Abstract
In this paper, we predict the impact of traffic event on urban roads in Xi'an, including the range and the total time of the influence. The author creatively proposes to use Recurrent Neural Network (RNN) algorithm to predict the change of road traffic index by calculating the basic information of road the basic information of event and weather data, combining with the road traffic index and time series forecasting. Among them, RNN algorithm uses deep recurrent neural network and long-short term memory (LSTM) to achieve. Finally, the predicted change sequence is compared with the historical road condition index of the road section to determine whether the road is affected and the total time of the influence.
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