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<p><br  /></p><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.25" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmyCWLOIYOoZFf8abibcEA2XzMRwqQx2MY6QQn3k7icrX2xRgvia5aleiaIRA/640?wx_fmt=jpeg" data-type="jpeg" data-w="1000" style=""  /></p><p><br  /></p><section><section style="display: inline-block;width: 100%;vertical-align: top;padding-left: 5px;letter-spacing: 0px;box-shadow: rgb(0, 0, 0) 0px 0px 0px;box-sizing: border-box;" powered-by="gulangu"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;box-sizing: border-box;"><section style="display: inline-block;vertical-align: bottom;width: auto;align-self: flex-end;flex: 0 0 0%;height: auto;box-sizing: border-box;"><section style="text-align: left;font-size: 0px;margin-right: 0%;margin-left: 0%;justify-content: flex-start;transform: translate3d(-5px, 0px, 0px);box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 10px;height: 10px;vertical-align: top;overflow: hidden;border-width: 2px;border-radius: 50%;border-style: solid;border-color: rgb(255, 172, 63);background-color: rgb(234, 44, 44);box-sizing: border-box;"><br  /></section></section></section><section style="display: inline-block;vertical-align: bottom;width: auto;align-self: flex-end;min-width: 10%;max-width: 100%;flex: 0 0 auto;height: auto;background-color: rgba(255, 172, 63, 0.23);box-sizing: border-box;"><section style="color: rgb(204, 17, 17);padding-right: 10px;padding-left: 10px;box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">摘 要</strong></p></section></section></section></section><section style="display: inline-block;width: 100%;vertical-align: top;border-left: 1px dashed rgb(204, 17, 17);border-bottom-left-radius: 0px;box-sizing: border-box;" powered-by="gulangu"><section style="margin: 10px 0%;box-sizing: border-box;" powered-by="gulangu"><section style="padding-right: 15px;padding-left: 15px;line-height: 1.8;letter-spacing: 1.8px;font-size: 15px;box-sizing: border-box;"><p style="white-space: normal;box-sizing: border-box;">研究基于LBS/手机信令大数据对城市交通现状进行实证分析，进而对规划方案进行情景模拟评价。对交通现状的分析，主要包括居民出行特征分析、机动车（道路）运行特征分析、空间职住特征（职住平衡度）分析等几个方面。其中，对居民出行特征的分析，包括了手机大数据和传统居民出行调查数据的校核与互补。空间职住特征分析主要通过职住空间关联的动态OD来反映城市空间结构的内在关系。对规划方案的评价，主要研究了在大数据现状分析的基础上，情景模拟评价方法在城市规划空间方案制定过程中的探索应用。也包括桥梁、隧道等重要交通基础设施的选择以及特殊城市如旅游城市的特色分析等。以期在规划中，对城市交通出行方式划分、交通大通道战略制定、城市空间结构的确定等多个方面提供参考与技术支撑。研究尚处于探索阶段，一些初步结论可能还存在有待商榷之处，未来从理论建设到项目应用还需更多实践。</p></section></section></section></section><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;vertical-align: top;padding-left: 5px;letter-spacing: 0px;box-sizing: border-box;"><section style="display: inline-block;width: 100%;vertical-align: top;border-left: 1px dashed rgb(204, 17, 17);border-bottom-left-radius: 0px;box-sizing: border-box;" powered-by="gulangu"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;margin-top: 10px;margin-right: 0%;margin-left: 0%;box-sizing: border-box;"><section style="display: inline-block;vertical-align: bottom;width: auto;align-self: flex-end;flex: 0 0 0%;height: auto;box-sizing: border-box;"><section style="text-align: left;font-size: 0px;margin-right: 0%;margin-left: 0%;justify-content: flex-start;transform: translate3d(-5px, 0px, 0px);box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 10px;height: 10px;vertical-align: top;overflow: hidden;border-width: 2px;border-radius: 50%;border-style: solid;border-color: rgb(255, 172, 63);background-color: rgb(234, 44, 44);box-sizing: border-box;"><br  /></section></section></section><section style="display: inline-block;vertical-align: bottom;width: auto;align-self: flex-end;min-width: 10%;max-width: 100%;flex: 0 0 auto;height: auto;background-color: rgba(255, 172, 63, 0.23);box-sizing: border-box;"><section style="color: rgb(204, 17, 17);padding-right: 10px;padding-left: 10px;box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">关 键 词</strong></p></section></section></section></section><section style="margin: 10px 0%;box-sizing: border-box;" powered-by="gulangu"><section style="padding-right: 15px;padding-left: 15px;line-height: 1.8;letter-spacing: 1.8px;font-size: 15px;box-sizing: border-box;"><p style="white-space: normal;box-sizing: border-box;">交通分析与评价 LBS/手机信令大数据 职住平衡度 交通模式 情景模拟</p></section></section></section></section></section><section style="box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><br style="box-sizing: border-box;"  /></p><p style="text-indent: 28px;line-height: 125%;"><br  /></p><section style="text-indent: 2em;"><span style="font-size: 16px;">大数据时代的到来为城市交通规划带来新一轮的技术革新。