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TRANSIMS Microsimulator Application for Improving Fuel Consumption at Urban Corridor

TRANSIMS Microsimulator Application for Improving Fuel Consumption at Urban Corridor. Jaesup Lee University of Virginia & Virginia DOT Byungkyu “Brian” Park & Jaeyoung Kwak University of Virginia.

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TRANSIMS Microsimulator Application for Improving Fuel Consumption at Urban Corridor

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  1. TRANSIMS Microsimulator Application for Improving Fuel Consumption at Urban Corridor Jaesup Lee University of Virginia & Virginia DOT Byungkyu “Brian” Park & Jaeyoung Kwak University of Virginia Presented at the 12th TRB National Transportation Planning Applications Conference, May 17-21, 2009, Houston, Texas

  2. Sponsor • Federal Highway Administration • Broad Agency Announcement • Project Manager: Brian Gardner, FHWA

  3. Motivations

  4. TRANSIMS • Extensively developed in 1990s and demonstrated in Dallas/Ft. Worth and Portland case studies • Integrated activity based modeling and microscopic traffic simulation (cellular automata) • Open source community

  5. Proposed Research • Application of TRANSIMS for Sustainable Transportation: mainly focused on Microsimulator • Microscopic simulator calibration/validation • Integration of the Microsimulator, a fuel consumption and emission model, and an optimizer • Demonstrate feasibility via a case study

  6. TRANSIMS Microsimulator • Explicitly models individual vehicles • Updates vehicle status (e.g., speed and acceleration) every 1-second

  7. Calibration/Validation Procedure See: http://faculty.virginia.edu/brianpark/SimCalVal/

  8. Case Study Network Charlottesville, VA

  9. Calibration Parameters

  10. Calibration Validation Procedure • Experimental Design Approach • Exhaustive search infeasible • Latin Hypercube Sampling method • Developed 200 sets and made 5 replications for each set

  11. Default vs. Calibrated Default Parameters Calibration using an Experimental Design

  12. Validation Calibrated parameters were validated with untried field data

  13. Achieving Sustainable Transportation: Saving Fuel Consumption…

  14. Why VT-Micro Model? • Current EPA Mobile uses average link speed…

  15. VT-Micro Model

  16. Fuel/Emission Estimation Procedure

  17. Traffic Signal Timing Optimization • SYNCHRO for minimizing delay and stops • Proposed approaches • Minimizing fuel consumption • Minimizing total vehicle-hours-traveled

  18. Genetic Algorithm Convergence

  19. Performance Evaluation SYNCHRO Optimized – Base Case Note: Results are based on 50 TRANSIMS Microsimulator replications.

  20. Performance Evaluation Proposed Approach – VHT Minimization Note: Results are based on 50 TRANSIMS Microsimulator replications.

  21. Performance Evaluation Proposed Approach – Fuel Consumption Minimization Note: Results are based on 50 TRANSIMS Microsimulator replications.

  22. Comparison of VHT

  23. Comparison of Fuel Consumption

  24. Concluding Remarks • Calibration/Validation is necessary for TRANSIMS Microsimulator to properly reflect field condition • Successfully integrated VT-Micro emission estimation module, an GA-based optimizer, and Microsimulator

  25. Concluding Remarks (cont’d) • The integrated approach improved fuel consumption and emission over state-of-the-practice tool (i.e., SYNCHRO) • More efficient computation is required for a large scale optimization

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