Modeling real time CBTC operation in mixed traffic networks: A simulation-based approach

Vehicle automation and continuous connection with communication networks are the key innovations currently redefining transport systems. Just as autonomous cars are rapidly changing road transport, increasing railway automation will help to maximize the use of infrastructure, increase schedule reliability, improve safety, and increase energy efficiency. However, railway operations are fundamentally different from road-based transport systems and automation must be specifically tailored to railway characteristics. This paper investigates how optimization methods (e.g., for energy consumption minimization) can be integrated into mixed traffic railway operations supported by CBTC (Communications Based Train Control) systems and ATO (Automated Train Operation). It presents a method for simulation-based modeling to precisely evaluate potential trajectory modifications by taking into consideration the entire process, from the decision to modify train operation, through the computing phase to final implementation. The proposed method generates solutions that fully consider the surrounding rail traffic and schedule constraints. This proposed simulation based optimization method was tested by developing alternative trajectories for energy efficient driving in real time and then applying them in a case study performed using the OpenTrack railway simulation model. The case study results showed that it was possible to integrate optimization methods with simulation models to provide instructions that can be implemented via CBTC. In the case study example, it was possible to achieve a general energy saving of 23% on average with an increased travel time of 8% on average