论文标题
连通性和自动化对饱和进展的影响以及信号交叉处的容量
The Effects of Connectivity and Automation on Saturation Headway and Capacity at Signalized Intersections
论文作者
论文摘要
本文分析了连接和自动化车辆对信号交叉路口饱和性进展的潜在影响。在Vissim作为测试台创建了信号交叉点，在其中对四种车辆类型进行了建模和测试：（i）人类驱动的车辆（HVS），（ii）连接的车辆（CVS），（III）自动化车辆（AVS）和（IV）连接的自动车辆（CAVS）。根据这四种车辆类型的不同市场渗透率定义了各种情况。与人类驾驶员相比，假定AV更加谨慎地移动。简历和骑士应该接收有关未来交通信号灯状态的信息，并调整其速度以避免在十字路口停止。结果，他们的运动有望在停止数量较低的情况下更加顺畅。这些车辆类型在混合交通中的影响是根据交叉路口不同车道组的饱和度，容量，旅行时间，延迟和队列长度研究的。 Vissim开发的Python脚本代码用于提供信号控制器和CVS和CAVS之间的通信，以相应地调整其速度。结果表明，CV和CAV市场渗透率的提高会降低饱和性进展，从而增加信号交叉点的能力。另一方面，提高AV市场渗透率会恶化交通运营。结果还表明，在100％CAVS和100％AVS的交通流量中，分别观察到泳道群的最高增加（80％）和减少（20％）。
This paper analyzes the potential effects of connected and automated vehicles on saturation headway and capacity at signalized intersections. A signalized intersection is created in Vissim as a testbed, where four vehicle types are modeled and tested: (I) human-driven vehicles (HVs), (II) connected vehicles (CVs), (III) automated vehicles (AVs), and (IV) connected automated vehicles (CAVs). Various scenarios are defined based on different market penetration rates of these four vehicle types. AVs are assumed to move more cautiously compared to human drivers. CVs and CAVs are supposed to receive information about the future state of traffic lights and adjust their speeds to avoid stopping at the intersection. As a result, their movements are expected to be smoother with a lower number of stops. The effects of these vehicle types in mixed traffic are investigated in terms of saturation headway, capacity, travel time, delay, and queue length in different lane groups of an intersection. A Python script code developed by Vissim is used to provide the communication between the signal controller and CVs and CAVs to adjust their speeds accordingly. The results show that increasing CV and CAV market penetration rate reduces saturation headway and consequently increases capacity at signalized intersections. On the other hand, increasing the AV market penetration rate deteriorates traffic operations. Results also indicate that the highest increase (80%) and decrease (20%) in lane group capacity are observed, respectively, in a traffic stream of 100% CAVs and 100% AVs.
