Research on Driving Status Recognition of Heavy Duty Vehicle Based on Double-layer HMM Model

doi:10.3969/j.issn.1000-1093.2015.10.002

Abstract

Abstract: In order to detect the risky driving status of heavy duty vehicle, the double-layer hidden Markov model（HMM）is used for the rollover warning system of heavy duty vehicle, which can identify the driving status dynamically. The data is collected during the typical driving conditions, and the T-G test method is used to delete the abnormal data. The driving limit value of vehicle status is set based on K-means algorithm. Then finally Baum-Welch algorithm is used to optimize the proposed double-layer HMM, and the optimized HMM is used to identify the driving status in real-time. The identification results show that the proposed model can identify the driving status under every single driving condition as well as under the multiple driving conditions accurately and effectively. At the same time this model has a good real-time capacity.

Key words: ordnance science and technology, double-layer hidden Markov model, heavy duty vehicle, driving status identification, rollover warning

CLC Number:

U462.2

ZHU Tian-jun，KONG Xian-wei，LI Bin. Research on Driving Status Recognition of Heavy Duty Vehicle Based on Double-layer HMM Model[J]. Acta Armamentarii, 2015, 36(10): 1832-1840.

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