A Bayesian network approach for assessing the general resilience of road transportation systems: A systems perspective

Abstract

We proposed a Bayesian Network Model (BNM) based on function-oriented resilience framework and ontological interdependence among 10 system qualities to probabilistically assess the general resilience of the road transportation system in Beijing from 1997 to 2016. We tested the model with multi-source data collected from various sectors. The system qualities were examined by analysis of sensitivity and influence. The result shows that the general resilience of Beijing's road system exhibits a "V" shape in its trend, with the probability of being generally resilient between 50% and 70%, and at its minimum in 2006. There was a steep increase in such a probability since 2006. In addition, the general resilience of Beijing's road transportation system is most affected by its capabilities: (1) to rebuild its performance, (2) to be robust, (3) to adapt, (4) to change, and (5) to quickly repair damaged parts. The proposed BNM is a promising tool for multi-dimensional and systematic analysis, instead of finding a one-size-fits-all quantification criterion for resilience.