Infrastructures — Open Access Journal

This paper presents a reliability-based method for the design of intersection sight distance (ISD) at traffic roundabouts using the linear and nonlinear deceleration profiles of the entry vehicles. The reliability method is based on the first-order second moment method which is simple and relatively accurate compared with advanced methods. The nonlinear deceleration profile includes a shape parameter that produces the linear profile as a special case. Deterministic and reliability-based formulas for the required ISD for an approaching vehicle are developed for the entry vehicle on the left and the vehicle on the circulating roadway. Then, the design values of the ISD legs, applicable to any type of roundabout, are presented for different probabilities of non-compliance (P_nc) and different coefficients of variations. For the special case of single-lane symmetrical roundabouts, which have a well-defined geometry, the lateral clearance needs are established. The sensitivity analysis shows that ISD is very sensitive to both the mean and variance of the critical headway. The results show that the deterministic method results in ISD values that correspond to a very small P_nc, indicating that the method is very conservative. The proposed method, which provides flexibility in selecting ISD for any given P_nc, should be of interest to highway designers and practitioners to promote roundabout safety. Full article

Calcite-induced precipitation methods (CIPMs) have recently become potential techniques in geotechnical engineering for improving the shear strength of sandy soil. One of the most promising methods among them is enzyme-induced calcite precipitation (EICP). In this technique, a mixed solution composed of reagents and the urease enzyme, which produces calcite, is utilized as the grouting material. The precipitated calcite in granular soil provides ties among the grains of soil and limits their mobility, thus promoting an improvement in strength and stiffness and also a reduction in the hydraulic conductivity of sandy soil. This paper discusses the potential increase in the strength and stiffness of the soil, the additional materials for grouting, the effect of these materials on the treatment process, and the engineering properties of the soil. The possible sources of the urease enzyme and the applicability of the EICP method to other soil types are also discussed in this paper. The environmental and economic impacts of the application of EICP are also presented. The envisioned plans for application, potential advantages, and limitations of EICP for soil stabilization are discussed. Finally, the primary challenges and opportunities for development in future research are briefly addressed. Full article

Lidar and other remotely sensed data such as UAV photogrammetric data capture are being collected and utilized for roadway design on an increasing basis. These methods are desirable over conventional survey due to their efficiency and cost-effectiveness over large areas. A high degree of relative accuracy is achievable through the establishment of survey control. In this case study, elevations (z-values) derived from mobile-terrestrial lidar, aerial lidar, and UAV photogrammetric capture collected with survey control were statistically compared to conventionally surveyed elevations. A cost comparison of the methods is also included. Each set of z-values corresponds to a discrete horizontal point originally part of the conventional survey, collected as cross-sections. These cross-sections were surveyed at three approximate tenth-mile sample locations along US-30 near Georgetown, Idaho. The cross-sections were collected as elevational accuracy verification, and each sample location was selected as an area where the mobile-terrestrial lidar in particular was expected to have more difficulty achieving accuracy off the road surface. Processing and analysis were performed in Esri ArcMap 10.6, and all data were obtained from the Idaho Transportation Department, District 5. Overall, the aerial lidar elevations were found to be closest to conventionally surveyed elevations; on road surface and level terrain, mobile-terrestrial and UAV photogrammetric capture elevations were closer to the conventionally measured elevations. Full article

Ground settlement above urban tunnels is a threat for nearby buildings, because it may lead to their differential settlement, tilting, and damage, depending on their structural characteristics, on ground conditions, and on the excavation procedure. Still, for few cases only details on ground settlement are known. In this article we analyze ground subsidence data during the excavation of Lines 2 and 3 of the Athens Metro. Based on this evidence, and in comparison with previous studies, we show that observations of elevation changes and of tilting of buildings may underestimate the amount of ground loss; this is because part of the ground deformation may be compensated by the stiffness of buildings or accommodated by internal deformation of sizeable buildings hosting measuring benchmarks. This effect can be described as static soil–structure interaction (sSSI), in analogy to the dynamic SSI produced during earthquakes. sSSI can produce bias in monitoring data above an advancing tunnel front, leading to skew and not to symmetric subsidence curves if observations are made on one side on buildings and on the other side in open spaces (‘greenfields’). Furthermore, we show that ‘bowls’ of increased subsidence are observed along subsidence troughs during excavation; such ‘bowls’, not infrequently underestimated because of sSSI, may conceal a potential for sinkholes and other types of failure. Isolated towers on the contrary describe well ground subsidence and tilting. Full article

