IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0184191.html
   My bibliography  Save this article

An experimental study of the Online Information Paradox: Does en-route information improve road network performance?

Author

Listed:
  • Kasun P Wijayaratna
  • Vinayak V Dixit
  • Laurent Denant-Boemont
  • S Travis Waller

Abstract

This study investigates the empirical presence of a theoretical transportation paradox, defined as the “Online Information Paradox” (OIP). The paradox suggests that, for certain road networks, the provision of online information deteriorate travel conditions for all users of that network relative to the situation where no online information is provided to users. The analytical presence of the paradox was derived for a specific network structure by using two equilibrium models, the first being the Expected User Equilibrium (EUE) solution (no information scenario) and the other being the User Equilibrium with Recourse (UER) solution (with information scenario). An incentivised computerised route choice game was designed using the concepts of experimental economics and administered in a controlled laboratory environment to investigate the physical presence of the paradox. Aggregate statistics of path flows and Total System Travel Costs (TSTC) were used to compare the experimental results with the theoretical findings. A total of 12 groups of 12 participants completed the experiment and the OIP and the occurrence of the OIP being significant was observed in 11 of the 12 cases. Though information increased travel costs for users on average, it reduced the volatility of travel costs experienced in the no information scenario indicating that information can achieve a more reliable system. Further replications of similar experiments and more importantly field based identification of the phenomena will force transport professionals to be aware of the emergence of the paradox. In addition, studies such as this emphasise the need for the adoption of adaptive traffic assignment techniques to appropriately model the acquisition of information on a road network.

Suggested Citation

  • Kasun P Wijayaratna & Vinayak V Dixit & Laurent Denant-Boemont & S Travis Waller, 2017. "An experimental study of the Online Information Paradox: Does en-route information improve road network performance?," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-17, September.
  • Handle: RePEc:plo:pone00:0184191
    DOI: 10.1371/journal.pone.0184191
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0184191
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0184191&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0184191?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
    ---><---

