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Policy-makers of today's public transportation investment projects engage in debates in which the reasonableness and clarity of their judgment are tested many times. How to recommend the transportation system that achieves project's goals and different stakeholders' needs in a most logical and justifiable manner is the main question of this dissertation. This study develops a new decision-making approach, Belief Reasoning method, for evaluating public transportation systems in the planning process. The proposed approach applies a reasoning map to model how experts perceive and reason transportation alternatives to lead to the project's goals. It applies the belief measures in the Dempster-Shafer theory of evidence as the mathematical mechanism to represent knowledge under uncertainty and ambiguity and to analyze the degree of achievement of stated goals. Three phases are involved in implementing the Belief Reasoning method. First, a set of goals, a set of characteristics of the alternatives, a set of performances and impacts are identified and the reasoning map, which connects the alternatives to the goals through a series of causal relations, is constructed. Second, a knowledge base is developed through interviewing the experts their degree of belief associated with individual premises and relations, and then aggregating the expert opinions. Third, the model is executed and the results are evaluated in three ways: (i) the transportation alternatives are evaluated based on the degree of belief for achieving individual goals; (ii) the integrity of the reasoning process is evaluated based on the measures of uncertainty associated with information used; and (iii) the critical reasoning chains that significantly influence the outcome are determined based on the sensitivity analysis. The Belief Reasoning method is compared with the Bayesian reasoning, which uses the probability measures as the measure of uncertainty. Also it is compared with the Analytical Hierarchy Process method, which uses a hierarchical tree structure and a weighting scheme. The numerical examples in transit planning are developed for comparison. The proposed Belief Reasoning method has advantages over these traditional evaluation and reasoning methods in several ways. • Use of a reasoning map structure together with an inference process, instead of a tree structure together with a weighting scheme, allows modeling interdependency, redundancy and interactions among variables, usually found in transportation systems. • Use of belief measures in Dempster-Shafer theory can preserve non-deterministic nature of inputs and performances as well as handle incomplete or partial knowledge of experts or citizens, i.e. "I don't know" type opinion. The "degrees of belief" measures allow experts to express their strength of opinions in the conservative and optimistic terms. Such operation is not possible by the probability-based approach. • Dempster-Shafer theory can avoid the scalability issue encountered in Bayesian reasoning. It can also measure uncertainty in the reasoning chains, and identify information needed for improving the reasoning process. • Use of Dempster's rule of combination, instead of the average operator in probability theory, to merge expert opinions about inputs or relations is a better way for combining conflicting and incomplete opinions. In the dissertation, the Belief Reasoning method is applied in real-world Alternatives Analysis of a transit investment project. The results show its potential to analyze and evaluate the alternatives and to provide reasons for recommending a preferred alternative and to measure the uncertainty in the reasoning process. In spite of some shortcomings, discussed in the dissertation, the Belief Reasoning method is an effective method for transportation planning compared with the existing methods. It provides means for the planners and citizens to present their own reasons and allows review and analysis of reasoning and judgments of all participating stakeholders. The proposed method can promote focused discourse among different groups of stakeholders, and enriches the quality of the planning process. / Ph. D.

Emergency vehicle traffic signal priority systems allow emergency vehicles such as fire and emergency medical vehicles to request and receive a green traffic signal indication when approaching an intersection. Such systems have been around for a number of years, however, there is little understanding of the costs and benefits of such systems once they are deployed. This research develops an improved method to assess the travel time impacts of emergency vehicle traffic signal priority systems for transportation planning analyses. The research investigates the current state of available methodologies used in assessing the costs and benefits of emergency vehicle traffic signal priority systems. The ITS Deployment Analysis System (IDAS) software is identified as a recently developed transportation planning tool with cost and benefit assessment capabilities for emergency vehicle traffic signal priority systems. The IDAS emergency vehicle traffic signal priority methodology is reviewed and recommendations are made to incorporate the estimation of non-emergency vehicle travel time impacts into the current methodology. To develop these improvements, a simulation analysis was performed to model an emergency vehicle traffic signal priority system under a variety of conditions. The simulation analysis was implemented using the CORSIM traffic simulation software as the tool. Results from the simulation analysis were used to make recommendations for enhancements to the IDAS emergency vehicle traffic signal priority methodology. These enhancements include the addition of non-emergency vehicle travel time impacts as a function of traffic volume on the transportation network. These impacts were relatively small and ranged from a 1.1% to 3.3% travel time increase for a one-hour analysis period to a 0.6% to 1.7% travel time increase for a two-hour analysis period. The enhanced methodology and a sample application of the methodology are presented as the results of this research. In addition, future research activities are identified to further improve assessment capabilities for emergency vehicle traffic signal priority systems. / Ph. D.

