Thesis (M.App.Sc.) - Carleton University, 2007. / Includes bibliographical references (p. 142-144). Also available in electronic format on the Internet.

Os sistemas de transporte público por ônibus têm sido cada vez mais relevantes para o desenvolvimento das cidades. Técnicas para melhorar o planejamento e o controle da operação diária dos serviços de ônibus apresentaram melhorias significativas ao longo dos anos, e a previsão do tempo de viagem desempenha um importante papel no planejamento e nas estratégias da operação diária. A antecipação dos tempos de viagem ajuda os planejadores e controladores a evitar os vários problemas que surgem durante a operação diária da linha de ônibus. Ela também permite manter os usuários informados para que eles possam planejar com antecedência a sua viagem. Vários estudos relacionados à previsão do tempo de viagem podem ser encontrados na literatura. Devido a sua dificuldade intrínseca, o problema foi abordado por diferentes técnicas. Resultados numéricos de estudos demonstram o potencial uso de redes neurais em relação a outras técnicas. No entanto, a literatura não apresenta aplicações que incorporem uma retroalimentação das informações contidas em séries temporais, como é feito por redes neuronais recorrentes. A maioria dos estudos na literatura tem sido realizada com dados de cidades específicas e com linhas de ônibus com paradas fixas. A situação que surge em linhas de ônibus sem paradas fixas operadas com micro-ônibus apresenta uma dinâmica diferente dos estudos de caso da literatura Além disso, os estudos existentes não usam o gráfico de marcha como um instrumento de apoio para a previsão do tempo de viagem em ônibus. Nesta tese, estuda-se o problema da previsão do tempo de viagem para linhas de micro-ônibus sem paradas fixas, utilizando as informações básicas do gráfico de marcha. O modelo proposto é baseado em redes neurais recorrentes. Os dados de entrada incluem: (i) a hora de início da viagem do ônibus, (ii) sua posição atual em coordenadas GPS, (iii) o tempo atual e (iv) a distância percorrida após um minuto. As redes são treinadas com dados de uma linha de micro-ônibus da cidade de Porto Alegre, Brasil. Os dados correspondem ao ano de 2015. Os modelos fornecem previsões para a distância percorrida minuto a minuto e para uma janela de tempo de 30 minutos. O modelo desenvolvido foi treinado com um conjunto abrangente de dados de dias úteis, incluindo períodos de pico e fora de pico. Os dados de treinamento não desconsideraram informações de qualquer dia devido à ocorrência de eventos especiais. Concluiu-se que os modelos de redes neurais recorrentes desenvolvidos são capazes de absorver a dinâmica do movimento dos micro-ônibus. A informação produzida apresenta um nível adequado de precisão a ser utilizado para informar os usuários. Também é adequada para planejadores e controladores da operação, pois pode ajudar a identificar situações problemáticas em janelas de tempo futuras. / Public transport systems by bus have been increasingly relevant for the development of cities. Techniques to improve planning and control of daily operation of bus services presented significant improvements along the years, and travel time forecast plays an important hole in both planning and daily operation strategies. Travel times anticipation helps planners and controllers to anticipate the various issues that arise during the daily bus line operation. It also allows keeping users informed, so they can plan in advance for their trip. Several studies related to travel time prediction can be found in the literature. Due to its intrinsic difficulty, the problem has been addressed by different techniques. Numerical results from studies demonstrate the potential use of neural networks in relation to other techniques. However, the literature does not present applications that incorporate a feedback of the information contained in time series as it is done by recurrent neural networks. Most of the studies in the literature have been conducted with data from specific cities and buses lines with fixed stops. The situation that arises in bus lines without fixed stops operated with microbuses present a different dynamics from the literature case studies. In addition, existing studies do not use time-space trajectories as a supporting instrument for bus travel time prediction. In this thesis we study the problem of travel time prediction for microbus lines without fixed stops using the basic information of the time-space trajectories The proposed model is based on recurrent neural networks. The input data includes: (i) the start time of the bus trip, (ii) its current position in GPS coordinates, (iii) the current time and (iv) distance travelled after one minute. The networks are trained with data from a microbus line from the city of Porto Alegre, Brazil. Data corresponds to the year 2015. The model provide forecasts for distance travelled minute by minute, and for a time window of 30 minutes. The developed models were trained with a comprehensive set of data from working days including peak and off-peak periods. The training data did not disregard information from any day due to occurrence of special events. It was concluded that the recurrent neural network model developed is capable of absorbing the dynamics of the microbuses movement. The information produced present an adequate level of precision to be used for users information. It is also adequate for planners and operation controllers as it can help to identify problematic situations in future time windows.

