The invention relates to the technical field of intelligent driving, in particular to a traffic flow data derivation system and a data derivation method. A training set is obtained through a driving data set of a typical scene and processing the driving data set, then massive traffic flow data conforming to typical scene data features are generated through an improved adversarial network with an auxiliary classifier, and then indexes are selected from a macroscopic perspective to evaluate a generated traffic flow scene. And finally, a rationality index is proposed to evaluate the closeness degree of the motion states of the model generation vehicle and the original vehicle, and the result shows that the generated traffic flow scene has high conformity with the natural driving traffic flow scene characteristics. According to the method, the characteristics of the traffic flow of the natural driving scene are extracted, a large number of traffic flow scenes conforming to the natural driving condition characteristics can be generated, and the test scene is enriched when the automatic driving vehicle test is carried out.
本发明涉及智能驾驶技术领域,特别涉及一种交通流数据衍生系统及数据衍生方法。通过典型场景的驾驶数据集并对其进行处理的得到训练集,而后通过改进的具有辅助分类器的对抗网络,生成海量符合该典型场景数据特征的交通流数据,然后从宏观角度选取指标对生成的交通流场景进行评估,最后提出了合理性指标来评估模型生成车辆与原始车辆运动状态的接近程度,结果表明生成的交通流场景与自然驾驶交通流场景特性有较高的符合性。本发明对自然驾驶场景的交通流的特征进行提取,能够生成大量符合自然驾驶情况特性的交通流场景,在进行自动驾驶车辆测试时,丰富了测试场景。
Traffic flow data derivation system and data derivation method
一种交通流数据衍生系统及数据衍生方法
2024-08-27
Patent
Electronic Resource
Chinese
IPC: | G06F ELECTRIC DIGITAL DATA PROCESSING , Elektrische digitale Datenverarbeitung / G06N COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS , Rechnersysteme, basierend auf spezifischen Rechenmodellen / G06V / G08G Anlagen zur Steuerung, Regelung oder Überwachung des Verkehrs , TRAFFIC CONTROL SYSTEMS |
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