An Autonomous Vehicle Group Cooperation Model in an Urban Scene
Document Type
Article
Publication Date
12-1-2023
Abstract
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.
Identifier
85170531725 (Scopus)
Publication Title
IEEE Transactions on Intelligent Transportation Systems
External Full Text Location
https://doi.org/10.1109/TITS.2023.3300278
e-ISSN
15580016
ISSN
15249050
First Page
13852
Last Page
13862
Issue
12
Volume
24
Grant
JP22H03643
Fund Ref
Department of Sport and Recreation, Government of Western Australia
Recommended Citation
Yuan, Guiyuan; Cheng, Jiujun; Zhou, Meng Chu; Cheng, Sheng; Gao, Shangce; Jiang, Changjun; and Abusorrah, Abdullah, "An Autonomous Vehicle Group Cooperation Model in an Urban Scene" (2023). Faculty Publications. 1306.
https://digitalcommons.njit.edu/fac_pubs/1306