Search results for: traffic density measurement

Authors: Sudipta Ghorai, Ossama Salem

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Pavement maintenance, repair, and rehabilitation (MRR) processes may have considerable environmental impacts due to traffic disruptions associated with work zones. The simulation models in use to predict the emission of work zones were mostly static emission factor models (SEFD). SEFD calculates emissions based on average operation conditions e.g. average speed and type of vehicles. Although these models produce accurate results for large-scale planning studies, they are not suitable for analyzing driving conditions at the micro level such as acceleration, deceleration, idling, cruising, and queuing in a work zone. The purpose of this study is to prepare a comprehensive work zone environmental assessment (WEA) framework to calculate the emissions caused due to disrupted traffic; by integrating traffic microsimulation tools with emission models. This will help highway officials to assess the benefits of accelerated construction and opt for the most suitable TMP not only economically but also from an environmental point of view.

Keywords: accelerated construction, pavement MRR, traffic microsimulation, congestion, emissions

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Authors: Gabriele Borg, Alexei De Bono, Charlie Abela

Abstract:

There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale.

Keywords: Big Data, vehicular traffic, traffic management, mobile data patterns

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Authors: Adinarayana Badveeti, Mohammad Shafi Mir

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In Srinagar City, in India, traffic congestion is a condition on transport networks that occurs as use increases and is characterized by slower speeds, longer trip times, and increased vehicular queuing. Traffic congestion is conventionally measured using indicators such as roadway level-of-service, the Travel Time Index and their variants. Several measures have been taken in order to counteract congestion like road pricing, car pooling, improved traffic management, etc. While new road construction can temporarily relieve congestion in the longer term, it simply encourages further growth in car traffic through increased travel and a switch away from public transport. The full paper report, on which this abstract is based, aims to provide policymakers and technical staff with the real-time data, conceptual framework and guidance on some of the engineering tools necessary to manage congestion in such a way as to reduce its overall impact on individuals, families, communities, and societies dynamic, affordable, liveable and attractive urban regions will never be free of congestion. Road transport policies, however, should seek to manage congestion on a cost-effective basis with the aim of reducing the burden that excessive congestion imposes upon travellers and urban dwellers throughout the urban road network.

Keywords: traffic congestion, modeling, traffic management, travel time index

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Authors: Christos Karolemeas, Avgi Vassi, Georgia Christodoulopoulou

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Although the past decades, planning a cycle network became an inseparable part of all transportation plans, there is still a lot of room for improvement in the way planning is made, in order to create safe and direct cycling networks that gather the parameters that positively influence one's decision to cycle. The aim of this article is to study, evaluate and visualize the bikeability of cities. This term is often used as the 'the ability of a person to bike' but this study, however, adopts the term in the sense of bikeability as 'the ability of the urban landscape to be biked'. The methodology used included assessing cities' accessibility by cycling, based on international literature and corresponding walkability methods and the creation of a 'bikeability index'. Initially, a literature review was made to identify the factors that positively affect the use of bicycle infrastructure. Those factors were used in order to create the spatial index and quantitatively compare the city network. Finally, the bikeability index was applied in two case studies: two Greek municipalities that, although, they have similarities in terms of land uses, population density and traffic congestion, they are totally different in terms of geomorphology. The factors suggested by international literature were (a) safety, (b) directness, (c) comfort and (d) the quality of the urban environment. Those factors were quantified through the following parameters: slope, junction density, traffic density, traffic speed, natural environment, built environment, activities coverage, centrality and accessibility to public transport stations. Each road section was graded for the above-mentioned parameters, and the overall grade shows the level of bicycle accessibility (low, medium, high). Each parameter, as well as the overall accessibility levels, were analyzed and visualized through Geographic Information Systems. This paper presents the bikeability index, its' results, the problems that have arisen and the conclusions from its' implementation through Strengths-Weaknesses-Opportunities-Threats analysis. The purpose of this index is to make it easy for researchers, practitioners, politicians, and stakeholders to quantify, visualize and understand which parts of the urban fabric are suitable for cycling.

