Pavement maintenance is essential to prevent the deterioration of asset value and to satisfy the expectations of all stakeholders (objectives). However, the budgets are often insufficient to keep the road pavement at optimum levels. Therefore, a decision making process ought to be used for prioritizing different maintenance activities in order to achieve pre-defined goals by optimizing the use of the available budget. One of the biggest difficulties in multiobjective optimization method is the large number of the feasible solutions (Pareto optimal set or its approximation), which makes it hard for the Decision Maker to select the best solution. To support interaction with the decision maker for identifying the best combination of maintenance actions, this paper proposes a new methodology named “Interactive Multiobjective Optimization-Dominance Rough Set Approach” (IMO-DRSA), using a decision-rule preference model. The preference information, obtained by the Decision Maker (DM) during the course of the interaction, is processed using the Dominance-based Rough Set Approach in order to achieve a decision model expressed in terms of easily understandable “if ….then …” decision rules. This approach makes possible an interaction between the analyst and the decision maker and helps the decision maker to classify maintenance options and allocate limited funds according to predefined objectives (quantitative or qualitative). An application of the proposed methodology to road pavements of an Italian urban sub-network is presented.

Background: Since the beginning of the new millennium, sensitivity towards the environment has been spreading globally. In fact, countries are adopting measures to develop new decision support tools that can evaluate the impact of interventions to promote and encourage sustainable mobility. To reduce the levels of pollution related to road traffic, policies that favor multimodal transport alternatives have been strengthened. This involves the combined use of public transport, cycling and walking paths, as well as sharing services where available. Regardless of the type of transport, the pedestrian component remains relevant in cities, even if the infrastructures are often not adequate to accommodate it and conflicts arise that must be managed. It is, therefore, necessary to assess the exposure to risk in terms of road safety. Methods: To this end, the work proposes a forecasting model to estimate the pedestrian flows that load the network. The methodology employs a hybrid approach that appears to better capture the movements of pedestrians. Results: By comparing the results of the model with the real data collected on the study area, satisfactory estimates were obtained. Conclusions: Therefore, this can be an effective tool to help road managers to evaluate the actions to protect vulnerable users.

Road networks are classified as critical infrastructure systems. Their loss of functionality not only hinders residential and commercial activities, but also compromises evacuation and rescue after disasters. Dealing with risks to key strategic objectives is not new to asset management, and risk management is considered one of the core elements of asset management. Risk analysis has recently focused on understanding and designing strategies for resilience, especially in the case of seismic events that present a significant hazard to highway transportation networks. Following a review of risk and resilience concepts and metrics, an innovative methodology to stochastically assess the economic resources needed to restore damaged infrastructures, one that is a relevant and complementary element within a wider resilience-based framework, is proposed. The original methodology is based on collecting and analyzing ex post reconstruction and hazard data and was calibrated on data measured during the earthquake that struck central Italy in 2016 and collected in the following recovery phase. Although further improvements are needed, the proposed approach can be used effectively by road managers to provide useful information in developing seismic retrofitting plans.