New Taxi–Passenger Dispatching Model at Terminal Station
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 145, Issue 7
Abstract
The taxi–passenger problem is more and more prominent in terminal stations; passengers usually wait in a long queue for taking a taxi in rush hour, and otherwise taxis wait in a queue for passengers. Nevertheless, there are few ways for dispatchers handling taxis’ and passengers’ queues to save time. In this paper, we build a new taxi–passenger dispatching model to solve this problem. The model contains four parts: information collection, passenger dispatching model with dispatcher control, taxi dispatching model, and emergency dispatching strategies. Different from traditional thought in the problem of double-ended queue theory, it is an analytical model with a simulation method. The numerical result of the passenger and taxi dispatching model can be used in station engineering and management. The method is based on queue theory, the simulation model, and technologies on the sensors and wireless communication. From the passenger dispatching results, we obtain the optimal release curve to direct the optimal number of passengers to be released in different arrival rates. The taxi dispatching results shows the strategy point of dispatching taxis. And the simulation results with the dispatching model perform much better than the traditional method in four scenarios. Sensitivity analysis is conducted that shows the different pattern of optimal release curve in variable conditions.
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Acknowledgments
This study is financially supported by National Natural Science Foundation (Nos. 91746201 and 71621001). The authors are grateful to the anonymous reviewers for their most helpful comments.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 145 • Issue 7 • July 2019
Copyright
©2019 American Society of Civil Engineers.
History
Received: Apr 7, 2018
Accepted: Dec 5, 2018
Published online: Apr 25, 2019
Published in print: Jul 1, 2019
Discussion open until: Sep 25, 2019
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