Constructing a fundamental diagram for traffic flow with automated vehicles: Methodology and demonstration
Constructing a fundamental diagram for traffic flow with automated vehicles: Methodology and demonstration
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DOI：
10.1016/j.trb.2021.06.011
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发表时间：
2021-08
期刊：
影响因子：
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通讯作者：
Xiaowei Shi;X. Li
中科院分区：
文献类型：
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作者：
Xiaowei Shi;X. Li
商用车辆越来越多地配备有自动车辆（AV）特征，诸如自适应巡航控制系统。自动驾驶功能可以以自适应的方式自动控制当前车辆和前车之间的车头时距。与人类驾驶的车辆相比，自动控制可能导致显著不同的车辆跟驰运动，这挑战了经典交通流理论对新兴道路交通与AV的适用性。为了研究商用自动驾驶汽车对交通流的影响，本文提出了一种将经验实验和理论模型相结合的一般方法来构建基本图（FD），即，AV交通的交通流理论基础。为了证明实证实验设置，我们收集了高分辨率的轨迹数据，其中多个商用AV在具有不同车头时距设置的队列中彼此跟随。现场实验结果表明，传统的三角形FD结构仍然适用于描述AV交通的交通流特性。此外，通过比较自动驾驶汽车和人类驾驶车辆之间的FD，发现虽然最短的自动驾驶车头时距设置可以显着提高道路容量，但与现有的人类驾驶车辆交通相比，其他车头时距设置可能会降低道路容量。研究还发现车头时距设置可能会影响交通流的稳定性，这一点已被理论研究所揭示，但首先被经验AV数据所证实。根据这些发现，通过结合不同的车头时距设置和AV渗透率，得出混合交通流FD。本文提出的方法，包括实验设计，数据收集方法，交通流特性分析，混合交通流FD构建方法，可以作为一个方法学基础，研究未来的混合交通流特性与不确定性和不断发展的自动驾驶技术。
Increasingly, commercial vehicles are equipped with automated vehicle (AV) features such as adaptive cruise control systems. The AV feature can automatically control the headway between the current vehicle and the preceding vehicle in an adaptive manner. The automatic control may lead to significantly different car- following motions compared with those of human-driven vehicles, which challenges the applicability of classic traffic flow theory to emerging road traffic with AVs. To investigate the impacts of commercial AVs on traffic flow, this paper proposes a general methodology that combines both empirical experiments and theoretical models to construct a fundamental diagram (FD), i.e., the foundation for traffic flow theory for AV traffic. To demonstrate the empirical experiment settings, we collected high-resolution trajectory data with multiple commercial AVs following one another in a platoon with different headway settings. The field experiment results revealed that the traditional triangular FD structure remains applicable to describe the traffic flow characteristics of AV traffic. Further, by comparing the FDs between AVs and human-driven vehicles, it was found that although the shortest AV headway setting can significantly improve road capacity, other headway settings may decrease road capacity compared with existing human-driven-vehicle traffic. It was also found that headway settings may affect the stability of traffic flow, which has been revealed by theoretical studies but was first verified by empirical AV data. With these findings, mixed traffic flow FDs were derived by incorporating different headway settings and AV penetration rates. The method proposed in this paper, including experiment designs, data collection approaches, traffic flow characteristics analyses, and mixed traffic flow FD construction approaches, can serve as a methodological foundation for studying future mixed traffic flow features with uncertain and evolving AV technologies.