To understand the operating status of the road network and measure the traffic congestion problem, an intelligent calculation method for the intelligent traffic flow index based on big data mining is proposed. According to the error data discriminating rules, the error data in the traffic flow data is discriminated, all lanes are detected according to the data discriminating result, the traffic data of each lane are recorded in chronological order, and the traffic data is converted. Fuzzy data mining technology is used to predict the converted traffic flow, combined with traffic flow sequence segmentation and BP neural network model to realize the intelligent calculation of the smart traffic flow index. Experimental results show that the method can achieve accurate calculation of daily and weekly smart traffic index, and the calculation time is short, indicating that it can provide a reliable data basis for traffic operation state estimation and traffic early warning mechanism formulation.

中文翻译：

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基于大数据挖掘的智能交通流量指标智能计算方法研究

为了解路网运行状况，衡量交通拥堵问题，提出一种基于大数据挖掘的智能交通流指数智能计算方法。根据错误数据判别规则，对交通流数据中的错误数据进行判别，根据数据判别结果检测所有车道，按时间顺序记录各车道的交通数据，并对交通数据进行转换。采用模糊数据挖掘技术对转换后的交通流进行预测，结合交通流序列分割和BP神经网络模型，实现智能交通流指标的智能计算。实验结果表明，该方法能够实现每日和每周智能交通指数的准确计算，