The activity-based approach to the study of travel behavior implies a shift in focus from discrete trips to activities. A fundamental tenet of this approach is that individuals, when making their own activity-travel decisions, tend to interact with other members within a household. However, most activity-based research to date has been conducted at the individual level, but not at the household level. It is now well recognized that incorporating intra-household interactions is crucial to the development of improved activity-based models, which allow for more accurate travel demand forecasts and policy evaluations. In this context, the studies described in this dissertation have been conducted to explore several critical issues that have remained largely neglected in past studies. One such issue is the identification of joint participation in activity and travel episodes, due to the fact that most activity-travel surveys have failed to collect information on involved persons. In this dissertation, an integrated spatio-temporal GIS toolkit is initially developed to automatically identify and visualize (3D) joint activity/travel episodes. Such identification makes it possible to uniquely and directly incorporate intra-household interactions into studies of activity/travel behavior. The research described in this dissertation utilizes the 2003 CHASE (Computerized Household Activity Scheduling Elicitor) survey collected in the Greater Toronto Area. Several aspects of activity/travel behavior are investigated.. First, quantitative models are developed and estimated for investigating household activity time use patterns while capturing intra-household interactions. Second, the dynamics of household time use patterns are explored through descriptive analysis and structural equations models. Finally, the household activity decision-making process is further delved into with a focus on the planning priority of joint activities. Overall, the research presented in this dissertation makes important contributions to activity-based time use and travel behavior research: (1) technically, the developed GIS toolkit is helpful to reduce costs of processing large activity-travel datasets; and (2) theoretically, the empirical results presented will form the basis toward the development and implementation of an improved activity-based model. / Thesis / Doctor of Philosophy (PhD)

Activity-based travel demand model systems are increasingly being deployed to microsimulate daily activity-travel patterns of individuals. However, a critical dimension that is often missed in these models is that of vehicle type choice. The current dissertation addresses this issue head-on and contributes to the field of transportation planning in three major ways. First, this research develops a comprehensive vehicle micro-simulation framework that incorporates state-of-the-art household vehicle type choice, usage, and evolution models. The novelty of the framework developed is that it accommodates all the dimensions characterizing vehicle fleet/usage decisions, as well as accommodates all dimensions of vehicle transactions (i.e., fleet evolution) over time. The models estimated are multiple discrete-continuous models (vehicle type being the discrete component and vehicle mileage being the continuous component) and spatial discrete choice models that explicitly accommodate for multiple vehicle ownership and spatial interactions among households. More importantly, the vehicle fleet simulator developed in this study can be easily integrated within an activity-based microsimulation framework. Second, the vehicle fleet evolution and composition models developed in this dissertation are used to predict the vehicle fleet characteristics, annual mileage, and the associated fuel consumption and green-house gas (GHG) emissions for future years as a function of the built environment, demographics, fuel and related technology, and policy scenarios. This exercise contributes in substantial ways to the identification of promising strategies to increase the penetration of alternative-fuel vehicles and fuel-efficient vehicles, reduce energy consumption, and reduce greenhouse gas emissions. Lastly, this research captures several complex interactions between vehicle ownership, location, and activity-travel decisions of individuals by estimating 1) a joint tour-based model of tour complexity, passenger accompaniment, vehicle type choice, and tour length, and 2) an integrated model of residential location, work location, vehicle ownership, and commute tour characteristics. The methodology used for estimating these models allows the specification and estimation of multi-dimensional choice model systems covering a wide spectrum of dependent variable types (including multinomial, ordinal, count, and continuous) and may be viewed as a major advance with the potential to lead to redefine the way activity-based travel model systems are structured and implemented. / text

Recent developments in microsimulation modeling of activity and travel demand have called for the explicit recognition of time-space constraints under which individuals perform their activity and travel patterns. The estimation of time-space prism vertex locations, i.e., the perceived time constraints, is an important development in this context. Stochastic frontier modeling methodology offers a suitable framework for modeling and identifying the expected vertex locations of time space prisms within which people execute activity-travel patterns. In this work, stochastic frontier models of time space prism vertex locations are estimated for samples drawn from a household travel survey conducted in 2001 in the city of Thane on the west coast of India and National Household Travel Survey 2001, United States. This offers an opportunity to study time constraints governing activity travel patterns of individuals in a developing as well as developed country context. The work also includes comparisons between males and females, workers and non-workers, and developed and developing country contexts to better understand how socio-economic and socio-cultural norms and characteristics affect time space prism constraints. It is found that time space prism constraints in developing country data set can be modeled using the stochastic frontier modeling methodology. It is also found that significant differences exist between workers and non-workers and between males and females,possibly due to the more traditional gender and working status roles in the Indian context. Finally, both differences and similarities were noticed when comparisons were made between results obtained from the data set of India and United States. Many of these differences can be explained by the presence of other constraints including institutional, household, income, and transportation accessibility constraints that are generally significantly greater in the developing country context.

