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ACS Lite in the City of Anaheim

ACS Lite in the City of Anaheim. John Thai Principal Traffic Engineer at City of Anahei m. About the City of Anaheim. Population – 340,000 residents (10 th largest in CA and 54 th in US)

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ACS Lite in the City of Anaheim

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  1. ACS Lite in the City of Anaheim John Thai Principal Traffic Engineer at City of Anaheim

  2. About the City of Anaheim • Population – 340,000 residents (10th largest in CA and 54th in US) • Home to Disneyland Resort, MLB Angels Baseball, NHL Anaheim Ducks, US Men’s and Women’s National Volleyball Teams • Anaheim Convention Center – largest convention center on West Coast • Over 20 million annual visitors

  3. Anaheim Resort and Stadium Events

  4. Anaheim Adaptive Control Project Area • CHALLENGES FOR TOY STORY LOT • Additional 2678 new spaces to • existing 1000 spaces • Shuttle buses to Disneyland • Accommodate varying tourist conditions • Accommodate varying park hours • Total parking to be 29,000 spaces

  5. Needs and Objectives • Straightforward algorithm + user friendly interface • Straightforward integration • Cost effective • Maintains system integrity • Maintenance staff buy-in

  6. Needs and Objectives • Adaptive solution objectives • Do no-harm if poor detection • Must NOT change cycle length (functions with adjacent fine-tuned arterial systems) • Fine-tune splits to accommodate varying demands • Fine-tune offsets to accommodate varying platoon arrivals • Adaptive solution with user friendly interface • Must be straightforward for full time and part time event operators • Lots of MOEs for monitoring efficiency and effectiveness • Cost effectiveness and system integrity • Per intersection + central license concerns • Uses what we already have in the field as much as possible • Straightforward system integration at field and at TMC • On-going maintenance costs must be predictable • Will maintenance staff embrace it? • System reliability is critical • On-going training + active support desirable

  7. Aligning Needs with System Selection Phase Utilization Flow Profile

  8. Evaluating Adaptive How well does Adaptive perform against FREE mode and optimized timing plans? • Travel Times (measured) • Delays (measured) • Average Speeds (measured) • Stops (measured) • Emissions (CMEM model)

  9. Evaluation Methodology (56 F, 58 C, 55 A) (55 F, 56 C, 55 A) (56 F, 101 C, 74 A) (51 F, 100 C, 74 A) Total Timing Runs: NB – 225, SB – 231 EB – 166, WB – 169

  10. Measuring Travel Times

  11. Measuring Delays

  12. Measuring Speeds

  13. Estimating Fuel Consumption

  14. Preliminary Findings • The selected system tries to do the right thing • Not much gained from Adaptive Control if a system is perfectly tuned and is well maintained • Need a larger study area and sample (> 5 traffic signals)

  15. What’s Ahead? • Expand adaptive capability where applicable • Need evaluations for: • Non ideal cycle lengths • Non-through traffic MOEs • Non-coordinated phase MOEs • Correlating Adaptive system MOEs vs. measured MOEs • Presentation and preliminary results posted at http://sites.google.com/site/anaheimacs/home

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