Exploiting Data Analytics and Deep Learning Systems to Support Pavement Maintenance Decisions

Ronald Roberts,Laura Inzerillo,Gaetano Di Mino

doi:10.3390/app11062458

Abstract

Road networks are critical infrastructures within any region and it is imperative to maintain their conditions for safe and effective movement of goods and services. Road Management, therefore, plays a key role to ensure consistent efficient operation. However, significant resources are required to perform necessary maintenance activities to achieve and maintain high levels of service. Pavement maintenance can typically be very expensive and decisions are needed concerning planning and prioritizing interventions. Data are key towards enabling adequate maintenance planning but in many instances, there is limited available information especially in small or under-resourced urban road authorities. This study develops a roadmap to help these authorities by using flexible data analysis and deep learning computational systems to highlight important factors within road networks, which are used to construct models that can help predict future intervention timelines. A case study in Palermo, Italy was successfully developed to demonstrate how the techniques could be applied to perform appropriate feature selection and prediction models based on limited data sources. The workflow provides a pathway towards more effective pavement maintenance management practices using techniques that can be readily adapted based on different environments. This takes another step towards automating these practices within the pavement management system.

Highlights

The feature on the list is that of the population density within the traffic zone showing how important it is to understand the density of people living near a particular road for the maintenance activities
The analyses and models were developed relying on data analytics tools, open source algorithms and deep learning models
Feature selection tools were developed to identify which of the features are the most important towards explaining the point in time at which intervention activities need to be done

Summary

Introduction

In many countries worldwide the public road network is the biggest publicly owned asset [3] To this end, these networks must be kept in a suitable condition making the road agencies’ job of maintaining them a critical component towards the development of any region. Road agencies have the responsibility to develop programs that guide rehabilitation and maintenance practices and they have to enact critical decisions in terms of which areas should be prioritized and when interventions should be made. Further complicating their decisions are steadily reducing budgets for these activities [4,5] that will likely see greater depletions given the current global economic pandemic related situation [6]

Methods

Results

Conclusion