The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Development of a Speed Prediction Model for Urban Network Based on Gated Recurrent Unit

GRU 기반의 도시부 도로 통행속도 예측 모형 개발

  • Hoyeon Kim (Dept. of Transportation Eng, Univ. of Ajou) ;
  • Sangsoo Lee (Dept. of Transportation Eng, Univ. of Ajou) ;
  • Jaeseong Hwang (Dept. of Transportation Eng, Univ. of Ajou)
  • 김호연 (아주대학교 교통공학과 ) ;
  • 이상수 (아주대학교 교통공학과 ) ;
  • 황재성 (아주대학교 교통공학과)
  • Received : 2022.11.30
  • Accepted : 2022.12.25
  • Published : 2023.02.28
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Abstract

This study collected various data of urban roadways to analyze the effect of travel speed change, and a GRU-based short-term travel speed prediction model was developed using such big data. The baseline model and the double exponential smoothing model were selected as comparison models, and prediction errors were evaluated using the RMSE index. The model evaluation results revealed that the average RMSE of the baseline model and the double exponential smoothing model were 7.46 and 5.94, respectively. The average RMSE predicted by the GRU model was 5.08. Although there are deviations for each of the 15 links, most cases showed minimal errors in the GRU model, and the additional scatter plot analysis presented the same result. These results indicate that the prediction error can be reduced, and the model application speed can be improved when applying the GRU-based model in the process of generating travel speed information on urban roadways.

본 연구에서는 도시부 도로의 다양한 자료를 수집하여 통행속도 변화에 대한 영향을 분석하였고, 이와 같은 빅데이터를 활용하여 GRU 기반의 단기 통행속도 예측 모형을 개발하였다. 그리고 Baseline 모형과 이중지수평활 모형을 비교 모형으로 선정하여 RMSE 지표로 예측 오차를 평가하였다. 모형 평가 결과, Baseline 모형과 이중지수평활 모형의 RMSE는 평균 7.46, 5.94값으로 각각 산출되었다. 그리고 GRU 모형으로 예측한 평균 RMSE는 5.08 값이 산출되었다. 15개 링크별로 편차가 있지만, 대부분의 경우 GRU 모형의 오차가 최소의 값을 나타내었고, 추가적인 산점도 분석 결과도 동일한 결과를 제시하였다. 이러한 결과로부터 도시부 도로의 통행속도 정보 생성 과정에서 GRU 기반의 예측 모형 적용 시 예측 오차를 감소시키고 모형 적용 속도의 개선을 기대할 수 있을 것으로 판단된다.

Keywords

Acknowledgement

이 논문은 2022년도 정부(경찰청)의 재원으로 과학치안진흥센터의 지원을 받아 수행된 연구임.(No.092021C28S01000, 자율주행 혼재 시 도로교통 통합관제시스템 및 운영기술 개발)

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