<p>The purpose of this report is to implement and evaluate parts of the simulation software used in the SoCBUS project. In order to complete and evaluate the entire software package, a traffic model and a stimuli generator must be implemented. They are implemented and evaluated together with the entire simulator software. The purpose of the Traffic model is to model communication traffic as good and descriptive as possible. The output of the Traffic model is called a test case, which works as input for the Stimuli generator. The Stimuli generator computes and creates an event list for the Simulator. This report will investigate and motivate the presented traffic model and stimuli generator in detail. The simulator software is then tested with two separate test cases in order to investigate if the simulator software works properly. The results are promising and the simulator software behaves as expected.</p>

A safe and efficient highway infrastructure is a critical component and a valuable asset in terms of its monetary value, as well as supporting the way of life and economic activities of the people it serves. In North America, performing maintenance, repair, and expansion of an aging highway infrastructure to a target level of performance while dealing with ever-increasing traffic demands creates a significant challenge in terms of road user safety and mobility. Much of the current highway infrastructure was built several decades ago and it is therefore requiring increasing levels of maintenance and rehabilitation. <p>The cost of delays resulting from traffic congestion induced by work zones is estimated to be more than $6 billion per year. Work zone related traffic fatalities exceed more than 1000 lost lives per year in North America. Work zone related fatalities account for approximately 2.8 percent of highway fatalities in United States and 1.3 percent in Canada. While overall fatal crash rates have been steadily decreasing in both Canada and United States, work zone related fatalities have not been decreasing. <p>Smart Work Zones are an emerging technology designed to improve the safety and mobility within work zones on highways. Smart Work Zones employ various technologies to monitor current traffic conditions and provide relevant information to road managers and road users on current traffic flow conditions and automatically provide guidance to motorists for safer and more efficient navigation of the work zone. <p>This research examined the effects of a Smart Work Zone deployment by modeling traffic flow with and without a Smart Work Zone at the case study site in North Carolina to provide inputs into a performance analysis framework. The quantification of benefits and costs related to the deployment of a Smart Work Zone was developed in a probabilistic analysis framework model. The performance was quantified in economic terms of expected benefit cost ratio and net value realized from the deployment of a Smart Work Zone. The model considers the cost of deployment and potential savings in terms of motorist safety (fatal and injury crash reduction) as well as improvements in traveler mobility including reductions in user delays, vehicle operating costs, and emissions.<p>The model output is a risk profile that provides a range of expected values and associated probabilities of occurrence to quantify the expected benefits while also taking into consideration the uncertainty of the most sensitive input variables. The uncertainty of input variables determined to be the most sensitive were those associated with the amount of user delay and the valuation of user delay. The next most sensitive inputs are those associated with the cost of deploying and operating the Smart Work Zone system. <p>The model developed in this research concurs with the approach and analysis used in other models for the analysis of transportation projects. The model developed in this research provides a tool that can be used for decision making regarding the deployment of a Smart Work Zone and comparison with other transportation project alternatives. The model employs a user definable approach that enables it to be adapted to the specific conditions of a diverse range of field state conditions and has the ability to interface with several traffic flow models. <p>When applied to a case study project on Interstate 95 in North Carolina, the model was found to be capable of providing useful and relevant results that correlated to observed performance. The case study represented one of many operating scenarios on the project, and is not necessarily representative of all the field state conditions occurring over the period of the entire deployment. <p>The model results included a sensitivity analysis that identified the sensitivity of the outcome to uncertainty in the input values and a risk analysis that quantified the uncertainty of the predictions. The findings indicated that, at a 95 percent confidence level, the expected benefit / cost ratio of deploying a Smart Work Zone system was between 1.2 and 11.9 and the net value was between $10,000 and $225,000 per month of operation. Approximately 94 percent of the expected benefits were from savings in user delay and the remainder from savings due to improved safety, reduced emissions, and reduced vehicle operating costs. The results indicate that when applied under appropriate conditions, Smart Work Zones have the potential to provide significant benefits to road users. Under heavily congested conditions, the diversion of even a small amount of traffic to a more efficient route can provide sizable travel time improvements for all traffic.<p>In summary, the model developed in this research was specifically developed to apply to Smart Work Zones, but in its general form could also be applied to other work zone traffic management applications. In the case study the model was applied to a single rural work zone, but the framework could be extended for an integrated analysis of multiple work zones and network analysis in an urban setting. The research provides a fundamental framework and model for the analysis of Smart Work Zones and a method to determine the sensitivity of the uncertainty of input values. The research also identifies areas for continued examination of the effects of Smart Work Zone deployment and the prediction of expected benefits.

