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

dc.contributor.authorRamesh, G.
dc.contributor.authorKiran Raj, K.M.
dc.contributor.authorAbhishek
dc.contributor.authorDevadiga, M.T.
dc.contributor.authorManohara, M.
dc.contributor.authorBoloor, S.
dc.contributor.authorSowjanya, N.
dc.date.accessioned2026-02-06T06:33:28Z
dc.date.issued2025
dc.description.abstractVehicle 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. © 2025 IEEE.
dc.identifier.citation2025 International Conference on Artificial Intelligence and Data Engineering, AIDE 2025 - Proceedings, 2025, Vol., , p. 466-471
dc.identifier.urihttps://doi.org/10.1109/AIDE64228.2025.10987533
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/28680
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectAdaptive Cruise Control (ACC)
dc.subjectAdvanced Driver Assistance Systems (ADAS)
dc.subjectAutonomous Emergency Braking (AEB)
dc.subjectMachine Learning
dc.subjectRoad Safety
dc.subjectSensor Technology
dc.subjectV2X Communication
dc.subjectVehicle Collision Avoidance Systems (VCAS)
dc.titleA Survey on Vehicle Collision Avoidance Systems: Innovations, Challenges, and Future Prospects

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