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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
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Investigation of HOV Modeling Capability in Microscopic simulation Models Jun-Seok Oh Western Michigan University Lianyu Chu University of California, Irvine
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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
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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
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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
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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
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HOV Operations
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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 )
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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
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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
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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
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Study Network I-405, Irvine, California
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HOV: openHOV: closed HOV: open Northbound I-405 6 km freeway stretch
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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
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S1: Volume Comparison GP lane volume HOV lane traffic is underestimated Paramics HOV lane traffic: constant during simulation period
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S1: HOV traffic % of HOV lane traffic % of HOVs on HOVL
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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
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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
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S2: Volume Comparison % of HOV lane traffic Close to observed HOVL volume % of HOVs on HOVL 70 – 80% during congested period
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S2: HOVs on HOVL w.r.t GPL Speed Paramics AIMSUN
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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
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S3: Volume Comparison % of HOV lane traffic Underestimates HOVL volume % of HOVs on HOVL Low HOLV utilization
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S3: HOVs on HOVL w.r.t GPL Speed Paramics AIMSUN
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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
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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
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Overall Travel Time Comparison Limited analyses Compulsory and No HOV lane case outperformed Elasticity of HOV demand NOT considered
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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
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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
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Thank you!
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