Planning urban pavement maintenance by a new interactive multiobjective optimization approach

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

Planning urban pavement maintenance by a new interactive multiobjective optimization approach

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."br/""br/"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."br/""br/"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. Document type: Articl

Il processo di gestione della sicurezza stradale e l'analisi dei dati di incidentalita'

Dottorato di ricerca in costruzione e gestione di strade ferrovie ed aeroporti. 11. ciclo. Coordinatore e tutore Antonino D'AndreaConsiglio Nazionale delle Ricerche - Biblioteca Centrale - P.le Aldo Moro, 7 , Rome; Biblioteca Nazionale Centrale - P.za Cavalleggeri, 1, Florence / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

Dominance-Based Rough Set Approach to Network Bridge Management

Bridge management is essential for optimizing available resources. Prioritising maintenance and assessing the effectiveness of different maintenance strategies are based on the conventional condition ratings of bridge components. This paper presents the development of a Decision Support System for maintenance management at the Network Bridge Level, based on the theory of the Dominance-Based Rough Set Approach. Dominance-Based Rough Set Approach produces a decision model expressed in terms of easily understandable “if…, then…” decision rules which control the decision process and avoid the “black box” effects of many alternative decision support methods. In the proposed Decision Support System, bridges are described by a set of 16 parameters that describe the state of degradation, structure, territory, traffic and network characteristics. To illustrate this Decision Support System, a case study involving Italian roads is presented. The proposed Decision Support System is a flexible tool because it allows updating parameters periodically as a consequence of practice, expertise and management policies

Safety Index for evaluation of urban roundabouts

Recently, there is a growing interest in road safety assessments based on the examination of the characteristics of the road aimed at identifying the presence of risk factors. This approach, named road assessment program or network wide road safety assessment, is required by the EU Directive 2019/1936 on road infrastructure safety management. Reliable procedures for assessing the inherent safety of all the elements of the road network are required to conduct roadway safety assessments. To provide a contribution toward the development of pro-cedures for network wide road safety assessment, this paper develops and validates a Safety Index (SI) for evaluating urban roundabouts.The SI is assessed both at the roundabout level as well as at the roundabout approach level. This procedure detects the safety issues that are the largest contributors to crash risk in order to identify the safety measures that provide the greatest crash reduction at roundabouts. The SI is formulated by combining two components: the exposure of road users to road hazards (Exposure) and the risk factors which increase the probability of involvement in crashes (Risk Index). The procedure considers 33 detailed safety issues and 5 general safety issues to compute the Risk Index. Criteria for identifying and ranking the safety issues are defined. The SI procedure was validated in a sample of 50 urban roundabouts located in Rome, Italy. The sample consisted of 12 single-lane roundabouts and 38 two-lane roundabouts, with a total number of approaches equal to 179. In these roundabouts, the SI scores and the EB crash estimates were compared with reference both to the whole roundabouts as well as to the single roundabout approaches. The correlation between the SI scores and EB estimates was highly significant both at the roundabout level (R2 = 0.85, t =16.49, p-value < 0.001) as well as at the approach level (R2 = 0.56, t = 14.88, p-value < 0.001). The results from Spearman's rank-correlation analysis provided further validation for the SI indicating that rankings from the SI and the EB estimates agree at the 99.9 % confidence level both at the roundabout level (rho s = 0.80) as well as at the approach level (rho s = 0.70)

Economic risk evaluation in road pavement management

Pavement maintenance is essential to prevent the deterioration of asset value and satisfy all stakeholders' expectations. However, the budgets are often insufficient to keep the road pavement at optimum levels. Therefore, a decision-making process ought to be used to prioritize different maintenance activities to optimize the fulfillment of the pre-defined goals. At the same time, there is a growing need to integrate risk management into asset management, and therefore into the Pavement Management System. It is the best way to understand risk in decision-making at the program and organizational levels. This paper examines how risk-based pavement management practices can be implemented. The idea is to identify the best combination of maintenance actions given budget constraints, also considering budget risk reduction within a multiobjective optimization process. As far as economic risk assessment is concerned, probabilistic LCCA with Monte Carlo Simulation was used to investigate the risk of budget exceeding in Pavement Management Systems as a secondary criterion for choosing the optimal maintenance strategy on a road network. The method allows assessing epistemic uncertainties regarding discount rate and materials, man-power, transportation, and equipment rental costs. Outputs were able to show the possible variability of maintenance strategies costs. Moreover, probability density functions provide for establishing the most economically advantageous solutions (lower mean value) and for the riskiest ones (greater standard deviation). The optimal strategy might be selected by minimizing the probability of budget exceeding. The innovation of this research is in the introduction of the quantitative economic risk analyses into pavement management, with the aim to integrate epistemic and aleatory uncertainties in the process