This study presents an analytical model of the interaction between urban form and the demand for transit travel, in which residential location, transit demand, and the spatial dispersion of non-work activities are endogenously determined. In this model, travel demand is considered a derived demand brought about by the necessity to engage in out-ofhome activities whose geographical extent is affected by urban form. In a departure from the urban monocentric model, residential location is defined as a job-residence pair in an urban area in which jobs, residences, and non-work activities are dispersed. Transit demand is then determined by residential location, work trips, non-work trip chains, and goods consumption. Theoretically derived hypotheses are empirically tested using a dataset that integrates travel and land-use data. There is evidence of a significant influence of land-use patterns on transit patronage. In turn, transit demand affects consumption and non-work travel. Although much reliance has been placed on population density as a determinant of transit demand, it is found here that population density does not have a large impact on transit demand and, moreover, that the effect decreases when residential location is endogenous. To increase transit use, urban planners have advocated a mix of residential and commercial uses in proximity to transit stations. In this study, it is found that the importance of transit-station proximity is weakened by idiosyncratic preferences for residential location. In addition, when population density and residential location are jointly endogenous, the elasticity of transit demand with respect to walking distance to a transit station decreases by about 33 percent over the case in which these variables are treated an exogenous. The research reported here is the first empirical work that explicitly relates residential location to trip chaining in a context in which individuals jointly decide residential location and the trip chain. If is found that households living farther from work use less transit and that trip-chaining behavior explains this finding. Households living far from work engage in complex trip chains and have, on average, a more dispersed activity space, which requires reliance on more flexible modes of transportation. Therefore, reducing the spatial allocation of non-work activities and improving transit accessibility at and around subcenters would increase transit demand. Similar effects can be obtained by increasing the presence of retail locations in proximity to transit-oriented households. Although focused on transit demand, the framework can be easily generalized to study other forms of travel.

The classic time geography concept (space-time path) provides a powerful framework to study travel survey data which is an important source for travel behavior studies. Based on the space-time concept, this research will present a visualizing approach to analyze travel survey data. By inputting the data into GIS software such as TransCAD and ArcGIS and editing the needed information, this study will explain how to create 3D images of travel paths for showing the variation of trip distribution in relation to different social-economic factors deemed as the driving forces of such patterns. Also, this report will address the technical challenges involved in this kind of study and will discuss directions of future research. / text

The projected growth of persons ages 65 and older in the U.S. over the next few decades will usher in an era of unprecedented numbers of seniors licensed to drive. For some members of this group, there will come a time where driving will have to cease due to a variety of factors. At that juncture in their lives, these seniors may have to consider transportation alternatives other than the personally operated vehicle. The objective of this study is to evaluate potential changes in transit market share arising from travel behavior changes of seniors who lose their driving privileges. This includes determining seniors interest in, ability to, and subsequent use of public transit. First, a literature review of developments that have impacted senior travel behavior is presented. Developments such as the changing demographics of seniors, senior socio-economic status, the process of driving retirement, and factors influencing transit use by seniors are presented. Estimates of the numbers of licensed and former drivers are derived for the year 2030 using several methodological approaches. Trip rates are applied to the predicted non-driving population to derive estimates of the potential demand for transit and subsequent market share. Discussion of the estimated market share results also incorporates a descriptive overview of senior travel behavior as derived from analyses of publicly available datasets followed by focus group results illustrating the experiences of seniors and their transportation choices.Recommendations range from transit agencies engaging in direct "generational" marketing to seniors in order to understand their transportation needs as well as perceptions about transit, promoting the use of transit, and demonstrating the viability of transit for specific trip purposes and partner with rideshare providers. Despite the predicted increase in transit market shares attributable to the senior population, transit providers have extensive work to do to change the perceptions of transit service provision and subsequently encourage the use of such services by senior populations in forthcoming generations if transit is to become a viable transportation alternative for those seniors ceasing to drive.

