Search results for: traffic analysis

Authors: Jagdeep Kaur, Parvinder S. Sandhu, Birinderjit Singh, Amit Verma, Sanyam Anand

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In today-s hip hop world where everyone is running short of time and works hap hazardly,the similar scene is common on the roads while in traffic.To do away with the fatal consequences of such speedy traffics on rushy lanes, a software to analyse and keep account of the traffic and subsequent conjestion is being used in the developed countries. This software has being implemented and used with the help of a suppprt tool called Critical Analysis Reporting Environment.There has been two existing versions of this tool.The current research paper involves examining the issues and probles while using these two practically. Further a hybrid architecture is proposed for the same that retains the quality and performance of both and is better in terms of coupling of components , maintainence and many other features.

Keywords: Critical Analysis Reporting Environment, coupling, hybrid architecture etc.

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Authors: Ali Reza Honarvar , Naser Ghasem Agaee

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For controlling urban transportations, traffic lights show similar behavior for different kinds of vehicles at intersections. Emergency vehicles need special behavior at intersections, so traffic lights should behave in different manner when emergency vehicles approach them. At the present time, intelligent traffic lights control urban transportations intelligently. In this paper the ethical aspect of this topic is considered. A model is proposed for adding special component to emergency vehicles and traffic lights for controlling traffic in ethical manner. The proposed model is simulated by JADE.

Keywords: Ethical traffic control, intelligent transportation, Ethical agent, Multi-agent system.

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Authors: Siliang Wang, Minghui Wang

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This work proposes a novel market-based air traffic flow control model considering competitive airlines in air traffic network. In the flow model, an agent based framework for resources (link/time pair) pricing is described. Resource agent and auctioneer for groups of resources are also introduced to simulate the flow management in Air Traffic Control (ATC). Secondly, the distributed group pricing algorithm is introduced, which efficiently reflect the competitive nature of the airline industry. Resources in the system are grouped according to the degree of interaction, and each auctioneer adjust s the price of one group of resources respectively until the excess demand of resources becomes zero when the demand and supply of resources of the system changes. Numerical simulation results show the feasibility of solving the air traffic flow control problem using market mechanism and pricing algorithms on the air traffic network.

Keywords: Air traffic control, Nonlinear programming, Marketmechanism, Route policy.

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Authors: Muhammad Farhan, Sayed Faruque, Amr Mohammed, Sami Osman, Omar Al-Jabari, Abdul Almojil

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Saudi Arabia in recent years has seen drastic increase in traffic related crashes. With population of over 29 million, Saudi Arabia is considered as a fast growing and emerging economy. The rapid population increase and economic growth has resulted in rapid expansion of transportation infrastructure, which has led to increase in road crashes. Saudi Ministry of Interior reported more than 7,000 people killed and 68,000 injured in 2011 ranking Saudi Arabia to be one of the worst worldwide in traffic safety. The traffic safety issues in the country also result in distress to road users and cause and economic loss exceeding 3.7 billion Euros annually. Keeping this in view, the researchers in Saudi Arabia are investigating ways to improve traffic safety conditions in the country. This paper presents a multilevel approach to collect traffic safety related data required to do traffic safety studies in the region. Two highway corridors including King Fahd Highway 39 kilometre and Gulf Cooperation Council Highway 42 kilometre long connecting the cities of Dammam and Khobar were selected as a study area. Traffic data collected included traffic counts, crash data, travel time data, and speed data. The collected data was analysed using geographic information system to evaluate any correlation. Further research is needed to investigate the effectiveness of traffic safety related data when collected in a concerted effort.

Keywords: Crash Data, Data Collection, Traffic Safety.