    References listed on IDEAS

    as
    1. Daganzo, Carlos F., 2011. "On the macroscopic stability of freeway traffic," Transportation Research Part B: Methodological, Elsevier, vol. 45(5), pages 782-788, June.
    2. Morgan, John & Orzen, Henrik & Sefton, Martin, 2009. "Network architecture and traffic flows: Experiments on the Pigou-Knight-Downs and Braess Paradoxes," Games and Economic Behavior, Elsevier, vol. 66(1), pages 348-372, May.
    3. Avinash Unnikrishnan & Steven Waller, 2009. "User Equilibrium with Recourse," Networks and Spatial Economics, Springer, vol. 9(4), pages 575-593, December.
    4. Lindsey, Robin & Daniel, Terry & Gisches, Eyran & Rapoport, Amnon, 2014. "Pre-trip information and route-choice decisions with stochastic travel conditions: Theory," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 187-207.
    5. Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
    6. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    7. Xuan Lu & Song Gao & Eran Ben-Elia & Ryan Pothering, 2014. "Travelers' Day-to-Day Route Choice Behavior with Real-Time Information in a Congested Risky Network," Mathematical Population Studies, Taylor & Francis Journals, vol. 21(4), pages 205-219, December.
    8. Daganzo, Carlos F. & Gayah, Vikash V. & Gonzales, Eric J., 2011. "Macroscopic relations of urban traffic variables: Bifurcations, multivaluedness and instability," Transportation Research Part B: Methodological, Elsevier, vol. 45(1), pages 278-288, January.
    9. Rey, David & Dixit, Vinayak V. & Ygnace, Jean-Luc & Waller, S. Travis, 2016. "An endogenous lottery-based incentive mechanism to promote off-peak usage in congested transit systems," Transport Policy, Elsevier, vol. 46(C), pages 46-55.
    10. F. H. Knight, 1924. "Some Fallacies in the Interpretation of Social Cost," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 38(4), pages 582-606.
    11. Henn, Vincent & Ottomanelli, Michele, 2006. "Handling uncertainty in route choice models: From probabilistic to possibilistic approaches," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1526-1538, December.
    12. Vinayak Dixit & Laurent Denant-Boemont, 2014. "Is equilibrium in transport pure Nash, mixed or Stochastic?," Post-Print halshs-02319751, HAL.
    13. Rapoport, Amnon & Mak, Vincent & Zwick, Rami, 2006. "Navigating congested networks with variable demand: Experimental evidence," Journal of Economic Psychology, Elsevier, vol. 27(5), pages 648-666, October.
    14. Rapoport, Amnon & Kugler, Tamar & Dugar, Subhasish & Gisches, Eyran J., 2009. "Choice of routes in congested traffic networks: Experimental tests of the Braess Paradox," Games and Economic Behavior, Elsevier, vol. 65(2), pages 538-571, March.
    15. Eran Ben-Elia & Erel Avineri, 2015. "Response to Travel Information: A Behavioural Review," Transport Reviews, Taylor & Francis Journals, vol. 35(3), pages 352-377, May.
    16. Selten, R. & Chmura, T. & Pitz, T. & Kube, S. & Schreckenberg, M., 2007. "Commuters route choice behaviour," Games and Economic Behavior, Elsevier, vol. 58(2), pages 394-406, February.
    17. Amnon Rapoport & Tamar Kugler & Subhasish Dugar & Eyran J. Gisches, 2008. "Braess Paradox in the Laboratory: Experimental Study of Route Choice in Traffic Networks with Asymmetric Costs," Springer Optimization and Its Applications, in: Tamar Kugler & J. Cole Smith & Terry Connolly & Young-Jun Son (ed.), Decision Modeling and Behavior in Complex and Uncertain Environments, pages 309-337, Springer.
    18. Wijayaratna, Kasun P. & Dixit, Vinayak V., 2016. "Impact of information on risk attitudes: Implications on valuation of reliability and information," Journal of choice modelling, Elsevier, vol. 20(C), pages 16-34.
    19. Gao, Song & Chabini, Ismail, 2006. "Optimal routing policy problems in stochastic time-dependent networks," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 93-122, February.
    20. Rapoport, Amnon & Gisches, Eyran J. & Daniel, Terry & Lindsey, Robin, 2014. "Pre-trip information and route-choice decisions with stochastic travel conditions: Experiment," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 154-172.
    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. Nicholas Janusch & Stephan Kroll & Christopher Goemans & Todd L. Cherry & Steffen Kallbekken, 2021. "Learning to accept welfare-enhancing policies: an experimental investigation of congestion pricing," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 59-86, March.
    2. Zhang, Qianran & Ma, Shoufeng & Tian, Junfang & Rose, John M. & Jia, Ning, 2022. "Mode choice between autonomous vehicles and manually-driven vehicles: An experimental study of information and reward," Transportation Research Part A: Policy and Practice, Elsevier, vol. 157(C), pages 24-39.
    3. Vasiliki Kostami, 2020. "Price and Lead time Disclosure Strategies in Inventory Systems," Production and Operations Management, Production and Operations Management Society, vol. 29(12), pages 2760-2788, December.
