Jesus M. Barajas; Cal Poly Pomona

1. Regional Bicycle Planning in Los Angeles
County: An Analysis of the Metro Bicycle
Transportation Strategic Plan
Bike-Transit Integration
Jesus M. Barajas
Cal Poly Pomona
November 6, 2009

2. Overview
 Background
 Metro approach to bike-transit integration
 Data analysis
 Recommendations

3. Background
 Low rates of bicycling across US and in LA
 Bike-transit integration
 Beneficial for transit
 Beneficial for bicyclists
 Agencies across North America are increasing multimodal
efforts

4. Metro approach to bike-transit
integration
 $12 million in FY09 to bike improvement projects
 Prioritizing “bike-transit hubs” in Call for Projects
 Locations weighted based on transit access and ridership,
population, income
 Rankings were transit-centric

5. Data analysis
 Census and spatial data used to determine and predict
bicycling rates
 Census data included most socioeconomic variables
 Spatial data related proximity to bicycle facility

6. Data analysis
Category No bicycling Bicycling p-value
White 50.9% 49.4% 0.015
Asian 11.4% 10.3% 0.002
Black 11.0% 7.5% <0.001
Hispanic/Latino 39.1% 49.3% <0.001
Percentage students 68.9% 67.7% <0.001
Median Age 34.3 31.3 <0.001
Median household income $51,477.79 $42,357.24 <0.001
Number of vehicles available 1.69 1.55 <0.001
Percentage owner-occupied 56.1% 43.0% <0.001
Percentage in poverty 15.6% 19.6% <0.001
Population density (per km2) 45,189 62,041 <0.001
Within 1/4 mi of any bike facility 59.6% 59.9% 0.824
Within 1/2 mi of any bike facility 74.6% 74.8% 0.858

7. Data analysis
 Significant predictors
 Hispanic/Latinos
 College students
 Owner-occupied housing
 Proximity to bicycle facilities not significant
 Significant predictors used to rank suitable transit-hub
locations

8. Bike-Transit Hub Locations

9. Data analysis
 Locations generally near Downtown and South LA
 Geographic component to rankings helps distribute hubs
 Alternate methodologies
 Include transit and bike data
 “Goodness” of bicycle network

10. Recommendations
 Gather and incorporate more data
 Diversify planning methods
 Find innovative approaches to implementation