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.

A region's evacuation strategy encompasses a variety of areas and needs. Primary among these is the minimization of total evacuation time, represented in models as the clearance time estimate (CTE). A generic testbed simulation network model was developed. An input/output (I/O) analysis was performed to establish a theoretical baseline CTE. Results were compared with simulations; analysis showed that the I/O method underestimated simulated CTE as a function of network size, with a correction factor range of 1.09 to 1.19. A regression model was developed for the generic network. Predictors were total trips, and network size defined as a function of origin-destination distance. Total Trips ranged between 40,000 and 60,000. Holding size constant, R-squared values ranged from 97.1 to 99.3, indicating a high goodness of fit. Holding Total Trips constant, R-squared values ranged from 74.5 to 89.2. Finally, both Total Trips and size were used as predictors; the resulting regression model had an R-squared value of 97.3. This overall model is more useful, since real world situations are not fixed in nature. The overall regression model was compared to a case network. The generic network regression model provided a close CTE approximation; deltas ranged from -4.7% to 8.6%. It was concluded that a generic network can serve as a surrogate for a case network over these ranges. This study developed and evaluated heuristic strategies for evacuation using the generic network. Strategies were compared with a simultaneous departure loading scenario. Six different grouping strategies were evaluated. An initial evaluation was conducted using the generic network, and strategies that showed potential CTE reduction were implemented on the case study network. Analysis indicated that the HF-10 (half-far) grouping for 60k total trips showed potential reduction. A complete simulation was conducted on the case network for all HF scenarios; an ANOVA was run using Dunnett's comparison. Results indicated that the HF grouping with 20% and 30% departure shifts showed potential for CTE reduction. From this it was concluded that the generic network could be used as a testbed for strategies that would show success on a case network.

<p>This study explores telecommuter travel behaviour by examining discretionary travel distance and mode choice. The study utilizes data obtained from the 2005 origin-destination survey conducted by TRANS, a joint transportation planning committee serving the National Capital Region of Canada. The study compares and explains the discretionary travel behavior of teleworkers relative to other population groups and identifies that the average teleworker travels 3 times farther than regular workers and 1.7 times farther than non-workers for discretionary purposes. Regression indicates that dependent children, vehicle accessibility, housing type, residential distance to the urban core, land-use mix, residence within a Greenbelt region and day of the week all positively affect travel distance. Conversely, age, proximity to shopping centers and inclement weather demonstrate significant negative effects. Then, through binary logistic regression, the study confirms that work status significantly influences mode choice. Similarly, the following predictor variables demonstrate a significant positive effect towards active mode choice: teleworker work status, larger household size, greater income, warmer temperature, closer proximity to shopping centers, apartment housing type, trips for recreational and restaurant purposes, taking subsequent trips in a day, and travel between 8:00 A.M. and 4:00 P.M. On the contrary, increased entropy, trips within the Greenbelt region, dependent children under 16 years old, increased vehicle accessibility and trips for transporting someone or for shopping purposes all reduce the probability of active travel mode choice.</p> / Master of Arts (MA)

A Região Metropolitana de São Paulo (RMSP) sofre de sérios problemas de congestionamento, assim como muitas outras cidades de grande porte. Uma possível solução, proposta por pesquisadores de transportes, economia e ciências ambientais, é a implantação de um sistema de congestion charging, chamada no Brasil de pedágio urbano. Um dos objetivos do presente trabalho foi estabelecer os conceitos relacionados a este assunto e ilustrar as principais questões relacionadas à sua implantação. Espera-se que este trabalho possa auxiliar o desenvolvimento de estudos de avaliação da viabilidade e de impactos de sistemas propostos de congestion charging. Para atingir este objetivo, toca-se em diversos assuntos, como a definição de congestionamento e as formas de medi-lo, a base conceitual e teórica dos sistemas de congestion charging e seus diversos esquemas de diferenciação. São expostas também as medidas de mitigação de congestionamento que já foram implantadas na RMSP, quais foram os estudos já desenvolvidos considerando este tipo de política para a RMSP, e casos em que sistemas de congestion charging já foi implantado. Neste trabalho, desenvolveu-se também um modelo de escolha discreta a partir dos dados da Pesquisa Origem e Destino 2007 do METRÔ, onde pessoas deveriam escolher entre \"Transporte Coletivo\" e \"Transporte Público\". Este modelo foi utilizado para avaliar o potencial de impacto na divisão modal e de arrecadação de um congestion charge aplicado ao centro expandido de São Paulo. Adverte-se, porém, que os resultados obtidos são meramente ilustrativos. Mostra-se, também, que é possível avaliar a capacidade ociosa do sistema de transporte coletivo a partir dos dados disponíveis de bilhetagem e de GPS dos ônibus. Este processo é exemplificado através do cálculo de capacidade de uma única viagem de um único ônibus, dada a dificuldade de automatização deste processo para abranger toda a frota. / The São Paulo Metropolitan Region (SPMR) suffers from severe traffic congestion, as do many other large-scale urban areas around the world. A possible solution to this issue, which has been suggested by transportation, economics and environmental researchers, is the implementation of a congestion charging system. One of the objectives of this project is to establish clear concepts and shed light on the main issues regarding these systems by means of a comprehensive literary review. It is expected that this project may help the development of in-depth studies carried in order to evaluate the viability and impacts of congestion charging proposals. In order to achieve this goal, many subjects are addressed, such as the definition of congestion, how its measured, the theoretical backgrounds that support congestion charging schemes, their different degrees of differentiation, which policies were enacted in order to reduce traffic congestion in São Paulo, what considerations and studies have already been developed for Brazil and São Paulo regarding these systems and where have these systems been successfully installed. Later chapters deal with another goal of this project: estimating how a congestion charging system would affect SPMR. This was achieved through a multinomial logit model, where decision-makers choose between \"Public Transportation\" and \"Private Automobile\". The results presented at this phase are merely indicative of certain tendencies and should not be considered final. This project also attempts to show that given the available Automated Fare Collection (AFC) data and Automated Vehicle Location (AVL) data, it is possible to estimate the current public transportation system\'s unused capacity. The author shows this by calculating the capacity of one bus trip using these data, but also explains the difficulties of expanding this analysis to the whole of SPMR\'s public transportation system.

