Shortest Path and Distance Queries on Road Networks: An Experimental Evaluation

TL;DR

This paper provides a comprehensive experimental comparison of spatial-coherence-based and vertex-importance-based shortest path algorithms on large-scale road networks, offering practical guidelines for choosing suitable methods based on various performance metrics.

Contribution

It systematically evaluates and compares the two main categories of shortest path algorithms on large real-world networks, addressing previous evaluation gaps and inconsistencies.

Findings

Spatial-coherence-based methods excel in query speed on large networks.

Vertex-importance-based approaches have lower preprocessing times.

Guidelines are provided for selecting algorithms based on network size and application needs.

Abstract

Computing the shortest path between two given locations in a road network is an important problem that finds applications in various map services and commercial navigation products. The state-of-the-art solutions for the problem can be divided into two categories: spatial-coherence-based methods and vertex-importance-based approaches. The two categories of techniques, however, have not been compared systematically under the same experimental framework, as they were developed from two independent lines of research that do not refer to each other. This renders it difficult for a practitioner to decide which technique should be adopted for a specific application. Furthermore, the experimental evaluation of the existing techniques, as presented in previous work, falls short in several aspects. Some methods were tested only on small road networks with up to one hundred thousand vertices; some approaches were evaluated using distance queries (instead of shortest path queries), namely, queries that ask only for the length of the shortest path; a state-of-the-art technique was examined based on a faulty implementation that led to incorrect query results. To address the above issues, this paper presents a comprehensive comparison of the most advanced spatial-coherence-based and vertex-importance-based approaches. Using a variety of real road networks with up to twenty million vertices, we evaluated each technique in terms of its preprocessing time, space consumption, and query efficiency (for both shortest path and distance queries). Our experimental results reveal the characteristics of different techniques, based on which we provide guidelines on selecting appropriate methods for various scenarios.