本文中所指手机大数据主要包括两类：其一，LBS（Location-Based Service）数据，即手机APP数据。这类数据采集原理包括：周期更新，登陆APP后，后台上报SDK平台，频率最大可达15分钟/次,不登陆APP无法截取；及时事件，用户登陆、操作、发送信息，或APP自动推送消息、更新等事件将被即时上报SDK平台。其二，手机信令数据。该数据又主要包括三类，即话单数据、PS域信令数据和CS域信令数据。话单数据信令是只有当用户拨打或接听电话、发送或接收短信时才可以触发信令；CS域信令则是指BSC（基站）切换、位置更新、开关机和位置区切换等信令；PS域信令增添了上网信令，受智能手机与4G网络影响，PS域的数据量大幅度增长。</span></section><p style="white-space: normal;box-sizing: border-box;"><br  /></p><section style="text-indent: 2em;"><span style="font-size: 16px;">尽管数据源不同，但两类数据经过数据筛选处理之后，主要都是以计算得到的OD数据形式应用于城市交通分析与评价上，因此本文研究内容，不涉及数据获取前端的分析，即不对比讨论两类大数据的优缺点，重点在于手机大数据的后端应用。研究内容主要包括两大版块：其一，基于手机大数据的城市交通现状分析；其二，基于现状分析的规划模拟评价研究。</span></section><section style="text-indent: 2em;"><br  /></section></section><section style="text-align: center;justify-content: center;margin: 16px 0% 10px;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: auto;vertical-align: top;min-width: 10%;max-width: 100%;height: auto;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;box-sizing: border-box;"><section style="display: inline-block;vertical-align: top;width: auto;align-self: flex-start;flex: 4.1445 4.1445 0%;margin-top: -8px;height: auto;border-width: 0px;z-index: 1;border-style: solid;border-radius: 0px;border-color: rgb(62, 62, 62);box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 30px;height: 30px;vertical-align: top;overflow: hidden;border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 172, 63);background-color: rgb(255, 255, 255);box-sizing: border-box;"><section style="text-align: justify;color: rgb(234, 44, 44);box-sizing: border-box;" powered-by="gulangu"><p style="text-align: center;white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">1</strong></p></section></section></section></section><section style="display: inline-block;vertical-align: middle;width: auto;align-self: center;background-color: rgb(255, 255, 255);margin-left: -12px;flex: 100 100 0%;height: auto;z-index: auto;padding: 5px 8px 5px 20px;border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 172, 63);box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="color: rgb(234, 44, 44);letter-spacing: 2px;box-sizing: border-box;"><p style="text-align: justify;white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">基于手机大数据的城市交通现状分析</strong></p></section></section></section></section></section></section></section><section style="box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><br style="box-sizing: border-box;"  /></p><section style="text-indent: 2em;"><span style="font-size: 16px;">现状分析包括居民出行特别分析、机动车（道路）运行特征分析、空间职住特征分析（职住平衡度）三部分内容。</span></section><section style="text-indent: 2em;"><br  /></section></section><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;margin: 10px 0%;box-sizing: border-box;"><section style="display: inline-block;vertical-align: middle;width: auto;border-style: none;border-width: 1px;border-radius: 0px;border-color: rgb(62, 62, 62);min-width: 10%;max-width: 100%;flex: 0 0 auto;height: auto;align-self: center;box-sizing: border-box;"><section style="text-align: center;justify-content: center;margin-right: 0%;margin-left: 0%;transform: translate3d(1px, 0px, 0px);box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: auto;vertical-align: top;min-width: 10%;max-width: 100%;height: auto;background-color: rgb(255, 255, 255);border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 172, 63);padding-right: 6px;padding-left: 6px;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;margin: -1px 0%;box-sizing: border-box;"><section style="display: inline-block;width: 100%;vertical-align: middle;flex: 0 0 auto;align-self: center;height: auto;border-top: 2px solid rgb(255, 255, 255);border-top-left-radius: 0px;border-bottom: 2px solid rgb(255, 255, 255);border-bottom-right-radius: 0px;box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="color: