It is important to study traffic vehicle collision data. Chicago is the third largest city in the United States with a population of more than two million. Thus efficient traffic management systems are needed. However, from the data in recent years, the collision data of traffic vehicles in Chicago is not optimistic, and people's life is threatened. Now there are some shortcomings in the current research. First, there are few analysis models for traffic vehicle collision data. What’s more, it is difficult to apply related methods to traffic car collision data because of too much data. Third, there are many kinds of data, and sometimes relationships can be complex. This paper analyzes Chicago traffic crash data from 2015 to 2019. Important information such as the date of the traffic vehicle collision, the road surface and weather conditions, and the condition of the vehicle is analyzed in this article. This paper used geographical location analysis, multicomponent analysis and exploratory data analysis to analyze the relationships of many variables. It is found that good driver conditions and fine weather are difficult to cause traffic vehicle collisions, high alcohol content and improper vehicle speed are likely to lead to traffic collision accidents. More intelligent transportation facilities which is intelligent roadside parking spaces and infrared motor vehicle induction signal equipment are needed on the road. The conclusions obtained in this paper are of great significance for the analysis of the establishment and application of traffic vehicle collision data models.

Traffic vehicle collision data;Exploratory Data Analysis;Multivariate analysis