An interdisciplinary survey on origin-destination flows modeling: Theory and techniques

C Rong, J Ding, Y Li - ACM Computing Surveys, 2024 - dl.acm.org
Origin-destination (OD) flow modeling is an extensively researched subject across multiple
disciplines, such as the investigation of travel demand in transportation and spatial …

Mobility trajectory generation: a survey

X Kong, Q Chen, M Hou, H Wang, F **a - Artificial Intelligence Review, 2023 - Springer
Mobility trajectory data is of great significance for mobility pattern study, urban computing,
and city science. Self-driving, traffic prediction, environment estimation, and many other …

Towards generative modeling of urban flow through knowledge-enhanced denoising diffusion

Z Zhou, J Ding, Y Liu, D **, Y Li - Proceedings of the 31st ACM …, 2023 - dl.acm.org
Although generative AI has been successful in many areas, its ability to model geospatial
data is still underexplored. Urban flow, a typical kind of geospatial data, is critical for a wide …

Harnessing llms for cross-city od flow prediction

C Yu, X **e, Y Huang, C Qiu - … of the 32nd ACM International Conference …, 2024 - dl.acm.org
Understanding and predicting Origin-Destination (OD) flows is crucial for urban planning
and transportation management. Traditional OD prediction models, while effective within …

[HTML][HTML] A fusion model of temporal graph attention network and machine learning for inferring commuting flow from human activity intensity dynamics

Q Shi, L Zhuo, H Tao, J Yang - … Journal of Applied Earth Observation and …, 2024 - Elsevier
Accurately estimating commuting flow is essential for optimizing urban planning and traffic
design. The latest graph neural network (GNN) model with the encoder-decoder-predictor …

Predicting origin-destination flows by considering heterogeneous mobility patterns

Y Zhao, S Cheng, S Gao, P Wang, F Lu - Sustainable Cities and Society, 2025 - Elsevier
The accurate prediction of origin-destination (OD) flows is essential for advancing
sustainable urban mobility and supporting resilient urban planning. However, the inherent …

Dual-teacher de-biasing distillation framework for multi-domain fake news detection

J Li, X Feng, T Gu, L Chang - 2024 IEEE 40th International …, 2024 - ieeexplore.ieee.org
Multi-domain fake news detection aims to identify whether various news from different
domains is real or fake and has become urgent and important. However, existing methods …

A large-scale benchmark dataset for commuting origin-destination matrix generation

C Rong, J Ding, Y Liu, Y Li - arxiv preprint arxiv:2407.15823, 2024 - arxiv.org
The commuting origin-destination~(OD) matrix is a critical input for urban planning and
transportation, providing crucial information about the population residing in one region and …

[HTML][HTML] DistOD: A Hybrid Privacy-Preserving and Distributed Framework for Origin–Destination Matrix Computation

J Kim - Electronics, 2024 - mdpi.com
The origin–destination (OD) matrix is a critical tool in understanding human mobility, with
diverse applications. However, constructing OD matrices can pose significant privacy …

Commuting flow prediction using OpenStreetMap data

KS Atwal, T Anderson, D Pfoser, A Züfle - Computational Urban Science, 2025 - Springer
Accurately predicting commuting flows is crucial for sustainable urban planning and
preventing disease spread due to human mobility. While recent advancements have …