Search results for: road damage detection

Authors: Catherine Thompson, Maryam Jalali, Peter Hills

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The allocation of visual attention is critical when driving and anything that limits attention will have a detrimental impact on safety. Engaging in a secondary task reduces the amount of attention directed to the road because drivers allocate resources towards this task, leaving fewer resources to process driving-relevant information. Yet the dangers associated with a secondary task do not end when the driver returns their attention to the road. Instead, the attentional settings adopted to complete a secondary task may persist to the road, affecting attention, and therefore affecting driver performance. This 'attentional inertia' effect was investigated in the current work. Forty drivers searched for hazards in driving video clips while their eye-movements were recorded. At varying intervals they were instructed to attend to a secondary task displayed on a tablet situated to their left-hand side. The secondary task consisted of three separate computer games that induced horizontal, vertical, and random eye movements. Visual search and hazard detection in the driving clips were compared across the three conditions of the secondary task. Results showed that the layout of information in the secondary task, and therefore the allocation of attention in this task, had an impact on subsequent search in the driving clips. Vertically presented information reduced the wide horizontal spread of search usually associated with accurate driving and had a negative influence on the detection of hazards. The findings show the additional dangers of engaging in a secondary task while driving. The attentional inertia effect has significant implications for semi-autonomous and autonomous vehicles in which drivers have greater opportunity to direct their attention away from the driving task.

Keywords: attention, eye-movements, hazard perception, visual search

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Authors: Palash Dey, Sudip Talukdar

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In this work, a cross-breed approach is presented for obtaining both the amount of the damage intensity and location of damage existing in thin-walled members. This cross-breed approach is developed based on response surface methodology (RSM) and genetic algorithm (GA). Theoretical finite element (FE) model of cracked angle section thin walled curved beam has been linked to the developed approach to carry out trial experiments to generate response surface functions (RSFs) of free, forced and heterogeneous dynamic response data. Subsequently, the error between the computed response surface functions and measured dynamic response data has been minimized using GA to find out the optimum damage parameters (amount of the damage intensity and location). A single crack of varying location and depth has been considered in this study. The presented approach has been found to reveal good accuracy in prediction of crack parameters and possess great potential in crack detection as it requires only the current response of a cracked beam.

Keywords: damage parameters, finite element, genetic algorithm, response surface methodology, thin walled curved beam

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Authors: F. Ben Abdelghani, W. Maherezi

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Dredging operations generate, each year, a great quantity of marine sediments. These raw materials can not be used in road construction without a specific treatment process. Sediments suitability tests has shown that most of studied sediments are not suitable to be used in road construction. In order to improve their compacity and their mechanical performance, addition of a granular material is recommended. The use of a dredged sand, to improve the granular mixture containing sediments, allows a better management of the two types of dredge materials (sand and sediment). In this study, a new road material containing dredged marine sediments and dredged sand is formulated and treated by adding various binders. Mechanical performance investigation of different mixtures by measuring Proctor-IPI values and simple compressive strengths is realized.

Keywords: dredged sediments, suitability tests, road construction, hydraulic binder, mechanical performance

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Authors: Bivek Bhusal, Ana Legrand

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Detection of crop stress is one of the major applications of remote sensing in agriculture. Multiple studies have demonstrated the capability of remote sensing using Unmanned Aerial Vehicle (UAV)-based multispectral imagery for detection of plant stress, but none so far on Nitrogen (N) stress and PLH feeding stress on green beans. In view of its wide host range, geographical distribution, and damage potential, Potato leafhopper- Empoasca fabae (Harris) has been emerging as a key pest in several countries. Monitoring methods for potato leafhopper (PLH) damage, as well as the laboratory techniques for detecting Nitrogen deficiency, are time-consuming and not always easily affordable. A study was initiated to demonstrate if the multispectral sensor attached to a drone can detect PLH stress and N deficiency in beans. Small-plot trials were conducted in the summer of 2023, where cages were used to manipulate PLH infestation in green beans (Provider cultivar) at their first-trifoliate stage. Half of the bean plots were introduced with PLH, and the others were kept insect-free. Half of these plots were grown with the recommended amount of N, and the others were grown without N. Canopy reflectance was captured using a five-band multispectral sensor. Our findings indicate that drone imagery could detect stress due to a lack of N and PLH damage in beans.

