Optimization of Lateral Wandering of Automated Vehicles to Reduce Hydroplaning Potential and to Improve Pavement Life

Abstract

The deployment of automated vehicles (AVs) has many potential benefits, such as reductions in congestion and emissions, and safety improvements. However, two notable aspects of AVs are their impact on roadway hydroplaning and pavement life. Since most AVs are programmed to follow a set path and maintain a lateral position in the center of the lane, over time, significant rutting will occur in asphalt surfaced pavements. This study measured AV lateral wandering patterns and compared them with human driven vehicles. Both wandering patterns could be modeled with a normal distribution but have significantly different standard deviations. AVs have a standard deviation for the lateral traffic wander pattern at least three times smaller than human driven vehicles. The influences of AVs with smaller lateral wandering on pavement rutting and fatigue life were analyzed with the Texas Mechanistic-Empirical Flexible Pavement Design system. The research discovered that AVs would shorten pavement fatigue life by 20%. Additionally, pavement rut depths (RD) increased by 13% and reached critical values of the RD 30% earlier. Deeper ruts formed more quickly leading to thicker water films on wet roads, and consequently, a much higher risk of hydroplaning. The research also calculated maximum tolerable RDs at different hydroplaning speeds. AVs have a much smaller tolerable RD human driven vehicles because of a greater water film in the rutted wheel path. This research thus proposed an optimal AV lateral wandering pattern: a uniform distribution. A uniformly distributed lateral wandering pattern for AVs prolongs pavement fatigue life, reduces pavement RD, and decreases hydroplaning potential.