, 但波, 朱盼The influence of rail transit accessibility on the shift of travel modal choice: Empirical analysis based on the micro survey of the 1980s generation in Shanghai
LIWan, DANBo, ZHUPan通讯作者:
收稿日期:2016-10-21
修回日期:2017-02-23
网络出版日期:2017-05-20
版权声明:2017《地理研究》编辑部《地理研究》编辑部
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1 引言
近年来,中国汽车拥有量呈井喷式增长。根据《中国统计年鉴（2011）》和《中国统计年鉴（2015）》,2010-2014年民用汽车拥有量从7801.83万辆上升到14598.11万辆,增加了87.12%。根据上海市第五次综合交通调查（http://www.moc.gov.cn/st2010/shanghai/sh_zhengwudt/201510/t20151013_1895639.html）,2014年上海市实有小客车总量近320万辆,较2009年增加约一倍,且潜在拥车需求依然强烈。汽车保有量迅猛增长的后果之一就是城市交通拥堵愈演愈烈,环境污染也益发严重,这些问题已成为困扰中国大城市可持续发展的普遍难题[1,2]。与此同时,轨道交通建设在中国正如火如荼地展开,地铁的重要性日渐凸显。2010-2015年,中国有轨道交通运行的城市由16增加到27个,站点达2154座,运营总里程达3521 km。根据新浪上海网（http://sh.sina.com.cn/news/g/2016-01-02/detail-ifxncyar6176840.shtml）统计,截至2015年底,上海轨道交通运营总里程最长达617 km,站点最多达366座。发展城市轨道交通的目的之一就是希望通过提高轨道交通的可达性,引导居民由小汽车转向轨道交通出行,进而缓解城市交通拥堵与减轻空气污染。其基本逻辑在于：良好的轨道交通可达性能促使居民更多地选择地铁出行,从而降低购买和使用小汽车的可能性,产生交通转移效应。交通转移最大的优点在于,出行者可以主动选择更为绿色低碳的轨道交通,这种转移不像限购、限牌、限行、限号等“大棒型”交通管制措施会导致福利损失,而是为出行者提供更多可行选择的“胡萝卜型”政策,在不降低社会福利的基础上改善城市交通。更为重要的是,轨道交通建设还涉及到城市尤其是大城市未来空间发展战略的选择：小汽车主导的蔓延式发展还是轨道交通主导的紧凑式发展?而大城市人口密集和土地资源紧缺的现实,使得以地铁为导向的紧凑式发展几乎成了中国大城市发展的必然选择。那么,在城市居民对小汽车日渐依赖的今天,回答提高轨道交通可达性能否真正地减轻居民对小汽车的依赖这一问题就显得尤为重要。
实际上,交通转移效应假设面临着理论和实证的双重挑战。理论上,交通转移效应的竞争性假说是唐斯定律[3],或称之为交通创造理论[4]。这种理论不仅认为新增道路的分流作用有限,且会创造出新的交通需求。具体来说,轨道交通的建设也可能会鼓励居住在市中心的居民搬迁到房价相对便宜的郊区,从而创造出新的通勤者与通勤需求。此外,轨道交通在减少地面交通流量、缓解交通拥堵的同时,也有可能会诱发由于交通拥堵而放弃购买和使用私家车的居民重新考虑小汽车这一出行方式。因此,从理论上来说,建设轨道交通对交通行为的影响并不确定。目前,尚无研究发现建设轨道交通会鼓励小汽车的拥有和使用,而轨道交通会削减小汽车的拥有或使用[5-7]却得到了不少证据支撑。另外,也有研究发现二者并不存在相关关系[6,7],尤其是对于小汽车的使用来说[8]。除了结论不统一外,已有研究大多针对发达国家的城市,对发展中国家的城市研究涉及较少[9-11]。与以汽车为主导交通方式的发达国家不同,以中国为代表的发展中国家的小汽车和轨道交通几乎处于同一发展阶段,因此有必要检验发展中国家的轨道交通建设与居民出行之间是否存在与发达国家相同的规律。
实证上面临的主要挑战则是如何处理自选择问题。不可否认的是,靠近轨道交通居住的居民很可能由于自己偏好地铁出行而选择轨道交通可达性高的区位居住,而远离轨道交通居住的居民则可能是因为自己偏好小汽车出行而选择远离地铁的社区,进而可以观察到距离轨道交通越近的家庭购买和使用小汽车更少的现象。因此,实证发现的结果有可能不是轨道交通可达性改善的结果,而是由于遗漏了居民出行态度与偏好这组变量,或由于居住选址的不同而造成轨道交通可达性的差异,即存在反向因果的可能性。尽管自选择问题是交通出行研究领域的前沿和热点之一[12-14],但在轨道交通建设对交通行为影响的研究中,只有个别少数研究对自选择[5,10,11]问题进行了处理。
具体到关于中国的研究来看,Huang等[9,11]分别基于广州和北京进行研究并发现,与发达国家相同,轨道交通可达性提高能够降低居民私家车的拥有率;但Huang等的研究并没有处理自选择问题[9],而张英杰等的研究仅仅是基于北京市的826个调查个体[11]。基于以上认识,本文以中国轨道交通最发达的城市之一——上海市作为研究区,基于上海市2000个左右个体的样本,检验轨道交通对居民出行方式选择的影响,并且通过两种不同的方案处理自选择问题,结论相比于已有研究将更加可靠。
2 研究方法与数据来源
2.1 数据来源
本文数据来源于2013年长三角地区社会变迁（上海地区基线调查）数据库,该数据库以跟踪1980-1989年出生的一代人（简称80后）为主体,按区县分层,对乡镇街道、居/村委会、地址和80后人群进行四阶段抽样,共抽取40个街道（镇）、80个居（村）委会,获得有效问卷2368份。如今80后正处在人生的转折阶段,正面临买车、买房以及建立出行习惯的关键时期,且这部分人群更可能是家庭重大耐用消费品和投资品的实际决策者。根据第六次人口普查数据,上海约三分之一的家庭有80后,因此这部分样本具有相当的代表性。本文研究区域为上海都市区,即剔除了2013年与都市区无轨道交通相连接的崇明岛样本。另外还剔除了无家用小汽车却选择了驾车为最主要的通勤方式的12个异常样本。具体样本所在街道或镇以及轨道交通线路和站点分布如图1所示。
显示原图|下载原图ZIP|生成PPT图12013年抽样街道（镇）与轨道交通的空间分布
-->Fig. 1Location of samples and Shanghai metro in 2013
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本文的重点在于回答轨道交通可达性的提高是否促进了城市居民由小汽车转向轨道交通进行通勤。这一问题具体可分为购买和使用两个层次：首先,对于购买行为而言,轨道交通可达性的提高是否会影响家庭小汽车的购买决策?其次,对于使用行为来说,轨道交通可达性的提高是否会减少小汽车的使用,进而促进其更多地乘坐地铁?因此本文核心被解释变量分别为家庭是否拥有小汽车、最主要的通勤方式是否为小汽车或地铁。同时结合2013年上海市轨道交通站点的空间分布,通过ArcGIS测算得到本文核心解释变量：轨道交通的可达性,即样本家庭所在街道或镇的中心点到最近轨道交通站点的距离①(① 出于对调查对象的保护,数据库只公布了样本所在街道信息,核心变量的精确性不足。),该距离越大意味着轨道交通的可达性越差,反之则表明轨道交通可达性越高。
其他控制变量的选择主要参考已有研究。事实上有关居民小汽车拥有与使用的影 响因素已经得到了广泛讨论[15-19]。总体而言,可将影响因素归并为两个层面：宏观的街道或镇建成环境因素和微观的个体和家庭社会经济特征。为此,本文也将控制变量分为宏观和微观两个层面。在宏观层面,对建成环境经典的系统性描述是3“D”,即密度（density）、混合度（diversity）和设计（design）[20,21]。首先,密度不仅影响道路的供给和使用,也影响可替代的其他公共交通的供给和使用,是已有研究最常见的变量。本文的人口密度采用2010年上海市第六次人口普查的街道（镇）常住人口除以行政区面积计算得到。其次,混合度是指土地利用的混合程度,本文认为城市中心土地利用更多样化,因此距城市主/副中心的远近在一定程度上也能反映土地利用的混合程度。目前上海已基本形成的“一主四副”（即人民广场、徐家汇街道、五角场街道、花木街道与真如街道）城市总体构架②(② 凤凰网财经（http://finance.ifeng.com/news/region/20110915/4591923.shtml）。),故本文距最近主/副中心的距离采用样本家庭所在街道的中心点到“一主四副”的最近距离来测算。最后,设计包括道路网络特征、街区类型、停车场等及其他微观设计,本文采用街道或镇公交站点密度（公交站点数/行政区面积[22]）作为代理变量。在微观层面,本文控制了个体特征（性别、年龄、婚姻、教育以及户口情况）和家庭特征（财富水平和孩子个数）等基本信息。需要说明的是,除了控制是否为非农户籍外,异地户口在上海市买车的程序也相对复杂,因此也将是否拥有上海市户口作为虚拟变量纳入模型。在家庭财富水平上,除了控制家庭上年收入,本文还考虑家庭的不动资产（被访人汇报的房屋现价估计值）对个人出行方式选择的影响。具体变量的描述性统计如表1所示。
Tab. 1
表1
表1各变量的描述性统计
Tab. 1The descriptive statistics of variables
| 变量 | 样本量 | 平均值 | 标准差 | 最小值 | 最大值 | ||
|---|---|---|---|---|---|---|---|
| 核心被解释变量 | 家庭是否拥有小汽车 | 2088 | 0.318 | 0.466 | 0 | 1 | |
| 最主要的通勤方式是否为小汽车 | 1598 | 0.136 | 0.343 | 0 | 1 | ||
| 最主要的通勤方式是否为轨道交通 | 1598 | 0.265 | 0.442 | 0 | 1 | ||
| 核心解释变量 | 距最近地铁站的距离（ln） | 2088 | 7.298 | 1.395 | 5.507 | 9.953 | |
| 宏观街道或镇 层面变量 | 人口密度（ln, 2010） | 2088 | 9.076 | 1.339 | -3.738 | 10.825 | |
| 距最近主/副中心的距离（ln） | 2088 | 8.864 | 2.183 | 6.538 | 10.840 | ||
| 公交站点密度（ln） | 2088 | 2.751 | 1.307 | 0.248 | 4.485 | ||
| 微观个人和家庭 层面变量 | 是否是男性 | 2088 | 0.466 | 0.499 | 0 | 1 | |
| 年龄 | 2088 | 28.527 | 2.840 | 24 | 33 | ||
| 教育 | 初中及以下 | 2088 | 0.157 | 0.364 | 0 | 1 | |
| 高中、中专和专科 | 2088 | 0.472 | 0.499 | 0 | 1 | ||
| 本科及以上 | 2088 | 0.371 | 0.483 | 0 | 1 | ||
| 是否结婚或同居 | 2088 | 0.548 | 0.498 | 0 | 1 | ||
| 是否有上海户口 | 2088 | 0.739 | 0.439 | 0 | 1 | ||
| 是否为非农户口 | 2088 | 0.713 | 0.453 | 0 | 1 | ||
| 家庭上年收入的自然对数 | 2088 | 11.180 | 1.409 | 1.69 | 13.122 | ||
| 2013年房价估计值 | 1535 | 6.310 | 3.566 | 0 | 16.118 | ||
| 孩子个数 | 2088 | 0.484 | 0.604 | 0 | 5 | ||
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2.2 研究方法
本文的被解释变量为二元分类变量,故主要采用非线性的probit进行回归分析,具体模型为：式中：被解释变量分别为家庭是否拥有小汽车（Car_ownership）、是否使用小汽车（Car_use）或地铁（Metro_use）作为主要通勤方式,关键解释变量为距最近地铁站的距离（Near_dis）,个体和家庭层面特征（Household）,即性别、年龄、教育、婚姻状态、户口情况、家庭财富和孩子个数,街道或镇层面特征（Neighbourhood）,即人口密度、距最近主/副中心的距离和公交站点密度。本文预期轨道交通可达性的提高对于小汽车的拥有和使用均具有抑制作用,即变量估计系数的符号而正,而对于轨道交通的使用则具有促进作用,即变量估计系数的符号为负。
在模型（2）中,是否使用小汽车作为最主要的交通方式还取决于该样本所在家庭是否有汽车,即样本数据发生了偶然断尾（incidental truncation）。如果简单的将所有样本纳入模型回归就会造成偏差,因此本文使用Heckman二步法对汽车使用进行估计[23]。该模型的实际估计过程包括两步：首先利用模型（1）得到是否拥有小汽车的拟合值,并由此得到修正参数逆米尔斯比率（lambda）;再将修正参数作为一个额外的控制变量加入模型（2）中,由此得到更为确切的小汽车使用影响方程。相较于直接控制家庭是否有小汽车变量,修正参数可以提供更细致的关于概率大小的信息,进而更好地估计决策方程的干扰方差[24]。
尽管在轨道交通对交通行为的研究中,自选择问题尚未得到有效解决,但其从属的更大的研究背景,即城市建成环境对交通行为影响的研究,提供了不少可供参考的解决方案。已有解决方案往往有针对性地去处理遗漏变量或反向因果,或者同时解决这两种来源造成的估计偏误。遗漏变量的解决主要是通过问卷调查补充出行态度与偏好这组变量,包括最常见地设置居民偏好相关问题[25-27]、甚至直接问被调查对象是否存在居住区自选择[28]（如在选择居住地时会多大程度上考虑建成环境）;反向因果的解决则主要通过设置多方程模型来考察整个系统,如SEM[29,30]、Heckman[31]、嵌套模型[32-34]等;而同时解决两种不同来源的自选择则主要是使用工具变量[35,36]、准自然实验[10]等方法,或者利用样本的异质性筛选不存在自选择的子样本[11]。
