Road Crossings Research Articles

Rapid Surface Inspection of Steel Bridges Using ACFM

Many bridges feature bolted or welded steel sections as part of their structure. These are susceptible to fatigue cracking due to the cyclic action of traffic and wind forces on the bridge. Since the structure is often painted to reduce corrosion, detection of surface cracks at early stages by conventional means can be slow and costly as the paint must be removed and then reapplied in order to conduct magnetic particle testing (MT). Alternating Current Field Measurement (ACFM) is an electromagnetic inspection technique capable of reliably detecting and sizing surface-breaking fatigue cracks in metals. Importantly, it can do so without the need to remove most paints and coatings. Its common use for the inspection of offshore structures, above and below sea level, have demonstrated the technique’s suitability to inspect large structural welds in difficult conditions, both environmentally and with less than ideal surface conditions. ACFM provides information on the length and depth of detected cracks, allowing repair efforts to be concentrated on the most serious defects, without wasting time on insignificant ones. Recent improvements to ACFM equipment portability, speed of acquisition and sensitivity, combined with the introduction of advanced multi-element array probes, have improved the speed and ease of inspections. Use of the ACFM technique can therefore greatly speed up inspection, reduce waste and save time compared to MT inspection. Civil structures are sometimes corrosion protected using conductive coatings which are known to pose a challenge to electromagnetic inspection techniques. In this article, simulations, experimental results and recommendations related to the application of ACFM on galvanized and thermal sprayed aluminum structures are presented. Examples of various bridges inspections are presented; from a historic span over the river Thames, originally built in 1867, to more recent road and rail crossings.

Mitigating the effect of linear infrastructure on arboreal mammals in dense forest: A canopy bridge trial

SummaryRoads and other linear infrastructure create treeless gaps that can limit the movement of non‐flying, arboreal animals. These negative effects are particularly strong in dense forests, where even narrow infrastructure corridors represent a significant change in habitat structure. Artificial canopy bridges are an increasingly common approach to mitigating the barrier effect of roads and other linear infrastructure on the movement of arboreal mammals; however, questions remain about the success of various designs for different species. Here we conduct an experimental evaluation of the response of a critically endangered possum, Leadbeater's Possum (Gymnobelideus leadbeateri), to two artificial canopy bridge designs: single‐rope bridges and ladder bridges. We found that both bridges were used by Leadbeater's Possum and five other species of arboreal marsupial to cross narrow, forestry roads. However, Leadbeater's Possums crossed ladder bridges 13 times more often than the single‐rope design (average of 564.5 and 41.75 crossings per design respectively). Radiotelemetry conducted on four Leadbeater's Possums prior to bridge installation detected no road crossings, providing preliminary evidence that the bridges improved cross‐road movement. Ladder bridges appear to be the better design choice for a wider range of arboreal marsupials as they were used more frequently, offer greater stability, and provide better predator avoidance than single‐rope designs.

Analisa Pengaruh Hambatan Samping terhadap Kinerja Jalan Di Jalan Orang Kayo Pingai Kota Jambi

Increased volume of traffic flow will cause changes in traffic behavior of a road segment, especially on urban roads. This increase is caused by the increasing number of residents and the need for transportation facilities so that enough space is needed for traffic infrastructure such as roads, parking locations and so on. High road side activity has a major effect on road capacity and performance in an urban area. Among them such as pedestrians, road crossings, street vendors (Street vendors), slow-walking vehicles (rickshaws, bicycles, horse-drawn carriages), vehicles stopped carelessly (city transportation, inner-city buses), parking on the street (on street parking), and vehicles in and out of road-side land use activities. The purpose and purpose of the study conducted by this author is to find out the performance of the road against side obstacles. And the objectives can be described as follows, namely:To find out the volume of traffic, the amount of capacity and level of service on the road people kayo pingai during rush hour.To analyze the modeling of side barriers and road capacity of Kayo Pingai people using simple linear regression. As for the benefits that are expected and can be taken by the authors of the implementation of this study, including: Increase knowledge and insight into the characteristics of traffic and vehicle parking on the road body and know the various lalaulintas problems that occur in urban areas, especially on Jalan Orang Kayo Pingai.

