A Review of Vehicle Longitudinal Speed Control in Autonomous Driving
Main Article Content
Keywords
autonomous driving vehicles, longitudinal control, control method, model predictive control
Abstract
With the continuous development of the automotive industry and intelligent transportation technologies, vehicles are gradually moving toward unmanned operation. Within this context, longitudinal control, which mainly focuses on regulating speed, acceleration, and braking, has become a core component of intelligent driving systems and has attracted significant attention. In recent years, various approaches have been proposed in both academia and industry; however, existing studies still lack systematic reviews and comprehensive classifications, limiting the overall understanding of their characteristics and applications. To address this gap, this paper provides a systematic review of longitudinal control methods for autonomous vehicles. These methods are categorized into three groups: rule-based control, optimization-based control, and learning-based control. This review summarizes the state of the art, highlights the strengths and limitations of existing methods, and provides a reference framework and potential directions for future research and applications.
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