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.
Safety assessment of vehicle behaviour based on the improved D–S evidence theory
IET Intelligent Transport Systems ; 14 , 11 ; 1396-1402
2020-11-01
7 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
traffic engineering computing , road safety , road accidents , sensor fusion , uncertainty handling , road vehicles , vehicular ad hoc networks , road traffic , inference mechanisms , alarm systems , vehicle dangerous behaviour warning , improved D‐S evidence theory , road traffic safety , safety assessment method , improved Dempster‐Shafer evidence theory , vehicle collision accident mechanism , vehicle safety , vehicle‐mounted sensors , active safety warning , vehicle state awareness , vehicle behaviour identification , VANET , weighted correction method , evidence variance , multisource heterogeneous information , evidence conflict , reliability , road traffic management department , traffic accident warning
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