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Open AccessArticle

Accident Prediction System Based on Hidden Markov Model for Vehicular Ad-Hoc Network in Urban Environments

1
School of Computer Science and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
2
National Center for Materials Service Safety, University of Science and Technology Beijing, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Information 2018, 9(12), 311; https://doi.org/10.3390/info9120311
Received: 22 October 2018 / Revised: 24 November 2018 / Accepted: 5 December 2018 / Published: 7 December 2018
(This article belongs to the Special Issue Vehicular Networks and Applications)
With the emergence of autonomous vehicles and internet of vehicles (IoV), future roads of smart cities will have a combination of autonomous and automated vehicles with regular vehicles that require human operators. To ensure the safety of the road commuters in such a network, it is imperative to enhance the performance of Advanced Driver Assistance Systems (ADAS). Real-time driving risk prediction is a fundamental part of an ADAS. Many driving risk prediction systems have been proposed. However, most of them are based only on vehicle’s velocity. But in most of the accident scenarios, other factors are also involved, such as weather conditions or driver fatigue. In this paper, we proposed an accident prediction system for Vehicular ad hoc networks (VANETs) in urban environments, in which we considered the crash risk as a latent variable that can be observed using multi-observation such as velocity, weather condition, risk location, nearby vehicles density and driver fatigue. A Hidden Markov Model (HMM) was used to model the correlation between these observations and the latent variable. Simulation results showed that the proposed system has a better performance in terms of sensitivity and precision compared to state of the art single factor schemes. View Full-Text
Keywords: accident prediction system; driver assistance system; hidden markov model; VANET; ITS; HMM; ADAS accident prediction system; driver assistance system; hidden markov model; VANET; ITS; HMM; ADAS
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Aung, N.; Zhang, W.; Dhelim, S.; Ai, Y. Accident Prediction System Based on Hidden Markov Model for Vehicular Ad-Hoc Network in Urban Environments. Information 2018, 9, 311.

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