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IEICE Transactions on Information and Systems 2006 E89-D(2):857-860; doi:10.1093/ietisy/e89-d.2.857
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Copyright © 2006 The Institute of Electronics, Information and Communication Engineers

Regular Section -- Letters -- Biocybernetics, Neurocomputing

Prediction of Human Driving Behavior Using Dynamic Bayesian Networks

Toru KUMAGAI1 and Motoyuki AKAMATSU1

1 The authors are with the Institute for Human Science and Biomedical Engineering, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba-shi, 305–8566 Japan. E-mail: kumagai.toru{at}aist.go.jp

This paper presents a method of predicting future human driving behavior under the condition that its resultant behavior and past observations are given. The proposed method makes use of a dynamic Bayesian network and the junction tree algorithm for probabilistic inference. The method is applied to behavior prediction for a vehicle assumed to stop at an intersection. Such a predictive system would facilitate warning and assistance to prevent dangerous activities, such as red-light violations, by allowing detection of a deviation from normal behavior.

Key Words: dynamic Bayesian network, switching linear dynamic system, collision warning system, collision avoidance system, driving behavior prediction

Manuscript received November 4, 2004.


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