Regional Bicycle Planning in Los AngelesCounty: An Analysis of the Metro Bicycle     Transportation Strategic Plan        ...
Overview Background Metro approach to bike-transit integration Data analysis Recommendations
Background Low rates of bicycling across US and in LA Bike-transit integration   Beneficial for transit   Beneficial f...
Metro approach to bike-transitintegration $12 million in FY09 to bike improvement projects Prioritizing “bike-transit hu...
Data analysis Census and spatial data used to determine and predict  bicycling rates   Census data included most socioec...
Data analysisCategory                             No bicycling   Bicycling    p-valueWhite                                ...
Data analysis Significant predictors   Hispanic/Latinos   College students   Owner-occupied housing   Proximity to bi...
Bike-Transit Hub Locations
Data analysis Locations generally near Downtown and South LA   Geographic component to rankings helps distribute hubs A...
Recommendations Gather and incorporate more data Diversify planning methods Find innovative approaches to implementation
LTC, Jack R. Widmeyer Transportation Research Conference, Going to San Bernardino A Symposium on Intermodal Transit Statio...
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LTC, Jack R. Widmeyer Transportation Research Conference, Going to San Bernardino A Symposium on Intermodal Transit Stations and Transit-Oriented Design, 11/06/2009, Jesus Barajas

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Jesus M. Barajas; Cal Poly Pomona

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LTC, Jack R. Widmeyer Transportation Research Conference, Going to San Bernardino A Symposium on Intermodal Transit Stations and Transit-Oriented Design, 11/06/2009, Jesus Barajas

  1. 1. Regional Bicycle Planning in Los AngelesCounty: An Analysis of the Metro Bicycle Transportation Strategic Plan Bike-Transit Integration Jesus M. Barajas Cal Poly Pomona November 6, 2009
  2. 2. Overview Background Metro approach to bike-transit integration Data analysis Recommendations
  3. 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. 4. Metro approach to bike-transitintegration $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. 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. 6. Data analysisCategory No bicycling Bicycling p-valueWhite 50.9% 49.4% 0.015Asian 11.4% 10.3% 0.002Black 11.0% 7.5% <0.001Hispanic/Latino 39.1% 49.3% <0.001Percentage students 68.9% 67.7% <0.001Median Age 34.3 31.3 <0.001Median household income $51,477.79 $42,357.24 <0.001Number of vehicles available 1.69 1.55 <0.001Percentage owner-occupied 56.1% 43.0% <0.001Percentage in poverty 15.6% 19.6% <0.001Population density (per km2) 45,189 62,041 <0.001Within 1/4 mi of any bike facility 59.6% 59.9% 0.824Within 1/2 mi of any bike facility 74.6% 74.8% 0.858
  7. 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. 8. Bike-Transit Hub Locations
  9. 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. 10. Recommendations Gather and incorporate more data Diversify planning methods Find innovative approaches to implementation

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