Designing and trialling a fully implicit data collector for eye- and head-tracking

Recent advancements in computer graphics and human-computer interaction have made it possible to create traffic simulators that contain complex environments for the participants to navigate. These can be used to understand how changes to the environment affect travellers without having to perform the changes in real life. There have also been improvements in how to collect information about what the user is experiencing in these simulators. There is a wide range of variables that could be used to better understand what the user is focusing on, but which of these are giving the most information? This paper aims to compare and uncover what the movements of the head and the eyes can explain regarding where a person is focusing their attention when searching for information. Using a VR HMD with built-in eye-tracking, participants were asked to search for objects in static and dynamic environments. The results showed that eye-tracking had a higher hit rate than the head-tracking, as expected. Information from the head-tracking was found in the eye-tracking to a higher degree than the eye-tracking was found in the head-tracking across all scenarios. In conclusion, eye-tracking shows signs that it is the preferred method for understanding information searching among travellers.