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Computer Science > Robotics

arXiv:2506.02688 (cs)
[Submitted on 3 Jun 2025 ]

Title: Stochastic Modeling of Road Hazards on Intersections and their Effect on Safety of Autonomous Vehicles

Title: 交叉路口道路危险的随机建模及其对自动驾驶车辆安全的影响

Authors:Peter Popov, Lorenzo Strigini, Cornelius Buerkle, Fabian Oboril, Michael Paulitsch
Abstract: Autonomous vehicles (AV) look set to become common on our roads within the next few years. However, to achieve the final breakthrough, not only functional progress is required, but also satisfactory safety assurance must be provided. Among those, a question demanding special attention is the need to assess and quantify the overall safety of an AV. Such an assessment must consider on the one hand the imperfections of the AV functionality and on the other hand its interaction with the environment. In a previous paper we presented a model-based approach to AV safety assessment in which we use a probabilistic model to describe road hazards together with the impact on AV safety of imperfect behavior of AV functions, such as safety monitors and perception systems. With this model, we are able to quantify the likelihood of the occurrence of a fatal accident, for a single operating condition. In this paper, we extend the approach and show how the model can deal explicitly with a set of different operating conditions defined in a given ODD.
Abstract: 自动驾驶车辆(AV)在未来几年内有望成为道路上常见的交通工具。然而,要实现最终的突破,不仅需要功能上的进步,还需要提供令人满意的安全保障。其中,一个需要特别关注的问题是如何评估和量化自动驾驶车辆的整体安全性。这种评估必须同时考虑自动驾驶车辆功能的缺陷以及它与环境的交互作用。在之前的一篇论文中,我们提出了一种基于模型的方法来评估自动驾驶车辆的安全性,在该方法中,我们使用概率模型来描述道路危险,并结合自动驾驶功能(如安全监控系统和感知系统)的不完美行为对安全性的影响。通过这个模型,我们可以量化单个运行条件下致命事故发生的可能性。在这篇文章中,我们将扩展这种方法,并展示该模型如何明确地处理一组定义在特定ODD中的不同运行条件。
Comments: This work has been submitted to the IEEE for possible publication
Subjects: Robotics (cs.RO)
Cite as: arXiv:2506.02688 [cs.RO]
  (or arXiv:2506.02688v1 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2506.02688
arXiv-issued DOI via DataCite

Submission history

From: Cornelius Buerkle [view email]
[v1] Tue, 3 Jun 2025 09:41:34 UTC (4,040 KB)
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