Transcendental Idealism of Planner: Evaluating Perception from Planning Perspective for Autonomous Driving
Wei-Xin Li, Xiaodong Yang

TL;DR
This paper introduces a systematic framework for evaluating how perceptual noise affects autonomous vehicle planning, using a geometric interpretation inspired by transcendental idealism to provide a universal perception quality metric.
Contribution
It proposes a novel, holistic framework that links perception errors to planning outcomes through a Hilbert space geometric model, enabling consistent evaluation of perception modules.
Findings
Framework provides a universal metric for perception evaluation.
Geometric interpretation links perception noise to planning impact.
Holistic approach improves understanding of perception-planning relationship.
Abstract
Evaluating the performance of perception modules in autonomous driving is one of the most critical tasks in developing the complex intelligent system. While module-level unit test metrics adopted from traditional computer vision tasks are feasible to some extent, it remains far less explored to measure the impact of perceptual noise on the driving quality of autonomous vehicles in a consistent and holistic manner. In this work, we propose a principled framework that provides a coherent and systematic understanding of the impact an error in the perception module imposes on an autonomous agent's planning that actually controls the vehicle. Specifically, the planning process is formulated as expected utility maximisation, where all input signals from upstream modules jointly provide a world state description, and the planner strives for the optimal action by maximising the expected utility…
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Taxonomy
TopicsAdversarial Robustness in Machine Learning · Ethics and Social Impacts of AI · Psychology of Moral and Emotional Judgment
