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Do high visibility crosswalks improve pedestrian safety? A correlated grouped random parameters approach using naturalistic driving study data
Analytic Methods in Accident Research ( IF 12.9 ) Pub Date : 2020-12-30 , DOI: 10.1016/j.amar.2020.100155
Sarvani Sonduru Pantangi , Sheikh Shahriar Ahmed , Grigorios Fountas , Kevin Majka , Panagiotis Ch. Anastasopoulos

In this study, the effectiveness of High-Visibility Crosswalks (HVCs) in improving pedestrian safety at urban settings is assessed using SHRP2 (Second Strategic Highway Research Program) Naturalistic Driving Study (NDS) data. Various HVCs located at different positions on the roadway segment (mid-block vs end-of-block) and featuring different HVC marking designs (continental, bar-pair, and ladder) were selected for the assessment. As no pedestrian-vehicle crashes or conflicts were identified from the forward-facing videos and time series information of the SHRP2 Naturalistic Driving Study data, crash surrogate measures (i.e., speed; acceleration; throttle pedal actuation; and brake application) were employed to identify and analyze modifications in driving behavior at or near the HVCs.

The surrogate measures were statistically modeled using a correlated grouped random parameters estimation framework. This can account for panel effects arising from multiple traversals undertaken by each participant, for the effect of unobserved characteristics, as well as for their unobserved correlations, which constitute possible misspecification issues of statistical modeling. The results of the analysis showed that the presence of HVC modifies driving behavior, thus reducing the risk of motor vehicle – pedestrian conflicts. Apart from the presence of HVC, the HVC type (ladder, continental or bar-pair), the HVC location (mid-block or end-of-block) and various driver, roadway and trip characteristics were found to affect the vehicle speed, acceleration, throttle pedal actuation, and brake application.



中文翻译:

高能见度的人行横道是否可以改善行人安全性?使用自然驾驶研究数据的相关分组随机参数方法

在这项研究中,使用SHRP2(第二战略公路研究计划)自然驾驶研究(NDS)数据评估了高可见度人行横道(HVC)在改善城市环境中行人安全方面的有效性。选择了位于道路段不同位置(街区中段与街区末段)且具有不同HVC标记设计(大陆,对杆和梯子)的各种HVC进行评估。由于没有从SHRP2自然驾驶研究数据的前向视频和时间序列信息中识别出行人车辆碰撞或冲突,因此采用了碰撞替代措施(即速度,加速度,油门踏板致动和制动应用)进行识别并分析HVC处或附近对驾驶行为的修改。

使用相关的分组随机参数估计框架对替代度量进行统计建模。这可以解释由每个参与者进行的多次遍历引起的面板效应,未观察到的特征的效应以及它们未观察到的相关性,这些构成了统计建模的可能的错误指定问题。分析结果表明,HVC的存在改变了驾驶行为,从而降低了机动车与行人冲突的风险。除了存在HVC外,还发现HVC类型(梯形,大陆或酒吧对),HVC位置(街区中段或街区终点)以及各种驾驶员,道路和行车特性会影响车速,加速,油门踏板致动和制动应用。

更新日期:2021-01-29
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