DESTINE: Developing Predictable Vehicle Software Utilizing Time Sensitive Networking
| Reference number | |
| Coordinator | Mälardalens Universitet - Akademin för innovation, design och teknik, Västerås |
| Funding from Vinnova | SEK 6 709 606 |
| Project duration | January 2019 - December 2023 |
| Status | Completed |
| Venture | Electronics, software and communication - FFI |
Purpose and goal
The objective of this project is to develop new techniques and tools for vehicular applications using TSN as the backbone for onboard real-time communication. All project goals (Gs) are fulfilled. G1: Develop a new modelling technique for TSN and integrate it into state-of-the-art software development frameworks. G2: Developing end-to-end timing analysis for TSN. Develop a methodology for efficient TSN-based application design. G3: Develop a modular TSN switch design and prototype. G4: Proof-of-concept implementation and validation in industrial settings.
Expected results and effects
DESTINE developed novel techniques to support modelling, timing and resource analysis, simulation, configuration, optimisation, and execution of end-to-end behaviour of complex distributed software functions that are deployed over a TSN backbone. The project results are validated by implementing them to tool prototypes and developing an efficient design methodology for end-users while demonstrating on an industrial use case. The project results are disseminated beyond the scientific publications via industrial seminars, trainings, workshops, and other projects.
Planned approach and implementation
The project results are implemented, and their industry usability is demonstrated by: (i) implementing them to tool prototypes and an industrial use-case demonstrator, (ii) developing an efficient design methodology for end-users. The project consortium established an efficient value chain: from MDU (academia) developing new scientific techniques, to Arcticus (tool vendor) implementing these techniques as tool prototypes, to Volvo (end user) applying the tools and new techniques in the industrial use case, and back-propagation of the feedback on usability for refinement.