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Road maintenance management aims to satisfy quality, comfort, and safety requirements for the various assets. To overcome delays and barriers in the widespread adoption of road management systems, the Building Information Modeling (BIM) approach may offer significant advantages as a convenient alternative for road maintenance management. Although existing BIM platforms are not fully equipped for this purpose, defining original modules and scripts can extend their capabilities, allowing for the handling of road condition information and maintenance management. In this context, this paper presents an operative framework designed to leverage BIM benefits for road maintenance management, particularly in terms of virtual inspection, asset condition assessment, and maintenance design. To achieve this, specific original and customized smart objects and routines were coded in I-BIM platforms, tailored to different scales, aims, and detail levels. These smart objects incorporate user-defined extended attributes related to pavement condition and maintenance planning (such as roughness, rutting, structural capacity). In particular, the authors have developed original virtual smart objects in different platforms, serving as "containers" for the survey information. These objects are adapted to display quality levels of the pavement segments in a realistic and user-friendly environment. Additionally, original routines were coded to automatically import survey data from external datasets and associate this information with the appropriate objects. This customized and extended approach, not available in commercial platforms, can effectively support maintenance operators. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The road alignment design relies on the knowledge of vehicle dynamics variables. However, it assumes that drivers faithfully follow the lane axis on straights and curves. Deviating from this assumption leads to unexpected outcomes and can significantly impact users' safety. In this context, vehicle speed and longitudinal acceleration play a crucial role as key references in the international standards. They provide insights into critical driving aspects; therefore, it is essential to thoroughly analyze their real trends. Broad data collection campaigns should derive synthetic indicators in order to highlight eventual significant deviations between the ideal and real dynamics. To achieve this objective, the authors propose some indexes deduced during an experimental study with a Sim-Easy driving simulator, by AVSimulation. Importantly, these indicators can be freely applied in real driving scenarios without limitations. These indexes were tested on four different horizontal curves and proved effective in identifying relevant characteristics related to longitudinal acceleration and speed. Looking ahead, by analyzing similar data for numerous driving contexts on real roads, infrastructure managers could use this methodology to identify those sections with increased vulnerability for users' safety. Moreover, the collected data from sensors, processed using these indicators, can be filtered and transmitted to users (via ADAS tools) while driving on a specific road to provide timely warnings about potential difficulties. The indicators control the physical variable (acceleration or speed) on a certain geometric element with reference to what is prescribed by the standard. For example, the acceleration indicators are normalized with respect to a threshold value while for speed indexes, the result depends on the difference between the end control points of the geometrical element. In both cases, international regulations report prescribed or recommended reference values, so the analyst is immediately aware of any critical issues in the maneuver. [ABSTRACT FROM AUTHOR]

The presence of numerous sensors inside modern vehicles leads to the development of new driving assistance tools, the real usefulness of which depends, however, on the environmental context. This study proposes a procedure capable of quantifying the effectiveness of some warnings produced by an On-Board Unit (OBU) inside the vehicle in a specific environmental context, even if limited only to the considered road. The experimentation was carried out by means of a driving simulator with a sample of young users with sufficiently homogeneous characteristics. The collected data were treated by ANOVA to highlight any differentiation between a traditional driving condition, without any instrumental support, and another involving the OBU was present. The results showed that only in relation to the investigated road, the OBU ensured the advantage of sending information of interest to the driver without invalidating their performance in terms of longitudinal and transverse acceleration, speeding, and steering angle. This research could be of interest to the infrastructure managers who, in case of inappropriate use of a road, could intensify active and passive safety devices for users' safety. [ABSTRACT FROM AUTHOR]