To evaluate the traffic state over time and space, several models can be used. A typical model for estimating the state of the traffic for a stretch of road or a road network is the cell transmission model, which is a form of state space model. This kind of model typically needs to be calibrated since the different roads have different properties. This thesis will present a calibration framework for the velocity based cell transmission model, the CTM-v. The cell transmission model for velocity is a discrete time dynamical system that can model the evolution of the velocity field on highways. Such a model can be fused with an ensemble Kalman filter update algorithm for the purpose of velocity data assimilation. Indeed, enabling velocity data assimilation was the purpose for ever developing the model in the first place and it is an essential part of the Mobile Millennium research project. Therefore a systematic methodology for calibrating the cell transmission is needed. This thesis presents a framework for calibration of the velocity based cell transmission model that is combined with the ensemble Kalman filter. The framework consists of two separate methods, one is a statistical approach to calibration of the fundamental diagram. The other is a black box optimization method, a simplification of the complex method that can solve inequality constrained optimization problems with non-differentiable objective functions. Both of these methods are integrated with the existing system, yielding a calibration framework, in particular highways were stationary detectors are part of the infrastructure. The output produced by the above mentioned system is highly dependent on the values of its characterising parameters. Such parameters need to be calibrated so as to make the model a valid representation of reality. Model calibration and validation is a process of its own, most often tailored for the researchers models and purposes. The combination of the two methods are tested in a suit of experiments for two separate highway models of Interstates 880 and 15, CA which are evaluated against travel time and space mean speed estimates given by Bluetooth detectors with an error between 7.4 and 13.4 % for the validation time periods depending on the parameter set and model.

A safe and efficient highway infrastructure is a critical component and a valuable asset in terms of its monetary value, as well as supporting the way of life and economic activities of the people it serves. In North America, performing maintenance, repair, and expansion of an aging highway infrastructure to a target level of performance while dealing with ever-increasing traffic demands creates a significant challenge in terms of road user safety and mobility. Much of the current highway infrastructure was built several decades ago and it is therefore requiring increasing levels of maintenance and rehabilitation. <p>The cost of delays resulting from traffic congestion induced by work zones is estimated to be more than $6 billion per year. Work zone related traffic fatalities exceed more than 1000 lost lives per year in North America. Work zone related fatalities account for approximately 2.8 percent of highway fatalities in United States and 1.3 percent in Canada. While overall fatal crash rates have been steadily decreasing in both Canada and United States, work zone related fatalities have not been decreasing. <p>Smart Work Zones are an emerging technology designed to improve the safety and mobility within work zones on highways. Smart Work Zones employ various technologies to monitor current traffic conditions and provide relevant information to road managers and road users on current traffic flow conditions and automatically provide guidance to motorists for safer and more efficient navigation of the work zone. <p>This research examined the effects of a Smart Work Zone deployment by modeling traffic flow with and without a Smart Work Zone at the case study site in North Carolina to provide inputs into a performance analysis framework. The quantification of benefits and costs related to the deployment of a Smart Work Zone was developed in a probabilistic analysis framework model. The performance was quantified in economic terms of expected benefit cost ratio and net value realized from the deployment of a Smart Work Zone. The model considers the cost of deployment and potential savings in terms of motorist safety (fatal and injury crash reduction) as well as improvements in traveler mobility including reductions in user delays, vehicle operating costs, and emissions.<p>The model output is a risk profile that provides a range of expected values and associated probabilities of occurrence to quantify the expected benefits while also taking into consideration the uncertainty of the most sensitive input variables. The uncertainty of input variables determined to be the most sensitive were those associated with the amount of user delay and the valuation of user delay. The next most sensitive inputs are those associated with the cost of deploying and operating the Smart Work Zone system. <p>The model developed in this research concurs with the approach and analysis used in other models for the analysis of transportation projects. The model developed in this research provides a tool that can be used for decision making regarding the deployment of a Smart Work Zone and comparison with other transportation project alternatives. The model employs a user definable approach that enables it to be adapted to the specific conditions of a diverse range of field state conditions and has the ability to interface with several traffic flow models. <p>When applied to a case study project on Interstate 95 in North Carolina, the model was found to be capable of providing useful and relevant results that correlated to observed performance. The case study represented one of many operating scenarios on the project, and is not necessarily representative of all the field state conditions occurring over the period of the entire deployment. <p>The model results included a sensitivity analysis that identified the sensitivity of the outcome to uncertainty in the input values and a risk analysis that quantified the uncertainty of the predictions. The findings indicated that, at a 95 percent confidence level, the expected benefit / cost ratio of deploying a Smart Work Zone system was between 1.2 and 11.9 and the net value was between $10,000 and $225,000 per month of operation. Approximately 94 percent of the expected benefits were from savings in user delay and the remainder from savings due to improved safety, reduced emissions, and reduced vehicle operating costs. The results indicate that when applied under appropriate conditions, Smart Work Zones have the potential to provide significant benefits to road users. Under heavily congested conditions, the diversion of even a small amount of traffic to a more efficient route can provide sizable travel time improvements for all traffic.<p>In summary, the model developed in this research was specifically developed to apply to Smart Work Zones, but in its general form could also be applied to other work zone traffic management applications. In the case study the model was applied to a single rural work zone, but the framework could be extended for an integrated analysis of multiple work zones and network analysis in an urban setting. The research provides a fundamental framework and model for the analysis of Smart Work Zones and a method to determine the sensitivity of the uncertainty of input values. The research also identifies areas for continued examination of the effects of Smart Work Zone deployment and the prediction of expected benefits.

