Public transit is considered a cost-effective alternative to mitigate the effects of traffic gridlock through the implementation of innovative service designs, and deploying new smart systems for operations control and traveller information. Public transport planners use transit assignment models to predict passenger loads and levels of service. Existing transit assignment approaches have limitations in evaluating the effects of information technologies, since they are neither sensitive to the types of information that may be provided to travellers nor to the traveller’s response to that information. Moreover, they are not adequate for evaluating the impacts of Intelligent Transportation Systems (ITS) deployments on service reliability, which in turn affect passengers’ behaviour. This dissertation presents an innovative transit assignment framework, namely the MIcrosimulation Learning-based Approach to TRansit ASsignment – MILATRAS. MILATRAS uses learning and adaptation to represent the dynamic feedback of passengers’ trip choices and their adaptation to service performance. Individual passengers adjust their behaviour (i.e. trip choices) according to their experience with the transit system performance. MILATRAS introduces the concept of ‘mental model’ to maintain and distinguish between the individual’s experience with service performance and the information provided about system conditions. A dynamic transit path choice model is developed using concepts of Markovian Decision Process (MDP) and Reinforcement Learning (RL). It addresses the departure time and path choices with and without information provision. A parameter-calibration procedure using a generic optimization technique (Genetic Algorithms) is also proposed. A proof-of-concept prototype has been implemented; it investigates the impact of different traveller information provision scenarios on departure time and path choices, and network performance. A large-scale application, including parameter calibration, is conducted for the Toronto Transit Commission (TTC) network. MILATRAS implements a microsimulation, stochastic (nonequilibrium-based) approach for modelling within-day and day-to-day variations in the transit assignment process, where aggregate travel patterns can be extracted from individual choices. MILATRAS addresses many limitations of existing transit assignment models by exploiting methodologies already established in the areas of traffic assignment and travel behaviour modeling. Such approaches include the microsimulation of transportation systems, learning-based algorithms for modelling travel behaviour, agent-based representation for travellers, and the adoption of Geographical Information Systems (GIS). This thesis presents a significant step towards the advancement of the modelling for the transit assignment problem by providing a detailed operational specification for an integrated dynamic modelling framework – MILATRAS.

Understanding how households make decisions with regards to their vehicle fleet based on their demographics, socio-economic status and travel patterns is critical for managing the financial, economic, social and environmental health of cities. Vehicle fleets therefore form a component of the Integrated Land Use, Transportation and Environment (ILUTE) modelling system under development at the University of Toronto. ILUTE is a year-by-year agent-based microsimulation model of demographics, land use and economic patterns, vehicle fleet decisions and travel choices in the Greater Toronto and Hamilton Area. This thesis extends previous work that modelled the quantity, class and vintage of vehicles in ILUTE households. This revised model offers three key improvements: transaction decisions are made sensitive to travel patterns, fuel costs are better represented, and vehicle purchases are considered in the context of the overall household budgeting. Results are promising, but further model validation is required. Potential extensions of the research are discussed.

The study assessed the extent of child poverty in South Africa using five different policy scenarios, and modelled the impact on poverty and inequalities of people living in households with children using the Foster-Greer-Thorbecke (FGT) index of poverty measurement, including poverty rate P0, (headcount index ratio), poverty gap index P1, (the depth of poverty), and the severity of poverty P2 (squared poverty gap index). Societal welfare inequalities have been measured using the Gini co-efficient. In general, the scenario analysis was based on the 2007 population baseline and 2008 government policy rules. The results of the study clearly indicate that there is a positive correlation between cash transfer (Child Support Grant) and a reduction in poverty and the inequalities of people living in households with children in South Africa. An increase in the Child Support Grant amount and the number of child beneficiaries, in modelling, produced a positive effect in addressing increasing child poverty and vulnerability. In addition, the research process identified four interrelated gaps that hinder the successful implementation of the social welfare policies underlying the Child Support Grant to reduce the poverty and inequality profile of people living in households with children in South Africa. First, inadequate understanding of the constitutional rights of the child exists. Second, failure to use proven best practice of institutional arrangements and implementation modalities was identified. Third, lack of political will for the championship of a universal basic income grant (UBIG) is present. Fourth, insufficient research, monitoring and evaluation (M&E) and dissemination of best practices is done. Within the context of the abovementioned analysis, the study finally brings into focus general observations gained from the investigation and provides recommendations to policy makers and other stakeholders.

