Path prediction is the only way that an active safety system can predict a driver's intention. In this paper, a model-based description of the traffic environment is presented - both vehicles and infrastructure - in order to provide, in real time, sufficient information for an accurate prediction of the ego-vehicle's path. The proposed approach is a hierarchical-structured algorithm that fuses traffic environment data with car dynamics in order to accurately predict the trajectory of the ego-vehicle, allowing the active safety system to inform, warn the driver, or intervene when critical situations occur. The algorithms are tested with real data, under normal conditions, for collision warning (CW) and vision-enhancement applications. The results clearly show that this approach allows a dynamic situation and threat assessment and can enhance the capabilities of adaptive cruise control and CW functions by reducing the false alarm rate.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Sensor Fusion for Predicting Vehicles' Path for Collision Avoidance Systems


    Contributors:


    Publication date :

    2007-09-01


    Size :

    547375 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Sensor fusion for predicting vehicles' path for collision avoidance systems

    Polychronopoulos, A. / Tsogas, M. / Amditis, A.J. et al. | Tema Archive | 2007



    Collision Avoidance in Vehicles Using Ultrasonic Sensor

    Bhuvaneswary, N. / Jayapriya, V. / Mounika, V. et al. | Springer Verlag | 2021


    Converging path collision avoidance

    GOUDY ROY / PROBERT NEAL / CHAMBERS JEREMY et al. | European Patent Office | 2019

    Free access

    Collision avoidance among vehicles

    LANGGOOD JOHN K / LEWIS THOMAS F / REINBERG KEVIN M et al. | European Patent Office | 2016

    Free access