城市快速通道衔接节点交通风险识别研究
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摘要
为深入研究城市快速通道衔接节点安全性,识别其交通风险,针对快速通道衔接节点处车辆变道及车速变化行为,将实测变道及车速数据作为分析对象,定量分析衔接节点变道、车速变化规律。在此基础上建立多级模糊综合评判模型,结合工程资料对昆玉高速昆明市境内快速通道桩号K11+115m典型衔接节点进行交通风险识别。结果表明:衔接节点过渡段、加减速段相较其他区间具有较高风险等级。最后,根据识别结果,对潜在交通风险区间成因进行分析,并提出相应改善措施。
In order to deeply study the safety of urban fast-track connection nodes and identify their traffic risks, the measured lane change and vehicle speed data are taken as the analysis object for the vehicle lane change and vehicle speed change behavior at the fast-track connection node, and the change of the joint node and the speed change are quantitatively analyzed law.On this basis, a multi-level fuzzy comprehensive evaluation model is established, and the traffic risk identification is carried out on the K11+115 m typical connection node of Kunyu expressway Kunming city. The results show that the transition section of the connecting node and the acceleration/deceleration section have higher risk levels than other sections. Finally, based on the identification results, the causes of the potential traffic risk interval are analyzed, and corresponding improvement measures are proposed.
In order to deeply study the safety of urban fast-track connection nodes and identify their traffic risks, the measured lane change and vehicle speed data are taken as the analysis object for the vehicle lane change and vehicle speed change behavior at the fast-track connection node, and the change of the joint node and the speed change are quantitatively analyzed law.On this basis, a multi-level fuzzy comprehensive evaluation model is established, and the traffic risk identification is carried out on the K11+115 m typical connection node of Kunyu expressway Kunming city. The results show that the transition section of the connecting node and the acceleration/deceleration section have higher risk levels than other sections. Finally, based on the identification results, the causes of the potential traffic risk interval are analyzed, and corresponding improvement measures are proposed.
引文
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[2]赵倩,柴干.高速公路匝道交通安全综合评价[J].交通信息与安全,2009,27(4):88-91.
[3]马艳丽,祁首铭,吴昊天,等.基于PET算法匝道合流区交通冲突识别模型[J].交通运输系统工程与信息,2018,18(2):142-148.
[4]徐慧智,裴玉龙,程国柱.基于期望运行轨迹车道变换行为安全性分析[J].中国安全科学学报,2010,20(1):90-95.
[5]孙璐,李颜平,钱军,等.基于交通冲突技术交织区交通安全评价[J].中国安全科学学报,2013,23(1):55.
[6]王世明,徐建闽,罗强,等.面向高速公路车辆换道安全预警模型[J].华南理工大学学报(自然科学版),2014,42(12):40-50.
[7]孟祥海,林兰平.高速公路分合流区潜在事故风险研究[J].中国安全科学学报,2015,25(8):164-170.
[8] Vechione M, Balal E, Cheu R L. Comparisons of Mandatory and Discretionary Lane Changing Behavior on Freeways[J].International Journal of Transportation Science&Technology, 2018,7(2):124-136.
[9]孙吉贵,刘杰,赵连宇.聚类算法研究[J].软件学报,2008,19(1):48-61.
[10]刘莉,王承民,侯昀,等.配网并联电容器优化分组问题研究[J].电气应用,2005,24(12):39-42.
[11]李秀文,荣建,刘小明,等.快速路分、合流影响区交通特性及通行能力研究[J].公路交通科技,2006,23(1):101-104.
[12] Saaty T, Vargas L. Models, Methods, Concepts&Applications of the Analytic Hierarchy Process[M]. 2版. Springer, NewYork, 2012.