Data-driven predictive maintenance scheduling policies for railways

Inspection and maintenance activities are essential to preserving safety and cost-effectiveness in railways. However, the stochastic nature of railway defect occurrence is usually ignored in literature; instead, defect stochasticity is considered independently of maintenance scheduling. This study presents a new approach to predict rail and geometry defects that relies on easy-to-obtain data and integrates prediction with inspection and maintenance scheduling activities. In the proposed approach, a novel use of risk-averse and hybrid prediction methodology controls the underestimation of defects. Then, a discounted Markov decision process model utilizes these predictions to determine optimal inspection and maintenance scheduling policies. Furthermore, in the presence of capacity constraints, Whittle indices via the multi-armed restless bandit formulation dynamically provide the optimal policies using the updated transition kernels. Results indicate a high accuracy rate in prediction and effective long-term scheduling policies that are adaptable to changing conditions

How Random Incidents Affect Travel-Time Distributions

We present a novel analytical model to approximate the travel-time distribution of vehicles traversing a freeway corridor that experiences random quality of service degradations due to non-recurrent incidents. The proposed model derives the generating function of travel times in closed-form using clearance time, incident frequency and severity, and other ordinary traffic characteristics. We validate the model using data from a freeway corridor where weather events and traffic accidents serve as the principal causes of service degradation. The resulting model is equivalent in performance to widely used methodologies while uniquely providing a clear connection on how incidents affect travel time distribution. With this connection, the model readily yields travel time reliability measures for alternative roadway behaviors, providing crucial information for long-term planning

Efficient Network Protection Games Against Multiple Types of Strategic Attackers

International audienceThis paper considers network protection games against different types of attackers for a heterogeneous network system with N units. A defender, by applying resources to networked units, can decrease the units' vulnerabilities. At the same time, the defender needs to take into account the cost of using defense resources. Two non-zero sum Nash games against two different types of attackers are studied. The first type tries to maximize damage based on the value of security assets related to networked units, while the second type aims at infiltrating the network. The analyses show that there exists a cutoff index determining the set of units that will be protected in the equilibrium strategies of the first game, while either all units or none will be covered in the equilibria of the second game. Numerical examples detail an application for wireless communication networks

Imperfect rail-track inspection scheduling with zero-inflated miss rates

Despite the technological advances in track monitoring, track quality control systems are not always reliable. Inspections may miss defects; all defects may not be registered or recorded due to human or mechanical errors. In this study, first, we develop a zero-inflated Bayesian approach to model the rate of missed defects during imperfect inspections where defect arrivals follow a Poisson process. The proposed model reveals information on two parameters: the actual defect arrival rate and the probability of not finding any defects, namely, the zero-inflation rate. Then, we study optimizing the track maintenance based on this model. We demonstrate that a temporal threshold-type inspection policy is optimal, and we derive this threshold under imperfect inspections. Furthermore, we implement a Gibbs sampler for drawing inferences on the posterior distribution of the aforementioned Poisson process parameters from data. Application results provide a realistic perspective on imperfect inspections and offer risk and cost savings in railway systems and, by and large, in other imperfect maintenance systems

Two-Person Zero-Sum Communicating Stochastic Games

For undiscounted two-person zero-sum communicating stochastic games with finite state and action spaces, a solution procedure is proposed that exploits the communication property, i.e., working with irreducible games over restricted strategy spaces. The proposed procedure gives the value of the communicating game with an arbitrarily small error when the value is independent of the initial state