Search results for: mixed traffic condition

Authors: Min Jung Kim

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Fe-(9, 19, 28, 37) wt%Cr alloys were corroded at 700 and 800 °C for 70 h under 1 atm of N₂, 1 atm of N₂/3.2%H₂O-mixed gas, and 1 atm of N₂/3.1%H₂O/2.42%H₂S-mixed gas. The corrosion rate of Fe-9Cr alloy increased with the addition of H₂O and increased further with the addition of H₂S in N₂/H₂O gas. Fe-9Cr alloy was non-protective in all gas types. In contrast, Fe-(19, 28, 37) wt%Cr alloys were protective in N₂ and N₂/H₂O-mixed gas because of the formation of the Cr₂O₃ layer. They were, however, non-protective in N₂/H₂O/H₂S-mixed gas because sulfidation dominated, forming the outer FeS layer and the inner Cr₂S₃ layer containing some FeCr₂S₄.

Keywords: Fe-(9, 19, 28, 37) wt%Cr alloys, corrosion, sulfidation, FeS

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Authors: Sayed Abdul Rahman Sadaat, Nsenda Lukumwena

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Traffic congestion is a worldwide issue, especially in developing countries. This is also the case of Afghanistan, especially in Kabul-the capital city, whose rapid population growth makes it the fifth fastest growing city in the world. Traffic congestion affects not only the mobility of people and goods but also the air quality that leads to numerous deaths (3000 people) every year. There are many factors that contribute to traffic congestion. The insufficiency and inefficiency of public transportation system along with the increase of private vehicles can be considered among the most important contributing factors. This paper addresses the traffic congestion and attempts to suggest possible solutions that can help improve the current public transportation system in Kabul. To this end, the methodology used in this paper includes field work conducted in Kabul city and literature review. The outcome suggests that improving the public transportation system is likely to contribute to the reduction of traffic congestion and the improvement of air quality, thereby reducing the number of death related to air quality.

Keywords: air quality, Kabul, Afghanistan, public transportation system, improvements, traffic congestion

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Authors: Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh

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Traffic congestion has become a severe worldwide problem, affecting everyday life, fuel consumption, time, and air pollution. The primary causes of these issues are inadequate transportation infrastructure, poor traffic signal management, and rising population. Traffic flow forecasting is one of the essential and effective methods in urban congestion and traffic management, which has attracted the attention of researchers. With the development of technology, undeniable progress has been achieved in existing methods. However, there is a possibility of improvement in the extraction of temporal and spatial features to determine the importance of traffic flow sequences and extraction features. In the proposed model, we implement the convolutional neural network (CNN) and long short-term memory (LSTM) deep learning models for mining nonlinear correlations and their effectiveness in increasing the accuracy of traffic flow prediction in the real dataset. According to the experiments, the results indicate that implementing Conv-LSTM networks increases the productivity and accuracy of deep learning models for traffic flow prediction.

Keywords: deep learning algorithms, intelligent transportation systems, spatiotemporal features, traffic flow prediction

Procedia PDF Downloads 138

Authors: Muhammad Nouman, Fahad Tiwana, Muhammad Irfan, Mohsin Tiwana

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Traffic congestion has been increasing significantly in major metropolitan areas as a result of increased motorization, urbanization, population growth and changes in the urban density. Traffic congestion compromises efficiency of transport infrastructure and causes multiple traffic concerns; including but not limited to increase of travel time, safety hazards, air pollution, and fuel consumption. Traffic management has become a serious challenge for federal and provincial governments, as well as exasperated commuters. Effective, flexible, efficient and user-friendly traffic information/database management systems characterize traffic conditions by making use of traffic counts for storage, processing, and visualization. While, the emerging data collection technologies continue to proliferate, its accuracy can be guaranteed through the comparison of observed data with the manual handheld counters. This paper presents the design of tablet based manual traffic counting application and framework for development of traffic database management system for Pakistan. The database management system comprises of three components including traffic counting android application; establishing online database and its visualization using Google maps. Oracle relational database was chosen to develop the data structure whereas structured query language (SQL) was adopted to program the system architecture. The GIS application links the data from the database and projects it onto a dynamic map for traffic conditions visualization. The traffic counting device and example of a database application in the real-world problem provided a creative outlet to visualize the uses and advantages of a database management system in real time. Also, traffic data counts by means of handheld tablet/ mobile application can be used for transportation planning and forecasting.

