Project Summary
Train automation is key to reducing carbon emissions, but full automation is still a long way off. Driver Advisory Systems (DAS) offer a transition to automation, with demonstrated energy savings. However, usability challenges remain. The project aims to identify the impact of DAS, propose solutions to improve performance and energy savings, and contribute to the UK’s decarbonisation objectives. Improved system design and user interactions will be explored to overcome existing limitations.
Project Achievements
This project includes the development of a DAS solution aimed at reducing traction energy consumption. The solution considers driver requirements and seeks to maximise acceptance while improving user trust. To achieve this goal, the project team consulted with various individuals in the rail industry regarding DAS use and development. Based on the feedback received, the team developed a DAS system based on a prototype DAS system previously developed and validated through field trials in both the UK and worldwide. The new system underwent verification and further adjustments in a laboratory environment at University of Birmingham. Furthermore, a trial test of the DAS was conducted on a real tram line to further assess system performance. The test results demonstrate that by using the developed DAS, train energy consumption can be significantly reduced by up to 11% without affecting journey time constraints.
Conclusions
The outcomes of this project have the potential to significantly reduce the energy usage for railway transportation. The developed DAS has demonstrated its potential benefits through field tests showing a up to 11% reduction in energy consumption. Based on the saving, approx. £70,000 of the annual traction bill can be reduced on a single rail line. Considering the number of railway network in the UK and worldwide, the potential saving would be even larger. Furthermore, the new DAS solution aims to enhance the knowledge and improve the skills for human drivers, rather than use automation machines (e.g., ATO) to replace them.
Next Steps
The developed DAS solution is cost-effective and highly efficient, making it suitable for widespread adoption on various urban rail lines with line-of-sight driving. The project team at the Birmingham Centre for Railway Research and Education (BCRRE) is planning to collaborate with railway consulting companies to provide additional support for Nottingham Tram, Manchester Tram, West Midlands Metro, and other rail networks, including training courses, field tests, and implementation. The project team has also established contact with experts from Network Rail, Resonate, Hitachi, and other railway companies to further investigate the application of DAS on the UK mainline. Regular meetings have been arranged to exchange knowledge on DAS and advance the technology for the benefit of the UK railway. Furthermore, the project team is planning to integrate new image processing and object detection functions into the DAS. Thes e new functions will utilise cameras, lidar, and radar sensors along with AI algorithms to automatically detect trackside signals, potential obstacles, and nearby pedestrians and vehicles. This will provide early warnings to the drivers, enhancing train safety and improving operational performance.
