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Development and Evaluation of Cooperative Intersection Management Algorithm under Connected and Automated Vehicles Environment
Transportation Research Record: Journal of the Transportation Research Board ( IF 1.6 ) Pub Date : 2021-02-28 , DOI: 10.1177/0361198121994580
Slobodan Gutesa 1 , Joyoung Lee 2 , Dejan Besenski 3
Affiliation  

Recent technological advancements in the automotive and transportation industry established a firm foundation for development and implementation of various connected and automated vehicle solutions around the globe. Wireless communication technologies such as the dedicated short-range communication protocol are enabling information exchange between vehicles and infrastructure. This research paper introduces an intersection management strategy for a corridor with automated vehicles utilizing vehicular trajectory-driven optimization method. Trajectory-Driven Optimization for Automated Driving provides an optimal trajectory for automated vehicles based on current vehicle position, prevailing traffic, and signal status on the corridor. All inputs are used by the control algorithm to provide optimal trajectories for automated vehicles, resulting in the reduction of vehicle delay along the signalized corridor with fixed-time signal control. The concept evaluation through microsimulation reveals that, even with low market penetration (i.e., less than 10%), the technology reduces overall travel time of the corridor by 2%. Further increase in market penetration produces travel time and fuel consumption reductions of up to 19.5% and 22.5%, respectively.



中文翻译:

互联自动驾驶环境下协同交叉口管理算法的开发与评估

汽车和运输行业的最新技术进步为全球各种联网和自动车辆解决方案的开发和实施奠定了坚实的基础。诸如专用短距离通信协议之类的无线通信技术使车辆与基础设施之间能够进行信息交换。该研究论文介绍了一种利用车辆轨迹驱动的优化方法的自动车辆走廊的交叉口管理策略。自动驾驶的轨迹驱动优化基于当前车辆位置,主要交通和走廊上的信号状态,为自动车辆提供了最佳轨迹。控制算法使用所有输入为自动驾驶汽车提供最佳轨迹,从而通过固定时间的信号控制减少了沿信号化走廊的车辆延误。通过微观仿真进行的概念评估表明,即使在市场渗透率较低(即小于10%)的情况下,该技术也可以将走廊的总体旅行时间减少2%。市场渗透率的进一步提高分别使出行时间和燃油消耗分别减少了19.5%和22.5%。

更新日期:2021-03-01
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