It is proposed a method of training a computer-implemented system (500) for predicting the future development of a traffic scene, the system (500) comprising at least: a. A perceptual level aggregating scene-specific information of an input scene, b. A backbone network (120) for generating a feature set of potential features based on the scene-specific information, c. A classifier network (140) for classifying the feature set of potential features based on the scene-specific information. And d. A prediction module (560, 580, 571, 721) for each mode for generating a prediction for the future development of the input scene, which evaluates a predetermined number of different modes for the future development of the input scene based on the feature set. The backbone network (120) is trained with the classifier network (140) by modifying the weights of the backbone network (120) and/or the classifier network (140) such that the deviation between the learning phase evaluations (131) and the true evaluations of the classifier network (140) of different patterns is reduced (506).

    提出一种训练用于预测交通场景未来发展的计算机实现的系统(500)的方法,系统(500)至少包括:a.聚合输入场景的场景特定信息的感知层面,b.主干网络(120),用于基于场景特定信息生成潜在特征的特征集,c.分类器网络(140),其基于特征集而评价针对输入场景未来发展的预给定数量的不同模式,和d.针对每个模式的预测模块(560、580、571、721),用于生成针对输入场景未来发展的预测。通过修改主干网络(120)和/或分类器网络(140)的权重使得不同模式的分类器网络(140)的学习阶段评价(131)与真实评价间的偏差减少(506),将主干网络(120)与分类器网络(140)一起训练。


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    Title :

    Method for training system for predicting future development of traffic scene and corresponding system


    Additional title:

    训练用于预测交通场景未来发展的系统的方法和相应系统


    Contributors:

    Publication date :

    2023-06-02


    Type of media :

    Patent


    Type of material :

    Electronic Resource


    Language :

    Chinese


    Classification :

    IPC:    G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS



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