Quantifying the Benefits of Autonomous Vehicles to Roadway Infrastructure Efficiency

Compared with human-driven vehicles, Au-tonomous Vehicles (AVs) have the potential to improve efficiency, safety, and sustainability. Although recent studies have focused on the technological and operational sides of AVs, there is a paucity of research on the quantification of AVs benefits to the roadway infrastructure efficiency. This paper quantifies the infrastructure efficiency improvement as the increase in the asset value. In addition to commonly used historical costs and physical condition, this paper employs a utility-based valuation methodology to consider functionality and overall asset utilization, which are impacted by the features of AVs. A case study is performed using a real expressway segment in Austin, Texas. Monte Carlo simulation and sensitivity analysis are conducted to model the uncertainties of crash rate, and to investigate the marginal impact of each performance measure. Results from case study suggest that AVs are capable of increasing the asset value of a roadway, even after the incorporation of crash rate uncertainties. The findings provide insights on how asset value of roadway infrastructures will be changed with more AVs on the road.