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The effects of food and drink intake to driving performance: a systematic review

Sutalaksana Iftikar Zahedi, Pratama Gradiyan Budi, Yamin Putra Alif Ramdhani, Soetisna Herman Rahadian

Transport Problems

2019

T. 14, z. 1

5--12

Human-related factors are considered to be the main cause of traffic incidents or accidents, causing 69.70% of the incidents. Several studies have been conducted to identify the relationship between drowsiness or fatigue and driving performance. Furthermore, a number of other studies not only discussed the symptoms causing drowsiness but also tried to investigate related factors that cause sleepiness or fatigue while driving. On the other hand, some discussed the quantity and quality of sleep as well as food and drink intake before and while driving. This systematic review, which is based on the PRISMA method, aims to map previous studies that investigated the effect of different food/drink consumption, either taken prior to driving or while driving, on the on-road driving characteristics of drivers. Furthermore, this article is expected to serve as a reference for further research that could potentially contribute to minimizing driving errors that lead to incident or accident. From 1871 articles screened, 7 studies related to food/drink intake and driving performance were reviewed. On the basis of the existing studies, no real evidence showing the presence of the association between food intake and the monotony of the road to decrease the driving performance has been found; therefore, further research is needed.

Cognitive Failures, Driving Errors and Driving Accidents

Allahyari T., Saraji G. N., Adl J., Hosseini M., Iravani M., Younesian M., Kass S. J.

International Journal of Occupational Safety and Ergonomics

2008

Vol. 14, No. 2

149--158

Introduction. The impact of a driver’s cognitive capability on traffic safety has not been adequately studied. This study examined the relationship between cognitive failures, driving errors and accident data. Method. Professional drivers from Iran (160 males, ages 18–65) participated in this study. The cognitive failures questionnaire (CFQ) and the driver error questionnaire were administered. The participants were also asked other questions about personal driving information. A principal component analysis with varimax rotation was performed to determine the factor structure of the CFQ. Poisson regression models were developed to predict driving errors and accidents from total CFQ scores and the extracted factors. Results. Total CFQ scores were associated with driving error rates, but not with accidents. However, the 2 extracted factors suggested an increased effect on accidents and were strongly associated with driving errors. Discussion. Although the CFQ was not able to predict driving accidents, it could be used to identify drivers susceptible to driving errors. Further development of a driving-oriented cognitive failure scale is recommended to help identify error prone drivers. Such a scale may be beneficial to licensing authorities or for developing driver selection and training procedures for organizations.