Understanding how households make decisions with regards to their vehicle fleet based on their demographics, socio-economic status and travel patterns is critical for managing the financial, economic, social and environmental health of cities. Vehicle fleets therefore form a component of the Integrated Land Use, Transportation and Environment (ILUTE) modelling system under development at the University of Toronto. ILUTE is a year-by-year agent-based microsimulation model of demographics, land use and economic patterns, vehicle fleet decisions and travel choices in the Greater Toronto and Hamilton Area. This thesis extends previous work that modelled the quantity, class and vintage of vehicles in ILUTE households. This revised model offers three key improvements: transaction decisions are made sensitive to travel patterns, fuel costs are better represented, and vehicle purchases are considered in the context of the overall household budgeting. Results are promising, but further model validation is required. Potential extensions of the research are discussed.

Increasing demand for road freight has lead to a widespread adoption of more-productive large freight vehicles (LFVs), such as B-Doubles, by Australia's road freight industry. Individual LFVs have a greater potential to impact traffic efficiency through their greater length and poorer longitudinal performance. However, this is offset to an extent as fewer vehicles are required to perform a given freight task on a tonne-km basis. This research has developed a means of characterising the effects that large freight vehicles have on the performance of an urban arterial corridor managed by signalised intersections. A corridor-level microsimulation model was developed from first principles, which modelled the longitudinal performance of individual vehicles to a greater accuracy than most existing traffic simulation software does. The model was calibrated from traffic counts and GPS-equipped chase car surveys conducted on an urban arterial corridor in Brisbane's southern suburbs. The model was applied to various freight policy and traffic management scenarios, including freight vehicle mode choice, lane utilisation and traffic signal settings; as well as the effectiveness of green time extension for approaching heavy vehicles. Benefits were able to be quantified in terms of reduced travel times and stop rates for both heavy and light vehicles in urban arterial corridors.

abstract: Rapid developments are occurring in the arena of activity-based microsimulation models. Advances in computational power, econometric methodologies and data collection have all contributed to the development of microsimulation tools for planning applications. There has also been interest in modeling child daily activity-travel patterns and their influence on those of adults in the household using activity-based microsimulation tools. It is conceivable that most of the children are largely dependent on adults for their activity engagement and travel needs and hence would have considerable influence on the activity-travel schedules of adult members in the household. In this context, a detailed comparison of various activity-travel characteristics of adults in households with and without children is made using the National Household Travel Survey (NHTS) data. The analysis is used to quantify and decipher the nature of the impact of activities of children on the daily activity-travel patterns of adults. It is found that adults in households with children make a significantly higher proportion of high occupancy vehicle (HOV) trips and lower proportion of single occupancy vehicle (SOV) trips when compared to those in households without children. They also engage in more serve passenger activities and fewer personal business, shopping and social activities. A framework for modeling activities and travel of dependent children is proposed. The framework consists of six sub-models to simulate the choice of going to school/pre-school on a travel day, the dependency status of the child, the activity type, the destination, the activity duration, and the joint activity engagement with an accompanying adult. Econometric formulations such as binary probit and multinomial logit are used to obtain behaviorally intuitive models that predict children's activity skeletons. The model framework is tested using a 5% sample of a synthetic population of children for Maricopa County, Arizona and the resulting patterns are validated against those found in NHTS data. Microsimulation of these dependencies of children can be used to constrain the adult daily activity schedules. The deployment of this framework prior to the simulation of adult non-mandatory activities is expected to significantly enhance the representation of the interactions between children and adults in activity-based microsimulation models. / Dissertation/Thesis / M.S. Civil and Environmental Engineering 2010

