摘要
在RP/SP融合分析中,当部分选项有一定相似性时,常用Nested Logit(NL)框架构建RP或SP子模型;但既有研究中,2个子模型往往采用不同的阶层结构,导致对行为机制的认识缺乏统一性、不同层次误差项对应关系不明确、无法正确描述SP选择的阶层性等问题。本文针对RP-NL/SP-NL的同构融合框架,提出分层考虑误差项测度、引入融合系数修正SP效用函数的融合方法,以北京市新设快速路公交专用道为对象进行问卷调查,标定和对比3种RP-NL/SP-NL模型及RP、SP单独模型的结果。研究表明:分层考虑SP与RP的误差项关系,可以更清晰地揭示SP数据的阶层结构,真实表现SP的选择机制,也有利于减小误差项的影响,提高变量对SP选择行为的解释能力。
To accommodate the similarity between alternatives, the Nested Logit （NL） model is usually applied to construct sub - models in RP/SP combined analysis. In previous literatures, however, RP and SP sub - models often adopt different hierarchical struc- tures, which result in problems such as inconsistent comprehension for behavioral mechanisms, unclear corresponding relation between error - components and incorrectly description of the real hierarchical structure of SP data. This paper formulates a joint method, which considers hierarchical difference between error terms within a unified RP - NL/SP - NL framework and introduces fusion coefficients to rescale SP utility. Based on the survey data collected from new bus lanes on freeway in Beijing, three different RP - NL/SP - NL mod- els, RP and SP independent NL model were estimated and compared. Taking into account the hierarchical relation between errors of RP and SP, the result implies that the proposed method can clearly reveal the choice process and hierarchical structure of SP data, reduce the impact of error terms and improve the explanatory power of variables to understand SP choice behavior better.
作者
吾晨晨
吴戈
李春艳
李先
WU Chenchen WU Ge LI Chunyan LI Xian(School of Urban Rail Transportation, Soochow University, Suzhou 215131 China Beijing Transportation Research Center, Beijing 100161 China)
出处
《西华大学学报（自然科学版）》
CAS
2017年第2期61-67,共7页
Journal of Xihua University:Natural Science Edition
