Road Administration Research Articles

Co-production of public policy to mitigate animal-vehicle collisions on roads in Brazil

ABSTRACT Roads worldwide contribute to biodiversity loss through animal-vehicle collisions, impacting ecological connectivity and ecosystem functioning. Despite existing environmental impact assessment procedures for road operations, the absence of specific rules for planning mitigation measures raises major concerns about the effectiveness of current practices. To address these challenges, a two-year co-production process was initiated to develop a novel regulation for mitigating animal-vehicle collisions in Brazil. This collaborative effort involved over 90 stakeholders, including the state environmental agency, road administrators, researchers, and legal representatives. The process, characterized by its context-based, pluralistic, goal-oriented, and interactive nature, resulted in a framework for developing and implementing mitigation plans. The process included detailing context definition, reviewing existing public policies, identifying participants, creating an official working group, conducting monthly virtual meetings, and a public consultation. Despite challenges in participant engagement and decision-making in the absence of evidence, the co-production process demonstrated the importance of inclusivity, a formalized working group, and a core team in structuring discussions. Recommendations for future practice include participative processes, transparent public consultation, and a realistic schedule for implementing mitigation measures. We emphasize the importance of credibility, relevance, legitimacy, and iterativity in the co-production process, highlighting its increased potential to inform evidence-based decision-making.

Assessing the Impact of Reduced Vehicle Volume and Increased Speed on Air Quality in Qom City Using AERMOD

Urbanization and traffic congestion significantly worsen air pollution, leading to serious health risks. This study examines a scenario involving a 9% reduction in vehicle volume and a 4% increase in vehicle speed on the main roads of Area 6 in Qom City (District 2). The focus is on evaluating the impact of these changes on air quality, specifically concerning pollutants carbon monoxide (CO), nitrogen oxides (NOx), and particulate matter (PM2.5), utilizing AERMOD software for modeling. Data were collected through various methods, including statistical analysis, field sampling within the area, archived records from the Road Administration and the Road Transport Organization of Iran, GPS data for Qom City, and local meteorological information. The results reveal that implementing the proposed traffic management scenario can lead to significant reductions in pollutant levels: CO levels could decrease by approximately 20.19%, NOx by 7.29%, and PM2.5 by 9.00%. These findings underscore the potential of strategic adjustments in traffic patterns to improve urban air quality. The insights gained from this study are valuable for policymakers aiming to tackle environmental challenges in rapidly urbanizing regions, highlighting the importance of effective traffic management in promoting healthier urban environments. Ultimately, enhancing air quality through targeted traffic interventions can improve public health outcomes and contribute to a more sustainable urban future.

Assessment and management of existing bridges following the innovative Italian guidelines: A pilot study

In 2022, the Italian Government introduced innovative regulations for evaluating and monitoring existing bridges and viaducts, tackling issues related to risk classification, safety assessment, and monitoring. These regulations employ a multilevel approach for bridge inspections, safety assessments and monitoring procedures. The guidelines have garnered international acclaim for their forward-thinking approach. This paper proposes a comprehensive study concerning the whole process proposed in the new Italian guidelines, using a case study constituted by two prestressed RC box-girder half-joint span bridges that exhibited signs of ageing several years ago. The paper in deeply addresses all phases of the existing bridge safety assessment and management discussed in the guidelines from both a scientific and practical standpoint, in collaboration with the national agency for road administration. It starts from visual inspections, conducted for supporting the bridge safety assessments, and concludes with the experimental testing and structural monitoring of bridges. For the first time in the scientific literature, this work provides a pilot study for a proper and aware use of the innovative Italian guidelines, with focus on prestressed concrete bridges. The paper objective is to present advanced procedures for the classification, evaluation, and management of existing bridges to be adopted by road administrator, which may inspire international readers in upgrading codes of their own countries.

THIN CONCRETE OVERLAYS ON OLD ASPHALT ROADS

"Thin Concrete on Asphalt" is a joint-venture project involving the Stockholm Regional Road Administration, Cementa AB (a Swedish cement producer) and the Swedish Cement and Concrete Research Institute (CBI). The project aims at building a test road in the Stockholm area in 1993. This presentation is a summary of a state-of-the-art report developed for the project.

