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首页> 外文期刊>Transportation research >Don't pass the automated vehicles! System level impacts of multi-vehicle CAV control strategies
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Don't pass the automated vehicles! System level impacts of multi-vehicle CAV control strategies

机译：不要通过自动驾驶汽车！多车CAV控制策略对系统级的影响

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With increasing number of vehicles registered on road the CO2 emissions and the amount of fuel wasted because of congestion has been rising. V2X and Connected and Automated Vehicle (CAV) technology allows vehicles and traffic infrastructure to communicate with each other, and could facilitate better use of existing resources by providing vehicles information about their surroundings and traffic signals. The information regarding the phase of traffic signal, vehicles' position and vehicles' speed can be used by drivers and autonomous vehicle control algorithms to make informed decisions as they approach traffic signals. This research proposes a coordination heuristic to improve traffic flow of CAV vehicles through traffic signals and reduce system wide emissions. A simulation was used to compare the system level impacts to emissions, travel time, and wait time of the proposed coordination heuristic to a single vehicle optimization strategy and baseline driver behavior. The results of this research suggest that traffic density and CAV market penetration impact the potential benefits of CAV control strategies. At low CAV penetration rates both the single vehicle and coordination heuristic produced increased emissions primarily driven by driving behavior of non-V2X enabled vehicles. At higher CAV penetration rates the co-ordination heuristic significantly outperformed the single vehicle control strategy and baseline driver behavior with regards to emissions reduction. The analysis indicates that at 900 vehicles per hour for either of the two driving strategies: coordination heuristic or single-vehicle optimization, to be more preferred over baseline driver behavior, at least 50% of the vehicles should be CAV. Once a threshold penetration rate of CAV vehicles is achieved, vehicles following the coordination heuristic generate nearly 10% fewer CO2 emissions than vehicles following baseline driver behavior, a 30% improvement over the reduction in CO2 emissions obtained using single-vehicle optimization. The vehicles following the coordination heuristic also have less travel time than vehicles following single-vehicle optimization, and less wait times than vehicles following baseline driver behavior.
机译：随着道路上登记的车辆数量的增加，由于拥堵导致的二氧化碳排放量和燃料浪费量一直在上升。 V2X和联网自动驾驶汽车（CAV）技术允许车辆和交通基础设施彼此通信，并可以通过提供有关其周围环境和交通信号的信息来促进更好地利用现有资源。驾驶员和自主车辆控制算法可使用有关交通信号灯相位，车辆位置和速度的信息，在他们接近交通信号灯时做出明智的决定。这项研究提出了一种协调启发法，以通过交通信号改善CAV车辆的交通流量并减少系统范围的排放。仿真用于比较系统水平对排放，行驶时间和拟议的协调启发法对单个车辆优化策略和基线驾驶员行为的等待时间的影响。这项研究的结果表明，交通密度和CAV市场渗透率会影响CAV控制策略的潜在利益。在低CAV渗透率的情况下，单车和协调启发法均会增加排放量，这主要是由未启用V2X的车辆的驾驶行为所驱动。在较高的CAV渗透率下，在减少排放方面，协调启发法明显优于单一车辆控制策略和基线驾驶员行为。分析表明，对于两种驾驶策略中的任何一种，每小时900辆车：协调启发式或单车优化（要比基线驾驶员行为更可取），至少50％的车辆应为CAV。一旦达到CAV车辆的阈值渗透率，遵循协调启发法的车辆产生的CO2排放量将比遵循基线驾驶员行为的车辆减少近10％，比使用单车优化获得的CO2排放量减少30％。遵循协调启发法的车辆比单车辆优化后的车辆具有更少的行驶时间，并且比基准驾驶员行为后的车辆具有更少的等待时间。

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