本文就是利用样本的异质性,尝试采用两种不同的方案来解决轨道交通可达性和交通行为之间的自选择问题。第一种,筛选出在最近地铁站运营的10年前就已经在其附近买房的子样本单独进行检验③(③ 上海市地铁站的具体运营时间从百度百科中查知,购房时间来源于本文数据库。)。城市轨道交通从规划到运营是一个长期的过程,大约需要8~10年的时间。也就是说,10年前就已经在现在才开始运营的地铁站附近购房的样本对于轨道交通并没有强烈的偏好,将时间推后到10年前主要是为了排除由于对轨道交通存在预期而购房的样本。然而不可否认的是这种方案仍存在一定问题：① 最近地铁站点会随着轨道交通的不断建设发生改变,虽然距离2013年居住地最近的轨道交通站点还未落成,但不能排除轨道交通的可达性已经比较好的情况。② 这种方案只能部分地解决对地铁的偏好,无法排除偏好小汽车从而选择远离地铁的样本。第二种方案是借鉴张英杰等的做法,利用中国的多元化住房体系,筛选出相对被动的住房选址样本。调查中的拆迁安置房、房改房、单位福利分房和集资房样本,其居住选址并非是完全自由选择的结果,而是在政府或者就业单位干预下的被动选择。较第一种方案,这种方案能更好地缓解自选择问题。
3 结果分析
3.1 描述性统计分析
从可视化结果来看（图2a）,小汽车的拥有与轨道交通可达性的关系与预期相符。在轨道交通可达性较差的外围地区,小汽车拥有占比较高,如上海西北部的嘉定区新成路街道拥有小汽车家庭比例最高为69.23%,东部浦东新区的惠南镇拥有小汽车家庭比例也高达65.52%,但在轨道交通可达性较好的外环内区域,小汽车家庭拥有率相对较低,如黄浦区的半淞园路街道拥有小汽车家庭比例为39.29%,静安区的江宁路街道的小汽车拥有率仅为28%。这种现象反映出,当小汽车不仅仅是一种交通工具,且成为身份象征的炫耀型消费时,能够支付起在轨道交通可达性高的中心城区居住的群体并不会放弃汽车的拥有[35]。从通勤方式的选择来看,小汽车与地铁的使用与轨道交通可达性的关系更加明显。从图2b和图2c中可以观察到,使用小汽车作为主要通勤方式的样本主要分布在外围地区,而使用地铁作为主要通勤方式的样本则主要分布在轨道交通可达性较好的市中心地区。
显示原图|下载原图ZIP|生成PPT图2家庭汽车拥有率、小汽车与轨道交通通勤占比的分布
-->Fig. 2The distribution of the proportion of car ownership, car user and metro user
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从距离的描述性统计结果来看（表2）,轨道交通可达性与小汽车拥有、使用以及地铁使用的关系更为清晰。将距离按百分位点分为三份,统计发现：距地铁站点距离越远,拥有小汽车家庭比率呈上升趋势,分别为26.83%、28.61%、38.90%;上下班自驾车出行比率也从9.98%上升到17.79%,而上下班轨道交通出行比率则不断下降。
Tab. 2
表2
表2家庭小汽车拥有率及通勤方式比例（%）
Tab. 2The proportion of car ownership, car user and metro user by distance (%)
| 指标 | 距地铁站距离（三分位点） | ||
|---|---|---|---|
| 0~33% | 33%~66% | >66% | |
| 小汽车家庭占比 | 26.83 | 28.61 | 38.90 |
| 小汽车通勤占比 | 9.98 | 13.10 | 17.79 |
| 轨道交通通勤占比 | 41.18 | 28.97 | 6.77 |
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上述现象基本符合预期,即交通转移效应理论可能比交通创造理论更贴近上海市交通发展的实际情况。在接下来的计量分析中将进一步检验轨道交通可达性与居民交通行为转变的关系,并尝试解决自选择问题。
3.2 多元回归分析
为了进一步肯定轨道交通可达性的提高的确促进了城市居民通勤由小汽车转向轨道交通,加入已有研究中常见控制变量,进行多元回归分析。表3的第（1）~第（3）列分别对应家庭是否拥有小汽车、是否使用小汽车或地铁作为主要通勤方式的回归结果。从模型的拟合优度上来看,伪判定系数（Pseudo R2）在0.16左右,表明模型有一定的解释力。Tab. 3
表3
表3居民小汽车拥有及通勤方式的估计结果
Tab. 3Results of regression for car ownership, car user and metro user
| 模型（1） | 模型（2） | 模型（3） | |
|---|---|---|---|
| 是否有小汽车probit | 是否使用小汽车 Heckman | 是否使用地铁probit | |
| 距最近地铁站的距离（ln） | 0.158*** | 0.0665 | -0.221*** |
| (3.01) | (0.80) | (-3.35) | |
| 距最近主/副中心的距离（ln） | 0.0459** | 0.0543* | -0.0160 |
| (2.12) | (1.71) | (-0.79) | |
| 人口密度（ln, 2010） | -0.087 | -0.040 | 0.0091 |
| (-1.01) | (-0.47) | (0.10) | |
| 人均公交站点（ln） | 0.112 | 0.0354 | 0.195* |
| (1.26) | (0.39) | (1.89) | |
| 家庭收入（ln） | 0.165*** | 0.0830 | 0.0422 |
| (4.16) | (0.99) | (1.30) | |
| 2013年房价 | 0.0238** | 0.0228* | 0.0146 |
| (2.44) | (1.73) | (1.22) | |
| 孩子个数 | 0.153* | 0.0034 | -0.166 |
| (1.67) | (0.04) | (-1.44) | |
| 男性 | -0.0535 | 0.215*** | -0.125 |
| (-0.73) | (3.22) | (-1.44) | |
| 年龄 | 0.0105 | 0.0014 | -0.0115 |
| (0.72) | (0.09) | (-0.65) | |
| 高中、中专和专科 | 0.639*** | 0.450 | 0.606** |
| (以初中及以下为对照组) | (4.74) | (1.54) | (2.15) |
| 本科及以上 | 1.003*** | 0.643 | 0.723** |
| (以初中及以下为对照组) | (6.79) | (1.44) | (2.55) |
| 已婚 | 0.790*** | 0.583 | -0.0741 |
| (7.62) | (1.42) | (-0.61) | |
| 有上海户口 | 0.521*** | 0.460 | -0.049 |
| (4.35) | (1.42) | (-0.34) | |
| 有非农户口 | -0.0205 | -0.00295 | 0.214 |
| (-0.20) | (-0.03) | (1.43) | |
| 常数 | -5.408*** | -6.463 | -0.480 |
| (-4.97) | (-1.38) | (-0.39) | |
| lambda | 0.860 | ||
| (1.32) | |||
| Number of obs /Uncensored obs | 1535 | 1422/452 | 1215 |
| Log likelihood | -839.7 | - | -589.1 |
| Pseudo R2 | 0.169 | - | 0.163 |
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本文重点关注的核心变量（距最近地铁站点的距离）在家庭是否拥有小汽车的模型中的确显著为正。这说明随着距最近地铁站的距离的增加,轨道交通的可达性变差,家庭购买小汽车的概率显著提高。出乎意料的是,在是否使用小汽车作为最主要通勤方式的回归中,虽然距最近地铁站点的距离的系数的符号仍与预期一致为正,但并不显著。也就是说,提高轨道交通的可达性,在统计意义上并不会减少小汽车的使用。这可能是由于小汽车的拥有者很有可能形成了采用小汽车通勤的习惯,尽管存在可替代的、高效且舒适的通勤方式,也很难打破这种路径依赖。因此,在68%的没有小汽车家庭中如何引导其形成采用轨道交通出行的习惯显得尤为重要。而在是否使用地铁作为最主要通勤方式的回归结果中,核心变量符号显著为负,所得结果与预期一致。换而言之,距最近地铁站的距离越近,轨道交通可达性越高,居民更倾向选择使用地铁通勤。
虽然上述结果已经进一步排除了受已控制的街道或镇、个人、家庭特征的影响而发生改变的可能性,但不可避免地由于居民出行态度与偏好存在自选择偏误。而这种自选择偏误最有可能会导致回归系数趋近于0并导致显著性水平下降。根据表3,距最近地铁站点的距离增加2.72 m（exp(1)）,拥有小汽车的概率增加17%（exp(0.158)-1）,使用轨道交通的概率减少20%（exp(-0.221)-1）,且均在1%显著水平上通过检验。本文距最近地铁站的平均距离为1.48 km,这实际上为自选择偏误预留了较为充分空间,自选择问题基本不会导致本文基本结论发生根本性变化。
其他控制变量的结果与已有研究基本一致。在街道或镇特征方面,距最近主/副中心的距离越远,居民购买和使用小汽车的概率均越大,这就暗示了居住郊区化很有可能最终形成以小汽车主导的城市蔓延式发展模式。在个体和家庭特征方面,家庭财富、孩子个数、结婚、教育和上海户口对小汽车拥有均是正向影响,且男性更倾向选择小汽车通勤。需要说明的是,在回归结果中发现高的受教育程度既促进了小汽车的购买,也同时鼓励了居民选择地铁出行,这种结果并不矛盾。受教育程度一方面反映个人文化水平的高低,进而影响环保意识的强弱,故受教育程度高的人群会倾向选择轨道交通上下班;另一方面教育在一定程度上也是个人财富的表征,即收入越高的群体越有能力负担起长时间的教育投资,这部分群体同时也更有可能购买小汽车。与已有研究略有差异的是,年龄变量在3个模型中均不显著。这主要是由于本文的分析主要是针对80后,即年龄主要为24~33岁之间的人群,年龄的变异有限,故在统计上没有发现显著影响,但这并不影响本文的基本结论。
综上所述,在其他条件一致的情况下,轨道交通可达性的提高能显著降低小汽车拥有的概率,并提高使用地铁通勤的可能性;没有发现轨道交通可达性对小汽车使用强度的显著影响。虽然该结果存在自选择偏误,但已经进一步排除了受已控制的街道或镇、个人、家庭特征的影响而发生改变的可能性。
3.3 自选择问题
为检验上述实证发现的稳健性,本文尝试采用上文介绍的两种方案来解决轨道交通可达性和交通行为之间的自选择问题。表4中,前三列为方案一回归结果,即在最近地铁站运营10年前就已经在其附近买房的样本;后三列为方案二结果,即住房类型是拆迁安置房、房改房、单位福利分房和单位集资房的样本。整体而言,表4的回归结果在显著性水平上较表3有较大程度的下降,这表明在本文的研究中确实可能存在自选择效应。Tab.4
表4
表4居民小汽车拥有及通勤方式子样本的估计结果
Tab.4Results of regression for car ownership, car user and metro user in subsamples
| 方案一 | 方案二 | |||||
|---|---|---|---|---|---|---|
| （1） | （2） | （3） | （4） | （5） | （6） | |
| 是否拥有小汽车probit | 是否使用小汽车Heckman | 是否使用地铁probit | 是否拥有小汽车probit | 是否使用小汽车Heckman | 是否使用地铁probit | |
| 距最近地铁站的距离（ln） | 0.300* | 0.264 | 0.0263 | 0.278** | -0.0284 | -0.229* |
| （1.77） | （0.41） | （0.14） | （1.99） | （-0.08） | （-1.65） | |
| 其他控制变量 | 控制 | 控制 | 控制 | 控制 | 控制 | 控制 |
| lambda | 1.935 | -0.864 | ||||
| （0.79） | （-0.58） | |||||
| Number of obs /Uncensored obs | 206 | 197/59 | 169 | 394 | 367/68 | 311 |
| Log likelihood | -93.92 | - | -87.37 | -156.6 | - | -193.9 |
| Pseudo R2 | 0.281 | - | 0.141 | 0.281 | - | 0.059 |
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在表4的回归结果中,距最近地铁站的距离这个核心变量对小汽车拥有的作用,在显著性水平上有所下降,但仍是正向的促进作用。对于小汽车的使用来说,距离地铁站的远近仍没有显著影响。另外对于是否使用地铁作为主要的通勤方式,在购房选址滞后10年的子样本回归中,距最近地铁站的距离这个变量不再显著。本文猜测这可能是由于样本量太少,只有169个样本的微观回归分析很难支撑得出有效的结论。必须要承认的是,这两种处理自选择的方案所涉及的样本量是总样本的11%~26%左右,样本量略显不足,并没有直接检验自选择问题在整体样本中的影响。但总体而言,克服自选择问题后的子样本回归基本支持上述基于全样本的实证结论,即居民居住区周边轨道交通可达性的提高,确实能够显著降低家庭的小汽车购买的可能性,并提高乘坐地铁通勤的概率;对于已经拥有小汽车的家庭而言,本文没有发现轨道交通可达性对小汽车使用的影响。
4 结论与讨论
