DOI QR코드

DOI QR Code

Autonomous Vehicle Situation Information Notification System

자율주행차량 상황 정보 알림 시스템

  • Jinwoo Kim (Autonomous Driving Intelligence Research Section, ETRI) ;
  • Kitae Kim (Autonomous Driving Intelligence Research Section, ETRI) ;
  • Kyoung-Wook Min (Autonomous Driving Intelligence Research Section, ETRI) ;
  • Jeong Dan Choi (Intelligent Robotics Research Division, ETRI)
  • 김진우 (한국전자통신연구원 자율주행지능연구실) ;
  • 김기태 (한국전자통신연구원 자율주행지능연구실) ;
  • 민경욱 (한국전자통신연구원 자율주행지능연구실 ) ;
  • 최정단 (한국전자통신연구원 지능로보틱스연구본부)
  • Received : 2023.09.27
  • Accepted : 2023.10.24
  • Published : 2023.10.31

Abstract

As the technology and level of autonomous vehicles advance and they drive in more diverse road environments, an intuitive and efficient interaction system is needed to resolve and respond to the situations the vehicle faces. The development of driving technology from the perspective of autonomous driving has the ultimate goal of responding to situations involving humans or more. In particular, in complex road environments where mutual concessions must be made, the role of a system that can respond flexibly through efficient communication methods to understand each other's situation between vehicles or between pedestrians and vehicles is important. In order to resolve the status of the vehicle or the situation being faced, the provision and method of information must be intuitive and the efficient operation of an autonomous vehicle through interaction with intention is required. In this paper, we explain the vehicle structure and functions that can display information about the situation in which the autonomous vehicle driving in a living lab can drive stably and efficiently in a diverse and complex environment.

자율주행차량의 기술과 수준이 발전하고 보다 다양한 도로 환경에서 주행함에 따라 차량이 직면한 상황을 해결하고 대응하기 위한 직관적이고 효율적인 상호작용 시스템이 필요하다. 자율주행의 관점에서의 주행 기술 개발은 사람 혹은 그 이상의 상황을 대응하기 위한 궁극적인 목표를 가지고 있다. 특히, 복잡하고 상호 양보해야 하는 도로환경에서는 차량 간 혹은 보행자와 차량 간의 서로의 상황을 이해할 수 있는 효율적인 의사소통에 대한 방법을 통해 유연한 대처가 가능한 시스템의 역할이 중요하다. 차량의 상태 혹은 직면한 상황을 해결하기 위해서는 정보의 제공과 방법이 직관적이고 의도에 대한 상호 작용을 통해 효율적인 자율주행 차량을 운영해야 한다. 본 논문에서는 리빙랩에 주행하는 자율주행차량이 다양하고 복잡한 환경에서 안정적이고 효율적인 주행을 하기 위해 차량이 처한 상황에 대한 정보를 표출할 수 있는 차량 구조와 그 기능을 설명한다.

Keywords

Acknowledgement

본 논문은 국토교통부와 국토교통과학기술진흥원의 지원(RS-2021-KA160548)으로 수행하였습니다.

References

  1. CNBN, https://www.cnbc.com/2023/04/25/cruise-robotaxis-now-run-24-7-in-san-francisco-public-access-at-night.html, 2023.04.25.
  2. Fengjiao, Z., Jennifer, O., Weimin, J., Patrick, G., Daniel, P. and Andrew, R.(2023), "Pedestrian Behavior Interacting with Autonomous Vehicles-Role of AV Operation and Signal Indication and Roadway Infrastructure", 2023 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops(VRW), pp.821-822. doi: 10.1109/VRW58643.2023.00253
  3. Ha, J., Jeung, Y. and Choi, J.(2023), "Analysis of Priority in the Robotaxi Design Elements: Focusing on Application of AHP Methodology", The Korea Institute of Intelligent Transport Systems, vol. 22, no. 4, pp.180-193. https://doi.org/10.12815/kits.2023.22.4.179
  4. JALOPNIK, https://jalopnik.com/california-votes-to-expand-robotaxi-service-to-24-hours-11850728951, 2023.08.11.
  5. Kim, H., Lim, K., Kim, J. and Son, W.(2020), "Operational Design Domain for Testing of Autonomous Shuttle on Arterial Road", The Korea Institute of Intelligent Transport Systems, vol. 19, no. 2, pp.135-148. https://doi.org/10.12815/kits.2020.19.2.135
  6. Riener, A., Jeon, M. and Alvarez, I.(2022), "User Experience Design in the Era of Automated Driving", Studies in Computational Intelligence, vol. 980, pp.207-236, pp.1860-9503. https://doi.org/10.1007/978-3-030-77726-5
  7. Sheen, British Standards Institution(BSI)(2020), PAS 1883:2020, Operational Design Domain(ODD) taxonomy for an automated driving system (ADS)-Specification.
  8. Society of Automotive Engineers(SAE)(2020), SAE J3216, Surface Vehicle Information Report:(R) Taxonomy and Definitions for Terms Related to Cooperative Driving Automation for On-Road Motor Vehicles.
  9. WAYMO, https://waymo.com/blog/2023/09/waymo-one-tour-LA.html, 2023.09.20.
  10. Yinshuai, Z., Chun, Y. and Yuanchu, S.(2018), "Designing Autonomous Driving HMI System: Interaction Need Insight and Design Tool Study", HCI International 2018, vol. 852, pp.433-426.
  11. Zhu, Z. and Zhao, H.(2023), "Learning Autonomous Control Policy for Intersection Navigation With Pedestrian Interaction", IEEE Transactions on Intelligent Vehicles, vol. 8, pp.3270-3284. https://doi.org/10.1109/TIV.2023.3256972