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Road rage driver dangerous behavior characteristic variable screening method based on random forest algorithm

A random forest algorithm, a technology of feature variables, applied in computing, computer parts, instruments, etc., can solve problems such as difficulty in evaluating the impact of driving behavior

Pending Publication Date: 2019-08-06
TONGJI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] Due to the variety of driving behavior data collected by driving simulators, it is difficult to evaluate the impact of different parameters on driving behavior by general methods

Method used

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  • Road rage driver dangerous behavior characteristic variable screening method based on random forest algorithm
  • Road rage driver dangerous behavior characteristic variable screening method based on random forest algorithm
  • Road rage driver dangerous behavior characteristic variable screening method based on random forest algorithm

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Embodiment Construction

[0024] Preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0025] The random forest algorithm-based screening method for road rage drivers’ dangerous behavior characteristic variables extracts the driver’s driving behavior parameters from the driving simulator to realize the screening of road rage driver characteristic variables based on driver behavior characteristics; the specific method flow is as follows:

[0026] Get the road rage driver driving behavior dataset.

[0027] The data set mainly includes: driver anger level set and driving behavior feature set.

[0028] The driver's anger level set includes non-angry driving state and angry driving state, and the driver's anger level is a binary variable.

[0029] The driving behavior feature set includes vehicle lateral / longitudinal acceleration, steering wheel angle, brake pedal pressure, accelerator pedal pressure, vehicle lateral / longitudinal s...

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Abstract

The invention provides a road rage driver dangerous behavior characteristic variable screening method based on a random forest algorithm. Based on original driving simulator experimental data, a driver behavior data set and a driving anger state set are constructed, dangerous feature recognition is conducted on driver behaviors in the road rage state through a random forest, and the method has practical significance in the aspects of designing a driving anger early warning system subsequently and the like.

Description

technical field [0001] The invention relates to a method for screening characteristic variables of road rage drivers' dangerous behavior based on random forest algorithm. Background technique [0002] Angry driving was originally defined as a specific situation constituted by an affective structure, including anger-related emotions and thoughts generated during driving. Angry driving is a common occurrence in everyday life, and it is a noticeable and dangerous form of anger. [0003] Anger while driving is associated with the risk of a near-collision or crash. From the perspective of driving behavior, road rage drivers are more likely to take risks and deliberately drive unsafely during driving. The driver's anger during driving will have a negative impact on the driver's driving ability. For example, angry driving will increase the proportion of drivers making mistakes and prolong the reaction time to danger. Research shows that angry driving increases the likelihood of ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/597G06F18/2415
Inventor 蔡博文张旭欣柴晨王雪松
Owner TONGJI UNIV
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