IDEAS home Printed from https://ideas.repec.org/a/eee/transa/v50y2013icp86-104.html
   My bibliography  Save this article

A novel agent-based transportation model of a university campus with application to quantifying the environmental cost of parking search

Author

Listed:
  • Guo, Liya
  • Huang, Shan
  • Sadek, Adel W.

Abstract

This paper develops a novel agent-based transportation model of a university campus, primarily focusing on vehicle-related travel and the associated parking search process. In developing and validating the model, the study uses a wide range of data sources including: (1) a brief “trip-diary” type survey; (2) 24-h traffic counts at the entry and exit points to the campus; (3) information about the university buildings’ class room capacities and class schedules; (4) parking occupancy surveys; and (5) select intersections’ turn movement counts. The agent-based model is designed to explicitly capture trip chaining behavior, and the often-overlooked phenomenon of drivers searching for an available parking spot. The parking search process is modeled using a sequential game-theoretic, neo-additive capacity model which accounts for drivers optimistic and pessimistic attitudes regarding parking availability in their most desirable lot. The agent-based demand model is then integrated with the Transportation Analysis and Simulation System (TRANSIMS), which serves as the traffic micro-simulation engine, and with the MOVES2010 emissions model. Following the validation of the integrated model, it is used to quantify the environmental cost of the parking search process on campus. The study may be regarded as one of the few studies to integrate an agent- or activity based model of travel demand, albeit admittedly simplified, with a fine-grained transportation network, a detailed traffic micro-simulation, and a project-level emissions model. Another contribution of the study is in terms of quantifying the environmental cost, in terms of wasted fuel and increased emissions, associated with the parking search process on campus.

Suggested Citation

  • Guo, Liya & Huang, Shan & Sadek, Adel W., 2013. "A novel agent-based transportation model of a university campus with application to quantifying the environmental cost of parking search," Transportation Research Part A: Policy and Practice, Elsevier, vol. 50(C), pages 86-104.
    • Handle: RePEc:eee:transa:v:50:y:2013:i:c:p:86-104
    DOI: 10.1016/j.tra.2013.01.045
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0965856413000682
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tra.2013.01.045?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. Chateauneuf, Alain & Eichberger, Jurgen & Grant, Simon, 2007. "Choice under uncertainty with the best and worst in mind: Neo-additive capacities," Journal of Economic Theory, Elsevier, vol. 137(1), pages 538-567, November.
    2. Arentze, Theo A. & Timmermans, Harry J. P., 2004. "A learning-based transportation oriented simulation system," Transportation Research Part B: Methodological, Elsevier, vol. 38(7), pages 613-633, August.
    3. I. Meloni & L. Guala & A. Loddo, 2004. "Time allocation to discretionary in-home, out-of-home activities and to trips," Transportation, Springer, vol. 31(1), pages 69-96, February.
    4. Davidson, William & Donnelly, Robert & Vovsha, Peter & Freedman, Joel & Ruegg, Steve & Hicks, Jim & Castiglione, Joe & Picado, Rosella, 2007. "Synthesis of first practices and operational research approaches in activity-based travel demand modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 464-488, June.
    5. Roorda, Matthew J. & Miller, Eric J. & Habib, Khandker M.N., 2008. "Validation of TASHA: A 24-h activity scheduling microsimulation model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 42(2), pages 360-375, February.
    6. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    7. Ram Pendyala & Toshiyuki Yamamoto & Ryuichi Kitamura, 2002. "On the formulation of time-space prisms to model constraints on personal activity-travel engagement," Transportation, Springer, vol. 29(1), pages 73-94, February.
    8. DeSerpa, A C, 1971. "A Theory of the Economics of Time," Economic Journal, Royal Economic Society, vol. 81(324), pages 828-846, December.
    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. Nourinejad, Mehdi & Roorda, Matthew J., 2017. "Impact of hourly parking pricing on travel demand," Transportation Research Part A: Policy and Practice, Elsevier, vol. 98(C), pages 28-45.
    2. Hamad, Khaled & Obaid, Lubna, 2022. "Tour-based travel demand forecasting model for a university campus," Transport Policy, Elsevier, vol. 117(C), pages 118-137.
    3. Chidambaram, Bhuvanachithra & Janssen, Marco A. & Rommel, Jens & Zikos, Dimitrios, 2014. "Commuters’ mode choice as a coordination problem: A framed field experiment on traffic policy in Hyderabad, India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 65(C), pages 9-22.
    4. Lewe, J.-H. & Hivin, L.F. & Mavris, D.N., 2014. "A multi-paradigm approach to system dynamics modeling of intercity transportation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 71(C), pages 188-202.
    5. Chai, Huajun, 2019. "Dynamic Traffic Routing and Adaptive Signal Control in a Connected Vehicles Environment," Institute of Transportation Studies, Working Paper Series qt9ng3z8vn, Institute of Transportation Studies, UC Davis.
    6. Cao, Jin & Menendez, Monica, 2018. "Quantification of potential cruising time savings through intelligent parking services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 116(C), pages 151-165.