rgb(234, 44, 44);letter-spacing: 4px;box-sizing: border-box;"><p style="box-sizing: border-box;"><strong style="box-sizing: border-box;">1.1</strong></p></section></section></section></section></section></section></section></section><section style="display: inline-block;vertical-align: middle;width: auto;padding-left: 8px;align-self: center;flex: 10 10 0%;height: auto;border-width: 0px;box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="color: rgb(234, 44, 44);letter-spacing: 4px;box-sizing: border-box;"><p style="white-space: normal;box-sizing: border-box;">居民出行特征分析</p></section></section></section></section></section><section powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><br style="box-sizing: border-box;"  /></p><section style="text-indent: 2em;"><span style="font-size: 16px;">传统的居民出行调查对居民出行特征的解析是比较深入的。其调查深度大，内容全面。包括了平均出行次数、出行方式构成、出行目的构成、出行时耗与距离、出行时间分布、出行空间分布等多项重要指标（图1）。而其不足在于，空间上到交通大区居多，大区内部的细化分析相对较弱；关注交通本身的问题较多，对空间结构的分析较弱，交通与空间的互动协调关系分析较弱；最后，也是最难解的问题，数据门槛过高。一方面，不是所有城市都有财力进行完整的居民出行调查。另一方面，已有的调查，通常无法拿到原始数据，仅有调查报告，难以进行其他深入分析，比如计算道路饱和度等。</span></section><p style="white-space: normal;box-sizing: border-box;"><br  /></p><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.5749385749385749" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmyb4rOAsPxiaic8GTfqLia93MQkxeG9bWvRDSPYxPSib3GshsIRMIiaEDR9Zg/640?wx_fmt=jpeg" data-type="jpeg" data-w="1221" style=""  /></p><p style="text-align: center;"><span style="font-size: 12px;color: rgb(136, 136, 136);">图1 居民出行调查结果举例</span></p><p style="text-align: center;"><span style="font-size: 12px;color: rgb(136, 136, 136);">资料来源：2015年厦门市居民出行调查统计分析报告（阶段报告）</span></p><p style="white-space: normal;box-sizing: border-box;"><br  /></p><section style="text-indent: 2em;"><span style="font-size: 16px;">而对于手机大数据，其特点包括：大样本，空间覆盖全面；被动性，手机用户被动提供位置信息；空间精确度高，能够细化到各个交通小区；动态、连续：能够连续、动态地反映手机持有者的空间位置变化。而其主要不足在于数据的采集精度问题，以及难以判定居民的属性及出行方式。手机大数据的突出优点在于能够获取原始数据，可用于多样分析。同时，通过手机大数据可以研究城市居民出行活动的时空特征，如出行OD等，并可以区分职住OD、住娱OD等，能够一定程度上反映城市的空间结构和特征（图2）。</span></section><section style="text-indent: 2em;"><br  /></section><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.34077750206782464" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmy8CWZfN63urUu8ffed2qDtKa7X81o46zre5eoCQu2tNY37b3WGpnwYA/640?wx_fmt=jpeg" data-type="jpeg" data-w="1209" style=""  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">图2 手机大数据可视化结果举例</span></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">数据来源：厦门市LBS大数据</span></p><section><br  /></section><section style="text-indent: 2em;"><span style="font-size: 16px;">手机大数据能够分析出包括职住OD、住娱OD、城市内部出行OD、外来人口出行OD等在内的各类居民出行OD；也可根据这些OD计算出城市居民的平均出行次数、平均出行距离、平均出行时耗等重要指标。在此之外，传统居民出行调查由于受到行政区划的影响，往往集中在城市内部，区域性的人流活动特征难以涉及，而大数据刚好可以弥补这一缺憾，可以抓取并分析出跨城市的区域性人流活动特征。以福建省厦漳泉大都市区为例，手机大数据可以分析出居住地分别为厦门、漳州、泉州三市的人群在整个厦漳泉区域的活动特征，如图3所示：</span></section><section><br  /></section><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.38623005877413935" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmy3tMKNWiak07aqQfaj848d17H45nPOaYcExHJbwsSI8JJqVpLN7yYrVg/640?wx_fmt=jpeg" data-type="jpeg" data-w="1191" style=""  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">图3 厦漳泉区域人流活动特征</span></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">数据来源：厦门市LBS大数据</span></p><section><br  /></section><p style="text-indent: 2em;"><span style="font-size: 16px;">研究中，尽管大数据能够做出多种现状分析，但是大数据与传统居民出行调查结果的相互校核仍是重要的一步。以厦门为例，研究发现尽管在大区出行OD分布上，两者的总体趋势基本吻合，但是手机大数据的大区内部出行比例比交通调查结果偏小很多，远距离出行比例比交通调查结果高很多。分析认为，短距离的出行，居民未使用手机，或者1小时内完成来回（研究使用的OD数据精度是1小时），导致这部分出行没有记录到手机数据里。因此，这里的大数据应该根据传统居民出行调查内容进行校核，否则直接使用得出的结果将不符合厦门现状。在条件允许的情况下，传统交通调查与大数据分析相结合，能够更有效地保障分析的科学性、合理性和说服力。