Keywords: accessibility, cycling, green spaces, spatial data, urban environment

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Authors: Devineni Vijay Bhaskar, Yendluri Raja

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We recommend a model for traffic sign detection stranded on Convolutional Neural Networks (CNN). We first renovate the unique image into the gray scale image through with support vector machines, then use convolutional neural networks with fixed and learnable layers for revealing and understanding. The permanent layer can reduction the amount of attention areas to notice and crop the limits very close to the boundaries of traffic signs. The learnable coverings can rise the accuracy of detection significantly. Besides, we use bootstrap procedures to progress the accuracy and avoid overfitting problem. In the German Traffic Sign Detection Benchmark, we obtained modest results, with an area under the precision-recall curve (AUC) of 99.49% in the group “Risk”, and an AUC of 96.62% in the group “Obligatory”.

Keywords: convolutional neural network, support vector machine, detection, traffic signs, bootstrap procedures, precision-recall curve

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Authors: Kumar Manoj, Ramesh Kumar, Kumari Arti, Kumar Prashant

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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 analyses these routing protocols by extensive simulations in OPNET simulator and show that how 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, data traffic sent, throughput, retransmission attempts.

Keywords: MANET, AODV, DSDV, DSR, ZRP

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Authors: Supriya H. S., Chandrakala B. M.

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Deep learning based models have been recently successful adoption for network traffic prediction. However, training a deep learning model for various prediction tasks is considered one of the critical tasks due to various reasons. This research work develops Multi-Layer Hybrid Network (MLHN) for network traffic prediction and analysis; MLHN comprises the three distinctive networks for handling the different inputs for custom feature extraction. Furthermore, an optimized and efficient parameter-tuning algorithm is introduced to enhance parameter learning. MLHN is evaluated considering the “Big Data Challenge” dataset considering the Mean Absolute Error, Root Mean Square Error and R^2as metrics; furthermore, MLHN efficiency is proved through comparison with a state-of-art approach.

Keywords: MLHN, network traffic prediction

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Authors: Andrey V. Timofeev, Dmitry V. Egorov

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This paper presents development results of usage of C-OTDR monitoring systems for rail traffic management. The C-OTDR method is based on vibrosensitive properties of optical fibers. Analysis of Rayleigh backscattering radiation parameters changes which take place due to microscopic seismoacoustic impacts on the optical fiber allows to determine seismoacoustic emission source positions and to identify their types. This approach proved successful for rail traffic management (moving block system, weigh- in-motion system etc).

Keywords: C-OTDR systems, moving block-sections, rail traffic management, Rayleigh backscattering, weigh-in-motion

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Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

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Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

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Authors: Nor Fazlina Iryani Abdul Hamid, Mohamad Khatim Hasan

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Evolution of software quality measurement has been started since McCall introduced his quality model in year 1977. Starting from there, several software quality models and software quality measurement methods had emerged but none of them focused on telecommunication industry. In this paper, the implementation of software quality measurement system for telecommunication industry was compulsory to accommodate the rapid growth of telecommunication industry. The quality value of the telecommunication related software could be calculated using this system by entering the required parameters. The system would calculate the quality value of the measured system based on predefined quality metrics and aggregated by referring to the quality model. It would classify the quality level of the software based on Net Satisfaction Index (NSI). Thus, software quality measurement system was important to both developers and users in order to produce high quality software product for telecommunication industry.

Keywords: software quality, quality measurement, quality model, quality metric, net satisfaction index

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Authors: Gabriela V. Angeles Perez, Jose Castillejos Lopez, Araceli L. Reyes Cabello, Emilio Bravo Grajales, Adriana Perez Espinosa, Jose L. Quiroz Fabian

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Road traffic accidents are among the principal causes of traffic congestion, causing human losses, damages to health and the environment, economic losses and material damages. Studies about traditional road traffic accidents in urban zones represents very high inversion of time and money, additionally, the result are not current. However, nowadays in many countries, the crowdsourced GPS based traffic and navigation apps have emerged as an important source of information to low cost to studies of road traffic accidents and urban congestion caused by them. In this article we identified the zones, roads and specific time in the CDMX in which the largest number of road traffic accidents are concentrated during 2016. We built a database compiling information obtained from the social network known as Waze. The methodology employed was Discovery of knowledge in the database (KDD) for the discovery of patterns in the accidents reports. Furthermore, using data mining techniques with the help of Weka. The selected algorithms was the Maximization of Expectations (EM) to obtain the number ideal of clusters for the data and k-means as a grouping method. Finally, the results were visualized with the Geographic Information System QGIS.