Os sistemas de transporte público por ônibus têm sido cada vez mais relevantes para o desenvolvimento das cidades. Técnicas para melhorar o planejamento e o controle da operação diária dos serviços de ônibus apresentaram melhorias significativas ao longo dos anos, e a previsão do tempo de viagem desempenha um importante papel no planejamento e nas estratégias da operação diária. A antecipação dos tempos de viagem ajuda os planejadores e controladores a evitar os vários problemas que surgem durante a operação diária da linha de ônibus. Ela também permite manter os usuários informados para que eles possam planejar com antecedência a sua viagem. Vários estudos relacionados à previsão do tempo de viagem podem ser encontrados na literatura. Devido a sua dificuldade intrínseca, o problema foi abordado por diferentes técnicas. Resultados numéricos de estudos demonstram o potencial uso de redes neurais em relação a outras técnicas. No entanto, a literatura não apresenta aplicações que incorporem uma retroalimentação das informações contidas em séries temporais, como é feito por redes neuronais recorrentes. A maioria dos estudos na literatura tem sido realizada com dados de cidades específicas e com linhas de ônibus com paradas fixas. A situação que surge em linhas de ônibus sem paradas fixas operadas com micro-ônibus apresenta uma dinâmica diferente dos estudos de caso da literatura Além disso, os estudos existentes não usam o gráfico de marcha como um instrumento de apoio para a previsão do tempo de viagem em ônibus. Nesta tese, estuda-se o problema da previsão do tempo de viagem para linhas de micro-ônibus sem paradas fixas, utilizando as informações básicas do gráfico de marcha. O modelo proposto é baseado em redes neurais recorrentes. Os dados de entrada incluem: (i) a hora de início da viagem do ônibus, (ii) sua posição atual em coordenadas GPS, (iii) o tempo atual e (iv) a distância percorrida após um minuto. As redes são treinadas com dados de uma linha de micro-ônibus da cidade de Porto Alegre, Brasil. Os dados correspondem ao ano de 2015. Os modelos fornecem previsões para a distância percorrida minuto a minuto e para uma janela de tempo de 30 minutos. O modelo desenvolvido foi treinado com um conjunto abrangente de dados de dias úteis, incluindo períodos de pico e fora de pico. Os dados de treinamento não desconsideraram informações de qualquer dia devido à ocorrência de eventos especiais. Concluiu-se que os modelos de redes neurais recorrentes desenvolvidos são capazes de absorver a dinâmica do movimento dos micro-ônibus. A informação produzida apresenta um nível adequado de precisão a ser utilizado para informar os usuários. Também é adequada para planejadores e controladores da operação, pois pode ajudar a identificar situações problemáticas em janelas de tempo futuras. / Public transport systems by bus have been increasingly relevant for the development of cities. Techniques to improve planning and control of daily operation of bus services presented significant improvements along the years, and travel time forecast plays an important hole in both planning and daily operation strategies. Travel times anticipation helps planners and controllers to anticipate the various issues that arise during the daily bus line operation. It also allows keeping users informed, so they can plan in advance for their trip. Several studies related to travel time prediction can be found in the literature. Due to its intrinsic difficulty, the problem has been addressed by different techniques. Numerical results from studies demonstrate the potential use of neural networks in relation to other techniques. However, the literature does not present applications that incorporate a feedback of the information contained in time series as it is done by recurrent neural networks. Most of the studies in the literature have been conducted with data from specific cities and buses lines with fixed stops. The situation that arises in bus lines without fixed stops operated with microbuses present a different dynamics from the literature case studies. In addition, existing studies do not use time-space trajectories as a supporting instrument for bus travel time prediction. In this thesis we study the problem of travel time prediction for microbus lines without fixed stops using the basic information of the time-space trajectories The proposed model is based on recurrent neural networks. The input data includes: (i) the start time of the bus trip, (ii) its current position in GPS coordinates, (iii) the current time and (iv) distance travelled after one minute. The networks are trained with data from a microbus line from the city of Porto Alegre, Brazil. Data corresponds to the year 2015. The model provide forecasts for distance travelled minute by minute, and for a time window of 30 minutes. The developed models were trained with a comprehensive set of data from working days including peak and off-peak periods. The training data did not disregard information from any day due to occurrence of special events. It was concluded that the recurrent neural network model developed is capable of absorbing the dynamics of the microbuses movement. The information produced present an adequate level of precision to be used for users information. It is also adequate for planners and operation controllers as it can help to identify problematic situations in future time windows.