轨道交通被认为是解决当前城市交通拥堵及其衍生的环境污染问题的有效措施,且有助于形成紧凑的城市空间结构。而评估轨道交通建设重要的一环就是,判断轨道交通可达性的提高是否真的能促进居民交通行为转变,尤其是减轻对小汽车的依赖。基于2013年上海市80后群体的微观调查数据,本文考察了轨道交通可达性的提高是否促进了城市居民通勤方式由小汽车转向轨道交通。通过描述性统计分析,构建居民小汽车购买、使用以及轨道交通使用的估计模型,并进一步地克服轨道交通可达性与交通行为之间的自选择。本文发现：居民居住区周边轨道交通可达性的提高,确实能够显著降低家庭的小汽车购买概率,并提高乘坐地铁通勤的可能性;未能找到提高轨道交通可达性对减少小汽车使用的证据。本文证明了轨道交通可达性的提高确实能带来居民交通行为的转变。整体而言,轨道交通可达性的提高有利于实现对路面私人出行方式尤其是小汽车的替代,有显著的交通缓解和污染减排效应,并且促进以轨道交通为导向的紧凑式城市空间结构的形成,因此发展轨道交通是缓解交通拥堵、减轻环境污染和城市蔓延的一种有效的思路。尤其需要注意的是,对于已经拥有小汽车的家庭来说,轨道交通可达性并没有显著地减少小汽车的使用,高效舒适的轨道交通没有成为居民通勤的主要选择,这很有可能是具有很强路径依赖性的通勤习惯所引起的,因此在中国成为“汽车王国”之前,引导轨道交通出行十分必要。另外,本文还在一定程度上回答了交通转移效应和交通创造的理论之争,并尝试解决了建成环境和交通行为的实证研究中一直被诟病的自选择问题。
本文也存在一些不足。受数据可得性限制,本文的研究对象是上海市的80后,虽然对这个群体进行分析有一定的代表性,但本文所得结论在完整年龄层的有效性仍待检验。另外,影响交通行为发生转变或维持现状的机制尚不清晰,这也是未来值得深入研究的方向。
The authors have declared that no competing interests exist.
参考文献 原文顺序
文献年度倒序
文中引用次数倒序
被引期刊影响因子
| [1] | . 根据2007年北京市居民活动日志调查数据,利用Amos7.0软件建立单效标因素的路径分析模型,试图在"社区-家庭"层面上挖掘"空间利用-出行特征-碳排放"的内在发生机理,藉此寻找城市空间组织低碳化的调控路径。研究发现:影响居民家庭日常出行碳排放的主要因素是出行距离和出行方式。社区空间利用特征对家庭出行的距离总量有显著影响,对小汽车出行比率则没有明显作用效果;私家车的购置对居民家庭出行行为的高碳化具有不可逆的作用特点;在现有设施条件、空间环境和车辆使用政策下,公共交通对私人交通出行没有替代性。研究认为,城市空间组织和调控优化应通过土地混合利用、设施供给等物质空间组织与再组织手段,形成空间行为组织和行为规划策略,引导居民降低交通发生量,优化居民交通发生的时空结构,建构低碳的城市空间结构。 根据2007年北京市居民活动日志调查数据,利用Amos7.0软件建立单效标因素的路径分析模型,试图在"社区-家庭"层面上挖掘"空间利用-出行特征-碳排放"的内在发生机理,藉此寻找城市空间组织低碳化的调控路径。研究发现:影响居民家庭日常出行碳排放的主要因素是出行距离和出行方式。社区空间利用特征对家庭出行的距离总量有显著影响,对小汽车出行比率则没有明显作用效果;私家车的购置对居民家庭出行行为的高碳化具有不可逆的作用特点;在现有设施条件、空间环境和车辆使用政策下,公共交通对私人交通出行没有替代性。研究认为,城市空间组织和调控优化应通过土地混合利用、设施供给等物质空间组织与再组织手段,形成空间行为组织和行为规划策略,引导居民降低交通发生量,优化居民交通发生的时空结构,建构低碳的城市空间结构。 |
| [2] | . <p>中国高能耗的经济增长模式和不生态的城镇化模式是PM<sub>2.5</sub>污染的主要诱因,为了弄清PM<sub>2.5</sub>的本质,着重研究PM<sub>2.5</sub>污染的产出机理与模型。首先用逐步回归分析法,确定对PM<sub>2.5</sub>影响较大的变量,再对PM<sub>2.5</sub>及其相关变量进行空间相关分析,在GIS技术与空间统计学的支持下,建立中国区域性细颗粒物空气污染评估模型。结果表明：中国PM<sub>2.5</sub>污染具有东高西低的区域差异特点,这与中国人口分布密度特征曲线（胡焕庸线）所划分出的人口空间分布特点相一致。考虑了空间效应影响的模型拟合度（<i>R</i><sup>2</sup>=0.71）优于传统统计模型（<i>R</i><sup>2</sup>=0.62）。PM<sub>2.5</sub>与总人口、人均汽车保有量的平方、第二产值比例的平方成正比,与森林覆盖率的平方成反比,其中对PM<sub>2.5</sub>贡献率最大的是人均汽车保有量。</p> <p>中国高能耗的经济增长模式和不生态的城镇化模式是PM<sub>2.5</sub>污染的主要诱因,为了弄清PM<sub>2.5</sub>的本质,着重研究PM<sub>2.5</sub>污染的产出机理与模型。首先用逐步回归分析法,确定对PM<sub>2.5</sub>影响较大的变量,再对PM<sub>2.5</sub>及其相关变量进行空间相关分析,在GIS技术与空间统计学的支持下,建立中国区域性细颗粒物空气污染评估模型。结果表明：中国PM<sub>2.5</sub>污染具有东高西低的区域差异特点,这与中国人口分布密度特征曲线（胡焕庸线）所划分出的人口空间分布特点相一致。考虑了空间效应影响的模型拟合度（<i>R</i><sup>2</sup>=0.71）优于传统统计模型（<i>R</i><sup>2</sup>=0.62）。PM<sub>2.5</sub>与总人口、人均汽车保有量的平方、第二产值比例的平方成正比,与森林覆盖率的平方成反比,其中对PM<sub>2.5</sub>贡献率最大的是人均汽车保有量。</p> |
| [3] | This paper examines peak-hour traffic congestion and the nature of its relationship to traffic equilibrium theory as supported by Down's Law of Peak-Hour Traffic Congestion. This Law states that on urban commuter expressways, peak-hour traffic congestion rises to meet maximum capacity. A complex set of forces lie behind this Law, which are analyzed by presentation of a model of commuter decision-making and its underlying set of assumptions. Traffic equilibrium is further discussed and illustrated through 3 commuting scenarios or cases: 1) a city with automobile-driving commuters only; 2) a city with both automobile-driving and bus-riding commuters; and 3) a city with segregated track public transit and automobile-driving commuters. |
| [4] | No abstract is available for this item. |
| [5] | There is a growing interest in exploring the relationships between the built environment and auto ownership and a number of studies have investigated the impact of rail transit on travel behaviour. However, few have disentangled the impact of rail transit on auto ownership from the influences of the built environment and residential self-selection. Using the light rail transit (LRT) in the Minneapolis-St. Paul metropolitan area, USA, this study applies the statistical control approach and quasi-longitudinal design to examine the effects of LRT, neighbourhood design and self-selection on auto ownership. It is found that residential self-selection influences auto ownership; backyard size, off-street parking and business density marginally affect auto ownership; and the LRT does not have an independent impact on auto ownership beyond neighbourhood design and self-selection. The results point to the importance of neighbourhood design in rail transit development. |
| [6] | This paper attempts to determine whether the provision of good, inexpensive public transportation can discourage the purchase of a car. Many previous studies have suggested that traffic demand management measures designed to make public transport more attractive have little impact on car ownership and use, however, much of the work on this subject relates to piecemeal changes in public transport provision. This paper presents an attitudinal survey of 389 university students in Hong Kong, where public transport is both plentiful and inexpensive, and car ownership and use is extremely low. Results indicate that good public transportation can deter car ownership, with 65% of respondents stating that they are unlikely to buy a car in the next five years. Nearly 40% of respondents agreed with the statement that public transportation was so good that they did not need a car. However, among male students, there did appear to be a substantial latent demand for a car and favorable attitude towards car ownership. Overall results from this study suggest that individual traffic demand measures, especially when public transport is perceived to be of poor quality, may have little impact on mode choice because such measures are not sufficient in scale to have an impact on the choice decisions. |
| [7] | This study develops econometric models to predict the effect of access to and distance to public transit on automobile ownership and miles driven. Ordered logit model is used for automobile ownership and multiple regression model is used for vehicle miles traveled (VMT).Inverse square root of transit distance is used as a measure for transit accessibility. Important findings in the analysis are (i) the number of licensed drivers is the primary determinant of the number of automobiles owned, (ii) the presence of children is not a significant factor in automobile ownership and VMT, and (iii) the VMT of multi-vehicle households is more sensitive to transit than one-vehicle households. Transit simulations are performed by improving the distance to and access to public transit. The results showed that total VMT in National Ambient Air Quality Standard non-attained metropolitan statistical area is reduced by 11% (approximately 60 billion miles) with 0.1 miles simulation. |
