This study aimed to investigate various aspects of cyclist exposure to common urban air pollutants, including CO, PM10, PM2.5, PM1.0 and UFPs. The initial part of the study compared cyclist exposure to that of other transport modes, while the second part addressed the implications of route choice. The final part analysed the effect of proximity to traffic. Data was collected in Christchurch and Auckland cities over a nine week period, with a total of 53 inter-modal and 7 separate cyclist sampling runs completed. Mobile sampling was conducted using a collection of instruments in four portable kits. Fixed-site meteorological data was used to find associations between pollutants and temperature and wind speed. Spatial patterns were also considered by means of time-series comparative graphs and colour-coded pollutant concentration GPS mapping. The cyclist mode was up to 61% less exposed than the car for primary pollutants (CO and UFPs), but up to 26% more exposed for PM1.0-10. The bus was generally the most exposed for all pollutants apart from CO. The effect of route choice was substantial, with the off-road cyclist route recording a reduction of 31% for CO and PM1.0, and 53% for UFPs while PM10 was 6%. At a distance of 7 m from traffic, exposure dropped by 30% (UFPs), 22% (CO) and 14% (PM2.5). At 19 m, concentrations decreased a further 17%, 13% and 8%, respectively. When moving much further away from traffic (~700 m), the effect was far less pronounced and no difference was observed for CO past 19 m. Conclusions suggest that for most pollutants studied, the cyclist mode faces much lower exposure than other modes, especially when traveling through backstreets and cycle tracks. Significant exposure reductions can also be made when only a very small distance away from traffic emissions. This has positive implications for health, sustainable city planning and active-mode transport promotion.

This study aimed to investigate various aspects of cyclist exposure to common urban air pollutants, including CO, PM10, PM2.5, PM1.0 and UFPs. The initial part of the study compared cyclist exposure to that of other transport modes, while the second part addressed the implications of route choice. The final part analysed the effect of proximity to traffic. Data was collected in Christchurch and Auckland cities over a nine week period, with a total of 53 inter-modal and 7 separate cyclist sampling runs completed. Mobile sampling was conducted using a collection of instruments in four portable kits. Fixed-site meteorological data was used to find associations between pollutants and temperature and wind speed. Spatial patterns were also considered by means of time-series comparative graphs and colour-coded pollutant concentration GPS mapping. The cyclist mode was up to 61% less exposed than the car for primary pollutants (CO and UFPs), but up to 26% more exposed for PM1.0-10. The bus was generally the most exposed for all pollutants apart from CO. The effect of route choice was substantial, with the off-road cyclist route recording a reduction of 31% for CO and PM1.0, and 53% for UFPs while PM10 was 6%. At a distance of 7 m from traffic, exposure dropped by 30% (UFPs), 22% (CO) and 14% (PM2.5). At 19 m, concentrations decreased a further 17%, 13% and 8%, respectively. When moving much further away from traffic (~700 m), the effect was far less pronounced and no difference was observed for CO past 19 m. Conclusions suggest that for most pollutants studied, the cyclist mode faces much lower exposure than other modes, especially when traveling through backstreets and cycle tracks. Significant exposure reductions can also be made when only a very small distance away from traffic emissions. This has positive implications for health, sustainable city planning and active-mode transport promotion.

Indiana University-Purdue University Indianapolis (IUPUI) / The use of Global Positioning Systems (GPS) and/or accelerometers to identify trips and transportation modes such as walking, running, bicycling or motorized transportation has been an active goal in multiple disciplines such as Transportation Engineering, Computer Science, Informatics and Public Health. The purpose of this study was to review existing methods that determined trip and travel mode from raw Global Positioning System (GPS) and accelerometer data, and test a select group of these methods. The study had three specific aims: (1) Create a systematic review of existing literature that explored various methods for determining trip and travel mode from GPS and/or accelerometer data, (2) Collect a convenience sample of subjects who were assigned a GPS and accelerometer unit to wear while performing and logging travel bouts consisting of walking, running, bicycling and driving, (3) Replicate selected method designs extracted from the systematic review (aim 1) and use subject data (aim 2) to compare the methods. The results were be used to examine which methods are effective for various modes of travel.

