{"title":"Do existing split failure metrics accurately reflect pedestrian operation at signalized intersections?","authors":"Ferdousy Runa , S. Ilgin Guler , Vikash V. Gayah","doi":"10.1016/j.ijtst.2023.02.006","DOIUrl":null,"url":null,"abstract":"<div><p>Automated Traffic Signal Performance Measures (ATSPMs) uses high-resolution data to develop operational performance measures for signalized intersections. Split Failure (SFs) is one of the primary metrics to identify intersections with operational issues. These SFs are determined by measuring vehicle occupancy for a given movement during its green time (i.e., Green Occupancy Ratio or GOR) and immediately after the signal turns red (i.e., Red Occupancy Ratio or ROR<sub>5</sub>). While the SF metric is a great tool for signal operations and rebalancing green times, it focuses entirely on vehicular measures and ignores the treatment of pedestrians at the intersection. Prioritizing vehicular movements may lead to excess pedestrian delay, which may cause pedestrians to violate traffic signals.</p><p>To address this issue, this paper examines the relationship between pedestrian delay and GOR or ROR<sub>5</sub>. The main objective was to identify whether the GOR and ROR<sub>5</sub> could be adequately used as a proxy for pedestrian delays. To achieve this goal, high-resolution data was collected from the ATSPMs database at a signalized intersection in Salt Lake City, Utah. To predict GOR or ROR<sub>5</sub> as a function of pedestrian delay, a linear regression model was developed. The results reveal that there is very weak to no relationship between these metrics. This implies that using only GOR or ROR<sub>5</sub> in quantifying signal performance does not meaningfully capture pedestrian delay and thus might overemphasize vehicle movements. Specific pedestrian delay metrics should be included in a signal operation analysis to identify operational issues.</p></div>","PeriodicalId":52282,"journal":{"name":"International Journal of Transportation Science and Technology","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2046043023000217/pdfft?md5=3a79aba752813d78828e6fd9083e258b&pid=1-s2.0-S2046043023000217-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Transportation Science and Technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2046043023000217","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TRANSPORTATION","Score":null,"Total":0}
引用次数: 0
Abstract
Automated Traffic Signal Performance Measures (ATSPMs) uses high-resolution data to develop operational performance measures for signalized intersections. Split Failure (SFs) is one of the primary metrics to identify intersections with operational issues. These SFs are determined by measuring vehicle occupancy for a given movement during its green time (i.e., Green Occupancy Ratio or GOR) and immediately after the signal turns red (i.e., Red Occupancy Ratio or ROR5). While the SF metric is a great tool for signal operations and rebalancing green times, it focuses entirely on vehicular measures and ignores the treatment of pedestrians at the intersection. Prioritizing vehicular movements may lead to excess pedestrian delay, which may cause pedestrians to violate traffic signals.
To address this issue, this paper examines the relationship between pedestrian delay and GOR or ROR5. The main objective was to identify whether the GOR and ROR5 could be adequately used as a proxy for pedestrian delays. To achieve this goal, high-resolution data was collected from the ATSPMs database at a signalized intersection in Salt Lake City, Utah. To predict GOR or ROR5 as a function of pedestrian delay, a linear regression model was developed. The results reveal that there is very weak to no relationship between these metrics. This implies that using only GOR or ROR5 in quantifying signal performance does not meaningfully capture pedestrian delay and thus might overemphasize vehicle movements. Specific pedestrian delay metrics should be included in a signal operation analysis to identify operational issues.
自动交通信号性能测量(ATSPMs)使用高分辨率数据来制定信号交叉口的运行性能测量方法。分离故障 (SF) 是识别存在运行问题的交叉口的主要指标之一。这些 SF 是通过测量绿灯时间内(即绿灯占用率或 GOR)和信号灯变为红灯后(即红灯占用率或 ROR5)的车辆占用率来确定的。虽然 SF 指标是信号灯运行和重新平衡绿灯时间的一个很好的工具,但它完全侧重于车辆措施,而忽略了交叉口行人的处理。优先考虑车辆通行可能会导致过多的行人延迟,从而导致行人违反交通信号。为了解决这个问题,本文研究了行人延迟与 GOR 或 ROR5 之间的关系。主要目的是确定 GOR 和 ROR5 是否可以充分用作行人延迟的替代指标。为实现这一目标,我们从 ATSPMs 数据库中收集了犹他州盐湖城一个信号灯路口的高分辨率数据。为了预测作为行人延迟函数的 GOR 或 ROR5,开发了一个线性回归模型。结果显示,这些指标之间的关系很弱,甚至没有关系。这意味着,仅使用 GOR 或 ROR5 来量化信号性能并不能有意义地反映行人延迟情况,因此可能会过分强调车辆通行。信号灯运行分析中应包括具体的行人延迟指标,以确定运行问题。