This paper reports on the real-data testing of a real-time adaptive freeway traffic state estimator that is based on macroscopic traffic flow modelling and extended Kalman filtering. The testing intends to demonstrate some main features of the estimator that are partly due to its adaptive capability based on on-line model parameter estimation. These features are (1 ) avoiding off-line model calibration ; (2) adaptation to changing environmental conditions; (3) enabling incident alarms. The reported testing results are quite satisfactory and promising for future applications of the estimator.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    An adaptive freeway traffic state estimator and its real-data testing-part II: adaptive capabilities


    Contributors:
    Wang, Y. (author) / Papageorgiou, M. (author) / Messmer, A. (author)


    Publication date :

    2005-01-01


    Size :

    525418 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English