Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
7-2018
Abstract
Traditional taxi fleet operators world-over have been facing intense competitions from various ride-hailing services such as Uber and Grab.Based on our studies on the taxi industry in Singapore, we see that the emergence of Uber and Grab in the ride-hailing market has greatly impacted the taxi industry: the average daily taxi ridership for the past two years has been falling continuously, by close to 20% in total. In this work, we discuss how efficient real-time data analytics and large-scale multiagent optimization technology could help taxi drivers compete against more technologically advanced service platforms. Our system has been in field trial with close to 400 drivers, and our initial results show that by following our recommendations, drivers on average save 21.5% on roaming time.
Keywords
mobility-on-demand, multiagent optimization, taxi driver guidance
Discipline
Databases and Information Systems | Transportation
Research Areas
Intelligent Systems and Optimization
Publication
AAMAS '18: Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems, Stockholm, July 10-15
First Page
1820
Last Page
1822
Publisher
IFAAMAS
City or Country
Richland, SC
Citation
JHA, Shashi Shekhar; CHENG, Shih-Fen; LOWALEKAR, Meghna; WONG, Nicholas; RAJENDRAM, Rishikeshan; VARAKANTHAM, Pradeep; TROUNG, Nghia Troung; and BIN ABD RAHMAN, Firmansyah.
A driver guidance system for taxis in Singapore. (2018). AAMAS '18: Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems, Stockholm, July 10-15. 1820-1822.
Available at: https://ink.library.smu.edu.sg/sis_research/4118
Copyright Owner and License
Publisher
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://dl.acm.org/citation.cfm?id=3237989