Analysis and forecast of air transportation safety: system dynamics modeling

We developed a complex of system dynamics models intended to analyze and forecast key safety characteristics of an air transportation system. The models use the graph of causal relationships where graph nodes represent characteristics of the transportation system and links represent causal relationships between different characteristics. The graph defines a system of nonlinear differential equations. The regression parameters were estimated from official historical data since 1992 to 2009 years. The causal graph includes system variables such as the number of incidents per year and external parameters such as average pilot flying hours etc. The quality of the model was evaluated on 2010-2013 years incidents statistics in CIS. Our model was able to predict the number of incidents with reasonable accuracy. The additional analysis shows that the system obtained can demonstrate chaotic behavior under specific parameter values. The proposed model can reveal trends in the analyzed safety characteristics of an air transportation system.