## 1 Introduction  
As the volume of domestic traffic increases, traffic accidents continue to increase, leading to increased casualties. According to data surveyed in 2019 by the Korea National Police Agency, the death rate due to traffic accidents has been decreasing every year as of 1991, but the number of injuries continues to increase. A total of 45,921 pedestrian traffic accidents were reported in 2019, with 1487 deaths and 46,400 injuries. Among them, children under the age of 13 were very vulnerable to traffic accidents, with 34 deaths, and 12,543 injuries [1]. Safety concerns are also increasing due to traffic accidents. As a way to solve this problem, the Advanced Driver Assistance System (ADAS) concept, which helps vehicles prevent or mitigate accidents and reduces drivers' fatigue by responding to incidents that the driver does not recognize, is developing rapidly and at the same time playing an important role. A typical ADAS function is the Autonomous Emergency Braking (AEB) system that performs braking in an emergency. By using car-sensing devices (radars, cameras, and sensors), the AEB system can recognize the surrounding driving environment [2; 3]. This system operates when the preceding vehicle suddenly brakes due to an accident, or when there is an object that is suddenly entering the driveway of the vehicle in the road. The AEB system can effectively improve the driving safety of vehicles, reduce the occurrence of collision traffic accidents [4], and the working intensity of drivers. For that reason, it is evaluated as a useful system for preventing and mitigating accidents [5]. After looking at the research trends of ADAS tests and pedestrian AEB, [PERSON] et al. [6] proceeded with the design and simulation of a vehicle test bed based on intelligent transport systems (ITS). The ITS- based intelligent vehicle test bed was constructed to meet the growing demand for test and verification for ADAS and ITS systems. This test bed is carefully designed to meet the requirements of the International Organization for Standardization (ISO)/Technical Committee (TC)204 standards. [PERSON] et al. [7] presented a driver study on longitudinal active collision avoidance of the AEB-P system. The lower-layer controller of the Autonomous Emergency Braking-Pedestrian (AEB-P) system was designed based on the Proportional Integral Derivative (PID) controller theory, which realizes the conversion of the expected speed reduction to the pressure of a vehicle braking pipeline. The relevant pedestrian test scenarios were set up based on the China-New Car Assessment Program (C-NCAP) test standards. The CarSim and Simulink co-simulation model of the AEB-P system was established, and a multi-condition simulation analysis was performed. [PERSON] et al. [8] studied typical pedestrian accident scenarios for the development of autonomous emergency braking test protocols. This paper aimed to contribute to the development of relevant test conditions by describing pedestrian accidents' typical circumstances. Cluster analysis was applied to two large British databases, and both highlighted an urban scenario in daylight and fine weather where a small pedestrian walks across the road, especially from the near curb, in clear view of a driver who is traveling straight ahead. For each dataset, the main test configuration was defined to represent the conditions of the most common accident scenario along with test variations to reflect the characteristics of less common accident scenarios. [PERSON] et al. [9] studied issues and challenges for pedestrian active safety systems based on real world accidents. The purpose of this study was to analyze real crashes involving pedestrians in order to evaluate the potential effectiveness of AEB in pedestrian protection. These were assessed to determine their impact on pedestrian safety. The influence of the detection and the activation of the AEB system were explored by varying the field of view (FOV) of the sensor and the level of deceleration.