Abstract: In some embodiments, an electronic device displays suggested routes based on the characteristics of respective vehicles. In some embodiments, an electronic device receives data for respective vehicles from a source external to the electronic device. In some embodiments, an electronic device anonymizes a vehicle identifier and determines customized suggested routes using the anonymized vehicle identifier. In some embodiments, Starting Charge Maps and/or Buffer Maps are generated and/or utilized for route generation or suggestion.

Abstract: A vehicle path routing method is disclosed for determining a lowest-cost path from a source to a destination. A graph representing a road network includes vertices and edges between vertices. Vertices in the graph represent locations and edges represent paths between locations. Edge weights represent costs, such as travel times and energy consumptions for travel along edges of the graph. Significantly, edge weights are represented as probability distributions. The routing method partitions the edges into multiple tiers, for which convolutions of probability distributions can and cannot be feasibly replaced with functional approximations. A Dijkstra search of the graph from a vehicle origin to a vehicle destination computes, for vertices along a path, convolutions of distributions and sums of functional approximations.

Abstract: A method for stochastic electrical vehicle route planning associates weights with road segments, where the weights are probability distributions representing travel time along the segments. Weights representing energy consumption along the segments may be represented as a probability distribution or a deterministic value representing an expectation of a distribution. The method involves performing a Dijkstra search on the road network graph from the vehicle origin to the vehicle destination, where the Dijkstra search computes for each vertex along a path in the network from the vehicle origin to the vehicle destination a convolution of edge weights along the path. The Dijkstra search also includes computing and propagating along the path labels representing the tradeoffs between charging times and total travel-time.