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Assessment and Refinement of Real-Time Travel Time Algorithms for Use in Practice November 8 th, 2007
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Agenda Status Update TRB Paper Accepted for Presentation, possibly Publication OTREC FY02 Proposal Accepted (~6 more months of funding) Theoretical Basis for detecting and adjusting for congestion wave Example Runs Sensitivity Analysis Data Quality Next Steps
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Three Causes of Errors Large Detector Spacing Detector Failure Changing Traffic Conditions We consider applying traffic flow theory to reduce error due to changing conditions Idea: identify current congestion, predict how that congestion will change as time progresses
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Adjusting for Changing Conditions Two Scenarios Before the onset of congestion Vehicles that may not be affected by congestion Vehicles that may be affected by congestion After the onset of congestion simpler problem (but not necessarily simple) Will focus on this problem, before the onset of congestion requires prediction from historical data Congestion exists, estimate how that congestion will change as a vehicle travels through a freeway segment
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Intuition Traffic flow VMS End of segment (VMS predicts travel time to this location) Location of Congestion when Vehicle arrives at VMS Vehicle (60 mph) Congestion Wave (?? mph) Location where vehicle encounters congestion Adjust travel time estimation in this section of freeway
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After the onset of congestion location (space) time BN Congestion wave onset of congestion prediction time Vehicle Path
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Required Information Bottleneck activation time and location Prediction is required if there is no congestion at the time of travel-time prediction (ignore this case for now) Wave travel time Flow or speed before the activation Bottleneck capacity (and corresponding speed) Inhomogeneity: on-ramp, off-ramp, lane-reduction Vehicle travel time before and after joining the queue Inhomogeneity: on-ramp, off-ramp, lane-reduction
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After the onset of congestion x t wave onset of congestion 1 2 3 1b 2b 3b 1a 2a 3a q k 1b 2b 3b 1a 2a 3a 4b 4a 4b 4a What we have… 4 Loop station
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Initial Assumptions & Issues Assume free flow speed is 60mph Need to calculate speed of congestion wave May vary with traffic conditions, location, etc. Big question is whether wave speed is consistent day-to-day Initially assume wave propagates at a the same speed down a freeway (off- and on- ramps have minimal effect) Later will test if this is a good assumption or not
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How do we estimate wave speeds? Use historical data to measure the average wave speed (in each segment) and its variability from day to day. Technique: manual inspection, cross-correlation using cumulative curves (manual inspection for today) Practical and reasonable if day-to-day conditions (including ramp flows) are similar if average wave speed is not sensitive to change in traffic conditions Or if estimated travel time in the segment is not sensitive to different wave speeds
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Run 338 April 25, 2007 start: 16:57:58 ground truth tt: 42:59 estimated tt: 17:21 Error: -60% (underestimation) Segment: I-5 NB Downtown to River Run 338 – Underestimation – Changing Conditions
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Denver Ave, mp 306.51 Portland Blvd, mp 305.12 Jantzen Beach, mp 307.9Marine Dr, mp 307.46
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Run 338 – Congestion Wave Speed Wave speed: 6.3 mph
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Predicting When Congestion Wave Arrives Observed Congestion Start (7.2 mph wave) Predicted Start of Congestion (Jantzen) Predicted Start of Congestion (Denver) Estimated Vehicle Arrival at FF Jantzen (307.9) 16:33 Marine (307.46) 16:37 Denver (306.51) 16:4016:4517:05 Portland (305.12) 16:5416:5616:5317:03 Alberta (304.4) 16:5917:0217:0017:02:30 Going (303.88) 17:0017:0617:02 Run start time: 16:58, at that time, Portland is just getting congested
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Portland Blvd - Detail
