Research and analysis on the trajectory of online car-hailing vehicles

The problem of climate warming caused by greenhouse gas emissions has become a huge challenge faced by people all over the world. In order to reduce greenhouse gas emissions, various countries are making relevant policies as much as possible. In the transportation sector, the exhaust emissions generated by the driving of automobiles account for a large proportion of the overall carbon emissions. It is of great significance to formulate relevant plans to reduce the distribution of carbon emissions in accordance with the relationship between the distribution of carbon emissions in traffic trajectories and urban functional areas. This paper preprocesses the online car-hailing trajectory information, and converts the fuel consumption and gas consumption data in the trajectory information into carbon emissions calculations. Then the obtained data is visually displayed, and the SARIMA (Seasonal Autoregressive Integrated Moving Average model) algorithm is used to predict and analyze the carbon emission value and perform error analysis. The experimental results prove that the short-term prediction through the SARIMA algorithm has high accuracy. The analysis shows that when SARIMA (1,1,1)x(0,1,1,7), the mean square error of the prediction result is 10.57. It can predict the efficiency of online car-hailing.