Optimal clustering analysis for airport parking

Abstract

Air travelers are often hurried and at risk of missing their flights. Many of them are quite sensitive to service quality and overall travel times. In larger airports the demand for parking spaces forces many users to park quite far from passenger terminals. Thus, it is desirable to allocate available parking spaces at any given time in ways that minimize the users' access distances. Although the major layout and allocation decisions for airport parking are highly constrained by available land and physical parking infrastructure, a well-designed parking clustering scheme based on expected parking durations could assist airport operators in effectively allocating limited space, which minimizes the travelers' average access distances between parking facilities and an airport terminal by employing grouping concepts based on the expected parking time durations of vehicles. In subdividing the available parking facilities, the boundaries between different user groups (e.g., short, medium, and long term) are optimized based on the distributions of (1) expected vehicle dwell times and (2) available parking capacity at various access distances from airport terminals. Even with only two clusters (e.g., short-term and long-term parking), results show that average access distances from parking spaces to terminals can be reduced by 25–44%. Although additional subdivisions of the available parking areas can yield additional savings of travelers’ time and access distances, the marginal benefits decrease rapidly as the number of subdivisions grows.