Keywords: potato leafhopper, nitrogen, remote sensing, spectral reflectance, beans

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Authors: Serge Tshibangu, Turgay Celik, Zenzo Ncube

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Road crashes kill nearly over a million people every year, and leave millions more injured or permanently disabled. Various annual reports reveal that the percentage of fatal crashes due to fatigue/driver falling asleep comes directly after the percentage of fatal crashes due to intoxicated drivers. This percentage is higher than the combined percentage of fatal crashes due to illegal/Un-Safe U-turn and illegal/Un-Safe reversing. Although a relatively small percentage of police reports on road accidents highlights drowsiness and fatigue, the importance of these factors is greater than we might think, hidden by the undercounting of their events. Some scenarios show that these factors are significant in accidents with killed and injured people. Thus the need for an automatic drivers fatigue detection system in order to considerably reduce the number of accidents owing to fatigue.This research approaches the drivers fatigue detection problem in an innovative way by combining cues collected from both temporal analysis of drivers’ faces and environment. Monotony in driving environment is inter-related with visual symptoms of fatigue on drivers’ faces to achieve fatigue detection. Optical and infrared (IR) sensors are used to analyse the monotony in driving environment and to detect the visual symptoms of fatigue on human face. Internal cues from drivers faces and external cues from environment are combined together using machine learning algorithms to automatically detect fatigue.

Keywords: intelligent transportation systems, bayesian networks, yawning computing, machine learning algorithms

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Authors: Malleshappa Japagal, Srinivas Chitragar

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The use of waste plastic in pavement is becoming important alternative worldwide for disposal of plastic as well as to improve the stability of pavement and to meet out environmental issues. However, there are still concerns on fatigue and fracture resistance of Hot Mix Asphalt with the addition of plastic waste, (HMA-Plastic mixes) and moisture damage potential. The present study was undertaken to evaluate fracture resistance of HMA-Plastic mixes using semi-circular bending (SCB) test and moisture damage potential by Indirect Tensile strength (ITS) test using retained tensile strength (TSR). In this study, a dense graded asphalt mix with 19 mm nominal maximum aggregate size was designed in the laboratory using Marshall Mix design method. Aggregates were coated with different percentages of waste plastic (0%, 2%, 3% and 4%) by weight of aggregate and performance evaluation of fracture resistance and Moisture damage was carried out. The following parameters were estimated for the mixes: J-Integral or Jc, strain energy at failure, peak load at failure, and deformation at failure. It was found that the strain energy and peak load of all the mixes decrease with an increase in notch depth, indicating that increased percentage of plastic waste gave better fracture resistance. The moisture damage potential was evaluated by Tensile strength ratio (TSR). The experimental results shown increased TRS value up to 3% addition of waste plastic in HMA mix which gives better performance hence the use of waste plastic in road construction is favorable.

Keywords: hot mix asphalt, semi circular bending, marshall mix design, tensile strength ratio

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Authors: Gou-Moon Choi, Woo-Young Jung, Chan-Young Yune

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Recently, the natural disaster has increased worldwide. In Korea, the damage to life and property caused by a typhoon, heavy rain, heavy snow, and an extreme wind also increases every year. Among natural disasters, the frequency and the strength of wind have increased because sea surface temperature has risen due to the increase of the average temperature of the Earth. In the case of extreme wind disaster, it is impossible to control or reduce the occurrence, and the recovery cost always exceeds the damage cost. Therefore, quantitative estimation of the damage cost for extreme wind needs to be established beforehand to install proactive countermeasures. In this study, the damage cost for private properties was analyzed based on the data for the past 10 years in Korea. The damage cost curve was also suggested for the metropolitan cities and provinces. The result shows the possibility for the regional application of the damage cost curve because the damage cost of the regional area is estimated based on the cost of cities and provinces.

