<p>Driving simulators are used to conduct experiments on for example driver behavior, road design, and vehicle characteristics. The results of the experiments often depend on the traffic conditions. One example is the evaluation of cellular phones and how they affect driving behavior. It is clear that the ability to use phones when driving depends on traffic intensity and composition, and that realistic experiments in driving simulators therefore has to include surrounding traffic.</p><p>This thesis describes a model that generates and simulates surrounding vehicles for a driving simulator. The proposed model generates a traffic stream, corresponding to a given target flow and simulates realistic interactions between vehicles. The model is built on established techniques for time-driven microscopic simulation of traffic and uses an approach of only simulating the closest neighborhood of the driving simulator vehicle. In our model this closest neighborhood is divided into one inner region and two outer regions. Vehicles in the inner region are simulated according to advanced behavioral models while vehicles in the outer regions are updated according to a less time-consuming model. The presented work includes a new framework for generating and simulating vehicles within a moving area. It also includes the development of enhanced models for car-following and overtaking and a simple mesoscopic traffic model.</p><p>The developed model has been integrated and tested within the VTI Driving simulator III. A driving simulator experiment has been performed in order to check if the participants observe the behavior of the simulated vehicles as realistic or not. The results were promising but they also indicated that enhancements could be made. The model has also been validated on the number of vehicles that catches up with the driving simulator vehicle and vice versa. The agreement is good for active and passive catch-ups on rural roads and for passive catch-ups on freeways, but less good for active catch-ups on freeways.</p>

Internet connectivity takes a strategic importance for a growing number of companies. Therefore, for reliability and performance reasons, many Internet service providers and corporate networks connect to at least two providers, a practice called multihoming. However, the current multihoming mechanism contributes to the explosive growth of the Internet routing tables. This growth has major implications for routers on storage requirements, protocol overhead and stability, and forwarding performance. As a consequence, the traditional way to be multihomed in IPv4 is prevented in the next generation IPv6 Internet. Many approaches for IPv6 multihoming were proposed, with little consideration for traffic engineering aspects. The aim of the thesis is to bridge this gap. The thesis investigates the way to best provide traffic engineering for IPv6 multihomed sites. It first demonstrates that Host-Centric multihoming, the foreseen approach for IPv6 multihoming, is the most promising in terms of fault-tolerance and traffic engineering capabilities. Compared to traditional multihoming approaches, our simulation results show that Host-Centric IPv6 multihomed sites are able to obtain lower delays by leveraging the path diversity that underlies the Internet. Unfortunately, no traffic engineering mechanism is available for this multihoming approach. Therefore, this thesis next presents a technique to effectively use the multiple interdomain paths that exist between multihomed sites. The proposed mechanism allows the multihomed sites to control how their flows are distributed over the links with their providers. The mechanism is able to take into account complex and very dynamic routing policies. Finally, the thesis proposes the use of synthetic coordinates as a scalable and efficient way to help hosts in selecting the interdomain paths with the lowest delays. Experimental results with real measurements show that this mechanism allows sites to avoid all paths with really bad delays, and to most often select the lowest delay path.

In a few years, the Internet has quickly evolved from a research network connecting a handful of users to the largest distributed system ever built. The Internet connects more than 20,000 Autonomous Systems (ASs) which are administratively independent networks. While the initial Internet was designed to provide a best-effort connectivity among these ASs, there is nowadays a growing trend to deploy new services such as Voice/Video over IP or VPNs. To support these emergent services, ASs need to better engineer their Internet traffic. Traffic Engineering encompasses several goals such as better spreading the traffic load inside a network and obtaining better end-to-end performance (lower latency or higher bandwidth).<br><br> Engineering the traffic inside a single AS is feasible and pretty well understood. To the opposite, interdomain traffic engineering is still a difficult problem. The main issue comes from the current Internet routing architecture, articulated around the Border Gateway Protocol (BGP). BGP propagates a subset of the Internet topology for scalability and stability reasons and does not optimize a single global objective. This limits the control each AS has on its routing and has dramatic implications for interdomain traffic engineering.<br><br> In this thesis, we evaluate the primitive BGP-based routing control mechanisms. For this purpose, we designed and implemented a new approach for modeling BGP on large Internet-scale network topologies. Finally, to overcome the limitations of BGP in terms of routing control, we propose Virtual Peerings, a new mechanism based on a combination of BGP and IP tunneling. We apply Virtual Peerings to solve various interdomain traffic engineering problems such as balancing the load of Internet traffic received by an AS or decreasing the end-to-end latency of Internet paths.