The overall goal of the dissertation is to contribute to the growing literature on the activity-based framework by focusing on the modeling of choices that are influenced by land-use and travel environment attributes. An accurate characterization of activity-travel patterns requires explicit consideration of the land-use and travel environment (referred to as travel environment from here on). There are two important categories of travel environment influences: direct (or causal) and indirect (or self-selection) effects. The direct effect of travel environment refers to how travel environment attributes causally influence travel choices. This direct effect may be captured by including travel environment variables as exogenous variables in travel models. Of course, determining if a travel environment variable has a direct effect on an activity/travel choice of interest is anything but straightforward. This is because of a potential indirect effect of the influence of the travel environment, which is not related to a causal effect. That is, the very travel environment attributes experienced by a decision maker (individual or household) is a function of a suite of a priori travel related choices made by the decision maker. The specific emphasis of the current dissertation is on moving away from considering travel environment choices as purely exogenous determinants of activity-travel models, and instead explicitly modeling travel environment decisions jointly along with activity-travel decisions in an integrated framework. Towards this end, the current dissertation formulates econometric models to analyze multidimensional choices. The multidimensional choice situations examined (and the corresponding model developed) in the research effort include: (1) reason for residential relocation and associated duration of stay (joint multinomial logit model and a grouped logit model), (2) household residential location and daily vehicle miles travelled (Copula based joint binary logit and log-linear regression model), (3) household residential location, vehicle type and usage choices (copula based Generalized Extreme Value and log-linear regression model) and (4) activity type, travel mode, time period of day, activity duration and activity location (joint multiple discrete continuous extreme value (MDCEV) model and multinomial logit model (MNL) with sampling of alternatives). The models developed in the current dissertation are estimated using actual field data from Zurich and San Francisco. A variety of policy exercises are conducted to illustrate the advantages of the econometric models developed. The results from these exercises clearly underline the importance of incorporating the direct and indirect effects of travel environment on these choice scenarios. / text

abstract: The development of microsimulation approaches to urban systems modeling has occurred largely in three parallel streams of research, namely, land use, travel demand and traffic assignment. However, there are important dependencies and inter-relationships between the model systems which need to be accounted to accurately and comprehensively model the urban system. Location choices affect household activity-travel behavior, household activity-travel behavior affects network level of service (performance), and network level of service, in turn, affects land use and activity-travel behavior. The development of conceptual designs and operational frameworks that represent such complex inter-relationships in a consistent fashion across behavioral units, geographical entities, and temporal scales has proven to be a formidable challenge. In this research, an integrated microsimulation modeling framework called SimTRAVEL (Simulator of Transport, Routes, Activities, Vehicles, Emissions, and Land) that integrates the component model systems in a behaviorally consistent fashion, is presented. The model system is designed such that the activity-travel behavior model and the dynamic traffic assignment model are able to communicate with one another along continuous time with a view to simulate emergent activity-travel patterns in response to dynamically changing network conditions. The dissertation describes the operational framework, presents the modeling methodologies, and offers an extensive discussion on the advantages that such a framework may provide for analyzing the impacts of severe network disruptions on activity-travel choices. A prototype of the model system is developed and implemented for a portion of the Greater Phoenix metropolitan area in Arizona to demonstrate the capabilities of the model system. / Dissertation/Thesis / Ph.D. Civil and Environmental Engineering 2012

