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Estimating Bicycling Demand

机译：估算骑车需求

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Simple and reliable tools for estimating and predicting the amount of bicycling in an area would be useful for a variety of investment and policy decisions. Previous efforts to develop such tools have typically tried to develop demand estimates from basic descriptors of the population, land use, and bicycling facilities of an area. This paper takes an alternative approach by using the idea of deriving estimates of the likely range of total bicycling demand in an area on the basis of census commute-to-work data. The paper makes three contributions. The first is a general discussion of the total amount of bicycling in the United States and how it varies across places, on the basis of a number of surveys and some original data analysis. The second is the development of an argument that predictive models based on land use and transportation factors are unlikely to ever be accurate or useful because of a number of intractable problems. Third, a simple model is developed for estimation of a range of current levels of bicycling in a given geographic area with reasonable and known accuracy and by use of easily available data. While this model stops short of predicting bicycling levels or demand on specific facilities, it is an important first step in reaching these objectives. There is such a high degree of local variation in bicycling rates in the United States that attempts to predict bicycling levels directly without accounting for current levels are unlikely to be consistently successful.
机译：简单可靠的工具来估算和预测某个地区的自行车骑行量，对于各种投资和政策决策都是有用的。以前开发此类工具的努力通常尝试根据人口，土地使用和某个地区的自行车设施的基本描述来开发需求估算。本文采用一种替代方法，即根据人口普查上下班数据推算某个地区总骑自行车需求的可能范围。本文做出了三点贡献。首先是根据多项调查和一些原始数据分析，对美国自行车的总量及其在各地的变化情况进行一般性讨论。第二个观点的发展是，由于许多棘手的问题，基于土地利用和运输因素的预测模型不太可能是准确的或有用的。第三，开发了一种简单模型，用于以合理和已知的准确度并使用容易获得的数据来估算给定地理区域中当前骑自行车水平的范围。尽管此模型无法预测骑行水平或对特定设施的需求，但这是实现这些目标的重要的第一步。在美国，自行车骑行率存在很大程度的局部差异，因此尝试直接预测自行车骑行水平而不考虑当前的骑行水平不太可能始终如一地成功。

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