Modeling cooperative driving strategies of automated vehicles considering trucks’ behavior

Peng Zhang, Huibing Zhu and Yijiang Zhou

Physica A: Statistical Mechanics and its Applications, 2022, vol. 585, issue C

Abstract: Modeling impact of trucks on the cooperative driving strategies of automated vehicles would be a challenge. It needs to figure out the behaviors of CACC cars and CACC trucks during the formation and disengagement of CACC strings when the manually driven vehicles, i.e., cars and trucks, are mixed in the traffic flow. Also it requires depicting the behaviors of manually driven cars and trucks under the influence of CACC cooperative strategy that are intended to enhance the CACC strings. Furthermore it needs to investigate the effect of CACC trucks and manually driven trucks on the characteristics of traffic flow respectively. To deal with these problems, we propose a four-lane cellular automaton traffic modeling framework to simulate the interaction between automated vehicles and manually driven vehicles. Numerical results show that trucks do have negative effect on CACC strings’ incorporating, and reduce the traffic capacity. Besides the CACC strings always maintain small scale due to the complicated composition of vehicles. According to the different mixing rate of CACC trucks and manually driven trucks, the managed lane strategy for trucks is proposed aiming to improve the traffic capacity. It indicates that this strategy exhibits different effects depending on the penetrations of CACC trucks, manually driven trucks and CACC cars. However the restriction strategy for trucks is recommended when CACC trucks’ penetration is larger than manually driven trucks’ penetration.

Keywords: Cooperative adaptive cruise control (CACC); Adaptive Cruise Control (ACC); Cooperative driving strategy; Trucks’ behavior; Cellular automaton traffic model (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:585:y:2022:i:c:s0378437121006592

DOI: 10.1016/j.physa.2021.126386

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