Keywords: damage cost, extreme wind, natural disaster, private property

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Authors: Yanjie Zhu, André Jesus, Irwanda Laory

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Structural Health Monitoring (SHM), involving data acquisition, data interpretation and decision-making system aim to continuously monitor the structural performance of civil infrastructures under various in-service circumstances. The main value and purpose of SHM is identifying damages through data interpretation system. Research on SHM has been expanded in the last decades and a large volume of data is recorded every day owing to the dramatic development in sensor techniques and certain progress in signal processing techniques. However, efficient and reliable data interpretation for damage detection under environmental variations is still a big challenge. Structural damages might be masked because variations in measured data can be the result of environmental variations. This research reports a novel method based on single-channel Blind Signal Separation (BSS), which extracts environmental effects from measured data directly without any prior knowledge of the structure loading and environmental conditions. Despite the successful application in audio processing and bio-medical research fields, BSS has never been used to detect damage under varying environmental conditions. This proposed method optimizes and combines Ensemble Empirical Mode Decomposition (EEMD), Principal Component Analysis (PCA) and Independent Component Analysis (ICA) together to separate structural responses due to different loading conditions respectively from a single channel input signal. The ICA is applying on dimension-reduced output of EEMD. Numerical simulation of a truss bridge, inspired from New Joban Line Arakawa Railway Bridge, is used to validate this method. All results demonstrate that the single-channel BSS-based method can recover temperature effects from mixed structural response recorded by a single sensor with a convincing accuracy. This will be the foundation of further research on direct damage detection under varying environment.

Keywords: damage detection, ensemble empirical mode decomposition (EEMD), environmental variations, independent component analysis (ICA), principal component analysis (PCA), structural health monitoring (SHM)

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Authors: M. Abou-Amouna, A. Radwan, L. Al-kuwari, A. Hammuda, K. Al-Khalifa

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There is growing concern over increasing incidences of road accidents and consequent loss of human life in Qatar. In light to the future planned event in Qatar, World Cup 2022; Qatar should put into consideration the future deaths caused by road accidents, and past trends should be considered to give a reasonable picture of what may happen in the future. Qatar roads should be arranged and paved in a way that accommodate high capacity of the population in that time, since then there will be a huge number of visitors from the world. Qatar should also consider the risk issues of road accidents raised in that period, and plan to maintain high level to safety strategies. According to the increase in the number of road accidents in Qatar from 1995 until 2012, an analysis of elements affecting and causing road accidents will be effectively studied. This paper aims to identify and criticize the factors that have high effect on causing road accidents in the state of Qatar, and predict the total number of road accidents in Qatar 2022. Alternative methods are discussed and the most applicable ones according to the previous researches are selected for further studies. The methods that satisfy the existing case in Qatar were the multiple linear regression model (MLR) and artificial neutral network (ANN). Those methods are analyzed and their findings are compared. We conclude that by using MLR the number of accidents in 2022 will become 355,226 accidents, and by using ANN 216,264 accidents. We conclude that MLR gave better results than ANN because the artificial neutral network doesn’t fit data with large range varieties.

Keywords: road safety, prediction, accident, model, Qatar

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Authors: Eric Mensah, Carlos Mensah

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The road maintenance backlogs created as a result of deferred maintenance especially in developing countries has caused considerable deterioration of many road assets. This is usually due to difficulties encountered in selecting and prioritising maintainable roads based on objective criteria rather than some political or other less important criteria. In order to ensure judicious use of limited resources for road maintenance, five factors were identified as the most important criteria for road management within the study area. This was based on the judgements of 40 experts. The results were further used to develop weightings using the Multi-Criteria Decision Process (MCDP) to analyse and select road alternatives according to maintenance goal. Using Geographical Information Systems (GIS), maintainable roads were grouped using the Jenk’s natural breaks to allow for further prioritised in order of importance for display on a dashboard of maps, charts, and tables. This reduces the problems of subjective maintenance and road selections, thereby reducing wastage of resources and easing the maintenance process through an object organised spatial decision support system.

