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Determining risk-based safety thresholds through naturalistic driving patterns using trajectory data on expressways

机译：通过在高速公路上使用轨迹数据确定基于风险的安全阈值

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The present research work is initiated, probing for safety levels, evolving as an outcome of analysis of micro-level interactions due to naturalistic vehicular movements on Indian expressways. The research work reported here, devised a micro-level parameter, namely instant perception time (IPT) as a safety measure, which is a function of vehicular interactions. As a step towards deriving IPT, video-graphic surveys were conducted and traffic data was collected on two intercity Indian expressways. As a part of this work, first microscopic trajectory data was developed for capturing naturalistic driving behavior under heterogeneous traffic environment. Thereafter, hysteresis plots were developed between leader-follower pairs using relative speed and spacing between the vehicles. By means of the developed hysteresis plots, a novel approach for identification and quantifying chances of rear-end crashes using follower's Instantaneous perception time (IPT), is proposed in the present study. To study the IPT approach under different flow conditions, well-calibrated and validated simulation model is also developed using real trajectory data collected for the prevailing traffic conditions observed on the study sections. From the obtained IPTs using simulation model, three cluster ranges are delineated pertaining to different levels of risks of crashes. The cluster-analysis suggests that the least values of space-headway (m) and IPT (s) (space headway < 10.91 m, IPT < 5.61 s) at a given location shows most severe chances of rear-end collision. While, lower to moderate values indicate (with thresholds: space headway in the range 10.91-18.5 m; IPT 5.61-11.91 s), whereas higher values of IPT (more than 12 s) suggest the least chances of rear-end collision. The methodological approach, results and findings thus developed under naturalistic driving environment, presented here can be very useful in understanding the operational deficiencies of traffic streams, road geometry, coupled with safety assessment of traffic streams on uninterrupted roadway facilities. Furthermore, traffic control or geometry improvement related decisions can also be taken at different unsafe locations using IPT as a risk measure to enhance safety.
机译：启动了本研究工作，探讨了安全水平，作为印度高速公路上的自然车辆运动的微观相互作用分析的结果不断发展。这里报道的研究工作设计了微级参数，即即时感知时间（IPT）作为安全措施，这是车辆交互的函数。作为推导IPT的步骤，进行了视频图形调查，并在两条间城市高速公路上收集了交通数据。作为这项工作的一部分，开发了第一微观轨迹数据，用于在异构交通环境下捕获自然主义驾驶行为。此后，使用车辆之间的相对速度和间隔在引导脚手对之间开发滞后地块。通过开发的滞后图，在本研究中提出了一种用于使用追随瞬间感知时间（IPT）的识别和量化后端碰撞机会的新方法。为了在不同的流动条件下研究IPT方法，还使用在研究部分上观察到的现行交通状况收集的实际轨迹数据来开发良好校准和验证的仿真模型。从获得的IPTS使用仿真模型，三个集群范围逐次划分的崩溃风险。聚类分析表明，在给定位置的空间通道（M）和IPT（SPASE10.91 M，IPT <5.91M）的最小值显示出后端碰撞的最严重的机会。虽然，降低到中等值表示（具有阈值：10.91-18.5 m的空间前进路线; IPT 5.61-11.91 S），而IPT的更高值（超过12秒钟）表明后端碰撞的最小可能性。因此，在自然驾驶环境下制定的方法论方法，结果和结果在这里呈现在理解交通流量，道路几何的操作缺陷，以及在不间断的巷道设施上交通流量的安全评估。此外，使用IPT作为风险尺寸以增强安全性的风险尺寸，还可以在不同的不安全位置采取交通管制或几何改善相关决策。

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