Fast Exact Shortest Path and Distance Queries on Road Networks with Parametrized Costs

TL;DR

This paper introduces a lightweight, topologically-based method for efficiently answering shortest path and distance queries with parametrized costs on large road networks, outperforming previous approaches.

Contribution

It presents a novel technique that relies solely on network topology to handle dynamic cost changes, enabling faster queries without extensive preprocessing.

Findings

Significantly faster query times on large real-world networks.

Effective handling of changing costs in route planning.

Lightweight preprocessing suitable for large-scale networks.

Abstract

We study a scenario for route planning in road networks, where the objective to be optimized may change between every shortest path query. Since this invalidates many of the known speedup techniques for road networks that are based on preprocessing of shortest path structures, we investigate optimizations exploiting solely the topological structure of networks. We experimentally evaluate our technique on a large set of real-world road networks of various data sources. With lightweight preprocessing our technique answers long-distance queries across continental networks significantly faster than previous approaches towards the same problem formulation.