Unmanned vehicles ensure the vehicle a safe driving without the driver's active control through the computer, sensors and other technical equipment. Among them, the pavement feature has an important influence on the driving speed of the unmanned vehicle and the judgment of the safety space between two vehicles. Therefore, real-time access to the features of the road ahead and timely adjustment of intelligent driving behavior are significant to unmanned driving.Most of the researches nowadays make full use of vehicle sensor technology and environment perception technology. Vehicle sensor is commonly used to collect the features of the road ahead. While in this paper, a new type of pavement characterization is proposed based on the vehicle speed parameters collected by vehicle under the premise of less vehicle sensor, and then the pavement parameters can be estimated. Based on the vehicle dynamics, this paper studies the relationship between vehicle speed and resistance, and obtains the influence of different road characteristics on vehicle speed. According to the change of vehicle state parameters on the same road surface under different driving conditions, the pavement characteristic parameter identification model is established, and the pavement characteristic parameters are deduced. The model is modified by the hardware-in-the-loop simulation platform. Finally, a real vehicle test was carried out to verify the correctness of the model. The experimental results show that the error of the road rolling resistance is less than 1% when the precision of the mining point is more than the decimal point and the time precision is 0.1s and 0.01s. The method of determining the pavement characteristic parameter is accurate. This article joints the car and traffic, and can reduce the use of vehicle sensors, providing a new way of thinking for unmanned research.