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A method for predicting crash configurations using counterfactual simulations and real-world data

机译：一种使用反事实模拟和现实世界数据预测崩溃配置的方法

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Traffic safety technologies revolve around two principle ideas; crash avoidance and injury mitigation for inevitable crashes. The development of relevant vehicle injury mitigating technologies should consider the interaction of those two technologies, ensuring that the inevitable crashes can be adequately managed by the occupant and vulnerable road user (VRU) protection systems. A step towards that is the accurate description of the expected crashes remaining when crash-avoiding technologies are available in vehicles. With the overall objective of facilitating the assessment of future traffic safety, this study develops a method for predicting crash configurations when introducing crash-avoiding countermeasures. The predicted crash configurations are one important factor for prioritizing the evaluation and development of future occupant and VRU protection systems. By using real-world traffic accident data to form the baseline and performing counterfactual model-in-the-loop (MIL) pre-crash simulations, the change in traffic situations (vehicle crashes) provided by vehicles with crash-avoiding technologies can be predicted. The method is built on a novel crash configuration definition, which supports further analysis of the in-crash phase. By clustering and grouping the remaining crashes, a limited number of crash configurations can be identified, still representing and covering the real-world variation. The developed method was applied using Swedish national- and in-depth accident data related to urban intersections and highway driving, and a conceptual Autonomous Emergency Braking system (AEB) computational model. Based on national crash data analysis, the conflict situations Same-Direction rear-end frontal (SD-ref) representing 53 % of highway vehicle-to-vehicle (v2v) crashes, and Straight Crossing Path (SCP) with 21 % of urban v2v intersection crashes were selected for this study. Pre-crash baselines, for SD-ref (n = 1010) and SCP (n = 4814), were prepared based on in-depth accident data and variations of these. Pre-crash simulations identified the crashes not avoided by the conceptual AEB, and the clustering of these revealed 5 and 52 representative crash configurations for the highway SD-ref and urban intersection SCP conflict situations, respectively, to be used in future crashworthiness studies. The results demonstrated a feasible way of identifying, in a predictive way, relevant crash configurations for in-crash testing of injury prevention capabilities.
机译：交通安全技术围绕着两个原理的想法;不可避免地崩溃的碰撞避免和伤害缓解。相关车辆伤害减轻技术的发展应考虑这两种技术的互动，确保乘员和弱势道路用户（VRU）保护系统可以充分管理不可避免的崩溃。迈出的一步是当车辆中有碰撞技术时，预期碰撞的准确描述。随着促进对未来交通安全评估的总体目标，该研究开发了一种在引进碰撞的对策时预测碰撞配置的方法。预测的崩溃配置是优先考虑未来乘员和VRU保护系统的评估和开发的一个重要因素。通过使用真实世界的交通事故数据来形成基线并执行违背循环模型（MIL）预崩溃模拟，可以预测车辆提供的车辆提供的流量情况（车辆崩溃）的变化。该方法基于新颖的崩溃配置定义，支持进一步分析崩溃阶段。通过群集和分组剩余的崩溃，可以识别有限数量的崩溃配置，仍然代表和涵盖真实世界的变化。使用与城市交叉路口和公路驾驶相关的瑞典国家和深入事故数据以及概念自主动力制动系统（AEB）计算模型，应用开发的方法。基于国家崩溃数据分析，相同方向前端正面（SD-REF），代表公路车辆到车辆（V2V）崩溃的53％，以及21％的城市V2V的直接交叉路径（SCP）为这项研究选择了交叉崩溃。对于SD-REF（n = 1010）和SCP（n = 4814），基于深入的事故数据和这些变化来编制预崩溃基线。预崩溃模拟确定了概念AEB不避免的崩溃，并且这些群集在未来的崩溃研究中分别用于公路SD-REF和城市交叉路口SCP冲突局势的5和52个代表性碰撞配置。结果表明，以预测的方式，以预测的方式识别可行的方式，有关损失预防能力的崩溃测试的相关碰撞配置。

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