Keywords: data mining, k-means, road traffic accidents, Waze, Weka

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Authors: Shuo Huang, Huomiao Guo, Wenrui Huang

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In navigation channels located in coasts and estuaries as the waterways connecting coastal water to ports or harbors, density-induced flow often exist due to the density-gradient or gravity gradient as the results of mixing between fresh water from coastal rivers and saline water in the coasts. The density-induced flow often carries sediment transport into navigation channels and causes sediment depositions in the channels. As a result, expensive dredging may need to maintain the water depth required for navigation. In our study, we conduct a series of experiments to investigate the characteristics of density-induced flow in the estuarine navigation channels under different density gradients. Empirical equations between density flow and salinity gradient were derived. Effects of coastal structures for regulating navigation channel on density-induced flow have also been investigated. Results will be very helpful for improving the understanding of the characteristics of density-induced flow in estuarine navigation channels. The results will also provide technical support for cost-effective waterway regulation and management to maintain coastal and estuarine navigation channels.

Keywords: density flow, estuarine, navigation channel, structure

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Authors: Shiva Kumar G.

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The present study is to know the level of noises emanated from vehicles in intersections located in urban areas using Sound Level Meter and the possibility of reducing noise levels through traffic flow optimization. The main objective is to study traffic noise level of the Intersections located at on-going metro construction activities and which are away from metro construction activities. To compare traffic noise level between stop phase, go phase and drive phase at the Intersections. To study the effect of traffic noise level of directional movement of traffic and variation in noise level during day and night times. The range of Noise level observed at intersections is between 60 to 105 decibel. The noise level of stop and drive phases were minimum and almost same where go phase had maximum noise level. By comparing noise level of directional movement of traffic, it has been noticed that Vijayanagar intersection has no significant difference in their noise level and all other intersection has a significant difference in their noise level. By comparing noise level of stop, go and drive phase it has been noticed that there was a significant difference in noise level during peak hours compared to off-peak hour. By comparing noise level between Metro and Non-Metro construction activity intersections it has been noticed that there was a significant difference in noise level. By comparing noise level during day and night times, significant differences in noise level were observed at all intersections.

Keywords: noise, metro and non-metro intersections, traffic flow optimization, stop-go and drive phase

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Authors: Hong Geng, Zaiyu Fan

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With the acceleration of urbanization and motorization in China, the scale of cities and the travel distance of residents are constantly expanding, and the number of cars is continuously increasing, so the urban traffic problem is more and more serious. Traffic congestion, environmental pollution, energy consumption, travel safety and direct interference between traffic and other urban activities are increasingly prominent problems brought about by motorized development. This not only has a serious impact on the lives of the residents but also has a major impact on the healthy development of the city. The paper found that, in order to solve the development of motorization, a number of problems will arise; urban planning and traffic planning and design in residential planning often take into account the development of motorized traffic but neglects the demand for street life. This kind of planning has resulted in the destruction of the traditional communication space of the residential area, the pollution of noise and exhaust gas, and the potential safety risks of the residential area, which has disturbed the previously quiet and comfortable life of the residential area, resulting in the inconvenience of residents' life and the loss of street vitality. Based on these facts, this paper takes a residential area in Wuhan as the research object, through the actual investigation and research, from the perspective of micro-transformation analysis, combined with the concept of traffic micro-reconstruction governance. And research puts forward the residential traffic optimization strategies such as strengthening the interaction and connection between the residential area and the urban street system, street traffic classification and organization.