    4. Xinming Zang & Zhenqi Guo & Jingai Ma & Yongguang Zhong & Xiangfeng Ji, 2021. "Target-Oriented User Equilibrium Considering Travel Time, Late Arrival Penalty, and Travel Cost on the Stochastic Tolled Traffic Network," Sustainability, MDPI, vol. 13(17), pages 1-22, 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. Levy, Nadav & Klein, Ido & Ben-Elia, Eran, 2018. "Emergence of cooperation and a fair system optimum in road networks: A game-theoretic and agent-based modelling approach," Research in Transportation Economics, Elsevier, vol. 68(C), pages 46-55.
    2. Terry E. Daniel & Eyran J. Gisches & Amnon Rapoport, 2009. "Departure Times in Y-Shaped Traffic Networks with Multiple Bottlenecks," American Economic Review, American Economic Association, vol. 99(5), pages 2149-2176, December.
    3. Xiao Han & Yun Yu & Bin Jia & Zi‐You Gao & Rui Jiang & H. Michael Zhang, 2021. "Coordination Behavior in Mode Choice: Laboratory Study of Equilibrium Transformation and Selection," Production and Operations Management, Production and Operations Management Society, vol. 30(10), pages 3635-3656, October.
    4. Sun, Xiaoyan & Han, Xiao & Bao, Jian-Zhang & Jiang, Rui & Jia, Bin & Yan, Xiaoyong & Zhang, Boyu & Wang, Wen-Xu & Gao, Zi-You, 2017. "Decision dynamics of departure times: Experiments and modeling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 74-82.
    5. Rapoport, Amnon & Qi, Hang & Mak, Vincent & Gisches, Eyran J., 2019. "When a few undermine the whole: A class of social dilemmas in ridesharing," Journal of Economic Behavior & Organization, Elsevier, vol. 166(C), pages 125-137.
    6. Emmanuel Dechenaux & Shakun Mago & Laura Razzolini, 2014. "Traffic congestion: an experimental study of the Downs-Thomson paradox," Experimental Economics, Springer;Economic Science Association, vol. 17(3), pages 461-487, September.
    7. Tanjim Hossain & Dylan Minor & John Morgan, 2011. "Competing Matchmakers: An Experimental Analysis," Management Science, INFORMS, vol. 57(11), pages 1913-1925, November.
    8. Nicholas Janusch & Stephan Kroll & Christopher Goemans & Todd L. Cherry & Steffen Kallbekken, 2021. "Learning to accept welfare-enhancing policies: an experimental investigation of congestion pricing," Experimental Economics, Springer;Economic Science Association, vol. 24(1), pages 59-86, March.
    9. Qi, Hang & Jia, Ning & Qu, Xiaobo & He, Zhengbing, 2023. "Investigating day-to-day route choices based on multi-scenario laboratory experiments, Part I: Route-dependent attraction and its modeling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 167(C).
    10. Yamada, Takashi & Hanaki, Nobuyuki, 2016. "An experiment on Lowest Unique Integer Games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 88-102.
    11. Vincent Mak & Darryl A. Seale & Eyran J. Gisches & Amnon Rapoport & Meng Cheng & Myounghee Moon & Rui Yang, 2018. "A network ridesharing experiment with sequential choice of transportation mode," Theory and Decision, Springer, vol. 85(3), pages 407-433, October.
    12. Rapoport, Amnon & Gisches, Eyran J. & Daniel, Terry & Lindsey, Robin, 2014. "Pre-trip information and route-choice decisions with stochastic travel conditions: Experiment," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 154-172.
    13. Wijayaratna, Kasun P. & Dixit, Vinayak V., 2016. "Impact of information on risk attitudes: Implications on valuation of reliability and information," Journal of choice modelling, Elsevier, vol. 20(C), pages 16-34.
    14. Kucharski, Rafał & Gentile, Guido, 2019. "Simulation of rerouting phenomena in Dynamic Traffic Assignment with the Information Comply Model," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 414-441.
    15. Miller, Harvey J., 2013. "Beyond sharing: cultivating cooperative transportation systems through geographic information science," Journal of Transport Geography, Elsevier, vol. 31(C), pages 296-308.
    16. Eyran Gisches & Amnon Rapoport, 2012. "Degrading network capacity may improve performance: private versus public monitoring in the Braess Paradox," Theory and Decision, Springer, vol. 73(2), pages 267-293, August.
    17. Sun, Xiaoyan & Li, Wentao & Jiang, Rui & Zhu, Yubing & Chen, Dong, 2022. "Study on the influence of road capacity and information feedback on urban traffic system equilibrium state," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    18. Fosgerau, Mogens & Jiang, Gege, 2019. "Travel time variability and rational inattention," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 1-14.
    19. Rey, David & Dixit, Vinayak V. & Ygnace, Jean-Luc & Waller, S. Travis, 2016. "An endogenous lottery-based incentive mechanism to promote off-peak usage in congested transit systems," Transport Policy, Elsevier, vol. 46(C), pages 46-55.
    20. John Hartman, 2012. "Special Issue on Transport Infrastructure: A Route Choice Experiment with an Efficient Toll," Networks and Spatial Economics, Springer, vol. 12(2), pages 205-222, June.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0184191. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.