The invention relates to the technical field of automobile industry, in particular to an automatic driving decision-making platform based on a machine learning model, and solves the problem that an automatic driving decision-making platform in the prior art mainly depends on environment information acquired by various sensors and an advanced machine learning algorithm. The algorithms can perceive and understand the environment and make a driving decision accordingly. However, an existing automatic driving decision-making platform still has many challenges in the aspects of processing complex traffic conditions, predicting other vehicle behaviors, optimizing self driving strategies and the like. The automatic driving decision-making platform based on the machine learning model comprises a data preprocessing module which is used for processing original data of a multi-source sensor and providing high-quality input data for a machine learning decision-making module. According to the method, deep fusion and analysis are carried out on the multi-source sensor data through the machine learning model, the traffic environment can be sensed and understood more accurately, and thus a more accurate driving decision is made.
本发明涉及汽车工业技术领域,尤其涉及基于机器学习模型的自动驾驶决策平台,解决了现有技术中自动驾驶决策平台主要依赖于各种传感器获取的环境信息以及先进的机器学习算法。这些算法能够对环境进行感知、理解,并据此做出驾驶决策。然而,现有的自动驾驶决策平台在处理复杂交通情况、预测他车行为以及优化自身驾驶策略等方面仍存在诸多挑战的问题。基于机器学习模型的自动驾驶决策平台,包括数据预处理模块,用于处理多源传感器的原始数据,提供高质量的输入数据给机器学习决策模块。本发明通过机器学习模型对多源传感器数据进行深度融合与分析,能够更准确地感知和理解交通环境,从而做出更精准的驾驶决策。
Automatic driving decision platform based on machine learning model
基于机器学习模型的自动驾驶决策平台
2024-11-05
Patent
Electronic Resource
Chinese
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 |
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