A short-term highway traffic flow forecasting model based on CNN-LSTM with an attention mechanism

Abstract

Domestic and foreign scholars have researched traffic flow forecasting and established mature systems; however, these systems are mainly based on normal weather. The influence of weather on traffic flow forecasting is rarely considered in existing studies. Therefore, the correlation between meteorology and traffic flow is analyzed, and an attention mechanism is introduced to improve the ability of the model to extract characteristics of time series data. The results show that the model proposed in this paper is better than other models and the traffic flow forecast using meteorological data is more accurate when an attention mechanism is added.