Implementation of Autonomous Vehicle Situational Awareness Technology using Infrastructure Edge on a Two- way Single Lane in Traffic-isolated Area

교통소외지역 양방향 단일차선에서 인프라 엣지를 이용한 자율주행 차량 상황 인지 기술 구현

  • 김성종 (한국교통대학교 컴퓨터공학과) ;
  • 송석일 (한국교통대학교 컴퓨터공학과)
  • Received : 2023.10.14
  • Accepted : 2023.12.28
  • Published : 2023.12.30

Abstract

In this paper, we propose a sensor data sharing system for the safe and smooth operation of autonomous vehicles on two-way single lanes in traffic-isolated areas and implement the core module, the situational awareness technology. Two-way single lanes pose challenges for autonomous vehicles, particularly when encountering parked vehicles or oncoming traffic, leading to reversing issues. We introduce a system using infrastructure cameras to detect vehicles' approach, enter, and leave on twoway single lanes in real-time, transmitting this information to autonomous vehicles via V2N communication, thereby expanding the sensing range of the autonomous vehicles. The core part of the proposed system is the situational awareness of the two-way single lane using infrastructure cameras. In this paper, we implement this using object detection and tracking technology. Finally, we validate the implemented situational awareness technology using data collected from actual two-way single lanes.

이 논문에서는 교통소외지역의 양방향 단일 차선에서 자율주행 차량의 안전하고 원활한 운행을 위한 센서 데이터 공유 시스템을 제안하고 핵심 모듈인 상황인지 기술을 구현한다. 양방향 단일 차선 도로는 주차된 차량이나 마주오는 차량으로 인한 자율주행 차량의 후진 문제를 야기한다. 이 논문에서는 인프라 카메라를 사용하여 양방향 단일 차선 도로에 대한 차량의 접근, 진입 진출 상황을 실시간으로 인지하고 이 정보를 V2N 통신을 통해 자율주행 차량에 전송하여 자율주행 차량의 센싱 범위를 확장하는 시스템을 제안한다. 제안하는 시스템의 핵심은 인프라 카메라를 통해 양방향 단일 차선의 상황을 인지하는 것이며 이 논문에서는 이를 객체인식 및 객체 추적기술을 이용하여 구현한다. 마지막으로, 구현한 상황인지 기술을 실제 양방향 단일 차선에서 수집한 데이터를 이용하여 검증한다.

Keywords

Acknowledgement

This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 23AMDP-C160549-02).

References

  1. A. Vinel, N. Lyamin, and P. Isachenkov, "Modeling of V2V communications for C-ITS safety applications: A CPS perspective," IEEE Commun. Lett., Vol. 22, No. 8, pp. 1600-1603, Aug. 2018. https://doi.org/10.1109/LCOMM.2018.2835484
  2. S. Maaloul, H. Aniss, M. Kassab, and M. Berbineau, "Classification of C-ITS services in vehicular environments," IEEE Access, Vol. 9, pp. 117868-117879, 2021. https://doi.org/10.1109/ACCESS.2021.3105815
  3. A. Kim, B. Woo, S. Tak, and S. Lim, "Comparison Analysis of the Road Environment between Urban and Suburban Area for Connected and Automated Driving(CAD) Mobility Services," J. Korea Inst. Intell. Transp. Syst., Vol. 21, No. 5, pp. 287-300, Oct. 2022. https://doi.org/10.12815/kits.2022.21.5.287
  4. A. Kim and S. Lim, "A study to improve the effectiveness of mobile services in traffic underprivileged area based on autonomous vehicles using the KANO model," in Proc. of the 88th Conf. Korean Soc. Transp., April 2023, pp. 467-468.
  5. G. Eom and S. Jang, "Policy Requirements for Implementing Mobility Services with Autonomous Vehicles for the Disabled," in Proc. of the 88th Conf. of Korean Soc. of Transp., April. 2023, pp. 168-169.
  6. Y. S. Song and J. D. Choi, "Analysis of Level 4 Autonomous Driving System Requirements and Architecture for Mobility Services in Poor Transport Provision Area," in Proc. KSAE 2021 Annu. Autumn Conf. Exhib., Nov. 2021, pp. 391-391.
  7. P. Jiang, D. Ergu, F. Liu, Y. Cai, and B. Ma, "A Review of Yolo algorithm developments," Procedia Comput. Sci., Vol. 199, pp. 1066-1073, 2022 https://doi.org/10.1016/j.procs.2022.01.135
  8. A T. L. Dang, G. T. Nguyen, and T. Cao, "Object tracking using improved deep SORT YOLOv3 architecture," ICIC Express Lett., Vol. 14, No. 10, pp. 961-969, Oct. 2020.
  9. "YOLO-ROS Docker Image," Docker Hub, [Online]. Available: https://hub.docker.com/r/cjh2626002/yolo-ros/tags
  10. M. Stevens and E. Atkins, "Geofence definition and deconfliction for UAS traffic management," IEEE Trans. Intell. Transp. Syst., Vol. 22, No. 9, pp. 5880-5889, 2020. https://doi.org/10.1109/TITS.2020.3040595