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Www.company.com Student Travel: Evidence from 13 Diverse Metro Regions of the United States Guang Tian and Reid Ewing Department of City & Metropolitan.

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Presentation on theme: "Www.company.com Student Travel: Evidence from 13 Diverse Metro Regions of the United States Guang Tian and Reid Ewing Department of City & Metropolitan."— Presentation transcript:

1 www.company.com Student Travel: Evidence from 13 Diverse Metro Regions of the United States Guang Tian and Reid Ewing Department of City & Metropolitan Planning, University of Utah Guang Tian City and Metropolitan Planning University of Utah guang.tian@utah.edu Presented by:

2 www.company.com Department of City & Metropolitan Planning, University of Utah Introduction 2009 1969 13% 46% 48% 12% Less and less students walk and bike to school. Travel to school

3 www.company.com Department of City & Metropolitan Planning, University of Utah Why are there less and less students choosing walk or bike to school? http://c10.nrostatic.com/sites/default/files/uploaded/pic_related_030415_RVBA.jpg

4 www.company.com Department of City & Metropolitan Planning, University of Utah (Black et al., 2001; Bringolf-Isler et al., 2008; Emond and Handy, 2010; Ewing et al., 2004; Frank et al., 2007; Larsen et al., 2011; McDonald, 2007; Mitra and Buliung, 2012; Müller et al., 2008; Schlossberg et al., 2006; Stewart, 2011; Timperio et al., 2006; Yarlagadda and Srinivasan, 2008). https://i.imgur.com/kPs9B2q.jpg Distance is reported as a primary factor that impacts children’s walking or biking to school. Some built environments are associated with walking and biking to school. ().

5 www.company.com Department of City & Metropolitan Planning, University of Utah However, the relationship is not generally found (Ewing et al., 2004; Yarlagadda and Srinivasan, 2008; Wong et al., 2011). Both the positive and negative relationships between walking and biking to school and built environment are reported (Boarnet et al., 2005; Frank et al., 2007; Giles-Corti et al., 2011; Larsen et al., 2011; Marique et al., 2013; Mitra and Buliung, 2012; Panter et al., 2008; Schlossberg et al., 2006Larsen et al., 2011; Timperio et al., 2006). The evidence of how built environment impact student’s travel-to-school choice is not consistent.

6 www.company.com Research Question Department of City & Metropolitan Planning, University of Utah How do students travel to and from school? What is the relationship between built environment around schools and homes and student’s travel choices?

7 www.company.com Research Design Department of City & Metropolitan Planning, University of Utah Local characteristics -Density -Diversity -Design -Distance to transit -Destination accessibility Traveler characteristics -Household income -Household size -Vehicle ownership -Driver license -Gender Mode choice -Walk -Bike -Transit -school bus -Auto External factors -Weather -Social/culture norm -Safety -etc. Regional characteristics -Region Size -Compactness index -Gas price

8 www.company.com Methodology Department of City & Metropolitan Planning, University of Utah Household Travel Surveys Data Collection http://www.nanaimo.ca/assets/Departments/Engineering~Public~ Works/Transportation~Master~Plan/Complex%20Travel2.png

9 www.company.com Department of City & Metropolitan Planning, University of Utah Built environment: Other GIS layers Parcel level land use Population and employment Street network (buffers) Intersections Transit stops Travel time skims (TAZs)

10 www.company.com Department of City & Metropolitan Planning, University of Utah

11 www.company.com Department of City & Metropolitan Planning, University of Utah Analysis method multilevel binomial logistic regressions Boston … Houston … … Level 1: student Level 2: region

12 www.company.com Department of City & Metropolitan Planning, University of Utah Mode share of all K-12 school trips Results

13 www.company.com Department of City & Metropolitan Planning, University of Utah Walk coefficient standard error t-ratiop-value Constant -3.5890.276-12.993<0.001 Travel time -0.0330.002-20.546<0.001 Household income -0.0030.0003-7.784<0.001 Vehicles per capita -0.8220.076-10.787<0.001 Driver license -0.8410.080-10.495<0.001 female -0.1960.032-6.048<0.001 Transit stop density within 0.25 mile buffer 0.0010.00033.5570.001 Activity density within 0.5 mile buffer 0.0130.0028.094<0.001 Job-population balance within 1 mile buffer 0.3610.0744.876<0.001 Intersection density within 1 mile buffer 0.0040.000410.228<0.001 % of 4-way intersection within 1 mile buffer 0.0030.0013.3210.001 Employment can be reached within 30 mins by auto 0.0030.0013.0260.003 Employment can be reached within 30 mins by transit 0.0060.0014.104<0.001 Compactness of metro area 0.0180.0036.890<0.001 sample size: 5017 walk trips of 39,880 trips pseudo-R2: 0.88 ( = 1 - variance of fit model / null model)

14 www.company.com Department of City & Metropolitan Planning, University of Utah Bike coefficient standard error t-ratiop-value Constant-13.5153.267-4.1370.002 Travel time-0.0220.009-2.5590.011 Vehicles per capita-1.3900.315-4.413<0.001 Driver license-0.5010.181-2.7610.006 female-0.7720.130-5.941<0.001 Job-population balance within 1 mile buffer 1.0610.3882.7350.007 Intersection density within 1 mile buffer 0.0060.0014.015<0.001 Gas price of metro area3.1331.1242.7860.018 sample size: 628 bike trips of 39,880 trips pseudo-R2: 0.37 ( = 1 - variance of fit model / null model)

15 www.company.com Limitations Department of City & Metropolitan Planning, University of Utah o Sample of Regions (the more regions, the more powerful of the regression) o Missing variables (weather, SRTS program etc.) o Self-selection – attitudes and preferences o Street network assumptions

16 www.company.com Conclusions Department of City & Metropolitan Planning, University of Utah o Sociodemographic characteristics have strong influences on student travel choice. o Students travel differs from metro to metro.  Students from compact metro areas have higher probability of walking and biking to school.  There are statistically significant positive relationships between built environment (D variables) and students’ walking and biking choice. o Built environment matters.  With the increase of D variables, the probability of students’ walking and biking increase.  With the increase of gas price, the probability of students’ biking to school increase.

17 www.company.com Department of City & Metropolitan Planning, University of Utah Thank you ! Guang Tian University of Utah guang.tian@utah.edu


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