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为分析城市群内低频率城际出行行为,对长三角城市群内上海与其他城市间的城际出行进行选择方案抽样调查,基于城际出行行为调查数据建立出行方式选择的多项Logit(MNL)模型;选择方案抽样调查数据与随机抽样调查数据存在方案分层结构偏差和因素重视度偏差,故引入反转因子(IPW),分别用外源性样本极大似然估计(ESMLE)简单修正法和加权外源性样本极大似然估计(WESMLE)法对MNL模型进行修正。结果表明:未修正模型及2种修正法下的模型命中率分别为57%,75%和84%;WESMLE修正后的模型能基本满足建模精度要求;城市群内低频率城际出行行为受出行时间、费用及个人属性等因素影响,同时,也表现出一定程度的随机性和随意性。
In order to analyze inter-city low-frequency inter-city travel in urban agglomerations, a sample survey of inter-city trips between Shanghai and other cities in the Yangtze River Delta is conducted. Based on inter-city travel survey data, multiple Logit (MNLs) (IPW) were introduced, and the simple extrinsic sample maximum likelihood estimation (ESMLE) was used to amend the model respectively. Method and weighted exogenous sample maximum likelihood estimation (WESMLE) method to amend the MNL model. The results show that the unmodified model and the two correction methods have hit rates of 57%, 75% and 84%, respectively. The WESMLE modified model can basically meet the modeling accuracy requirements. The low frequency intercity travel behavior in the urban agglomeration Travel time, costs and personal attributes and other factors, but also showed a certain degree of randomness and arbitrariness.