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Assessing Travel Data Accuracy Across Data Platforms: Evidence from Smartphone-based Travel Diaries of University Students in Sydney

Xianliang Liu
Vol.1, No.6, pp.94-107, 2026 DOI: 10.62051/ajmse.v1n6.11 September 29, 2026
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Abstract: Smartphones have been used to collect data on people's travel behaviour, but the quality of this data varies in accuracy and completeness. Using Google Maps Timeline and Fourstep, three study days in October-November 2025 were analysed for travel logs of 20 university students in Sydney. Collect records from both platforms and organise and align them by participant and day. Python was used to convert Google Maps Timeline JSON files into a structured dataset and obtain anonymised Fourstep records from the platform backend. The accuracy of trip completion, temporal-spatial consistency, segmentation accuracy, mode recognition accuracy and participant-level error rate were also recorded. FourStep had a finer division of trips and fewer missing or misclassified segments; Google Maps Timeline was better at locating major activity spots and some types of motorised travel. The mean error rate was 1.3% for Fourstep and 18.9% for Google Maps Timeline, with a significant within-participant difference, F(1,19)=10.67, p=0.004. The findings indicate that platform choice should depend on the intended modelling task rather than on a single notion of accuracy.
Keywords: Data Platform, Travel Data, Accuracy
APA Citation: Xianliang Liu (2026). Assessing Travel Data Accuracy Across Data Platforms: Evidence from Smartphone-based Travel Diaries of University Students in Sydney. Academic Journal of Management Science and Engineering, 1(6), 94-107. https://doi.org/10.62051/ajmse.v1n6.11

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