Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

[Slides] Equity in Motion: Bikeshare in Low-Income Communities

741 views

Published on

Overview of emerging trends, challenges, analysis, findings and recommendations from my UCLA Capstone research for the District Department of Transportation (DDOT) entitled, "Equity in Motion: Bikeshare in Low-Income Communities". Presented at "Transportation Techies" at WeWork Crystal City on 11/3.

Published in: Data & Analytics
  • I can advise you this service - ⇒ www.HelpWriting.net ⇐ Bought essay here. No problem.
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here
  • Yes you are right. There are many research paper writing services available now. But almost services are fake and illegal. Only a genuine service will treat their customer with quality research papers. ⇒ www.WritePaper.info ⇐
       Reply 
    Are you sure you want to  Yes  No
    Your message goes here

[Slides] Equity in Motion: Bikeshare in Low-Income Communities

  1. 1. EQUITY IN MOTION BIKESHARE IN LOW-INCOME COMMUNITIES Aysha Cohen ULI Senior Associate UCLA Institute of Transportation Studies Email: Aysha.Cohen@ULI.orgFull report: goo.gl/BrVQWL
  2. 2. It’s only typically a couple times in any given century that a city gets to introduce a new form of public transportation. It’s very important that you do it in a way that creates as much opportunity as possible for as many citizens as possible. -Andrew Stober Philadelphia’s former Chief of Staff
  3. 3. PROMISING TRENDS SOCIAL EQUITY ENVIRONMENT ECONOMY SAFETY 49% Renewal rate after low-income subsidy, 53% were people of color 2x low-income ridership increase in London (2010-13) after changing station siting practices 2x growth rate in bicycling since bikeshare started in DC (32% in DC vs 15% nationally) 60% mode shift from sedentary modes to bikeshare in 5 US, Australian & UK cities 2-3% traffic decrease when bikeshare stations are present in DC (causal link) 66% chose retail as their destination by bikeshare in DC 0 deaths from bikeshare after 23+ million rides in the US 88% car-free HHs added (vs. a 1% increase in HHs with cars) in DC
  4. 4. CHALLENGES AHEAD SOCIAL EQUITY SAFETY 95% college education rate for bikeshare users (vs 15% in low-income areas)80% salaries are $50k+ for bikeshare users (vs $34k AMI in low- income areas) 2x pedestrian fatalities in low- income vs upper-income communities nationally 50% dangerous intersections are in lower-income areas of the city (approx.) 3% African- American bikeshare users, vs 23% of commuters regionally
  5. 5. BUFFER ANALYSIS D2a_EP = -A/(ln(N)) Where: A = (HH/TotAct)*ln(HH/TotAct) + (E5_Ret10/ TotAct)*ln(E5_Ret10/ TotAct) + (E5_Off10/ TotAct)*ln(E5_Off10/ TotAct) + (E5_Ind10/ TotAct)*ln(E5_Ind10/ TotAct) + (E5_Svc10/ TotAct)*ln(E5_Svc10/ TotAct) + (E5_Ent10/ TotAct)*ln(E5_Ent10/ TotAct)
  6. 6. A GEOSPATIAL APPROACH 381,317 members members 24,271 trips 946 trips VS. =+ Dupont Circle: Wards 7/8: -April 2011-
  7. 7. A STATISTICAL APPROACH 84Possible Factors Barrier #1: Convenience/Reliability Land Use (11 metrics) Destinations (5 metrics) Connectivity (11 metrics) Travel Modes (22 metrics) Canopy Cover (1 metric) Barrier #2: Perception of Safety Collision Rates (2 metrics) Crime Rates (5 metrics) Lighting (2 metrics) Topography (1 metric) Traffic Volume (1 metric) Barrier #3: Affordability Welfare (2 metrics) Housing (8 metrics) Income (5 metrics) Unbanked (1 metric) Barrier #4: Diversity Education (1 metric) Gender (1 metric) Race (4 metrics) 50Significant Factors 15Algorithmically Selected Factors
  8. 8. RESULTS (BIVARIATE) vs
  9. 9. RESULTS (MULTI-LINEAR) 1- Income 7- Demographics 4- Topography 6- Urban Form 5- Safety2- Land Use 3- Connectivity TOP PREDICTORS: 1 Low Wages (-95%) 2 Retail Jobs (24%) 3 Network Density (20%) 4 Unemployment (-19%) 5 Topography (-18%) MODERATE PREDICTORS: 6 Intersection Density (17%) 7 Collision Rate (17%) 8 Alternative Commuters (17%) 9 Arts/Cultural Facilities (15%) 10 Occupied Housing (15%) WEAK PREDICTORS: 11 Median Home Sales Price (13%) 12 Female-Headed Households (2%) 13 Pedestrian Lighting (2%)
  10. 10. RECOMMENDATIONS Targeted outreach needed for Low-to-medium wage work sites (in red) in areas of low residential density (in light green) Recommendation 1: Leverage intra-agency connections in safety outreach and communications through the Vision Zero Working Group. Partner #1: Vision Zero Working Group Recommendation 2: Integrate Capital Bikeshare into the DC Office of Planning’s design review process and the EPA Environmental Justice Working Group’s programs. Partner #2: EPA Environmental Justice Coordinator Partner #3: DC Office of Planning Recommendation 3: Identify new ways to reach financially burdened residents and workers using the DC Office of Tax and Revenue and the Federal Financial Institutions Examination Council data to increase access to affordable Capital Bikeshare resources for those who need it most. Partner #4: DC Office of Tax and Revenue Partner #5: Federal Financial Institutions Examination Council Recommendation 4: Foster new community partnerships to promote equity in bikeshare access, mobility and public health in across all eight wards of the District of Columbia. Partner #6: The District Department of Health & Human Services Partner #7: Non-traditional Partners
  11. 11. THANK YOU! FULL REPORT:GOO.GL/BRVQWL Aysha Cohen ULI Senior Associate UCLA Institute of Transportation Studies /AyshaRuyaCohen /Aysha.Ruya Aysha.Cohen@ULI.org

×