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Since a considerable portion of our work considers state-of-the-art research we produce a large amount of peer-reviewed papers, conference presentations and project reports. On this page we accumulate all published works and their abstracts. Feel free to get in touch if you have any further questions.


The aim of the project was to design an indicator-based tool that can be used for future life cycle management of infrastructure structures on the basis of an international literature study, expert surveys in workshops and existing data from the three modes of transport. In particular, current developments in relation to new forms of data collection and processing in the condition assessment of engineering structures using a Bayesian approach were taken into account. Finally, an IT prototype was developed on the basis of the review and evaluation of the available data and applied to sample data.

Link to the report

Verkehrswege bilden das Rückgrat einer modernen, arbeitsteiligen Volkswirtschaft. Planung, Entwurf und Bau haben einen erheblichen Einfluss auf die Dauerhaftigkeit der Straßeninfrastruktur, auch wenn diese Lebensphasen im Vergleich zur gesamten Lebensdauer einer Anlage relativ kurz ist. Daher ist eine umfassende Dokumentation der bei der Inbetriebnahme (Abnahme) einer Anlage vorherrschenden Eigenschaften und Randbedingungen essentiell. Dies dient als Grundlage zur Aufbereitung von relevanten Informationen während der Nutzungsphase, um objektspezifische Erhaltungsmaßnahmen vorzubereiten.

Infrastrukturbetreiber benötigen qualitativ hochwertige Bestands- und Zustandsinformationen zu ihrer Straßeninfrastruktur, um Maßnahmen zu ergreifen, die die Sicherheit und Gebrauchstauglichkeit der Straßeninfrastruktur gewährleisten und dabei zu möglichst geringen negativen Auswirkungen auf die Verfügbarkeit und Nachhaltigkeit führen. Die Informationen über den Anlagenzustand werden durch regelmäßige Zustandserfassungen und -bewertungen (ZEB), Bauwerksprüfungen und übrige Überwachungsmaßnahmen gewonnen. Während der Lebensdauer einer Anlage können diese Überwachungsmaßnahmen eine große Menge an Daten erzeugen, die digital verwaltet werden müssen. Bauwerksprüfungen und Erhaltungsplanung erfordern organisierte, automatisierte, offene und intuitive digitale Prozesse, die sowohl Anlagedaten als auch zugehörige Zustandsdaten berücksichtigen sollten. Dieser nahtlose digitale Prozess wird durch bestehende Asset Management Systeme (AMS) bereits unterstützt, kann aber noch erheblich verbessert werden. So unterstützen die meisten AMS keine geometrische Darstellung der Anlagen, was die Datenerfassung, insbesondere bei den Brückenbauwerken, im Rahmen der Bauwerksprüfung erschwert.

Die Verknüpfung des Building Information Modeling (BIM) mit AMS kann die Erfassung und Auswertung von Prüfdaten erheblich erleichtern und zusätzliche Überwachungsdaten präzise lokalisieren. Darüber hinaus unterstützt die exakte geometrische Darstellung von Ingenieurbauwerken und erfassten Schäden die Erhaltungsplanung. Durch detaillierte Simulationen kann das Tragverhalten unter verschiedenen Umwelteinflüssen analysiert und interpretiert werden.

Eine Verknüpfung von BIM mit AMS schafft ein vollständig digitales Speichersystem und eine Plattform für den Datenaustausch mit bestehenden BIM-Lösungen. Dies ermöglicht ein umfassendes Asset Management mit Prognose-, Optimierungs- und Analysemodellen. Das Ziel besteht in einem software- und hardwareunabhängigen Datenaustausch zwischen verschiedenen Softwareanwendungen während der gesamten Nutzungsdauer. Die Verwendung einer offenen BIM-Technologie zur Interoperabilität auf technischer, semantischer und organisatorischer Ebene ist hierbei von zentralem Interesse. Der aktuelle Entwicklungsstand und die zu bewältigenden Herausforderungen für eine erfolgreiche Umsetzung dieses Ziels werden diskutiert.

Link zum Paper

According to modern structural codes, a design is considered to be adequate if the limit states are not exceeded. For the ultimate limit state, the design value of action effect Ed is required to be less or equal than the design value of ultimate resistance Rd. This ensures, according to the Eurocode, a sufficiently low probability of failure expressed as the target reliability index β. Consequently, the distributions of action effect and of resistance need to satisfy the following conditions: 𝑃(𝐸>𝐸𝑑)Φ(+𝛼𝐸𝛽) and 𝑃(𝑅𝑅𝑑)Φ(𝛼𝑅𝛽), where αE and αR, with |α| ≤ 1, are the values of the FORM sensitivity factors. The values of the sensitivity factors αE and αR are suggested, according to EN1990, as −0.7 and 0.8, respectively; for the accompanying actions, the sensitivity factor is recommended as 0.28. In this paper, the dependence of the sensitivity factors for traffic live load, dead load, and resistance on the ratio of traffic load to dead load is studied (which is directly proportional to the maximum span of the bridge). Significantly different sensitivity factors for resistance, dead load, and traffic load, other than proposed by the Eurocode, has been calculated for typical ratio of traffic to dead load. It further showed that, if it is assumed that Ed = Rd and the Eurocode partial safety factors are used, a different design point than the starting point, i.e., Ed = Rd, is obtained.



Transportation infrastructure is vulnerable to threats such are natural and man-made hazards and each agency needs to improve their own ability to adequately and decisively respond to sudden and unforeseen challenges to infrastructure performance. It is pivotal for countries to learn from past experiences to form a shared view on possible future development of transportation networks and how to improve current management approaches to be flexible and adaptive to address future threats, which are likely to be more damaging due to climate change. However, the complexity of approaches being developed depends on the experience of the road operator with natural hazards. Usually, the trigger for improvement of current procedures is related either to a recent hazard event that had a severe impact on network users and society or to a frequently occurring event of a lesser magnitude and consequences thereof.
The report shows that road owners/operators currently apply measures that are aimed at evaluation of asset performance, infrastructure protection, preservation and recovery after failures, which is along the lines of a resilience-based framework. However, there is a need to embrace resilience as a core component of decision making. This will provide valuable insights on potential vulnerabilities in network and the capacity of infrastructure to withstand and recover from disruptions. This important information supports road agencies in prioritisation of maintenance projects fostering the long-term sustainability and adaptability of their infrastructure assets in the face of threats.
The terminology used in the report and the background on evaluation of resilience aspects: robustness, redundancy, rapidity of response and resourcefulness is discussed in the beginning, while the main body of the report is a collection of examples from practice on measures to improve resilience aspects. The approaches in practice comprise planning of preventative maintenance measures, which target reduction of threat magnitudes, mitigation of failure probability/rates of assets and further, mitigation of consequences of failure and recovery measures. The agency-wide approaches that incorporate resilience aspects in a decision-making process are discussed at the end of the report. The variety of presented examples allows that a broad audience of owners/operators of road infrastructure coming from low to high-income countries can relate to similar issues and learn from the experience of others.

Link to the report

Even though BIM is still rarely used in operation over the lifetime of infrastructure assets, it promises significant benefits for national road authorities with regard to condition updating and the effects of maintenance measures required in contemporary asset management. This paper introduces new approaches for a task-related data exchange between BIM and Infrastructure Management Systems. Concepts to manage semantic information and to visualize geometric-related information are presented. For selected use cases, country-specific information containers were defined to support the general process map which differ fundamentally according to the ontologies, links and documents that are used and stored. The proposed approach was implemented in a web application and tested for three predefined use cases within the framework of a case study.


An performant and safe road infrastructure is the prerequisite for social progress: it enables economic growth, employment and well-being and thus represents the backbone of a modern society. A vigilant road infrastructure manager needs to identify the scenarios that could endanger the safety and performance of the road infrastructure in timely manner in order to plan and launch countermeasures to prevent these scenarios. Decision-making on these measures is the main task of maintenance management, the quality of which depends on the extent and quality of the available data. At the same time, the methods of decision-making are determined by the amount of data that can be collected and processed with a reasonable effort. It was recognised already in the second half of last century that digitalisation can provide a remedy in terms of the amount of data that can be collected and processed. Many infrastructure managers have developed IT systems at that time, firstly the databases in which the road nfrastructure is represented. To this digital representation the monitoring data and the data on performed maintenance measures are linked. Later, analytical tools were added, which use the data in the databases to forecast condition of infrastructure objects and generate intervention options, i. e. proposed measures, on the basis of these forecasts. The database and the analytical tool are components of a maintenance management system. The current maintenance management systems have their limitations. Due to the rather rudimentary representation of the real road infrastructure, the results of the analytical tools are only suitable for a rough determination of the maintenance measure. The more realistic representation of the road infrastructure together with the associated monitoring data and the data on performed maintenance measures is very time-consuming if the corresponding data collection and data maintenance is carried out manually, as has been the case up to now. Digitalisation, i. e. the use of Building Information Modeling (BIM) in the planning and execution of road infrastructure projects, is changing this situation as the detailed digital representation of the road infrastructure is available at least for the newly constructed infrastructure objects – even if not in a suitable form. Infrastructure managers are now required to define requirements so that a smooth transfer of data from the construction phase can take place. This means that a large amount of data of higher quality is available for maintenance management. The potential benefits of BIM-based maintenance management, referred to here as EMS 2.0, are currently hard to predict, but certain areas can be identified where EMS 2.0 will bring efficiency and effectiveness benefits for operators and other stakeholders. In addition to the visualisation of road infrastructure, monitoring can be more intuitive and findings can be precisely located. These findings can be used in making forecasts, for which sophisticated but data-hungry models have been developed in recent decades. The BIM(odel) or the three-dimensional geometry can, for example, be imported directly into finite element software to analyse the behaviour of the infrastructure objects under various actions. In order to exploit this potential, BIM(odels) must be created not only for infrastructure objects that have been newly built or for which maintenance measures have been performed, but also for existing infrastructure objects. New sensing technologies, such as 3D laser scanning, photogrammetry, ground penetration radar (GPR), thermography and artificial intelligence (AI) methods, offer promising new options for efficiently creating BIM(odels) of existing infrastructure objects. The quality of these BIM(odels) is currently not always satisfactory and in some cases still has to be processed manually, although this will change over time. Currently, intensive research is being carried out in the field of sensing technology and artificial intelligence and it is expected that further progress will be made in the near future. Finally, organisational measures are also necessary to exploit the potential benefits of EMS 2.0. In particular, infrastructure operators must take over data governance as well as actively manage data flows.