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Authors: Bo Yang, Christopher Monterola

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Urban intersection control without the use of the traffic light has the potential to vastly improve the efficiency of the urban traffic flow. For most proposals in the literature, such lightless intersection control depends on the mass market commercialization of highly intelligent autonomous vehicles (AV), which limits the prospects of near future implementation. We present an efficient lightless intersection traffic control scheme that only requires Level 1 AV as defined by NHTSA. The technological barriers of such lightless intersection control are thus very low. Our algorithm can also accommodate a mixture of AVs and conventional vehicles. We also carry out large scale numerical analysis to illustrate the feasibility, safety and robustness, comfort level, and control efficiency of our intersection control scheme.

Keywords: Intersection control, autonomous vehicles, traffic modelling, intelligent transport system.

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Authors: Shuguo Yang, Xiaoyan Yang

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It is practically significant to research the traffic flow of intersection because the capacity of intersection affects the efficiency of highway network directly. This paper analyzes the traffic conditions of an intersection in certain urban by the methods of queuing theory and statistical experiment, sets up a corresponding mathematical model and compares it with the actual values. The result shows that queuing theory is applied in the study of intersection traffic flow and it can provide references for the other similar designs.

Keywords: Intersection, Queuing theory, Statistical experiment, System metrics.

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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: 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: Jouhra Dad, Mohammed Ouali, Yahia Lebbah

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Urban road network traffic has become one of the most studied research topics in the last decades. This is mainly due to the enlargement of the cities and the growing number of motor vehicles traveling in this road network. One of the most sensitive problems is to verify if the network is congestion-free. Another related problem is the automatic reconfiguration of the network without building new roads to alleviate congestions. These problems require an accurate model of the traffic to determine the steady state of the system. An alternative is to simulate the traffic to see if there are congestions and when and where they occur. One key issue is to find an adequate model for road intersections. Once the model established, either a large scale model is built or the intersection is represented by its performance measures and simulation for analysis. In both cases, it is important to seek the queueing model to represent the road intersection. In this paper, we propose to model the road intersection as a BCMP queueing network and we compare this analytical model against a simulation model for validation.

Keywords: Queueing theory, transportation systems, BCMPqueueing network, performance measures, modeling, simulation

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Authors: Shih-Ching Lo

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Understanding driving behavior is a complicated researching topic. To describe accurate speed, flow and density of a multiclass users traffic flow, an adequate model is needed. In this study, we propose the concept of standard passenger car equivalent (SPCE) instead of passenger car equivalent (PCE) to estimate the influence of heavy vehicles and slow cars. Traffic cellular automata model is employed to calibrate and validate the results. According to the simulated results, the SPCE transformations present good accuracy.

Keywords: traffic flow, passenger car equivalent, cellular automata

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Authors: Sakshi Kausha, R.K Sharma

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High speed networks provide realtime variable bit rate service with diversified traffic flow characteristics and quality requirements. The variable bit rate traffic has stringent delay and packet loss requirements. The burstiness of the correlated traffic makes dynamic buffer management highly desirable to satisfy the Quality of Service (QoS) requirements. This paper presents an algorithm for optimization of adaptive buffer allocation scheme for traffic based on loss of consecutive packets in data-stream and buffer occupancy level. Buffer is designed to allow the input traffic to be partitioned into different priority classes and based on the input traffic behavior it controls the threshold dynamically. This algorithm allows input packets to enter into buffer if its occupancy level is less than the threshold value for priority of that packet. The threshold is dynamically varied in runtime based on packet loss behavior. The simulation is run for two priority classes of the input traffic – realtime and non-realtime classes. The simulation results show that Adaptive Partial Buffer Sharing (ADPBS) has better performance than Static Partial Buffer Sharing (SPBS) and First In First Out (FIFO) queue under the same traffic conditions.

Keywords: Buffer Management, Consecutive packet loss, Quality-of-Service, Priority based packet discarding, partial buffersharing.