Keywords: micro-transformation, residential traffic, residents demand, traffic microcirculation

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Authors: Lennon Furtado, Sandro Oliveira

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The importance of an effective measurement program lies in the ability to control and predict what can be measured. Thus, the measurement program has the capacity to provide bases in decision-making to support the interests of an organization. Therefore, it is only possible to apply for an effective measurement program with a team of software engineers well trained in the measurement area. However, the literature indicates that are few computer science courses that have in their program the teaching of the software measurement process. And even these, generally present only basic theoretical concepts of said process and little or no measurement in practice, which results in the student's lack of motivation to learn the measurement process. In this context, according to some experts in software process improvements, one of the most used approaches to maintaining the motivation and commitment to software process improvements program is the use of the gamification. Therefore, this paper aims to present a proposal of teaching the measurement process by gamification. Which seeks to improve student motivation and performance in the assimilation of tasks related to software measurement, by incorporating elements of games into the practice of measurement process, making it more attractive for learning. And as a way of validating the proposal will be made a comparison between two distinct groups of 20 students of Software Quality class, a control group, and an experiment group. The control group will be the students that will not make use of the gamification proposal to learn software measurement process, while the experiment group, will be the students that will make use of the gamification proposal to learn software measurement process. Thus, this paper will analyze the objective and subjective results of each group. And as objective result will be analyzed the student grade reached at the end of the course, and as subjective results will be analyzed a post-course questionnaire with the opinion of each student about the teaching method. Finally, this paper aims to prove or refute the following hypothesis: If the gamification proposal to teach software measurement process does appropriate motivate the student, in order to attribute the necessary competence to the practical application of the measurement process.

Keywords: education, gamification, software measurement process, software engineering

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Authors: Nasrin Bakhshizadeh, Ashkan Forootan

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A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

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Authors: Gabriele Borg, Alexei Debono, Charlie Abela

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There on a constant rise in the availability of high volumes of data gathered from multiple sources, resulting in an abundance of unprocessed information that can be used to monitor patterns and trends in user behaviour. Similarly, year after year, Malta is also constantly experiencing ongoing population growth and an increase in mobilization demand. This research takes advantage of data which is continuously being sourced and converting it into useful information related to the traffic problem on the Maltese roads. The scope of this paper is to provide a methodology to create a custom dataset (MalTra - Malta Traffic) compiled from multiple participants from various locations across the island to identify the most common routes taken to expose the main areas of activity. This use of big data is seen being used in various technologies and is referred to as ITSs (Intelligent Transportation Systems), which has been concluded that there is significant potential in utilising such sources of data on a nationwide scale. Furthermore, a series of traffic prediction graph neural network models are conducted to compare MalTra to large-scale traffic datasets.

Keywords: graph neural networks, traffic management, big data, mobile data patterns

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Authors: Babu Veeregowda, Rongfang Liu

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The current traffic impact assessment methodology and environmental quality review process for approval of land development project are conventional, stagnant, and one-dimensional. The environmental review policy and procedure lacks in providing the direction to regulate or seek alternative land uses and sizes that exploits the existing or surrounding elements of built environment (‘4 D’s’ of development – Density, Diversity, Design, and Distance to Transit) or smart growth principles which influence the travel behavior and have a significant effect in reducing vehicular traffic. Additionally, environmental review policy does not give directions on how to incorporate urban planning into the development in ways such as incorporating non-motorized roadway elements such as sidewalks, bus shelters, and access to community facilities. This research developed a methodology to optimize the mix of land uses and sizes using the heuristic optimization process to minimize the auto dependency development and to meet the interests of key stakeholders. A case study of Willets Point Mixed Use Development in Queens, New York, was used to assess the benefits of the methodology. The approved Willets Point Mixed Use project was based on maximum envelop of size and land use type allowed by current conventional urban renewal plans. This paper will also evaluate the parking accumulation for various land uses to explore the potential for shared parking to further optimize the mix of land uses and sizes. This research is very timely and useful to many stakeholders interested in understanding the benefits of integrated land uses and its development.

