Identifying suitable car-following models to simulate automated vehicles on highways

被引:6
|
作者
Kim, Bumsik [1 ]
Heaslip, Kevin P. [2 ]
机构
[1] Texas A&M Transportat Inst, 505 E Huntland Dr,Ste 455, Austin, TX 78751 USA
[2] Univ Tennessee, 309L UT Conf Ctr, 600 Henley St, Knoxville, TN 37996 USA
关键词
Automated vehicle; Calibration; Capacity; Car-following model; ACC; ADAPTIVE CRUISE CONTROL;
D O I
10.1016/j.ijtst.2023.02.003
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
This study addresses car-following models that are currently used for simulating AV and CAV. Diverse car-following models, Intelligent Driver Model (IDM), Improved IDM (IIDM), IIDM with Constant-Acceleration Heuristic (CAH), and MIcroscopic model for Simulation of Intelligent Cruise control (MIXIC) are examined with the state-of-the-art vehicle trajectory data, Highway Drone dataset (HighD), and genetic algorithm. There is no commercial level 5 AV or CAV as of 2022; therefore, the authors generate hypothetical AV trajectories based on the actual vehicle trajectories and the assumption of an ideal AV. Based on the analysis, the calibrated IIDM with CAH shows the most fit on AV behavior. & COPY; 2023 Tongji University and Tongji University Press. Publishing Services by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/ by/4.0/).
引用
收藏
页码:652 / 664
页数:13
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