Classification of Road Network Function in Local City Based on OD Proportion of Link Traffic Flow
DOI: 10.11361/journalcpij.28.349
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Summary
This paper addresses the challenge of classifying road network functions in local cities, specifically focusing on the mismatch between a road’s intended hierarchical function and its actual usage. In small local cities, passing traffic is significant, and existing classification methods often rely on multivariate analysis of traffic volume or network topology without explicitly accounting for traffic flow characteristics. The authors argue that functional mismatches—such as local traffic using arterial roads or through-traffic entering local streets—cause safety and efficiency issues. The study aims to develop a simple, traffic-flow-based classification method and a corresponding traffic assignment technique suitable for local cities where standard zoning data is lacking. To achieve this, the authors propose a two-phase traffic assignment method and a classification metric based on the Origin-Destination (OD) proportion of link traffic flow. The assignment method first distributes regional OD data to aggregate passing traffic into boundary links, then estimates and corrects a detailed local OD matrix using observed traffic volumes, and finally assigns this to the local network. For classification, the authors aggregate OD pairs into three categories: internal (both ends within the city), mixed (one end within), and external (passing through). The proportion of these categories in a link’s total volume serves as the classification basis, plotted on a triangular coordinate system to compare actual usage against expected functions (primary, district, and local distributor roads). The methodology was applied to Saijo City, a local city in Ehime Prefecture with a population of approximately 60,000. The traffic assignment model successfully reproduced current traffic conditions, with a correlation coefficient of 0.78 between observed and calculated volumes. The analysis revealed distinct usage patterns: Group A links were dominated by passing and mixed traffic, fitting primary arterial functions; Group C links served primarily internal traffic, fitting local distributor functions. However, significant mismatches were identified. Many primary arterials carried substantial internal traffic, reducing their traffic efficiency. Conversely, some auxiliary arterials carried passing traffic they were not designed to handle. Furthermore, the distinction between district and auxiliary arterials was unclear, with many district roads functioning like lower-tier roads. The study concludes that the functional hierarchy of Saijo City’s road network requires improvement. The findings indicate that internal traffic is pervasive across all road types, and passing traffic infiltrates lower-tier roads, leading to functional confusion. The authors suggest that network planning should avoid direct connections between primary arterials and local distributors to prevent such mismatches. The proposed OD-proportion method provides a practical tool for diagnosing functional inconsistencies and guiding network restructuring in local cities where passing traffic is a dominant factor.
Provenance
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| Stage | Outcome | Tool | Model | Prompt | Attempts | Completed |
|---|---|---|---|---|---|---|
| discover | success | Crossref | — | — | 1 | 2026-06-20 |
| archive | success | unpaywall | — | — | 2 | 2026-06-26 |
| extract | success | pdftotext | — | — | 2 | 2026-06-26 |
| clean | success | clean | — | — | 1 | 2026-06-26 |
| chunk | success | chunk | — | — | 1 | 2026-06-26 |
| embed | success | embed | Qwen/Qwen3-Embedding-8B | — | 1 | 2026-06-26 |
| enrich | success | openalex | — | — | 1 | 2026-06-26 |
| promote | success | — | — | — | 1 | 2026-06-20 |
| summarize | success | llm | qwen3.6-27b-prismaquant | summ-v5 | 1 | 2026-06-26 |
| tag | success | vector_similarity | — | — | 6 | 2026-06-26 |
| verify | success | — | — | — | 1 | 2026-06-26 |
Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.
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