Customizing the following behavior models to mimic the weak lane based mixed traffic conditions. Issue 1 (31st December 2022)

• Record Type: Journal Article
• Authors: Raju, Narayana; Arkatkar, Shriniwas; Easa, Said; Joshi, Gaurang
• Is Part Of: Transportmetrica. Volume 10:Issue 1(2022)
• Page Start: 20
• Page End: 47
• Publication Date: 2022-12-31
• Subjects: Traffic flow modeling -- car following -- Intelligent driver model -- Gipps -- heterogonous traffic conditions; Transportation -- Mathematical models -- Periodicals; 388.015118
• DOI: 10.1080/21680566.2021.1954562
• Languages: English
• ISSNs: 2168-0566

Abstract

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.