The possibility of using some warnings inside modern vehicles should be an aid to driving activity. However, the information transferred to users is not always received in the expected way due to the variability and complexity of the road environment. This study, therefore, aims to identify a procedure that allows to ascertain whether drivers receive the data in an appropriate way even during particular maneuvers, such as passing cyclists on a winding road or, on the contrary, if they represent an unnecessary overload. To answer this question, an experimentation in a simulated environment was set up for recording the drivers' visual behavior in both the presence and absence of a driving aid device (On-Board Unit, OBU). The results show that, in some situations, the information provided by the OBU helps to maintain a more virtuous driving behavior but, in the most complex ones, drivers acquire information from a smaller number of sources, excluding the aid devices inside the cockpit. This procedure is useful for Advanced Driver Assistance Systems (ADAS) designers to refine these instruments, but also for road managers who can improve safety by inserting appropriate signs or speed limits. [ABSTRACT FROM AUTHOR]

Traffic loads and environmental factors cause various forms of distress on road pavements (cracks, depressions, potholes, ruts, etc.). Depressions and ruts produce localized variations of longitudinal and cross slopes, which are very hazardous for drivers, especially during rain. In such conditions, these defects alter the surface water path, creating abnormal water accumulations and significant water film depths to induce aquaplaning risk. In current practice, in preliminary analysis phases and at the network scale, the control of road surfaces is carried out with expeditious techniques and with synthetic indicators, e.g., pavement condition index (PCI), through which a quality judgment related to the detected distresses on the pavement surface, is given. In truth, the detection of specific defects (ruts and depressions) should also include further analyses to evaluate the hydraulic efficiency of the carriageway related to their severity. Therefore, in this paper, a synthetic indicator called Hydraulic Condition Index (HCI) is proposed for evaluating the hydraulic quality of road pavement surfaces. This index is related to the hydrologic conditions of the site, the pavement characteristics, and the defects that can alter the flow of water on the carriageway, determining and increasing the risk of aquaplaning. The methodological framework is discussed by means of some numerical applications developed for different road typologies according to their functional classification. The final aim is to provide road agencies with another solution to evaluate road quality and ensure safer roads for users. The methodological framework for evaluating the HCI may be adopted by the road agencies for the network-scale priority ranking of road segments maintenance needs also involving safety traffic conditions. [ABSTRACT FROM AUTHOR]

Summary: Especially in urban contexts, the detection of damages in road infrastructures is crucial for their management and efficiency. This entails complex measurement chains. Several solutions were already developed and applied (e.g., high speed monitoring systems or sensor‐based systems), but the emerging smart city and smart road paradigms call for innovations in these fields. A possible solution could be the development of smart, non‐intrusive, and sustainable sensing systems able to perform continuous monitoring, allowing automatic and timely generation of alarms and proper maintenance strategies from Road Management Systems (RMSs). Consequently, this study aims to demonstrate the feasibility of integrating miniaturized sensing systems with high‐speed monitoring systems, to obtain innovative RMSs. In this regard, a specific web‐based platform, the core of a Smart RMS, properly defined to acquire, correlate, and exploit data from several sources was developed. To this end, high‐performance monitoring systems, an innovative sensing system (i.e., based on miniaturized devices and on feature‐ and signature‐based methods), and Micro‐electromechanical systems (i.e., smartphones accelerometers) were used. A new set of indicators has been set up and partly validated in the pursuit of setting out a new paradigm where Pavement Management Systems are supposed to become urban‐oriented and less expensive. Results show that combining traditional and innovative solutions allows providing a comprehensive overview of both the structural condition and the performance of road infrastructures. This information could be used to exponentially improve the efficiency of current RMSs in forecasting the occurrence of damages and in scheduling more effective and sustainable management interventions. [ABSTRACT FROM AUTHOR]