| [8] | The causal structure underlying household mobility is examined in this study using a sample obtained from the Dutch National Mobility Panel survey. The results indicate that car ownership is strongly associated with mode use, but that it has no influence on weekly person trip generation by household members. Characteristics of mode use are examined through a causal analysis of changes in car ownership, number of drivers, number of car trips, and number of transit trips. It is shown that observed changes in mode use cannot be adequately explained by assuming that a change in transit use influences car use. The finding suggests that the increase in car use, which is a consequence of increasing car ownership, may not be suppressed by improving public transit. |
| [9] | In many developing countries, massive investment in transit infrastructure is concurrent with the proliferation of automobiles. Planners expect that investment can slow the growth of auto ownership. However, few studies have examined the relationships between transit access and auto ownership in developing countries, whereas research in developed countries offers mixed findings and the outcomes may not be applicable to developing countries. This study employs a random effect ordered probit model on data collected from Guangzhou residents in 2011--2012. We find that transit access is negatively associated with auto ownership, after controlling for demographics and other built environment variables. This result suggests that, although income is the dominant driver for auto ownership in growing developing countries, transit investment is a promising strategy to slow the growth of auto ownership. This study also highlights the importance of addressing spatial dependency in clustered data. |
| [10] | Bus Rapid Transit (BRT) has become popular as a means to provide non-automobile-based mobility and alleviate the impacts of rising traffic congestion in cities around the world. However, there is little empirical evidence supporting BRT’s potential to meet these objectives. This research improves our knowledge of BRT’s potential as an alternative to vehicle ownership at the household level and provides new evidence of the role of urban form in supporting transit investment. We use a difference-in-differences research design to examine the change in vehicle ownership from before to after implementation of Bogotá, Colombia’s TransMilenio BRT system. Our results indicate access to TransMilenio’s main trunk system is significantly and negatively associated with vehicle ownership for higher wealth households. Among lower wealth households, access to the trunk system and the complementary feeder system (designed to bring passengers from peripheral neighborhoods into the main trunk system) are both associated with an unexpected increase in the odds of vehicle ownership; however, that increase appears to be reversed in neighborhoods where the built environment supports transit and non-motorized travel. This research contributes a methodology for joint analysis of urban form and transit availability on vehicle ownership, and demonstrates that urban form and transit access can have a synergistic effect. Neglecting this synergy would be a missed opportunity to further leverage the benefits of BRT investments. Our findings also suggest that, in the case of Bogotá, the vehicle ownership impacts of BRT investment may not accrue to lower income households unless that investment is coordinated with policies to promote supportive urban form. |
| [11] | . |
| [12] | Numerous studies have found that suburban residents drive more and walk less than residents in traditional neighborhoods. What is less well understood is the extent to which the observed patterns of travel behavior can be attributed to the residential built environment (BE) itself, as opposed to attitude-induced residential self-selection. To date, most studies addressing this self-selection issue fall into nine methodological categories: direct questioning, statistical control, instrumental variables, sample selection, propensity score, joint discrete choice models, structural equations models, mutually dependent discrete choice models and longitudinal designs. This paper reviews 38 empirical studies using these approaches. Virtually all of the studies reviewed found a statistically significant influence of the BE remaining after self-selection was accounted for. However, the practical importance of that influence was seldom assessed. Although time and resource limitations are recognized, we recommend usage of longitudinal structural equations modeling with control groups, a design which is strong with respect to all causality requisites. |
| [13] | Empirical studies that include travel‐related attitudes to identify the role of residential self‐selection in the relationship between the built environment and travel behaviour display a wide variety in the type of attitudes that they include, the relationships between the variables that they analyse and the ways they measure attitude. This paper discusses what theories on attitudes and behaviour can contribute to examining the role of self‐selection and reviews those studies on residential self‐selection and travel behaviour that explicitly include attitudes. Although several studies state that residential self‐selection is accounted for by the inclusion of attitudes, the complexity of the inclusion and the measurement of attitudes often leads to an underestimation of the role of residential self‐selection. Because of their relevance to the reliability of results, the options for measuring travel‐related attitudes are also discussed. When attitudes are included in questionnaires, it is essential to consider reliability, efficiency, response and the number of variables. |