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Travel Time Estimation Adjustment Observed Congestion Start (7.2 mph wave) Predicted Start of Congestion (Jantzen) Predicted Start of Congestion (Denver) Estimated Vehicle Arrival at FF Jantzen (307.9)16:33 Marine (307.46)16:37 Denver (306.51)16:4016:4517:05 Portland (305.12)16:5416:5616:5317:03 Alberta (304.4)16:5917:0217:0017:02:30 Going (303.88)17:0017:0617:02 Ground Truth Travel Time: 42:59 Midpoint Estimated Travel Time: 17:21 (-60% error) Adjusting Speeds at Portland and Alberta: 28:42 (-33% error) Adjusting Speeds at Portland, Alberta, Going: 34:15 (-21% error)
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Observations Technique appeared to work for this run Also looked at run 331 – error reduced -21% to - 13% However This run was hand-picked Many manual observations were involved Not general at all now One big question is how much speed of congestion wave varies day to day
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Initial Sensitivity Study Calculate Wave Speed 217 N – four days Average 5.6 mph Min 3.2 mph, Max 9.5 mph I-5 S North of Downtown – three days Average 5.5 Min 4, Max 7.3 Caveat: Visual Inspection used to calculate wave speed, all show sharp speed drop, speed may be different when speed drop is slower
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Next Steps Sensitivity study on wave speed Sensitive to traffic conditions? (day-to-day sensitivity) If speed is very sensitive day-to-day, will make the problem much more difficult Sensitive to station? If speed is sensitive to station location, this can probably be handled with limited extra effort Continue development of theory Identify how to select ‘adjusted’ speed systematically Test results on additional runs
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Data Quality Results from UW visit… 3 stations visited I-5 NB Kruse Way/217 I-5 NB Multnomah I-5 NB Bertha/Terwilliger Investigated loop detector calibration and controller configuration using ALEDA
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I-5 NB OR 217/Kruse Way (mp 292.18) Perceived Problem: Low nighttime speeds are a serious problem at this detector. Daytime speeds look reasonable. Lane 3 shows similar issues, lane 1 shows fewer issues with low nighttime speeds. Fixes Applied: ALEDA used to tune loop detector sensitivity Results: slight improvement in overnight speed – issues still not resolved Cabinet Observations: Lane 1 (lane 3 in field) has different type of controller; suspect controller is thie issue for lanes 2 and 3
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I-5 NB OR 217/Kruse Way (mp 292.18) Sept 18, 2007 Lane 1 Sept 18, 2007 Lane 2Sept 18, 2007 Lane 3 Sept 24, 2007 Lane 3 Sept 24, 2007 Lane 2Sept 24, 2007 Lane 1
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I-5 NB Multnomah Perceived Problems: Lanes 1 and 3 exhibited a high number of readings with occupancy > 95% Lanes 1 and 3 behaved very differently from lane 2. Low overnight speeds Cabinet Comments: cabinet was in poor shape, ALEDA could not be used due (no ground) Fixes Applied: Observed that a button that was pushed in (out?) on lane 2 was out (in?) on lanes 1 and 3. Pushed button in (out?) on lanes 1 and 3 Results: Significant improvement in speed and occupancy measurements for lanes 1 and 3
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I-5 NB Multnomah (mp 296.6) (speed) Sept 19, 2007 Lane 1 Sept 19, 2007 Lane 2Sept 19, 2007 Lane 3 Sept 21, 2007 Lane 3 Sept 21, 2007 Lane 2Sept 21, 2007 Lane 1
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I-5 NB Multnomah (mp 296.6) (occupancy) Sept 19, 2007 Lane 1 Sept 19, 2007 Lane 2Sept 19, 2007 Lane 3 Sept 21, 2007 Lane 3 Sept 21, 2007 Lane 2Sept 21, 2007 Lane 1
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I-5 NB Bertha/Terwilliger (mp 297.33) Perceived Problem: Unusually low occupancy Fixes Applied: Observed controllers were set to pulse mode, changed controller setting to medium presence mode Used ALEDA to calibrate loop detector sensitivity Results: significant improvement in occupancy measurements
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I-5 NB Bertha/Terwilliger Sept 19, 2007 - Occupancy All LanesSept 19, 2007 - Speed All Lanes Sept 20, 2007 - Occupancy All Lanes Sept 20, 2007 - Speed All Lanes
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Next Steps Sensitivity study on wave speed Sensitive to day and traffic conditions? Sensitive to station? Continue development of theory Test results on additional runs ODOT Research?
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Extras
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Denver Ave, mp 306.51 Portland Blvd, mp 305.12 Going St, mp 303.88 Alberta St, mp 304.4
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