Theories and Confirmed Model of Urban Resident's Travel Demand: Considering Intra-household Interaction
Received date: 2008-04-18
Revised date: 2008-09-19
Online published: 2008-12-25
Supported by
National Natural Science Foundation of China. No.40671058
From the 1950s to the present, the research perspective of urban resident's travel demand transits from trip-based to activity-based， while the study units divide Traffic Analytical Zone (TAZ) into the individuals and even household. This paper summarizes that there are many problems of trip-based travel demand model in theory and practice. For this, the researches of activity-based and intra-household interaction come into being. Activity-based approach is the theoretical foundation of household-based travel behavior analysis, while its own foundation dated from the seminal work of Chapin (1974) and Hägerstrand (1970). Many literatures have confirmed that activity-based analysis could solve the problems using trip-based models so commendably that its contents extend and deepen from the 1980s to now. Thought most activity-based models still focus on the theories, household-based travel models gradually become the mainstream in transport planning in Western countries. Researches of household-based travel behaviors require to synthetically consider the effect on individual's activity-travel behavior of family attribute, the constraint to individual's behavior from household demand, and the couple constraint between household members. These aspects are briefly reviewed in this article. We discover that trip-based approach is hardly competent for studies of intra-household interaction. By contrast, activity-based approach could employ utility-based model, rule-based model, micro-simulation model and complex multi-variable model, such as structural equation model, to better interpret resident's activity-travel behaviors. Finally, Tianjin's time-use dairy survey data are used to confirm the theories of intra-household activity-based approach and to deeply understand the Tianjin's activity-travel behaviors. We model the socio-demographics as exogenous, and activity duration time and relevant travel time as endogenetic in the context of structural equation model (SEM). The final LIRSEL model fits well. The estimate results confirm that travel is derived of activity participation, and activity-based approach can better solve the problems of trip-based model, such as linking the discrete travels through activities interaction. Moreover, significance of activity-travel interaction between household heads positively exists. In particularly, males dominate the outside work-related activities and females dominate the outside household-related activities, and they jointly participate in non-work activities in Tianjin's households. Furthermore, comparing the total effect and direct effect on household heads' travel time of socio-demographics, which takes both the indirect effect of activities and other household members into consideration, we found the significance is not the same and positively argue that the total effect contains more actual information about activity-travel behavior. In conclusion, theories and confirmed model have proved that activity-based approaches are much better than the trip-based one, especially in terms of the intra-household interaction. In the future research, we should spread this perspective and approach to a better understanding of the behavior and transportation in transiting China.
ZHANG Wenjia, CHAI Yanwei . Theories and Confirmed Model of Urban Resident's Travel Demand: Considering Intra-household Interaction[J]. Acta Geographica Sinica, 2008 , 63(12) : 1246 -1256 . DOI: 10.11821/xb200812002
[1] Chai Yanwei, Liu Zhilin, Li Zhengrong et al. Time-space Structure of Chinese Cities. Beijing: Peking University Press, 2002. 60-69.
[柴彦威, 刘志林, 李峥嵘等. 中国城市的时空间结构. 北京: 北京大学出版社, 2002. 60-69.]
[2] Cao Xiaoshu, Xue Desheng, Yan Xiaopei. Development tendency of urban transport geography. Scientia Geographica Sinica, 2006, 26(1): 111-117.
[ 曹小曙, 薛德升, 阎小培. 城市交通运输地理发展趋势. 地理科学, 2006, 26(1): 111-117]
[3] Chai Yanwei et al. (trans.). Jonhnston R J, Derek Gregory, David M Smith. The Dictionary of Human Geography. Beijing: The Commercial Press, 2005.
[柴彦威等译. 人文地理学词典. 北京: 商务印书馆, 2005.]
[4] Behrens R. Action in transport for the new millennium. Paper presented at the South African Transport Conference, 2000.
[5] Algers S, Eliasson J, Mattsson Lars-Göran. Is it time to use activity-based urban transport models? A discussion of planning needs and modelling possibilities. The Annals of Regional Science, 2005, 39: 767-789.
[6] Pas E I. Recent advances in activity-based travel demand modeling. Paper presented at Travel Model Improvement Program Activity-Based Travel Forecasting Conference Proceedings, June 2-5, 1996, Summary, Recommendations and Compendium of Papers, February 1997.
[7] Davidson W, Donnelly R, Vovsha P et al. Synthesis of first practices and operational research approaches in activity-based travel demand modeling. Transportatoon Research Part A, 2007, 41: 464-488.
[8] Chai Yanwei, Shen Jie. Travel-activity based research frame of urban spatial structure. Human Geography, 2006, 21(5): 108-113.
[柴彦威, 沈洁. 基于居民移动—活动行为的城市空间研究. 人文地理, 2006, 21(5): 108-113.]
[9] Juan Zhicai, Li Zhiyao, Zong Fang. A review of activity-based travel demand forecasting method. Journal of Highway and Transportation Research and Development, 2005, 22(6): 108-113.