Forecasting seasonal peaks in roadkill patterns for improving road management

For several species, roadkill is not spatially aggregated on hotspots, having instead a more diffuse pattern along the roads. For such species, management measures such as road passages may be insufficient for effective mitigation, since a large part of the road crossings is likely to occur outside the influence of those structures. One complementary approach could be to implement temporary mitigation actions, such as traffic calming. This requires understanding when roadkill peaks may occur. We tested the feasibility of predicting seasonal peaks of roadkill using data from a 3-year systematic monitoring (78 surveys over ca. 960 km of roads) from eight non-flying vertebrate species from Mato Grosso do Sul, Brazil, with different body size and life history traits (ca. 6400 records from focal species). We modelled the time-series of the roadkill of these species at large scale (state level) using generalized additive mixed models (GAMMs). We used the data of the first 2 years as training datasets, and the information from the third year of surveys as testing datasets to evaluate the prediction performance of models. Overall, the models of species feed with a higher number of records were able to follow reasonably well the variations of roadkill over time, although they were not able to correctly predict the number of collisions. For species with fewer observations, the models presented a poorer goodness-of-fit and prediction ability. Our results suggest that, at least for those species with higher roadkill rates, it can be possible to forecast periods of higher probability of occurring hot-moments of mortality. Such models can provide valuable information to implement seasonal management actions.

Rapid Colonization of Upstream Habitats by Oncorhynchus Mykiss Following Culvert Modification

AbstractHabitat fragmentation threatens the persistence of fish populations, and road crossings (e.g., culverts) are particularly problematic because they are globally ubiquitous and can block access to critical habitats. Barrier removal or modifications that allow upstream access can result in expanded distributions, increased abundances, and gene flow among historically isolated populations. Actions that promote connectivity, gene flow, and the potential expression of multiple life history forms (e.g., anadromy in Pacific salmon Oncorhynchus spp.) are thought to buffer against extinction and are increasingly important given the high rates of imperilment for many fish species. We collected genetic samples from juvenile O. mykiss (anadromous steelhead and resident Rainbow Trout) prior to and following the modification of a culvert that served as a historical barrier to upstream movement and tested for changes in genetic composition through time. Prior to culvert modification, levels of genetic diversity were low and genetic differentiation with reference collections of anadromous steelhead was high. After treatment, we observed increased levels of genetic diversity, larger estimates of effective population size, and decreased genetic differentiation with steelhead, indicating an influx of individuals from a downstream population. Using an inexpensive genetic‐based monitoring approach, we show that culvert modification can result in the rapid reestablishment of connectivity between historically isolated populations.

Semantic Segmentation of Traffic Landmarks Using Classical Computer Vision and U-Net Model

Due to the deterioration of traffic landmarks such as (crosswalks, lanes, speed limits, …etc) in Mie prefecture-Japan, the sudden stop rate during road crossings reached 3.4% in the year 2020. It has been deemed necessary by the local authorities to implement a reliable maintenance process for these road signs. Such a process would rely on an automatic camera-based monitoring system in order to keep track of the deterioration status of road signs. The first step consists of achieving successful detection and segmentation of these landmarks. In this paper, we try to accomplish this initial goal by using a dataset of around 13000 high resolution images taken from Mie prefecture streets. In order to achieve our goal of landmark detection we relied on some classical computer vision techniques as well as a deep learning approach. We developed a method to separate landmarks from other objects in a given image by relying on distinctive features of these landmarks. The method in question was then used to build a semi-assisted labelling tool, which was used to annotate a set of around 182 images and used them to train a CNN model to perform semantic segmentation of the road signs. In the end we managed to achieve a successful segmentation with a dice score of 78.90% on the validation set, as well as a solid proof of concept for a CNN based approach to solve this particular problem

Evaluation of the Influence of Road Geometry on Overtaking Cyclists on Two-Lane Rural Roads.

