RAPIDS
Project leader:
- Tony Lindgren, Associate Professor, DSV, SU
Researchers
- Zahra Kharazian, PhD student, DSV, SU
Partners
- Scania Vehicle Service Information
- Royal institute of Technology, Division of software and computer systems
- Linköping University, Department of Computer Science and Engineering (ISY)
Project period: 2022-01-01 to 2024-12-31
Funding: Vinnova and Scania
Budget: Approx 19.4M SEK
Description
Customer demands on operational uptime of vehicles have increased in recent years and are expected to be further accentuated with the introduction of autonomous and electrified vehicles. Forecasting, and data analysis in general, is an area where machine learning has a strong industrial potential. In a previous research projects, CODA, funded by FFI and Scania the potential of using data-driven and interpretable methods to plan maintenance was demonstrated.
The project revolves around developing machine learning models based on increased availability of streamed log data from vehicles and integration of these models in the decision-making processes for maintenance. It specifically deals with how uncertainty in predictions can be estimated and weighed in order to make robust individual-based decisions. Central is also how new data can be fed back to the models in order to improve performance and predictive power.
The project will develop theory and generally applicable methods which are then tested and demonstrated on real use cases. The project will help to strengthen the research fields of machine learning and forecasting, specifically in the areas of models for streamed log data, data-driven decision making under uncertainty and efficient model feedback.
The main work packages of the project are:
- Predictive models based on streaming data
Project manager: Erik Frisk, Linköping University. - Data driven decision making under uncertainty
Project Manager: Anders Vesterberg, Scania. - Feedback for data driven models
Project Manager: Tony Lindgren, Stockholm University.
The main applicant for the project is Scania CV AB (project leader: Olof Steinert) and the other parties are Linköping University, Department of Systems Engineering, Stockholm University, Department of Computer Science, and Royal Institute of Technology, Division of software and computer systems.
People
Tony Lindgren, Associate Professor
