Short-term estimation and prediction of pedestrian density in urban hot spots (eg, railway
station, shopping mall, etc.) is an important topic for traffic management and control in …

This paper describes a pedestrian population trend estimation method using location data of
smartphone users. This technique is intended to be an alternative to traffic censuses using …

Urban crowd density prediction is essential for transport demand management and public
safety monitoring. Existing studies for crowd density prediction only focus on a few transport …

Recently, population density has grown quickly with the increasing acceleration of
urbanization. At the same time, overcrowded situations are more likely to occur in populous …

Pedestrian volume prediction is a key strategy to explore the spatial patterns of pedestrian
mobility and develop urban policies. However, due to the expensive costs of field sampling …

With the development of human society, the shortcomings of the existing transportation
system become increasingly prominent, so people hope to use advanced technology to …

In this paper, we focus on developing a model and system for predicting the city foot traffic.
We utilise historical records of pedestrian counts captured with thermal and laser-based …

Modelling and forecasting citywide crowd information (eg, crowd volume of a region, the
inflow of crowds into a region, outflow of crowds from a region) at a fine spatio-temporal …

Fine-grained crowd distribution forecasting benefits smart transportation operations and
management, such as public transport dispatch, traffic demand prediction, and transport …

Accurately forecasting how crowds of people are distributed in urban areas during daily
activities is of key importance for the smart city vision and related applications. In this work …