[隽志才, 李志瑶, 宗芳. 基于活动链的出行需求预测方法综述. 公路交通科技, 2005, 22(6): 108-113.]
[10] Zong Fang, Juan Zhicai. Activity-based travel mode choice model and analysis on traffic demand management. Journal of Jilin University (Engineering and Technology Edition), 2007, 37(1): 48-53.
[宗芳, 隽志才. 基于活动的出行方式选 择模型与交通需求管理策略. 吉林大学学报(工学版), 2007, 37(1): 48-53.]
[11] Yang Min, Chen Xuewu, Wang Wei et al. Comparative study between activity-based and traditional transportation prediction. Planners, 2007, 23(11): 4-6.
[杨敏, 陈学武, 王炜等. 基于活动的交通需求预测方法与传统方法之比较 研究. 规划师, 2007, 23(11): 4-6.]
[12] Ettema D. Activity-based travel demand modeling. Ph.D. Dissertation. Universiteit van Amsterdam, 1996.
[13] Kitamura R. Review Paper: An evaluation of activity-based travel analysis. Transportation, 1988, 15: 9-34.
[14] Chapin F S Jr. Human Activity Patterns in the City. New York: John Wiley & Sons, Inc., 1974.
[15] Hägerstrand T. What about people in regional science? Papers of the Regional Science Association, 1970, 24: 7-21.
[16] Scott D M. Embracing activity analysis in transport geography: Merit, challenges and research frontiers. Journal of Transport Geography, 2006, 14: 389-392.
[17] Timmermans H, Arentze T, Joh C-H. Analysing space-time behaviour: New approaches to old problems. Progress in Human Geography, 2002, 26(2): 175-190.
[18] Ma H, Goulias K G. A dynamic analysis of person and household activity and travel patterns using data from the first two waves in the Puget Sound Transportation Panel. Transportation, 2007, 24(3): 309-324.
[19] Buliung R N, Kanaroglou P S. Urban form and household activity-travel behavior. Growth and Change, 2006, 37(2): 172-199.
[20] Thulin E, Vilhelmson B. Virtual mobility of urban youth: ICT-based communication in Sweden. Tijdschrift voor Economische en Sociale Geografie, 2005, 96(5): 477-487.
[21] Jones P M, Dix M C, Clarke M I et al. Understanding Travel Behavior. Aldershot, UK: Gower Publishing Co., Ltd., 1983.
[22] Srinivasan K K, Athuru R S. Analysis of within-household effects and between-household differences in maintenance activity allocation. Transportation, 2005, 32: 495-521.
[23] Bhat C R, Gossen R. A mixed multinomial logit model analysis of weekend recreational episode type choice. Transportation Research B, 2002, 38: 767-787.
[24] Bhat C R, Srinivasan S. A multidimensional mixed ordered-response model for analyzing weekend activity participation. Transportation Research B, 2005, 39: 255-278.
[25] Levinson D. Space, time, life-stage, and the allocation of time. Transportation, 1999, 26: 141-171.
[26] Golob T F, McNally M G. A model of activity participation and travel interactions between household heads. Transportation Research B, 1997, 31(3): 177-194.
[27] Simma A, Axhausen K W. Within household allocation of travel: The case of upper Austria. Paper presented at the 80th Annual Conference of the Transportation Research Board, Washington, D.C., 2001.
[28] Cao Xinyu, Chai Yanwei. Gender-role based differences in time allocation: A case study of Shenzhen, China. Paper presented at the 87th Annual Meeting of TRB, Washington, D.C., 2007.
[29] Lu X, Pas E I. Socio-demographics, activity participation and travel behaviour. Transportation Research Part A, 1998, 33: 1-18.
[30] Golob T F. Structural equation modeling for travel behavior research. Transportation Research B, 2003, 37: 1-25.
[31] Hau Jietai, Wen Zhonglin, Cheng Zijuan. Structural Equation Model and Its Application. Beijing: Education Science Press, 2006.
[侯杰泰, 温忠麟, 成子娟. 结构方程模型及其应用. 北京: 教育科学出版社. 2006.]
[32] Mathilda du Toit, Stephen du Toit. Interactive LISREL: User's Guide. IL: Scientific Software International, Inc., 2001.
[33] Zheng Jie, Lu Huapu. Study on the impacts of urban land use on travel demand. Central South Highway Engineering, 2007, 32(2): 175-179.
[ 郑洁, 陆化普. 城市土地利用对交通需求特性影响研究. 中南公路工程, 2007, 32(2): 175-179.]
[34] Zhou Suhong, Yan Xiaopei. The relationship between urban structure and traffic demand in Guangzhou. Acta Geographica Sinica, 2005, 60(1): 131-142.
[周素红, 闫小培. 广州城市空间结构与交通需求关系. 地理学报, 2005, 60(1): 131-142.]
[35] Hanson S, Hanson P. The travel-activity patterns of urban residents: Dimensions and relationships to sociodemographic characteristics. Economic Geography, 1981, 57(4): 332-347.
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