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A Machine Vision Based Surveillance System for California Roads

Author

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  • Malik, J.
  • Russell, S.

Abstract

In this report we address the problem of automation of heavy-duty vehicles. After a brief description of the dynamic model used in our design and simulations, we develop nonlinear controllers with adaptation, first for speed control and then for vehicle follower longitudinal control. We consider both autonomous operation as well as intervehicle communication, and evaluate the performance of our controllers in several different scenarios through simulation.

Suggested Citation

  • Malik, J. & Russell, S., 1995. "A Machine Vision Based Surveillance System for California Roads," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1hh5x9jw, Institute of Transportation Studies, UC Berkeley.
    • Handle: RePEc:cdl:itsrrp:qt1hh5x9jw
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    References listed on IDEAS

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    1. Ioannou, P. & Xu, Z., 1994. "Throttle And Brake Control Systems For Automatic Vehicle Following," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt1vb6380h, Institute of Transportation Studies, UC Berkeley.
    2. Xu, Z. & Ioannou, P., 1994. "Adaptive Throttle Control For Speed Tracking," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0vx1w6wc, Institute of Transportation Studies, UC Berkeley.
    3. Sheikholeslam, Shahab & Desoer, Charles A., 1990. "Longitudinal Control Of A Platoon Of Vehicles. III, Nonlinear Model," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0dx8t12z, Institute of Transportation Studies, UC Berkeley.
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    Cited by:

    1. Hall, Randolph & Mehta, Yatrik, 1998. "Incident Management: Process Analysis And Improvement Phase 1: Review Of Procedures," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt45r743q6, Institute of Transportation Studies, UC Berkeley.

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