Keywords: manual count, emerging data sources, traffic information quality, traffic surveillance, traffic counting device, android; data visualization, traffic management

Procedia PDF Downloads 172

Authors: Esther Burkitt

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Background: Evidence is mounting that mixed emotions can be experienced simultaneously in different ways across the lifespan. Four types of patterns of simultaneously mixed emotions (sequential, prevalent, highly parallel, and inverse types) have been identified in middle childhood and adolescence. Moreover, the recognition of these experiences tends to develop firstly when children consider peers rather than the self. This evidence from children and adolescents is based on examining the presence of experiences specified in adulthood. The present study, therefore, applied an exhaustive coding scheme to investigate whether children experience types of previously unidentified simultaneous mixed emotional experiences. Methodology: One hundred and twenty children (60 girls) aged 7 years 1 month - 9 years 2 months (X=8 years 1 month; SD = 10 months) were recruited from mainstream schools across the UK. Two age groups were formed (youngest, n = 61, 7 years 1 month- 8 years 1 months: oldest, n = 59, 8 years 2 months – 9 years 2 months) and allocated to one of two conditions hearing vignettes describing happy and sad mixed emotion events in age and gender-matched protagonist or themselves. Results: Loglinear analyses identified new types of flexuous, vertical, and other experiences along with established sequential, prevalent, highly parallel, and inverse types of experience. Older children recognised more complex experiences other than the self-condition. Conclusion: Several additional types of simultaneously mixed emotions are recognised in middle childhood. The theoretical relevance of simultaneous mixed emotion processing in childhood is considered, and the potential utility of the findings in emotion assessments is discussed.

Keywords: emotion, childhood, self, other

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Authors: Maria Ezziani, Rabie Zine, Amine Amar, Ilhame Kissani

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This paper introduces a predictive model for urban transportation engineering, which is vital for efficient traffic management. Utilizing comprehensive datasets and advanced statistical techniques, the model accurately forecasts travel times by considering temporal variations and traffic dynamics. Machine learning algorithms, including regression trees and neural networks, are employed to capture sequential dependencies. Results indicate significant improvements in predictive accuracy, particularly during peak hours and holidays, with the incorporation of traffic flow and speed variables. Future enhancements may integrate weather conditions and traffic incidents. The model's applications range from adaptive traffic management systems to route optimization algorithms, facilitating congestion reduction and enhancing journey reliability. Overall, this research extends beyond travel time estimation, offering insights into broader transportation planning and policy-making realms, empowering stakeholders to optimize infrastructure utilization and improve network efficiency.

Keywords: predictive analytics, traffic flow, travel time estimation, urban transportation, machine learning, traffic management

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Authors: M. Taha, Hala H. Zayed, T. Nazmy, M. Khalifa

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Recently, traffic monitoring has attracted the attention of computer vision researchers. Many algorithms have been developed to detect and track moving vehicles. In fact, vehicle tracking in daytime and in nighttime cannot be approached with the same techniques, due to the extreme different illumination conditions. Consequently, traffic-monitoring systems are in need of having a component to differentiate between daytime and nighttime scenes. In this paper, a HSV-based day/night detector is proposed for traffic monitoring scenes. The detector employs the hue-histogram and the value-histogram on the top half of the image frame. Experimental results show that the extraction of the brightness features along with the color features within the top region of the image is effective for classifying traffic scenes. In addition, the detector achieves high precision and recall rates along with it is feasible for real time applications.

