Decision analysis to address extreme weather : extreme weather effects on ridership and modeling the decision to invest in canopy coverage.
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Decision analysis to address extreme weather : extreme weather effects on ridership and modeling the decision to invest in canopy coverage.

Filetype[PDF-836.47 KB]


English
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  • Creators:
  • Corporate Contributors:
    University of South Florida. Center for Urban Transportation Research
  • Subject/TRT Terms:
  • Resource Type:
    Tech Report
  • Geographical Coverage:
    Florida
  • Corporate Publisher:
    University of South Florida. Center for Urban Transportation Research
  • Abstract:
    This project applies a decision analytic methodology that takes considerations of extreme weather events to quantify and assess canopy investment options. The project collected data for two cases studies in two different transit agencies: Chicago Transit Authority (CTA) and Utah Transit Authority (UTA). The UTA analysis focuses on bus stop canopy coverage while the CTA case focuses on rail transit station coverage.

    The report is constructed in three parts. Part I presents the decision analysis approach and overall project design. Part II presents analysis to assess how canopy coverage effects ridership and revenue on extreme weather days. Part III integrates the analysis from Part II and other data into a final decision tree to present a workable decision model.

    Findings from Part II demonstrate that bus stop shelter and bench installation in UTA service area can effectively reduce the ridership losses due to extreme hot and cold weather, and shelters provide additional benefits on heavy rain days. These findings generally suggest that transit infrastructure and amenities that reduce passengers’ exposure to weather can save more rides on extreme weather days. Finding from the CTA analysis are less conclusive, largely because of significant data limitations.

    Part III takes a further step to examine the cost-effectiveness of installing such weather-proof infrastructure by integrating the existing cost and fare revenue data with the estimated effects of station amenities. Overall, our research extends the extant weather and transit literature and presents the first attempt to empirically estimate the moderating effect of transit amenities. It is also highly relevant for transit planners and managers by providing a systematic approach to evaluating the cost and benefits of extreme weather mitigating facilities and infrastructure.

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