The invention relates to an automatic driving route planning method and system based on vehicle-road cloud collaboration and a medium, and the method comprises the steps: U1, obtaining the data information of vehicles, pedestrians and fixed obstacles of each branch route in real time based on road side RSU equipment, carrying out the preprocessing of the data information of vehicles, pedestrians and fixed obstacles of each branch route, and obtaining the data information of vehicles, pedestrians and fixed obstacles of each branch route; outputting road condition representation matrix data information of each branch line; u2, dividing the road condition representation matrix data information of each branch line into a training data set and a test training set, and inputting the training data set into an XGboost regression prediction model for training and learning to obtain a trained XGboost regression prediction model; and U3, a regression prediction model based on the trained XGboost is carried out. According to the method, the problems that the intelligent automatic driving vehicle cannot recognize the road condition of the front operation line and cannot perform optimal selection of the passing line are solved, and the operation efficiency of the automatic driving vehicle is improved.
本发明涉及一种基于车路云协同的自动驾驶线路规划方法、系统及介质,所述方法包括U1.基于路侧RSU设备,实时获取各个分支线路的车辆、行人和固定障碍物数据信息,对每个分支线路的车辆、行人和固定障碍物数据信息进行预处理,输出每个分支线路的路况表征矩阵数据信息;U2.将所述每个分支线路的路况表征矩阵数据信息分为训练数据集和测试训练集,并将所述训练数据集输入XGboost回归预测模型进行训练和学习,得到训练好的XGboost回归预测模型;U3.基于所述训练好的XGboost回归预测模型。本发明不仅解决车智能自动驾驶车辆无法识别前方运营线路的路况,无法做通行线路的最优选择的问题,而且提高了自动驾驶车辆的运行效率。
Automatic driving route planning method and system based on vehicle-road cloud collaboration and medium
一种基于车路云协同的自动驾驶线路规划方法、系统及介质
2024-02-23
Patent
Electronic Resource
Chinese
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