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Evidence record 19030 · automatically gathered

Learning-Based Behavior Planning for Automated Driving: Real-World Integration and Deployment

Recent research in machine and deep learning has shown the potential of learningbased motion planning approaches to improve the driving behavior of automated vehicles, especially in complex environments. However, their complex nature and lack of transparency can hinder explainability and trustworthiness and complicate safety assurance. Motivated by these challenges, we propose a hybrid planning architecture that combines the advantages of machine learning with the verifiability and the determini

Record details

Published: 12 August 2026
Source: arXiv cs.AI
Category: Research
Topics: Transparency · Environment
Retrieved: 13 August 2026

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How to cite this record

ethics.ai (12 August 2026), “Learning-Based Behavior Planning for Automated Driving: Real-World Integration and Deployment,” evidence record 19030, https://ethics.ai/record/19030 (originally published by arXiv cs.AI).

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