Building Information Modelling (BIM) is becoming increasingly prevalent in infrastructure asset management, as it facilitates current management practices. This includes the construction of BIM models for roads, rails, bridges, tunnels etc. Bridges are particularly challenging to digitalize due to their complex geometry. The manual construction of bridge BIM models based on 2D plans is hardly feasible due to the related workload. Given the recent advancements in the field of 3D surveying and artificial intelligence, new possibilities emerge for an automated generation of as-is bridge BIM models.

This paper presents a novel, modular framework for the automatic processing of point clouds into as-is BIM models, based on a fusion of artificial intelligence and heuristic algorithms. Representative bridge element datasets were provided to train neural network. Trained neural network can identify elements of a bridge, which are further processed using geometric algorithms into surface and solid bridge elements. This result can be additionally enriched with semantic information from existing databases. The final BIM models are exported in the standardized vendor-free Industry Foundation Classes (IFC) format.


To facilitate decision-making on optimal maintenance strategies for ageing traffic networks, a novel quantitative framework is presented. The framework comprises evaluation of the four KPI: reliability, safety for users and third parties, availability, and sustainability. The evolution of KPIs over time is subject to damaging processes and maintenance interventions. To characterize the impact of damaging processes and maintenance interventions, relevant performance indicators (PI) are selected that are used to estimate the key performance indicators (KPI). The native units of each KPI are normalized to a scale from 1-5. Normalized KPI values are plotted on spider diagram for each time instance, rendering a 3D body with the volume which represents the network’s quality over time, for considered maintenance strategies. The framework is aimed for medium to long-term maintenance planning and can be further upgraded to account for risk & resilience analyses. The framework is implemented in a web-based prototype to demonstrate its utilization in practice and future management systems.


Structures represent a decisive key function within transportation networks. In the event of their failure or limited availability, there are usually considerable negative effects on the traffic flow. Therefore, their failure must be avoided at an early stage with suitable maintenance measures. The further development of key performance indicators (KPIs) is increasingly being discussed with regard to the description of condition and the assessment of target fulfilment of the life cycle management of structures. Performance indicators measure various properties that are decisive for the performance assessment of an engineering structure. They can be structured hierarchically and those at the top level of the hierarchy are called key performance indicators (KPI). The key performance indicators show whether a structure meets the performance targets. This paper presents a methodology for the creation of an indicator-based KPI system that can be used for the life cycle management of structures. The methodology was prototypically implemented within the framework of a research project and tested on the basis of application examples.


The linking of the Building Information Modeling (BIM) method and asset management currently represents a necessary innovation process in the life span consideration of infrastructures. With consequent usage, it can be expected that the data and information needed in the different phases of the life span will be available. This requires the consistent and lossless transfer of data from different data systems. How this can be done has been investigated in two research projects, which are reported in the represented paper. After a description of the fundamentals of asset management (AM) and BIM, approaches for the implementation of the BIM method in the life span are shown using the example of roadways and bridges. One project addresses the implementation in the European context, the second project the implementation in the D-A-CH context. The challenge in these research projects was to take into account the different country-specific technical requirements and the different database systems used. In order to set up such a model, the architecture and process flows of the relevant infrastructure asset management systems (IAMS) had to be analysed first in order to formulate detailed requirements for the information needs and data exchange in the IAMS. The challenge here is to develop an approach in which different ontologies and different semantics can be handed over barrier-free between different participants in the IAMS process. For this purpose, the processes of an IAMS were described using the BPMN method. As a result, a generic process and data model for the operation and maintenance phase could be defined, in which essential data exchange points are evident. For these data exchange points, it was simultaneously defined which property sets and properties must be transferred so that the engineering tasks of an asset management can be fulfilled. As a result, a container-based data exchange was developed as a linked data approach and its functionality was demonstrated by means of a prototype.

The existing asset management systems are used both as information systems and as a basis for decision-making in maintenance management. The transport infrastructure is mostly visualised in a 2D GIS; the asset management systems are not based on 3D geometry so far. Initial pilot projects have clearly shown that BIM-based asset management has great potential benefits. This is not limited to intuitive interactions during data queries, but also contributes to the visual and technical understanding of the interconnection of the individual components of the transport infrastructure and the comprehensive documentation that is handed over to the operator after the new construction or maintenance measure. In addition, previous breaks in the information chain between construction and maintenance management can be closed. Thus, a very detailed information base is available, which can be used over the lifetime of the structure. The asset management systems, for their part, contain well-structured data with adequate semantics and ontology, which lend themselves as a basis for this linkage. Linking this data with the BIM models from the field of construction increases the usefulness of already existing information systems and enables intuitive asset management. This paper shows how this linkage can be done over the entire life cycle.

Bridge Management Systems (BMSs) are sophisticated software tools, widely used for managing bridges. Comprising a centralized database of all relevant information for the entire bridge stock and analytics to forecast bridges’ condition and maintenance cost, BMSs are irreplaceable tools, used by all the National Road Authorities (NRAs) around the world. These powerful tools, although different from one another, all lack adequate visualization of bridges. Recently, numerous researchers proposed using the Building Information Models (BIMs) to address this issue.

This paper presents a geometric approach of introducing BIM to BMS. Rather than trying to thoroughly connect these two robust systems on the object definition level, this approach focuses on geometry. The paper firstly shows how all the inventory information from BMS can be associated with corresponding BIM objects, and afterwards, the ways to include the condition assessment data into BIM are proposed. Once the basics of the geometric approach are explained, the example of connecting BIM with BMS is presented. The example is based on KUBA, the Swiss BMS. Finally, the feasibility, as well as the challenges of the presented approach, are analyzed. The analysis focused on two important questions.

Firstly, it considered if BIM is capable of making workflow changes in the Infrastructure Asset Management (IAM) the same way it did it in the construction industry. Secondly, it evaluated the BIM capability to describe all the condition assessment information relevant to IAM.

You can download the paper here.


Building Information Modelling (BIM) methods are already being used successfully for planning and construction in the field of building construction and infrastructure projects. The use of BIM in operation over the lifetime of road infrastructure has not yet been in focus, but promises a considerable increase in benefits, especially, not only, for road authorities. The updating of the status and effects of maintenance measures required for asset management gains added value with BIM, especially through the associated, precise geometric information. In this context, it is necessary to expand the proven data flow of the asset management systems with BIM data. Within the framework of the BIM4AMS research project, the construction material data relevant over the service life of the road pavements was integrated into a consistent and comprehensive BIM concept for the asset management of the road infrastructure and linked with the already existing asset management data.
For this purpose, a methodology was developed and exemplarily tested with the help of an IT prototype, how relevant, technical information for the assessment of the condition in life cycle assessments of the road infrastructure can be provided in the form of information containers according to ISO 21597 and how the results can be verifiably queried. Three relevant use cases were identified and tested, in which data exchange takes place between the infrastructure manager or owner and external service providers.

Bridges are a vital, but also extremely vulnerable part of transportation infrastructure. The design and construction of a bridge have a large influence on its longevity although these phases are short compared to its life span. It is therefore essential that at the acceptance the bridge together with the accurate as-built information is delivered to the owner. A bridge owner relies on as-built high-quality information and on information on a bridge condition to initiate interventions that ensure its safety and serviceability. The information on the bridge condition is obtained through regular inspections as well as monitoring activities. During the lifetime of a bridge, these diagnostic activities may generate a huge amount of data that needs to be managed. With changing environmental actions, accurate and usable information from the inspection and monitoring – in conjunction with as-built data – is essential for efficient and timely maintenance planning.

Inspections and maintenance planning require organized, automated, open and intuitive digital processes, which should consider both object data and related condition data. This seamless digital process is supported by existing Bridge Management Systems but can be vastly improved. In particular, most BMS do not support geometric representation which makes data collection during inspections quite tedious. The introduction of BIM in BMS can substantially facilitate the collection of inspection data and accurately localize monitoring data. Moreover, the exact geometry of bridges can enhance maintenance planning by simulation of the structural behaviour of the as-is structure under different environmental actions. BIM’s incorporation would evolve BMS into a fully digital storage system and a platform for data exchange with existing BIM solutions as well as for maintenance planning that include deterioration forecast, optimization and analysis models. The vision includes 3D+ software and hardware independent data exchange between different software technologies during life span and beyond. Open BIM technology for interoperability from the technical, semantic and organizational points is of main interest. The current status of  development and challenges that need to be overcome for the successful fulfilment of the presented vision are discussed.

You can download the paper here.

