Research On Metro Passenger Flow Short-time Prediction And Evacuation Simulation

ABSTRACT:In the research field of Metro passenger flow organization and optimization, short-time passenger flow prediction and pedestrian movement simulation are significant technologies. Although a lot of researchers have done some related works, several difficulties, such as how to increase the passenger forecasting performance with the metro transportation business, predict the real-time passenger flow for important events effectively, and simulate the pedestrian evacuations in different metro scenes for some special cases, need to be improved. The main works in this dissertation include:1. A wavelet based support vector machine short-time passenger prediction algorithm is presented. This method firstly decomposes the original passenger flow time series into low-frequency and high-frequency information by wavelet, and then the least squares support vector machine method is applied to learn from the decomposed information and then to forecast, and finally the predicted low-frequency and high-frequency time series are reconstructed to obtain the predicted passenger flow data. The experiments are based on the passenger flow data from Beijing Metro system and standard evaluation methods, and the results show that the proposed algorithm has better prediction effectiveness than the two existing forecasting methods.2. This paper introduces a grey Markov based larger passenger flow real-time prediction method, and this algorithm establishes the grey model for passenger time-series data by grey prediction method at first, and then constructs the improved Markov model, and grey forecasting results are corrected by the prediction error to acquire the predicted large-scale passenger flow finally. Based on several kinds of large-scale activities and major holiday events, the experimental results indicate that the presented model has achieved better predicting effectiveness for large-scale passenger flows in important events.3. A vector floor field model for mixed movement with multi-direction pedestrian evacuation flow is proposed. It is used to simulate the pedestrian dynamic process in subway stations. As the pedestrians’ sensitivities in different direction are diverse, this model considers the direction factor, and the interactions among pedestrians with different directions can be reproduced much better in the vector floor field model. The results show that this model could realistically and effectively simulate and reproduce the complex interactions and self-organization phenomena among multi-directional pedestrians under a variety of subway station scenarios.4. Considering the fact that the interactions among pedestrians are regarded as mutual repllsion at normal circumstance, a new floor field model for pedestrian evacuation movement with dynamic repulsion field is presented, and in this model the repulsion is used to instead the following effect widely applied in the emergency evacuation. The results show that the appropriate repulsion can improve the congestion critical density in simulation scenarios.