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    Prioritizing Low-Stress Bicycle Accessibility in Baltimore

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    margaret_kent_prioritizing_low_stress_bicycle_accessibility_in_baltimore.pdf (6.033Mb)
    Date
    2017-05
    Author
    Kent, Margaret
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    Abstract
    The Baltimore City Department of Transportation (BCDOT) completed a Master Bike Plan in 2015. In addition, the completion in 2016 of a citywide quality of service analysis using Level of Traffic Stress (LTS) has created the perfect springboard from which to launch further GIS-based analysis. An opportunity exists to assess the performance of the existing and proposed network in terms of accessibility and equityラtwo concepts that are mentioned but not evaluated in the plan. The plan does not make clear the method used to prioritize projects, so this research offers an example of how projects could be prioritized to maximize accessibility and equity. The methods section develops six performance measures to establish 2 the baseline level of accessibility to four types of commercial and institutional destinations for each neighborhood. The paper then evaluates the equity of performance measure outcomes using demographic indicators of disadvantage as an additional consideration for the prioritization process. Additional motivations for developing this method are to explore how a department such as BCDOT could use their existing LTS network not only for visualization, but also for quantitative analysis at citywide and neighborhood levels, and assess accessibility despite data limitations. The Baltimore region has not had a household travel survey conducted since 2007, and it contains limited information about bicycle trips (personal communication, Baltimore Metropolitan Council staff, January 19, 2017). Given the lack of recent empirical data for bicycle trip demand and route choice, a cumulative opportunities approach is useful for evaluating the degree to which the bicycle network can potentially serve anyone, but especially disadvantaged communities, regardless of whether they currently travel by bicycle. The method is tailored to the City of Baltimoreメs data but could by adapted for other places.
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    http://hdl.handle.net/1853/58533
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    • School of City and Regional Planning Applied Research and Option Papers [241]

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