Esta tese está voltada para dois temas que vêm sendo, embora raramente juntos, objeto de freqüentes estudos por pesquisadores de todo o mundo: os modelos baseados em atividades para análise da demanda por transportes, e as complexas inter-relações entre características do uso do solo e transportes. De forma geral, o objetivo principal deste estudo é, a partir da aplicação de um modelo baseado em atividades, caracterizar a influência das características do uso do solo nas decisões individuais sobre quais atividades e viagens realizar. O esforço para tal estudo se justifica por alguns motivos. Primeiro, pelo fato da modelagem baseada em atividades ser apontada como metodologia promissora na análise de demanda por transportes, o que conduz à expectativa de que a mesma seja capaz de fornecer resultados que permitam alcançar o objetivo principal desta tese. Segundo, por não existirem, até os dias de hoje, registros de aplicação dessa nova metodologia em cidades brasileiras, este estudo irá permitir que alguns objetivos secundários sejam alcançados. São eles: verificar tanto a viabilidade de aplicação dessa metodologia nas cidades brasileiras de médio porte, bem como buscar a metodologia mais adequada para a coleta dos dados necessários para a calibração desses modelos. Este estudo exploratório torna possível ainda a divulgação no meio acadêmico de uma experiência do uso desses modelos no contexto brasileiro, o que poderá auxiliar e incentivar outros pesquisadores a desenvolverem novos estudos sobre o tema. Em termos concretos, esta pesquisa tornou possível identificar os custos e dificuldades associados à coleta de dados, bem como avaliar o desempenho do modelo, tanto em termos gerais, como em relação aos resultados direcionados para o objetivo geral proposto. No tocante a este último aspecto, os resultados do modelo não permitiram a realização de análises conclusivas sobre a inter-relação uso do solo e transportes, ao que tudo indica em virtude da quantidade de dados coletados não sido suficiente para caracterizar as variáveis de uso do solo de modo claro. Ainda assim, esta tese cumpre um importante papel do ponto de vista acadêmico, na medida em que inova nos campos conceitual, metodológico e tecnológico, além de servir como guia e incentivo para que outros pesquisadores aprofundem o estudo dos modelos baseados em atividades para modelagem da demanda por transportes / This study is directed to two themes that frequently are, although rarely together, the subject of research projects in many parts of the world: the use of activity based models for the analysis of transportation demand and the complex relationships among land use characteristics and transportation. The main aim of this work is to verify the influence of land use characteristics on individual activities and travel decisions, by means of an activity based model. The motivation for it comes from two aspects. First, activity based models are pointed by many authors as the most promising approach currently available for transportation demand analysis. As a consequence, it may be able to produce results that contribute for reaching the main objective of this study. Second, given that the search in the literature has shown no records of activity-based models applied to brazilian cities, this study also contributes to the some secondary objectives, as follows. It helps to test the viability of the modeling approach in Brazilian medium-sized cities and it is also useful for seeking the most appropriate method for the collection of data needed for model calibration. In addition, exploratory studies such as this one are important to disseminate the possibilities offered by the models in the brazilian context, what can encourage other researchers to direct efforts to the topic. In concrete terms, the application carried out in this investigation made possible not only to identify the costs and difficulties associated to data collection, but also to evaluate the model performance. Its performance was assessed in two ways: in general terms, and concerning the results specifically associated with the main objective of the study. With regard to the latter, the model results did not allow conclusive analyses about the land use-transportation relationship, apparently because the data sample was not comprehensive enough to clearly characterize land use variables. Even though, this investigation plays an important role from an academic standpoint, given that it brings innovation to the country in conceptual, methodological, and technological fields. As a consequence, its main merit is certainly to serve as a guide and an incentive to other brazilian researchers interested in the development of new studies about activity based models and their application to transportation demand modeling

