Citation

Roets B, Christiaens J. J. Transp. Saf. Secur. 2019; 11(2): 207-224.

Copyright

(Copyright © 2019, Southeastern Transportation Center, and Beijing Jiaotong University, Publisher Informa - Taylor and Francis Group)

DOI

10.1080/19439962.2017.1376022

PMID

unavailable

Abstract

Fatigue is a major contributor to transportation accidents. Shift workers are particularly prone to fatigue, and organizations increasingly rely on fatigue risk models to evaluate work schedules. In this article, the authors empirically examine the relationship between fatigue risk and human errors in railway traffic control. Despite their safety-critical role, research on railway traffic controller fatigue has remained limited. The authors evaluate the predictive validity of a commonly used fatigue risk tool (the Risk Index) and investigate the effect of additional risk factors (age, gender, part-time work, and day of week). In close cooperation with Belgian railways, the authors analyze a unique full-year data set, containing more than 11,000 work shifts. By adopting a Tobit regression for censored data, the authors account for work shifts with zero error occurrence.

RESULTS validate the applied fatigue risk model under real-world circumstances and reveal risk predictors above and beyond shift schedule design: significant day-of-week effects are observed. The probability of making at least one error is highest on Saturdays (+6% compared to Mondays), and lowest on Tuesdays, Wednesdays, and Thursdays. Thus, results suggest that safe work schedule design should also take into account the day of the week and not exclusively rely on fatigue risk scores.

Language: en

Keywords

day-of-week; fatigue; human factor; railway; Tobit; traffic control