Generalized Multiphase Car-Following Model for Vehicles with Adaptive Cruise Control: Behavioral Dynamics and Experimental Validation for Electric Vehicles

Electric vehicles (EVs) are revolutionizing the transportation industry by offering sustainability benefits over internal combustion engine vehicles. Concurrently, most commercially available vehicles are equipped with advanced driver assistance systems (ADAS), such as adaptive cruise control (ACC). However, existing car-following models used in microsimulation are unable to adequately capture the unique driving dynamics of electric vehicles with ACC and their resulting impacts on overall traffic flow stability, throughput, and energy consumption. To address this gap, this study develops a generalized modeling approach for EV-ACC vehicles. The contributions include calibrating a novel electric vehicle model (EVM) and assessing the stability impacts of EV-ACC vehicles on the overall traffic flow. The results demonstrated the superiority of the EVM in representing the unique car-following behavior of EV-ACC vehicles compared with traditional car-following models. Furthermore, traffic simulations highlighted how EV-ACC vehicles can enhance traffic stability, throughput, and efficiency compared with internal combustion engine (ICE)-ACC vehicles.

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Publication Details

Journal
Journal of Transportation Engineering Part A Systems
Published
2026-04-01
DOI
https://doi.org/10.1061/jtepbs.teeng-9330
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
0.00
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article

Generalized Multiphase Car-Following Model for Vehicles with Adaptive Cruise Control: Behavioral Dynamics and Experimental Validation for Electric Vehicles

Raphael Stern, Mingfeng Shang, Arian Zare, Xingan “David” Kan
Journal of Transportation Engineering Part A Systems
Traffic control and management
article

Generalized Multiphase Car-Following Model for Vehicles with Adaptive Cruise Control: Behavioral Dynamics and Experimental Validation for Electric Vehicles

Raphael Stern, Mingfeng Shang, Arian Zare, Xingan “David” Kan
article en

Abstract

Electric vehicles (EVs) are revolutionizing the transportation industry by offering sustainability benefits over internal combustion engine vehicles. Concurrently, most commercially available vehicles are equipped with advanced driver assistance systems (ADAS), such as adaptive cruise control (ACC). However, existing car-following models used in microsimulation are unable to adequately capture the unique driving dynamics of electric vehicles with ACC and their resulting impacts on overall traffic flow stability, throughput, and energy consumption. To address this gap, this study develops a generalized modeling approach for EV-ACC vehicles. The contributions include calibrating a novel electric vehicle model (EVM) and assessing the stability impacts of EV-ACC vehicles on the overall traffic flow. The results demonstrated the superiority of the EVM in representing the unique car-following behavior of EV-ACC vehicles compared with traditional car-following models. Furthermore, traffic simulations highlighted how EV-ACC vehicles can enhance traffic stability, throughput, and efficiency compared with internal combustion engine (ICE)-ACC vehicles.

Journal of Transportation Engineering Part A SystemsVol. 152(6)
Texas State University (US), University of Arizona (US), University of Minnesota System (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 33%
Traffic control and management
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