Keywords: day/night detector, daytime/nighttime classification, image classification, vehicle tracking, traffic monitoring

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity

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Authors: Theresa Steiner, Markus Pajones, Christian Haider

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Traffic is being induced by companies due to their economic behavior. Basically, two different types of traffic occur at company sites: freight traffic and commuting traffic. Due to the fact that these traffic types are connected to each other in different kinds, an integrated approach to manage them is useful. Mobility management is a proved method for companies, to handle the traffic processes caused by their business activities. According to recent trend analysis in Austria, the freight traffic as well as the individual traffic, as part of the commuting traffic, will continue to increase. More traffic jams, as well as negative environmental impacts, are expected impacts for the future. Mobility management is a tool to control the traffic behavior with the scope to reduce emissions and other negative effects which are caused by traffic. Until now, mobility management is mainly used for optimizing commuting traffic without taking the freight logistics processes into consideration. However, the method of mobility management can be used to improve the freight traffic area of a company as well. The focus of this paper will be particularly laid on analyzing to what extent companies are already using mobility management to influence not only the commuting traffic they produce but also their processes of freight logistics. A further objective is to acquire knowledge about the motivating factors which persuade companies to introduce and apply mobility management. Additionally, advantages and disadvantages of this tool will be defined as well as limitations and factors of success, with a special focus on freight logistics, will be depicted. The first step of this paper is to conduct a literature review on the issue of mobility management with a special focus on freight logistics processes. To compare the theoretical findings with the practice, interviews, following a structured interview guidline, with mobility managers of different companies in Upper Austria will be undertaken. A qualitative analysis of these surveys will in a first step show the motivation behind using mobility management to improve traffic processes and how far this approach is already being used to especially influence the freight traffic of the companies. An evaluation to what extent the method of mobility management is already being approached at Upper Austrian companies to regulate freight logistics processes will be one outcome of this publication. Furthermore, the results of the theoretical and practical analysis will reveal not only the possibilities but also the limitations of using mobility management to influence the processes of freight logistics.

Keywords: freight logistics processes, freight traffic, mobility management, passenger traffic

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Authors: Chun-Ying Lee, Mei-Wen Wu, Li-Yi Cheng, Chiang-Ho Cheng

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This research studies the electroplating of zinc coating in the zinc chloride bath mixed with supercritical CO2. The sodium fluoride (NaF) was used as the bath additive to change the structure and property of the coating, and therefore the roughness and corrosion resistance of the zinc coating was investigated. The surface characterization was performed using optical microscope (OM), X-ray diffractometer (XRD), and α-step profilometer. Moreover, the potentiodynamic polarization measurement in 3% NaCl solution was employed in the corrosion resistance evaluation. Because of the emulsification of the electrolyte mixed in Sc-CO2, the electroplated zinc produced the coating with smoother surface, smaller grain, better throwing power and higher corrosion resistance. The main role played by the NaF was to reduce the coating’s roughness and grain size. In other words, the CO2 mixed with the electrolyte under the supercritical condition performed the similar function as brighter and leveler in zinc electroplating to enhance the throwing power and corrosion resistance of the coating.

Keywords: supercritical CO2, zinc-electroplating, sodium fluoride, electroplating

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Authors: Shiri Elisheva Decktor, Sharon Hornstein

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Highway merges and unmarked junctions are key components in any urban road network, which can act as bottlenecks and create traffic disruption. Inefficient highway merges may trigger traffic instabilities such as stop-and-go waves, pose safety conditions and lead to longer journey times. These phenomena occur spontaneously if the average vehicle density exceeds a certain critical value. This study focuses on modeling the traffic using a microscopic traffic flow model. A hybrid traffic model, which combines human-driven and controlled vehicles is assumed. The controlled vehicles obey different driving policies when approaching the merge, or in the vicinity of other vehicles. We developed a co-simulation model in SUMO (Simulation of Urban Mobility), in which the human-driven cars are modeled using the IDM model, and the controlled cars are modeled using a dedicated controller. The scenario chosen for this study is a closed track with one merge and one exit, which could be later implemented using a scaled infrastructure on our lab setup. This will enable us to benchmark the results of this study obtained in simulation, to comparable results in similar conditions in the lab. The metrics chosen for the comparison of the performance of our algorithm on the overall traffic conditions include the average speed, wait time near the merge, and throughput after the merge, measured under different travel demand conditions (low, medium, and heavy traffic).

