IDEAS home Printed from https://ideas.repec.org/a/kap/netspa/v18y2018i3d10.1007_s11067-019-09452-x.html
   My bibliography  Save this article

Urban Activity Mining Framework for Ride Sharing Systems Based on Vehicular Social Networks

Author

Listed:
  • Bilong Shen

    (Tsinghua University)

  • Weimin Zheng

    (Tsinghua University)

  • Kathleen M. Carley

    (Carnegie Mellon University)

Abstract

Ride sharing has been widely studied over the past several decades as a means of reducing traffic and pollution by utilizing empty car seats in vehicles that are being driven no matter what. As they increase in popularity, ride sharing applications have already encountered several challenges: Vehicle allocation, price strategy, and route planning, are just a few such examples among many. Tracking human activity patterns with regard to ride share applications can potentially improve these systems in numerous ways. For example, taxi GPS trajectories offer a remarkable source of data for determining human activity patterns, among other things, in cities across the world. However, existing studies either focus solely on meeting order requirements or analyzing Points Of Interest (POI) based only on static information. The former issue cannot solve problems with balancing vehicle allocation, while the latter cannot precisely describe the POI locational feature. In order to develop a more specific analysis of activity patterns for ride sharing systems, we propose a Vehicular Social Network Based Analytical Framework (NBAF) to determine the specific urban activity of ride sharing systems at a low computational cost. The analytical framework contains two special contributions: Firstly, a novel trip mapping method named Trip-Embedding POI Decomposition Method (TEPID) is proposed to describe the feature of geo-nodes in the network. Secondly, the particular features for ride sharing systems are generated by vehicular social networks. Based on this framework, we propose a clustering method to reveal trip activity and regional features. As a case study, we analyze 30 days of taxi trips in New York City in 2016. The results demonstrate that NBAF can effectively determine urban activity and location patterns for vehicle allocation, price strategy, and route planning for ride sharing systems.

