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Integrated Route, Charging and Activity Planning for Whole Day Mobility with Electric Vehicles

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Agents and Artificial Intelligence (ICAART 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11352))

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Abstract

Over the last two decades, route planning algorithms have revolutionized the way we organize car travel. The advent of electric vehicles (EVs), however, bring new challenges for travel planning. Because of electric vehicle limited range and long charging times, it is beneficial to plan routes, charging, and activities jointly and in the context of the whole day—rather than for single, isolate journeys as done by standard route planning approaches. In this work, we therefore present a novel approach to solving such a whole day mobility problem. Our method works by first preprocessing an energy-constrained route planning problem and subsequently planning the temporally and spatially constrained activities. We propose both an optimal algorithm for the day mobility planning problem and a set of sub-optimal speedup heuristics. We evaluate the proposed algorithm on a set of benchmarks based on real-world data and show that it is significantly faster than the previous state-of-the-art approach. Moreover, the speedups provide dramatic memory and time improvements with a negligible loss in solution quality.

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Notes

  1. 1.

    https://download.geofabrik.de/europe/germany/bayern.html.

  2. 2.

    The charging station locations are based on http://ev-charging.com.

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Acknowledgments

This research was funded by the European Union Horizon 2020 research and innovation programme under the grant agreement \(N^{\mathrm {\circ }}713864\) and by the Grant Agency of the Czech Technical University in Prague, grant No. SGS16/235/ OHK3/3T/13.

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Correspondence to Michal Štolba .

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Cuchý, M., Štolba, M., Jakob, M. (2019). Integrated Route, Charging and Activity Planning for Whole Day Mobility with Electric Vehicles. In: van den Herik, J., Rocha, A. (eds) Agents and Artificial Intelligence. ICAART 2018. Lecture Notes in Computer Science(), vol 11352. Springer, Cham. https://doi.org/10.1007/978-3-030-05453-3_13

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  • DOI: https://doi.org/10.1007/978-3-030-05453-3_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-05452-6

  • Online ISBN: 978-3-030-05453-3

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