Keywords: highway merges, traffic modeling, SUMO, driving policy

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Authors: B. Karabuluter, O. Karaduman

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Traffic management and traffic planning are important issues, especially in big cities. Due to the increase of personal vehicles and the physical constraints of urban roads, the problem of transportation especially in crowded cities over time is revealed. This situation reduces the living standards, and it can put human life at risk because the vehicles such as ambulance, fire department are prevented from reaching their targets. Even if the city planners take these problems into account, emergency planning and traffic management are needed to avoid cases such as traffic congestion, intersections, traffic jams caused by traffic accidents or roadworks. In this study, in smart traffic management issues, proposed solutions using intelligent vehicles acting in cooperation with urban roads are examined. Traffic management is becoming more difficult due to factors such as fatigue, carelessness, sleeplessness, social behavior patterns, and lack of education. However, autonomous vehicles, which remove the problems caused by human weaknesses by providing driving control, are increasing the success of practicing the algorithms developed in city traffic management. Such intelligent vehicles have become an important solution in urban life by using 'swarm intelligence' algorithms and cooperative driving methods to provide traffic flow, prevent traffic accidents, and increase living standards. In this study, studies conducted in this area have been dealt with in terms of traffic jam, intersections, regulation of traffic flow, signaling, prevention of traffic accidents, cooperation and communication techniques of vehicles, fleet management, transportation of emergency vehicles. From these concepts, some taxonomies were made out of the way. This work helps to develop new solutions and algorithms for cities where intelligent vehicles that can perform cooperative driving can take place, and at the same time emphasize the trend in this area.

Keywords: intelligent traffic management, cooperative driving, smart driving, urban road, swarm intelligence, connected vehicles

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Authors: Praveen Vayalamkuzhi, Veeraragavan Amirthalingam

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Studies on safety on highways are becoming the need of the hour as over 400 lives are lost every day in India due to road crashes. In order to evaluate the factors that lead to different levels of crash severity, it is necessary to investigate the level of safety of highways and their relation to crashes. In the present study, an attempt is made to identify the factors that contribute to road crashes and to quantify their effect on the severity of road crashes. The study was carried out on a four-lane divided rural highway in India. The variables considered in the analysis includes components of horizontal alignment of highway, viz., straight or curve section; time of day, driveway density, presence of median; median opening; gradient; operating speed; and annual average daily traffic. These variables were considered after a preliminary analysis. The major complexities in the study are the heterogeneous traffic and the speed variation between different classes of vehicles along the highway. To quantify the impact of each of these factors, statistical analyses were carried out using Logit model and also negative binomial regression. The output from the statistical models proved that the variables viz., horizontal components of the highway alignment; driveway density; time of day; operating speed as well as annual average daily traffic show significant relation with the severity of crashes viz., fatal as well as injury crashes. Further, the annual average daily traffic has significant effect on the severity compared to other variables. The contribution of highway horizontal components on crash severity is also significant. Logit models can predict crashes better than the negative binomial regression models. The results of the study will help the transport planners to look into these aspects at the planning stage itself in the case of highways operated under heterogeneous traffic flow condition.

Keywords: geometric design, heterogeneous traffic, road crash, statistical analysis, level of safety

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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Fatalities of Road Traffic Crashes (RTCs) on rural roads are usually higher than that on urban roads. The likelihood of traffic accidents may increase with the presence of factors that are associated with the rural type of community such as long-distance, road type, road geometry (e.g., curves and steepens), poor lighting, terrain, obstacles (e.g., animals crossing, boulders or tree branches), heavy truck traffic, weather conditions, and road flaws. Most of these factors are present on the rural roads of Oman. As many cities in Oman are surrounded by mountains and connected by rural roads, this is of great concern. In this paper, the causes of traffic crashes on rural roads in Oman are analyzed. The fatality rate of traffic deaths on rural roads is compared with the fatality rate on urban roads for different regions in Oman. Statistical data and police reports show that the leading cause of RTCs and deaths on rural roads is vehicle speeding, especially on long-distance roads. It is shown that crashes on rural roads result in higher fatalities than crashes on urban roads. In comparison to speed, the numbers of RTCs and deaths that resulted from other causes are small.

