The impact of innovative devices in the train cab on train driver workload and distraction

Dutch train drivers have several innovative devices and applications to their disposal when operating trains, such as a tablet or smartphone. These innovations replace out-dated devices and provide opportunities for displaying... [ view full abstract ]

Dutch train drivers have several innovative devices and applications to their disposal when operating trains, such as a tablet or smartphone. These innovations replace out-dated devices and provide opportunities for displaying integrated information, which train drivers can use to optimise their driving strategy.  

The application of these innovations has an impact on train driver workload, and potentially increases the risk of train driver distraction. Currently there is no overall picture of the impact of (the combination of) these devices on the train driver. To create this ‘picture’, the researchers developed a practical applicable method, using the PARRC-model by Parnell et al (2016) and the Multiple Resources model by Wickens (2002).

The PARRC-model identified five key factors (Priority, Adapt, Resource, Regulate, Conflict) of driver distraction, including aspects of workload from the Multiple Resources Model. To assess train driver workload and distraction, each of the five key factors was assessed for the driving task in combination with the application of devices during driving.

First the train driver workload was calculated. Based on task analyses, relevant steps of the driving task were defined. For each of these steps, the ‘baseline’ level of workload was determined, using the Multiple Resources Model. This model was also used to calculate the workload caused by each of the devices. The ‘baseline’ workload combined with the workload caused by devices resulted in the total train driver workload.

Second, potential conflicts between the driving task and application of devices during driving were identified using the conflict matrix by Wickens (2002). This workload and conflict assessment has been performed for different combinations of devices.

Following the analyses of workload and conflict, the other three key factors were assessed for each devices-driving task combination. Based on decision rules, the level of potential distraction using devices during driving was determined.

The current study resulted in a method to assess workload and train driver distraction. This method is applied at the Netherlands Railways to determine the overall level of workload and potential distraction. The application of this method provided useful insights in the level of workload for the driving task. Workload levels were highest when approaching signals, combined with the use of communication devices. This increased the risk of potential distraction during driving. Interestingly, the method also showed that the level of workload and potential of distraction could be decreased for more complex steps in the driving task (i.e. approach of a red signal), when devices are strategically used during driving steps earlier on the route, which require less workload. This gives train drivers the possibility to actively manage workload during driving.

An advantage of this newly developed method is that it can be applied to assess workload and distraction for scenarios with innovations which haven’t been implemented yet. The Netherlands Railways aim to apply this method for future innovations in the train cab.

We’d like this paper to be considered for inclusion in the special edition of Applied Ergonomics.