Die Prognose der Zustandsentwicklung ist eine wesentliche Komponente innerhalb des Erhaltungsmanagements der Straßeninfrastruktur. In Deutschland wird hierfür derzeit ein deterministisches Prognoseverfahren eingesetzt, das mit Hilfe von Verhaltensfunktionen und deren Kalibrierung die Zustandsentwicklung eines Straßenabschnittes prognostiziert. Gleichwohl ist das Zustandsverhalten von Straßen von einer großen Anzahl an Einflussfaktoren geprägt, die eine treffende Prognose erschwert. Die damit verbundenen Unsicherheiten sind mit den bisher eingesetzten deterministischen Prognosemethoden nicht abbildbar. In diesem Beitrag wird eine zweistufige probabilistische Bayes’sche Methodik zur Prognose der Zustandsentwicklung von Fahrbahnen auf der Grundlage des Extended Kalman-Filters (EKF) vorgestellt und deren praktische Anwendung auf Straßenzustandsdaten aufgezeigt. Das entwickelte Modell ist in der Lage, sowohl die Unsicherheiten im zukünftigen Verhalten des Straßenzustands aufgrund von zahlreichen Einflussfaktoren, wie z. B. den Materialeigenschaften und der Verkehrsbelastung, als auch Unsicherheiten aufgrund der Messpräzision der Zustandserfassung abzubilden. Der entwickelte Bayes‘sche Ansatz ist für beliebige Zustandsmerkmale (z. B. Längs- und Querebenheit, Griffigkeit, Risse usw.) anwendbar. Die Methodik wurde in einen webbasierten IT-Prototyp implementiert und anhand von Daten aus Straßennetzen in Deutschland, Österreich und der Schweiz erprobt. Die Prognoseergebnisse zeigen eine hohe Übereinstimmung zu den Daten aus dem Validierungsdatensatz. Neben der Prognose der mittleren Zustandsentwicklungen bietet das Verfahren den wesentlichen Vorteil der Quantifizierung von Unsicherheiten in der objektbezogenen Zustandsprognose. Damit liefert die Methodik einen wichtigen Baustein auf dem Weg zu einem risikobasierten Erhaltungsmanagement.
Eine leistungsfähige und sichere Straßeninfrastruktur ist die Grundvoraussetzung für gesellschaftlichen Fortschritt: Sie ermöglicht Wirtschaftswachstum, Beschäftigung und Wohlstand und stellt damit das Rückgrat einer modernen Gesellschaft dar. Ein wachsamer Infrastrukturbetreiber kann die Szenarien, welche die Sicherheit und Leistungsfähigkeit der Straßeninfrastruktur gefährden könnten, rechtzeitig erkennen und Gegenmaßnahmen zur Abwendung dieser Szenarien planen und einleiten. Die Entscheidungsfindung zu diesen Maßnahmen ist die Hauptaufgabe des Erhaltungsmanagements und ihre Qualität ist von Umfang und Qualität der verfügbaren Daten abhängig ist. Durch den Einsatz von Building Information Modeling (BIM) stehen Daten zur Verfügung, mit welchen die Straßeninfrastruktur realitätstreu während der gesamten Lebensdauer abgebildet wird. Mit dieser Datengrundlage können die in den letzten Jahrzehnten entwickelten da- tenhungrigen Modelle eingesetzt werden, mit welchen das Verhalten der Infrastruktur unter verschiedenen Einwirkungen simuliert werden kann. Diese Simulationen ermöglichen bessere Entscheidungen in Bezug auf die Auswahl von baulichen Maßnahmen und folglich eine effizientere Nutzung der Straßeninfrastruktur. Der Artikel zeigt das Nutzenpotential eines BIM-basierten Erhaltungsmanagements sowie wie die hierfür erforderlichen BIM(odelle) bereitgestellt werden können.
The paper proposes a solution for a Building Information Modeling (BIM)-enabled Infrastructure Asset Management System (AMS) for road owners. The approach provides asset managers with a strategy for the dynamic use of Information Containers for Linked Document Delivery (ICDDs), considering the requirements of stakeholders across domains in the operational phase. The state of the art shows how information management can be carried out utilizing information containers employing Semantic Web technologies Resource Description Framework (RDF), SPARQL, and R2RML. The key output is developing a web-based platform that implements ICDD containers for asset management. Existing AMS are integrated by using SQL data mapped to RDF-based ontology data in the container. The use of existing domain-specific ontologies for infrastructure in combination with the linkage of domain knowledge to a three-dimensional BIM model is a step beyond the state of the art and practice in the construction industry. Linking inside the container allows for querying data across several information models and ontology-based data to create stakeholder-specific data views. The approach was demonstrated in two use cases. The first was related to the visual inspection of a concrete bridge. The detection of damage and the process of communicating the damage to a contractor charged with the repair were described. The second use case was related to a road pavement and demonstrated how decision-making about maintenance activities can be supported using cross-domain information containers.
Decision making in pavement management relies on current road condition and the condition forecast. In this study, it is shown that both the condition forecast as well as the condition measurements are affected by uncertainties as demonstrated in a literature review and in preliminary studies of road condition data. If these uncertainties are to be considered in forecast models, the need for a probabilistic approach is evident. In this study a methodology based on an Extended Kalman filter (EKF) was developed and tested, which allows combining both empirical models and collected condition data for the development of section-based pavement forecast models. The model has been validated to predict the condition state effectively for all selected condition indicators. All relevant steps for the condition forecast have been implemented into a prototype to evaluate the applicability of the methodology using collected data on road networks from Germany, Austria, and Switzerland.
DOI: https://doi.org/10.1080/15732479.2022.2077769

As a result of the CEDR Call 2015 (project Interlink) a framework for a European road OTL is available. AMSfree builds on this result and aims for a wider implementation among individual CEDR members. The AMSfree project analyses the architecture of Infrastructure Asset Management Systems (IAMSs) used by National Road Authorities (NRAs), as well as the asset information content in current IAMSs in order to establish detailed technical requirements for linking IAMS and Building Information Models (BIMs) as infrastructure asset databases on a macro and micro level. The analysis is performed on a range of BIM models utilized by designers and contractors, so the level of development (LOD) for the common infrastructure asset BIM can be agreed on. Hereafter the recommendations for handling the insufficient exchange data are established, as well as the rules for semantic transformation. All data from the source systems is transferred to a reference database by using the established transformation rules.

The semantic transformation between different legacy systems is enabled on the basis of the Industry Foundation Classes (IFC) property templates, taking into account the IFC import/export capabilities of various systems. Specifically, a universal mapping approach between different IFC properties of different legacy systems is defined. For this purpose, a corresponding architecture is developed and prototypical implemented. Existing national data formats (e.g. OKSTRA, Interlis2) are linked with the IFC format.

Based on the results, the interoperability proof-of-concept is developed. Afterwards, the requirements are defined to enable the linkage between the data in IAMS and the IFC model. Based on the requirement a prototype is developed and documented.

The ageing of bridge stock in developed countries worldwide and the increasing number of recorded bridge collapses have underlined the need for more sophisticated and comprehensive assessment procedures concerning the safety and serviceability of structures. In many recent failures, construction errors or deficiencies have contributed to the unfortunate outcome either by depleting the safety margin or speeding up the deterioration rate of structures. This research aims to quantify the impact of construction errors on the structural safety of a bridge considering corresponding models available in the literature that probabilistically characterise the occurrence rate and severity of some of these errors. The nominal probability of failure of structures, neglecting construction errors, is typically computed in numerous works in the literature. Therefore, the novelty of this paper lies in the consideration of an additional source of uncertainty (i.e., construction errors) combined with sophisticated numerical methods leading to a more refined estimation of the probability of failure of structures. Accordingly, some benchmark results focussing on error-free and error-included scenarios are established, providing useful information to close the gap between the nominal and the actual probability of failure of a railway bridge.

Bridge Management Systems (BMSs) are sophisticated software tools, widely used for managing bridges. Comprising a centralized database of all relevant information for the entire bridge stock and analytics to forecast bridges’ condition and maintenance cost, BMSs are irreplaceable tools, used by all the National Road Authorities (NRAs) around the world. These powerful tools, although different from one another, all lack adequate visualization of bridges. Recently, numerous researcher proposed using the Building Information Models (BIMs) to address this issue.

This paper presents the geometric approach of introducing BIM to BMS. Rather than trying to thoroughly connect these two robust systems on the object definition level, this approach focuses on geometry. The paper firstly shows how all the inventory information from BMS can be associated with corresponding BIM objects. Afterward, the ways to include the condition assessment data into BIM are proposed. Once the basics of the geometric approach are explained, the example of connecting BIM with BMS is presented. The example is based on KUBA, the Swiss BMS.

Finally, the feasibility, as well as the challenges of the presented approach are analyzed. The analysis focused on two important questions. Firstly, it considered if BIM is capable of making workflow changes in the Infrastructure Asset Management (IAM) the same way it did it in the construction industry. Secondly, it evaluated the BIM capability to describe all the condition assessment information relevant to IAM.

