Thesis (M. Sc.)--University of Hong Kong, 2002. / Includes bibliographical references (leaves 131-133).

Thesis (MScEng)--Stellenbosch University, 2001. / ENGLISH ABSTRACT: With the increased focus on the use of innovative and state-of-the-art technology in Intelligent Transport Systems (ITS), the need for more accurate and more detailed road traffic flow data has become apparent. Data obtained from vehicle detector loops, which merely act as vehicle presence sensors, is neither reliable nor accurate enough anymore. This type of sensor poses the problem that it has to be inserted into the road surface; temporarily obstructing traffic flows, and has to be replaced after pavement reconstruction. One of the solutions to this problem is to develop a traffic surveillance system that uses video image processing. In cities where Intelligent Transport Systems are used extensively, roadways are monitored through Closed Circuit Television Cameras (CCTV) that are closely watched by traffic control centre personnel. These cameras are mounted on posts on the roadside. These cameras can serve a dual purpose, being used for both human monitoring and as inputs to Video Image Processing Systems. In this study some of the digital image processing techniques that could be used in a traffic surveillance system were investigated. This report leads the reader through the various steps in the processing of a scene by a traffic surveillance system based on feature tracking, and discusses the pitfalls and problems that are experienced. The tracker was tested using three image sequences and the results are presented in the final chapter of this report. / AFRIKAANSE OPSOMMING: Met die toenemende fokus op die gebruik van innoverende oplossings en gevorderde tegnologie in Intelligente Vervoerstelsels, het die noodsaaklikheid van akkurater en meer gedetailleerde padverkeer vloeidata duidelik geword. Data wat verkry word d.m.v. voertuig deteksie lusse, wat alleenlik voertuig teenwoordigheid/afwesigheid meet, is nie meer akkuraat of betroubaar genoeg nie. Hierdie tipe sensors het egter die nadeel dat dit in die plaveisel ingesny moet word, dus vloei tydelik kan belemmer, en moet vervang word elke keer as plaveisel rekonstruksie gedoen word. Een van die oplossings vir hierdie probleem is om 'n verkeers waarnemingstelsel te ontwikkel wat van videobeeldverwerking gebruik maak. In stede waar van uitgebreide intelligente verkeerstelsels gebruik gemaak word, word paaie gemonitor d.m.v. geslote baan televisiekameras wat op pale langs die paaie aangebring is. Personeellede van die verkeers beheer sentrum hou dan die inkomende televisiebeelde dop. Hierdie kameras kan 'n dubelle rol vervul deurdat dit vir beide menslike waarneming en as invoer in 'n video-beeldverwerking stelsel gebruik kan word. In hierdie studie was verskeie digitale beeldverwerking tegnieke wat gebruik kan word in 'n verkeers waarnemingstelsel ondersoek. Hierdie verslag lei die leser deur die verskeie stappe in die verwerking van 'n toneel deur 'n verkeers waarneming stelsel wat gebaseer is op die volg van kenmerke. Die verslag beskryf ook die slaggate en probleme wat ondervind word. Die voertuig volger was getoets deur van drie reekse beelde gebruik te maak en die resultate word weergegee in die finale hoodfstuk van hierdie verslag.

Manual video analysis is apparently a tedious task. An efficient solution is of highly importance to automate the process and to assist operators. A major goal of video analysis is understanding and recognizing human activities captured by surveillance cameras, a very challenging problem; the activities can be either individual or interactional among multiple objects. It involves extraction of relevant spatial and temporal information from visual images. Most video analytics systems are constrained by specific environmental situations. Different domains may require different specific knowledge to express characteristics of interesting events. Spatial-temporal trajectories have been utilized to capture motion characteristics of activities. The focus of this dissertation is on how trajectories are utilized in assist in developing video analytic system in the context of surveillance. The research as reported in this dissertation begins real-time highway traffic monitoring and dynamic traffic pattern analysis and in the end generalize the knowledge to event and activity analysis in a broader context. The main contributions are: the use of the graph-theoretic dominant set approach to the classification of traffic trajectories; the ability to first partition the trajectory clusters using entry and exit point awareness to significantly improve the clustering effectiveness and to reduce the computational time and complexity in the on-line processing of new trajectories; A novel tracking method that uses the extended 3-D Hungarian algorithm with a Kalman filter to preserve the smoothness of motion; a novel camera calibration method to determine the second vanishing point with no operator assistance; and a logic reasoning framework together with a new set of context free LLEs which could be utilized across different domains. Additional efforts have been made for three comprehensive surveillance systems together with main contributions mentioned above.

published_or_final_version / Transport Policy and Planning / Master / Master of Arts in Transport Policy and Planning

Thesis (Ph.D.)--University of California, Berkeley, 2009. / Text document (PDF). Title from PDF title page (viewed on April 2, 2010). "Fall 2009." Includes bibliographical references (p. 41-42).

No description available.

No description available.

published_or_final_version / Urban Planning / Master / Master of Science in Urban Planning

Research on connected vehicles (CV) has attracted attention in the last decade due to numerous potential applications and challenges related to exchange of information between the vehicles (and infrastructure). Most of the relevant studies focus on these applications and challenges with the help of novel or existing simulation frameworks. The simulation framework often contains the mobility and communication components, and these components are frequently simplified. In this study, the authors aim to provide the detailed information for developing a fully V2X capable infrastructure within the lab environment. The physical components of the proposed infrastructure include: (i) userdriven Driving Simulator (DS) with the embedded micro-simulation tool (MS); (ii) external traffic signal controller (TSC); (iii) Road Side Unit (RSU) and omnidirectional antenna attached to RSU; (iv) On-Board Unit (OBU) that is integrated within DS‘s cockpit. The proposed framework can be used for advanced applications in the context of connected vehicles. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Originally presented as the author's Thesis--Technische Hochschule Aachen, 2008. / Includes bibliographical references.