With reliable models to forecast travel demand, traffic planners and decision-makers can be assisted in choosing the best solutions to obtain traffic performance goals. Practitioners have traditionally been relying on infrequent, costly and respondent pressurized travel surveys as their main source of data for these models. The drawbacks of the data collection method highlight a need to search for alternative sources of data used for the purpose. One such source is public transport “tap-in” data. This thesis executed a case study with the target of improving the travel demand model of Norrköping via public transport data. An algorithm that estimates the alighting station of travellers was applied to a data set provided by the public transport operator of the city. By allocating the OD-demand from stations to the traffic analysis zones used in the model a straightforward integration method using the tap-in estimate as a reference matrix could be used. The target with the method was to redistribute the demand in such a way that the public transport demand approached the tap-in estimate but that the total demand for all modes for the OD-pair remained unchanged. The results gave some indication that the integration of tap-in data improved the model performance from the perspective of public transports. In a regression analysis comparing the number of entries per station the integration of tap-in data increased the correlation coefficient from 0,845 to 0,864. Further was the performance for other transport modes seemingly not worsened by the integration of tap-in data. Finding an allocation procedure that was generic but still accurate proved complex. Further were drawbacks with the integration procedure highlighted where the method executed affected the results of the model, not its behaviour. The consequence of this is that, though the model might be an accurate representation of the current state of traffic, it is difficult to execute the same procedure when investigating future states. Still, the thesis stressed some of the potential for public transport data in modelling contexts, where the role of the data, given the procedure executed, still is of complementary character to travel surveys.

Pricing decision support systems have been developed in order to help retail companies optimise the prices they set when selling their goods and services. This research aims to enhance the essential forecasting and optimisation techniques that underlie these systems. This is first done by applying the method of Dynamic Linear Models in order to provide sales forecasts of a higher accuracy compared with current methods. Secondly, the method of Support Vector Regression is used to forecast future competitor prices. This new technique aims to produce forecasts of greater accuracy compared with the assumption currentlyused in pricing decision support systems that each competitor's price will simply remain unchanged. Thirdly, when competitor prices aren't forecasted, a new pricing optimisation technique is presented which provides the highest guaranteed profit. Existing pricing decision support systems optimise price assuming that competitor prices will remain unchanged but this optimisation can't be trusted since competitor prices are never actually forecasted. Finally, when competitor prices are forecasted, an exhaustive search of a game-tree is presented as a new way to optimise a retailer's price. This optimisation incorporates future competitor price moves, something which is vital when analysing the success of a pricing strategy but is absent from current pricing decision support systems. Each approach is applied to the forecasting and optimisation of daily retail vehicle fuel pricing using real commercial data, showing the improved results in each case.

Shared modes of transport, including car sharing, have been pointed out as one way of reducing private car use, contributing to an efficient transportation system that fulfills societal and environmental goals.Previous studies show that a share of car sharing users sells or refrains from acquire a new vehicle, when entering car sharing. Also, on average, car sharing has been shown to reduce Vehicle Kilometers Traveled (VKT) by car among the users.This study is conducted in three parts. First, a literature review of the effects of car sharing on travel behavior and car ownership is presented. Second, an implementation of car sharing in an existing transport model is described and the estimated effects are analyzed in relation to the findings in the literature study. In the final part, the car sharing module is reformulated to model a station-based car sharing system, where the distances to car sharing vehicles are used to distribute the effect of car sharing on car ownership spatially.This work contributes to the field by connecting the results from previous research about car sharing with practical transport modelling. The model of the station-based car sharing system is a useful tool for planners when considering the placement of car sharing stations. Also, this study provides an updated literature review covering findings of the effects of car sharing on travel behaviour and car ownership.Keywords: car sharing, station-based car sharing, travel demand modelling, vehicle ownership modelling, four-step model

Assessing the impact of domestic low-carbon technologies on the electricity distribution network requires a detailed insight into the operation of networks and the power demands of consumers. When used on a wide-scale, low-carbon technologies, including domestic scale micro-generation, heat pumps, electric vehicles and flexible demand, will change the nature of domestic electricity use. In providing a basis for the quantification of the impact upon distribution networks, this thesis details the construction and use of a high-resolution integrated model that simulates both existing domestic electricity use and low voltage distribution networks. Electricity demand is modelled at the level of individual household appliances and is based upon surveyed occupant time-use data. This approach results in a simulation that exhibits realistic time-variant demand characteristics, in both individual dwellings, as well as, groups of dwellings together. Validation is performed against real domestic electricity use data, measured for this purpose, from dwellings in Loughborough in the East Midlands, UK. The low voltage distribution network is modelled using real network data, and the output of its simulation is validated against measured network voltages and power demands. The integrated model provides a highly detailed insight into the operation of networks at a one-minute resolution. This integrated model is the main output of this research, alongside published articles and a freely downloadable software implementation of the demand model.

