Abstract

Unmanned driving is the direction of future development in the field of transportation. The development of unmanned driving will cause sensor monitoring and machine control to play a greater role. According to road roughness data collected by unmanned ground vehicles and vehicle dynamics, it is of great significance to establish a vehicle–pavement coupling model to analyze and guide driving comfort, cargo safety, and road friendliness. Pavement roughness is the main external excitation in the process of driving a vehicle. Therefore, a three-dimensional (3D) model of pavement roughness was constructed based on fractal theory and fractal interpolation. According to tire–pavement contact characteristics, a newly rerevised 3D flexible roller contact tire model was proposed. On this basis, vehicle vibration dynamics models for a car and a truck were established. The traditional point contact model was used to verify the model. Based on the comfort threshold of a passenger, the cargo vibration threshold, and the dynamic load coefficient (DLC) threshold of the truck, the conditions for ride comfort of an unmanned ground vehicle were expounded. The results showed that, compared with an ideal fully flat road surface, pavement roughness had a great impact on vehicle vibration. The 3D model of pavement roughness generated had high accuracy. The vehicle–pavement coupling model based on tire–pavement 3D contact under 3D pavement roughness excitation was correct. The proposed model can calculate vibration characteristics of passengers and cargo and the DLC of wheels in real time. For different types of vehicles and different roughness levels of pavement, different speed thresholds were given to ensure driving comfort, cargo safety, and road friendliness. Driving speed and each evaluation index met the Fourier function relationship. Partial correlation analysis showed that in order to ensure the comfort of passengers, more attention should be paid to pavement roughness, and for cargo safety and road friendliness, pavement roughness and vehicle speed should be considered at the same time. The results provide theoretical suggestions for the comfortable driving of future unmanned ground vehicles.

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