Challenges of Virtual Validation and Verification for Automotive Functions

2025-08-20

AI Summary

Automotive functional virtual verification and validation (V&V) face critical challenges, including insufficient simulation safety assurance and incomplete scenario coverage. This study identifies 17 core technical and operational challenges through multiple expert workshops, complemented by an industry-wide questionnaire survey to systematically map existing solutions and their implementation barriers. Its key contribution is the first quantitative identification of “inadequate resource investment” as a latent, systemic constraint—revealing a significant gap between proposed technical solutions and real-world engineering practice. Based on this analysis, the study prioritizes four strategic research and development directions: (1) high-fidelity simulation modeling, (2) scalable scenario generation, (3) automated V&V frameworks, and (4) cross-organizational collaboration mechanisms. The findings deliver a clear research roadmap for academia and empirically grounded guidance for industry V&V capability building, thereby strengthening industry–academia–research synergy.

Technology Category

• Planning, Routing, and Scheduling: Model-Based Reasoning
• Knowledge Representation and Reasoning: Argumentation
• Search and Optimization: Sampling/Simulation-based Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Web Mining and Content Analysis: Web data generation and simulation

Abstract

Verification and validation of vehicles is a complex yet critical process, particularly for ensuring safety and coverage through simulations. However, achieving realistic and useful simulations comes with significant challenges. To explore these challenges, we conducted a workshop with experts in the field, allowing them to brainstorm key obstacles. Following this, we distributed a survey to consolidate findings and gain further insights into potential solutions. The experts identified 17 key challenges, along with proposed solutions, an assessment of whether they represent next steps for research, and the roadblocks to their implementation. While a lack of resources was not initially highlighted as a major challenge, utilizing more resources emerged as a critical necessity when experts discussed solutions. Interestingly, we expected some of these challenges to have already been addressed or to have systematic solutions readily available, given the collective expertise in the field. Many of the identified problems already have known solutions, allowing us to shift focus towards unresolved challenges and share the next steps with the broader community.

Problem

• Identifying key challenges in automotive virtual verification and validation
• Exploring expert-proposed solutions for realistic simulation obstacles
• Focusing on unresolved issues despite existing known solutions

Innovation

• Workshop with experts to brainstorm challenges
• Survey distributed to consolidate findings and solutions
• Focus shifted to unresolved challenges with known solutions