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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Mathematical Model of Cellular Automata in Urban Taxi Network – Take GanZhou as an Example
verfasst von : Zhaosheng Wang, Shiyu Li
Erschienen in: Computational Intelligence and Intelligent Systems
Verlag: Springer Singapore
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Abstract
Urban traffic is an extremely complex dynamic system. Urban traffic modeling and forecasting is still a challenge, the main difficulty is how to determine supply and demand and how to parameterize the model. This paper tries to solve these problems with the help of a large number of floating taxi data. We describe the first solution to the challenge of finding a taxi destination. The tasks included at the beginning of its trajectory prediction of a taxi destination, it is expressed as the GPS point of variable length sequences, and related information, such as the departure time, the driver id and customer information. We use a neural network based approach that is almost completely automated. The architecture we are trying to use is a multi-layer perception, bidirectional recursive neural network, and a model inspired by the recently introduced memory network. Our approach can be easily adapted to other applications, with the goal of predicting the fixed-length output of a variable length sequence.