Studying the effect of fatigue and sleepiness of long-haul truck drivers on road accidents by adopting structural equation models analysis

• Main Authors: Shams, Zhaleh, Sanij, Hamed Khani, Afshani, Alireza, Khansari, Ehsan Ramezani, Nejad, Fereidoon Moghadas, Olazar, Martin
• Format: Article
• Language: English
• Published: Penerbit Universiti Kebangsaan Malaysia 2022
• Online Access: http://journalarticle.ukm.my/19971/1/16.pdf; http://journalarticle.ukm.my/19971/; https://www.ukm.my/jkukm/volume-3402-2022/

The significant increase in transportation and heavy vehicle traffic has caused freeway routes with heavy traffic to face a decrease in safety levels. Furthermore, fatigue and sleepiness are proven to be two of the main reasons of road accidents, and therefore focus on these issues is crucial. Factors such as “use of engineering (safety) technology for road transport”, “informing the drivers on various educational methods”, “controlling the drivers’ work hours”, “use of different routes (alignment inconsistency)” and “observing the drivers’ mental health” should be approached to reduce the accidents caused by fatigue and sleepiness. Given the complex interrelationships between these variables and the number of road accidents, structural equation modelling has been used in this study to estimate the effect and relationships between multiple variables. Data were collected during a 5-month period by interviewing heavy vehicle drivers (2765 filled-out questionnaires). The Confirmatory Factor Analysis (CFA) has also been used to ascertain the validity of the questionnaires. The mentioned factors affecting the drivers’ fatigue were analyzed using SPSS 24.0 package, which allowed ascertaining that the drivers’ mental health is the factor of greater influence on road accidents caused by fatigue and drowsiness. Therefore, actions to improve the drivers’ mental and emotional health (by improving the currently used engineering (safety) technology and alignment inconsistency) should be enhanced rather than excessive controls on the drivers’ work hours by using GPS, work papers and inspections.