A Modular and Layered Perspective on Lateral Vehicle Motion Control: A Survey for ADAS and Autonomous Driving Systems

Abstract

This paper reviews modular and layered approaches to lateral vehicle motion control for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) applications. Motivated by the growing need for scalable, reusable, and robust control architectures, the study systematically analyzes how existing academic and industrial contributions organize lateral control functionalities across four key domains: State and Parameter Estimation, Motion Limit Estimation, High-Level Control, and Low-Level Control. Special emphasis is placed on industry-backed implementations and emerging standardization efforts such as SAE J3131 and AUTOSAR. The review highlights practical advantages associated with functional decomposition, real-time constraint integration, and estimation-enabled control feasibility. By synthesizing insights from diverse sources, the work provides an architectural perspective that complements algorithmic advancements and supports scalable system integration for future ADAS and automated driving platforms.