Automobile use is associated with significant problems such as air pollution and obesity. Decisions to use the automobile or its alternatives, including walk, bicycle, and public transit, are believed to be associated with urban form. However, in contrast to the hypothesis that compact urban form significantly reduces automobile travel, previous studies reported only a modest effect on travel behavior. These studies, largely built on microeconomic utility theory, are not sufficient for assessing the effect of compactness, for several reasons: (1) The studies postulate that travel invokes only disutility, but travel may also provide intrinsic utility or benefits insomuch as people travel for its own sake; (2) the studies have traditionally focused on how urban compactness reduces the distance between trip origin and destination and accordingly reduces trip time, but urban compactness also increases congestion and reduces trip speed, and thus increases trip time; and (3) the studies have mostly examined automobile commuting, but people travel for various purposes, using different travel modes, and the impact of urban compactness on the utility of non-automobile non-commuting travel has not been duly examined. On this ground, to better explain the effects that urban compactness has on travel behavior, this dissertation refines the concept of travel utility using two additions to the microeconomic utility theory: activity-based utility theory of derived travel demand and approaches to positive utility of travel. Accordingly, it designs a conceptual model that specifies travel utility as an intermediary between urban compactness and travel behavior and examines the behavior associated with and utility derived from travel mode choices for alternative purposes of travel. Twenty individual models are derived from the conceptual model and tested within the context of Seoul, Korea, using a confirmatory approach of structural equation modeling and data from geographic information systems and a structured sample survey, which is initially designed and validated by semi-structured interviews and subsequent statistical tests. By comparing the individual models, this research concludes that the urban compactness effect on travel behavior, represented by trip frequencies and supplemented by mode shares, is better explained when travel utility is considered and if travel purposes are separately examined. Major empirical findings are that urban compactness affects travel behavior mainly by increasing the benefits of travel in comparison to its modest effect on the cost reduction and people’s behavioral response to urban compactness is to shift modes of commuting travel, decrease travel for shopping, and increase travel for leisure. These purpose-specific findings have implications for transportation planners and public health planners by assisting them in linking plans and policies concerning urban compactness to travel purposes.

