TaxiSim: A multiagent simulation platform for evaluating taxi fleet operations

Taxi service is an important mode of public transportation in most metropolitan areas since it provides door-to-door convenience in the public domain. Unfortunately, despite all the convenience taxis bring, taxi fleets are also extremely inefficient to the point that over 50% of its operation time co...

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Main Authors: CHENG, Shih-Fen, NGUYEN, Thi Duong
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2011
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Online Access:https://ink.library.smu.edu.sg/sis_research/1405
https://ink.library.smu.edu.sg/context/sis_research/article/2404/viewcontent/taxi_sim_iat11_final.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-24042019-11-18T06:38:16Z TaxiSim: A multiagent simulation platform for evaluating taxi fleet operations CHENG, Shih-Fen NGUYEN, Thi Duong Taxi service is an important mode of public transportation in most metropolitan areas since it provides door-to-door convenience in the public domain. Unfortunately, despite all the convenience taxis bring, taxi fleets are also extremely inefficient to the point that over 50% of its operation time could be spent in idling state. Improving taxi fleet operation is an extremely challenging problem, not just because of its scale, but also due to fact that taxi drivers are self-interested agents that cannot be controlled centrally. To facilitate the study of such complex and decentralized system, we propose to construct a multiagent simulation platform that would allow researchers to investigate interactions among taxis and to evaluate the impact of implementing certain management policies. The major contribution of our work is the incorporation of our analysis on the real-world driver’s behaviors. Despite the fact that taxi drivers are selfish and unpredictable, by analyzing a huge GPS dataset collected from a major taxi fleet operator, we are able to clearly demonstrate that driver’s movements are closely related to the relative attractiveness of neighboring regions. By applying this insight, we are able to design a background agent movement strategy that generates aggregate performance patterns that are very similar to the real-world ones. Finally, we demonstrate the value of such system with a real-world case study. 2011-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1405 info:doi/10.1109/WI-IAT.2011.138 https://ink.library.smu.edu.sg/context/sis_research/article/2404/viewcontent/taxi_sim_iat11_final.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University multiagent simulation urban transportation driver behavior mobility pattern taxi fleet Artificial Intelligence and Robotics Business Operations Research, Systems Engineering and Industrial Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic multiagent simulation
urban transportation
driver behavior
mobility pattern
taxi fleet
Artificial Intelligence and Robotics
Business
Operations Research, Systems Engineering and Industrial Engineering
spellingShingle multiagent simulation
urban transportation
driver behavior
mobility pattern
taxi fleet
Artificial Intelligence and Robotics
Business
Operations Research, Systems Engineering and Industrial Engineering
CHENG, Shih-Fen
NGUYEN, Thi Duong
TaxiSim: A multiagent simulation platform for evaluating taxi fleet operations
description Taxi service is an important mode of public transportation in most metropolitan areas since it provides door-to-door convenience in the public domain. Unfortunately, despite all the convenience taxis bring, taxi fleets are also extremely inefficient to the point that over 50% of its operation time could be spent in idling state. Improving taxi fleet operation is an extremely challenging problem, not just because of its scale, but also due to fact that taxi drivers are self-interested agents that cannot be controlled centrally. To facilitate the study of such complex and decentralized system, we propose to construct a multiagent simulation platform that would allow researchers to investigate interactions among taxis and to evaluate the impact of implementing certain management policies. The major contribution of our work is the incorporation of our analysis on the real-world driver’s behaviors. Despite the fact that taxi drivers are selfish and unpredictable, by analyzing a huge GPS dataset collected from a major taxi fleet operator, we are able to clearly demonstrate that driver’s movements are closely related to the relative attractiveness of neighboring regions. By applying this insight, we are able to design a background agent movement strategy that generates aggregate performance patterns that are very similar to the real-world ones. Finally, we demonstrate the value of such system with a real-world case study.
format text
author CHENG, Shih-Fen
NGUYEN, Thi Duong
author_facet CHENG, Shih-Fen
NGUYEN, Thi Duong
author_sort CHENG, Shih-Fen
title TaxiSim: A multiagent simulation platform for evaluating taxi fleet operations
title_short TaxiSim: A multiagent simulation platform for evaluating taxi fleet operations
title_full TaxiSim: A multiagent simulation platform for evaluating taxi fleet operations
title_fullStr TaxiSim: A multiagent simulation platform for evaluating taxi fleet operations
title_full_unstemmed TaxiSim: A multiagent simulation platform for evaluating taxi fleet operations
title_sort taxisim: a multiagent simulation platform for evaluating taxi fleet operations
publisher Institutional Knowledge at Singapore Management University
publishDate 2011
url https://ink.library.smu.edu.sg/sis_research/1405
https://ink.library.smu.edu.sg/context/sis_research/article/2404/viewcontent/taxi_sim_iat11_final.pdf
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