1种基于浮动车数据的多车车速融合算法

在浮动车处理技术中,多浮动车样本车速的融合是整个计算的最后1个环节,算法的好坏直接影响到动态交通信息的准确性。从多权重系数和多种路况状态的角度构建了1种新的基于浮动车数据的多车车速融合算法,该算法从浮动车行驶特征等角度,综合考量在表征实时路况时浮动车多车样本间的共性与个性差异去融合多车车速,提高了实时路况的准确性,并且可根据实际交通环境快速调整相关参数。最后通过实证分析对其准确性进行了评估验证,结果表明能有效提高动态交通信息的准确性,具有良好的实用性。

A Multi-vehicle Speed Fusion Algorithm Based on Probe Vehicle Data

In the processing technology of probe vehicle data,fusion of multi-vehicle speed is the last link of the entire calculation process,and the fusion algorithm has a direct influence on the accuracy of the dynamic traffic information estimation.Considering multi-weighting factors and many kinds of traffic states,this paper constructed a new fusion algorithm based on the probe vehicle speed data.Based on the travel characteristics of the probe vehicle,this algorithm fused multi-vehicle speed by considering the universality and individuality among the multi vehicle samples.The proposed algorithm could adjust the relative parameters rapidly to respond to the actual traffic conditions.Finally,the proposed algorithm was validated by real-world field test.The results show that it can improve the accuracy of dynamic traffic state estimation effectively,and has good feasibility.