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Cross-nested logit model for the joint choice of residential location, travel mode, and departure time

2013.09.22

作者:杨励雅 等

  

 

 Liya YangGuo Zheng and Xiaoning Zhu2013),“Cross-nested logit model for the joint choice of residential location, travel mode, and departure time”,Habitat International , Vol37, pp.157-166.

This paper aims to describe the joint choice of residential location, travel mode, and departure time. First, based on random utility maximization theory, the Cross-Nested Logit model and traditional NL models are formulated respectively. House price, travel time, travel cost, and factors depicting the individual socio-economic characteristics are defined as exogenous variables, and the model choice sets are the combination of residential location subset, departure time subset, and travel mode choice subset. Second, using Beijing traffic survey data of 2005, the model parameters are estimated, and the direct and cross elasticity are calculated to analyze the change of alternatives probability brought by factors variation. Estimation results show the Cross-Nested Logit model outperforms the three kinds of NL model. It is also found by estimation results that decision makers will change first their departure times, then their travel modes, and finally their residential locations, when exogenous variables alter. Moreover, elasticity analysis results suggest that, for long-distance commuting, it is difficult to decrease car travels even if additional charges are imposed on car users. The effect on choice probability by variations in travel time of other travel mode can be considered as negligible for alternatives within 5kmcommuting distance, and this effect are greatest for alternatives between 10 and20kmcommuting distance. These findings have important implications for transport demand management and residence planning.

居住选址、出行方式与出发时间联合选择的交叉巢式logit模型

 

摘要:本文旨在定量刻画居住地、出行方式与出发时间的联合选择行为,选取房价、出行耗时、出行费用及个人属性等作为效用变量,以居住地选择子集合、出行方式选择子集合和出发时间选择子集合的组合作为模型的选择项,构建基于广义极值(GEV)理论的交叉巢式Logit模型,为方便对比,同时构建三种结构的传统NL模型。利用2005年北京市第三次居民出行调查数据,对模型参数进行估计和检验,并进行弹性分析,分析效用变量的改变引起的备选方案选择概率的改变。参数估计结果表明,交叉巢式Logit模型具有比NL模型更优的统计学特征,并发现当效用变量改变时,选择者最先变更其出发时间,然后是出行方式,最后才考虑改变其居住地;直接和交叉弹性分析表明,对于小汽车方式的远距离通勤者,即使额外收取费用亦难以降低其出行比例,当通勤距离小于5公里时,一种方式出行时间的变化对另一种方式选择概率的影响微乎其微,而当通勤距离在10-20km时,这种影响最显著。论文研究成果对于交通需求管理以及居住区规划具有重要的决策参考价值。(Habitat International2013, SSCI