Taxis strike back: A field trial of the driver guidance system

• Main Authors: CHENG, Shih-Fen, JHA, Shashi Shekhar, RAJENDRAM, Rishikeshan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: taxi; driver guidance; field trial; mobility ondemand; Artificial Intelligence and Robotics; Databases and Information Systems; Transportation
• Online Access: https://ink.library.smu.edu.sg/sis_research/4117; https://ink.library.smu.edu.sg/context/sis_research/article/5120/viewcontent/taxis_strike_back.pdf
• Institution: Singapore Management University

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.