Analysis of the Predictive Power of Highway Traffic Flow with Weather Conditions

Traffic systems can be greatly affected by factors such as accidents and weather. In particular, bad weather can have a big impact on travel time and traffic In this paper, we try to predict the traffic volume according to weather variables using the ARIMA model and the LSTM model. For traffic volume and weather data, data from the "Siheung TG of Seoul Outer Ring Expressway" was used, and performance evaluation was performed using RMSE and MAPE.