Traffic congestion has been imposing a tremendous burden on society as a whole. For decades, the most widely applied solution has been building more roads to better accommodate traffic demand, which turns out to be of limited effect. Active Traffic and Demand Management (ATDM) is getting more attention recently and is considered here, as it leverages market-ready technologies and innovative operational approaches to manage traffic congestion within the existing infrastructure. The key to a successful Active Traffic and Demand Management strategy is to effectively induce travelers' behavior to change. In spite of the increased attention and application throughout the U.S. or even the world, most ATDM strategies were implemented on-site through small-scale pilot studies. A systematic framework for analysis and evaluation of such a system in order to effectively track the changes in travelers' behavior and the benefit brought about by such changes has not been established; nor has the effect of its strategies been quantitatively evaluated. In order to effectively evaluate the system benefit and to analyze the behavior changes quantitatively, a systematic framework capable of supporting both macroscopic and microscopic analysis should be established. Such system should be carefully calibrated to reflect the traffic condition in reality, as only after the calibration can the baseline model be used as the foundation for other scenarios in which alternative design or management strategies are incorporated, so that the behavior changes and system benefit can be computed accurately by comparing the alternative scenarios with the baseline scenario. Any effective traffic management strategy would be impossible if the traveler route choice behavior in the urban traffic network has not been fully understood. Theoretical research assumes all users are homogeneous in their route choice decision and will always pick the route with the shortest travel cost, which is not necessarily the case in reality. Researchers in Minnesota found that only 34% of drivers strictly traveled on the shortest path. Drivers' decision is made usually based on several dimensions, and a full understanding of the travel route choice behavior in the urban traffic network is essential. The existence of most current Advanced Traveler Information Systems (ATIS) offer the capability to provide pre-trip and/or en route real time information, allowing travelers to quickly assess and react to unfolding traffic conditions. The basic design concept is to present generic information to drivers, leaving drivers to react to the information their own way. This "passive" way of managing traffic by providing generic traffic information has difficulty in predicting outcome and may even incur adverse effect, such as overreaction (aka herding effects). Furthermore, other questions remain on how to utilize the real-time information better and guide the traffic flow more effectively towards a better solution, and most current research fails to take the traveler's external cost into consideration. Motivated by those concerns, in this research, a behaviorally induced system optimal model is presented, aimed at further improving the system-level traffic condition towards System Optimal through incremental routing, as well as establishing the analysis methodology and evaluation framework to calibrate quantitatively the behavior change and the system benefits. In this process, the traffic models involved are carefully calibrated, first using a two-stage calibration model which is capable of matching not only the traffic counts, but also the time dependent speed profiles of the calibrated links. To the best of our knowledge, this research is the first with a methodology to incorporate the use of field observed data to estimate the Origin-Destination (OD) matrices departure profile. Also proposed in this dissertation is a Constrained K Shortest Paths algorithm (CKSP) that addresses route overlap and travel time deviation issues. This proposed algorithm can generate K Shortest Paths between two given nodes and provide sound route options to the drivers in order to assist their route choice decision process. Thirdly, a behaviorally induced system optimal model includes the development of a marginal cost calculation algorithm, a time-dependent shortest path search algorithm, and schedule delay as well as optimal path finding models, is present to improve the traffic flow from an initial traffic condition which could be User Equilibrium (UE) or any other non-UE or non-System-Optimal (SO) condition towards System Optimal. Case studies are conducted for each individual research and show a rather promising result. The goal of establishing this framework is to better capture and evaluate the effects of behaviorally induced system optimal traffic management strategies on the overall system performance. To realize this goal, the three research models are integrated in order to constitute a comprehensive platform that is not only capable of effectively guiding the traffic flow improvement towards System Optimal, but also capable of accurately evaluating the system benefit from the macroscopic perspective and quantitatively analyzing the behavior changes microscopically. The comprehensive case study on the traffic network in Tucson, Arizona, has been conducted using DynusT (Dynamic Urban Simulation for Transportation) Dynamic Traffic Assignment (DTA) simulation software; the outcome of this study shows that our proposed modeling framework is promising for improving network traffic condition towards System Optimal, resulting in a vast amount of economic saving.

