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Cognitive load evaluation method, device and system and storage medium

A cognitive load and evaluation method technology, applied in other database retrieval, other database clustering/classification, etc., can solve the problem of not truly and comprehensively reflecting the driver's cognitive load

Inactive Publication Date: 2020-01-14
CHINA INTELLIGENT & CONNECTED VEHICLES (BEIJING) RES INST CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this type of evaluation method uses a single index, which cannot truly and comprehensively reflect the cognitive load of the driver.

Method used

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  • Cognitive load evaluation method, device and system and storage medium
  • Cognitive load evaluation method, device and system and storage medium
  • Cognitive load evaluation method, device and system and storage medium

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Experimental program
Comparison scheme
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Embodiment 1

[0044] Embodiment 1 of the present invention provides a cognitive load evaluation method, figure 1 It is a schematic flow chart of the cognitive load evaluation method in Embodiment 1 of the present invention, such as figure 1 As shown, the cognitive load evaluation method of Embodiment 1 of the present invention includes the following steps:

[0045] S101: Acquire a cognitive data set, and determine a cognitive environment in which the cognitive data set is located.

[0046] In Embodiment 1 of the present invention, cognitive data set A n Include multiple attribute values ​​{a 1 ,a 2 ,...,a i, ...,a n}. Example, Cognitive Dataset A n Including driver operation reaction time a 1 , The driver's peripheral vision detection scene reaction time a 2 , The correct rate of the driver's peripheral vision detection scene a 3 and the driver's heart rate variability a 4 .

[0047]The cognitive environment described in the embodiment of the present invention refers to the driv...

Embodiment 2

[0056] Embodiment 2 of the present invention provides a cognitive load evaluation method, and the cognitive load evaluation method in Embodiment 2 of the present invention includes the following steps:

[0057] S201: Construct the cluster center database according to the sample cognitive data.

[0058] As a specific implementation manner, Embodiment 2 of the present invention provides a method for constructing a cluster center database. figure 2 It is a schematic flow diagram of constructing a cluster center database in Embodiment 2 of the present invention, such as figure 2 shown, including the following steps:

[0059] Step 1: Acquire multiple sample cognitive datasets of the same cognitive environment.

[0060] Step 2: Use the preset benchmark data to correct each sample cognitive data set to obtain the corrected sample cognitive data set.

[0061] As a specific implementation, each sample cognition data set is corrected by using the preset benchmark data, and obtainin...

Embodiment 3

[0075] Embodiment 3 of the present invention provides a cognitive load evaluation device, image 3 It is a schematic structural diagram of the cognitive load evaluation device in Embodiment 3 of the present invention, such as image 3 As shown, the cognitive load assessment device according to Embodiment 3 of the present invention includes: an acquisition module 30 , a processing module 32 , a calculation module 34 and a cognitive load determination module 36 .

[0076] Specifically, the obtaining module 30 is configured to obtain a cognitive data set.

[0077] The processing module 32 is configured to determine the cognitive environment where the cognitive data set is located.

[0078] The calculation module 34 is used to calculate the Euclidean distance between the cognitive data set and each cluster center in the cognitive environment of the preset cluster center database.

[0079] The cognitive load determination module 36 is configured to select the minimum Euclidean di...

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Abstract

The invention discloses a cognitive load evaluation method, device and system and a storage medium, and the method comprises the steps: obtaining a cognitive data set, and determining a cognitive environment where the cognitive data set is located; respectively calculating the Euclidean distance between the cognitive data set and each clustering center in the cognitive environment of a preset clustering center database; and selecting the minimum Euclidean distance, and taking the cognitive load level to which the clustering center corresponding to the minimum Euclidean distance belongs as thecognitive load level of the cognitive data set. According to the scheme, the Euclidean distance between the cognitive data set and each clustering center in the cognitive environment of the preset clustering center database is calculated; therefore, the cognitive load level of the cognitive data set can be determined, and the cognitive load change caused by the automobile driving function change to the driver of the intelligent connected automobile can be rated before the intelligent connected automobile is designed and shaped, so that the rationality and the humanization of the man-machine interface design of the intelligent connected automobile are determined.

Description

technical field [0001] The present invention relates to the technical field of intelligent driving, in particular to a cognitive load evaluation method, device, system and storage medium. Background technique [0002] In the cockpit of intelligent connected cars, with the continuous upgrading of information technology and the integration of new technologies, the driver's information cognition has increased, and the driver's cognitive load has also increased accordingly. If the driver's cognitive load is too large, the driver's actions will be slow, incoherent, sluggish, attention will be weakened, and visual acuity will be reduced. The response speed and ability of personnel to deal with emergency situations is reduced. [0003] Therefore, it is necessary to evaluate the driver's cognitive load before the design of the car is finalized, so as to determine whether the new human-machine function allocation has caused an excessive cognitive load on the driver and thus affects ...

Claims

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Application Information

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IPC IPC(8): G06F16/906
CPCG06F16/906
Inventor 王群高景伯孙宁姜川陈瀚鲁鹏孔维星谢勃毅
Owner CHINA INTELLIGENT & CONNECTED VEHICLES (BEIJING) RES INST CO LTD