement of Real-Time Travel Time Algorithms for Use in Practice Nov 8, 2006
Outline
Ramp Meter Data Fidelity Assessment Inrix Data Update Data Collection Plan Travel Time Best Practices Results Schedule update
Ramp Meter Data Fidelity Assessment Impacts of Various Factors on Travel Time
Estimation Accuracy Algorithms Detector Spacing Data Quality
Algorithm Comparison: Uncongested Runs
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Link No
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Coifman u/s
Coifman d/s
Midpoint
I-5 N(217-405)
I-5 S (Bridge-84)
I-5 S(405-217)
217 S I-205 S(84-O.City)
I-84 E(5-205)
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Link No
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Coifman u/s
Coifman d/s
Midpoint
Algorithm Comparison: Congested Runs
I-5 SB (405-217)
217 N 217 S I-205 N(5-O.City)
I-5 NB (84-Bridge)
I-5 S (Bridge-84)
I-84 E(5-205)
Large detector spacingSome probe runs encountered an incidentSignificant recurring congestion
293.00
294.00
295.00
296.00
297.00
298.00
299.00
300.00
8:11:00 8:13:00 8:15:00 8:17:00 8:19:00 8:21:00 8:23:00
Time
Mil
ep
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t (m
i.)
Probe
Coifman u/s
Coifman d/s
Midpt
Algorithms: Trajectory Comparison
Conclusions - Algorithms
FHWA says 90% accuracy is ideal, accuracy must be no less than 80% (Agrees with what we discussed last time)
No algorithm is consistently better and consistently < 10%
Many runs have error > 10% Appears to be associated with large detector spacing and
incidents Need more data to verify impacts of algorithms, spacing, etc.
Moderate impact from algorithm, but probably not enough to overcome infrastructure issues (more when we examine other states practices)
Detector Spacing Impacts-Analytical More detector stations => more data samples Lower error due to more samples If one detector has issues, others will mitigate
that problem Shockwave Propagation
When an incident/bottleneck occurs far from a detector, it takes time for the congestion to reach the detector
Shockwave propagation 12-16 mph, 15 mph = 4 minutes/mile
2 miles
1.5 miles = approx. 6 minutes
Detector 1
Detector 2
Bottleneck
Detector Spacing Impacts: Congested Conditions
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Average Detector Spacing (mi.)
Ave
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r (%
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Coifman (u/s)
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Average Detector Spacing (mi.)
Ave
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Midpoint
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Average Detector Spacing (mi.)
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Coifman (d/s)
I-205 NB – Stafford – MP 3.55 – Lane 2
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occupancy
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I-5 NB – Delta Park – MP 306.51 – Lane 2 speed
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occupancy
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810
1214
1618
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Conclusions – Detector Spacing and Data Quality Detector Spacing
Expect and think we see association with detector spacing Need more data to verify Are also creating an analytical model for detector spacing
impacts
Data quality Suspect there is an impact Need more data to verify Would like to clarify speed calculation procedure
Inrix Data
Provide flow and travel time data XML data stream
Data Sources Current data is a processed version of the ODOT
Region 1 loop detector data As of mid-November, probe data will be included
(transponder detectors from instrumented fleets (taxis, etc.))
Data Validation
Inrix has validated accuracy of their data for three east-coast cities The networks in these cities use probe data only Validation not valid for Portland (different city,
probe + detector data) Potential good source of data, but do not
believe we can use it as ground truth without more validation
We are getting sample data (NDA in process) Meeting with Inrix Technical Staff?
