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Prediction of Human Driving Behavior Using Dynamic Bayesian Networks
Toru KUMAGAI Motoyuki AKAMATSU
IEICE TRANSACTIONS on Information and Systems
Publication Date: 2006/02/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Biocybernetics, Neurocomputing
dynamic Bayesian network, switching linear dynamic system, collision warning system, collision avoidance system, driving behavior prediction,
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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.