PCNN: Deep Convolutional Networks for Short-Term Traffic Congestion Prediction

• Published in: IEEE transactions on intelligent transportation systems Vol. 19; no. 11; pp. 3550 - 3559
• Main Authors: Chen, Meng, Yu, Xiaohui, Liu, Yang
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Artificial neural networks; convolutional neural network; Data models; Dependence; Driving conditions; Folding; Forecasting; Modelling; periodic traffic data; Predictive models; Roads; Short term; Solid modeling; Time series; Time series analysis; Traffic congestion; Traffic congestion prediction; Traffic flow; Traffic information; Traffic models; Urban development

Traffic problems have seriously affected people's life quality and urban development, and forecasting short-term traffic congestion is of great importance to both individuals and governments. However, understanding and modeling the traffic conditions can be extremely difficult, and our observat...