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Development of V2I2V Communication-based Collision Prevention Support Service Using Artificial Neural Network

인공신경망을 활용한 V2I2V 통신 기반 차량 추돌방지 지원 서비스 개발

  • Received : 2019.09.06
  • Accepted : 2019.09.25
  • Published : 2019.10.31

Abstract

One of the Cooperative Intelligent Transportation System(C-ITS) priority services is collision prevention support service. Several studies have considered V2I2V communication-based collision prevention support services using Artificial Neural Networks(ANN). However, such services still show some issues due to a low penetration of C-ITS devices and large delay, particularly when loading massive traffic data into the server in the C-ITS center. This study proposes the Artificial Neural Network-based Collision Warning Service(ACWS), which allows upstream vehicle to update pre-determined weights involved in the ANN by using real-time sectional traffic information. This research evaluates the proposed service with respect to various penetration rates and delays. The evaluation result shows the performance of the ACWS increases as the penetration rate of the C-ITS devices in the vehicles increases or the delay decreases. Furthermore, it reveals a better performance is observed in more advanced ANN model-based ACWS for any given set of conditions.

차세대첨단교통시스템(C-ITS)의 우선 도입 서비스 항목 중 하나로 차량 추돌방지 지원 서비스가 고려되고 있다. 이에 인공신경망을 적용한 V2I2V 통신 기반의 후미추돌사고 예방 방법들이 몇몇 제시되었지만, 낮은 C-ITS 단말기 보급률 및 대용량 교통정보로 인한 지연 현상 등 한계로 인해 그 효과가 미미하다. 따라서 본 연구는 실시간 구간교통 정보를 활용한 인공신경망 기반 추돌 경고 서비스(ACWS, Artificial Neural Network-based Collision Warning Service)를 제안한다. 제안 서비스는 실시간 구간 교통정보를 반영해 인공신경망의 가중치를 갱신하고 구간 진입 차량에게 제공한다. 본 연구는 C-ITS 단말 보급률과 지연시간에 따른 제안 서비스의 성능 평가를 수행한다. 분석결과 C-ITS 단말 보급률이 높고 지연시간이 낮을수록 제안 서비스가 더 나은 성능을 나타내고, 같은 조건일 경우 고도화된 인공신경망을 적용한 서비스 성능이 더 뛰어난 것으로 확인된다.

Keywords

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