Road cycling, both individually and in groups, is common in Spain, where most two-lane rural roads have no cycle lanes. Due to this, and the difference in speed between drivers and cyclists, the overtaking manoeuvre is one of the most dangerous interactions. This study analyses how road geometry influences the overtaking manoeuvre performance. Field data of 1355 overtaking manoeuvres were collected using instrumented bicycles, riding along different rural road segments, and considering individual, medium and large groups of cyclists. The safety variables that characterise the overtaking manoeuvre are overtaking vehicle speed and lateral clearance. These variables have been correlated to geometric characteristics of the road, such as the type of centre line, the horizontal alignment, the speed limit, and the road cross section. Regression models have been fitted considering each cyclist group size and configuration. For individuals and medium groups, wider roads generate higher lateral clearances and lower overtaking speeds, while for large groups only the solid centre line was significant, generating lower clearances and higher speeds. Results suggest that other factors need to be considered, especially for large groups. Results offer a deeper understanding of the phenomenon by providing key points for improving road geometry design, such as widening the shoulders.

Safe access to road crossings and the issue of quiet vehicles in relation to pedestrians with a vision impairment: A literature review

This New Zealand study explored the research literature about quiet motor vehicles, like electric and hybrid cars, and the safety of pedestrians with vision impairment when making road-crossing decisions through an integrative literature review. A search of four research databases, two public library databases, and the New Zealand and the United States’ Departments of Transport online resources, as well as three relevant journals was conducted using key words. A rapid critical appraisal tool was used to assess whether the 38 found articles were valid and important, provided any answers to the research questions, and met the study’s inclusion criteria. A thematic analysis of 25 studies, which were included in this study, was completed to answer the following research questions: (1) What does the current literature say, as a whole, about the potential effects of ‘quiet vehicles’ on road-crossing procedures for pedestrians with a vision impairment? and (2) what remedies may exist to alleviate these effects, including possible changes to orientation and mobility (O&M) practice? Five emerging themes were found in the research: (1) crossing the road as a pedestrian with a vision impairment with quiet cars; (2) O&M instruction needs to change; (3) environmental access to road crossings; (4) developing and adapting technology and car sounds; and (5) rights of people with a vision impairment, policy, and legislation. The literature also confirmed that road crossings, when quiet vehicles are present, are dangerous for pedestrians with a vision impairment because such pedestrians rely on vehicular sounds for safe crossings. However, the review concluded that further research is needed in order to answer the research questions in this study. There were no studies about road-crossing procedures and quiet cars, and little research about possible remedies and O&M practice.

Automatic Roadside Feature Detection Based on Lidar Road Cross Section Images.

The United Nations (UN) stated that all new roads and 75% of travel time on roads must be 3+ star standard by 2030. The number of stars is determined by the International Road Assessment Program (iRAP) star rating module. It is based on 64 attributes for each road. In this paper, a framework for highly accurate and fully automatic determination of two attributes is proposed: roadside severity-object and roadside severity-distance. The framework integrates mobile Lidar point clouds with deep learning-based object detection on road cross-section images. The You Only Look Once (YOLO) network was used for object detection. Lidar data were collected by vehicle-mounted mobile Lidar for all Croatian highways. Point clouds were collected in .las format and cropped to 10 m-long segments align vehicle path. To determine both attributes, it was necessary to detect the road with high accuracy, then roadside severity-distance was determined with respect to the edge of the detected road. Each segment is finally classified into one of 13 roadside severity object classes and one of four roadside severity-distance classes. The overall accuracy of the roadside severity-object classification is 85.1%, while for the distance attribute it is 85.6%. The best average precision is achieved for safety barrier concrete class (0.98), while the worst AP is achieved for rockface class (0.72).