Providing a Robust Optimization Model for the Preventive Maintenance of Asphalt Road Pavements

Road maintenance and transportation administration must plan the maintenance of the road asphalt network and manage the annual budget. In addition, the primary purpose of doing preventive maintenance (PM) activities is to improve the condition of the asphalt. The purpose of this paper is to present a model for pavement maintenance planning. The goal of this research is to reduce the total International Roughness Index of asphalt roads by taking into account the weight of each part of the road. This research focuses on pavement conditions, addressing the surface layer and its direct impacts on ride quality and durability. A budget has also been set aside annually for road asphalt maintenance. Additionally, sensitivity analysis is performed on the presented model to observe the impact of parameters on the objective function. As a result of changing the budget values, it is established that the objective function improves when that parameter is increased, since it is more flexible. Additionally, the cost of the PM activity was changed, but the objective function remained unchanged. By providing a proper schedule for PM activities and accurate budget management, this model can assist in improving the condition of asphalt. Moreover, this model has been implemented for the roads of North Khorasan province in Iran and its results have been presented. Road maintenance and transportation administrations could use this model to manage their budgets and carry out their PM activities.

Top causes of road traffic accidents in Romania

Abstract Road accidents worldwide impose a significant burden on national budgets, particularly affecting the least developed countries. According to the latest WHO “Global Status Report on Road Safety 2023,” road fatalities are the leading cause of death among young people aged 5 to 29. Among the European Union countries, Romania has the highest mortality rate. Between 2011 and 2021, approximately 2.8% to 1.1% of Romania’s GDP represented the social costs caused by road accidents. Statistical analysis of serious road accidents in Romania during this period reveals five main causes responsible for at least 50% of the total deaths recorded on the national public road network. The most significant cause is “speed not adapted to road conditions,” accounting for approximately 19% of the total. A road accident occurs due to the action or interaction of three determining factors: human, vehicle, and road (road environment). In most cases, the blame for road accidents is attributed to human error or behaviour. This conclusion is often influenced by data collection methods that do not consider all the influences of road infrastructure on the accident’s dynamics. A closer analysis shows that road infrastructure deficiencies often influence or cause road accidents, highlighting the importance of continuous evaluation and improvement of infrastructure to reduce accident risk. The implementation of Directive 2008/96/EC on road infrastructure safety management has prompted authorities to pay particular attention to infrastructure deficiencies in fatal accidents. During 2018-2021, following road safety inspections, auditors provided police and road administrators with detailed reports on deficiencies that caused or favored fatal accidents. Processing and analysing these reports can form the basis for developing a statistical model that provides a unified approach to road infrastructure deficiencies. This model can set up best practices for road safety, contributing to the uniform treatment of infrastructure problems found by auditors. With the transposition of Directive (EU) 2019/1936, which amends Directive 2008/96/EC, through Romanian Government Ordinance no. 3/2022, an innovative approach to managing road infrastructure deficiencies has been introduced. At the EU level, emphasis is placed on finding main road sections with low safety levels. Specific inspections are directed towards road sections with multiple risks, and remedial measures will focus on cost-effective solutions to enhance safety. Continuous evaluation and improvement of road infrastructure are crucial for reducing accident risk. By addressing deficiencies contributing to serious accidents, authorities can create safer road environments. This proactive approach involves detailed inspections and thorough data analysis to find and rectify potential hazards. The goal is to set up a system that not only responds to accidents but also prevents them by mitigating infrastructure risks. In conclusion, road safety management needs a multi-faceted approach that integrates human, vehicle, and road factors. By implementing directives and conducting rigorous inspections, authorities can significantly reduce road accidents. The development of a statistical model from inspection data will systematically address deficiencies, leading to safer roads and reduced fatalities, highlighting road safety as a public health issue.

