Analyzing method for accessory vehicles

Abstract

The invention provides an analyzing method for accessory vehicles. The method includes checking running tracks of suspected vehicles from a database during a period, classifying all the locations appeared in the database according to belonged administrative areas to acquired different areas, and meanwhile setting the times when the suspected vehicles pass by each area during a period to be time nodes; automatically generating corresponding checking threads as many as the areas by an application server according to the number of areas; checking all the vehicles passing by the corresponding areas in a plurality minutes before or after the time nodes by each checking thread checking in the database; reading all the running tracks of related vehicles and matching the running tracks with that of the suspected vehicles by the application server, and considering the related vehicles accessory to the suspected vehicles if the matching is successful; and extracting data of all similar vehicles to acquire a list of similar vehicles. By the analyzing method for similar vehicles, the high performance of the application server is fully played, most of the analyzing tasks by the application server are executed, and the pressure of database is highly decreased and the efficiency of data analyzing Is improved.

Description

technical field [0001] The invention relates to the field of computer data processing, and more specifically, relates to a method for analyzing peer vehicles under big data. Background technique [0002] With the deepening of information construction and application, the checkpoints, electronic police and other related vehicle collection systems built all over the country are becoming more and more perfect, and the passing data and driving tracks of vehicles have been retained in the database. At present, when the public security department is looking for a suspect vehicle for an incident, it generally combines the characteristics of criminal gangs’ vehicles that often form groups. When querying the information of the suspect vehicle, it also queries the historical passing data, and digs out the suspect vehicles before and after the incident. Vehicles with the same or similar driving trajectories provide clues to solve the case, thus killing the criminal gangs. However, due...

AI Technical Summary

Problems solved by technology

However, due to the rapid growth of vehicles on the road, the accumulated passing data in the database has grown exponentially, and the capacity has reached the PB level. If you still rely on the database to combine queries, the pressure on the database will be greatly increased, and it will be impossible to analyze and suspect. Vehicle-associated peer vehicles process, ensuring efficient and fast

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