Parc marin du Saguenay - Saint-Laurent, Groupe de recherche et d'éducation sur les mammifères marins, GREMM, excursions aux baleines, bélugas, Tadoussac, règlementation, ArcCatalog, ArcMap. / L'important volume des excursions de bateaux touristiques liées aux activités d'observation en mer des mammifères marins (AOM) dans le Parc marin Saguenay-Saint-Laurent (PMSSL) pourrait avoir un impact négatif sur la santé des baleines qui fréquentent cette région de l’estuaire du fleuve Saint-Laurent. Cette situation a poussé les gestionnaires du Parc à désirer un outil d'information et de gestion pour mieux suivre l’évolution des AOM. Le présent mémoire décrit la conception de cet outil en proposant un modèle de l'excursion et des activités d'observation qui sert à l’élaboration d’une base de données. En s’appuyant sur le concept de la trajectoire spatiotemporelle, utilisée pour l'étude du comportement de déplacement basé sur l'activité, et sur le concept de l'objet mobile, développé en géomatique, notre modèle de données permet de reproduire graphiquement les trajectoires des excursions et l'enchaînement des activités qui ont lieu au cours de celles-ci. Le modèle est orienté objet et implanté dans une Geodatabase, une base de données relationnelle exploitable par le système d'information géographique (SIG) ArcGIS. Les objets de la base de données sont créés à partir des données de trois années de suivi des AOM réalisés par le Groupe de recherche et d'éducation sur les mammifères marins (GREMM). Nous montrons que le SIG peut exploiter la base de données de façon à répondre correctement aux besoins en information exprimés par les gestionnaires et que la représentation informatique des excursions sous la forme de trajectoires spatiotemporelles ouvre de nouvelles avenues de recherche sur les patrons d’activités et le comportement de déplacement des bateaux. / The considerable volume of commercial boat trips associated with whale-watching activities (WWAs) in the Saguenay-Saint-Laurent National Marine Park (PMSSL) may have negative impacts on the health of the whales visiting the Saint-Lawrence River estuary. This situation has led park officials to seek an appropriate information management system in order to better monitor WWAs. This paper contributes to the design of such a tool by modeling excursion patterns of WWAs, resulting in a database. Based on the space-time path concept used for the study of activity-based travel behavior as well as the mobile-object geomatical concept, our data-model enables us to plot the trajectories of the excursions and the sequence of activities taking place during those excursions. The model is object-oriented and built into a Geodatabase (an ArcGis-processable relational database). The objects in the database are based on data collected by the Marine Mammal Research and Education Group (GREMM) during a three-year WWA monitoring program. Finally, this report demonstrates that geographic information systems can be effectively used to process the database in a way that serves the needs of park officials, and that the representation of excursion data in a GIS opens up new avenues for research on the space-time pattern of observation activities and the travel behavior of boats.

L'important volume des excursions de bateaux touristiques liées aux activités d'observation en mer des mammifères marins (AOM) dans le Parc marin Saguenay-Saint-Laurent (PMSSL) pourrait avoir un impact négatif sur la santé des baleines qui fréquentent cette région de l’estuaire du fleuve Saint-Laurent. Cette situation a poussé les gestionnaires du Parc à désirer un outil d'information et de gestion pour mieux suivre l’évolution des AOM. Le présent mémoire décrit la conception de cet outil en proposant un modèle de l'excursion et des activités d'observation qui sert à l’élaboration d’une base de données. En s’appuyant sur le concept de la trajectoire spatiotemporelle, utilisée pour l'étude du comportement de déplacement basé sur l'activité, et sur le concept de l'objet mobile, développé en géomatique, notre modèle de données permet de reproduire graphiquement les trajectoires des excursions et l'enchaînement des activités qui ont lieu au cours de celles-ci. Le modèle est orienté objet et implanté dans une Geodatabase, une base de données relationnelle exploitable par le système d'information géographique (SIG) ArcGIS. Les objets de la base de données sont créés à partir des données de trois années de suivi des AOM réalisés par le Groupe de recherche et d'éducation sur les mammifères marins (GREMM). Nous montrons que le SIG peut exploiter la base de données de façon à répondre correctement aux besoins en information exprimés par les gestionnaires et que la représentation informatique des excursions sous la forme de trajectoires spatiotemporelles ouvre de nouvelles avenues de recherche sur les patrons d’activités et le comportement de déplacement des bateaux. / The considerable volume of commercial boat trips associated with whale-watching activities (WWAs) in the Saguenay-Saint-Laurent National Marine Park (PMSSL) may have negative impacts on the health of the whales visiting the Saint-Lawrence River estuary. This situation has led park officials to seek an appropriate information management system in order to better monitor WWAs. This paper contributes to the design of such a tool by modeling excursion patterns of WWAs, resulting in a database. Based on the space-time path concept used for the study of activity-based travel behavior as well as the mobile-object geomatical concept, our data-model enables us to plot the trajectories of the excursions and the sequence of activities taking place during those excursions. The model is object-oriented and built into a Geodatabase (an ArcGis-processable relational database). The objects in the database are based on data collected by the Marine Mammal Research and Education Group (GREMM) during a three-year WWA monitoring program. Finally, this report demonstrates that geographic information systems can be effectively used to process the database in a way that serves the needs of park officials, and that the representation of excursion data in a GIS opens up new avenues for research on the space-time pattern of observation activities and the travel behavior of boats. / Parc marin du Saguenay - Saint-Laurent, Groupe de recherche et d'éducation sur les mammifères marins, GREMM, excursions aux baleines, bélugas, Tadoussac, règlementation, ArcCatalog, ArcMap.

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