Reliability of the traffic network against cascading failures with individuals acting independently or collectively

The domino-like cascading failures may deteriorate traffic network reliability for both system and users. As the microscopic origin of this dynamic process, route choice behavior should be essential for the pattern of reliability against cascading failures, but the mechanism has not been systematically investigated. To uncover this, we propose a two-level cascading failure model to observe route choice patterns during the evolution of traffic jams: (i) the upper-level depicts how cascading failures spread out in network topologies, while (ii) the lower-level models what paths travelers may select in the trade-off between user equilibrium (UE) and system optimum (SO). Given nearly-one million OD pairs on large-scale traffic networks, the influence mechanisms of four factors on two reliability indicators are explored. We find that under certain perturbations, staying at the identified critical tolerance is the most profitable for investment yet unstable for reliability. Surprisingly, phase transition patterns are found in different topologies of traffic networks, where the lattice network is the most unreliable. Network reliability is found to increase by modifying travelers’ route choices from independent UE toward collective SO, whereas, the reliability is found to decrease if travelers have stochastic perception errors of travel time or have risk preferences to probabilistic travel time. Furthermore, if the overload failures can be recovered from the failed states, a traffic network may become more reliable. Our finding may help to improve reliability management of future transportation with multiple states between UE and SO.