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Sensors 2018, 18(12), 4313; https://doi.org/10.3390/s18124313

A Novel Framework for Road Traffic Risk Assessment with HMM-Based Prediction Model

1
State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing 100084, China
2
School of Information Engineering, Zhengzhou University, Zhengzhou 450001, China
3
Jiangsu Key Laboratory of Traffic and Transportation Security, Huaiyin Institute of Technology, Huai’an 223001, China
These authors contributed equally to this work.
*
Authors to whom correspondence should be addressed.
Received: 22 October 2018 / Revised: 13 November 2018 / Accepted: 5 December 2018 / Published: 7 December 2018
(This article belongs to the Special Issue Enhances in V2X Communications for Connected Autonomous Vehicles)
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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. View Full-Text
Keywords: road traffic risk assessment; intelligent transportation system; hidden Markov model; V2X road traffic risk assessment; intelligent transportation system; hidden Markov model; V2X
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Zheng, X.; Zhang, D.; Gao, H.; Zhao, Z.; Huang, H.; Wang, J. A Novel Framework for Road Traffic Risk Assessment with HMM-Based Prediction Model. Sensors 2018, 18, 4313.

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