O transporte urbano de cargas tem importÃncia fundamental dentro do processo de urbanizaÃÃo, o qual requer um modo de transportar seus bens e mercadorias. Entretanto, esse deslocamento, em uma percepÃÃo geral, contribui, de forma significativa, para problemas de congestionamento, poluiÃÃo, ruÃdo, dentre outros. Esta dissertaÃÃo tem por objetivo avaliar o impacto do uso de um VeÃculo Urbano de Cargas (VUC) sobre a operaÃÃo do trÃfego em Ãrea urbana, fazendo uso de uma ferramenta de microssimulaÃÃo de trÃfego, atravÃs da elaboraÃÃo e comparaÃÃo de cenÃrios propostos, tomando por base a Ãrea central do municÃpio de Fortaleza. O modelo inicial utilizou parÃmetros calibrados de um estudo em ambiente rodoviÃrio e foram criados trÃs cenÃrios alternativos que permitiram a anÃlise dos impactos do VUC na Ãrea estudada. Os resultados obtidos na simulaÃÃo apontam que a adoÃÃo de um VUC nÃo contribui de forma significativa na reduÃÃo do atraso e dos tempos de viagem, entretanto, apresenta melhoras quando associada à proibiÃÃo de estacionamento em via pÃblica. / Urban transport cargo is paramount within the urbanization process, which requires a way to transport their goods and merchandise. However, this displacement in a general sense, contributes significantly to problems of congestion, pollution, noise, among others. This paper aims to assess the impact of using a vehicle on Urban Freight traffic operation in an urban area, making use of a microsimulation tool traffic through the development and comparison of proposed scenarios, based on the central area the city of Fortaleza. The initial model used calibrated parameters of a study on road environment and three alternative scenarios were created that allowed the analysis of the impacts of VUC in the study area. The simulation results indicate that the adoption of a VUC not show performance gains in traffic, however, shows improvement when combined with prohibition of parking on public roads.

nÃo hà / A modelagem do trÃfego veicular em grandes Ãreas urbanas à uma ferramenta fundamental na anÃlise do desempenho de novas estratÃgias e polÃticas de gerÃncia e controle de trÃfego, idealizadas para potencializar a eficiÃncia do sistema de transportes. Com o uso de simuladores de trÃfego à possÃvel realizar estudos sobre os impactos de diferentes alternativas de intervenÃÃo, tais como a implementaÃÃo ou duplicaÃÃo de vias, alteraÃÃes na circulaÃÃo viÃria, entre outras aplicaÃÃes. Entretanto, os simuladores mais utilizados foram desenvolvidos em outros paÃses e geralmente nÃo representam o comportamento do trÃfego das redes viÃrias urbanas brasileiras, sendo, portanto necessÃria a calibraÃÃo dos seus parÃmetros. Com a evoluÃÃo tecnolÃgica dos modelos de microssimulaÃÃo de trÃfego, o processo de calibraÃÃo tornou-se ainda mais difÃcil devido ao maior nÃvel de complexidade dos modelos, o que implica no aumento do nÃmero de parÃmetros a serem calibrados. Diante do exposto e a fim de permitir a utilizaÃÃo de microssimuladores de trÃfego na modelagem de malhas viÃrias urbanas brasileiras, torna-se indispensÃvel o uso de mÃtodos computacionais de otimizaÃÃo que garantam, de forma eficaz, a calibraÃÃo simultÃnea de uma grande quantidade de parÃmetros. Essa dissertaÃÃo de mestrado busca verificar a aplicabilidade de algoritmos genÃticos para calibraÃÃo de modelos de microssimulaÃÃo do trÃfego veicular em malhas viÃrias urbanas como as encontradas no cenÃrio nacional. Ao final dessa pesquisa, concluiu-se que o mÃtodo de calibraÃÃo utilizado revelou-se eficiente considerando os resultados atingidos no estudo de caso realizado. AlÃm disto, acredita-se que a metodologia aqui proposta juntamente com os valores encontrados para os parÃmetros do microssimulador e do algoritmo genÃtico possam ser utilizados em outras malhas viÃrias urbanas, desde que estas apresentem caracterÃsticas semelhantes as da malha viÃria aqui simulada. / Traffic simulation modeling of mid-sized and big cities is a fundamental tool to analyze the performance of strategies idealized to maximize efficiency of urban transport systems. Traffic microsimulation models allow for foreseeing the impacts of different alternatives of solution, such as creation or duplication of lanes, reversion of flow direction, and implementation of priority lanes for public transport. However, the main microsimulation software packages available were developed in other countries, what means that they usually do not suit traffic behavior found in Brazilian urban centers, so parameter calibration is necessary to better adjust the models to local reality. Advances in computational capabilities have allowed traffic microsimulation models incorporate greater amount of parameters to be calibrated, so the process of calibration has become relatively more complex. Therefore, the use of computational methods to optimize the parametersâ values simultaneously is indispensable. This Masterâs thesis aims to verify the applicability of genetic algorithms to calibrate microsimulation traffic models in urban Brazilian networks. At the end of this study, it was concluded that the calibration method used proved to be efficient. It is believed that the proposed methodology to calibrate the microsimulation software and the genetic algorithm, as well as the final configuration of the genetic algorithm selected, may be applied to other urban networks, provided that they present similar characteristics to the studied network.