| [14] | . 西方国家各级政府已经采用各种土地利用和交通政策来抑制蔓延式发展的负面效应。西方规划和交通****通过分析建成环境和交通行为的关系来评价这些政策的作用,并取得了丰硕的成果。这对西方国家的规划实践具有重要的指导意义。中国近年的城市发展已经呈现出美国的蔓延式发展特征。它的负面效应也逐渐显现出来。然而,由于中国建成环境和交通行为的研究起步较晚,很多方面亟待学习和发展。本文主要以美国的研究进程为例,回顾了建成环境和交通行为研究理念、方法和理论基础的演变,总结了以往的研究问题和成果,并结合中国的实际对学术前沿的热点问题进行展望。 西方国家各级政府已经采用各种土地利用和交通政策来抑制蔓延式发展的负面效应。西方规划和交通****通过分析建成环境和交通行为的关系来评价这些政策的作用,并取得了丰硕的成果。这对西方国家的规划实践具有重要的指导意义。中国近年的城市发展已经呈现出美国的蔓延式发展特征。它的负面效应也逐渐显现出来。然而,由于中国建成环境和交通行为的研究起步较晚,很多方面亟待学习和发展。本文主要以美国的研究进程为例,回顾了建成环境和交通行为研究理念、方法和理论基础的演变,总结了以往的研究问题和成果,并结合中国的实际对学术前沿的热点问题进行展望。 |
| [15] | Abstract The potential to moderate travel demand through changes in the built environment is the subject of more than 50 recent empirical studies. The majority of recent studies are summarized. Elasticities of travel demand with respect to density, diversity, design, and regional accessibility are then derived from selected studies. These elasticity values may be useful in travel forecasting and sketch planning and have already been incorporated into one sketch planning tool, the Environmental Protection Agency's Smart Growth Index model. In weighing the evidence, what can be said, with a degree of certainty, about the effects of built environments on key transportation "outcome" variables: trip frequency, trip length, mode choice, and composite measures of travel demand, vehicle miles traveled (VMT) and vehicle hours traveled (VHT)? Trip frequencies have attracted considerable academic interest of late. They appear to be primarily a function of socioeconomic characteristics of travelers and secondarily a function of the built environment. Trip lengths have received relatively little attention, which may account for the various degrees of importance attributed to the built environment in recent studies. Trip lengths are primarily a function of the built environment and secondarily a function of socioeconomic characteristics. Mode choices have received the most intensive study over the decades. Mode choices depend on both the built environment and socioeconomics (although they probably depend more on the latter). Studies of overall VMT or VHT find the built environment to be much more significant, a product of the differential trip lengths that factor into calculations of VMT and VHT. |
| [16] | ABSTRACT Problem: Localities and states are turning to land planning and urban design for help in reducing automobile use and related social and environmental costs. The effects of such strategies on travel demand have not been generalized in recent years from the multitude of available studies.Purpose: We conducted a meta-analysis of the built environment-travel literature existing at the end of 2009 in order to draw generalizable conclusions for practice. We aimed to quantify effect sizes, update earlier work, include additional outcome measures, and address the methodological issue of self-selection.Methods: We computed elasticities for individual studies and pooled them to produce weighted averages.Results and conclusions: Travel variables are generally inelastic with respect to change in measures of the built environment. Of the environmental variables considered here, none has a weighted average travel elasticity of absolute magnitude greater than 0.39, and most are much less. Still, the combined effect of several such variables on travel could be quite large. Consistent with prior work, we find that vehicle miles traveled (VMT) is most strongly related to measures of accessibility to destinations and secondarily to street network design variables. Walking is most strongly related to measures of land use diversity, intersection density, and the number of destinations within walking distance. Bus and train use are equally related to proximity to transit and street network design variables, with land use diversity a secondary factor. Surprisingly, we find population and job densities to be only weakly associated with travel behavior once these other variables are controlled.Takeaway for practice: The elasticities we derived in this meta-analysis may be used to adjust outputs of travel or activity models that are otherwise insensitive to variation in the built environment, or be used in sketch planning applications ranging from climate action plans to health impact assessments. However, because sample sizes are small, and very few studies control for residential preferences and attitudes, we cannot say that planners should generalize broadly from our results. While these elasticities are as accurate as currently possible, they should be understood to contain unknown error and have unknown confidence intervals. They provide a base, and as more built-environment/travel studies appear in the planning literature, these elasticities should be updated and refined.Research support: U.S. Environmental Protection Agency. |
| [17] | . 选取中国235 个地级以上城市为样本,研究了1990-2009 年中国城市私人汽车拥有量演变的时空特征,并选取了9 个解释变量,使用1995-2009 年的面板数据,建立面板数据模型量化各影响因素的贡献率,分析各因素对城市私人汽车拥有量的作用机制。研究结果表明:① 中国城市私人汽车的发展呈现出一定的阶段性特点,并具有明显的空间集聚及区域分异特征;② 中国城市私人汽车发展的空间差异呈先增大后缩小的倒“U”形变动轨迹;2000 年后,中国城市私人汽车发展的空间差异出现了地带间趋异而地带内趋同的现象;③ 经济因素是私人汽车拥有量的决定性因素,私人汽车拥有量随人均收入的发展呈现出“S”形增长,城市化水平对私人汽车拥有量具有显著正效应,但对特大及巨大城市却产生了不显著的负效应;④ 城市空间扩张带来的城市规模增加会导致城市私人交通工具使用需求增大,当城市人口规模达到一定的临界值以上后,城市人口密度的增加能抑制私人汽车拥有量的增加;⑤ 城市公共交通及出租车的服务能力对私人汽车的增长有抑制作用,但并不显著,且随着城市规模的扩大,城市公共交通发展对私人汽车增长的抑制作用逐渐增强。 选取中国235 个地级以上城市为样本,研究了1990-2009 年中国城市私人汽车拥有量演变的时空特征,并选取了9 个解释变量,使用1995-2009 年的面板数据,建立面板数据模型量化各影响因素的贡献率,分析各因素对城市私人汽车拥有量的作用机制。研究结果表明:① 中国城市私人汽车的发展呈现出一定的阶段性特点,并具有明显的空间集聚及区域分异特征;② 中国城市私人汽车发展的空间差异呈先增大后缩小的倒“U”形变动轨迹;2000 年后,中国城市私人汽车发展的空间差异出现了地带间趋异而地带内趋同的现象;③ 经济因素是私人汽车拥有量的决定性因素,私人汽车拥有量随人均收入的发展呈现出“S”形增长,城市化水平对私人汽车拥有量具有显著正效应,但对特大及巨大城市却产生了不显著的负效应;④ 城市空间扩张带来的城市规模增加会导致城市私人交通工具使用需求增大,当城市人口规模达到一定的临界值以上后,城市人口密度的增加能抑制私人汽车拥有量的增加;⑤ 城市公共交通及出租车的服务能力对私人汽车的增长有抑制作用,但并不显著,且随着城市规模的扩大,城市公共交通发展对私人汽车增长的抑制作用逐渐增强。 |
