  This paper aims to predict the traffic flow at one road segment based on
nearby traffic volume and weather conditions. Our team also discover the impact
of weather conditions and nearby traffic volume on the traffic flow at a target
point. The analysis results will help solve the problem of traffic flow
prediction and develop an optimal transport network with efficient traffic
movement and minimal traffic congestion. Hourly historical weather and traffic
flow data are selected to solve this problem. This paper uses model VAR(36)
with time trend and constant to train the dataset and forecast. With an RMSE of
565.0768111 on average, the model is considered appropriate although some
statistical tests implies that the residuals are unstable and non-normal. Also,
this paper points out some variables that are not useful in forecasting, which
helps simplify the data-collecting process when building the forecasting
system.
