With the development of economy, the road cleaning faces great challenges because the road area keeps increasing and the road types tend to be diversified. Cleaning vehicle is widely used in road surface cleaning, but it is more and more difficult to meet the demand of road surface cleaning only through using a single road surface cleaning method. If the way of manual adjustment of cleaning parameters is adopted, the driver is required to have rich experience. At present, there is an urgent need for a cleaning vehicle that can autonomously adjust cleaning parameters according to the road surface. This study is based on road recognition technology. After the pavement category is reflected by the visual sensor feedback information and the pavement adhesion coefficient, the parameters of the cleaning vehicle are adjusted by the controller to adapt to different roads. Firstly, the vehicle dynamics model is established, and the road adhesion coefficient is estimated by the least square method to realize the accurate identification of the road adhesion coefficient. On this basis, according to the image features of the camera, the visual sensor is used to comprehensively judge the categories of the road surface, to realize the distinction and recognition of the road surface, and control the cleaning parameters of the cleaning vehicle to adjust to a reasonable range to ensure the cleaning effect. The results show that the proposed algorithm can accurately estimate the road adhesion coefficient. At the same time, it can accurately distinguish and recognize dry asphalt pavement, wet asphalt pavement and muddy asphalt pavement, and adjust the cleaning parameters of the cleaning vehicle. The overall cleaning efficiency of the cleaning vehicle has been improved by 7% compared with the cleaning vehicle without the installation of this system.