Short-Term Estimation and Prediction of Pedestrian Density in Urban Hot Spots Based on Mobile Phone Data

• Published in: IEEE transactions on intelligent transportation systems Vol. 23; no. 8; pp. 10827 - 10838
• Main Authors: Huo, Jinbiao, Fu, Xiao, Liu, Zhiyuan, Zhang, Qi
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.08.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Cell phones; Cellular telephones; Computer vision; Density; Estimation; Extended Kalman filter; Forecasting; Hilbert R-tree; Kalman filter; Kalman filters; Mobile handsets; mobile phone data; particle filter; Pedestrian density estimation; Pedestrians; Predictive models; Rail transportation; Railway stations; Shopping malls; short-term prediction; Spatial data; Traffic control; Traffic management

Short-term estimation and prediction of pedestrian density in urban hot spots (e.g., railway station, shopping mall, etc.) is an important topic for traffic management and control in densely populated areas. In this paper, we propose a short-term pedestrian density estimation and prediction method b...