Driver Advisory System for Freight Train Based on Energy-saving Operation Optimization

To improve operation efficiency, more and more intelligent technologies are applied to the railway system. Compared with subway and high-speed rail, the intelligence level of the freight trains is relatively low, due to restrictions of the running environment. In this paper, a Connected Driver Advisory System(C-DAS) for freight trains is developed, which is mainly divided into two parts: onboard terminal and ground server. The onboard terminal provides a Man-Machine Interface(MMI), which can provide an energy-saving speed curve and control strategy for the train driver. Another function of the onboard terminal is to realize the train positioning. We use the position filtering algorithm based on electronic map to improve the positioning accuracy of the trains. The ground server and the onboard terminal are communicated by the 4G network. Different train energy-saving operation optimization algorithms can be integrated on the ground server. This paper proposes an Adaptive Differential Evolution(ADE) to provide an optimized train operation scheme for the onboard terminal. The simulation results have been compared with that of the traditional Differential Evolution(DE) algorithm, and the energy-saving ratio of ADE is improved by 12.1% to DE. Through field tests, it can be seen that the C-DAS can achieve precise positioning of the train, and provide train drivers with energy-saving train control schemes, which can improve the intelligence level of freight trains.