Effects of Driver Task-related Fatigue on Driving Performance

Gastaldi, Massimiliano; Rossi, R.; Gecchele, Gregorio

doi:10.1016/j.sbspro.2014.01.130

Cited by 61 publications

(51 citation statements)

References 25 publications

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“…Previous research has investigated the driving duration effect on physiological and performance decrement (Schleicher et al, 2008;Di Stasi et al, 2012;Wang & Pei, 2014;Gastaldi et al, 2014). However, most of the prior research has studied the effect of short driving duration, which is defined as below two hours (Schleicher et al, 2008;Di Stasi et al, 2012;Gastaldi et al, 2014). Wang and Pei (2014) investigated the effect of four hours of driving on performance measures; however, a study looking at the possibility of using other indicators has not yet been conducted.…”

Section: Introductionmentioning

confidence: 99%

Effect Of Driving Duration On Eeg Fluctuations

Puspasari¹,

Iridiastadi

Sutalaksana

et al. 2017

IJTech

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Road accidents are a major issue in Indonesia, and their number increases every year. Based on previous studies, mental fatigue is one of the biggest factors leading to road accidents and is majorly affected by mental workload. Driving duration is one of the factors that triggers mental fatigue. The prior literature cites electroencephalogram (EEG) measurement as the gold standard for measuring fatigue. However, there has been only limited study to examine the EEG indicators that are affected by driving duration, and the prior research still contains disagreements regarding the best EEG parameter for use in measuring fatigue. Therefore, this study aimed to evaluate the effect of driving duration on EEG fluctuation and determine the best EEG parameter related to fatigue. Seven participants were asked to spend three hours driving in a medium-fidelity simulator. A one-way ANOVA and correlation analysis were performed to measure the effect of driving duration on the EEG indicators and determine the correlation of the indicators. A Receiver Operating Characteristics (ROC) curve was also utilized to determine the variable with the greatest correlation with the subjective sleepiness indices. The results showed that at the end of three hours' driving, there was an increment in delta and theta activities, followed by a decrement in alpha and beta activities. In addition, the correlation of all bands was significant, with positive results for the alpha-beta and theta-delta bands, and a negative result in relation to each other. Furthermore, the results from the ROC curve revealed the Relative Power Ratio (RPR) of theta, the RPR of alpha, and the ratio of θ/α+β to be the best indicators among others, demonstrating a high degree of accuracy (above 85%).

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Section: Introductionmentioning

confidence: 99%

Effect Of Driving Duration On Eeg Fluctuations

Puspasari¹,

Iridiastadi

Sutalaksana

et al. 2017

IJTech

View full text Add to dashboard Cite

show abstract

“…Sobre las horas de conducción, diferentes estudios muestran resultados semejantes, donde el tiempo de conducción por lo general es mayor de 10 horas (14,15) , esto demuestra que la actividad laboral de los conductores es inversamente proporcional a sus horas de sueño, pudiendo ser este el motivo por el cual los conductores presenten excesiva somnolencia diurna; además, en el presente estudio la somnolencia diurna se podría atribuir al sistema de rotación, teniendo en consideración el turno laboral de cada uno de los conductores, como es el caso del estudio de Gastaldi et al (22) .…”

Section: Discussionunclassified

Factores asociados a somnolencia diurna en conductores de transporte público de Lima Metropolitana

Peña-Prado

Castro

Talaverano-Ojeda

2019

Rev Peru Med Exp Salud Publica

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Objetivos. Determinar la frecuencia de somnolencia y sus factores asociados en conductores de transporte público de Lima Metropolitana. Materiales y métodos. Estudio analítico transversal realizado en conductores de entre 18 y 65 años, que laboren en alguna empresa de transporte público registrada en la Municipalidad de Lima. La somnolencia se evaluó mediante una versión de la Escala de Somnolencia de Epworth validada en Perú. Las variables que se pudieron comportar como factores asociados se obtuvieron mediante una ficha de recolección de datos. Se utilizó la regresión logística para estimar la magnitud de la asociación entre la somnolencia y las variables consideradas como factores asociados. Resultados. Se incluyeron a 440 conductores, cuya mediana de edad fue 38,0 años y la mayoría (99,3%) fueron varones. Del total de conductores el 17,7% (78) presentaron somnolencia diurna. Se encontró una asociación significativa entre la somnolencia y el sistema de rotación 2 x 1 (p=0,038) y entre la somnolencia y las horas de sueño menores a siete (p=0,011). El análisis de regresión logística demostró que aquellos conductores con seis o menos horas de sueño tienen mayor probabilidad de somnolencia diurna (OR 1,83; IC95%: 1,03-3,25). Conclusiones. Aproximadamente, uno de cada cinco conductores presentó somnolencia diurna, la cual estuvo asociada con tener seis o menos horas de sueño al día.

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“…One of the most relevant processes related to driving behavior that is at risk is fatigue [31]. In the specific case of professional drivers, it has been shown that in the context of work, fatigue predicts a greater prevalence of occupational diseases (e.g.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Vehicle Reaction Time in Arriving the Toll Gate

Surianto¹,

Purwantoro²,

Santosa³

et al. 2019

IJARET

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This paper presents the level of road density and the number of vehicles passing on the Jakarta city toll road. This study was conducted at the Jakarta Toll Gate namely Semanggi I, Semanggi II and Halim. Data is obtained from observations when the driver pays the cost of the expressway at the toll gate. This study shows a reaction time for the payment of expressway costs, which are influenced by types of motorized vehicles such as sedans, jeeps, buses, and trucks. The results show that the reaction time of driver when before and after paying, the longest toll road costs is 48 seconds and the shortest is 1 second. Reaction time for the payment of expressway costs could shorten the travel time, with an average reaction time of 6.04 seconds on vehicles. The number of vehicles crossing the toll gate on 24 hours from the three Toll Gates amount 17.256 vehicles. As a result, Most of vehicle traffic contributed by the behavior of driver at the Toll Gate.

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Effects of Driver Task-related Fatigue on Driving Performance

Cited by 61 publications

References 25 publications

Effect Of Driving Duration On Eeg Fluctuations

Effect Of Driving Duration On Eeg Fluctuations

Factores asociados a somnolencia diurna en conductores de transporte público de Lima Metropolitana

Analysis of Vehicle Reaction Time in Arriving the Toll Gate

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