Commuting reflects the long-term travel behavior of people and significantly impacts urban
traffic congestion and emission. Recent advances in data availability provide new …

A common feature of large-scale extreme events, such as pandemics, wildfires, and major
storms is that, despite their differences in etiology and duration, they significantly change …

Predictive models for human mobility have important applications in many fields including
traffic control, ubiquitous computing, and contextual advertisement. The predictive …

Bike-sharing systems have rapidly expanded around the world. Previous studies found that
docked and dockless bike-sharing systems are different in terms of user demand and travel …

Trip purpose is crucial to travel behavior modeling and travel demand estimation for
transportation planning and investment decisions. However, the spatial-temporal complexity …

In this paper, we proposed a new method to extract travel patterns for transit riders from
different public transportation systems based on temporal motif, which is an emerging notion …

Background GPS tracking is increasingly used in health and aging research to objectively
and unobtrusively assess individuals' daily-life mobility. However, mobility is a complex …

Mobility diaries of a large number of people are needed for assessing transportation
infrastructure and spatial development planning. Acquisition of personal mobility diaries …

Agent-based models (ABM) play a prominent role in guiding critical decision-making and
supporting the development of effective policies for better urban resilience and response to …

The lifestyles of urban dwellers could reveal important insights regarding the dynamics and
complexity of cities. The availability of human movement data captured from cell phones …