Bridges are a vital, but also extremely vulnerable part of transportation infrastructure. The design and construction of a bridge have a large influence on its longevity although these phases are short compared to its life span. It is therefore essential that, at the acceptance the bridge together with the accurate as-built information is delivered to the owner. A bridge owner relies on an as-built high-quality information and on information on bridge condition to initiate interventions that ensure its safety and serviceability. The information on bridge condition is obtained by regular inspections as well as monitoring activities. During the lifetime of a bridge these diagnostic activities may generate huge amount of data that needs to be managed. With changing environmental actions, accurate and usable information from the inspection and monitoring – in conjunction with as-built data – is essential for efficient and timely maintenance planning. Inspections and maintenance planning require organized, automated, open and intuitive digital processes, which should consider both object data and related condition data. This seamless digital process is supported by existing Bridge Management Systems but can be vastly improved. In particular, most BMS don’t support geometric representation that render data collection during inspections quite tedious. The introduction of BIM in BMS can substantially facilitate the collection of inspection data and accurately localize monitoring data. Moreover, the exact geometry of bridges can enhance maintenance planning by simulation of structural behavior of as-is structure under different environmental actions. BIM’s incorporation would evolve BMS into a fully digital storage system and a platform for data exchange with existing BIM solutions as well as for maintenance planning that include deterioration forecast, optimization and analysis models. The vision includes 3D+ software and hardware independent data exchange between different software technologies during life span and beyond. Open BIM technology for the interoperability from technical, semantic and organizational point is of main interest. Current status of development and challenges that need to be overcome for successful fulfilment of the presented vision are discussed.
Die bestehenden Asset-Managementsysteme werden sowohl als Auskunftssysteme als auch als Basis für die Entscheidungsfindung im Erhaltungsmanagement benutzt. Die Verkehrsinfrastruktur wird dabei meist in einem 2D-GIS visualisiert, auf einer 3D-Geometrie basieren die Asset-Managementsysteme bisher nicht. Erste Pilotprojekte haben deutlich gezeigt, dass das BIM-basierte Asset Management ein großes Nutzenpotenzial hat. Dies beschränkt sich nicht nur auf intuitive Interkationen bei den Datenabfragen, sondern trägt auch zum visuellen und fachlichen Verständnis der Verknüpfung der einzelnen Bestandteile der Verkehrsinfrastruktur und der umfassenden Dokumentation bei, welche dem Betreiber nach dem Neubau oder der Erhaltungsmaßnahme übergeben wird. Zudem können bisherige Unterbrüche in der Informationskette zwischen Bauausführung und Erhaltungsmanagement geschlossen werden. Somit ist eine sehr detaillierte Informationsbasis vorhanden, welche über die Lebensdauer genutzt werden kann. Die Asset-Managementsysteme ihrerseits enthalten gut strukturierte Daten mit adäquater Semantik und Ontologie, welche sich als eine Grundlage für diese Verknüpfung anbieten. Eine Verknüpfung dieser Daten mit den BIM Modellen aus dem Bereich der Bauausführung steigert die Nützlichkeit von bereits vorhandenen Informationssystemen und ermöglicht ein intuitives Asset Management. In diesem Beitrag wird aufgezeigt wie diese Verknüpfung über die gesamte Lebensdauer erfolgen kann.

In maintenance management, the aim is to achieve or maintain a required level of performance of the existing road infrastructure by systematically determining necessary and optimal maintenance measures. Models for the condition development of roadways are an important building block for the estimation of long-term maintenance costs. The aim of the mapFALKE research project was the further development of methods for the formation of condition prediction models using extended calibration procedures for the determination of behaviour-oriented material properties.

The methodology for the development of deterministic and probabilistic models was identical to the procedure for empirical investigations using observations and their influencing factors. The novelty in the field of condition development models is the use of road data available throughout the network on the one hand, which usually includes only the condition data, and on the other hand data from existing or additionally easily collected laboratory results from local material investigations for the calibration of the models of individual road sections. Within the framework of the model development and calibration, data from material investigations were required, which were available through existing laboratory results from past research work in Germany and Switzerland, on which further material investigations could be carried out. In addition, existing research data could be evaluated again for the modelling. In addition, correlations were tested on existing condition data. Different types of models for the development of the condition were identified and a simple model was developed with a step-by-step approach for calibration depending on the data basis. The current data situation in Switzerland does not yet allow a calibration based on the material investigations. The developed approach can nevertheless be used with a limited data basis to generate models of the condition development from the road operator’s own existing road data. The requirements for the input data were defined and the application in different use cases was demonstrated. The calibration includes the use of new information from current survey campaigns. In addition, the use of additional material investigations is shown.

Within the framework of this research project, various insights were gained from the processing and the results obtained, and corresponding conclusions were drawn. These concern the existing data situation and quality of the condition data of the road surface as well as the data on the layer structure and the associated material investigations. Recommendations for practice, standardisation and further research are derived from this.

With increasing heavy traffic, the maintenance needs to ensure safe and reliable utilization in particular on federal highways, but also on state roads will substantially increase in the future. At the same time, these roads in urban areas are already reaching the limits of their capacity. Therefore, the negative impacts of work zones on traffic flow caused by maintenance interventions should be avoided as far as possible. So far, the effects of maintenance-related road work on road users can only be determined with insufficient accuracy. However, this is indispensable to perform a benefit-cost comparison of the different technically possible maintenance measures for roads and road structures as well as the cross-asset decision-making. The present article describes the developed framework for the application of macroscopic traffic simulation in the field of maintenance management. In this way, the influence of maintenance-related work zones on travel times can be estimated and taken into account in decision-making in a macroeconomic approach. Finally, recommendations for practice and further research needs are discussed.

Safety, reliability, and availability of transportation infrastructure are jeopardized by oncoming natural and man-made hazards that may inflict severe consequences to its stakeholders. In order to avoid or mitigate these extreme events with adequate activities and expedite the recovery in a case of failure, risk-based information-driven approaches are applied in asset management. Here, the main challenges for engineers are to be far-sighted in detecting possible threat scenarios that lead to critical failures, and in estimating related consequences over time. Within these tasks, there are numerous uncertainties to consider: hazards’ intensity & frequency and related asset exposure, increased traffic demand and asset deterioration. Evidently, the prudent decision-making must be based on previous experience, involve various engineering expertise, and entail handling with large amounts of data. Thus, decision support tools (DST) are being developed to aid infrastructure managers to extract the diagnostic information from inspections/monitoring and consider diverse types of risks while balancing stakeholders’ demands and optimizing priorities over all infrastructure asset types.

Recently, risk-based approaches are being expanded to include the aspects of early warning of imminent failure(s) and contingency planning for an extreme event. These topics have been investigated within the scope of a European HORIZON2020 project SAFEWAY, which has a goal to develop a robust, resilience-based decision support framework for management of terrestrial transportation infrastructure. The paper presents the features of the web-based DST prototype, which is one of the main outputs of the SAFEWAY project. The DST allows for temporal risk analysis of assets in an infrastructure network for predefined threat scenarios and maintenance strategies. Here, the benefits of possible maintenance activities can be expressed as a discounted risk reduction, which in turn can be understood as resilience improvement. The resilience of an analysed network can be evaluated for contingency plans, both in medium to long-term as well as in short-term. The application of the DST is demonstrated on the pilot case study within the SAFEWAY project – the road and rail networks in the Santarem region in Portugal. The analysed case study comprises risk/resilience evaluation for predefined failure scenarios of bridges and road/track due to a future extreme flooding event.

In order to be able to estimate the financial resources required for the maintenance of the entire federal trunk road network, maintenance demand forecasts are carried out for a period of 15 years. Pavement Management Systems (PMS) are used for the forecast calculation for pavements. The derivation of technically and economically reasonable maintenance measures and times for sections in need of maintenance is essentially based on an analysis of causes of damage. These are described in a so-called defect class model. During the implementation of the last maintenance needs forecast 2016-2030, it became apparent that this model was severely outdated. The existing model variants were then analysed and revised. The examination and further development of the existing model variants showed that even simplified approaches for deriving maintenance measures in a decentralised context lead to plausible and comparable results at the network level.


Keeping transport links open in adverse conditions and being able to restore connections quickly after extreme events are important and demanding tasks for infrastructure owners/operators. This paper is developed within the H2020 project SAFEWAY, whose main goal is to increase the resilience of terrestrial transportation infrastructure. Risk-based approaches are excellent tools to aid in the decision-making process of planning maintenance and implementation of risk mitigation measures with the ultimate goal of reducing risk and increasing resilience. This paper presents a framework for quantitative risk assessment which guides an integrated assessment of the risk components: hazard, exposure, vulnerability and consequences of a malfunctioning transportation infrastructure. The paper guides the identification of failure modes for transportation infrastructure exposed to extreme events (natural and human-made) and provides models for and examples of hazard, vulnerability and risk assessment. Each assessment step must be made in coherence with the other risk components as an integral part of the risk assessment.
The link to the paper is here.

There are endangering scenarios that don’t announce themselves such as natural hazards, so there is no ample time to prevent failures of road infrastructure by maintenance measures. It should be noted that the consequences of failures depend not only on immediate losses (e.g., life and limb and material loss), but also on unavailability of infrastructure until it is fully available as before a failure. This means that not only by preventative measures but also by judicious planning of recovery measures, the consequence of failure and therefore risk can be reduced. The consideration of recovery time is essential in estimation of resilience. This article gives an overview on theoretical background of resilience approach and discusses the current state of application of the resilience frameworks in practice. The measures, which target specific resilience aspects, are presented within the case studies that are presented in a separate paper.

PIARC Ref.: RR389-023

The transportation infrastructure networks are exposed to oncoming natural and man-made hazards that may inflict severe consequences to network stakeholders. Current solution is to mitigate such threats with timely maintenance measures, relying on the outputs from risk-based information-driven approaches. However, the recent failures of infrastructure assets are painful reminders that risk methodologies need to be expanded to allow for emergency and post-hazard recovery i.e., account for the resilience of transportation networks. Thus, one of the main research topics in the asset management is development of a robust, resilience-based decision support frameworks. This is also in a scope of an ongoing European HORIZON2020 project SAFEWAY. This paper elaborates on the features of the web-based Decision Support Tool (DST) prototype, one of the main outputs of the SAFEWAY project. The DST enables both fusion and visualization of data necessary for risk and resilience analysis of multi-modal terrestrial transportation networks. In the DST, threats, related asset failure scenarios and maintenance/repair measures can be predefined. For the case of medium to long-term maintenance planning, temporal risk and resilience of networks are evaluated based on the Monte Carlo simulations of an annual extreme event magnitude, predefined assets’ fragility curves and related consequences’ scenarios. The preventative maintenance measures reduce risks of failure(s), which is regarded as a benefit, ultimately increasing resilience.
ISBN: 3030918777
Building Information Modelling methods are already successfully used for planning and construction in the field of building construction and infrastructure projects. Digital building models (BIM) are exchanged in an openBIM environment based on open standards, such as the Industry Foundation Classes (IFC), and used by different engineering disciplines independent of the task. Various extensions to IFC are currently being developed for road and bridge construction to enable efficient data exchange. The use of BIM in operation over the lifetime of road infrastructure has not yet been a focus, but it promises a significant increase in benefits, especially but not only for road administrations. The updating of the condition and the effects of maintenance measures required for asset management gains added value with BIM, especially through the precise geometric information. In this context, it is necessary to expand the proven data flow of the asset management systems with BIM data. For this purpose, the aim is to develop standardised exchange formats based on IFC. ISSN: 2748-9221

The EU-funded HORIZON 2020 project SAFEWAY aims to design, validate and implement holistic methods, strategies, tools and technical interventions to increase resilience of terrestrial transport infrastructure in the face of natural and man-made hazards. The basis for the project is establishing a robust decision support framework which can utilize remotely monitored data on hazards, infrastructure condition and traffic, to yield knowledge on the dynamics of relevant risk factors associated with potential asset failure scenarios. The first task of the framework is elaborating a value system regarding network resilience, based on monetized direct and indirect consequences of inadequate asset performance. Here, the quantitative risk assessment is will be used to estimate the expected loss of benefit of infrastructure due to failures for both single mode and for multi-modal transportation. The benefits of possible maintenance strategies can be expressed as discounted risk reduction, which in turn can be understood as maximizing resilience.


