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2023 Vol.41, Issue 3 Preview Page

Article

Development of Autonomous Vehicle Critical Situation Scenarios in Urban Areas Based on Kinetic 3D-LiDAR PCD with Triggered Vehicle Detection

3D-LiDAR PCD 및 사고유발차량 분류 기반 자율주행차 도심부 사고 취약 시나리오 개발

Minhee KANG1
,
Saeyan EOM2
,
Keeyeon HWANG3*
강 민희1
,
엄 새얀2
,
황 기연3*
1Ph.D. Candidate, Industrial Convergence Interdepartmental Program, Smartcity, Hongik University, Seoul 04066, Korea
2BE, Department of Urban Design & Planning, Hongik University, Seoul 04066, Korea
3Professor, Department of Urban Design & Planning, Hongik University, Seoul 04066, Korea
1홍익대학교 스마트도시전공 박사수료
2홍익대학교 도시공학과 학사
3홍익대학교 도시공학과 교수
*Corresponding Author
30 June 2023. pp. 353-374
PDF XML Citation
Abstract

The commercialization of Autonomous Vehicle(AV) is rapidly approaching with the technical progress of Advanced Driver Assistance Systems (ADAS). However, ensuring AV safety through a robust framework is crucial, given the escalating safety concern. To address this issue, we propose a scenario-based approach method for AV safety assessment. We generated logical scenarios based on a data-driven approach method using 3D-LiDAR PCD by extracting kinetic features, such as distance, velocity, and acceleration, to complement the lack of a knowledge-based approach. For generating logical scenarios, we detected critical situation-triggered vehicles and identified the importance of kinetic features. As a result, the detection model showed 96% accuracy by DNN model, and location, distance, and velocity were ranked as the top factors by RandomForeast model (RF). Beyond simply presenting scenarios using data and AI, our study is significant in offering practical variables that can be utilized for actual AV safety assessment.

Keywords
3D-LiDAR PCD
artificial intelligence
kinetic value
logical scenario
safety assessment

자율주행시스템의 기술적 진보로 자율주행차 상용화가 가시화되고 있으나, 안전성 이슈가 계속하여 제시되어 이를 보장할 수 있는 체계가 요구된다. 이에 따라 자율주행차 안전성 평가를 위한 시나리오 접근법이 제시되고 있으며, 지식 기반 접근법과 데이터 기반 접근법으로 구분되어 연구되고 있다. 본 연구에서는 지식 기반 접근법의 한계를 보완하고자 데이터 기반 접근법으로 3D-LiDAR PCD를 활용하여 거리, 속도, 가속도 등 운동학적 속성을 추출하여 시나리오를 제시하였다. Logical 시나리오 제시를 위해 사고 유발 객체를 검출하였으며, 사고를 유발시키는 요인의 중요도를 파악하여 logical 시나리오의 제시되어야 하는 변수를 제안하였다.

키워드
3D-LiDAR PCD
인공지능
운동학 변수
Logical scenario
자율주행차 안전성 평가
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Information
  • Publisher :Korean Society of Transportation
  • Publisher(Ko) :대한교통학회
  • Journal Title :Journal of Korean Society of Transportation
  • Journal Title(Ko) :대한교통학회지
  • Volume : 41
  • No :3
  • Pages :353-374
  • Received Date : 2023-04-11
  • Revised Date : 2023-05-19
  • Accepted Date : 2023-06-02
  • DOI :https://doi.org/10.7470/jkst.2023.41.3.353
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