To provide technology that can accurately estimate a shape of a road in front of an own lane, taking into consideration machine learning technology even in various environments where it is not easy to recognize a white line on the road.SOLUTION: A road shape estimation device 9 includes an image acquisition unit 15 and an estimation processing unit 17. The estimation processing unit 17 includes a learning recognition unit 31, a marker extraction unit 23, and a state transition determination unit 41, and further includes, of a non-learning estimation unit 45, a partial learning estimation unit 37, and a total learning estimation unit 39, at least two types of estimation units 45, 37, and 39. The road shape estimation device 9 compares, of division line information used by the non-learning estimation unit 45, division line information used by the partial learning estimation unit 37, and image boundary line information used by the total learning estimation unit 39, information of at least two types of estimation units 45, 37, and 39, and determines which estimated result of the non-learning estimation unit 45, the partial learning estimation unit 37, and the total learning estimation unit 39 is used.SELECTED DRAWING: Figure 4
【課題】道路の白線等の認識が容易ではない等の各種の環境においても、機械学習の技術を考慮に入れて、自車線の前方の道路の形状を精度良く推定することが可能な技術を提供すること。【解決手段】道路形状推定装置9は、画像取得部15と推定処理部17とを備える。推定処理部17は、学習認識部31とマーカ抽出部23と状態遷移判定部41とを備え、さらに、非学習推定部45と部分学習推定部37と全学習推定部39とのうち、少なくとも2種の推定部45、37、39を備える。道路形状推定装置9は、非学習推定部45で用いた区分線の情報と、部分学習推定部37で用いた区分線の情報と、全学習推定部39で用いた画像境界線の情報と、のうち少なくとも2種の推定部45、37、39の情報を比較し、非学習推定部45と部分学習推定部37と全学習推定部とのうちどの推定結果を用いるかを判定する。【選択図】図4
ROAD SHAPE ESTIMATION DEVICE
道路形状推定装置
2021-09-02
Patent
Electronic Resource
Japanese
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