A Probabilistic Approach Determining When to Turn on/off Signal Coordination

1. A Probabilistic Approach Determining When to Turn on/off Signal Coordination Rasool Andalibian Center for Advanced Transportation Education and Research April 2014

2. Outline • Background and Problem Statement • Signal Coordination: Common Practice • Stop Probabilistic Model • Model Outputs • Summary and Conclusions

3. Problem Statement • Major signalized arterials are generally coordinated during peak periods. • They run free (actuated) during non-peak periods. • Traffic demand level is a key element to consider. • At what demand level signal coordination is warranted?

4. Signal Coordination Strategy • Signal Timing Manual: intersections in close proximity with large amount of traffic on coordinated street. • MUTCD: Traffic signal within 0.5 mile of each other • FHWA: Intersections close together (i.e., within ¾ mile): advantageous to coordinate them. At greater distances (over ¾ mile), consider the traffic volumes and potential for platoons

5. Research Objectives • Develop a probabilistic model that predicts the number of stops for non-coordinated signalized arterials. • Develop # stop thresholds using the model that can guide engineers to decide when signals should be coordinated.

6. Previous Work • TRB 2013: Performance Assessment on Non-coordinated Signalized Arterials and Guidelines for Signal Coordination

7. Stop Prediction Model • Signal are running free. • Min-recall placed on major arterial. • Probability of stop is independent. • Probability of stop: • Probability of hitting green is: • Traffic is under-saturated.

8. Probabilistic Model: Basic Equations i i = direction of travel a = intersection index

9. Probability of Making Stops • Probability of making x stops out of n intersections: • An approximation to the above equation is: )

10. Stop Probability: Stop Example #1 #2 #3

11. Stop Probability: Stop Example Probability of making 1 stop .

12. Stop Probability: Stop Example Probability of making 1 stop • )

13. Probability Distribution of Stops n=10 n=4 1.6 4 2.0 5 2.4 6

14. Traffic Volume vs. g/C RatioIntersection Inventory

15. Traffic Volume vs. g/C Ratio Volume Distribution Directionality Total Volume Distribution Total entry traffic volume varies from 100 to 5000 vph

16. Traffic Volume vs. g/C Ratio

17. Stop Thresholds s.t. It is interpreted as 50 percent of drivers will make more than 6 stops.

18. Results of Stop Thresholds

19. Model Outputs: Recommendation for Signal Coordination • Establishing various stop thresholds results in different level of traffic volumes. • Considering more than 0.5n and 0.6n stops with the probability of 0.5 and 0.6 the recommended traffic volume for signal coordination would be: 250 to 350 vphpl

20. ITE Survey • A survey conducted on the ITE Community Website: When Signals are Coordinated • Florida: 250 vphpl • San Diego: 300 vphpl • Portland: 300 vphpl • Sacramento: 350 vphpl

21. Summary and Findings • Lack of consistency in traffic demand in signal coordination practice. • This study looks at signal coordination from number of stops standpoint. • A probabilistic stop-base model is developed predicting the distribution of stops.

22. Summary and Findings Cont. • The number of stops is a function of number of intersections and average g/C ratio of all intersections. • An attempt is made to relate actuated g/C ratios and traffic volumes. • Establishing various stop-base thresholds leads to different traffic level for signal coordination. • The author’s threshold is : 50 to 60 percent of drivers making more than 05n and 0.6n stops.

23. Summary and Findings Cont. • The recommended traffic level to trigger signal coordination is 250 to 350 vphpl. • ITE survey shows that the results of this study is compatible with state-of-the-practice.

24. QUESTION? “Signals are coordinated according to speed limit thus, NEVER SPEED UP!” Rasool Andalibian THANK YOU