Currently, the stage of technological development for commercialization of autonomous driving level 3 has been achieved. However, the legal and institutional bases and traffic safety facilities for safe driving on actual roads in autonomous driving mode are insufficient. Therefore, in this study, a measurement method using a camera(monocular or dual) was used to evaluate autonomous vehicles. In addition, integrated scenarios was proposed wherein the scenarios proceeded continuously. The precision of the autonomous vehicle safety evaluation method using cameras was verified via comparisons and analyses with the results of real vehicle tests. As a result of the test, the difference in the average error rate of inter-vehicle distance between the monocular camera and the dual camera was 0.34%. The difference in the average error rate of the distance to the lane was 0.3 to 0.5%, showing similar results. It is judged that it will be possible to compensate for each other’s shortcomings if they are used at the same time rather than the independent use of monocular cameras and dual cameras.

Among surrounding information-gathering devices, cameras are the most accessible and widely used in autonomous vehicles. In particular, stereo cameras are employed in academic as well as practical applications. In this study, commonly used webcams are mounted on a vehicle in a dual-camera configuration and used to perform lane detection based on image correction. The height, baseline, and angle were considered as variables for optimizing the mounting positions of the cameras. Then, a theoretical equation was proposed for the measurement of the distance to the object, and it was validated via vehicle tests. The optimal height, baseline, and angle of the mounting position of the dual camera configuration were identified to be 40 cm, 30 cm, and 12°, respectively. These values were utilized to compare the performances of vehicles in stationary and driving states on straight and curved roads, as obtained by vehicle tests and theoretical calculations. The comparison revealed the maximum error rates in the stationary and driving states on a straight road to be 3.54% and 5.35%, respectively, and those on a curved road to be 9.13% and 9.40%, respectively. It was determined that the proposed method is reliable because the error rates were less than 10%.

Traffic accidents continue to increase in Korea as traffic increases, and the resulting loss of life is also on the rise. According to data surveyed by the South Korean National Police Agency, 45,921 pedestrian traffic accidents were reported in 2019, resulting in 1487 deaths and 46,400 injuries. Due to the increased interest in traffic accident safety, the Advanced Driver Assistance System (ADAS) concept is rapidly developing and playing a significant role in coping with activities that are not recognized by the driver. Autonomous Emergency Braking (AEB), a representative ADAS system, is a system that is useful for preventing and mitigating accidents by braking vehicles in emergencies. For the study of AEBs’ safety evaluation methods for pedestrians, a distance measurement method using a monocular camera with excellent accessibility, and measurement equipment required to validate data on the movement of vehicles, and a dummy to replace pedestrians are used. Based on the evaluation scenario considering the proposed Korea road environment, the relative distance obtained from equipment like DGPS and the relative distance using a monocular camera is compared and analyzed to verify safety. Comparative analysis shows that the minimum deviation is 2.3 cm, the third test result of 30 km/h of Car-to-Pedestrian Nearside Child (CPNC), and the maximum deviation is 25 cm, the first test result of 25 km/h of Car-to-Pedestrian Nearside Adult (CPNA). The main factor in error generation is that the lane recognition in the camera image is not accurate, and the perception of small children is slow, which is why emergency braking is considered to have been slow. It is deemed that a safety assessment in weather conditions of adverse conditions will be required in the future.

This study attempts to enhance the formability and electromagnetic properties of Fe-Si-based soft magnetic composites via process parameter optimization. Two silicon compositions (5.0 and 6.5 wt.%) were examined to determine their influence on density, internal stress, microstructure stability, and magnetic properties using a factorial design comprising 96 different condition combinations. A Pearson correlation analysis revealed a negative relationship between Si content and formability, while magnetic permeability increased with higher Si content. The 5.0 wt.% Si samples exhibited superior density (7.42 g/cm³ vs. 7.28 g/cm³), uniform microstructure, and coating stability. Conversely, the 6.5 wt.% Si samples achieved better permeability (126 at 10 kHz) than 5.0 wt.% Si samples but exhibited higher internal stress, uneven compaction, and thicker insulation layers (~400 nm vs. <10 nm). Scanning electron microscopy and transmission electron microscopy analyses identified necking and damage to the insulation layer. X-ray diffraction verified the stability of the Fe_1.6Si_0.4 phase after the forming and annealing processes. Secondary molding temperature exhibited the most significant impact on densification, and annealing generally degraded the quality factor (Q-factor). The highest Q-factor value (7.18 at 10 kHz), indicating lower core loss, was observed in the 5.0 wt.% Si samples without annealing.

Recently, the hot stamping process using local blank heating has been widely used to manufacture lightweight and crashworthy automotive parts. However, the hardness prediction of hot stamped parts produced using local blank heating is difficult because it involves many process variables, such as the heating temperature, heating time, and cooling rate. The purpose of this study was to predict the hardness of hot stamped parts fabricated using local blank heating based on quench factor analysis (QFA). The volume fraction of austenite was measured to consider the phase transformation in the heating stage, and it was expressed by the Johnson–Mehl–Avrami–Kolmogorov (JMAK) equation. Additionally, a dilatometry test was performed to measure the hardness according to the cooling rates, which was used to determine the material constants for QFA. Finite-element simulation was performed to predict the temperature histories during the hot stamping process and the results were used to predict the hardness according to QFA with the JMAK equation. A hot stamping experiment with local blank heating equipment was performed, and the predicted and experimental results were compared for verification of the proposed hardness prediction method.