Festival, date and limit line: Predicting vehicle accident rate in Beijing

Thousands of vehicle accidents happen every day in Beijing, leading to huge losses. Government traffic management bureau, hospitals, and insurance companies put massive manpower and material resources to deal with accidents. For more reasonable resource assignment, in this study we focus on the prediction of daily Vehicle Accident Rate (VAR), namely the percentage of vehicles with accidents. Specifically, we analyze how the variation of VAR correlates with the macroscopic features, like Chinese festival, date, tail-number limit line etc., and develop the prediction model for VAR based on these features. Our analysis is based on the records of two-year accidents on the vehicles, which are insured by a local insurance giant in Beijing. Experiments show that the proposed model can predict the long-term VAR for at least three months in advance, with satisfactory results. Note also that our study is based on the local conditions in Beijing with Chinese characteristics. It not only helps government bureaus and insurance companies to operate more efficiently, but also helps to know many underlying characteristics of this China capital in a macroscopic perspective.