Freeway Lane Management Strategy for Autonomous Trucks Considering Pavement Rutting

Abstract

The lateral control mechanism and lateral distribution characteristics of autonomous truck are significantly different from those of human-driven vehicle. To support the evaluation of autonomous truck on road durability and provide instructions for lane planning in human-autonomous hybrid driving environment, this paper investigates freeway lane management considering pavement rutting. Based on freeway naturalistic driving data, lateral distribution characteristics of human-driven truck was extracted. And lateral position distribution mode for autonomous truck based on normal distribution was proposed. Then, three freeway lane management strategies with different lane types were proposed including dedicated lane strategy, mixed-flow lane strategy, dedicated and mixed-flow lane strategy. Based on different lane management strategies and lateral position distribution parameters, traffic volume proportions of human-driven and autonomous truck were calculated from the perspective of balancing rut development. A three-dimensional finite element method (FEM) model was developed to evaluate the asphalt pavement maintenance year. The results showed that dedicated lane width of dedicated lane strategy varies, but the proportions of autonomous truck should be fixed to obtain the lowest asphalt pavement maintenance year. The mixed-flow lane strategy is applicable to all proportions of autonomous truck and results in the highest maintenance year. Besides, the dedicated and mixed-flow lane strategy is suitable for freeway with a high proportion of autonomous truck.