用本体论明确自动驾驶行为规范中的假设,提升安全性和可追溯性。
An Ontology-based Approach Towards Traceable Behavior Specifications in Automated Driving
- 基于本体构建自动驾驶行为规范,形式化表达目标环境下的行为要求。
- 在德国法律背景下验证,显式记录假设可识别并处理规范缺陷。
- 适合自动驾驶系统设计者与法规合规团队使用。
配备自动化驾驶系统的车辆需满足安全、遵守交通规则及提供出行服务等多重期望。开发者在系统设计阶段需定义其行为,但此类规范常依赖隐含假设与权衡,可能导致不充分甚至不安全的行为表现。为识别这些不足,需显式呈现需求与假设。本文提出语义规范行为分析(Semantic Norm Behavior Analysis)方法,利用本体技术形式化表示特定运行环境下的行为规范,并建立规范与利益相关方需求间的可追溯性。通过两个德国法律情境的案例,验证该方法有效性:显式记录假设能有效支持发现并处理规范缺陷。研究提供了用于自动化驾驶中本体驱动行为规范的术语、需求与方法论。
原文摘要 · Abstract (English)
Vehicles in public traffic that are equipped with Automated Driving Systems are subject to a number of expectations: Among other aspects, their behavior should be safe, conforming to the rules of the road and provide mobility to their users. This poses challenges for the developers of such systems: Developers are responsible for specifying this behavior, for example, in terms of requirements at system design time. As we will discuss in the article, this specification always involves the need for assumptions and trade-offs. As a result, insufficiencies in such a behavior specification can occur that can potentially lead to unsafe system behavior. In order to support the identification of specification insufficiencies, requirements and respective assumptions need to be made explicit. In this article, we propose the Semantic Norm Behavior Analysis as an ontology-based approach to specify the behavior for an Automated Driving System equipped vehicle. We use ontologies to formally represent specified behavior for a targeted operational environment, and to establish traceability between specified behavior and the addressed stakeholder needs. Furthermore, we illustrate the application of the Semantic Norm Behavior Analysis in a German legal context with two example scenarios and evaluate our results. Our evaluation shows that the explicit documentation of assumptions in the behavior specification supports both the identification of specification insufficiencies and their treatment. Therefore, this article provides requirements, terminology and an according methodology to facilitate ontology-based behavior specifications in automated driving.
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