IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v129y2019icp271-287.html
   My bibliography  Save this article

A comparison of time-use behavior in metropolitan areas using pattern recognition techniques

Author

Listed:
  • Allahviranloo, Mahdieh
  • Aissaoui, Leila

Abstract

A better understanding of the connection of urban forms and travel behavior is critical to the operation of the existing and the design of the future transportation infrastructure. A comprehensive analysis of travel behavior across different regions would capture the underlying dependency among time-use behavior, the built environment, and the demographics of travelers. This paper introduces a method to measure the similarity of activity chains in different regions based on pattern segmentation and recognition. Travel behavior of residents of five different urban regions in the United States are compared: New York City, Los Angeles County, Chicago, San Francisco, and Atlanta. A total of 80,894 activity patterns is analyzed to address three goals: (1) to find a set of representative activity patterns for the residents of each region; (2) to analyze the dissimilarities/similarities in the activity patterns within and between the regions; and (3) to develop econometric models to assess and compare the role of demographic attributes on time use behavior. The outcome of the analysis supports and highlights the differences between study areas.

Suggested Citation

  • Allahviranloo, Mahdieh & Aissaoui, Leila, 2019. "A comparison of time-use behavior in metropolitan areas using pattern recognition techniques," Transportation Research Part A: Policy and Practice, Elsevier, vol. 129(C), pages 271-287.
  • Handle: RePEc:eee:transa:v:129:y:2019:i:c:p:271-287
    DOI: 10.1016/j.tra.2019.08.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856416310011
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tra.2019.08.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jianchuan Xianyu & Soora Rasouli & Harry Timmermans, 2017. "Analysis of variability in multi-day GPS imputed activity-travel diaries using multi-dimensional sequence alignment and panel effects regression models," Transportation, Springer, vol. 44(3), pages 533-553, May.
    2. Goulias, Konstadinos G., 1999. "Longitudinal analysis of activity and travel pattern dynamics using generalized mixed Markov latent class models," Transportation Research Part B: Methodological, Elsevier, vol. 33(8), pages 535-558, November.
    3. Abdul Pinjari & Ram Pendyala & Chandra Bhat & Paul Waddell, 2007. "Modeling residential sorting effects to understand the impact of the built environment on commute mode choice," Transportation, Springer, vol. 34(5), pages 557-573, September.
    4. Adler, Thomas & Ben-Akiva, Moshe, 1979. "A theoretical and empirical model of trip chaining behavior," Transportation Research Part B: Methodological, Elsevier, vol. 13(3), pages 243-257, September.
    5. Mokhtarian, Patricia L. & Cao, Xinyu, 2008. "Examining the impacts of residential self-selection on travel behavior: A focus on methodologies," Transportation Research Part B: Methodological, Elsevier, vol. 42(3), pages 204-228, March.
    6. Lee, Ming S. & McNally, Michael G., 2003. "On the structure of weekly activity/travel patterns," Transportation Research Part A: Policy and Practice, Elsevier, vol. 37(10), pages 823-839, December.
    7. Lee, Ming S. & McNally, Michael G., 2003. "On the Structure of Weekly Activity/Travel Patterns," University of California Transportation Center, Working Papers qt15w464vp, University of California Transportation Center.
    8. Arentze, Theo A. & Timmermans, Harry J.P., 2009. "A need-based model of multi-day, multi-person activity generation," Transportation Research Part B: Methodological, Elsevier, vol. 43(2), pages 251-265, February.
    9. Moshe Ben-Akiva & John L. Bowman, 1998. "Integration of an Activity-based Model System and a Residential Location Model," Urban Studies, Urban Studies Journal Limited, vol. 35(7), pages 1131-1153, June.
    10. Auld, Joshua & Mohammadian, Abolfazl(Kouros), 2012. "Activity planning processes in the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1386-1403.
    11. Gronau, Reuben, 1977. "Leisure, Home Production, and Work-The Theory of the Allocation of Time Revisited," Journal of Political Economy, University of Chicago Press, vol. 85(6), pages 1099-1123, December.
    12. Bhat, Chandra R. & Guo, Jessica Y., 2007. "A comprehensive analysis of built environment characteristics on household residential choice and auto ownership levels," Transportation Research Part B: Methodological, Elsevier, vol. 41(5), pages 506-526, June.
