居住地、出行方式与出发时间联合选择的

为刻画居住地、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3种结构的传统巢式模型.利用2005年北京市第3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(Nested logit)模型更优的统计学特征,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5km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.

Cross nested Logit Model for Joint Choice of Residential Location, Travel Mode and Departure Time

This paper aims to describe the joint choice of residential location, travel mode, and departure time. First, based on random utility maximization theory, the innovative cross nested logit model and traditional nested logit model 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, based on 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 is more accurate statistically than any kind of NL model. When exogenous variables altered, decision makers will change their departure time in the first place, subsequently, the mode choice, finally, the residential location. Moreover, elasticity analysis results reveal that the car travel proportion will not decrease even if there is an extra toll on car using for long distance commuters. The effect on choice probability by variations in travel time of the other travel mode can be considered as negligible for commuters living within 5km from their workplaces, and this effect is the greatest for commuters living between 10 and 20km from their workplaces.