No description available.

Because most grizzly bear mortalities occur near roads, the Province of Alberta plans to implement gated access management. Little is known about how grizzly bears will respond to road closures because the effects of roads are confounded by habitat and human use. I examined mechanisms underlying grizzly bear habitat selection near roads on private and public lands of southwestern Alberta. I incorporated habitat selection models into an analysis of conflict risk. Grizzly bears selected areas near roads with low traffic and were most active at night on private lands, where human use was low. However, habitat selection varied among individuals, and roads were not a consistent predictor of overall habitat selection across individual bears. Patterns of habitat selection led to the emergence of ecological traps on private land. Access and attractant management should be implemented to reduce bear-human conflicts, and decrease displacement of bears from high-quality habitats. / Ecology

The purpose of this report is to implement and evaluate parts of the simulation software used in the SoCBUS project. In order to complete and evaluate the entire software package, a traffic model and a stimuli generator must be implemented. They are implemented and evaluated together with the entire simulator software. The purpose of the Traffic model is to model communication traffic as good and descriptive as possible. The output of the Traffic model is called a test case, which works as input for the Stimuli generator. The Stimuli generator computes and creates an event list for the Simulator. This report will investigate and motivate the presented traffic model and stimuli generator in detail. The simulator software is then tested with two separate test cases in order to investigate if the simulator software works properly. The results are promising and the simulator software behaves as expected.

no / In this paper, a performance analysis of adaptive routing is presented for packet-switched inter-satellite link (ISL)networks, based on shortest path routing and two alternate link routing forwarding policies. The selected routing algorithm and link-cost function are evaluated for a low earth orbit satellite system, using a demographically weighted traffic flow model. Two distinct traffic flow patterns are modelled: hot spot and regional. Performance analysis, in terms of quality of service and quantity of service, is derived using specifically developed simulation software to model the ISL network, taking into account topology adaptive routing only, or topology and traffic adaptive routing.

