The quality of traffic big data is crucial for accurate traffic flow prediction and the efficiency improvement of intelligent transportation systems.Taking Huizhou City as an example,the Python language was used to process the operating vehicle data for one month,the error values were filtered by the method based on location and speed thresholds,the outliers were repaired by the mean repair method,the trajectory was segmented based on time intervals,and the hidden Markov model was used to match the road network,so as to obtain the data results for prediction and visual analysis,and select specific road sections and time periods for testing.The results show that the traffic big data processing method shows the potential and high practicability of accurate prediction in practical applications.
关键词
惠州市/交通大数据/均值修复法/数据质量/精准预测
Key words
Huizhou city/traffic big data/mean repair method/data quality/precise prediction
万方数据