A disproportionate number of Americans drive to work alone – at the individual state level, the figure ranges from a low of 58% in New York to 85% in Alabama. What factors explain this travel behavior and what sort of policy responses are required to effect changes? In responding to this question, we used multiple test beds and made the case for a demand side management approach to remedy parking problems particularly observed in cities central business districts. To this end, we provide an overview of travel behavior and information on policy levers by generating detailed profiles that capture the travel behavior of commuters in the Pacific states of the continental United States. Building off the result that revealed San Francisco as an outlier, we examine the efficacy of modifying parking rates, via elasticity measures, to influence the demand for parking by developing a two-stage panel data regression optimization model for managing parking in the City of San Francisco. A key contribution of the research is deriving these price elasticities of parking demand estimates using panel data methods. Coefficient estimates from the panel data regression are used to fit a linear prediction model that is the primary input to the optimization model. The balance of the thesis focuses on parking information by discussing the design and implementation of ParkPGH, a novel smart parking application that provides real time and predictive information on garage parking availability in downtown Pittsburgh. At its core is a predictive model that uses as input historical parking, weather and event data to provide estimates of available parking spaces. We provide an example of the model implementation using data from the Theater Square garage where we utilize neural network-based predictors and multiple net searches to generate both continuous and binary estimates of parking availability. Provision was made for the binary classifier given the need to reduce the possibility of Type II errors.

Children’s everyday travel and parents’ choices of mode of travel.   Karola Fors, Department of Geography, Umeå University, Sweden     Abstract The purpose of this interview study was to investigate parents’ choice of travel mode for their child and behavioral change towards sustainable travel. The study was conducted in Umeå, a city in northern Sweden, in March and April 2019. The interview focused on parents describing from travel journals one week of their child’s travel arrangements. The analysis of the interviews was based on The Theory of Planned Behavior (Azjen 1991). Attitude, perceived Control and Norms, lead to the Intentions to change behavior and this is described by Azjen (1991) and is also noticeable in the study conducted. Mobility Management projects in the municipalities aim to increase the use of sustainable travel modes. The parents described that the reasons for choosing their child’s mode of travel was time, distance, safety and weather conditions as determined by seasons. Some described practical reasons, age and maturity. None of the parents described health and environmental concerns when describing the choice of travel mode. The travel journals showed that most commutes were made by car, especially concerning trips to leisure activities. The intention to make changes towards sustainable travel modes varied in accordance to attitude, perceived control and norms described. Some described the child biking or taking the bus more often, others described future trips mainly by car. The norms in society is a challenge for Mobility Management projects in establishing habits towards sustainable travel modes.

