Distance between Road Networks: A Macroscopic Method for Road Network Datasets Comparison Using Traffic-weighted Geographic Distribution

2026-05-20

AI Summary

Existing approaches to comparing road network datasets predominantly emphasize topological structure while neglecting traffic flow dynamics, thereby limiting their utility for traffic-oriented data selection. This study proposes a macroscopic quantitative evaluation framework that explicitly incorporates traffic flow into the comparison process. The method generates traffic-weighted spatial distributions through static traffic assignment and quantifies their spatial discrepancies using the two-dimensional Wasserstein distance. By integrating traffic flow as an explicit component, this approach enables functional assessment of road network datasets from a transportation perspective. Case studies demonstrate that the framework effectively discriminates between datasets of varying sources and levels of simplification, offering a novel and practical tool for informed dataset selection in traffic analysis.

Abstract

In transportation network analysis, various types of road network data can be used even when focusing on the same region. Since different road network datasets can make different performance in analyses, it is necessary to compare them and make appropriate selections in a qualitative manner. However, many of the existing methods for comparing road network datasets are limited to specific topological evaluations and do not consider transportation. This study proposes a method for quantitative comparison of different road network datasets with explicit consideration for traffic flows on them. The method first conducts a static traffic assignment with hypothetical demand for each dataset, and then compare the results using Wasserstein distance on two dimensional plane. Case study on different sources of road network datasets and their simplifications suggests the potential use of the proposed method in evaluating and selecting road network datasets.

Problem

• road network comparison
• traffic-weighted
• Wasserstein distance
• transportation network analysis
• dataset evaluation

Innovation

• Wasserstein distance
• traffic-weighted geographic distribution
• road network comparison
• static traffic assignment
• macroscopic evaluation