Scenario-Based ADS Compliance Validation
Defines repeatable scenario-based methods to validate automated driving system behavior and generate evidence for compliance and safety claims during testing and validation.
The Problem
“Scenario-Based ADS Compliance Validation for Evidence-Backed Safety Claims”
Organizations face these key challenges:
Regulatory and safety requirements are spread across standards, internal policies, and engineering documents
Scenario definitions and test methods are inconsistent across teams and programs
Manual review of telemetry, video, and event logs is slow and difficult to reproduce
Pass/fail criteria for dynamic driving tasks are often ambiguous or encoded in analyst-specific scripts
Impact When Solved
The Shift
Human Does
- •Interpret regulations, ODD constraints, and safety requirements into scenario definitions
- •Define test methods, metrics, and pass/fail criteria across simulation, track, and road testing
- •Review telemetry, logs, and video manually to judge ADS behavior in each scenario
- •Compile traceable evidence and reports for safety case, compliance, and release decisions
Automation
Human Does
- •Approve scenario catalogs, validation criteria, and evidence standards for compliance use
- •Review flagged edge cases, ambiguous outcomes, and exceptions requiring engineering judgment
- •Decide on safety claims, release readiness, and required corrective actions from validation results
AI Handles
- •Extract obligations from regulations and internal requirements and map them to applicable scenarios
- •Identify scenario segments in test data, compute validation metrics, and apply pass/fail rules consistently
- •Detect behavioral deviations, coverage gaps, and missing evidence across simulation, track, and road-test results
- •Generate traceable evidence packs, summaries, and linked artifacts for compliance and safety case workflows
Operating Intelligence
How it works
AI runs the first three steps autonomously.
Humans own every decision.
The system gets smarter each cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Assemble Context
Step 2
Analyze
Step 3
Recommend
Step 4
Human Decision
Step 5
Execute
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.
The Loop
6 steps
Assemble Context
Combine the relevant records, signals, and constraints.
Analyze
Evaluate options, risk, and likely outcomes.
Recommend
Present a ranked recommendation with supporting rationale.
Human Decision
A human accepts, edits, or rejects the recommendation.
Authority gates · 1
The system must not approve scenario catalogs, validation criteria, or evidence standards for compliance use without review by validation, safety, or compliance leaders [S1].
Why this step is human
The decision carries real-world consequences that require professional judgment and accountability.
Execute
Carry out the approved action in the operating workflow.
Feedback
Outcome data improves future recommendations.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in Scenario-Based ADS Compliance Validation implementations:
Key Players
Companies actively working on Scenario-Based ADS Compliance Validation solutions: