|Coordinator||KUNGLIGA TEKNISKA HÖGSKOLAN - KTH CSC-skolan|
|Funding from Vinnova||SEK 1 286 084|
|Project duration||April 2016 - June 2019|
Purpose and goal
The goal of project SafeCOP was to develop product validation technologies for distributed software applications embedded in co-operative cyber-physical systems-of-systems (CO-CPS) such as vehicle platoons. Such applications often have a safety critical aspect, and need to be validated and possibly even certified. KTH has successfully developed a quantitive approach to safety analysis using machine learning technology. Our approach can be used to efficiently compute the safe operational range of embedded software in a fast and energy efficient way.
Expected results and effects
The quantitative safety analysis method developed by KTH will allow industrial developers of safety-critical software applications (e.g. autonomous vehicle designers) to quickly assess the safe operational range of their products. By using virtualized simulation environments, our research results speed up calculations by factors of 100-100000 and remove the risks of physical hardware testing. Our approach is energy efficient and can lower the energy costs of vehicle products. We are now investigating the commercial potential of these methods.
Planned approach and implementation
The KTH research was carried out in 3 stages: (i) analysis of needs for testing safety requirements (including quantitative and certification needs), (ii) requirements on tool support for safety analysis, and current tool capabilities, and (iii) design of a methodology for quantitative safety analysis and its evaluation on an industrial case study. The evaluation aspect was conducted in collaboration with SafeCOP partner QAMCOM AB. The evaluation case study was based on a wireless emergency brake protocol for a vehicle platoon.