TY - JOUR
T1 - Analyzing Cognitive Load Measurements of the Truck Drivers to Determine Transportation Routes and Improve Safety Driving
T2 - A Review Study
AU - Sudiarno, Adithya
AU - Ma’arij, Ahmad Murtaja Dzaky
AU - Tama, Ishardita Pambudi
AU - Larasati, Aisyah
AU - Hardinigtyas, Dewi
N1 - Publisher Copyright:
© 2023, Universitas Muhammadiyah Magelang. All rights reserved.
PY - 2023/1/1
Y1 - 2023/1/1
N2 - As part of the Supply Chain (SC), oftentimes Land Logistic Driver (LLD) are held by various uncontrollable occurrences from the surroundings. This caused the cognitive load of the drivers to become higher, which could potentially affect the performance of the LLD to meet the Key Performance Indicator (KPI) of the SC overall. Not only the performance that is affected, but a higher load also could affect the driving behavior towards negativity, as anger and stress perceived become higher, hence a higher crash possibility. Therefore, the need to study the possibility to measure the cognitive load in a certain route that they are on, so any adjustments could be made during a transport activity, with Electroencephalogram (EEG) used as the means to measure it. This study is done by reviewing 15 available research as references regarding EEG and cognitive load. It is possible to use EEG in measuring cognitive load during driving activity, with the focus area of data gathering on the central lobe, parietal lobe, and temporal lobes, with the data extracted from EEG should use the most accurate classifier that focuses on analyzing beta (β) and alpha (α) band as the significant brain wave of the active state. The possible result of the brain wave analysis could be used to determine whether the current route option is burdening LLDs' cognitive load and should be corrected to improve safety driving. Further inclusion of the analysis result could be incorporated into a set of KPI in measuring SC performance.
AB - As part of the Supply Chain (SC), oftentimes Land Logistic Driver (LLD) are held by various uncontrollable occurrences from the surroundings. This caused the cognitive load of the drivers to become higher, which could potentially affect the performance of the LLD to meet the Key Performance Indicator (KPI) of the SC overall. Not only the performance that is affected, but a higher load also could affect the driving behavior towards negativity, as anger and stress perceived become higher, hence a higher crash possibility. Therefore, the need to study the possibility to measure the cognitive load in a certain route that they are on, so any adjustments could be made during a transport activity, with Electroencephalogram (EEG) used as the means to measure it. This study is done by reviewing 15 available research as references regarding EEG and cognitive load. It is possible to use EEG in measuring cognitive load during driving activity, with the focus area of data gathering on the central lobe, parietal lobe, and temporal lobes, with the data extracted from EEG should use the most accurate classifier that focuses on analyzing beta (β) and alpha (α) band as the significant brain wave of the active state. The possible result of the brain wave analysis could be used to determine whether the current route option is burdening LLDs' cognitive load and should be corrected to improve safety driving. Further inclusion of the analysis result could be incorporated into a set of KPI in measuring SC performance.
KW - Cognitive load
KW - Driving fatigue
KW - Electroencephalogram
KW - Safety driving
KW - Transportation route
UR - http://www.scopus.com/inward/record.url?scp=85159423278&partnerID=8YFLogxK
U2 - 10.31603/ae.8301
DO - 10.31603/ae.8301
M3 - Review article
AN - SCOPUS:85159423278
SN - 2615-6202
VL - 6
SP - 149
EP - 161
JO - Automotive Experiences
JF - Automotive Experiences
IS - 1
ER -