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Driving state recognition method based on approximate entropy template matching

A driving state and template matching technology, applied in the field of driving state recognition, can solve problems such as impossible to predict real-time road conditions

Active Publication Date: 2017-02-22
陕西智慧路衡电子科技有限公司
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AI Technical Summary

Problems solved by technology

Although the driver may know the macro situation of the next road section, it is impossible to predict the real-time road conditions at the next moment. The real-time information of the road determines the driver's operation actions, and then determines the vehicle driving status information

Method used

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  • Driving state recognition method based on approximate entropy template matching
  • Driving state recognition method based on approximate entropy template matching
  • Driving state recognition method based on approximate entropy template matching

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Embodiment Construction

[0123] Such as figure 1 A driving state identification method based on advanced entropy template matching is shown, comprising the following steps:

[0124] Step 1. Establishment of the sample library: the data processor 2 is used to establish the sample library. There are two types of samples stored in the established sample library. For the multiple steering wheel angle signals measured, another type of sample is a dangerous driving state sample and this type of sample includes multiple steering wheel angle signals under the dangerous driving state of the monitored driver;

[0125] Step 2. Road information stripping based on advanced entropy template matching: using the data processor 2 and calling the signal correction module based on advanced entropy template matching to correct each steering wheel angle signal in the sample library, and all steering wheel angle signals The correction methods are all the same; when any one of the steering wheel angle signal x(t) is correc...

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Abstract

The invention discloses a driving state recognition method based on approximate entropy template matching, and the method comprises the steps: 1, sample library building, wherein samples of one type in the sample library are a plurality of steering wheel turning angle signals in a normal driving state, and samples of the other type in the sample library are a plurality of steering wheel turning angle signals in a dangerous driving state; 2, road information segmentation based on the approximate entropy template matching: carrying out the call of a signal correction module based on the approximate entropy template matching to correct the steering wheel turning angle signals in the library sample, wherein the correction process of any one steering wheel turning angle signal is as follows: carrying out the EMD (Empirical Mode Decomposition), the effectiveness recognition of an intrinsic mode function component, and signal reconstruction; 3, feature extraction; 4, two-class model building and training; 4, driving state information collection and synchronous classification. The method is simple in steps, is reasonable in design, is easy and convenient to implement, is good in use effect, can accurately recognize the driving state of a driver simply and conveniently, and is high in recognition precision.

Description

technical field [0001] The invention belongs to the technical field of driving state identification, and in particular relates to a driving state identification method based on progressive entropy template matching. Background technique [0002] Traffic accidents on the road are the result of the interaction of factors such as people, vehicles, roads, and the environment, and the driver is the most active factor affecting traffic safety. A traffic accident appears to be an accidental phenomenon on the surface, but in essence it is an instability phenomenon caused by the closed-loop system formed by the driver-vehicle-environment because it cannot respond to the sudden change of working conditions encountered. Through the investigation of a large number of evidence of collision marks and vehicle remains left at the scene of traffic accidents, combined with questionnaire surveys of survivors, researchers from Indiana University in the United States came to the conclusion that ...

Claims

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Application Information

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IPC IPC(8): G06K9/00
CPCG06F2218/00G06F2218/12
Inventor 赵栓峰
Owner 陕西智慧路衡电子科技有限公司
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