</span></p><section><br  /></section></section><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;margin: 10px 0%;box-sizing: border-box;"><section style="display: inline-block;vertical-align: middle;width: auto;border-style: none;border-width: 1px;border-radius: 0px;border-color: rgb(62, 62, 62);min-width: 10%;max-width: 100%;flex: 0 0 auto;height: auto;align-self: center;box-sizing: border-box;"><section style="text-align: center;justify-content: center;margin-right: 0%;margin-left: 0%;transform: translate3d(1px, 0px, 0px);box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: auto;vertical-align: top;min-width: 10%;max-width: 100%;height: auto;background-color: rgb(255, 255, 255);border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 172, 63);padding-right: 6px;padding-left: 6px;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;margin: -1px 0%;box-sizing: border-box;"><section style="display: inline-block;width: 100%;vertical-align: middle;flex: 0 0 auto;align-self: center;height: auto;border-top: 2px solid rgb(255, 255, 255);border-top-left-radius: 0px;border-bottom: 2px solid rgb(255, 255, 255);border-bottom-right-radius: 0px;box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="color: rgb(234, 44, 44);letter-spacing: 4px;box-sizing: border-box;"><p style="box-sizing: border-box;"><strong style="box-sizing: border-box;">1.2</strong></p></section></section></section></section></section></section></section></section><section style="display: inline-block;vertical-align: middle;width: auto;padding-left: 8px;align-self: center;flex: 10 10 0%;height: auto;border-width: 0px;box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="color: rgb(234, 44, 44);letter-spacing: 4px;box-sizing: border-box;"><p style="white-space: normal;box-sizing: border-box;">机动车（道路）运行特征分析</p></section></section></section></section></section><section powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><br style="box-sizing: border-box;"  /></p><section style="text-indent: 2em;"><span style="font-size: 16px;">运用VISUM软件搭建现状路网模型，可根据大数据OD，计算得到道路饱和度、流量等指标，并做可视化表达。以哈尔滨市大数据现状分析为例，计算结果如图4所示：</span></section><section style="text-indent: 2em;"><span style="font-size: 16px;"><br  /></span></section><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.3982978723404255" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmy2wRT6pasficHgcicU9rVHrdMz0ZoTb7cj1RFUqScZBaINnT94OC8XfuQ/640?wx_fmt=jpeg" data-type="jpeg" data-w="1175" style=""  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">图4  哈尔滨市现状道路流量(左)、饱和度（右）图</span></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">数据来源：哈尔滨市LBS大数据</span></p><p style="white-space: normal;box-sizing: border-box;"><br  /></p></section><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;margin: 10px 0%;box-sizing: border-box;"><section style="display: inline-block;vertical-align: middle;width: auto;border-style: none;border-width: 1px;border-radius: 0px;border-color: rgb(62, 62, 62);min-width: 10%;max-width: 100%;flex: 0 0 auto;height: auto;align-self: center;box-sizing: border-box;"><section style="text-align: center;justify-content: center;margin-right: 0%;margin-left: 0%;transform: translate3d(1px, 0px, 0px);box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: auto;vertical-align: top;min-width: 10%;max-width: 100%;height: auto;background-color: rgb(255, 255, 255);border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 172, 63);padding-right: 6px;padding-left: 6px;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;margin: -1px 0%;box-sizing: border-box;"><section style="display: inline-block;width: 100%;vertical-align: middle;flex: 0 0 auto;align-self: center;height: auto;border-top: 2px solid rgb(255, 255, 255);border-top-left-radius: 0px;border-bottom: 2px solid rgb(255, 255, 255);border-bottom-right-radius: 0px;box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="color: rgb(234, 44, 44);letter-spacing: 4px;box-sizing: border-box;"><p style="box-sizing: border-box;"><strong style="box-sizing: border-box;">1.3</strong></p></section></section></section></section></section></section></section></section><section style="display: inline-block;vertical-align: middle;width: auto;padding-left: 8px;align-self: center;flex: 10 10 0%;height: auto;border-width: 0px;box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="color: rgb(234, 44, 44);letter-spacing: 4px;box-sizing: border-box;"><p style="white-space: normal;box-sizing: border-box;">空间职住特征</p></section></section></section></section></section><section style="box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><br style="box-sizing: border-box;"  /></p><section style="text-indent: 2em;"><span style="font-size: 16px;">既往研究中，城市内部职住关系往往用静态职住比表达。