Many claim that, with regard to transportation infrastructure, only partnerships between public and private entities, which draw on the strengths of both, can achieve the goals of enhancing operational efficiency, increasing service delivery, improving asset maintenance, and stretching scarce federal, state, and local tax dollars. While some completed public-private partnership (P3) agreements on existing toll roads in the United States have seen a measure of success, others have raised critical questions pertaining to the true costs and benefits associated with these agreements for all stakeholders. Of particular concern is an apparent reliance on monetary calculations alone to determine toll road lump sum value. This primary focus on monetary considerations appears to neglect a number of non-monetary variables associated with potential costs and benefits. Four distinct groups of variables to consider in the decision process are presented in the dissertation: Monetary, Monetizable, Quantitative, and Qualitative. The last two groups represent variables of a non-monetary nature, which can reflect the much larger stewardship role that government plays in our society. The objectives of this research are twofold: to formulate a conceptual framework for a decision support system (DSS); and to propose an approach, including a set of analytical methods, that assesses the costs, benefits and other impacts associated with alternative P3 strategies. The primary user of the conceptual framework is identified as the public sector decision maker who has been asked to make recommendations regarding different strategies of toll road operation. Two analytical methods are presented. The first uses cash flow diagrams to calculate the net present value (NPV) for each of three core P3 strategies. The second, weighs the relative importance of quantitative and qualitative (non-monetizable) variables. When used as part of a seven-step process, these two analytical methods help create a decision support system framework that provides stakeholders with a more complete analysis of the costs and benefits associated with the P3 toll road decision process.

The forces which led to widespread suburbanization resulted in the migration of job opportunities, especially in retailing and in industry. This migration in part led to public transit service decline since a substantial share of transit trips in urban areas consisted of work trips, particularly to the CBD. Most planning agencies in small and medium urban areas include transportation improvements as an integral part of their efforts to stimulate economic development in the central city. The extent to which transportation improvements impact the central city in such areas is an important issue for urban planners, transportation engineers, and other professionals involved in attempts to enhance the local economy. While it is extremely difficult to attribute changes in demographic and economic activity to specific transportation improvements, it is posited in this research that general conclusions regarding such changes can be drawn and related to transportation improvements if consistent patterns of changes can be observed in demographic and economic activities among a large number of cities. The objective of this research is twofold: (1) to examine the relationship between transportation, central city and CBD development, and (2) to develop an econometric model that will depict such relationships. This research depicts selected relationships between employment, population, economic activity and transportation using a system of equations in a recursive model. The models are based on a sample of 112 small and medium sized cities with a 1980 population between 50,000 to 500,000, located in 36 different states. The models were tested using data from 11 cities with a 1980 population of 500,000 to 1,000,000 from 10 different states. The consistent results suggest that growth in the basic manufacturing sector is an important factor for central city growth. Increases in manufacturing employment attract more people to the cities, which in turn changes the retail sector. Also transit service improvements help to improve the downtown economy, since a relatively large share of peak trips are by transit and most of these transit trips are work trips, particularly to the CBD. Increased work trips to the CBD will have a positive (although small) impact on CBD sales. (Abstract shortened with permission of author.)

<p>Transportation engineering has taken upon a new role; to empower the alternative modes of travel: walking, biking, and bus transit. In this new era, engineers are rethinking a network designed predominately for the automobile. The ultimate goal of this research is to create a process that can make a vehicle dominant corridor a desirable, livable thoroughfare by livability design and context sensitive performance measures. Balancing travel modes requires an account of vehicular traffic and the impact of reconfiguring existing conditions. The analysis herein is conducted by field data collection, transportation equations and microsimulation. Simulating traffic behavior will be the means to apply livable alternatives comparable to existing Southeast Florida conditions. The results herein have shown that micro-simulation can be utilized in transportation planning to reveal good livability alternatives. </p>

