Spatial behavioral analysis and agent-based modeling of terminal passengers, case-study of San Diego International Airport

Keywords: spatial behavior, time budget, agent-based modeling, traffic flow, airport passengers
Abstract Type: Paper Abstract

Abstract

Terminals are important commercial hubs that provide attractions and services for waiting passengers. Airport operations are expensive and rely on the efficiency of passenger mobility and revenue of in-terminal attractions to maximize profits. Understanding passenger behaviors to optimize airport operations is essential, however, airports possess unique topography in terms of place and interior structure, resulting in difficulties in applying generalized studies. To address this difficulty, the study looks to utilize big data of passengers and flights from San Diego International Airport, alongside agent-based modeling, to simulate activities of waiting passengers compared to airport data of passenger activities. By using validation model techniques, this research aims to provide a methodology of developing agent behavior directly from airport datasets to improve airport terminal flow and reduce costs in constructing future terminals.