Estimation of Traffic Risk of Level Crossing Based on Stochastic Petri Nets Models and Social Economic Data

This paper focuses on the estimation of traffic risk of passive level railway crossing based on a formal graphic model. Traditional analysis and estimation approaches of traffic risk are based on the aggressive mathematical algorithms. Compared with these traditional methods, formal graphic model has better graphical interface to users, better modeling flexibility to the change of system conditions. Following an explanation of application of social statistic data, Stochastic Petri nets are used to model the level railway crossing in respect of process. The inputs and output of this model are both calculated from available social statistic data. Road userspsilabehavior, one of the key parameters, is assumed to be predicted by an approximation function representing the dependence of the behavior from the Gross Domestic Production (GDP) of their nations. The model is validated by available social statistic and empirical data. Finally level railway crossing traffic risks of different nations are estimated based on the analysis and simulation of this model.