Thesis (M.S.)--Ohio State University. / Includes bibliographical references. Available online via OhioLINK's ETD Center

Thesis (M. P. A.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Thesis (M. A.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

Recurring traffic congestion is attributable to steadily increasing travel demand coupled with constrained space and financial resources for infrastructure expansion. Another major source of congestion is non-recurrent incidents that disrupt the normal operation of the infrastructure. Aiming to optimize the utilization of the transportation infrastructure, innovative infrastructure management techniques that incorporate on edge technological equipment and information systems need to be adopted to manage recurrent and non-recurrent congestion and reduce their adverse externalities. The framework presented in this thesis lays the foundation for multi-disciplinary semantic web based incident management. During traffic incident response, involved stakeholders will share their knowledge and resources, forming an ad-hoc framework within which each party will focus on its core competencies and cooperate to achieve a coherent incident management process. Negotiation between various response agencies operators is performed using intelligent software agents, alleviating the coordination and synchronization burden of the massive information flow during the incident response. The software agents provide a decision support to human operators based on the reasoning provided from the underlying system knowledge models. Ontological engineering is used to lay the foundation of the knowledge models, which are coded in a web based ontology language, allowing a decentralized access to various elements of the system. The whole system communication infrastructure is based on the Semantic Web technologies. The semantic web facilitates the use of, in an enhanced manner, the already existing web technologies as the communication infrastructure of the proposed system. Its semantic capabilities help to resolve the information and data interoperability issues among various parties. The web services concepts combined with the semantic web allow the direct exploration and access of knowledge models, resources, and data repertories held by various parties. The developed ontology along with the developed software system were tested and evaluated by domain experts and targeted system users. Based on the conducted evaluation, both the ontology and the software system were found to be promising tools in developing pervasive, collaborative and multi-disciplinary traffic incident management systems

Recurring traffic congestion is attributable to steadily increasing travel demand coupled with constrained space and financial resources for infrastructure expansion. Another major source of congestion is non-recurrent incidents that disrupt the normal operation of the infrastructure. Aiming to optimize the utilization of the transportation infrastructure, innovative infrastructure management techniques that incorporate on edge technological equipment and information systems need to be adopted to manage recurrent and non-recurrent congestion and reduce their adverse externalities. The framework presented in this thesis lays the foundation for multi-disciplinary semantic web based incident management. During traffic incident response, involved stakeholders will share their knowledge and resources, forming an ad-hoc framework within which each party will focus on its core competencies and cooperate to achieve a coherent incident management process. Negotiation between various response agencies operators is performed using intelligent software agents, alleviating the coordination and synchronization burden of the massive information flow during the incident response. The software agents provide a decision support to human operators based on the reasoning provided from the underlying system knowledge models. Ontological engineering is used to lay the foundation of the knowledge models, which are coded in a web based ontology language, allowing a decentralized access to various elements of the system. The whole system communication infrastructure is based on the Semantic Web technologies. The semantic web facilitates the use of, in an enhanced manner, the already existing web technologies as the communication infrastructure of the proposed system. Its semantic capabilities help to resolve the information and data interoperability issues among various parties. The web services concepts combined with the semantic web allow the direct exploration and access of knowledge models, resources, and data repertories held by various parties. The developed ontology along with the developed software system were tested and evaluated by domain experts and targeted system users. Based on the conducted evaluation, both the ontology and the software system were found to be promising tools in developing pervasive, collaborative and multi-disciplinary traffic incident management systems

This paper will examine transportation as follows; first it will discuss traffic as a whole and in Claremont. Second, sustainability in Claremont will be looked at great depth highlighting the city’s goals and methods for creating sustainable transportation. Examples of roadways in the city will be given and reevaluated as satisfying sustainable traffic. Policy regulations and restrictions will then be discussed on how the contribute to congestion and affect sustainable transportation. Finally sustainability will be redefined in regards to transportation and assessing city roadways.

The aim of this thesis project is to develop the Traffic Sign Recognition algorithm for real time. Inreal time environment, vehicles move at high speed on roads. For the vehicle intelligent system itbecomes essential to detect, process and recognize the traffic sign which is coming in front ofvehicle with high relative velocity, at the right time, so that the driver would be able to pro-actsimultaneously on instructions given in the Traffic Sign. The system assists drivers about trafficsigns they did not recognize before passing them. With the Traffic Sign Recognition system, thevehicle becomes aware of the traffic environment and reacts according to the situation.The objective of the project is to develop a system which can recognize the traffic signs in real time.The three target parameters are the system’s response time in real-time video streaming, the trafficsign recognition speed in still images and the recognition accuracy. The system consists of threeprocesses; the traffic sign detection, the traffic sign recognition and the traffic sign tracking. Thedetection process uses physical properties of traffic signs based on a priori knowledge to detect roadsigns. It generates the road sign image as the input to the recognition process. The recognitionprocess is implemented using the Pattern Matching algorithm. The system was first tested onstationary images where it showed on average 97% accuracy with the average processing time of0.15 seconds for traffic sign recognition. This procedure was then applied to the real time videostreaming. Finally the tracking of traffic signs was developed using Blob tracking which showed theaverage recognition accuracy to 95% in real time and improved the system’s average response timeto 0.04 seconds. This project has been implemented in C-language using the Open Computer VisionLibrary.