Uppsatsens syfte är att undersöka hur unga män respektive kvinnor boende i Sverige resonerar kring sitt beteende vid resandet till ett annat land och om resandet i sig bidrar till identitetsskapande. Vi ämnar att undersöka om individer bedömer det mer legitimt att utföra handlingar som i hemlandet anses vara mindre accepterat och om det finns någon skillnad mellan dessa föreställningar beroende på individens könstillhörighet. Uppsatsen baseras på ett kvalitativt tillvägagångssätt då tio intervjuer har genomförts med fem män respektive fem kvinnor i åldersspannet 20-30 år. Intervjuerna har kodats och därefter analyserats med hjälp av de valda teorierna vilka bland andra är identitet, genus och ojämlikhet. Vid analysprocessen har även tidigare forskning tillämpats för att stärka de resultat som framkommit under studieprocessen. Studien visar att en utlandssemester är av betydelse för en individs liv och resan bidrar till att individen utvecklar sin identitet. Att resa ses som viktigt för individen för att berätta och stärka vem den är och vill vara. Vidare visar studien på att det inte finns skillnader könen emellan då det gäller beteendeförändringar utan det sker en förändring oavsett kön. Utifrån studiens resultat har vi identifierat att individer som förflyttar sig från sin vardagliga zon till en utlandssemester intar en specifik roll som vi väljer att kalla turistidentitet. Turistidentitet innebär att individen har lämnat sitt vanliga jag hemma för att inta en ny roll där gränserna anses kunna förflyttas. Begreppet turistidentitet blir ett verktyg för att få en förståelse för en individs beteende och att det finns en skillnad individer emellan. I och med att det finns skillnader individer emellan ser turistidentiteten olika ut beroende på vem individen är. / The purpose of this paper is to examine how young men and women living in Sweden discuss about their behavior during travel to another country, and if traveling in itself contributes to identity creation. We intend to examine whether individuals consider it more legitimate to perform acts that in their home country is considered to be less accepted, and if there are any difference between these performances depending on the individual's gender. The study are based on a qualitative approach and interviews were conducted with five men and five women in the age 20-30 years. The interviews were coded and then analyzed by means of the chosen theories which among others are, identity, gender and inequality. In the analyzed process previous research has also been applied to strengthen the results that emerged during the process. The study shows that overseas holiday is relevant to an individual's life and the journey helps individuals to develop their identity. Traveling is seen as important for individuals to tell and strengthen who they are and want to be. The study shows that no differences exist between the sexes when it comes to behavior changes, there is a change regardless of gender. Based on the study results, we have identified that individuals who move from their everyday zone to a holiday abroad take a specific role, which we choose to call the tourist identity. The conception of the Tourist Identity is that the individual has left one´s usual self at home to take on a new role where the boundaries are considered to be moved. The concept of tourist identity becomes a tool to gain an understanding of an individual's behavior and that there is a difference between individuals. Depending on who the individual is the tourist identity differs.

Thesis (M.S.)--University of California, Davis, 2006. / Text document in PDF format. Title from PDF title page (viewed on September 1, 2009). "Received by ITS-Davis: September 2006"--Publication detail webpage. Includes bibliographical references (p. 75-78).

