Samenvatting
We present a weighted sampling strategy for distributing a system of taxi agents on a road network. We consider a setting, in which each agent operates independently, following a prescribed strategy based on historical data. Furthermore, customer requests appear dynamically and are assigned to the closest unoccupied taxi agent.
We demonstrate that in this setting a simple sampling strategy based on the spatial distribution of historical data performs well in minimizing the average time that agents are unoccupied. The strategy is evaluated on taxi trip data in Manhattan and compared to various, more complex strategies.
We demonstrate that in this setting a simple sampling strategy based on the spatial distribution of historical data performs well in minimizing the average time that agents are unoccupied. The strategy is evaluated on taxi trip data in Manhattan and compared to various, more complex strategies.
Originele taal-2 | Engels |
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Titel | 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2019 |
Redacteuren | Farnoush Banaei-Kashani, Goce Trajcevski, Ralf Hartmut Guting, Lars Kulik, Shawn Newsam |
Uitgeverij | Association for Computing Machinery, Inc. |
Pagina's | 616-619 |
Aantal pagina's | 4 |
ISBN van elektronische versie | 9781450369091 |
ISBN van geprinte versie | 978-1-4503-6909-1 |
DOI's | |
Status | Gepubliceerd - 5 nov. 2019 |
Evenement | 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems - Chicago, IL, Verenigde Staten van Amerika Duur: 5 nov. 2019 → 8 dec. 2019 http://sigspatial2019.sigspatial.org/ |
Congres
Congres | 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems |
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Verkorte titel | ACM SIGSPATIAL 2019 |
Land/Regio | Verenigde Staten van Amerika |
Stad | Chicago, IL |
Periode | 5/11/19 → 8/12/19 |
Internet adres |