From trajectory to behavior: Capturing individual travel details using an applet-based GPS tracking system

• An applet-based GPS tracking system is proposed to reduce installation and response burdens. • Three-phase travel survey data collected through interview, app, and applet are compared. • Smartphone-based survey outperforms interviews in capturing multi-modal trips. • Applet-based survey tends to encourage greater participation than app-based survey. Household travel survey data form the foundation of travel behavior modeling and transportation planning, yet traditional interview-based methods face significant challenges related to high labor costs and data quality limitations. Smartphone-based travel surveys have emerged as promising alternatives, but barriers to participation persist despite technological advances. This paper presents an innovative applet-based GPS tracking system designed to minimize participant burden through four integrated modules: (i) data collection via a freely-installed mini-program embedded within a widely-used social media platform, (ii) automated trip extraction using cloud-based algorithms, (iii) intuitive user interfaces for trip validation, and (iv) a comprehensive survey supervision platform. We evaluate this system through comparative analysis across three survey phases conducted in an urban district: an app-based pilot study, a traditional interview-based survey, and our applet-based field implementation. Results indicate that smartphone-based methods match interview-based methods in capturing trip chains, while significantly outperforming them in detecting multi-modal trip details. The applet-based survey approach also achieved notably lower recruitment rejection rates compared to the app-based method, demonstrating greater effectiveness in participant engagement. These findings underscore the feasibility and advantages of lightweight, participant-friendly smartphone-based travel survey methods, providing valuable insights for transportation research and planning practices.

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Institutions

Publication Details

Journal
Travel Behaviour and Society
Published
2025-06-03
DOI
https://doi.org/10.1016/j.tbs.2025.101078
Primary Topic
Human Mobility and Location-Based Analysis
Type
article
Field-Weighted Citation Impact
0.00

Funders

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article

From trajectory to behavior: Capturing individual travel details using an applet-based GPS tracking system

Fangyi Ding, Quan Yuan, Yang Zhou, Tianren Yang et al.
Travel Behaviour and Society
Human Mobility and Location-Based Analysis
article

From trajectory to behavior: Capturing individual travel details using an applet-based GPS tracking system

Fangyi Ding, Quan Yuan, Yang Zhou, Tianren Yang, Chao Yang, Xiaoyi Ma
article en

Abstract

• An applet-based GPS tracking system is proposed to reduce installation and response burdens. • Three-phase travel survey data collected through interview, app, and applet are compared. • Smartphone-based survey outperforms interviews in capturing multi-modal trips. • Applet-based survey tends to encourage greater participation than app-based survey. Household travel survey data form the foundation of travel behavior modeling and transportation planning, yet traditional interview-based methods face significant challenges related to high labor costs and data quality limitations. Smartphone-based travel surveys have emerged as promising alternatives, but barriers to participation persist despite technological advances. This paper presents an innovative applet-based GPS tracking system designed to minimize participant burden through four integrated modules: (i) data collection via a freely-installed mini-program embedded within a widely-used social media platform, (ii) automated trip extraction using cloud-based algorithms, (iii) intuitive user interfaces for trip validation, and (iv) a comprehensive survey supervision platform. We evaluate this system through comparative analysis across three survey phases conducted in an urban district: an app-based pilot study, a traditional interview-based survey, and our applet-based field implementation. Results indicate that smartphone-based methods match interview-based methods in capturing trip chains, while significantly outperforming them in detecting multi-modal trip details. The applet-based survey approach also achieved notably lower recruitment rejection rates compared to the app-based method, demonstrating greater effectiveness in participant engagement. These findings underscore the feasibility and advantages of lightweight, participant-friendly smartphone-based travel survey methods, providing valuable insights for transportation research and planning practices.

Travel Behaviour and SocietyVol. 41
Tongji University (CN), City University of Hong Kong, Shenzhen Research Institute (CN), Guangzhou Urban Planning Survey & Design Institute (CN), University of Hong Kong (HK)
China Association for Science and Technology, National Natural Science Foundation of China, Research Grants Council, University Grants Committee, Basic and Applied Basic Research Foundation of Guangdong Province
Openalex Percentile: Top 87%
Human Mobility and Location-Based Analysis
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