华南理工大学学报(自然科学版) ›› 2014, Vol. 42 ›› Issue (12): 26-34.doi: 10.3969/j.issn.1000-565X.2014.12.005

• 交通与运输工程 • 上一篇    下一篇

新城土地利用空间分布模拟与交通需求预测

胡郁葱1 陈海伟1 欧阳剑1 朴莲花2 梁枫明2   

  1. 1. 华南理工大学 土木与交通学院,广东 广州 510640;2. 广州市城市规划勘察设计研究院,广东 广州 510600
  • 收稿日期:2014-03-13 修回日期:2014-08-27 出版日期:2014-12-25 发布日期:2014-11-17
  • 通信作者: 胡郁葱(1970-),女,博士,副教授,主要从事交通与土地一体化研究. E-mail:ychu@scut.edu.cn
  • 作者简介:胡郁葱(1970-),女,博士,副教授,主要从事交通与土地一体化研究.
  • 基金资助:

    国家自然科学基金资助项目(61174188)

Land-Use Spatial Distribution Simulation and Traffic Demand Forecasting in New Town

Hu Yu-cong1 Chen Hai-wei1 Ouyang Jian1 Piao Lian-hua2 Liang Feng-ming2   

  1. 1.School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,Guangdong,China;2.Guangzhou Urban Planning and Design Survey Research Institute,Guangzhou 510600,Guangdong,China
  • Received:2014-03-13 Revised:2014-08-27 Online:2014-12-25 Published:2014-11-17
  • Contact: 胡郁葱(1970-),女,博士,副教授,主要从事交通与土地一体化研究. E-mail:ychu@scut.edu.cn
  • About author:胡郁葱(1970-),女,博士,副教授,主要从事交通与土地一体化研究.
  • Supported by:

    国家自然科学基金资助项目(61174188)

摘要: 为解决新城交通需求预测难题,运用随机效用理论,将居住选址和活动选址分布定义为土地租金和交通区位的 Logit 形式,并建立家庭参与居住选址和活动选址分配的平衡等式,从而得到模拟新城土地利用的空间分布的 Logit 模型. 在此基础上,将新城的人口就业分布和选址函数嵌入到交通需求预测模型中,使其成为一个出行生成与分布的组合模型. 最后以广州南沙新城为例,对模型进行验证. 结果显示:模型能较好地模拟新城的土地利用分布,对居住选址和活动选址的分布具有良好的解析能力;在考虑住房、店铺空置的情况下,预测 2030 年南沙总人口数为 242 万,日交通生成总量为 732. 2 万人次,与未考虑该因素的常规方法相比,总人口数和日交通生成总量分别降低 19. 3%和 12. 8%.

关键词: 新城, 土地利用, 空间分布, 交通需求预测, 随机效用

Abstract:

In order to forecast the traffic demand in a new town,by using the random utility theory,the distributionof residential and activity locations is defined as a Logit formulation of land rent and traffic location,and a balanceequation is established to simulate the assignment of houses and activities.Thus,a Logit model is constructed tosimulate the spatial distribution of land use in the new town.On this basis,a combination model of trip generationand distribution is constructed by embedding the population and employment distribution and the location functioninto the traffic demand forecasting model.Finally,Guangzhou Nansha new town is taken as an example to test andverify the two models.The results show that (1) the Logit model is able to simulate the spatial distribution of landuse and analyze the distribution of the selected residential and activity locations in the new town; and (2) when thevacancy rate of housing and shopping is taken into account,the total population and daily trip generations of Nanshanew town in 2030 are predicted to be 2420 thousand and 7322 thousand respectively,which decrease respectivelyby 19.3% and 12.8% in comparison with the results of the conventional method.

Key words: new town, land use, spatial distribution, travel demand forecasting, random utility

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