Challenges and opportunities in taxi fleet anomaly detection
To enhance fleet operation and management, logistics companies instrument their vehicles with GPS receivers and network connectivity to servers. Mobility traces from such large fleets provide significant information on commuter travel patterns, traffic congestion and road anomalies, and hence severa...
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sg-smu-ink.sis_research-32412020-04-01T02:13:32Z Challenges and opportunities in taxi fleet anomaly detection SEN, Rijurekha BALAN, Rajesh Krishna To enhance fleet operation and management, logistics companies instrument their vehicles with GPS receivers and network connectivity to servers. Mobility traces from such large fleets provide significant information on commuter travel patterns, traffic congestion and road anomalies, and hence several researchers have mined such datasets to gain useful urban insights. These logistics companies, however, incur significant cost in deploying and maintaining their vast network of instrumented vehicles. Thus research problems, that are not only of interest to urban planners, but to the logistics companies themselves are important to attract and engage these companies for collaborative data analysis. In this paper, we show how GPS traces from taxis can be used to answer three different questions that are of great interest to a taxi operator. These questions are 1) What is the occupancy rate of the taxi fleet?, 2) What is the effect of route selection on the distance and time of a chosen route?, and 3) Does an analysis of travel times show deviations from the posted speed limits? We provide answers to each of these questions using a 2 month dataset of taxi records collected from over 10,000 taxis located in Singapore. The goal of this paper is to stimulate interest in the questions listed above (as they are of high interest to fleet operators) while also soliciting suggestions for better techniques to solve the problems stated above. 2013-11-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/2241 info:doi/10.1145/2536714.2536715 https://ink.library.smu.edu.sg/context/sis_research/article/3241/viewcontent/Sen.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 anomaly detection GPS taxi fleet Software Engineering Transportation |
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anomaly detection GPS taxi fleet Software Engineering Transportation SEN, Rijurekha BALAN, Rajesh Krishna Challenges and opportunities in taxi fleet anomaly detection |
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To enhance fleet operation and management, logistics companies instrument their vehicles with GPS receivers and network connectivity to servers. Mobility traces from such large fleets provide significant information on commuter travel patterns, traffic congestion and road anomalies, and hence several researchers have mined such datasets to gain useful urban insights. These logistics companies, however, incur significant cost in deploying and maintaining their vast network of instrumented vehicles. Thus research problems, that are not only of interest to urban planners, but to the logistics companies themselves are important to attract and engage these companies for collaborative data analysis. In this paper, we show how GPS traces from taxis can be used to answer three different questions that are of great interest to a taxi operator. These questions are 1) What is the occupancy rate of the taxi fleet?, 2) What is the effect of route selection on the distance and time of a chosen route?, and 3) Does an analysis of travel times show deviations from the posted speed limits? We provide answers to each of these questions using a 2 month dataset of taxi records collected from over 10,000 taxis located in Singapore. The goal of this paper is to stimulate interest in the questions listed above (as they are of high interest to fleet operators) while also soliciting suggestions for better techniques to solve the problems stated above. |
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SEN, Rijurekha BALAN, Rajesh Krishna |
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SEN, Rijurekha BALAN, Rajesh Krishna |
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SEN, Rijurekha |
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Challenges and opportunities in taxi fleet anomaly detection |
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Challenges and opportunities in taxi fleet anomaly detection |
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Challenges and opportunities in taxi fleet anomaly detection |
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Challenges and opportunities in taxi fleet anomaly detection |
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Challenges and opportunities in taxi fleet anomaly detection |
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challenges and opportunities in taxi fleet anomaly detection |
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Institutional Knowledge at Singapore Management University |
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2013 |
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https://ink.library.smu.edu.sg/sis_research/2241 https://ink.library.smu.edu.sg/context/sis_research/article/3241/viewcontent/Sen.pdf |
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