<p> This dissertation presents a methodology for the joint optimization of a variety of pavement construction and management activities for segment and system problems under multiple budget constraints. The objective of pavement management is to minimize the total discounted life time costs for the agency and the highway users by finding optimal policies. The scope of the dissertation is focused on continuous time and continuous state formulations of pavement condition. We use a history-dependent pavement deterioration model to account for the influence of history on the deterioration rate. </p><p> Three topics, representing different aspects of the problem are covered in the dissertation. In the first part, the subject is the joint optimization of pavement design, maintenance and rehabilitation (M&R;) strategies for the segment-level problem. A combination of analytical and numerical tools is proposed to solve the problem. In the second part of the dissertation, we present a methodology for the joint optimization of pavement maintenance, rehabilitation and reconstruction (MR&R;) activities for the segment-level problem. The majority of existing Pavement Management Systems (PMS) do not optimize reconstruction jointly with maintenance and rehabilitation policies. We show that not accounting for reconstruction in maintenance and rehabilitation planning results in suboptimal policies for pavements undergoing cumulative damage in the underlying layers (base, sub-base or subgrade). We propose dynamic programming solutions using an augmented state which includes current surface condition and age. In the third part, we propose a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. Within a bottom-up solution approach, Genetic Algorithm (GA) is adopted. The complexity of the algorithm is polynomial in the size of the system and the policy-related parameters. </p>

<p> Greenhouse gas (GHG) emissions, known as a major cause of climate change, have been emitted by the combustion of fossil fuels over the past few decades. The transportation sector contributes significantly to global GHG emissions. Inspired by the successful implementation of tradable credit schemes (TCSs) in pollution control programs, this dissertation focuses on multi-period TCSs to minimize vehicular emissions. In this scheme, a central authority (CA) allocates travel credits to travelers (credit allocation scheme) and then, charges them to travel on each link (credit charging scheme). Travelers are able to trade credits amongst themselves in the market. </p><p> To address the long-term planning goals of the CA, the dissertation proposes the concept of a multi-period TCS framework. This framework enables the CA to achieve steady progress toward system-level goals, i.e., reducing traffic congestion and GHG emissions, over the long-term planning horizon. First, a TCS-based multi-period equilibrium modeling framework is developed to address the planning problem of a CA that seeks to achieve system-level goals by varying the credit supply and the link usage credit charging schemes across the various periods of the planning horizon. Further, the CA seeks stable credit prices across these periods to provide them as information to travelers in an operational context. Based on this information, bank interest rate and their travel needs, travelers determine their actions in terms of the consumption or sale of credits in the current period or the transfer of credits to future periods. It is proved that the credit price volatility is dampened by the ability to transfer credits. Since a TCS is subject to market manipulation and the artificial control of credit price, a transfer fee, which is shown to be an effective instrument to control hoarding among travelers, is proposed. </p><p> Using the proposed multi-period TCS framework, the dissertation develops different system optimal (SO) TCS designs, as bi-level models, to derive credit allocation and charging schemes to achieve system-level goals. In the first SO multi- period TCS design, the CA minimizes the vehicular emissions in the upper level over the long-term planning horizon. This enables the CA to plan the trajectory of vehicular emissions during the planning horizon. This trajectory can be used to predetermine the emissions standard for each period to use in the second SO multi-period TCS design, which aims to minimize total system travel time, in the upper level, over the planning horizon. These designs include bounds on increases in travel costs, allowing travelers to better adapt to the TCS implementation. The lower-level models are the equilibrium conditions in which travelers minimize their costs under the obtained multi-period TCS in the upper level. </p><p> To enhance realism in capturing the equilibrium conditions under the multi-period TCS, this dissertation factors different travelers&rsquo; characteristics and bank interest rates. In making route choices, travelers factor value of time (VOT) and tradeoff credit consumption and travel costs. Hence, travelers&rsquo; heterogeneity in terms of VOT is factored. It is shown that if the CA does not factor VOT in SO TCS design, it leads to a socially inequitable policy in practice. Further, the heterogeneity of travelers in terms of perceived future credit prices is factored. Travelers decide to consume or transfer credits in each period based on several factors, including future credit prices. However, due to the uncertainty in traffic network demand/supply forecasts over the long-term horizon, the CA cannot provide an accurate forecast of future credit prices <i>a priori</i>. It is shown that as the difference between travelers&rsquo; perceptions of future CPs and the actual CPs set by the CA for each period increases, the effectiveness of the SO TCS design in minimizing total system travel time decreases; this has implications for traffic congestion management. </p><p> Fourth, the dissertation investigates the robust design of multi-period TCS to account for travel demand uncertainty and achieve system-level goals. To minimize vehicular emissions, the CA leverages the TCS to promote zero-emissions vehicles (ZEVs), which circumvents the need for current subsidy-based incentive policies. The incentive to shift to ZEVs is fostered by allocating more credits and charging fewer credits to ZEV travelers compared to other travelers. To factor the uncertainty in travel demand forecasts, this research proposes a robust multi-period TCS design that minimizes the worst-case vehicular emissions, i.e. maximum vehicular emissions, under different traffic network demand scenarios. It is shown that the robust TCS design increases reliability in achieving system-level goals, compared to the SO TCS design that does not factor travel demand uncertainty. </p><p> Finally, the dissertation analyzes the ability of a TCS to manage morning commute congestion while factoring the market loss aversion of commuters. (Abstract shortened by ProQuest.) </p><p>

