A novel framework for road traffic risk assessment with HMM-based prediction model

Xunjia Zheng, Di Zhang, Hongbo Gao, Zhiguo Zhao, Heye Huang, Jianqiang Wang

研究成果: Article査読

6 被引用数 (Scopus)

抄録

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.

本文言語English
論文番号4313
ジャーナルSensors (Switzerland)
18
12
DOI
出版ステータスPublished - 2018 12
外部発表はい

ASJC Scopus subject areas

  • 分析化学
  • 生化学
  • 原子分子物理学および光学
  • 器械工学
  • 電子工学および電気工学

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