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山区双车道公路货车碰撞预测的双变量冲突极值模型
引用本文:戢晓峰,耿昭师.山区双车道公路货车碰撞预测的双变量冲突极值模型[J].交通运输系统工程与信息,2022,22(2):230-238.
作者姓名:戢晓峰  耿昭师
作者单位:昆明理工大学,交通工程学院,昆明 650500
摘    要:为预测山区双车道公路货车与冲突车辆发生的碰撞,本文基于无人机视频,提取货车与交互车辆的高精度轨迹数据,选取适用于不同运行轨迹的交通冲突指标,结合极值理论,构建双变量冲突极值(BTCEV)模型,将后侵入时间(PET)与碰撞时间(TTC)纳入统一框架,实现山区双车道公路货车与冲突车辆的碰撞预测,并以云南省货车事故高发的山区双车道公路为例,验证 BTCEV模型的预测性能。研究表明:PET为0.382 s、TTC为4.471 s是山区双车道公路货车严重冲突的阈值;BTCEV 模型预测山区双车道公路货车年事故发生率为 5.84%,预测准确性高达 98.92%,较PET模型以及TTC模型分别提高了167.33%和10.80%;且相比于单变量模型,双变量模型所估计的置信区间更窄,预测精度更高。研究结果将山区双车道公路货车碰撞预测方法从单变量扩展到双变量,在山区货车交通安全分析方面有广阔的应用前景。

关 键 词:交通工程  货车碰撞预测  双变量冲突极值模型  山区双车道公路  车辆运行轨迹  
收稿时间:2021-10-31

Bivariate Traffic Conflict Extreme Value Model of Truck Collision Prediction on Two-lane Mountain Highway
JI Xiao-feng,GENG Zhao-shi.Bivariate Traffic Conflict Extreme Value Model of Truck Collision Prediction on Two-lane Mountain Highway[J].Transportation Systems Engineering and Information,2022,22(2):230-238.
Authors:JI Xiao-feng  GENG Zhao-shi
Institution:Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500, China
Abstract:To predict collisions between trucks and conflicting vehicles on two-lane mountain highway, this paper proposes a bivariate traffic conflict extreme value (BTCEV) model. The high-precision trajectory data of trucks and interactive vehicles were extracted based on drone video. The traffic conflict indicators suitable for different trajectories were selected and the extreme value theory was also considered in the model. The Post Encroachment Time (PET) and Time to Collision (TTC) were incorporated into a unified framework to realize the collision prediction of trucks and conflicting vehicles on two-lane mountain highway. The prediction performance of the BTCEV model was verified by the example of the two-lane mountain highway that has a high truck incidence rate in Yunnan Province. The result shows that PET is 0.382 s and TTC is 4.471 s are the thresholds for serious conflicts of trucks on two-lane mountain highway. The annual accident probability of truck on two-lane mountain highway predicted by the BTCEV model is 5.84%, and the prediction accuracy is as high as 98.92%. The prediction accuracy is respectively 167.33% and 10.80% higher than that of the PET model and the TTC model. Compared with the univariate model, the confidence interval estimated by the bivariate model is narrower and the prediction accuracy is higher. The proposed method extends the truck collision prediction method on two-lane mountain highway from single variable to double variables, and has broad application prospects in the truck safety analysis on two-lane mountain highway.
Keywords:traffic engineering  truck collision prediction  bivariate traffic conflict extreme value model  two-lane  mountain highway  vehicle trajectory  
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