AI/ML-based services and applications for 6G-connected and autonomous vehicles

Abstract

AI and ML emerge as pivotal in overcoming the limitations of traditional network optimization techniques and conventional control loop designs, particularly in addressing the challenges of high mobility and dynamic vehicular communications inherent in the domain of connected and autonomous vehicles (CAVs). The survey explores the contributions of novel AI/ML techniques in the field of CAVs, also in the context of innovative deployment of multilevel cloud systems and edge computing as strategic solutions to meet the requirements of high traffic density and mobility in CAV networks. These technologies are instrumental in curbing latency and alleviating network congestion by facilitating proximal computing resources to CAVs, thereby enhancing operational efficiency also when AI-based applications require computationally-heavy tasks. A significant focus of this survey is the anticipated impact of 6G technology, which promises to revolutionize the mobility industry. 6G is envisaged to foster intelligent, cooperative, and sustainable mobility environments, heralding a new era in vehicular communication and network management. This survey comprehensively reviews the latest advancements and potential applications of AI/ML for CAVs, including sensory perception enhancement, real-time traffic management, and personalized navigation.