Train management operators and asset management operators deal with complex control room environments and repeatedly make critical decisions with large scale impacts onto the whole train network and system. In IN2DREAMS we are improving the existing visualization systems in the control room environments allowing operators to better focus and respond to critical events. We support their decision-making process by embedding prediction models for predictive maintenance into the visualizations as well as forecasting the impact of the operators decisions onto the train network. We strive to implement these optimizations and enhancements in a non-obtrusive way such that the highly trained operators must not be retrained in using the systems and management processes.
- How can visualization systems in complex control room environments be improved sustainably?
- How can additional information from data-driven models for predictive maintenance be embedded into the existing visualization systems?
- How can the user’s attention be better steered to critical events in location and time?
- How can the decision-making process of the operator be improved through artificial intelligence?
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No: 777596.