SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis

Zhu, Yuanshao1,2; Ye, Yongchao1; Wu, Ying1,3; Zhao, Xiangyu2; Yu, James J. Q.4

2023

37th Conference on Neural Information Processing Systems (NeurIPS)

1049-5258

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 36 (NEURIPS 2023)

DEC 10-16, 2023

null,New Orleans,LA

10010 NORTH TORREY PINES RD, LA JOLLA, CALIFORNIA 92037 USA

NEURAL INFORMATION PROCESSING SYSTEMS (NIPS)

Urban mobility analysis has been extensively studied in the past decade using a vast amount of GPS trajectory data, which reveals hidden patterns in movement and human activity within urban landscapes. Despite its significant value, the availability of such datasets often faces limitations due to privacy concerns, proprietary barriers, and quality inconsistencies. To address these challenges, this paper presents a synthetic trajectory dataset with high fidelity, offering a general solution to these data accessibility issues. Specifically, the proposed dataset adopts a diffusion model as its synthesizer, with the primary aim of accurately emulating the spatial-temporal behavior of the original trajectory data. These synthesized data can retain the geo-distribution and statistical properties characteristic of real-world datasets. Through rigorous analysis and case studies, we validate the high similarity and utility between the proposed synthetic trajectory dataset and real-world counterparts. Such validation underscores the practicality of synthetic datasets for urban mobility analysis and advocates for its wider acceptance within the research community. Finally, we publicly release the trajectory synthesizer and datasets, aiming to enhance the quality and availability of synthetic trajectory datasets and encourage continued contributions to this rapidly evolving field. The dataset is released for public online availability https://github.com/Applied-Machine-Learning-Lab/SynMob.

第一

英语

CPCI-S

Research Impact Fund[R1015-23] ; APRC -CityU New Research Initiatives (City University of Hong Kong)[9610565] ; CityU -HKIDS Early Career Research Grant[9360163] ; Hong Kong ITC Innovation and Technology Fund Midstream Research Programme for Universities Project[ITS/034/22MS] ; Hong Kong Environmental and Conservation Fund[88/2022] ; SIRG -CityU Strategic Interdisciplinary Research Grant["7020046","7020074"]

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Information Systems

WOS:001229826601026

Web of Science

1.Southern Univ Sci & Technol, Shenzhen, Peoples R China
2.City Univ Hong Kong, Hong Kong, Peoples R China
3.Univ Leeds, Leeds, England
4.Univ York, York, England

Zhu, Yuanshao,Ye, Yongchao,Wu, Ying,et al. SynMob: Creating High-Fidelity Synthetic GPS Trajectory Dataset for Urban Mobility Analysis[C]. 10010 NORTH TORREY PINES RD, LA JOLLA, CALIFORNIA 92037 USA:NEURAL INFORMATION PROCESSING SYSTEMS (NIPS),2023.