This study analyzes travel behaviour patterns of different age groups using urban railways in the Keihanshin metropolitan area, to examine the relationship between urban public transport and urban activities — particularly the impact on the area surrounding the rail stations. The analysis uses the Railway Station Database, which includes attributes of rail stations and their surroundings, and results of a person trip survey. Differences in rail usage patterns have been identified, related to commercial activities such as shopping and recreation. The results make it possible to put forward proposals for urban rail services that facilitate town development.
It is required to change transportation policy from an overemphasis on automobile traffic to support for sustainable transportation. Business, research, and education with regard to such a policy are all important. In this presentation, the direction of such a transportation policy will be described. Especially, I would like to introduce Dr. KitamuraÂ’s later-life activity to establish with us a private school, “SAISEI-JUKU”, for transport practitioners to promote sustainable community development.
Ryuichi Kitamura for 30 years developed conceptual models and tested hypotheses about activity participation, time allocation, and travel using implied and explicitly described conceptual frameworks that enable the analysis of change. In this presentation, I will first review a few of Ryuichi’s early ideas. Then, I will link these ideas with time geography and behavioral geography and conclude with examples of models that emerged directly from his pioneering efforts and are moving to practice.
It is known that traffic congestion is caused by demand concentration during peak time periods, and therefore considering departure time choice behaviour is important to mitigating congestion. This presentation introduces some studies showing how departure time choice behaviour affects congestion on roads.
In the mid-1990’s Ryuichi Kitamura engaged in a series of studies with his UC Davis colleagues and students addressing questions of how travelers choose routes and the effect of traffic information on those choices. A series of travel surveys and laboratory experiments were conducted seeking to better understand and model these processes. This paper reviews this research and discusses how it has been used in the intervening 10-15 years.
We have developed an integrated micro-simulation system of daily travel. This micro-simulation system is probably the first attempt in which all steps of the four-step procedure are performed by micro-simulation. This presentation introduces an outline and an extension of the PCATS-DEBNetS.
RyuichiÂ’s career spanned arguably the most pervasive shift in the trajectory of human activity organisation since the industrial revolution. Â He was a consummate observer of what this may mean for transport and communication systems, and his reflections inspired countless research enquiries and methods, including the search for causes of that trajectory.
We are interested in travel behavior and the tools of behavior analysis. This presentation will focus especially on the cognitive process of departure time choice behavior and the property of discrete choice models which are used frequently in behavior analysis.
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From the late 1970s onward, Ryuichi played an instrumental role in driving trip chaining analyses in Asia toward the activity-based modeling approach. First, the root of his trip chaining research will be introduced, reviewing Markov chain models developed by senior professors of Kyoto University. It will be emphasized that his trip chaining studies laid the foundations of activity-based approaches in Japan in the following decades. Second, we will discuss how he influenced that research, focusing on key subjects such as activity & travel linkages, time-space paths, causal relationships, and panel data surveys.
Traffic breakdown phenomena at freeway bottlenecks are considered as types of stochastic phenomena. This study develops a platoon-based traffic flow model which describes traffic breakdown stochastically. This presentation also introduces Kitamura senseiÂ’s teachings, good memories and my colleaguesÂ’ research topics on public space and worldviews.
This presentation explores the potential of using multi-day GPS data on travel to develop a new paradigm for tour-choice models. The paradigm is based on prior research on freight tours, that uses a tour-generating paradigm, instead of a choice of tour patterns, and uses observed probabilities from the multi-day GPS data.
Residential energy use is affected by many interrelated factors, including household characteristics, lifestyles and living environments. To understand household energy use behavior, potential causal relationships are studied using data from a residential energy survey.
Ryuichi Kitamura’s interest in all aspects of travel-related behavior with important implications for policy analysis, and an enthusiasm for mentoring and working with a wide range of colleagues to pursue that interest, leaves a multi-faceted and complex legacy that will long endure. One such facet is in the area of vehicle choice modeling to support California¹s ongoing leadership role in creating new public policies to improve the environment through reductions in emissions and energy consumption. We discuss a recent manifestation of the UC Davis branch of the Kitamura legacy.