Summary: Recently, even the road industry has been involved in an evolutionary process, inspired by the novel 'Industry 4.0'. This transition moves the attention towards big‐data and Internet of Things concepts, determining novel data flows and relevant management efforts. In smart roads, modern instrumented vehicles and networks of sensors will provide frequent helpful measures (traffic, weather, condition, accidents, mechanical performance, etc.), with reduced efforts and costs. However, this process is currently at the preliminary phases and several issues raise. Since the management and elaboration of huge amounts of data represent a relevant novel issue, in this study, an original web platform for collection and analysis of road performance data is proposed. This platform can acquire and process several data classes and support maintenance activity planning. This paper focuses on pavement maintenance, to provide a reliable decision support tool for road agencies, alternatively feedable by modern survey equipment and, in future, widespread sensors (when effective smart road sensors are installed on the main highways). The platform has been tested, in a preliminary form, on an existing motorway, considering high‐performance survey systems data, with interesting and positive results. [ABSTRACT FROM AUTHOR]

Cyclists are a vulnerable group of road users, especially when no separate infrastructure for cyclists is provided. Then, road factors such as distance and altitude differences can indirectly affect cyclists' safety. Therefore, the authors proposed a procedure based on the geometric characteristics of the road that can determine riding difficulties for cyclists. The proposed procedure can be used both by the public authorities who manage cyclists' safety and as a method of classifying the road network for cycling. The proposed procedure, based on the use of pattern recognition techniques, analyses data from a sample of nine riders who travelled on rural roads within the Municipality of Messina (Italy) to classify the roads according to their cycling difficulty. For each rider, duration, distance, road slope, altitude difference and spent calories have been measured and analysed. The collected data were used for the development of a model capable of predicting the cyclist's physical effort as a function of the road alignment itself. Knowing the effort required to cycle along a route can contribute to a more complete assessment of road classification, commonly defined according to motor vehicles. Moreover, it may constitute a measure determining the safety of cycling by encouraging cyclists to travel along roads compatible with their physical abilities. [ABSTRACT FROM AUTHOR]

The existing international standards suggest a methodology to assign a specific functional class to a road, by the values of some features, both geometrical and use-related. Sometimes, these characteristics are in contrast with each other and direct the analyst towards conflicting classes for a road or, worse, one or more of these features vary heterogeneously along the road. In these conditions, the analyst assigns the class that, by his capability and experience, he retains the most appropriate, in a very subjective way. On the contrary, the definition of an automatic procedure assuring an objective identification of the most appropriate functional class for each road would be desirable. Such a solution would be useful, especially when the road belongs to the existing infrastructure network or when it was not realised by out of date standards. The proposed procedure regards the definition of a classification model based on Pattern Recognition techniques, considering 13 input variables that, depending on their assumed value, direct the analyst towards one of the four functional classes defined by the Italian standards. In this way, it is possible to classify a road even when its characteristics are heterogeneous and conflicting. Moreover, the authors analysed the model limitations, in terms of is exploitable for both planned and existing roads and becomes particularly advantageous for road agencies aiming to optimally allocate their limited funds for specific interventions assuring the achievement of a fixed functional class. [ABSTRACT FROM AUTHOR]

The BIM (Building Information Modeling) approach potential in the civil engineering field opened novel scenarios in the design idea concept, from planning to executive and constructive phases. The related advantages are numerous and not only limited to a realtime interaction among the involved subjects, that can actually operate in an optimized 3D shared environment. Owing to the sharing information philosophy and to the features of various "smart objects" combined in the project, this innovation reduces potential errors and increases the effectiveness of the design solution in terms of both functionality and cost. Despite these advantages, the highway alignment design problem remains very complicated and not easy to solve without appropriate supporting tools. In recent years, several efforts have been spent in defining highway optimization procedures for helping designers in the selection of an optimal solution in compliance with numerous different constraints. Introducing these procedures in a BIM environment may represent a crucial step in the improvement of the highway design procedures, exploiting the full representation and modelling potential of the approach. In this paper, the authors present the advantages of a 3D highway alignment optimization algorithm, based on the Particle Swarm Optimization method, and its possible implementation in a BIM platform. A proper I-BIM environment can exploit the potential of the alignment optimization algorithms, simplifying the analysis of the different solutions, the final representation and the eventual manual modifications. [ABSTRACT FROM AUTHOR]