O tema deste trabalho compreende o estudo do impacto da educação no nível da renda e sua respectiva distribuição no Brasil ao longo dos anos (1993 a 2011). A metodologia adotada no estudo é um modelo de decomposição microeconométrica com simulações, no qual conseguimos avaliar o impacto da escolaridade sobre a pobreza e a desigualdade de renda. Destacamos dois principais resultados. Na simulação do efeito quantidade, temos que a educação explica 34% da queda no indicador de proporção de pobres entre 1993 e 2011, 43% da queda na proporção de extremamente pobres e 13% da queda no Gini (desigualdade de renda) no mesmo período. Para os anos entre 2001 e 2011, o efeito quantidade da educação explica 27% da queda na proporção de pobres e de extremamente pobres e apenas 1% da queda na desigualdade de renda ocorrida no período analisado. Já na simulação do efeito preço da educação, o impacto se mostrou relevante somente na queda na desigualdade de renda: a educação explica 15% da queda observada entre 1993 e 2011 e 33% da queda ocorrida entre 2001 e 2011. / The subject of this work is the impact of education on the level of income and its respective distribution in Brazil over the years (1993-2011). The methodology used in the study is a model of microeconometric decomposition with simulations in which we can isolate the impact of education on poverty and income inequality. We can highlight two main results. In the simulation of the quantity e ect, we have concluded that education explains 34% of the fall in the headcount index between the years 1993 and 2011, 43% of the fall in the headcount index using an indigence line and 13% of the fall in the Gini indicator (income inequality) in the same period . For the years between 2001 and 2011, the quantity e ect of education explains 27% of the fall in the headcount index (using both poverty and indigence lines) and only 1% of the fall in income inequality that happened during the period. In the simulation of the price e ect of education, the impact was also relevant but only in the fall in income inequality: education explains 15% of the fall observed between 1993 and 2011 and 33% of the fall that has occurred between 2001 and 2011.

[pt] Desenvolvemos um modelo de mercado de ações baseado em agentes e o simulamos numericamente. Os agentes são heterogêneos, possuem aversão ao risco e adotam estratégias de negociação provenientes da análise técnica. As flutuações são governadas por uma componente estocástica no investimento dos agentes. O modelo reproduz os fatos estilizados observados empiricamente nos mercados de ações no regime normal, tais como distribuição de retornos com caudas longas, memória de curto-alcance na série temporal de retornos e correlação de longo-alcance na volatilidade. Nossas simulações mostram que estes fenômenos empíricos emergem endogenamente do comportamento coletivo dos agentes, apesar da simplicidade do modelo. Isto sugere que a dinâmica complexa do mercado não surge da complexidade do comportamento individual dos investidores, mas sim da interação entre eles através da formação do preço de mercado. / [en] We develop a multi-agent based model of stock market and simulate it numerically. The agents are heterogeneous and risk-averse, adopting trading strategies deriving from technical analysis. The fluctuations are driven by a stochastic component in agent´s investment. The model is able to capture the stylized facts observed empirically in the stock markets in the normal regime, such as long tails in the distribution of returns, short-memory in the return temporal series and long-range correlation in volatility. Our simulations show that these empirical phenomenons emerge endogenously from the collective behavior of the agents, despite the simplicity of the model. This suggests that the complex market dynamics do not arise from the complexity of the individual investors but rather from interactions between them trough the market price formation.