Real-time railway traffic management under moving-block signalling: A literature review and research agenda

Railway traffic management is responsible for the detection and resolution of conflicts in case of disturbed operations. To minimise delay propagation, rescheduling decisions are taken by human dispatchers, possibly supported by mathematical models. Existing conflict detection and resolution (CDR) models mostly refer to conventional fixed...

A literature review of Artificial Intelligence applications in railway systems

Nowadays it is widely accepted that Artificial Intelligence (AI) is significantly influencing a large number of domains, including railways. In this paper, we present a systematic literature review of the current state-of-the-art of AI in railway transport. In particular, we analysed and discussed papers from a holistic railway perspective,...

Reinforcement Learning in Railway Timetable Rescheduling

Real-time railway traffic management is important for the daily operations of railway systems. It predicts and resolves operational conflicts caused by events like excessive passenger boardings/alightings. Traditional optimization methods for this problem are restricted by the size of the problem instances. Therefore, this paper proposes a...

Automated real-time railway traffic control: an experimental analysis of reliability, resilience and robustness

Railway transportation provides sustainable, fast and safe transport. Its attractiveness is linked to a broad concept of service reliability: the capability to adhere to a timetable in the presence of delays perturbing traffic. To counter these phenomena, real-time rescheduling can be used, changing train orders and times, according to rules of...

Optimal Management of Railway Perturbations by Means of an Integrated Support System for Real-Time Traffic Control

Automatic real-time control of railway traffic perturbations has recently received the attention of practitioners. The aim is to make use of mathematical algorithms to maintain the required service availability during unplanned disturbances to operations. In the literature many tools for real-time traffic control are proposed, but their effects...

The Copula Bayesian Network with mixed discrete and continuous nodes to forecast railway disruption lengths

The highly uncertain nature of a railway disruption complicates the tasks carried by the Dutch Operational Control Centre Rail (OCCR) in the Netherlands. A good prediction of disruption length is believed to help the decision making in dealing with the disruption. Zilko, et al. [Non-Parametric Bayesian Network to Forecast Railway Disruption...

Stability of railway dispatching solutions under a stochastic and dynamic environment

In the last decade simulation models and optimization environments have been developed that are able to address the complexity of real-time railway dispatching. Nevertheless, actual implementations of these systems in practice are scarce. Essential for implementation of an advanced dispatching system is the trust of traffic controllers into a...

An online railway traffic prediction model

Prediction of train positions in time and space is required for traffic control and passenger information. However, in practice only the last measured train delays are known and dispatchers must predict the arrival times of trains without adequate computer support. This paper presents a real-time tool for continuous online prediction of train...

Rescheduling models for network-wide railway traffic management

In the last decades of railway operations research, microscopic models have been intensively studied to support traffic operators in managing their dispatching areas. However, those models result in long computation times for large and highly utilized networks. The problem of controlling country-wide traffic is still open since the coordination...