A crescente complexidade das redes de comunicação de dados tem como conseqüência direta tornar cada vez mais complexas as tarefas de projetar seu dimensionamento e evolução. Um passo preliminar vitalmente importante no projeto de uma rede é a coleta de dados relacionados ao uso esperado da rede. Os padrões de tráfego estimados são usados nos cálculos de dimensionamento dos recursos. Fortemente relacionada a estas atividades está a previsão da performance em termos de throughput da rede, tempos de resposta, probabilidade de congestionamento, entre outras. Uma análise de performance efetiva depende de se representar precisamente a configuração da rede e da carga de tráfego a ela submetida. Técnicas de modelagem analítica ou de simulação podem ser usadas para determinar a performance esperada do sistema. Neste trabalho a usada a técnica de simulação para modelar o tráfego da rede usando dados coletados em uma rede real por monitoração. Trabalhando-se com o modelo validado e possível ajustar a carga de tráfego para representar mudanças esperadas nos volumes de tráfego, e testar o efeito na performance de diferentes configurações de rede. Isso possibilita que os processos de planejamento e projeto sejam executados com confiança, alem dos custos da rede poderem ser otimizados. O sistema apresentado neste trabalho e orientado à gerência de performance de redes, apoiando as atividades de gerência e planejamento de capacidade. Defende-se a idéia de que, a partir do perfil dos usuários de uma rede, derivado do tráfego por eles gerado, pode-se construir um modelo de tráfego significativamente representativo para a análise e previsão do desempenho da rede. O modelo foi desenvolvido para redes de comutação de pacotes com serviço orientado a conexão, e validado sobre o tráfego de uma rede X.25 através de um modelo de simulação, implementado em GPSS. O protótipo do sistema é composto por três processos principais que incorporam as etapas da análise de performance: monitoração do tráfego, análise do tráfego e simulação do tráfego. Na monitoração, são contabilizadas uma série de variáveis para cada conexão gerada na rede. Para cada tipo de aplicação são calculados os respectivos fatores de carga de tráfego. As aplicações são classificadas em dois grandes grupos: interativas e não-interativas. O processo de análise do tráfego gera os fatores de carga de tráfego na forma de tabelas e gráficos. As conexões e as métricas de performance produzidas na simulação do tráfego podem ser analisadas e validadas graficamente. O sistema proposto foi especificado em SDL (Specification and Description Language). / The increasing complexity of communication networks turns each time more complex the task to plan its expansion and evolution. A vitally important preliminar step in computer network design is the gathering of data relating to the expected use of the network. The estimated traffic patterns are used in resource usage computations. Closely related to these activities is the estimation of performance in terms of network throughput, response times, congestion probability, among others. An efective performance analysis requires the accurate representation of computer network configuration and traffic load. Analytical or simulation techniques can be used to establish the expected system performance. This work makes use of simulation to model the network traffic, based on collected data of a real network. network. Working with the validated model is possible to adjust the traffic load to represent future demand, and to test the performance impact under distinct network configurations. This enable a trustful execution of network planning and design, besides of the cost optimization. The system presented at this work is network performance management oriented, giving support to capacity management and capacity planning. The central idea is that, through network users profile achieved from generated traffic, it's possible to build a representative traffic model to aim at the network performance analysis and forecast. The model was developed to connection oriented packet switched networks, and validated by means of a simulation model to X.25 network traffic, implementd in GPSS. The system prototype comprises three process: traffic monitoring, traffic analysis and traffic simulation. In monitoring, a set of variables are registered for each network connection generated. The traffic load factors are computed according the application type. The applications are classified in two groups: interactive and non-interactive. The traffic analysis process produces traffic load factors in form of tables and graphics. Connections and performance metrics generated at traffic simulation can be graphically analyzed and validated. The proposed system was specified in SDL (Specification and Description Language).

Wireless communication is facing an increasingly severe spectrum scarcity problem. Hybrid free space optical (FSO)/ millimetre wavelength (MMW) radio frequency (RF) systems and cognitive radios are two candidate solutions. Hybrid FSO/RF can achieve high data rate transmission for wireless back haul. Cognitive radio transceivers can opportunistically access the underutilized spectrum resource of existing systems for new wireless services. In this work we carry out accurate performance analysis on these two transmission techniques. In particular, we present and analyze a switching based transmission scheme for a hybrid FSO/RF system. Specifically, either the FSO or RF link will be active at a certain time instance, with the FSO link enjoying a higher priority. We consider both a single threshold case and a dual threshold case for FSO link operation. Analytical expressions are obtained for the outage probability, average bit error rate and ergodic capacity for the resulting system. We also investigate the delay performance of secondary cognitive transmission with interweave implementation. We first derive the exact statistics of the extended delivery time, that includes both transmission time and waiting time, for a fixed-size secondary packet. Both work-preserving strategy (i.e. interrupted packets will resume transmission from where interrupted) and non-work-preserving strategy (i.e. interrupted packets will be retransmitted) are considered with various sensing schemes. Finally, we consider a M/G/1 queue set-up at the secondary user and derive the closed-form expressions for the expected delay with Poisson traffic. The analytical results will greatly facilitate the design of the secondary system for particular target application. / Graduate