Impacts of Private Autonomous and Connected Vehicles on Transportation Network Demand in the Triangle Region, North Carolina

Abstract

Autonomous and connected vehicle technologies have the potential to bring profound changes in travel behavior and transportation network performance with moderate to significant market penetration rates (MPRs) within the next few decades. To better understand the long-term impacts of these technologies, this study predicts the network-level effects of privately owned autonomous vehicles (AVs) and connected and autonomous vehicles (CAVs) for the Triangle Region, North Carolina, in the year 2045. Market penetration scenarios of personal AVs and CAVs along with results from microscopic mixed-traffic simulations and travel behavior assumptions are incorporated into a regional travel demand model. Results indicate that a 75% MPR of personal AVs deteriorates the performance of the network, leading to a 5.4% increase in vehicle-hours traveled, and a 17.2% increase in hours of delay. The opposite holds for private CAV adoption, which is found to result in higher peak-period link speed and less congestion. The results of this research help planners and engineers to make informed transportation planning decisions and work toward harnessing the benefits of these technologies while minimizing any negative impacts.