The 'sharing'business models and on-demand services have been altering city dwellers'
travel habits from buying the means of transport to buying mobility services based on needs …

ABSTRACT New Big Data sources such as mobile phone call data records, smart card data
and geo-coded social media records allow to observe and understand mobility behaviour on …

For intelligent urban transportation systems, the ability to predict individual mobility is crucial
for personalized traveler information, targeted demand management, and dynamic system …

Individual mobility is driven by demand for activities with diverse spatiotemporal patterns, but
existing methods for mobility prediction often overlook the underlying activity patterns …

Human mobility analysis is one of the most important research problems in the field of urban
computing. Existing research mainly focuses on the intra-city ground travel behavior …

Understanding and predicting human mobility is vital to a large number of applications,
ranging from recommendations to safety and urban service planning. In some travel …

Key challenges in vehicular transportation and communication systems are understanding
vehicular mobility and utilizing mobility prediction, which are vital for both solving the …

With the emergence of smartphones and location-based services, user mobility prediction
has become a critical enabler for a wide range of applications, like location-based …

Accurately forecasting ridesourcing demand is important for effective transportation planning
and policy-making. With the rise of Artificial Intelligence (AI), researchers have started to …

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