Steering Control Driver Model of Skid Steering Vehicle Based on Gaussian Mixture Model-Hidden Markov Model

doi:10.3969/j.issn.1000-1093.2017.12.002

Abstract

Abstract: In order to solve the unmanned lateral control problem of the skid-steering vehicle based on clutch and brake steering structure, the GMM-HMM model is used to predict the steering mode. The skilled driver's steering operation data acquired from the numerous filed tests is applied to establish the model. The observation states of the HMM model are made up of the velocity and the heading deviation based on the GMM model. The hidden states of the HMM model are made up of the cluster labels of the steering stick position including both of the left and the right sides. The driver-vehicle interaction model of the skid-steering vehicle based on clutch and brake steering structure is established from data training. The driving skills and the vehicle dynamics are described in the statistics way. The model is applied to estimate the steering mode, and the results have proved that the steering mode can be estimated properly based on the driving skills. Key

Key words: ordnancescienceandtechnology, skidsteering, steeringcontrol, drivermodel, Gaussianmixturemodel-hiddenMarkovmodel, machinelearning, motionprimitive

CLC Number:

TJ810.1

WANG Bo-yang， GONG Jian-wei， GAO Tian-yun， CHEN Hui-yan， XI Jun-qiang. Steering Control Driver Model of Skid Steering Vehicle Based on Gaussian Mixture Model-Hidden Markov Model[J]. Acta Armamentarii, 2017, 38(12): 2301-2308.

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第38卷第12期
2017 年12月兵工学报ACTA
ARMAMENTARIIVol.38No.12Dec.2017

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