Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/110043
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Type: Conference paper
Title: A decremental search approach for large scale dynamic ridesharing
Author: Shemshadi, A.
Sheng, Q.
Zhang, W.
Citation: Web Information Systems Engineering – WISE 2014: Proceedings Part 1, 2014 / Benatallah, B., Bestavros, A., Manolopoulos, Y., Vakali, A., Zhang, Y. (ed./s), vol.8786, pp.202-217
Publisher: Springer
Issue Date: 2014
Series/Report no.: Lecture Notes in Computer Science; vol. 8786
ISBN: 9783319117485
ISSN: 0302-9743
1611-3349
Conference Name: 15th International Conference on Web Information Systems Engineering (WISE 2014) (12 Oct 2014 - 14 Oct 2014 : Thessaloniki, Greece)
Statement of
Responsibility: 
Ali Shemshadi, Quan Z Sheng, and Wei Emma Zhang
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.
Keywords: Taxi ridesharing; Web of Things; Spatio-temporal data; incomplete data
Rights: © Springer International Publishing Switzerland 2014
RMID: 0030021104
DOI: 10.1007/978-3-319-11749-2_16
Appears in Collections:Computer Science publications

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