基于概率神经网络的轨道交通车站客流安全状态评价

Evaluation of Safety Status of Station Passengers in Urban Rail Transit Based on Probabilistic Neural Network

以城市轨道交通车站安全为研究对象,建立基于概率神经网络的车站客流安全状态评价模型。模型将提炼出的城市轨道交通车站客流安全状态评价指标作为输入参数,将评价等级结果作为输出参数,以各指标不同等级的评价标准作为模型训练数据来源。为验证方法的有效性,设计不同的客流场景,利用微观仿真软件VISSIM对车站客流运行状态进行仿真实验,以获得各指标的数据。仿真应用结果表明,该方法能够对城市轨道交通车站客流安全状态进行评价。

This paper presents a model for evaluating station passenger safety status in urban rail transit by using probabilistic neural network. The indexes extracted from the model are taken as input parameters while the results of the evaluation level as output ones. Different levels of evaluation criteria for each indicator are regarded as the model training data sources. To verify the effectiveness of the method, different passenger scenarios are designed, and data for each indicator are obtained by conducting simulation experiments for station passenger status using microscopic simulation software VISSIM. The simulation results show that this method can evaluate urban rail transit station passenger safety status.