Keywords: causes of traffic crashes, road safety, road traffic crash, rural roads

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Authors: Serban Stere, Stefan Burciu

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The challenging and continuously growing competition in the urban freight transport market emphasizes the need for optimal planning of transportation processes in terms of identifying the solution of consolidating traffic flows in congested urban areas. The aim of the present paper is to present the mathematical framework and propose a methodology of combining urban traffic flows between the distribution centers located at the boundary of a congested urban area. The three scenarios regarding traffic flow between consolidation centers that are taken into consideration in the paper are based on the same characteristics of traffic flows. The scenarios differ in terms of the accessibility of the four consolidation centers given by the infrastructure, the connections between them, and the possibility of consolidating traffic flows for one or multiple destinations. Also, synthetical indicators will allow us to compare the scenarios considered and chose the indicated for our distribution system.

Keywords: distribution system, single and multiple destinations, urban consolidation centers, traffic flow consolidation schemes

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Authors: Aodai Abdul-Illah Ismail

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Even though the dramatic progress that has been made in traffic safety, but still millions of peoples get killed or injured as a result of traffic crashes, besides the huge amount of economic losses due to these crashes. So traffic safety continues to be one of the most important serious issues worldwide, and it affects everyone who uses the road network system, whether you drive, walk, cycle, or push a pram. One of the most important sides that offers promise for further progress in relation to traffic safety is related to risky groups (special population groups) who may have higher potential to be involved in accidents. Traffic safety needs of risky groups are different from each other and also from the average population. Due to the various limitations between these special groups from each other and from the average population, it is not possible to address all the issues –at the same time- raising the importance ranking among the other safety issues. This paper explains a procedure used to identify the most critical traffic safety issues of five risky groups, which include younger, older and female drivers, people with disabilities and school aged children. Multi criteria used in selecting the critical issues because the single criteria is not sufficient. Highway safety professionals were surveyed to obtain the ranking of importance among the risky groups and then to develop the final ranking among issues by applying weight for each of the criteria.

Keywords: traffic safety, risky groups, old drivers, young drivers

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Authors: Van Nhan Nguyen, Harald Holone

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Over the past few years, a lot of research has been conducted to bring Automatic Speech Recognition (ASR) into various areas of Air Traffic Control (ATC), such as air traffic control simulation and training, monitoring live operators for with the aim of safety improvements, air traffic controller workload measurement and conducting analysis on large quantities controller-pilot speech. Due to the high accuracy requirements of the ATC context and its unique challenges, automatic speech recognition has not been widely adopted in this field. With the aim of providing a good starting point for researchers who are interested bringing automatic speech recognition into ATC, this paper gives an overview of possibilities and challenges of applying automatic speech recognition in air traffic control. To provide this overview, we present an updated literature review of speech recognition technologies in general, as well as specific approaches relevant to the ATC context. Based on this literature review, criteria for selecting speech recognition approaches for the ATC domain are presented, and remaining challenges and possible solutions are discussed.

Keywords: automatic speech recognition, asr, air traffic control, atc

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Authors: Khaled A. Alsaif, Mosaad A. Foda

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The present work aims at development of traffic noise maps for Riyadh City using the software Lima. Road traffic data were estimated or measured as accurate as possible in order to obtain consistent noise maps. The predicted noise levels at some selected sites 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 maps show that noise levels remain over 50 dBA and can exceed 70 dBA at the nearside of major roads and highways.

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

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Authors: Mohammed Bakhit Kashoob, Mohammed Salim Al-Maashani, Ahmed Abdullah Al-Marhoon

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Traffic calming measures are different design features or strategies used to reduce the speed of a traveling vehicle on a particular road. These calming measures are common on rural roads of Oman. Some of these measures are road speed limits, vertical deflections, horizontal deflections, and road signs. In general, vertical deflections such as rumble strips, road studs (cat’s eye), speed tables, and speed humps are widely used. In this paper, as vehicle speeding is a major cause of road traffic crashes and high fatalities in Oman, the effectiveness of existing traffic calming measures at current locations on rural roads is assessed. The study was conducted on the rural roads of Dhofar Governorate, which is located in the south of Oman. A special focus is given to the calming measures implemented on the mountain roads of Dhofar. It is shown that vertical deflection calming measures are effective in reducing vehicle speed to 20 to 40 kph, depending on the vertical deflection type and spacing. Calming measures are also proposed at locations with a high probability of traffic crashes based on the number of traffic crashes at these locations, road type, and road geometry.

