Road Infrastructure Asset Management Research Articles

Integrating disaster management planning into road infrastructure asset management

Climate change presents challenges for road infrastructure asset managers, with uncertainty about the impacts of increasingly frequent and intense disasters on asset functionality and lifespan. Budgeting for disaster response and recovery is improving; however, there are calls for more evidence to support budget allocations. This exploratory study aimed to create a systematic approach for integrating climate-related disaster risks within road asset evaluation, towards improving the evidence-base for capital works and maintenance budgets. It involved a systematic literature review of 63 research papers about resilient road infrastructure, followed by sense-checking key findings through eight semi-structured interviews with road asset management experts from the Australian government and industry. The authors present a set of 15 parameters for evaluating road infrastructure resilience, within four commonly used asset management categories: robustness, redundancy, resourcefulness and rapidity. These are placed within a disaster management planning framework for resilient road infrastructure outcomes, with the key parameters matched to the commonly used disaster management phases of ‘Prevent, Prepare, Respond, Recover’. The parameters and the framework have immediate use for road infrastructure asset managers, providing clear decision-support regarding what data are important to collect and analyse and at what time, to inform capital works and maintenance budgets.

CoDEC: Connected Data For Road Infrastructure Asset Management

Road infrastructure asset management is rapidly transforming into a digital environment where data accessibility, effective integration and collaboration and accessibility from different sources and assets are key. However, current asset management processes are not yet fully integrated or linked, and there are incompatibilities between various systems and platforms that limit the ability to integrate asset management with BIM. The CoDEC project has sought to understand the current status of information management for assets, including inventory, condition and new data sources such as sensors and scanning systems, to identify the challenges and needs for linking and integrating different data sets to support effective asset management. As a result, CoDEC has developed a data dictionary framework to help link/integrate static and dynamic data for the “key” infrastructure assets (road pavements, bridges, tunnels). This will enable BIM and Asset Management Systems (AMS) to exchange data and help optimise and integrate data management across systems and throughout the different asset lifecycle phases, from build to operation. This work will be followed up with three pilot projects to demonstrate the feasibility of integrating asset data from various sources through linked data/semantic web technology to build the connection between AMS and BIM platforms.

Modeling Pavement Performance Based on LTPP Database for Flexible Pavements

In many countries, incredible investments have been made in constructing roads that require conducting periodic evaluation and timely maintenance and rehabilitation (M&R) plan to keep the network operating under acceptable level of service. The timely M&R plan necessitates accurately predicting pavement performance, which is an essential element of road infrastructure asset management systems or Pavement Management Systems (PMS). Consequently, there is always a need to develop and to update performance prediction models embedded in PMS applications. This study focuses in developing distress prediction models for flexible pavements located in non-freeze climatic zone, which represent most of developing countries such as Egypt, using data extracted from the Long-Term Pavement Performance (LTPP) program. Ten distress performance prediction models were developed in this study for both wet- and dry-non freeze climatic zones, which are alligator (Fatigue) cracking, longitudinal cracking, transverse cracking, ravelling, bleeding, and rut depth models. These models can play an important role assisting decision makers in predicting pavement performance, identifying M&R needs, rational budget planning and resource allocation.

Road infrastructure asset management strategy and its impact on the environment

The development of the economic sector is determined by services to the public through reforms that aim to place public satisfaction through the management of road infrastructure assets. Some research on road infrastructure assets still requires a deepening of studies related to the delivery of public services related to asset management systems. The purpose of this study is to find an appropriate road infrastructure asset management strategy through an integrated asset management system and asset management policies that can provide public satisfaction. This comprehensive approach to management strategies ensures that the performance of service provider assets is in line with the expectations of stakeholders including road users. This descriptive qualitative research is based on the perspective of road users as respondents, consisting of vehicle drivers from 50 transportation companies (people or goods) through interviews and observations. The results show aspects of asset performance based on the user’s perspective there are five aspects, namely productivity, efficiency, effectiveness, use of resources and institutions and this performance is integrated in the asset management system related to policies from the management authority through service delivery namely quality and mobility, risk and use and maintenance of resources. The conclusion of this research is that road infrastructure asset services can be improved through the concept of road infrastructure asset management strategies in an integrated management system with five aspects of performance and more directed towards asset management policies related to the provision of road infrastructure asset services.

Defining road service to facilitate road infrastructure asset management

Road infrastructure asset management requires making decisions that affect how infrastructure provides service – for example, the intervention strategies to follow for specific assets, the intervention programmes to implement for entire networks and the way for interventions to be executed once it is decided that they should be executed. These decisions should be made to maximise the net benefit of infrastructure for all stakeholders and be made consistently and transparently. Currently, the definitions of service used by road infrastructure asset managers either are incomplete or are built on combinations of metrics, which give an idea of service but do not measure service directly. Neither allows for consistent and transparent decision-making that leads to the maximisation of the net benefit for all stakeholders. In this paper, a definition of the service provided by road infrastructure is provided that enables consistent and transparent decisions to maximise the net benefit for all road infrastructure stakeholders. The service definition is used to determine the net-benefit-maximising intervention strategy that shows its usefulness and its ability to let stakeholders see how they will be affected by decisions and that all of their concerns have been adequately taken into consideration when decisions are made.