    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. Marcela Munizaga & Sergio Jara-Díaz & Paulina Greeven & Chandra Bhat, 2008. "Econometric Calibration of the Joint Time Assignment--Mode Choice Model," Transportation Science, INFORMS, vol. 42(2), pages 208-219, May.
    2. 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.
    3. Lee, Yuhwa & Washington, Simon & Frank, Lawrence D., 2009. "Examination of relationships between urban form, household activities, and time allocation in the Atlanta Metropolitan Region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 360-373, May.
    4. Chandra Bhat & Konstadinos Goulias & Ram Pendyala & Rajesh Paleti & Raghuprasad Sidharthan & Laura Schmitt & Hsi-Hwa Hu, 2013. "A household-level activity pattern generation model with an application for Southern California," Transportation, Springer, vol. 40(5), pages 1063-1086, September.
    5. Linda Nijland & Theo Arentze & Harry Timmermans, 2013. "Representing and estimating interactions between activities in a need-based model of activity generation," Transportation, Springer, vol. 40(2), pages 413-430, February.
    6. Bhat, Chandra R. & Srinivasan, Sivaramakrishnan & Sen, Sudeshna, 2006. "A joint model for the perfect and imperfect substitute goods case: Application to activity time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 40(10), pages 827-850, December.
    7. Moyin Li & Nebiyou Tilahun, 2020. "A comparative analysis of discretionary time allocation for social and non-social activities in the U.S. between 2003 and 2013," Transportation, Springer, vol. 47(2), pages 893-909, April.
    8. Dianat, Leila & Habib, Khandker Nurul & Miller, Eric J., 2020. "Modeling and forecasting daily non-work/school activity patterns in an activity-based model using skeleton schedule constraints," Transportation Research Part A: Policy and Practice, Elsevier, vol. 133(C), pages 337-352.
    9. Nurul Habib, Khandker M. & Day, Nicholas & Miller, Eric J., 2009. "An investigation of commuting trip timing and mode choice in the Greater Toronto Area: Application of a joint discrete-continuous model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(7), pages 639-653, August.
    10. Bhat, Chandra R., 2005. "A multiple discrete-continuous extreme value model: formulation and application to discretionary time-use decisions," Transportation Research Part B: Methodological, Elsevier, vol. 39(8), pages 679-707, September.
    11. Castro, Marisol & Bhat, Chandra R. & Pendyala, Ram M. & Jara-Díaz, Sergio R., 2012. "Accommodating multiple constraints in the multiple discrete–continuous extreme value (MDCEV) choice model," Transportation Research Part B: Methodological, Elsevier, vol. 46(6), pages 729-743.
    12. Jara-Díaz, Sergio & Rosales-Salas, Jorge, 2017. "Beyond transport time: A review of time use modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 97(C), pages 209-230.
    13. Ozonder, Gozde & Miller, Eric J., 2021. "Longitudinal investigation of skeletal activity episode timing decisions – A copula approach," Journal of choice modelling, Elsevier, vol. 40(C).
    14. Kuriyama, Koichi & Shoji, Yasushi & Tsuge, Takahiro, 2020. "The value of leisure time of weekends and long holidays: The multiple discrete–continuous extreme value (MDCEV) choice model with triple constraints," Journal of choice modelling, Elsevier, vol. 37(C).
    15. Yasmin, Farhana & Morency, Catherine & Roorda, Matthew J., 2015. "Assessment of spatial transferability of an activity-based model, TASHA," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 200-213.
    16. Lin, Tao & Wang, Donggen, 2015. "Tradeoffs between in- and out-of-residential neighborhood locations for discretionary activities and time use: do social contexts matter?," Journal of Transport Geography, Elsevier, vol. 47(C), pages 119-127.
    17. Yoon, Seo Youn & Ravulaparthy, Srinath K. & Goulias, Konstadinos G., 2014. "Dynamic diurnal social taxonomy of urban environments using data from a geocoded time use activity-travel diary and point-based business establishment inventory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 3-17.
    18. Dane, Gamze & Arentze, Theo A. & Timmermans, Harry J.P. & Ettema, Dick, 2014. "Simultaneous modeling of individuals’ duration and expenditure decisions in out-of-home leisure activities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 93-103.
    19. Saxena, Shobhit & Pinjari, Abdul Rawoof & Paleti, Rajesh, 2022. "A multiple discrete-continuous extreme value model with ordered preferences (MDCEV-OP): Modelling framework for episode-level activity participation and time-use analysis," Transportation Research Part B: Methodological, Elsevier, vol. 166(C), pages 259-283.
    20. Italo Meloni & Erika Spissu & Massimiliano Bez, 2007. "A Model of the Dynamic Process of Time Allocation to Discretionary Activities," Transportation Science, INFORMS, vol. 41(1), pages 15-28, February.

    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:50:y:2013:i:c:p:86-104. 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.