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Driver Gaze-Aware Adaptive LiDAR Sensing for Advanced Driver Assistance Systems

Conference Paper (2025)
Author(s)

F. Scarí (TU Delft - Human-Robot Interaction)

A. Zgonnikov (TU Delft - Human-Robot Interaction)

C. Quan (TU Delft - Signal Processing Systems)

N.J. Myers (TU Delft - Team Nitin Myers)

Research Group
Human-Robot Interaction
DOI related publication
https://doi.org/10.1109/VTC2025-Spring65109.2025.11174490
More Info
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Publication Year
2025
Language
English
Research Group
Human-Robot Interaction
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/publishing/publisher-deals Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
ISBN (electronic)
979-8-3315-3147-8
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Abstract

Light detection and ranging (LiDAR) plays a crucial role in machine perception for advanced driver assistance systems. Existing LiDARs, however, do not adapt their sensing strategy to complement driver's perception. We demonstrate a novel LiDAR prototype that dynamically adapts its range and resolution over the field of view, according to real-time driver gaze. Our gaze-aware LiDAR emphasizes scanning peripheral zones the driver may overlook, i.e., critical areas during driving. Our demonstration showcases enhanced perception, highlighting the potential of hybrid human-machine sensing for safer driving.

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