Our industry partner TomTom is one of the largest routing providers. While they already have sophisticated solutions for individual routing with petrol-powered cars, TomTom is interested in improving their service for electric vehicles. Their software is used in built-in car navigation systems as well as in apps for smart devices.
TomTom currently has a prototype implementation for computing and visualizing the reachable area, but there is room for improvement. For example, this prototype can compute the exact polygon (see the figures below), but this computation is very slow. They also have a much faster implementation that computes a simplified polygon with less precision, i.e., it may mark points as reachable that actually cannot be reached without charging.
Our goal is to find a suitable middleground between efficiency, precision, and "beauty" for the range visualization problem. On the one hand, this requires lots of domain knowledge on routing, such as the employed power consumption model. On the other hand, given the large underlying graph that models the street network, efficient algorithms and a suitable implementation are needed. Visualizations of the reachable area for a given EV. Finally, there's the human interaction aspect: How do people want to use these visualizations and how can we support that best? Which visualizations look good and inspire confidence?