human mobility

dinosaur

packets

trip

pedestrians

donor nephrectomy

traffic network

travel demand

user interfaces

mobility patterns

commonwealth_90236

la comunidad

mobility_135882

route choice_135366

crime_125988

mass movement

endometrial_9718

high cycle fatigue

valve_54594

Transportation Research Part C Emerging Technologies

Even though a variety of human mobility models have been recently developed, models that can capture real-time human mobility of urban populations in a sustainable and economical manner are still lacking. Here, we propose a novel human mobility model that combines the advantages of mobile phone signaling data (i.e., comprehensive penetration in a population) and urban transportation data (i.e., continuous collection and high accuracy). Using the proposed human mobility model, travel demands during each 1-h time window were estimated for the city of Shenzhen, China. Significantly, the estimated travel demands not only preserved the distribution of travel demands, but also captured real-time bursts of mobility fluxes during large crowding events. Finally, based on the proposed human mobility model, a predictive model is deployed to predict crowd gatherings that usually cause severe traffic jams.

Modeling real-time human mobility based on mobile phone and transportation data fusion