Www.company.com Student Travel: Evidence from 13 Diverse Metro Regions of the United States Guang...

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 TianCity and Metropolitan Planning

University of [email protected]

Presented by:

www.company.comDepartment 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


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


(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.

().


• 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.

www.company.com

Research Question


• How do students travel to and from school?

• What is the relationship between built environment around schools and homes and student’s travel choices?

www.company.com

Research Design


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

www.company.com

Methodology


Household Travel Surveys

Data Collection

http://www.nanaimo.ca/assets/Departments/Engineering~Public~Works/Transportation~Master~Plan/Complex%20Travel2.png


Built environment: Other GIS layers

• Parcel level land use

• Population and employment

• Street network (buffers)

• Intersections

• Transit stops

• Travel time skims (TAZs)


Survey Date Surveyed Households

Surveyed Trips Surveyed School Trips

Atlanta, GA 2011 9,575 93,681 7,687Boston, MA 2011 7,826 86,915 3,616Denver, CO 2010 5,551 67,764 2,559Detroit, MI 2005 939 14,690 1,501Eugene, OR 2011 1,679 16,563 905Houston, TX 2008 5,276 59,552 4,687Indianapolis, IN 2009 3,929 37,473 1,922Kansas City, MO 2004 3,022 31,779 2,595Minneapolis-St. Paul, MN 2010 8,234 79,236 3,229Portland, OR 2011 4,513 47,551 3,230Sacramento, CA 2000 3,520 33,519 2,008San Antonio, TX 2007 1,563 14,952 1,443Seattle, WA 2006 3,908 40,450 4,498Total 59,535 624,125 39,880

Survey year Households Trips School trips


Analysis method

multilevel binomial logistic regressions

Boston

…

Houston

…

…

Level 1: student

Level 2: region


Mode share of all K-12 school trips

Results


Walk coefficient standard

errort-ratio p-value

Constant -3.589 0.276 -12.993 <0.001Travel time -0.033 0.002 -20.546 <0.001Household income -0.003 0.0003 -7.784 <0.001Vehicles per capita -0.822 0.076 -10.787 <0.001Driver license -0.841 0.080 -10.495 <0.001female -0.196 0.032 -6.048 <0.001Transit stop density within 0.25 mile buffer

0.001 0.0003 3.557 0.001

Activity density within 0.5 mile buffer 0.013 0.002 8.094 <0.001Job-population balance within 1 mile buffer

0.361 0.074 4.876 <0.001

Intersection density within 1 mile buffer 0.004 0.0004 10.228 <0.001% of 4-way intersection within 1 mile buffer

0.003 0.001 3.321 0.001

Employment can be reached within 30 mins by auto

0.003 0.001 3.026 0.003

Employment can be reached within 30 mins by transit

0.006 0.001 4.104 <0.001

Compactness of metro area 0.018 0.003 6.890 <0.001sample size: 5017 walk trips of 39,880 tripspseudo-R2: 0.88 ( = 1 - variance of fit model / null model)


Bike coefficient standard

errort-ratio p-value

Constant -13.515 3.267 -4.137 0.002Travel time -0.022 0.009 -2.559 0.011Vehicles per capita -1.390 0.315 -4.413 <0.001Driver license -0.501 0.181 -2.761 0.006female -0.772 0.130 -5.941 <0.001Job-population balance within 1 mile buffer

1.061 0.388 2.735 0.007

Intersection density within 1 mile buffer

0.006 0.001 4.015 <0.001

Gas price of metro area 3.133 1.124 2.786 0.018sample size: 628 bike trips of 39,880 tripspseudo-R2: 0.37 ( = 1 - variance of fit model / null model)

www.company.com

Limitations


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

www.company.com

Conclusions


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.


Thank you !

Guang TianUniversity of Utah

[email protected]

Www.company.com Student Travel: Evidence from 13 Diverse Metro Regions of the United States Guang...

Documents

Transcript of Www.company.com Student Travel: Evidence from 13 Diverse Metro Regions of the United States Guang...