Keywords: decision support, geographical information systems, multi-criteria decision process, weighted sum

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Authors: Latha Nataraj, Todd Henry, Micheal Wallock, Asha Hall, Christine Hatter, Babak Anasori, Yury Gogotsi

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Multifunctional composites with enhanced strength and toughness for superior damage tolerance are essential for advanced aerospace and military applications. Detection of structural changes prior to visible damage may be achieved by incorporating fillers with tunable properties such as two-dimensional (2D) nanomaterials with high aspect ratios and more surface-active sites. While 2D graphene with large surface areas, good mechanical properties, and high electrical conductivity seems ideal as a filler, the single-atomic thickness can lead to bending and rolling during processing, requiring post-processing to bond to polymer matrices. Lately, an emerging family of 2D transition metal carbides and nitrides, MXenes, has attracted much attention since their discovery in 2011. Metallic electronic conductivity and good mechanical properties, even with increased polymer content, coupled with hydrophilicity make MXenes a good candidate as a filler material in polymer composites and exceptional as multifunctional damage indicators in composites. Here, we systematically study MXene-based (Ti₃C₂) coated on glass fibers for fiber reinforced polymer composite for self-sensing using microscopy and micromechanical testing. Further testing is in progress through the investigation of local variations in optical, acoustic, and thermal properties within the damage sites in response to strain caused by mechanical loading.

Keywords: damage sensing, fiber composites, MXene, self-sensing

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Authors: Arefeh Lotfi, Mahdi Babaei, Ayda Mashhadizadeh, Samira Nikpour, Morteza Bagheri

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The main objective of this study is to investigate the key factors in accidents’ severity at rail-road level crossings. The data required for this study is obtained from both accident and inventory database of Iran Railways during 2009-2015. The Ordered Probit model is developed using SPSS software to identify the significant factors in the accident severity at rail-road level crossings. The results show that 'train speed', 'vehicle type' and 'weather' are the most important factors affecting the severity of the accident. The results of these studies assist to allocate resources in the right place. This paper suggests mandating the regulations to reduce train speed at rail-road level crossings in bad weather conditions to improve the safety of rail-road level crossings.

Keywords: rail-road level crossing, ordered probit model, accidents’ severity, significant factors

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Authors: David Nkurunziza, Rahman Tafahomi

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The population growth rate of the city of Kigali is increasing annually. In 1960 the population was six thousand, in 1990 it became two hundred thousand and is supposed to be 4 to 5 million incoming twenty years. With the increase in the residents living in the city of Kigali, there is also a need for an increase in social and economic infrastructures connected by the road networks to serve the residents effectively. A road network is a route that connects people to their needs and has to facilitate people to reach the social and economic facilities easily. This research analyzed the social and economic aspects of three selected roads networks passing through all three districts of the city of Kigali, whose center is the city center roundabout, thorough evaluation of the proximity of the social and economic facilities to the road network. These road networks are the city center to nyabugogo to karuruma, city center to kanogo to Rwanda to kicukiro center to Nyanza taxi park, and city center to Yamaha to kinamba to gakinjiro to kagugu health center road network. This research used a methodology of identifying and quantifying the social and economic facilities within a limited distance of 300 meters along each side of the road networks. Social facilities evaluated are the health facilities, education facilities, institution facilities, and worship facilities, while the economic facilities accessed are the commercial zones, industries, banks, and hotels. These facilities were evaluated and graded based on their distance from the road and their value. The total scores of each road network per kilometer were calculated and finally, the road networks were ranked based on their percentage score per one kilometer—this research was based on field surveys and interviews to collect data with forms and questionnaires. The analysis of the data collected declared that the road network from the city center to Yamaha to kinamba to gakinjiro to the kagugu health center is the best performer, the second is the road network from the city center to nyabugogo to karuruma, while the third is the road network from the city center to kanogo to rwandex to kicukiro center to nyaza taxi park.

Keywords: social economical aspect, road network functionality, urban road network, economic and social facilities

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Authors: Rania Alshikhe, Vinita Jindal

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Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

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Authors: Wei Li, Tuo Yang

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In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

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Authors: Elbert S. Moyon, Edsel Matt O. Morales, Jaymer M. Jayoma, Kent C. Espejon, Jayson C. Dollete, Mark Phil B. Pacot

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This research paper focuses on the potential of using Web-GIS technology in prioritizing farm-to-market road projects by the Philippines’ Department of Agriculture (DA). The study aimed to explore the benefits of Web-GIS in addressing the limitations faced by the DA in terms of Farm to Market Road profiling and project prioritization, which include a lack of access to updated data, limited spatial analysis capabilities, and difficulties in sharing information between stakeholders. The research methodology involves a comprehensive literature review and a case study of a Web-GIS application developed for the DA, which was used to profile and prioritize farm-to-market road projects in the Philippines. The results showed that the Web-GIS technology provides the DA with an effective tool for analyzing and visualizing data, which can help in profiling and prioritizing road projects based on various criteria such as economic, social, and environmental impacts. The study also showed that Web-GIS technology could help in reducing the time and effort required for road project prioritization and improve communication between stakeholders.

