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A validation study comparing performance in a low-fidelity train-driving simulator with actual train driving performance
Swedish National Road and Transport Research Institute, Traffic and road users, Driver and vehicle. Luleå University of Technology (LTU).ORCID iD: 0000-0001-9536-8358
2023 (English)In: Transportation Research Part F: Traffic Psychology and Behaviour, ISSN 1369-8478, E-ISSN 1873-5517, Vol. 97, p. 109-122Article in journal (Refereed) Published
Abstract [en]

Background: Although common in other industries, such as the automotive sector, no train-driving validation study has been found in the existing literature. The present paper intends to fill that gap by comparing the results of train-driving performance in a physically low-fidelity but highly functional simulator with real train-driving performance.

Method: Thirty-four train driver students in the final part of their basic education were assessed in a 45-minute simulator test using the number of driving errors as the performance indicator. The results were compared with the performance at 11 weeks of internship as measured by supervisors grading according to a standard procedure. One of the classes (17 to-be drivers) was affected by restrictions related to COVID-19, which led to a shortened internship and distance learning during parts of the internship. The study also intended to measure the effect of the restrictions and the types of errors the drivers made by comparing the two classes.

Results: A significant correlation was found between the number of driving errors and internship grades, r = −0.45, p <.05. The results also revealed that COVID-19 restrictions negatively affected performance, as the students from Class B made significantly more driving errors and obtained a lower internship grade than those from Class A.

Conclusions: This paper shows that this type of low-fidelity simulator is well suited for measuring real train-driving performance. A measurement method that can predict long-term driving should have implications for both research and practical usability. Researchers can use this for studying the effects of, for example, different training methods, while train operation companies can use the method to test their drivers' skills and intervene before an actual accident occurs.

Place, publisher, year, edition, pages
Elsevier, 2023. Vol. 97, p. 109-122
Keywords [en]
COVID-19, Ecological validity, Low-fidelity simulator, Relative validity, Simulator, Train driver, Automobile drivers, Automotive industry, Distance education, Driver training, Errors, Grading, Students, Vehicle performance, Driving errors, Driving performance, Low fidelities, Performance, Train drivers, Train drivings, Validation study
National Category
Vehicle and Aerospace Engineering
Identifiers
URN: urn:nbn:se:vti:diva-19817DOI: 10.1016/j.trf.2023.07.007ISI: 001060425700001Scopus ID: 2-s2.0-85165082733OAI: oai:DiVA.org:vti-19817DiVA, id: diva2:1785723
Available from: 2023-08-04 Created: 2023-08-04 Last updated: 2025-09-11Bibliographically approved
In thesis
1. Mastering Skills in an Unpredictable World: Simulator Training for Train Drivers
Open this publication in new window or tab >>Mastering Skills in an Unpredictable World: Simulator Training for Train Drivers
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Train drivers play a crucial role in the railway system, with their performance significantly impacting accident rates and punctuality. This is particularly true during abnormal situations, such as signal failures or the presence of people on or near the tracks. In these circumstances, good driver performance enhances overall railway performance, leading to better punctuality, fewer accidents, and a reduction in collisions between trains and other vehicles, animals, or people.

One of the most critical skills for a train driver to minimize errors is situational awareness, a person’s ability to comprehend what is happening in a given situation, which is essential for responding effectively. This skill becomes especially important in abnormal situations. A situationally unaware driver results from either a lack of expertise or failure of expertise. Lack of expertise means that the driver does not possess the necessary knowledge to build an accurate situational model, increasing the risk of misinterpreting a situation. Naturally, novice drivers, lacking experience in many situations, are more prone to making mistakes due to this knowledge gap.

Basic train driver education in Sweden includes around 20 weeks of on-the-job training. However, it is debatable whether this provides enough exposure to various situations for drivers to gain adequate experience. In response to this criticism, a low-fidelity train driving simulator has been introduced in the last decade to complement traditional training. This thesis explores how the simulator can enhance the internship experience and help produce more well-prepared train drivers.

Still, even experienced drivers can misinterpret situations (failures of expertise), often due to distractions from multiple information sources, which may direct their attention away from critical elements. A train driver must process information from outside the train (e.g., signals, marker boards, and other objects) and from within the cab to build an accurate situational model. Modern train cabins feature at least three screens, providing vital information about the train’s condition, energy-efficient driving, and, most importantly, automatic train protection (ATP) systems, which display details like, speed limits and signal status. This complexity increases when drivers simultaneously gather and process information from outside and inside the cab. Consequently, this thesis also examines how in-cab information systems influence driver attention and the possibility of developing accurate situational awareness.

Abstract [sv]

Lokförare är en central del av järnvägssystemet, och deras prestationer påverkar både olycksstatistik och tågens punktlighet. Förarens insats är särskilt avgörande i avvikande situationer, som vid signalfel eller när människor befinner sig på eller nära spåret. I sådana situationer bidrar en bra prestation till bättre järnvägsprestanda, vilket innebär högre punktlighet, färre olyckor och färre kollisioner mellan tåg och andra fordon, djur eller människor.

En avgörande färdighet för lokförare för att minska risken för misstag är situationsmedvetenhet, vilket definieras som en persons förståelse för vad som sker i en given situation. Denna medvetenhet är avgörande för att kunna agera rätt, och är särskilt viktig i avvikande situationer. En bristande situationsmedvetenhet kan bero på antingen bristande kompetens eller ett misslyckande att använda befintlig kompetens. Bristande kompetens innebär att föraren saknar tillräcklig kunskap för att göra en korrekt bedömning av situationen, vilket ökar risken för missförstånd. Noviser, som naturligt saknar erfarenhet av många situationer, riskerar därför att göra misstag på grund av denna brist. Eftersom grundutbildningen för lokförare i Sverige omfattar cirka 20 veckors praktik under produktion är det tveksamt om denna praktik ger tillräckligt många tillfällen att öva på olika situationer och därmed erhålla nödvändig erfarenhet. Under det senaste decenniet har dock en lokförarsimulator introducerats i utbildningen, och denna avhandling undersöker hur simulatorn kan komplettera praktiken.

Även erfarna förare kan dock missbedöma en situation (misslyckande användning av befintlig kompetens), vilket ofta beror på distraktioner från en eller flera informationskällor. För att kunna göra en korrekt situationsbedömning måste en lokförare inhämta och bearbeta information både från omgivningen (exempelvis signaler, skyltar eller andra objekt) och inifrån hytten genom flera informationskällor. I moderna tåghytter får föraren information från minst tre skärmar som visar bland annat tågets status, energieffektiv körning och, viktigast av allt, ett tågskyddssystem som ger information om exempelvis hastighetsbegränsningar och signalers status. Informationsinhämtningen och bearbetningen kan därför vara komplex, särskilt när information måste samlas in från flera källor samtidigt. Den här avhandlingen undersöker därför också hur invändiga informationssystem påverkar lokförarens uppmärksamhet och därmed möjligheten att bygga en korrekt situationsmodell (att vara situationsmedveten).

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2024. p. 250
Series
Doctoral thesis - Luleå University of Technology, ISSN 1402-1544
National Category
Applied Psychology Transport Systems and Logistics
Identifiers
urn:nbn:se:vti:diva-21255 (URN)9789180486460 (ISBN)9789180486477 (ISBN)
Public defence
2024-11-15, A109, Luleå University of Technology, Luleå, 10:00 (Swedish)
Opponent
Supervisors
Available from: 2024-10-25 Created: 2024-10-25 Last updated: 2025-09-11Bibliographically approved

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