Estimating Driver Unawareness of Pedestrian Based On Visual Behaviors and Driving Behaviors

Minh Tien Phan (1) , Indira Thouvenin (1) , Vincent Fremont (1) , Véronique Cherfaoui (1)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]

Every year, more than 1.24 million people die in traffic accidents around the world, half of which are among pedestrians and cyclists, and 22 percent of which are children (WHO, 2013). Thus, preventing pedestrians from motor accidents is an important problem in achieving a safe and secure society. A lot of research in the advanced driver assistance is able to detect the pedestrian with the in-vehicle sensors and inform the driver of their presence. However, most of these alert systems do not adapt to the driver, they become distracting, annoying the driver and will be often ignored or deactivated. Therefore, taking into account the driver's state and understanding fully the situation are the challenges for these systems. This study is the first step of a project named MINARDA (Mobile and Interactive Augmented Reality for Driving Assistance). This system is strongly connected to the user. It aims to use a suitable visualization metaphor in augmented reality that allows the driver to avoid dangerous situations. Particularly, we focus on the situation in which the pedestrian is in danger.

Mots clés: human-machine interaction; visual behaviors; driver unawareness; pedestrian detection

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Interface homme-machine [cs.HC]; Sciences de l'ingénieur [physics]

Minh Tien Phan, Indira Thouvenin, Vincent Fremont, Véronique Cherfaoui. Estimating Driver Unawareness of Pedestrian Based On Visual Behaviors and Driving Behaviors. International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Jan 2014, Lisbon, Portugal. pp.35-39. ⟨hal-01083909⟩