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Transfer Problem in a Cloud-based Public Vehicle System with Sustainable Discomfort

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Abstract

The increasing population in urban areas gives rise to a huge traffic pressure. A cloud-based industrial system, public vehicle (PV) system, is promising to mitigate the traffic congestion in smart cities, where passengers can share PVs and transfer among them with scheduling decisions made by the cloud. This paper studies the transfer problem in the PV system due to that transfer can improve the whole traffic efficiency with sacrificing a little comfort with the corporation of all the PVs. The transfer problem is NP-Complete through our analysis. Our work can be separated into three steps. First, we introduce several factors to guarantee the comfort of passengers during transfer. Second, we propose two algorithms through the graph-based scheduling problem aiming at reducing the travel distance of all the PVs with service guarantee. Third, simulations based on the Shanghai (China) urban road network show that, the total travel distance of PVs is reduced under the quality of service for passengers, and the traffic efficiency is improved.

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References

  1. Zhu M, Liu X-Y, Tang F, Qiu M, Shen R, Shu W, Wu M-Y (2016) Public vehicles for future urban transportation systems. (under revision) IEEE Transactions on Intelligent Transportation Systems (TITS)

  2. Zhou Z, Zhao D, Xu X, Du C, Sun H (2015) Periodic query optimization leveraging popularity-based caching in wireless sensor networks for industrial iot applications. Springer Mobile Networks and Applications (MONET) 20(2):124–136

    Article  Google Scholar 

  3. Drews F, Luxen D (2013) Multi-hop ride sharing. In: Sixth Annual Symposium on Combinatorial Search

  4. Teubner T, Flath CM (2015) The economics of multi-hop ride sharing. In: Business & Information Systems Engineering, pp 1–14

  5. Galland S, Knapen L, Yasar A.-U.-H., Gaud N, Janssens D, Lamotte O, Koukam A, Wets G (2014) Multi-agent simulation of individual mobility behavior in carpooling. In: Transportation Research Part C: Emerging Technologies

  6. Handke V, Jonuschat H (2013) Flexible ridesharing. Springer

  7. Qiu M, Zhong M, Li J, Gai K, Zong Z (2015) Phase-change memory optimization for green cloud with genetic algorithm. IEEE Trans Comput (TC) 64(12):3528–3540

    Article  MathSciNet  Google Scholar 

  8. Wan J, Zhang D, Sun Y, Lin K, Zou C, Cai H (2014) Vcmia: a novel architecture for integrating vehicular cyber-physical systems and mobile cloud computing. Springer Mobile Networks and Applications (MONET) 19(2):153–160

    Article  Google Scholar 

  9. Qiu M, Chen Z, Ming Z, Qin X, Niu J (2014) Energy-aware data allocation with hybrid memory for mobile cloud systems. IEEE Syst J PP(99):1–10

    Article  Google Scholar 

  10. Li Y, Dai W, Ming Z, Qiu M (2015) Privacy protection for preventing data over-collection in smart city. IEEE Trans Comput (TC) PP(99):1–14

    Google Scholar 

  11. Bit-Monnot A, Artigues C, Huguet M-J, Killijian M-O (2013) Carpooling: the 2 synchronization points shortest paths problem. In: OASIcs-OpenAccess Series in Informatics, vol 33, Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik

  12. Trasarti R, Pinelli F, Nanni M, Giannotti F (2011) Mining mobility user profiles for car pooling. In: ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), pp 1190–1198

  13. Zhang D, Li Y, Zhang F, Lu M, Liu Y, He T (2013) Coride: carpool service with a win-win fare model for large-scale taxicab networks. In: ACM Conference on Embedded Networked Sensor Systems (SenSys)

  14. Coltin B, Veloso M (2014) Ridesharing with passenger transfers. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp 3278–3283

  15. Ray J-B (2014) Planning a real-time ridesharing: network Critical mass and role of transfers. In: Transport Research Arena (TRA) Conference: Transport Solutions from Research to Deployment

  16. Ben Cheikh S, Hammadi S, Tahon C (2014) Based-agent distributed architecture to manage the dynamic multi-hop ridesharing system. In: IEEE International Symposium on Network Computing and Applications (NCA), pp 101–104

  17. Bouros P, Sacharidis D, Dalamagas T, Sellis T (2011) Dynamic pickup and delivery with transfers. In: Springer Advances in Spatial and Temporal Databases, pp 112–129

  18. Masson R, Lehuédé F, Péton O (2012) Simple temporal problems in route scheduling for the dial–a–ride problem with transfers. In: Springer Integration of AI and OR Techniques in Contraint Programming for Combinatorial Optimzation Problems, pp 275–291

  19. Zhu M, Liu X-Y, Kong L, Shen R, Shu W, Wu M-Y (2014) The charging-scheduling problem for electric vehicle networks. In: IEEE Wireless Communications and Networking Conference (WCNC), pp 3178–3183

  20. Hong kong: Airport express, bus or taxi? http://www.tripadvisor.com/Travel-g294217-c178763/Hong-Kong:China:Airport.Express.Bus.Or.Taxi.html

  21. Uber proves 40 % cheaper than sydney taxis and more reliable in choice test. http://www.theguardian.com/australia-news/2015/sep/24/uber-cheaper-sydney-taxis-more-reliable-choice-test

  22. Hou Y, Li X, Qiao C (2012) Tictac: From transfer-incapable carpooling to transfer-allowed carpooling. In: IEEE Global Communications Conference (GLOBECOM), pp 268–273

  23. Asif MT, Dauwels J, Goh CY, Oran A, Fathi E, Xu M, Dhanya MM, Mitrovic N, Jaillet P (2014) Spatiotemporal patterns in large-scale traffic speed prediction. IEEE Trans Intell Transp Syst (TITS) 15(2):794–804

    Article  Google Scholar 

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Acknowledgments

This work was supported by the Natural Science Foundation of China (NSFC) projects (Nos. 61373155, 91438121 and 61373156).

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

    Ming Zhu, Xiao-Yang Liu, Ruimin Shen & Min-You Wu

  2. Department of Computer Science, Pace University, New York, NY, USA

    Meikang Qiu

  3. Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, USA

    Wei Shu

Authors
  1. Ming Zhu
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  2. Xiao-Yang Liu
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  3. Meikang Qiu
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  4. Ruimin Shen
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  5. Wei Shu
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  6. Min-You Wu
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Correspondence to Ming Zhu or Xiao-Yang Liu.

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Zhu, M., Liu, XY., Qiu, M. et al. Transfer Problem in a Cloud-based Public Vehicle System with Sustainable Discomfort. Mobile Netw Appl 21, 890–900 (2016). https://doi.org/10.1007/s11036-016-0675-y

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