Ground Truth Data Collection – Phase 1 Initial Study to confirm methodology and
process Issues:
Collection Process Corridor selection - focus on two corridors for this
phase Number of Runs Timing of Runs
Quality Counts
Recommended by ODOT personnel $45/hour + mileage (currently ~$0.49/mile) We provide list of highways, hours, and a list
of locations on the highways that we want timed
They use a stopwatch and record the time when they pass each specified location
Corridor Selection
Corridor Selection Criteria Moderate-severe recurrent congestion Variable loop detector spacing (some low some
high) to allow evaluation of spacing effects Some situations with high data quality Construction Schedule – avoid times/areas when
there is construction Propose:
OR 217 (‘good’ conditions) I-205 or I-5 (more variable detector spacing)
Credit to Sue Ahn for her ideas for corridor selection in SWARM
217 N, Weekdays - April, 2006
traffic flow
217 S, Weekdays - April, 2006
traffic flow
217 Notes
Congestion: moderate congestion both NB and SB Congestion NB and SB in both AM and PM Peaks PM congestion generally worse than AM SB congestion generally worse than NB
Detector Spacing: good NB: 9 stations SB: 11 stations Length: ~7 miles
Data Quality 217 N - ~1% disqualified data 217 S - ~2% disqualfied data
Timing & Cost Specifics – 217 PM Peak 217 S
Peak: 3:00-6:00 Min/Max/Avg TT: 14.3/25.0/20.5 min 217 N:
Peak: 4PM – 6PM Min/Max/Avg TT:10.2/14.2/12 min Average Round trip ~32 minutes Need ~50 runs for 5% error at 95% confidence
Start with 20 runs/corridor 2 runs/hr, 10 hrs = 20 runs = $450 ($45/hr) Gas cost: 20 runs * 7 miles * 0.5/mile = $70
Data from weekdays – April, 2006
Timing – 217 AM Peak AM Peak
217 N Peak: 7:30-8:15 Min/Max/Avg TT: 8.2/10.6/9.3 min
217 S: Peak: 7:00-9:00 Min/Max/Avg TT:12.5/20.7/16.1 min
Avg round trip time ~25 min Data from weekdays – April, 2006 Similar costs $500 for 20 runs
Detector Locations - 217
I-205 N, Weekdays – October, 2006
traffic flow
Detector spacing poor before mp 8
I-205 S, Weekdays – October, 2006
traffic flow
Detector spacing poor after mp 8
Detector Locations I-205
SB Stark/Washington mp 20.34
SBClackamas Hwy mp 12.67
SBJohnson Creek mp 16.24
I-205 Notes Detector spacing is poor for mileposts 0-8
Do not collect data on that portion of 205 – means can not capture the congestion that occurs there
Consider collecting mp 13 – mp 20 Congestion:
Some congestion on northern end of I-205 NB and SB, AM and PM peaks
NB AM congestion appears worst Detector Spacing:
See Map Data Quality
I-205 NB - ~1% disqualified data I-205 SB - ~2% disqualified data
I-5 N Weekdays – October, 2006
traffic flow
I-5 S, Weekdays – October, 2006
traffic flow
Detector Locations I-5 S of Downtown
NB, Nyberg, mp 289.4
NB, Macadam, mp 299.7
Detector Locations I-5 N of Downtown
NB, Macadam, mp 299.7
SB, Swift/Marine, mp 307.35
I-5 Notes Congestion:
N of Portland: SB congestion in AM and PM peaks, NB congestion PM peak
S of Portland: Minimal SB congestion, NB congestion through curves in AM peak
NB PM congestion (going over the bridge) appears worst More severe congestion than 205
Detector Spacing: Variable - See Map
Data Quality I-5 NB - ~2% disqualified data I-5 SB - ~4% disqualified data
Milwaukee, WI
Detector Spacing 0.25 miles in urban areas 2 miles in rural areas
Data from detectors transmitted to TOC Center Freeway Traffic Management System (FTMS) Server
Travel Time = Known Distance/Average Speed Website updated every 3 minutes DMS signs updated every 1 minute No probe vehicle data; all detector derived travel times
Other States – Best Practices…
San Antonio, TX
Travel Times calculated from/to major interchanges Detectors
Loop Detectors Video Detectors
