Modeling HOV lane choice behavior for microscopic simulation models and its application to evaluation of HOV lane operat

1. Modeling HOV lane choice behavior for microscopic simulation models and its application to evaluation of HOV lane operation strategies Jun-Seok Oh Western Michigan University Lianyu Chu University of California, Irvine

2. Investigation of HOV Modeling Capability in Microscopic simulation Models Jun-Seok Oh Western Michigan University Lianyu Chu University of California, Irvine

3. Content • Motivation and Objectives • Classification and Operation of HOV System • Analytical Model for HOV Lane Traffic Estimation • HOV Modeling in Microsimulation Models • Experiment and Performance Comparison • New Modeling Approach • Concluding Remarks

4. Motivation • FHWA encourages the installation of HOV lanes as an important part of an area-wide approach • There are still questions on • the effectiveness of HOV systems • their impacts on air quality • The benefits of HOV systems have not been well quantified • Microsimulation might be a good way, but still involves some limitations

5. Objectives • Compare HOV modeling capability and performance in • Paramics • AIMSUN • Identify limitations and investigate methods to enhance HOV behavior modeling in microsimulation • Develop an improved HOV simulation analysis tool using API capability

6. Classification of HOV System

7. HOV Operations

8. Analytical Model for HOV Lane Traffic Estimation • User Equilibrium between HOV/GP • HOV lane is faster than GP lanes • tHL≤ tGL • fHOV(VHOV - VHG) ≤ fGP(VSOV + VHG) • If fHOV(VHOV) ≤ fGP(VSOV), VHG = 0 • If fHOV(VHOV) > fGP(VSOV), VHG > 0 • VHG can be found by solving • fHOV(VHOV - VHG) = fGP(VSOV + VHG)

9. HOV Modeling in Microsimulation Models • Vehicle Types • SOV & HOV • Defining HOV Lane (Open HOV System) • Allow HOV only on HOV lane • Lane barrier (Closed HOV System) • Closed HOV available in AIMSUN • Closed HOV via plug-in in Paramics

10. HOV Behavior Modeling • Optional • By allowing HOV only on HOV lane • May underestimate HOV on HOV lane • Compulsory • By forcing all HOV to use HOV lane • 100% HOV on HOV lane  Unrealistic • Separate links for HOV lane • Route choice with dynamic feedback • Not applicable to Open HOV • Paramics provides HOV plug-in for more HOVs on HOV lanes

11. Experiment Scenarios • Scenario 1: Closed HOV • Using given capability • Scenario 2: Separate Links for Closed HOV • Treating closed HOV lanes as separated links • Scenario 3: Open HOV • No barrier between HOVL & GPL • Assumption: HOV demand - 15% of total traffic • MOEs • Traffic volume split between HOVL & GPL • HOV demand split b/w HOVL & GPL • HOV demand split w.r.t speed of GPL

12. Study Network I-405, Irvine, California

13. Study Network I-405, Irvine, California HOV: open HOV: closed HOV: open HOV: closed • Northbound I-405 6 km freeway stretch

14. Dotted-line: open area Solid-line: barrier Scenario 1: Closed HOV • Paramics: Plug-in provided by vendor • add additional layers of detail to the HOV modeling • influence lane changing behavior and lane discipline • model both open/closed HOV lanes • AIMSUN: Default function • Restrict lane-changing with solid-line

15. S1: Volume Comparison • GP lane volume • HOV lane traffic is underestimated • Paramics HOV lane traffic: constant during simulation period

16. S1: HOV traffic • % of HOV lane traffic • % of HOVs on HOVL

17. S1: HOVs on HOVL w.r.t GPL Speed • Paramics • Not sensitive to the traffic condition on GPL • AIMSUN • Slower speed on GPL leads to more HOVs on HOVL

18. Dotted-line: open area Separate link for HOV lane Scenario 2: Separate links for closed HOV lanes • Separate links for closed HOV lanes • Use route choice model in HOV lane choice • Dynamic link costs update • HOVs are treated as guided drivers • change route (lane) while driving

19. S2: Volume Comparison • % of HOV lane traffic • Close to observed HOVL volume • % of HOVs on HOVL • 70 – 80% during congested period

20. S2: HOVs on HOVL w.r.t GPL Speed • Paramics • AIMSUN

21. Scenario 3: Open HOV Lane • HOV can access anywhere • HOV lanes are restricted only for HOVs • Rely only on lane-changing & restriction model Dotted-line: all open area

22. S3: Volume Comparison • % of HOV lane traffic • Underestimates HOVL volume • % of HOVs on HOVL • Low HOLV utilization

23. S3: HOVs on HOVL w.r.t GPL Speed • Paramics • AIMSUN

24. Findings • Closed HOV Lanes • Underestimates HOVL traffic • Paramics 65%, AIMSUN 85% of observed • Paramics Plug-in need improvement • Better when incorporating route choice behavior with dynamic cost update • Performance varies by route choice model • Open HOV Lanes • Current HOV modeling NOT satisfactory • Paramics 60%, AIMSUN 78% of observed • Underestimates due to the lack of capability to measure lane-by-lane traffic condition

25. Other Scenarios • Compulsory HOV Lane • AIMSUN has an option for compulsory HOV • Almost 100% HOVs use HOVL • Not realistic for HOV lane analysis • Useful tool for exclusive bus-lane • Paramics • Can implement by defining HOV only lane and SOV only lane • But need to define area where both types can use for exiting and entering • No HOV Lane

26. Overall Travel Time Comparison • Limited analyses • Compulsory and No HOV lane case outperformed • Elasticity of HOV demand NOT considered

27. Using API (Applications Programming Interface) capability Consider HOV driver’s visual perception on traffic condition Visual perception-based instant HOV lane choice model New HOV Modeling Approach

28. Concluding Remark • Microsimulation needs to be enhanced for HOV analysis • Closed HOV can be analyzed by incorporating route choice model with separate HOV links • Open HOV analysis needs enhanced model • Need to develop improved HOV behavior model considering driver’s visual perception on traffic condition • Need to calibrate model using real-world data • HOV demand and elasticity survey • Microsimulation has potential for HOV evaluation, but only with enhanced behavior model

29. Thank you!