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Article Dans Une Revue International Journal of Human-Computer Interaction Année : 2020

Adaptive Visual Assistance System for Enhancing the Driver Awareness of Pedestrians

Résumé

In the past decade, Pedestrian Collision Warning Systems have been proposed to detect pedestrians and warn drivers of imminent collision. However, such systems are often limited by eye-off-road and cognitive overload problems. Head Up displays with augmented reality are being considered as a key technology for changing drivers' user experiences. In this paper, we propose a new visual assistance system that can enhance drivers' perception by dynamically directing attention to pedestrians to avoid collisions using Augmented Reality cues. The proposed system takes into account driver behaviors through vehicle driving signals analysis, in order to warn it at the right moments. To that end, we statistically model correct and incorrect driver behaviors in situations with pedestrians. Based on this model, a warning visual metaphor is displayed if unawareness is detected and a driving simulator was used to evaluate the concept. The experimental results suggest that our proposed adaptive visual aids can enhance driver awareness of pedestrians in critical situations.
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Dates et versions

hal-02399904 , version 1 (09-12-2019)

Identifiants

Citer

Vincent Frémont, Minh-Tien Phan, Indira Thouvenin. Adaptive Visual Assistance System for Enhancing the Driver Awareness of Pedestrians. International Journal of Human-Computer Interaction, 2020, 36 (9), pp.856-869. ⟨10.1080/10447318.2019.1698220⟩. ⟨hal-02399904⟩
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