Commute time analysis using mobile location information

In this paper, authors indicate that 95% of the South Korean population owns a mobile device. Telecom providers can collect an individual's location data at short intervals by utilizing communication information from their mobile devices. By continuously tracking daily location data, it is possible to estimate an individual's residential location, employment status, and workplace location. Based on residential and workplace locations, the purposes of trips—such as commuting, work-related travel, leisure, and returning home—can be inferred.This study develops a methodology for constructing a personal trip chain database (DB) that includes trip purposes using mobile location data and analyzes commuting conditions by city in South Korea. It examines factors such as the average commuting time, standard deviation, and the proportion of individuals experiencing poor commuting conditions based on city-specific commuting time distributions. Additionally, it analyzes urban commuting self-sufficiency levels based on the consistency between residential and workplace locations.By assessing the commuting environments of those with particularly challenging commutes, this study aims to propose transportation infrastructure investment policies (SOC) to improve travel conditions.

Authors

Publication Details

Journal
AHFE international
Published
2025-01-01
DOI
https://doi.org/10.54941/ahfe1006702
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Commute time analysis using mobile location information

Juyoung Kim
1 links
AHFE international
Human Mobility and Location-Based Analysis
article

Commute time analysis using mobile location information

Juyoung Kim
article en

Abstract

In this paper, authors indicate that 95% of the South Korean population owns a mobile device. Telecom providers can collect an individual's location data at short intervals by utilizing communication information from their mobile devices. By continuously tracking daily location data, it is possible to estimate an individual's residential location, employment status, and workplace location. Based on residential and workplace locations, the purposes of trips—such as commuting, work-related travel, leisure, and returning home—can be inferred.This study develops a methodology for constructing a personal trip chain database (DB) that includes trip purposes using mobile location data and analyzes commuting conditions by city in South Korea. It examines factors such as the average commuting time, standard deviation, and the proportion of individuals experiencing poor commuting conditions based on city-specific commuting time distributions. Additionally, it analyzes urban commuting self-sufficiency levels based on the consistency between residential and workplace locations.By assessing the commuting environments of those with particularly challenging commutes, this study aims to propose transportation infrastructure investment policies (SOC) to improve travel conditions.

AHFE internationalVol. -5
Openalex Percentile: Top 84%
Human Mobility and Location-Based Analysis
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Commute time analysis using mobile location information — Juyoung Kim · AHFE international (2025) | TGRS Research Map | TGRS