Made available in DSpace on 2016-06-02T20:00:38Z (GMT). No. of bitstreams: 1 3798.pdf: 2095976 bytes, checksum: b15115384f7a1b3abfa6d6b28d9ed7a0 (MD5) Previous issue date: 2011-10-22 / Financiadora de Estudos e Projetos / In the late years, the number of children who go to school by active modes of transport has decreased significantly. This fact causes several problems both in the area of urban transport (creating traffic congestions and accidents in the school neighborhood during the periods of starting and finishing classes) and in the area of public health (increasing the indices of child obesity). In this context, the objective of this research is to identify which factors influence the mode choice of elementary school children to access the schools. The focus of the research are the public elementary schools, because the geographic area that these schools traditionally serve (neighborhoods) permits that the trips be made by non motorized modes, for a great fraction of the students. The case study was developed in the city of São Carlos, SP with students that attend Municipal Elementary Schools. The survey was carried with the students´ parents by means of questionnaires about the children s personal characteristics, as well as their perception of the route from the residence to the school. The data showed that several factors influence the mode choice for the children trip to school, like the perception of safety and security in the neighborhood, the automobile availability in the residence, the parents habits and culture in relation to the motorized modes of transport and the distance for the residence to the school (the factor that proved to have the strongest impact in the parents decision). The discrete choice models were chosen for the estimation of the modal choice because they are largely used in transportation studies. Among the models that were tested, the multinomial logit was the most adequate. The calibrated model showed satisfactory and significant results, demonstrating that the chosen approach is adequate to the analysis of the mode choice for the trips of children to school. / Nos últimos anos, o número de crianças que vão por modos ativos para a escola vem diminuindo significativamente. Este fato causa problemas tanto na área de transporte urbano, (gerando congestionamentos e acidentes na região das escolas nos horários de entrada e saída) como na área de saúde pública (aumentando os índices de obesidade infantil). Neste contexto, esta pesquisa visa identificar quais os fatores que influenciam na opção de modo de transporte para acesso das crianças à escola. O foco da pesquisa são as escolas de ensino público fundamental porque a área geográfica que estas escolas tradicionalmente servem (bairros) permite que as viagens se dêem por modos não motorizados, para uma grande parcela dos alunos. O estudo de caso foi realizado na cidade de São Carlos, SP, junto aos alunos de Escolas Municipais de Ensino Básico (EMEBs). A coleta de dados foi realizada junto aos pais dos alunos através de questionários sobre características pessoais das crianças, bem como a percepção do ambiente a ser percorrido no caminho casa-escola. Os dados demonstraram que vários fatores influenciam a escolha do modo de transporte das crianças para a escola, como a percepção de seguridade e segurança do bairro, a disponibilidade de automóveis nas residências, os hábitos e a cultura dos pais em relação ao uso de modos motorizados e a distância casa-escola (fator de maior impacto na decisão dos pais). Para estimativa do modelo de opção modal, optou-se pelo uso de modelos de escolha discreta, devido ao fato de este modelo ser largamente utilizado para estudos na área de transportes. Dentre os modelos testados, o modelo logit multinomial se mostrou mais adequado. O modelo calibrado apresentou resultados satisfatórios e significativos, demonstrando que a abordagem utilizada é adequada à análise da escolha modal para viagens de crianças para a escola.

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.

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.

There are a number of issues preventing the rollout of cargo bikes as a transportation mode in the United States. One concern that has been raised is whether cargo bikes can function as a gender equitable transportation solution in the United States, given documented gender gaps in national bike riding statistics and ongoing inequities in childcare in 2-parent heterosexual households. The research is aimed at reviewing the practicality, enjoyment, and outcome of cargo bike use as a gender equitable transportation solution. This research contributes to new knowledge in gender equitable transportation in 2 ways — a) gender-focused analysis of survey data regarding cargo bikes use; b) extended open-ended interviews with mothers with cargo bikes. Qualitative and quantitative data from surveys and interviews explore the influence of cargo bikes on transportation patterns and follow how behavior, attitude, spatial context, and perception varies between riders. Specific attention is given to the use of cargo bikes by women with children, as this demographic represents a minority group in the bicycle community and a group who could benefit most from the capabilities of a cargo bike design. Research shows, mothers spend more hours a day around their children and take part in more child-related activities. Therefore, the comfort and feasibility of the cargo bike for women with children becomes the topic of exploration to determine whether this mode type is a functional substitution for trips usually made by an automobile. Through the collection of a nation-wide survey of cargo bike riders and in-person interviews with mothers in San Luis Obispo, CA who currently use a cargo bike to transport their children and goods, the research assesses the travel patterns of women and the emotional and physical benefits cargo bikes can provide to this specific demographic. Results show that benefits of cargo bike use include boding opportunities with children and a more enjoyable commute, while barriers to use include ill-performing bicycle infrastructure and time allocation for trips made by the cargo bike, in comparison to the automobile. Mode substitution behavior from the automobile to the cargo bike is geographically and culturally specific, but as results from both parts of the study show, women are receptive to cargo bike use and demonstrate a powerful demographic that has the potential to influence the travel patterns of current and future commuters to shift away from automobile dependency.

