Throughput Capacity Comparison for Airport Pickup and Dropoff Facilities

Abstract

An airport serves as an interface between ground and air transportation; the efficient processing of ground transportation arrivals and departures is, therefore, an important part of airport operations. At many airports, the current pickup and dropoff locations for taxis and other passenger cars are along the terminal curb or in existing parking facilities, and many of these pickup and dropoff facilities suffer from excessive congestion. In addition, in recent years there has been growth in the use of on-demand ground transportation to and from airports, with the increased adoption of ride-hailing services, resulting in increased congestion. Since most airports are severely space constrained, there is a need to consider pickup and dropoff facilities that are more efficient (in vehicle throughput per unit space) than terminal curbs. In this paper we compare the throughput capacities of different pickup and dropoff facility layouts. We take into account the effect of the facility layout and operational rules on conflicts between the movements of different vehicles, the resulting delays in the movements of vehicles, as well as the spatial requirements of different layouts. We demonstrate the impact of mean service times, variability in service times and vehicle movement times, and operational rules on the relative throughput capacities of different facility layouts.

Mitigating Landside Congestion at Airports through Predictive Control of Diversionary Messages

“…Two papers from this line of work are more directly related to our specific problem. One studied how advance signs (albeit for airlines, not diversions) guide and improve vehicle search times [24] and the other compared the throughput characteristics of pickup to dropoff facilities (of which Arrivals and Departures are canonical examples) [25]. This body of work is useful for developing context and understanding the general problems and opportunities to improve, but they have no notion of optimization or control that we can use in a computational framework.…”

Travel Mode Choice Behavior for High-Speed Railway Stations Based on Multi-Source Data

“…Gege et al ( 6 ) analyzed spatial and temporal distributions of origin–destination (OD) of travelers connecting to airports and train stations in second-tier cities in China. Studies related to service capacity assessments of feeder facilities have also gradually emerged, including capacity analyses of connection facilities ( 7 ), passenger flow predictions, and anomaly detection ( 8 ). HSR stations in China carry far more passengers than airport stations.…”