详情

原文传递 A two-stage trajectory planning model for cooperative truck platooning on freeways

题名：	A two-stage trajectory planning model for cooperative truck platooning on freeways
正文语种：	eng
作者：	Tao Zhou;Fangfang Zheng;Xiaobo Liu;Zhichen Fan
作者单位：	School of Transportation and Logistics Southwest Jiaotong University Sichuan P.R. China\|\|National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan P.R. China;School of Transportation and Logistics Southwest Jiaotong University Sichuan P.R. China\|\|National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan P.R. China\|\|National United Engineering Laboratory of Integrated and Intelligent Transportation Southwest Jiaotong University Sichuan P.R. China;School of Transportation and Logistics Southwest Jiaotong University Sichuan P.R. China\|\|National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan P.R. China;School of Transportation and Logistics Southwest Jiaotong University Sichuan P.R. China\|\|National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Sichuan P.R. China
关键词：	fuel consumption; permutation strategies; truck platooning; trajectory optimization
摘要：	Truck platooning is considered as a promising approach to improve traffic stability and to reduce fuel consumption and emissions on freeways. This article develops a two-stage trajectory planning model for cooperative and automated trucks (CATs) traveling on freeways to minimize overall fuel consumption considering platooning time and velocity change. In the first stage, five different strategies are proposed to determine the permutation of the platoon given the initial states and travel information of CATs. Once the feasibility is confirmed, the model is formulated as a mixed-integer programming to optimize the trajectories of all CATs on the entire freeway section. The results from the numerical experiments show that the platooning time optimization (PTO) strategy has superior performance in optimizing overall platooning time. Moreover, the velocity change under the condition of maximum platooning time is generally lower for the PTO and the passing time minimum strategies. These characteristics make the PTO strategy combined with the trajectory optimization program a suitable application for cooperative truck platooning management.
出版年：	2023
期刊名称：	Journal of Intelligent Transportation Systems
卷：	27
期：	1/6
页码：	217-237