A Região Metropolitana de São Paulo (RMSP) sofre de sérios problemas de congestionamento, assim como muitas outras cidades de grande porte. Uma possível solução, proposta por pesquisadores de transportes, economia e ciências ambientais, é a implantação de um sistema de congestion charging, chamada no Brasil de pedágio urbano. Um dos objetivos do presente trabalho foi estabelecer os conceitos relacionados a este assunto e ilustrar as principais questões relacionadas à sua implantação. Espera-se que este trabalho possa auxiliar o desenvolvimento de estudos de avaliação da viabilidade e de impactos de sistemas propostos de congestion charging. Para atingir este objetivo, toca-se em diversos assuntos, como a definição de congestionamento e as formas de medi-lo, a base conceitual e teórica dos sistemas de congestion charging e seus diversos esquemas de diferenciação. São expostas também as medidas de mitigação de congestionamento que já foram implantadas na RMSP, quais foram os estudos já desenvolvidos considerando este tipo de política para a RMSP, e casos em que sistemas de congestion charging já foi implantado. Neste trabalho, desenvolveu-se também um modelo de escolha discreta a partir dos dados da Pesquisa Origem e Destino 2007 do METRÔ, onde pessoas deveriam escolher entre \"Transporte Coletivo\" e \"Transporte Público\". Este modelo foi utilizado para avaliar o potencial de impacto na divisão modal e de arrecadação de um congestion charge aplicado ao centro expandido de São Paulo. Adverte-se, porém, que os resultados obtidos são meramente ilustrativos. Mostra-se, também, que é possível avaliar a capacidade ociosa do sistema de transporte coletivo a partir dos dados disponíveis de bilhetagem e de GPS dos ônibus. Este processo é exemplificado através do cálculo de capacidade de uma única viagem de um único ônibus, dada a dificuldade de automatização deste processo para abranger toda a frota. / The São Paulo Metropolitan Region (SPMR) suffers from severe traffic congestion, as do many other large-scale urban areas around the world. A possible solution to this issue, which has been suggested by transportation, economics and environmental researchers, is the implementation of a congestion charging system. One of the objectives of this project is to establish clear concepts and shed light on the main issues regarding these systems by means of a comprehensive literary review. It is expected that this project may help the development of in-depth studies carried in order to evaluate the viability and impacts of congestion charging proposals. In order to achieve this goal, many subjects are addressed, such as the definition of congestion, how its measured, the theoretical backgrounds that support congestion charging schemes, their different degrees of differentiation, which policies were enacted in order to reduce traffic congestion in São Paulo, what considerations and studies have already been developed for Brazil and São Paulo regarding these systems and where have these systems been successfully installed. Later chapters deal with another goal of this project: estimating how a congestion charging system would affect SPMR. This was achieved through a multinomial logit model, where decision-makers choose between \"Public Transportation\" and \"Private Automobile\". The results presented at this phase are merely indicative of certain tendencies and should not be considered final. This project also attempts to show that given the available Automated Fare Collection (AFC) data and Automated Vehicle Location (AVL) data, it is possible to estimate the current public transportation system\'s unused capacity. The author shows this by calculating the capacity of one bus trip using these data, but also explains the difficulties of expanding this analysis to the whole of SPMR\'s public transportation system.

This thesis explores how revenue management (RM) principles would integrate into a parking system, and how advanced reservation-making, coupled with dynamic pricing (based on booking limits) could be used to maximize parking revenue. Detailed here is a comprehensive RM strategy for the parking industry, and an integer programming formulation that maximizes parking revenue over a system of garages is presented. Furthermore, an intelligent parking reservation model is developed that uses an artificial neural network procedure for online reservation decision-making. Next, the work evaluates whether the implementation of a parking RM system in a dense urban parking district (and thus avoiding "trial-and-error" behaviors exhibited by drivers) mitigates urban congestion levels. In order to test this hypothesis, a parallel modeling structure was developed that uses a real-time decision-making model that either accepts or rejects requests for parking via a back-propagation neural network. Coupled with the real-time decision-making model is a micro-simulation model structure used to evaluate the policy's effects on network performance. It is clear from the results that the rate at which parkers renege is a primary determinant of the value of the implementation of RM. All other things being equal, the RM model in which the majority of parkers is directed to their precise parking spot via the most direct route is much more robust to the random elements within the network that can instigate extreme congestion. The thesis then moves from micro-evaluation to macro-evaluation by measuring the performance of the urban parking system from the perspective of the set of relevant stakeholders using the hyperbolic DEA model within the context of the matrix DEA construct. The stakeholder models, including that of the provider, the user, and the community, have defined inputs/outputs to the hyperbolic DEA model, which allows for the inclusion of undesirable outputs such as network delay and incidence of extreme congestion. Another key contribution of this work is that of identifying design issues for current and future dense urban parking districts. Clearly, reneging rate and the tenacity of perspective parkers is a key consideration in cases where RM policy is not implemented. / Ph. D.

Many metropolitan cities motivate people to exploit public bike-sharing programs as alternative transportation for many reasons. Due to its’ popularity, multiple types of research on optimizing public bike-sharing systems is conducted on city-level, neighborhood-level, station-level, or user-level to predict the public bike demand. Previously, the research on the public bike demand prediction primarily focused on discovering a relationship with weather as an external factor that possibly impacted the bike usage or analyzing the bike user trend in one aspect. This work hypothesizes two external factors that are likely to affect public bike demand: weather and air pollution. This study uses a public bike data set, daily temperature, precipitation data, and air condition data to discover the trend of bike usage using multiple machine learning techniques such as Decision Tree, Naïve Bayes, and Random Forest. After conducting the research, each algorithm’s output is evaluated with performance comparisons such as accuracy, precision, or sensitivity. As a result, Random Forest is an efficient classifier for the bike demand prediction by weather and precipitation, and Decision Tree performs best for the bike demand prediction by air pollutants. Also, the three class labelings in the daily bike demand has high specificity, and is easy to trace the trend of the public bike system.