This paper presents a methodology that incorporates vulnerability to natural hazards into current infrastructure management systems. The paper is mainly concerned with presenting the methodology applied to assess the transport-related consequences of link failures, including congestion effects on a networkwide scale. Four possible demand shifts caused by single link failures can be expected: detours, shifts in mode choice, shifts in destination choice, and trip–activity suppression. The paper demonstrates that detours are by far the predominant demand reaction. Hence, the quantification of detour-based principal consequences is the main focus. The main challenge was to overcome the calculation time intensity of this equilibrium-based approach. Since demand shift effects were assumed to be spatially restricted around the failed link, subnetworks were used, that is, limited sections of the complete network that were cut out, including their internal and transit demands. The resulting failures turned out to be consistent with those that involved the full network, even for links with long path distances or long detours. On the basis of computed consequences of link failures and on link parameters, a statistical model was developed to reveal and quantify the main factors defining transport-related consequences. Furthermore, the findings highlight potential gains, including rail networks, mode shifts, and destination choice shifts in network vulnerability assessments.
Decision makers use bridge management systems to determine the optimal allocation of available resources. These systems are currently focused on the structural condition of deteriorating bridges with respect to traffic loads. Bridges, however, are affected by multiple hazards, such as flooding and earthquakes, and not only traffic loading. These multiple hazards should be considered in these management systems when determining the optimal intervention.A risk-based approach can be used to determine the optimal intervention for a bridge subjected to multiple hazards. It requires the determination of the likely 'levels of service' to be provided by the bridge, (e.g. both lanes of traffic open, only one lane of traffic open or both lanes closed), the evaluation of the probability of having these levels of service due to the multiple hazards as well as the consequences of each of these levels of service, and selecting the interventions to minimise the risk of inadequate service.This article gives the methodology to be used when determining the optimal intervention for a bridge affected by multiple hazards. The risk-based approach is illustrated using a simple example in which the optimal intervention of two interventions is found.
To improve the allocation of funds for the maintenance and risk mitigation of transportation infrastructure, there is a dire need for a simplified, yet sufficiently accurate, methodology to estimate bridge vulnerability to scour. The methodology should make use of existing data and indicate the basic variables needed to assess the vulnerability of bridges located around a future expressway in southeastern Serbia. The first part of the paper discusses the identification of possible modes of bridge failure caused by scouring that depend on soil, structure, and river hydraulic properties. The degradation of soil parameters is assumed to be the main cause of bridge failure. The capacity of a bridge to withstand a certain amount of structural damage governs the direct and indirect costs attributable to bridge failure; the subsequent work zones related to rehabilitation reduce the performance of the whole network. In the second part of the paper, a simulation of the redistribution of traffic flows is described for several possible scenarios; the simulations use state-of-the-art software VISUM, which was developed for computer-aided transportation planning and analysis. The simulated scenarios include the partial and full closure of road links as a result of bridge failures. The simulations confirmed that the most significant contribution to indirect costs stems from the increase in the total travel time of all network users.
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