RESILIENT AND CONTINUOUS SAFETY ASSURANCE METHODOLOGY FOR CCAM AND ITS HMI COMPONENTS
Sector: Warehouse • Location: Spain, Germany, Greece, Netherlands, Austria, Belgium, United Kingdom, France
Source: EU Funding & Tenders Portal
User acceptance, AI-based systems validation, continuous assessment, and virtualization are essential to extend the harmonized SAF and ensure safe CCAM introduction and operation. SUNRISE is developing an advanced SAF in collaboration with regulatory bodies, using a scenario-based approach enabled by the SYNERGIES project. CERTAIN will develop and embed additional components to extend the SAF for
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ongoing |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | User acceptance, AI-based systems validation, continuous assessment, and virtualization are essential to extend the harmonized SAF and ensure safe CCAM introduction and operation. SUNRISE is developing an advanced SAF in collaboration with regulatory bodies, using a scenario-based approach enabled by the SYNERGIES project. CERTAIN will develop and embed additional components to extend the SAF for immediate implementation, ensuring stakeholder agreement. This will be achieved through four Use Cases covering all automation levels, vehicle types, and diverse road users. CERTAIN aims to create a comprehensive SAF addressing gaps in CCAM development and deployment, emphasizing safety, trust, acceptance, and comfort for all road users. The CERTAIN consortium, comprising leading European research institutions, industry partners, and stakeholders, will tackle critical challenges in CCAM system validation. Continuous engagement with stakeholders and regulatory entities will aim for the framework's acceptance and deployment. The project's outcomes will provide a solid foundation for widespread CCAM system adoption, fostering trust among users, industry stakeholders, and regulators. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
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