This paper presents a novel approach in train control systems based on the concept called virtual coupling or train convoys. This approach follows the recent developments in the field of safe platooning of autonomous vehicles. We use a decentralized model predictive control (MPC) framework for each train participating in a convoy formation. Control designs for the leading and following trains are presented. An optimal control formulation for both controllers is used and its design relies on a numeric solution of a finite horizon optimal control problem. This paper compares the proposed method with alternative control strategies including the well-studied moving block train control concept. A study of a metro line has been chosen as a first analysis for this control approach. The simulation results for this kind of railway lines demonstrate better performance and the benefits of this new concept versus the moving block system. We show that the virtual coupling concept substantially reduces headway and distance between trains while guaranteeing safe separation between two consecutive trains at any instant.

The current mobility situation is constantly changing as people are increasingly moving to urban areas. Therefore, a flexible mode of transport with high-capacity passenger trains and a high degree of modularity in the trains’ composition is necessary. Virtual coupling (VC) is a promising solution to this problem because it significantly increases the capacity of a line and provides a more flexible mode of operation than conventional signaling systems. This novel review, in which approximately 200 papers were analyzed, identifies the main topics of current railway-related VC research, and represents the first step toward the implementation of VC in future railways. It was found that industry research has mainly focused on the feasibility of VC implementation and operation, whereas in academia, which is coordinated with industry, research has focused on control and communication systems. From a technological perspective, the main challenges for VC were identified with regard to aspects such as safety, control technology, interlocking, vehicle-to-vehicle communication, cooperative train protection and control, and integrated traffic management. The important directions for future research that have been identified for future development include complete dynamic models, real-time controllers, reliable and secure communication, different communication topologies, cybersecurity, intelligent control, reinforcement learning, and Big Data analytics.

This paper describes a microscopic model that is able to simulate traffic situations in an urban environment in real time for use in driving simulators. Two types of vehicles are considered in the simulation, namely the user-driven vehicle at the center of the simulation model and the other vehicles that interact with it and its surroundings, which configure the developed traffic model. Simulation is performed in a reduced zone, called the control zone, surrounding the user-driven vehicle. This control zone is a mobile zone centered on the user-driven vehicle. The size of the control zone depends on the maximum number of vehicles involved simultaneously, the traffic density, and the driver's limit of visibility. The other vehicles involved in the traffic simulation are created or destroyed within the limits of the control zone. The general behavior of the traffic model is based on the following theory. Vehicles have an associated driver model that establishes several control functions for them to follow the path, while the steering, acceleration, and braking maneuvers follow certain models of behavior. A traffic light regulation is also included but only in the control area. The possibility of introducing anomalous traffic situations into the simulation is also considered, such as the presence of obstacles, abnormal maneuvers, etc. The developed model is immediately applicable to large-scale driving simulators for driver training, traffic control studies, and safety studies

This paper addresses the challenge of decarbonizing residential energy consumption by developing an advanced energy management system (EMS) optimized for cost reduction and energy efficiency. By leveraging the thermal inertia of building envelopes as a form of thermal energy storage (TES), the proposed EMS dynamically balances energy inputs from the electrical grid, photovoltaic (PV) systems, and battery storage, while regulating HVAC operations. Employing model predictive control (MPC) and integrating real-time data on energy prices, weather conditions, and consumption patterns, the system minimizes energy costs, while maintaining indoor thermal comfort. Simulations conducted for both summer and winter scenarios demonstrate significant reductions in energy costs. Laboratory and real-world testing confirm the EMS’s efficacy in enhancing energy efficiency, increasing PV self-consumption, and reducing reliance on grid energy, marking a step forward in sustainable energy solutions for residential applications.

In recent decades, the demand for rail transport has been growing steadily and faces a double problem. Not only must the transport capacity be increased, but also a more flexible service is needed to meet the real demand. Both objectives can be achieved through virtual coupling (VC), which is an evolution of the current moving block systems. Trains under VC can run much closer together, forming what is called a virtually coupled train set (VCTS). In this paper, we propose an approach in which virtual coupling is implemented via model predictive control (MPC). For this purpose, we define a robust controller that can predict, based on a dynamic model of the train, the state of the system at later moments of time and make the appropriate control decisions. A robust MPC (RMPC) is obtained by introducing two uncertain variables. The first uncertain variable is added to the acceleration equation of the dynamic model, while the second uncertain variable is used to define the uncertainty in the train positioning. To test the RMPC for virtual coupling, two simulation cases are performed for a metro line, analysing the influence of both the uncertainties. In all cases, the results obtained show a safer operation of the virtual coupling without significantly affecting the service.