通勤出行方式—出行链模式联合选择模型

交通运输系统工程与信息 ›› 2016, Vol. 16 ›› Issue (5): 143-148.

通勤出行方式—出行链模式联合选择模型

鲜于建川*

上海电机学院商学院，上海201306

收稿日期:2016-01-05 修回日期:2016-04-27 出版日期:2016-10-25 发布日期:2016-10-25
作者简介:鲜于建川(1976-), 女, 四川绵阳人, 副教授, 博士.
基金资助:
上海市教委科研创新项目/Innovative Program of Shanghai Municipal Education Commission (15ZS078); 国家自然科学基金项目/National Natural Science Foundation of China (51008190).

A Model for the Joint Choice of Commute Mode and Trip Chaining Pattern

XIANYU Jian-chuan

Business School, Shanghai Dianji University, Shanghai 201306, China

Received:2016-01-05 Revised:2016-04-27 Online:2016-10-25 Published:2016-10-25

摘要/Abstract

摘要：

以单个通勤出行者为研究对象，构造基于广义极值理论的Cross-Nested Logit模型，分析了通勤出行方式和出行链模式联合选择行为.模型以通勤出行方式选择子集和出行链模式选择子集的组合为选择集，描述了在出行者社会经济属性、居住地和工作地区位、工作活动属性影响下的出行方式和出行链模型联合选择行为，能准确刻画两个选择维度之间的相关关系.利用居民出行调查数据完成模型标定.研究表明，通勤出行方式和出行链模式选择之间有显著的相互影响，出行者性别、家庭收入、家庭结构、家庭交通工具、工作活动作息时间、居住地和工作地区位是重要影响因素.当上述因素发生改变时，出行者会优先调整其出行链模式而非出行方式.

关键词: 系统工程, 出行方式, 出行链模式, 联合选择, Cross-Nested Logit模型, 通勤出行

Abstract:

Using single commuter as the base analysis unit, a Cross- Nested Logit model with two dimensions of commute mode and trip chaining pattern is developed in this paper to describe the joint choice based on generalized extreme value model. Duplets of commute mode and trip chaining pattern is used as elementary alternatives in the established model. The model describes how commuters jointly choose commute mode and trip chaining patter under the influences from individual ocioeconomics, residence and work location, and work schedule and the inter-alternative correlation along the two choice dimensions. The model is estimated using travel survey data. Empirical research results show that there are significant interrelation between commute mode and trip chaining. Gender, household income, household structure, household traffic tools, work schedule, residence and work locations are all important influences for the joint choice. Changes in the utility influential variables will result in changes in trip chaining pattern first instead of commute mode choice.

Key words: system engineering, travel mode, trip chaining pattern, joint choice, Cross-Nested Logit model, commute

中图分类号:

U491

鲜于建川. 通勤出行方式—出行链模式联合选择模型[J]. 交通运输系统工程与信息, 2016, 16(5): 143-148.

XIANYU Jian-chuan. A Model for the Joint Choice of Commute Mode and Trip Chaining Pattern[J]. Journal of Transportation Systems Engineering and , 2016, 16(5): 143-148.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract19277.shtml

http://www.tseit.org.cn/CN/Y2016/V16/I5/143

参考文献

[1] YUN M P, CHEN ZH, LIU J Y. Comparison of mode choice behavior for work tours and non-work tours considering trip chain complexity[C]// Transportation Research Board 93rd Annual Meeting. Washington, D. C., 2014.

[2] YANG M, WANG W, CHEN X W, et al. Empirical analysis of commute trip chaining: Case study of Shangyu, China[J]. Transportation Research Record, 2007(2038): 139-147.

[3] PRIMERANO F, TAYLOR M, PITAKSRINGKARN L, et al. Defining and understanding trip chaining behavior[J]. Transportation, 2008, 35(1): 55-72.

[4] 褚浩然，郑猛，杨晓光，等. 出行链特征指标的提出及应用[J]. 城市交通, 2006, 4(2): 64- 67. [CHU H R, ZHENG M, YANG X G. A study on trip-chain and their application[J]. Urban Transport of China, 2006, 4(2): 64- 67.]

[5] 鲜于建川，隽志才. 出行链与出行方式相互影响模式[J]. 上海交通大学学报, 2010, 44(6): 792- 796. [XIANYU J C, JUAN Z C. Research on the interdependencies between trip chaining behavior and travel mode[J]. Journal of Shanghai Jiaotong University, 2010, 44(6): 792-796.]

[6] SRINIVASAN, KK, NAIDU GM, PRADHAN GN. Commute mode choice in a developing country: role of subjective factors and variations in responsiveness across captive, semicaptive, and choice segments[J]. Transportation Research Record, 2007(2038): 53-61.

[7] WASHBROOK K, HAIDER W, JACCARD M. Estimating commuter mode choice: A discrete choice analysis of the impact of road pricing and parking charges[J]. Transportation, 2006, 33(6): 621-639.

[8] CAO X, MOKHTARIAN P, HANDY S. Differentiating the influence of accessibility, attitudes, and demographics on stop participation and frequency during the evening commute[J]. Environment and Planning B, 2008, 35(3): 432-442.

[9] WU Z, YE X. Joint modeling analysis of trip chaining behavior on round-trip commute in the context of Xiamen, China[J]. Transportation Research Record, 2008(2076): 62-69.

[10] SUBBARAO SSV, KRISHNA RK. Trip chaining behavior in developing countries: A study of Mumbai metropolitan region, India[J]. European Transport, 2013, 53(3): 1-30.

[11] KITAMURA R. Sequential history dependent approach to trip-chaining behavior[J]. Transportation Research Record, 1983(944): 13-22.

[12] BHAT C R. Work travel mode choice and number of non-work commute stops[J]. Transportation Research Part B, 1997, 31(1): 41-54.

[13] YE X, PENDYALA RM, GOTTARDI G. An exploration of the relationship between mode choice and complexity of trip chaining patterns[J]. Transportation Research Part B, 2007, 41(1): 96-113.

[14] ISLAM MT, HABIB KMN. Unraveling the relationship between trip chaining and mode choice: Evidence from a multi- week travel diary[J]. Transportation Planning and Technology, 2012, 35(4): 409-426.

[15] HESS S, FOWLER M, ADLER T, et al. A joint model for vehicle type and fuel type choice: Evidence from a cross-nested logit study[J]. Transportation, 2012, 39(3): 593-625.

[16] YANG LY, ZHENG G, ZHU XN. Cross-nested Logit model for the joint choice of residential location, travel mode, and departure time[J]. Habitat International, 2013 (38): 157-166.

[17] WEN CH, KOPPELMAN FS. The generalized nested logit model[J]. Transportation Research Part B, 2001, 35 (7): 627-641.