자동차안전학회지 (Journal of Auto-vehicle Safety Association)

한국자동차안전학회 (Korean Auto-vehicle Safety Association)
권호 표지
DOI QR코드

DOI QR Code

듀얼카메라를 활용한 ACC 안전성 평가 방법에 관한 연구

A Study on the ACC Safety Evaluation Method Using Dual Cameras

  • 김봉주 (계명대학교 기계공학과) ;
  • 이선봉 (계명대학교 자동차시스템공학과)
  • 투고 : 2021.10.26
  • 심사 : 2022.04.05
  • 발행 : 2022.06.30
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

Recently, as interest in self-driving cars has increased worldwide, research and development on the Advanced Driver Assist System is actively underway. Among them, the purpose of Adaptive Cruise Control (ACC) is to minimize the driver's driving fatigue through the control of the vehicle's longitudinal speed and relative distance. In this study, for the research of the ACC test in the real environment, the real-road test was conducted based on domestic-road test scenario proposed in preceding study, considering ISO 15622 test method. In this case, the distance measurement method using the dual camera was verified by comparing and analyzing the result of using the dual camera and the result of using the measurement equipment. As a result of the comparison, two results could be derived. First, the relative distance after stabilizing the ACC was compared. As a result of the comparison, it was found that the minimum error rate was 0.251% in the first test of scenario 8 and the maximum error rate was 4.202% in the third test of scenario 9. Second, the result of the same time was compared. As a result of the comparison, it was found that the minimum error rate was 0.000% in the second test of scenario 10 and the maximum error rate was 9.945% in the second test of scenario 1. However, the average error rate for all scenarios was within 3%. It was determined that the representative cause of the maximum error occurred in the dual camera installed in the test vehicle. There were problems such as shaking caused by road surface vibration and air resistance during driving, changes in ambient brightness, and the process of focusing the video. Accordingly, it was determined that the result of calculating the distance to the preceding vehicle in the image where the problem occurred was incorrect. In the development stage of ADAS such as ACC, it is judged that only dual cameras can reduce the cost burden according to the above derivation of test results.

키워드

과제정보

본 연구는 한국산업기술평가관리원이 지원하는 산업기술혁신사업(10079967, 자율주행자동차핵심기술개발사업)으로 수행된 연구결과입니다. 이에 관계자 여러분께 감사드립니다.