Preferential treatments are employed to provide preemption for emergency vehicles (EV) and conditional priority for transit vehicles at signalized intersections. EV preemption employs technologies and signal control strategies seeking to reduce emergency vehicle crash potential and response times. Transit priority employs the same technologies with signal control strategies seeking to reduce travel time and travel time variability. Where both preemption and transit technologies are deployed, operational strategies deconflict simultaneous requests. Thus far, researchers have developed separate evaluation frameworks for preemption and priority. This research addresses the issue of preemption and priority signal control strategies in breadth and depth. In breadth, this research introduces a framework that reveals planning interdependence and operational interaction between preemption and priority from the controlling strategy down to roadway hardware operation under the inclusive title: preferential treatment. This fulfills a current gap in evaluation. In depth, this research focuses on evaluation of EV preemption. There are two major analytical contributions resulting from this research. The first is a method to evaluate the safety benefits of preemption based on conflict analysis. The second is an algorithm, suitable for use in future traffic simulation models, that incorporates the impact of auto driver behavior into the determination of travel time savings for emergency vehicles operating on signalized arterial roadways. These two analytical methods are a foundation for future research that seeks to overcome the principal weakness of current EV preemption evaluation. Current methods, which rely on modeling and simulation tools, do not consider the unique auto driver behaviors observed when emergency vehicles are present. This research capitalizes on data collected during a field operational test in Northern Virginia, which included field observations of emergency vehicles traversing signalized intersections under a wide variety of geometric, traffic flow, and signal operating conditions. The methods provide a means to quantify the role of EV preemption in reducing the number and severity of conflict points and the delay experienced at signalized intersections. This forms a critical basis for developing deployment and operational guidelines, and eventually, warrants. / Ph. D.

Transportation is not merely a derived demand, but a determinant of new production possibilities. In developing economies, where the lack of mobility is self-evident, it is absolutely necessary to consider the catalytic impacts of transport services. Transportation not only directly affects the overall output in an economy through accessibility and costs, but also stimulates and influences the shift in the demographic sector in terms of population movements and unemployment rates. To successfully plan for the development of a region, one must understand the possible causal relationships, feedbacks and interactions between the different sectors of both the investment region and the possible spatially impacted region. In this study, the impacts of three investment strategies for the Essequibo Coast region, in Guyana, are evaluated through the use of a computer simulation and system dynamics methodology. The model consists of two regions -- the region in which investment is provided and the region that is spatially impacted due to this investment. The hypothesized interrelationships of the main sectors (demographic, economic and transport) and components of each region were first developed as causal submodels. Secondly, the submodels were synthesized to form a compre- hensive system dynamics computer model represented by approximately 280 equations to evaluate the three strategies: (1) Do Nothing; (2) Investments in Roads Only; and (3) Investment in Roads, Drainage and Irrigation. Sensitivity analyses were performed on the key socio-economic variables (Drainage, Irrigation, Fertilizer, Mechanization and Regional Migration) to determine which variables most significantly influence regional behavior. These tests showed that a tacit acceptance (i.e., not explicitly incorporating the above factors in a model) of the availability of these resources overstates the impacts due to transport investments -- i.e., roads equal development is also a misconception. The investment strategy in Roads, Drainage and Irrigation provided the greatest net benefits and most favorable socio-economic characteristics in terms of population level, regional income per capita, outmigration and unemployment. So, given its financial feasibility, it is reco1m1ended for implementation. Further, it is also suggested, because of the model's demonstrable flexibility, that it be used for post investment analyses and future model calibration. / Ph. D.

