Pedestrian volume is essential for optimizing midblock pedestrian signals as well as for quantifying pedestrian exposure in safety analyses. However, previous methods of pedestrian volume collection require either time-consuming ground-truth data collection, or the purchase and maintenance of costly sensors in a large-scale application. Therefore, this paper proposes a novel method for large-scale pedestrian estimation at midblock crosswalks using button-pushing and signal timing events. The pedestrian arrival is modeled as a Poisson process, and two submethods are developed to estimate pedestrian volume at one-stage and two-stage button-activated midblock crosswalks (BAMCs). To address the issue of missing signal cycles at two-stage BAMCs, all missing cycles that are identified by using the proposed paired signal cycle identification algorithm are accounted for and added by minimizing the error between estimation results of two stages. Eight days of the ground-truth pedestrian volume is manually collected from two study midblock crosswalks to evaluate the proposed methods. On average, 235 and 230 pedestrians per day were observed to cross the one-stage BAMC and two-stage BAMC, respectively. The average mean absolute error of estimated pedestrian volume using a one-hour interval is 2.27 and 1.78 ped/hour at two study locations, respectively. The evaluation results indicate that the proposed methods are promising for estimating pedestrian volume at midblock crosswalks using event-based data. A further sensitivity analysis of changing the estimation interval shows that the one-hour interval pedestrian volume estimation is recommended as having the least error.

行人体积对于优化中间街区行人信号以及量化安全分析中的行人暴露至关重要。但是，以前的行人流量收集方法需要耗时的地面真实数据收集，或者在大规模应用中需要购买和维护昂贵的传感器。因此，本文提出了一种新的方法，该方法用于使用按钮按下和信号定时事件进行中块人行横道的大规模行人估计。行人的到来被建模为泊松过程，并且开发了两个子方法来估计一阶段和两阶段按钮激活的中型人行横道（BAMC）的行人流量。为了解决两级BAMC信号周期丢失的问题，通过使用建议的配对信号周期识别算法来识别所有丢失的周期，并通过最小化两个阶段的估计结果之间的误差来加以解决和相加。从两个研究中段人行横道手动收集了八天的地面真相行人量，以评估所提出的方法。平均每天观察到有235名和230名行人分别经过一级BAMC和二级BAMC。在两个研究地点，使用一小时间隔估算的行人流量的平均平均绝对误差分别为2.27和1.78 ped /小时。评估结果表明，所提出的方法有望使用基于事件的数据来估计人行横道中段的行人流量。