• Title/Summary/Keyword: Automated driving license test

Search Result 2, Processing Time 0.016 seconds

Design and Implementation of Automatic Scoring Software to improve the Efficiency of Driving License Test (운전면허시험 효율성 향상을 위한 자동채점 소프트웨어 설계 및 구현에 관한 연구)

  • Kim, Cheol Woo;Yang, Jaesoo;Na, Wonshik
    • The Journal of The Korea Institute of Intelligent Transport Systems
    • /
    • v.16 no.2
    • /
    • pp.180-189
    • /
    • 2017
  • Some people who take a driver's license test retake it again because of license cancellation, but most of them take the test for the first time to drive the car. Driving a car is directly linked to life, and the initial correct driving habits are more important than anything else. In particular, it is very important to obtain a license by evaluating the correct driving ability based on objective and fair standards when learning the first driving, because many people acquire a driving license while entering the society for the first time. In this paper, we propose the S / W design and its main functions that can emit high quality drivers through efficient, fair and accurate automated scoring. Through this, it is proposed to improve the automatic grading driver's license system, to prevent traffic accidents, and to reduce traffic accidents through proper driving.

Toward Real-world Adoption of Autonomous Driving Vehicle on Public Roadways: Human-Centered Performance Evaluation with Safety Critical Scenarios (자율주행 차량의 실도로 주행을 위한 안전 시나리오 기반 인간중심 시스템 성능평가)

  • Yunyoung Kook;Kyongsu Yi
    • Journal of Auto-vehicle Safety Association
    • /
    • v.15 no.2
    • /
    • pp.6-12
    • /
    • 2023
  • For the commercialization and standardization of autonomous vehicles, demand for rigorous safety criteria has been increased over the world. In Korea, the number of extraordinary service permission for automated vehicles has risen since Hyundai Motor Company got its initial license in March 2016. Nevertheless, licensing standards and evaluation factors are still insufficient for operating on public roadways. To assure driving safety, it is significant to verify whether or not the vehicle's decision is similar to human driving. This paper validates the safety of the autonomous vehicle by drawing scenario-based comparisons between manual driving and autonomous driving. In consideration of real traffic situations and safety priority, seven scenarios were chosen and classified into basic and advanced scenarios. All scenarios and safety factors are constructed based on existing ADAS requirements and investigated via a computer simulation and actual experiment. The input data was collected by an experimental vehicle test on the SNU FMTC test track located at Siheung. Then the offline simulation was conducted to verify the output was appropriate and comparable to the manual driving data.