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Edara, Praveen Kumar. "Mode Choice Modeling Using Artificial Neural Networks." Thesis, Virginia Tech, 2003. http://hdl.handle.net/10919/9845.
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Artificial intelligence techniques have produced excellent results in many diverse fields of engineering. Techniques such as neural networks and fuzzy systems have found their way into transportation engineering. In recent years, neural networks are being used instead of regression techniques for travel demand forecasting purposes. The basic reason lies in the fact that neural networks are able to capture complex relationships and learn from examples and also able to adapt when new data become available. The primary goal of this thesis is to develop mode choice models using artificial neural networks and compare the results with traditional mode choice models like the multinomial logit model and linear regression method. The data used for this modeling is extracted from the American Travel Survey data. Data mining procedures like clustering are used to process the extracted data. The results of three models are compared based on residuals and error criteria. It is found that neural network approach produces the best results for the chosen set of explanatory variables. The possible reasons for such results are identified and explained to the extent possible. The three major objectives of this thesis are to: present an approach to handle the data from a survey database, address the mode choice problem using artificial neural networks, and compare the results of this approach with the results of traditional models vis-à-vis logit model and linear regression approach. The results of this research work should encourage more transportation researchers and professionals to consider artificial intelligence tools for solving transportation planning problems.Master of Science
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Ashiabor, Senanu Y. "Modeling Intercity Mode Choice and Airport Choice in the United States." Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/26221.
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The aim of this study was to develop a framework to model travel choice behavior in order to estimate intercity travel demand at nation-level in the United States. Nested and mixed logit models were developed to study national-level intercity transportation in the United States. A separate General Aviation airport choice model to estimates General Aviation person-trips and number of aircraft operations though more than 3000 airports was also developed. The combination of the General Aviation model and the logit models gives the capability to estimate a full spectrum of intercity travel demand in the United States.
The logit models were calibrated using a nationwide revealed preference survey (1995 American Travel Survey). Separate models were developed for business and non-business trip purposes. An airport choice model is integrated into the mode choice model to estimate both the market share between any origin-destination pair and other modes of transportation, and the market share split between airports associated with the origin-destination pairs. The explanatory variables used in the utility functions of the models are travel time, travel cost, and travelerâ s household income. The logit models are used to estimate the market share of automobile and commercial air transportation between 3091 counties and 443 commercial service airports in the United States. The model was also used to estimate market share for on-demand air taxi services. Given an input county-to-county trip demand table, the models were used to estimate county-to-county travel demand by automobile and commercial airline between all counties and commercial service airports in the United States. The model has been integrated into a computer software framework called the Transportation Systems Analysis Model (TSAM) that estimates nationwide intercity travel demand in the United States.Ph. D.
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Bouscasse, Hélène. "Essays on travel mode choice modeling : a discrete choice approach of the interactions between economic and behavioral theories." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE2106/document.
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Cette thèse a pour objectif d’incorporer des éléments de théories de psychologie et d’économie comportementale dans des modèles de choix discret afin d’améliorer la compréhension du choix modal réalisé à l’échelle régionale. Les estimations se basent sur une enquête de type choice experiment présentée en première partie. Une deuxième partie s’intéresse à l’incorporation de variables latentes pour expliquer le choix modal. Après une revue de littérature sur les modèles de choix hybrides, c’est-à-dire des modèles combinant modèle d’équations structurelles et modèle de choix discret, un tel modèle est estimé pour montrer comment l’hétérogénéité d’outputs économiques (ici, la valeur du temps) peut être expliquée à l’aide de variables latentes (ici, le confort perçu dans les transports en commun) et de variables observables (ici, la garantie d’une place assise). La simulation de scénarios montre cependant que le gain économique (diminution de la valeur du temps) est plus élevé lorsque les politiques agissent sur des dimensions palpables que sur des dimensions latentes. S’appuyant sur un modèle de médiation, l’estimation d’un modèle d’équations structurelles montre par ailleurs que l’effet de la conscience environnementale sur les habitudes de choix modal est partiellement médié par l’utilité indirecte retirée de l’usage des transports en commun. Une troisième partie s’intéresse à deux formalisations de l’utilité issues de l’économie comportementale : 1) l’utilité dépendante au rang en situation de risque et 2) l’utilité dépendante à la référence. Dans un premier temps, un modèle d’utilité dépendante au rang est inséré dans des modèles de choix discret et, en particulier, un modèle à classes latentes, afin d’analyser l’hétérogénéité intra- et inter-individuelle lorsque le temps de déplacement n’est pas fiable. La probabilité de survenue d’un retard est sur-évaluée pour les déplacements en train et sous-évaluée pour les déplacements en voiture, en particulier pour les automobilistes, les usagers du train prenant d’avantage en compte l’espérance du temps de déplacement. Dans les modèles prenant en compte l’aversion au risque, les fonctions d’utilité sont convexes, ce qui implique une décroissance,de la valeur du temps. Dans un deuxième temps, une nouvelle famille de modèles de choix discret généralisant le modèle logit multinomial, les modèles de référence, est estimée. Sur mes données, ces modèles permettent une meilleure sélection des variables explicatives que le logit multinomial et l’estimation d’outputs économiques plus robustes, notamment en cas de forte hétérogénéité inobservée. La traduction économique des modèles de référence montre que les meilleurs modèles empiriques sont également les plus compatibles avec le modèle de dépendance à la référence de Tversky et KahnemanThe objective of this thesis is to incorporate aspects of psychology and behavioral economics theories in discrete choice models to promote a better understanding of mode choice at regional level. Part II examines the inclusion of latent variables to explain mode choice. A literature review of integrated choice and latent variable models – that is, models combining a structural equation model and a discrete choice model – is followed by the estimation of an integrated choice and latent variable model to show how the heterogeneity of economic outputs (here, value of time) can be explained with latent variables (here, perceived comfort in public transport) and observable variables (here, the guarantee of a seat). The simulation of scenarios shows, however, that the economic gain (decrease in value of time) is higher when policies address tangible factors than when they address latent factors. On the basis of a mediation model, the estimation of a structural equation model furthermore implies that the influence of environmental concern on mode choice habits is partially mediated by the indirect utility derived frompublic transport use. Part III examines two utility formulations taken from behavioral economics: 1) rankdependent utility to model risky choices, and 2) reference-dependent utility. Firstly, a rank-dependent utility model is included in discrete choice models and, in particular, a latent-class model, in order to analyze intra- and inter-individual heterogeneity when the travel time is subject to variability. The results show that the probability of a delay is over-estimated for train travel and under-estimated for car travel, especially for car users, as train users are more likely to take into account the expected travel time. In the models that account for risk aversion, the utility functions are convex, which implies a decrease in value of time. Secondly, a new family of discrete choice models generalizing the multinomial logit model, the reference models, is estimated. On my data, these models allow for a better selection of explanatory variables than the multinomial logit model and a more robust estimation of economic outputs, particularly in cases of high unobserved heterogeneity. The economic formulation of reference models shows thatthe best empirical models are also more compatible with Tversky et Kahneman’s reference-dependent model
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Chung, Soon. "Mode choice modeling with neural network : Boston area case study." FIU Digital Commons, 1997. http://digitalcommons.fiu.edu/etd/2358.
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Demand forecasting is an essential element in the analysis of transportation systems. It is concerned with the behavior of consumers of transportation services and facilities. We choose geographic, demographic, and socioeconomic characteristics of consumers that may affect the travel demand of each selected. We use an artificial neural network to predict travel demand with characteristics selected from three different database sources: Census Summary Tape files, TIGER/Line files, and Federal Transit Administration's National Transit GIS database.
A neural network is an information processing system that is intensely parallel and neural networks are capable of learning how to classify and associate input/output patterns. This capability makes neural network a suitable approach for mode choice modeling for this study.
A neural network has two phases: the training and the testing. In the training phase, we find weights between inputs and outputs, and in the testing phase, neural network calculates outputs representing travel demand with weights from the training phase.
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Ye, Xin. "An exploration of the relationship between mode choice and complexity of trip chaining patterns." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000417.
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Zuehlke, Kai M. "Impossibility of Transit in Atlanta: GPS-Enabled Revealed-Drive Preferences and Modeled Transit Alternatives for Commute Atlanta Participants." Thesis, Atlanta, Ga. : Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19788.
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Alharbi, Abdulmajeed A. "Investigating Survey Response Rates and Analytic Choice of Survey Results fromUniversity Faculty in Saudi Arabia." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1585051418774214.
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Rice, William Ronald. "How We Got to School A Study of Travel Choices of Christchurch Primary School Pupils." Thesis, University of Canterbury. Civil Engineering, 2008. http://hdl.handle.net/10092/1242.
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There has been a noticeable swing towards school pupils being driven to and from school, and away from active modes like walking and cycling, in recent decades. This has had a number of side effects. Less reliance on active modes of transport has been a contributing factor in the reducing levels of physical activity for school children. Traffic volumes associated with school trips have also increased. This increased has tended to contribute to an increase in traffic congestion, adverse environmental effects and reductions in levels of sustainability. School trip traffic contributes specifically to congestion at school gates. Schools have been identified as having significant effects on the transportation system adjacent to them. Schools which seek Resource Consents for new or changed activities are often being required to take measures to mitigate their adverse effects The purpose of this study is to explore the factors contributing to primary school pupils' travel choices. This will help to identify travel choice patterns which may, in turn, be useful in developing policies and planning initiatives which contribute to achieving an efficient and sustainable transport system. A range of literature relevant to school and general commuting travel demand was reviewed. A case study involving the pupils of twenty two Christchurch primary schools was carried out. Pupils and their parents were surveyed to establish mode choices and the factors influencing those choices. The study found that between 55% and 60% of pupils surveyed travel to and from school by car. 30% to 35% walk or scooter, and 5% to 7% cycle. This compares with 34% travelling by car in the late 1980s. In addition, a greater proportion of those pupils who walk, scooter or cycle to school are accompanied by an adult than in the past. The results of the study also suggested that School Travel Plans, when combined with the energy and commitment to implement them can have a significant effect on school travel choices. As part of the case study, parents were asked to rank the importance of a number of factors which could influence choices regarding their children's school travel. The responses from parents identified safety concerns, regarding both road and personal safety, as the major factor behind decisions regarding their children's travel choices. Time constraints coupled with the complexity of travel requirements of many families were identified as significant factors. Multinomial Logit Models for both mode choice and pupils travel independence were then produced for both the journey to and from school. These models were based on the results of the case study. The models produced indicate that, at a school level, there is a correlation between increasing school roll and an increasing proportion of pupils travelling by car. A slight negative correlation between school decile and car usage was also indicated. This is contrary to the normally accepted understanding that in most transport situations there is a positive correlation between increasing affluence and car usage. Superior model results were obtained at a disaggregated individual level, using nine variables relating to the school, the neighbourhood, and the home, than the results obtained using the school based variables of. However, it is not considered that the effort required to obtain information on the additional variables is justified when estimating mode choices of pupils at an individual school. It is therefore recommended that a model using Decile, Average Age, and School Roll variables be used to estimate mode choices at an individual school. At a family level, there was a strong positive correlation between distance from school, age of the pupils, and the number of major roads between school and home, and car usage. It became apparent that the decisions made regarding children's school travel are very complex. Families juggle a number of factors, many of which are in conflict with one another. For example a desire to care for the environment may be in conflict with the demand to get the children to school, and get to work on time. This complex interrelationship between factors has resulted in some instances where normally accepted "Rules of Thumb", such as the understanding that increased car usage is generally associated with increasing wealth, do not appear to be applicable to school travel. The complexity of interrelationships has further meant that it has not been possible to quantify the impact of any one factor on its own.
