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Route optimization for energy efficient airport shuttle operations – A case study from Dallas Fort worth International Airport

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  • Sigler, Devon
  • Wang, Qichao
  • Liu, Zhaocai
  • Garikapati, Venu
  • Kotz, Andrew
  • Kelly, Kenneth J.
  • Lunacek, Monte
  • Phillips, Caleb

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.

Suggested Citation

  • Sigler, Devon & Wang, Qichao & Liu, Zhaocai & Garikapati, Venu & Kotz, Andrew & Kelly, Kenneth J. & Lunacek, Monte & Phillips, Caleb, 2021. "Route optimization for energy efficient airport shuttle operations – A case study from Dallas Fort worth International Airport," Journal of Air Transport Management, Elsevier, vol. 94(C).
    • Handle: RePEc:eee:jaitra:v:94:y:2021:i:c:s0969699721000600
    DOI: 10.1016/j.jairtraman.2021.102077
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    References listed on IDEAS

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    Cited by:

    1. Liu, Zhaocai & Wang, Qichao & Sigler, Devon & Kotz, Andrew & Kelly, Kenneth J. & Lunacek, Monte & Phillips, Caleb & Garikapati, Venu, 2023. "Data-driven simulation-based planning for electric airport shuttle systems: A real-world case study," Applied Energy, Elsevier, vol. 332(C).
    2. Ma, Jiaxin & Chen, Xumei & Xing, Ziwen & Zhang, Yixin & Yu, Lei, 2023. "Improving the performance of airport shuttle through demand-responsive service with dynamic fare strategy considering mixed demand," Journal of Air Transport Management, Elsevier, vol. 112(C).
    3. Ming Wei & Congxin Yang & Tao Liu, 2022. "An Integrated Multi-Objective Optimization for Dynamic Airport Shuttle Bus Location, Route Design and Departure Frequency Setting Problem," IJERPH, MDPI, vol. 19(21), pages 1-20, November.

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