In this paper, a piecewise-defined function is proposed to estimate traffic noise in urban areas. The proposed approach allows the use of the model even in the case of very low or zero flows for which the classical logarithmic form is not suitable. A model based on the proposed approach is calibrated for a real case and compared with the results obtained with a model based only on the logarithmic form. The results obtained show how the proposed piecewise-defined function, linear for low traffic flows and logarithmic for medium-high volumes, is able to better represent real noise pollution levels in all conditions. The proposed approach is particularly useful when comparing two plan scenarios from the point of view of noise effects. Full article

Generating meaningful inferences from crash data is vital to improving highway safety. Classic statistical methods are fundamental to crash data analysis and often regarded for their interpretability. However, given the complexity of crash mechanisms and associated heterogeneity, classic statistical methods, which lack versatility, might not be sufficient for granular crash analysis because of the high dimensional features involved in crash-related data. In contrast, machine learning approaches, which are more flexible in structure and capable of harnessing richer data sources available today, emerges as a suitable alternative. With the aid of new methods for model interpretation, the complex machine learning models, previously considered enigmatic, can be properly interpreted. In this study, two modern machine learning techniques, Linear Discriminate Analysis and eXtreme Gradient Boosting, were explored to classify three major types of multi-vehicle crashes (i.e., rear-end, same-direction sideswipe, and angle) occurred on Interstate 285 in Georgia. The study demonstrated the utility and versatility of modern machine learning methods in the context of crash analysis, particularly in understanding the potential features underlying different crash patterns on freeways. Full article

Crash severity is undoubtedly a fundamental aspect of a crash event. Although machine learning algorithms for predicting crash severity have recently gained interest by the academic community, there is a significant trend towards neglecting the fact that crash datasets are acutely imbalanced. Overlooking this fact generally leads to weak classifiers for predicting the minority class (crashes with higher severity). In this paper, in order to handle imbalanced accident datasets and provide a better prediction for the minority class, the random undersampling the majority class (RUMC) technique is used. By employing an imbalanced and a RUMC-based balanced training set, we propose the calibration, validation, and evaluation of four different crash severity predictive models, including random tree, k-nearest neighbor, logistic regression, and random forest. Accuracy, true positive rate (recall), false positive rate, true negative rate, precision, F₁-score, and the confusion matrix have been calculated to assess the performance. Outcomes show that RUMC-based models provide an enhancement in the reliability of the classifiers for detecting fatal crashes and those causing injury. Indeed, in imbalanced models, the true positive rate for predicting fatal crashes and those causing injury spans from 0% (logistic regression) to 18.3% (k-nearest neighbor), while for the RUMC-based models, it spans from 52.5% (RUMC-based logistic regression) to 57.2% (RUMC-based k-nearest neighbor). Organizations and decision-makers could make use of RUMC and machine learning algorithms in predicting the severity of a crash occurrence, managing the present, and planning the future of their works. Full article

The work described in this paper investigated, by calculating critical flutter speed, the aeroelastic response of suspended pedestrian bridges made of a laminated wood structure and hemp cables and compared them to bridges with a steel structure and harmonic steel cables. Critical flutter speed was estimated using a numerical two degree of freedom (2-DOF) generalized deck model based on finite-element modal analysis. The critical flutter speeds of two sets of 25 different structural configurations, obtained by varying the deck chord and the permanent deck loads, made of steel and of laminated wood respectively, were estimated using experimental flutter derivatives obtained from 30 wind tunnel experiments. One of the most significant results was that pedestrian bridges made of laminated wood and hemp have a higher torsional frequency than those made of steel and that this affects critical flutter speed. A case study was performed and discussed by analyzing the structural and aeroelastic response of a 250 m pedestrian bridge with a 12 m deck chord and two approximately 32 m tall towers. Full article

Although building information modeling (BIM) has been widely adopted in the building industry for several decades, the use of BIM in the context of transportation infrastructure has been slow in terms of both adoption and application. Industry and academia are increasingly making efforts to adopt BIM for other non-building civil infrastructure but, so far, there has not been a comprehensive review of these efforts specifically regarding transportation. This paper explores BIM implementation in an infrastructure design project. An Autodesk ^® BIM-based tool, Civil 3D, is proposed as a potential BIM tool platform. This paper also focuses on modeling specific road elements not editable from the standard library, such as guardrails and retaining walls, as well as proposing different solutions using Revit and Subassembly Composer and analyzing the interoperability among BIM-based tools. Full article

The scarcity of resources, the limited land, and the overstressing of tourism, as well as the estrangements of movement, make the insular territories relevant case studies in terms of their regional management and governance and, consequently, sustainable development. Thereby, Transportation and Infrastructures’ Sustainability in these territories is not an exception. In this regard, the present study, through exploratory tools, expects to analyze, using accessibility and connectivity indicators, the impacts over the social-economic sphere that the local Transportation and Infrastructures may deliver to the populations of the Canary Islands Archipelago. The study enables us to identify the islands of La Palma, El Hierro, Fuerteventura, and La Gomera as those with better accessibility patterns. Full article

