| 山区公路弯道预警方法研究 |
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| 引用本文： | 许多,方守恩,陈雨人.山区公路弯道预警方法研究[J].交通信息与安全,2017,35(6):19. |
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| 作者姓名： | 许多 方守恩 陈雨人 |
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| 作者单位： | 同济大学道路与交通工程教育部重点实验室 上海201804 |
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| 基金项目： | 国家重点研发计划项目国家科技支撑计划课题项目 |
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| 摘 要： | 山区公路弯道的事故率往往高于普通路段,驾驶人由于视距等原因对弯道风险产生识别模糊的现象,基于此提出了一种弯道预警方法.针对山区公路上行驶前方是否为弯道进行预警,以前车的驾驶状态和环境因素为依据进行建模,为后车提供有效的信息以完成信息的链式传递.分析了速度和三向加速度与弯道条件的关系,通过频率分布图与相关系数的计算,从统计学的角度说明了4个变量作为模型自变量的可行性.同时考虑到驾驶人的性格等个人因素的影响,以历史数据为基础,利用以处理时序数据见长的Elman递归神经网络构建预警模型,并将该模型与二元逻辑回归、BP神经网络等方法进行对比,其准确率达到85.59%,验证了模型的有效性.
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| 关 键 词： | 交通安全 弯道预警 驾驶状态 Elman神经网络 ROC曲线 阈值 |
An Early Warning Method of Curve Roads in Mountain Areas |
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| Abstract: | Accident rate of curve roads in mountain areas is often higher than which in general sections.Due to sight distance and some reasons,drivers cannot easily identify risks of curve roads.A method for early warning of curve roads is developed.A simulation is set up based on driving modes of front vehicles and road conditions in mountain areas,in order to provide valid information and complete chain transfer of information.The relations between velocity,acceleration,and curves are analyzed.Frequency diagrams and distribution of correlation coefficients are computed.The results show that four variables taken into this model as independent variables is feasible.An early warning model is developed by using the historical data and Elman recurrent neural network.Compared with two binary logistic regression and BP neural network,the accuracy rate of this model is 85.59%.The validity of the model is verified. |
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