IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v270y2015icp179-192.html
   My bibliography  Save this article

The peloton superorganism and protocooperative behavior

Author

Listed:
  • Trenchard, Hugh

Abstract

A theoretical framework for protocooperative behavior in pelotons (groups of cyclists) is proposed. A threshold between cooperative and free-riding behaviors in pelotons is modeled, together comprising protocooperative behavior (different from protocooperation), hypothesized to emerge in biological systems involving energy savings mechanisms. Further, the tension between intra-group cooperation and inter-group competition is consistent with superorganism properties. Protocooperative behavior parameters: 1. two or more cyclists coupled by drafting benefit; 2. current power output or speed; and 3. maximal sustainable outputs (MSO). Main characteristics: 1. relatively low speed phase in which cyclists naturally pass each other and share highest-cost front position; and 2. free-riding phase in which cyclists maintain speeds of those ahead, but cannot pass. Threshold for protocooperative behavior is equivalent to coefficient of drafting (d), below which cooperative behavior occurs; above which free-riding occurs up to a second threshold when coupled cyclists diverge. Range of cyclists’ MSOs in free-riding phase is equivalent to the energy savings benefit of drafting (1-d). When driven to maximal speeds, groups tend to sort such that their MSO ranges equal the free-riding range (1-d).

Suggested Citation

  • Trenchard, Hugh, 2015. "The peloton superorganism and protocooperative behavior," Applied Mathematics and Computation, Elsevier, vol. 270(C), pages 179-192.
  • Handle: RePEc:eee:apmaco:v:270:y:2015:i:c:p:179-192
    DOI: 10.1016/j.amc.2015.08.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300315010619
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2015.08.006?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. Dirk Helbing & Wenjian Yu, 2008. "Migration As A Mechanism To Promote Cooperation," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 11(04), pages 641-652.
    2. Trenchard, Hugh & Richardson, Ashlin & Ratamero, Erick & Perc, Matjaž, 2014. "Collective behavior and the identification of phases in bicycle pelotons," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 405(C), pages 92-103.
    3. Trenchard, Hugh & Ratamero, Erick & Richardson, Ashlin & Perc, Matjaž, 2015. "A deceleration model for bicycle peloton dynamics and group sorting," Applied Mathematics and Computation, Elsevier, vol. 251(C), pages 24-34.
    4. Zhong, Li-Xin & Xu, Wen-Juan & Shi, Yong-Dong & Qiu, Tian, 2013. "Coupled dynamics of mobility and pattern formation in optional public goods games," Chaos, Solitons & Fractals, Elsevier, vol. 47(C), pages 18-26.
    5. Hisashi Ohtsuki & Christoph Hauert & Erez Lieberman & Martin A. Nowak, 2006. "A simple rule for the evolution of cooperation on graphs and social networks," Nature, Nature, vol. 441(7092), pages 502-505, May.
    6. Zhang, Jun & Wang, Wei-Ye & Du, Wen-Bo & Cao, Xian-Bin, 2011. "Evolution of cooperation among mobile agents with heterogenous view radii," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(12), pages 2251-2257.
    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. Li, Meng & Chen, Tao & Du, Hao & Ma, Na & Xi, Xinwei, 2022. "The speed and configuration of cyclist social groups: A field study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    2. Hugh Trenchard & Matjaz Perc, 2016. "Equivalences in Biological and Economical Systems: Peloton Dynamics and the Rebound Effect," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-9, May.

    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. Wang, Chaoqian & Sun, Chengbin, 2023. "Public goods game across multilayer populations with different densities," Chaos, Solitons & Fractals, Elsevier, vol. 168(C).
    2. Chiong, Raymond & Kirley, Michael, 2012. "Random mobility and the evolution of cooperation in spatial N-player iterated Prisoner’s Dilemma games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(15), pages 3915-3923.
    3. Charles G Nathanson & Corina E Tarnita & Martin A Nowak, 2009. "Calculating Evolutionary Dynamics in Structured Populations," PLOS Computational Biology, Public Library of Science, vol. 5(12), pages 1-7, December.
    4. Li, Meng & Chen, Tao & Du, Hao & Ma, Na & Xi, Xinwei, 2022. "The speed and configuration of cyclist social groups: A field study," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    5. Xu, Jiwei & Deng, Zhenghong & Gao, Bo & Song, Qun & Tian, Zhihong & Wang, Qiuling & Gao, Mingyu & Niu, Zhenxi, 2019. "Popularity-driven strategy updating rule promotes cooperation in the spatial prisoner's dilemma game," Applied Mathematics and Computation, Elsevier, vol. 353(C), pages 82-87.
    6. Li, Yan & Ye, Hang, 2015. "Effect of migration based on strategy and cost on the evolution of cooperation," Chaos, Solitons & Fractals, Elsevier, vol. 76(C), pages 156-165.
    7. Zhang, Liming & Li, Haihong & Dai, Qionglin & Yang, Junzhong, 2022. "Migration based on environment comparison promotes cooperation in evolutionary games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 595(C).
    8. R. Bentley & Michael O’Brien & Paul Ormerod, 2011. "Quality versus mere popularity: a conceptual map for understanding human behavior," Mind & Society: Cognitive Studies in Economics and Social Sciences, Springer;Fondazione Rosselli, vol. 10(2), pages 181-191, December.
    9. Jorge Peña & Yannick Rochat, 2012. "Bipartite Graphs as Models of Population Structures in Evolutionary Multiplayer Games," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-13, September.
    10. Ping Zhu & Guiyi Wei, 2014. "Stochastic Heterogeneous Interaction Promotes Cooperation in Spatial Prisoner's Dilemma Game," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-10, April.
    11. Peng Liu & Haoxiang Xia, 2015. "Structure and evolution of co-authorship network in an interdisciplinary research field," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 101-134, April.
    12. Aslihan Akdeniz & Matthijs van Veelen, 2019. "The cancellation effect at the group level," Tinbergen Institute Discussion Papers 19-073/I, Tinbergen Institute.
    13. Li, Bing & Zhao, Xiaowei & Xia, Haoxiang, 2019. "Promotion of cooperation by Hybrid Migration mechanisms in the Spatial Prisoner’s Dilemma Game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 1-8.
    14. Zhao, Zhengwu & Zhang, Chunyan, 2023. "The mechanisms of labor division from the perspective of task urgency and game theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    15. Lessard, Sabin & Lahaie, Philippe, 2009. "Fixation probability with multiple alleles and projected average allelic effect on selection," Theoretical Population Biology, Elsevier, vol. 75(4), pages 266-277.
    16. Takahiro Ezaki & Naoki Masuda, 2017. "Reinforcement learning account of network reciprocity," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-8, December.
    17. Tanimoto, Jun, 2009. "Promotion of cooperation through co-evolution of networks and strategy in a 2 × 2 game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 953-960.
    18. Genki Ichinose & Masaya Saito & Shinsuke Suzuki, 2013. "Collective Chasing Behavior between Cooperators and Defectors in the Spatial Prisoner’s Dilemma," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-10, July.
    19. Zheng, Xiaoping & Cheng, Yuan, 2011. "Conflict game in evacuation process: A study combining Cellular Automata model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1042-1050.
    20. Liu, Chen & Guo, Hao & Li, Zhibin & Gao, Xiaoyuan & Li, Shudong, 2019. "Coevolution of multi-game resolves social dilemma in network population," Applied Mathematics and Computation, Elsevier, vol. 341(C), pages 402-407.

    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:apmaco:v:270:y:2015:i:c:p:179-192. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.