Abstract
The Web of Things (WoT) paradigm introduces novel applications to improve the quality of human lives. Dynamic ridesharing is one of these applications, which holds the potential to gain significant economical, environmental, and social benefits particularly in metropolitan areas. Despite the recent advances in this area, many challenges still remain. In particular, handling large-scale incomplete data has not been adequately addressed by previous works. Optimizing the taxi/passengers schedules to gain the maximum benefits is another challenging issue. In this paper, we propose a novel system, MARS (Multi-Agent Ridesharing System), which addresses these challenges by formulating travel time estimation and enhancing the efficiency of taxi searching through a decremental search approach. Our proposed approach has been validated using a real-world dataset that consists of the trajectories of 10,357 taxis in Beijing, China.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Agatz, N., Erera, A., Savelsbergh, M., Wang, X.: Optimization for dynamic ride-sharing: A review. European J. of Operational Research 223(2), 295–303 (2012)
Bhaumik, C., Agrawal, A.K., Sinha, P.: Using social network graphs for search space reduction in internet of things. In: Proceedings of the 2012 Conference on Ubiquitous Computing (Ubicomp), pp. 602–603. ACM (2012)
Caulfield, B.: Estimating the environmental benefits of ride-sharing: A case study of dublin. Transportation Research Part D: Transport and Environment 14(7), 527–531 (2009)
Crowcroft, J.: Fie: Future internet enervation. In: ACM SIGCOMM Computer Communication Review, vol. 40, pp. 48–52. ACM, New York (2010)
Dimitrieski, V.: Real-time carpooling and ride-sharing: Position paper on design concepts, distribution and cloud computing strategies. In: Proceedings of the 2013 Federated Conference on Computer Science and Information Systems (FedCSIS), Kraków, Poland, pp. 781–786 (2013)
Gidófalvi, G., Herenyi, G., Bach Pedersen, T.: Instant social ride-sharing. In: Proceedings of the 15th World Congress on Intelligent Transport Systems, p. 8. Intelligent Transportation Society of America, New York (2008)
Huang, Y., Jin, R., Bastani, F., Wang, X.S.: Large scale real-time ridesharing with service guarantee on road networks. Computing Research Repository (2013)
Lin, Y., Li, W., Qiu, F., Xu, H.: Research on optimization of vehicle routing problem for ride-sharing taxi, Shaoxing, China, pp. 494–502 (2012)
Ma, S., Zheng, Y., Wolfson, O.: T-share: A large-scale dynamic taxi ridesharing service. In: Proceedings of 29th International Conference on Data Engineering (ICDE 2013), pp. 410–421. IEEE, Brisbane (2013)
Qiu, D., Papotti, P., Blanco, L.: Future locations prediction with uncertain data. In: Blockeel, H., Kersting, K., Nijssen, S., Železný, F. (eds.) ECML PKDD 2013, Part I. LNCS, vol. 8188, pp. 417–432. Springer, Heidelberg (2013)
Santos, D.O., Xavier, E.C.: Dynamic taxi and ridesharing: A framework and heuristics for the optimization problem. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), pp. 2885–2891. AAAI Press, Beijing (2013)
Sghaier, M., Zgaya, H., Hammadi, S., Tahon, C.: A distributed optimized approach based on the multi agent concept for the implementation of a real time carpooling service with an optimization aspect on siblings. International Journal of Engineering 5(2), 217–241 (2011)
Sheng, Q.Z., Li, X., Zeadally, S.: Enabling Next-Generation RFID Applications: Solutions and Challenges. IEEE Computer 41(9), 21–28 (2008)
Tao, C.C.: Dynamic taxi-sharing service using intelligent transportation system technologies. In: Proceedings of International Conference on Wireless Communications, Networking and Mobile Computing (WiCom 2007), pp. 3209–3212. IEEE, Shanghai (2007)
Tian, C., Huang, Y., Liu, Z., Bastani, F., Jin, R.: Noah: a dynamic ridesharing system. In: Proceedings of the 2013 ACM SIGMOD Conference (SIGMOD 2013), pp. 985–988. ACM, New York (2013)
Xue, A.Y., Zhang, R., Zheng, Y., Xie, X., Huang, J., Xu, Z.: Destination prediction by sub-trajectory synthesis and privacy protection against such prediction. In: Proceedings of 29th International Conference on Data Engineering (ICDE 2013), Brisbane, Australia, pp. 254–265 (2013)
Xue, A.Y., Zhang, R., Zheng, Y., Xie, X., Yu, J., Tang, Y.: Desteller: A system for destination prediction based on trajectories with privacy protection. In: Proceedings of the VLDB Endowment, vol. 6, pp. 1198–1201. VLDB Endowment (2013)
Yousaf, J., Li, J., Chen, L., Tang, J., Dai, X., Du, J.: Ride-sharing: A multi source-destination path planning approach. In: Thielscher, M., Zhang, D. (eds.) AI 2012. LNCS, vol. 7691, pp. 815–826. Springer, Heidelberg (2012)
Yuan, J., Zheng, Y., Xie, X., Sun, G.: Driving with knowledge from the physical world. In: Proceedings of the 17th International Conference on Knowledge Discovery and Data Mining (SIGKDD), pp. 316–324. ACM (2011)
Yuan, J., Zheng, Y., Zhang, C., Xie, W., Xie, X., Sun, G., Huang, Y.: T-drive: driving directions based on taxi trajectories. In: Proceedings of the 18th International Conference on Advances in Geographic Information Systems (SIGSPATIAL), pp. 99–108. ACM (2010)
Zhan, X., Hasan, S., Ukkusuri, S.V., Kamga, C.: Urban link travel time estimation using large-scale taxi data with partial information. Transportation Research Part C: Emerging Technologies 33, 37–49 (2013)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Shemshadi, A., Sheng, Q.Z., Zhang, W.E. (2014). A Decremental Search Approach for Large Scale Dynamic Ridesharing. In: Benatallah, B., Bestavros, A., Manolopoulos, Y., Vakali, A., Zhang, Y. (eds) Web Information Systems Engineering – WISE 2014. WISE 2014. Lecture Notes in Computer Science, vol 8786. Springer, Cham. https://doi.org/10.1007/978-3-319-11749-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-11749-2_16
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11748-5
Online ISBN: 978-3-319-11749-2
eBook Packages: Computer ScienceComputer Science (R0)