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Efficient matching of offers and requests in social-aware ridesharing

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Abstract

Ridesharing has been becoming increasingly popular in urban areas worldwide for its low cost and environmental friendliness. Much research attention has been drawn to the optimization of travel costs in shared rides. However, other important factors in ridesharing, such as the social comfort and trust issues, have not been fully considered in the existing works. In this paper, we formulate a new problem, named Assignment of Requests to Offers (ARO), that aims to maximize the number of served riders while satisfying the social comfort constraints as well as spatial-temporal constraints. We prove that the ARO problem is NP-hard. We then propose an exact algorithm for a simplified ARO problem. We further propose three pruning strategies to efficiently narrow down the searching space and speed up the assignment processing. Based on these pruning strategies, we develop two novel heuristic algorithms, the request-oriented approach and offer-oriented approach, to tackle the ARO problem. We also study the dynamic ARO problem and present a novel algorithm to tackle this problem. Through extensive experiments, we demonstrate the efficiency and effectiveness of our proposed approaches on real-world datasets.

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References

  1. Didi. http://www.didichuxing.com/shunfengche.html

  2. Gowalla. https://snap.stanford.edu/data/loc-gowalla.html

  3. Nyc tlc trip data. http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml

  4. Online news. http://www.cnsoftnews.com/news/201801/71658.html

  5. Uber. https://www.uber.com

  6. Agatz N, Erera A, Savelsbergh M, Wang X (2009) Sustainable passenger transportation: dynamic ridesharing

  7. Chen L, Xu J, Lin X, Jensen CS, Hu H (2016) Answering why-not spatial keyword top-k queries via keyword adaption. In: 2016 IEEE 32nd international conference on data engineering (ICDE). IEEE, pp 697–708

  8. Cici B, Markopoulou A, Frias-Martinez E, Laoutaris N (2014) Assessing the potential of ride-sharing using mobile and social data: a tale of four cities. In: Proceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing. ACM, pp 201–211

  9. Cordeau J-F, Laporte G (2007) The dial-a-ride problem: models and algorithms. Ann Oper Res 153(1):29–46

    Article  Google Scholar 

  10. Fu X, Huang J, Lu H, Xu J, Li Y (2017) Top-k taxi recommendation in realtime social-aware ridesharing services. In: Advances in spatial and temporal databases: 15th international symposium, SSTD 2017, Arlington, VA, USA, August, 2017, pp 221–241

  11. Fu X, Zhang C, Lu H, Xu J (2018) Efficient matching of offers and requests in social-aware ridesharing. In: 2018 19th IEEE international conference on mobile data management (MDM), pp 197–206

  12. Gidófalvi G, Pedersen TB, Risch T, Zeitler E (2008) Highly scalable trip grouping for large-scale collective transportation systems. In: EDBT 2008, 11th international conference on extending database technology, Nantes, France, March 25-29, 2008, Proceedings, pp 678–689

  13. Huang Y, Bastani F, Jin R, Wang XS (2014) Large scale real-time ridesharing with service guarantee on road networks. PVLDB 7(14):2017–2028

    Google Scholar 

  14. Li Y, Chen R, Chen L, Xu J (2017) Towards social-aware ridesharing group query services. IEEE Trans Serv Comput 10(4):646–659

    Article  Google Scholar 

  15. Ma S, Zheng Y, Wolfson O (2013) T-share: a large-scale dynamic taxi ridesharing service. In: 29th IEEE international conference on data engineering, ICDE 2013, Brisbane, Australia, April 8–12, 2013, pp 410–421

  16. Ma S, Zheng Y, Wolfson O (2015) Real-time city-scale taxi ridesharing. IEEE Trans Knowl Data Eng 27(7):1782–1795

    Article  Google Scholar 

  17. Psaraftis HN (1980) A dynamic programming solution to the single vehicle many-to-many immediate request dial-a-ride problem. Transp Sci 14(2):130–154

    Article  Google Scholar 

  18. Psaraftis HN (1980) An exact algorithm for the single vehicle many-to-many dial-a-ride problem with time windows. Transp Sci 14(2):130–154

    Article  Google Scholar 

  19. Vazirani VV (2013) Approximation algorithms. Springer Science & Business Media, Berlin

    Google Scholar 

  20. Xiang Z, Chu C, Chen H (2006) A fast heuristic for solving a large-scale static dial-a-ride problem under complex constraints. Eur J Oper Res 174(2):1117–1139

    Article  Google Scholar 

  21. Zhao W, Qin Y, Yang D, Zhang L, Zhu W (2014) Social group architecture based distributed ride-sharing service in vanet. Int J Distrib Sens Netw 2014:1–8

    Google Scholar 

Download references

Acknowledgment

A preliminary version of this work has appeared in [11]. This work was supported by the Hong Kong Research Grants Council (RGC) under projects 12200817 and 12201615.

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Authors and Affiliations

  1. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Xiaoyi Fu, Ce Zhang & Jianliang Xu

  2. Department of Computer Science, Aalborg University, Aalborg, Denmark

    Hua Lu

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  1. Xiaoyi Fu
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  2. Ce Zhang
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  3. Hua Lu
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  4. Jianliang Xu
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Correspondence to Xiaoyi Fu.

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Fu, X., Zhang, C., Lu, H. et al. Efficient matching of offers and requests in social-aware ridesharing. Geoinformatica 23, 559–589 (2019). https://doi.org/10.1007/s10707-019-00369-8

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  • DOI: https://doi.org/10.1007/s10707-019-00369-8

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