Abstract

It has been widely shown that pedestrians’ level of frustration grows with the increase of pedestrian delay, and may cause pedestrians to violate the signals. However, for agencies seeking to use multimodal signal performances for signal operations, the pedestrian delay is not always readily available. To tackle this issue, this study proposed a finite mixture modeling method to estimate pedestrian delay using high-resolution event-based data collected from the smart sensors. The proposed method was used to estimate pedestrian delay at four signalized intersections on a major arterial corridor in Pima County, Arizona. The results showed the proposed method was able to capture and track the actual pedestrian delay fluctuations during the day at all the study intersections with average errors of 10 s and 13 s for mean-absolute-error and root-mean-square-error, respectively. In addition, the proposed model was compared with three conventional methods (HCM 2010 HCM (2010). Transportation Research Board of the National Academies. Google Scholar. [Google Scholar], Virkler, Dunn) and the comparison results showed that the proposed method outperforms all the other methods in terms of both mean-absolute-error and root-mean-square-error. Furthermore, it was found that the proposed method is transferable and can be used as a network-wide delay estimation model for intersections with similar traffic patterns. The application of the proposed method could provide agencies with a more reliable, robust, and yet accurate approach for estimating pedestrian delay at signalized intersections where the pedestrian data are not readily available. In addition, it will allow system operators to quantitatively assess existing delays and enact changes to incorporate the better serve pedestrian needs.

摘要

已经广泛表明，行人的沮丧程度随着行人延误的增加而增加，并可能导致行人违反信号。然而，对于寻求将多模式信号性能用于信号操作的机构来说，行人延迟并不总是很容易获得。为了解决这个问题，本研究提出了一种有限混合建模方法，使用从智能传感器收集的基于事件的高分辨率数据来估计行人延误。所提出的方法用于估计亚利桑那州皮马县主要干道走廊上四个信号交叉口的行人延误。结果表明，所提出的方法能够捕捉和跟踪所有研究交叉口白天的实际行人延迟波动，平均绝对误差和均方根误差的平均误差分别为 10 s 和 13 s . 此外，将所提出的模型与三种常规方法（HCM2010人力资源管理委员会（2010 年）。美国国家科学院交通研究委员会。谷歌学术。 [Google Scholar]，Virkler，Dunn）和比较结果表明，所提出的方法在平均绝对误差和均方根误差方面都优于所有其他方法。此外，发现所提出的方法是可转移的，并且可以用作具有相似交通模式的交叉口的全网延迟估计模型。所提出的方法的应用可以为机构提供一种更可靠、稳健且准确的方法来估计行人数据不易获得的信号交叉口的行人延误。此外，它将允许系统运营商定量评估现有的延误并制定变更以更好地满足行人的需求。