新城土地利用空间分布模拟与交通需求预测

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

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%.

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