A Method for Crash Prediction and Avoidance Using Hidden Markov Models
2019 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)(2019)
摘要
In recent years, automotive technology has made a steady progress. In particular, Advanced Driver Assistance System (ADAS) has enabled many safety features in commercial vehicles, for instance, pedestrian detection, lane keeping assist, emergency automatic braking, etc. Although these features provide drivers with a safer operational environment, crashes still happen occasionally due to the complex road conditions and the unpredictable movement of road users including vehicles, pedestrians, bicyclists, and non-motorized vehicles. In this paper, we aim at predicting the possibilities of crashes between vehicles on highway and implementing an appropriate active safety system to prevent the same. In particular, hidden Markov models are developed for the traffic lanes and speed change of vehicles on highway. Algorithms are developed for the prediction of crash probabilities. Simulation experiments are conducted using Matlab, the results illustrate the effectiveness of the proposed research.
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关键词
ADAS,safety features,commercial vehicles,road conditions,active safety system,hidden Markov models,traffic lanes,crash probabilities,crash prediction,automotive technology,Advanced Driver Assistance System,crash avoidance
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