A civil engineering work can be performed by organizing the available resources (manpower, equipment and materials) in many different ways. Each different configuration results in a realization time and a cost that a building company has to bear. To produce reliable duration forecasts and money savings, it is essential to take into account all the uncertainties involved in the project operations. Generally, since it is impractical to process numerous uncertain variables - also undefined from a statistical point of view -, traditional probabilistic methods involve application difficulties for complex environments such as construction sites. To properly handle this issue, the authors propose in this paper the application of the Affine Arithmetic technique. This method treats the variables as intervals and returns reliable results, even when the variables are mutually dependent. The numerical example presented in the paper proves the efficiency of the procedure, even if some analytical complications are included in the analysis (dependency between variables, non-linear functions, etc.). Comparisons with Interval Analysis and traditional procedures are also provided. Adopting Affine Arithmetic, the results are reported in terms of intervals, avoiding the definition of unrealistic deterministic values that can strongly affect the operation organization. Furthermore, without increasing the problem complexity, the model admits continuous modifications (interval amplitudes, new variable dependencies, etc.) to correct and optimize the durations. [ABSTRACT FROM AUTHOR]

The compaction of the asphalt layer is a fundamental operation in pavement construction but, at the same time, its control is very difficult. The consequences on costs, on execution time and on duration of the pavement are very relevant and, for that reason, we wanted to prepare a predictive model able to minimize the attempts, often unsuccessful, which the executor is forced to make in the early stages of the construction. Due to a very large number of variables, we could not control the phenomenon with any known physical models; so, for the purpose of this research paper, we preferred to make use of a so-called black-box linear model, calibrating it with an appropriate procedure of trials and errors. The results achieved with this model have made it possible to predict the value of the material density with a reliability of 88% that, for the number of involved variables, can be considered a satisfactory target. With this procedure and knowing the boundary conditions (characteristics of the roller and the material), it is possible to arrange the compaction very quickly, achieving a good compromise between layer density and execution times. [ABSTRACT FROM AUTHOR]

In the civil engineering field, there are usually unexpected troubles that can cause delays during execution. This situation involves numerous variables (resource number, execution time, costs, working area availability, etc.), mutually dependent, that complicate the definition of the problem analytical model and the related resolution. Consequently, the decision-maker may avoid rational methods to define the activities that could be conveniently modified, relying only on his personal experience or experts' advices. In order to improve this kind of decision from an objective point of view, the authors analysed the operation correction using a data mining technique, called Fuzzy Clustering. This allows the analysts to represent complex real scenarios and classify the various activities according to their influence on the reduction of the total execution time. The proposed procedure provides positive results that are also in compliance with significant operational constraints, such as the control of costs and areas needed by the workers to perform the tasks. Finally, it is possible to increase the input variable number preserving the algorithm simplicity and avoiding lacks of accuracy in the final numerical outcomes. [ABSTRACT FROM AUTHOR]

This research proposes a fuzzy model built to predict the track paths of a motor vehicle on a two-lane road and two-way traffic. The purpose of this study stems from the awareness that the position of the vehicle within the cross-section hardly coincides with the axis of the lane but deviates from this one because of some conditions generally not provided in the road standards. To solve this problem, the authors prepared an instrumented vehicle, measuring many variables during some trials in a rural road located in Sicily, Italy. The resulting database was treated at first with subtractive clustering techniques to correctly size the membership functions and rules without the subjective help of an analyst. Therefore, the fuzzy model was built only on the basis of the measured data, and the result was the position of the vehicle within the cross-section of the examined road. This research can help the analyst to look for the real cause of user's misbehavior even when the variables involved are fully respectful with the road standard to modify or eliminate disturbing elements in the understanding of the road by the users. [ABSTRACT FROM AUTHOR]