Keywords: GIS, web application, farm-to-market road, FMR prioritization, Django, GeoServer

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Authors: Pedro Pablo Ramírez Sánchez, Alassane Ballé Ndiaye, Roberto Rendeiro Martín-Cejas

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The aim of this paper is to analyse the different environmental policies adopted in Europe for car emissions, to comment on some of the possible perverse effects generated and point out these policies which are considered more efficient under the environmental perspective. This paper is focused on passenger cars as this category is the most significant in road transport. The utility of this research lies in this being the first step or basis to improve and optimise actual policies. The methodology applied in this paper refers to a comparative analysis from a practical and theoretical point of view of European environmental policies in road transport. This work describes an overview of the road transport industry in Europe pointing out some relevant aspects such as the contribution of road transport to total emissions and the vehicle fleet in Europe. Additionally, we propose a brief practice guide with the combined policies in order to optimise their aim.

Keywords: air quality, climate change, emission, environment, perverse effect, road transport, tax policy

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Authors: Ami Nkumbuye

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Background: Every year 1.3 million people die due to Road crashes, according to the Global status report. Road crashes remain the greatest killer aged between 15-29 years. Young people are paying an unacceptable price for their own safer mobility. 23,498 students attending class daily from home crossing the roads of 3 districts Kigali and Southern province is showing a similar trend with 40320 cross road daily. As most of them don't have any idea about the safety, they should have when they are crossing roads and traffic rules and signs as well. Despite the high number of mortality related to road crashes in Rwanda, we don't have any approved calendar to teach young people road safety as the most affected age group. Objective: The objective of this study was to identify the causes of road crashes and the outcome of victims after being involved in road crashes over a period of two years, from January 2020 to December 2021, in Huye district and Kigali City. Methods: A retrospective descriptive study with open questions and then data analysis, students were identified from 15 schools in Kigali City and Southern Province and through the Local Action Project supported by Global Youth Coalition for Road Safety and Youth for Road Safety (YOURS), students asked about the cause of road crashes through open and closed question and data analyzed. Result: There were 354 students from 15 schools: 198 males and 156 females. Their age ranged from 10 to 25 years. The commonest cause of road crashes among students attending schools daily was: high speed, lack of education on safe behavior on the road, drinking and driving, and poor road infrastructures, with 47%, 32%, 13% and 8 %, respectively. The hospital admission after road crashes for the victims was 32.3%. In most scenes where road crashes occur, students report that they didn't see any person who could provide post-crash care until the ambulance came, in some cases, resulted in bad outcomes for the victims after road crashes. Conclusion: This study revealed that high speed and lack of education n road safety are the major cause of road crashes among young people in Rwanda. If local Non-Governmental Organization and Decision makers work on these issues like never before, we can see a decrease in road crash among young people and adult as well. We would like to give a recommendation to two institutions: the first is the Rwanda National Police Traffic department to set 30km/m as the maximum speed limit in City and near schools. The second is for the Ministry of Education to put Road Safety and Post Crash Care curricula in both Primary and Secondary schools.

Keywords: road safety, post-crash care, young people, students

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Authors: Han Bai, Tong Zhang, Lemei Yu, Doudou Xie, Liang Zhao

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Road transition design on freeway tunnel entrance and exit is one vital factor in realizing smooth transition and improving traveling safety for vehicles. The goal of this research is to develop a horizontal road transition design tool that considers the transition technology of traffic capacity consistency to explore its accommodation mechanism. The influencing factors of capacity are synthesized and a modified capacity calculation model focusing on the influence of road width and lateral clearance is developed based on the VISSIM simulation to calculate the width of road transition sections. To keep the traffic capacity consistency, the right side of the transition section of the tunnel entrance and exit is divided into three parts: front arc, an intermediate transition section, and end arc; an optimization design on each transition part is conducted to improve the capacity stability and horizontal alignment transition. A case study on the Panlong Tunnel in Ji-Qing freeway illustrates the application of the tool.