Deciphering Motorists’ Perceptions of Scenic Road Visual Landscapes: Integrating Binocular Simulation and Image Segmentation

Traditional scenic road visual landscape assessment methods struggle to quantify drivers’ subjective visual perceptions. This study aims to develop a new method to decipher Scenic Road Visual Landscape Evaluation (SRVLE) of motorists’ visual field, reconciling the longstanding subjectivity–objectivity dichotomy in landscape quality research. By adopting binocular visual simulation and image segmentation, this paper conceptualizes a novel “non-scale semantic differential approach” to quantify landscape qualities across the dimensions of naturalness–artificiality (NA), diversity–coherence (DC), and openness–deepness (OD), constructing a three-dimensional visual landscape quality evaluation system. Taking the Nujiang Beautiful Road in Yunnan as a case study, the results show the following: (1) The three indicators reveal the scenic road’s distinctive visual landscape characteristics, marked by high naturalness, coherence, and relative openness. (2) SRVLE is found to vary between the two driving directions and different sections. (3) The three-dimensional evaluation cube intuitively displays the comprehensive characteristics of landscape quality, providing a basis for scenic road planning. This method offers a new approach to resolving the subjective–objective divide in SRVLE and can assist road administrations in enhancing policy planning, construction, and management, thereby promoting the high-quality development of scenic roads.

Automatic detection of loose gravel condition using acoustic observations

Maintaining gravel roads is crucial, as loose gravel poses safety risks and increases vehicle costs. Current methods used by the Swedish road administration, Trafikverket, are subjective and time-consuming. Road agencies need a cost-effective, efficient, and unbiased approach to assess gravel road conditions. Studies show human ratings are error-prone and inconsistent. This study aims to develop an automatic method for estimating loose gravel using audio recordings from inside a vehicle, capturing the sound of gravel hitting the car's bottom. These recordings were classified into four classes based on Trafikverket regulations. Sound features were extracted and analysed using supervised machine-learning methods. The Multilayer Perceptron (MLP) achieved the highest classification accuracy of 0.96, with an F1 score, recall, and precision of 0.97. Results indicate that audio data can effectively classify loose gravel conditions.

Integration of ten years of daily weather, traffic, and air pollution data from Norway’s six largest cities

This study integrates ten years of daily weather, traffic, and air pollution data across the six largest Norwegian cities, utilizing data from the Norwegian Public Roads Administration, the Norwegian Institute of Air Research, and the Norwegian Meteorological Institute. The compilation of this dataset involved detailed selection and verification of monitoring stations to ensure consistency and accuracy. Initial data collection focused on the top ten most populous cities in Norway, with the subsequent examination of traffic and air pollution monitoring sites. Weather variables were then matched to the selected sites, resulting in a comprehensive dataset from 2009 to 2018. The resulting dataset encompasses extensive information, including harmful pollutants such as Nitric oxide (NO), Nitrogen dioxide (NO2), Nitrogen oxides (NOx), Particulate Matter less than 2.5 micrometers in diameter (PM2.5), and Particulate Matter less than 10 micrometers in diameter (PM10). The dataset’s potential for further analysis and its utility in informing policy decisions underscore its significance. This integrated dataset is a valuable resource for researchers and policymakers alike, facilitating comprehensive studies on the intersection of weather, traffic, and air pollution in urban environments.

APPLICATION OF PERMEABLE ASPHALT PAVEMENT CONSTRUCTION IN TRAFFIC AREAS

Lithuania’s total road network consists of more than 84000 km of roads, of which more than 21000 km are national roads. Roads of national importance are managed by the Lithuanian Road Administration. The remaining roads are classified as local roads managed by local governments. Road installation and maintenance often lead to the problem of surface water drainage and accumulation on the road surface. The aim of this study is to identify and propose the most appropriate permeable asphalt pavement construction to solve this problem, taking into account the purpose of the application and the class of pavement structure. The scope of the study identifies three recommended permeable asphalt pavement designs for the installation of DK 0.1-DK 1 pavement structures in ancillary streets, parking and recreation areas where light vehicle traffic with occasional heavy vehicle traffic. It has also been found that in areas of high traffic intensity, it is appropriate to use an alternative to permeable pavements – a permeable pavement design for the shoulder, where the roadway structure is impermeable to water and the shoulders are permeable to water (a permeable pavement structure is installed). The recommended permeable asphalt pavement structures, when properly selected, reduce the risk of flooding on the roadway.

