The Self-Adapted Taxi Dispatch Platform Based on Geographic Information System
In order to improve the efficiency of taxi dispatching, we build a center-controlled, real-time management system. With the help of the real-time data collected by recorders in taxis and the wavelet neural network utilized to predict passenger current, the whole system can work more precisely. Besides, the exceptional situations are also taken into consideration in this system. Thus, the whole system is able to distribute taxis efficiently in any situation. Simulation results indicate that the wavelet neural network could make more accurate prediction than former methods and the self-adapting distribution strategy can increase load rate effectively.
KeywordsTaxi dispatching Passenger flow prediction Dynamic model
The project was supported by the Fundamental Research Founds for National University, China University of Geosciences (Wuhan) 1210491B08.
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