Keywords: traffic safety, road transition, freeway tunnel, traffic capacity

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Authors: Zhiyong Zheng, Xu Li, Liang Huang, Zhengliang Sun, Jianhua Xu

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Yaw angle plays a significant role in many vehicle safety applications, such as collision avoidance and lane-keeping system. Although the estimation of the yaw angle has been extensively studied in existing literature, it is still the main challenge to simultaneously achieve a reliable and cost-effective solution in complex urban environments. This paper proposes a multi-stage learning framework to estimate the yaw angle with a monocular camera, which can deal with the challenge in a more reliable manner. In the first stage, an efficient road detection network is designed to extract the road region, providing a highly reliable reference for the estimation. In the second stage, a variational auto-encoder (VAE) is proposed to learn the distribution patterns of road regions, which is particularly suitable for modeling the changing patterns of yaw angle under different driving maneuvers, and it can inherently enhance the generalization ability. In the last stage, a gated recurrent unit (GRU) network is used to capture the temporal correlations of the learned patterns, which is capable to further improve the estimation accuracy due to the fact that the changes of deflection angle are relatively easier to recognize among continuous frames. Afterward, the yaw angle can be obtained by combining the estimated deflection angle and the road direction stored in a roadway map. Through effective multi-stage learning, the proposed framework presents high reliability while it maintains better accuracy. Road-test experiments with different driving maneuvers were performed in complex urban environments, and the results validate the effectiveness of the proposed framework.

Keywords: gated recurrent unit, multi-stage learning, reliable estimation, variational auto-encoder, yaw angle

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Authors: Tzong-Ying Hao, Mohammad T. Rahmani

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This article presents the structural health monitoring (SHM) method based on changes in wave traveling times (wave method) within a layered 1-D shear beam model of structure. The wave method measures the velocity of shear wave propagating in a building from the impulse response functions (IRF) obtained from recorded data at different locations inside the building. If structural damage occurs in a structure, the velocity of wave propagation through it changes. The wave method analysis is performed on the responses of Torre Central building, a 9-story shear wall structure located in Santiago, Chile. Because events of different intensity (ambient vibrations, weak and strong earthquake motions) have been recorded at this building, therefore it can serve as a full-scale benchmark to validate the structural health monitoring method utilized. The analysis of inter-story drifts and the Fourier spectra for the EW and NS motions during 2010 Chile earthquake are presented. The results for the NS motions suggest the coupling of translation and torsion responses. The system frequencies (estimated from the relative displacement response of the 8th-floor with respect to the basement from recorded data) were detected initially decreasing approximately 24% in the EW motion. Near the end of shaking, an increase of about 17% was detected. These analysis and results serve as baseline indicators of the occurrence of structural damage. The detected changes in wave velocities of the shear beam model are consistent with the observed damage. However, the 1-D shear beam model is not sufficient to simulate the coupling of translation and torsion responses in the NS motion. The wave method is proven for actual implementation in structural health monitoring systems based on carefully assessing the resolution and accuracy of the model for its effectiveness on post-earthquake damage detection in buildings.

Keywords: Chile earthquake, damage detection, earthquake response, impulse response function, shear beam model, shear wave velocity, structural health monitoring, torre central building, wave method

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Authors: Tim D. Sass

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The experience of engineers and architects practicing today is typically limited to current building code requirements and modern construction methods and materials. However, many cities have a mix of new and old buildings with many buildings constructed over one hundred years ago when building codes and construction methods were much different. When a brick building sustains damage, a structural engineer is often hired to determine the cause of damage as well as determine the necessary repairs. Forensic studies of dozens of brick buildings shows an appreciation of historical building methods and materials is needed to correctly identify the cause of damage and design an appropriate repair. Damage on an older, brick building can be mistakenly attributed to storms or seismic events when the real source of the damage is deficient original construction. Assessing and remediating damaged brickwork on older brick buildings requires an understanding of the original construction, an understanding of older repair methods, and, an understanding of current building code requirements.