Suggested Citation

  • Bilong Shen & Weimin Zheng & Kathleen M. Carley, 2018. "Urban Activity Mining Framework for Ride Sharing Systems Based on Vehicular Social Networks," Networks and Spatial Economics, Springer, vol. 18(3), pages 705-734, September.
    • Handle: RePEc:kap:netspa:v:18:y:2018:i:3:d:10.1007_s11067-019-09452-x
    DOI: 10.1007/s11067-019-09452-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11067-019-09452-x
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s11067-019-09452-x?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. Oren Bahat & Shlomo Bekhor, 2016. "Incorporating Ridesharing in the Static Traffic Assignment Model," Networks and Spatial Economics, Springer, vol. 16(4), pages 1125-1149, December.
    2. César Ducruet & Laurent Beauguitte, 2014. "Network science and spatial science : Review and outcomes of a complex relationship," Post-Print hal-03246947, HAL.
    3. Alexander Erath & Michael Löchl & Kay Axhausen, 2009. "Graph-Theoretical Analysis of the Swiss Road and Railway Networks Over Time," Networks and Spatial Economics, Springer, vol. 9(3), pages 379-400, September.
    4. Lee, Li Way, 1984. "The Economics of Carpools," Economic Inquiry, Western Economic Association International, vol. 22(1), pages 128-135, January.
    5. César Ducruet & Laurent Beauguitte, 2014. "Spatial Science and Network Science: Review and Outcomes of a Complex Relationship," Networks and Spatial Economics, Springer, vol. 14(3), pages 297-316, December.
    6. Carlo Ratti & Stanislav Sobolevsky & Francesco Calabrese & Clio Andris & Jonathan Reades & Mauro Martino & Rob Claxton & Steven H Strogatz, 2010. "Redrawing the Map of Great Britain from a Network of Human Interactions," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-6, December.
    7. Song Gao & Yaoli Wang & Yong Gao & Yu Liu, 2013. "Understanding Urban Traffic-Flow Characteristics: A Rethinking of Betweenness Centrality," Environment and Planning B, , vol. 40(1), pages 135-153, February.
    8. Yu Liu & Zhengwei Sui & Chaogui Kang & Yong Gao, 2014. "Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-11, January.
    9. Loet Leydesdorff, 2007. "Betweenness centrality as an indicator of the interdisciplinarity of scientific journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(9), pages 1303-1319, July.
    10. Petter Holme, 2003. "Congestion And Centrality In Traffic Flow On Complex Networks," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(02), pages 163-176.
    11. Paul Minett & John Pearce, 2011. "Estimating the Energy Consumption Impact of Casual Carpooling," Energies, MDPI, vol. 4(1), pages 1-14, January.
    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. F. Crawford & D. P. Watling & R. D. Connors, 2023. "Analysing Spatial Intrapersonal Variability of Road Users Using Point-to-Point Sensor Data," Networks and Spatial Economics, Springer, vol. 23(2), pages 373-406, June.
    2. Ben Derudder & Zachary Neal, 2018. "Uncovering Links Between Urban Studies and Network Science," Networks and Spatial Economics, Springer, vol. 18(3), pages 441-446, 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. Rui Ding & Norsidah Ujang & Hussain Bin Hamid & Mohd Shahrudin Abd Manan & Rong Li & Safwan Subhi Mousa Albadareen & Ashkan Nochian & Jianjun Wu, 2019. "Application of Complex Networks Theory in Urban Traffic Network Researches," Networks and Spatial Economics, Springer, vol. 19(4), pages 1281-1317, December.
    2. Cats, Oded, 2017. "Topological evolution of a metropolitan rail transport network: The case of Stockholm," Journal of Transport Geography, Elsevier, vol. 62(C), pages 172-183.
    3. Fangxia Zhao & Jianjun Wu & Huijun Sun & Ziyou Gao & Ronghui Liu, 2016. "Population-driven Urban Road Evolution Dynamic Model," Networks and Spatial Economics, Springer, vol. 16(4), pages 997-1018, December.
    4. Liu, Xi & Gong, Li & Gong, Yongxi & Liu, Yu, 2015. "Revealing travel patterns and city structure with taxi trip data," Journal of Transport Geography, Elsevier, vol. 43(C), pages 78-90.
    5. Zachary Neal, 2018. "Is the Urban World Small? The Evidence for Small World Structure in Urban Networks," Networks and Spatial Economics, Springer, vol. 18(3), pages 615-631, September.
    6. Andrés Fielbaum & Sergio Jara-Diaz & Antonio Gschwender, 2017. "A Parametric Description of Cities for the Normative Analysis of Transport Systems," Networks and Spatial Economics, Springer, vol. 17(2), pages 343-365, June.
    7. Dimitrios TSIOTAS & Nikolaos AXELIS & Serafeim POLYZOS, 2022. "Detecting City-Dipoles In Greece Based On Intercity Commuting," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 11-30, June.
    8. Laure Rousset & César Ducruet, 2020. "Disruptions in Spatial Networks: a Comparative Study of Major Shocks Affecting Ports and Shipping Patterns," Networks and Spatial Economics, Springer, vol. 20(2), pages 423-447, June.
    9. Peng Gao & Dan He & Zhijing Sun & Yuemin Ning, 2020. "Characterizing functionally integrated regions in the Central Yangtze River Megaregion from a city‐network perspective," Growth and Change, Wiley Blackwell, vol. 51(3), pages 1357-1379, September.
    10. Daniel Griffith & Yongwan Chun, 2015. "Spatial Autocorrelation in Spatial Interactions Models: Geographic Scale and Resolution Implications for Network Resilience and Vulnerability," Networks and Spatial Economics, Springer, vol. 15(2), pages 337-365, June.
    11. Gergő Tóth & Zoltán Elekes & Adam Whittle & Changjun Lee & Dieter F. Kogler, 2022. "Technology Network Structure Conditions the Economic Resilience of Regions," Economic Geography, Taylor & Francis Journals, vol. 98(4), pages 355-378, August.
    12. Igor Lazov, 2019. "A Methodology for Revenue Analysis of Parking Lots," Networks and Spatial Economics, Springer, vol. 19(1), pages 177-198, March.
    13. Poorthuis, Ate & van Meeteren, Michiel, 2019. "Containment and connectivity in Dutch urban systems: A network-analytical operationalization of the three-systems model," SocArXiv y7dxf, Center for Open Science.
    14. Ben Derudder, 2021. "Network Analysis of ‘Urban Systems’: Potential, Challenges, and Pitfalls," Tijdschrift voor Economische en Sociale Geografie, Royal Dutch Geographical Society KNAG, vol. 112(4), pages 404-420, September.
    15. Tsiotas, Dimitrios, 2021. "Drawing indicators of economic performance from network topology: The case of the interregional road transportation in Greece," Research in Transportation Economics, Elsevier, vol. 90(C).
    16. Ducruet, César, 2017. "Multilayer dynamics of complex spatial networks: The case of global maritime flows (1977–2008)," Journal of Transport Geography, Elsevier, vol. 60(C), pages 47-58.
    17. Fei Ma & Yixuan Wang & Kum Fai Yuen & Wenlin Wang & Xiaodan Li & Yuan Liang, 2019. "The Evolution of the Spatial Association Effect of Carbon Emissions in Transportation: A Social Network Perspective," IJERPH, MDPI, vol. 16(12), pages 1-23, June.
    18. Wang, Duo & Sipahi, Rifat, 2024. "Betweenness centrality can inform stability and delay margin in a large-scale connected vehicle system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    19. Tom Broekel & Marcel Bednarz, 2018. "Disentangling link formation and dissolution in spatial networks: An Application of a Two-Mode STERGM to a Project-Based R&D Network in the German Biotechnology Industry," Networks and Spatial Economics, Springer, vol. 18(3), pages 677-704, September.
    20. KYDROS Dimitrios & FILENTA Pagona, 2022. "Literature Review of Economic and Regional Development through Quantitative Methods and Social Network Analysis," European Journal of Interdisciplinary Studies, Bucharest Economic Academy, issue 01, March.

    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:kap:netspa:v:18:y:2018:i:3:d:10.1007_s11067-019-09452-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.