Impact of Autonomous and Human-Driven Trucks on Flexible Pavement Design

Abstract

Truck platooning with autonomous and connected vehicles has several advantages compared with traditional trucking. Platooning improves overall road safety and reduces fuel consumption by up to 15%. This is a result of the advanced control systems and high steering accuracy of autonomous vehicles. These advanced control systems present an opportunity to pavement design engineers, as the lateral positions of the vehicles could be altered to create less damaging loading scenarios. This study introduces an expected response framework to quantify the impact of lateral position on pavement performance. Using the expected response framework, any mixture of human-driven and autonomous vehicles can be analyzed by characterizing lane position as a mixture probability distribution instead of point loads. Pavement damage can subsequently be computed by using the expectation of the responses. This approach requires little computational effort and is easily incorporated in any mechanistic–empirical design or optimization framework. The approach is illustrated by analyzing four flexible pavement sections using the expected response framework. Compared with human-driven trucks, optimized lateral position could decrease pavement damage by 40%. Channelized traffic on the other hand could increase pavement damage by 60%. A simplified approach is introduced alongside a reliability analysis and fragility curves for various pavement structures. Distributed traffic was found to have the lowest probability of failure among all traffic scenarios.