The efficacy of wildlife fences for keeping reindeer outside a chronic wasting disease risk area

Abstract Emerging wildlife diseases often comes with negative cultural and economic impact. Limiting disease spread is a recurrent goal and challenge, but the efficacy of various mitigation measures is rarely assessed. Chronic wasting disease (CWD) is a lethal disease among cervids that was discovered among alpine reindeer (Rangifer tarandus) in the Nordfjella mountain range of Norway in 2016. After de‐population, the entire range was fallowed to avoid re‐emergence from environmental pathogen reservoirs. This involved installing perimeter fences in the alpine areas in order to keep reindeer from adjacent populations outside of the CWD risk area, while other cervids (red deer Cervus elaphus, roe deer Capreolus capreolus and moose Alces alces) were likely to enter through the forested areas. We used camera trapping and surveillance reports to assess the efficacy of the perimeter fences. All four species of cervids were documented inside the CWD risk area. For reindeer, only 12.0% of observations were inside the CWD risk area, while this was 28.7% for the other cervids. The higher proportion of observations outside of the fenced area indicate that fences provided a barrier and lowered the number of crossings also of red deer, roe deer and moose. Fences do not provide complete barriers, and we discuss practical solutions for how to avoid ‘intruders’ entering a given area, such as maintenance at critical points (e.g. river and road crossings) and height of fences (e.g. species variation in jumping; deep snow) to uphold their desired effect. We argue that two fence lines with a buffer zone would be required when re‐introduction of reindeer are planned in the CWD risk area after fallowing, similar to what has been suggested for other wildlife diseases.

Određivanje trajnih deformacija savitljivih kolničkih konstrukcija pomoću metode konačnih elemenata

The unbound granular material used in flexible road pavements exhibits an elastoplastic behaviour under repetitive traffic loads. Permanent deformation occurring on pavement surface under traffic load is one of the main road pavement problems affecting road performance. Therefore, many permanent deformation models for calculating road pavement rutting have recently been developed by researchers. Most of these studies involve performance of dynamic triaxial tests. In this study, deformation characteristics of unbound granular materials are determined using the resonant column test. Then, instead of determining the total permanent deformation by summing up the calculated permanent deformations obtained in each pavement layer, dynamic 2D axisymmetric finite element analyses are performed for four different pavement cross sections to predict the total permanent deformation occurring on pavement surface under certain load cycles. The first modelled cross section of unbound granular material consists of natural aggregate. The base and/or subbase of remaining three cross sections consists of steel slag waste material. The permanent deformation versus load cycle is presented for four multi-layer road cross sections using semi logarithmic graphs. Finally, the permanent deformation model equation is developed for each pavement cross section using their fitting curves.

Refurbishment of the three river crossings that form Rochester Bridge in Kent, UK

Rochester Bridge consists of two road crossings and a services bridge across the tidal River Medway in Kent, UK. A challenging and comprehensive refurbishment of all three structures was completed safely and on time in 2020, to a very high quality and under budget. Furthermore, greenhouse gas emissions were fully offset by a new mixed woodland of 8000 trees and ongoing routine maintenance has been redesigned to achieve net-zero emissions. This paper describes the planning, procurement and delivery of the refurbishment, including its focus on quality, safety, sustainability, minimisation of disruption, ease of future maintenance and promotion of civil engineering.

Tower Road bascule bridge, Birkenhead, UK

The A554 Tower Road connects Wallasey and Birkenhead on the Wirral, north west England. The road crosses the entrance to Birkenhead docks from the River Mersey by way of a moveable bridge, which is of major strategic importance in the local highway network. The previous ‘A’ bridge, built in 1933, was a Scherzer type bascule lifting bridge with 34.4 m main span, one of four similar bridges that once existed along Tower Road. The deteriorating condition of the bridge, the increasing maintenance costs and the consequential impact of maintenance on the local economy resulted in a decision to replace the bridge with a modern, low-maintenance, lifting bridge. This paper provides the background to the bridge replacement project, including the reasons for replacement with a similar Scherzer bascule bridge. The civil, mechanical and electrical design is described and some of the significant issues encountered during implementation and commissioning are discussed. The new bridge has successfully created a local landmark, contributing to the client Wirral Council's vision for the redevelopment of this dockland area as part of the Wirral Waters regeneration project.

