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• This paper uses a hazard-independent method to assess road network robustness. • This approach considers all scenarios concurrently disrupting up to five linksoptins. • It allows understanding the impact of random, localised, and targeted link failuresoptins. • The most-critical link combinations disrupting M and M + 1 links are relatedoptins. • The link criticality rankings evolve with the travel demandoptins. A range of predictable and unpredictable events can cause road perturbations, disrupting traffic flows and more generally the functioning of society. To manage this threat, stakeholders need to understand the potential impact of a multitude of predictable and unpredictable events. The present paper adopts a hazard-independent approach to assess the robustness (ability to maintain functionality despite disturbances) of the Sioux Falls network to all possible disruptions. This approach allows understanding the impact of a wide range of disruptive events, including random, localised, and targeted link failures. The paper also investigates the predictability of the link combinations whose failure would lead to the highest impacts on the network performance, as well as, the correlation between the link-criticality rankings derived when only single-link failures are considered as opposed to when multiple-link failures are considered. Finally, the sensitivity of the robustness-assessment results to the intensity and distribution of the travel demand is evaluated. [ABSTRACT FROM AUTHOR]