Graduation Year

2005

Document Type

Thesis

Degree

M.S.

Degree Granting Department

Civil Engineering

Major Professor

Jian Lu, Ph.D.

Committee Member

Ram Pendyala, Ph.D.

Committee Member

Elaine Chang, Ph.D.

Committee Member

Larry Hagen, M.S.C.E.

Keywords

Florida specific, Components, Parameters, Optimization, IDAS Modules

Abstract

Traditional transportation planning models are not very sensitive to many of the benefits derived from Intelligent Transportation Systems (ITS) technologies. With the recent availability of ITS Deployment Analysis System (IDAS), there is an opportunity to conduct detailed cost-benefit analyses of ITS Alternatives. IDAS is able to estimate the impacts, benefits, and costs resulting from the deployment of many ITS components. This is accomplished by comparing the average cost of deploying and integrating the appropriate technologies, to the estimated benefits experienced by the network. The ratio of average benefits to average costs is termed the B/C ratios. While the use of IDAS has been limited primarily to comparing ITS alternatives, this research goes a step further. After developing a local model, this research develops a strategy to maximize the benefits of using ITS components through prioritized deployment schedules.

Effective priority strategies are most often based on B/C ratios and therefore require the outputs from IDAS to accurately reflect local conditions. Because local parameters vary considerably from the national averages used in IDAS as default values, this paper establishes input parameters in all five of IDAS’s analysis modules that accurately model conditions in the Tampa Bay area. Outputs from the local Transportation forecasting model (FSUTMS), along with some other specialized IDAS conversion tools supplied by the Florida Department of Transportation (FDOT), were used to develop an accurate control alternative. Instead of default equipment costs, project costs were used to develop User Defined Costs within the cost module, local V/C curves replaced default curves in the benefits module, and the Sunguide report was used to establish Florida specific parameters used to value the benefits associated with each ITS alternative.

To develop a scenario that maximized the overall benefits to the system, individual projects were modeled in IDAS and their corresponding B/C ratio used to re-prioritize projects during deployment. Projects were deployed in order from highest to lowest B/C, while controlling for variations in time available for deployment and budgetary constraints.

To account for variations in the time available for deployment, the impact of time was evaluated and the findings used along with project limitations to develop appropriate phase schedules. Three scenarios were developed to test the impact of time. These scenarios were: compressed schedule, actual FDOT schedule, and an extended schedule. The test concluded that compressed schedules offered the highest benefits to the system. Based on this observation, it was desirable to develop a deployment scenario that compressed the time necessary for full deployment. Budget constraints were also a major limiting factor. Because these heavy constraints are often placed on planners, it was desirable that the final scenario accounted for budget constraints in the deployment schedule. To account for budgetary constraints, an average phase budget was developed from current FDOT plans and used as an upper limit for the cost of each phase of the deployment scenarios.

Based on project priority, time considerations, and budget constraints, a final deployment scenario was developed and compared to the FDOT deployment scenario. Comparing theses scenarios showed that some considerable improvements to the system can be achieved. By tracking the B/C ratio throughout the lifetime of the project, 80% higher B/C ratio was evident one year after full deployment and a 15% higher B/C ratio after 10 years of full project deployment. This represents an additional $350 million in benefits to the system over the ten year period. These results highlight both the effectiveness of ITS technologies as well as the need to develop more efficient strategies for using them.

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