참고문헌

  1. Marsden, G., Mcdonald, M. and Brackstone, M., 2001, "Towards an Understanding of Adaptive Cruise Control", Journal of Transportation Research Part C: Emerging Technologies, Vol. 9, pp. 33~51. doi:https://doi.org/10.1016/S0968-090X(00)00022-X
  2. Kim, S., Tomizuka, M. and Cheng, K., 2012, "Smooth Motion Control of the Adaptive Cruise Control System by a Virtual Lead Vehicle", Int. J. Automotive Technology, Vol. 13, pp. 77~85. doi:https://doi.org/10.1007/s12239-012-0007-6
  3. Kim, N., Lee, J., Soh, M., Kwon, J., Hong, T. and Park, K., 2013, "Improvement of Longitudinal Safety System's Performance on Near Cut-In Situation by Using the V2V", 2013 KSAE Annual Conference Proceedings, pp. 747~755.
  4. Moon, C., Lee, Y., Jeong, C. and Choi, S., 2018, "Investigation of Objective Parameters for Acceptance Evaluation of Automatic Lane Change System", Int. J. Automotive Technology, Vol. 19, pp. 179~190. doi:https://doi.org/10.1007/s12239-018-0017-0
  5. Ulbrich, S. and Maurer, M., 2015, "Towards Tactical Lane Change Behavior Planning for Automated Vehicles", 2015 IEEE 18th International Conference on Intelligent Transportation Systems, Las Palmas, pp. 989~995. doi:https://doi.org/10.1109/ITSC.2015.165
  6. Butakov, V. and Ioannou, P., 2015, "Personalized Driver/Vehicle Lane Change Models for ADAS", IEEE Transactions on Vehicular Technology, Vol. 64, pp. 4422~4431. doi:https://doi.org/10.1109/TVT.2014.2369522
  7. Venhovens, P., Noab, K. and Adiprasito, B., 2000, "Stop&Go Cruise Control", Proceedings of FISITA World Automotive Congress, Seoul, 2000, pp. 61~69.
  8. Kim, B.J. and Lee, S.B., 2017, "A Study on Evaluation Method of the Adaptive Cruise Control", Journal of Drive and Control, Vol. 14, pp. 8~17.
  9. Kim, B.J. and Lee, S.B., 2017, "A Study on Evaluation Method of ACC Test Considering Domestic Road Environment", Journal of Korean Auto-vehicle Safety Association, Vol. 9, pp. 38~47.
  10. Kim, B.J. and Lee, S.B., 2020, "Comparison of simulation and Actual Test for ACC Function on Real-Road", Journal of the Korea Academia-Industrial cooperation Society, Vol. 21, pp. 457~467. https://doi.org/10.5762/KAIS.2020.21.1.457
  11. Son, S.H., Jeong, C.H., Park, J.W. and Choi, S.J., 2019, "Development of Simulation Environment for Evaluating Safety of the Adaptive Cruise Control System", Proceedings of The Korean Society of Automotive Engineers Conference, pp. 1980~1985.
  12. Moon, Y.J. and Park, Y.K., 2002, "Establishment of performance test site for Advanced Safety Vehicle (ASV) and development of evaluation technology - Focusing on ACC evaluation program", Journal of The Korean Institute of Communication Sciences, Vol. 19, pp. 68~76.
  13. Yoon, K.H. and Lee, J.W., 2002, "A Study of Test Methods and Procedures for thd ACC and FVCWS", Proceedings of The Korean Society of Automotive Engineers Conference, pp. 109~115.
  14. Sun, X., Liu, W., Wen, M., Wu, Y., Li, H., Huang, J., Hu, C. and Huang, Z., 2021, "A Real-Time Optimal Car-Following Power Management Strategy for Hybrid Electric Vehicles with ACC Systems", Energies, Vol. 14, 3438. doi:https://doi.org/10.3390/en14123438
  15. Chen, C., Guo, J., Guo, C., Chen, C., Zhang, Y. and Wang, J., 2021, "Adaptive Cruise Control for Cut-In Scenarios Based on Model Predictive Control Algorithm", applied sciences, Vol. 11, 5293. doi:https://doi.org/10.3390/app11115293
  16. Pier Giuseppe Anselma, 2021, "Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort", energies, Vol. 14, 2897. doi:https://doi.org/10.3390/en14102897
  17. Beukel, A., Driel, C., Boelhouwer, A., Veders, N. and Heffelaar, 2021, "T. Assessment of Driving Proficiency When Drivers Utilize Assistance Systems-The Case of Adaptive Cruise Control", safety, Vol. 7, 33. doi:https://doi.org/10.3390/safety7020033
  18. Liu, L., Zhang, Q., Liu, R., Zhu, X. and Ma, Z. 2021, "Adaptive Cruise Control System Evaluation According to Human Driving Behavior Characteristics", actuators, Vol. 10, 90. doi:https://doi.org/10.3390/act10050090
  19. Bae, G.H. and Lee, S.B., 2019, "A Study on Calculation Method of Distance with Forward Vehicle Using Single-Camera", Proceedings of Symposium of the Korean Institute of communications and Information Sciences, 2019, pp. 256~257.
  20. Lee, S.H., Kim, B.J. and Lee, S.B., 2021, Study on Image Correction and Optimization of Mounting Positions of Dual Cameras for Vehicle Test. energies, Vol. 14, 2857. doi:https://doi.org/10.3390/en14164857
  21. Lee, J.M., Han, J.H. and Kim, S.J., 2021, "Visual Positioning and Distance Measurement Using by Object Recognition", Proceedings of Korean Institute of Information Technology Conference, pp. 95~97.
  22. Han, B.W. and Lim, S.J., 2013, "Development of HD Resolution Stereoscopic Camera and Apparatus for Recognizing Depth of Object", Journal of the Korea Academia-Industrial cooperation Society, Vol. 14, pp. 351~357. https://doi.org/10.5762/KAIS.2013.14.1.351
  23. Zhu, J., Wang, Z., Wang, S. and Chen, S., 2020, "Moving Object Detection Based on Background Compensation and Deep Learning", symmetry, Vol. 12, 1965. doi:https://doi.org/10.3390/sym12121965
  24. Hsu, Y.W., Lai, Y.H., Zhong, K.Q., Yin, T.K. and Perng, J.W., 2020, "Developing an On-Road Object Detection System Using Monovision and Radar Fusion†", energies, Vol. 13, 116. doi:https://doi.org/10.3390/en13010116
  25. Zhu, X., Ding, B., Meng, Q., Gu, L. and Yang, Y., 2018, "Statistic Experience Based Adaptive One-Shot Detector (EAO) for Camera Sensing System", Sensors, Vol. 18, 3041. doi:https://doi.org/10.3390/s18093041