In this master thesis, multiagent simulation was implemented with MATSim to study the change would take place on travel behaviors in Stockholm County when all residents travel in a sustainable way under a predefined emission limit. In this multiagent simulation, individual person was simulated as agent with attributes, daily travel plans and behaviors. The attributes contained home location, workplace locations, and some socioeconomic attributes, which were assigned according to the demographic data and travelling statistics data collected. Two trips, morning commuting from home to workplace and evening commuting from workplace to home, were simulated while the daily travel plans included travelling by car, public transit, bike and working at home. Each day, the person was set to select a travel plan based on socioeconomic attributes, his current greenhouse gas emission and a monthly emission limit. The selected plan was then executed and his emission was updated. In the model, a working population of 771614 people in Stockholm County was used and one month period with 21 working days was simulated. Totally four monthly emission limits were tested: 30kg, 37kg, 50kg, and infinity representing the current scenario. The research shows that multiagent simulation is effective in simulating individual travel behaviors. The results suggest that under current scenario car is the most frequently selected travel mode accounting for 32%, followed by public transit 31%. There are about 12% of people working at home and 25% travelling by bike. Nearly 1 percent fails to select a plan because of the plan selection setting. When emission limit is set, the percentage of people changing travel behaviors is 21.2%, 25.8% and 29.9% under the emission limit 50kg, 37kg and 30kg respectively. Most of them would abort from car and public transit to bike, public transit or even failing to keep their emission under the limit. The percentage of people changing plan to bike is 9.4%, 11.8%, 13.4% under the three limits 50kg, 37kg and 30kg respectively while the percentage of people changing plan to public transit or failure is 10.2%, 12.5% and 15.2%. The result also shows that when 37kg limit is set, the people having problems with keeping their emission under the limit are mainly distributed at three regions: Stockholm City, some cities in southwest and northeast of Stockholm County, where there would also be more demand for public transit service. The people changing plans to bike are mainly  distributed  in  Stockholm  City  area,  where  sustainable  travel  behavior  should  be promoted

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Increasing vehicular travel and environmental issues are trends increasing the pressure on urban transport systems. The new concept Mobility as a Service (MaaS) is one approach to tackle these challenges. The aim of MaaS is to reduce the need of the private car and increase the use of shared resources by providing one single application that integrates all transport modes, payment, and services. Several ongoing societal trends such as urbanization, technologic development, and sharing economy are examples of reasons for the emergence of MaaS. Young people are often leading the development and are early adopters of new technologies. The mobility demands of young people today and in the future will therefore play an important role in the implementations of MaaS. This qualitative study uses focus groups to explore mobility demands today and in the envisioned future of young people (aged 15-23) living in Stockholm. Our understanding of travel behaviour and mobility demands among young people is limited, and this study also aims to get deeper understanding of the underlying values and attitudes towards mobility that influence those demands and behaviours. This study aims to answer how young people’s mobility demands look like and if they correspond to the visions of MaaS as stated by developers and experts of the concept. Findings indicate that mobility demands and behaviour are strongly influenced by parents, and underlying values such as ‘Freedom’ and ‘Comfortable life’ affect mobility more than factors such as availability and travel time. There is little need for increased accessibility to transport today and in the envisioned future. Findings also indicate a relatively widespread environmental awareness, but an unwillingness to convert awareness to change of behaviour. The demands of young people correspond to some extent with the visions of MaaS, and the probability of young people to adopt MaaS and to choose environmentally friendly journey is high if demands for convenience and comfort are fulfilled.

With the recent upsurge in mental health concerns and ongoing isolation regulations brought about by the COVID-19 pandemic, it is important to understand how an individual's daily travel behavior can affect their mental health. Before finding any correlations to mental health, researchers must first have individual travel behavior information: an accurate number of activities and locations of those activities. One way to obtain daily travel behavior information is through the interpretation of cellular Global Positioning System (GPS) data. Previous methods that interpret GPS data into travel behavior information have limitations. Specifically, rule-based algorithms are structured around subjective rule-based tests, clustering algorithms include only spatial parameters that are chosen sequentially or require further exploration, and imputation algorithms are sensitive to provided context (input parameters) and/or require lots of training data to validate the results of the algorithm. Due to the lack of provided training data that would be required for an imputation algorithm, this thesis uses a previously adopted clustering method. The objective of this thesis is to determine which spatial, entropy, and time parameters cause the clustering algorithm to give the most accurate travel behavior results. This optimal set of parameters was determined using a comparison of two non-linear optimization methods: simulated annealing and a limited-memory Broyden-Fletcher-Goldfarb-Shanno Bound (L-BFGS-B) optimizer. Ultimately, simulated annealing optimization found the best set of clustering parameters leading to 91% clustering algorithm accuracy whereas L-BFGS-B optimization found parameters that were only able to produce a maximum of 79% accuracy. Using the most optimal set of parameters in the clustering algorithm, an entire set of GPS data can be interpreted to determine an individual's daily travel behavior. This resulting individual travel behavior sets the groundwork to answer the question of how individual travel behavior can affect mental health.