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El, amine Samar. "Agent-based modeling of the social and economic factors affecting the choice of transportation mode : application to the Beirut city." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCA035/document.
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En milieu urbain et périurbain, les transports et la mobilité sont étroitement liés aux activités socio-économiques. Ils sont influencés par la psychologie personnelle de l'individu, les normes sociales, la résistance au changement, l'attitude personnelle, les habitudes, les peurs et les croyances. A Beyrouth, la possession de véhicules a augmenté rapidement en raison de la pénurie de transports en commun amenant l’opportunité de développer des services de mobilité durable et d’accessibilité. Cela nécessite que les modes de transport soient abordables, efficaces et respectueux de l'environnement, ainsi que des technologies qui minimisent la consommation d'énergie en mettant l'accent sur trois points principaux: réduire les besoins de déplacement, adopter des modes de transport plus respectueux de l'environnement et améliorer l'efficacité de la technologie des véhicules. Cette thèse porte sur la modélisation orientée-agent du comportement de déplacement. Nous avons analysé les données obtenues à partir d’une enquête menée à Beyrouth. Une relation entre l’emploi, le statut social et le choix du mode de transport a été mise en évidence. Un modèle de simulation orientée agent, incluant les architectures et les algorithmes des agents, du trafic routier utilisant une approche économique institutionnelle a été proposé. Les questions scientifiques concernent les effets de facteurs économiques, sociaux, professionnels et liés aux ménages sur le choix d'un mode de transport. Ce travail fait partie d'un projet de la société S&A (Belgique et Liban) visant à fournir des outils permettant la transition des moyens de transport vers une pratique plus respectueuseIn urban and peri-urban environments, transport and mobility are strongly linked to socio-economic activities. They are influenced by individual's personal psychology, social norms, resistance to change, personal attitude, habits, fears and beliefs. Beirut is a mono-centric city with transport supply poverty. Vehicle ownership has increased rapidly in response to the shortage of public transportation. Currently, there is an opportunity to develop mobility management services and establish sustainable mobility and accessibility in Beirut. This requires that transport modes be affordable, efficient and environmentally friendly, as well as technologies that minimize the energy consumption by focusing on three main points: reducing travel needs, adopting more environmentally friendly modes of transportation, and improving the efficiency of vehicle technology. This thesis focuses on the modeling of displacement behavior, based on agent-oriented modeling. We analyzed the data obtained from a survey we conducted for Beirut. We established a relation between employment, social status and mode of transportation selection. The subject of the thesis is an agent-oriented simulation model of road traffic using an institutional economic approach. We propose an architecture, algorithms and methods to implement the agents model in order to model and reproduce their modes of transport behavior. Associated scientific questions are the effects of economic, social, career and household factors on choosing a mode of transport. This work is part of a project of the company S&A (Belgium and Lebanon) to provide tools to enable the transition of means of transport to a more respectful practice
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Hole, Arne Risa. "Modelling commuters' mode choice in Scotland." Thesis, University of St Andrews, 2005. http://hdl.handle.net/10023/14115.
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This thesis contributes to the literature on the choice of transport mode for commuting trips, with special focus on the difference between urban and rural commuting in Scotland. The thesis begins by giving an overview of discrete choice theory and some empirical models consistent with this theory, before reviewing the literature on empirical applications of mode choice models for commuting trips. In the following, multinomial, nested and mixed logit models using data from a survey of commuters in the University of St Andrews are developed. The models are used to estimate aggregate mode-choice elasticities that can assist the development of efficient car reduction policies in St Andrews and other small towns in rural areas. The direct elasticities of the car mode are found to be comparable to estimates reported in studies of urban commuting, while the demand for public transport is found to be considerably more elastic. The value of in-vehicle travel time is found to be lower than in most studies of urban commuting, reflecting that the roads in the St Andrews area are relatively uncongested. Subsequently, current car drivers' willingness to use a Park and Ride service prior to the implementation of such a service are examined. The results show that the modal shift away from parking on-site will be small unless the new service is accompanied by measures aimed at making parking on-site less attractive such as introducing parking charges. Finally, the effect of the 'compact city' on modal split and congestion are examined. As well as making urban transport more sustainable as a result of an increase in the use of public transport, making cities more compact is found to contribute to lower levels of congestion in urban areas through a reduction in complex trip chains.
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Hunt, John Douglas. "Modelling commuter parking location choice and its influence on mode choice." Thesis, University of Cambridge, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.237902.
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Khan, Omer Ahmed. "Modelling passenger mode choice behaviour using computer aided stated preference data." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16500/.
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Redland Shire Council (RSC) has recently completed the preparation of Integrated Local Transport Plan (ILTP) and started its implementation and monitoring program. One of the major thrusts of the ILTP is to reduce the car dependency in the Shire and increase the shares of sustainable environmental-friendly travelling modes, such as walking, cycling and public transport. To achieve these objectives, a mathematical model is needed that is capable of modelling and forecasting the travelling mode choice behaviour in the multi modal environment of Redland Shire. Further, the model can be employed in testing the elasticity of various level-of-service attributes, under a virtual travel environment, as proposed in the ILTP, and estimating the demand for the new travelling alternatives to private car, namely the bus on busway, walking on walkway and cycling on cycleway. The research estimated various nested logit models for different trip lengths and trip purposes, using the data from a stated preference (SP) survey conducted in the Shire. A unique computer assisted personal interviewing (CAPI) instrument was designed, using both the motorised (bus on busway) and non-motorised travelling modes (walking on walkway and cycling on cycleway) in the SP choice set. Additionally, a unique set of access modes for bus on busway was also generated, containing hypothetical modes, such as secure park and ride facilities and kiss and ride drop-off zones at the busway stations, walkway and cycleway facilities to access the busway stations and a frequent and integrated feeder bus network within the Shire. Hence, this study created a totally new virtual travel environment for the population of Redland Shire, in order to record their perceived observations under these scenarios and develop the mode choice models. From the final model estimation results, it was found that the travel behaviour forecasted for regional trip-makers is considerably different from that of local trip-makers. The regional travellers for work, for instance, were found not to perceive the non-motorised modes as valid alternatives to car, possibly due to longer trip lengths. The value of time (VoT) determined for local work trip-makers (16.50 A$/hr) was also found to be higher than that of regional work trip-makers (11.70 A$/hr). From the survey analysis, a big part of the targeted population was found to be car captives, who are not likely to switch from cars to public transport; even if a more efficient transit infrastructure is implemented. In the past, the models have been generally calibrated using the mode choice survey data only, while that of the captive users were ignored. This yields a knowledge gap in capturing the complete travel behaviour of a region, since the question of what particular biases can be involved with each model estimation parameter by the captives remain unresolved. In this research, various statistical analyses were performed on the car captive users' data by categorising them into various trip characteristics and household parameters, in order to infer the relative influence of the car captive population on the travel behaviour of the study area. The outcomes of the research can assist the policy makers in solving the strategic issues of transit planning, including the future development of a busway corridor, with an efficient transit access mode network. The research findings can also be utilised in evaluating the feasibility of developing walkways and cycleways in the Shire, along with appraising the relative influence of car captive users on the travel behaviour forecasts for the study area.
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Zaman, Nishat. "Understanding Immigrants' Travel Behavior in Florida: Neighborhood Effects and Behavioral Assimilation." FIU Digital Commons, 2014. http://digitalcommons.fiu.edu/etd/1690.
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The goal of this study was to develop Multinomial Logit models for the mode choice behavior of immigrants, with key focuses on neighborhood effects and behavioral assimilation. The first aspect shows the relationship between social network ties and immigrants’ chosen mode of transportation, while the second aspect explores the gradual changes toward alternative mode usage with regard to immigrants’ migrating period in the United States (US). Mode choice models were developed for work, shopping, social, recreational, and other trip purposes to evaluate the impacts of various land use patterns, neighborhood typology, socioeconomic-demographic and immigrant related attributes on individuals’ travel behavior. Estimated coefficients of mode choice determinants were compared between each alternative mode (i.e., high-occupancy vehicle, public transit, and non-motorized transport) with single-occupant vehicles. The model results revealed the significant influence of neighborhood and land use variables on the usage of alternative modes among immigrants. Incorporating these indicators into the demand forecasting process will provide a better understanding of the diverse travel patterns for the unique composition of population groups in Florida.
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Habib, Pathan Agha Faisal. "Modelling travellers' choice of information sources and of mode." Thesis, University of Leeds, 2010. http://etheses.whiterose.ac.uk/3884/.
