Assessing Test Scenarios for Autonomous Driving Using Probabilistic Model Checking

doi:10.1007/978-3-032-05188-2_18

2026-01-01

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DOI：10.1007/978-3-032-05188-2_18

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摘要

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测试自动驾驶车辆是一项具有挑战性的任务，通常通过测试场景进行，这些场景通常从事故统计和真实交通数据集中手动导出。该过程依赖专家知识和直觉来选择最相关的场景，这对于这些数据集的大规模而言是一项繁琐的任务。在本文中，我们提出了一种基于模型的方法，通过概率模型检测计算用户定义时序逻辑属性的定量度量来比较场景，这些属性表征了有趣的事件序列。这种方法有助于选择在覆盖率和总体测试成本（包括模拟和实地测试）之间具有最佳权衡的场景。我们通过比较从事故统计中常见情况导出的场景变体，使用碰撞概率、到达概率和持续时间等度量来阐述该方法。

Keyword:

test scenarios

autonomous driving

probabilistic model checking

temporal logic

scenario assessment

期刊

TESTING SOFTWARE AND SYSTEMS, ICTSS 2025

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论文数:

被引数:

机构

communaute universite grenoble alpes

学者数:

3.5W

论文数: 2.7W

被引数: 29

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