The economic and social losses due to increasing bridges collapse over the years have underlined the importance of the development of more robust bridge structural systems when exposed to harmful events, such as natural hazards, human-made hazards and human errors. Natural and human-made hazards are usually explicitly addressed in the numerous works available in the literature, but when it comes to human errors, very few studies can be found. It is worth mentioning that human errors have been identified as one of the main causes of bridges failure. Consequently, the main goal of this paper is the assessment of human errors impact on the robustness and safety of a prestressed reinforced concrete bridge through a probabilistic-based approach. Uncertainties concerning the numerical model, material strength, geometry and loading condition are used as key input parameters for the probabilistic assessment. Considering the structural system performance in its early days (i.e., virgin reliability index) the human error impact in structural safety is measured according to the structural system performance reduction given different errors with different magnitudes. Therefore, the structural system ability to maintain acceptable levels of performance, given such errors, is assessed.
DOI: 10.1080/15732479.2021.1876105
By developing a probabilistic model, it is possible to take into account the uncertainties contained in the input variables when forecasting the condition of roads. In the project, an extended Kalman filter is used, which forecasts the condition of surface features with continuous time and condition space. The quality of the probabilistic forecast results is comparable to that of the deterministic forecast. However, it becomes possible to represent uncertainties in the state forecast at arbitrary points in time, which opens up new possibilities for probability-based evaluations for the decision-makers. The developed methodology has a modular structure and makes it possible to integrate results from future research work. It was implemented as a prototype and extensively tested in pilot applications. Numerous evaluation possibilities are shown on the basis of application examples. It can be seen that the proposed and tested method provides an important building block on the way to risk-based maintenance management.


The impact on road users plays an essential role in decisions of road agencies. At the same time, the road agencies face rising maintenance costs due to least possible influence on road users by work zone during intervention. So far, the expected impact on road users can be calculated only insufficiently accurate especially on high volume roads. However, this is mandatory for a cost-benefit comparison to support the decision process. Macroscopic traffic simulations with existing traffic models are appropriate tools for determining user costs. The research project will develop missing model fundamentals in the form of CR-functions primarily for the changes in travel time by increasing link volumes or reduced link capacity in work zones or the changes in route choice behavior by work zones of planned intervention packages and the resulting changes of link volumes in the network. Basically this research for user cost calculation benefits decision-makers in the area of road maintenance management and scenario evaluation of road object intervention packages. The CR-functions are determined for relevant work zone traffic regimes, enabling a more accurate determination of time travel for the period of intervention. In addition, a prototype will show methodology for the use of user costs determined from macroscopic traffic simulations in the decision process for road object intervention packages.
For efficient bridge maintenance, bridge management systems (BMS) have been developed worldwide. In order to improve and further develop, PE Roads of Serbia has initiated a project entitled: Updating the methodology for reviewing and evaluating the condition of bridges and developing new applications for managing the database of bridges. The paper presents a new technical solution for the database on bridges, based on which a new application was established.
Reliable and proactive asset management is becoming increasingly important for transport infrastructure owners in the face of ageing assets, increasing traffic demand and changing weather patterns due to climate change. Current strategic asset management practice is assisted by various decision support methodologies and tools, but there are certain limitations to existing approaches. The EU-funded SAFE-10-T project is addressing these shortcomings through the development of a Decision Support Tool (DST) for effective and reliable management of bridges, tunnels and earthworks along Europe’s TEN-T network. Within the DST, one can evaluate temporal risk of failure of an infrastructure in multi-modal road, rail and inland waterway networks. This paper discusses required input data for this evaluation and the process of data ingestion into the DST. To showcase implementation in asset management practice, the DST is applied to a demo project located in the vicinity of the Port of Rotterdam.
The subject of this paper is heavy-duty transport in the Republic of Serbia. Permits for heavy-duty transport issued by the public company Roads of Serbia for two representive months: April and September in 2019 were considered. The following data from permits were analyzed: dimension of vehicle, number of axles, total vehicle weight and axle overload. The first part of this paper presents short review of the current analysis of heavy-duty transport in Europe and the world over the last 20 years, and also trends and expectations in the future. Second part of this paper represent statistical processing and analysis of data from permits of heavy-duty transport. On the end of this paper are given conclusions based on analysis of data from permits.

Inspection of bridges has been a standard assessment procedure for decades. Its purpose is to identify and record all defects of the bridge structure. Normally used inspection techniques are rather simple, mainly relying on visual assessment. This dissertation proposes an improvement of concrete bridge inspection in terms of visual data acquisition, damage identification and digital representation of the bridge with identified damages. Instead of depending strictly on the human eye, photogrammetrically obtained 3D point clouds are used to identify and extract concrete damage features. As the most comprehensive substitute for the old-fashioned inspection report, Bridge Information Model (BrIM) is used as an inventory and inspection data repository. An Industry Foundation Classes (IFC) semantic enrichment framework is proposed to inject the extracted and reconstructed damage features into the as-is IFC model. After the general data model for damage description and its IFC representation are established, the method for generating the as-is IFC model of the bridge is proposed. Damage is identified as a deviation of the as-is geometry, represented by the 3D point cloud, from the as-built geometry, represented by BrIM. Geometric and semantic enrichment of the IFC model is achieved by injecting the reconstructed 3D meshes representing damaged regions and corresponding BMS catalogbased damage information. The proposed method uses Constructive Solid Geometry (CSG) Boolean operations to geometrically enrich the IFC geometry elements, which align with corresponding damage regions from the as-is point cloud. Damage information (e.g., type, extent, and severity) is structured so that it complies to the BMS data structure. Finally, the proposed data model, damage identification, feature extraction, and semantic enrichment method are validated in the presented case study.

URI: https://grafar.grf.bg.ac.rs/handle/123456789/2170

In 2011 a long-term pavement performance (LTPP) section was established on a part of the Federal Highway BAB A5 in the centre of Hesse. The aim of this project is to build up a high- quality database for research activities within the field of road maintenance. In addition to the six-monthly pavement condition surveys, data on pavement structure and traffic loads as well as on maintenance and rehabilitation activities are documented in high detail. This article gives an overview of the extent and quality of the collected data.

In order to exemplify the potential of the available data of this LTPP-section to answer various research issues, the influence of different factors on changes in road condition is analysed based on the road condition indicator rutting. Within four years, changes in rutting are more effected by the scattering of the measuring method than being true condition changes. In conclusion, statements about changes in rutting are not reliable without any additional information on the age of the pavements. As a conclusion, an outlook on future investigations is given.

Efficient and secure transport infrastructure is the fundamental prerequisite for social progress. It enables economic growth, employment, and prosperity and thus represents the backbone of modern society. Planning, construction, operation, and maintenance of roadways require significant use of both financial and human resources. The Federal Transport Infrastructure Plan 2030 provides for a total volume of about € 270 billion, of which about € 70 billion will be used to maintain the existing road network by 2030 [BMVI 2016].

In Germany, a Pavement Management System (PMS) is used for a purposeful and objective distribution of funds, which estimates the maintenance requirements of federal highways based on the current state of the network and its future development. For this purpose, modern evaluation methods, as well as sound expertise, are needed. Estimates of the temporal status of pavement fortifications represent an essential element within the PMS in order to estimate the section-related maintenance requirements. The results of these previously deterministic calculations provide the basis for the subsequent decision-making process. The inherent uncertainties within this planning and decision- making process are due to various causes, such as data collection, data maintenance, different material behavior, and traffic and climatic boundary conditions. For future risk-based decision-making, suitable methods are required that can quantify possible events and their associated probabilities of occurrence based on scenarios.

An accurate description of road deterioration is one of the most challenging aspects within the scope of Pavement Management Systems (PMS). However, the data quality is often insufficient, as research has shown a high amount of road sections with measured condition improvements based on a simple comparison of two condition monitoring campaigns. The reasons for these improvements are often unknown due to restricted data quality of recorded maintenance works. Concerning an asset of the current state of a road network, this aspect is not that relevant because measurement errors lead to condition improvements as well as to condition deteriorations. However, concerning a longitudinal analysis of road condition, a consequent exclusion of measured condition improvements leads to a systematic violation of type one and type two errors from a statistical point of view: Road sections whose condition truly got worse are excluded due to measured condition improvements. Even though the mentioned problem is already partially known, suitable methods to handle this issue hardly exist.

The aim of the present study is the development and validation of a probabilistic forecasting model, which takes both the uncertainties in the condition state detection and the estimation of the condition state development into account. Based on a comparison of the predicted condition states with the results of the previously used deterministic methods, the applicability of the developed model shall be assessed. The developed method should enable a future risk-based decision-making process within systematic pavement management. This research is based on data from a long-term observation section in Hesse, Germany. In addition to the condition assessment and evaluation (ZEB), which is carried out every four years, semi-annual condition surveys on each driving lane have been carried out on the approx. 76 km long section of BAB A5 for several years. Furthermore, data on traffic loads, structure, and climatic conditions are collected, and all maintenance and rehabilitation treatments are documented in great detail.

