基于网络广义极值模型的居住地和通勤方式同时选择模型研究

北京大学学报（自然科学版）

基于网络广义极值模型的居住地和通勤方式同时选择模型研究

李霞^1,2,邵春福²,曲天书³,杨励雅⁴,王江峰²

1. 北京理工大学机械与车辆学院,北京 100081; 2. 北京交通大学交通运输学院, 北京 100044; 3. 北京大学机器感知与智能教育部重点实验室, 北京 100871; 4.中国人民大学公共管理学院,北京 100872;

收稿日期:2009-11-03 出版日期:2010-11-20 发布日期:2010-11-20

Application of Network Generalized Extreme Value Model to Estimate Residential Location and Commute Mode Choice

LI Xia^1,2, SHAO Chunfu², QU Tianshu³, YANG Liya⁴, WANG Jiangfeng²

1. School of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing 100081; 2. School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044; 3. Key Laboratry of Machine Perception, Ministry of Education, Peking University, Beijing 100871; 4. School of Public Administration, Renmin University of China, Beijing 100872;

Received:2009-11-03 Online:2010-11-20 Published:2010-11-20

摘要/Abstract

摘要： 基于随机效用最大化理论, 选取个人属性、社会经济属性、出行特性和土地利用属性因素为联合选择模型影响变量, 以居住地区位选择集合和通勤出行方式选择集合的组合作为模型的选择项, 构建居住和出行方式联合选择的网络广义极值模型, 刻画日益增长的交通拥堵情况的影响变化及其在不同的就业地模式下对居住再选址和出行方式转变的潜在影响, 从微观角度研究居住就业与城市通勤交通出行关系。利用 Biogeme 软件, 对模型参数进行估计和检验, 同时对模型进行弹性分析, 分析不同影响因素的变化引起的方式选择概率的变化。结果表明, 相比郊区的通勤者, 中心区的通勤者对出行时间的增加更为敏感, 更易于改变出行方式和居住区位, 以抵消交通拥挤引起的负效用。

关键词: 网络广义极值模型, 居住选址, 通勤方式选择, 直接弹性, 空间相关

Abstract: Relationship between jobs-housing spatial distribution and travel to work were studied from a microscopic perspective. Based on random utility maximization theory, factors depicting the individual and socio-economic characteristics and attribute of travel and land use are defined as exogenous variables, meanwhile, the model choice sets are the combination of residential location choice and commute mode choice subsets. Discrete choice model specified as Network Generalised Extreme Value(NetworkGEV) is employed to investigate the joint decisions of where to live and how to get to workplace which attempts to describe the change of aggravated traffic congestion and discover the potential change caused by residential relocation and travel mode shift under different employment location patterns. This model is estimated in Biogeme, and the direct and cross elasticities are calculated to analyze the change of alternatives probability brought by factors variation. The results reveal that the model yields plausible estimation of exogenous variables in the joint residential location and travel mode choice context. Compared with suburban commuters, commuters in CBD are more sensitive to the increase of travel time and intend to change travel mode and residential location thus trading off the disutility of traffic congestion.

Key words: NetworkGEV model, residential location, commute mode choice, direct elasticities, spatial correlation

中图分类号:

U491

李霞,邵春福,曲天书,杨励雅,王江峰. 基于网络广义极值模型的居住地和通勤方式同时选择模型研究[J]. 北京大学学报（自然科学版）.

LI Xia,SHAO Chunfu,QU Tianshu,YANG Liya,WANG Jiangfeng. Application of Network Generalized Extreme Value Model to Estimate Residential Location and Commute Mode Choice[J]. Acta Scientiarum Naturalium Universitatis Pekinensis.

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