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首页> 外文期刊>Journal of Transportation Engineering >Estimating Transit Route OD Flow Matrices from APC Data on Multiple Bus Trips Using the IPF Method with an Iteratively Improved Base: Method and Empirical Evaluation
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Estimating Transit Route OD Flow Matrices from APC Data on Multiple Bus Trips Using the IPF Method with an Iteratively Improved Base: Method and Empirical Evaluation

机译：使用IPF方法以迭代改进的基础从多条公交线路上的APC数据估算公交路线OD流矩阵：方法和经验评估

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摘要

An iterative method is proposed to estimate bus route origin-destination (OD) passenger flow matrices from boarding and alighting data for time-of-day periods in the absence of good α priori estimates of the flows. The algorithm is based on the widely used iterative proportional fitting (IPF) method and takes advantage of the large quantities of boarding and alighting data that are routinely collected by transit agencies using automatic passenger count (APC) technologies. An arbitrarily chosen OD matrix can be used as the base matrix required to initialize the algorithm, and the IPF method is applied with bus trip-level boarding and alighting data and the base matrix to produce an estimate of the OD flow matrix for each bus trip. The trip-level OD flow matrices are then aggregated to produce an estimate of the period-level OD flow matrix, which in turn is used as the base matrix for the following iteration. The process is repeated until convergence. Empirical results are conducted on operational bus routes using APC data collected during multiple season-years, where directly observed OD passenger flows are available to represent the ground truth. In all cases in which APC data are available for even a reasonably small number of bus trips, the iteratively improved base method produces better estimates than the application of the traditional IPF method when using a null base matrix, which is commonly adopted in the absence of a priori information without updating. Moreover, the algorithm converges in minimal computational time to the same estimates regardless of the initializing matrices used.
机译：提出了一种迭代方法，可在缺乏良好的α先验估计量的情况下，根据一天中的上下车数据来估计公交路线的始发地（OD）客流矩阵。该算法基于广泛使用的迭代比例拟合（IPF）方法，并利用了运输机构使用自动乘客计数（APC）技术常规收集的大量登机和下车数据。可以使用任意选择的OD矩阵作为初始化算法所需的基本矩阵，并且IPF方法与公交车出行级别的登机和下车数据一起应用，并且该基本矩阵可以为每个公交车出行提供OD流矩阵的估计。然后，将行程级别的OD流量矩阵进行汇总，以生成对周期级别的OD流量矩阵的估计，然后将其用作后续迭代的基础矩阵。重复该过程直到收敛。使用在多个季节年中收集的APC数据在运行的公交路线上得出实证结果，在这里可以直接观察到的OD客流量代表地面事实。在所有APC数据甚至可以用于相当少量的公交车出行的所有情况下，与使用传统IPF方法的应用（使用空基本矩阵时）相比，迭代改进的基本方法所产生的估计值要好于传统IPF方法，而在没有先验信息，无需更新。此外，无论使用哪种初始化矩阵，该算法都能在最少的计算时间内收敛到相同的估计值。

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