Study on Vehicle-Road Interaction for Autonomous Driving

Autonomous vehicles (AVs) are becoming increasingly popular, and this can potentially affect road performance. Road performance also influences driving comfort and safety for AVs. In this study, the influence of changes in traffic volume and wheel track distribution caused by AVs on the rutting distress of asphalt pavement was investigated through finite element simulations. A vehicle-mounted three-dimensional laser profiler was used to obtain pavement roughness and texture information. The vehicle vibration acceleration was obtained through vehicle dynamics simulations, and the skid resistance indexes of 20 rutting specimens were collected. The results showed that an increase in traffic volume caused by the increasing AV traffic accelerated the occurrence of rutting distress; however, the uniform distribution of vehicles at both ends of the transverse direction could prolong the maintenance life of flexible and semi-rigid pavements by 0.041 and 0.530 years, respectively. According to Carsim and Trucksim vehicle simulations and multiple linear regression fitting, the relationship models of three factors, namely speed, road roughness, and comfort, showed high fitting accuracies; however, there were some differences among the models. Among the texture indexes, the arithmetic mean's height (R-a) had the greatest influence on the tire-road friction coefficient; R-a greatly influenced the safe driving of AVs. The findings of this study were used to present a speed control strategy for AVs based on the roughness and texture index for ensuring comfort and safety during automatic driving.

Automated summary

This study investigated the influence of AVs on the rutting distress of asphalt pavement by simulating changes in traffic volume and wheel track distribution. The results showed that increased AV traffic accelerated the occurrence of rutting distress, but a uniform distribution of vehicles at both ends of the transverse direction could prolong the maintenance life of the pavement. The study also found that speed, road roughness, and comfort had high accuracy in predicting the relationship models for AVs, and the arithmetic mean's height had the greatest influence on tire-road friction coefficient.