The invention provides a driver braking intention prediction method based on AdaBoost integrated learning, and belongs to the technical field of vehicle braking intention prediction. (2) preprocessing the acquired braking data and dividing training sets for input and output; (3) constructing an integrated learning training model and outputting an integrated learning strong classifier; and (4) inputting the driver data into a learning device to realize braking intention prediction. The strong classifier is trained through ensemble learning according to the driver braking data, prediction of the driver braking intention is achieved by means of the generated strong learner, and the problem that a traditional weak classifier is under-fitted for braking intention prediction is effectively solved.

    本发明提出一种基于AdaBoost集成学习的驾驶员制动意图预测方法,属于车辆制动意图预测技术领域。其步骤为:(1)采集驾驶员大量制动数据样本(2)对采集到的制动数据进行预处理并划分训练集输入输出(3)构建集成学习训练模型,输出集成学习强分类器(4)将驾驶员数据输入到学习器,实现制动意图预测。本发明根据驾驶员制动数据通过集成学习对强分类器进行训练,借助生成的强学习器,实现驾驶员制动意图的预测,有效解决了传统弱分类器对于制动意图预测的欠拟合。


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    Titel :

    Driver braking intention prediction method based on AdaBoost integrated learning


    Weitere Titelangaben:

    一种基于AdaBoost集成学习的驾驶员制动意图预测方法


    Beteiligte:
    LIU LIFENG (Autor:in) / LI ZHICHENG (Autor:in)

    Erscheinungsdatum :

    2023-03-03


    Medientyp :

    Patent


    Format :

    Elektronische Ressource


    Sprache :

    Chinesisch


    Klassifikation :

    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 / G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung



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