TRANSIT NETWORK RELIABILITY: AN APPLICATION OF ABSORBING MARKOV CHAINS

This study applies an absorbing Markov chain model to transit assignment to analyze the impact of vertex failure on the probability of trip failure. Vertex failure probabilities are treated as either known or unknown, and if unknown then worst vertex probabilities are sought. Reviewed are the lessons learned from recent random graph research on the robustness of different network topologies. An analysis of a number of elemental transit network topologies using the absorbing Markov chain model shows that the hub and spoke graph is the most robust to random vertex failure but also among the most vulnerable to directed vertex attack. The study analyzes a particular form of unreliability, namely the probability of being unable to board a transit line due to insufficient capacity, using the absorbing Markov chain model.