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This study investigates the travellers' choice of information sources and their subsequent mode choice decisions. The goal of this study is to develop a comprehensive choice model that can capture the information acquisition process by predicting the choice of information sources together with its effects on modal choices of the travellers. A decision making framework for travel information acquisition is developed and the abstract terms, necessary to be tested in the models, are identified. A Stated Preference experiment is developed based on the complicated decision making process and an interactive CATI questionnaire is designed to cope with it. Utility functions are formulated by expanding travellers' choice set to include different combinations of the viable sources of information and with the inclusion of policy sensitive variables. The research employs a wide range of modelling methodologies and examines a range of traditional and newly developed calibration and estimation procedures including Mixed Logit models with individual specific parameters and the newly developed Random Regret Minimisation framework. The study also analyses the effects of travel planning websites on travel decisions and establishes a link between content, design, advertisements, and presentation of information on overall modal shift. The results indicate that travellers give credence to government owned sources and give more importance to their own previous experiences followed by multimodal websites, train websites, friends and coach websites respectively. A website with less search time, specific infonnation on users' own criteria, and real time information is regarded as most attractive by the travellers. The study also found that the market share of the modes increases when information sources show decreased travel time and cost values and the maximum results are achieved when different information sources give the same information to the travellers. These results show that information sources could be used to influence the mode choice of the travellers.
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Beville, S. T. "Modelling differences in angler choice behaviour with advanced discrete choice models." Lincoln University, 2009. http://hdl.handle.net/10182/2332.
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New Zealand is internationally renowned for having some of the finest and most challenging trout fishing in the world. However, due to continuing development and angling pressure many fishing sites are showing signs of environmental degradation and over fishing. This trend is almost certain to continue into the future given continued population and economic growth. Understanding the determinants of site choice, preference heterogeneity and anglers’ substitution patterns is fundamentally important to fishery managers who have the difficult task of maintaining quality angling experiences on a number of fishing sites, managing angling pressure and maintaining license sales. Recent advances in simulation techniques and computational power have improved the capability of discrete choice models to reveal preference heterogeneity and complex substitution patterns among individuals. This thesis applies and evaluates a number of state-of-the-art discrete choice models to study angler site choice in New Zealand. Recreation specialisation theory is integrated into the analysis to enhance the behavioural representation of the statistical models. A suite of models is presented throughout the empirical portion of this thesis. These models demonstrate different ways and degrees of explaining preference heterogeneity as well as identifying anglers’ substitution patterns. The results show that North Canterbury anglers’ preferences vary considerably. Resource disturbances such as riparian margin erosion, reduced water visibility and declines in catch rates can cause significant declines in angler use of affected sites, and at the same time non-proportional increases in the use of unaffected sites. Recreation specialisation is found to be closely related to the types of fishing site conditions, experiences and regulations preferred by anglers. Anglers’ preference intensities for fishing site attributes, such as catch rates, vary across different types of fishing sites. This location specific preference heterogeneity is found to be related to specialisation. Overall, the empirical findings indicate that conventional approaches to modelling angler site choice which do not incorporate a strong understanding of angler preference heterogeneity can lead to poorly representative models and suboptimal management and policy outcomes.
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Silberhorn, Nadja. "Four essays on modeling brand choice and brand loyalty." Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2010. http://dx.doi.org/10.18452/16094.
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Die vorliegende Arbeit besteht aus vier Aufsätzen, die sich mit der Modellierung von Markenwahlverhalten und Markentreue beschäftigen. Der erste Aufsatz gibt eine Einführung in das Nested Logit Modell und weist auf die Existenz von zwei unterschiedlichen Spezifikationen hin. Das utility maximization nested logit (UMNL) und das non-normalized nested logit (NNNL) Modell besitzen unterschiedliche Eigenschaften, die die Schätzergebnisse beeinflussen. Mit einer Simulationsstudie werden die Konsequenzen der Verwendung verschiedener Softwarepakete demonstriert. Außerdem wird gezeigt, dass nur die UMNL Spezifikation bei Auferlegung einer Parameterrestriktion mit der Zufallsnutzentheorie konform ist. Der zweite Aufsatz untersucht anhand von realen Haushaltspaneldaten den Erfolg einer Familienmarkenstrategie. Die Signaling Theorie liefert einen Rahmen für die dem Markenwahlverhalten zugrunde liegenden psychologischen Prozesse zur Entstehung und Erklärung von produktkategorieübergreifender Markentreue. In einer empirischen Studie wird untersucht, inwieweit in einer Kategorie markentreue Kunden dieser Marke auch in anderen Produktkategorien treu sind. Es wird ein Markentreue-Hebel-Index entwickelt. Im dritten Aufsatz stehen die psychologischen Determinanten von kategorieübergreifenden Zusammenhängen im Markenwahlverhalten im Mittelpunkt. In einer empirischen Studie wird die Risikoaversion als entscheidender Bestimmungsfaktor von kategorieübergreifender Markentreue untersucht. Die konsumentenspezifische Risikoaversion wird dabei über Innovativeness und Status Quo Bias erfasst. Im vierten Aufsatz wird das Hybride Wahlmodell einem breiten Marketingpublikum vorgestellt. Klassische Wahlmodelle gehen davon aus, dass das beobachtbare Verhalten das Resultat eines nicht spezifizierten Evaluationsprozesses des Individuums ist. Der kausalanalytische Ansatz hingegen erlaubt die Spezifikation nicht direkt messbarer Faktoren als latente Variablen und kann somit Wahlmodelle sinnvoll ergänzen.This thesis is composed of four essays that pick up topics in brand choice and brand loyalty modeling. The first essay gives an introduction to the nested logit model and points attention to the existence of two different specifications. The utility maximization nested logit (UMNL) model and the non-normalized nested logit (NNNL) model have different properties which impact the estimation results. In a simulation study, the consequences of the usage of different software packages for model estimation on the estimation results is demonstrated. It is also shown that only the UMNL specification with an imposed parameter restriction is consistent with the underlying random utility theory. The second essay investigates the success of an umbrella branding strategy using household panel data. Signaling theory provides a framework for the underlying psychological processes in consumers'' brand choice behavior and can contribute in the formation and explanation of loyalty to the brand in multiple categories. An empirical study determines whether there is a tendency for loyal consumers from one product category to be loyal to the same brand in other product categories as well. Therefore, a cross-category brand loyalty leverage index is developed. In the third essay, consumer-specific psychological determinants of cross-category relations between brand loyal choice decisions are discussed. In an empirical study, the concept of risk aversion is considered as the key determinant of cross-category brand loyalty. Consumers'' risk aversion is derived from their innovativeness and status quo bias. In the fourth essay, the hybrid choice model is introduced to the broad marketing audience. Traditional choice models assume that observable behavior results from an unspecified evaluation process of the observed individual. The causal-analytic approach offers the possibility to specify not directly measurable factors as latent variables, and can thus reasonably supplement choice models.
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Gardner, Benjamin David. "What drives car use? : modelling psychological antecedents of travel mode choice." Thesis, University of Sussex, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.444119.
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Richter, Vide. "Transport Choices and Vehicle Ownership with Autonomous Vehicles : A modelling effort on car ownership, transport mode choice and travel demand with Driverless Technology." Thesis, KTH, Hållbar utveckling, miljövetenskap och teknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233863.
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Transport is one of the basic needs of a functioning society. Unfortunately, transport also pollutes our cities and release greenhouses gases. Driverless technology is a technology predicted to disrupt the future transport system, and perhaps change how we travel from private cars to shared vehicles. This study focuses on the aspect of privately owned versus shared driverless vehicles, to create more knowledge of how the future transport system will look. A utility-based demand model is used to find the demand for private and shared transport when driverless vehicles are available. The utility of different transport options is estimated by looking at earlier studies about the performance of driverless cars, driverless buses and shared driverless taxis, which is used as input for the utility model. The results indicate that driverless technology will not be a catalyst that makes transport go from private to shared. While driverless buses can improve public transport, and shared driverless taxis outcompete current taxis, driverless technology will also improve private vehicles. The results in this study imply that the sustainability improvements earlier reports have predicted with a high use of shared driverless transportation might not materialise unless efforts are done to increase use of shared transportation.Transport är ett av de grundläggande behoven för ett välfungerande samhälle. På samma gång släpper transporter ut både växthusgaser och skadliga partiklar. Självkörande teknik är något som förväntas revolutionera framtidens transportsystem, förhoppningen är att de ska förändra hur folk reser från privata bilar till delade transporter. Denna studie fokuserar på den förhoppningen. Kommer framtidens transporter ske i privata självkörande fordon eller delade självkörande fordon och vad i sin tur betyder det för framtidens transportsystem? Med en nyttobaserad efterfråge- och bilinnehavsmodell modelleras efterfrågan av självkörande delade taxis, självkörande bussar och självkörande privatbilar. Resultaten indikerar att självkörande teknik inte nödvändigtvis kommer vara en katalysator som får människor att sluta äga och använda privatbilar. Självkörande bussar kan göra kollektivtrafiken bättre, och självkörande delade taxibilar kommer troligtvis användas mer än dagens taxis. Men självkörande privatbilar kommer också ha många fördelar, och de som äger dem kommer dessutom troligtvis köra längre sträckor än dagens bilister. Resultatet av denna rapport indikerar därför att de stora förväntningarna som finns på självkörande teknik gällande delade transporter kan vara felaktiga, om inte andra åtgärder också görs för att öka delning. Att delningen inte ökar gör också att de hållbarhetsförbättringar som vissa tidigare rapporter förutspått inte nödvändigtvis kommer ske.
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Marais, Andre Louis. "Developing an alternative approach to mode choice modelling with the application of modelling Gautrain patronage." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86475.
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Thesis (MScEng)--Stellenbosch University, 2014.ENGLISH ABSTRACT: Mode choice modelling is an important and versatile tool that can aid decision makers with transit related strategies and scenario planning. The traditional approach to modelling public transport is labour intensive and requires many resources. The expensive nature of developing mode choice models can also act as a deterrent for developing a model. Not having access to a functional mode choice model can force decision makers to make important decisions without having access to proper information. There is therefore a need to provide a simplified solution for developing a functional mode choice model that can be developed and maintained with fewer resources. This research project explores the possibility of developing a simplified alternative approach to public transport modelling that can model mode choice behaviour with the same degree of accuracy as traditional models. The modelling steps employed in this research project were the typical four step demand modelling approach, but the principles employed differ slightly. The focus area of this research project is the development of simplified utility functions and the calibration thereof. Typical mode choice models coincide with many assumptions, variations and uncertainties. In this research project the proposed utility functions are simplified by incorporating most of the assumptions and intangible components of the utility function into a single station to station specific calibration factor. The hypothesis is that a simplified alternative approach to the utility functions can still provide a model that is purpose built and functional. The application of the proposed mode choice model is to model the mode choice between the Gautrain and private vehicles as the major mode of transport.