The increasing number of travelers in urban areas has led to new opportunities for local government and private mobility providers to offer new travel modes besides and in addition to traditional ones. Multimodal travel provides an especially promising opportunity. However, until now the underlying reasons why consumers choose specific alternatives have not been fully understood. Hence, the design of new travel modes is mainly driven by obvious criteria such as environmental friendliness and convenience but might not consider consumers’ real or latent needs. To close this research gap, sixty in-depth interviews with urban travelers were conducted. To identify the perceptual differences of customers among different travel modes, the repertory grid technique as an innovative, structured interview method was applied. Our data show that urban travelers distinguish and select travel alternatives based on 28 perceptual determinants. While some determinants associated with private cars such as privacy, flexibility and autonomy are key indicators of travel mode choice, costs and time efficiency also play a major role. Furthermore, by comparing travel modes to an ideal category, we reveal that some perceptual determinants do not need to be maximized in order to fulfill customer needs optimally. A comparison of consumers’ perceptual assessments of alternative travel modes identifies specific advantages and disadvantages of all alternatives, and provides fruitful implications for government and private mobility providers.

Reliable forecasting models are needed to achieve the climate related goals in the face of increasing transport demand. Such models can predict the long-term behavioural response to policy interventions, including infrastructure investments, and thus provide valuable pre-dictions for decision makers. Contemporary forecasting models are mainly based on national travel surveys. Unfortunately, the response rates of such surveys have steadily declined, implying that the respondents become less representative of the whole population. A particular weakness is that it is likely that respondents with a high valuation of time are less willing to respond to surveys (because they have less time available for such), and therefore there is a high chance that they are underrepresented among the respondents. The valuation of time plays an important role for the cost benefit analyses of public policies including transport investments, and there is no reliable way of controlling for this uneven sampling of time preferences. Fortunately, there is simultaneously an increase in the number of signals sent between mobile phones and network antennae, and research has now reached the point where it is possible to determine not only the travel destination but also the travel mode based on mobile phone network antennae connections. The aim of this thesis is to investigate if and how mobile phone network data can be used to estimate transportation mode choice demand models that can be used for forecasting and planning. Key challenges with using this data source in the context of mode choice models are identified and met. The identified challenges include uncertainty in the choice variable, the difficulty to distinguish car and bus trips, and the lack of information about the trip purpose. In the first paper we propose three possible model formulations and analyse how the uncertainty in the choice outcome variable would play a role in the different model formulations. We also conclude that it is indeed possible to estimate mode choice demand models based on mobile phone network data, with good results in terms of behavioural interpretability and significance. In the second paper we estimate models using a nested logit structure to account for the difficulty in separating bus and car, and a latent class model specification to meet the challenge of having an unknown trip purpose. / <p><strong>Funding agencies:</strong> The research in this thesis has mainly been funded by the research projects DEMOPAN and DEMOPAN-2 within the research program Transportekonomi at The Swedish Transport Administration.</p>

Purpose To strengthen our understanding of the impact of baseline variability in mode choice on the likelihood of travel behaviour change. Methods Quasi-experimental analyses in a cohort study of 450 commuters exposed to a new guided busway with a path for walking and cycling in Cambridge, UK. Exposure to the intervention was defined using the shortest network distance from each participant’s home to the busway. Variability in commuter travel behaviour at baseline was defined using the Herfindahl–Hirschman Index, the number of different modes of transport used over a week, and the proportion of trips made by the main (combination of) mode(s). The outcomes were changes in the share of commute trips (i) involving any active travel, (ii) involving any public transport, and (iii) made entirely by car. Variability and change data were derived from a self-reported seven-day record collected before (2009) and after (2012) the intervention. Separate multinomial regression models were estimated to assess the influence of baseline variability on behaviour change, both independently and as an interaction effect with exposure to the intervention. Results All three measures of variability predicted changes in mode share in most models. The effect size for the intervention was slightly strengthened after including variability. Commuters with higher baseline variability were more likely to increase their active mode share (e.g. for HHI: relative risk ratio [RRR] for interaction 3.34, 95% CI 1.41, 7.89) and decrease their car mode share in response to the intervention (e.g. for HHI: RRR 7.50, 95% CI 2.52, 22.34). Conclusions People reporting a higher level of variability in mode choice were more likely to change their travel behaviour following an intervention. Future research should consider such variability as a potential predictor and effect modifier of travel and physical activity behaviour change, and its significance for the design and targeting of interventions.