静态职住比，即职/住，由于不能直观确定就近就业的比例，静态职住比仅仅是一个理论数值，需要进一步通过居民就业出行地和居住地的动态关联分析才能够准确测度真实的就业均衡程度。这里，我们提出动态职住比，即“职住平衡度”的概念。职住平衡度并非传统意义的“职”与“住”的静态比值，而是指城市区域内部通勤出行占总通勤出行量的百分比。如此分析得到的结果与静态职住比结果差异明显，如图5所示：</span></section><p style="white-space: normal;box-sizing: border-box;"><br  /></p><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.3826164874551971" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmyCibCvq1ggXmm0q0rONUnwSVV502BlltAoN2xEOLyEPap78eCibnmeCibw/640?wx_fmt=jpeg" data-type="jpeg" data-w="1116" style=""  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">图5 厦门市静态（左）与动态（右）职住比</span></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">数据来源：厦门市LBS大数据</span></p><p style="white-space: normal;box-sizing: border-box;"><br  /></p><section style="text-indent: 2em;"><span style="font-size: 16px;">通过职住空间关联的动态OD来反映城市空间结构的内在关系，能够一定程度地促进城市交通与空间的协同发展研究。</span></section><p style="white-space: normal;box-sizing: border-box;"><br  /></p></section><section style="text-align: center;justify-content: center;margin: 16px 0% 10px;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: auto;vertical-align: top;min-width: 10%;max-width: 100%;height: auto;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;box-sizing: border-box;"><section style="display: inline-block;vertical-align: top;width: auto;align-self: flex-start;flex: 4.1445 4.1445 0%;margin-top: -8px;height: auto;border-width: 0px;z-index: 1;border-style: solid;border-radius: 0px;border-color: rgb(62, 62, 62);box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 30px;height: 30px;vertical-align: top;overflow: hidden;border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 172, 63);background-color: rgb(255, 255, 255);box-sizing: border-box;"><section style="text-align: justify;color: rgb(234, 44, 44);box-sizing: border-box;" powered-by="gulangu"><p style="text-align: center;white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">2</strong></p></section></section></section></section><section style="display: inline-block;vertical-align: middle;width: auto;align-self: center;background-color: rgb(255, 255, 255);margin-left: -12px;flex: 100 100 0%;height: auto;z-index: auto;padding: 5px 8px 5px 20px;border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 172, 63);box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="color: rgb(234, 44, 44);letter-spacing: 2px;box-sizing: border-box;"><p style="text-align: justify;white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">基于现状分析的规划模拟评价研究</strong></p></section></section></section></section></section></section></section><section powered-by="gulangu"><section style="text-indent: 2em;"><br  /></section><section style="text-indent: 2em;"><span style="font-size: 16px;">空间方案的情景模拟与评价，即以职住平衡度和出行方式占比为主要参考指标，运用VISUM软件搭建规划路网模型，模拟城市在既定空间结构、路网布局、出行方式下的空间（交通运行）绩效，为规划方案提出反馈意见，形成动态互动机制（图6）。在本文目前的研究与应用中，基于大数据的规划模拟主要有三种类型：第一，规划空间方案总体评价；第二，规划中的交通基础设施：如桥梁、隧道等；第三，特殊城市如江河分割的城市、旅游城市的特殊分析。期望对城市交通出行方式划分、交通大通道战略制定以及区域或城市空间结构的确定提供参考。</span></section><p style="white-space: normal;box-sizing: border-box;"><br  /></p><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="1.0078247261345852" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmygcnBy0eXhibGmD7lXzjWEnbhUKaURfBsDOib3I6jsBjSHdqYVHccA1CQ/640?wx_fmt=jpeg" data-type="jpeg" data-w="639" style=""  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">图6 基本技术路线</span></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">资料来源：作者自绘</span></p><p style="white-space: normal;box-sizing: border-box;"><br  /></p><section style="text-indent: 2em;"><span style="font-size: 16px;">以厦门市为例，依托现状特征，根据城市交通发展规律选择可能的、不同导向的交通情景模式发展战略目标；根据城市空间和用地特征与发展规律选择可能的、不同导向的空间结构（职住平衡）情景模式发展战略目标，形成3*3的九种情景（表1）。</span></section><p style="white-space: normal;box-sizing: border-box;"><br  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">表1 九种“空间结构—交通模式”复合情景模式</span></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">资料来源：作者自绘</span></p><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.1618334892422825" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_png/E4LhH9HickWBYGkDGPK9stlJErJwpacmyWgeFfqic0e6pwaOz2rHtMFHDqzRAEQERYMhqenwibPgibohcLeonmzFFA/640?wx_fmt=png" data-type="png" data-w="1069" style=""  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><br  /></p><p style="text-indent: 2em;box-sizing: border-box;"><span style="font-size: 16px;">本研究确定的未来职住平衡仍对应于现状空间格局，即现状职住平衡度为“基础”，以已有规划方案（静态职住量）为“辅助”，可施以适当提升或降低平衡度的宏观调节，最后根据试模拟结果进行反馈调整。