Keywords: brick, damage, deterioration, facade

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Authors: Stanislovas Buteliauskas, Aušrius Juozapavičius

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City road transport contributes significantly to climate change, and the ongoing world urbanization is only increasing the problem. The paper describes a city planning concept minimizing the number of vehicles on the roads while increasing overall mobility. This becomes possible by utilizing a recently invented two-level road junction with a unique property of serving both as an intersection of uninterrupted traffic and an easily accessible transport hub capable of accumulating private vehicles, and therefore becoming an especially effective park-and-ride solution, and a logistics or business center. Optimized layouts of city road infrastructure, living and work areas, and major roads are presented. The layouts are suitable both for the development of new cities as well as for the expansion of existing ones. Costs of the infrastructure and a positive impact on climate are evaluated in comparison to current city growth patterns.

Keywords: congestion, city infrastructure, park-and-ride, road junctions

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Authors: Okyu Kwon, Dongho Kang, Byungsik Kim, Seungkwon Jung

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We propose a technique to measure the impact of loss of traffic function in a particular area to surrounding areas. The proposed method is applied to the city of Seoul, which is the capital of South Korea, with a population of about ten million. Based on the actual road network in Seoul, we construct an abstract road network between 1kmx1km grid cells. The link weight of the abstract road network is re-adjusted considering traffic volume measured at several survey points. On the modified abstract road network, we evaluate the traffic vulnerability by calculating a network measure of betweenness centrality (BC) for every single grid cells. This study analyzes traffic impacts caused by road dysfunction due to heavy rainfall in urban areas. We could see the change of the BC value in all other grid cells by calculating the BC value once again when the specific grid cell lost its traffic function, that is, when the node disappeared on the grid-based road network. The results show that it is appropriate to use the sum of the BC variation of other cells as the influence index of each lattice cell on traffic. This research was supported by a grant (2017-MOIS31-004) from Fundamental Technology Development Program for Extreme Disaster Response funded by Korean Ministry of Interior and Safety (MOIS).

Keywords: vulnerability, road network, beweenness centrality, heavy rainfall, road impact

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Authors: H. Benmoussa, A. A. El Kalam, A. Ait Ouahman

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The design and implementation of intrusion detection systems (IDS) remain an important area of research in the security of information systems. Despite the importance and reputation of the current intrusion detection systems, their efficiency and effectiveness remain limited as they should include active defense approach to allow anticipating and predicting intrusions before their occurrence. Consequently, they must be readapted. For this purpose we suggest a new generation of distributed intrusion detection system based on preventive detection approach and using intelligent and mobile agents. Our architecture benefits from mobile agent features and addresses some of the issues with centralized and hierarchical models. Also, it presents advantages in terms of increasing scalability and flexibility.

Keywords: Intrusion Detection System (IDS), preventive detection, mobile agents, distributed architecture

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Authors: Hossam M. Moftah, Aboul Ella Hassanien

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In the recent years the importance of automatic traffic control has increased due to the traffic jams problem especially in big cities for signal control and efficient traffic management. Traffic counting as a kind of traffic control is important to know the road traffic density in real time. This paper presents a fast and robust traffic counting system using different image processing techniques. The proposed system is composed of the following four fundamental building phases: image acquisition, pre-processing, object detection, and finally counting the connected objects. The object detection phase is comprised of the following five steps: subtracting the background, converting the image to binary, closing gaps and connecting nearby blobs, image smoothing to remove noises and very small objects, and detecting the connected objects. Experimental results show the great success of the proposed approach.

Keywords: traffic counting, traffic management, image processing, object detection, computer vision

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Authors: Anjula Negi, D. T. V. Raghu Ramaswamy, Rajneesh Sareen

Abstract:

