교통신호제어기 유지보수를 위한 수명예측 - 김은영; 이기한; 장중순; 박상철 (한국설비안전학회지, 2018)
This paper proposes a methodology for the effective maintenance planning of traffic signal controllers, which are important for the safety of vehicles and pedestrians. For the effective maintenance planning, it is necessary to estimate the lifespan of a traffic signal controller. Since a traffic signal controller operates outdoors, the lifespan depends on the environmental factors including temperature, humidity, and salinity. We devise a deep learning model to estimate the lifespan of a traffic signal controller by using environmental conditions. The proposed maintenance planning methodology computes the optimal maintenance period which provides the lowest maintenance cost.
Keywords: Lifespan Estimation; Maintenance Planning; Deep Learning; Traffic Signal Controller