Distinguishing Driver Intentions in Visual Distractions Kumano, Shiro ; Horiguchi, Kenichi ; Yamaguchi, Daisuke ; Sato, Yoichi ; Suda, Yoshihiro ; Suz, Takahiro
Publication details: Bryssel ITS in daily life: 16th world congress and exhibition on intelligent transport systems and services, Stockholm 21-25 September 2009. Paper, 2009Description: 10 sSubject(s): Bibl.nr: VTI P1835:16 [World]Location: Abstract: The authors of this paper tackle the problem of distinguishing driver intentions in visual distractions to accomplish comfortable human-machine interactions. The discrimination targets are threefold: no visual distractions, i.e., looking directly ahead, and two types of visual distractions that have opposite affects on safety, i.e., checking side blind spots and gazing at non-driving-related objects. The stochastic relationship between driver states and the three types of observations, or the driver's physical actions, artifact operations, and driving situations, is modeled with a Dynamic Bayesian Network. The experiments with a realistic driving simulator demonstrated how effectively of the proposed method enabled these driver states to be recognized.| Current library | Status | |
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| Statens väg- och transportforskningsinstitut | Available |
The authors of this paper tackle the problem of distinguishing driver intentions in visual distractions to accomplish comfortable human-machine interactions. The discrimination targets are threefold: no visual distractions, i.e., looking directly ahead, and two types of visual distractions that have opposite affects on safety, i.e., checking side blind spots and gazing at non-driving-related objects. The stochastic relationship between driver states and the three types of observations, or the driver's physical actions, artifact operations, and driving situations, is modeled with a Dynamic Bayesian Network. The experiments with a realistic driving simulator demonstrated how effectively of the proposed method enabled these driver states to be recognized.