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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: Saad Roustom, Hajo Ribberink

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In most cities in the world, traffic has increased strongly over the last decades, causing high levels of congestion and deteriorating inner-city air quality. This study analyzes the impact of connected and automated vehicles (CAVs) on traffic performance and greenhouse gas (GHG) emissions under different CAV penetration rates in mixed fleet environments of CAVs and driver-operated vehicles (DOVs) and under three different traffic demand levels. Utilizing meso-scale traffic simulations of the City of Ottawa, Canada, the research evaluates the traffic performance of three distinct CAV driving behaviors—Cautious, Normal, and Aggressive—at penetration rates of 25%, 50%, 75%, and 100%, across three different traffic demand levels. The study employs advanced correlation models to estimate GHG emissions. The results reveal that Aggressive and Normal CAVs generally reduce traffic congestion and GHG emissions, with their benefits being more pronounced at higher penetration rates (50% to 100%) and elevated traffic demand levels. On the other hand, Cautious CAVs exhibit an increase in both traffic congestion and GHG emissions. However, results also show deteriorated traffic flow conditions when introducing 25% penetration rates of any type of CAVs. Aggressive CAVs outperform all other driving at improving traffic flow conditions and reducing GHG emissions. The findings of this study highlight the crucial role CAVs can play in enhancing urban traffic performance and mitigating the adverse impact of transportation on the environment. This research advocates for the adoption of effective CAV-related policies by regulatory bodies to optimize traffic flow and reduce GHG emissions. By providing insights into the impact of CAVs, this study aims to inform strategic decision-making and stimulate the development of sustainable urban mobility solutions.

Keywords: Connected and automated vehicles, congestion, GHG emissions, mixed fleet environment, traffic performance, traffic simulations.

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Authors: Mohamad K. Hasan, Hameed Al-Qaheri

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Optimization plays an important role in most real world applications that support decision makers to take the right decision regarding the strategic directions and operations of the system they manage. Solutions for traffic management and traffic congestion problems are considered major problems that most decision making authorities for cities around the world are looking for. This review paper gives a full description of the traffic problem as part of the transportation planning process and present a view as a framework of urban transportation system analysis where the core of the system is a transportation network equilibrium model that is based on optimization techniques and that can also be used for evaluating an alternative solution or a combination of alternative solutions for the traffic congestion. Different transportation network equilibrium models are reviewed from the sequential approach to the multiclass combining trip generation, trip distribution, modal split, trip assignment and departure time model. A GIS-Based intelligent decision support system framework for urban transportation system analysis is suggested for implementation where the selection of optimized alternative solutions, single or packages, will be based on an intelligent agent rather than human being which would lead to reduction in time, cost and the elimination of the difficulty, by human being, for finding the best solution to the traffic congestion problem.

Keywords: Multiclass simultaneous transportation equilibrium models, transportation planning, urban transportation systems analysis, intelligent decision support system.

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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: Reginald D. Smith

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The dynamics of User Datagram Protocol (UDP) traffic over Ethernet between two computers are analyzed using nonlinear dynamics which shows that there are two clear regimes in the data flow: free flow and saturated. The two most important variables affecting this are the packet size and packet flow rate. However, this transition is due to a transcritical bifurcation rather than phase transition in models such as in vehicle traffic or theorized large-scale computer network congestion. It is hoped this model will help lay the groundwork for further research on the dynamics of networks, especially computer networks.

Keywords: congestion, packet flow, Internet, traffic dynamics, transcritical bifurcation

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Authors: Lei Guo, Xu Zhang, Weigang Hou

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Since the traditional network is closed and it has no architecture to create applications, it has been unable to evolve with changing demands under the rapid innovation in services. Additionally, due to the lack of the whole network profile, the quality of service cannot be well guaranteed in the traditional network. The Software Defined Network (SDN) utilizes global resources to support on-demand applications/services via open, standardized and programmable interfaces. In this paper, we implement the traffic grooming application under a real SDN environment, and the corresponding analysis is made. In our SDN: 1) we use OpenFlow protocol to control the entire network by using software applications running on the network operating system; 2) several virtual switches are combined into the data forwarding plane through Open vSwitch; 3) An OpenFlow controller, NOX, is involved as a logically centralized control plane that dynamically configures the data forwarding plane; 4) The traffic grooming based on SDN is demonstrated through dynamically modifying the idle time of flow entries. The experimental results demonstrate that the SDN-based traffic grooming effectively reduces the end-to-end delay, and the improvement ratio arrives to 99%.

