%0 Journal Article
%T An MBSE Approach for Development of Resilient Automated Automotive Systems
%A Arun Adiththan
%A Azad M. Madni
%A Edwin Ordoukhanian
%A Joseph DĄŻAmbrosio
%A Padma Sundaram
%A Prakash Peranandam
%A S. Ramesh
%J -
%D 2019
%R https://doi.org/10.3390/systems7010001
%X Abstract 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. View Full-Tex
%K MBSE
%K advanced driver assistance systems
%K automated driving systems
%K safety of the intended functionality
%K utility function
%K test scenario
%U https://www.mdpi.com/2079-8954/7/1/1