Chapter
Jul 3, 2013
Optimizing Hidden Markov Model with Baum-Welch Algorithm for Vehicle Driver's Intention Recognition
Authors: Liang-li Zhang, Chao-zhong Wu, Zhen Huang, and Bin WangAuthor Affiliations
Publication: ICTIS 2013: Improving Multimodal Transportation Systems-Information, Safety, and Integration
Abstract
In this paper, a method for vehicle driver's intention recognition is investigated through an optimized hidden Markov model (HMM). As uncertainties exist between modeling and application of intention recognition with HMM, the Baum-Welch (B-W) algorithm is introduced to optimize and update the parameters of the established HMM. The major steps within the optimization process, such as acquisitions of forward probabilities, backward probabilities, maximum expected probabilities ratio, elements updates of matrixes π, A and B, and setups of recursion terminated condition, are fully described in the paper. An elaborate example presented at the end of the paper shows the credibility and effectiveness of the proposed algorithm.
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© 2013 American Society of Civil Engineers.
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Published online: Jul 3, 2013
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Liang-li Zhang
Wuhan University of Science and Technology, Heping 947, Wuhan 430081, China; Wuhan University of Technology, Heping 1040, Wuhan 430063, China
Chao-zhong Wu
Wuhan University of Technology, Heping 1040, Wuhan 430063, China
Zhen Huang
Wuhan University of Technology, Heping 1040, Wuhan 430063, China
Bin Wang
Wuhan University of Science and Technology, Heping 947, Wuhan 430081, China
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