Effect of Train-Driving Simulator Practice in the European Rail Traffic Management System: An Experimental Study. Issue 5 (May 2023)

• Record Type: Journal Article
• Authors: Olsson, Niklas; Lidestam, Björn; Thorslund, Birgitta
• Is Part Of: Transportation research record. Volume 2677:Issue 5(2023)
• Page Start: 694
• Page End: 706
• Publication Date: 2023-05
• Subjects: human factors -- passenger rail transportation -- rail -- rail safety -- railroad simulators -- train; Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/03611981221135802
• Languages: English
• ISSNs: 0361-1981

Abstract

Many European train drivers face major changes in their work with the introduction of the new train-protection system, the European Rail Traffic Management System (ERTMS), as information retrieval shifts from outside to in-cab, and a new rulebook is introduced. Therefore, many train drivers have to be educated in a short time, to make the transition safe and efficient. The purpose was to find out how a successful ERTMS practice can be designed in a physically low-fidelity but highly functional train-driving simulator. An experimental design was used, with 16 drivers divided into two groups: one group practiced in a simulator, and the other in reality. Standard training methodology was used, and the learning outcome was assessed by both measuring driving errors and via instructor evaluation of a simulator test. The drivers also filled in a questionnaire to capture how different factors, such as repeated practice, experience, and self-estimated confidence, correlate with performance. Results show that the simulator group committed significantly fewer driving errors and received significantly higher scores from the instructor. In addition, the simulator group's better performance is mostly caused by the possibility of repeated training of different special cases. The findings also imply that several of the more common special cases on the ERTMS can hardly be provoked in real train driving. Furthermore, this work strengthens the theory that novices can hardly estimate their own ability. Therefore, we argue that this type of low-fidelity simulator is well suited for research purposes, for practicing special cases, and for train operation companies to assess drivers' skills.