In order to achieve scalability and robustness, verification and validation (V&V) of self-driving vehicle systems need to be largely performed virtually. This requires validated models on sensors, vehicles and environments where the systems are to operate. The aim of this pre-study is to identify state-of-the-art (SoA) and high-priority research questions within methods for validating models required for virtual V&V of self-driving vehicle systems within a fenced area, and to formulate a joint project application with identified key actors for further studies.<\/p>\n\n\n\n
The pre-study is expected to result in a SoA report and in a joint project application with identified key actors for further studies. The long-term goal is to obtain objective measures of the reliability of virtual V&V of self-driving vehicle systems. With a working method where validated models and real tests are used side by side, an efficient and predictable continuous V&V of the product\u00b4s quality and safety during its entire life cycle is enabled; pre-study phase, development phase; commissioning; maintenance & system optimizations.<\/p>\n\n\n\n
BTH project leader:<\/strong> Professor Tobias Larsson<\/a><\/p>\n\n\n\n Time span:<\/strong> 20220201 \u2013 20220831<\/p>\n\n\n\n Funding: <\/strong>2.2 MSEK (1.1 MSEK VINNOVA – Drive Sweden Innovation Programme<\/a>)<\/p>\n\n\n\n Partners:<\/strong><\/p>\n\n\n\n\n
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