The Road Pavement Condition (RPC) represents one of the main indices that describe both the political stability and the economic level of a country. To date, maintaining the high efficiency of the road network is one of the greatest challenges for the Road Authorities (RAs). Pavement Degradation Prediction Models (PDPMs) can be a valuable tool for assessing current and future RPC, helping RAs to keep roads in proper service condition. Currently, many PDPMs are already developed. However, these appear either too complicated or too specific and usable only within the boundary conditions on which were developed or only after proper recalibrations with local data. Furthermore, the constrained budgets and the consequent limited technical resources to collect data on the condition of pavements that RAs normally have available for urban roads, highlight their evident need to have specific and simple deterioration models for these roads based on a process that allows them to optimize the road pavement management as a function of the available budget and data. This research aims to illustrate a simple PDPM which intends to support the RAS’ making-decision tool to describe both the current road pavement condition and the road surface distresses evolution over time along with the urban road network. The proposed PDMP was developed on the basis of data from a global index collected on 246 homogeneous road sections within the road network of the Municipality of Florence. The monitoring process for data collection was performed using a high-performance and low-cost methodology which is based on the vertical accelerations recorded by black boxes located inside the vehicles that routinely pass on the road network. A simplified linear model was used to describe the distress trend of the road surface conditions. The results, evaluated by means of the coefficient of determination (R2), show that the model predicts with good precision the pavement distress, thus supporting the use-fulness of these tools in assisting the decisions of the RAs for the allocation of adequate and timely funds for the maintenance of a high efficiency also of the urban road network.

Simplified road pavement surface deterioration model in urban area / Monica Meocci; Valentina Branzi. - ELETTRONICO. - (2023), pp. 179-188. (Intervento presentato al convegno SURF 2022 – The 9th Symposium on pavement surface characteristics tenutosi a Milano nel 12-14 settembre 2022) [10.1201/9781003429258-18].

Simplified road pavement surface deterioration model in urban area

Monica Meocci;Valentina Branzi
2023

Abstract

The Road Pavement Condition (RPC) represents one of the main indices that describe both the political stability and the economic level of a country. To date, maintaining the high efficiency of the road network is one of the greatest challenges for the Road Authorities (RAs). Pavement Degradation Prediction Models (PDPMs) can be a valuable tool for assessing current and future RPC, helping RAs to keep roads in proper service condition. Currently, many PDPMs are already developed. However, these appear either too complicated or too specific and usable only within the boundary conditions on which were developed or only after proper recalibrations with local data. Furthermore, the constrained budgets and the consequent limited technical resources to collect data on the condition of pavements that RAs normally have available for urban roads, highlight their evident need to have specific and simple deterioration models for these roads based on a process that allows them to optimize the road pavement management as a function of the available budget and data. This research aims to illustrate a simple PDPM which intends to support the RAS’ making-decision tool to describe both the current road pavement condition and the road surface distresses evolution over time along with the urban road network. The proposed PDMP was developed on the basis of data from a global index collected on 246 homogeneous road sections within the road network of the Municipality of Florence. The monitoring process for data collection was performed using a high-performance and low-cost methodology which is based on the vertical accelerations recorded by black boxes located inside the vehicles that routinely pass on the road network. A simplified linear model was used to describe the distress trend of the road surface conditions. The results, evaluated by means of the coefficient of determination (R2), show that the model predicts with good precision the pavement distress, thus supporting the use-fulness of these tools in assisting the decisions of the RAs for the allocation of adequate and timely funds for the maintenance of a high efficiency also of the urban road network.
2023
Pavement management System, Deterioration Prediction Model, Vertical accel-eration, Urban Road
SURF 2022 – The 9th Symposium on pavement surface characteristics
Milano
12-14 settembre 2022
Goal 11: Sustainable cities and communities
Monica Meocci; Valentina Branzi
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1349196
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