Transit trips include four parts: the trip from the front door to the transit stop; the wait at the transit stop for the transit vehicle; the transit ride; and the trip from the transit drop off point to the final destination. This thesis explores methods of improving the pedestrian trips to and from the transit stop and the waiting period at the transit stop. People are not satisfied with their transit trips. People want better quality waiting areas, increased safety, comfortable surroundings, transit information, and convenience during the transit trip. This thesis explores the positive relationship between the quality of public streets and transit facilities, and ridership satisfaction. The thesis proposes that the transit trip can be improved by improving transit waiting areas, and the paths people take arriving at and departing from transit stops. BC Transit's Vancouver Regional Transit System's transit facilities are the focus of the study. Transit facilities include: bus stops, bus loops, bus exchanges, SkyTrain stations, and SeaBus terminals. The study reviews people's attitudes towards transit facilities and discusses the items that people consider important to a transit trip. This review includes a survey conducted by the author and a review of surveys conducted for BC Transit. A review of the literature provides further evidence on the basic requirements for transit facilities and a comparison is made with the local situation. The thesis explores the potential for land use planning, urban design and on-site design to improve the safety, comfort, and convenience of transit facilities. The role of BC Transit, in providing adequate transit facilities, is discussed along with the roles and responsibilities of other associated organizations including: the Province, the Greater Vancouver Regional District, municipal governments located within the Vancouver Region, private enterprise, and business improvement districts. The study concludes BC Transit should give more thought to the transit customer in the design and location of transit facilities. And that municipal governments must take action to improve the quality of streets and transit facilities in their own communities. / Applied Science, Faculty of / Community and Regional Planning (SCARP), School of / Graduate

Congested traffic corridors in dense urban areas are key contributors to the degradation of urban air quality. While waiting at bus stops, transit patrons may be exposed to greater amounts of vehicle-based pollution, including particulate matter, due to their proximity to the roadway. Current guidelines for the location and design of bus stops do not take into account air quality or exposure considerations. This thesis provides a unique contribution to roadside air quality studies and presents an innovative method for the consideration of bus shelter placement. Exposure to roadside pollutants is estimated for transit riders waiting at three-sided bus stop shelters that either: 1) face roadway traffic, or 2) face away from roadway traffic. Shelters were instrumented with particulate matter monitoring equipment, sonic anemometers for wind speed and direction, and vehicle counters capable of categorizing vehicles by length. Temperature and relative humidity were gathered from a nearby monitoring station. Data were collected for two different days at three shelters during both the morning and afternoon peak periods for a total of eleven data periods. Bus shelter orientation is found to significantly affect concentration of four sizes of particulate matter: ultrafine particles, PM1, PM2.5, and PM10. Shelters with an opening oriented towards the roadway were observed to have significantly higher concentrations inside the shelter than outside the shelter. In contrast, shelters oriented away from the roadway were observed to have significantly lower concentrations inside the shelter than outside the shelter. The differences in average particulate matter concentrations are statistically significant across all four sizes of particulate matter studied. Additional correlation and linear regression investigation reveals interactions between particulate concentrations and built environment characteristics, vehicle flow, and weather conditions. Temperature and relative humidity played a large role in the diurnal variation of average concentration levels. In all instances, particulate concentrations were greater during the morning period, often substantially so. Particulate concentrations are shown to vary based on both wind speed and direction. Vehicle flow is correlated with particulate levels, though significance is not consistent. Lagged vehicle flow is demonstrated to be more consistently significant. Regression analysis suggests weather factors such as wind, temperature, and relative humidity explain roughly 70% of particulate variation, while vehicle flow explains less than 6%.

The diploma thesis focuses on the assessment of transport infrastructure in Brno, the Sadová area and presents a solving proposal for selected problems. The work is based on the site's survey and measurement, as well as data collected from all available sources. The CDV methodology on road safety inspections in accordance with EU Directive 2008/96/EC was used as a basis for processing the analysis of individual sites. A detailed risk assessment is performed at four sites in the area where problems are identified and a proposal for their solution is given. In relation to public transport, the work also evaluates the individual bus stops, identifies major drawbacks, and contains suggestions for a comprehensive solution of bus stops emplacement. The proposal also includes suitable places for the implementation of pedestrian crossings on Kociánka.

No description available.

