Vehicle reidentification is the process of tracking a vehicle along a highway as it crosses detection stations. Inductive loop detectors are by far the most widely deployed vehicle detectors. In the present work, vehicle reidentification is performed by combining vehicle-specific information (length and electromagnetic signatures) and some contextual information (lane, speed, and time) to form a decision tree. This approach provides a specific decision tree for tracking vehicles along each highway section. After training, the decision tree successfully classified about 95% of the unseen test records—a significant improvement relative to the literature and our own previous work on the same data. This success rate has been consistently obtained from two data sets: one consisting only of passenger vehicles and another consisting of a representative traffic mix.


    Zugriff

    Download

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Using Decision Trees to Improve the Accuracy of Vehicle Signature Reidentification


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Tawfik, Ahmed Y. (Autor:in) / Abdulhai, Baher (Autor:in) / Peng, Aidong (Autor:in) / Tabib, Seyed M. (Autor:in)


    Erscheinungsdatum :

    01.01.2004




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Using Decision Trees to Improve the Accuracy of Vehicle Signature Reidentification

    Tawfik, A. Y. / Abdulhai, B. / Peng, A. et al. | British Library Conference Proceedings | 2004


    New Inductive Signature Method for Vehicle Reidentification

    National Research Council (U.S.) | British Library Conference Proceedings | 2005


    Deconvolution of Vehicle Inductance Signature for Vehicle Reidentification

    National Research Council (U.S.) | British Library Conference Proceedings | 2005


    Vehicle Reidentification using multidetector fusion

    Sun, C.C. / Arr, G.S. / Ramachandran, R.P. et al. | IEEE | 2004