Road infrastructure is emphatically one of the top most critical infrastructure to the Indian economy. Road network in the country of around 3.3 million km is the second largest in the world. Nationwide statistics released by Ministry of Road, Transport and Highways reveal that every minute an accident happens and one death every 3.7 minutes. This reported scale in terms of safety is a matter of grave concern, and economically represents a national loss of 3% to the GDP. Union Budget 2016-17 has allocated USD 12 billion annually for development and strengthening of roads, an increase of 56% from last year. Thus, highlighting the importance of roads as critical infrastructure. National highway alone represent only 1.7% of the total road linkages, however, carry over 40% of traffic. Further, trends analysed from 2002 -2011 on national highways, indicate that in less than a decade, a 22 % increase in accidents have been reported, but, 68% increase in death fatalities. Paramount inference is that accident severity has increased with time. Over these years many measures to increase road safety, lessening damage to physical assets, reducing vulnerabilities leading to a build-up for resilient road infrastructure have been taken. In the context of national highway development program, policy makers proposed implementation of around 20 % of such road length on PPP mode. These roads were taken up on high-density traffic considerations and for qualitative implementation. In order to understand resilience impacts and safety parameters, enshrined in various PPP concession agreements executed with the private sector partners, such highway specific projects would be appraised. This research paper would attempt to assess such safety measures taken and the possible reasons behind an increase in accident severity through these PPP case study projects. Delving further on safety features to understand policy measures adopted in these cases and an introspection on reasons of severity, whether an outcome of increased speeds, faulty road design and geometrics, driver negligence, or due to lack of discipline in following lane traffic with increased speed. Assessment exercise would study these aspects hitherto to PPP and post PPP project structures, based on literature review and opinion surveys with sectoral experts. On the way forward, it is understood that the Ministry of Road, Transport and Highway’s estimate for strengthening the national highway network is USD 77 billion within next five years. The outcome of this paper would provide an understanding of resilience measures adopted, possible options for accessible and safe road network and its expansion to policy makers for possible policy initiatives and funding allocation in securing critical infrastructure.

Keywords: national highways, policy, PPP, safety

Procedia PDF Downloads 233

Authors: Khalid A. Alsaif, Mosaad A. Foda

Abstract:

The primary objective of this study is to develop the first round of road traffic noise maps for Riyadh City using Geographical Information Systems (GIS) and software LimA 7810 predictor. The road traffic data were measured or estimated as accurate as possible in order to obtain reliable noise maps. Meanwhile, the attributes of the roads and buildings are automatically exported from GIS. The simulation results at some chosen locations are validated by actual field measurements, which are obtained by a system that consists of a sound level meter, a GPS receiver and a database to manage the measured data. The results show that the average error between the predicted and measured noise levels is below 3.0 dB.

Keywords: noise pollution, road traffic noise, LimA predictor, GIS

Procedia PDF Downloads 383

Authors: Sarim Ahmad

Abstract:

The Single Cell Gel Electrophoresis Assay (SCGE, known as comet assay) is a potential, uncomplicated, sensitive and state-of-the-art technique for quantitating DNA damage at individual cell level and repair from in vivo and in vitro samples of eukaryotic cells and some prokaryotic cells, being popular in its widespread use in various areas including human biomonitoring, genotoxicology, ecological monitoring and as a tool for research into DNA damage or repair in different cell types in response to a range of DNA damaging agents, cancer risk and therapy. The method involves the encapsulation of cells in a low-melting-point agarose suspension, lysis of the cells in neutral or alkaline (pH > 13) conditions, and electrophoresis of the suspended lysed cells, resulting in structures resembling comets as observed by fluorescence microscopy; the intensity of the comet tail relative to the head reflects the number of DNA breaks. The likely basis for this is that loops containing a break lose their supercoiling and become free to extend towards the anode. This is followed by visual analysis with staining of DNA and calculating fluorescence to determine the extent of DNA damage. This can be performed by manual scoring or automatically by imaging software. The assay can, therefore, predict an individual’s tumor sensitivity to radiation and various chemotherapeutic drugs and further assess the oxidative stress within tumors and to detect the extent of DNA damage in various cancerous and precancerous lesions of oral cavity.

Keywords: comet assay, single cell gel electrophoresis, DNA damage, early detection test

Procedia PDF Downloads 275

Authors: Ammar Maziz, Mostapha Tarfaoui, Said Rechak

Abstract:

The high mechanical performance of composite pipes can be adversely affected by their low resistance to impact loads. Loads in dynamic origin are dangerous and cause consequences on the operation of pipes because the damage is often not detected and can affect the structural integrity of composite pipes. In this work, an advanced 3-D finite element (FE) model, based on the use of intralaminar damage models was developed and used to predict damage under low-velocity impact. The performance of the numerical model is validated with the confrontation with the results of experimental tests. The results show that at low impact energy, the damage happens mainly by matrix cracking and delamination. The model capabilities to simulate the low-velocity impact events on the full-scale composite structures were proved.

Keywords: composite materials, low velocity impact, FEA, dynamic behavior, progressive damage modeling

Procedia PDF Downloads 146