A Study on the Evaluation Method of Autonomous Emergency Vehicle Braking for Pedestrians Test Using Monocular Cameras

Author:

Kim Bong-JuORCID,Lee Seon-Bong

Abstract

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.

Funder

Korea Evaluation Institute of Industrial Technology

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference20 articles.

1. TTAS (Traffic Accident Analysis System) Statistical Report 2019 http://taas.koroad.or.kr/web/bdm/srs/selectStaticalReportsDetail.do

2. Real-world effects of rear automatic braking and other backing assistance systems

3. A Fast Learning Method for Accurate and Robust Lane Detection Using Two-Stage Feature Extraction with YOLO v3

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