Cette thèse porte sur l’hybridation des dimensions virtuelle et corporelle de la mobilité. Elle interroge les effets de la mise en connexion de la mobilité quotidienne, et en particulier de la mobilité pendulaire, sous la double impulsion de la diffusion du smartphone et de l’amélioration de la qualité de la connexion aux réseaux de télécommunication dans les transports en commun. La mobilité, que nous décrivons comme connectée, permet à la fois le déploiement d’activités numériques au cours du déplacement, et l’accès facilité à une information personnalisée sur les conditions d’un déplacement projeté ou en cours via les applications d’aide à la mobilité sur smartphone. La problématique générale de ce travail de recherche peut être comprise à travers l’interrogation suivante : comment les usagers des transports en commun se saisissent-ils de la mise en connexion de la mobilité pour agir sur les contraintes spatio-temporelles du quotidien ? Trois hypothèses structurent cette recherche. La première hypothèse est celle d’un effet positif de la mise en connexion de la mobilité sur la valorisation du temps de déplacement. La deuxième hypothèse est celle de la recomposition, à l’heure de la mobilité connectée, de la spécificité de l’espace-temps du déplacement au regard des activités qui y sont déployées. La troisième hypothèse est celle d’une meilleure maîtrise de la mobilité résultant de l’ancrage dans les habitudes du recours à l’information personnalisée au moyen d’applications d’aide à la mobilité. À partir d’une enquête par entretiens semi-directifs réalisée entre 2013 et 2014 et d’une enquête par la passation de questionnaires en ligne en 2015, nous avançons, en réponse à ces trois hypothèses, l’idée que la mise en connexion de la mobilité soutient une banalisation du déplacement. À défaut de produire une valorisation du temps de déplacement, le smartphone atténue, pour l’individu, les effets négatifs des variations des conditions de trajets sur le niveau de confort du déplacement. De plus, du point la mise en connexion de la mobilité rend plus perméable cet espace-temps au déploiement d’activités structurant par ailleurs le quotidien. Enfin, les applications d’aide à la mobilité offrent, outre des voies d’optimisation temporelle des déplacements quotidiens, une forme de sécurisation de la mobilité / This thesis focuses on hybridity between virtual and corporeal mobility. We study the effects of growing connectivity on daily mobility, and especially on commuting. ‘Connected’ mobility is characterised by the large-scale diffusion of smartphones and the improvement of broadband connection in public transportation. ‘Connected’ mobility allows travellers to use a wider range of on-trip activities and to receive personalised information about their current or future trips. The main issue is to determine how public transportation users use ‘connected’ mobility to their advantage to soften daily time-space constraints. Three hypotheses led this research. The first is the hypothesis of the valorisation of travel time through the use of ICT devices such as smartphones. The second is about the reshaping of mobility time-space through connectivity, regarding the activities practised by travellers in their daily lives. The third concerns the better control of daily mobility allowed by the use of mobile apps that provide personalised information. The study is based on two surveys. The first occurred during the years 2013 and 2014. It is composed of in-depth semi-directive interviews. The second is a large-scale survey led by on-line questionnaires in 2015. The main results support the idea that the growing connectivity of mobility underlines a banalisation of mobility. The use of smartphones does not clearly imply a greater valorisation of travel time, but softens the negative effects on travel comfort due to the variations of travel conditions. Moreover, the growing connectivity of mobility time-space allows the travellers to import in this specific time-space their daily activities. Finally, the mobile apps providing personalised information about mobility authorise travel optimisation but also secure the daily trips, improving the feeling of control on mobility

