Evidence map›Paper›PMID 36056159›Full record

ArticleScientific reports2022

A comprehensive evaluation model for the intelligent automobile cockpit comfort.

Jianjun Yang, Shanshan Xing, Yimeng Chen, Ruizhi Qiu, Chunrong Hua, Dawei Dong

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jianjun Yang *School of Automobile and Transportation, Xihua University, Chengdu, 610039, China. yangjj@mail.xhu.edu.cn.
Shanshan Xing *School of Automobile and Transportation, Xihua University, Chengdu, 610039, China.
Yimeng ChenSchool of Automobile and Transportation, Xihua University, Chengdu, 610039, China.
Ruizhi QiuSchool of Automobile and Transportation, Xihua University, Chengdu, 610039, China.
Chunrong HuaSchool of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China.
Dawei DongSchool of Mechanical Engineering, Southwest Jiaotong University, Chengdu, 610031, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Under the background of automobile intelligence, cockpit comfort is receiving increasing attention, and intelligent cockpit comfort evaluation is especially important. To study the intelligent cockpit comfort evaluation model, this paper divides the intelligent cockpit comfort influencing factors into four factors and influencing indices: acoustic environment, optical environment, thermal environment, and human-computer interaction environment. The subjective and objective evaluation methods are used to obtain the subjective weights and objective weights of each index by the analytic hierarchy process and the improved entropy weight method, respectively. On this basis, the weights are combined by using the game theory viewpoint to obtain a comprehensive evaluation model of the intelligent automobile cockpit comfort. Then, the cloud algorithm was used to generate the rank comprehensive cloud model of each index for comparison. The research results found that among the four main factors affecting the intelligent automobile cockpit comfort, human-computer interaction has the greatest impact on it, followed by the thermal environment, acoustic environment, and optical environment. The results of the study can be used in intelligent cockpit design to make intelligent cockpits provide better services for people.

Indexed as

AlgorithmsAutomobilesEntropyHumansIntelligence

Identifiers

PMID36056159
PMCPMC9440248

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.