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Risk driving scene rapid extraction and grading method for intelligent network connection automobile testing

A technology for driving scenarios and vehicle testing, applied in vehicle testing, machine/structural component testing, measuring devices, etc., can solve problems such as limited research and development, and achieve the effect of reducing data dimensions

Pending Publication Date: 2020-01-24
AUTOMOBILE RES INST OF TSINGHUA UNIV IN SUZHOU XIANGCHENG
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AI Technical Summary

Problems solved by technology

The premise of risky driving scene analysis is to accurately, quickly and effectively extract and classify its fragments from the massive driving scene database. This method is very dependent on the technical level of driving data encoding, and the current research and development of this technical method is very limited.

Method used

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  • Risk driving scene rapid extraction and grading method for intelligent network connection automobile testing
  • Risk driving scene rapid extraction and grading method for intelligent network connection automobile testing
  • Risk driving scene rapid extraction and grading method for intelligent network connection automobile testing

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Embodiment Construction

[0031] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0032] Time series is a set of event data or sequence values ​​based on time follow-up, reflecting the follow-up characteristics of data attribute values ​​on the time axis, and time series data are usually large in volume, high in dimension, and fast in update frequency. During the test phase of intelligent networked vehicles, a large amount of driving time-series data will be collected, including vehicle speed, acceleration, steering wheel angle, accelerator pedal, brake pedal, video surveillance and other information. The simplification method of driving time-series data can greatly reduce the data capacity. , providing strong technical support for the rapid extraction and classification of risky driving scenarios. Symbolic representation is an effective discretized time series dimensionality reduction method. It has been widely used in man...

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Abstract

The invention discloses a risk driving scene rapid extraction and grading method for intelligent network connection automobile testing. The risk driving scene rapid extraction and grading method comprises the steps that (1) carrying out intelligent network connection automobile driving time sequence data normalization processing; (2) carrying out dimension reduction processing on the intelligent networked automobile driving time sequence data; (3) performing discretization and symbolization processing on the intelligent networked automobile driving time series data; and (4) carrying out rapidextraction and hierarchical processing on the intelligent networked automobile risk driving scene. According to the risk driving scene rapid extraction and grading method for the intelligent networkedautomobile test, various risk driving scenes in the intelligent networked automobile test working condition can be rapidly extracted and graded, and a theoretical method support can be provided for comprehensive construction and refining optimization of a driving scene library in the subsequent intelligent networked automobile test stage.

Description

technical field [0001] The invention belongs to the field of smart car testing, and relates to a method for quickly extracting and grading risky driving scenes oriented to smart connected car testing. Background technique [0002] R&D, testing, and on-road are the three stages of the marketization of ICVs. At present, the development of ICV technology in China is mainly concentrated in the testing phase. Testing can be divided into software-in-the-loop, hardware-in-the-loop, vehicle-in-the-loop, proving ground testing, road testing, etc. The driving data in the test stage can be fed back to the R&D stage for product optimization iterations, and the data results of the road test can be used in the test stage to enrich the capacity of the real driving scene library and the virtual driving scene library, so that the test field can better restore the reality driving environment. Throughout the testing phase, driving data is an important source of driving the above process. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06Q10/06G01M17/007
CPCG06F16/2474G06Q10/0635G01M17/007
Inventor 孙川马育林郑四发田欢李茹
Owner AUTOMOBILE RES INST OF TSINGHUA UNIV IN SUZHOU XIANGCHENG
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