Esta dissertação baseia-se na aplicação de um procedimento empírico envolvendo técnicas de preferência declarada para a estimativa do valor do tempo de viagem de motoristas em deslocamentos regionais, em um contexto de escolha entre rotas pedagiadas e não pedagiadas. Inicialmente é feita uma revisão das abordagens teórica e empírica sobre a valoração do tempo. São também revistos os conceitos básicos de outros dois elementos fundamentais na metodologia aqui utilizada: a teoria da escolha e técnicas de preferência declarada. Uma aplicação a um estudo de caso específico é feita usando informações coletadas em ampla pesquisa de preferência declarada, realizada em 2005 com motoristas de automóvel em diversos pontos da malha rodoviária do estado de São Paulo. O desenho experimental da preferência declarada envolvia três atributos: tempo de viagem por uma rota pedagiada, custo tarifário e tempo de viagem por uma rota não pedagiada. O conjunto das informações foi analisado e utilizado na obtenção de modelos de escolha discreta do tipo logit multinomial; os valores do tempo de viagem foram obtidos a partir dos coeficientes estimados em funções de utilidade aditivas e lineares nos parâmetros. Analisou-se também a variação do valor do tempo em função de características do motorista e da viagem, questão abordada através da estimação de diferentes modelos por segmentos da amostra e da especificação de funções de utilidade que incorporam variáveis dummies para representação das características analisadas. Os resultados indicaram, para a escolha específica estudada, valores de tempo médios de cerca de R$ 16/h, variando de R$12/h a R$23/h para diferentes segmentos de viajantes analisados. A duração da viagem foi uma importante característica associada a variações no valor do tempo, que decresceu na medida em que as durações aumentaram. Variações expressivas no valor do tempo de viagem foram também observadas para viagens a lazer, motoristas de renda familiar baixa e aqueles com alta posse de veículos. / This dissertation is based on the application of an empirical procedure using stated preference techniques for the estimation of the value of travel time for drivers in regional trips, in the context of a choice between tolled and non-tolled routes. It first reviews the theoretical and the empirical approaches for the valuation of travel time and then presents the basic concepts of two other topics relevant for the methodology adopted: choice theory and stated preference methods. An application to a specific case study is then presented, using information from a stated preference survey conducted in 2005 with a large sample of car drivers intercepted at several points in the highway network of the state of São Paulo. The stated preference experimental design considered three attributes: trip time on a tolled route, value of toll and trip time on a non-tolled route. Survey data were analyzed and used for the estimation of discrete choice (multinomial logit) models; values of travel time were derived from estimates of coefficients of an additive linear in the parameters utility function. The specification of the models and the segmentation of the sample allowed the estimation of the variation of travel time according to some selected driver and trip characteristics. Results indicated, for the specific choice context analyzed, an average value of travel time of approximately R$16/h, varying from about R$12/h to R$23/h for different segments of travelers. Trip length was an important characteristic influencing the variation of the value of travel time, which declined as trip length increased. Other important effects were found for leisure trips, for travelers with low income and for those with high family car ownership.

The overall aim of this study is to understand how average daily individuals’ accessibility to other individuals has changed in Sweden and what the impact of changes in intra-travel time is on changes in daily individuals’ accessibility in Dalarna County. This thesis was conducted by applying quantitative research method via secondary data collection method. The required data for the purpose of this study were collected from Official Statistic of Sweden (SCB), Swedish Road Administration (NVDB) and Swedish National Travel Survey (RVU). Research population or target population for this study is all Swedish workforce population, aged 20-64. For the first part of the aim, the entire research population has been investigated and for the second part of the aim, non-probability sampling method (purposive sampling method) has been applied. The datasets have been applied to compute different variables. The variables were computed by using formulas extracted from previous empirical studies and with help of GIS and R software. The relationship between response and predictors variables has been statistically analyzed by multiple linear regression. The findings indicate that average daily individuals’ accessibility increased within the Swedish context between the years 1990 and 2008. It was found that the most increment was related to years 1995 to 2000. Also the statistical analysis showed that the relationship between the changes in average intra-travel time and changes in average daily individuals’ accessibility was not significant in municipalities in Dalarna County. Meanwhile, it was concluded that among predictor variables, changes in average daily mobility had a significant relationship with the changes in average daily individuals’ accessibility to other individuals within municipalities in Dalarna County.