Keywords: traffic impact, mixed use, optimization, trip generation

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Authors: Shoji Mori, Kunito Okuyama

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Annular two phase flow is encountered in many industrial equipments, including flow near nuclear fuel rods in boiling water reactor (BWR). Especially, disturbance waves play important roles in the pressure drop, the generation of entrainments, and the dryout of the liquid film. Therefore, it is important to clarify the behavior of disturbance waves and base film. However, most of the previous studies have been performed under atmospheric pressure conditions that provides the properties of liquid and gas which are significantly different from those of a BWR. Therefore, the effect of properties in gas and liquid on liquid film characteristics should be clarified. In this paper we focus on the effect of gas-liquid density ratio on liquid film thickness characteristics. The experiments have been conducted at four density ratio conditions (ρL/ρG =763, 451, 231, and 31). As a result, it is found that and interfacial shear stress collapse not only tF ave but also tF max and tF min successfully under the same liquid mass flow rate conditions irrespective of ρL/ρG, and moreover a non-dimensional parameter tends to collapse tF max，tF ave，and tF min in the wide range of experimental conditions (ρL/ρG：31～763，We：10～1800，ReL:500 ～ 2200).

Keywords: two phase flow, liquid film, annular flow, disturbance wave

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Authors: Namrata Ghosh, Sapan Tiwari

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Public transport service plays an important role in people's transportation needs in urban areas. Bus Rapid Transit System (BRTS) is a transport service that provides passengers with a quick and efficient mode of transport. It is developed by changing the existing infrastructure, vehicles, route, or by developing a new dedicated corridor for the bus route. This dedicated lanes transport passengers to their destination quickly and efficiently and flexible in meeting demand. However, with rapid urbanization and increasing population density in Indian cities, traffic congestion has become a significant issue. In a few Indian cities, the BRTS concept is implemented to address the issue of traffic congestion that eventually resulted in less road congestion. The research aims to provide a literature review on the overall outlook of the BRTS system and its practical implementation in mass urban transit. First, it reflects a literature review on the concept of the BRTS system in both developed and developing countries. Afterward, comparative analysis of BRTS, hindrances associated with the permanent integrated system, and the need for establishing the Bus Rapid Transit System in Indian cities is demonstrated. The research concludes with some recommendations that could help in improving the loopholes in the existing system.

Keywords: bus rapid transit system(BRTS), dedicated corridor, public transport, traffic congestion

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Authors: Laboratory of Semiconducting, Metallic Materials (LMSM) Biskra Algeria

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InZnSnO2 (IZTO)/β-Ga2O3 Schottky solar barrier photodetector (PhD) exposed to 255 nm was simulated and compared to the measurement. Numerical simulations successfully reproduced the photocurrent at reverse bias and response by taking into account several factors, such as conduction mechanisms and material parameters. By adopting reducing the density of the trap as an improvement. The effect of reducing the bulk trap densities on the photocurrent, response, and time-dependent (continuous conductivity) was studied. As the trap density decreased, the photocurrent increased. The response was 0.04 A/W for the low Ga2O3 trap density. The estimated decay time for the lowest intensity ET (0.74, 1.04 eV) is 0.05 s and is shorter at ∼0.015 s for ET (0.55 eV). This indicates that the shallow traps had the dominant effect (ET = 0.55 eV) on the continuous photoconductivity phenomenon. Furthermore, with decreasing trap densities, this PhD can be considered as a self-powered solar-blind photodiode (SBPhD).

Keywords: IZTO/β-Ga2O3, self-powered solar-blind photodetector, numerical simulation, bulk traps

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Authors: Ghazwan Al-Haji

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Traffic safety has become a major concern in Southeast Asia due to the increasing number of road accidents resulting in fatalities and injuries. Southeast Asia has one of the highest road traffic fatality rates in the world, in terms of both population and number of cars, nearly six times higher than the EU region. One of the reasons for this concerning trend is the increasing share of motorcycles as a form of transportation throughout Southeast Asia. The purpose of this study is to benchmark traffic safety situations and statistics in six countries in Asia and the EU, which Indonesia, Malaysia, Vietnam, Italy, Portugal and Sweden. The research will assess the priorities and causes of road accidents in the target nations. Further, the study will analyze the existing practices and promote best practices that can be implemented toward safer roads in Asian target countries. In order to achieve this goal, the study categorizes various factors contributing to traffic accidents and best practices into 4 pillars (Safer Behavior, Safer Roads, Safer Vehicles and Road Safety Management). The result of the study consists of a list of recommendations that can be applied by policymakers to promote safer roads in Asia towards 2030. The study is co-financed by the EU project ASIASAFE.