Keywords: NOX, OpenFlow, software defined network, traffic grooming.

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Authors: M. A. Hasan, M. R. Islam, R. A. Tarefder

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This study investigates how the site specific traffic data differs from the Mechanistic Empirical Pavement Design Software default values. Two Weigh-in-Motion (WIM) stations were installed in Interstate-40 (I-40) and Interstate-25 (I-25) to developed site specific data. A computer program named WIM Data Analysis Software (WIMDAS) was developed using Microsoft C-Sharp (.Net) for quality checking and processing of raw WIM data. A complete year data from November 2013 to October 2014 was analyzed using the developed WIM Data Analysis Program. After that, the vehicle class distribution, directional distribution, lane distribution, monthly adjustment factor, hourly distribution, axle load spectra, average number of axle per vehicle, axle spacing, lateral wander distribution, and wheelbase distribution were calculated. Then a comparative study was done between measured data and AASHTOWare default values. It was found that the measured general traffic inputs for I-40 and I-25 significantly differ from the default values.

Keywords: AASHTOWare, Traffic, Weigh-in-Motion, Axle load Distribution.

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Authors: D. Prangchumpol

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This paper is a description approach to predict incoming and outgoing data rate in network system by using association rule discover, which is one of the data mining techniques. Information of incoming and outgoing data in each times and network bandwidth are network performance parameters, which needed to solve in the traffic problem. Since congestion and data loss are important network problems. The result of this technique can predicted future network traffic. In addition, this research is useful for network routing selection and network performance improvement.

Keywords: Traffic prediction, association rule, data mining.

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Authors: Anjaneyulu M.V.L.R., Harikrishna M., Chenchuobulu S.

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Rapid urbanization, industrialization and population growth have led to an increase in number of automobiles that cause air pollution. It is estimated that road traffic contributes 60% of air pollution in urban areas. A case by case assessment is required to predict the air quality in urban situations, so as to evolve certain traffic management measures to maintain the air quality levels with in the tolerable limits. Calicut city in the state of Kerala, India has been chosen as the study area. Carbon Monoxide (CO) concentration was monitored at 15 links in Calicut city and air quality performance was evaluated over each link. The CO pollutant concentration values were compared with the National Ambient Air Quality Standards (NAAQS), and the CO values were predicted by using CALINE4 and IITLS and Linear regression models. The study has revealed that linear regression model performs better than the CALINE4 and IITLS models. The possible association between CO pollutant concentration and traffic parameters like traffic flow, type of vehicle, and traffic stream speed was also evaluated.

Keywords: CO pollution, Modelling, Traffic stream parameters.

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Authors: Yang Zhang, Yuncai Liu

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Accurately predicting non-peak traffic is crucial to daily traffic for all forecasting models. In the paper, least squares support vector machines (LS-SVMs) are investigated to solve such a practical problem. It is the first time to apply the approach and analyze the forecast performance in the domain. For comparison purpose, two parametric and two non-parametric techniques are selected because of their effectiveness proved in past research. Having good generalization ability and guaranteeing global minima, LS-SVMs perform better than the others. Providing sufficient improvement in stability and robustness reveals that the approach is practically promising.

Keywords: Parametric and Nonparametric Techniques, Non-peak Traffic Forecasting

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Authors: Wah Wah Aung, Cho Cho San

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The paper deals with a mathematical model for fluid dynamic flows on road networks which is based on conservation laws. This nonlinear framework is based on the conservation of cars. We focus on traffic circle, which is a finite number of roads that meet at some junctions. The traffic circle with junctions having either one incoming and two outgoing or two incoming and one outgoing roads. We describe the numerical schemes with the particular boundary conditions used to produce approximated solutions of the problem.

