Look at Me: Augmented Reality Pedestrian Warning System Using an In-Vehicle Volumetric Head Up Display
Current pedestrian collision warning systems use either auditory alarms or visual symbols to inform drivers. These traditional approaches cannot tell the driver where the detected pedestrians are located, which is critical for the driver to respond appropriately. To address this problem, we introduce a new driver interface taking advantage of a volumetric head-up display (HUD). In our experimental user study, sixteen participants drove a test vehicle in a parking lot while braking for crossing pedestrians using different interface designs on the HUD. Our results showed that spatial information provided by conformal graphics on the HUD resulted in not only better driver performance but also smoother braking behavior as compared to the baseline.
Recently, a lot of mobile devices spread rapidly. However, an issue of the battery of the mobile device appeared because the capacity of the battery limits usage time of the mobile device. Therefore, some mobile devices are installed with photovoltaic modules but the photovoltaic module is easily breakdown. Because consumers want to know the breakdown, the diagnostic method focused on mobile device is needed. In this paper, a fault diagnostic method of photovoltaic modules on mobile device is implemented and the algorithm is proposed. The proposed method has high accuracy for diagnostic photovoltaic.