Name
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. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.3390/systems7010001 | SYSTEMS |
Keywords | Field | DocType |
MBSE, advanced driver assistance systems, automated driving systems, safety of the intended functionality, utility function, test scenario | Psychological resilience,Advanced driver,Systems engineering,Computer science,Partially observable Markov decision process,Advanced driver assistance systems,Markov decision process,Design methods,Scenario testing,Automotive systems,Artificial intelligence,Natural language processing | Journal |
Volume | Issue | ISSN |
7 | 1 | 2079-8954 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
7 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Joseph D'Ambrosio | 1 | 3 | 0.74 |
| Arun Adiththan | 2 | 13 | 8.26 |
| Edwin Ordoukhanian | 3 | 0 | 1.01 |
| Prakash Peranandam | 4 | 9 | 0.80 |
| Ramesh, S. | 5 | 144 | 19.02 |
| Azad M. Madni | 6 | 188 | 34.57 |
| Padma Sundaram | 7 | 0 | 0.34 |