Advanced traffic management systems information infrastructure: The ITS Centre and Testbed (ICAT) platform.
Published: 2006
Language: eng
Number of pages: 209
ISBN-13: 9780494217917
Description: The ITS Centre and Testbed at the University of Toronto enables the research and development of the advanced computer algorithms required to improve the efficiency of traffic networks. The ITS Centre receives live traffic data and video from the Ontario Ministry of Transportation (MTO) and from the City of Toronto via fibre-optic connections. The ITS Centre and Testbed (ICAT) platform was created to furnish an elaborate information infrastructure for Advanced Traffic Management Systems (ATMS).The second tool is a dynamic probabilistic traffic flow model (PTFM). The model has an efficient calibration procedure and it provides soft predictions---i.e., the uncertainty of the predictions can be determined. It is shown that the PTFM performs well compared to other current models.In addition to being contributions on their own, the above research tools show the versatility of the ICAT platform and the benefits of research that is both repeatable and transferable. This thesis also documents three research works that were led by others but involved the author in a significant way. They demonstrate how the ICAT platform enables a broad spectrum of research topics.The ICAT platform is designed to handle data from many jurisdictions. It has been tested with data from MTO, the City of Toronto, Minnesota and the Netherlands. The ICAT software architecture facilitates future expansions in new analysis tools. In addition to providing many basic data visualization capabilities, the ICAT also facilitates traffic data driven research and development that is both repeatable and transferable. In this thesis, we apply the ICAT framework and develop three substantial research tools. Detailed methodologies, results and analysis are provided.The first tool provides a new look at traffic data using concepts from information theory. It provides insights about the randomness of traffic flow variables, as well as the dependency between the variables.The third tool is the first to quantify the impact of CMS messages on traffic flow diversion. It also quantifies the temporal span beyond which the impact on diversion diminishes, in both the short and long term.
Notes: Source: Dissertation Abstracts International, Volume: 68-01, Section: B, page: 0471.

Thesis (Ph.D.)--University of Toronto, 2006.

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