El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado. / Cities in the world aim to ensure the mobility of people, through the implementation of efficient Integrated Transportation Systems (ITS). This aims to improve the transport of people, which guarantees that they can be mobilized safely and without delays in the terminals and bus stops of the public transport system. The present article proposes a design of public transport stops aimed at optimizing the waiting time of users when transferring from one bus to another. For the validity of the proposal, the social force model of the Vissim program was used, where the behavior of the users within the bus stops was reflected. The results showed that the waiting times in the calibrated and validated microsimulation model were optimized by approximately 20%, which generates an improvement in the efficiency of the public transport system. / Revisión por pares

Satisfactory public transportation (PT) should enable people to reach attractive destinations and desired activities fast, comfortably, safely, and affordably. When PT fails to do so it will have negative effects on the overall accessibility in a society. Evaluating a PT system essentially means measuring to what extent the demand from the users is met, and for such an analysis understanding the concept of accessibility is paramount. Whether an individual will experience a high or a low level of accessibility will likely depend on their personal capabilities, as well as on the surrounding environment. Barriers obstructing an individual from using PT could for example be of physical of phycological nature or come in the shape of public space management disproportionally favoring certain groups of society. Low accessibility can thus be linked to social exclusion, since when a person cannot reach important destinations, their chances to participate in society will be subdued. To measure the accessibility of a PT system, and how a PT system affects the overall accessibility of a destination, it is common practice to use indicators that can represent different categories of social exclusion. This approach was the basis for constructing the performance measurement tool called Bus Stop Ranking Algorithm (BSRA) which was created in the QGIS application Graphical Modeler. BSRA calculates the usefulness of bus stops by counting the number of vulnerable groups, the number of workplaces, and the total population within comfortable walking distance from bus stops, as well as comparing travel times by car and bicycle from residential areas to important locations. The tool was ordered by a private PT company which will use it to make decisions regarding e.g., creating new bus stops, or for relocating, removing, or redesigning existing bus stops or bus routes. The Swedish municipality Lidingö was used as the study area to demonstrate how to use BSRA and how to interpret its output. Using equal weights for all indicators, it was discovered that 9 bus stops in the southern part of Lidingö could be regarded as particularly useful compared to the other 207 bus stops in the municipality. Variables such as the space-temporal component, i.e., changes during the day were not used. Socio economic factors such as segregation were also not highlighted, since all indicators had the same effect on the total scores. Adjusting the weights for some indicators could expose underlying dynamics affecting the total scores for the bus stops and help the PT company make design changes where they will be needed the most.

No description available.

