Influence of Autonomous Vehicles on Freeway Traffic Performance for Undersaturated Traffic Conditions

Autonomous vehicles (AVs) are smart driving technology that is expected to alter the perception of transportation. The purpose of this study is to evaluate the impacts of AVs on freeway traffic performance at different percentages of AVs ranging from 0% to 100% and at two different undersaturated traffic volume levels with demand to capacity ratios of 0.6 and 0.8. The well-known VISSIM software was used to develop a microsimulation model to evaluate different scenarios that represent different market penetration rates of AVs and different demand to capacity ratios. The results showed that the minimum improvement was at 5% AVs and 0.6 demand to capacity ratio and the maximum improvement was achieved at 100% AVs and 0.8 demand to capacity ratio. The increase in the average speed ranges from about 5% to about 15%, the reduction in travel time ranges from about 1% to about 12% and the delay reduction is about 18% to about 97%. The improvement in traffic performance when AVs market penetration rates increases from 0% to 100% is attributed to the fact that the conventional vehicles (CVs) are replaced by AVs that can travel with higher constant speed and with a smaller time headway. Statistical t-test was carried out to examine the statistical significance of the difference between scenarios’ average speeds and between the average speed of both AVs and CVs. The test revealed that there average speed values of AVs are significantly higher than CVs values for all AVs market penetration rates at demand to capacity ratios of 0.6 and 0.8. Because at these demand to capacity ratios the congestion is low. Thus, AVs can travel freely with speeds significantly higher than CVs. Keywords: Autonomous vehicles, Freeway performance, Conventional vehicles, Average speed, Travel time, Delay