Resilient post-disaster recovery is crucial for the long-term sustainable development of
modern cities, and in this regard, predicting the unusual flows of human mobility when …

Human mobility is of importance in supporting smart cities, urban planning and constructions
of resilient environments. Previous studies on dominant mobility models (ie, gravity and …

Crowd gathering in public infrastructures increases the challenges to safety management.
To control the risk of crowd accidents, it is crucial to investigate the specific pedestrian …

Understanding human mobility patterns amid natural hazards is crucial for enhancing urban
emergency responses and rescue operations. Existing research on human mobility has …

Accurate prediction of individual mobility is crucial for develo** intelligent transportation
systems. However, while previous models usually focused on predicting individual mobility …

There are still lacking effective approaches to comprehensively quantify the attractions of
different regions to human mobility. Here, we employ the mobility field approach to analyze …

The concept of spatiotemporal correlation, initially rooted in the domain of physics, has
increasingly become of interest to scholars across various fields. This burgeoning interest is …

Abstract System crowding relates to the general congestion phenomenon of clients,
products or patients waiting concurrently, and its adequate representation and measurement …

Predicting individual mobility of subway passengers in large crowding events is crucial for
subway safety management and crowd control. However, most previous models focused on …

In this paper we develop a pseudo Markov-chain model to understand time-elapsed flows,
over multiple intervals, from time and space aggregated collective inter-location trip data …