We describe the design and evaluation of a system named Quantified Traveler (QT). QT is a Computational Travel Feedback System. Travel Feedback is an established programmatic method whereby travelers record travel in diaries, and meet with a counselor who guides her to alternate mode or trip decisions that are more sustainable or otherwise beneficial to society, while still meeting the subject's mobility needs. QT is a computation surrogate for the counselor. Since counselor costs can limit the size of travel feedback programs, a system such as QT at the low costs of cloud computing, could dramatically increase scale, and thereby sustainable travel. QT uses an app on the phone to collect travel data, a server in the cloud to process it into travel diaries and then a personalized carbon, exercise, time, and cost footprint. The subject is able to see all of this information on the web. We evaluate with 135 subjects to learn if subjects let us use their personal phones and data-plans to build travel diaries, whether they actually use the website to look at their travel information, whether the design creates pro-environmental shifts in psychological variables measured by entry and exit surveys, and finally whether the revealed travel behavior records reduced driving. Before and after statistical analysis and the results from a structural equation model suggest that the results are a qualified success.3
We develop a general framework that extends choice models by including an explicit representation of the process and context of decision making. Process refers to the steps involved in decision making. Context refers to factors affecting the process, focusing in this paper on social networks. The extended choice framework includes more behavioral richness through the explicit representation of the planning process preceding an action and its dynamics and the effects of context (family, friends, and market) on the process leading to a choice, as well as the inclusion of new types of subjective data in choice models. We discuss the key issues involved in applying the extended framework, focusing on richer data requirements, theories, and models, and present three partial demonstrations of the proposed framework. Future research challenges include the development of more comprehensive empirical tests of the extended modeling framework.
We present empirical and theoretical analyses to investigate the relationship between happiness (or subjective well-being) and activity participation and develop a framework for using well-being data to enhance activity-based travel demand models. The overriding hypothesis is that activities are planned and undertaken to satisfy needs so as to maintain or enhance subjective well-being. The empirical analysis consists of the development of a structural equations exploratory model of activity participation and happiness using data from a cross-sectional survey of a sample of commuters. The model reveals significant correlations between happiness and behavior for different types of activities: higher propensity of activity participation is associated with greater activity happiness and greater satisfaction with travel to the activity. The theoretical analysis consists of the development of a modeling framework and measures for the incorporation of well-being within activity-based travel demand models. The motivation is that activity pattern models have been specified in ad-hoc ways in practice as a function of mobility, lifestyle, and accessibility variables. We postulate that well-being is the ultimate goal of activity patterns which are driven by needs and propose two extensions of activity pattern models. The first extension consists of the use of well-being measures as indicators of the utility of activity patterns (in addition to the usual choice indicators) within a random utility modeling framework. The second extension models conceptually the behavioral process of activity generation based on needs satisfaction. We present an example of an operational activity pattern model and propose well-being measures for enhancing it.
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