Customizing the Following Behavior Models to Mimic the Weak lane based Mixed Traffic Conditions

Journal article (2021)

Authors

Narayana Raju Transport and Planning - CEG , Sardar Vallabhbhai National Institute of Technology
Shriniwas Arkatkar Sardar Vallabhbhai National Institute of Technology
Said Easa Toronto Metropolitan University
Gaurang Joshi Sardar Vallabhbhai National Institute of Technology
Research Group
Transport and Planning (CEG) (TU Delft)
Copyright: © 2021 Narayana Raju, Shriniwas Arkatkar, Said Easa, Gaurang Joshi
DOI
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https://doi.org/10.1080/21680566.2021.1954562
Car following Traffic flow modeling Intelligent driver model Gipps Heterogonous traffic conditions
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Published Date

2021

Language

English

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Faculty

Civil Engineering & Geosciences

Department

Transport and Planning

Research Group

Transport and Planning

Abstract

This study aims to model traffic flow under weak lane based heterogonous (mixed) traffic conditions. Unlike homogeneous traffic, when a follower (subject) vehicle in mixed traffic moves closer to its leader vehicle, it tends to adjust its longitudinal movement or change its lane and acts discretely. Due to this phenomenon, traffic flow modeling under such conditions is always challenging. A new driver behavioral logic is conceptualized for the vehicles' movement within a combination of surrounding vehicles. In which the following behavior was dissected with the lateral shift distance between vehicles. Two car-following models for homogeneous traffic conditions, the IDM and Gipps models were adapted with relevant lateral behavior parameters to different vehicle classes under mixed-traffic conditions. The new driving behavior logic was incorporated externally in place of default logic. The results showed that the performance of the adapted models was better accurate than the classical models.