Keywords: traffic safety, ASIASAFE, Southeast Asia, EU project

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Authors: C. B. Masera, M. Imprialou, L. Budd, C. Morton

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Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.

Keywords: connected vehicles, GLOSA, intelligent transport systems, vehicle-to-infrastructure communication

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Authors: Attiq Ur Rahman Dogar, Sohaib Ishaq

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Pakistan had experienced rapid motorization in the last decade. Due to the soft leasing schemes of banks and increase in average household income, even the middle class can now afford cars. The public transit system is inadequate and sparse. Due to these reasons, traffic demand on urban arterials has increased manifold. Poor urban transit planning and aging transportation systems have resulted in traffic congestion. The focus of this study is to improve traffic flow on a section of N-5 passing through the Rawalpindi downtown. Present efforts aim to carry out the analysis of traffic conditions on this section and to investigate the impact of traffic signal co-ordination on travel time. In addition to signal co-ordination, we also examined the effect of different infrastructure improvements on the travel time. After the economic analysis of alternatives and discussions, the improvement plan for Rawalpindi downtown urban arterial section is proposed for implementation.

Keywords: signal coordination, infrastructure intervention, infrastructure improvement, cycle length, fuel consumption cost, travel time cost, economic analysis, travel time, Rawalpindi, Pakistan, traffic signals

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Authors: Chaitanya Varma, Arpan Mehar

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The present study demonstrates the procedure to analyse speed data collected on various four-lane divided sections in India. Field data for the study was collected at different straight and curved sections on rural highways with the help of radar speed gun and video camera. The data collected at the sections were analysed and parameters pertain to speed distributions were estimated. The different statistical distribution was analysed on vehicle type speed data and for mixed traffic speed data. It was found that vehicle type speed data was either follows the normal distribution or Log-normal distribution, whereas the mixed traffic speed data follows more than one type of statistical distribution. The most common fit observed on mixed traffic speed data were Beta distribution and Weibull distribution. The separate operating speed model based on traffic and roadway geometric parameters were proposed in the present study. The operating speed model with traffic parameters and curve geometry parameters were established. Two different operating speed models were proposed with variables 1/R and Ln(R) and were found to be realistic with a different range of curve radius. The models developed in the present study are simple and realistic and can be used for forecasting operating speed on four-lane highways.

Keywords: highway, mixed traffic flow, modeling, operating speed

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Authors: Anum Ali, Kashaf ad Dooja, Asif Saleem

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The future smart cities trend will be towards Internet of Things (IoT); IoT creates dynamic connections in a ubiquitous manner. Smart cities offer ease and flexibility for daily life matters. By using small devices that are connected to cloud servers based on IoT, network traffic between these devices is growing exponentially, whose security is a concerned issue, since ratio of cyber attack may make the network traffic vulnerable. This paper discusses the latest machine learning approaches in related work further to tackle the increasing rate of cyber attacks, machine learning algorithm is applied to IoT-based network traffic data. The proposed algorithm train itself on data and identify different sections of devices interaction by using supervised learning which is considered as a classifier related to a specific IoT device class. The simulation results clearly identify the attacks and produce fewer false detections.

Keywords: IoT, traffic security, deep learning, classification

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Authors: S. B. Provost, Susan Sheng

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An alternative bivariate density estimation methodology is introduced in this presentation. The proposed approach involves estimating the density function associated with the marginal distribution of each of the two variables by means of the saddlepoint approximation technique and applying a bivariate polynomial adjustment to the product of these density estimates. Since the saddlepoint approximation is utilized in the context of density estimation, such estimates are determined from empirical cumulant-generating functions. In the univariate case, the saddlepoint density estimate is itself adjusted by a polynomial. Given a set of observations, the coefficients of the polynomial adjustments are obtained from the sample moments. Several illustrative applications of the proposed methodology shall be presented. Since this approach relies essentially on a determinate number of sample moments, it is particularly well suited for modeling massive data sets.

