Assessing the impact of driver advisory systems on train driver workload, attention allocation and safety performance

Document Type

Journal Article

Publication Date


Subject Area

place - europe, place - urban, mode - rail, ridership - drivers, planning - safety/accidents


Driver advisory system, Workload, Attention allocation, Train driver performance, Railway safety, Simulator, Eye tracker, Human factors


Netherlands Railways has developed driver advisory systems (DAS) to provide the train driver with route context information and coasting advice in order to benefit punctuality and energy efficiency. However, the impact of these DAS on human factors aspects and safety performance is unclear. The current study assesses the impact of two DAS levels (route context information and coasting advice) on mental workload, attention allocation and safety performance, using eye tracking, a subjective mental workload rating scale (RSME) and simulator data. The overall findings suggest that the application of DAS levels has no negative impact on safety performance and attention allocation towards the trackside compared to a control condition with static timetable information. Furthermore, safety performance benefits significantly from DAS with route context information. DAS were originally developed to benefit punctuality and energy efficiency goals. This study implicates that DAS can also benefit safety performance. The current study found that DAS could decrease workload when the functionalities meet the requirements of the situation. The possible presence of mental underload and its effect on driving performance should be taken into consideration when implementing DAS. It is essential in the development of DAS that it meaningfully enriches the train driving task in stead of simply increasing mental workload.


Permission to publish the abstract has been given by Elsevier, copyright remains with them.


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