Thermal stresses are generated in concrete during the accelerated curing process in precast concrete. These stresses may cause concrete to crack, which would have a negative effect on the general concrete performance. This paper provides the results of the thermal stress analysis of concrete containing 25% replacement of ordinary Portland cement (OPC) by ground granulated blast-furnace slag cement (GGBFS) with 3000 cm²/g fineness. A total of 2.5% of limestone powder and 1.75% of fine gypsum by mass of OPC were incorporated in the other concrete mix proportion to check their effect on the cracking tendency of concrete. The concrete was subjected to heat curing. JCMAC, a 3D finite element analysis software developed in Japan, was used in this study for the thermal stress analysis. The heat curing period of one day, similar to generally used in the precast concrete industry for civil engineering products consisting of 3 h preheating period, heating to a peak temperature of 65 °C and this temperature was kept for 3 h, and lastly cooling was used in the study. A standard precast box culvert model member together with some experimental results obtained in the laboratory were used in the analysis. Lower cracking resistance at 1 day was observed in both mix proportions that would lead to cracking at demolding time. Curing sheets were then introduced in the analysis to cover the precast mold during accelerated curing and this showed improvement in cracking resistance of concrete containing limestone powder and fine gypsum. Full article

There are a number of pavement management systems, but most of them are limited in providing pavement design and pavement design sensitivity information. This paper presents efforts towards the integrated pavement design and management system, by developing smart pavement design sensitivity analysis software. In this paper, the sensitivity analyses of critical design input parameters have been performed to identify input parameters which have the most significant impacts on the pavement thickness. Based on the existing pavement design procedures and their sensitivity analysis results, a smart pavement design sensitivity analysis (PDSA) software package was developed, to allow a user to retrieve the most appropriate pavement thickness and immediately perform pavement design sensitivity analysis. The PDSA software is a useful tool for managing pavements, by allowing a user to instantaneously retrieve a pavement design for a given condition from the database and perform a design sensitivity analysis without running actual pavement design programs. The proposed smart PDSA software would result in the most efficient pavement management system, by incorporating the optimum pavement thickness as part of the pavement management process. Full article

Building Information Modeling (BIM) has a crucial role in smart road applications, not only limited to the design and construction stages, but also to traffic monitoring, autonomous vehicle navigation, road condition assessment, and real-time data delivery to drivers, among others. Point clouds collected through LiDAR are a powerful solution to capture as-built conditions, notwithstanding the lack of commercial tools able to automatically reconstruct road geometry in a BIM environment. This paper illustrates a two-step procedure in which roads are automatically detected and classified, providing GIS layers with basic road geometry that are turned into parametric BIM objects. The proposed system is an integrated BIM-GIS with a structure based on multiple proposals, in which a single project file can handle different versions of the model using a variable level of detail. The model is also refined by adding parametric elements for buildings and vegetation. Input data for the integrated BIM-GIS can also be existing cartographic layers or outputs generated with algorithms able to handle LiDAR data. This makes the generation of the BIM-GIS more flexible and not limited to the use of specific algorithms for point cloud processing. Full article

The transport of dangerous goods by rail carries a high risk of accident and every effort should be made to ensure that such transport is carried out under the best possible safety conditions. The research objective was to analyze and identify the main risks associated with the transport of dangerous goods by rail as well as to identify and assess the main factors of safe transport in order to reduce the risk of accident. For this purpose, analysis of the literature, systematization, generalization, and evaluation by experts was applied. The article states that in order to ensure the safe transport of dangerous goods by rail, it is necessary to comply with the rules for loading and unloading dangerous goods, the established requirements and instructions, and technical conditions of wagons and their labelling as well as preventive measures to reduce the risk. Recommendations are provided on how to reduce accidents and incidents in the transport of dangerous goods by rail. Full article

In recent years, the smart car sector has been increasing enormously in the Internet of Things (IoT) market. Furthermore, the number of smart cars seems set to increase over the next few years. This goal will be achieved because the application of recent IoT technologies to the automotive sector opens up innovative opportunities for the mobility of the future, in which connected cars will be more and more prominent in smart cities. This paper aims to provide an overview of the current status and future perspectives of smart cars, taking into account technological, transport, and social features. An analysis concerning the approaches to making smart a generic car, the possible evolutions that could occur in the coming decades, the characteristics of 5G, ADAS (advanced driver assistance systems), and the power sources is carried out in this paper. Full article

