Enabling Safe Co‐Existence of Connected/Autonomous Cars and Road Users Using Machine Learning and Deep Learning Algorithms
深度学习
计算机科学
人工智能
算法
机器学习
作者
Juan Contreras‐Castillo,Sherali Zeadally,Juan Antonio Guerrero Ibáñez,Pedro C. Santana-Mancilla,Iyad Katib
出处
期刊:Transactions on Emerging Telecommunications Technologies日期:2025-03-01卷期号:36 (3)
标识
DOI:10.1002/ett.70103
摘要
ABSTRACT As the number of vehicles increases in cities, traffic accidents continue to rise. Connected and Autonomous Cars have become important because they aim to be safer than non‐intelligent vehicles. Connected and Autonomous Cars can reduce up to 90% of vehicular accidents caused by human drivers. Connected and Autonomous Cars must interact safely with other cars and Vulnerable Road Users because the latter are more susceptible to injury after a road collision. Thus, careful interaction between Connected and Autonomous Cars and Vulnerable Road Users is necessary to create a safer road ecosystem for Vulnerable Road Users. We discuss several interaction challenges that must be addressed between Connected and Autonomous Cars and Vulnerable Road Users, and we propose solutions to each challenge to achieve the safe coexistence of both Connected and Autonomous Cars and Vulnerable Road Users.