Abstract
The article concerns eye tracking research conducted in order to improve simulators for train drivers’ training, as well as simulator games for railway enthusiasts. The image viewed in the simulator window changes dynamically, but it can be divided into certain sectors that change in a slow and predictable way. We propose a method of analyzing the focus of the driver’s or player’s attention based on these quasi-static sectors. With quasi-static sectors it is possible to identify certain strategies for observing the route. These strategies are similarly used by train drivers or game players both in the case of simulators and in the case of observing the actual train passage. Such an approach can be used to analyze the attention and performance of a driver or player, as well as to assess the realism of a virtual route against a real route. In particular, an important assessment of the relevant graphic elements of the designed virtual route may be made for the developer of the simulator.
Supported by the Polish National Centre for Research & Development (NCBR) within the Smart Growth Operational Programme grant No. POIR.01.01.01-00-0382/20 as a part of the European Regional Development Fund (ERDF).
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Acknowledgements
The presented work was part of the R&D project “Generation of the train routes realistic visualization for the professional railway simulators” (grant No. POIR.01.01.01-00-0382/20). The authors wish to express their appreciation to the CEO and CTO of Simteract SA, Mr. Marcin Jaśkiewicz and Mr. Grzegorz Ociepka for empowering this research to happen. Also the authors would like to thank the company technical team, especially Artur Szymański, Adam Rzepka, Marcin Gomoła, Miłosz Szczygielski for their help in preparing routes for planned experiments. Special thanks to Dominika Gołuńska for preparing and discussing eyetracking data.
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Węgrzyn, P., Kepski, M., Grabska-Gradzińska, I. (2022). Eye Tracking Measurement of Train Drivers’ Attention Based on Quasi-static Areas of Interest. In: Ferrández Vicente, J.M., Álvarez-Sánchez, J.R., de la Paz López, F., Adeli, H. (eds) Bio-inspired Systems and Applications: from Robotics to Ambient Intelligence. IWINAC 2022. Lecture Notes in Computer Science, vol 13259. Springer, Cham. https://doi.org/10.1007/978-3-031-06527-9_1
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