November 15, 2005 Dr. Robert Bertini Dr. Sue Ahn Using Archived Data to Measure Operational Benefits of a System-wide Adaptive Ramp Metering (SWARM) System

Presentation Outline 1. Research Objectives 2. Introduction 3. Overview of SWARM 4. Previous Studies 5. Measures of Potential Benefits (based on previous studies) 6. Data Sources (ITS infrastructure and Portal) 7. Study Scope (Work Plan)

1. Research Objectives Demonstrate the use and display of archived data from multiple sources as a tool for evaluation and monitoring of freeway operations. Evaluate the effectiveness of the new SWARM program in Portland, Oregon Develop tools to facilitate efficient deployment of ramp metering programs in Portland and other places

2. Introduction Goals of Ramp Metering  Efficient management of traffic congestion Maximize the capacity of the freeway by limiting the amount of traffic entering a freeway Break up the platoons of vehicles discharged from a traffic signal upstream.

2. Introduction (con’t) Advantages of Ramp Metering Improved mainline traffic flow and efficient merging Improved safety Improved air quality Balance and efficiency in network routings Disadvantages of Ramp Metering Delays for on-ramp traffic Potential negative effect on alternate routes due to rerouting

2. Introduction (con’t) Types of Ramp Metering Control Pre-timed - based on historical information Traffic-responsive - based on real-time information - Local: based on local conditions around ramps (e.g. Demand-capacity, ALINEA, etc.) - Coordinated: based on conditions around a series of on-ramps (e.g. Bottleneck, SWARM, MEATLINE, Fuzzy Logic, etc.)

3. Overview of SWARM How does it work? SWARM 1: Global control Forecasts density at a bottleneck and determines the required volume reduction from upstream ramps Determines the individual metering rates based on the overall volume reduction required SWARM 2: Local control Determines the metering rate independently for each on- ramp based on the local condition (density)  Actual rates: more restrictive of the two rates

3. Overview of SWARM (con’t) Capabilities Potential to detect congestion in advance with high accuracy Robustness: Built-in failure management (data clean- up) Potential Problems Potential ill-performance when forecasts are not accurate  Good prediction models are key

3. Overview of SWARM (con’t) Implementation Schedule Already implemented on I-84 and OR 217 SB OR 217 NB: November 16, 2005 I-205 SB: December, 2005 I-205 NB: January 2006 US 26 EB: February 1, 2006 US 26 WB: February 15, 2006 I-5 (lower section): March 1, 2006 I-5 (upper section): March 20, 2006 I-405: April, 2006

4. Previous Studies Evaluation via field testing Portland, OR (Bertini et al., 2004) Study location: I-5N from Broadway Bridge to Interstate Bridge Data: loop detector data, probe vehicles with AVL Analysis: – Bottleneck characteristics: location, capacity, etc. – Manual traffic simulation: system-wide delay savings

4. Previous Studies (con’t) Evaluation via field testing (con’t) Portland, OR (Bertini et al., 2004) Weekend ramp meter shutdown (US Hwy 26) –Meters were off on one weekend and turned back on the following weekend –Ramp metering led to more travel at better quality of service

4. Previous Studies (con’t) Evaluation via field testing (con’t) Minneapolis, Minnesota Evaluation (2000) The meters were shut down Minneapolis, Minnesota for eight weeks and a before and after analysis was performed. During the peak periods, freeway mainline throughput declined by an average of 14% with the ramp meters off Travel time increased by more than 25,000 (annualized) hours. Crash frequency increased by 26% while the meters were off.

4. Previous Studies (con’t) Evaluation via simulation Orange County, CA (Zhang et al., 2001) Paramics to compare four algorithms: ALINEA, Bottleneck, Zone, and SWARM Results: –All algorithm improved mainline traffic flow –Little difference in performance –Performance of SWARM was sensitive to the accuracy of the predictions

4. Previous Studies (con’t) Performance measureChange Freeway mainline speedIncreases Accident rate/frequencyDecreases Overall travel time/delay timeDecreases Freeway mainline volume/flow/stability of flow Increases and Stabilizes Fuel SavingsIncreases Benefit/Cost Ratio4:1 to 62:1 Ramp delaysIncreases Arterial vehicle volumeIncreases, but insignificant Summary of benefits measured

5. Measures of Potential Benefits Potential BenefitsMeasures/parameters Savings in delayMainline: Delay, Travel Time Speed, Flow, VHT, VMT On-ramps: Queue length, Waiting time Improved safetyNumber of Incidents Improved air quality Engine emissions Fuel consumption

6. Data Sources 98 CCTV cameras 19 variable message signs 135 ramp meters 485 inductive loop detectors Digital archives of incident logs AVL Archives of COMET movements Extensive fiber optics network Weather data station Transportation System Management In the Portland metro area ODOT currently operates an extensive advanced traffic management system from the TMOC including:

6. Data Sources (con’t) Inductive Loop DetectorsClosed-Circuit Television Cameras  Data Archived in Portal

6. Data Sources (con’t) Potential BenefitsMeasures / ParametersData Sources Savings in delay Mainline: Delay, Travel Time, Speed, Flow, VHT, VMT On-ramps: Queue length, Waiting time Mainline: Loop Detectors (Portal) Probe vehicles (travel time) On-ramps: CCTV (queue length) Probe vehicles (waiting time) Improved safetyNumber of Incidents Incident Logs State wide crash database Improved air quality Engine emissions Fuel consumption

6. Data Sources (PORTAL) Portland Transportation Archive Listing (PORTAL) PSU Designated as Regional Archive Center

6. Data Sources (PORTAL) PORTAL: Speed Contour Plot

6. Data Sources (PORTAL) PORTAL: Vehicle Miles Traveled

6. Data Sources (PORTAL) PORTAL: Weather

7. Study Scope TaskTask DescriptionTimeline / Duration 1. Literature Review -Past field testing results -Past evaluation methods 2. Field Reconnaissance and Data Collection -Compile relevant data -Field reviews of ramp metering corridors 3. Select Study Corridors -Pilot study corridor -Regional study corridors for complete analysis 4. Experimental Design - Data collection plan for pilot study

7. Study Scope (con’t) TaskTask DescriptionTimeline / Duration 5. Pilot Study-Analysis of “before” and “after” data -Design modification for regional study 6. Regional Corridor Study - Perform larger corridor analyses 7. Evaluation and Recommendations -Evaluation of benefits of new ramp metering -Recommendations for improved strategy 8. Final Report