Design a system for autonomous vehicles to dynamically adjust to changing road conditions and traffic patterns.

Example answer

Start with the decision the external information can influence: traffic-aware routing, weather-domain monitoring or another defined function. Identify source coverage, update delay, location resolution and failure modes. Forecasts and infrastructure reports are evidence with uncertainty, not guaranteed descriptions of the current scene.

Maintain timestamps, provenance, validity limits and conflict handling. Compare relevant local observations and avoid silently overriding a reliable observation with an older remote report. The system must have a defined response to unavailable or inconsistent information within its approved capabilities.

Evaluate prediction accuracy and calibration separately from end-to-end outcomes. Use held-out locations or periods appropriate to the intended generalization, and report exposure and scenario mix. A falling takeover count can reflect a changed driver policy or easier routes; it is not by itself proof of better autonomy.

Use replay and authorized closed-loop tests to investigate counterfactual effects while acknowledging their limitations. Release parameter or policy changes through review rather than automatically learning from every live feed. Record remaining gaps and monitor version-specific outcomes after an approved change.