Description
Mapping the Travel Behavior Genome covers the latest research on the biological, motivational, cognitive, situational, and dispositional factors that drive activity-travel behavior. Organized into three sections, Retrospective and Prospective Survey of Travel Behavior Research, New Research Methods and Findings, and Future Research, the chapters of this book provide evidence of progress made in the most recent years in four dimensions of the travel behavior genome. These dimensions are Substantive Problems, Theoretical and Conceptual Frameworks, Behavioral Measurement, and Behavioral Analysis. Including the movement of goods as well as the movement of people, the book shows how traveler values, norms, attitudes, perceptions, emotions, feelings, and constraints lead to observed behavior; how to design efficient infrastructure and services to meet tomorrow's needs for accessibility and mobility; how to assess equity and distributional justice; and how to assess and implement policies for improving sustainability and quality of life.Mapping the Travel Behavior Genome examines the paradigm shift toward more dynamic, user-centric, demand-responsive transport services, including the "sharing economy," mobility as a service, automation, and robotics. This volume provides research directions to answer behavioral questions emerging from these upheavals.- Offers a wide variety of approaches from leading travel behavior researchers from around the world- Provides a complete map of the methods, skills, and knowledge needed to work in travel behavior- Describes the state of the art in travel behavior research, providing key directions for future research
Table of Contents
1. Introduction and the genome of travel behaviorPart I: Retrospective and Prospective Survey of Travel Behavior Research2. OUR IATBR: 45 years contributing to travel behavior research3. Travel demand models, the next generation: boldly going where no-one has gone before4. Travel behavior and psychology: life time achievement 1982-20185. Consumer choice modeling: the promises and the cautionsPart II: New Research Methods and Findings6. Environmental correlates of travel behavior from a destination attractiveness and activity timing perspectives7. The role of attitudes in on-demand mobility usage - an example from Shanghai8. Influence of pricing on mode choice decision integrated with latent variable: the case of Jakarta Greater Area 9. An empirical assessment of the impact of incorporating attitudinal variables on model transferability10. Panel approach: travel behavior and psycho-attitudinal factors evolution 11. Long-distance and intercity travel: who participates in global mobility? 12. To play but not for travel: utilitarian versus hedonic and non-cyclists in Cagliari, Italy 13. Influence of childhood experiences and present life circumstances on elderly wellbeing: a hybrid multiple ordered probit model with analytical estimation approach 14. Exploring the positive utility of travel and mode choice: subjective well-being and travel-based multitasking during the commute15. Travel, social networks and time use: modeling complex real-life behavior16. A flexible activity scheduling conflict resolution framework17. Explore daily activity-travel behavior of the elderly using multiyear survey data18. Modeling activity-travel behavior of non-workers grouped by their daily activity patterns19. Sequence analysis of place-travel fragmentation in California20. Choice modeling perspectives on the use of interpersonal social networks and social interactions in activity and travel behavior21. Impacts of built environment and travel behavior on high school students' life satisfaction and future life plans: a preference-based case study in depopulated areas of Japan22. A collective household model of driving cessation of older adults23. Who has more say on your daily time use? A quantitative intra-household time-use altruism analysis 24. Data-oriented sequential modeling of pedestrian behavior in urban spaces based on dynamic-activity domains25. Open source data–driven method to identify most influencing spatiotemporal factors. An example of station–based bike sharing 26. Modeling the interactions between mobility options in the surrounding of bikesharing stations 27. Virtual immersive reality based analysis of behavioural responses in connected and autonomous vehicle environment28. Estimating impact of autonomous driving on value of travel time savings for long-distance trips using revealed and stated preference methods29. Stated ownership and intended in-vehicle time use of privately-owned autonomous vehicles30. Assessment of fast charging station locations - an integrated model based approach 31. Innovative pricing policies for commuting: a field experimentPart III: IATBR2018 Research Workshops32. Workshop summary and research themesIntroduction and backgroundWorkshop on automation and self-drivingWorkshop on mobility as a serviceWorkshop on time use and travelWorkshop on data-driven learning and travelWorkshop on transport for healthy, happy, and holistic livingWorkshop on life-course and dynamicsWorkshop on big data and travelWorkshop on connected freight
