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Ali Gholami Center for Advanced Transportation Education and Research (CATER)

Using Detector Information to Determine Turning Movement Proportions at Signalized Intersections with Shared Lanes. Ali Gholami Center for Advanced Transportation Education and Research (CATER) Department of Civil & Environmental Engineering University of Nevada, Reno. Outline.

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Ali Gholami Center for Advanced Transportation Education and Research (CATER)

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  1. Using Detector Information to Determine Turning Movement Proportions at Signalized Intersections with Shared Lanes Ali Gholami Center for Advanced Transportation Education and Research (CATER) Department of Civil & Environmental Engineering University of Nevada, Reno

  2. Outline • Volume application • Problem statement • Proposed methods • Case study intersections

  3. Turning Movement Volume Applications • Intersection operational analyses • Traffic safety studies • Travel demand modeling • Identifying critical flow time periods • …

  4. Loop Detector

  5. Loop Detector

  6. What is the current practice?

  7. Loop Detector Data , Aggregated

  8. Loop Detector Data, High Resolution Sample data collected from the data communication adaptor Data Communication Adaptor

  9. Collecting intersection Volume in Nevada

  10. Determine Turning Movement Proportions at Signalized Intersections with Shared Lanes

  11. Network Equilibrium (NE) Intersection j Intersection i

  12. Determine Turning Movement Proportions at Signalized Intersections with Shared Lanes

  13. Volume and Queue Length of Shared Lanes (VQ)

  14. Determine Turning Movement Proportions at Signalized Intersections with Shared Lanes

  15. Flow Characteristics of Shared Lanes (FC)

  16. Determine Turning Movement Proportions at Signalized Intersections with Shared Lanes

  17. Considerations

  18. Making the Models

  19. What does GP do?

  20. What does GP do?

  21. How GP Works? • GP is based on evolution process, (cross over, mutation, and elitism) • We can use ready applications

  22. GPTIPS

  23. R

  24. Accuracy MAPE: Mean Absolute Percentage Error Di: the detector data value Bi: the reference (base) data value n: the total number of intervals

  25. Case Study Intersections 8th Street and Center Street 9thSt. and Sierra St. N McCarran Blvd and Clear Acre Ln

  26. Sample of data collected for VQ method

  27. Sample of data collected for FC method

  28. Models

  29. Results

  30. Results

  31. Errors using inadequate data are much less than those using no data at all.

  32. Thank you Any comments or questions? If we have data, let’s look at data. If all we have are opinions, let’s go with mine! Jim Barksdale, former Netscape CEO

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