Auxiliary responsibility determination method and system for fender bender

Abstract

The invention relates to the technical field of traffic management, and discloses an auxiliary responsibility determination method and system for a fender bender. The method comprises the following steps: S10, receiving traveling data sequences which are sent by car-mounted information terminals in cars immediately after the occurrence of an accident, receiving video clips sent by the car-mountedinformation terminals in the cars, and receiving pictures of an accident site; S20, processing and analyzing the video clips and the pictures of the accident site through the video information processing technology and the image recognition technology, so that the type of the traffic accident is determined; and S30, extracting and analyzing key information in the video clips, the pictures of the accident site and the traveling data sequences according to the type of the traffic accident and a preset responsibility determination model, so that the car responsible for the accident is determined.The method and system disclosed by the invention has the advantages that multi-source data are actively integrated for effective accident content digging, so that the occurrence of the accident can be rapidly reproduced, the accident responsibility can be scientifically and pertinently determined according to the accident type, spending of the police force can be reduced, an unimpeded road can bequickly restored, and fewer subsequent disputes can be achieved.

Description

technical field [0001] The invention relates to the technical field of traffic management, in particular to a method and system for assisting in determining responsibility for minor traffic accidents. Background technique [0002] With the development of society, vehicles are becoming more and more popular in people's daily life. The huge number of vehicles leads to traffic congestion on the daily commuting road. Big data shows that the traffic congestion problems during peak hours are not only the large traffic flow, but the road infrastructure is not perfect. In addition to other objective factors, subjectively, it is often caused by uncivilized behaviors such as malicious jamming, dangerous overtaking, and random lane changes by a very small number of drivers in a hurry, and minor traffic accidents such as scratches and rear-end collisions are prone to occur. Congestion is difficult to quickly reach the accident scene for immediate processing, and the processing efficienc...

AI Technical Summary

Problems solved by technology

The system does not require traffic police or claim personnel to arrive at the accident scene for processing, and can carry out online liability determination and claim settlement procedures, which improves the efficiency of traffic accident handling. , Whether the collection is accurate depends entirely on the subjective consciousness of the vehicle client operator. For car owners who have never been in contact with or rarely experienced car accident evidence collection, it is difficult to complete the on-site evidence collection calmly and orderly when they are the parties involved in the accident. The owner of the car is likely to miss some important evidence or take a lot of invalid evidence. Although the system will review the image, if it fails to pass the review all the time, it will inevitably delay time and processing efficiency. It cannot be guaranteed, and the responsibility determination can only be made through the collection of accident status images of vehicles on the vehicle-mounted client. Not only the image processing task is heavy, but the result of the responsibility determination is easily denied by the vehicle owner, and it cannot completely solve the subjective problem. The issue of subsequent disputes caused by car owners who choose to keep private and do not collect evidence

[0004] Another example is the patent document with the publication number CN105005932A disclosing "a method for determining liability and claim settlement in traffic accidents". Including the location of the accident, the time of the accident, the license plate of the accident vehicle, and the camera at the scene of the accident. The accident information is collected by the front-end equipment built in the vehicle. In addition, how the appraisal center remotely analyzes the accident and determines the responsibility is to ensure whether the final responsibility determination result is reasonable, whether it can be quickly accepted by both car owners, and whether it can effectively reduce police expenditure. The top priority of the accident, but the above-mentioned plan does not carry out detailed and accurate responsibility determination for the accident

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