排
燃料效率
启发式
弹道
巡航控制
协同自适应巡航控制
计算机科学
序列(生物学)
控制理论(社会学)
汽车工程
工程类
模拟
控制(管理)
遗传学
生物
物理
人工智能
天文
作者
Qinzheng Wang,Xianfeng Yang,Zhitong Huang,Yun Yuan
标识
DOI:10.1177/0361198120913290
摘要
Cooperative adaptive cruise control (CACC) organizes connected and automated vehicles (CAVs) in platoons to improve traffic flow and reduce fuel consumption. Platoon formation involves a very complex process, however, because lateral and longitudinal misbehavior of CAVs results in greater fuel consumption and risk of collision. This study aims to design optimal vehicle trajectories of CAVs during CACC platoon formation. First, a basic scenario and a destination-based protocol are described to determine vehicle sequence in the platoon. A space-time lattice based model is then formulated to construct vehicle trajectories considering boundary conditions of kinematic limits, vehicle-following safety, and lane-changing rules. The objective is to optimize the vehicle sequence and fuel consumption simultaneously. A two-phase algorithm is proposed to solve this model, where the first phase is a heuristic algorithm that determines vehicle sequence and in the second phase dynamic programming is adapted to optimize fuel consumption based on the determined sequence. To evaluate the effectiveness of the proposed model in designing CAV trajectories, extensive experimental tests have been conducted in this study. Results show that the proposed model and algorithm can effectively optimize CAV sequence in the platoon based on their destinations. After optimization, CAV fuel consumption was reduced by 42%, 46%, and 43%, respectively, in three different tested scenarios.
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