Comparing different types of the track side view in high speed train driving

The introduction of high speed trains featuring an increasing number of automated components raises imperative questions concerning the future tasks and the general role of the train driver. Previous work showed that train protection systems provoke train drivers to relocate their visual attention from the track side towards the displays within the cabin. The introduction of high speed routes allowing automatic train operation (ATO) has major implications that question the importance of the track side view for the train driver: (1) all relevant driving parameters are displayed within the cabin in high speed railway operations. (2) Supervisory tasks based on in-cab display information shift into the train driver´s focus. This study investigated the influence of three differently sized track side views (real size, monitor size, none) on a) the allocation of visual attention towards displays and the track, measured by Eye-Tracking parameters and b) the situation awareness of the train driver supervising a high speed train featuring ATO measured with the SPAM method. Empirical data are presented for both research questions. The implications are discussed in order to identify how the delivery of relevant information in the context of the changing train driver’s task can be facilitated

Railway Simulators at the German Aerospace Center - Testing, Research and Development

The presentation includes an overview of the existing rail simulation technology at the Institute for Transportation Systems of the DLR. In Addition, current projects making use of this infrastructure as well as a future Outlook are provided

Is the driver´s traditional outside view still necessary to ensure situation awareness in high speed/ automated train operation?

When considering the introduction of high speeds (up to 400 kilometres per hour), ECTS level 3 control and protection mechanisms and automatic train operation (ATO) functionality to long distance passenger train operation, general questions concerning the role of the train driver are central. More specifically, the attentional focus of the driver will be required to remain on the displays in the cabin. Reasons for this change of attentional focus include the fact that the driver´s ability to clearly perceive the track ahead may decrease due to speed and that the yet perceived outside information will become less relevant as an indicator for future behaviour, because of the sluggish reaction of the train to driver input. Additionally, ETCS in cabin signalling and ATO functionality redirect the drivers attentional resources towards the monitoring of Information provided within the cabin rather than outside. Based on a task analysis that determined the allocation of task between train driver and technical ATO components, we plan to investigate the main research question whether minimized outside view and ATO functionality interfere with the train driver`s situation awareness and driving performance. Therefore a high fidelity simulator study is set out within the facilities of the German Aerospace Centre (DLR e.V.). There we are working on collecting subjective, objective, and physiological measures from train drivers (n= approx. 30) in an two and a half hours lasting experimental setting, to assess the effects of minimized outside view and ATO functionality on the driver´s situation awareness, performance, fatigue and workload. Measures will include SPAM, gaze-pattern analysis through eye tracking, pupillometry, NASA-TLX, and Stanford Sleepiness Scale. Results will be provided as soon as they are available

Enabling automatic train operation through human problem solving

In future rail operations, the introduction of automatic train operations on main lines will be accompanied by questions concerning the role of the train driver in delivering a safe and punctual service every day. In this article, we advocate the symbiosis of automatic train operation and human decision-making in order to ensure the safety and efficiency of the service in an automated railway future. Increasing the amount of rolling stock on the tracks by means of automatic train operation while relying on unique human judgement and perception to maintain operations may bring together the best of both worlds

Determining the allocation of tasks in automated high speed train driving

Adhering to the increasing demands in terms of numbers of passengers, travel time, energy efficiency and optimal exploitation of infrastructure, from an operational point of view future high speed trains are in need to evolve towards higher grades of automation (GoA). Nowadays higher grades of automation (GoA2 and beyond) are mainly found in subway systems or other specialized systems that basically provide a closed system environment. Introducing higher grades of automation into high speed train operation covering long distances above ground poses significant challenges to safe and secure operation. The train driver has always played a major role in railway safety, but he is increasingly assisted by technical components. Introducing higher grades of automation to high speed train operation is seen as a step further along the path of pairing up technological assistance and human performance to reach a maximal level of safety. The role of the train driver within a highly automated system needs to be considered in detail in order to provide clarification what tasks the future train driver is able and needs to execute reliably to ensure the required level of operational safety. To this end a series of studies is set into place at the German Aerospace Center e.V. (DLR) embarking with semi-structured expert interviews, later involving scenarios being tested in a high fidelity simulator and finally participatory design approaches being applied to prototype potential cabin design measures based on empirical research. The current paper describes the first step taken in this current line of research. Based on an interview guideline covering 29 questions, two hour semi structured interviews with five high speed train drivers and trainers touched upon the current state and possible future development of in cab signaling, informational sources, and function allocation in two scenarios. One scenario included a braking procedure in a regular operational environment. The other scenario was concerned with system failure and measures to restore safe operation. The possible future development of the tasks and means were based on certain parameters (GoA 2, an operating speed of 400 km/h, the moving block logic, and a reduced outside view). Additionally, the experts indicated their view on future task allocation for ten specific tasks provided on a continuous dimension ranging from train driver to technical assistance. From this, a classification of the ten specific tasks regarding the function allocation between human and machine was generated. Based on this classification and an earlier developed HTA (Hierarchical Task Analysis) of the current tasks of a high speed train driver, the results of the interviews were integrated into a comprehensive set of future tasks. This set of future tasks will be thoroughly discussed in the paper. Additionally, the interviews gave first hints where technical assistance in the cabin needs to be implemented to ensure safe operation, e.g. in terms of a technically enhanced preview of the route ahead

