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Dangerous driving behavior identification method

A recognition method and dangerous driving technology, applied in the field of dangerous driving behavior recognition, can solve problems such as limited accuracy and anti-noise interference, and achieve the effect of improving usability, comprehensive and accurate reasoning and judgment

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AI Technical Summary

Problems solved by technology

[0003] The existing algorithm mechanism for dangerous driving behavior recognition is relatively simple, with limited accuracy and anti-noise interference ability, and there is no relevant recognition ability for some dangerous driving behaviors, so it is necessary to propose a new dangerous driving behavior recognition system

Method used

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  • Dangerous driving behavior identification method
  • Dangerous driving behavior identification method
  • Dangerous driving behavior identification method

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Embodiment Construction

[0044] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0045] As shown in the figure, a dangerous driving behavior identification method uses Beidou high-precision positioning technology, high-precision map and camera-based vehicle trajectory tracking system to obtain all aspects of vehicle information, laying a data foundation for real-time identification of dangerous driving behavior .

[0046] Synthesizing multi-source information can avoid large errors caused by interference of a single information source, transmission delay, equipment failure, etc. At the same time, there is a certain degree of redundancy among multi-source data, which improves the availability and robustness of the system, thereby Get more comprehensive and accurate reasoning and judgment than any single source of information.

[0047] Using the non-extended Kalman filter information fusion algorithm, the vehicle trajectory ...

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Abstract

The invention relates to the field of high-speed monitoring. The invention particularly relates to a dangerous driving behavior identification method which fuses vehicle trajectory tracking of Beidoupositioning and vehicle trajectory tracking recognized by a camera through a non-extended Kalman filtering information fusion algorithm, predicts dangerous lane changing behaviors which need to be identified emphatically by using an HMM model based on GMM description output, and identifies overspeed behaviors, rapid acceleration and rapid deceleration behaviors, dangerous lane changing behaviors and fatigue driving behaviors in combination with camera identification, judgment and verification. According to the scheme, after the dangerous driving behavior recognition system based on Beidou high-precision positioning and camera recognition vehicle trajectory tracking fusion is combined with the high-precision map, various dangerous driving behavior recognition and prediction functions are well completed.

Description

technical field [0001] The invention relates to the field of high-speed monitoring, in particular to a dangerous driving behavior identification method. Background technique [0002] As people pay more and more attention to traffic safety, coupled with the formulation and promotion of relevant national policies, the demand for early warning technology for dangerous driving is increasing. With the rapid development and expansion of expressways, traffic accidents continue to increase. Although there are various reasons for traffic accidents, human factors are its main component. The driver's dangerous driving behavior is the cause of some major traffic accidents. If these abnormal driving behaviors can be identified and combined with prompts and alarms, some traffic accidents can be avoided to a certain extent. [0003] The existing algorithm mechanism for dangerous driving behavior recognition is relatively simple, with limited accuracy and anti-noise interference ability, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62H04W4/029H04W4/40
CPCH04W4/029H04W4/40G06V20/54G06F18/23G06F18/25G06F18/214
Inventor 亓凌王长华陶杰朱熙豪汪内利郑于海于涵诚
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