以厦门市现状及历年出行方式构成变化为基础，综合考虑厦门市未来可能的交通发展模式，并参考国内外城市交通发展案例，分别拟定高小汽车、中小汽车、低小汽车三种交通情景。将以上职住情景和交通发展模式情景做两两交叉，运用VISUM软件建立规划交通模型，输入相应的参数分别对九种情景方案进行模拟，可得到高峰小时道路饱和度、交通流量以及出行时耗与距离分布等结果，据此做方案的比较分析。九种情景方案高峰小时道路饱和度如图7所示：</span></p><p style="text-indent: 2em;box-sizing: border-box;"><span style="font-size: 16px;"><br  /></span></p><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.9748549323017408" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmy07ISpWBeTuNar2dzTgOiboQ7ibhmqcXEVHq1icdmPCVMq3sMCAWicfqLMg/640?wx_fmt=jpeg" data-type="jpeg" data-w="1034" style=""  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">图7 九种情景方案高峰小时道路饱和度图</span></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">资料来源：作者自绘</span></p><p style="text-indent: 2em;box-sizing: border-box;"><br  /></p><p style="text-indent: 2em;box-sizing: border-box;"><span style="font-size: 16px;">研究为规划方案提供了动态持续的交通模型模拟工具。通过城市空间结构的调整来缓解大城市交通拥堵问题的方法逐渐成为共识，城市交通问题必须与城市空间布局结构的调整同步协调进行，这既是交通治本的出路，又是城市未来结构优化的客观需求。非交通配规划，交通在规划项目的初期深入参与到城市空间方案的形成，通过不断地情景模拟，形成空间与交通的互动机制，为规划方案提出动态反馈意见。</span></p><p style="text-indent: 2em;box-sizing: border-box;"><br  /></p><p style="text-indent: 2em;box-sizing: border-box;"><span style="font-size: 16px;">除了对方案总体评价，研究还对城市交通基础设施如桥梁等进行模拟评价，如哈尔滨跨江大桥的数量分析：</span></p><p style="text-indent: 2em;box-sizing: border-box;"><br  /></p><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.30811662726556344" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmyQJqL6icAJFFKqG7HnVpOOU1m4cbNQp1X4a6OFPc2ID4icFKJiaiaYDqYmw/640?wx_fmt=jpeg" data-type="jpeg" data-w="1269" style=""  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">图8 哈尔滨跨江大桥间距（左）与饱和度（右）分析</span></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">资料来源：同济课题组成果</span></p><p><br  /></p><p style="text-indent: 2em;box-sizing: border-box;"><span style="font-size: 16px;">以及特殊城市如旅游城市的特殊分析，如对西双版纳景洪市中心城旅游交通与城市交通的拥堵影响分析。通过本地居民全目的+旅游人口OD的叠加算法，考虑不同公交出行情景，对景洪市未来在旅游蓬勃发展影响下的城市道路交通运行情况进行了模拟，并对规划提出了改进意见和建议。</span></p><p><br  /></p><p style="text-align: center;"><img class="rich_pages js_insertlocalimg" data-ratio="0.36485421591804573" data-s="300,640" src="http://mmbiz.qpic.cn/mmbiz_jpg/E4LhH9HickWBYGkDGPK9stlJErJwpacmyQZMDHG3TM1Bt4mVDoUos0MW4eUODE56VM6opan1jtRPxIZFJd3Fmvw/640?wx_fmt=jpeg" data-type="jpeg" data-w="1269" style=""  /></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">图9景洪市主城区旅游高峰小时OD联系（左）与道路交通流量（右）</span></p><p style="text-align: center;box-sizing: border-box;font-size: 16px;"><span style="font-size: 12px;color: rgb(136, 136, 136);">数据来源：景洪市手机信令大数据</span></p><p><br  /></p></section><section style="text-align: center;justify-content: center;margin: 16px 0% 10px;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: auto;vertical-align: top;min-width: 10%;max-width: 100%;height: auto;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;box-sizing: border-box;"><section style="display: inline-block;vertical-align: top;width: auto;align-self: flex-start;flex: 4.1445 4.1445 0%;margin-top: -8px;height: auto;border-width: 0px;z-index: 1;border-style: solid;border-radius: 0px;border-color: rgb(62, 62, 62);box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 30px;height: 30px;vertical-align: top;overflow: hidden;border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 172, 63);background-color: rgb(255, 255, 255);box-sizing: border-box;"><section style="text-align: justify;color: rgb(234, 44, 44);box-sizing: border-box;" powered-by="gulangu"><p style="text-align: center;white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">3</strong></p></section></section></section></section><section style="display: inline-block;vertical-align: middle;width: auto;align-self: center;background-color: rgb(255, 255, 255);margin-left: -12px;flex: 100 100 0%;height: auto;z-index: auto;padding: 5px 8px 5px 20px;border-style: solid;border-width: 1px;border-radius: 0px;border-color: rgb(255, 172, 63);box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="color: rgb(234, 44, 44);letter-spacing: 2px;box-sizing: border-box;"><p style="text-align: justify;white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">总结与展望</strong></p></section></section></section></section></section></section></section><section powered-by="gulangu"><p style="text-indent: 2em;box-sizing: border-box;"><br  /></p><p style="text-indent: 2em;box-sizing: border-box;"><span style="font-size: 16px;">本文结合城市规划实践，探索基于LBS/手机信令大数据的城市交通分析与评价技术方法，以期为城市宏观层面规划的编制实践提供参考。