Does Knowledge About Perceptual Uncertainty Help an Agent in Automated Driving?

The paper examines how agents in automated driving respond to perceptual uncertainty and how providing explicit uncertainty information affects their behavior. Experiments on a proxy driving task show that unreliable perception leads to defensive driving, while incorporating uncertainty data enables the agent to adapt, complete the task faster, and better manage risks.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

• agents
• reinforcement-learning