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Shen, Yu. "Car fleet modelling : Data processing and discrete choice model estimation." Thesis, KTH, Transportvetenskap, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-43719.
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This thesis deals with the modelling of the choice of new car based on the registration data of the whole Sweden car fleet for 2005 to 2010. It is divided into two parts. In the first part, to obtain the observations of new car choices for the discrete choice modelling, a subset based on the first registration date of each car is extracted. Then, a descriptive analysis based on the new car choice data is presented to find the variances of the attributes for the modelling. Specifically, two major issues are paid attention to. One is the change of market share of each car make in these years and the other is the incremental demand of diesel and hybrid fuel cars. The second part of the thesis deals with the discrete choice modelling. In order to designate the alternatives, another dataset showing the new car supply in Sweden is introduced. In the supply data, the alternatives are shown in the car version level, whereas the registration data only contain the names of car models. Additionally, the supply data also have some attributes that are unavailable in the registration, e.g. price. Thus, this thesis presents various matching methods to match the supply and the registration to define the alternatives for the modelling and also to obtain a higher precision of each attribute than that in matching with model names only. Finally, we choose to match the data by the same model name with the same maximum power, which is defined as the “model-engine” level. Therefore, based on these model-engine level alternatives, 18 MNL models are estimated from 2005 to 2010, with 3 different ownerships, namely private owned, company owned and company owned but leasing to its employee which is named as “leasing users”. The results show the slump of the brand constants of Saab among these years in private owners and leasing users due to the close-down crisis when the coefficient of Volvo is fixed to zero. By contrast, the brand value of Kia for private owners and the value of VW for leasing users go up. Meanwhile, this thesis analyses a shift of car buyers’ attitude to the alternative fuel car from negative in 2006 to positive in 2007 when a “clean car” compensation policy is implemented from Jan. 2007 to Jul. 2009. And in 2010, the coefficient of the alternative fuel remains positive. These results indicate that this policy was quite successful.
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Fennell, Alex. "Does Response Modality Influence Conflict? Modelling Vocal and Manual Response Stroop Interference." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1490611523266134.
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Cats, Oded. "Dynamic Modelling of Transit Operations and Passenger Decisions." Doctoral thesis, KTH, Trafik och logistik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-49962.
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Efficient and reliable public transport systems are fundamental in promoting green growth developments in metropolitan areas. A large range of Advanced Public Transport Systems (APTS) facilitates the design of real-time operations and demand management. The analysis of transit performance requires a dynamic tool that will enable to emulate the dynamic loading of travelers and their interaction with the transit system. BusMezzo, a dynamic transit operations and assignment model was developed to enable the analysis and evaluation of transit performance and level of service under various system conditions and APTS. The model represents the interactions between traffic dynamics, transit operations and traveler decisions. The model was implemented within a mesoscopic traffic simulation model. The different sources of transit operations uncertainty including traffic conditions, vehicle capacities, dwell times, vehicle schedules and service disruptions are modeled explicitly. The dynamic path choice model in BusMezzo considers each traveler as an adaptive decision maker. Travelers’ progress in the transit system consists of successive decisions that are defined by the need to choose the next path element. The evaluations are based on the respective path alternatives and their anticipated downstream attributes. Travel decisions are modeled within the framework of discrete random utility models. A non-compensatory choice-set generation model and the path utility function were estimated based on a web-based survey. BusMezzo enables the analysis and evaluation of proactive control strategies and the impacts of real-time information provision. Several experiments were conducted to analyze transit performance from travelers, operator and drivers perspectives under various holding strategies. This analysis has facilitated the design of a field trial of the most promising strategy. Furthermore, a case study on real-time traveler information systems regarding the next vehicle arrival time investigated the impacts of various levels of coverage and comprehensiveness. As passengers are more informed, passenger loads are subject to more fluctuation due to the traveler adaptations.QC 20111201
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Majeed, Zahid. "Modelling international entry mode choice and speed : locational and cognitive insights in Pakistani small businesses." Thesis, University of Huddersfield, 2014. http://eprints.hud.ac.uk/id/eprint/23401/.
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This thesis intends to explore the process of foreign investment and entry mode choices of small firms from Pakistan. Pakistan being an epicure of global terrorism and ethnictension is an economy that is driven by small sector. The small sector is facing extreme difficulties to expand their international operations. This needs a comprehensive research to see beyond basic infrastructural impediments to small firms in Pakistan. What are the major behavioural and analytical impedimentsto their international expansion? Cognitive biases are the behavioural impediments and so far there is no research in Pakistan in general and in advanced countries in particular, to see how cognitive heuristics and biases affectthe foreign investment decision process? Entry mode is said to be the building block of internationalisation, and due to their small size, resource limitations and lack of international knowledge, small firms often try to obtain first-mover advantages through strategic alliances or joint venture operations abroad. Post entry speed is the international development of small firm, once the process of entry mode choice is completed. Entrepreneurial managers perceive cooperative modes and other equity investments as high-risk oriented strategies due to the legal and moral hazards associated with co-operative modes of entry. This creates a dilemma as to how to maintain a sustainable post-entry international speed? The absence of a unique set of enduring dispositional preferences is striking. There is no research that explores the role of entrepreneurial cognition/biases in small firm entry mode choices process. This applies particularly when small firms expand their international operations from emerging to developed economies. Based on the integration of cognitive capabilities and the Dunning eclectic framework, this study develops a rigorous model by introducing the new resource value generation taxonomies, and explores the impact of cognitive biasness in small firm entry mode choice process and cognitive dynamism in post-entry speed. A sub-modal for the enquiry of cognitive biases in foreign investment decision process is also introduced. This sub model by qualitative enquiry found the significant role or heuristics and biases in foreign investment decision process. The data was collected from a stratified sample of three major provinces of Pakistan through postal and drop-off survey/personal visits. Ten in-depth personal and telephonic interviewswere conducted to triangulate the entry mode choice process with speed model. Triangulation of positivist and interpretivist approach confirms the validity and reliability of the research findings. The dependent variable is dichotomous for post-entry speed. Logistic regression for post-entry speed is used to analyse the quantitative data set. Foreign investment and/or entry mode choice process are the simultaneous terms used in the entire thesis. The findings support the central role of biases in foreign investment decision process and ownership, location and cognitive advantages in the post-entry speed. The new value generation entry mode choice taxonomies (high and low value generation modes) and cognitive biases during the three stages of foreign investment decision process introduced in this research, contributes significantly to present literature. Complexities associates with IB research highlight the need for further empirical, cross-cultural and longitudinal studies. One of the most important challenges that the managers in small firm in developing economies face is to find new ways to enhance the probability of their exports‘ success through a suitable entry mode choice process (foreign investment decision process). This research through careful deliberation presents useful implications that will enhance the international activity of small firms from developing economies in general and advanced economies in particular. The findings are generalizable because the cognitive biases emerge as behavioural and analytical impediments in any event, process and/or in any system of relationships. The dispositional tendencies of managers identified in this thesis are the source of mitigating the negative effects of the biases. Thus this study is unique in its nature that contributes to both economic and behavioural theories.
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Shimonishi, Kei. "Modeling and Estimation of Selection Interests through Gaze Behavior." Kyoto University, 2017. http://hdl.handle.net/2433/227658.
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Christensen, Darren Robert. "The Extended Decision Model." Thesis, University of Canterbury. Psychology, 2009. http://hdl.handle.net/10092/3441.
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The quantification of choice has been a major area of research for behavioural scientists for several decades. This is, in part, due to the discovery of the matching law (Herrnstein, 1961) which stipulates that relative response rates on concurrently available alternatives “match” the available relative reinforcement rates. This theoretical construct has been developed to describe response allocation in more complex situations, such as concurrent chains, and successfully describes both human and non-human behaviour. Typically, this phenomenon becomes evident when behaviour settles at an asymptote after several sessions of training where contingencies are held constant, and is often called “steady-state” behaviour. However, a fundamental question still remains: what causes matching – that is, what are the underlying momentary process(es) that produce matching? Researchers have suggested that what is necessary to answer this question is to take a molecular approach to the analysis of choice behaviour, thereby assessing choice in transition (Grace, 2002a). Recently, a new model of choice acquisition has been developed that appears to offer promise. It combines two separate mechanisms; a “winner-takes-all” categorical discrimination, and a linear-operator acquisition process (Grace & McLean, 2006). The initial results suggest this model could provide an alternative explanation for what underlies matching – that two separate processes are cooccurring in the acquisition of choice behaviour – allowing response allocation to be either linear or non-linear. This thesis extends the Grace and McLean model to include the situation of response strength ‘carrying-over’ from session to session to describe the process of acquisition gradually accumulating with experience. Moreover, additional assumptions have been added to describe temporal phenomena 2 and presumed discounting of previous experience on current choice behaviour. A steady-state version of the extended model was derived and, when fitted to published data sets, describes choice behaviour equally well when compared to existing models of steady-state choice. As a consequence of these additions, the Extended Decision Model (EDM) predicts a unique response allocation pattern – choice behaviour follows a bitonic function when initial-link durations were increased and the terminallink delays were held constant. The results from experiments presented in this thesis support this prediction, whilst steady-state analyses found the EDM was parameter invariant – differences between parameters from two schedule types across several archival data sets were non-significant, while existing steady-state models had significant differences. These findings provide further support for the claim that the EDM and the Decision Model (DM) mechanisms provide unique and accurate descriptions of the molecular processes governing choice behaviour. Moreover, the implication from these results is that the underlying assumption of the EDM and DM – that choice is determined by the propensity to respond rather than conditioned reinforcement – appears to have further foundation. This challenges the assumptions of existing models of choice behaviour and presents the possibility that probabilistic approaches are perhaps more appropriate for describing response allocations than discrete estimates of relative value when contingencies change.
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Zhou, Liren. "Modeling the impacts of an employer based travel demand management program on commute travel behavior." [Tampa, Fla] : University of South Florida, 2008. http://purl.fcla.edu/usf/dc/et/SFE0002309.
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Takama, Takeshi. "Stochastic agent-based modelling for reality : dynamic discrete choice analysis with interaction." Thesis, University of Oxford, 2005. http://ora.ox.ac.uk/objects/uuid:07a643ed-c98a-4e66-936b-e8b558dbc1e3.
