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dc.contributorUpayokin, Auttawiten_US
dc.date.accessioned2009-09-16T18:20:38Z
dc.date.accessioned2011-08-24T21:42:59Z
dc.date.available2009-09-16T18:20:38Z
dc.date.available2011-08-24T21:42:59Z
dc.date.issued2009-09-16T18:20:38Z
dc.date.submittedJanuary 2008en_US
dc.identifier.urihttp://hdl.handle.net/10106/1887
dc.description.abstractFreeway traffic congestion represents an increasing concern for urban areas throughout the United States. In addition, faced with limited roadway expansion alternatives, transportation agencies are considering investment in traffic management centers (TMCs) as a more viable way to operate and manage freeways effectively. The TMCs' responsibilities include monitoring roadway conditions using the various data collection strategies and determining performance measures for freeway operations. At the same time, traffic engineers at the TMCs may react to the traffic congestion problems by implementing operational strategies. In order to provide reliable decision support for TMC freeway operations and management systems, this dissertation aims to examine the factors influencing the TMCs' investment, the effective methods for persuading the public to support TMC deployment, and the legal issues involved with deciding to deploy a TMC. Second, this research presents an innovative approach, using a multi-criteria decision framework for selecting data collection strategies by considering the limitation of data collection strategies and candidate performance measures at the same time. The multi-criteria decision framework includes establishing a statement of purpose, identifying the alternatives and their criteria, developing a screening approach using the decision makers' priorities, and multi-criteria decision models. This research suggests both qualitative and quantitative criteria that affect the quality of operational performance measures and data collection strategies; these include understanding, measurability, availability, importance, time, cost, accuracy, and reliability. Then, multi-criteria models such as Simple Additive Weight (SAW) and ELECTRE III are used to select the best freeway data collection strategies. Third, this research examines the characteristics of good performance measures, constraints for data collection strategies, current and expected daily performance measures using a modified Delphi Method and stated preference surveys from TMCs in the United States. The same proposed framework is applied to develop the individual performance measures and integrate these performance measures to evaluate the overall impacts on daily freeway operations based on TMC goals. During the discussion and presentation of the proposed framework, this dissertation uses five minute aggregated traffic data from Lane 1 on SB Loop 12 at Irving Boulevard, Irving, Texas and four lanes on SB-I35W at Alta Mesa, Fort Worh, Texas to illustrate the application of the integrated performance measures.en_US
dc.language.isoENen_US
dc.publisherCivil & Environmental Engineeringen_US
dc.titleMulti-criteria Assessment For Supporting Freeway Operations And Management Systemsen_US
dc.typePh.D.en_US


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