Detection of steering events using hidden Markov models with multivariate observations

In this article the authors propose a method to identify steering events, such as curves and manoeuvres for vehicles. The authors use a hidden Markov model with multidimensional observations, to estimate the number of events. Three signals, lateral acceleration, steering angle speed and vehicle speed, are used as observations. The authors demonstrate that hidden Markov models with a combination of continuous and discrete distributions for observations can be used to detect steering events. Further, the expected number of events is estimated using the transition matrix of hidden states. The results from both measured and simulated data show that the method works well and accurately estimates the number of steering events.

• Record URL:
  https://doi.org/10.1504/IJVSMT.2016.083752
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/17456436
• Supplemental Notes:
  • Copyright © 2016 Inderscience Enterprises Ltd.
• Authors:
  • Maghsood, Roza
  • Johannesson, Par
  • Wallin, Jonas
• Publication Date: 2016

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 313-329
• Serial:
  • International Journal of Vehicle Systems Modelling and Testing
  • Volume: 11
  • Issue Number: 4
  • Publisher: Inderscience Enterprises Limited
  • ISSN: 1745-6436
  • EISSN: 1745-6444
  • Serial URL: http://www.inderscience.com/jhome.php?jcode=IJVSMT

Subject/Index Terms

• TRT Terms: Detection and identification; Lateral acceleration; Markov chains; Speed; Steering
• Subject Areas: Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01639120
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 27 2017 4:10PM