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Linking gaze tracking with a simulated world
Swedish National Road and Transport Research Institute, Traffic and road users, Driving Simulation and Visualization.
Swedish National Road and Transport Research Institute, Traffic and road users, Human Factors in the Transport System.ORCID iD: 0000-0003-4134-0303
2017 (English)Report (Other academic)
Abstract [en]

The main focus of this study was to develop a software able to link eye tracking data to simulator data, making it possible to automatically detect what the driver is looking at in the simulated world. This was achieved by merging data from a SmartEye system with data from the simulator. Thereby realtime visualisation of where the driver is looking is facilitated, and what the driver is targeting can be shown to the test leader to trigger events in the scenarios, etc. This also facilitates automatic gaze annotations that can be used in subsequent analyses when studying visual behaviour.

The developed software, VIMSI, is responsible for collecting eye tracking data from SmartEye, filter and aggregate this data with data from the simulation and then send processed data to the graphics to visualize the result. The software was tested in one of VTI’s driving simulators. This initial testing of VIMSI showed that the software is capable of visualising what the driver is looking at in real time. The software also makes it possible to log data from the test drives which can be useful when studying driver behaviour. To improve the functionality of VIMSI, it is necessary to consider using UDP instead of IPC when directing data from the VIMSI software to the graphics engine VISIR. This will enable the use of another software, ScenarioReplay, developed at VTI for replaying test drives. A proper configuration and calibration of the SmartEye cameras is necessary to achieve high quality of the data from the SmartEye Pro software, which is a precondition for VIMSI.

Place, publisher, year, edition, pages
Linköping: ViP - Virtual Prototyping and Assessment by Simulation , 2017. , p. 23
Series
ViP PM ; 2017-1
Identifiers
URN: urn:nbn:se:vti:diva-12730OAI: oai:DiVA.org:vti-12730DiVA, id: diva2:1171017
Available from: 2018-01-05 Created: 2018-01-05 Last updated: 2018-01-05Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • nn-NB
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Output format
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