Errors in bridge/lock operations can have fatal consequences, which means adequate situation awareness (SA) is crucial during operators’ inspection process. Although operators from Rijkswaterstaat are well-trained and use carefully designed systems, accident reports revealed that SA is not always sufficient. Rijkswaterstaat considers smart cameras to support operators during their inspection process. Smart cameras have high detection rates, but they are not yet able to detect all relevant circumstances. This study therefore investigates whether reliable but partially inaccurate smart cameras enhance operators’ SA. Performance, eye movements and subjective SA were measured during an experiment. Results indicate that the applied (simulated) signals enhanced operators’ performance, which suggests SA was higher when assisted by smart cameras. Dwell time and time to first fixation revealed that signals were effective in gaining operators’ attention, and operators still actively searched for road users without awaiting signals. Subjective SA was not different when smart cameras were used.
EndsleyM. R. (2000). Direct measurement of situation awareness: Validity and use of SAGAT. In EndsleyM. R.GarlandD. J. (Eds.), Situation awareness analysis and measurement (pp. 147-173). Mahwah, NJ, US: Lawrence Erlbaum Associates Publishers.
5.
EndsleyM. R.GarlandD. J. (2000). Situation awareness analysis and measurement. Mahwah, NJ: Lawrence Erlbaum Associates
6.
HasanzadehS.EsmaeiliB.DoddM. D. (2016). Measuring construction workers’ real-time situation awareness using mobile eye-tracking. Proceedings of the 2016 Construction Research Congress (pp. 2894-2904). https://doi.org/10.1061/9780784479827.288
7.
HaulandG. (2008). Measuring individual and team situation awareness during planning tasks in training of en route air traffic control. The International Journal of Aviation Psychology, 18(3), 290-304. https://doi.org/10.1080/10508410802168333
MooreK.GugertyL. (2010). Development of a novel measure of situation awareness: The case for eye movement analysis. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 54(19), 1650-1654. https://doi.org/10.1177/154193121005401961
12.
RamachandranK. M.TsokosC. P. (2009). Sampling distributions. In RamachandranK.M.TsokosC.P. (Eds.), Mathematic statistics with applications (pp. 183-224). Elsevier.
TaylorR. M. (1990). Situational Awareness Rating Technique (SART): The development of a tool for aircrew systems design. Proceedings of the AGARD AMP Symposium on Situational Awareness in Aerospace Operations, CP478: Seuilly-sur Seine: NATO AGARD.
20.
Van de MerweK.Van DijkH.ZonR. (2012). Eye movements as an indicator of situation awareness in a flight simulator experiment. The International Journal of Aviation Psychology, 22(1), 78-95. https://www.doi.org/10.1080/10508414.2012.635129
21.
Van DoornE. C. (2018). Information engineering for supporting situation awareness of nautical traffic management operators (Doctoral dissertation, Delft University of Technology, Delft, the Netherlands). https://doi.org/10.4233/uuid:f8cb0602-d19d-48ac-bc5a-46e3c48ea4c1
22.
WickensC. D.DixonS. R. (2007). The benefits of imperfect diagnostic automation: A synthesis of the literature. Theoretical Issues in Ergonomics Science, 8(3), 201-212. https://www.doi.org/10.1080/14639220500370105
23.
WickensC. D.GordonS. E.LiuY. (2004). An introduction to human factors engineering. Upper Saddle River, N.J: Pearson Prentice Hall.