Over the last few decades, the attention on the safety of existing reinforced concrete (RC) structures has significantly increased. RC bridges, in particular, are highly relevant for strategic importance. In the Italian context, several of these bridges were built around 1960, when engineering practice commonly ignored or underestimated the presence of seismic actions. Therefore, it is fundamental to quantify as accurately as possible their seismic safety level with state-of-the-art analysis techniques. In this paper, an efficient procedure based on the multi-modal pushover analysis approach is proposed for the risk evaluation of several bridges of the Italian highway network. This procedure, tailored for portfolio level assessment, takes into account the non-linear behavior and the complex dynamic response this type of structure with limited computational effort. Three fundamental aspects are defined for the structural modelling of bridges, i.e., materials’ constitutive law, finite element type and nonlinear hinge models. Flexural and shear nonlinearities of piers are included to account for ductile and brittle damage potential. The standardized procedure guarantees consistent comparisons among different bridges of the same network in the form of risk indexes. Full article

Obtaining pedestrian trajectories by a vision-based methodology is receiving increasing attention in the literature over recent decades. Within the field of study of human-induced vibrations on footbridges, practical challenges arise when collecting the trajectories of high-density crowds during measurement campaigns. A cheap and robust methodology tackling these issues is presented and applied on a case study consisting of a real-life footbridge occupied with many pedestrians. A static camera setup consisting of low-cost action cameras with limited installation height is used. In addition, a drone camera was employed to collect a limited amount of footage. Pedestrians are equipped with colored hats and detected using a straightforward color-segmenting approach. The measurements are subjected to both systematic and random measurement errors. The influence of the former is theoretically investigated and is found to be of limited importance. The effect of the latter is minimized using a Kalman filter and smoother. A thorough assessment of the accuracy results reveals that the remaining uncertainty is in the order of magnitude of 2 to 3 cm, which is largely sufficient for the envisaged purpose. Although the methodology is applied on a specific case study in the present work, the conclusions regarding the obtained accuracy and employability are generic since the measurement setup can be extended to a footbridge with virtually any length. Moreover, the empirically obtained results of the presented case study should find use in the calibration of pedestrian dynamic models that describe the flow of high-density crowds on footbridges and the further development of load models describing crowd-induced loading. Full article

To a certain degree, composite railway sleepers and bearers have been recently employed as a replacement for conventional timber sleepers. Importantly, attributed to the rise in traffic demand, structural health monitoring of track structural members is essential to improve the maintenance regime and reduce risks imposed by any structural damage. A potential modern technique for detecting damage in railway components by using energy waves is called acoustic emission (AE). This technique has been widely used for concrete structures in other engineering applications, but the application for composites is relatively limited. Recently, fiber-reinforced foamed urethane (FFU) composites have been utilized as railway sleepers and bearers for applications in the railway industry. Neither does a design standard exist, nor have the inspection and monitoring criteria been properly established. In this study, three-point bending tests were performed together with using the AE method to detect crack growth in FFU composite beams. The ultimate state behaviors are considered to obtain the failure modes. This paper is thus the world’s first to focus on damage detection approaches for FFU composite beams using AE technology, additionally identifying the load-deflection curves of the beams. According to the experimental results, it is apparent that the failure modes of FFU composite beams are likely to be in brittle modes. Through finite element method, the results were in good agreement with less than 0.14% discrepancy between the experimental and numerical data. The attractive insights into an alternative technique for damage assessment of the composite components will help railway engineers to establish structural monitoring guidelines for railway composite sleepers and bearers. Full article

This article presents the latest improvements in a recently developed nondestructive testing (NDT) approach for early detection of various flaws (corrosion, delamination, and concrete cracking) in reinforced concrete (RC) bridge decks. The proposed method involves the use of internal steel reinforcement as a wave guide for transmitting ultrasonic waves through the system and the measurement of leaked energy from the surface of the concrete. This paper builds upon the progress made in the previously published phases of the project and aims to further explore the capabilities and practicality of the proposed NDT method. Specifically, the limits of propagation distance, effect of bidirectional reinforcement, methods of attachment and coupling of the sensors to the reinforcement and concrete, and suggestions for optimal sensor arrays are discussed in this paper based on the findings from the most recent laboratory tests and pilot field tests. The results show that with careful placement of sensors and data interpretation, early stages of localized corrosion and delamination can be detected, even when bidirectional and multiple layers of reinforcement are present. For field applications, an angled seat made of fast-setting Hydrocal gypsum cement is recommended, and it is projected that the optimal angle of attachment is 33 degrees or less from the vertical axis. Full article