Citation

Zheng X, Zhang D, Gao H, Zhao Z, Huang H, Wang J. Sensors (Basel) 2018; 18(12): s1812431.

Affiliation

State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China. wjqlws@tsinghua.edu.cn.

Copyright

(Copyright © 2018, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/s18124313

PMID

30544496

Abstract

Over the past decades, there has been significant research effort dedicated to the development of intelligent vehicles and V2X systems. This paper proposes a road traffic risk assessment method for road traffic accident prevention of intelligent vehicles. This method is based on HMM (Hidden Markov Model) and is applied to the prediction of steering angle status to (1) evaluate the probabilities of the steering angle in each independent interval and (2) calculate the road traffic risk in different analysis regions. According to the model, the road traffic risk is quantified and presented directly in a visual form by the time-varying risk map, to ensure the accuracy of assessment and prediction. Experiment results are presented, and the results show the effectiveness of the assessment strategies.

Language: en

Keywords

V2X; hidden Markov model; intelligent transportation system; road traffic risk assessment