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为了准确地反映城市交通网络布局、人口分布和职业分布等因素与交通行为之间的相互影响机制,同时考虑到发展中城市交通调查数据的完整性和准确性相对较差,首先建立了一种新的交通需求反馈模型,并对其进行改进,进而形成了一种新型集成模型。通过基于同一套发展中城市交通调查数据对不同模型进行参数标定以及对标定结果进行比较分析,本文得出结论：与被广泛应用的传统四阶段模型相比较,新的反馈和集成模型的标定结果的准确性有了明显提高。随后,根据新型集成模型的标定结果,本文又以富有代表性的发展中城市区域,即印度尼西亚的雅加达首都城市圈作为研究对象,对该区域将来的城市和交通可持续发展政策进行了探究。研究结果表明：随着对城市人口增长的控制、城市道路的建设、公共交通设施的不断完善,多副都心发展模式将成为该地区未来可持续发展的城市形态。     

Identifying variations and co-variations in discrete choice models

This study introduces an extended version of a standard multilevel cross-classified logit model which takes co-variations into account, i.e., variations jointly caused by two or more unobserved factors. Whilst focusing on mode choice behavior, this study deals with four different types of variation: spatial variations, inter-individual variations, intra-individual variations and co-variations between inter-individual and spatial variations. Such co-variations represent individual-specific spatial effects, reflecting different responses to the same space among individuals, which may for example be due to differences in their spatial perceptions. In our empirical analysis, we use data from Mobidrive (a continuous six-week travel survey) to clarify the existence of co-variation effects by comparing two models with and without co-variation terms. The results of this analysis indicate that co-variations certainly exist, especially for utility differences in bicycle and public transport use in comparison with car use. We then sequentially introduce four further sets of explanatory variables, examine the sources of behavioral variations and determine what types of influential factors are dominant in mode choice behavior.