Koncepcja ujednolicenia wzajemnie niekompatybilnych modeli informacyjnych oraz danych przechowywanych w relacyjnych bazach danych zarządców dróg

Road Administrations (RAs) implement Building Information Modelling (BIM) through pilot projects developed for new or reconstructed structures. Each model is processed with respect to BIM standards and practices valid at the time of its creation. Consequently, models are incompatible and cannot be interconnected to create a combined model of the managed network or even its selected parts. Existing structures are often not included in the BIM effort until some major repair is planned. In addition, RAs usually store data on fixed and variable parameters of structures in relational databases. This results in a situation in which a relatively small number of structures are included in mutually incompatible models and data regarding the majority of structures is contained in relational databases. It creates a heterogeneous data environment for RAs. The goals of the paper are as follows: to analyse the described problem, to propose a method of model unification models, a method of creation of simplified compatible information models using data on existing structures stored in relational databases and a method of storing data at the level of the managed network, to support RA asset management systems which can be treated as a dynamic part of BIM.

Liability of Perpetrators of Road Accidents and their Insurers for Damages Related to the Post-Accident Clean-Up. Remarks on the Supreme Court's Resolution of 20 January 2022, III CZP 9/22

The article addresses the issue of the liability of the motor vehicle owner (the perpetrator of a road accident) and the third-party motor liability insurer for damages related to the costs of post-accident road cleaning. It is a polemic with the concept of a broad understanding of the scope of liability of the perpetrator and the insurer, presented by the Supreme Court and some legal doctrine, because it contradicts, among others, the statutory catalogue of obligations imposed on (particularly public) road administrators. Moreover, arguments have been advanced for a different interpretation of the terms "property damage" and "destruction" as well as the unjustified enrichment of the road administrator seeking cost refund from the perpetrator or the third-party liability insurer.

Systematic review, evaluation and comparison of different approaches for the implementation of road network safety analysis

IntroductionRoad safety is still a major issue all around the world. The capability to analyze the road network and identify high risk sections is crucial in road safety management. Therefore, it is essential for road administrations, practitioners, and researcher to have a clear and practical framework of the available road network safety analysis procedures. The aim of this study is to provide such a framework by carrying out an exhaustive analysis of the main procedures available all around the world. MethodThe proposed literature review has started considering a web search on Web of Science (WoS). Then, a systematic review of each publication has been carried out using the Bibliometrix software, to identify the main characteristics of the publications within the specific topic. Then, the most relevant and widespread safety analysis procedures have been considered and the following aspects have been analyzed: the type of approach (crash analysis, crash prediction models procedures, based on road safety inspections, etc.), which and how many data are required (crashes, traffic, visual inspections, geometrical data, etc.), which is the effectiveness of the procedure, and which are the segmentation criteria used (fixed length, variable length based on geometry, traffic, etc.). ResultsTen different procedures for road network safety analysis have been considered for detailed analysis. The research findings highlight that each procedure has its own pros and cons. ConclusionsThe choice of the best procedure to use is highly related to the characteristics of the road network that need to be analyzed, to the availability of data, and to the main elements the Road Authorities (RA) wants to give priority to. Practical applicationsThis collection and review of different procedures will be of great interest for RAs, practitioners, and researchers in the process of selecting the most useful procedure to use to carry out a road network safety analysis.

