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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