Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-06-02T19:19:17Z No. of bitstreams: 1 RanmsesEmanuelMartinsBastos_DISSERT.pdf: 3544164 bytes, checksum: 0be0a21709a7526cbbea13cf73f55d8e (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-06-05T19:52:50Z (GMT) No. of bitstreams: 1 RanmsesEmanuelMartinsBastos_DISSERT.pdf: 3544164 bytes, checksum: 0be0a21709a7526cbbea13cf73f55d8e (MD5) / Made available in DSpace on 2017-06-05T19:52:51Z (GMT). No. of bitstreams: 1 RanmsesEmanuelMartinsBastos_DISSERT.pdf: 3544164 bytes, checksum: 0be0a21709a7526cbbea13cf73f55d8e (MD5) Previous issue date: 2017-02-17 / O Problema do Caixeiro Viajante com Passageiros e Lota??o ? uma vers?o do PCV cl?ssico onde o caixeiro ? o motorista de um ve?culo que compartilha os custos de viagem com passageiros. Al?m de dividir os custos do percurso, o caixeiro pode se valer, tamb?m, dos descontos das high-occupancy vehicle lanes, que s?o faixas de tr?nsito que isentam ve?culos lotados do pagamento de ped?gio. A adi??o de passageiros ao PCV, um problema restrito ao roteamento, cria um vi?s colaborativo que ? intensificado pela considera??o das faixas especiais. Tal cen?rio confere ao problema estudado um aspecto ecol?gico, uma vez que seu estudo tem consequ?ncias diretas sobre o uso eficiente do espa?o urbano e a diminui??o da emiss?o de gases poluentes, contribuindo sobremaneira para o incremento da qualidade de vida. A pesquisa compreendeu desde a correla??o entre esse novo problema e outros constantes na literatura at? a concep??o de um conjunto de seiscentas inst?ncias artificiais e a cria??o de diversos m?todos de solu??o. Para a determina??o de ?timos, ? proposto um modelo matem?tico que suportou as solu??es por Programa??o Matem?tica e por Restri??es. Adicionalmente, ? apresentado um algoritmo branch-and-bound especificamente desenvolvido para o problema. Visando a busca por solu??es de qualidade em curto espa?o de tempo, s?o expostos cinco algoritmos experimentais com base nas abordagens heur?sticas Simulated Annealing, Variable Neighborhood Search, Coloniza??o de Abelhas e Algoritmos Gen?ticos. Diversos procedimentos auxiliares para constru??o de solu??es e execu??o de buscas locais s?o tamb?m expostos. Um experimento computacional ? realizado para compara??o entre os m?todos de solu??o. Uma amostra de cem casos teste ? utilizada para o processo estat?stico de ajuste de par?metros dos algoritmos heur?sticos, enquanto o restante das inst?ncias ? extensivamente abordado pelos m?todos. S?o determinados os ?timos para cento e cinquenta e cinco casos com tamanhos 10 e 20 cidades. Dentre os m?todos experimentais, cabe destacar a superioridade do algoritmo heur?stico que une as meta-heur?sticas Simulated Annealing e Variable Neighborhood Search. / The Traveling Salesman with Passengers and High Occupancy Problem is a version of the classic TSP where the salesman is the driver of a vehicle who shares travels? expenses with passengers. Besides shared expenses, the driver also benefits from discounts of the highoccupancy vehicle lanes, i.e. traffic lanes in which high occupancy vehicles are exempted from tolls. The addition of passengers to the TSP, a routing-only problem, creates a sharing view which is intensified by the consideration of special lanes. This scenario grants to the problem an ecological feature, since its study have direct consequences for the efficient use of urban space and the greenhouse gas emissions reduction, greatly contributing for quality of life improvement. This work addresses the study of this novel combinatorial optimization problem, going from the relationship it draws with other ones in the literature until the conception of a six hundred set of artificial test cases and the creation of many solution methods. To find optimal solutions, a mathematical model is proposed. This model supported the search for exact solutions by Mathematical and Constraint Programming. Additionally, is presented a branchand- bound algorithm specifically developed for the problem. Aiming the search for good quality solutions in short time period, five experimental algorithms based on the heuristics approaches Simulated Annealing, Variable Neighborhood Search, Bees Colony and Genetic Algorithms are introduced. Several auxiliary procedures for solutions generations and local search execution are revealed as well. A computational experiment is fulfilled to comparison between the solution methods. A sample of a hundred test cases is used for the heuristics algorithms? parameter tuning statistical process, while the rest of them are extensively addressed by the methods. The optimal solution for a hundred and fifty five test cases with sizes of 10 and 20 cities are determined. Among the experimental methods, one has to highlight the advantage of the heuristic algorithm that unites the metaheuristics Simulated Annealing and Variable Neighborhood Search.

