Search results for "pavement management system"
showing 10 items of 10 documents
Exploiting 3D Modelling and Life Cycle Assessment to Improve the Sustainability of Pavement Management
2020
Today road agencies worldwide face difficult decisions for construction, maintenance and rehabilitation of their road infrastructure as they try to balance limited budgets. This is further complicated rising environmental concerns over equipment and techniques used for these practices. This has led agencies to consider alternative approaches for smarter and sustainable pavement asset management systems. This paper considers the use of a low-cost 3D image modelling distress identification and classification proposal for data acquisition and analysis. To establish its environmental friendliness, a case study in Palermo, Italy, is considered wherein a Life Cycle Assessment (LCA) exercise is do…
An advanced pavement management system based on a genetic algorithm for a motorway network
2013
Maintenance and improvement, through the rehabilitation, of the road infrastructure is a strategic and priority objective for road agencies, nevertheless the economic resources required are often inadequate. Within road management, the pavement management system (PMS) plays an essential role because of both the money needed and the performance that should be provided in terms of safety, ride quality and transport cost. The PMS is based on searching for a balanced solution between the lowest cost and the increased level of performance (i.e. pavement condition). In this paper a PMS multi-objective optimization method, was proposed, using a genetic algorithm (GA) to identify the best solution …
UN APPROCCIO BASATO SULLA MODELLAZIONE 3D E IL LIFE CYCLE ASSESSMENT PER UNA GESTIONE SOSTENIBILE DELLA MANUTENZIONE STRADALE
2021
Among several goals of the road agencies, one of the most relevant is the maintenance and rehabilitation of the road pavement. The growth of traffic, the longstanding lack of funding and, sometimes, an emergency-based planning of intervention, are common drivers leading to low level of pavement conditions in terms of ride quality and safety. In addition both cost and environmental concerns due to monitoring stage are relevant issues within the management system of local and urban road network, especially. With the purpose of implementing sustainability in the road pavement management, this paper provides an approach based on coupled low- cost 3D image modelling distress identification and L…
Exploiting Data Analytics and Deep Learning Systems to Support Pavement Maintenance Decisions
2021
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 authorit…
Towards More Sustainable Pavement Management Practices Using Embedded Sensor Technologies
2019
Road agencies are constantly being placed in difficult situations when making road maintenance and rehabilitation decisions as a result of diminishing road budgets and mounting environmental concerns for any chosen strategies. This has led practitioners to seek out new alternative and innovative ways of monitoring road conditions and planning maintenance routines. This paper considers the use of innovative piezo-floating gate (PFG) sensors and conventional strain gauges to continuously monitor the pavement condition and subsequently trigger maintenance activities. These technologies can help develop optimized maintenance strategies as opposed to traditional ad-hoc approaches, which often le…
Towards Low-Cost Pavement Condition Health Monitoring and Analysis Using Deep Learning
2020
Governments are faced with countless challenges to maintain conditions of road networks. This is due to financial and physical resource deficiencies of road authorities. Therefore, low-cost automated systems are sought after to alleviate these issues and deliver adequate road conditions for citizens. There have been several attempts at creating such systems and integrating them within Pavement management systems. This paper utilizes replicable deep learning techniques to carry out hotspot analyses on urban road networks highlighting important pavement distress types and associated severities. Following this, analyses were performed illustrating how the hotspot analysis can be carried out to…
Optimizing artificial neural networks for the evaluation of asphalt pavement structural performance
2019
Artificial Neural Networks represent useful tools for several engineering issues. Although they were adopted in several pavement-engineering problems for performance evaluation, their application on pavement structural performance evaluation appears to be remarkable. It is conceivable that defining a proper Artificial Neural Network for estimating structural performance in asphalt pavements from measurements performed through quick and economic surveys produces significant savings for road agencies and improves maintenance planning. However, the architecture of such an Artificial Neural Network must be optimised, to improve the final accuracy and provide a reliable technique for enriching d…
Tecniche di Rilievo ad Alto rendimento nel Pavement Management System: verifica sperimentale nel Campus Universitario di Parma
2011
Optimization and sensitivity analysis of existing deep learning models for pavement surface monitoring using low-quality images
2022
Automated pavement distress detection systems have become increasingly sought after by road agencies to in crease the efficiency of field surveys and reduce the likelihood of insufficient road condition data. However, many modern approaches are developed without practical testing using real-world scenarios. This paper ad dresses this by practically analyzing Deep Learning models to detect pavement distresses using French Secondary road surface images, given the issues of limited available road condition data in those networks. The study specifically explores several experimental and sensitivity-testing strategies using augmentation and hyper- parameter case studies to bolster practical mode…
Developing a framework for using structure-from-motion techniques for road distress applications
2020
On Urban road networks, road agencies need to quickly identify road pavement distresses in order to identify appropriate maintenance and rehabilitation strategies. This is integral as agencies are plagued with financial and time constraint issues. There have been several attempts over the last few years to identify new solutions and techniques to solve these issues. Several of these have shown merit and accuracy in identifying distresses. However, the techniques in many instances are not correlated to available distress identification standards. One of the considered techniques is the use of Structure-from-Motion, which tries to recreate 3D distress models for identification and analysis. T…