Ramesh, G.Kiran Raj, K.M.AbhishekDevadiga, M.T.Manohara, M.Boloor, S.Sowjanya, N.2026-02-0620252025 International Conference on Artificial Intelligence and Data Engineering, AIDE 2025 - Proceedings, 2025, Vol., , p. 466-471https://doi.org/10.1109/AIDE64228.2025.10987533https://idr.nitk.ac.in/handle/123456789/28680Vehicle 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.Adaptive Cruise Control (ACC)Advanced Driver Assistance Systems (ADAS)Autonomous Emergency Braking (AEB)Machine LearningRoad SafetySensor TechnologyV2X CommunicationVehicle Collision Avoidance Systems (VCAS)