Travel demand Management (TDM) focuses on improving the efficiency of the transportation system through changing traveler's travel behavior rather than expanding the infrastructure. An employer based integrated TDM program generally includes strategies designed to change the commuter's travel behavior in terms of mode choice, time choice and travel frequency. Research on TDM has focused on the evaluation of the effectiveness of TDM program to report progress and find effective strategies. Another research area, identified as high-priority research need by TRB TDM innovation and research symposium 1994 [Transportation Research Circular, 1994], is to develop tools to predict the impact of TDM strategies in the future. These tools are necessary for integrating TDM into the transportation planning process and developing realistic expectations. Most previous research on TDM impact evaluation was worksite-based, retrospective, and focused on only one or more aspects of TDM strategies. That research is generally based on survey data with small sample size due to lack of detailed information on TDM programs and promotions and commuter travel behavior patterns, which cast doubts on its findings because of potential small sample bias and self-selection bias. Additionally, the worksite-based approach has several limitations that affect the accuracy and application of analysis results. Based on the Washington State Commute Trip Reduction (CTR) dataset, this dissertation focuses on analyzing the participation rates of compressed work week schedules and telecommuting for the CTR affected employees, modeling the determinants of commuter's compressed work week schedules and telecommuting choices, and analyzing the quantitative impacts of an integrated TDM program on individual commuter's mode choice. The major findings of this dissertation may have important policy implications and help TDM practitioners better understand the effectiveness of the TDM strategies in terms of person trip and vehicle trip reduction. The models developed in this dissertation may be used to evaluate the impacts of an existing TDM program. More importantly, they may be incorporated into the regional transportation model to reflect the TDM impacts in the transportation planning process.

Since the beginning of the 21st Century, the world has seen the rapid development of the so-called "sharing economy" or collaborative consumption (Botsman, 2010). One of the first areas affected by the shared economy is vehicle ownership. With the emergence of several new providers of mobility services, such as Uber and car2go, there has been the promise of changes to the traditional way of owning and using a vehicle (Wong, Hensher, & Mulley, 2017). One potential consequence of shared mobility services is the reduction in vehicle ownership. At the same time, cities are trying to anticipate these changes by reducing the amount of space dedicated to parking, including parking requirements for residential developments. This thesis aims to assess the extent to which new shared mobility services (specifically, carsharing, bikesharing, and ridehailing) and travel demand management strategies (especially parking requirements and transit pass availability) relate to vehicle ownership among residents of multifamily dwellings. To do this, we use a web-based survey targeted to residents of multifamily apartments from Portland, Oregon. With these data, we built a multinomial logistic of the number of the vehicles owned as a function of socio-demographics, built environment, parking supply, transit passes, and three forms of shared mobility services. Results suggest that there is a strong association between shared mobility use and car ownership. However, it is not as significant as the effects of income, household size, distance to work, transit pass ownership, or even parking availability. Carshare use was negatively associated with the number of household vehicles, suggesting that it may be a useful tool in reducing car ownership. For respondents with higher education and income levels, increased carshare use was associated with fewer cars. Ridehail use, however, was not as clearly associated with reducing vehicle ownership and the effect was much smaller than that of carsharing. Parking availability in the building also has a significant and positive association with vehicle ownership. In sites with no parking available, there is an increased chance of the household owning less than two or more vehicles. However, this effect seems to disappear with the increased use of shared mobility. For all income levels, monthly use of ridehail and carshare between two and three times may decrease the odds of owning two or more vehicles. The use of both options, relaxing parking requirements and shared mobility availability, seems the best strategy to reduce vehicle ownership. In the short term, it is an alternative to those residents that decide to get rid of one or all cars but still are not ready to give up using cars. For the long term, a new relationship with vehicle ownership can be built now for the younger generation.

Thesis (Ph.D. (Town and Regional Planning))--North-West University, Potchefstroom Campus, 2008.

