Transportation systems are becoming increasingly complex and represent systems-of-systems (SoS) of many independent actors, including also energy and communication systems. At the same time, disruptions in transportation systems are multiplying as an effect of climate change and geopolitical factors. This leads to an increasing need for methods to analyze and strengthen resilience in SoS. This report presents the findings from a pre-study project aiming at understanding how SoS and resilience engineering can be applied to contemporary and future transportation systems.
To establish the state-of-the-art of SoS resilience in general, a systematic literature review was conducted. It showed that there are two different worldviews of relevance to resilience, namely specified resilience which assumes knowledge about the disturbances, and general resilience which does not assume such knowledge. The specified resilience view dominates the literature and also lends itself to typical engineering approaches, but lacks realism when it comes to availability of data.
Among the many different techniques that have been used for modeling SoS for resilience analysis, a layered graph representation stands out. It describes the SoS in four layers: macro-layer, capturing its capabilities; meso-layer, showing how constellations contribute to the capabilities; micro-layer, showing how individual actors interact; and spatial layer, which describes the physical environment.Typical approaches to measuring resilience in SoS are also based on such a hierarchical structure,where macro-level resilience is aggregated from lower-level performance indicators, and also aggregated temporally over the resilience phases of preparation, absorption, recovery, and adaptation. The literature suggests various methods for improving SoS resilience, by interventions at different hierarchical levels, by improving the SoS architecture, or by considering sociotechnical aspects.
Based on these findings from the SoS literature, the road transportation system was analyzed in workshops with experts. The generic model of a layered graph was used, identifying concrete entities in each of the layers as well as some of their interactions. This analysis did not only consider the core transportation capabilities, but also, e.g., actors related to building and maintaining the infrastructure, energy providers, digital service providers, and authorities.
Existing methods for analyzing the resilience of the transportation system were evaluated, with an emphasis on tools for traffic forecasting and infrastructure planning. These established tools have a value in assessing steady-state traffic flows, but to investigate the dynamics of a disruption, brute force methods are needed where parameters are varied systematically.
To broaden the perspectives beyond the physical infrastructure and traffic flows, a broad set of further indicators were identified. The indicators were classified according to resilience phase, system layer, type, analysis method, required data, and to what types of disruptions they are relevant. Further, they were grouped into what parts of the SoS they relate to, such as transport infrastructure, operations, logistics, energy, digital connectivity, economic and environmental effects, etc.
Based on these investigations, a number of challenges and knowledge gaps were identified, including the need for methods to handle general resilience where possible disruptions are not known; to improve analysis methods; to take into account the perspectives and incentives of different stakeholders; sociotechnical aspects and the human ability to contribute to resilience; costs of resilience; management of resilience; and addressing complexity.
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This work was funded by the Swedish Strategic Vehicle Research and Innovation program, FFI (Vinnova grant no. 2025-00860).