    13. Crane, Randall & Crepeau, Richard, 1998. "Does Neighborhood Design Influence Travel?: Behavioral Analysis of Travel Diary and GIS Data," University of California Transportation Center, Working Papers qt4pj4s7t8, University of California Transportation Center.
    14. Cao, Xinyu & Mokhtarian, Patricia & Handy, Susan, 2008. "Examining The Impacts of Residential Self-Selection on Travel Behavior: Methodologies and Empirical Findings," Institute of Transportation Studies, Working Paper Series qt08x1k476, Institute of Transportation Studies, UC Davis.
    15. W C Wilson, 1998. "Activity Pattern Analysis by Means of Sequence-Alignment Methods," Environment and Planning A, , vol. 30(6), pages 1017-1038, June.
    16. Allahviranloo, Mahdieh & Recker, Will, 2013. "Daily activity pattern recognition by using support vector machines with multiple classes," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 16-43.
    17. Peter T.L. Popkowski Leszczyc & Harry Timmermans, 2002. "Unconditional and conditional competing risk models of activity duration and activity sequencing decisions: An empirical comparison," Journal of Geographical Systems, Springer, vol. 4(2), pages 157-170, June.
    18. George Sammour & Koen Vanhoof, 2018. "A validation measure for computational scheduler activity-based transportation models based on sequence alignment methods," Transportation Planning and Technology, Taylor & Francis Journals, vol. 41(7), pages 736-751, October.
    19. Mahdieh Allahviranloo & Will Recker, 2015. "Mining activity pattern trajectories and allocating activities in the network," Transportation, Springer, vol. 42(4), pages 561-579, July.
    20. Kitamura, Ryuichi & Fujii, Satoshi & Pas, Eric I., 1997. "Time-use data, analysis and modeling: toward the next generation of transportation planning methodologies," Transport Policy, Elsevier, vol. 4(4), pages 225-235, October.
    21. Mokhtarian, Patricia L. & Chen, Cynthia, 2004. "TTB or not TTB, that is the question: a review and analysis of the empirical literature on travel time (and money) budgets," Transportation Research Part A: Policy and Practice, Elsevier, vol. 38(9-10), pages 643-675.
    22. Pyrialakou, V. Dimitra & Gkritza, Konstantina & Fricker, Jon D., 2016. "Accessibility, mobility, and realized travel behavior: Assessing transport disadvantage from a policy perspective," Journal of Transport Geography, Elsevier, vol. 51(C), pages 252-269.
    23. Bhat, Chandra R., 2011. "The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 923-939, August.
    24. Jinhyun Hong & Qing Shen & Lei Zhang, 2014. "How do built-environment factors affect travel behavior? A spatial analysis at different geographic scales," Transportation, Springer, vol. 41(3), pages 419-440, May.
    25. Handy, Susan & Cao, Xinyu & Mokhtarian, Patricia L., 2005. "Correlation or causality between the built environment and travel behavior? Evidence from Northern California," University of California Transportation Center, Working Papers qt5b76c5kg, University of California Transportation Center.
    26. Pollak, Robert A & Wachter, Michael L, 1975. "The Relevance of the Household Production Function and Its Implications for the Allocation of Time," Journal of Political Economy, University of Chicago Press, vol. 83(2), pages 255-277, April.
    27. Recker, W. W., 1995. "The household activity pattern problem: General formulation and solution," Transportation Research Part B: Methodological, Elsevier, vol. 29(1), pages 61-77, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hu, Songhua & Xiong, Chenfeng & Chen, Peng & Schonfeld, Paul, 2023. "Examining nonlinearity in population inflow estimation using big data: An empirical comparison of explainable machine learning models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    2. Hui-Huang Tai & Yun-Hua Chang, 2022. "Reducing pollutant emissions from vessel maneuvering in port areas," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(3), pages 651-671, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kamruzzaman, Md. & Baker, Douglas & Washington, Simon & Turrell, Gavin, 2013. "Residential dissonance and mode choice," Journal of Transport Geography, Elsevier, vol. 33(C), pages 12-28.
    2. Ding, Chuan & Wang, Donggen & Liu, Chao & Zhang, Yi & Yang, Jiawen, 2017. "Exploring the influence of built environment on travel mode choice considering the mediating effects of car ownership and travel distance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 65-80.
    3. Watanabe, Hajime & Maruyama, Takuya, 2024. "A Bayesian sample selection model with a binary outcome for handling residential self-selection in individual car ownership," Journal of choice modelling, Elsevier, vol. 51(C).