Keywords: boundary conditions, conservation laws, finite difference Schemes, traffic flow.

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Authors: S. Rokhsari, M. Delavar, A. Sadeghi-Niaraki, A. Abed-Elmdoust, B. Moshiri

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Traffic incident has bad effect on all parts of society so controlling road networks with enough traffic devices could help to decrease number of accidents, so using the best method for optimum site selection of these devices could help to implement good monitoring system. This paper has considered here important criteria for optimum site selection of traffic camera based on aggregation methods such as Bagging and Dempster-Shafer concepts. In the first step, important criteria such as annual traffic flow, distance from critical places such as parks that need more traffic controlling were identified for selection of important road links for traffic camera installation, Then classification methods such as Artificial neural network and Decision tree algorithms were employed for classification of road links based on their importance for camera installation. Then for improving the result of classifiers aggregation methods such as Bagging and Dempster-Shafer theories were used.

Keywords: Aggregation, Bagging theory, Dempster-Shafer theory, Site selection

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Authors: Keunhong Chae, Youngpo Lee, Seokho Yoon

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In cognitive radio (CR) systems, the primary user (PU) signal would randomly depart or arrive during the sensing period of a CR user, which is referred to as the high traffic environment. In this paper, we propose a novel spectrum sensing scheme based on the cyclostationarity of PU signals in high traffic environments. Specifically, we obtain a test statistic by applying an estimate of spectral autocoherence function of the PU signal to the generalized- likelihood ratio. From numerical results, it is confirmed that the proposed scheme provides a better spectrum sensing performance compared with the conventional spectrum sensing scheme based on the energy of the PU signals in high traffic environments.

Keywords: Spectrum sensing, cyclostationarity, high traffic environments.

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Authors: Ghazwan Al-Haji

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Most accidents occur in urban areas, and the most related casualties are vulnerable road users (pedestrians and cyclists). The traffic calming measures (TCMs) are widely used and considered to be successful in reducing speed and traffic volume. However, TCMs create unwanted effects include: noise, emissions, energy consumption, vehicle delays and emergency response time (ERT). Different vertical and horizontal TCMs have been already applied nationally (Sweden) and internationally with different impacts. It is a big challenge among traffic engineers, planners, and policy-makers to choose and priorities the best TCMs to be implemented. This study will assess the existing guidelines for TCMs in relation to safety and ERT with focus on data from Norrkoping city in Sweden. The expected results will save lives, time, and money on particularly Swedish Roads. The study will also review newly technologies and how they can improve safety and reduce ERT.

Keywords: Traffic safety, traffic calming measures, speeding, emergency response time.

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Authors: Alejandro Gomez Suarez, H. Srikanth Kamath

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In this paper, SFQ (Start Time Fair Queuing) algorithm is analyzed when this is applied in computer networks to know what kind of behavior the traffic in the net has when different data sources are managed by the scheduler. Using the NS2 software the computer networks were simulated to be able to get the graphs showing the performance of the scheduler. Different traffic sources were introduced in the scripts, trying to establish the real scenario. Finally the results were that depending on the data source, the traffic can be affected in different levels, when Constant Bite Rate is applied, the scheduler ensures a constant level of data sent and received, but the truth is that in the real life it is impossible to ensure a level that resists the changes in work load.

Keywords: Cbq, Cbr, Nam, Ns2.

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Authors: Srimuruganandam. B, S.M. Shiva Nagendra

