Non-recurring incidents on our nation's freeways is estimated to cost over $60 billion a year. The challenge is to develop an effective methodology to electronically identify these incidents quickly in order to manage the freeway operation and restore the facility to its optimum operating level in the minimum time. Single vehicle loop detectors have traditionally been used to measure occupancy on the freeway segments as a means of determining when incidents have occurred. Most incident detection algorithms using the traditional occupancy parameter have either taken too long to report an incident or they have given an excessive number of false alarms. Trap travel time obtained from two loops in each lane is shown in this paper to have the promise of much faster detection of the incidents with a lower false alarm rate.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Intelligent Data for Incident Detection


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    International Pacific Conference On Automotive Engineering ; 1993



    Publication date :

    1993-11-01




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




    Intelligent Data for Incident Detection

    Wall, H. B. / Marsden, B. G. / Hunt, J. et al. | British Library Conference Proceedings | 1992


    Intelligent data for incident detection

    Marsden,B.G. / Wall,H.B. / Hunt,J. et al. | Automotive engineering | 1993


    Intelligent Data for Incident Detection

    Marsden, B. G. / Wall, H. B. / Hunt, J. et al. | British Library Conference Proceedings | 1993


    Traffic incident intelligent detection system

    RONG XIAOPING | European Patent Office | 2021

    Free access

    Using VRC Data for Incident Detection

    Parkany, E. / Bernstein, D. / ASCE | British Library Conference Proceedings | 1993