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

Bo Yang Wang, Jian Wei Gong, Tian Yun Gao, Hui Yan Chen*, Jun Qiang Xi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)2301-2308
Number of pages8
JournalBinggong Xuebao/Acta Armamentarii
Volume38
Issue number12
DOIs
Publication statusPublished - 1 Dec 2017

Keywords

  • Driver model
  • Gaussian mixture model-hidden Markov model
  • Machine learning
  • Motion primitive
  • Ordnance science and technology
  • Skid steering
  • Steering control

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