Route optimization for energy efficient airport shuttle operations – A case study from Dallas Fort worth International Airport. (July 2021)

• Record Type: Journal Article
• Authors: Sigler, Devon; Wang, Qichao; Liu, Zhaocai; Garikapati, Venu; Kotz, Andrew; Kelly, Kenneth J.; Lunacek, Monte; Phillips, Caleb
• Is Part Of: Journal of air transport management. Volume 94(2021)
• Publication Date: 2021-07
• Subjects: Air travel -- Bus schedule optimization -- Energy efficiency -- Airport shuttles -- Discrete event simulation; Airlines -- Management -- Periodicals; Aeronautics, Commercial -- Management -- Periodicals; 387.7068
• DOI: 10.1016/j.jairtraman.2021.102077
• Languages: English
• ISSNs: 0969-6997

Abstract

Abstract: The objective of this research is to reduce energy consumption from intra airport shuttle operations by optimizing routes and schedules, without compromising on passenger travel experience. To achieve this objective, we propose an optimization model that generates optimal airport shuttle routes for a given set of constraints and a discrete-event simulator that evaluates the optimal shuttle routes in a stochastic environment to understand the tradeoffs between the amount of time passengers wait for shuttles, and shuttle energy consumption. The proposed optimization model and stochastic simulation are tested using shuttle route data provided by the Dallas Fort Worth International Airport. Results indicate that optimized routes can lead to a 20% energy reduction in shuttle operations with a modest 2-min increase in average shuttle wait times. The optimization model and simulator presented here are designed to be generalizable and can be adapted to optimize shuttle operations at any major airport. Highlights: This research effort contributes to the state-of-practice on airport shuttle route optimization by: Focusing on within airport shuttle operations as opposed to shuttle operations connecting city centers and airports. Providing a novel mathematical model for selecting routes, shuttles per route, and route shuttle size. Integrating optimization with discrete-event simulation to explore the tradeoff between passenger travel time and energy use.