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Driving style estimation method based on driving pattern transition probability

A driving mode and driving style technology, applied in the field of sensors, can solve problems such as inaccurate estimation results, achieve the effect of avoiding road environment and traffic, breaking through the limitations of evaluation dimensions, and high reliability

Active Publication Date: 2016-10-12
TSINGHUA UNIV
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AI Technical Summary

Problems solved by technology

[0007] Aiming at the problem of inaccurate estimation results existing in the prior art when estimating driving style, the technical problem to be solved by the present invention is to provide a driving style estimation method based on the driving mode transition probability to improve the accuracy of estimation

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  • Driving style estimation method based on driving pattern transition probability
  • Driving style estimation method based on driving pattern transition probability
  • Driving style estimation method based on driving pattern transition probability

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Embodiment Construction

[0044] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the drawings and specific embodiments.

[0045] The purpose of the present invention is to overcome the deficiencies of the prior art, and propose a driving style estimation method based on the transition probability of driving modes. The converted probability matrix is ​​used to classify the driving style according to the characteristics of the transition probability matrix to obtain the driver's driving style estimation.

[0046] A method for estimating driving style based on the transition probability of driving modes proposed by the present invention obtains the probability matrix of the transition between driving modes of different drivers, and classifies the driving style according to the characteristics of the transition probability matrix to obtain the driving style. Driver's driving st...

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Abstract

The invention provides a driving style estimation method based on driving pattern transition probability, wherein the method includes the steps: step 1, acquiring actual driving data of a driver, wherein the actual driving history data at least include the steering wheel rotary angle, the vehicle speed, the longitudinal acceleration speed and the transverse acceleration speed; step 2, according to the actual driving data, dividing driving behaviors into N driving behavior patterns; step 3, determining the driving behavior pattern transition probability, wherein the driving behavior pattern transition probability is the transition probability between arbitrary two driving behavior patterns in the N driving behavior patterns; and step 4, taking the driving behavior pattern transition probability as a training sample training classifier, to perform driving style estimation through the classifier.

Description

technical field [0001] The present invention relates to the field of sensor technology, in particular to a driving style estimation method based on driving mode conversion probability. Background technique [0002] The popularization of automobiles has made people's travel more convenient, but also brought a lot of troubles to people. Therefore, automobile manufacturers have equipped vehicles with advanced driver assistance systems, ACC and other automotive electronic systems to improve driving safety and comfort, and reduce the number of drivers. driving load. [0003] It has been shown in many studies that different drivers have different driving styles and judge the danger of driving situations differently. For example, the perceived risk of male drivers is lower than that of female drivers, so male drivers generally show more aggressive driving styles, such as shorter following distances, more frequent lane changes, and so on. Automotive electronic systems such as driv...

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Application Information

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IPC IPC(8): G07C5/08G06K9/62
CPCG07C5/0808G07C5/0841G06F18/24323
Inventor 李升波成波李国法俞佳莹王文军段京良王建强李克强
Owner TSINGHUA UNIV
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