This work describe a theoretical model to integrate the parking traffic into the traffic demand modelling. Placed at program VISUM served from the PTV AG Karlsruhe for the traffic system modelling and rating, as well as the EVA demand model developed by LOHSE. / In dieser Arbeit wird ein modelltheoretischer Ansatz beschrieben, der neben dem fließenden Verkehr, auch den ruhenden Verkehr innerhalb der Verkehrsangebots- und Verkehrsnachfragemodellierung berechnet. Dazu dient das von der PTV AG Karlsruhe zur Verfügung gestellte Programm VISUM zur Verkehrsnetzmodellierung und Umlegung, sowie das von LOHSE entwickelte EVA-Modell zur Verkehrserzeugung, -verteilung und -aufteilung als Grundlage.

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.

This thesis is a study on the liberalization of trade in tourism services that has taken place between the European Union and Organisation of Eastern Caribbean States (OECS) under the Caribbean Forum (CARIFORUM) -European Union (EU) Economic Partnership Agreement (EPA). It focuses on Antigua and Barbuda, Dominica, Grenada, St. Kitts and Nevis, St. Lucia and St. Vincent and the Grenadines. They are all members of the OECS, the Caribbean Community and Common Market (CARICOM) and CARIFORUM and they are EPA signatories. Using Panel Auto Regressive Distributed Lag modelling, the study is the first to empirically test the effect of liberalizing trade in tourism services (proxied by the EPA) on inflows of tourism related foreign direct investment and European tourism demand regarding the aforementioned countries. It focuses on the period 1997 – 2013. The results indicate that Gross Domestic Product Per Capita (GDPPC) is a statistically significant determinant of tourism related foreign direct investment. This supports the established hypothesis that market size measured by GDP per capita is a key determinant of FDI. Inflation rate (IR) and trade openness (OPEN) are also significant determinants of tourism related foreign direct investment whilst the EPA is not. Regarding European tourism demand income, prices, prices in a substitute destination and room supply are statistically significant determinants in the long run. Barbados is viewed as a complementary destination to the OECS EPA signatories. However, in the short run the EPA is not a statistically significant determinant of European tourism demand which it negatively affects.

Um dos tópicos mais importantes na análise de demanda por transportes é a relação entre as necessidades individuais de realização de atividades geograficamente distribuídas, a estrutura urbana, as características individuais e domiciliares, o sistema de transporte e as diferenças no comportamento relacionado a viagens. Isto motivou o desenvolvimento desta pesquisa, que tem como objetivo principal analisar o comportamento individual subjacente ao encadeamento de viagens sob a perspectiva de três grupos de variáveis: (1) participação em atividades; (2) características socioeconômicas; e (3) uso do solo. Há dois objetivos secundários, fundamentais para se atingir a finalidade do trabalho: (a) propor um conjunto de variáveis de uso do solo; e (b) testar a significância do grupo de variáveis ora proposto. Este trabalho baseou-se nos dados da pesquisa origem-destino de 1997 da região metropolitana de São Paulo, sendo extraídas e analisadas seis amostras finais que foram caracterizadas por setor econômico (no caso de trabalhadores) e grau de instrução (no caso de estudantes). Com utilização conjunta de técnicas de análise multivariadas, confirmatórias e exploratórias, foi possível representar a variável dependente (Análise de Cluster), bem como encontrar relações entre variáveis envolvidas (Árvore de Decisão) e, finalmente, mensurar a significância estatística das variáveis independentes (Regressão Linear Múltipla). Através dos resultados obtidos, foi possível analisar a influência dos três grupos de variáveis na seqüência de viagens: (1) variáveis socioeconômicas (renda familiar, usa vale transporte, nº provável de carteiras de habilitação no domicílio, idade, nº de automóveis no domicílio) afetam principalmente a seqüência de modos de transporte utilizados durante as viagens; (2) participação em atividades (estuda, trabalha) interfere na seqüência de motivos de viagem; e, enfim, (3) variáveis de uso do solo (parcela acumulada de empregos ou escolas por faixas de distância a partir do centróide da zona de residência) influenciam a seqüência de destinos escolhidos. Espera-se que o presente trabalho constitua uma contribuição ao meio acadêmico, tanto em termos de representação da intensidade e distribuição geográfica das atividades no meio urbano (variáveis de uso do solo), quanto em relação à influência de tais variáveis nos deslocamentos dos indivíduos. / One of the most important topics in transportation demand is the relationship between individual needs to carry out geographically distributed activities, urban configuration, individual and household characteristics, transportation system and travel behavior. For that reason, the main aim of this work is to analyze the individual trip-chaining behavior in terms of three variables groups: (1) activity participation; (2) socioeconomic characteristics; and (3) land use. There are also two secondary objectives derived from the main objective: (a) to propose one set of land use variables; and (b) to verify the statistical significance of the created land use group variables. This work was based on the origin-destination survey carried out in the São Paulo metropolitan area in 1997, from which six final samples were extracted, analyzed and characterized by economic sector (for workers) and level of education (for students). Applying multivariate analysis techniques, confirmatory and exploratory, it was possible to represent the dependent variable (Cluster Analysis), as well as to find relationships between the concerned variables (Decision Tree) and, finally, to measure the statistical significance of the independent variables (Multiple Regression). From the results, it was possible to analyze the influence of the three variables groups on trip-chaining: (1) socioeconomic variables (household income, transit voucher use, probable number of driver licenses per household, age, car-ownership) affect the travel mode sequence used for the trips; (2) activity participation (study, work) has an effect on the trip purpose sequence; and (3) land use variables (accumulated proportion of jobs or schools by distance buffers starting from the residence zone centroid) influence the sequence of chosen destinations. It is expected that the present work could be a contribution to the scientific community for the representation of the activities level and their geographic distribution in the urban configuration (land use variables), and the influence of such variables on individuals displacements.

