Autonomous vehicles could improve mobility, safety, and inclusion in trafc. While this technology seems within reach, its successful introduction depends on the intended user's acceptance. A substantial factor for this acceptance is trust in the autonomous vehicle's capabilities. Visualizing internal information processed by an autonomous vehicle could calibrate this trust by enabling the perception of the vehicle's detection capabilities (and its failures) while only inducing a low cognitive load. Additionally, the simultaneously raised situation awareness could beneft potential take-overs. We report the results of two comparative online studies on visualizing semantic segmentation information for the human user of autonomous vehicles. Efects on trust, cognitive load, and situation awareness were measured using a simulation (N=32) and state-ofthe-art panoptic segmentation on a pre-recorded real-world video (N=41). Results show that the visualization using Augmented Reality increases situation awareness while remaining low cognitive load.
CITATION STYLE
Colley, M., Eder, B., Rixen, J. O., & Rukzio, E. (2021). Efects of semantic segmentation visualization on trust, situation awareness, and cognitive load in highly automated vehicles. In Conference on Human Factors in Computing Systems - Proceedings. Association for Computing Machinery. https://doi.org/10.1145/3411764.3445351
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