The purpose of this thesis was to investigate how children experience their everyday travel. More specifically how do certain travel characteristics influence children’s current mood, experiences of their everyday travel, and their cognitive performance. The thesis consists of two papers (Papers I and II). In Paper I, 206 children (101 girls) in grade 4 (aged 10), in the city of Staffanstorp in Sweden, recorded all their journeys in a diary during one school week, along with reports of their travel mode, their current mood while travelling (ranging from very sad to very happy and from very tired to very alert), their activities on arrival, and their experiences regarding those activities. In Paper II, a sample of 344 children (165 girls) between the ages of 10 and 15 was taken at five public schools in Värmland County, Sweden. The children rated their current mood, filled out the Satisfaction with Travel Scale (capturing the travel experience), reported details about their journeys, and took a word-fluency test. The findings show that children’s immediate affective experiences (current mood) vary with how they travel and where they go, and that there is a difference between boys’ and girls’ experiences. Children who travel by car experience the lowest degree of quality and activation, something which is also maintained throughout the school day (as the case with activation). Social activities during travel add to higher degree of quality and excitement, while solitary activities bring more stress. The findings further show that using a smartphone or doing a combination of activities during the journey results in better cognitive performance, as do longer traveling times. It is concluded that where and how children travel, what they do when traveling, and for how long they travel all affect children’s travel experiences, mood, and/or cognitive performance. This thesis sheds light on a neglected research area – which is the experiences of travel – through the lens of a child. / The purpose of this licentiate thesis is to examine how children experience their everyday travel. More specifically, do travel mode, travel time, and travel activities influence children’s experiences of their everyday travel, how they feel, and how they perform at school. In Paper 1 we investigate whether children’s moods, while travelling, vary with travel mode and destination. In Paper 2 we investigate whether children’s experiences of travel and current mood vary with travel mode, traveling time, and activities during travel. We also investigate whether the travel experience affects cognitive performance. The overall findings of the two studies suggest that where and how children travel, what they do when traveling, and for how long they travel all affect children’s travel experiences, moods, and cognitive performance. These novel findings bring important knowledge of the impact of a journey. Children are the next generation of traveler; how they experience their day-to-day travel may contribute toward their future travel behavior and influence how societies travel in the future.

The general aim of this thesis was to investigate affective forecasting in the context of public transport. Paper I, Study 1 revealed that non-users of public transport were less satisfied with the services than users. It was hypothesised that non-users were biased in their satisfaction ratings, a claim that was subsequently investigated in Paper I, Study 2, where a field experiment revealed that car users suffer from an impact bias, due to being more satisfied with the services after a trial period than they predicted they would be. To address the question of whether a focusing illusion is the psychological mechanism responsible for this bias, two experiments containing critical incidents were conducted in Paper II. These experiments investigated whether car users exaggerate the impact that specific incidents have on their future satisfaction with public transport. A negative critical incident generated lower predicted satisfaction with public transport, both for car users with a stated intention to change their current travel mode (in Paper II, Study 1) and for car users with no stated intention to change their travel mode (in Paper II, Study 2), which support the hypothesis that the impact bias in car users’ predictions about future satisfaction with public transport is caused by a focusing illusion. Paper III showed that car users misremember their satisfaction with public transport as a result of their recollections of satisfaction with public transport being lower than their on-line experienced satisfaction. Additionally, the desire to repeat the public transport experience is explained only by remembered satisfaction, not by on-line experienced satisfaction. Paper IV investigated whether a defocusing technique would counteract the focusing illusion by introducing a broader context, thereby generating higher predicted satisfaction. A generic defocusing technique, conducted in Paper IV, Study 1, did not generate higher predicted satisfaction, whereas a self-relevant defocusing technique conducted in Paper IV, Study 2 generated higher predicted satisfaction with public transport. Additionally, it was found that car-use habit accounts for the level of predicted satisfaction regardless of defocusing; the stronger the car-use habit, the lower the predicted satisfaction. The conclusions from this thesis are that non-users of public transport rate the services lower than users do, and that car users become more satisfied when using the services than they predicted. These mispredictions are a result of over-focusing on a limited range of aspects in public transport (i.e., a focusing illusion). Car users’ desire to repeat the public transport experience is influenced by their inaccurate memories of the services and not by their actual experiences. However, defocusing techniques may help car users make more accurate predictions about future satisfaction with public transport; this could facilitate a mode switch from using the car to using public transport services more often. Switching to a more sustainable transport mode could be beneficial for the individual and for society.

