Unfactored analysis component matrix.

<div><p>Different driving environments may lead to increased mental workload and fatigue among drivers, consequently diminishing driving safety. To investigate the impact of various factors on drivers’ driving load, this study approaches the issue from three perspectives: external weathe...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Hao Li (31608) (author)
مؤلفون آخرون: Heng Jiang (1414696) (author), Jiabao Yang (1678540) (author)
منشور في: 2024
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author Hao Li (31608)
author2 Heng Jiang (1414696)
Jiabao Yang (1678540)
author2_role author
author
author_facet Hao Li (31608)
Heng Jiang (1414696)
Jiabao Yang (1678540)
author_role author
dc.creator.none.fl_str_mv Hao Li (31608)
Heng Jiang (1414696)
Jiabao Yang (1678540)
dc.date.none.fl_str_mv 2024-12-06T18:26:45Z
dc.identifier.none.fl_str_mv 10.1371/journal.pone.0315180.t011
dc.relation.none.fl_str_mv https://figshare.com/articles/dataset/Unfactored_analysis_component_matrix_/27982679
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Ecology
Science Policy
Space Science
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
provincial highway s208
external weather environment
vehicle driving environment
four visual indicators
driver distraction decreases
mountainous road section
increased mental workload
fatigue among drivers
drivers &# 8217
various factor combinations
road driving environment
driving workload indicate
driving sub
driving load
visual characteristics
factor analysis
driver experiences
various factors
xianning city
traffic flow
three perspectives
study approaches
saccade velocity
saccade angle
pupil area
plant spacing
night based
mountain area
minimum level
influence exerted
fixation duration
experimental modeling
evaluation results
depth exploration
comprehensive examination
chongyang county
6 meters
dc.title.none.fl_str_mv Unfactored analysis component matrix.
dc.type.none.fl_str_mv Dataset
info:eu-repo/semantics/publishedVersion
dataset
description <div><p>Different driving environments may lead to increased mental workload and fatigue among drivers, consequently diminishing driving safety. To investigate the impact of various factors on drivers’ driving load, this study approaches the issue from three perspectives: external weather environment, road driving environment, and in-vehicle driving environment. Through the experimental modeling of the mountainous road section of Provincial Highway S208 in Chongyang County, Xianning City, and employing simulated driving experiments, various factor combinations were designed to investigate the visual characteristics of drivers. Through factor analysis, a comprehensive examination is conducted on four visual indicators: the rate of change in pupil area, fixation duration, saccade velocity, and saccade angle, to explore the patterns of influence exerted by these factors on the driving load of drivers. The evaluation results of driving workload indicate that the degree of driver distraction decreases when the plant spacing is set at 6 meters and the type of road traffic auxiliary facilities is configured to two. When the traffic flow on the road is zero and no driving sub-mission are present, the driver experiences the minimum level of workload. The findings of this study provide robust theoretical support for nighttime mountain driving safety, contributing to the in-depth exploration of traffic safety theories.</p></div>
eu_rights_str_mv openAccess
id Manara_0e33593fb1cd48bbfbb2d2ae66355c97
identifier_str_mv 10.1371/journal.pone.0315180.t011
network_acronym_str Manara
network_name_str ManaraRepo
oai_identifier_str oai:figshare.com:article/27982679
publishDate 2024
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
rights_invalid_str_mv CC BY 4.0
spelling Unfactored analysis component matrix.Hao Li (31608)Heng Jiang (1414696)Jiabao Yang (1678540)EcologyScience PolicySpace ScienceEnvironmental Sciences not elsewhere classifiedBiological Sciences not elsewhere classifiedprovincial highway s208external weather environmentvehicle driving environmentfour visual indicatorsdriver distraction decreasesmountainous road sectionincreased mental workloadfatigue among driversdrivers &# 8217various factor combinationsroad driving environmentdriving workload indicatedriving subdriving loadvisual characteristicsfactor analysisdriver experiencesvarious factorsxianning citytraffic flowthree perspectivesstudy approachessaccade velocitysaccade anglepupil areaplant spacingnight basedmountain areaminimum levelinfluence exertedfixation durationexperimental modelingevaluation resultsdepth explorationcomprehensive examinationchongyang county6 meters<div><p>Different driving environments may lead to increased mental workload and fatigue among drivers, consequently diminishing driving safety. To investigate the impact of various factors on drivers’ driving load, this study approaches the issue from three perspectives: external weather environment, road driving environment, and in-vehicle driving environment. Through the experimental modeling of the mountainous road section of Provincial Highway S208 in Chongyang County, Xianning City, and employing simulated driving experiments, various factor combinations were designed to investigate the visual characteristics of drivers. Through factor analysis, a comprehensive examination is conducted on four visual indicators: the rate of change in pupil area, fixation duration, saccade velocity, and saccade angle, to explore the patterns of influence exerted by these factors on the driving load of drivers. The evaluation results of driving workload indicate that the degree of driver distraction decreases when the plant spacing is set at 6 meters and the type of road traffic auxiliary facilities is configured to two. When the traffic flow on the road is zero and no driving sub-mission are present, the driver experiences the minimum level of workload. The findings of this study provide robust theoretical support for nighttime mountain driving safety, contributing to the in-depth exploration of traffic safety theories.</p></div>2024-12-06T18:26:45ZDatasetinfo:eu-repo/semantics/publishedVersiondataset10.1371/journal.pone.0315180.t011https://figshare.com/articles/dataset/Unfactored_analysis_component_matrix_/27982679CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/279826792024-12-06T18:26:45Z
spellingShingle Unfactored analysis component matrix.
Hao Li (31608)
Ecology
Science Policy
Space Science
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
provincial highway s208
external weather environment
vehicle driving environment
four visual indicators
driver distraction decreases
mountainous road section
increased mental workload
fatigue among drivers
drivers &# 8217
various factor combinations
road driving environment
driving workload indicate
driving sub
driving load
visual characteristics
factor analysis
driver experiences
various factors
xianning city
traffic flow
three perspectives
study approaches
saccade velocity
saccade angle
pupil area
plant spacing
night based
mountain area
minimum level
influence exerted
fixation duration
experimental modeling
evaluation results
depth exploration
comprehensive examination
chongyang county
6 meters
status_str publishedVersion
title Unfactored analysis component matrix.
title_full Unfactored analysis component matrix.
title_fullStr Unfactored analysis component matrix.
title_full_unstemmed Unfactored analysis component matrix.
title_short Unfactored analysis component matrix.
title_sort Unfactored analysis component matrix.
topic Ecology
Science Policy
Space Science
Environmental Sciences not elsewhere classified
Biological Sciences not elsewhere classified
provincial highway s208
external weather environment
vehicle driving environment
four visual indicators
driver distraction decreases
mountainous road section
increased mental workload
fatigue among drivers
drivers &# 8217
various factor combinations
road driving environment
driving workload indicate
driving sub
driving load
visual characteristics
factor analysis
driver experiences
various factors
xianning city
traffic flow
three perspectives
study approaches
saccade velocity
saccade angle
pupil area
plant spacing
night based
mountain area
minimum level
influence exerted
fixation duration
experimental modeling
evaluation results
depth exploration
comprehensive examination
chongyang county
6 meters