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This D.Phil. thesis develops a new agent-based simulation model to improve the results of analysis, which solely uses discrete choice modelling, as well as to analyse the effects of a road user charging scheme for the Upper Derwent Valley in the Peak District National Park. The advantages of discrete choice analysis are well known. However, results with these conventional conventional approaches, which conduct analysis solely with discrete choice models, can be biased if interaction and learning effects are significant. The Minority Game, in which agents try to choose the option of the minority side, is an appropriate tool to deal with these problems. The situation in the Upper Derwent Valley can be explained with economic game theories and the Minority Game. The two approaches mutually help to analyse the situation in the Upper Derwent Valley leading to the development of a stochastic Minority Game. The stochastic Minority Game was tested with an online game (questionnaire), which was played 3,886 times by response in all around the world. The practical part of this thesis examines the components of the stochastic Minority Game with the data collected around the Upper Derwent Valley. The main data was collected using a stated preference survey. Overall, 700 questionnaires were distributed and 323 of them were returned (i.e. a return rate of 46.1 %). In the practical part, the agent-based model has four sub modules: 1) Multinomial mixed logit model for mode choice, 2) Binary logit model for parking location choice, 3) Markov queue model for parking network, and 4) the Minority Game for parking congestion and learning. This simulation model produces comprehensive outputs including mode choices, congestion levels, and user utilities. The results show that the road user charging scheme reduces car demand in the Upper Derwent Valley and ensures a reduction in congestion at the parking areas. The model also shows that an exemption will increase the utilities of elderly visitors without substantially sacrificing those of younger visitors. In conclusion, the simulation model demonstrated that oversimplification in conventional approaches solely using discrete choice models gave significant biases when real world problems were analysed.
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Kitthamkersorn, Songyot. "Modeling Overlapping and Heterogeneous Perception Variance in Stochastic User Equilibrium Problem with Weibit Route Choice Model." DigitalCommons@USU, 2013. https://digitalcommons.usu.edu/etd/1970.
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In this study, a new SUE model using the Weibull random error terms is proposed as an alternative to overcome the drawbacks of the multinomial logit (MNL) SUE model. A path-size weibit (PSW) model is developed to relax both independently and identically distributed assumptions, while retaining an analytical closed-form solution. Specifically, this route choice model handles route overlapping through the path-size factor and captures the route-specific perception variance through the Weibull distributed random error terms. Both constrained entropy-type and unconstrained equivalent MP formulations for the PSW-SUE are provided. In addition, model extensions to consider the demand elasticity and combined travel choice of the PSW-SUE model are also provided. Unlike the logit-based model, these model extensions incorporate the logarithmic expected perceived travel cost as the network level of service to determine the demand elasticity and travel choice. Qualitative properties of these minimization programs are given to establish equivalency and uniqueness conditions. Both path-based and link-based algorithms are developed for solving the proposed MP formulations. Numerical examples show that the proposed models can produce a compatible traffic flow pattern compared to the multinomial probit (MNP) SUE model, and these models can be implemented in a real-world transportation network.
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Li, Xiaofei. "Dynamic Goal Choice when Environment Demands Exceed Individual’s Capacity: Scaling up the Multiple-Goal Pursuit Model." Ohio University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1493389920717575.
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Phonphitakchai, Thanawat. "Modelling the usage rate of a DRT service : a discrete choice model with latent variables." Thesis, University of Aberdeen, 2011. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=165208.
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Demand Responsive Transport (DRT) is a relatively new form of public transport provision; it is an intermediate form somewhere between conventional bus and taxi services. Over the last decade, DRT services have grown in popularity mainly influenced by the development of transport telematics. The telematics-based DRT system, which forms the focus of this research, allows new generation DRT services to have greater flexibility in time and route design, and to enable immediate advance booking and response to travel requests. These DRT services have shown important advantages and benefits in several European cities and regions particularly as an alternative solution of public transport in low/dispersed demand areas and times. Moreover, DRT services have an important role to tackle social exclusion. However, several previous works reveal that many existing DRT services are still not performing to their true potential and there is still a research need to investigate DRT services from the passengers’ perspective. Therefore, this research studies DRT services from the passengers’ perspective by selecting the LinkUp DRT scheme as the case study. LinkUp is a telematics-based DRT scheme which operates as a public transport service in Tyne and Wear, UK with fully flexible routes in defined operating areas. A discrete choice model with latent variables is applied to model the passengers’ usage rate of the LinkUp DRT services. The assumption of the usage rate model developed in this research is that each passenger has an underlying utility for using the LinkUp services and the passengers who use LinkUp at different levels of frequencies have different levels of utility. The individual’s utility has an underlying latent variable and his usage rate of LinkUp in terms of number of trips per week serves as choice indicators. This study hypothesises that characteristics, and attitude and perception towards the LinkUp services of the passenger affect his utility. The passengers’ attitude and perception are constructed as latent variables (models) in the usage rate model. Therefore, the usage rate model consists of two sub-models: latent variable and discrete choice models which are specified as Multiple Indicators and MultIple Causes (MIMIC) and ordered probit models respectively. Three latent variables are proposed to quantify the passengers’ attitude and perception, which are latent Awareness, Satisfaction, and Relative Advantage. Consequently, the usage rate model is represented by the utility, which is hypothesised to be the function of the individual passenger’s characteristics and three latent variables. The results provide useful information for improving the LinkUp DRT scheme, implementing and developing telematics-based DRT services, further developing the travel behaviour model for DRT passengers, as well as for the DRT operators and policy makers.
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Kristoffersson, Ida. "Incorporation of Departure Time Choice in a Mesoscopic Transportation Model for Stockholm." Licentiate thesis, Stockholm : Transport- och samhällsekonomi, Kungliga Tekniska högskolan, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-10516.
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Jiao, Xihe. "A new travel demand model for outdoor recreation trips." Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/285006.
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Travel to outdoor recreational spaces belongs to a general class of research questions for understanding destination and travel mode choices. In travel demand modelling, discrete choice models (DCMs) have been applied to understand and predict a wide range of choices, such as how people choose among alternative destinations for jobs, homes, shopping, personal services etc. Surprisingly, DCMs have rarely been used to understand and model travel to outdoor recreational spaces. In the current literature for modelling travel to outdoor recreational spaces, the established models are Negative Binomial Regression (NBR) models, such as what was used in the UK NEA studies. However, these NBR models were developed to assess the effects of travel to outdoor recreational spaces at a national level, and they are not intended for assessing choices of individual sites. One reason for this is, as identified by previous studies, is that compared with the DCMs, the NBR models have certain limits on estimating people's choice behaviours. There is, therefore, no existing model that can represent and predict how people choose to travel to outdoor recreational spaces. Given the importance of outdoor recreational activities to urban land use planning and public health, this is a clear gap in the field. The aim of this study is to develop a new travel demand model capable of representing and predicting travel to individual outdoor recreational sites. This is achieved by answering four main research questions: First, how to build the new model for outdoor recreational travel? Secondly, is the estimation accurate enough? Thirdly, to what extent can the new model be transferred to destinations outside the case study area? And, finally, how can city planners and designers use this new method? The new model draws upon ideas from random utility theory that underlies the conventional travel demand models to represent trip generation, trip distribution and mode choice. This research follows the standard modelling procedure: data collection and preliminary analysis, model calibration, model validation and model application. The data are collated from a wide range of sources that, importantly for model transferability, cover all areas in England. The new model has been calibrated for a case study area which spanned 14 selected districts in the North-West region. Validation of the new model is based on estimating the numbers of trips to two outdoor recreational sites (Wigg Island and Wigan Flashes) and to nine English National Parks where data on visitor trips exist. In the final stage of the research, the new model is applied to estimate the changes that would arise from planning and design interventions in existing (Wigg Island and Moore Nature Reserve) and proposed (Arpley Country Park) sites. At the end of this process, it is possible to show that the new model can predict the number of trips to individual destinations and that the model can be transferred to other outdoor recreation sites. Furthermore, the new model presented here is capable of predicting the changes in the volume and catchment of visits to an existing green space after land use planning or urban ecological interventions. This is a completely new theoretical model that is focused on understanding and quantifying the travel choices to outdoor recreation sites, which can inform decision makers by forecasting changes in outdoor recreational travel demand, according to different planning scenarios.
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Acheampong, Ransford Antwi. "Understanding the co-emergence of urban location choice and mobility patterns : empirical studies and an integrated geospatial and agent-based model." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/267913.
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Understanding and simulating the relationship between urban land-use configuration and patterns of human spatial interaction has been the subject of multi-disciplinary research. Conceptually, it is recognized that the location decisions of several urban actors including individuals, households, firms and public sector institutions, collectively determine the spatial distribution of land-use activities; the emergent land-use patterns, in turn, provide the structural conditions within which flows and interactions between locations occur daily and respond to each other over time. Over the past six decades, various theories and concepts from urban economics, social-physics, transportation studies, and the complexity sciences have underpinned empirical research and development of state-of-the-art simulation models to explore the land-use and travel nexus. Using a case study design and selecting the Kumasi Metropolis, a medium-size metropolis of nearly two-million inhabitants in Ghana, West Africa as the case study area, two main objectives, which reflect research trends and gaps in both the empirical literature and simulation model development have been addressed in this thesis. The first objective was to examine empirically, the location choice behaviour of households and individuals with respect to their residential and job locations, and the mobility patterns associated with the observed home-work location combinations within the metropolis. The second objective was to develop an integrated geospatial and agent-based model to simulate how the residential and job location choice behaviour of heterogeneous households and individuals co-emerge with mobility patterns in the metropolis. The empirical studies presented in this thesis contributes to a deeper understanding of how location-defining attributes at multiple spatial-scales interact with socio-demographic attributes of heterogeneous households and individuals to determine their residential location choice, job location choice and mobility characteristics. The development of the Metropolitan Location and Mobility Patterns Simulator (METLOMP-SIM)—an integrated geospatial and agent-based model also demonstrates how the encoded micro-scale behaviour of purposive households and individuals, interacting with each other and their environment dynamically, could reproduce macro-scale urban location patterns, property market price formation and evolution, and patterns and attributes of spatial flows and interactions anchored on the population’s residential-job location combinations.
