going nowhere fast?
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Going Nowhere Fast? . Roy Samaan 14 March 2011 UP 206 A. Effects of Service Reduction on Transit Quality . Roadmap. Research Basis Review of Previous Conclusions Examination of New Variables Use of New Variables to Construct Transit Quality Index Summary of Findings Conclusion - PowerPoint PPT PresentationTRANSCRIPT
GOING NOWHERE FAST? Roy Samaan14 March 2011UP 206 A
Effects of Service Reduction on Transit Quality
Roadmap Research Basis Review of Previous Conclusions Examination of New Variables Use of New Variables to Construct Transit
Quality Index Summary of Findings Conclusion Need for Refinement Questions
Central Policy Questions Does the elimination of METRO bus lines
significantly degrade access to transit? How is quality of transit in most transit
dependent tracts affected? Are there existing alternatives to
eliminated service?
Poverty Rates Around Cancelled Lines
Poverty Rates Around Existing Rapid Lines
DEC 2010: Access Maintained, Quality Reduced
Only East/West Rapid Buses connecting SE LA & SW LA are eliminated & replaced with local service
Rapids connected high poverty areas with transit hubs & job centers
No Additional East/West Rapids Within 1mile of Cancelled Rapid Lines
Standard walk distance is ¼ mile Cancelled North/South Rapids are within1 mile of existing Rapid service
Cancelled Rapid Lines Are in High Usage Corridors
Transit usage in study area high among those earning less than $65k Indicates strong preference for public transit, if not outright transit dependency
Poverty is Useful For Predicting Need, Not Quality of Service
Quality of Service based on multiple factors: Congestion, transit dependency factors,
and speed of rapid bus relative to local bus contribute to service quality
Combining indexed Need Factors and Congestion Factors Gives a rough estimate of service quality
Generation of Need Index Need Index = (% Poverty in tract + %
under 18 + % 65 and up + Usage Intensity)
Weighted towards toward FTA-defined transit dependency variables
Intensity of use given slightly more weight than other factors
Comparison of Need Score vs. Poverty
Highest need scores do not correlate directly to highest poverty Cancelled rapid lines covered need areas not currently covered by
existing rapid service
Calculation of Congestion Index
Factors examined include: Existing bus stop density, local line density, rapid line
density, roadway density and took into account rapid line speed relative to local line speed
Densities were calculated using the following formula: Attribute Density = (Attribute/Area)*(Population/Area)
=> [Attribute *population/(Area*Area)] Spatial joins, field calculator and field geometry used to
generate data Stop density and road density weighted least; rapid
density highest
How does Congestion Score Correlated to Poverty?
High poverty tracts around cancelled east/west lines are only moderately congested relative to DTLA & SFV
Combining Need Index and Congestion Index
Very few High Need areas also had high congestion However, the higher the poverty rate, the higher the average index scores
Creating Transit Quality Index Need Index scores were weighted
slightly higher than Congestion Index scores
Calculated TQI for each census tract It looks like this….
Computation of Transit Quality Index
Countywide Transit Quality Scores
Cancelled rapid lines were an efficient way to get from one low transit quality area to another
Summary of Findings Does the elimination of METRO bus lines
significantly degrade access to transit? No.
How is quality of transit in most transit dependent tracts affected? Negatively.
Are there existing alternatives to eliminated service? Yes for north/south Rapid lines; No for east/west Rapid lines
Conclusions Cancelled rapid lines, especially
east/west lines, served high poverty riders
These lines served census tracts with high need scores and with lower congestion costs than other parts of the city
The loss of these lines reduces the transit quality in southeast and southwest Los Angeles
Necessary Refinement Both Need and Congestion Indices only
give rough estimates Correlating high index scores with
demographic data beyond poverty rates Analysis of forthcoming and proposed
(30/10) rail lines
Questions?