How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities
How built environment affects travel behavior: A comparative analysis of the connections between land use and vehicle miles traveled in US cities
复制标题
DOI：
10.5198/jtlu.v5i3.266
复制
发表时间：
2012-12
影响因子：
1.9
通讯作者：
Lei Zhang;Jinhyun Hong;Arefeh A. Nasri;Qing Shen
中科院分区：
文献类型：
--
作者：
Lei Zhang;Jinhyun Hong;Arefeh A. Nasri;Qing Shen
在以往的研究中，关于建筑环境对旅行行为的影响的研究结果好坏参半，即在一些实证研究中发现了统计上和实践上显著的影响，而在许多其他研究中发现了不显著的相关性。目前尚不清楚为什么在某些城市地区估计的影响会更强或更弱，以及拟议的土地使用变化/政策在改变某些旅行行为方面的效果如何。这一知识差距使决策者难以根据土地利用计划和政策对车辆行驶里程的影响，从而对缓解拥堵、节约能源、减少污染和温室气体排放的影响进行评估。本研究有以下几个目标：(1)重新审视建筑环境因素对出行行为的影响，特别是在美国五个大都市地区（分为四个案例研究区域）的VMT；(2)在所有案例研究领域中使用相同的模型规格和数据集开发一致的模型，以便进行直接比较；(3)识别现有土地利用特征和土地利用政策决策过程等因素可能解释不同城市地区建筑环境对车辆行驶里程的不同影响；(4)为政府机构和决策者评估拟议的土地利用变化对车辆行驶里程的影响提供一个原型工具。四个案例研究区域包括：华盛顿州西雅图；里士满-彼得堡和诺福克-弗吉尼亚海滩；马里兰州巴尔的摩;和华盛顿特区。我们的实证分析采用贝叶斯多层模型，包含各种个人层面的社会经济和人口变量，以及五个建筑环境因素，包括居住密度、就业密度、熵（衡量混合用途开发水平）、平均街区大小（衡量交通/步行友好性）和到市中心的距离（衡量分散化和填充开发水平）。我们的研究结果表明，在所有四个案例研究区域中，推广紧凑、混合用途、小块和填充开发可以有效地减少人均VMT。然而，鼓励这类土地发展的土地使用计划和政策的有效性，在不同的个案研究区域和同一个案研究区域内都是不同的。我们已经确定了几个可能影响建筑环境变化与车辆行驶里程变化之间联系的因素，包括城市面积、现有建筑环境特征、交通服务覆盖范围和质量，以及土地使用决策过程。
Mixed findings have been reported in previous research regarding the impact of built environment on travel behavior, i.e. statistically and practically significant effects found in a number of empirical studies and insignificant correlations shown in many other studies. It is not clear why the estimated impact is stronger or weaker in certain urban areas, and how effective a proposed land use change/policy will be in changing certain travel behavior. This knowledge gap has made it difficult for decision makers to evaluate land use plans and policies according to their impact on vehicle miles traveled (VMT), and consequently their impact on congestion mitigation, energy conservation, and pollution and green house gas emission reduction. This research has several objectives: (1) Re-examine the effects of built-environment factors on travel behavior, in particular VMT in five U.S. metropolitan areas grouped into four case study areas; (2) Develop consistent models in all case study areas with the same model specification and datasets to enable direct comparisons; (3) Identify factors such as existing land use characteristics and land use policy decision-making processes that may explain the different impacts of built environment on VMT in different urban areas; and (4) Provide a prototype tool for government agencies and decision-makers to estimate the impact of proposed land use changes on VMT. The four case study areas include Seattle, WA; Richmond-Petersburg and Norfolk-Virginia Beach, VA; Baltimore, MD; and Washington DC. Our empirical analysis employs Bayesian multilevel models with various person-level socio-economic and demographic variables and five built-environment factors including residential density, employment density, entropy (measuring level of mixed-use development), average block size (measuring transit/walking friendliness), and distance to city center (measuring decentralization and level of infill development). Our findings show that promoting compact, mixed-use, small-block and infill developments can be effective in reducing VMT per person in all four case study areas. However, the effectiveness of land use plans and policies encouraging these types of land developments is different both across case study areas and within the same case study area. We have identified several factors that potentially influence the connection between built environment shifts and VMT changes including urban area size, existing built environment characteristics, transit service coverage and quality, and land use decision-making processes.