As transportation policies are changing to encourage alternative modes of transportation to reduce congestion problems and air quality impacts, more planning organizations are considering or implementing activity-based travel demand models to forecast future travel patterns. The proclivity towards operating activity-based models is the capability to model disaggregate travel data to better understand the model results that are generated with respect to the latest transportation policy implementations. This thesis first examines the differences between the two major modeling techniques used in the United States and then describes the assessment tool that was developed to recommend whether a region should convert to the advanced modeling procedures. This tool consists of parameters that were decided upon based on their known linkages to the advantages of activity-based models.

This research develops a framework to estimate the effective sample size of Global Positioning System (GPS) based panel surveys in urban travel behavior studies for a variety of planning purposes. Recent advances in GPS monitoring technologies have made it possible to implement panel surveys with lengths of weeks, months or even years. The many advantageous features of GPS-based panel surveys make such surveys attractive for travel behavior studies, but the higher cost of such surveys compared to conventional one-day or two-day paper diary surveys requires scrutiny at the sample size planning stage to ensure cost-effectiveness. The sample size analysis in this dissertation focuses on three major aspects in travel behavior studies: 1) to obtain reliable means for key travel behavior variables, 2) to conduct regression analysis on key travel behavior variables against explanatory variables such as demographic characteristics and seasonal factors, and 3) to examine impacts of a policy measure on travel behavior through before-and-after studies. The sample size analyses in this dissertation are based on the GPS data collected in the multi-year Commute Atlanta study. The sample size analysis with regard to obtaining reliable means for key travel behavior variables utilizes Monte Carlo re-sampling techniques to assess the trend of means against various sample size and survey length combinations. The basis for the framework and methods of sample size estimation related to regression analysis and before-and-after studies are derived from various sample size procedures based on the generalized estimating equation (GEE) method. These sample size procedures have been proposed for longitudinal studies in biomedical research. This dissertation adapts these procedures to the design of panel surveys for urban travel behavior studies with the information made available from the Commute Atlanta study. The findings from this research indicate that the required sample sizes should be much larger than the sample sizes in existing GPS-based panel surveys. This research recommends a desired range of sample sizes based on the objectives and survey lengths of urban travel behavior studies.

Urban traffic congestion is recognised as a major problem by most people in world cities. However, the implementation of congestion reducing measures on a wide scale eludes most world cities suffering from traffic congestion, as many oppose the notion of road pricing and despite economists and transportation professionals having advocated its benefits for a number of decades. The effects of road pricing have attracted considerable attention from researchers examining its effects, as it is thought to hold the key in understanding and overcoming some inherent obstacles to implementation. Unfortunately, many of the attempts consider the effects in isolation and with hypothetical, idealised and analytical tools, sometimes loosing sight of the complexities of the problem. This research empirically investigates the effects of road pricing in London, and identifies factors, which may prove to sustain it as a traffic reduction instrument. The results indicate that an integrated approach has to be developed and implemented, based upon the recognition of local perceptions, concerns, aspirations and locally acceptable solutions, if the acceptance of road pricing is to be improved. The key to dealing with the effects of road pricing, is to encourage a concerted effort by various stakeholders developing strategies considering a range of differing initiatives, coordinating and managing them in the realm of the political-economic context in which they exist. / Thesis (M.Art. et Scien. (Town and Regional Planning))--North-West University, Potchefstroom Campus, 2005.

Urban traffic congestion is recognised as a major problem by most people in world cities. However, the implementation of congestion reducing measures on a wide scale eludes most world cities suffering from traffic congestion, as many oppose the notion of road pricing and despite economists and transportation professionals having advocated its benefits for a number of decades. The effects of road pricing have attracted considerable attention from researchers examining its effects, as it is thought to hold the key in understanding and overcoming some inherent obstacles to implementation. Unfortunately, many of the attempts consider the effects in isolation and with hypothetical, idealised and analytical tools, sometimes loosing sight of the complexities of the problem. This research empirically investigates the effects of road pricing in London, and identifies factors, which may prove to sustain it as a traffic reduction instrument. The results indicate that an integrated approach has to be developed and implemented, based upon the recognition of local perceptions, concerns, aspirations and locally acceptable solutions, if the acceptance of road pricing is to be improved. The key to dealing with the effects of road pricing, is to encourage a concerted effort by various stakeholders developing strategies considering a range of differing initiatives, coordinating and managing them in the realm of the political-economic context in which they exist. / Thesis (M.Art. et Scien. (Town and Regional Planning))--North-West University, Potchefstroom Campus, 2005.