In the US transportation system, environmental justice (EJ) issues are regulated by a variety of laws to ensure that all have fair treatment with respect to implementation of policies. If State Departments of Transportation adhere to all regulations properly but unconsciously, then an underlying negative impact on a community may still exist as a result of a newly implemented project. Since the implementation of High Occupancy Toll (HOT) lanes are fairly new, and since there have been numerous concerns from the public about their discriminatory nature, a decision support system is needed to identify potential EJ violations and issues when implementing a new or converted HOT lane. No prior model exists. The goal of this research is to assist state's Department of Transportation (DOT) in the early stages of the development of an HOT lane by developing a Potential Environmental Justice Violation Model that will help state agencies predict potential EJ violations before additional resources are invested into a project. By developing a model, this study identifies and classifies characteristic drivers of potential EJ violations related to communities' economic, social, or health and safety status. The Potential Environmental Justice Violation Model (PEJVM) allows state DOTs employees to define and evaluate the distribution of impacts in the relevant categories. The model provides a method for transforming complex qualitative and quantitative data about a project into a user-friendly format where the results can then be visualized using a spider radar diagram to determine the level of impact of each identified variable. The PEJVM was validated using two previous anonymous HOT case studies and demonstrated using the Interstate 85 Case Study in Atlanta, Georgia. This model offers a uniform method of identifying potential environmental justice violations when implementing a HOT lane. The model will also help inform state agencies of potential violations early in the planning stages of HOT lane projects so that the agency can solve any potential EJ issues before additional resources are invested.

High Occupancy Toll (HOT) lanes were recently proposed for I-85 in Atlanta as a way to relieve congestion and provide a reliable commute time for single occupant drivers that are willing to pay a toll. It is important to evaluate the air quality impacts of such a proposal to meet environmental regulations, such as the National Environmental Policy Act (NEPA) and Transportation Conformity Regulations. The goal of this study is to understand how vehicle mass emissions change as a result of implementing HOT lanes on I-85 in Atlanta . This is done by considering a number of factors affect mass vehicle emissions, such as vehicle activity, vehicle speeds, vehicle age distributions, and vehicle class distributions. These factors are incorporated into a base scenario, which models the current condition on I-85 with HOV lanes, and a future scenario, which models the implementation of HOT lanes on this corridor. The base scenario mainly uses data from a data collection effort by Georgia Tech during the summer of 2007 on the I-85 corridor, while the future scenario makes alterations to these data using information from other cities that have already implemented HOT lanes. The MOBILE-Matrix modeling tool, which was recently developed by Georgia Tech [16], was used to run the emissions analysis using the input factors from these data sources. This tool calculated mass emissions for five pollutants: HC, NOx, CO, PM2.5, and PM10. The results show very small increases in mass emissions for NOx, CO, PM2.5, and PM10, and very small decreases in mass emissions for HC. Therefore, the implementation of HOT lanes on I-85 in Atlanta is unlikely to violate the Transportation Conformity Rule. For NEPA purposes, this analysis could be used to make the case that air quality impacts are not significant, and therefore further detailed analyses are not required.

