The commercial application of automation technology in passenger and freight transport will bring positive revolutionary changes in transportation mobility. Despite having more advantages, automation in trucking technology has some detrimental effects on the performance of asphalt pavement and highway safety. This study focuses on optimization of asphalt pavement distresses and prediction of rutting induced traffic safety factors for movement of autonomous trucks. This study optimizes the asphalt concrete (AC) pavement distresses by devising traffic input in Mechanistic-Empirical Pavement Design Software, AASHTOWare. An increase in pavement distresses was observed for a small increase in the standard deviation of wheel wander, uniform distribution of truck traffic loading, and equal distribution of vehicle positioning on the road lanes. Permanent deformation of the asphalt concrete layer for roads (PEDRO) model was incorporated to predict AC pavement rutting for a typical pavement section. Hydroplaning speed and skid resistance as traffic safety factors were evaluated from widely accepted empirical equations for the induced rutting. A standard tire rather than a truck tire was considered due to its high susceptibility to traffic safety. A graphical relationship has been proposed to obtain a design threshold value for hydroplaning speed, water film depth and autonomous truck speed. An attempt was made to improve pavement performance by increasing frequency of truck load in low-temperature period of a day.