| 基于冲突极值模型的非常规信号交叉口安全评价 |
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| 引用本文： | 郭延永,刘攀,吴瑶,李清韵.基于冲突极值模型的非常规信号交叉口安全评价[J].中国公路学报,2022,35(1):85-92. |
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| 作者姓名： | 郭延永 刘攀 吴瑶 李清韵 |
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| 作者单位： | 1. 东南大学交通学院, 江苏 南京 21009;2. 南京邮电大学现代邮政学院, 江苏 南京 210003 |
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| 基金项目： | 国家杰出青年科学基金项目（51925801）；国家自然科学基金项目（52131203，51878165） |
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| 摘 要： | 为了评估非常规信号交叉口交通安全，提出了基于冲突极值模型的横断面分析方法。利用计算机视频技术提取了南京市3个信号交叉口（1个设施组和2个参照组）96 h的交通冲突数据和交通流数据，构建了包含数据层-处理层-先验层的3层贝叶斯超阈值冲突极值模型，利用马尔可夫链蒙特卡罗仿真方法对模型参数进行估计，采用预测交通事故和比值比计算了非常规信号交叉口安全改善效用。研究结果表明：外置左转车道非常规信号交叉口比常规信号交叉口的交通安全性高21.8%；平均左转弯半径、平均小时左转车流量和左转大车比对交通事故风险有显著影响；平均左转弯半径越大，交通事故风险越小；小时平均左转车流量越大，左转大车比越大，交通事故风险越大。研究结论显示层级贝叶斯超阈值冲突极值模型对交通冲突的数据利用率高，并且可以刻画冲突极值的非稳态性和异质性，应用前景广阔。
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| 关 键 词： | 交通工程 非常规信号交叉口 极值统计 交通冲突 安全评价 |
| 收稿时间： | 2021-01-18 |
Safety Evaluation of Unconventional Signalized Intersection Based on Traffic Conflict Extreme Model |
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| GUO Yan-yong,LIU Pan,WU Yao,LI Qing-yun.Safety Evaluation of Unconventional Signalized Intersection Based on Traffic Conflict Extreme Model[J].China Journal of Highway and Transport,2022,35(1):85-92. |
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| Authors: | GUO Yan-yong LIU Pan WU Yao LI Qing-yun |
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| Affiliation: | 1. School of Transportation, Southeast University, Nanjing 210096, Jiangsu, China;2. School of Modern Post&Institute of Modern Posts, Nanjing University of Posts and Telecommunications, Nanjing 210003, Jiangsu, China |
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| Abstract: | To assess the safety of unconventional signalized intersections, a cross sectional analysis based on traffic conflict extreme model is proposed. The traffic conflicts and traffic flow data were extracted from 96 h video data, collected from three signalized intersections in Nanjing, using computer vision techniques. Further, a data level-processing level-prior level hierarchical Bayesian peak over threshold (POT) model is proposed. The model parameters were estimated using the Markov Chain Monte Carlo Simulation approach. The safety effect was calculated based on the predicted traffic crashes using the odds ratio technique. The results show that the safety of the unconventional signalized intersection with outside left lane is 21.8% higher than that of the conventional signalized intersection. The average left-turning radius, average hourly left-turning traffic volume, and heavy vehicle ratio of the left-turning volume have significant impacts on traffic crash risk. The larger the average left turn radius, the lower the traffic crash risk; the greater the average hourly left turn traffic volume and heavy vehicle ratio of left-turning volume, the higher the traffic crash risk. In conclusion, the hierarchical Bayesian POT conflict extreme model has a high utilization rate of the traffic conflict data, and can effectively describe the instability and heterogeneity of the traffic conflict extremes. Overall, it has a broad application prospect. |
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| Keywords: | traffic engineering unconventional signalized intersection extreme statistics traffic conflicts safety evaluation |
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