Balancing efficiency and fairness in ridesharing dispatching
Ridesharing Apps have increased its significance in urban mobility that provides convenience and higher flexibility to match riders and on-demand drivers with immediate response time. Traditional systems for taxis dispatching were designed to match the driver to a request in terms of shortest det...
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sg-ntu-dr.10356-771672023-02-28T23:14:18Z Balancing efficiency and fairness in ridesharing dispatching Wu, Shanshan Bei Xiaohui School of Physical and Mathematical Sciences DRNTU::Science::Mathematics Ridesharing Apps have increased its significance in urban mobility that provides convenience and higher flexibility to match riders and on-demand drivers with immediate response time. Traditional systems for taxis dispatching were designed to match the driver to a request in terms of shortest detour distance or minimal waiting time, without considering other factors, which may affect the overall matching efficiency. In recent years, different scheduling algorithms were proposed to address trade-offs among waiting time, detour, profits, and costs, etc. to tailor the dynamic needs of passengers. However, there is yet a solution that can balance on drivers’ benefits and fairness. In this project, drivers’ fairness, which specifically refers to the discrepancy of their daily profits, was taken into consideration. Corresponding efficient matching algorithms were designed to balance the trade-off between dispatching efficiency and drivers’ fairness. Instead of assigning the driver simply based on shortest detour or shortest waiting time, the algorithm takes the historic profits earned by on-demand drivers as a partial weight for matching, and evaluate an innovative index - Balanced Satisfaction Index (BSI). Historic large-scale Chicago Taxi Trip dataset containing average 30,000 daily trip records were used for testing of algorithm performance. Results indicate a significant improvement of driver’s fairness with a range of 60% to 85% given order range between 2,000 to 30,000. While Efficiency is only slightly impaired. Other analyses on Radius and weight parameter were also conducted. That being said, taking into consideration of drivers’ fairness does not impose a serious effect on overall efficiency, while playing an important role in guaranteeing that each driver can receive similar amounts of order every day. As the principle of fairness is vital for an inclusive workplace, this project provides a useful reference for ridesharing companies to promote the fairness among their designated drivers, to realize a less cut-throat competitive but more harmonious ridesharing environment. Bachelor of Science in Mathematical Sciences 2019-05-14T13:32:04Z 2019-05-14T13:32:04Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77167 en 79 p. application/pdf |
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DRNTU::Science::Mathematics Wu, Shanshan Balancing efficiency and fairness in ridesharing dispatching |
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Ridesharing Apps have increased its significance in urban mobility that provides convenience
and higher flexibility to match riders and on-demand drivers with immediate
response time. Traditional systems for taxis dispatching were designed to match the
driver to a request in terms of shortest detour distance or minimal waiting time, without
considering other factors, which may affect the overall matching efficiency. In recent
years, different scheduling algorithms were proposed to address trade-offs among waiting
time, detour, profits, and costs, etc. to tailor the dynamic needs of passengers. However,
there is yet a solution that can balance on drivers’ benefits and fairness.
In this project, drivers’ fairness, which specifically refers to the discrepancy of their daily
profits, was taken into consideration. Corresponding efficient matching algorithms were
designed to balance the trade-off between dispatching efficiency and drivers’ fairness. Instead
of assigning the driver simply based on shortest detour or shortest waiting time, the
algorithm takes the historic profits earned by on-demand drivers as a partial weight for
matching, and evaluate an innovative index - Balanced Satisfaction Index (BSI). Historic
large-scale Chicago Taxi Trip dataset containing average 30,000 daily trip records were
used for testing of algorithm performance. Results indicate a significant improvement of
driver’s fairness with a range of 60% to 85% given order range between 2,000 to 30,000.
While Efficiency is only slightly impaired. Other analyses on Radius and weight parameter
were also conducted.
That being said, taking into consideration of drivers’ fairness does not impose a serious
effect on overall efficiency, while playing an important role in guaranteeing that each
driver can receive similar amounts of order every day. As the principle of fairness is vital
for an inclusive workplace, this project provides a useful reference for ridesharing companies
to promote the fairness among their designated drivers, to realize a less cut-throat
competitive but more harmonious ridesharing environment. |
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Bei Xiaohui |
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Bei Xiaohui Wu, Shanshan |
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Final Year Project |
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Wu, Shanshan |
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Wu, Shanshan |
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Balancing efficiency and fairness in ridesharing dispatching |
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Balancing efficiency and fairness in ridesharing dispatching |
title_full |
Balancing efficiency and fairness in ridesharing dispatching |
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Balancing efficiency and fairness in ridesharing dispatching |
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Balancing efficiency and fairness in ridesharing dispatching |
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balancing efficiency and fairness in ridesharing dispatching |
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2019 |
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http://hdl.handle.net/10356/77167 |
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