A 15.5-mile portion of the I-85 high-occupancy vehicle (HOV) lane in the metropolitan area of Atlanta, GA was converted to a high-occupancy toll (HOT) lane as part of a federal demonstration project designed to provide a reliable travel option through this congested corridor. Results from the I-85 demonstration project provided insight into the results that may follow the Georgia Department of Transportation's planned implementation of a $16 billion HOT lane network along metropolitan Atlanta's other major roadways [2]. To evaluate the impacts of the conversion, it was necessary to measure changes in corridor travel speed, reliability, vehicle throughput, passenger throughput, lane weaving, and user demographics. To measure such performance, a monitoring project, led by the Georgia Institute of Technology collected various forms of data through on-site field deployments, GDOT video, and cooperation from the State Road and Toll Authority (SRTA). Changes in the HOT lane's speed, reliability or other performance measure can affect the demographic and vehicle characteristics of those who utilize the corridor. The purpose of this particular study was to analyze the changes to the vehicle characteristics by comparing vehicle occupancy, vehicle classifications, and vehicle registration data to their counterparts from before the HOV-to-HOT conversion. As part of the monitoring project, the Georgia Tech research team organized a two-year deployment effort to collect data along the corridor during morning and afternoon peak hours. One year of data collection occurred before the conversion date to establish a control and a basis from which to compare any changes. The second year of data collection occurred after the conversion to track those changes and observe the progress of the lane's performance. While on-site, researchers collected data elements including visually-observed vehicle occupancy, license plate numbers, and vehicle classification [25]. The research team obtained vehicle records by submitting the license plate tag entries to a registration database [26]. In previous work, vehicle occupancy data were collected independently of license plate records used to establish the commuter shed. For the analyses reported in this thesis, license plate data and occupancy data were collected concurrently, providing a link between occupancy records of specific vehicles and relevant demographic characteristics based upon census data. The vehicle records also provided characteristics of the users' vehicles (light-duty vehicle vs. sport utility vehicle, model year, etc.) that the researchers aggregated to identify general trends in fleet characteristics. The analysis reported in this thesis focuses on identifying changes in vehicle characteristics that resulted from the HOV-to-HOT conversion. The data collected from post-conversion are compared to pre-conversion data, revealing changes in vehicle characteristics and occupancy distributions that most likely resulted from the implementation of the HOT lane. Plausible reasons affecting the vehicle characteristics alterations will be identified and further demographic research will enhance the data currently available to better pinpoint the cause and effect relationship between implementation and the current status of the I-85 corridor. Preliminary data collection outliers were identified by using vehicle occupancy data. However, future analysis will reveal the degree of their impact on the project as a whole. Matched occupancy and license plate data revealed vehicle characteristics for HOT lane users as well as indications that the tested data collectors are predominantly synchronized when concurrently collecting data, resulting in an argument to uphold the validity of the data collection methods. Chapter two provides reasons for why HOT lanes were sought out to replace I-85's HOV lanes. Chapter two will also provide many details regarding how the HOT lanes function and it will describe the role the Georgia Institute of Technology played in the assessment the HOV-to-HOT conversion. Chapter three includes the methodologies used to complete this document while chapter four provides results and analysis for the one year period before the conversion and the one year period after the conversion.

This paper examines the issues of equity, as applicable to the HOV-to-HOT conversion project planned for the I-85 North corridor in the Metropolitan Atlanta Region. A review of literature is undertaken to describe the typology of transportation equity issues within the wider context of environmental justice, and to highlight socio-economic factors and local and national transportation funding factors that influence people's travel choices and their mobility and accessibility options. Demographic data on the I-85 corridor peak period commuters in Metropolitan Atlanta is analyzed, in addition to results of focus groups polling current Metropolitan Atlanta interstate commuters on the topic of managed lanes during 2008. The thesis makes a conclusion that a final decision about the equity impact of the I-85 HOV-to-HOT conversion is likely not possible without undertaking a Metropolitan area-wide analysis. Some of the equity findings that emerge indicate that there are no significant income differences between the the HOV lane users and general purpose lane I-85 commuters; that there are differences between median incomes of block groups represented by current I-85 commuters (both HOV lane users and general purpose lane users) and median incomes of block groups typical for the base geography; and that investing in Xpress bus service improvements would primarily serve those households with more vehicles than drivers, unless improvements to reverse commute options and feeder bus networks are made. The focus group findings suggest that current interstate highway users in Metropolitan Atlanta, originating in the suburbs, are generally accepting of the HOT concept and recognize the value of travel time savings.