Point travel speeds used to calculate travel times from detector to detector Segment travel speed is the lower of u/s and d/s speed Point to point travel times are summation of segment travel times
Travel times posted on TransGuide website use the same algorithm
Chicago, IL DMS Travel Times
From three sources (IPASS, RTMS, Loops) GCM Webpage
Only IPASS travel times IPASS Data
Travel times from toll plaza to toll plaza Based on toll transponder data collected by ETC system > 1.5 million users on tollways Significant number of probe vehicles provide time stamp and
location Travel times calculated using location and time stamp
information High quality of data
RTMS Data IDOT Loop detector data
Houston, TX
Vehicle Probes with transponder tags Readers collect data as vehicles pass
2-3 miles apart Time Location of probe
Software Average Speeds Average Travel Times Transtar website DMS
Updated every 10 minutes
Nashville, TN RTMS detectors
0.25 mile spacing Speeds Ensure data quality by regular calibration CCTV cameras
Travel Time verification
Data Collection & Processing Average speed from RTMS every 2 minutes Travel time calculation
average speed and distances between sensors Travel Times automatically posted to the DMS by TMC software Travel Times are only reported for segments < 5 miles
Atlanta, GA
VDS Cameras Monitoring and Video Detection Cameras Fixed black and white cameras Placed along all major freeways Provide volumes and speeds
Travel Times between 6 a.m. – 9 p.m. Average speeds from Video Detection Cameras
Software Automatic message generation for DMS
San Francisco, CA
Existing Caltrans System Dual Loop Detectors
Speeds
New MTC System Antennas to read FasTrak Toll Tags Average Travel Times and speeds of all vehicles
511 System Combination of data from both sources to calculate travel times
Other Cities
www.smartroute.com Real Time Traveler Information
Boston Miami St. Louis North Carolina New Jersey
Summary
Two main approaches for generating travel times In house
Loop Detectors High Density (0.25 mile spacing)
Video Detectors RTMS Toll Tags
Private providers Smartroute Systems Inrix
Schedule Update…
217 N/S Peak Pictures
217 N, AM Peak Weekdays - April, 2006
traffic flow
217 N, PM Peak Weekdays - April, 2006
traffic flow
217 S, Weekdays, AM Peak - April, 2006
traffic flow
217 S, Weekdays, PM Peak - April, 2006
traffic flow
I-84 (East and Westbound) Limited number of loop detectors and poor data quality
I-405 (North) Relatively short (≈ 3.5 miles) and limited loop detectors
I-405 (South) This freeway corridor is relatively short (≈ 3.5 miles), lightly congested during peaks
US-26 (East and Westbound) Was under construction – what is data quality like on 26?
OR217 Northbound Sue had problems with the queue location – when are we getting detectors again?
OR217 Southbound Looks pretty good – when are detectors going to be turned on?
I-205 Northbound Looks pretty good. When are new loop detectors going in?
I-205 Southbound This corridor is lightly congested during the peak periods. The speed remains above 40 mph throughout the entire corridor.
I-5 Upper-section Northbound Poor data quality
I-5 Upper-section Southbound Poor data quality??
I-5 Lower-section Southbound A recurrent bottleneck is located near the Wheeler Ave. on-ramp. The resulting queue, however, usually propagates only 2 – 3 miles
upstream. A queue that forms near Wheeler Ave. often overrides the upstream bottleneck near Columbia Blvd (in the upper-section of I-5). In
this case, the entire queue propagates upstream of the Interstate bridge, where loop detector data are not available to PSU. I-5 Lower-section Northbound
There are several of sections along this corridor where the spacing of adjacent loop detectors is very large. 2.5 miles between Terwilliger Blvd. and Macadam Ave., 3 miles between Nyberg Rd. and Stafford Rd.