In this paper, we investigated drivers’ visual behaviour while travelling a road regularly opened to traffic in order to evaluate the effectiveness of the traditional scientific models and propose, at the same time, further measures useful for understanding the complex phenomenon. As is known, drivers acquire the necessary information for knowing the road geometry by visually detecting certain areas of the surrounding context. Some models in the literature have shown in a simple and convincing way these mechanisms, but they are valid only with specific assumptions, often very restrictive, such as a two-lane road, horizontal sign clearly visible and no interaction with other vehicles. For this reason, in this study we wanted to investigate different conditions, by estimating the visual strategy of some regular drivers on a three-lane road in presence of other vehicles. The visual behaviour was surveyed with theTobii Glasses Eye Tracker® and the resulting raw data were further manipulated by us to extract more useful information for our purposes. In particular, we quantified the driver’s dedicated attention to the various elements present inside the environmental context, both static (road edges, road signs, dashboard, etc.) and dynamic (other vehicles), meaning by this term those that could potentially collide with the trajectories of our vehicle. The achieved results, highlighting the limits of validity of some recent studies, contain some proposed indexes useful to give a better understanding of the visual behaviour in order to detect any eventual weakness of the road. [ABSTRACT FROM AUTHOR]

Various studies have emphasized the interesting advantages related to the use of new transition curves for improving the geometric design of highway horizontal alignments. In a previous paper, one of the writers proposed a polynomial curve, called a polynomial parametric curve (PPC), proving its efficiency in solving several design problems characterized by a very complex geometry (egg-shaped transition, transition between reversing circular curves, semidirect and inner-loop connections, and so on). The PPC also showed considerable advantages from a dynamic perspective, as evidenced by the analysis of the main dynamic variables related to motion (as well as rate of change of radial acceleration, steering speed, roll speed, and so on). In this paper, an optimization procedure using genetic algorithms (GAs) for selecting the different parameters of the PPC has been proposed. In particular, a specific algorithm defines the parameter values in order to minimize an appropriate fitness function. Besides, the final PPC can be examined from a dynamic point of view for evaluating the compliance with the comfort and safety conditions. Moreover, to simplify the geometric representation and the calculation of the dynamic variables of the PPC, using computer software, a specific and innovative routine has been specifically developed by the writers. [ABSTRACT FROM AUTHOR]

The proposed research addresses the problem of predicting driver's visual behavior. Notably, this issue is of great importance for road safety because it provides information about the true perception of the road environment. This need is particularly felt when the real situation is so complex that it cannot be represented by simple analytical audits contained in the road international standard. Therefore, with the help of an instrumented vehicle, the authors conducted some trials to identify relevant data useful to recognize the road environment as perceived by drivers. Based on this data, the authors prepared a linear model that, properly calibrated, would enable them to predict the drivers’ visual strategy. The results were encouraging, because a model so simple in structure as well as in the number of variables involved could control a very complex phenomenon, such as that of visual perception. The proposed methodology can be applied as a further control in the design of new roads and in the maintenance of existing ones and, in particular, in the analysis of special scenarios (e.g., unusual conditions of weather or traffic) that are not represented by ordinary audits contained in the road standards. [ABSTRACT FROM PUBLISHER]

The current international road standards, in order to give organization and safety, promote the classification of roads according to their technical and functional characteristics beyond their administrative membership, but the procedures are yet strongly based on the expertise's judgment. In fact, although this activity has a great importance for the consequences that produces in terms of responsibility and allocation of economic resources, it is solely based on the quantification of some variables without specifying methods or analytical procedures. In this paper, after an instrumental survey of the road environment, we applied data mining techniques that consider the ‘vagueness’ of the analysed scenario. The type of algorithms used, therefore, permits to quantify a degree of membership (among 0 and 1) of a road to the groupings provided and to prepare any corrective action in order to direct the final result towards a specific class with greater precision. In addition, this method is very flexible and willing to contain new variables or observations at different times with great easiness. Moreover, the geographical location of the individual observations, as it was done also in this research, can be transferred to a GIS system, with a positive impact on maintenance programs. [ABSTRACT FROM AUTHOR]

