ヒント: 日本語の検索結果のみ表示します。検索言語は [表示設定] で指定できます
2024/01/17 · The test results show that the proposed model can work properly in certain scenarios, and can reach up to 97.7% prediction accuracy and 2.3s ...
This study analyses the characteristics of vehicle motions at intersections, segments vehicle motion processes, and proposes a data compensation method.
A Neural Network-Based Model with Conditional-Deactivation Structure for Autonomous Vehicle Motivation Prediction at Intersections. https://doi.org/10.1145 ...
文献「交差点における自律車両動機付け予測のための条件付き不活性化構造によるニューラルネットワークベースモデル【JST・京大機械翻訳】」の詳細情報です。
A Neural Network-Based Model with Conditional-Deactivation Structure for Autonomous Vehicle Motivation Prediction at Intersections. Conference Paper. Jan 2024.
2023/10/01 · A Neural Network-Based Model with Conditional-Deactivation Structure for Autonomous Vehicle Motivation Prediction at Intersections. 2023, ACM ...
This study proposes a collaborative simulation environment integrating traffic scenario construction, driving environment perception, and neural network ...
A Neural Network-Based Model with Conditional-Deactivation Structure for Autonomous Vehicle Motivation Prediction at Intersections. Cheng Wei, Fei Hui, Kenan ...
2023/10/31 · In this work, we propose a behavioral model that encodes drivers' interacting intentions into latent social-psychological parameters.
含まれない: Conditional- Deactivation Structure Motivation Intersections.
関連する質問
Are neural networks used for autonomous vehicles?
Which deep learning algorithms are used in autonomous vehicles?
A Neural Network-Based Model with Conditional-Deactivation Structure for Autonomous Vehicle Motivation Prediction at Intersections · Cheng WeiFei HuiKenan Mu ...