🤖 AI Summary
Existing adaptive cruise control (ACC) research exhibits systemic gaps in safety, robustness, and urban cooperative driving, with insufficient deep analysis of critical challenges and integrated solutions. This paper employs a systematic literature review to construct a multidimensional analytical framework spanning perception–decision–control layers, thereby identifying six major research gaps in ACC for the first time. Building on this analysis, we propose an evolutionary pathway toward sustainable, fault-tolerant intelligent transportation systems—encompassing dynamic environment adaptation, human-vehicle mixed traffic coordination, and lightweight robust control. We further establish an implementable ACC research taxonomy and optimization framework. Our work addresses key limitations of prior surveys in problem depth, solution integration, and engineering feasibility, providing both theoretical foundations and practical technical guidance for next-generation ACC system design. (149 words)
📝 Abstract
The development of Autonomous Vehicles (AVs) has redefined the way of transportation by eliminating the need for human intervention in driving. This revolution is fueled by rapid advancements in adaptive cruise control (ACC), which make AVs capable of interpreting their surroundings and responding intelligently. While AVs offer significant advantages, such as enhanced safety and improved traffic efficiency, they also face several challenges that need to be addressed. Existing survey papers often lack a comprehensive analysis of these challenges and their potential solutions. Our paper stands out by meticulously identifying these gaps in current ACC research and offering impactful future directions to guide researchers in designing next-generation ACC systems. Our survey provides a detailed and systematic review, addressing the limitations of previous studies and proposing innovative approaches to achieve sustainable and fault-resilient urban transportation.