Road Surface Status Recognition and Estimation: State-of-the-art Review and Research Perspectives

Accurate recognition and estimation of road state in real-time is an important prerequisite for vehicle driving safety, transient handling stability, ride comfort, and other performance. In order to grasp the main development trend in this field systematically and in a timely manner, in this paper, the latest research progress of the identification and estimation methods of two key road state parameters, road roughness and road surface adhesion coefficient, is comprehensively reviewed. Firstly, according to the difference in basic theory and implementation principle, the research progress of road roughness recognition and estimation methods is reviewed from three aspects: section class method, system response-based method, and machine learning-based method. Then, the research progress of road surface adhesion coefficient recognition and estimation methods is summarized from four aspects: cause-based method, effect-based method, data-driven method, and multi-method fusion method. Finally, the advantages and disadvantages, technical challenges, and future development trends of different road recognition and estimation methods are analyzed.