As states continue to consider taking on more responsibility in transportation, a major issue State Departments of Transportation (DOTs) face relates to financing future transportation investments. At present, many state transportation policymakers and State DOT administrators are considering alternative financing approaches to generate future revenue sources for transportation investments. This dissertation focuses on several user fee based approaches currently being considered by state transportation policymakers and administrators in the U.S. Examples of such approaches include: increasing the current fuel tax and indexing the fuel tax to inflation; implementing an odometer based vehicle miles traveled (VMT) fee approach through vehicle inspection programs in selected states; establishing a global positioning system (GPS) based VMT fee approach for heavy vehicles where privacy and implementation costs are less of a concern; and increasing existing tolls and charging tolls on existing roads that do not have tolls, preferably with open-road tolling (ORT) and all-electronic toll (AET) payment systems. Meanwhile, major questions of interest relate to the potential impacts or consequences of such financing approaches. Central to this dissertation is the development of a conceptual framework and analytical methods to aid state transportation policymakers and administrators in the planning and formulation of alternative financing approaches suitable for consideration in their state. The application of the framework and methods is illustrated in a case study. This case study includes an evaluation of alternative toll scenarios on a section of Interstate 93 in the Boston Metropolitan area where at present tolls are not charged. A major conclusion of the case study is that placing tolls along interstate highways where tolls are not currently collected has the potential to provide a significant source of revenue for State DOTs but that other impacts including route diversion, privacy, and equity need to be considered and addressed in the decision-making process. It is expected that the results of the dissertation will be of interest to state transportation policy makers as well as State DOT administrators currently involved in the development of a comprehensive transportation finance policy.

The traditional travel demand modeling process is designed to develop relationships among travel characteristics, land use activities, and a simulated transportation system network. The models are calibrated to base year conditions through comparisons of theoretical travel patterns, trip length characteristics, and traffic volumes with similar observed values. For projections of travel to future time periods, the assumption is made that the established database and relationships, and in particular the traffic analysis zones to which these data are assigned, will be the same for the forecast period as at the time of calibration. The primary objective of this research was to establish criteria for decision-making regarding which zones should be subdivided and to develop a technique for deciding how to subdivide. The eventual goal of the research was to improve travel demand forecasts. This research investigated whether travel demand estimates can be improved through the reconfiguration of traffic analysis zones for the future year projection period and through an associated restructuring of the centroid connectors for the future network. Similar subarea techniques have been applied by others in attempts to develop more accurate traffic data for project-specific needs. The subarea approach suffices for project needs, but the adjustments and modifications are not usually fed back into the modeling process. Therefore, the time and effort expended in obtaining project data are not applied to the improvement of the overall travel demand forecasts on a study-wide or regional basis. Under these conditions, system planning efforts and corridor analyses do not receive the benefit of updated information or system refinements. The findings of this research indicate that there is little improvement in the travel forecasts as a result of the subdivision of 9 zones in the New Castle County model into a total of 23 new units. Link-by-link comparisons of traffic assignments based on the New Castle County original 228 zone system and the modified 242 zone system reveal no significant improvements. One reason that can be identified is the detail of the simulated roadway system, which nearly duplicates the existing street and highway network and leaves little opportunity to provide alternative travel routings resulting from the creation of small traffic analysis zones.

Thesis (Ph. D.)--Rutgers University, 2007. / "Graduate Program in Civil and Environmental Engineering." Includes bibliographical references.