Project Summary
A new scenario modelling tool is being developed to provide operational planners with a better understanding of how their decisions impact fuel consumption and emissions. This proof-of-concept project uses data science techniques to validate theoretical models with real-world fuel consumption data, enabling Northern Trains to test and demonstrate how data can deliver greener, cleaner, and more affordable rail services.
Project Achievements
The project provided an opportunity to collaborate w ith industry partners to experiment and develop this PoC. We actively engaged w ith potential end users throughout the project to ensure w e were always focussed on delivering value and insights that could be of use. We identified 4 use cases this PoC w ould specifically focus on as part of the Requirements Specification, and w e focussed on ensuring that these produced viable and useful outputs w hich could be used to explore the next steps and provide further improvements to the model. The model focussed specifically on a section of route w here the Operator is trying to implement improvements. This enabled us to engage w ith the right people to develop a good understanding of user needs. We successfully engaged 5 organisations to assist w ith the delivery of this project, w ithout w hom w e would not have been able to deliver these results or engage in discussions for next steps.
Conclusions
The project demonstrated it is viable to mathematically model the complex relationships betw een the variables that define how the train operates and interacts w ith its environment to calculate estimated fuel consumption and CO2 emissions. Further w ork is required to test and validate thoroughly, but in its current form, it is useful for engaging in discussions supporting operational decision making. E.g. the model illustrated that differing driving styles can have differing fuel consumption and emissions. A project like this requires collaborative w orking with Industry representatives, subject matter experts and technical delivery partners to ensure that the outputs are usable and useful.
Next Steps
We are in active discussions to develop the model further with the Train Operating Company. Specifically, there are two new work streams: 1. To expand the use case around Driving Styles by looking at other sections of the route where there is variation in driving style that could impact consumption and emissions 2. To expand the use case around emissions modelling to look at the contribution of different traction types in and around Manch ester Victoria Station We would also like to continue to develop and improve the base model by further testing and validation (with real data) and consulting with subject matter experts to model the variables that we have not yet been able to. The TRIG programme gave us the opportunity to bring together an experienced and diverse team who contributed to this project. This enabled us to bring together expertise, background knowledge and capability to build the modelling tool. Direct engagement with potential end users also meant that we focused our PoC on use cases which had the potential to deliver value as part of this project.