Keywords: density estimation, empirical cumulant-generating function, moments, saddlepoint approximation

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Authors: Liu Canqi, Zeng Junsheng

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This study identifies two typical bottlenecks that occur when a vehicle cannot change lanes: car following and car stopping. The ideas of traffic field and traffic mass are presented in this work. When there are other vehicles in front of the target vehicle within a particular distance, a force is created that affects the target vehicle's driving speed. The characteristics of the driver and the vehicle collectively determine the traffic mass; the driving speed of the vehicle and external variables have no bearing on this. From a physical level, this study examines the vehicle's bottleneck when following a car, identifies the outside factors that have an impact on how it drives, takes into account that the vehicle will transform kinetic energy into potential energy during deceleration, and builds a calculation model for traffic mass. The energy-time conversion coefficient is created from an economic standpoint utilizing the social average wage level and the average cost of motor fuel. Vissim simulation program measures the vehicle's deceleration distance and delays under the Wiedemann car-following model. The difference between the measured value of deceleration delay acquired by simulation and the theoretical value calculated by the model is compared using the conversion calculation model of traffic mass and deceleration delay. The experimental data demonstrate that the model is reliable since the error rate between the theoretical calculation value of the deceleration delay obtained by the model and the measured value of simulation results is less than 10%. The article's conclusion is that the traffic field has an impact on moving cars on the road and that physical and socioeconomic factors should be taken into account while studying vehicle-following behavior. The deceleration delay value of a vehicle's driving and traffic mass have a socioeconomic relationship that can be utilized to calculate the energy-time conversion coefficient when dealing with the bottleneck of cars stopping and starting.

Keywords: traffic field, social economics, traffic mass, bottleneck, deceleration delay

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Authors: Ka-Yan Yim, Chi-Wai Kan

Abstract:

This paper conducts a comparison study using KES-FB and PhabrOmeter to measure 58 selected warp knitted fabric hand properties. Fabric samples were selected and measured by both KES-FB and PhabrOmeter. Results show differences between these two measurement methods. Smoothness and stiffness values obtained by KES-FB were found significant correlated (p value = 0.003 and 0.022) to the PhabrOmeter results while softness values between two measurement methods did not show significant correlation (p value = 0.828). Disagreements among these two measurement methods imply limitations on different mechanism principles when facing warp knitted fabrics. Subjective measurement methods and further studies are suggested in order to ascertain deeper investigation on the mechanisms of fabric hand perceptions.

Keywords: fabric hand, fabric objective measurement, KES-FB, PhabrOmeter

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Authors: Serge B. Provost

Abstract:

Numerous statistical inference and modeling methodologies are based on sample moments rather than the actual observations. A result justifying the validity of this approach is introduced. More specifically, it will be established that given the first n moments of a sample of size n, one can recover the original n sample points. This implies that a sample of size n and its first associated n moments contain precisely the same amount of information. However, it is efficient to make use of a limited number of initial moments as most of the relevant distributional information is included in them. Two types of density estimation techniques that rely on such moments will be discussed. The first one expresses a density estimate as the product of a suitable base density and a polynomial adjustment whose coefficients are determined by equating the moments of the density estimate to the sample moments. The second one assumes that the derivative of the logarithm of a density function can be represented as a rational function. This gives rise to a system of linear equations involving sample moments, the density estimate is then obtained by solving a differential equation. Unlike kernel density estimation, these methodologies are ideally suited to model ‘big data’ as they only require a limited number of moments, irrespective of the sample size. What is more, they produce simple closed form expressions that are amenable to algebraic manipulations. They also turn out to be more accurate as will be shown in several illustrative examples.

Keywords: density estimation, log-density, polynomial adjustments, sample moments

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