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This study aims at the development of a projection pattern that is capable of shortening the time required by a driver to perceive a pedestrian at night when a vehicle’s high beams are utilized. Our approach is based on the spatio-temporal frequency characteristics of human vision. Visual contrast sensitivity is dependent on spatiotemporal frequency, and maximum contrast sensitivity frequency varies depending on environmental luminance. Conventionally, there are several applications that utilize the spatio-temporal frequency characteristics of human vision. For example, the National Television System Committee (NTSC) television format takes into consideration low-sensitivity visual characteristics. In contrast, our approach utilizes high-sensitivity visual characteristics based on the assumption that the higher contrast sensitivity of spatio-temporal frequencies will correlate more effectively with shorter perception times.

We investigated a lighting method that supports pedestrian perception by vehicle drivers. This lighting method makes active use of visual characteristics such as the spatio-temporal frequency of contrast sensitivity. Using reasonable parameter values derived from preliminary experiments using a Campbell-Robson chart, we determined a suitable lighting pattern that improves the driver's pedestrian perception. In order to assess the influence of visual characteristics on a reaction-time-dependent task, such as pedestrian perception in nighttime, tests were performed in the target environment, the results of which validated the proposed method.

Automating the inspection of the piston combustion chamber volume is difficult and prevents establishing an unmanned machining process of the piston in the future. So, we developed an inspection technique which uses a Range Finder, non-contact visual sensor, and calculate the chamber volume by integrating 3D position data. We applied this real-time measurement technique which enables 100 % inspection to our production lines. Then, we developed the “Defect Free Production Line”, which calibrates itself by feeding back the measured volume data to the machining process. Our paper will explain this inspection technique and our “Defect Free Production Line”.