可进化性
计算机科学
趋同(经济学)
无线自组网
光学(聚焦)
骨料(复合)
车辆跟踪系统
分布式计算
人工智能
分割
经济增长
生物
无线
经济
光学
进化生物学
复合材料
材料科学
物理
电信
作者
Guiyuan Yuan,Jiujun Cheng,MengChu Zhou,Sheng Cheng,Shangce Gao,Changjun Jiang,Abdullah Abusorrah
出处
期刊:IEEE Transactions on Intelligent Transportation Systems
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:: 1-11
标识
DOI:10.1109/tits.2023.3300278
摘要
Formulating a cooperative autonomous vehicle group is challenging in an urban scene that has complex road networks and diverse disturbance. Existing methods of vehicle cluster cooperation in a vehicular ad-hoc network cannot be applied to autonomous vehicles because the latter have different requirements for a vehicle group structure and communication quality. Existing studies focus on autonomous vehicle group cooperation in closed and highway scenes only. Their outcomes cannot be directly applied to an urban scene because of its complex road conditions, incomplete cooperation properties, and lack of a vehicle group size control strategy. In this work, we formulate a cooperation model for autonomous vehicle groups in such scene. First, we analyze cooperation criteria based on the non-colliding aggregate motion of flocks and deduce the connectivity, coupling, timeliness, evolvability, and adaptivity of a vehicle group, based on which we propose a cooperation model. Next, we solve our model by using a modified distributed evolutionary multi-objective optimization method, prove its convergence, and analyze its computational complexity. Finally, we conduct simulations on synthetic and real roads to show its performance in terms of average connectivity, coupling, timeliness, evolvability, and adaptivity of vehicle groups.
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