    4. Bhat, Chandra R. & Astroza, Sebastian & Sidharthan, Raghuprasad & Alam, Mohammad Jobair Bin & Khushefati, Waleed H., 2014. "A joint count-continuous model of travel behavior with selection based on a multinomial probit residential density choice model," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 31-51.
    5. Md. Kamruzzaman & Simon Washington & Douglas Baker & Wendy Brown & Billie Giles-Corti & Gavin Turrell, 2016. "Built environment impacts on walking for transport in Brisbane, Australia," Transportation, Springer, vol. 43(1), pages 53-77, January.
    6. Xinyu Cao & Patricia L. Mokhtarian, 2012. "The connections among accessibility, self- selection and walking behaviour: a case study of Northern California residents," Chapters, in: Karst T. Geurs & Kevin J. Krizek & Aura Reggiani (ed.), Accessibility Analysis and Transport Planning, chapter 5, pages 73-95, Edward Elgar Publishing.
    7. Van Acker, Veronique & Witlox, Frank, 2010. "Car ownership as a mediating variable in car travel behaviour research using a structural equation modelling approach to identify its dual relationship," Journal of Transport Geography, Elsevier, vol. 18(1), pages 65-74.
    8. Humphreys, John & Ahern, Aoife, 2019. "Is travel based residential self-selection a significant influence in modal choice and household location decisions?," Transport Policy, Elsevier, vol. 75(C), pages 150-160.
    9. Shen, Qing & Chen, Peng & Pan, Haixiao, 2016. "Factors affecting car ownership and mode choice in rail transit-supported suburbs of a large Chinese city," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 31-44.
    10. Abdul Rawoof Pinjari & Chandra R. Bhat, 2011. "Activity-based Travel Demand Analysis," Chapters, in: André de Palma & Robin Lindsey & Emile Quinet & Roger Vickerman (ed.), A Handbook of Transport Economics, chapter 10, Edward Elgar Publishing.
    11. Kamruzzaman, Md. & Shatu, Farjana Mostafiz & Hine, Julian & Turrell, Gavin, 2015. "Commuting mode choice in transit oriented development: Disentangling the effects of competitive neighbourhoods, travel attitudes, and self-selection," Transport Policy, Elsevier, vol. 42(C), pages 187-196.
    12. Metin Senbil & Ryuichi Kitamura & Jamilah Mohamad, 2009. "Residential location, vehicle ownership and travel in Asia: a comparative analysis of Kei-Han-Shin and Kuala Lumpur metropolitan areas," Transportation, Springer, vol. 36(3), pages 325-350, May.
    13. Cao, Xinyu & Mokhtarian, Patricia & Handy, Susan, 2008. "Examining The Impacts of Residential Self-Selection on Travel Behavior: Methodologies and Empirical Findings," Institute of Transportation Studies, Working Paper Series qt08x1k476, Institute of Transportation Studies, UC Davis.
    14. Chowdhury, Tufayel & Scott, Darren M., 2020. "An analysis of the built environment and auto travel in Halifax, Canada," Transport Policy, Elsevier, vol. 94(C), pages 23-33.
    15. Su, Qing & Zhou, Liren, 2012. "Parking management, financial subsidies to alternatives to drive alone and commute mode choices in Seattle," Regional Science and Urban Economics, Elsevier, vol. 42(1-2), pages 88-97.
    16. Md. Kamruzzaman & Simon Washington & Douglas Baker & Wendy Brown & Billie Giles-Corti & Gavin Turrell, 2016. "Built environment impacts on walking for transport in Brisbane, Australia," Transportation, Springer, vol. 43(1), pages 53-77, January.
    17. Ding, Yu & Lu, Huapu, 2016. "Activity participation as a mediating variable to analyze the effect of land use on travel behavior: A structural equation modeling approach," Journal of Transport Geography, Elsevier, vol. 52(C), pages 23-28.
    18. Singh, Abhilash C. & Faghih Imani, Ahmadreza & Sivakumar, Aruna & Luna Xi, Yang & Miller, Eric J., 2024. "A joint analysis of accessibility and household trip frequencies by travel mode," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    19. Allahviranloo, Mahdieh & Recker, Will, 2013. "Daily activity pattern recognition by using support vector machines with multiple classes," Transportation Research Part B: Methodological, Elsevier, vol. 58(C), pages 16-43.
    20. van de Coevering, Paul & Maat, Kees & van Wee, Bert, 2018. "Residential self-selection, reverse causality and residential dissonance. A latent class transition model of interactions between the built environment, travel attitudes and travel behavior," Transportation Research Part A: Policy and Practice, Elsevier, vol. 118(C), pages 466-479.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transa:v:129:y:2019:i:c:p:271-287. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/547/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.