Path-Structure Heterogeneity in Origin–Destination Pair–Day Observations: Rethinking Where and How Representative-Path Methods Should Be Evaluated

When extracting representative paths from large-scale vehicle trajectory data, origin–destination (OD) pairs have typically been treated as a homogeneous unit of analysis. This study used ~2.5 million OD pair–day (OD-day) navigation records collected over 21 days in Bucheon City, Republic of Korea, and evaluated representative paths and links using weighted indices and cumulative explained travel (CET). The results showed that 86.9% of OD-days exhibited a single observed path, whereas 13.1% exhibited multiple paths. Within multipath OD-days, 96.8% (12.7% of all OD-days) were classified as path-dispersed (top-path share ≤ 0.8). Although comprising only 13% of OD-days, multipath cases averaged 8.3 times more observed vehicles than single-path cases and accounted for 55.7% of observed vehicle trips. CET analysis showed that representative-path selection was primarily meaningful for dispersed OD-days. Across all OD-days, a single path covered, on average, 92.9% of an OD-day’s vehicle-kilometers traveled (VKT); on dispersed OD-days, the mean coverage was 45.2%, increasing to 84.7% and 93.5% with two and three paths, respectively. Further, weighted indices aligned substantially closer with the official arterial hierarchy than frequency-based indices: among top-50 representative links, the proportion of high-speed arterials increased from 30% to 80%, against a network average of 4.2%. These findings suggest that representative-path and link extraction should account for OD-day path-structure heterogeneity.

Authors

Institutions

Publication Details

Journal
Applied Sciences
Published
2026-08-27
DOI
https://doi.org/10.3390/app16178510
Primary Topic
Transportation Planning and Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Path-Structure Heterogeneity in Origin–Destination Pair–Day Observations: Rethinking Where and How Representative-Path Methods Should Be Evaluated

Choong Heon Yang
Applied Sciences
Transportation Planning and Optimization
article

Path-Structure Heterogeneity in Origin–Destination Pair–Day Observations: Rethinking Where and How Representative-Path Methods Should Be Evaluated

Choong Heon Yang
article en

Abstract

When extracting representative paths from large-scale vehicle trajectory data, origin–destination (OD) pairs have typically been treated as a homogeneous unit of analysis. This study used ~2.5 million OD pair–day (OD-day) navigation records collected over 21 days in Bucheon City, Republic of Korea, and evaluated representative paths and links using weighted indices and cumulative explained travel (CET). The results showed that 86.9% of OD-days exhibited a single observed path, whereas 13.1% exhibited multiple paths. Within multipath OD-days, 96.8% (12.7% of all OD-days) were classified as path-dispersed (top-path share ≤ 0.8). Although comprising only 13% of OD-days, multipath cases averaged 8.3 times more observed vehicles than single-path cases and accounted for 55.7% of observed vehicle trips. CET analysis showed that representative-path selection was primarily meaningful for dispersed OD-days. Across all OD-days, a single path covered, on average, 92.9% of an OD-day’s vehicle-kilometers traveled (VKT); on dispersed OD-days, the mean coverage was 45.2%, increasing to 84.7% and 93.5% with two and three paths, respectively. Further, weighted indices aligned substantially closer with the official arterial hierarchy than frequency-based indices: among top-50 representative links, the proportion of high-speed arterials increased from 30% to 80%, against a network average of 4.2%. These findings suggest that representative-path and link extraction should account for OD-day path-structure heterogeneity.

Applied SciencesVol. 16(17)
Korea Institute of Civil Engineering and Building Technology (KR)
Ministry of Land, Infrastructure and Transport, Korea Agency for Infrastructure Technology Advancement
Openalex Percentile: Top 6%
Transportation Planning and Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.