With the beginning of the COVID-19 outbreak and the restrictions put in place to prevent an uncontrolled spread of the virus, the circumstances for daily activities changed. A remarkable shift in the modal split distribution was observed. Cycling was seen as a reliable and resilient option in pandemic times as it allowed social distancing and poses a low risk of contagion. There are detailed studies on the effect of the pandemic on cycling traffic all over the globe which used different data sources, like app data. counters or surveys [1] [2]. Apart from the citizens' behavioral responses to the corona pandemic, the municipalities also put up interventions that were meant to support a shift to cycling-based movements in cities. The question to discuss is what changes will be permanent and which changed circumstances, e.g. increased subjective safety, lead to a long-term change of mobility patterns. The changes in mobility during the COVID-19 pandemic bad different impacts on road traffic collisions and road deaths in different countries. While there was a reduction of both indicators in 32 out of 36 countries in April 2020 compared to April 2019, there was an increase in the other four countries [3]. Others also found a reduction of traffic fatalities in 23 out of 24 countries in 2020 compared to a baseline of the previous years (2017-2019), the only exception being Switzerland [4]. The subjective well-being has also changed differently for the different transport modes throughout the pandemic. For example, in April 2020, 9% of respondents said they would feel more comfortable or much more comfortable if they used or would use a bicycle compared to pre-pandemic times; in summer and autumn 2020, this figure was 11 %, in spring 2021, it was 13%. In autumn 2021, 15% of respondents said they would feel more comfortable or much more comfortable if they used or would use a bicycle than before the spread of the coronavirus [ 5]. [From: Introduction]

Today’s sparse cities with for example workplaces located outside the city centre has led to increased travel levels for the inhabitants. The long distance between different attribute has resulted in a car dependency. To achieve the climate goals and a sustainable development it’s important to have a transition to more sustainable travel modes. This essay focus on socially and environmentally sustainable travels to workplaces outside the city centre. The aim of the study is the understand how the geographical location of the workplace affects the travel mode choice. The ambition is to examine the possibilities for environmentally sustainable travel at the same time as the travel also must be socially sustainable and feasible in the individual’s everyday life. This study is conducted in Umeå with a workplace located outside the city centre. The empirical material has been collected through interviews with employees in purpose the understand the individual conditions and travel patterns. The results are then discussed and analysed using, theories and previous research, time-geography, aspects of accessibility and travel mode choice to create an understanding of sustainable travel to workplaces with an external localisation. The results identified challenges linked to long distance, lack of accessibility to use other travel modes and individual constraints. The results shows that individuals have different constraints and opportunities to change their travel mode, but that it is also bound to how much an individual is willing, and able, to sacrifice.

Reliable forecasting models are needed to achieve the climate related goals in the face of increasing transport demand. Such models can predict the long-term behavioural response to policy interventions, including infrastructure investments, and thus provide valuable pre-dictions for decision makers. Contemporary forecasting models are mainly based on national travel surveys. Unfortunately, the response rates of such surveys have steadily declined, implying that the respondents become less representative of the whole population. A particular weakness is that it is likely that respondents with a high valuation of time are less willing to respond to surveys (because they have less time available for such), and therefore there is a high chance that they are underrepresented among the respondents. The valuation of time plays an important role for the cost benefit analyses of public policies including transport investments, and there is no reliable way of controlling for this uneven sampling of time preferences. Fortunately, there is simultaneously an increase in the number of signals sent between mobile phones and network antennae, and research has now reached the point where it is possible to determine not only the travel destination but also the travel mode based on mobile phone network antennae connections. The aim of this thesis is to investigate if and how mobile phone network data can be used to estimate transportation mode choice demand models that can be used for forecasting and planning. Key challenges with using this data source in the context of mode choice models are identified and met. The identified challenges include uncertainty in the choice variable, the difficulty to distinguish car and bus trips, and the lack of information about the trip purpose. In the first paper we propose three possible model formulations and analyse how the uncertainty in the choice outcome variable would play a role in the different model formulations. We also conclude that it is indeed possible to estimate mode choice demand models based on mobile phone network data, with good results in terms of behavioural interpretability and significance. In the second paper we estimate models using a nested logit structure to account for the difficulty in separating bus and car, and a latent class model specification to meet the challenge of having an unknown trip purpose. / <p><strong>Funding agencies:</strong> The research in this thesis has mainly been funded by the research projects DEMOPAN and DEMOPAN-2 within the research program Transportekonomi at The Swedish Transport Administration.</p>