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  • 标题:An MBSE Approach for Development of Resilient Automated Automotive Systems
  • 作者:Joseph D’Ambrosio ; Joseph D’Ambrosio ; Arun Adiththan
  • 期刊名称:Systems
  • 电子版ISSN:2079-8954
  • 出版年度:2019
  • 卷号:7
  • 期号:1
  • 页码:1
  • DOI:10.3390/systems7010001
  • 语种:English
  • 出版社:MDPI Publishing
  • 摘要:Advanced driver assistance and automated driving systems must operate in complex environments and make safety-critical decisions. Resilient behavior of these systems in their targeted operation design domain is essential. In this paper, we describe developments in our Model-Based Systems Engineering (MBSE) approach to develop resilient safety-critical automated systems. An MBSE approach provides the ability to provide guarantees about system behavior and potentially reduces dependence on in-vehicle testing through the use of rigorous models and extensive simulation. We are applying MBSE methods to two key aspects of developing resilient systems: (1) ensuring resilient behavior through the use of Resilience Contracts for system decision making; and (2) applying simulation-based testing methods to verify the system handles all known scenarios and to validate the system against potential unknown scenarios. Resilience Contracts make use of contract-based design methods and Partially Observable Markov Decision Processes (POMDP), which allow the system to model potential uncertainty in the sensed environment and thus make more resilient decisions. The simulation-based testing methodology provides a structured approach to evaluate the operation of the target system in a wide variety of operating conditions and thus confirm that the expected resilient behavior has indeed been achieved. This paper provides details on the development of a utility function to support Resilience Contracts and outlines the specific test methods used to evaluate known and unknown operating scenarios.
  • 关键词:MBSE; advanced driver assistance systems; automated driving systems; safety of the intended functionality; utility function; test scenario MBSE ; advanced driver assistance systems ; automated driving systems ; safety of the intended functionality ; utility function ; test scenario
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