| [18] | . 目前，中国城市私人汽车的拥有量高速增长，小汽车不仅日益成为居民日常出行的重要交通方式，更深刻影响着城市的空间结构和道路的拥堵状况。然而，目前国内对汽车使用的研究仍十分匮乏。为此，本文试图基于2011 年11 月到2012 年7 月在北京进行的一项问卷调查数据，分析家庭汽车使用行为的特征、强度及影响因素。描述性统计和（定序Logistic） 回归分析结果显示，汽车使用目的、建成环境和各种家庭/个人社会经济特征对大城市居民的汽车使用强度和依赖度有重要影响。其中，通勤是居民日常使用汽车的主要目的；公共交通条件较差和停车条件便利是促使居民大量使用汽车的重要原因；婚姻状态、工作状态、家庭规模和家庭内持有驾照的成员数等对居民的日常汽车使用也有重要影响；周末与工作日的汽车使用频次或时长没有显著差异。这些发现对道路交通规划和交通政策的制定有重要参考意义。不过，要想更有效地控制汽车使用行为，未来的研究仍有必要增强对因果关系、出行的限制条件和影响交通行为的心理机制等问题的考察。 目前，中国城市私人汽车的拥有量高速增长，小汽车不仅日益成为居民日常出行的重要交通方式，更深刻影响着城市的空间结构和道路的拥堵状况。然而，目前国内对汽车使用的研究仍十分匮乏。为此，本文试图基于2011 年11 月到2012 年7 月在北京进行的一项问卷调查数据，分析家庭汽车使用行为的特征、强度及影响因素。描述性统计和（定序Logistic） 回归分析结果显示，汽车使用目的、建成环境和各种家庭/个人社会经济特征对大城市居民的汽车使用强度和依赖度有重要影响。其中，通勤是居民日常使用汽车的主要目的；公共交通条件较差和停车条件便利是促使居民大量使用汽车的重要原因；婚姻状态、工作状态、家庭规模和家庭内持有驾照的成员数等对居民的日常汽车使用也有重要影响；周末与工作日的汽车使用频次或时长没有显著差异。这些发现对道路交通规划和交通政策的制定有重要参考意义。不过，要想更有效地控制汽车使用行为，未来的研究仍有必要增强对因果关系、出行的限制条件和影响交通行为的心理机制等问题的考察。 |
| [19] | . <p>机动化与郊区化对城市空间结构与社会生活产生了深远的影响,私人汽车已日渐成为中国城市居民日常出行的重要交通工具。汽车所有权与汽车出行快速上升及其所带来的日常行为变化已经成为中西方****共同关注的话题。西方****对机动化与居民活动空间的关系进行了深入的探讨,但是国内这一方面的研究刚刚起步。基于GPS与活动日志相结合的居民一周活动与出行数据,采用GIS空间分析,从非汇总角度对郊区居民的整日活动空间进行测度,分析汽车拥有量与汽车使用对居民整日活动空间的影响。结果表明：机动化对居民活动空间产生深刻影响,家庭汽车所有状况与家庭汽车分配影响个体日常活动空间的分布,活动空间与是否使用小汽车出行具有显著的相关关系。</p> <p>机动化与郊区化对城市空间结构与社会生活产生了深远的影响,私人汽车已日渐成为中国城市居民日常出行的重要交通工具。汽车所有权与汽车出行快速上升及其所带来的日常行为变化已经成为中西方****共同关注的话题。西方****对机动化与居民活动空间的关系进行了深入的探讨,但是国内这一方面的研究刚刚起步。基于GPS与活动日志相结合的居民一周活动与出行数据,采用GIS空间分析,从非汇总角度对郊区居民的整日活动空间进行测度,分析汽车拥有量与汽车使用对居民整日活动空间的影响。结果表明：机动化对居民活动空间产生深刻影响,家庭汽车所有状况与家庭汽车分配影响个体日常活动空间的分布,活动空间与是否使用小汽车出行具有显著的相关关系。</p> |
| [20] | The built environment is thought to influence travel demand along three principal dimensions —density, diversity, and design. This paper tests this proposition by examining how the ‘3Ds’ affect trip rates and mode choice of residents in the San Francisco Bay Area. Using 1990 travel diary data and land-use records obtained from the U.S. census, regional inventories, and field surveys, models are estimated that relate features of the built environment to variations in vehicle miles traveled per household and mode choice, mainly for non-work trips. Factor analysis is used to linearly combine variables into the density and design dimensions of the built environment. The research finds that density, land-use diversity, and pedestrian-oriented designs generally reduce trip rates and encourage non-auto travel in statistically significant ways, though their influences appear to be fairly marginal. Elasticities between variables and factors that capture the 3Ds and various measures of travel demand are generally in the 0.06 to 0.18 range, expressed in absolute terms. Compact development was found to exert the strongest influence on personal business trips. Within-neighborhood retail shops, on the other hand, were most strongly associated with mode choice for work trips. And while a factor capturing ‘walking quality’ was only moderately related to mode choice for non-work trips, those living in neighborhoods with grid-iron street designs and restricted commercial parking were nonetheless found to average significantly less vehicle miles of travel and rely less on single-occupant vehicles for non-work trips. Overall, this research shows that the elasticities between each dimension of the built environment and travel demand are modest to moderate, though certainly not inconsequential. Thus it supports the contention of new urbanists and others that creating more compact, diverse, and pedestrian-orientated neighborhoods, in combination, can meaningfully influence how Americans travel. |
| [21] | . <p>伴随中国快速城市化与机动化进程,私人汽车拥有量不断增长,由此引起的交通拥堵和环境问题已成为制约中国城市可持续发展的难题。基于上海市区的居民通勤问卷调查数据,采用多项Logit模型检验了街道尺度城市建成环境对于居民通勤方式选择的影响,结果表明,在控制了其他因素后,提高居住地的人口密度、土地利用混合度与十字路口比重,可以减少小汽车通勤方式的选择,而就业地建成环境对居民通勤方式选择影响相对较弱;建成环境对通勤方式选择的影响会因个体的社会经济异质性而不同。这些结论为通过优化土地利用规划来优化居民通勤结构的城市交通和城市规划政策提供了启示。</p> <p>伴随中国快速城市化与机动化进程,私人汽车拥有量不断增长,由此引起的交通拥堵和环境问题已成为制约中国城市可持续发展的难题。基于上海市区的居民通勤问卷调查数据,采用多项Logit模型检验了街道尺度城市建成环境对于居民通勤方式选择的影响,结果表明,在控制了其他因素后,提高居住地的人口密度、土地利用混合度与十字路口比重,可以减少小汽车通勤方式的选择,而就业地建成环境对居民通勤方式选择影响相对较弱;建成环境对通勤方式选择的影响会因个体的社会经济异质性而不同。这些结论为通过优化土地利用规划来优化居民通勤结构的城市交通和城市规划政策提供了启示。</p> |
| [22] | . |
| [23] | |
| [24] | |
| [25] | |
| [26] | Residents of dense, mixed-use, transit-accessible neighborhoods use autos less. Recent studies have suggested that this relationship is partly because transit-preferring and walk-preferring households seek and find such neighborhoods. If this is so, and if the number of such households is small, policies to alter the built environment may not influence auto use very much. I argue that many of these studies are inconclusive on methodological grounds, and that more research is needed. A purpose-designed survey of households in two urban regions in California is investigated, with the aid of a new methodological approach. I find that most surveyed households explicitly consider travel access of some kind when choosing a neighborhood, but that this process of residential self-selection does not bias estimates of the effects of the built environment very much. To the extent that it does exert an influence, the bias results both in underestimates and overestimates of the effects of the built environment, contrary to previous research. The analysis not only implies a need for deregulatory approaches to land-use and transportation planning, but also suggests that there may be value in market interventions such as subsidies and new prescriptive regulations. |
| [27] | The academic literature on the impact of urban form on travel behavior has increasingly recognized that residential location choice and travel choices may be interconnected. We contribute to the understanding of this interrelation by studying to what extent commute mode choice differs by residential neighborhood and by neighborhood type dissonance he mismatch between a commuter's current neighborhood type and her preferences regarding physical attributes of the residential neighborhood. Using data from the San Francisco Bay Area, we find that neighborhood type dissonance is statistically significantly associated with commute mode choice: dissonant urban residents are more likely to commute by private vehicle than consonant urbanites but not quite as likely as true suburbanites. However, differences between neighborhoods tend to be larger than between consonant and dissonant residents within a neighborhood. Physical neighborhood structure thus appears to have an autonomous impact on commute mode choice. The analysis also shows that the impact of neighborhood type dissonance interacts with that of commuters' beliefs about automobile use, suggesting that these are to be reckoned with when studying the joint choices of residential location and commute mode. |