The core element of the developed method is a Bayesian approach. The presented model differentiates between the true condition state of a road surface, observations in the form of condition measurements, and an estimated system behavior at discrete points in time. By combining an a priori system behavior with the continuous comparison between expected and noisy measured condition states, the true condition state of an evaluation section is deduced. The method offers the possibility of a probabilistic prognosis of the most likely condition development over time in order to reflect the large variety of possible condition state developments accurately. The developed method is presented by the example of rutting. Since the condition state development of a road surface is subject to a large number of influencing variables, considerable scattering is observed, which makes it challenging to arrive at an appropriate condition state prognosis. In order to reduce the uncertainties in the forecast, additional information is integrated into the model. First of all, potential influencing factors are identified, and the resulting hypotheses are subjected to a statistical test. The analyses are done with the help of a longitudinal structural equation model (SEM), which is gradually extended by the variable traffic loading. At the end of the investigations, the results calculated with the stochastic prediction model are compared to the results of the previously used deterministic prognosis methods.

As a result, the condition data can be improved by estimating the state distribution after 20 years. Compared to the unprocessed condition data, the deviation between true and predicted mean values can be reduced from 1.0 mm (SD = 1.2 mm) to 0.1 mm (SD = 1.5 mm). In addition to improved prognosis, the data can be enhanced significantly to provide the data basis used to estimate transition matrices. After data preparation, only about 5 % of all evaluation sections have a condition state improvement, whereas in the case of non-processed data, approx. 50 % of the data basis must be discarded due to measured condition state improvements. Due to the enlarged data basis, the transition distributions within the matrices can be modeled more precisely. Based on further differentiation of the state changes according to traffic loads and the respective present type of structure, the condition state distributions of all evaluation sections can be predicted with high accuracy. The deviation of the mean value between true and predicted condition state distribution is 0.0 mm. For the associated standard deviation, a value of 2.6 mm is predicted compared to the standard deviation of the true condition state distribution of 3.2 mm. The comparison between the deterministic and the stochastic method shows that the developed model provides comparable prognosis results to the deterministic method used in the current German guidelines RPE-Stra 01.

The developed probabilistic model allows consideration of the current uncertainties in the estimation of the remaining service life as well as in the planning of maintenance works. The comparison of different maintenance strategies based on probability distributions provides the basis for risk-based decision-making. This fact represents the main advantage, in contrast to deterministic prognosis methods. The high variability in the development of road condition indicates that essential factors influencing the temporal behavior of pavements are currently not recorded across the road network. In particular, this includes information on bearing capacity, which is not yet available at the current time throughout the network. This approach will be focussed in the future since the causes of road surface damages can be thoroughly analyzed only by considering the structural behavior of the road section. Furthermore, a fundamental prerequisite is the systematic documentation and maintenance of all collected data. With the help of this essential information, the condition prognosis can finally be refined.

DOI: 10.25534/tuprints-00013279

Building Information Modeling (BIM) representations of bridges enriched by inspection data will add tremendous value to future Bridge Management Systems (BMSs). This paper presents an approach for point cloud-based detection of spalling damage, as well as integrating damage components into a BIM via semantic enrichment of an as-built Industry Foundation Classes (IFC) model. An approach for generating the as-built BIM, geometric reconstruction of detected damage point clusters and semantic-enrichment of the corresponding IFC model is presented. Multiview-classification is used and evaluated for the detection of spalling damage features. The semantic enrichment of as-built IFC models is based on injecting classified and reconstructed damage clusters back into the as-built IFC, thus generating an accurate as-is IFC model compliant to the BMS inspection requirements.

DOI: https://doi.org/10.1016/j.autcon.2020.103088

By maintaining Uri road infrastructure, the cantonal road agency is ensuring safety, reliability and driving comfort on the roads for passengers and freight transport and thus, contributes to economic and social added value. The canton Uri has one of the first road agencies with an infrastructure division responsible for all road infrastructure objects. This includes inventory, condition inspections, maintenance planning and necessary data management. Uri maintenance and rehabilitation processes for pavements are embedded in a holistic road asset management process supported by an essential IT infrastructure.

One of the key applications is a flexible decision support tool “infFaros Uri” which was customized and developed together with the infrastructure division of canton Uri to meet their needs. infFaros can handle road sections and bridge together allowing synergy effects and corridor planning. It supports various methodologies including probabilistic and deterministic deterioration, cost/benefit and cost/effectiveness decision-making as well as consideration of four-year maintenance and rehabilitation plan and evaluation of its impact. By linking short- and long-term maintenance and rehabilitation planning using existing cantonal transportation data complex questions can be answered and decision making can be efficiently supported by scenario comparisons. infFaros is a modern web-based application. The paper presents both the technical background of the software and use of it to support four-year maintenance and rehabilitation planning within new Uri road asset management process.

DOI: https://doi.org/10.1007/978-3-030-48679-2_14


The increased need to manage road infrastructure in holistic manner led in the recent years to vivid research in diagnostics and maintenance planning of all types of road infrastructure objects. The practice lags behind this research and with very few exceptions a silo-based approach to maintenance planning is still dominant within the road agencies. The implementation of a holistic
approach in practice is also hampered by the lack of scientifically sound and yet flexible decision support tool that can handle data of varying quality. With the goal to remove this obstacle and based on the long-term research, the development of infFaros started in 2015. 

infFaros can handle road sections and road structures (e.g. bridges) together making use of synergy effects and allowing corridor planning. It supports various methodologies including probabilistic and deterministic deterioration, cost/benefit and cost/effectiveness decision-making as well consideration of already scheduled interventions and the evaluation of their impact. infFaros is a modern web-based application. The paper presents both technical background of the software and outlines its software architecture.

It is widely accepted that safety and serviceability are primary concerns in bridge design. However, for the most of bridges’ service life, these concerns are addressed indirectly by a qualitative measure, defined herein as condition rating, which is based upon observable damages recorded during inspections. Condition rating is at best, only loosely correlated to safety and serviceability. It would
be more reasonable to address safety and serviceability in an inspection process directly, using the information on bridge performance obtained during the design and construction. 

To address this issue, the reliability was chosen as a Key Performance Indicators (KPI) for existing bridges and a novel practical solution is proposed. It is based on survey of observation types (visible defects, measurements, etc.) used in Europe, which were examined with regard to their potential impact on reliability regarding safety and serviceability. The impact of these observations on reliability is also dependent on their type, location and intensity/extent as well as on bridge structural systems. The paper presents a methodology to assess reliability, which heavily relies on data from design and construction phase. It also proposes a set of data elaborated in design and/or construction phase that need to enter current bridge data bases to allow a rough reliability assessment of existing bridges.

The main objective of the COST Action TU1406 is to develop a guideline for the establishment of Quality Control plans for roadway bridges. The guideline is based on conclusions of Working groups 1 and 2 of the Action and is further developed with the contributions and findings of members of Working group 3. The paper presents the overview of the developed framework, where gradual damage processes as well as sudden events are being addressed in evaluation of Key Performance Indicators. The proposed framework relies on data from design and construction phase, as well as from results from visual inspections that are used for an assessment of safety and serviceability – the primary concerns of bridge managers. Special attention is aimed at possible Failure modes and related bridge Vulnerable zones. These are, for instance high moment regions, high shear regions and constructions joints, but can also be zones of bridge conceptual weaknesses. Since there are differences in design and materials for various bridge types, the suitability of the framework is tested separately for girder/frame bridges and arch bridges. Due to the specifics of sudden events, the application of the framework is given separately from gradual damage processes. Emphasis is given on flooding and scour as these are the most common culprits of bridge failures. The steps in the implementation of the framework are briefly shown and an illustrative example is presented.

In the last 40 years road organisations have been striving to adapt and upgrade their policies and procedures using the benefits of novel IT technologies. The efforts have been aimed at elaborating and applying innovative methods to collect useful data and to transform them into high-quality information. Furthermore, significant efforts have been put to resourceful approaches to use this information in decision making. The work of Technical Committee D1 “Asset Management” focused on investigating the organisations’ procedures/policies and management systems to identify innovative approaches.

ISBN: 978-2-84060-541-6

The report is available online here.

It is foreseeable that in not so distant future, Building Information Models (BIM) of both newly built and existing bridges will be available. These models can and will be included into the Bridge Management System (BMS) and will significantly enhance the quantity of useful information in future BMS. Apart from exact semantic and spatial specification, BIM can embed realistic structural system of a bridge as well as the relevant load situations. The evaluation of the reliability or safety/serviceability would be therefore possible quasi, on-the-fly within the future BMS, provided that the observations and results from SHM can be adequately integrated in BIM. In principle, the
inspection results can be directly captured in the BIM using photogrammetry or some other procedure. Cracks, spalling, deformation, and other defects will be a part of a BIM, which in the most cases alter the BIM geometry.

The data stored in future BMS include also other changes that a bridge experience during its life span. This includes strengthening,  widening, seismic retrofit and other structural changes. In short fBMS is similar to the 6D BIM or Asset Information Model, which continues to be updated during the whole service life of a bridge.

The paper discusses the BIM requirements of owner and operators and shows where these deviate from design and construction needs. It presents conceptual framework for integration of BIM in BMS developed by the authors in recent years. 

The prediction of road behavior is characterized as a variable process defined by several exogenous factors, such as traffic loads or climate, and endogenous factors, for instance planning, type and quality of construction. This paper discusses the procedure of analyzing big data and potential sources of error by using a pure statistical approach. Therefore, explanatory variables such as age of surface layer, traffic loads and structure thickness were analyzed con- cerning their power of influence on rut depths. This investigation was based on a part of the Ba- varian road network. The results confirmed that the age of a road section, structure thickness and traffic load are effective variables to explain the prospective condition of roads. The used methodological approach offers substantial advantages but has drawbacks as well that have to be taken into account and which are also discussed.

