Multiple vehicle cooperation and collision avoidance in automated vehicles : Survey and an AI‑enabled conceptual framework

• Main Authors: Abu Jafar, Md Muzahid, Syafiq Fauzi, Kamarulzaman, Rahman, Md Arafatur, Murad, Saydul Akbar, Kamal, Md Abdus Samad, Alenezi, Ali H.
• Format: Article
• Language: English
• Published: Nature Research 2023
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/37568/1/Multiple%20vehicle%20cooperation%20and%20collision%20avoidance%20in%20automated%20vehicles_survey%20and%20an%20AI-enabled.pdf; http://umpir.ump.edu.my/id/eprint/37568/; https://doi.org/10.1038/s41598-022-27026-9; https://doi.org/10.1038/s41598-022-27026-9
• Institution: Universiti Malaysia Pahang

Prospective customers are becoming more concerned about safety and comfort as the automobile industry swings toward automated vehicles (AVs). A comprehensive evaluation of recent AVs collision data indicates that modern automated driving systems are prone to rear-end collisions, usually leading to m...