居民出行链、出行方式与出发时间联合选择的 交叉巢式Logit模型

为刻画出行链、出行方式与出发时间的联合选择行为,选取出行耗时、出行费用及个人与家庭属性等作为效用变量,以出行链选择子集合、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NL模型。利用2010年北京市居民工作出行的小样本调查数据,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对备选方案选择概率的影响。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,最后才考虑改变其出行链结构。直接和交叉弹性分析表明,与简单链的小汽车出行者相比,复杂链的小汽车出行者对出行时间与出行费用的敏感性较低。研究结果可以为制定和评价交通需求管理政策提供依据。

Cross-Nested Logit Model for the Joint Choice of Residential Location,Travel Mode,and Departure Time

This paper aims to describe the joint choice of trip chaining, travel mode, and departure time. First, based on random utility maximization theory, the innovative Cross-Nested Logit model and traditional NL model are formulated respectively. Travel time, travel cost, and factors depicting the individual and family socio-economic characteristics are defined as exogenous variables, and the model choice sets are the combination of trip chaining subset, departure time subset, and travel mode choice subset. Second, using Beijing traffic survey data of 2010, 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. Estimation results show that decision makers will change their departure time in the first place, followed by mode choice, and finally, trip chaining type, when exogenous variables alter. Moreover, elasticity analysis results reveal that car travelers of complex trip chaining are less sensitive to travel time and travel cost than car traveler of simple trip chaining.