Application of Two-Level Joint Information Fusion Model in Intelligent Vehicle

International Journal of Online Engineering

Xiaodong Chen¹  Jiinying Huang¹  Yan Ting Lan² 

[1] North University of China, School of Computer Science and Control Engineering, Taiyuan, 030051,ChinaNorth University of China, School of Computer Science and Control Engineering, Taiyuan, 030051,ChinaNorth University of China, School of Computer Science and Control Engineering, Taiyuan, 030051,China

关键词: information fusion;    intelligent vehicle;    neural network;    D-S evidence theory;   

DOI  :  

学科分类：社会科学、人文和艺术（综合）

来源: International Association of Online Engineering

【 摘 要 】

This paper proposes a two-level joint information fusion model combining BP neural network and D-S evidence theory. The model of great practical value reduces target identification error probability by multiple features of the target information, shows good scalability with its two steps of information fusion model, and conveniently increases/reduces feature fusion information source according to different situations and different objects. The method used for intelligent vehicles has good flexibility and robustness in tracking and avoiding obstacle. The simulation and real vehicle tests have verified effectiveness of the method.

【 授权许可】

Unknown