Forecasting Bicycle Facility Demand
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2020-09-01
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Edition:Final Report
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Abstract:The objective of this report is to (1) evaluate current and past predictive models that are used for forecasting off-street bicycle facility demand; (2) create a statistical model from locally sourced data that is able to connect bicycle facility counts to time, demographic data, and weather data; (3) conclude if the statistical model can be applied to different bicycle facilities. If all objectives are met then the statistical model and findings can be used to estimate the impacts of bicycle facilities upon health, food availability, employment access and ultimately regional sustainability for any given area. To accomplish this goal, the research team will use multilinear regression to correlate the relationship between local off-street bicycle facilities count data and demographic/socioeconomic data that will enable a model that is able to accurately predict bicycle facility usage within any environment.
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