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Auteurs principaux: Li, Changwen, Sifakis, Joseph, Yan, Rongjie, Zhang, Jian
Format: Preprint
Publié: 2025
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Accès en ligne:https://arxiv.org/abs/2507.13661
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author Li, Changwen
Sifakis, Joseph
Yan, Rongjie
Zhang, Jian
author_facet Li, Changwen
Sifakis, Joseph
Yan, Rongjie
Zhang, Jian
contents Despite extensive research, the testing of autonomous driving systems (ADS) landscape remains fragmented, and there is currently no basis for an informed technical assessment of the importance and contribution of the current state of the art. This paper attempts to address this problem by exploring two complementary aspects. First, it proposes a framework for comparing existing test methods in terms of their intrinsic effectiveness and validity. It shows that many methods do not meet both of these requirements. Either because they are based on criteria that do not allow for rapid, inexpensive, and comprehensive detection of failures, or because the degree of validity of the properties tested cannot be accurately estimated. In particular, it is shown that most critical test methods do not take into account the nominal operational capabilities of autopilots and generate scenarios that are impossible for the tested vehicles to handle, resulting in unjustified rejections. Secondly, the paper shows that test effectiveness and validity are highly dependent on how autopilots are designed: how they choose between different control policies to perform maneuvers, as well as on the reproducibility of the results. In fact, most test methods take for granted two principles underlying traditional methods, but do not generally apply to ADS. We maintain that the absence of rationality and determinacy significantly impairs the effectiveness and validity of test methods, and provide test results on eight open autopilots, in which most do not satisfy these properties, thereby illustrating this fact. We conclude that under the current state of the art, it is impossible to obtain strong enough guarantees for essential autopilot properties and recommend that autopilots be developed with a view to both rationality and determinacy.
format Preprint
id arxiv_https___arxiv_org_abs_2507_13661
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Testing Autonomous Driving Systems -- What Really Matters and What Doesn't
Li, Changwen
Sifakis, Joseph
Yan, Rongjie
Zhang, Jian
Software Engineering
Despite extensive research, the testing of autonomous driving systems (ADS) landscape remains fragmented, and there is currently no basis for an informed technical assessment of the importance and contribution of the current state of the art. This paper attempts to address this problem by exploring two complementary aspects. First, it proposes a framework for comparing existing test methods in terms of their intrinsic effectiveness and validity. It shows that many methods do not meet both of these requirements. Either because they are based on criteria that do not allow for rapid, inexpensive, and comprehensive detection of failures, or because the degree of validity of the properties tested cannot be accurately estimated. In particular, it is shown that most critical test methods do not take into account the nominal operational capabilities of autopilots and generate scenarios that are impossible for the tested vehicles to handle, resulting in unjustified rejections. Secondly, the paper shows that test effectiveness and validity are highly dependent on how autopilots are designed: how they choose between different control policies to perform maneuvers, as well as on the reproducibility of the results. In fact, most test methods take for granted two principles underlying traditional methods, but do not generally apply to ADS. We maintain that the absence of rationality and determinacy significantly impairs the effectiveness and validity of test methods, and provide test results on eight open autopilots, in which most do not satisfy these properties, thereby illustrating this fact. We conclude that under the current state of the art, it is impossible to obtain strong enough guarantees for essential autopilot properties and recommend that autopilots be developed with a view to both rationality and determinacy.
title Testing Autonomous Driving Systems -- What Really Matters and What Doesn't
topic Software Engineering
url https://arxiv.org/abs/2507.13661