A deep learning-based vehicle path prediction method using rasterized lane information and a device thereof are disclosed. The disclosed deep learning-based vehicle path prediction method using rasterized lane information includes the steps of: taking centerline information of a lane based on a vehicle for predicting a path from a high definition map (HD Map); obtaining a rasterized image by rasterizing the centerline information of the lane; and predicting a vehicle path by using the acquired image and past path information of the vehicle as input of a deep learning model.

    차선 정보를 래스터화하여 활용하는 딥러닝 기반 차량 경로 예측 방법 및 장치가 제시된다. 본 발명에서 제안하는 차선 정보를 래스터화하여 활용하는 딥러닝 기반 차량 경로 예측 방법은 경로를 예측하기 위한 차량을 기준으로 하는 차선의 중심선 정보를 고정밀 지도(High Definition Map; HD Map)로부터 가져오는 단계, 차선의 중심선 정보를 래스터화 하여 래스터화된 이미지를 획득하는 단계 및 획득된 이미지와 차량의 과거 경로 정보를 딥러닝 모델의 입력으로 이용하여 차량 경로를 예측하는 단계를 포함한다.


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    Title :

    Deep Learning-based Vehicle Trajectory Prediction Method and Apparatus using Rasterized Lane Information


    Additional title:

    차선 정보를 래스터화하여 활용하는 딥러닝 기반 차량 경로 예측 방법 및 장치


    Contributors:
    CHOI JUN WON (author) / LEE SUK HAWN (author) / KIM BYEUNG DO (author)

    Publication date :

    2020-11-09


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Korean


    Classification :

    IPC:    G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / B60W CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION , Gemeinsame Steuerung oder Regelung von Fahrzeug-Unteraggregaten verschiedenen Typs oder verschiedener Funktion



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