Resilience analysis and design for mobility-as-a-service based on enterprise architecture modeling
The development of a service that integrates multiple systems, platforms, and businesses, such as Mobility as a Service (MaaS), has attracted the attention of engineers and scholars. However, because of the complexity of the interactions of its subsystems, it is difficult to ensure the reliability o...
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Veröffentlicht in: | Reliability engineering & system safety 2023-01, Vol.229, p.108812, Article 108812 |
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Sprache: | eng |
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Zusammenfassung: | The development of a service that integrates multiple systems, platforms, and businesses, such as Mobility as a Service (MaaS), has attracted the attention of engineers and scholars. However, because of the complexity of the interactions of its subsystems, it is difficult to ensure the reliability of an integrated service, and the analysis approach of the individual subsystems that influence each other is insufficient. Even though many studies on functional safety for road vehicles have been conducted, there are currently no theoretical or experimental reports on MaaS reliability issues at the service level. To fill the void, we propose in this paper a resilience analysis method to facilitate the development of reliable mobility services. As a result, we proposed a novel MaaS resilience analysis and design method. We contend that a connection with enterprise architecture modeling helps to address resilience concerns for MaaS reliability. The claim is based on the close connection between resilience and reliability. Furthermore, we conduct a controlled experiment to demonstrate the efficacy of the proposed method and compare it quantitatively to a referenced method.
•Defines a Stakeholder Value & Uncertainty Map to classify system functions.•Proposes a novel resilience engineering method.•Suggests a way to conduct resilience modeling, analysis, and design for MaaS.•Presents a use case of reliability development based on IEC 62853 standard. |
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ISSN: | 0951-8320 1879-0836 |
DOI: | 10.1016/j.ress.2022.108812 |