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Khoeini, Sara. "Modeling framework for socioeconomic analysis of managed lanes." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53408.
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Managed lanes are a form of congestion pricing that use occupancy and toll payment requirements to utilize capacity more efficiently. How socio-spatial characteristics impact users’ travel behavior toward managed lanes is the main research question of this study. This research is a case study of the conversion of a High Occupancy Vehicle (HOV) lane to a High Occupancy Toll (HOT) lane, implemented in Atlanta I-85 on 2011. To minimize the cost and maximize the size of the collected data, an innovative and cost-effective modeling framework for socioeconomic analysis of managed lanes has been developed. Instead of surveys, this research is based on the observation of one and a half million license plates, matched to household locations, collected over a two-year study period. Purchased marketing data, which include detailed household socioeconomic characteristics, supplemented the household corridor usage information derived from license plate observations. Generalized linear models have been used to link users’ travel behavior to socioeconomic attributes. Furthermore, GIS raster analysis methods have been utilized to visualize and quantify the impact of the HOV-to-HOT conversion on the corridor commutershed. At the local level, this study conducted a comprehensive socio-spatial analysis of the Atlanta I-85 HOV to HOT conversion. At the general scale, this study enhances managed lanes’ travel demand models with respect to users’ characteristics and introduces a comprehensive modeling framework for the socioeconomic analysis of managed lanes. The methods developed through this research will inform future Traffic and Revenue Studies and help to better predict the socio-spatial characteristics of the target market.
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Singh, Karandeep. "Statistical modelling and analysis of traffic : a dynamic approach." Thesis, Loughborough University, 2012. https://dspace.lboro.ac.uk/2134/9421.
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In both developed and emerging-economies, major cities continue to experience increasing traffic congestion. To address this issue, complex Traffic Management Systems (TMS) are employed in recent years to help manage traffic. These systems fuse traffic-surveillance-related information from a variety of sensors deployed across traffic networks. A TMS requires real-time information to make effective control decisions and to deliver trustworthy information to users, such as travel time, congestion level, etc. There are three fundamental inputs required by TMS, namely, traffic volume, vehicular speed, and traffic density. Using conventional traffic loop detectors one can directly measure flow and velocity. However, traffic density is more difficult to measure. The situation becomes more difficult for multi-lane motorways due to drivers lane-change behaviour. This research investigates statistical modelling and analysis of traffic flow. It contributes to the literature of transportation and traffic management and research in several aspects. First, it takes into account lane-changes in traffic modelling through incorporating a Markov chain model to describe the drivers lane-change behaviour. Secondly, the lane change probabilities between two adjacent lanes are not assumed to be fixed but rather they depend on the current traffic condition. A discrete choice model is used to capture drivers lane choice behaviour. The drivers choice probabilities are modelled by several traffic-condition related attributes such as vehicle time headway, traffic density and speed. This results in a highly nonlinear state equation for traffic density. To address the issue of high nonlinearity of the state space model, the EKF and UKF is used to estimate the traffic density recursively. In addition, a new transformation approach has been proposed to transform the observation equation from a nonlinear form to a linear one so that the potential approximation in the EKF & UKF can be avoided. Numerical studies have been conducted to investigate the performance of the developed method. The proposed method outperformed the existing methods for traffic density estimation in simulation studies. Furthermore, it is shown that the computational cost for updating the estimate of traffic densities for a multi-lane motorway is kept at a minimum so that online applications are feasible in practice. Consequently the traffic densities can be monitored and the relevant information can be fed into the traffic management system of interest.
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Aldebert, Clément. "Uncertainty in predictive ecology : consequence of choices in model construction." Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM4075/document.
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Les systèmes écologiques sont des systèmes complexes qui ne peuvent pas être d´écrits par un unique modèle mathématique. De nombreux modèles peuvent être construits pour un même système, selon les internets du modélisateur et ses choix dans la construction du modèle. Quel est l’impact de ces choix dans la construction du modèle sur les prédictions de la dynamique des systèmes écologiques et les informations qu’elles fournissent sur la résilience de ces systèmes est la question générale qui guide le travail présente dans cette thèse. Cette thèses focalise sur un choix entre formulations de modèle basées sur des mécanismes biologiques et qui décrivent les données empiriques avec la même efficacité. Ces modèles sont proches l’un de l’autre, donc on s’attendrait `a ce que leurs prédictions soient similaires. Cependant, nous montrons avec un exemple générique de modèle prédateur-proie que des formulations similaires du processus de prédation peuvent prédire des dynamiques qualitativement différentes en terme de: (i) nombre et type d'états stables, et (ii) réponse et résilience du système face à une perturbation extérieure. Ces différences dans les prédictions du modèle sont expliquées par une analyse mathématique détaillée du modèle prédateur-proie. Ensuite, ce modèle est étendu à des réseaux trophiques compos´es de dizaines d’espèces. La complexité de ces réseaux (nombre d'espèces et d’interactions) explique leur persistance, alors que leur dynamique temporelle est fortement affectée par la fonction utilisée pour modéliser la prédation. Des méthodes sont ´également proposées pour quantifier la sensibilités d’un modèle. Finalement, nous montrons que si un minimum de détails biologiques sont pris en compte, des modèles prédateurs-proies sont moins sensibles `a la formulation de la prédation. Ceci nous donne des pistes pour gérer les incertitudes dans la construction d’un modèle, qui sont intrinsèques à la complexité des systèmes naturelsEcological systems are complex systems which cannot be described by a single mathematical model. Multiple modelsof a same system can be built, depending on modeller’s interests and on its choices during model construction. Howfar these choices in model construction can affect the predicted dynamics of ecological systems and the informationthey provide on their resilience? is the general question that leads the research presented in this thesis. This thesisfocuses on a choice between model formulations that are based on biological mechanisms and describe empiricaldata with the same accuracy. These models are close to each other, so they are expected to predict similar systemdynamics. However, we show through a generic example of predator-prey model that similar formulations of thepredation process can predict qualitatively different system dynamics in term of: (i) number and type of stablestates, and (ii) system response to external disturbance and its potential for recovery. These differences in modelpredictions are explained by a detailed mathematical analysis of the predator-prey model. Next, this model isextended to complex food webs made of tens of species. The complexity of these networks (number of species andinteractions) drives their persistence, whereas their temporal dynamics is strongly affected by the function used tomodel predation. Methods to quantify model sensitivity are also proposed. Finally, we show that if a minimumlevel of biological details is included, predator-prey models are less sensitive to predation formulation. This providea clue to deal with uncertainties in model construction, which are intrinsic to the complexity of natural systems
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Shurtz, Timothy E. "Influence of Supraglottal Geometry and Modeling Choices on the Flow-Induced Vibration of a Computational Vocal Fold Model." BYU ScholarsArchive, 2011. https://scholarsarchive.byu.edu/etd/2885.
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Computational models of the flow-induced vibrations of the vocal folds are powerful tools that can be used in conjunction with physical experiments to better understand voice production. This thesis research has been performed to contribute to the understanding of vocal fold dynamics as well as several aspects of computational modeling of the vocal folds. In particular, the effects of supraglottal geometry have been analyzed using a computational model of the vocal folds and laryngeal airway. In addition, three important computational modeling parameters (contact line location, Poisson's ratio, and symmetry assumptions) have been systematically varied to determine their influence on model output. Variations in model response were quantified by comparing glottal width, frequency, flow rate, open quotient, pressures, and wave velocity measures. In addition, the glottal jet was qualitatively analyzed. It was found that for various supraglottal geometries (either symmetrically or asymmetrically positioned), there was little asymmetry of the vocal fold motion despite significant asymmetry in the glottal jet. In addition, the vocal fold motion was most symmetric when consistent jet deflection was present (even if asymmetric). Inconsistent deflection of the glottal jet led to slightly larger asymmetries in vocal fold motion. The contact line location was found to have minimal impact on glottal width, frequency, and flow rate. The largest influence of the contact line location was seen in predicted velocity fields during the closed phase and in the pressure profiles along the vocal fold surfaces. Variations in Poisson's ratio strongly affected vocal fold motion, with lower Poisson's ratios resulting in larger amplitudes. The model did not vibrate when a Poisson's ratio of 0.49999 was used. The response of a full model (with two vocal folds) was shown to vary slightly from that of a half model (one vocal fold and a symmetry boundary condition), the greatest difference being in the deflection and dissipation of the glottal jet. It was concluded that for many scenarios the half model will be sufficient for modeling vocal fold motion; however, a full model is suggested for studies of material asymmetry or glottal jet dynamics. Application of these results to computational models of the vocal folds will lead to improved modeling and understanding of vocal fold dynamics.
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Van, Nostrand Caleb. "A Discrete-Continuous Modeling Framework for Long-Distance, Leisure Travel Demand Analysis." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3389.
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This study contributes to the literature on national long-distance travel demand modeling by providing an analysis of households' annual destination choices and time allocation patterns for long-distance leisure travel purposes. An annual vacation destination choice and time allocation model is formulated to simultaneously predict the different destinations that a household visits and the time it spends on each of these visited destinations, in a year. The model takes the form of a Multiple Discrete-Continuous Extreme Value (MDCEV) structure (Bhat, 2005; Bhat, 2008). The model assumes that households allocate their annual vacation time to visit one or more destinations in a year to maximize the utility derived from their choices. The model framework accommodates variety-seeking in households' vacation destination choices in that households can potentially visit a variety of destinations rather than spending all of their annual vacation time for visiting a single destination. At the same time, the model accommodates corner solutions to recognize that households may not necessarily visit all available destinations. An annual vacation time budget is also considered to recognize that households may operate under time budget constraints. Further, the paper proposes a variant of the MDCEV model that avoids the prediction of unrealistically small amounts of time allocation to the chosen alternatives. To do so, the continuously non-linear utility functional form in the MDCEV framework is replaced with a combination of a linear and non-linear form.
The empirical data for this analysis comes from the 1995 American Travel Survey Data, with the U.S. divided into 210 alternative destinations. The empirical analysis provides important insights into the determinants of households' leisure destination choice and time allocation patterns.
An appealing feature of the proposed model is its applicability in a national, long-distance leisure travel demand model system. The annual destination choices and time allocations predicted by this model can be used for subsequent analysis of the number of trips made (in a year) to each destination and the travel choices for each trip. The outputs from such a national travel modeling framework can be used to obtain national-level Origin-Destination demand tables for long-distance leisure travel.
