UMD Theses and Dissertations

Permanent URI for this collectionhttp://hdl.handle.net/1903/3

New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.

More information is available at Theses and Dissertations at University of Maryland Libraries.

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    UNDERSTANDING AND MODELLING TIME USE, WELL BEING AND DYNAMICS IN ACTIVITY-TRAVEL BEHAVIOR: A CHOICE BASED APPROACH
    (2018) Dong, Han; Cirillo, Cinzia; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Understanding the determinants of activity and travel related choices is critical for policy-makers, planners and engineers who are in charge of the management and design of large scale transportation systems. These systems, and their externalities, are interwoven with human actions and communities’ evolution. Traditionally, individual decision-making and travel behaviour studies are based on random utility models (RUM) and discrete choice analysis. To extend the ability of modellers to represent and forecast complex travel behaviour, this dissertation expands existing models to accommodate the influence of variables other than the traditional socio-demographics or level of service variables. In this thesis, technology innovations, psychological factors, and perceptions of future uncertainty are integrated into the classical RUMs and their effects on activity-travel decision making are investigated. Technology innovations, such as telecommunication, online communities and entertainment, release individual’s time and space constraints. They also modify people’s activity and travel choices. An integrated discrete-continuous RUM is proposed to study individuals’ participation in leisure activities, which is an important component of activity scheduling analysis and tour/trip formation. Leisure alternatives considered include: computer/internet related activity, in-home activity, and out-of-home activity. Compared to previous discrete-continuous models, interdependence among activities and the related time usage is explored using a modelling structure that accommodate full correlation among decision variables of different types. Standard random utility models are extended by including attitudes and perceptions as latent variables; these constructs are expected to enhance the behavioural representation of the choice process. A simultaneous structural model is proposed to represent the mutual effects existing between psychological factors and activity choices. Biases due to endogeneity in psychological factors and activity choices are taken into consideration in the model. To further extend the behavioural realism of our model, this thesis proposes a new simultaneous equation model formulation that links psychological indicators to activity participation and time use decisions. Unlike previous studies, the proposed method allows the psychological factors to be correlated with time use decisions and serve as an attribute in time use choice model. A new iterative simulated maximization estimation method is also proposed to accommodate possible endogeneity bias in the model system. A simulation experiment shows that the estimation method produces consistent and unbiased estimation results. Moreover, a real case study is also implemented in the context of participation in leisure activities, linking emotions, activity involvement and time use. After exploring individual’s decisions on activity and time use choices, a dynamic discrete choice model framework is proposed to accommodate stochasticity in individual behaviour over time. Following previous studies, activity patterns are decomposed into tour and stop sequences. Accordingly, a tour choice model and a stop choice model are jointly formulated under a unified framework with a hierarchical structure where stop choices are assumed to be conditional on tour choices. The results indicate that individuals are sensitive to current and future changes in travel and activity characteristics and that a dynamic formulation better represents multi-day travel behaviour.
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    ANALYSIS OF ACTIVITY CHOICE: THE ROLE OF ACTIVITY ATTRIBUTES AND INDIVIDUAL SCHEDULES
    (2009) Akar, Gulsah; Clifton, Kelly J; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    Activity-based approaches have taken hold in transportation research over the last several decades. The foundation of the activity-based approach is to view travel as a result of our activity choices and scheduling decisions. Therefore, better understanding of activity choice, planning time horizons, and activity attributes will lead to more accurate demand forecasts. This dissertation extends the current activity choice modeling framework by incorporating the characteristics of the individuals' schedules, planning time horizons and focusing on the salient attributes of the activities. This study consists of three parts which are linked to one another by their conceptual and empirical findings. The first part identifies the determinants of the planning time horizons - defined as when people decide about performing their activities. Several household and individual characteristics, and activity attributes are tested for their association with planning times. The activity attributes which have significant impacts on the planning time horizons of the activities are used in the second part for generating new activity groups. The second part clusters activities based on their salient attributes, such as duration, frequency, number of involved people and flexibilities, rather than their functional types (work, leisure, household obligations, etc.) and creates activity groups such as "long, infrequent, personally committed activities", "quick, spatially fixed, temporally flexible activities" etc. The activity groups generated in this part inform the activity choice modeling structure developed in the third part. The main analytical techniques used in this research are the Principal Components Analysis (PCA) and discrete choice models. PCA is used to define the new activity groups. The analysis of the planning time horizons and activity choice are performed by mixed logit models. The model results reveal the significant relationships between socio-demographics, temporal characteristics, travel, and characteristics of the schedules on activity choice. The findings of these models could be integrated in the activity choice modules of the existing activity-travel simulation models by either applying the comprehensive model (which may face limitations due to the availability of data) or integrating the findings of the models in the decision rules.