Um dos tópicos mais importantes na análise de demanda por transportes é a relação entre as necessidades individuais de realização de atividades geograficamente distribuídas, a estrutura urbana, as características individuais e domiciliares, o sistema de transporte e as diferenças no comportamento relacionado a viagens. Isto motivou o desenvolvimento desta pesquisa, que tem como objetivo principal analisar o comportamento individual subjacente ao encadeamento de viagens sob a perspectiva de três grupos de variáveis: (1) participação em atividades; (2) características socioeconômicas; e (3) uso do solo. Há dois objetivos secundários, fundamentais para se atingir a finalidade do trabalho: (a) propor um conjunto de variáveis de uso do solo; e (b) testar a significância do grupo de variáveis ora proposto. Este trabalho baseou-se nos dados da pesquisa origem-destino de 1997 da região metropolitana de São Paulo, sendo extraídas e analisadas seis amostras finais que foram caracterizadas por setor econômico (no caso de trabalhadores) e grau de instrução (no caso de estudantes). Com utilização conjunta de técnicas de análise multivariadas, confirmatórias e exploratórias, foi possível representar a variável dependente (Análise de Cluster), bem como encontrar relações entre variáveis envolvidas (Árvore de Decisão) e, finalmente, mensurar a significância estatística das variáveis independentes (Regressão Linear Múltipla). Através dos resultados obtidos, foi possível analisar a influência dos três grupos de variáveis na seqüência de viagens: (1) variáveis socioeconômicas (renda familiar, usa vale transporte, nº provável de carteiras de habilitação no domicílio, idade, nº de automóveis no domicílio) afetam principalmente a seqüência de modos de transporte utilizados durante as viagens; (2) participação em atividades (estuda, trabalha) interfere na seqüência de motivos de viagem; e, enfim, (3) variáveis de uso do solo (parcela acumulada de empregos ou escolas por faixas de distância a partir do centróide da zona de residência) influenciam a seqüência de destinos escolhidos. Espera-se que o presente trabalho constitua uma contribuição ao meio acadêmico, tanto em termos de representação da intensidade e distribuição geográfica das atividades no meio urbano (variáveis de uso do solo), quanto em relação à influência de tais variáveis nos deslocamentos dos indivíduos. / One of the most important topics in transportation demand is the relationship between individual needs to carry out geographically distributed activities, urban configuration, individual and household characteristics, transportation system and travel behavior. For that reason, the main aim of this work is to analyze the individual trip-chaining behavior in terms of three variables groups: (1) activity participation; (2) socioeconomic characteristics; and (3) land use. There are also two secondary objectives derived from the main objective: (a) to propose one set of land use variables; and (b) to verify the statistical significance of the created land use group variables. This work was based on the origin-destination survey carried out in the São Paulo metropolitan area in 1997, from which six final samples were extracted, analyzed and characterized by economic sector (for workers) and level of education (for students). Applying multivariate analysis techniques, confirmatory and exploratory, it was possible to represent the dependent variable (Cluster Analysis), as well as to find relationships between the concerned variables (Decision Tree) and, finally, to measure the statistical significance of the independent variables (Multiple Regression). From the results, it was possible to analyze the influence of the three variables groups on trip-chaining: (1) socioeconomic variables (household income, transit voucher use, probable number of driver licenses per household, age, car-ownership) affect the travel mode sequence used for the trips; (2) activity participation (study, work) has an effect on the trip purpose sequence; and (3) land use variables (accumulated proportion of jobs or schools by distance buffers starting from the residence zone centroid) influence the sequence of chosen destinations. It is expected that the present work could be a contribution to the scientific community for the representation of the activities level and their geographic distribution in the urban configuration (land use variables), and the influence of such variables on individuals displacements.