Email this article Explainable AI for Enhancing Trust in Autonomous Vehicles
Abstract
As autonomous vehicles (AVs) become increasingly prevalent, ensuring user trust in their decision-making processes is paramount. This paper presents a framework for Explainable AI (XAI) tailored to AV systems. By employing interpretable machine learning models and visualization techniques, the framework provides real-time explanations for critical driving decisions. A user study is conducted to evaluate the impact of these explanations on trust and acceptance of AVs. Results indicate that explainability significantly enhances user confidence while maintaining system performance.
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