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Ziedén, Therése. "Development of a Logit model of the transition effect to public transport." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-141691.
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The importance of traffic planning has, throughout the years, been in- creased, providing sustainable developments of traffic and infrastructural investments. The analysis of the current traffic situation and the evalua- tion of the effects of a future investment are crucial for the socio-economic benefits maintenance. These analyses and evaluations are most commonly done using traffic simulation models. One of the main traffic planning aims, nowadays, is to increase the number of public transport users against the number of private car users. This change in mode choice is called transition effect and could be beneficial both from an environmental and socio-economic perspective. This thesis aims to evaluate and improve the macroscopic traffic demand and transition model, used fot the city of Norrköping. Additionally, the thesis investigates if a general transition Logit model can be developed and which parameters are the most important to be included in a modal choice estimation. For the needs of this study, the traffic planning software Visum is used. The travel mode distribution is calculated by Logit models coded in Python-scripts integrated in Visum. Then, a traffic assignment is performed by Visum, computing new travel times as inputs to the Logit model and this iterative procedure continues until the system reaches an equilibrium. The thesis aims for a more reliable prediction of the transition effect by correcting the Python-scripts and estimating the parameters of the Logit model using data from surveys. The study shows that travel times is the most important factor for realistic results generation. However, the data used for the estimation of the Logit model parameters did not include sufficient information of travel times. The travel times had to be calculated, using two different methods, in order to be included in the estimation of new parameters. Although these methods could not provide any positive effects on the transition, they did prove the importance and significance travel time have when developing a traffic model. The result of the study invokes the importance to further develop the method of calculating travel times, when the input data is not sufficient, and shows that the travel time parameters are case specific.
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Ye, Xin. "Development of models for understanding causal relationships among activity and travel variables." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001842.
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Li, Qian. "Evaluation of Parking Guidance Information System with Multi-agent Based Simulation." 京都大学 (Kyoto University), 2014. http://hdl.handle.net/2433/188568.
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Van-Ristell, Jessica Ann. "Investigating the impacts of policy on school travel." Thesis, Loughborough University, 2011. https://dspace.lboro.ac.uk/2134/9123.
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Millions of children travel to and from school each day as part of their daily routine. A large percentage of children make this journey by car, and the numbers are steadily rising and this is leading to many environmental and health implications for children. The current economic climate has persuaded the British Government to look again at policies relating to all school travel funding to highlight areas where savings and cuts can be made. This is interesting because the home-to-school transport provision policy has been in place since the Education Act 1944 and this policy costs local authorities in England over £1 billion a year. Therefore, the focus of this thesis is threefold. Firstly, it seeks to determine the main issues within school travel and reports on the views of current professionals in the school travel industry. Structured in-depth interviews were carried out with 16 UK and US school travel experts. The questions focused on the current stakeholders of school travel, issues regarding school travel, bus use in school travel, and the challenges faced by transport planners to ensure school pupils have a safe and pleasant journey to school. Secondly this thesis quantifies the traffic and environmental impacts of the school choice policy in England. It achieves this by analysing School Census data from 2009 from the Department for Education. Multinomial logit modelling and mixed multinomial logit modelling are used to illustrate the current travel behaviour of English children in their journey to school and examine how there can be a significant reduction in vehicle miles travelled, CO2 emissions and fuel consumption if the school choice policy is removed. The results suggest that if all children attended their nearest school, this would result in reductions in their personal mobility, vehicle miles travelled and CO2 emissions. Finally, this thesis examines the policies relating to the funding criteria of home-to-school public school transport provision. Specifically, the paper employs a multilevel modelling technique to develop a series of relationships between bus usage by school and the level of spending by local education authorities on home-to-school bus travel provision while controlling for other factors such as school quality, land-use patterns and various proxies for household incomes. The results suggest that there is a significant effect of funding on the total school-level bus passenger mileage for primary (aged less than 11), secondary (aged 11 to 16) and Post 16 schools.
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Nguyen, To Ngoc. "Essays on econometric modeling of subjective perceptions of risks in environment and human health." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2626.
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Hunt, Laurence T. "Modelling human decision under risk and uncertainty." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:244ce799-7397-4698-8dac-c8ca5d0b3e28.
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Humans are unique in their ability to flexibly and rapidly adapt their behaviour and select courses of action that lead to future reward. Several ‘component processes’ must be implemented by the human brain in order to facilitate this behaviour. This thesis examines two such components; (i) the neural substrates supporting action selection during value- guided choice using magnetoencephalography (MEG), and (ii) learning the value of environmental stimuli and other people’s actions using functional magnetic resonance imaging (fMRI). In both situations, it is helpful to formally model the underlying component process, as this generates predictions of trial-to-trial variability in the signal from a brain region involved in its implementation. In the case of value-guided action selection, a biophysically realistic implementation of a drift diffusion model is used. Using this model, it is predicted that there are specific times and frequency bands at which correlates of value are seen. Firstly, there are correlates of the overall value of the two presented options, and secondly the difference in value between the options. Both correlates should be observed in the local field potential, which is closely related to the signal measured using MEG. Importantly, the content of these predictions is quite distinct from the function of the model circuit, which is to transform inputs relating to the value of each option into a categorical decision. In the case of social learning, the same reinforcement learning model is used to track both the value of two stimuli that the subject can choose between, and the advice of a confederate who is playing alongside them. As the confederate advice is actually delivered by a computer, it is possible to keep prediction error and learning rate terms for stimuli and advice orthogonal to one another, and so look for neural correlates of both social and non-social learning in the same fMRI data. Correlates of intentional inference are found in a network of brain regions previously implicated in social cognition, notably the dorsomedial prefrontal cortex, the right temporoparietal junction, and the anterior cingulate gyrus.
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Chen, Minghui. "Analyse de la concurrence intermodale : l'évaluation de la qualité des dessertes ferroviaires et aériennes." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE2080.
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Sur la liaison Paris-Bordeaux, le temps de parcours en train est réduit de 1 heure grâce à la mise en service commerciale de la LGV SEA (Ligne à Grande Vitesse Sud Europe Atlantique) le 2 juillet 2017. Les effets envisagés sont une amélioration de la compétitivité du transport ferroviaire et un report modal en faveur du train. Dans cette thèse, nous nous intéressons aux effets de cette infrastructure ferroviaire sur les comportements de choix modal des voyageurs. En particulier, nous nous intéressons à la qualité des dessertes et les impacts de celle-ci sur les comportements des voyageurs.La qualité des dessertes est un sujet important pour les différents acteurs concernés par la nouvelle infrastructure ferroviaire. La seule prise en compte du nombre total des trains ou des arrêts intermédiaires n’est pas suffisante pour une évaluation pertinente de la qualité des dessertes. La présente thèse de doctorat a pour objet de montrer, d’un point de vue théorique et empirique, que l’approche pertinente doit être fondée sur les programmes d’activités et pas seulement sur l’offre de transport.Nous présentons des indicateurs permettant de mieux maîtriser les effets liés à la qualité des dessertes sur le choix modal des voyageurs. L’analyse commence par les indicateurs qui fournissent des informations complémentaires aux indicateurs standard comme la fréquence de service et l’intervalle de service vers un modèle plus sophistiqué capable de prendre en compte le programme d’activités et les caractéristiques des opportunités à destination. Nous nous orientons vers une approche désagrégée tout en assurant la mesurabilité des indicateurs.Les deux méthodes présentées dans cette thèse sont les indicateurs de temps utile à destination et le modèle combiné choix modal – choix d’horaires. A l’aide de la première méthode, nous améliorons notre connaissance aux effets de la qualité des dessertes avec un nouveau module intégré dans un modèle de choix modal. Grâce à la deuxième méthode, nous traitons la question de recherche avec une structure du modèle combiné qui explique à la fois le choix modal et le choix d’horaires des voyageurs. Ces méthodes sont élaborées sur la base des modèles de choix discrets.Nous effectuons une modélisation de la demande des voyageurs sur la liaison Paris - Bordeaux avec des données d’enquêtes « voyageurs ». Nous montrons que les questions conçues spécifiquement dans le questionnaire sont pertinentes pour évaluer la qualité des dessertes. Cette thèse est organisée de manière suivante :Dans la première partie, nous présentons les questions de concurrence dans le marché des transports. Parmi les différentes formes de concurrence, nous nous intéressons à la concurrence intermodale. Cette partie permet de comprendre de quoi il s’agit et pourquoi cette question est importante. Il s’agit d’une partie théorique qui comprend une revue de littérature nous permettant d’élaborer notre problématique.Nous présentons, dans la deuxième partie, nos méthodes pour évaluer la qualité des dessertes: le temps utile à destination et le modèle combiné choix modal – choix d’horaires. Nous présentons aussi les principes de la théorie de choix discrets qui est la base de nos approches.Le contexte de l’offre et la demande de transport sur la liaison Paris-Bordeaux, les données utilisées et les résultats de nos modèles sont présentés dans la troisième partie. Les avantages et les inconvénients de nos méthodes sont aussi présentés dans cette partieThe high speed line (Ligne à Grande Vitesse Sud Europe Atlantique) that has been operating since July 2, 2017, reduced train travel time by 1 hour on the Paris-Bordeaux line. The expected impacts are an improvement of the competitiveness of rail transport and a modal shift from plane to train. In this thesis, we are interested in the effects of this new railway infrastructure on travellers’ modal choice behaviour. In particular, we are interested in the quality of transport timetable and their impact on the travel behaviour.The quality of transport timetable is an important issue for the various relevant stakeholders. The total number of trains or intermediate stops are not sufficient for a relevant evaluation. The objective of this doctoral thesis is to demonstrate, from the theoretical and empirical point of view, that the relevant approach must be based on activity programs and not just on transport supply.We presented indicators for a better evaluation of the effects related to the quality of transport timetable on travellers’ modal choice. The analysis begins with indicators that provide complementary information to the standard indicators to a more sophisticated model that are able to take into account the characteristics of opportunities in destination. We directed our research to a disaggregated approach while ensuring the measurability of the indicators.Two methods are presented in this thesis: indicators of useful time at destination and the combined modal choice – schedule choice model. Using the first method, we improve our knowledge of the effects related to the quality of transport timetable with a new module integrated in modal choice models. With the second method, we study the research problem with a combined model structure that explains both the modal choice and the schedule choice. These methods are developed on the basis of discrete choice models.We performed an econometric analysis of passenger demand on the Paris - Bordeaux route with "passenger" survey data. We show that the variables specifically constructed for the evaluation of the quality of transport timetable are relevant to explain the travellers’ modal choice.This thesis is organized as follows:In the first part, we present the competition issues in the transport market. Among the different forms of competition, we are interested in intermodal competition. It helps us to understand what is involved in competition questions in the transport market and why this issue is important. This theoretical part includes a literature review that helped us to elaborate our research problem.We present, in the second part, our methods to study the quality of transport timetable: the useful time at destination and the combined modal choice – schedule choice model. In this methodological part, we also present the principles based on discrete choice theory that are the basis of our analysis.The context of our case study, the data and the results are presented in the third part. The advantages and disadvantages of our method are presented in this part of this thesis
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Vrtic, Milenko. "Simultanes Routen- und Verkehrsmittelwahlmodell." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2004. http://nbn-resolving.de/urn:nbn:de:swb:14-1085480924187-53794.
