Vehicle Collision Avoidance Systems (VCAS) enhance road safety by enabling vehicles to autonomously detect and respond to potential hazards using technologies such as radar, LiDAR, cameras, V2X communication, and machine learning algorithms. Key features like Adaptive Cruise Control, Autonomous Emergency Braking, and Lane Departure Warning help prevent accidents and improve driver assistance. Despite challenges like sensor limitations in adverse conditions, communication delays, and cybersecurity risks, advancements in sensor accuracy, decision-making algorithms, and edge computing continue to drive innovation. This paper highlights the importance of technological improvements, regulatory frameworks, and system interoperability in advancing VCAS adoption and achieving safer, autonomous transportation.


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    Title :

    A Survey on Vehicle Collision Avoidance Systems: Innovations, Challenges, and Future Prospects


    Contributors:


    Publication date :

    2025-02-06


    Size :

    476903 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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