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首页> 外文期刊>Proceedings of the Institution of Civil Engineers. Municipal Engineer >Using vehicle data as a surrogate for highway accident data
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Using vehicle data as a surrogate for highway accident data

机译：使用车辆数据作为公路事故数据的代理

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摘要

Many studies have tried to use the surrogate safety measures (SSM) estimated from the microscopic traffic simulations. However, it is difficult to adopt these developed SSM to reflect real-world traffic conditions when the developed network in the simulation is not calibrated and validated accordingly. This paper proposed a method to develop the pattern-based surrogate safety measure (PSSM) using individual vehicle trajectory data. The PSSM can be estimated based on the pattern of hazardous driving behaviour (HDB). Using digital tacho graph data collected from the commercial vehicles, HDB patterns were obtained. Various PSSMs were developed and validated with the observed crash data using Random Forest. Then, the surrogate safety performance function was estimated based on the frequency of HDB. To enhance model performance, machine learning and data mining techniques were applied. The results show that sudden deceleration, sudden lane change, sudden overtaking and sudden U-turn are related to traffic crashes during HDB. The results also show that high potential for safety improvement was identified in the road section linking the urban and suburban areas. The findings from this study can provide new approach to adopt real-time individual vehicle trajectory data to evaluate safety performance of network levels.
机译：许多研究试图使用从微观流量模拟估计的代理安全措施（SSM）。然而，难以采用这些开发的SSM来反映现实世界的交通条件，当模拟中的开发网络未被校准并相应地验证时。本文提出了一种使用单独的车辆轨迹数据开发基于模式的代理安全措施（PSSM）的方法。可以基于危险驾驶行为（HDB）的模式来估计PSSM。使用从商用车辆收集的数字Tacho图数据，获得了HDB模式。使用随机林的观察到的崩溃数据开发并验证了各种PSSMS。然后，基于HDB的频率估计代理安全性能函数。为了提高模型性能，应用机器学习和数据挖掘技术。结果表明，突然的减速，突然的车道变化，突然的超车和突然的粪便与HDB期间的交通崩溃有关。结果还表明，在联系城市和郊区地区的道路段中确定了高潜力。本研究的发现可以提供新的方法来采用实时单独的车辆轨迹数据来评估网络级别的安全性能。

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