Keywords: road safety, rural roads, speed, traffic calming measures, traffic crash

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Authors: Manju, Praveen Aggarwal

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Clayey soil is considered weakest subgrade soil from civil engineering point of view under moist condition. These swelling soils attract and absorb water and losses their strength. Certain inherent properties of these clayey soils need modification for their bulk use in the construction of highways/runways pavements and embankments, etc. In this paper, results of clayey subgrade modified with cement stabilizer is presented. Investigation includes evaluation of specific gravity, Atterberg’s limits, grain size distribution, maximum dry density, optimum moisture content and CBR value of the clayey soil and cement treated clayey soil. A series of proctor compaction and CBR tests (un-soaked and soaked) are carried out on clayey soil and clayey soil mixed with cement stabilizer in 2%, 4% & 6% percentages to the dry weight of soil. In CBR test, under soaked condition best results are obtained with 6% of cement. However, the difference between the CBR value by addition of 4% and 6% cement is not much. Therefore from economical consideration addition of 4% cement gives the best result after soaking period of 90 days.

Keywords: clayey soil, cement, maximum dry density, optimum moisture content, California bearing ratio

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Authors: Ahmad Mansoor Stanikzai, Yoshitaka Kajita

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This research is a very essential towards transportation planning of Kabul New City. In this research, the travel demand of Kabul metropolitan area (Existing and Kabul New City) are evaluated for three different target years (2015, current, 2025, mid-term, 2040, long-term). The outcome of this study indicates that, though currently the vehicle volume is less the capacity of existing road networks, Kabul city is suffering from daily traffic congestions. This is mainly due to lack of transportation management, the absence of proper policies, improper public transportation system and violation of traffic rules and regulations by inhabitants. On the other hand, the observed result indicates that the current vehicle to capacity ratio (VCR) which is the most used index to judge traffic status in the city is around 0.79. This indicates the inappropriate traffic condition of the city. Moreover, by the growth of population in mid-term (2025) and long-term (2040) and in the case of no development in the road network and transportation system, the VCR value will dramatically increase to 1.40 (2025) and 2.5 (2040). This can be a critical situation for an urban area from an urban transportation perspective. Thus, by introducing high-capacity public transportation system and the development of road network in Kabul New City and integrating these links with the existing city road network, significant improvements were observed in the value of VCR.

Keywords: Afghanistan, Kabul new city, planning, policy, urban transportation

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Authors: Bojan Najdenov, Danco Davcev

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Reduction of traffic congestions and the effects of pollution and waste of resources that come with them has been a big challenge in the past decades. Having reliable systems to facilitate the process of modeling and prediction of traffic conditions would not only reduce the environmental pollution, but will also save people time and money. Social networks play big role of people’s lives nowadays providing them means of communicating and sharing thoughts and ideas, that way generating huge knowledge bases by crowdsourcing. In addition to that, crowdsourcing as a concept provides mechanisms for fast and relatively reliable data generation and also many services are being used on regular basis because they are mainly powered by the public as main content providers. In this paper we present the Social-NETS-Traffic-Control System (SNTCS) that should serve as a facilitator in the process of modeling and prediction of traffic congestions. The main contribution of our system is to integrate data from social networks as Twitter and also implements a custom created crowdsourcing subsystem with which users report traffic conditions using an android application. Our first experience of the usage of the system confirms that the integrated approach allows easy extension of the system with other social networks and represents a very useful tool for traffic control.