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Bei verkehrspolitischen und infrastrukturellen Massnahmen folgen als wesentliche Nachfrageveränderungen vor allem Routen- und Verkehrsmittelwahleffekte. Mit der Anwendung der sequentiellen Routen- und Verkehrsmittelwahlmodelle, ist bei solchen Massnahmen aus verschiedenen Gründen eine konsistente und gesamthafte Gleichgewichtslösung nicht möglich. Das Ziel dieser Untersuchung war, ein konsistentes und verfeinertes Verfahren zu entwickeln, mit dem die Routen- und Verkehrsmittelwahl simultan bzw. in einem Schritt als eine Entscheidung berechnet werden kann. Neben dem Gleichgewicht bei der Verteilung der Verkehrsnachfrage auf die Alternativen, war die konsistente Schätzung der Modellparameter für die Bewertung von Einflussfaktoren bei den Entscheidungen hier eine weitere wichtige Anforderung. Das Modell ist in der Lage, ein realitätsentsprechendes Verhalten der Verkehrsteilnehmer, sowohl bei schwach, als auch bei stark belasteten Strassennetzen, zu beschreiben. Die unterschiedliche Wahrnehmung der Reisekosten der Verkehrsteilnehmer und die Netzüberbelastungen werden durch ein stochastisches Nutzergleichgewicht abgebildet. Das entwickelte Verfahren ermöglicht es: - die Nachfrageaufteilung mit einem konsistenten Gleichgewicht zwischen Verkehrsangebot und Verkehrsnachfrage zu berechnen. Dabei wird ein Gleichgewicht nicht nur innerhalb des Strassen- oder Schienennetzes, sondern zwischen allen verfügbaren Alternativen (unabhängig vom Verkehrsmittel) gesucht. - durch die iterative Kalibration der Modellparameter und die Nachfrageaufteilung ein konsistentes Gleichgewicht zwischen den geschätzten Modellparametern für die Nutzenfunktion und der Nachfrageaufteilung auf die vorhandenen Alternativen (Routen) zu berechnen. - mit einem stochastischen Nutzergleichgwicht die unterschiedliche Wahrnehmung der Nutzen bzw. der generalisierten Kosten der Verkehrsteilnehmer bei der Nachfrageaufteilung zu berücksichtigen. - die Auswirkungen von Angebotsveränderungen auf die Verkehrsmittelwahl und Routenwahl durch simultane Modellierung der Entscheidungen konsistent und ohne Rückkoppelungschritte zu berechnen.
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Kuklik, Robert G. "Capital Asset Prices Modelling - Concept VAPM." Doctoral thesis, Vysoká škola ekonomická v Praze, 2008. http://www.nusl.cz/ntk/nusl-196945.
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The key objective of this thesis is the outline of an alternative capital market modeling framework, the Volatility Asset Pricing Model, VAPM, inspired by the innovative dual approach of Mandelbrot and Hudson using the method based on synthesis of two seemingly antagonistic factors -- the volatility of market prices and their serial dependence determining the capital markets' dynamics. The pilot tests of this model in various periods using the market index as well as a portfolio of selected securities delivered generally satisfactory results. Firstly, the work delivers a brief recapitulation regarding the concepts of a consumer/investor choice under general conditions of hypothetical certainty. Secondly, this outline is then followed by a description of the "classical" methodologies in the risky environment of uncertainty, with assessment of their corresponding key models, i.e. the CAPM, SIM, MIM, APTM, etc., notwithstanding results of the related testing approaches. Thirdly, this assessment is based on evaluation of the underlying doctrine of Efficient Market Hypothesis in relation to the so called Random Walk Model. Fourthly, in this context the work also offers a brief exposure to a few selected tests of these contraversial concepts. Fifthly, the main points of conteporary approaches such as the Fractal Dimension and the Hurst Exponent in the dynamic framework of information entropy are subsequently described as the theoretical tools leading to development of the abovementioned model VAPM. The major contribution of this thesis is considered its attempt to apply the abovementioned concepts in practice, with the intention to possibly inspire a further analytical research.
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Justen, Andreas. "A time-space constrained approach for modeling travel and activity patterns." Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2011. http://dx.doi.org/10.18452/16378.
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Gegenstand der Arbeit ist die Entwicklung eines tour-basierten Verkehrsnachfragemodells zur Abbildung von Aktivitätenketten unter Berücksichtigung von raum-zeitlichen constraints. Den theoretischen Hintergrund bildet ein hierarchisch organisierter Entscheidungsprozess, um die theoretisch möglichen Entscheidungskombinationen zu reduzieren und damit eine wahrscheinlichkeitsbasierte Berechnung zu ermöglichen. Als Beispieltour dient die Aktivitätenkette ‚Wohnen-Arbeit-Sekundäraktivität-Wohnen’, auf deren Basis auch die statistischen Analysen der Mobilitätsbefragung Santiagos durchgeführt werden. Unter Verwendung eines GIS werden so genannte ‚Suchräume’ (Aktionsräume in denen Sekundäraktivitäten durchgeführt werden) ermittelt. Ein Ergebnis der Datenanalyse sind Grenzwerte der maximalen täglichen Reisezeit für eine Reihe von Modus-Kombinationen. Die Zeitfenster von Startzeiten und Aktivitätendauer werden in Abhängigkeit sozioökonomischer Gruppen ermittelt. Die Bestimmung der Suchräume erfolgt in Abhängigkeit von Arbeitsdauer sowie Distanz zwischen Wohn- und Arbeitsort. Beide Kriterien erwiesen sich in der Analyse als statistisch signifikant. Der Vergleich zwischen Modell und Empirie (Santiagos Mobilitätsbefragung) deutet darauf hin, dass die Suchräume geeignet sind und die Mehrheit der beobachteten Zielwahlentscheidungen beinhalten. Zur Berechnung der Wahrscheinlichkeitspfade (unter Verwendung der Programmsyntax von SPSS) wird ein im Umfang auf sieben Ziele reduziertes Alternativenset pro Wohn- und Arbeitsstandort bestimmt. Dabei werden Erreichbarkeit und Attraktivität der Ziele innerhalb des Suchraumes berücksichtigt. Die erzielten Ergebnisse stützen das Argument, dass die raum-zeitlichen constraints (tägliche Reisezeit, Suchräume) eine effektive Reduktion der kombinatorischen Vielfalt zulassen. Die Erfahrungen aus der Berechnung der Beispieltour eignen sich zum Übertrag auf weitere Tour-Typen, um eine Modellierung der städtischen Gesamtverkehrsnachfrage zu ermöglichen.In this thesis we develop a tour-based approach for modeling activity and travel pattern considering time-space constraints. A hierarchical structure of choice-making builds theoretical background for the model and is based on a set of axiomatic rules. Our central argument is that the time-space constraints can be used for reducing the number of choices and, respectively, control the combinatorics associated with the probabilistic approach. The empirical analysis of our use case, a tour of type ‘Home-Work-SecondaryActivity-Home’, is based on Santiago’s travel survey. In addition, we apply GIS to estimate the so-called search spaces (potential areas where secondary activities are realized) and justify their sizes with the empirical findings. From the data analysis we identify thresholds for the tour-based maximum daily travel times considering a set of mode combinations. We define regimes of starting times and duration of activities depending on socio-economic user groups. The estimation of search spaces is realized considering the time spent at work as well as the distance between the home and work locations. Both criteria were found to be statistically significant. The comparison of modeled results with survey observations allowed concluding that the search spaces are realistic since they capture most of the observed trip destinations. For the estimation of spatial path flows of activities and trips (using SPSS programming language), we define a final choice set of no more than seven alternatives per primary location considering zone-based accessibility and land-use attractiveness. The obtained results support the argument that time-space constraints (daily travel time, search spaces) allow an effective control of combinatorial complexity. Basing on the experience obtained in process of modeling the exemplary tour, the approach can be applied to further tour types offering the possibility to estimate the entire transport demand of Santiago city.
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Vrtic, Milenko. "Simultanes Routen- und Verkehrsmittelwahlmodell." Doctoral thesis, [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=971486174.
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Fuentes, Andrés. "Abolishing Stockholm’s Public Transport Fares." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-332459.
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The decrease of car emission levels has stagnated in the latter years in Stockholm, Sweden. Since the city’s publictransit system is highly developed via its large access to areas located in the city’s outskirts, it could serve as a tool topartially replace the city's car traffic and reduce emissions. This study therefore aims to examine expected travelbehavior changes from a fare-free public transport system and investigate potential limitations when increasing thepublic transport travel degree in Stockholm. The theoretical background consists of the mode choice theory thatdissects the reasons behind travel habits, and the zero-price effect which explains the effects from abolishing priceswhen purchasing a service product. The methodological approach was conducted through a random probabilitysurvey conducted in a face-to-face mix mode survey interviews in outdoor environments and via computer-assistedtelephone interviewing. The data was then analyzed through MS Excel and SPSS to extract patterns and correlations.The results thereafter implicated preferences from the survey participants implying their desire to primarily reduce orabolish the public transport fares, which would lead to significant travel habits changes among the majority ofrespondents. This would result in a high number of both frequent car drivers and frequent public transit commutersthat would commute more by public transit and drive less.