Work Packages
AI4SDV is organised in eight interconnected work packages, from requirements and methods to implementation, validation, impact and management.
WP1–WP3 focus on tool and toolchain development. WP4 orchestrates and validates the tools in realistic industrial environments, and WP5 demonstrates them in seven use cases. WP6 builds the ecosystem around the AI4SDV tools and platform, WP7 handles communication, dissemination, exploitation and standardisation, and WP8 manages the project.
WP1Requirements & Architecture
Lays the groundwork for the AI-assisted tools and services and for an open, extensible, standards-aligned platform architecture. WP1 investigates current ECS/SDV development practices, defines AI-relevant requirements (explainability, trustworthiness, data privacy, certification readiness, human–AI collaboration, EU AI Act and safety standards) and specifies toolchains and interfaces across all engineering phases.
Tasks
- T1.1 Requirements Engineering Phase
- T1.2 Architecture, Modelling & Design Phase
- T1.3 Implementation & Integration Phase
- T1.4 Testing, Verification & Validation Phase
- T1.5 Release Management & Deployment Phase
- T1.6 In-Use Monitoring & Data Analysis Phase
- T1.7 Orchestration Infrastructure
WP2Methodologies
Establishes the methodological and technological foundations for next-generation SDV engineering toolchains: AI-assisted engineering with generative, agentic and predictive AI, integration of formal and model-based methods, service-oriented toolchain architectures and workflow automation, including techniques against hallucination and for human feedback.
Tasks
- T2.1 LLM and Context Awareness
- T2.2 Agentic AI and Human-in-the-Loop
- T2.3 Model-Based Engineering and Formal Methods
- T2.4 Data Intelligence and Decisioning
WP3Implementation
Implements the AI-assisted tools and services that support every SDV engineering phase (A–F). Building on the requirements of WP1 and the methods of WP2, WP3 delivers prototype software components and toolchains that show how AI and model-based engineering work in practical SDV engineering.
Tasks
- T3.1 Requirement Engineering Phase
- T3.2 Architecture, Modelling & Design Phase
- T3.3 Implementation & Integration Phase
- T3.4 Testing, Verification & Validation Phase
- T3.5 Release Management & Deployment Phase
- T3.6 In-Use Monitoring & Data Analysis Phase
WP4Orchestration and Toolchain Integration
Orchestrates heterogeneous development tools into a cohesive, traceable and repeatable workflow, validates their interoperability end-to-end in realistic industrial environments with real-world data, and provides the credibility evidence needed to use AI-assisted tools for safety-critical automotive software.
Tasks
- T4.1 Process Formalization, Customization, Migration and Collaboration
- T4.2 Data and Interoperability Adapters
- T4.3 Control, Orchestration and Workflow Management
- T4.4 Deployment and Credibility Evidence
WP5Verification and Validation in Use Cases
Verifies and validates the AI4SDV tools against functional and non-functional requirements and KPIs by applying them in seven industry-led use cases, and turns these use cases into demonstrators that show reduced cycle times, lead times and defect rates.
Tasks
- T5.1 UC1 – Trustworthy OTA Testing and Validation Orchestration for SDV
- T5.2 UC2 – AI-driven Continuous Evolution for Enhanced Perception
- T5.3 UC3 – Secure Feedback-Driven Engineering
- T5.4 UC4 – SDV Augmented Vehicle-Human Interfaces
- T5.5 UC5 – Intelligent and Adaptive SDV Navigation and Positioning
- T5.6 UC6 – Evaluation of SDV AI Tools for Lighting Lifecycle
- T5.7 UC7 – Intelligent Configuration Assistant for SDV Middleware
WP6Impact and Ecosystem Building
Builds a sustainable ecosystem around the AI4SDV platform, its tool developers and users: collaboration and knowledge sharing with ECS engineering communities and open-source initiatives such as Eclipse, open standards and interfaces, and demonstrations released as open-source reference implementations.
Tasks
- T6.1 Establishment of the AI4SDV Ecosystem Forum
- T6.2 Development of Open Standards and Interfaces
- T6.3 Demonstration of Solutions in Automotive and Other Domains
WP7Communication, Dissemination, Exploitation, Standardization
Defines and implements the dissemination, communication and exploitation plan, establishes the AI4SDV brand, runs the project website as a knowledge hub for EU-funded SDV research, fosters clustering with related initiatives, supports standardisation and prepares a sustainable exploitation strategy beyond the project lifetime.
Tasks
- T7.1 Dissemination & Communication
- T7.2 Exploitation
- T7.3 Standardization
- T7.4 Liaison with Other Projects – Project Clustering and Partner Interfaces
WP8Project Management
Ensures the successful execution of the project through professional coordination: the contractual link with the funding authority, risk and quality management, effective communication between partners and work packages, scientific coordination and data management guidelines.
Tasks
- T8.1 Project Coordination and Technical Management
- T8.2 Data and Privacy Management
- T8.3 Risk and Quality Management
Milestones
| ID | Milestone | Work packages | Month |
|---|---|---|---|
| MS1 | Baseline of the AI4SDV solutions defined and documented: initial requirements, tooling and platform architecture, ecosystem strategy and validation strategy. | WP1, WP5, WP6 | M6 |
| MS2 | Base proof-of-concept toolset implemented, orchestrated into toolchains and initially validated (end of Iteration 1). | WP2, WP3, WP4, WP5 | M12 |
| MS3 | Refinement of the AI4SDV solution defined, based on the MS2 evaluation. | WP1, WP6 | M18 |
| MS4 | Refined toolset implemented, interfaces harmonised and validated again (end of Iteration 2). | WP5 | M24 |
| MS5 | Final refinement for industrialisation defined; integration methodology and compliance documented. | WP2 | M33 |
| MS6 | Final toolset for industrialisation implemented and validated; deployment strategy and impact summary delivered. | WP3, WP4, WP5, WP6 | M36 |