A road infrastructure asset management process: gains in efficiency and effectiveness

There are a large number of efforts around the world to obtain more net benefits from road infrastructure assets. This can be seen through the proliferation of codes and guidelines and the increasing amount of research in road infrastructure asset management. Many of these codes and guidelines and much of the research, however, are focused on only part of the large complex problem of road infrastructure asset management. In efforts to improve the efficiency and effectiveness of the process, however, it is likely that it is useful to define clearly the entire road infrastructure management process. In this paper, this is done at a high level. It is hoped that using this high-level process as a starting point will help ensure that further efforts to increase the efficiency and effectiveness of road infrastructure asset management are successful not only in general, but also in particular through the exploitation of computer systems. The process can be used as a starting point by road infrastructure asset managers as they establish their own more detailed process, in which all involved stakeholders agree as to the activities involved in the management of road infrastructure assets and the reasons why.

Prospect for Implementation of Road Infrastructure Asset Management

Infrastructure has to be adequately planned, designed, executed and maintained to keep its structural performance over respective requirements throughout its life-cycle. However, infrastructure suffering from serious deterioration in structural members and subsequent loss in performance have been often found due to various reasons. To meet these facts, it is extremely important to pursue coordination of engineering work in the stages of design, execution and maintenance. The infrastructure management including the concepts of the life-cycle management and the asset management is an organized system to support engineering-based decision making for ensuring sufficient structural performance and long life of a structure at the design, execution, maintenance, and all related work during its life-cycle. This paper deals with infrastructure management system and an example of its application for a road bridge from seriously deteriorated.

Roughness Progression Model for Asphalt Pavements Using Long-Term Pavement Performance Data

A reliable pavement performance prediction model is needed for road infrastructure asset management systems or pavement management systems. In this study, the data on roughness progression of asphalt pavements in the long-term pavement performance (LTPP) database was analyzed in order to develop such a model. The international roughness index (IRI) is a reasonable measure of the ride comfort perceived by occupants of passenger cars and hence used as the basis for the pavement performance prediction model developed in this research. A quantitative relationship between roughness progression and accumulative traffic load, structural number, annual precipitation, and freezing index was developed and validated. Five pavement performance levels were developed to express the extent of asphalt pavement deterioration. This is coupled with a reliability analysis based on the Weibull model to estimate the remaining service life of asphalt pavements. Effective treatments of pavements at the project level for each condition state level were also proposed, which can aid network level optimization of the overall condition and corresponding budget allocations.

Discussion on road infrastructure asset management practices

The objective of this study is to discuss and compare the practices of Road Infrastructure Asset Management System (RIAMS) adopted in different countries. This discussion mainly focuses on the pavement management system. Internationally, the RIAMS approach is moving from the condition-based towards the service-based approach focusing on the customer-driven priorities. This service-based approach needs to be balanced with the budget constraints, level of service and risk tolerance. The transportation agencies have not yet addressed the integrated land use and transportation modelling, the comparison of the relative advantages between capital and operating investments, the risk-based estimation, and the identification of a range of costs associated with the failure within the RIAMS. The transportation agencies should develop a performance-based RIAMS ensuring the serviceability, accountability, stewardship, long-term financial plans, and transparent investments. The RIAMS is still emerging and needs to incorporate the local mission, budget and other constraints within the scope of the local context.

통계기법을 활용한 포장파손자료의 잠재오차 보정

성공적인 자산관리시스템의 도입은 풍부하고도 신뢰할 수 있는 데이터와 함께 시작된다. 그러나 현실에서는 알려지지 않은 다양한 원인에서 비롯되는 관측 오차들은 항상 존재하기 마련이다. 이는 관리자의 유지보수활동을 방해하며 파손과정이나 생애주기비용 예측결과의 신뢰성에도 악영향을 미친다. 무엇보다도 관리자가 자신의 손으로 직접 조사한 자료를 믿지 못하는 모순된 결과를 낳는다. 이런 현상은 도로포장관리분야에서 특히나 심각하다. 도로관리자들은 이러한 사실에 대해 충분히 인식하고 있으나, 현실적으로 오차 없는 조사를 수행한다는 것은 하나의 큰 도전이라고도 할 수 있다. 이러한 점들을 고려하여 본 연구에서는 포장표면 조사자료에 포함된 오류 및 잠재오차를 보정하기 위한 통계적 방법론을 제시하고자 하였다. 방법론으로는 오차의 구조 및 신뢰도를 고려할 수 있도록 확률분포이론에 근거한 두 가지 기법(샘플기준법과 분포기준법)을 제안하였다. 제안된 방법론은 국도에서 수집된 포장상태자료들을 활용하여 적용 가능성을 살펴보았으며, 그 결과 눈에 보이는 오류들만을 제거하는 일반적인 방법론으로는 포장자료에 포함된 불확실성을 충분히 고려할 수 없음을 확인하였다. 제안된 방법론은 도로자산관리에 필요한 다양한 분석의 신뢰성을 개선하는데 유용하게 활용될 수 있을 것이다. Successful implementation of infrastructure asset management system can be started with rich and reliable data. However, measurement errors in the data have always existed in the real world caused for many unknown reasons. It disturbs maintenance activities of agencies, and makes negative effects to reliability of research results on forecasting deterioration process and life cycle cost. Above all, it makes a contradiction that road agencies cannot believe their inspection data surveyed by their hands. It is particularly serious in the road pavement management field. Although road agencies are well recognized the fact, inspecting without measurement error would be a great challenge. Considering the facts, this paper aimed to suggest statistical error processing methods to correct latent error included in pavement surface inspection data. As alternatives, this paper suggested two methods based on probability distribution to consider structure of error and reliability of the data. The suggested methods were empirically tested by using pavement inspection data from Korean National Highway. As the result, this paper confirmed that conventional error processing that just removes only visible errors is not enough to cover uncertainty in pavement deterioration process. The suggested methods would be useful for improving reliability of analysis results required for road infrastructure asset management.