This focuses on hydrological transport in shallow catchments with topography-driven flow paths. The thesis gives new insight to kinematic pathway models for estimation of tracer discharge at the catchment outlet. A semi-analytical methodology is presented for transient travel time and age distributions referred to as "kinematic pathway approach“(KPA) that accounts for dispersion at two levels of morphological and macro-dispersion. Macro-dispersion and morphological dispersion components are reflected in KPA by assuming an effective Péclet number and topographically driven pathway length distributions, respectively. The kinematic measure of the transport, defined as a characteristic velocity of water flow through the catchment is obtained from the overall water balance in the catchment. To include transformation process in its simplest form of linear decay/degradation a framework is presented that solves one-dimensional reactive transport with numerically simulated travel times as the independent variable. The proposed KPA and coupled transport framework for quantifying tracer discharge at the shallow catchment outlet are applied to two selected catchments in Sweden. KPA is applied to modeling of a 23-year long chloride data series for the Kringlan catchment whereas the implantation of the framework for quantifying natural attenuation is illustrated for the Forsmark catchment. Numerical simulations of Forsmark catchment advective travel times are obtained by means of particle tracking using the fully-integrated flow model MIKE SHE. The KPA is found to provide reasonable estimates of tracer discharge distribution when considering the transport controlled by hillslope processes associated with short topographically driven flow paths to adjacent discharge zones, e.g. rivers and lakes. Simulated natural attenuation for Forsmark is also estimated well provided that the pathway length distribution is skewed toward short pathway lengths. This fact is indicative of the controlling impact of topography on flow path length and travel time distributions in shallow catchments. Our work has shown that the pathway (Lagrangian) methodologies are promising as predictive tools for hydrological transport. / <p>QC 20170928</p>

Many modern mobile communication devices are equipped with a GPS receiver and anavigation tool. These devices are useful when a user seeks to reach a specified destinationas soon as possible, but may not be so when he/she only needs to arrive at thedestination in time and wants to focus on some activities on the way. To deal with thislatter situation, a method and device called “Space Time Alarm Clock” is presented forhelping the user reach the destination by a specified deadline and inform the user aboutthe consequences of his/her decisions. It does so by continuously and efficiently computinghow much more time the user may stay at his/her current location without failing toreach the destination by the deadline. Furthermore, it determines the possible movementchoices that a user can make with regards to an underlying road network, it computesthe shortest travel time associated with each choice and informs the user about the consequencesof his/her decisions. Advantage of this approach is that it works completelyin the background so that the user‘s en-route activities will never be interfered with. The“Space Time Alarm Clock” was implemented for Stockholm, where it was tested.

Vasaloppet is a cross country ski event which has been held in Sweden for about 50 years. Now more than 50,000 people of different ages participate in various cross country ski races during the Vasaloppet winter week in Dalarna County. This increasing demand needs good traffic and transportation planning to avoid congestion and provide safe, on time and environmentally friendly transportation for participants and visitors to the area. The key for a good event traffic planning is reliable and up-to-date traffic data which is not available for the Vasaloppet winter week. This study is an attempt to collect traffic data in order to find the movement patterns in the area and estimate origin-destination matrices for the main event of Vasaloppet week. Based on resources and time limitation it was decided to use a web-base d participants’ survey in order to collect traffic data. The link to the survey was sent to email address of a sample of 5000 participants. About 64% of the participants drove from their home town to the area and about 31 percent travelled by bus. Train and airplane have a very small share in travel mode to the area. Malungsälen, Mora and Älvdalen are three municipalities in Dalarna County with the highest share in accommodating participants. On the day of the race, bus and car have approximately the same share in travel mode with 45% and 47% respectively.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Civil Engineering, 1979. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Bibliography: leaves 231-237. / by Mark David Abkowitz. / Ph.D.