Prediction of Human Driving Behavior Using Dynamic Bayesian Networks

Authors:
Toru Kumagai;Motoyuki Akamatsu
Affiliations:
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: kuma ...;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: kuma ...
Venue:
IEICE - Transactions on Information and Systems
Year:
2006

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Abstract

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.