This paper deals with the analysis of the main variables involved in the visual activity of a driver of motor vehicles, in order to identify the most important quantities and implement, therefore, appropriate corrective actions to the achievement of road safety. The first step in this research was to survey a number of variables within the road environment and processing this data base with clustering techniques in order to extract useful information for purpose. In this case, a mixture of procedures based on Fuzzy Logic (FL) and Artificial Neural Network (ANN) were applied not only to extract knowledge not known a priori but, above all, to define the membership functions and rules of the fuzzy model without recourse to the skills of the analyst, not always so objective. This procedure, applied to a rural road open to traffic, showed a good performance in predicting the user's visual behavior and, especially, in identifying the most influential variables. This aspect may allow the agency to direct the maintenance operations so that to facilitate understanding of the information contained within the road environment, thus improving safety. [ABSTRACT FROM AUTHOR]

This article deals with the application of fuzzy techniques to the CREAM model of Hollnagel, already recognized in the scientific community in applications on the human component in complex systems. Among those most applied, the CREAM has the advantage of being extremely flexible and of being able to receive the support of opportune analytical instruments for the calculation of human reliability. In this article, the uncertainty of the environment within which driving takes place has been represented through fuzzy techniques. In particular, the variables that describe the state of the context perceived by the driver have been modeled by means of appropriate membership functions, characterized by lexical-type domains and nonlinear dependencies. The results obtained from the consequent process of defuzzification have been further transformed into intervals in order to conserve evidence of the uncertainty also subsequent to the analysis, up to determination of the reliability of the human component. The goals achieved, evidenced in a simple application, can be used in accident analysis but, above all, at the previsional stage, that is, the designing of new or existing roads, when we wish to deepen the presumed criticalities that haven't emerged from the rigorous application of the current standard. [ABSTRACT FROM PUBLISHER]

Copyright of Baltic Journal of Road & Bridge Engineering (Baltic Journal of Road & Bridge Engineering) is the property of Baltic Journal of Road & Bridge Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Transport (16484142) is the property of Vilnius Gediminas Technical University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Baltic Journal of Road & Bridge Engineering (Baltic Journal of Road & Bridge Engineering) is the property of Baltic Journal of Road & Bridge Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The compaction of a hot mix asphalt depends on a number of important factors whose control, during the execution of the pavement, is complex; however it is essential to achieve the results envisaged in the design with the least possible cost. Therefore, the evaluation of the effect of these variables on the material density is important as well as their quantification in real time. This research, starting from a survey of some environmental variables, together with the hot mix asphalt density using an electrical impedance device, through the application of a neuro-fuzzy technique, proposes a procedure to classify the most important features. These results can be rapidly deduced during the paving operations; calibrations required to correct the compaction can be applied on site without waiting further time necessary for the extraction of the cores and the subsequent laboratory analysis. In this way it is possible to identify with a better precision the aspects of the environmental context requiring more attention. In addition, the model permits the inclusion of new input variables and additional data that can be recorded in following phases. [ABSTRACT FROM AUTHOR]

This paper deals with the application of an analytical technique known as 'interval analysis' to the usual audits contained in international road standards. Generally, a design solution is constrained by a number of parameters (dependent on the morphology of territory, on existing conditions, on type of road, etc.) that, materially, cannot exceed certain values. Although the final choice is respectful of these constraints, the ordinary calculation techniques do not allow use of the full potential of the most critical variables. In order to determine all the possible solutions of the problem, the so-called interval analysis, which is generally used to treat uncertain problems when only the limits of existence of uncertain variables but not their probabilistic characteristics are known, was used. The application to the visibility of a horizontal curve has allowed different solutions to be identified, by starting from the knowledge of the range of existence of one or more input variables and isolating the result which was more convenient for that specific situation. This procedure is easily applicable to the design of new or existing roads, especially when one or more variables of the problem are close to the threshold imposed by the standards. [ABSTRACT FROM AUTHOR]