Abstract
Many transportation network vulnerability assessment methods are based on the static traffic assignment problem, which determines the distribution of traffic demand over a network for a static snapshot in time. However, transportation networks are dynamic because demand is time-varying. This paper proposes a mixed strategy, stochastic game-theoretic approach to determine the relative criticality of links in different time intervals. We quantitatively compare the results of the proposed approach with deterministic methods that do not scale efficiently. Our results indicate that the criticalities identified by the game-theoretic approach are strongly correlated with the slower deterministic method, suggesting that the proposed approach will enable efficient vulnerability assessment of dynamic transportation networks.