Much has been written about the desperate need to seek alternative solutions to the urban traffic congestion problems we face today. To manage these problems, three main streams of intervention have evolved from supply, demand and land-use management paradigms. Whilst their underlying measures all have the ability to reduce traffic congestion one way or another, little has been done to integrate the measures of each stream using a qualitative decision framework or process enabling the selection of site specific measures appropriate to local traffic and transport conditions. To this end the study reports the results of an empirical investigation by which a Multi-Criteria Analysis based Dynamic Adaptive Decision Framework (D.A.D.F.) were developed. This screens selected measures identifying those that have the potential to alleviate site specific road based traffic congestion. The product of the screening process is a set of sustainable measures transposed into an integrated strategy tailored to address local traffic congestion issues. Once the D.A.D.F. was developed, its usefulness and workability was tested by applying it to a case study. The case study results demonstrated that the D.A.D.F. is capable of producing integrated strategies with the ability to manage traffic congestion, encourage sustainable development and alleviate some site specific development challenges within the context of the study areas. Going beyond developing the decision framework, the study recommends positioning the D.A.D.F. within the South African planning system as part of a Traffic Congestion Management Plan (T.C.M.P.), setting out its likely components within the local context. It is concluded that the main innovation of the study is the development of the D.A.D.F., the T.C.M.P., the recommendations to situate both in the planning system and the comprehensive, but still transparent, approach undertaken to create integrated strategies for specific local conditions consisting of elements that work together to produce cumulative short to long term effects that attain a balanced set of environmental, social and economic goals - all imperative for sustainable development. / Thesis (Ph.D. (Town and Regional Planning))--North-West University, Potchefstroom Campus, 2008.

Much has been written about the desperate need to seek alternative solutions to the urban traffic congestion problems we face today. To manage these problems, three main streams of intervention have evolved from supply, demand and land-use management paradigms. Whilst their underlying measures all have the ability to reduce traffic congestion one way or another, little has been done to integrate the measures of each stream using a qualitative decision framework or process enabling the selection of site specific measures appropriate to local traffic and transport conditions. To this end the study reports the results of an empirical investigation by which a Multi-Criteria Analysis based Dynamic Adaptive Decision Framework (D.A.D.F.) were developed. This screens selected measures identifying those that have the potential to alleviate site specific road based traffic congestion. The product of the screening process is a set of sustainable measures transposed into an integrated strategy tailored to address local traffic congestion issues. Once the D.A.D.F. was developed, its usefulness and workability was tested by applying it to a case study. The case study results demonstrated that the D.A.D.F. is capable of producing integrated strategies with the ability to manage traffic congestion, encourage sustainable development and alleviate some site specific development challenges within the context of the study areas. Going beyond developing the decision framework, the study recommends positioning the D.A.D.F. within the South African planning system as part of a Traffic Congestion Management Plan (T.C.M.P.), setting out its likely components within the local context. It is concluded that the main innovation of the study is the development of the D.A.D.F., the T.C.M.P., the recommendations to situate both in the planning system and the comprehensive, but still transparent, approach undertaken to create integrated strategies for specific local conditions consisting of elements that work together to produce cumulative short to long term effects that attain a balanced set of environmental, social and economic goals - all imperative for sustainable development. / Thesis (Ph.D. (Town and Regional Planning))--North-West University, Potchefstroom Campus, 2008.