Review of Road Surface Unevenness Recognition for Vehicle Motion Control

doi:10.3901/JME.260443

Abstract

Abstract: Vehicle motion control requires real-time information on road surface unevenness to adjust control strategies, ensuring the safety, comfort, and efficiency of vehicle operation. Road surface unevenness is characterized by randomness and high uncertainty. Traditional methods based on time-domain and frequency-domain analysis of vibration signals are limited in their ability to provide accurate and predictable recognition results. With the development of vehicle intelligence, non-contact sensors such as cameras and Li DAR have enriched the sources of information for unevenness recognition. The application of artificial intelligence(AI) algorithms has further improved the precision of identification. This study focuses on road surface unevenness recognition for vehicle motion control, systematically analyzing the development, principles, technical challenges, and applications of three major technical approaches:contact-based methods, non-contact-based methods, and multi-source information fusion. Furthermore, by integrating the development trends of AI, the study provides insights into the future of pan-scenario, refined, and highly reliable road surface unevenness perception technologies.

Key words: vehicle engineering, motion control, road unevenness, identification algorithm

CLC Number:

TG156

XIONG Lu, HU Xuge, Lü Haoran, TANG Chen. Review of Road Surface Unevenness Recognition for Vehicle Motion Control[J]. Journal of Mechanical Engineering, 2026, 62(8): 139-156.

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