[pt] A medição e classificação de descargas parciais constituem uma importante ferramenta de avaliação dos sistemas de isolamento utilizados em equipamentos de alta tensão. Após o pré-processamento dos dados, que captura, digitaliza e filtra o sinal de descargas parciais, geralmente eliminando os ruídos, existem basicamente duas etapas principais, que são a extração de características e a classificação de padrões. As descargas parciais contêm um conjunto de características discriminatórias únicas que lhes permitem ser reconhecidas. Assim, o primeiro procedimento no processo de classificação é definir quais delas podem ser utilizadas e qual o método de extração destas características. O fenômeno de descargas parciais tem uma natureza transitória e é caracterizado por correntes pulsantes com uma duração de vários nanossegundos até poucos microssegundos. Sua magnitude não é sempre proporcional ao dano causado, sendo que descargas de pequena magnitude podem levar rapidamente à evolução de um defeito. Por isso a necessidade de se entender bem este fenômeno e saber interpretar os dados. Além disso, equipamentos de alta tensão de grande porte, como motores e geradores, podem apresentar mais de uma fonte interna de descargas parciais, sendo importante separar os sinais dessas diferentes fontes antes de realizar a classificação. No caso de outros equipamentos de alta tensão de menor porte, como para-raios e transformadores de corrente de subestação, a simples detecção da presença de descargas parciais interna ao equipamento, independente do número de fontes, já é suficiente para indicar a retirada de operação destes equipamentos, dado seu baixo custo relativo e o elevado grau de importância destes para a confiabilidade do sistema onde estão inseridos. Para um diagnóstico completo e confíável de isolamentos de alta tensão, há a demanda por um sistema de análise capaz de promover com eficácia a detecção de descargas parciais internas aos equipamentos, a separação das diversas fontes de descargas parciais, no caso dos equipamentos de grande porte, bem como realizar a correta classificação do tipo de defeito, com base principalmente na análise das características discriminantes das diferentes fontes e na assinatura dos sinais para os diferentes defeitos. Este estudo contribui para o preenchimento desta lacuna, apresentando metodologias que se mostram robustas e precisas nos testes realizados, de modo que possam efetivamente orientar os especialistas em manutenção na tomada de decisões. Para fazer isso, são propostas novas variáveis capazes de extrair informações relevantes de sinais no tempo medidos em diversos tipos de isolamentos, sendo aplicadas aqui em dados obtidos em campo e em laboratório para avaliar sua eficácia na tarefa. Essas informações são tratadas utilizando técnicas de classificação de padrões e inteligência artificial para determinar de forma automática a presença de descargas parciais, o número de fontes diferentes e o tipo de defeito nos isolamentos de alta tensão utilizados no estudo. Outra contribuição do estudo é a criação de um banco de dados histórico, baseada em processamento de imagem, com padrões de mapas de descargas parciais conhecidos na literatura em máquinas rotativas, para serem utilizados na classificação de novos mapas medidos neste tipo de equipamento. / [en] Measurement and classification of partial discharges are an important tool for the evaluation of insulation systems used in high voltage equipments. After pre-processing of data, which captures, scans and filters the signal of partial discharges, generally eliminating noises, there are basically two main steps, which are the extraction of characteristics and the pattern classification. Partial discharges contain a set of unique discriminatory characteristics that allow them to be recognized. Thus, the first procedure in the classification process is to define which of them can be used and which is the method for extraction of those characteristics. The phenomenon of partial discharges has a transient nature and is characterized by pulsating currents with a duration of several nanoseconds up to a few microseconds. Its magnitude is not always proportional to the damage caused, and discharges of small magnitude can quickly lead to the evolution of a failure. Therefore the need to understand this phenomenon well and to know how to interpret the data. In addition, large high voltage equipments such as motors and generators may have more than one internal source of partial discharges, and it is important to separate the signals from those different sources prior to classification. In the case of smaller high voltage equipments, as surge arrester and substation current transformers, the simple detection of the presence of partial discharges inside the equipment, regardless of the number of sources, is sufficient to indicate the withdrawal of operation of the equipment, given their low relative cost and the high degree of importance of these to the reliability of the system where they are part of. For a complete and reliable diagnosis of high voltage insulations, there is a demand for an analysis system capable of effectively promoting the detection of the partial discharges internal to the equipments, the separation of the various sources of partial discharges in the case of large equipments, as well as to carry out the correct classification of the type of failure. The system should be based mainly on the analysis of the discriminating characteristics of the different sources and the signature of the signals for the different failure. This study contributes to fill this gap by presenting methodologies that are robust and accurate in the tests performed, so that they can effectively guide maintenance specialists in decision making. To do this, new variables are proposed to extract relevant information from time signals measured in various types of insulations, being applied here in field and laboratory data to evaluate their effectiveness in the task. This information is treated using standard classification techniques and artificial intelligence to automatically determine the presence of partial discharges, the number of different sources and the type of defect in the high voltage insulations used in the study. Another contribution of the study is the creation of a historical database, based on image processing, with partial discharge map patterns known in the literature on rotating machines, to be used in the classification of new maps measured in this type of equipment.

