Real-time trip information service for a large taxi fleet

In this paper, we describe the design, analysis, implementation, and operational deployment of a real-time trip information system that provides passengers with the expected fare and trip duration of the taxi ride they are planning to take. This system was built in cooperation with a taxi operator t...

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Main Authors: BALAN, Rajesh Krishna, KHOA, Nguyen Xuan, JIANG, Lingxiao
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/1678
https://ink.library.smu.edu.sg/context/sis_research/article/2677/viewcontent/mobisys11taxi.pdf
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spelling sg-smu-ink.sis_research-26772017-02-21T03:38:03Z Real-time trip information service for a large taxi fleet BALAN, Rajesh Krishna KHOA, Nguyen Xuan JIANG, Lingxiao In this paper, we describe the design, analysis, implementation, and operational deployment of a real-time trip information system that provides passengers with the expected fare and trip duration of the taxi ride they are planning to take. This system was built in cooperation with a taxi operator that operates more than 15,000 taxis in Singapore. We first describe the overall system design and then explain the efficient algorithms used to achieve our predictions based on up to 21 months of historical data consisting of approximately 250 million paid taxi trips. We then describe various optimisations (involving region sizes, amount of history, and data mining techniques) and accuracy analysis (involving routes and weather) we performed to increase both the runtime performance and prediction accuracy. Our large scale evaluation demonstrates that our system is (a) accurate—with the mean fare error under 1 Singapore dollar ( 0.76 US$) and the mean duration error under three minutes, and (b) capable of real-time performance, processing thousands to millions of queries per second. Finally, we describe the lessons learned during the process of deploying this system into a production environment. 2011-06-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/1678 info:doi/10.1145/1999995.2000006 https://ink.library.smu.edu.sg/context/sis_research/article/2677/viewcontent/mobisys11taxi.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 Taxi Fleets Trip Information Service Partition-based Predictions Nearest Neighbour Queries History-based Predictions Software Engineering Transportation
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Taxi Fleets
Trip Information Service
Partition-based Predictions
Nearest Neighbour Queries
History-based Predictions
Software Engineering
Transportation
spellingShingle Taxi Fleets
Trip Information Service
Partition-based Predictions
Nearest Neighbour Queries
History-based Predictions
Software Engineering
Transportation
BALAN, Rajesh Krishna
KHOA, Nguyen Xuan
JIANG, Lingxiao
Real-time trip information service for a large taxi fleet
description In this paper, we describe the design, analysis, implementation, and operational deployment of a real-time trip information system that provides passengers with the expected fare and trip duration of the taxi ride they are planning to take. This system was built in cooperation with a taxi operator that operates more than 15,000 taxis in Singapore. We first describe the overall system design and then explain the efficient algorithms used to achieve our predictions based on up to 21 months of historical data consisting of approximately 250 million paid taxi trips. We then describe various optimisations (involving region sizes, amount of history, and data mining techniques) and accuracy analysis (involving routes and weather) we performed to increase both the runtime performance and prediction accuracy. Our large scale evaluation demonstrates that our system is (a) accurate—with the mean fare error under 1 Singapore dollar ( 0.76 US$) and the mean duration error under three minutes, and (b) capable of real-time performance, processing thousands to millions of queries per second. Finally, we describe the lessons learned during the process of deploying this system into a production environment.
format text
author BALAN, Rajesh Krishna
KHOA, Nguyen Xuan
JIANG, Lingxiao
author_facet BALAN, Rajesh Krishna
KHOA, Nguyen Xuan
JIANG, Lingxiao
author_sort BALAN, Rajesh Krishna
title Real-time trip information service for a large taxi fleet
title_short Real-time trip information service for a large taxi fleet
title_full Real-time trip information service for a large taxi fleet
title_fullStr Real-time trip information service for a large taxi fleet
title_full_unstemmed Real-time trip information service for a large taxi fleet
title_sort real-time trip information service for a large taxi fleet
publisher Institutional Knowledge at Singapore Management University
publishDate 2011
url https://ink.library.smu.edu.sg/sis_research/1678
https://ink.library.smu.edu.sg/context/sis_research/article/2677/viewcontent/mobisys11taxi.pdf
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