目前上述研究尚处于探索阶段，一些初步结论可能还存在有待商榷之处，未来仍然需要对手机大数据的校核开展详细研究，对手机大数据在不同层面、不同类型的规划编制中的应用应该更加符合规划需求，从理论建设到项目应用还需更多实践。 </span></p><p style="text-indent: 2em;box-sizing: border-box;"><span style="font-size: 16px;"><br  /></span></p><p style="text-indent: 2em;box-sizing: border-box;"><span style="font-size: 16px;">大数据不直接导致客观和科学，决策者和公众是通过数据分析师的眼睛看待世界（杨东援，2018），在纷繁的大数据海洋中获取可信数据是数据分析师应该承担的责任。“大数据”之“长”在于更加全面地观察研究对象，“大数据”之“短”在于缺少严谨的因果建模能力。因此，手机大数据、传统交通出行调查、人口数据、经济普查数据等多元数据综合分析是发展趋势。规划师对大数据的理性运用，是大数据有效服务于城市规划的重要基础。</span></p><p style="text-indent: 2em;box-sizing: border-box;"><span style="font-size: 16px;"> </span></p><p style="text-align: center;"><span style="color: rgb(136, 136, 136);font-size: 14px;">感谢同济大学赵民老师对本论文的指导和大力帮助！</span></p><p><br  /></p></section><section style="margin: 30px 0% 10px;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;vertical-align: top;border-style: solid;border-width: 3px;border-radius: 0px;border-color: rgb(255, 172, 63);padding-right: 10px;padding-bottom: 10px;padding-left: 10px;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;text-align: left;justify-content: flex-start;margin: -15px 0% 10px;box-sizing: border-box;"><section style="display: inline-block;width: auto;vertical-align: top;border-style: none solid;border-width: 1px 3px;border-radius: 0px;border-color: rgb(58, 153, 159) rgb(255, 172, 63);min-width: 10%;max-width: 100%;flex: 0 0 auto;height: auto;align-self: flex-start;padding: 3px 5px;background-color: rgb(255, 255, 255);box-sizing: border-box;"><section style="text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 100%;vertical-align: top;height: auto;border-left: 3px solid rgb(234, 44, 44);border-bottom-left-radius: 0px;padding-right: 8px;padding-left: 8px;border-right: 3px solid rgb(234, 44, 44);border-top-right-radius: 0px;box-sizing: border-box;"><section style="margin-right: 0%;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="text-align: justify;color: rgb(234, 44, 44);letter-spacing: 2px;line-height: 1.5;text-shadow: rgb(255, 255, 255) 1px -1px, rgb(255, 255, 255) 1px 1px, rgb(255, 255, 255) -1px 1px, rgb(255, 255, 255) -1px -1px, rgb(255, 255, 255) 1px 0px, rgb(255, 255, 255) 0px 1px, rgb(255, 255, 255) -1px 0px, rgb(255, 255, 255) 0px -1px;box-sizing: border-box;"><p style="white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">作者介绍</strong></p></section></section></section></section></section></section></section><section style="font-size: 15px;color: rgb(62, 62, 62);line-height: 1.8;box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">胡刚钰</strong>  黄建中教授工作室 主创规划师 工程师 注册城乡规划师 硕士 研究方向为城市规划理论与设计、城市交通与基础设施建设</p><p style="white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">黄建中</strong>  黄建中教授工作室 总规划师 教授 博导 博士 研究方向为城市规划理论与设计、城市土地利用与交通规划、城市发展战略</p><p style="white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">张乔 </strong> 黄建中教授工作室 主任规划师 高级工程师 注册城乡规划师 硕士 研究方向为城市规划理论与设计、城市交通与基础设施建设</p><p style="white-space: normal;box-sizing: border-box;"><strong style="box-sizing: border-box;">方文彦</strong>  黄建中教授工作室 副主任规划师 工程师 注册城乡规划师 硕士 研究方向为城市规划理论与设计、城市交通与基础设施建设</p></section></section></section><section style="box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><br style="box-sizing: border-box;"  /></p><section style="box-sizing: border-box;font-size: 16px;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="text-align: center;box-sizing: border-box;"><section style="display: inline-block;width: auto;vertical-align: top;min-width: 10%;max-width: 100%;height: auto;box-sizing: border-box;"><section style="transform: translate3d(0px, 0px, 1px) rotateX(180deg) rotateY(180deg);-webkit-transform: translate3d(0px, 0px, 1px) rotateX(180deg) rotateY(180deg);-moz-transform: