Evaluating the impact of connected and autonomous vehicles on airport roadway operations

Abstract

The introduction of connected and autonomous vehicles (AVs) offers significant potential to improve the capacity and efficiency of modern transportation systems. Although much of the existing research has concentrated on the beneficial effects of AVs on highway traffic flow and capacity, there has been limited exploration of how AVs might influence airport curbside and internal roadway operations. Therefore, this study is designed to examine and predict the effects of AVs on the operations of airport curbside roadways. To conduct this investigation, a microsimulation method was utilized through VISSIM, incorporating the Wiedmann 74 model to simulate car- following behavior. The parameters for autonomous vehicles were calibrated to meet the Level 4 automation standards established by the Society of Automotive Engineers (SAE). A conceptual curbside network was selected for simulation, with separate lanes designated for AVs and Human-Driven Vehicles (HDVs). Six scenarios were simulated, each representing incremental increases in AV penetration rates from 10% to 50%. The study focused on evaluating improvements in traffic flow metrics, including Maximum Queue Length, Vehicle Delay, and Vehicle Travel Time. Findings from this study indicate that discernible enhancements in curbside traffic flow at airports are only observed once AV penetration levels surpass 35%. Specifically, a significant improvement in traffic flow metrics, such as Maximum Queue Length, Vehicle Delay, and Vehicle Travel Time, was noted when AV penetration levels increased from 35% to 40%. The improvement in traffic flow from AVs can be primarily attributed to their ability to mitigate the stop-and-go nature of traffic which is typically observed in HDVs. Based on these findings, this study recommends simulating traffic flow scenarios with AV penetration levels of 35%, 40%, and 50% under mixed traffic conditions, without segregating lanes for AVs and HDVs to identify the exact optimal AV penetration level for curbside operations at airports.