• DocumentCode
    631818
  • Title

    Video Driven Traffic Modelling

  • Author

    Hailing Zhou ; Creighton, Douglas ; Lei Wei ; Gao, D.Y. ; Nahavandi, S.

  • Author_Institution
    Centre for Intell. Syst. Res. (CISR), Deakin Univ., Geelong, VIC, Australia
  • fYear
    2013
  • fDate
    9-12 July 2013
  • Firstpage
    506
  • Lastpage
    511
  • Abstract
    We propose Video Driven Traffic Modelling (VDTM) for accurate simulation of real-world traffic behaviours with detailed information and low-cost model development and maintenance. Computer vision techniques are employed to estimate traffic parameters. These parameters are used to build and update a traffic system model. The model is simulated using the Paramics traffic simulation platform. Based on the simulation techniques, effects of traffic interventions can be evaluated in order to achieve better decision makings for traffic management authorities. In this paper, traffic parameters such as vehicle types, times of starting trips and corresponding origin-destinations are extracted from a video. A road network is manually defined according to the traffic composition in the video, and individual vehicles associated with extracted properties are modelled and simulated within the defined road network using Paramics. VDTM has widespread potential applications in supporting traffic decision-makings. To demonstrate the effectiveness, we apply it in optimizing a traffic signal control system, which adaptively adjusts green times of signals at an intersection to reduce traffic congestion.
  • Keywords
    computer vision; decision making; road traffic control; road vehicles; video signal processing; Paramics traffic simulation platform; VDTM; computer vision techniques; green signal time; origin-destinations; real-world traffic behaviour simulation; road network; starting trips; traffic composition; traffic congestion; traffic decision making; traffic intervention effect evaluation; traffic management authorities; traffic parameter estimation; traffic parameter extraction; traffic signal control system optimization; traffic system model; vehicle types; video driven traffic modelling; Biological system modeling; Cameras; Computational modeling; Delays; Roads; Vehicle detection; Vehicles;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Intelligent Mechatronics (AIM), 2013 IEEE/ASME International Conference on
  • Conference_Location
    Wollongong, NSW
  • ISSN
    2159-6247
  • Print_ISBN
    978-1-4673-5319-9
  • Type

    conf

  • DOI
    10.1109/AIM.2013.6584142
  • Filename
    6584142