Effects of Expertise for Automatic Train Operations

We aimed at investigating the effects of automatic speed control and expertise on train driver performance in unexpected, non-routine situations in the railway domain. Research from other domains suggested increasing levels of automation to exert detrimental effects on non- routine performance. In addition, research about the role of expertise in different levels of railway automation is scarce. We assessed the reaction times of 26 train drivers to critical non-routine events in a high fidelity railway simulator featuring manual and automatic speed control. We reported longer reaction times to non-routine situations under automatic speed control. Based on occupational experience data we found more experienced train drivers to adapt their reliance on automation more accurately to the automation reliability level resulting in an interaction trend in terms of non- routine performance. These results highlight performance consequences of automatic speed control in railway operations and offer insights on how existing expertise needs to be taken into account when introducing automatic speed control into the railway domain

Automation in Railway Operations: Effects on Signaller and Train Driver Workload

Throughout the railway domain, increasing levels of automation are employed to ensure safety and increase efficiency on the tracks. This impacts the task characteristics of the signaller and train driver. In a scenario of German railway automation, an automated interlocking system routes trains automatically and trains equipped with “ATO over ETCS” (“Automatic Train Operation over the European Train Control System”) automatically drive along the predefined routes adhering to speed restrictions. Thus, the task load of signallers and train drivers decreases, as manual inputs decline in favour of monitoring the functioning of automatic systems. Yet, it remains unclear whether decreasing task load directly lowers subjective workload. Additionally, the question of optimal workload levels has yet to be addressed. In order to ensure optimal performance, under- and overload are to be avoided. In previous studies on workload in railway operations, workload was assessed without considering an individual optimum of workload. In the simulator studies described in the paper, subjective workload was assessed with the goal of analysing the impact of automation on achieving an optimal workload level. In two separate studies with train drivers and signallers, subjective workload was assessed by two self-report measures (NASA-TLX and DLR-WAT) after participants completed periods of manual driving and driving with automated systems. Results consistently indicate lower subjective workload in the automated work settings for both signallers and train drivers. Interestingly, signaller workload was close to optimal subjective levels while train driver workload scores were considerably lower than optimal. This highlights the need for thoughtful introduction of automation into the train driver environment. Furthermore, the DLR-WAT differentiates between mental workload caused by the different stages of information processing. In train drivers and signallers, workload stemming from information perception seems to be more pronounced than workload stemming from mental operations occurring at later stages of information processing, especially in automatic work settings. Assessing workload relative to an individual optimum and differentiating causes of mental workload along the different stages of information processing offers unique insights into signaller and train driver workload. The results make it possible to ascertain, which specific aspects of the introduction of automation in the signaller and train driver tasks lead to lowered overall workload

Die Entwicklung der Aufgaben des Triebfahrzeugführers in der Zukunft

Basierend auf inhaltlichen Überlegungen aus dem Projekt „Next Generation Train“ des Deutschen Zentrums für Luft- und Raumfahrt e.V. (DLR) wird in diesem Artikel der Frage nachgegangen, ob sich die zukünftigen Aufgaben des Triebfahrzeugführers von den aktuellen unterscheiden werden und wie eine effiziente Arbeitsteilung zwischen Mensch und Maschine im Führerstand aussehen kann. Treiber der neuartigen Aufgabeninhalte- und Verteilung werden ebenso benannt wie aus den Entwicklungen resultierende Fragestellungen für weiterführende Forschung

Countering Train Driver Fatigue in Automatic Train Operation

Extensive levels of train driver fatigue are associated with impaired performance. Increasing automation is expected to result in more driver fatigue. We assessed physiological and subjective fatigue in 26 train drivers in manual and automated driving mode in a two hour simulator study. Results show a significant progression of fatigue over time across measures, but do not reveal automation effects on fatigue. The results, possible conclusions, and a driver- centered approach to Automatic Train Operation (ATO) are discussed

Der Train Operator - Situative Fernsteuerung von automatisierten Zügen

Die Abteilung Human Factors des Instituts für Verkehrssystemtechnik des Deutschen Zentrums für Luft- und Raumfahrt e. V. (DLR) erforscht u. a. die Rolle des Menschen vor dem Hintergrund fortschreitender Automatisierung im Bahnbetrieb. Ziel der Human Factors Arbeiten im Projekt Next Generation Train 3 ist es, eine optimale Verteilung der Aufgaben zwischen Mensch und Triebfahrzeug zu erwirken, die als Voraussetzung einen sicheren und effizienten Bahnbetrieb ermöglicht und die die menschliche Leistungsfähigkeit optimiert. Damit kann einerseits mit zunehmender Automatisierung im Regelbetrieb die Effizienz des Bahnsystems erhöht und andererseits stark ausgeprägte Fähigkeiten des Menschen in der Situationsbeurteilung und Entscheidungsfindung genutzt werden, um den Betrieb in Störfällen aufrechtzuerhalten