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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
61

An Integrated Incident Detection Methodology With Gps-equipped Vehicles

Demiroluk, Sami 01 August 2007 (has links) (PDF)
Recurrent congestion in urban traffic networks, especially on arterials, is a growing problem. Non-recurrent congestion, mainly due to incidents, only aggravates the problem. Any solution requires monitoring of the network, for which many developing countries, such as Turkey, do not have the traditional surveillance systems on arterials mainly due to high costs. An alternative solution is the utilization of Global Positioning System (GPS) technology, which is increasingly used in traffic monitoring. It is easy and cheap to obtain the GPS track information,even in real-time, from a probe-vehicle or a fleet of vehicles / and spatial variation of speed and travel time of the vehicle(s) in a network can be determined. GPS-based data, especially with only one probe-vehicle, would not provide information on the concurrent states of upstream and downstream traffic, needed to define the state of traffic in a network. To overcome this obstacle, a methodology based on statistical analysis of archival traffic conditions obtained through different sources is proposed to analyze traffic fluctuations and identify daily traffic pattern. As a result, bottleneck and resulting queues can be detected on a corridor. Thus, it enables detection of recurrent congestion and queues that may result from incidents. The proposed methodology is tested on a corridor the roadway between METU and Kizilay of in&ouml / n&uuml / Boulevard. The results show that the methodology can effectively identify bottleneck locations on the corridor and also an incident observed during the data collection is detected correctly by the proposed algorithm.
62

Akıllı ulaşım sistemleri ve Türkiye'deki uygulamaları /

Çapalı, Buket. Terzi, Serdal. January 2009 (has links) (PDF)
Tez (Yüksek Lisans) - Süleyman Demirel Üniversitesi, Fen Bilimleri Enstitüsü, Yapı Eğitimi Anabilim Dalı, 2009. / Kaynakça var.
63

Self-organizing and optimal control for nonlinear systems

Dong, Wenjie. January 2009 (has links)
Thesis (Ph. D.)--University of California, Riverside, 2009. / Includes abstract. Title from first page of PDF file (viewed January 27, 2010). Includes bibliographical references (p. 82-87). Issued in print and online. Available via ProQuest Digital Dissertations.
64

Performance evaluation of cognitive radio in wireless vehicular communication.

Nyanhete, Eugenia Rudo. January 2012 (has links)
M. Tech. Electrical Engineering. / Discusses the performance of CRs that can be hampered by the environment, modulation schemes and how they can be selected based on the current environment i.e link adaptation, bandwidth efficient schemes and those that are prone to noise, formulate a set of decisions and actions based on the knowledge about the current environment and its effects on propagation and how to use a game theoretic approach for fair use of the spectrum.
65

Intelligent transportation systems

Locke, Danielle Marie 03 October 2011 (has links)
Many transportation systems used today are costly, slow, fragmented, and dangerous. This paper explores the inefficiencies and negative impacts associated with our current transportation systems. Simple to technologically advanced solutions are explored along with how to integrate these methods for all users in a sustainable fashion. The vision proposes a blend of scientific method, technological advancement, and common sense which is environmentally aware and integrated for all users by using the Dutch Regional and Sustainable Traffic Management Process. / text
66

An investigation of realtime data in intelligent transportation systems

Law, Lap-tak, Brendan., 羅立德. January 2002 (has links)
published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning
67

Applications of vehicle location and communication technology in fleetmanagement systems

Wong, Chi-tak, Keith., 黃志德. January 2001 (has links)
published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning
68