Drivers’ Steering Behavior in Curve by Means of New Indicators

The design of road geometry is based on a rather elementary assumption that the user strictly follows the lane axis. Based on this hypothesis, the ideal trend of some factors related to the driver’s performance, such as steering angle and speed, can be derived to optimize the most appropriate design choices. In practice, driving behavior differs from the assumed one and produces trends in these variables, which are very different from the ideal functions. The purpose of this research is therefore to propose synthetic performance indicators useful for highlighting the real characteristics of users’ driving behavior during road travel. Toward this aim, some driving experiments along four different curves in a simulated environment were studied in order to evidence possible criticisms. The proposed indicators showed a remarkable ability to represent and synthesize even very complex performance function trends. The proposed performance indicators can have multiple uses, such as, for example, in statistical analyses—which are generally carried out at a later stage—or constitute sufficient information to guide the decisions of infrastructure managers. In the long term, in a “smart road” perspective, they can be used by road administrators for information exchange among users (with each other and with the infrastructure) to improve road operation and safety.

Asset management, condition monitoring and Digital Twins: damage detection and virtual inspection on a reinforced concrete bridge

In April 2021 Stavå bridge, a main bridge on E6 in Norway, was abruptly closed for traffic. A structural defect had seriously compromised the bridge’s structural integrity. The Norwegian Public Roads Administration (NPRA) closed it, made a temporary solution and reopened with severe traffic restrictions. The incident was alerted through what constitutes the bridge’s Digital Twin processing data from Internet of Things sensors. The solution was crucial in online and offline diagnostics, the case demonstrating the value of technologies to tackle emerging dangerous situations as well as acting preventively. A critical and rapidly developing damage was detected in time to stop the development, but not in time to avoid the incident altogether. The paper puts risk in a broader perspective for an organization responsible for highway infrastructure. It positions online monitoring and Digital Twins in the context of Risk- and Condition-Based Maintenance. The situation that arose at Stavå bridge, and how it was detected, analysed, and diagnosed during virtual inspection, is described. The case demonstrates how combining physics-based methods with Machine Learning can facilitate damage detection and diagnostics. A summary of lessons learnt, both from technical and organisational perspectives, as well as plans of future work, is presented.

GoogleNet transfer learning with improved gorilla optimized kernel extreme learning machine for accurate detection of asphalt pavement cracks

Asphalt cracks are the initial indication and major pavement structural distress in the field of civil engineering because it might potentially intimidate road traffic and highway safety. Managing and maintaining pavement structures are the two crucial issues faced eventually by road administrators. It is essential to take immediate action regarding pavement structural damages to prevent its severity. In recent times, there established numerous deep learning-based image processing methods to detect pavement cracks, but due to the presence of interference factors such as noises and road markings in the images, those methods failed to provide high accuracy and efficiency. Therefore, with the aim to yield high accuracy of crack detection, this article designs a novel asphalt pavement crack identification system “GoogleNet transfer learning with improved gorilla optimized kernel extreme learning machine” (GNet TL with IGT-KELM). The road crack images used for perusal are acquired from NHA12D dataset, in which it consists of 40 asphalt pavement images with two different viewpoints. For the purpose of data balancing, some non-crack images are gathered by field survey. The images with large noise distortions and unwanted background information influence crack detection performance so that the preprocessing steps are executed before applying it to the prediction system. The most significant crack and non-crack features from the images are extracted using GNet TL model. With the extracted features, the KELM is well-trained to detect cracks and non-cracks separately. To increase crack detection performance of the classifier, an improved gorilla troop optimizer is introduced to optimize the KELM parameters. The experimental finding reveals that the proposed detection mechanism achieves crack recognition accuracy of about 98.93%, which is considerably greater than compared baseline approaches.

Portfolio management: the case of the Norwegian Public Roads Administration

The interest in portfolio management has grown in time, especially due to the economical restrictions of the recent years. Selecting the best portfolio of projects and manage it to reach the strategic goals is therefore crucial, but the criteria to consider in the evaluation are getting more complex. The Norwegian Public Roads Administration (NPRA) is one of the actors that operate in complex environment, dealing with different portfolios and different types of projects. In the management of these portfolios, the new strategic initiative is to bring sustainability among the set of criteria to be evaluated. This is creating a challenge where the importance in selecting the projects to form the portfolio and manage the existing portfolios actively has grown with the difficulty of handling inhomogeneous criteria, also difficult to measure. The structure of NPRA’s portfolios has been investigated, conducting semi-structured interviews and analyzing strategic and organizational NPRA’s documents and tools used for portfolio management. The paper describes the different portfolios for the NPRA and focuses on the actual system for the selection and management of the portfolio of projects, for chosen specific portfolios. For each of them, the strengths and weaknesses for the project portfolio selection and management in NPRA are discussed, with the focus on sustainability as evaluation criteria. Literature and portfolio practice is used to evaluate criticalities for the public agency and to suggest further work to develop a coherent and effective portfolio management focused on sustainability.

