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Evidence record 15715 · automatically gathered

Explainable AI analysis of brake control in CARLA through reference and distilled policies

This paper presents an explainable AI analysis of brake control in CARLA closed-loop driving. Longitudinal braking is studied through a threshold policy, a risk-aware reference policy, and a distilled policy learned from reference rollouts. The framework combines structured traffic-state features, high-fidelity XGBoost surrogates, and SHAP to analyze deployed brake behavior across Town10HD and Town05. Results show that brake generation is consistently dominated by front-vehicle distance, relativ

Record details

Published: 3 August 2026
Source: Frontiers in Robotics and AI
Category: Research
Topics: Regulation · Transparency
Retrieved: 3 August 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

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How to cite this record

ethics.ai (3 August 2026), “Explainable AI analysis of brake control in CARLA through reference and distilled policies,” evidence record 15715, https://ethics.ai/record/15715 (originally published by Frontiers in Robotics and AI).

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