MILATRAS: MIcrosimulation Learning-based Approach to TRansit ASsignment

Wahba, Mohamed Medhat Amin Abdel-Latif 26 February 2009 (has links)
Public transit is considered a cost-effective alternative to mitigate the effects of traffic gridlock through the implementation of innovative service designs, and deploying new smart systems for operations control and traveller information. Public transport planners use transit assignment models to predict passenger loads and levels of service. Existing transit assignment approaches have limitations in evaluating the effects of information technologies, since they are neither sensitive to the types of information that may be provided to travellers nor to the traveller’s response to that information. Moreover, they are not adequate for evaluating the impacts of Intelligent Transportation Systems (ITS) deployments on service reliability, which in turn affect passengers’ behaviour. This dissertation presents an innovative transit assignment framework, namely the MIcrosimulation Learning-based Approach to TRansit ASsignment – MILATRAS. MILATRAS uses learning and adaptation to represent the dynamic feedback of passengers’ trip choices and their adaptation to service performance. Individual passengers adjust their behaviour (i.e. trip choices) according to their experience with the transit system performance. MILATRAS introduces the concept of ‘mental model’ to maintain and distinguish between the individual’s experience with service performance and the information provided about system conditions. A dynamic transit path choice model is developed using concepts of Markovian Decision Process (MDP) and Reinforcement Learning (RL). It addresses the departure time and path choices with and without information provision. A parameter-calibration procedure using a generic optimization technique (Genetic Algorithms) is also proposed. A proof-of-concept prototype has been implemented; it investigates the impact of different traveller information provision scenarios on departure time and path choices, and network performance. A large-scale application, including parameter calibration, is conducted for the Toronto Transit Commission (TTC) network. MILATRAS implements a microsimulation, stochastic (nonequilibrium-based) approach for modelling within-day and day-to-day variations in the transit assignment process, where aggregate travel patterns can be extracted from individual choices. MILATRAS addresses many limitations of existing transit assignment models by exploiting methodologies already established in the areas of traffic assignment and travel behaviour modeling. Such approaches include the microsimulation of transportation systems, learning-based algorithms for modelling travel behaviour, agent-based representation for travellers, and the adoption of Geographical Information Systems (GIS). This thesis presents a significant step towards the advancement of the modelling for the transit assignment problem by providing a detailed operational specification for an integrated dynamic modelling framework – MILATRAS.
69

MILATRAS: MIcrosimulation Learning-based Approach to TRansit ASsignment

Wahba, Mohamed Medhat Amin Abdel-Latif 26 February 2009 (has links)
Public transit is considered a cost-effective alternative to mitigate the effects of traffic gridlock through the implementation of innovative service designs, and deploying new smart systems for operations control and traveller information. Public transport planners use transit assignment models to predict passenger loads and levels of service. Existing transit assignment approaches have limitations in evaluating the effects of information technologies, since they are neither sensitive to the types of information that may be provided to travellers nor to the traveller’s response to that information. Moreover, they are not adequate for evaluating the impacts of Intelligent Transportation Systems (ITS) deployments on service reliability, which in turn affect passengers’ behaviour. This dissertation presents an innovative transit assignment framework, namely the MIcrosimulation Learning-based Approach to TRansit ASsignment – MILATRAS. MILATRAS uses learning and adaptation to represent the dynamic feedback of passengers’ trip choices and their adaptation to service performance. Individual passengers adjust their behaviour (i.e. trip choices) according to their experience with the transit system performance. MILATRAS introduces the concept of ‘mental model’ to maintain and distinguish between the individual’s experience with service performance and the information provided about system conditions. A dynamic transit path choice model is developed using concepts of Markovian Decision Process (MDP) and Reinforcement Learning (RL). It addresses the departure time and path choices with and without information provision. A parameter-calibration procedure using a generic optimization technique (Genetic Algorithms) is also proposed. A proof-of-concept prototype has been implemented; it investigates the impact of different traveller information provision scenarios on departure time and path choices, and network performance. A large-scale application, including parameter calibration, is conducted for the Toronto Transit Commission (TTC) network. MILATRAS implements a microsimulation, stochastic (nonequilibrium-based) approach for modelling within-day and day-to-day variations in the transit assignment process, where aggregate travel patterns can be extracted from individual choices. MILATRAS addresses many limitations of existing transit assignment models by exploiting methodologies already established in the areas of traffic assignment and travel behaviour modeling. Such approaches include the microsimulation of transportation systems, learning-based algorithms for modelling travel behaviour, agent-based representation for travellers, and the adoption of Geographical Information Systems (GIS). This thesis presents a significant step towards the advancement of the modelling for the transit assignment problem by providing a detailed operational specification for an integrated dynamic modelling framework – MILATRAS.
70

Vertical transportation planning in buildings

Peters, Richard David January 1998 (has links)
This thesis is submitted for the degree of Doctor of Engineering in Environmental Technology. The degree is awarded for industrially relevant research, based in industry, and supported by a programme of development courses. This project aims to contribute to a reduction in the environmental burdens of vertical transportation systems. The author has carried out an environmental assessment showing that the dominating environmental burdens of vertical transportation systems arise from their use of electricity while in operation in buildings. An assessment of traffic demand has concluded that we are probably over-sizing lifts, and are therefore installing systems that consume more energy than necessary. Traffic planning techniques for single and double deck lifts have been reviewed and developed. The kinematics (motion) of lifts has been studied. New formulae have been derived that allow us to plot travel profiles for any input of journey distance, maximum velocity, maximum acceleration and maximum jerk. Taking these journey profiles as inputs, a mathematical model of a DC Static Converter Drive has been developed. The model can be used to calculate the energy consumption of any individual lift trip. A lift simulation program has been developed. The program uses the research in traffic, kinematics and motor modelling as a basis for developing energy saving lift control strategies.

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