The prediction of traffic congestion can serve a crucial role in making future decisions. Although many studies have been conducted regarding congestion, most of these could not cover all the important factors (e.g., weather conditions). We proposed a prediction model for traffic congestion that can predict congestion based on day, time and several weather data (e.g., temperature, humidity). To evaluate our model, it has been tested against the traffic data of New Delhi. With this model, congestion of a road can be predicted one week ahead with an average RMSE of 1.12. Therefore, this model can be used to take preventive measure beforehand.

翻译：虽然已就交通拥挤问题进行了许多研究,但其中大多数无法涵盖所有重要因素(如天气条件);我们提出了一个交通拥挤预测模型,可以根据日、时和若干天气数据(如温度、湿度)预测交通堵塞;为了评估我们的交通堵塞情况,已经根据新德里的交通数据对交通堵塞情况进行了测试;有了这一模型,可以提前一周预测公路堵塞情况,平均为1.12,因此,这一模型可以用来预先采取预防措施。