arXiv:2606. 10314v1 Announce Type: new Abstract: Although the study of human trajectory anomalies is critical for advancing spatial data mining, empirical research remains severely hindered by a pervasive lack of ground-truth datasets.
By Yueyang Liu, Joon-Seok Kim, Andreas Z\"ufle
arXiv:2608. 14570v1 Announce Type: new Abstract: Understanding human mobility is critical for a wide range of urban applications, including traffic management, epidemic control, and urban planning.
By Wen Ye, Muyan Weng, Chuizheng Meng, Hao Niu, Yizhou Zhang, Yan Liu
arXiv:2606. 12657v1 Announce Type: new Abstract: Human mobility data is important for transportation, urban planning, and epidemic control, but large-scale trajectory collection is often costly and privacy-constrained, motivating realistic synthetic trajectory generation.
By Siyu Li, Toan Tran, Lingyi Zhao, Khurram Shafique, Li Xiong
arXiv:2606. 13835v1 Announce Type: cross Abstract: LLM-based generative agents are increasingly used in urban simulators, yet it remains unclear whether they reproduce empirically realistic human mobility patterns or merely generate plausible mobility narratives.
By Gustavo H. Santos, Aline Carneiro Viana, Thiago H. Silva
arXiv:2606. 09086v1 Announce Type: new Abstract: Dynamic origin-destination (OD) flow generation seeks to synthesize realistic mobility dynamics from temporal context alone, without relying on historical OD observations.
By Jie Zhao, Xianqi Dai, Jie Feng, Huandong Wang, Yong Li
arXiv:2510. 06473v3 Announce Type: replace-cross Abstract: Understanding and modeling human mobility is central to challenges in transport planning, sustainable urban design, and public health.
By Ye Hong, Yatao Zhang, Konrad Schindler, Martin Raubal