Safety assessment of vehicle behaviour based on the improved D–S evidence theory

Autor: Xin Cheng, Jingmei Zhou, Xiangmo Zhao
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: IET Intelligent Transport Systems, Vol 14, Iss 11, Pp 1396-1402 (2020)
Druh dokumentu: article
ISSN: 1751-9578
1751-956X
DOI: 10.1049/iet-its.2019.0737
Popis: Vehicle dangerous behaviour warning plays an important role to improve road traffic safety and efficiency, so a safety assessment method of vehicle behaviour based on the improved Dempster–Shafer (D–S) evidence theory is proposed. Firstly, through analysis of vehicle collision accident mechanism, some factors closely related to vehicle safety are extracted. Also, multiple sensors are synthetically utilised to collect information, which realises the awareness of vehicle state, road attribute, driving environment etc. Then vehicle behaviour identification is accomplished according to the parameter information of the vehicle‐mounted sensors, as well as the related data of adjacent vehicles in vehicular ad hoc networks (VANET). Finally, a sequential type of weighted correction method based on evidence variance is used to integrate different levels of multi‐source heterogeneous information and to achieve safety assessment of vehicle behaviour. The experimental results show that the improved D–S evidence theory reduces the evidence conflict, increasing the accuracy and reliability of vehicle behaviour safety assessment. The study solves the fundamental core problem of active safety warning in VANET and provides a new means of traffic accident warning for the road traffic management department.
Databáze: Directory of Open Access Journals
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