Abstract
Characterisation of the driver’s non-driving activities (NDAs) is of great importance to the design of the take-over control strategy in Level 3 automation. Gaze estimation is a typical approach to monitor the driver’s behaviour since the eye gaze is normally engaged with the human activities. However, current eye gaze tracking techniques are either costly or intrusive which limits their applicability in vehicles. This paper proposes a low-cost and non-intrusive dual-cameras based gaze mapping system that visualises the driver’s gaze using a heat map. The challenges introduced by complex head movement during NDAs and camera distortion are addressed by proposing a nonlinear polynomial model to establish the relationship between the face features and eye gaze on the simulated driver’s view. The Root Mean Square Error of this system in the in-vehicle experiment for the X and Y direction is 7.80±5.99 pixel and 4.64±3.47 pixel respectively with the image resolution of $1440 \times 1080$ pixels. This system is successfully demonstrated to evaluate three NDAs with visual attention. This technique, acting as a generic tool to monitor driver’s visual attention, will have wide applications on NDA characterisation for intelligent design of take over strategy and driving environment awareness for current and future automated vehicles.
Highlights
I N RECENT years, the exciting developments of highly automated driving (HAD) vehicle have been made in the field of both academic research and industrial manufacturing [1]
At present legislation does not allow drivers in a Level 3 autonomous vehicle to engage in non-driving activities (NDAs), HAD may in the future allow drivers to more freely engage in NDAs during much of the time while the automated
Considering the NDA as a dynamical process, this study focuses on the eye gaze on a certain time window and a form of heat map is proposed for visualisation
Summary
I N RECENT years, the exciting developments of highly automated driving (HAD) vehicle have been made in the field of both academic research and industrial manufacturing [1]. According to SAE (J3016) Automation Levels, all the dynamic driving tasks can be achieved by the automated driving system, but drivers are expected to response appropriately when the intervene is requested by vehicle in Level 3 [2]. At present legislation does not allow drivers in a Level 3 autonomous vehicle to engage in non-driving activities (NDAs), HAD may in the future allow drivers to more freely engage in NDAs during much of the time while the automated. Manuscript received April 17, 2019; revised July 5, 2019; accepted August 28, 2019. The Associate Editor for this article was L.
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