Dynamic Trajectory Optimization Design for Railway Driver Advisory System

Driver Advisory Systems (DAS) aim to provide reliable and efficient driving instructions to the driver with optimized trajectory. This paper studies trajectory optimization method to achieve energy efficiency and punctuality for DAS. Firstly, the design of offline trajectory optimization is studied, using the Genetic Algorithm (GA) to optimize the energy-efficient trajectory. The performance of offline optimization is evaluated by the application of three different driving styles. Online optimization is constructed to dynamically adjust the trajectory when a driving deviation occurs. The combination of offline optimization and online optimization method is simulated as a dynamic trajectory optimization system, to represent a practical solution for DAS systems to achieve energy efficiency and punctuality by real-time adjustment during the journey. An evaluation of energy saving and computation efficiency for the trajectory optimization is conducted based on a simulation of a real-scale route.