基于模型的自动数据错误信号交叉口队列和延迟估计方法

S. Anusha, Anuj Sharma, L. Vanajakshi, S. Subramanian, L. Rilett
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引用次数: 19

摘要

摘要本文提出了一种基于模型的交叉口排队车辆数和总延误估计方法,这是表征交叉口信号化的典型指标。首先采用输入-输出和队列累积多边形方法进行估计。这些都是通过使用内布拉斯加州林肯市的两个仪器交叉路口的数据来评估的。然而,估计数与实际数据不太一致,主要是因为从自动检测器获得的计数存在误差。因此,对误差的特征进行了分析。然后提出了一种基于模型的卡尔曼滤波估计方法。通过在卡尔曼滤波估计方案中加入特定场地/交通条件的校准常数,进一步对估计过程进行了适当的修改。结果表明,该方案可用于信号交叉口的性能分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model-Based Approach for Queue and Delay Estimation at Signalized Intersections with Erroneous Automated Data
AbstractA model-based scheme has been developed in this paper to estimate the number of vehicles in queue and the total delay, which are typical measures for characterizing a signalized intersection. The estimation was first carried out by using the input-output and queue accumulation polygon methods. These were evaluated by using data from two instrumented intersections in the city of Lincoln, Nebraska. However, the estimates did not agree well with the actual data primarily because of the errors in counts obtained from the automated detectors. Hence, an analysis of the characteristics of the errors was carried out. A model-based estimation approach using the Kalman filter was then developed. Suitable modifications were further applied to the estimation process by incorporating calibration constants for particular site/traffic conditions in the Kalman filter estimation scheme. The results obtained were promising, indicating that the scheme could be used for performance analysis of signalized intersection...
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