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Social Equity in Distance Based Fares. GIS in Transit October 16-17, 2013. Steven Farber, University of Utah. Background. UTA transitioning from a flat fare to a distance based fare Title VI and EJ requirements (differential impacts)
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Social Equity in Distance Based Fares GIS in Transit October 16-17, 2013 Steven Farber, University of Utah
Background • UTA transitioning from a flat fare to a distance based fare • Title VI and EJ requirements (differential impacts) • Different populations will be impacted differently since trip gen’s and distances travelled vary systematically with demographics • Understanding of travel behavior required to assess differential impacts
Fares and Sustainability • Competing goals of transit agency • Economic – Increase Revenue • Environmental – Decrease automobile use • Social – Provide transit service to those in need or equally to all • Distance based fares • Economically efficient (capturing external costs) • Socially beneficial (shorter but more frequent trips) • Environmentally detrimental (increased costs for long distance discretionary riders)
Fares and Equity Social equity in transportation is summarized by Sanchez as the distribution of “benefits and burdens from transportation projects equally across all income levels and communities” Fairness: Whether the costs and benefits are equal after taking needs, means, and abilities into consideration. Are we interested in equality or fairness?
Research Questions • What are the social equity and fairness impacts of a transition to DBF? • How can travel behavior be used to assess social equity in this case? • If DBFs are generally desirable, how can we find and address exceptions to this rule?
Data • Utah Household Travel Survey • Spring 2012 • 1 day travel diary • 9,155 Households • 27,046 People • 101,404 Trips • Filtered to only those residing in UTA’s core service area - 68% of respondents • # daily of transit trips • Daily distance travelled by transit
Selection of Fares • UTA is considering fares that consist of a flat component and a distance-based component • For this study, we selected a revenue-neutral fare • $0.50 + $0.19 per mile • Distance is measured as Euclidean distance so that users are not penalized by indirect network design
Method • Estimate a joint model of transit trip generations and distance travelled • Spatially expanded coefficients – controls for contextual information not captured in the dataset • Convert travel behavior to fares and compare results
Low Income & Education Low Income & Elderly Non-White Ref.
Low Income & Education Low Income & Elderly Non-White Ref.
Conclusions • Distance based fares generally result in cheaper fares for those who need it most • Pockets of mismatch exist – suburbanization of the poor poses a problem • Burden on long-distance low-income travellers can be mitigated through reduced flat-fare components • Changes in price are likely to shift wealthy discretionary riders back to their cars, but it may attract a plethora of new low-income riders
Next Steps • Developing a GIS Decision Support System • Analysts at UTA can compute fare surfaces for different demographic profiles and different fare structures • Targeted studies of riders in particular at-risk neighborhoods identified by the DSS
Acknowledgements • Xiao Li, Graduate RA • Keith Bartholomew, UofU • Antonio Páez, McMaster University • Khandker M. NurulHabib, University of Toronto • Utah Transit Authority • Partial support from: • National Institute for Transportation and Communities (DTRT12-G-UTC15-540) • National Science Foundation (BCS-1339462)