Reducing Waiting Times at Charging Stations with Adaptive Electric Vehicle Route Planning
Sven Schoenberg, Falko Dressler

TL;DR
This paper presents an adaptive route planning strategy for electric vehicles that significantly reduces waiting times at charging stations by using precomputed shortest paths and a database to estimate station wait times, improving long-distance travel efficiency.
Contribution
The paper introduces a novel multi-criterion shortest-path algorithm with a charging station database to predict wait times, enhancing route planning for electric vehicles.
Findings
Reduces average waiting times at charging stations by up to 97%.
Substantially decreases total travel time even with partial adoption of the approach.
Demonstrates effectiveness through extensive simulation experiments.
Abstract
Electric vehicles are becoming more popular all over the world. With increasing battery capacities and a growing fast-charging infrastructure, they are becoming suitable for long distance travel. However, queues at charging stations could lead to long waiting times, making efficient route planning even more important. In general, optimal multi-objective route planning is extremely computationally expensive. We propose an adaptive charging and routing strategy, which considers driving, waiting, and charging time. For this, we developed a multi-criterion shortest-path search algorithm using contraction hierarchies. To further reduce the computational effort, we precompute shortest-path trees between the known locations of the charging stations. We propose a central charging station database (CSDB) that helps estimating waiting times at charging stations ahead of time. This enables our…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
MethodsEmirates Airlines Office in Dubai
