TY  - JOUR
PY  - 2018//
TI  - Modeling real-time human mobility based on mobile phone and transportation data fusion
JO  - Transportation research part C: emerging technologies
A1  - Huang, Zhiren
A1  - Ling, Ximan
A1  - Wang, Pu
A1  - Zhang, Fan
A1  - Mao, Yingping
A1  - Lin, Tao
A1  - Wang, Fei-Yue
SP  - 251
EP  - 269
VL  - 96
IS  - 
N2  - 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.    Keywords: Road transportation <p />  <p>Language: en</p>
LA  - en
SN  - 0968-090X
UR  - http://dx.doi.org/10.1016/j.trc.2018.09.016
ID  - ref1
ER  -