| 基于状态观测器的城市快速路交通事故识别 |
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| 引用本文： | 郭宇奇,陈阳舟.基于状态观测器的城市快速路交通事故识别[J].交通信息与安全,2017,35(6):10-18. |
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| 作者姓名： | 郭宇奇 陈阳舟 |
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| 作者单位： | 北京工业大学城市交通学院 北京100124;北京工业大学交通工程北京市重点实验室 北京100124;北京工业大学北京城市交通协同创新中心 北京100124 |
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| 摘 要： | 针对城市快速路网中交通事故频发的现象,为及时准确地对事故进行识别,提出一种基于宏观交通流模型的状态观测器估计算法.根据利用交通仿真软件Paramics的实验数据,并结合元胞传输模型(CTM)理论分析事故发生前后,事故路段及其上下游路段的交通流密度分布特征.同时基于路网的交通流模型构建了城市快速路事故的状态观测器估计模型,模型通过估计密度的变化规律,并结合交通状态分布特征来对事故进行识别.以京通快速路为例,通过对观测器估计误差进行计算,得出了实验路段平均百分比误差(MPE)的均值为11.56%,模型估计精度为88.44%.该方法能较为准确的对事故进行识别,为快速路中的交通事故识别提供有效的参考.
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| 关 键 词： | 交通安全 城市快速路网 交通事故识别 状态观测器 交通流密度 |
State-observer Based Identification of Traffic Accidents on Urban Freeways |
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| Abstract: | Traffic accidents are with a higher occurrence rate on urban freeways.An estimated algorithm of state observer based on a macroscopic traffic flow model is proposed with a purpose to identify traffic accidents accurately and timely.Data of traffic flow before and after accidents which simulated by Paramics software are recorded and analyzed by using the Cell Transmission Model (CTM) theory.Distribution characteristics of traffic densities around accident segments are studied.An estimation model is designed based on the traffic flow model.Therefore,this estimation model can be implemented to identify traffic accidents by checking variation feature of estimated densities and distribution characteristics of traffic.Finally,a case study on Jingtong freeway is conduct,the average value of Mean Percentage Error (MPE) of the experimental section is 11.56%,the accuracy of the model reaches 88.44%.The results show that the estimation model proposed in this study can be implemented for traffic accidents identification,and provide effective references in practice. |
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