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" Integrated Framework of Departure Time Choice, Mode Choice, and Route Assignment for Optimal Design of Time-Dependent Transit Pricing Strategies "
Taha, Islam Refaat Kamel
Abdulhai, Baher
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Latin Dissertation
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| Language of Document
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English
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| Record Number
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1052803
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| Doc. No
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TL51920
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| Main Entry
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Taha, Islam Refaat Kamel
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| Title & Author
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Integrated Framework of Departure Time Choice, Mode Choice, and Route Assignment for Optimal Design of Time-Dependent Transit Pricing Strategies\ Taha, Islam Refaat KamelAbdulhai, Baher
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| College
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University of Toronto (Canada)
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| Date
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2019
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| Degree
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Ph.D.
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| student score
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2019
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| Note
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3 p.
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| Abstract
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Modern travel demand management (TDM) strategies, such as time and distance-based congestion pricing, require evidence-based quantitative assessment to measure the potential effects on the transportation network performance and people’s responses to the dynamic consequences of such applications. This thesis focuses on building an integrated framework of departure time choice, mode choice, and dynamic multi-modal route assignment for optimal design of TDM strategies applied to large-scale transportation networks, with the focus on time-based transit pricing. The proposed platform integrates a simulation-based dynamic multi-modal multi-user-class route assignment model with an econometric model that jointly estimates departure time and mode choices and a genetic algorithm engine. The proposed platform has been used in optimizing time-dependent fares as a potential strategy to manage peak-hour transit crowding. Considering the traffic and transit networks as one system, the objective is to minimize travel times during peak periods by influencing travellers to alter their choice of transport mode, departure time, and/or route. The anticipated effect is to pace and spread out demand across space and time to yield the optimal spatio-temporal distribution of demand that minimizes end-to-end travel time. The control variables are the time-dependent transit fares. As a large and realistic use case, a model of the Greater Toronto Area has been developed to demonstrate and validate the results of this research. The main contributions of this research include: (1) developing a simulation-based large-scale dynamic route assignment model that captures the interactions between the traffic and transit sides; (2) integrating the route assignment model with a joint econometric model of departure time and mode choice to build a comprehensive model (the METRO platform) that can be used to assess dynamic TDM strategies; (3) integrating the METRO model with a cloud-based genetic algorithm engine to enable optimizing the design of TDM policies with emphasis on transit fares; and lastly (4) optimizing time-dependent transit fares in Toronto to minimize average weighted door-to-door travel time of all individuals in the system using all driving and transit modes, and quantitatively assessing the impacts of the resulting time-dependent fares as a policy and its strengths and weaknesses in addressing transit crowding.
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| Descriptor
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Engineering
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Transportation
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Abdulhai, Baher
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University of Toronto (Canada)
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