Vehicle Motion Control Using Data-Driven Varying Road Friction Map
| Reference number | |
| Coordinator | Volvo Personvagnar AB - 96360 - EP and Safe AD V&V |
| Funding from Vinnova | SEK 7 491 360 |
| Project duration | April 2021 - March 2026 |
| Status | Completed |
| Venture | Traffic safety and automated vehicles -FFI |
| Call | Road safety and automated vehicles - FFI - December 2020 |
| End-of-project report | 2020-05169 eng.pdf (pdf, 401 kB) |
Important results from the project
The project has fulfilled the objective of developing a pipeline for road condition estimation algorithm using different onboard sensors, as well as the potential use cases to improve vehicle motion planning and control at adverse weather conditions. Friction map performance requirements on uncertainty, accuracy, confidence, availability are generated using an optimal control framework.
Expected long term effects
The project has initiated the effort to close the unknown knowledge gap between estimation and users of this estimation. As the road condition friction information will be part of the shared information in the future together with smart route navigation apps, the data utilization business model and framework can be easily extended from the results of this proposed project. We foresee also the potential to better support the road authorities for more efficient road maintenance.
Approach and implementation
The project team includes two senior researchers, one Post doc and one PhD student from Chalmers, as well as one technical expert and several software engineers at Volvo Cars. The technical expert is the project leader, who makes sure that project reaches academic depth with high industrial relevance. The data collection and vehicle instrumentation went smoothly with full support from Volvo Cars. The collaboration was seamless which made the project on track given the challenging topic.