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The pit stop problem: how to plan your next road trip

Authors:

Sreenivas Gollapudi,

Kostas Kollias,

Debmalya PanigrahiAuthors Info & Claims

SIGSPATIAL '22: Proceedings of the 30th International Conference on Advances in Geographic Information Systems

Article No.: 47, Pages 1 - 9

https://doi.org/10.1145/3557915.3560982

Published: 22 November 2022 Publication History

Abstract

Many online trip planning and navigation software need to routinely solve the problem of deciding where to take stops during a journey for various services such as refueling (or EV charging), rest stops, food, etc. The goal is to minimize the overhead of these stops while ensuring that the traveller is not starved of any essential resource (such as fuel, rest, or food) during the journey. In this paper, we formally model this problem and call it the pit stop problem. We design algorithms for this problem under various settings: single vs multiple types of stops, and offline vs online optimization (i.e., in advance of or during the trip). Our algorithms achieve provable guarantees in terms of approximating the optimal solution. We then extensively evaluate our algorithms on real world data and demonstrate that they significantly outperform baseline solutions.

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Cited By

Gesang ZYu BZhu JJiang W(2025)Adaptive path planning for arriving at firelines in dynamic wildfires and complex landscapesSafety Emergency Science10.26599/SES.2025.9590004Online publication date: Feb-2025
https://doi.org/10.26599/SES.2025.9590004
Jiang WZhou JZhu JSu GWang F(2025)FRI: a firefighter risk index using spatiotemporal modelling of wildfire spread and individual travelInternational Journal of Disaster Risk Reduction10.1016/j.ijdrr.2024.105151(105151)Online publication date: Jan-2025
https://doi.org/10.1016/j.ijdrr.2024.105151

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cover image ACM Conferences

SIGSPATIAL '22: Proceedings of the 30th International Conference on Advances in Geographic Information Systems

November 2022

806 pages

ISBN:9781450395298

DOI:10.1145/3557915

General Chairs:
Matthias Renz
Kiel University, Germany
,
Mohamed Sarwat
Wherobots Inc. / Arizona State University

Copyright © 2022 Owner/Author.

This work is licensed under a Creative Commons Attribution International 4.0 License.

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

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Published: 22 November 2022

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SIGSPATIAL '22: The 30th International Conference on Advances in Geographic Information Systems

November 1 - 4, 2022

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Cited By

Gesang ZYu BZhu JJiang W(2025)Adaptive path planning for arriving at firelines in dynamic wildfires and complex landscapesSafety Emergency Science10.26599/SES.2025.9590004Online publication date: Feb-2025
https://doi.org/10.26599/SES.2025.9590004
Jiang WZhou JZhu JSu GWang F(2025)FRI: a firefighter risk index using spatiotemporal modelling of wildfire spread and individual travelInternational Journal of Disaster Risk Reduction10.1016/j.ijdrr.2024.105151(105151)Online publication date: Jan-2025
https://doi.org/10.1016/j.ijdrr.2024.105151

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