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Robert L. Bertini Department of Civil & Environmental Engineering Portland State University

Capacity and the Breakdown Phenomenon at a Freeway Merge Bottleneck: Unlocking the Potential of Loop Sensor Data. Robert L. Bertini Department of Civil & Environmental Engineering Portland State University February 22, 2002. Outline . Introduction Previous Studies Method Data Results

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Robert L. Bertini Department of Civil & Environmental Engineering Portland State University

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  1. Capacity and the Breakdown Phenomenon at a Freeway Merge Bottleneck: Unlocking the Potential of Loop Sensor Data Robert L. Bertini Department of Civil & Environmental Engineering Portland State University February 22, 2002

  2. Outline • Introduction • Previous Studies • Method • Data • Results • Summary • Implications • Ongoing and Future Research

  3. Introduction • Research Question • Empirically examine evolution of traffic from free flow to queued conditions at a freeway bottleneck downstream of a merge. • Exciting Opportunity • Bottlenecks are critical nodes in system. • First sixty years: • Promising theories (e.g., Lighthill-Whitham-Richards, Edie, Newell) needed validation. • Difficult to collect data. • Fundamental uncertainties. • Today: • Sensor-rich, “too much” data • Understand traffic behavior • Building blocks for proposing/validating models

  4. Research Implications • Understand traffic behavior at a merge. • Demonstrate benefits of traffic management sensor investment for research. • Reveal benefits of archived raw data. • Method for unequivocally pinpointing active bottleneck. • Resolve two-capacity issue. • Potential for future research: • Improve macroscopic models. • Assess ramp metering. • Enhance freeway management. • Update design standards.

  5. Active Bottleneck • Discharging from upstream queue (maximum). • Not impeded by downstream effects.

  6. Previous Studies • Data from fixed points • Bivariate plots • Scatter plots • Time dependencies & statistical fluctuations • Short time intervals • Long time intervals

  7. Method N(x,t) N(x,t) Flow t x Time, @

  8. Method

  9. Method

  10. Cumulative Curves

  11. Skewed Cumulative Curves

  12. Site – Gardiner Expressway

  13. Occupancy Data

  14. Loop Sensor Data Validation

  15. Loop Sensor Data Validation

  16. Pinpointing the Bottleneck

  17. Queue Presence

  18. Bottleneck Deactiviation

  19. Estimating Bottleneck Capacity

  20. Reproducibility

  21. Active Bottleneck Under Different Conditions

  22. Reproducible

  23. Precursors to Breakdown

  24. Summary • Benefits from applying method to archived sensor data. • Bottleneck location fixed: 1 km downstream of ramp. • Resolved two-capacity issue: high flow prior to queue formation. • Tell-tale breakdown signal. • Measured capacity: average discharge flow.

  25. Conclusions • Importance of bottlenecks. • Robust method. • Greater understanding of merge bottlenecks. • Contributions: • Empirical approach. • Metering, managing and modeling. • ATIS, ATMS, and ADUS

  26. Ongoing Research • Toronto merge trajectories • Lane drop bottleneck • London • Minneapolis • Other bottlenecks

  27. Ongoing Research

  28. Example Projects Using Archived ITS Data for Transportation Performance Measures Oregon Department of Transportation • Portland Advanced Traffic Management System (TransPort) • 90 ramp meters • 400 inductive loop detectors • 49 CCTV cameras • 13 variable message signs • Using archived data to demonstrate value of archiving, and expanding possibilities for generating information useful for planners, engineers, policymakers and ultimately the users via ATIS • Monica Leal, MS Student

  29. Example Projects Using Archived Data to Measure Operational Benefits of Intelligent Transportation System Investments U.S. Department of Transportation (TransNow) and ODOT • Use existing data, surveillance and communications infrastructure • Two case study evaluations for Oregon • COMET incident management program • Portland ramp metering system. • Set precedent for future evaluations of ITS programs.

  30. Example Projects Alternatives to Motor Fuel Tax Oregon Department of Transportation • Collaboration with Professor T. Rufolo, Urban and Regional Planning • Fuel tax revenue declining with fuel efficient/alternative fuel vehicles • Other road finance measures under consideration • Consider fee based on vehicle miles traveled • Three goals of this phase: • Validate alternative financing mechanisms • Evaluate technologies for assessing alternative fees • Consider transition issues to new system • Minimize equity concerns

  31. Example Projects Evaluation of Rural/Urban Incident Response Programs Oregon Department of Transportation Region 2 • Highway 18 and I-5 • Using archived data to measure effectiveness of existing program and assist ODOT in decision-making for future expansion of program to additional highway routes.

  32. Example Projects • Prototype for Advanced Public Transit Systems in Multimodal Corridor • Great Cities Universities Coalition: Federal Transit Administration • Multi-disciplinary/multi-university team: • PSU Civil Engineering • PSU Urban Studies • City College of New York/City University of New York • Northwestern University • University of Alabama, Birmingham • Interstate 5/Barbur Blvd. Corridor • Testing strategies for improving transit operations • and passenger information systems

  33. Example Projects Using Transit Vehicles as Traffic Probes Tri-Met

  34. Example Proposal Creating Safe and Sustainable Neighborhoods for Pedestrians and Bicyclists A Great City: Great University Partnership • PSU Civil Engineering • PSU Urban Studies and Planning • OHSU Department of Emergency Medicine • PSU School of Community Health • City of Portland • Multnomah County EMS • Oregon Department of Health Services • Oregon State Police • Tri-Met • Tualatin Valley Fire and Rescue • Willamette Pedestrian Coalition

  35. New Potential Project • Integrated E911/Emergency Response/Transportation Network • Oregon Testbed: First demonstration in the nation • Partnerships: Intel, Senator Wyden, Comcare Alliance, EMS, 911, Transportation Agencies, PSU

  36. Vision for Real-Time Traffic Management Center

  37. Conclusion Thank You!

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