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

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

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

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

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

Classification of HOV System Infrastructure  Mainline HOV lane  Freeway-to-freeway direct connectors  Direct local access ramps  Freeway ramp meter bypass lanes  Toll plaza bypass lanes Designed Access  Open system  Closed system (Limits access with barrier) Use Restriction  2 people minimum occupancy  3 people minimum occupancy  Buses  Vehicles paying toll (High Occupancy Toll) Operational Period  Full time operation  Part time operation

HOV Operations

Analytical Model for HOV Lane Traffic Estimation  User Equilibrium between HOV/GP HOV lane is faster than GP lanes t HL ≤ t GL f HOV (V HOV - V HG ) ≤ f GP (V SOV + V HG )  If f HOV (V HOV ) ≤ f GP (V SOV ), V HG = 0  If f HOV (V HOV ) > f GP (V SOV ), V HG > 0 V HG can be found by solving f HOV (V HOV - V HG ) = f GP (V SOV + V HG )

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

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

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

Study Network I-405, Irvine, California

HOV: openHOV: closed HOV: open  Northbound I km freeway stretch

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 Dotted-line: open area Solid-line: barrier

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

S1: HOV traffic  % of HOV lane traffic  % of HOVs on HOVL

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

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 Dotted-line: open area Separate link for HOV lane

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

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

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

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

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

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

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

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

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

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

Thank you!