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A Novel Multisensor Traffic State Assessment System Based on Incomplete Data

机译:基于不完整数据的新型多传感器交通状态评估系统

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摘要

A novel multisensor system with incomplete data is presented for traffic state assessment. The system comprises probe vehicle detection sensors, fixed detection sensors, and traffic state assessment algorithm. First of all, the validity checking of the traffic flow data is taken as preprocessing of this method. And then a new method based on the history data information is proposed to fuse and recover the incomplete data. According to the characteristics of space complementary of data based on the probe vehicle detector and fixed detector, a fusion model of space matching is presented to estimate the mean travel speed of the road. Finally, the traffic flow data include flow, speed and, occupancy rate, which are detected between Beijing Deshengmen bridge and Drum Tower bridge, are fused to assess the traffic state of the road by using the fusion decision model of rough sets and cloud. The accuracy of experiment result can reach more than 98%, and the result is in accordance with the actual road traffic state. This system is effective to assess traffic state, and it is suitable for the urban intelligent transportation system.
机译:提出了一种具有不完整数据的新型多传感器系统,用于交通状态评估。该系统包括探测车辆检测传感器,固定检测传感器和交通状态评估算法。首先,将交通流数据的有效性检查作为该方法的预处理。然后提出了一种基于历史数据信息的融合和恢复不完整数据的新方法。针对基于探测车探测器和固定探测器的数据空间互补特征,提出了一种空间匹配融合模型,用于估计道路平均行驶速度。最后,利用粗糙集与云的融合决策模型,将北京德胜门大桥与鼓楼大桥之间的交通流量,流量和占用率进行融合,以评估道路的交通状态。实验结果的准确性可以达到98%以上,结果符合实际道路交通状况。该系统可以有效地评估交通状况,适用于城市智能交通系统。

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