Data Quality Flags
Data is flagged as invalid if it meets any of the following criteria (adapted from TTI criteria) 20 second count > 17 Occupancy > 95% Speed > 100 MPH Speed < 5 MPH (probably being removed) Speed = 0 and Volume > 0 Speed > 0 and Volume = 0 Occupancy > 0 and Volume = 0
Data quality is determined (in part) by percentage of 20-second readings for which a detector fails one of the above tests
I-5 Lower Northbound 217 Southbound I-205 Northbound I-205 Southbound
Implemented February, 2006 November, 2005 December, 2005 December, 2005
Length of study section 17 miles 7 miles 19 miles 19 miles
Number of loops 51 24 46 46
Number of on-ramps (with loops) 16 12 9 18
Level of congestion: pre SWARM (duration, queue length, low speed)
(2-3 hrs, 6 miles, 25-35mph) (2-4 hrs, 4-6 miles, ~25mph) (2-3 hrs, 5 miles, ~30mph) (2 hrs, 4-6 miles, ~35mph)
Level of congestion: post SWARM (duration, queue length, low speed)
(2-3 hrs, 6 miles, 25-35mph) (2-4 hrs, 4 miles, ~25mph) (2-3 hrs, 5 miles, ~30mph) (2 hrs, 3-5 miles, ~40mph)
Queue contained within corridor? (pre SWARM, post SWARM)
AM: (Yes, Yes) PM: (Yes, Yes)
AM: (Yes, Yes) PM: (Not clear, Not clear)
AM: (Not clear, Not clear) PM: (Not clear, Not clear)
AM: (Yes, Yes) PM: (Yes, Yes)
Coverage of loop detectors (miles/loop station)
1.14 (max: 3.1) 0.74 (max: 1.2) 1.1 (max: 1.9) 1.46 (max:4.3)
Data quality (Avg % good readings, Min %)
(94.2, 21.8) (99.2, 98.9) (98.0, 94.8) (98.3, 85)
No. of Loops < 90% 3-7 0 0 1-2
Construction schedule Late summer of 2006
Uncongested Conditions
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OTHER STATES
Milwaukee, WI
Introduction
DMS Usage Travel Times Incidents Amber Alerts Special Events Construction and Weather Information Congestion Information
36 DMS signs present on Arterials and Freeways
Source: Kelly Langer: Keeping Wisconsin Moving – An Overview of WisDOT’s DMS Travel TimesNTOC Presentation, September 28th, 2005
Technology & Data Processing Detector Spacing
0.25 miles in urban areas 2 miles in rural areas
Data from detectors transmitted to Traffic Operations Center
Freeway Traffic Management System (FTMS) Server Travel Time = Known Distance/Average Speed
Website updated every 3 minutes DMS signs updated every 1 minute No probe vehicle data; all detector derived travel times
Travel Times - Report
San Antonio, TX
Introduction
Travel Times calculated from/to major interchanges Detectors
Loop Detectors Video Detectors
Point travel speeds used to calculate times from detector to detector based on distance between detectors
Travel times displayed on mainlane DMS from 6:00 a.m. to 10:00 p.m., seven days of the week
Travel times posted on TransGuide website use the same algorithm
Data Calculation
Segment Segment Speed Travel Time
(MPH) (Minutes)1 55 0.552 47 0.643 47 0.644 45 0.675 30 1.006 30 1.007 30 1.008 25 1.209 20 1.5010 15 2.0011 15 2.00
TOTAL 12.19
Travel Time Calculation-
- Segment travel speed is chosen as lower of upstream and downstream sensor speed
- Point to point travel speed is summation of segment travel times
Source: San Antonio TransGuide Travel Time Algorithm
DMS Display & Accuracy
Time of Day Non Peak
Travel time messages appear alone Peak Periods
Travel times in combination with congestion warnings Incidents
Travel times messages automatically overridden
Accuracy Tests indicate 85% accuracy within predicted travel time range Predictive algorithm tests showed low benefit for additional cost
Chicago, IL
Introduction
~33 DMS on tollways and DOT roads DMS messages
Incident alerts Amber alerts Travel time messages
Travel Times provided on tollways by ISTHA I-294 Tri-State Tollway (Indiana to Wisconsin) I-90 Northwest Tollway (Chicago to Wisconsin) I-88 East-West Tollway (Tri-State Tollway to Rock Falls, Illinois) I-355 North-South Tollway, extending north seventeen miles from
I-55 Stevenson Expressway
Technology
IPASS Data Travel times from toll plaza to toll plaza Based on toll transponder data collected by ETC system > 1.5 million users on tollways Significant number of probe vehicles provide time stamp and
location Travel times calculated using location and time stamp
information High quality of data
RTMS Data IDOT Loop detector data
Travel Time Estimation
Toll network Roadway segments Bounded by ramps and plazas
IPASS & RTMS data Provide redundancy on certain segments Travel time software allows choice of data
DMS Travel Times From all three sources (I-PASS, RTMS, Loops)
GCM Webpage Only I-PASS travel times
Real Time Speed Map
Travel Times - Report
Houston, TX
Introduction
DMS Signs Message Hierarchy Incidents Construction/Pre Construction Amber Alerts Travel Times Special Events Safety Campaigns
81 DMS locations
Source: www.ops.fhwa.gov/publications/travel_time_study/houston/houston_ttm.htm
Technology
AVI Toll Transponders Approximately 2 million transponders Data collected at 232 reader stations and transmitted to Transtar
TMC Reader stations 2-3 miles apart
Automated Travel Time Processor Posts travel times to 81 DMS signs every 10 minutes (5:30 a.m.
