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首页> 外文期刊>Journal of Transport and Land Use >Method to adjust Institute of Transportation Engineers vehicle trip-generation estimates in smart-growth areas
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Method to adjust Institute of Transportation Engineers vehicle trip-generation estimates in smart-growth areas

机译:调整智能增长地区交通工程师学会车辆出行估计的方法

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This paper describes a practical method of adjusting existing Institute of Transportation Engineers (ITE) estimates to produce more accurate estimates of motor-vehicle trip-generation at developments in smart-growth areas. Two linear regression equations, one for an A.M. peak-hour adjustment and one for a P.M. peak-hour adjustment, were developed using vehicle trip counts and easily measured site and surrounding area context variables from a sample of 50 smart-growth sites in California. Many of the contextual variables that were associated with lower vehicle trip generation at the smart-growth study sites were correlated. Therefore, variables representing characteristics such as residential population density, employment density, transit service, metered on-street parking, and building setback distance from the sidewalk were combined into a single “smart-growth factor” that was used in the linear regression equations. The A.M. peak-hour and P.M. peak-hour adjustment equations are only appropriate for planning-level analysis at sites in smart-growth areas. In addition, the method is only appropriate for single land uses in several common categories, such as office, mid- to high-density residential, restaurant, and coffee/donut shop. The method uses data from California, but the methodological approach could provide a framework for adjusting ITE trip-generation estimates in smart-growth areas throughout the United States.
机译:本文介绍了一种实用的方法,该方法可以调整现有的运输工程师协会(ITE)的估算,以便在智能增长地区的发展情况下得出更准确的机动车出行量估算。两个线性回归方程,一个代表A.M.高峰时间调整和一个下午高峰时段的调整是根据车辆行驶次数以及易于测量的站点和周围区域环境变量而开发的,该变量来自加利福尼亚州的50个智能增长站点。在智能增长研究地点,许多与较低的车辆出行相关的背景变量是相关的。因此,将代表居民人口密度,就业密度,公交服务,有偿停车收费以及距人行道的建筑物后退距离等特征的变量组合到一个线性回归方程中使用的单个“智能增长因子”中。上午高峰时间和下午高峰时间调整方程式仅适用于智能增长地区站点的计划级分析。此外,该方法仅适用于几种常见类别中的单个土地用途,例如办公室,中密度住宅,餐厅和咖啡/甜甜圈店。该方法使用来自加利福尼亚州的数据,但是该方法学方法可以提供一个框架,用于调整全美国智能增长地区的ITE行程生成估算。

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