SMARTPHONE-BASED TRAFFIC NOISE MAPPING SYSTEM

Abstract. Noise pollution is one of the most serious environmental threats to human health. Noise is becoming more prevalent in urban areas, and it is having a negative impact on human health. The increase in noise is due to the increase in the number of vehicles that creates chaos over the road due to honking. Smart monitoring using is smartphones is required to reduce human dependency and monitor data efficiently to reduce logistical obstacles. A smartphone-based noise monitoring solution can handle the problem of monitoring noise at various traffic crossings in a metropolis. The topographical data, noise data, and noise prediction models are required for forecasting noise levels and showing them as maps. In the Indian city of Lucknow, the entire procedure is being performed by providing a map of 2D and 3D forms. The smartphone-based software tracks noise levels at three road crossings at three different times each day. The collected noise levels were calibrated against a standard noise metre to achieve correct noise levels for these sites. Following that, three noise environment types are chosen and mapped using open-source satellite images and conventional noise models through the web on the GIS platform. The anticipated noise levels on the maps were compared to recorded noise data from identical locations using a conventional noise metre for these three crossings and were found to be within 5.5 dB of accuracy. For 3D mapping, shadow height provides the Z value for point cloud DEM generation for 3D model for noise data of city of Lucknow.

ROAD NETWORK EXTRACTION USING GPS TRAJECTORIES BASED ON MORPHOLOGICAL AND SKELETONIZATION ALGORITHMS

Abstract. In this article, a method for road network extraction is proposed, based on GPS (Global Positioning System) trajectories. Unlike existing methods, it is not necessary to resample the GPS trajectories into a raster structure; instead, all analyses are based on the polylines that represent the GPS trajectories. Basically, a morphological analysis and a skeletonization technique are used by the proposed method. Two main steps of the method can be identified: the first step consists in generating an elongated polygon (that delimitates an elongated ribbon) that represents the selected road; and the second step aims at reconstructing the road network. The proposed method was evaluated based on four GPS trajectory datasets and the results obtained can be considered good, but some inconsistencies were noted, as for example: extraction failures occur in places with very low trajectory density (such as 3–4 trajectories); merging of very close and parallel roads; some road crossings that are close to one another have been merged into a single point. The proposed method was also compared with existing methods in the literature and the obtained results showed good consistency between them.

DATA-DRIVEN UNDERSTANDING OF AI-BASED TRAFFIC SIGNAL CONTROL AND ITS IMPLICATIONS ON LOW-CARBON URBAN TRANSPORT SYSTEMS

Emission by vehicles is one of the main sources causing the exceedance of the Air Pollution Index at roadside. Therefore, reducing emissions from vehicles in busy corridors has been a priority of the Government in improving roadside air quality. The existing pedestrian lights, which follow a predetermined signal timing for road crossings, are typical static traffic lights. The pushbutton has been added to improve the pedestrian crossing efficiency by rendering the green phase to the pedestrian as soon as possible. However, the current detection devices are not capable of streamlining the traffic flows and prioritizing pedestrians on the curb according to the actual needs. With the use of artificial intelligence (AI) techniques such as deep learning, this project can analyze the traffic conditions of a designated area, including the length of traffic queues and the number of pedestrians waiting at a crossroad. Our system can then manage traffic lights to facilitate efficient traffic flow between vehicles and pedestrians. In addition, the IoT technologies enable the system to collect traffic information for big data analysis and facilitate efficient traffic management. In the implementation stage of the project, a local field study of a crossroad with a school, bus stops, and shopping malls in the vicinity was conducted and relevant data for further analysis was collected. The results showed that the system could help to shorten traffic queues and pedestrian waiting time at the crossroad. The goals are to examine strategies in traffic signal control based on AI to reduce carbon footprint. The deliverables will assess how urban transport systems can reduce carbon emissions and adapt to climate change with a focus on traffic signal rationalization. It provides guidance, policy recommendations, and outlines research and information needs.

Object Detection using YOLO

Abstract: A technical assessment is always conducted prior to the installation of traffic signs at crosswalks, safety lanes, or even expanding areas. In these cases, using cameras to gather local photos and then analysing them is a valuable method. This paper describes a technique for detecting and tracking four types of vehicles: automobiles, buses, trucks, and motorcyclists, by analysing video footage of road crossings. The first findings of vehicle route accounting reveal that the technique is highly promising, with good outcomes in a number of scenarios, but much more study is needed to make these systems resistant against occlusions and other unforeseen events. Keywords: Deep Learning, Tracking, Multiple Objects Tracking, CNNs, YOLO, DeepSORT.

