Parking Planning with Genetic Algorithm for Multiple Autonomous Vehicles Nanchang Institute

Format:

Book

Conference/Event

Author/Creator:

Luo, Chagen, author.

Contributor:

Deng, Zhenwen

Fu, Zhiqiang

Hu, Yiming

Li, Zhuoren

Xu, Feng

Zeng, Dequan

Zhang, Peizhi

Conference Name:

WCX SAE World Congress Experience (2022-04-05 : Detroit & Online, Michigan, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2022

Summary:

The past decade has witnessed the rapid development of autonomous parking technology, since it has promising capacity to improve traffic efficiency and reduce the burden on drivers. However, it is prone to the trap of self-centeredness when each vehicle is automated parking in isolation. And it is easy to cause traffic congestion and even chaos when multiple autonomous vehicles require of parking into the same lot. In order to address the multiple vehicle parking problem, we propose a parking planning method with genetic algorithm. Firstly, an optimal mathematic model is established to describe the multiple autonomous vehicle parking problem. Secondly, a genetic algorithm is designed to solve the optimization problem. Thirdly, illustrative examples are developed to verify the parking planner. The performance of the present method indicates its competence in addressing parking multiple autonomous vehicles problem

Notes:

Vendor supplied data

Publisher Number:

2022-01-0087

Access Restriction:

Restricted for use by site license