Method and system for detecting abnormal track in driver driving track

Abstract

The invention provides a method and a system for detecting abnormal tracks in driver driving tracks. By comparing with historical driving tracks of a driver and driving tracks of other drivers, whether tracks are abnormal driving tracks is detected. The method comprises the steps of acquiring an original data set, performing preliminary processing to data, performing training to generate an abnormal driving track detection model, and detecting the abnormal tracks in the original data of the driver by using the generated abnormal track detection model to obtain the abnormal driving tracks. The detection system comprises an acquisition device and a detection device. As compared with the existing abnormal driver track detection method, the method is applicable to diversified driver track data, the robustness to the number of abnormal tracks is very good, the abnormal driver tracks can be more accurately and efficiently detected, and better aids can be provided for identity authentication in settlement of insurance claim and identification in personalized service.

Description

technical field [0001] The invention relates to the technical field of abnormality detection and mobile crowd sensing, and in particular to a method and system for detecting abnormality in a driver's driving trajectory. Background technique [0002] Anomaly detection finds abnormal behavior in the network or system through collection and statistics, and then judges whether it is an abnormal behavior according to a certain decision operator. The anomaly detection model based on machine learning uses machine learning methods to build system images. Its biggest feature is to distinguish abnormalities based on normality, because most of its training data represent all normal behaviors. The advantage of this method is that the detection speed is fast and the false detection rate is low. However, this method still needs to be improved in terms of user dynamic behavior changes and individual anomaly detection. Adding complex similarity measures and prior knowledge to detection m...

AI Technical Summary

Problems solved by technology

[0005] The existing anomaly detection only considers whether the internal parts of the vehicle are damaged or abnormally consumed, and ignores the abnormal problem of the driver. The analysis from the parameters of the internal parts is not comprehensive.

On the other hand, in the problem of abnormal detection, the existing patents do not define the abnormal trajectory in the driver's driving trajectory, and there is a lack of research on related issues.

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