Assessing the effects of link-repair sequences on road network resilience

Disruptions to transport networks are inevitable and detrimental to the functioning of society. Improving the resilience of transport networks to disruptive events has, therefore, a significant impact on society. Although the resilience of a transport system depends on the ability of the network to sustain the consequences of initial disruption (i.e. robustness) and quickly recover its performance (i.e. rapidity), the latter attracted less attention than robustness. The present paper focuses on quantifying the impacts of recovery processes and, more specifically, link-repair strategies on resilience. Several link-repair strategies are compared across a multitude of perturbation scenarios in the well-known Sioux Falls network. The strategies considered include: (i) the optimal (minimising the disruption consequences over the recovery process), (ii) average (representing a recovery process where the disrupted links are repaired in random order), (iii) flow-based (where the links with the highest traffic flow in the undisrupted network are repaired first), and (iv) criticality-based (where the links whose individual failure result in the highest impacts on the system performance are repaired first) recovery. The results of this comparison are subsequently used to evaluate the correlation between robustness and resilience, and characterise the optimal repair strategy

Using a random road graph model to understand road networks robustness to link failures

Disruptions to the transport system have a greater impact on society and the economy now than ever before due to the increased interconnectivity and interdependency of the economic sectors. The ability of transport systems to maintain functionality despite various disturbances (i.e. robustness) is hence of tremendous importance and has been the focus of research seeking to support transport planning, design and management. These approaches and findings may nevertheless be only valid for the specific networks studied. The present study attempts to find universal insights into road networks robustness by exploring the correlation between different network attributes and network robustness to single, multiple, random and targeted link failures. For this purpose, the common properties of road graphs were identified through a literature review. On this basis, the GREREC model was developed to randomly generate a variety of abstract networks presenting the topological and operational characteristics of real-road networks, on which a robustness analysis was performed. This analysis quantifies the difference between the link criticality rankings when only single-link failures are considered as opposed to when multiple-link failures are considered and the difference between the impact of targeted and random attacks. The influence of the network attributes on the network robustness and on these two differences is shown and discussed. Finally, this analysis is also performed on a set of real road networks to validate the results obtained with the artificial networks

Using a hazard-independent approach to understand road-network robustness to multiple disruption scenarios

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