A Modern Intersection Data Analytics System for Pedestrian and Vehicular Safety
A Modern Intersection Data Analytics System for Pedestrian and Vehicular Safety
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DOI：
10.1109/itsc55140.2022.9921827
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发表时间：
2022-10
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通讯作者：
Tania Banerjee-Mishra;Ke Chen;Alejandro Almaraz;Rahul Sengupta;Yashaswi Karnati;Bryce Grame;E. Posadas;Subhadipto Poddar;R. Schenck;Jeremy Dilmore;Sivaramnakrishnan Srinivasan;A. Rangarajan;Sanjay Ranka
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作者：
Tania Banerjee-Mishra;Ke Chen;Alejandro Almaraz;Rahul Sengupta;Yashaswi Karnati;Bryce Grame;E. Posadas;Subhadipto Poddar;R. Schenck;Jeremy Dilmore;Sivaramnakrishnan Srinivasan;A. Rangarajan;Sanjay Ranka
作为道路安全举措的一部分，由于视频采集和处理技术的快速发展，替代道路安全方法已经得到普及。本文提出了一种端到端的软件管道，用于处理交通视频和运行基于替代安全措施的安全分析。我们开发了算法和软件来确定轨迹运动和相位，当与信号时序数据相结合时，使我们能够根据车辆与车辆和车辆与车辆交互的冲突类型进行准确的事件检测和分类。利用这些信息，我们引入了一个新的替代安全措施，“严重事件”，这是量化的多个现有的指标，如碰撞时间（TTC）和侵入后的时间（PET）记录在事件，减速和速度。我们提出了一个有效的多级事件过滤方法，然后由多属性决策树算法，修剪广泛的一组冲突的相互作用，一个强大的严重事件。上述管道用于处理来自多个城市的几个十字路口的交通视频，以测量和比较行人和车辆的安全性。详细的实验结果证明了该管道的有效性。
As a part of road safety initiatives, surrogate road safety approaches have gained popularity due to the rapid advancement of video collection and processing technologies. This paper presents an end-to-end software pipeline for processing traffic videos and running a safety analysis based on surrogate safety measures. We developed algorithms and software to determine trajectory movement and phases that, when combined with signal timing data, enable us to perform accurate event detection and categorization in terms of the type of conflict for both pedestrian-vehicle and vehicle-vehicle interactions. Using this information, we introduce a new surrogate safety measure, “severe event,” which is quantified by multiple existing metrics such as time-to-collision (TTC) and post-encroachment time (PET) as recorded in the event, deceleration, and speed. We present an efficient multistage event filtering approach followed by a multi-attribute decision tree algorithm that prunes the extensive set of conflicting interactions to a robust set of severe events. The above pipeline was used to process traffic videos from several intersections in multiple cities to measure and compare pedestrian and vehicle safety. Detailed experimental results are presented to demonstrate the effectiveness of this pipeline.