Browsing by Subject "Travel survey"
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Item School Choice and Children's School Commuting(University of Minnesota Center for Transportation Studies, 2009-01) Wilson, Elizabeth; Marshall, Julian; Krizek, Kevin; Wilson, RyanSome school districts allow parents to choose which school their child attends, a policy known as school choice. We study the impact of school choice on school transportation behavior. To do this, we examine the extent to which children’s commute mode and parental attitudes toward school selection and school travel differ by magnet versus neighborhood schools and by race. We conducted a survey of elementary-school parents to assess how children travel to school and identify underlying parental attitudes. Compared to national data, our sample of K-6 students had fewer children walking and traveling by personal vehicle, and more riding the school bus. Magnet (i.e. school choice) schools, which draw from broader geographic regions than neighborhood schools, have fewer students walking or biking to school and more students riding the bus rather than using a private automobile. Transportation attitudes and actions differ by school type and race. For example, compared to white parents, non- white parents are more concerned about availability and safety of school buses, and also are more likely to use school buses. This paper highlights the importance of school district policy on school transportation, mode choice, and the ability of students to walk or bike to school.Item SmarTrAC: A Smartphone Solution for Context-Aware Travel and Activity Capturing(2015-02) Fan, Yingling; Wolfson, Julian; Adomavicius, Gediminas; Vardhan Das, Kirti; Khandelwal, Yash; Kang, JieThe use of mobile phones in collecting travel behavior data has rapidly increased, especially after GPS tracking technology became widely available in commercial smartphones. Existing smartphone-based tools in the field have generally focused on capturing the “when”, “where”, and “how” of travel, i.e., using the smartphone’s automatic sensing functionality to detect travel mode and to collect position and route data. Although locations and modes of transportation derived from sensing data represent important travel behavior information, travel behavior has many other important dimensions—such as trip purpose, travel experience, and travel companionship (i.e., the “why”, “how”, and “who” of travel)—all of which are critical for understanding people’s travel choices. Some of these dimensions may be inferable from pure sensory data, but reliable inference will generally require long-term use data from a very large number of subjects. Other dimensions are simply inaccessible to passive sensing tools. In contrast, traditional travel diary methods and some first-generation smartphone-based travel survey tools enable the collection of multi-dimensional data through high-intensity sampling and qualitative survey techniques. However, these methods are often burdensome to study subjects and impractical for use in a diverse, mobile, and increasingly time-stressed population.