translate3d(0px, 0px, 1px) rotateX(180deg) rotateY(180deg);-o-transform: translate3d(0px, 0px, 1px) rotateX(180deg) rotateY(180deg);box-sizing: border-box;" 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border-box;line-height: 0;"><br  /></section></section></section><section style="display: inline-block;vertical-align: top;align-self: flex-start;width: auto;flex: 0 0 0%;height: auto;line-height: 0;letter-spacing: 0px;background-color: rgb(255, 172, 63);box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 1px;height: 15px;vertical-align: top;overflow: hidden;box-sizing: border-box;line-height: 0;"><br  /></section></section></section></section></section></section><section style="display: inline-block;vertical-align: top;width: 50%;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;margin-right: 0%;margin-bottom: 10px;margin-left: 0%;transform: translate3d(-18px, 0px, 0px);text-align: right;justify-content: flex-end;box-sizing: border-box;"><section style="display: inline-block;vertical-align: top;align-self: 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auto;flex: 100 100 0%;align-self: flex-end;height: auto;border-style: none;border-width: 0px;border-radius: 0px;border-bottom-color: rgb(132, 198, 255);box-shadow: rgb(0, 0, 0) 0px 0px 0px;box-sizing: border-box;line-height: 0;"><section style="line-height: 0;width: 0px;"><svg viewbox="0 0 1 1" style="vertical-align:top;"></svg></section></section><section style="display: inline-block;vertical-align: bottom;width: auto;align-self: flex-end;min-width: 10%;max-width: 100%;flex: 0 0 auto;height: auto;box-sizing: border-box;"><section style="box-sizing: border-box;" powered-by="gulangu"><section style="display: flex;flex-flow: row nowrap;margin-top: 10px;margin-right: 0%;margin-left: 0%;transform: translate3d(0px, 0px, 1px) rotateY(180deg);box-sizing: border-box;"><section style="display: inline-block;vertical-align: bottom;width: 18px;flex: 0 0 auto;height: auto;align-self: flex-end;border-style: none;border-width: 0px;border-radius: 0px;border-bottom-color: rgb(132, 198, 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style="display: flex;flex-flow: row nowrap;margin-right: 0%;margin-bottom: 10px;margin-left: 0%;transform: translate3d(-18px, 0px, 0px);text-align: right;justify-content: flex-end;box-sizing: border-box;"><section style="display: inline-block;vertical-align: top;align-self: flex-start;width: auto;flex: 0 0 0%;height: auto;line-height: 0;letter-spacing: 0px;background-color: rgb(255, 172, 63);box-sizing: border-box;"><section style="text-align: center;box-sizing: border-box;" powered-by="gulangu"><section style="display: inline-block;width: 1px;height: 15px;vertical-align: top;overflow: hidden;box-sizing: border-box;line-height: 0;"><br  /></section></section></section></section></section></section></section></section></section></section><section style="margin-right: 0%;margin-bottom: 10px;margin-left: 0%;box-sizing: border-box;" powered-by="gulangu"><section style="font-size: 14px;color: rgb(249, 110, 87);text-align: center;letter-spacing: 0px;line-height: 2;padding-right: 20px;padding-left: 20px;box-sizing: border-box;"><p style="box-sizing: border-box;"><strong style="box-sizing: border-box;"><span style="color: rgb(234, 44, 44);box-sizing: border-box;">此课题受上海同济城市规划设计研究院有限公司</span></strong></p><p style="box-sizing: border-box;"><strong style="box-sizing: border-box;"><span style="color: rgb(234, 44, 44);box-sizing: border-box;">种子计划科研资助</span></strong></p><p style="box-sizing: border-box;"><span style="letter-spacing: 0px;color: rgb(234, 44, 44);box-sizing: border-box;">扫码获取种子计划申请表<br style="box-sizing: border-box;"  /></span></p><p style="box-sizing: border-box;"><span style="color: rgb(234, 44, 44);box-sizing: border-box;">种子计划课题申报邮箱：research@tjupdi.com</span></p></section></section><section style="box-sizing: border-box;" powered-by="gulangu"><p style="white-space: normal;box-sizing: border-box;"><br style="box-sizing: border-box;"  /></p></section></section><p style="white-space: normal;box-sizing: border-box;"><br  /></p></section><section 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