ISBN 978-0-367-20989-6

The test methods for four scuffing devices had been written up as technical specification PR CEN/TS 12697-50, Resistance to scuffing, which was reviewed by the DRaT project, under CEDR Call 2014: Asset Management and Maintenance. Existing knowledge on scuffing was reviewed and a round robin testing programme was undertaken with four replicate samples of three variations each of three mixture types. A statistical analysis found that results from the different devices could not be accurately correlated, either for specific asphalt mixture types or overall, nor could specific designs of scuffing equipment be identified as be- ing best for identifying the scuffing-resistance of asphalt mixtures. Nevertheless, enhancements to PR CEN/TS 2697-50:2016 were identified that can be made to make a better and more unified document without rejecting any of the designs of scuffing apparatus. A copy of the revised version of the standard was given in the final report.


With the increasing automation in the field of transportation and the increased demands with regard to the quality of road data, the need to enhance spatial reference of road data from axis to lane referencing has become more importance. Strong drivers of this trend are
autonomous driving, traffic navigation, traffic management, traffic modelling and simulation. However, lane-related data is also widely used in the area of road infrastructure.

The aim of this project is to develop an extension of the model for spatial reference of road data, which allows for lane level instead of “just” road level location referencing. This allows a more precise location description of road data, which are primarily lane-related, such as usage, road condition, signaling, turn restrictions, traffic volume and accidents.

Accessible here. 

The Serbian road network includes a large portion of bridges with shallow foundations vulnerable to local scour as tragically demonstrated during the extreme flooding in May 2014. Currently, the bridge management procedures in Serbia and worldwide do not comprehensively account for a risk of bridge failure due to flooding and fail to provide sufficient information for the decision-making. Thus, a novel methodology for quantitative vulnerability assessment is suggested as a tool to identify the most vulnerable bridges in a network. Herein, the essential task is evaluation of the conditional probability of a bridge failure due to local scour in a flooding event of a certain magnitude. To apply this approach on a network level, there is a dire need to establish precise practice-ready guidelines on an optimal set of information to be used and/or collected in situ, which is discussed on an example of the Serbian bridge database. The vulnerability of a bridge to local scour may be used as a comprehensive indicator of a bridge performance in a flooding event. For a network level, the vulnerability maps with respect to flooding of different magnitudes will give road operators crucial information to apply adequate quality control plans to vulnerable bridges.


doi: 10.1080/15732479.2017.1406960

Following the principles and goals of COST TU1406 action and the results of preceding WG1 and WG2 reports, the WG3 report elaborates the framework to establish quality control plans for road bridges. The qualitative approach is suggested in evaluation of the key performance indicators (KPIs): Reliability, Availability, Safety, Economy and Environment, with a possibility for an upgrade to a full quantitative approach. It is intended to use all relevant information from inventory and inspections, coupled with engineering judgement. The latter is based on the knowledge on possible bridge failure modes and related vulnerable zones i.e. parts/segments of a bridge where damages have the most significant impact on the bridge performance. If this information is available before inspections, the inspection procedures need not to change significantly. The framework is to be applied on non-landmark bridges, and covers girder, frame and arch bridges types. It is envisioned to have two stages – static and dynamic. In general, the first one comprises the preparatory work, inspection tasks and static (i.e. snapshot) assessment of the KPIs. The second stage implies assessment of remaining service life, KPI development over time and finding an optimal maintenance scenario i.e. decision making.

ISBN: 978-86-7518-200-9

The report can get downloaded here.

Bridge quality, as a measure of its compliance with the performance goals is tracked by the quality control plan. In other words, the quality could be understood as a comparison between performance indicators and performance goals. Reliability is widely recognized as the most important key performance indicator. This paper proposes a new approach to the mentioned comparison that provides valuable information and consequently improve decision-making regarding future course of action.

A current quality control plan is facing certain limitations. Defects are being detected in the inspection and documented in the inspection report. In the most cases, however the essential information for reliability assessment i.e. the extent and location of the defects is not recorded. 

The proposed approach uses a Bayesian net for the prior analysis of the bridge. Afterwards, the net is updated after each inspection, allowing a posterior analysis of the bridge reliability. A damage free state of the bridge, so-called “virgin state” is adopted as a baseline, while inspectors are asked to estimate the severity of the defect and consider the vulnerability of the structural system for the locations of defects.


It is widely accepted that safety and serviceability are primary concerns in bridge design. However, for the most of bridges’ service life, these concerns are addressed indirectly by a qualitative measure, defined herein as condition state, which is based upon observable damages recorded during inspections. Condition state is at best, only loosely correlated to safety and serviceability. It would be more reasonable to address safety and serviceability in inspection process directly, using the information on bridge performance obtained during the design and construction. The future Bridge Management Systems (fBMS) should therefore include this information allowing assessment of safety and serviceability based on inspection results. By including Bridge Information Models that are currently being developed and Structural Health Monitoring, the fBMS will become an invaluable decision-support tool not only for maintenance planning but also for issuing special permits, specification of heavy vehicle corridors, risk assessment due to natural hazards, etc.

The state-of-the-art bridge management practice do not adequately account for flooding and related local scour, thus fail to provide crucial information to viably mitigate consequences of bridge failures. The current policies in practice, which are solely based on visual inspections, need to be updated with efficient, preferably quantitative methodologies for a comprehensive and timely screening of vulnerable bridges. The research is aimed at application of key performance indicators which consider relevant data for assessment of vulnerability to local scour. Herein, particularly bridge exposure and bridge resistance are assessed. The latter involves failure modes, an essential ingredient for evaluation of a probability of failure, which is related to the indicator of reliability. The guidelines are necessary for inspection of bridge vulnerable zones i.e. segments that have the key role in resistance to failure. The practical evaluation of the reliability class is presented for RC girder bridges, which support elaboration of adequate quality control plans.


The original objective of the research project was to combine three planning processes for pavements as defined in the VSS standards, to minimize the planning effort for various existing road networks and to optimize the condition assessment. On one hand, it was demonstrated that the combination of these processes, which was originally intended, does not lead to a minimization of the planning effort. On the other hand, since the majority of road owners already follow structured process for condition assessment, there is little room for further optimization. It is therefore that the original objective had to be adapted. 

The adapted goal of this project is, based on the current practice, to link the operative maintenance planning on the object level with a strategic approach based on a long-term consideration within the framework of life cycle cost analyses. 

This should enable decision-makers to identify the current and future maintenance needs as well as to identify the short-, medium- and long-term consequences of different maintenance strategies and budget provisions. 

Accessible here.

The present research project was proposed to answer the still open questions about the specific area of application of these  reinforcements and the effects on the interlayer bonding between wearing and base courses and between base course and road base layer. 

In a first phase of the work, the materials and structures to be investigated were defined. The selection was carried out based on interlayer bonding test results according to Leutner. In addition, the experimental setups were defined in collaboration with the
responsible persons of ASTRA and cantons. In a second phase, laboratory experiments on down-scaled pavement models were carried out using the Model Mobile Load Simulator (MMLS3). Finally, in the last phase, ad-hoc pavements were constructed and loaded with the traffic Mobile Load Simulator (MLS10). In addition, laboratory tests were carried out on cored specimens taken from the laboratory setups and in situ test sections. Further, numerical simulations were performed using the finite element method to model the effect of the position of the reinforcement in a pavement structure.

Accessible here.

One of the most important elements in the planning of maintenance interventions, and, therefore, in road structures management systems, is ability to estimate the costs of maintenance interventions. These costs are normally developed using element level and
structure level unit costs. 

In order to estimate these costs, unit costs need to be determined from the actual costs of completed interventions. This, however, is difficult as the costs of such interventions are reported per activity performed, e.g. pouring the concrete, and not per element. This is
because construction companies perform activities and are relatively ambivalent to the number of elements upon which they work. The costs using in the planning of maintenance interventions, however, need to be related directly to the elements or to the structure so
that the service level provided by the elements and structures can be appropriately taken into consideration and the optimal times to intervene can be determined. 

This discrepancy means that the actual costs of the completed interventions have to be converted to costs related to the elements or the structure. This conversion requires a cost model, i.e. a model containing the rules for the conversion from the costs of activities to the costs of elements and structure.

In this research project, such a cost model was developed. The developed cost model enables the conversion of costs associated to activities as defined in the NPK-activity catalogue from CRB into costs associated to elements and structures. The cost model was

implemented into the software referred to as DIXIS, after the work area in which the example bridge was located. The mapping table implemented in the software, which only has to be developed once, was developed using the descriptions in the NPK activity catalogue. The software proportionally distributes the cost of the activities are to the elements of the structure to have a maintenance intervention based on the extent of work to be done per element as documented by the construction company. An advantage of the method used in the software is that the current bidding and billing practices remain the same.

Accessible here.

The term Asset Management originates from the financial world and has also been used since the 1990s in the road and transport sector and is predominantly used in English-speaking countries. Although there is no uniform definition for Asset Management, the majority of users understands it as “a superordinate strategic approach to the optimal longterm use of road infrastructure with optimal use of resources, based on the fundamentals of engineering, economics and business management as well as corporate governance”. 

In this initial project various concepts and definitions of Asset Management were analyzed that have been developed or introduced in other countries in order to formulate a definition of Asset Management that is suitable for the context of Switzerland, including system definition, objectives and decision-making processes. 

The use of the term “Asset Management” was widely discussed because of the possible confusion due to its association with finance, and it was decided to rename this term (for use in Switzerland) “Integral Infrastructure Management”. 

In addition, the gaps in knowledge discovered in the context of the situation analysis were identified as topics for individual projects of a research package to be carried out.

