DOI QR코드

DOI QR Code

Development of Traffic Situation Integrated Monitoring Indicators Combining Traffic and Safety Characteristics

교통소통과 안전 특성을 결합한 교통상황 모니터링 지표 개발

  • Young-Been Joo (Dept. of Korea Land&Housing Corporation(LH), Prior Transport Planning Office) ;
  • Jun-Byeong Chae (Dept. of Dept. of D.N.A.Plus Convergence., Univ. of Ajou) ;
  • Jae-Seong Hwang (Dept. of Transportation Research Institute., Univ. of Ajou) ;
  • Choul-Ki Lee (Dept. of Transportation Systems Eng., Univ. of Ajou) ;
  • Sang-Soo Lee (Dept. of Transportation Systems Eng., Univ. of Ajou)
  • 주영빈 (한국토지주택공사 선교통계획처) ;
  • 채준병 (아주대학교 DNA플러스융합학과) ;
  • 황재성 (아주대학교 교통연구센터) ;
  • 이철기 (아주대학교 교통시스템공학과) ;
  • 이상수 (아주대학교 교통시스템공학과)
  • Received : 2023.12.04
  • Accepted : 2023.12.20
  • Published : 2024.02.28

Abstract

In traffic management, gaps in understanding traffic conditions continue to exist. While the self-belonging problem indicator develops relative to speed, belonging, and self-based relative inclination, it does not apply elimination criteria that may indicate situations that contrast with attribute-specific problems. In this study, we develop integrated indicators that specify communication situations and safety levels for modeling. We review indicators of changes in traffic conditions and raise safety issues, reviewing the indicators so that ITS data can be applied, analyzing the relationships between indicators through factor analysis. We develop combined, integrated indicators that can show changes and stability in traffic situations and that can be applied in traffic information centers to contribute to the development of a traffic environment that can monitor related traffic conditions.

교통관리에서 교통상황을 판단하는 판단지표의 중요성과 필요성은 계속해서 높아지고 있다. 기존 교통상황 판단지표들은 속도, 교통량, 밀도 기반으로 각각의 특성에 맞춰 개발되었지만, 속성별 가지는 문제점과 종합적인 상황을 보여줄 수 없어 모니터링 지표로는 적합하지 않았다. 이에 본 연구에서는 도로 소통상황과 안전도를 판단하는 지표들을 통합하여 모니터링에 적합한 통합지표 개발을 목표로 하였다. 교통상황의 변화를 판단할 수 있고 안전도를 판단할 수 있는 지표들을 검토하고 실시간 ITS 데이터를 적용할 수 있도록 지표를 재정립하였다. 요인분석을 통해 지표 간 관계성을 분석하여 가중치를 도출한 뒤 하나의 통합지표를 개발하였다. 통합지표는 교통상황의 변화와 안전도의 변화를 보여줄 수 있는 지표로 향후 교통정보센터에 적용하여 종합적인 교통상황을 모니터링할 수 있는 교통환경으로의 발전에 기여할 수 있을 것이다.

Keywords

Acknowledgement

이 논문은 2023년도 정부(경찰청)의 재원으로 과학치안진흥센터의 지원을 받아 수행하였습니다. (No.092021C28S01000, 자율주행 혼재 시 도로교통 통합관제시스템 및 운영기술 개발)

References

  1. Blog 'Beyond the Horizon'(2022.5.25), [Big Data Analysis Certification] Principal Component Analysis, https://it-utopia.tistory.com/entry/%EB%B9%85%EB%8D%B0%EC%9D%B4%ED%84%B0%EB%B6%84%EC%84%9D%EA%B8%B0%EC%82%AC-%EC%A3%BC%EC%84%B1%EB%B6%84%EB%B6%84%EC%84%9DPrincipal-Component-Analysis, 2023.11.10.
  2. Bok, G. C., Lee, S. J., Choe, Y. H., Gang, J. G. and Lee, S. H.(2009), "Development of a traffic condition index (TCI) on expressways", Journal of Korean Society of Transportation, vol. 27, no. 5, pp.85-95.
  3. Cheon, H. Y. and Lee, E. E.(2001), "A Study on Lateral Characteristics of Traffic Flow on Rural Freeway and Clibration of Lane Number Adjustment Factor", Journal of Civil and Environmental Engineering Research, vol. 21, no. 6, pp.775-783.
  4. Cho, J. H., Kim, S. H. and Rho, J. H.(2008), "A study on road characteristic classification using exploratory factor analysis", Journal of Korean Society of Transportation, vol. 26, no. 3, pp.53-66.
  5. Choi, C. H. and You, Y. Y.(2017), "The study on the comparative analysis of EFA and CFA", Journal of Digital Convergence, vol. 15, no. 10, pp.103-111. https://doi.org/10.14400/JDC.2017.15.10.103
  6. Han, Y. and Kim, Y.(2017), "A study of measuring traffic congestion for urban network using average link travel time based on DTG big data", The Journal of The Korea Institute of Intelligent Transport Systems, vol. 16, no. 5, pp.72-84. https://doi.org/10.12815/kits.2017.16.5.72
  7. Jung, S. H., Han, K. H., So, J. H. and Lee, C. K.(2023), "A Study of Classification Analysis about Traffic Conditions Using Factor Analysis and Cluster Analysis", The Journal of The Korea Institute of Intelligent Transport Systems, vol. 22, no. 1, pp.65-80. https://doi.org/10.12815/kits.2023.22.1.65
  8. Kim, D. K.(2022), Study on the Development of road safety indicators for the installation of automated traffic enforcement devices, Master's Thesis, Ajou University.
  9. Kim, H., Jang, K. and Kwon, O. H.(2016), "Methodology for Real-time Detection of Changes in Dynamic Traffic Flow Using Turning Point Analysis", Journal of Korean Society of Transportation, vol. 34, no. 3, pp.278-290. https://doi.org/10.7470/jkst.2016.34.3.278
  10. Lee, H. S. and Im, J. H.(2017), SPSS 24 Manual, Seoul: Jyphyunjae.
  11. Lee, J. H., Ryu, C. H. and Chung, T. Y.(2010), "Calculating the weights of indicators for science and technology innovation capability index", Kyungsung University Industrial Development Institute, vol. 26, no. 3, pp,1-34.
  12. Lee, S. B., Kim, J. M. and Cheon, S. H.(2020), "Recurring Congestion Priority Analysis Methodology Based On Mobility Big-Data", Journal of Korean Society of Transportation, vol. 39, no. 2, pp.164-176.
  13. Lee, S. G.(1997), A Study on the Development of Road Congestion Index, The Korea Research Institute of Human Settlements(KRIHS), pp.33-57.
  14. Lee, S. M., Shin, H. C. and Park, J. H.(2005), "Analysis of Travel Time Index of 5 Metropolitan Cities", Korean Society for Civil Engineers Conference, pp.4235-4238.
  15. So, H. J., Kim, Y. M., Kim, N. S., Hwang, J. S. and Lee, C. K.(2020), "Study on Estimation of Unmanned Enforcement Equipment Installation Criteria and Proper Installation Number", The Journal of The Korea Institute of Intelligent Transport Systems, vol. 19, no. 6, pp.49-60. https://doi.org/10.12815/kits.2020.19.6.49