Traffic modelling of existing infrastructures upgrading from the promoter's point of view: some technical, financial and environmental/climate risk challenges

Road projects comprising upgrading existing infrastructures have, as it is known, specificities in comparison with greenfield projects. The differences may be relevant in many aspects, being one of them the traffic modelling. In developed and built metropolitan areas these differences may be more challenging than in other scenarios. In this paper, challenges which may arise when modelling existing infrastructures in developed metropolitan areas will be addressed from the standpoint of the promoter, which in this case is typically the Road Administration. This approach may permit to cover almost all the issues which might appear when undertaking these projects. Other agents –private ones, for instance-, however, might not need to tackle all of them. In the paper, firstly, features of metropolitan areas relevant to traffic modelling will be exposed. Secondly, several challenges related to traffic modelling are presented. Thirdly, the state-of-the-art regarding the challenges is outlined. In the fourth place, in order to illustrate the paper contents, a real case in which the three authors have participated, some associated problems and solutions will be discussed. Next it is addressed how traffic modelling faces the challenges in the mentioned real case, and related modelling findings are set forth. Lastly conclusions are drawn.

Comfort evaluation of new bicycle paths with a laser profilometer: 15 years of experience in Belgium

Longitudinal evenness of a road or bicycle lane surface is important for users’ comfort. For roads, indicators for evenness, their relation to users’ comfort in cars or trucks, and acceptance levels for existing or newly constructed roads exist for decades. In Belgium, four indicators called “Evenness Coefficients” (EC) are in use. Considering the surface as a wave, each EC evaluates a different range of wavelengths. EC0.5, for the shortest wavelengths, was introduced in 2013 by the Flemish National Road Administration (Fl-NRA). In 2013/2014 two measurement devices dedicated to longitudinal evenness evaluation of cycle infrastructure were put in service. Fl-NRA set requirements for roughness on new bicycle lanes expressed in EC0.5 and EC2.5 and uses a combined indicator for the evaluation of the global condition of their bicycle lane network in two-year intervals. The Belgian Road Research Centre (BRRC) helped investigating the potential causes in cases where the requirements were not attained. This contribution reports on more than a decade of experiences with dedicated measurement devices, on factors influencing users’ comfort of bicycle infrastructure, and on the “comfort score” obtained from a less costly “measuring bike”. The article concludes addressing perspectives on European standardisation actions for roughness measurements on bicycle infrastructure.

Behavior of a Rock Mass in Uplift Field Tests of Rock Anchors

AbstractRock anchors are high-capacity reinforcement measures used to stabilize large-scale infrastructures. According to the literature, they can fail in one of the four ways: (1) steel tensile failure; (2) tendon–grout interface failure; (3) grout–rock interface failure; and (4) rock mass uplift failure. Rock mass uplift field tests were performed in a limestone quarry to test this fourth failure mode. The tests were designed to induce rock mass failure around rock anchors. The ground surface heaved asymmetrically around the anchors and the pre-existing joints in the rock mass tended to open first. The seismic activity in the rock mass was greatest close to the anchor, decreasing with distance. The failure crater in the rock followed the joint sets in the rock mass, and the shape was partly controlled by the pre-existing joints. The apex angle of the failures was measured to be between 125 and 140$$^{\circ }$$ ∘ . The horizontal stress in the rock mass increased when the anchor was pulled, indicating load arching around the anchor. The observed failure was a combination of rock mass uplift and grout–rock bond failure. The measured anchor capacity was much higher than the estimated rock mass capacity using the recommended design methods of the Norwegian Public Roads Administration.