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Prediction of Human Driving Behavior Using Dynamic Bayesian Networks Toru KUMAGAI Motoyuki AKAMATSU Publication IEICE TRANSACTIONS on Information and Systems Vol.E89-D No.2 pp.857-860 Publication Date: 2006/02/01 Online ISSN: 1745-1361 DOI: 10.1093/ietisy/e89-d.2.857 Print ISSN: 0916-8532 Type of Manuscript: LETTER Category: Biocybernetics, Neurocomputing Keyword: dynamic Bayesian network, switching linear dynamic system, collision warning system, collision avoidance system, driving behavior prediction, Full Text: PDF(369.1KB)>>
Summary: 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. | ||||||||||
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