Development and application of the Activity-BAsed Traveler Analyzer (ABATA) system

Eom, Jin Ki; Lee, Kwang Sub; Seong, Myeong-Eon

doi:10.1016/j.future.2019.12.048

Cited by 3 publications

(3 citation statements)

References 37 publications

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“…For this reason, extensive research has been conducted using mobile phone data. Several studies have been focused on movement patterns [42,65,66], travel behaviors [67,68], origin/destination (O/D) trips [41,69,70], and identification of activity locations [71] using mobile phone data.…”

Section: Literature Reviewmentioning

confidence: 99%

“…SKT mobile phone data are Long Term Evolution (LTE)-based signal data; that is, a phone is always connected to a base tower to maintain signal connection, and the base tower sends a push-alarm signal to the phone of the user every 15 min on average. In this manner, every record of the location of the user at each time is stored repeatedly as long as the phone is turned on [32,41]. Second, the mobile phone data represent all mobile phone users in Korea.…”

Section: Overview Mobile Phone Datamentioning

confidence: 99%

“…Several studies have highlighted the potential and significance of new data sources [31,[34][35][36][37][38][39][40], because they can include various sociodemographic and travel characteristics of all people without exception. Although most GPS-based studies have still been based on a sampled data, mobile phone data that represent the total population have been analyzed in a few recent studies [41,42]. Analysis using data representative of the total population is crucial for fully understanding the activity and mobility behaviors of people and is especially interesting when studying a population that may experience different activity and trip patterns between age groups.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of the Activity and Travel Patterns of the Elderly Using Mobile Phone-Based Hourly Locational Trajectory Data: Case Study of Gangnam, Korea

et al. 2021

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Rapid demographic ageing is a global challenge and has tremendous implications for transportation planning, because the mobility of elderly people is an essential element for active ageing. Although many studies have been conducted on this issue, most of them have been focused on aggregated travel patterns of the elderly, limited in spatiotemporal analysis, and most importantly primarily relied on sampled (2–3%) household travel surveys, omitting some trips and having concerns of quality and credibility. The objectives of this study are to present more in-depth analysis of the elderly’s spatiotemporal activity and travel behaviors, to compare them with other age and gender groups, and to draw implications for sustainable transportation for the elderly. For our analysis, we used locational trajectory-based mobile phone data in Gangnam, Korea. The data differs from sampled household travel survey data, as mobile phone data represents the entire population and can capture comprehensive travelers’ movements, including peculiarities. Consistent with previous researches, the results of this study showed that there were differences in activity and travel patterns between age and gender groups. However, some different results were obtained as well: for instance, the average nonhome activity time per person for the elderly was shorter than that of the nonelderly, but the average numbers of nonhome activities and trips were rather higher than those of nonelderly people. The results of this study and advantage of using mobile phone data will help policymakers understand the activities and movements of the elderly and prepare future sustainable transportation.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Overview Mobile Phone Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Analysis of the Activity and Travel Patterns of the Elderly Using Mobile Phone-Based Hourly Locational Trajectory Data: Case Study of Gangnam, Korea

et al. 2021

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Modeling Intrazonal Distance and Duration in Addressing Limitation of Intrazonal Generalized Cost Commonly Applied in Transport Models

Alam

Siddle²,

Colleary³

2021

J. Transp. Eng., Part A: Systems

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Agent-Based Travel Scheduler: Decomposing OD Data for Predicting Individual Travel Schedules through Agent-Based Modeling

Choi,

Seo,

Hohl

2024

Preprint

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This study introduces the Agent-Based Travel Scheduler (ABTS) model, designed to predict individual travel schedules by decomposing GPS-based aggregated Origin-Destination data according to demographic features and trip purposes. ABTS improves upon traditional models by generating detailed individual travel schedules based on agent-based modeling within an activity-based framework. The model's accuracy is refined through robust validation by calibrating key parameters that influence individual travel patterns in both spatial and temporal dimensions. Applied to Milwaukee, Wisconsin, USA, the model demonstrated 83% accuracy in estimating travel patterns, although it showed reduced performance in densely populated downtown areas and locations where special events that attract large crowds occurred. ABTS offers advantages in computational efficiency, flexibility in parameter adjustment, and adaptability to various urban scenarios, making it a valuable tool for policy analysis and urban planning.

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Development and application of the Activity-BAsed Traveler Analyzer (ABATA) system

Cited by 3 publications

References 37 publications

Analysis of the Activity and Travel Patterns of the Elderly Using Mobile Phone-Based Hourly Locational Trajectory Data: Case Study of Gangnam, Korea

Analysis of the Activity and Travel Patterns of the Elderly Using Mobile Phone-Based Hourly Locational Trajectory Data: Case Study of Gangnam, Korea

Modeling Intrazonal Distance and Duration in Addressing Limitation of Intrazonal Generalized Cost Commonly Applied in Transport Models

Agent-Based Travel Scheduler: Decomposing OD Data for Predicting Individual Travel Schedules through Agent-Based Modeling

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