This study examines the impact of the COVID-19 pandemic on residents' commuting patterns in the United States. Using the MNL (Multinomial Logit) and binary logit models, we analyze the factors influencing the choice of commuting modes before and during the pandemic. Our findings indicate that various personal, travel-related, and COVID-19-related factors significantly affect commuting choices. For commuting methods other than driving, factors such as gender, age, possession of a driver's license, bicycle ownership, car ownership, family size, working days per week, COVID-19 testing, and mask restrictions play a significant role. The decision to walk to work is influenced by gender, vehicle ownership, travel time, travel distance, working days per week, family income, COVID-19-related relocation, and level of COVID-19 anxiety. Public transportation choices are influenced by factors such as age, race, possession of a driver's license, car ownership, travel time, travel distance, COVID-19-related migration, and COVID-19 testing of cohabitants. Furthermore, the binary logit model reveals that personal factors (e.g., gender, driver's license) and COVID-19-related factors (e.g., mask restrictions, level of concern about the coronavirus) significantly impact the consistency of travel modes before and during the pandemic. This study contributes to our understanding of the changes in commuting patterns during the COVID-19 pandemic and provides insights into the factors that shape residents' commuting choices. The findings can inform transportation planning and policy-making to promote sustainable and resilient transportation systems in the face of future disruptions.

High levels of personal car use have negative effects on the environment and on human health. This thesis presents four empirical studies that aimed to develop our knowledge of personal travel choices, focussing on the malleability of attitudes and their sensitivity in relation to specific contexts and goals. The first study (Chapter 2) presents a systematic review and meta-analysis of mechanisms of travel mode choice. The study provides a comprehensive overview of antecedents of car use and non-car use, including sub-group analyses of different contextual factors. Results also highlight the need for standardised measures and consideration of implicit thought processes. The second study (Chapter 3) employs a repertory grid technique to elicit perceptions of seven different transport modes from high mileage car users and non-car users. Comparisons between car users and non-car users highlight potentially effective and ineffective intervention targets. Findings show how sustainable transport might be promoted amongst a portfolio of travel choices. The third study (Chapter 4) utilises qualitative methods to explore the extent to which individuals’ attitude expressions are changeable. The study demonstrates that all participants hold ambivalent and conflicting attitudes, highlighting specific situations in which those attitudes are more likely to be unstable. Two related priming experiments are presented in the final empirical chapter (Chapter 5). Both use survey methodology to investigate whether manipulating the salience of car-use-incongruent goals can lead to more positive attitudes towards and increased willingness to use non-car travel modes. The study confirms that people who are motivated to make changes are a potentially optimal target group for interventions based on subliminal messages. Overall, the research presented in this thesis introduces context sensitivity into the transport literature and offers novel insights into perceptions of a range of travel modes. Recommendations include relevant avenues for future research, findings are discussed in light of implications for transport policy and practice.

This dissertation focuses on the relationship between accessibility to job opportunities, travel mode choices and employment outcomes of the disadvantaged. In past research examining the impact of accessibility on employment outcomes of the underprivileged, it has been an implicit assumption that a poor individual's employment status is directly connected to accessibility to transport modes and job opportunities. This dissertation challenges such a fundamental assumption and argues that due to unique travel needs of the poor, a high level of access to transportation means or job accessibility provided by a given travel mode does not automatically determine the choice of that particular travel mode. What is missing in the existing literature is examination of how accessibility affects travel mode choices for low-income individuals, and how travel mode preferences subsequently influence their employment outcomes. The objective of this dissertation is to shed new light on current understanding of the relationship between transportation and employment of the disadvantaged. The study focuses on explaining what factors influence low-income individuals in their choice of a transportation mode, and more importantly, how modal preferences, along with job accessibility, affect employment of the poor. Household travel survey data from the San Francisco Bay Area and the Atlanta Metropolitan Region were used to examine this interrelationship. The research findings show that higher modal and job accessibility do not always determine the choice of a particular travel mode, defying the assumption of the previous studies. What is important for enhancing one's employment is whether or not a low-income person has regular access to cars and an individual circumstance allows the poor to utilize existing automobiles rather than the efficiency of highway network. In terms of public transportation, higher job accessibility by transit network is associated with better employment outcomes for transit users. Nonetheless, when transit riders had to access transit systems by walking, job accessibility did not have meaningful impact on employment. It is important to note that the impact that job accessibility by transit has on employment is found only in a transit-friendly Bay Area. Policy implication from this dissertation is discussed. / text