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 (specific to the Southeast Asia region). 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 multi-agent optimization technology could potentially help taxi drivers compete against more technologically advanced service platforms.
Keywords
taxi, driver guidance, field trial, mobility ondemand
Discipline
Artificial Intelligence and Robotics | 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
577
Last Page
584
ISBN
9781510868083
Publisher
IFAAMAS
City or Country
Richland, SC
Citation
CHENG, Shih-Fen; JHA, Shashi Shekhar; and RAJENDRAM, Rishikeshan.
Taxis strike back: A field trial of the driver guidance system. (2018). AAMAS '18: Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems, Stockholm, July 10-15. 577-584.
Available at: https://ink.library.smu.edu.sg/sis_research/4117
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=3237469
Included in
Artificial Intelligence and Robotics Commons, Databases and Information Systems Commons, Transportation Commons