Safety performance evaluation of freeway merging areas under autonomous vehicles environment using a co-simulation platform

维西姆 混蛋 计算机科学 交通模拟 流量(计算机网络) 驾驶模拟器 忠诚 模拟 MATLAB语言 软件 运输工程 微模拟 工程类 加速度 计算机安全 电信 程序设计语言 物理 经典力学 操作系统
作者
Peng Chen,Haoyuan Ni,Liang Wang,Guizhen Yu,Jian Sun
出处
期刊:Accident Analysis & Prevention [Elsevier BV]
卷期号:199: 107530-107530 被引量:7
标识
DOI:10.1016/j.aap.2024.107530
摘要

Merging areas serve as the potential bottlenecks for continuous traffic flow on freeways. Traffic incidents in freeway merging areas are closely related to decision-making errors of human drivers, for which the autonomous vehicles (AVs) technologies are expected to help enhance the safety performance. However, evaluating the safety impact of AVs is challenging in practice due to the lack of real-world driving and incident data. Despite the increasing number of simulation-based AV studies, most relied on single traffic/vehicle driving simulators, which exhibit limitations such as inaccurate description of AV behavior using pre-defined driving models, limited testing modules, and a lack of high-fidelity traffic scenarios. To this end, this study addresses these challenges by customizing different types of car-following models for AVs on freeway and developing a software-in-the-loop co-simulation platform for safety performance evaluation. Specifically, the environmental perception module is integrated in PreScan, the decision-making and control model for AVs is designed by Matlab, and the traffic flow environment is established by Vissim. Such a co-simulation platform is supposed to be able to reproduce the mixed traffic with AVs to a large extent. By taking a real freeway merging scenario as an example, comprehensive experiments were conducted by introducing a single AV and multiple AVs on the mainline of freeway, respectively. The single AV experiment investigated the performance of different car-following models microscopically in the case of merging conflict. The safety and comfort of AVs were examined in terms of TTC and jerk, respectively. The multiple AVs experiment examined the safety impact of AVs on mixed traffic of freeway merging areas macroscopically using the developed risk assessment model. The results show that AVs could bring significant benefits to freeway safety, as traffic conflicts and risks are substantially reduced with incremental market penetration rates.
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