The aims of the present study were twofold: (1) to determine the effectiveness of various map formats in presenting mass transit information; and (2) to assess subjects’ internal representation of spatial features of the environment. It was hypothesized that bus route selection would be a function of both the amount of detail and the road structure presented in maps and that the effect of detail and road structure would depend upon the familiarity of the mapped area. A 2 X 2 X 2 (Familiarity x Detail x Road Structure) factorial design was employed in the experiment. The familiarity factor was manipulated by mapping a familiar area (Blacksburg, Virginia) and an unfamiliar area (an altered section of London, England). Detail was manipulated by including or not including roads and landmarks on the maps. Road Structure was manipulated by presenting roads in either a veridical or a simplified manner. Performance on a map reading task was used to assess the effects of the independent variables. Fourty undergraduate subjects were required to first locate two intersections on a bus route map and second, to determine a bus route between the two intersections. Five dependent measures of map reading ability were obtained. Results indicated that, for both familiar and unfamiliar areas, a veridical road structure yielded less errors and faster times for determining a bus route than did a simplified road structure, and that detail lengthened the time to perform the task. / Master of Science

The purpose of this research is to develop a methodology to interface transportation planning and traffic simulation. Differences in representations of planning and traffic networks prohibits planners and engineers from sharing the input data for the same area being studied. Therefore the planning data need to be utilized to create data that the traffic engineers can use for traffic simulation, thus avoiding duplication of effort to collect data for the two purposes. The methodology developed specifically for the Urban Transportation Planning Software (UTPS) and Traffic Simulation Software (TRAF), can be modified to interface planning and simulation performed by other software as well. The methodology is demonstrated using a typical urban town network. / Master of Science

The objective of this study is to set a methodology for transportation systems evaluation using an approach different than the traditional. The first part consist on a description of the transportation problem, the different concerns over the years and how transportation planning faced it. The second part explains the systems point of view, that considers problems as part of a bigger ones and relate them through causal relationships that make possible to incorporate social and environmental impacts to the model. Then a description of the traditional approach for transportation systems evaluation is given as a background for the dynamic economic evaluation that allows the planner to see the evolution of the parameters over time. The methodology is applied to a scenario where a new transportation facility is going to be built and the best of the alternatives should be selected. This study also emphasizes that the methodology is a tool for the decision-maker but it will never replace his judgment. / M.S.

TRANSIMS is a disaggregate, behavioral, regional transportation planning package developed by Los Alamos National Laboratory (LANL) under funding from US DOT, EPA, and Department of Energy. It is an integrated system of travel forecasting models designed to give transportation planners accurate, complete information on traffic impacts, congestion, and pollution by simulating on a second-by-second basis the movements of every person and every vehicle through the transportation network of a large metropolitan area. This regional microsimulation approach provides a better assessment of the performance of a large network than the current link performance functions utilized in the current planning procedures. On the other hand, their microsimulation approach on a regional scale requires a lot of data that may not be readily available, and utilize a low fidelity microsimulation in order to make it operational. Some agencies may be interested in performing a more detailed investigation of traffic patterns within a sub area, such as the downtown area. The author implemented a subarea focusing methodology within TRANSIMS and also developed an interface that allows the investigator to use a high-fidelity, small-size network efficient traffic operational software package — CORSIM to perform sub area traffic operational analysis with demand and network extracted from applications of TRANSIMS. This methodology will allow TRANSIMS to take advantage of higher fidelity models for sub-network analysis and allow CORSIM to use planning inputs such as individual 24 hour travel activities and trip chains. An evacuation model is also built and applied to Virginia Tech main campus, Blacksburg, VA to evaluate this sub area focusing methodology. / Master of Science

The financial and environmental effects of traffic congestion and automobile-centric air pollution continue to be problems that must be addressed within the United States. In response, travel demand management (TDM) has emerged as a potential way to reduce automobile-based travel in order to minimize these effects. TDM strategies are highly dependent on specific urban form characteristics such as bicycle lanes, sidewalks, or transit facilities. A current gap exists in the analytical tools available to transportation planners when evaluating TDM projects. The standard transportation models do not take into account urban form characteristics in a systematic way. These characteristics play an import role in an individual's selection of walking, bicycling, or transit based travel modes. This gap needs to be filled in order to evaluate TDM projects with the same decision-making rigor that is applied to road expansion projects. The purpose of this project is to develop an enhanced transportation mode choice model that presents a systematic approach for incorporating urban form characteristics. This approach determines which elements of urban form have the strongest influence on transportation mode choice behavior. This work is being done in conjunction with the Roanoke Valley Allegheny Metropolitan Planning Organization as a way to evaluate the potential of TDM projects in promoting non-automobile forms of travel within the Roanoke region. This approach to developing an enhanced transportation mode choice model is a step forward in address the gap between TDM strategies and the tools needed to evaluate them. / Master of Urban and Regional Planning