Implementation of Good Governance Principles in the Land Transportation Management Center

To achieve globalization and modernization, public organizations must implement good governance in order to respond to and meet community expectations. One of these expectations is land transportation management, which in Indonesia is handled by the Land Transportation Management Center (BPTD). Good governance should be implemented in BPTD in the hopes of improving performance and, as a result, community satisfaction, and resolving problems with ground transportation. BPTD still has a number of issues to deal with, including the state of the transportation infrastructure for road, urban, river and lake transportation and crossings, transportation safety, and administrative issues. This study examined how four principles of good governance have been implemented at BPTD: accountability, transparency, openness, and the rule of law. The study focused on BPTD Region IX in West Java Province, BPTD Region IX in Central Java Province, and DIY provinces. This study employed qualitative descriptive methods. According to the findings, BPTD has implemented the principles of good governance, but it still has room for improvement by sharpening its performance indicator targets, making LAKIP more widely known, measuring community satisfaction, and pursuing independent innovation.
 Keywords: transportation, good governance, accountability, transparency

Predicting the intention of distracted pedestrians at road crossings

Despite improvements to road safety, accidents involving pedestrians are still numerous, for example in the UK there were over 20,000 pedestrian casualties on public roads in 2019. One of the potential causal factors is pedestrian distraction. Therefore, this study aimed to predict pedestrian intention to cross the road under conditions of distraction (using phone maps, talking to another pedestrian, listening to music through headphones), by applying the Theory of Planned Behaviour (TPB) using an online survey. This also involved investigation of the impact of selected traffic characteristics (traffic density, vehicle speed) and crossing type (pelican, zebra, unmarked). The survey consisted of 72 questions and took approximately 15 min to complete. The results (N = 81) revealed that the TPB construct of perceived behavioural control (PBC) was a significant predictor of intention to cross the road while distracted across all scenarios. Furthermore, crossing type was a significant predictor of PBC across all scenarios, with marked crossings facilitating feelings of PBC. Findings suggest that high feelings of PBC, as measured through ease and confidence, are linked with stronger intention to cross the road while distracted. This understanding of pedestrian motivation can be used to help design interventions (such as auditory and visual pedestrian warnings) that prevent conflict between distracted pedestrians and vehicles. These interventions should target marked crossing types, whereby pedestrians are more likely to cross while distracted.

Effects of roads on small-mammal movements: Opportunities and risks of vegetation management on roadsides

Roads can block animal movement and reduce persistence of species living in road surroundings. Movement restrictions on local populations may even increase extinction risk of abundant small mammals. However, road verges (road managed area between the edge of the road and the beginning of private land) may provide refuge and corridors for small mammals when properly managed. Information on the effects of roads and roadside management on small-mammal movement is still scarce for low traffic roads (<20,000 vehicles per day) crossing well-preserved habitats. We aimed to fill this gap by comparing fine-scale movement patterns of wood mice (Apodemus sylvaticus) in a road and in a similar roadless area without management. Both areas consisted of a well-preserved Mediterranean agro-silvo pastoral system. We studied several movement patterns: road crossings, verge use, length, and direction of movement. Additionally, we assessed how roadside management, animals’ sex and residency status, season and microhabitat affect movement at the road area. At the roadless area, we defined a virtual road and verges at equivalent locations to the road area for comparison purposes. We gathered capture-mark-recapture data for two years to characterize movement patterns. Wood mice tended to avoid the road by crossing it less often and moving away from it more frequently than from equivalent locations in the roadless area. Wood mice used road verges more frequently than virtual verges and moved more often parallel to the road than to the virtual road. Road crossings were more frequent after firebreak openings (strips of mowed land) in surrounding areas and near taller shrubs. Also, males used road verges more often than females. Differences on several movement patterns between areas and their trends within the road area can be explained mainly by the presence of the road and roadside vegetation management (e.g., firebreaks openings). We suggest roadside vegetation management practices (e.g., avoid land mowing; maintain vegetation strips) to promote the role of verges as refuges and/or corridors for small mammals.