A review of car-following and lane-changing models under heterogeneous environments

Yujia Chen, Changyin Dong, Keyun Lyu, Xiaomeng Shi, Gengyue Han and Hao Wang

Physica A: Statistical Mechanics and its Applications, 2024, vol. 654, issue C

Abstract: The coexistence of Connected Automated Vehicles (CAVs) and Human-driven Vehicles (HVs) in traffic scenarios is expected to persist in the long term. Hence, proposing effective mixed traffic flow control strategies is crucial for alleviating traffic congestion, reducing energy consumption, and enhancing traffic flow efficiency. However, existing reviews on car-following and lane-changing control encounter several issues: First, current studies are relatively disconnected, lacking a comprehensive framework to summarize both car-following and lane-changing models in heterogeneous environments; Second, existing reviews predominantly focus on individual vehicle-level models, rarely exploring coupling control strategies considering multi-vehicle interactions; Third, the explored driving scenarios in current review articles are relatively single or are not clearly distinguished. To fill this research gap, this paper offers a novel perspective on car-following and lane-changing models across three perspectives: i) HVs CF and LC behaviour simulation models; ii) CAVs CF and LC maneuver control models; and iii) The basic coupling architecture of CAV CF and LC maneuver control considering multi-vehicle interaction and its applications in some typical driving scenarios, including platoon scheduling, intersections, ramps, and CAV dedicated lanes. The objective of this paper is to provide valuable insights for future research on vehicle maneuver control in heterogeneous environments.

Keywords: Connected automated vehicles; Heterogeneous traffic; Car-following; Lane-changing; Coupling control; Driving scenarios (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:654:y:2024:i:c:s0378437124006368

DOI: 10.1016/j.physa.2024.130127

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