Keywords: traffic, congestion reduction, crowdsource, social networks, twitter, android

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Authors: Masahiro Miyaji

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When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

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Authors: Pradeepa Teegala, Ramreddy Chitteti

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This article analyzes the mixed convection flow of chemically reacting micropolar fluid over a truncated cone embedded in non-Darcy porous medium with convective boundary condition. In addition, heat generation/absorption and Joule heating effects are taken into consideration. The similarity solution does not exist for this complex fluid flow problem, and hence non-similarity transformations are used to convert the governing fluid flow equations along with related boundary conditions into a set of nondimensional partial differential equations. Many authors have been applied the spectral quasi-linearization method to solve the ordinary differential equations, but here the resulting nonlinear partial differential equations are solved for non-similarity solution by using a recently developed method called the spectral quasi-linearization method (SQLM). Comparison with previously published work on special cases of the problem is performed and found to be in excellent agreement. The effect of pertinent parameters namely, Biot number, mixed convection parameter, heat generation/absorption, Joule heating, Forchheimer number, chemical reaction, micropolar and magnetic field on physical quantities of the flow are displayed through graphs and the salient features are explored in detail. Further, the results are analyzed by comparing with two special cases, namely, vertical plate and full cone wherever possible.

Keywords: chemical reaction, convective boundary condition, joule heating, micropolar fluid, mixed convection, spectral quasi-linearization method

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Authors: Manoj Kumar

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Routing protocols have a central role in any mobile ad hoc network (MANET). There are many routing protocols that exhibit different performance levels in different scenarios. In this paper, we compare AODV, DSDV, DSR, and ZRP routing protocol in mobile ad hoc networks to determine the best operational conditions for each protocol. We analyze these routing protocols by extensive simulations in OPNET simulator and show how to pause time and the number of nodes affect their performance. In this study, performance is measured in terms of control traffic received, control traffic sent, data traffic received, sent data traffic, throughput, retransmission attempts.

Keywords: AODV, DSDV, DSR, ZRP

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Authors: Mohammad Farid

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In this paper, we introduce and study an explicit iterative method based on hybrid extragradient method to approximate a common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup in Hilbert space. Further, we prove that the sequence generated by the proposed iterative scheme converge strongly to the common solution of generalized mixed equilibrium problem and fixed point problem for a nonexpansive semigroup. This common solution is the unique solution of a variational inequality problem and is the optimality condition for a minimization problem. The results presented in this paper are the supplement, extension and generalization of the previously known results in this area.

Keywords: generalized mixed equilibrium problem, fixed-point problem, nonexpansive semigroup, variational inequality problem, iterative algorithms, hybrid extragradient method

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Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

Abstract:

In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

Procedia PDF Downloads 124

Authors: Y. Lasbet, A. L. Boukhalkhal, K. Loubar

Abstract:

The study of mixed convection is, usually, focused on the straight channels in which the onset of the mixed convection is well defined as function of the ratio between Grashof number and Reynolds number, Gr/Re. This is not the case for a complex channel wherein the mixed convection is not sufficiently examined in the literature. Our paper focuses on the study of the mixed convection in a complex geometry in which our main contribution reveals that the critical value of the ratio Gr/Re for the onset of the mixed convection increases highly in the type of geometry contrary to the straight channel. Furthermore, the accentuated secondary flow in this geometry prevents the thermal stratification in the flow and consequently the buoyancy driven becomes negligible. To perform these objectives, a numerical study in complex geometry for several values of the ratio Gr/Re with prescribed wall heat flux (H2), was realized by using the CFD code.

Keywords: complex geometry, heat transfer, laminar flow, mixed convection, Nusselt number

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Authors: Kay Thinzar Phu, Lwin Lwin Oo

Abstract:

In an intelligent transport system and advanced driver assistance system, the developing of real-time traffic sign detection and recognition (TSDR) system plays an important part in recent research field. There are many challenges for developing real-time TSDR system due to motion artifacts, variable lighting and weather conditions and situations of traffic signs. Researchers have already proposed various methods to minimize the challenges problem. The aim of the proposed research is to develop an efficient and effective TSDR in real time. This system proposes an adaptive thresholding method based on RGB color for traffic signs detection and new features for traffic signs recognition. In this system, the RGB color thresholding is used to detect the blue and yellow color traffic signs regions. The system performs the shape identify to decide whether the output candidate region is traffic sign or not. Lastly, new features such as termination points, bifurcation points, and 90’ angles are extracted from validated image. This system uses Myanmar Traffic Sign dataset.

Keywords: adaptive thresholding based on RGB color, blue color detection, feature extraction, yellow color detection

Procedia PDF Downloads 280