Accessible here.

The paper presents a framework to evaluate key performance indicators (KPIs) in qualitative manner. This framework is the basis for establishment of Quality Control plans for existing bridges. It addresses the dynamics of the damage processes that allows predicting the point in time, from which the performance goals are not met anymore. The KPIs are defined to address not only road users’ but also owner’s or operator’s perspective as well as environmental and societal concerns. To this end the RAMSSHE€P approach gas been modified. The proposed framework is also illustrated on a simple example.

Infrastructure managers works every day according to some kind of Quality Control Plan (QCP) in
order to ensure a desired quality with minimum traffic interruption balancing cost, risks (implicit
or explicit) and performance. These QCPs varies significantly among European countries, which
urges the establishment of a common European guideline. COST TU1406 Working Group 3 has the
aim of providing a detailed explanation of the steps towards the establishment of a QCP. The
approach is generic and evaluates performance values with due attention to: 1) Structure and its
constitutive element incl. background material such as birth certificates, 2) Time-dependent
Performance Indicators (PI) from observations (e.g. spalling) with due reference to the underlying
deterioration processes (e.g. alkali-silica reaction) and 3) Related Key Performance Indicators (KPI)
based on the Dutch risk-driven maintenance concept RAMSSHE€P [1]. This paper outlines QCP’s
for concrete girder and frame bridges.

Due to increasing age and decreasing budgets the need of road work activity will dramatically increase in the next years especially on heavily used sections of the road network.  Therefor decision makers will have more and more problems to solve the conflict between road user requirements and maintenance needs.  Besides new planning strategies long-term performing materials for repair and rehabilitation interventions in pavement management promise to show one way out of this dilemma.  Supplier and manufacturer of asphalt reinforcement interlayers are commending their products for repair and rehabilitation interventions to improve asphalt performance.  At the moment decision makers lack long-term experience to proof these assumptions independently.  The presented research project intents to close this gap for defined asphalt pavements with reinforcement interlayers.  It includes short term and long term analysis of pavement in the field and laboratory.  The results show the influence of reinforcement on cracking, stiffness and bearing capacity of pavement.  Additionally, criteria for an application of test methods for new asphalt reinforcement products will be developed.  This will enable decision makers in pavement management to evaluate independently the use of asphalt reinforcement products and estimate consequences for long-term pavement performance of these pavement repair and rehabilitation intervention types.

On high volume highway networks decision makers need to plan maintenance interventions considering their impact on traffic flow and related user costs. In urban agglomerations this impact is not limited to the highway sections but can propagate into the surrounding lower grade roads. Both classical pavement and bridge management fall short of addressing this problem since they, if at all, consider user costs related to maintenance intervention on a single object e.g. bridge, pavement section, tunnel, etc. However, classical pavement and bridge management provide long-term costs of maintenance interventions that can be used to find an optimum maintenance corridor that minimizes the sum of agency and user costs. This paper proposes a maintenance corridor optimization model that uses the results of pavement and bridge management systems. The basis of the model is a graph that models accurately the physical network structure and is augmented to accommodate all feasible object maintenance interventions and related traffic regimes. The optimization comes down to minimum cost problem in the augmented graph subject to costs corridor length constraints. The cost model considers agency costs for intervention and traffic control costs as well as the user costs due to additional travel time, accidents and vehicle operation. In addition, the augmented graph allows intervention scheduling dividing the duration of corridor interventions in four periods. In example the use of the work zone optimization model is provided. The results show consequences of different intervention strategies for objects within a corridor to agency and road user costs.
Road condition data are often fine-grained as they relate to relatively small patches of pavement surface i.e. assessment units. This data cannot be directly used for planning maintenance interventions, which are generally coarse-grained and stretch over much large pavement surfaces. In order to plan feasible maintenance interventions, it is necessary, based on fine-grained condition data to determine larger road sections, which are to be treated homogenously i.e. planning units. The existing approaches are mostly based on averaging condition data to aggregate small assessment units into larger sections with uniform attributes, derived by averaging procedure. For pavement management the results of these averaging methods are often not plausible in particular with regard to the extent and type of possible maintenance interventions. This paper presents a novel technique for road sectioning applicable for planning of maintenance interventions. It is focused on long-term economic efficiency and different constrains of intervention types, such as minimal length of intervention types, feasible application range and threshold values, determined from existing road condition data and pavement deterioration. This technique includes the optimization problem of minimizing long-term costs for all possible planning units in the considered road network. This optimization can, besides road agency costs include user and society costs if they are related directly to planning units. Mathematically it is formulated as an Integer Linear Problem and solved by an original heuristic algorithm, presented in this paper. The practical application of the developed technique and the impact of different constraints is shown in an illustrative example.
The oncoming natural hazards, especially floods, represent a serious threat to users of transportation infrastructure and societies in general. Thus, it is a fundamental responsibility of civil engineers to ensure adequate adaptation of infrastructure in the face of future extreme weather events. Here, one of the most challenging tasks is the assessment of a bridge performance over time, since bridges are particularly vulnerable to hazards both in terms of exposure and resistance. By rule, a validation or an update of bridge management practices only take place after an extreme event occurrence, which is not adequate approach for ageing infrastructure. The state-of-the-art Bridge Management Systems still do not comprehensively account for impacts of sudden events. Currently implemented qualitative risk-based approaches impose constraints in a decision making process and fail to provide factual risk of a bridge failure due to a flooding hazard. There is a demand for a methodology for quantitative assessment of a bridge performance on a network level, which will in turn lead to adequate performance measures with respect to flooding events. The accent is on a simplified, yet sufficiently accurate procedure, based on a modest data set, eligible for implementation on various bridge types and network topologies. As a convenient tool for the assessment, the measure of vulnerability is suggested here as a top level bridge performance indicator. It is based on the two values – the conditional probability of a bridge failure due to a flooding event of a certain magnitude, and the related total consequences. The primary culprit for failures inflicted in floods is the local scour at bridge substructures. Here, the estimation of the conditional probability of a bridge failure is a multidisciplinary problem where the combined resistance of the supporting soil at substructures and the bridge is accounted. The evaluation of the direct consequences of a failure is straightforward, but the calculation of indirect i.e. traffic related consequences requires a traffic simulation model based on the current transport supply in a road network. Prior to conducting the first-time vulnerability assessment on a network level, it is necessary to synthesize available information from databases & documentation and systematically collect the missing data from bridge sites. The measure of vulnerability will indicate which bridges need specific attention and should be investigated in more detail. The challenge is in setting the adequate vulnerability thresholds that trigger mitigation and maintenance activities. Here the influence of a planned activity or an information update, on the assessment results must be taken into consideration. Once integrated in the future Bridge Management Systems, the vulnerability assessments will enable timely scheduling of risk mitigation actions and making unambiguous decisions for resources allocation. The insight on vulnerabilities in a network would aid in emergency planning as well, since timely warnings could be issued in regions where intensive flooding is expected.
KUBA is a comprehensive road structure management system (RSMS), developed for the Swiss Federal Roads Office (FEDRO). KUBA relies heavily on the inspection data to obtain deterioration functions and on data on performed maintenance interventions to obtain unit cost data. The collection of inspection data is well established and proceeds quite smoothly. The collection of maintenance data poses a severe problem due to organizational and technical problems. In this experience report the data collection for KUBA is described with the focus on the measures to ensure data quality and work efficiency. In the first part, the lack of data in “bad” condition states is discussed, which proves to be a serious obstacle to obtain meaningful deterioration functions. The paper describes the consequences if the raw data is used to obtain deterioration functions. In the second part, the agency organization is described and the organizational issues are addressed that hinder the meaningful exploitation of data on maintenance interventions. The split in responsibilities between the asset management and construction management seems to pose an obstacle to obtain data that can be used for planning purposes. The possible organizational measures are described – some of them are implemented – that can improve the work flow and consequently facilitate the accessibility of necessary information. In the third part, a method for the monitoring of workload related to inspections and the analysis of the monitoring results are presented. The influence of different properties was analyzed in order to determine the ones that govern the inspection workload.

There is a broad consensus that the benefits of road infrastructure for the society cannot be over-estimated. Maintaining these benefits on the long run in economically efficient, environmentally friendly and socially reconcilable manner is the fundamental task of road authorities. This means that they are bound to provide de-sired service quality to road users, or in more concrete terms fast, safe, comfortable and affordable travel. From purely users’ perspective only the highest service quality is good enough. However, besides the technical limits to the service quality, there are also economic constraints. The technically achievable service quality may not be the affordable one. The conflict between the users’ and societal desires one side and available financial resources on the other, is supposed to be resolved in a political process. This occurs more often than not in pursue for short-term political gains, resulting in considerable funding volatility. Professional societies can smoothen this volatility by setting performance goals that are both affordable and acceptable to the road users. One would therefore expect that they differ from country to country mirroring their economic strength. In most cases there are defined as stiff limits on the performance indicators. The actual service quality – measured by performance indicators – is considered insufficient if performance indicators do not meet performance goals. These performance indicators can be quantitative such as posted cruising speed, accident rate, vehicle operational costs, availability etc. or qualitative such as condition state.

With regard to bridges, these performance indicators depend on observations obtained by visual examination, non-destructive testing or a permanent monitoring systems. Typically, they are related to bridge components e.g. girders, abutments, cross beams and indicate existing or expected bridge dysfunctionality that result in one or more insufficient performance indicators. The challenge is to define procedures that connect observations, detected visually or using other examination methods with performance indicators. These procedures should cover the whole range of assessment activities from regular visual inspection to in depth investigations. The confidence in obtained results should however mirror the investigation effort. Furthermore, triggering criteria for more elaborate and expensive examination methods should be provided.

The paper suggests a framework that may overcome the above mentioned challenge and derive the performance indicators from observations and other available data such as construction year, structure type, span, geological conditions, etc.

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