PURPOSES : This study aims to investigate the reliability of the real-time estimation of intersection traffic volumes based on the integration of location intelligence data and smart intersection data. METHODS : Location intelligence data (LID) and smart intersection data were obtained at eight intersections in Inju-daero, Incheon. The two datasets were then integrated to estimate traffic volumes for intersections in the shadow section, where traffic information was not expected to be obtained. The traffic estimation accuracy was evaluated using the total traffic, approach traffic, and turning movement volumes at the intersections. The estimated traffic was compared with the actual traffic volumes in the smart intersection data to validate the reliability of traffic estimation. RESULTS : The average traffic estimation error for the total intersection volume was approximately 4.5% for the five intersections in the shadow section. The estimation errors for the approach volumes (less than 5%) were also consistently low, except from 12 pm to 1 pm. CONCLUSIONS : The findings of this study suggest that location intelligence data can be combined with smart intersection data to estimate real-time traffic for shadow sections on roadways. This could enable a cost-effective cooperative intelligent transport system (C-ITS) when the municipal budget is limited, ultimately leading to the sustainable operation of C-ITS.

1. 서론
    1.1. 연구 배경 및 목적
2. 기존 문헌 검토
3. 방법론
    3.1. 분석 자료
    3.2. 분석 방법
4. 분석 결과
    4.1. 교통량 추정 정확도
5. 결론 및 정책제언
    5.1. 결론
    5.2. 정책제언
REFERENCES

• 손지언(인천연구원 교통물류연구부 연구위원) | Sohn Jhieon
• 김종형(인천연구원 교통물류연구부 선임연구위원) | Kim Jong Hyung
• 이태헌(인천연구원 교통물류연구부 연구위원) | Lee Taehun (Transportation & Logistics Research Division, The Incheon Institute, 98 Simgok-ro, Seo-gu, Incheon 22711, Republic of Korea) Corresponding author