论文标题
在无人驾驶汽车开发的概念阶段中有效危害识别
Towards Efficient Hazard Identification in the Concept Phase of Driverless Vehicle Development
论文作者
论文摘要
无人驾驶车辆的复杂功能结构引起了许多潜在的故障。既定的系统危害识别方法都会为每个发现的故障产生个体潜在的危险情况。这导致纯粹基于专家的危害分析过程中的效率低下，因为许多情况都必须单独检查。在这项贡献中，我们提出了对自动化车辆开发危险识别策略的改编。我们没有专注于故障，而是基于在概念阶段分析的选定操作场景中与所需车辆行为的偏差。通过评估外部可观察到的与所需行为的偏差，我们封装了个体故障并减少了产生的潜在危险场景的数量。在介绍了危害识别策略之后，我们说明了其在研究项目Unicar $ agil $中使用的操作方案之一上的应用。
The complex functional structure of driverless vehicles induces a multitude of potential malfunctions. Established approaches for a systematic hazard identification generate individual potentially hazardous scenarios for each identified malfunction. This leads to inefficiencies in a purely expert-based hazard analysis process, as each of the many scenarios has to be examined individually. In this contribution, we propose an adaptation of the strategy for hazard identification for the development of automated vehicles. Instead of focusing on malfunctions, we base our process on deviations from desired vehicle behavior in selected operational scenarios analyzed in the concept phase. By evaluating externally observable deviations from a desired behavior, we encapsulate individual malfunctions and reduce the amount of generated potentially hazardous scenarios. After introducing our hazard identification strategy, we illustrate its application on one of the operational scenarios used in the research project UNICAR$agil$.