The first three speakers in this session represent the current students in Kitamura’s lab. They will speak on why they chose to work with Ryuichi; how he influenced their work; their current research related to him; and a brief overview of research being conducted by other students in the lab. Takamasa Iryo is a current student of Prof. Yasuo Asakura, a close colleague of Ryuichi’s, and Nanako Tenjin is a UC Davis student who was mentored by Ryuichi in Japan. The moderator, Prof. Cynthia Chen, is Ryuichi’s last PhD student from his years at UC Davis.
Both travel behavior research and the evaluation of transport policy are indispensable topics in transportation research. In this presentation, we will describe how the psychological and behavioral sciences are essential to these two topics as advanced by Ryuichi Kitamura, and present our joint work on them.
This study takes a multi-level analysis approach to examine the variation in departure time choice behavior by activity type, using six-week travel survey data.
This presentation focuses on four themes – hypothetical bias in stated choice studies, relevancy vs. complexity in choice experiments, the role of heuristics to accommodate heterogeneity in the way individuals process attributes, and the growing importance of recognising group decision making and modelling the endogeneity of interacting agents.
Ryuichi Kitamura was a pioneer in both the analysis and modelling of travel behaviour within the activity-based paradigm; indeed he was a major contributor to the articulation of this paradigm. Among his many contributions, ones that stand out for me include his insistence on a truly behavioural approach to representing/modelling activity/travel, his early adoption of microsimulation as the natural framework for modelling complex human behaviour, and his interest in the dynamics of travel behaviour. In this brief talk I will attempt to sketch a few of RyuichiÂ’s contributions in these areas and how they flow through the current state of the art in activity-based travel modelling.
Having learned much about the methodology of activity analysis from Ryuichi Kitamura, I have since been engaged in an ongoing research partnership to ground research into consumers and transportation energy in both activity analysis and a theoretical approach that places people within on-going projects of lifestyle construction. Our primary theoretical influence, Anthony Giddens, states, “…self-identity, as a coherent phenomenon, presumes a narrativeÂ….” Thus, we have arrived at a point where we explicitly frame research within, and conduct research on, the stories people tell. IÂ’ll talk about how we listen to and tell peoplesÂ’ stories in ways that inform transportation energy and travel behavior researchers, providers, and planners. And, IÂ’ll tell a few stories.
Ryuichi Kitamura was a pioneer in both the analysis and modelling of travel behaviour within the activity-based paradigm; indeed he was a major contributor to the articulation of this paradigm. Among his many contributions, ones that stand out for me include his insistence on a truly behavioural approach to representing/modelling activity/travel, his early adoption of microsimulation as the natural framework for modelling complex human behaviour, and his interest in the dynamics of travel behaviour. In this brief talk I will attempt to sketch a few of RyuichiÂ’s contributions in these areas and how they flow through the current state of the art in activity-based travel modelling.
A number of methodologies for treating residential self-selection appear in the literature, but accounting for taste heterogeneity is one that has received little attention to date. Drawing on several themes from Ryuichi’s work, I will describe a prospective study that will compare several different ways of accounting for taste heterogeneity in this context, including interaction variables, deterministic segmentation, and latent class models.
Lessons from behavioral economics have made inroads in transportation, in particular in the areas of survey design, prospect theory, and attitudinal variables. Further infusion could lead to significant benefits in terms of increased ability to both predict and influence behavior. This talk will review what behavioral science has to say about experience, context and social influences, and the use of information and feedback to promote sustainable behavior.
Children’s travel behavior in the Osaka Metropolitan area is discussed in relation to the built environment and community connections of their neighborhoods. Other topics introduced will be defining the built environment, household lifecycle, and cohorts.
A stochastic traffic system is modeled within a Bayesian viewpoint. The model bridges the gap between traffic flow and stochastic travel behavior. The probability distribution of traffic flow given travel behavior rules is studied.
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