Route planning for electric vehicle efficiency using the Bellman-Ford algorithm on an embedded GPU

Traditional route planning algorithms, such as Dijkstra or A∗, are efficient in their execution due to low computational complexity. With the rise in popularity of electric vehicles, which have the capability of recharging their batteries while driving, energy costs to traverse road segments can now be negative values. Dijkstra or A∗ cannot process negative edge weights. This work presents the use of the Bellman-Ford algorithm to plan driving routes based on energy efficiency. To overcome the increased computational complexity and ensure reasonable processing speeds this work uses an embedded graphical processing unit and a parallel implementation of Bellman-Ford on an embedded GPU system. This method allows routes to be plotted with considerable reductions in energy requirements, while maintaining the performance of traditional route planning programs.