| [28] | <a name="Abs1"></a>Suburban development in the US is widely criticized for its contribution to automobile dependence and its consequences. Not surprisingly, then, a return to more urban-style development, where potential destinations are closer to home, is often put forth as a strategy for reducing automobile dependence. This paper evaluates the possibility that providing local shopping opportunities will help to reduce automobile dependence by exploring how residents of existing neighborhoods make use of the local shopping opportunities currently available to them. Using both quantitative and qualitative evidence for six neighborhoods in Austin, TX, we address two sets of questions. First, to what degree do residents choose local shopping over more distant opportunities and why? What are the implications for vehicle travel? Second, to what degree do residents choose to walk rather than drive to local shopping and why? What are the implications for vehicle travel? The results of this exploration suggest that local shopping will not prove a particularly effective strategy for reducing automobile dependence in the typical US city by either reducing travel distances or encouraging alternative modes of travel. Residents of such places choose more distant stores enough of the time that they increase total driving significantly, and they don't choose alternative modes enough of the time that they reduce total driving significantly. But while local shopping may not do much to reduce driving it does give residents the option to drive less and this option is something residents clearly value. Local shopping does not show great promise as a strategy for reducing automobile use, but it does show promise as a strategy for enhancing quality of life in neighborhoods, at least partly by making driving once again a matter of choice. |
| [29] | Using a system of structural equations, this paper empirically examines the relationship of residential neighborhood type to travel behavior, incorporating attitudinal, lifestyle, and demographic variables. Data on these variables were collected from residents of five neighborhoods in the San Francisco Bay Area in 1993 (final N = 515), including "traditional" and "suburban" as well as mixtures of those two extremes. A conceptual model of the interrelationships among the key variables of interest was operationalized with a nine-equation structural model system. The nine endogenous variables included two measures of residential location type, three measures of travel demand, three attitudinal measures, and one measure of job location. In terms of both direct and total effects, attitudinal and lifestyle variables had the greatest impact on travel demand among all the explanatory variables. By contrast, residential location type had little impact on travel behavior. This is perhaps the strongest evidence to date supporting the speculation that the association commonly observed between land use configuration and travel patterns is not one of direct causality, but due primarily to correlations of each of those variables with others. In particular, the results suggest that when attitudinal, lifestyle, and sociodemographic variables are accounted for, neighborhood type has little influence on travel behavior. |
| [30] | <a name="Abs1"></a>This contribution presents theoretical considerations concerning the connections between life situation, lifestyle, choice of residential location and travel behaviour, as well as empirical results of structural equation models. The analyses are based on data resulting from a survey in seven study areas in the region of Cologne. The results indicate that lifestyles influence mode choice, although slightly, even when life situation is controlled for. The influence of life situation on mode choice exceeds the influence of lifestyle. The influence that lifestyle, and in part also life situation, has on mode choice is primarily mediated by specific location attitudes and location decisions that influence mode choice, respectively. Here objective spatial conditions as well as subjective location attitudes are important. |
| [31] | ABSTRACT The issue of self-selection's role in shaping travel patterns, by impacting one's home location choice, is a critical question. Developers, planners and policymakers regularly debate to what extent the built environment and land use patterns can alleviate roadway congestion, greenhouse gas emissions and myriad other urban problems. This study illustrates the use of Heckman's (1976, 1979) latent index model to ascertain travel impacts of neighborhood type in Austin, Texas. Under this approach, self-selection is formulated as sample selection bias in receiving a treatment. Here, treatment is defined to be one's residence in a suburban or rural zone, rather than Austin's central business district and nearby urban zones. This treatment/no-treatment approach is a meaningful advance in models of self-selection effects, and requires estimation of three straightforward models. Model results suggest that the great majority (90%) of differences in vehicle-miles-traveled between central/CBD and suburban/rural locations is due to the treatment itself, rather than self-selection of such treatment (by households that wish to meet special travel needs). |