– 7:30 p.m.) Some signs updated more frequently than others
Data Collection and Processing Vehicle Probes with transponder tags
Readers collect data as vehicles pass Time Location of probe
Software Average Speeds Average Travel Times Transtar website DMS
Source: www.ops.fhwa.gov/publications/travel_time_study/houston/houston_ttm.htm
Real Time Speed Map
Real Time-Travel Times
Nashville, TN
Introduction
20 DMS Signs 2 signs display travel time Travel times displayed through the day unless incidents occur
Source:http://www.ops.fhwa.dot.gov/publications/travel_time_study/nashville/nashville_ttm.htm
Technology, Data Collection & Processing Technology
RTMS detectors at 0.25 mile spacing Speeds Ensure data quality by regular calibration
CCTV cameras Travel Time verification
Data Collection & Processing Average speed from RTMS every 2 minutes Travel time calculation
average speed and distances between sensors Travel Times automatically posted to the DMS by TMC software
Travel Time Facts
Travel Times provided in 2-3 minute ranges Allows for +/- 1-1.5 minutes variation in travel times
Incident messages override travel times\ Travel Times are reported only for segments < 5 miles
Real Time Travel Times
Atlanta, GA
Introduction
Changeable Message Signs (CMS) All major freeways HOV CMS
Information for express lane commuters Automatic message generation Travel Times between 6 a.m. – 9 p.m.
Average speeds from Video Detection Cameras Incident Messages
Incident location Number of lanes affected
Technology
VDS Cameras Monitoring and Video Detection Cameras Fixed black and white cameras Placed along all major freeways Provide volumes and speeds
Source: http://www.georgia-navigator.com/about.shtml
Real Time Speed & Travel Times
Travel Times - Web
San Francisco - Bay Area, CA
Introduction
Real Time Information (traffic.511.org) Traffic Conditions Travel Times Incident Reports
Technology
Existing Caltrans System Dual Loop Detectors
Speeds
New MTC System Antennas to read FasTrak Toll Tags Average Travel Times and speeds of all vehicles
511 System Combination of data from both sources to calculate travel times
Travel Times Coverage
-80: SF (US-101) to Suisun City (Hwy 12) including the Carquinez & Bay Bridges
I-880: Oakland (I-80) to San Jose (I-280) I-680: San Jose (US-101) to I-80 including the Benicia
Bridge I-580: San Rafael (US-101) to the Alameda County line
(I-205) including the Richmond Bridge I-280: SF (6th St.) to San Jose (I-680) I-780: Vallejo (I-80) to Benicia (I-680) I-980: I-880 to I-580 I-238: I-880 to I-580 US-101: SF (GG toll plaza) to Santa Rosa (Hwy 12)
including the Golden Gate Br. US-101: SF (I-80) to San Benito County line Hwy 92: Hayward (I-880) to Half Moon Bay (Hwy 1)
including the San Mateo Bridge Hwy 85: Mountain View (US-101) to San Jose (US-101) Hwy 84: East Palo Alto (US-101) to Newark (I-880) Hwy 24: Oakland (I-580) to Walnut Creek (I-680) Hwy 4: Hercules (I-80) to Antioch (Hwy 160) Hwy 17: San Jose (I-280) to Santa Cruz County line Hwy 13: I-580 to Hwy 24 Hwy 37: Novato (US-101) to Vallejo (I-80) Hwy 87: US-101 to Hwy 85 Hwy 242: I-680 to Hwy 4 Hwy 1: Half Moon Bay (Hwy 92) to Montara (coming
soon)
Travel Times -Web