É muito comum modelar problemas em finanças com processos estocásticos, dada a incerteza de suas variáveis de análise. Além disso, problemas reais nesse domínio são, em geral, de grande custo computacional, o que sugere a utilização de plataformas de alto desempenho (HPC) em sua implementação. As novas gerações de arquitetura de hardware gráfico (GPU) possibilitam a programação de propósito geral enquanto mantêm alta banda de memória e grande poder computacional. Assim, esse tipo de arquitetura vem se mostrando como uma excelente alternativa em HPC. Com isso, a proposta principal desse trabalho é estudar o ferramental matemático e computacional necessário para modelagem estocástica em finanças com a utilização de GPUs como plataforma de aceleração. Para isso, apresentamos a GPU como uma plataforma de computação de propósito geral. Em seguida, analisamos uma variedade de geradores de números aleatórios, tanto em arquitetura sequencial quanto paralela. Além disso, apresentamos os conceitos fundamentais de Cálculo Estocástico e de método de Monte Carlo para simulação estocástica em finanças. Ao final, apresentamos dois estudos de casos de problemas em finanças: \"Stops Ótimos\" e \"Cálculo de Risco de Mercado\". No primeiro caso, resolvemos o problema de otimização de obtenção do ganho ótimo em uma estratégia de negociação de ações de \"Stop Gain\". A solução proposta é escalável e de paralelização inerente em GPU. Para o segundo caso, propomos um algoritmo paralelo para cálculo de risco de mercado, bem como técnicas para melhorar a solução obtida. Nos nossos experimentos, houve uma melhora de 4 vezes na qualidade da simulação estocástica e uma aceleração de mais de 50 vezes. / Given the uncertainty of their variables, it is common to model financial problems with stochastic processes. Furthermore, real problems in this area have a high computational cost. This suggests the use of High Performance Computing (HPC) to handle them. New generations of graphics hardware (GPU) enable general purpose computing while maintaining high memory bandwidth and large computing power. Therefore, this type of architecture is an excellent alternative in HPC and comptutational finance. The main purpose of this work is to study the computational and mathematical tools needed for stochastic modeling in finance using GPUs. We present GPUs as a platform for general purpose computing. We then analyze a variety of random number generators, both in sequential and parallel architectures, and introduce the fundamental mathematical tools for Stochastic Calculus and Monte Carlo simulation. With this background, we present two case studies in finance: ``Optimal Trading Stops\'\' and ``Market Risk Management\'\'. In the first case, we solve the problem of obtaining the optimal gain on a stock trading strategy of ``Stop Gain\'\'. The proposed solution is scalable and with inherent parallelism on GPU. For the second case, we propose a parallel algorithm to compute market risk, as well as techniques for improving the quality of the solutions. In our experiments, there was a 4 times improvement in the quality of stochastic simulation and an acceleration of over 50 times.

É muito comum modelar problemas em finanças com processos estocásticos, dada a incerteza de suas variáveis de análise. Além disso, problemas reais nesse domínio são, em geral, de grande custo computacional, o que sugere a utilização de plataformas de alto desempenho (HPC) em sua implementação. As novas gerações de arquitetura de hardware gráfico (GPU) possibilitam a programação de propósito geral enquanto mantêm alta banda de memória e grande poder computacional. Assim, esse tipo de arquitetura vem se mostrando como uma excelente alternativa em HPC. Com isso, a proposta principal desse trabalho é estudar o ferramental matemático e computacional necessário para modelagem estocástica em finanças com a utilização de GPUs como plataforma de aceleração. Para isso, apresentamos a GPU como uma plataforma de computação de propósito geral. Em seguida, analisamos uma variedade de geradores de números aleatórios, tanto em arquitetura sequencial quanto paralela. Além disso, apresentamos os conceitos fundamentais de Cálculo Estocástico e de método de Monte Carlo para simulação estocástica em finanças. Ao final, apresentamos dois estudos de casos de problemas em finanças: \"Stops Ótimos\" e \"Cálculo de Risco de Mercado\". No primeiro caso, resolvemos o problema de otimização de obtenção do ganho ótimo em uma estratégia de negociação de ações de \"Stop Gain\". A solução proposta é escalável e de paralelização inerente em GPU. Para o segundo caso, propomos um algoritmo paralelo para cálculo de risco de mercado, bem como técnicas para melhorar a solução obtida. Nos nossos experimentos, houve uma melhora de 4 vezes na qualidade da simulação estocástica e uma aceleração de mais de 50 vezes. / Given the uncertainty of their variables, it is common to model financial problems with stochastic processes. Furthermore, real problems in this area have a high computational cost. This suggests the use of High Performance Computing (HPC) to handle them. New generations of graphics hardware (GPU) enable general purpose computing while maintaining high memory bandwidth and large computing power. Therefore, this type of architecture is an excellent alternative in HPC and comptutational finance. The main purpose of this work is to study the computational and mathematical tools needed for stochastic modeling in finance using GPUs. We present GPUs as a platform for general purpose computing. We then analyze a variety of random number generators, both in sequential and parallel architectures, and introduce the fundamental mathematical tools for Stochastic Calculus and Monte Carlo simulation. With this background, we present two case studies in finance: ``Optimal Trading Stops\'\' and ``Market Risk Management\'\'. In the first case, we solve the problem of obtaining the optimal gain on a stock trading strategy of ``Stop Gain\'\'. The proposed solution is scalable and with inherent parallelism on GPU. For the second case, we propose a parallel algorithm to compute market risk, as well as techniques for improving the quality of the solutions. In our experiments, there was a 4 times improvement in the quality of stochastic simulation and an acceleration of over 50 times.