Active Obstacle Avoidance Trajectory Planning for Vehicles Based on Obstacle Potential Field and MPC in V2P Scenario.

Pan, Ruoyu; Jie, Lihua; Zhao, Xinyu; Wang, Honggang; Yang, Jingfeng; Song, Jiwei

Pan, Ruoyu; Jie, Lihua; Zhao, Xinyu; Wang, Honggang; Yang, Jingfeng; Song, Jiwei.

Afiliación

Pan R; School of Communications and Information Engineering and School of Artificial Intelligence, Xi'an University of Posts and Telecommunications, Xi'an 710121, China.
Jie L; School of Communications and Information Engineering and School of Artificial Intelligence, Xi'an University of Posts and Telecommunications, Xi'an 710121, China.
Zhao X; School of Communications and Information Engineering and School of Artificial Intelligence, Xi'an University of Posts and Telecommunications, Xi'an 710121, China.
Wang H; School of Communications and Information Engineering and School of Artificial Intelligence, Xi'an University of Posts and Telecommunications, Xi'an 710121, China.
Yang J; Guangzhou Institute of Industrial Intelligence, Guangzhou 511458, China.
Song J; China Electronics Standardization Institute, Beijing 100007, China.

Sensors (Basel) ; 23(6)2023 Mar 19.

Article en En | MEDLINE | ID: mdl-36991959

Palabras clave

A*; MPC (model predictive control); V2P; artificial potential field

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Sensors (Basel) Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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