Title: The Effects of Varying Penetration Rates of L4-L5 Autonomous Vehicles on Fuel Efficiency and Mobility of Traffic Networks Show Chinese title

Title: 不同L4-L5自动驾驶车辆渗透率对交通网络燃油效率和 mobility 的影响

Abstract: Microscopic traffic simulators that simulate realistic traffic flow are crucial in studying, understanding and evaluating the fuel usage and mobility effects of having a higher number of autonomous vehicles (AVs) in traffic under realistic mixed traffic conditions including both autonomous and non-autonomous vehicles. In this paper, L4-L5 AVs with varying penetration rates in total traffic flow were simulated using the microscopic traffic simulator Vissim on urban, mixed and freeway roadways. The roadways used in these simulations were replicas of real roadways in and around Columbus, Ohio, including an AV shuttle routes in operation. The road-specific information regarding each roadway, such as the number of traffic lights and positions, number of STOP signs and positions, and speed limits, were gathered using OpenStreetMap with SUMO. In simulating L4-L5 AVs, the All-Knowing CoEXist AV and a vehicle with Wiedemann 74 driver were taken to represent AV and non-AV driving, respectively. Then, the driving behaviors, such as headway time and car following, desired acceleration and deceleration profiles of AV, and non-AV car following and lane change models were modified. The effect of having varying penetration rates of L4-L5 AVs were then evaluated using criteria such as average fuel consumption, existence of queues and their average/maximum length, total number of vehicles in the simulation, average delay experience by all vehicles, total number of stops experienced by all vehicles, and total emission of CO, NOx and volatile organic compounds (VOC) from the vehicles in the simulation. The results show that while increasing penetration rates of L4-L5 AVs generally improve overall fuel efficiency and mobility of the traffic network, there were also cases when the opposite trend was observed. Show Chinese abstract

Abstract: 在研究、理解和评估更多自动驾驶车辆（AVs）在包括自动驾驶和非自动驾驶的现实混合交通条件下的燃油使用和移动性影响方面，模拟真实交通流的微观交通仿真器至关重要。 本文利用微观交通仿真器Vissim，在城市道路、混合道路和高速公路场景下，模拟了具有不同渗透率的L4-L5级自动驾驶车辆。 这些仿真所使用的道路是俄亥俄州哥伦布市及其周边地区实际道路的复制品，其中包括一条正在运营的自动驾驶摆渡线路。 每条道路的道路特定信息，如交通信号灯的数量和位置、停车标志的数量和位置以及限速等信息，均通过OpenStreetMap与SUMO收集。 在模拟L4-L5级自动驾驶车辆时，采用了“全知CoEXist”自动驾驶车辆模型和配备Wiedemann 74驾驶员的车辆模型分别代表自动驾驶和非自动驾驶行为。 随后，对自动驾驶车辆的跟车头时距、车尾跟随、期望加减速特性以及非自动驾驶车辆的车尾跟随和变道模型进行了修改。 然后，通过平均燃油消耗、队列是否存在及其平均/最大长度、仿真中的总车辆数、所有车辆的平均延迟、所有车辆经历的总停车次数以及仿真中车辆排放的一氧化碳（CO）、氮氧化物（NOx）和挥发性有机化合物（VOC）总量等标准评估了L4-L5级自动驾驶车辆的不同渗透率的影响。 结果表明，虽然增加L4-L5级自动驾驶车辆的渗透率通常可以提高交通网络的整体燃油效率和流动性，但也存在相反趋势的情况。