(untitled) (American Journal of Engineering , Mechanics and Architecture (2993-2637), 2025)
Optimizing train operating modes is essential for enhancing energy efficiency, reducing operational costs, improving punctuality, and ensuring passenger comfort in modern railway systems. This paper outlines the key tasks involved in achieving optimal train performance under varying conditions. These tasks include real-time data acquisition, dynamic route profiling, predictive speed control, adaptive braking strategies, energy consumption forecasting, and integration of multi-objective optimization algorithms. The study also emphasizes the role of digital technologies such as AI, IoT, and model predictive control (MPC) in enabling smart, adaptive train operation. By systematically addressing these tasks, railway operators can enhance overall system reliability, reduce environmental impact, and support the transition to intelligent and sustainable transportation infrastructure.