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A planning tool for evaluating vehicles miles travelled and traffic safety forecasts of growth management scenarios: A case study of Baton Rouge and New Orleans

机译:用于评估车辆行驶里程和增长管理方案交通安全预测的规划工具:以巴吞鲁日和新奥尔良为例

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摘要

This study describes an adaptable planning tool that examines potential change in vehicle miles travelled (VMT) growth and corresponding traffic safety outcomes in two urbanized areas, Baton Rouge and New Orleans, based on built environment, economic and demographic variables. This model is employed to demonstrate one aspect of the potential benefits of growth management policy implementation aimed at curbing VMT growth, and to establish targets with which to measure the effectiveness of those policies through a forecasting approach. The primary objective of this research is to demonstrate the need to break with current trends in order to achieve future goals, and to identify specific policy targets for fuel prices, population density, and transit service within the two study regions. Models indicate based on medium growth scenarios, Baton Rouge will experience a 9 percent increase in VMTs and New Orleans will experience 10 percent growth. This translates to corresponding increases in crashes, injuries and fatalities. The paper provides forecasts for planners and engineers to consider an alternative future, based on desired goals to reduce VMTs and therefore improve safety outcomes. A constrained-forecast model shows a cap on VMTs and crash rates is achievable through policy that increases fuel prices, population density and annual transit passenger miles per capita at reasonable levels through a growth management approach.
机译:这项研究描述了一种适应性强的计划工具,该工具根据建筑环境,经济和人口变量,研究了两个城市化地区(巴吞鲁日和新奥尔良)的行驶里程(VMT)增长的潜在变化以及相应的交通安全结果。该模型用于说明旨在抑制VMT增长的增长管理政策实施的潜在好处的一个方面,并建立可通过预测方法衡量这些政策有效性的目标。这项研究的主要目的是证明有必要打破当前的趋势以实现未来的目标,并确定两个研究区域内燃油价格,人口密度和过境服务的具体政策目标。模型表明,根据中等增长情况,巴吞鲁日的VMT增长9%,新奥尔良的增长10%。这意味着相应的死机,受伤和死亡人数增加。本文提供了预测,供规划人员和工程师考虑基于减少VMT并因此改善安全结果的预期目标而考虑的替代未来。约束预测模型显示了VMT的上限,并且可以通过通过增长管理方法将燃油价格,人口密度和人均年度过境旅客英里数提高到合理水平的政策来实现崩溃率。

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