In response to the market’s need for luxurious automobile interiors, automotive parts makers are developing various types of crash pads to give drivers a sense of emotional luxury. In particular, a low-cost and high-quality crash pad manufacturing technology is being developed for mid- to low-priced vehicles, namely, the IMG-S (In Mold Grain-pre Stitch) technology. High defect rate of stitching is a critical problem during the manufacture of crash pad using the IMG-S technology. In order to solve this problem, this paper proposes a method of real-time machine vision inspection of stitches on the automotive crash pad. This paper presents the real-time machine vision inspection system configuration, proposes stitch and reference line detection methods, and method for calculating the distance between stitches and the reference line. According to the distance between the stitch and the reference line, the status of the stitch was judged as normal, warning, or erroneous, and the final result was displayed on the user interface. The applicability of the proposed real-time machine vision inspection method was verified by stitching the test line.

In this study, the behavior of the driver was derived by conducting a crash simulation considering automated vehicle accident conditions using autonomous emergency braking (AEB) and a human body model (HBM). Based on car-to-car intersection accident conditions in the OSCCAR project and the actual accident report, a crash accident case was selected. The base crash scenario was reconstructed by conducting a driving simulation with reference to the selected accident cases. Additional simulations applying AEB are performed. Based on the boundary conditions, a car-to-car crash simulation was performed to derive a crash pulse. This crash pulse and HBM were applied to a simple cabin model for conducting driver behavior analysis. The results confirmed that the head behavior of the driver of the opposing vehicle increased in the lateral direction.

An airborne black box should preserve the recorded data under the extreme environmental conditions such an aircraft crash. Through the recorded information from the black box, the cause of the aircraft crash can be analyzed. This requires the black box to safely protect its memory board inside from the external forces or heat generated by the aircraft crash. This paper is a case study conducted to develop the black box to satisfy the crash survival requirements of ED-112A, the standard of performance to develop the black box, and optimize its weight and size. Through the sequential design, analysis, and test process, the black box successfully demonstrated the optimized design, analysis and test subjected to crash survival requirements of ED-112A. The prototype of the black box was fabricated and tested for the verification of each analysis within the requirements of ED-112A.