Human mobility prediction is a key task in smart cities to help improve urban management
effectiveness. However, it remains challenging due to widespread intractable noises in large …

Human mobility prediction techniques are instrumental for many important applications
including service management and city planning. Previous work looks at the inherent …

With the rapid advancement of technology, modeling travel behavior based on large-scale
mobile trajectory data has become a core issue in urban traffic management. Mining …

Human mobility is the foundation of urban dynamics and its prediction significantly benefits
various downstream location-based services. Nowadays, while deep learning approaches …

Human mobility behavior is far from random, and its indicators follow non-Gaussian
distributions. Predicting human mobility has the potential to enhance location-based …

In literature, scientists describe human mobility in a range of granularities by several
different models. Using frameworks like MATSIM, VehiLux, or Sumo, they often derive …

Most mobility modeling methods are designed to solve specific tasks, leading to questions
regarding their deficiency in generalizability. Inspired by the bloom of foundation models, we …

Human mobility is a multidisciplinary field of physics and computer science and has drawn a
lot of attentions in recent years. Some representative models and prediction approaches …

Human mobility prediction is essential to a variety of human-centered computing
applications achieved through upgrading of location-based services (LBS) to future-location …

Predicting mobility-related behavior is an important yet challenging task. On one hand,
factors such as one's routine or preferences for a few favorite locations may help in …