| [32] | Transit oriented development is shown to produce an appreciable ridership bonus in California. This is partly due to residential self-selection 09“ i.e., a life-style preference for transit-oriented living 09“ as well as factors like employer-based policies that reduce free parking and automobile subsidies. Half-mile catchments of station areas appear to be indifference zones in the sense that residents generally ride transit regardless of local urban design attributes. Out-of-neighborhood attributes, like job accessibility and street connectivity at the destination, on the other hand, have a significant bearing on transit usage among station-area residents. The presence of self-selection, shown using nested logit modeling, underscores the importance of removing barriers to residential mobility so that households are able to sort themselves, via the marketplace, to locations wellserved by transit. Market-responsive zoning, flexible residential parking policies, location efficient mortgages, and adaptive re-use of parking lots are also promising tools for expanding the supply of transit-based housing. |
| [33] | There has been an increasing interest in the land use-transportation connection in the past decade, motivated by the possibility that design policies associated with the built environment can be used to control, manage, and shape individual traveler behavior and aggregate travel demand. In this line of research and application pursuit, it is critical to understand whether the empirically observed association between the built environment and travel behavior-related variables is a true reflection of underlying causality or simply a spurious correlation attributable to the intervening relationship between the built environment and the characteristics of people who choose to live in particular built environments. In this research paper, we identify the research designs and methodologies that may be used to test the presence of "true" causality versus residential sorting-based "spurious" associations in the land-use transportation connection. The paper then develops a methodological formulation to control for residential sorting effects in the analysis of the effect of built environment attributes on travel behavior-related choices. The formulation is applied to comprehensively examine the impact of the built environment, transportation network attributes, and demographic characteristics on residential choice and car ownership decisions. The model formulation takes the form of a joint mixed multinomial logit-ordered response structure that (a) accommodates differential sensitivity to the built environment and transportation network variables due to both demographic and unobserved household attributes and (b) controls for the self-selection of individuals into neighborhoods based on car ownership preferences stemming from both demographic characteristics and unobserved household factors. The analysis in the paper represents, to our knowledge, the first instance of the formulation and application of a unified mixed multinomial logit-ordered response structure in the econometric literature. The empirical analysis in the paper is based on the residential choice and car ownership decisions of San Francisco Bay area residents. |
| [34] | <a name="Abs1"></a>This paper presents an examination of the significance of residential sorting or self selection effects in understanding the impacts of the built environment on travel choices. Land use and transportation system attributes are often treated as exogenous variables in models of travel behavior. Such models ignore the potential self selection processes that may be at play wherein households and individuals choose to locate in areas or built environments that are consistent with their lifestyle and transportation preferences, attitudes, and values. In this paper, a simultaneous model of residential location choice and commute mode choice that accounts for both observed and unobserved taste variations that may contribute to residential self selection is estimated on a survey sample extracted from the 2000 San Francisco Bay Area household travel survey. Model results show that both observed and unobserved residential self selection effects do exist; however, even after accounting for these effects, it is found that built environment attributes can indeed significantly impact commute mode choice behavior. The paper concludes with a discussion of the implications of the model findings for policy planning. |
| [35] | Although previous research has supported the view that neo-traditional or new urbanist designs result in more walking activity, several questions remain: Do residents of these neighborhoods substitute walking for driving trips, or do they make more trips overall? What is the role of self-selection of residents in these developments? This paper aims to address these questions by examining differences in travel behavior in a matched pair of neighborhoods (one conventional and one neo-traditional) in Chapel Hill and Carrboro, North Carolina. A detailed behavioral survey of 453 households and two-stage regression models suggest that single-family households in the neo-traditional development make a similar number of total trips, but significantly fewer automobile trips and fewer external trips, and they travel fewer miles, than households in the conventional neighborhood, even after controlling for demographic characteristics of the households and for resident self-selection. The findings suggest that households in the neo-traditional development substitute driving trips with walking trips. |
| [36] | Transportation and urban planners are increasingly viewing land-use policy as a way to manage travel demand. Yet the evidence on the link between land use and travel behavior is inconclusive. This paper uses travel diary data for southern California residents to examine the link between land-use patterns at the neighborhood level and non-work trip generation for a sample of individuals. The number of non-work automobile trips that an individual makes in a specified period is modeled as a function of sociodemographic variables and land-use characteristics relative to the person's place of residence. Findings suggest the importance of both controlling for residential location choice and using different levels of geographic detail when studying the link between land use and travel behavior. |