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In this paper the influence of heterogeneous traffic on the temporal variation of ambient PM10, PM2.5 and PM1 concentrations at a busy arterial route (Sardar Patel Road) in the Chennai city has been analyzed. The hourly PM concentration, traffic counts and average speed of the vehicles have been monitored at the study site for one week (19th-25th January 2009). Results indicated that the concentrations of coarse (PM10) and fine PM (PM2.5 and PM1) concentrations at SP road are having similar trend during peak and non-peak hours, irrespective of the days. The PM concentrations showed daily two peaks corresponding to morning (8 to 10 am) and evening (7 to 9 pm) peak hour traffic flow. The PM10 concentration is dominated by fine particles (53% of PM2.5 and 45% of PM1). The high PM2.5/PM10 ratio indicates that the majority of PM10 particles originate from re-suspension of road dust. The analysis of traffic flow at the study site showed that 2W, 3W and 4W are having similar diurnal trend as PM concentrations. This confirms that the 2W, 3W and 4W are the main emission source contributing to ambient PM concentration at SP road. The speed measurement at SP road showed that the average speed of 2W, 3W, 4W, LCV and HCV are 38, 40, 38, 40 and 38 km/hr and 43, 41, 42, 40 and 41 km/hr respectively for the weekdays and weekdays.

Keywords: particulate matter, heterogeneous traffic, fineparticles, coarse particles, vehicle speed, weekend and weekday.

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Authors: Tuong Huan Nguyen, Quoc Bao Vo, Hai L. Vu

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In this paper we propose a new traffic simulation package, TDMSim, which supports both macroscopic and microscopic simulation on free-flowing and regulated traffic systems. Both simulators are based on travel demands, which specify the numbers of vehicles departing from origins to arrive at different destinations. The microscopic simulator implements the carfollowing model given the pre-defined routes of the vehicles but also supports the rerouting of vehicles. We also propose a macroscopic simulator which is built in integration with the microscopic simulator to allow the simulation to be scaled for larger networks without sacrificing the precision achievable through the microscopic simulator. The macroscopic simulator also enables the reuse of previous simulation results when simulating traffic on the same networks at later time. Validations have been conducted to show the correctness of both simulators.

Keywords: Macroscopic, Microscopic, Simulation, Traffic, Travel demand, Fundamental diagrams.

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Authors: H. Naghawi, M. Abu Shattal, W. Idewu

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Side friction factors can be defined as all activities taking place at the side of the road and within the traffic stream, which would negatively affect the traffic stream performance. If the effect of these factors is adequately addressed and managed, traffic stream performance and capacity could be improved. The main objective of this paper is to identify and assess the impact of different side friction factors on traffic stream performance of a hypothesized urban arterial road. Hypothetical data were assumed mainly because there is no road operating under ideal conditions, with zero side friction, in the developing countries. This is important for the creation of the base model which is important for comparison purposes. For this purpose, three essential steps were employed. Step one, a hypothetical base model was developed under ideal traffic and geometric conditions. Step two, 18 hypothetical alternative scenarios were developed including side friction factors such as on-road parking, pedestrian movement, and the presence of trucks in the traffic stream. These scenarios were evaluated for one, two, and three lane configurations and under different traffic volumes ranging from low to high. Step three, the impact of side friction, of each scenario, on speed-flow models was evaluated using AIMSUN microscopic traffic simulation software. Generally, it was found that, a noticeable negative shift in the speed flow curves from the base conditions was observed for all scenarios. This indicates negative impact of the side friction factors on free flow speed and traffic stream average speed as well as on capacity.

Keywords: AIMSUN, parked vehicles, pedestrians, side friction, traffic performance, trucks.

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Authors: Sameh H. Ghwanmeh

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Discovery schools in Jordan are connected in one flat ATM bridge network. All Schools connected to the network will hear broadcast traffic. High percentage of unwanted traffic such as broadcast, consumes the bandwidth between schools and QRC. Routers in QRC have high CPU utilization. The number of connections on the router is very high, and may exceed recommend manufacturing specifications. One way to minimize number of connections to the routers in QRC, and minimize broadcast traffic is to use PPPoE. In this study, a PPPoE solution has been presented which shows high performance for the clients when accessing the school server resources. Despite the large number of the discovery schools at MoE, the experimental results show that the PPPoE solution is able to yield a satisfactory performance for each client at the school and noticeably reduce the traffic broadcast to the QRC.

Keywords: Education, networking, performance, e-content.

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