论文信息 - Urban Road Short-term Traffic Flow Forecasting Based on the Delay and Nonlinear Grey Model

Urban Road Short-term Traffic Flow Forecasting Based on the Delay and Nonlinear Grey Model

Concerning the delay and nonlinear properties of traffic flow in urban road systems, this paper forecasts the short-term traffic flow based on the grey GM(1,1|τ,r). Firstly, the delay factor τ is determined by the speed-flow relationship when volume is greater than it capacity. Then, the nonlinear parameter r is determined by a particle swarm optimization algorithm, where the prediction effect is unsurpassed. Finally, verification of this model is done by collecting traffic flow data on one section of Youyi Avenue and comparing the prediction value of GM(1,1|τ,r) with GM(1,1) and SVM. The results show that the prediction effect of GM(1,1|τ,r) model for short-term traffic flow is significantly improved, which plays an important role in intelligent traffic systems.

[1] Adel W. Sadek,et al. A novel forecasting approach inspired by human memory: The example of short-term traffic volume forecasting , 2009 .

[2] B. Basu,et al. Bayesian Time-Series Model for Short-Term Traffic Flow Forecasting , 2007 .

[3] William R. McShane,et al. A review of pedestrian safety models for urban areas in Low and Middle Income Countries , 2016 .

[4] Zhongke Shi,et al. Short-Time Traffic Flow Prediction Based on Chaos Time Series Theory , 2008 .

[5] Ying Sun,et al. Gaussian Processes for Short-Term Traffic Volume Forecasting , 2010 .

[6] Casper J. Albers,et al. Intervention and Causality: Forecasting Traffic Flows Using a Dynamic Bayesian Network , 2009 .