基于交通冲突技术的无信号控制交叉口安全风险自动评价
发布时间：2018-08-05 16:05
【摘要】：交叉口是道路网的重要组成部分,也是交通事故频发的地点。为提高交叉口的安全管理水平,提出合理的改善方案、比较改善前后的效果,首先需对其进行交通安全评价。相对传统的事故评价法而言,基于交通冲突技术(Traffic Conflict Techniques,TCT)的评价方法具有“大样本、短周期、高信度”的特点,因而备受到研究者青睐。目前我国基于交通冲突技术的交义口安全评价方法中,定性分析多、定量分析较少；人工观测多、冲突的自动识别和采集较少。为此,本文以交通冲突的自动判别和记录为应用背景,建立了无信号控制交叉口危险度评价模型。 借鉴国内外已有的研究成果,论文首先系统的阐述了交通冲突和交通事故之间的关系,探讨了采用交通冲突评价交叉口安全的可行性与合理性。通过分析冲突产生的机理,给出了适用于机器自动识别场合的交通冲突的定义；分析了影响交通冲突严重程度的因素,给出了评价冲突严重程度的思路。 其次,论文利用最长公共子序列算法在处理不同长度的轨迹以及轨迹异值点上的优越性,将传统的最长公共子序列算法由名义序列的相似程度比较拓展至车辆轨迹的相似程度的比较,从而实现典型轨迹模式的提取。提出综合利用碰撞时间和车辆速度的“动态阈值法”判断两条预期轨迹是否为碰撞轨迹,根据两车轨迹的类型完成对潜在冲突的判断和识别。以车辆预测轨迹的条件概率和相应轨迹对应的碰撞时间为自变量,描述交通冲突与交通事故的接近程度；用相互作用的两车速度描述潜在事故的严重程度,建立了衡量交通冲突严重程度的评价模型。将其推广应用至整个交叉口,建立了评价整个交叉口的安全水平的自动分析模型。 最后,采用微观交通流仿真软件VISSIM和数学分析软件Matlab作为仿真工具,以某T型无信号控制交叉口为例,对其实施安全改善措施前、后的安全风险水平进行了比较,对改善措施的有效性进行了评价。研究结果表明该模型可以应用于平面无信号控制交叉口的交通安全自动评价,对于改善交叉口的安全状况具有重要的指导意义。
[Abstract]:Intersection is an important part of road network and also a place where traffic accidents occur frequently. In order to improve the safety management level of intersections, a reasonable improvement scheme is put forward, and the effect before and after improvement is compared. The first step is to evaluate the traffic safety of intersections. Compared with the traditional accident evaluation method, the evaluation method based on traffic conflict technology (Traffic Conflict technique TCT has the characteristics of "large sample, short period, high confidence", so it is favored by researchers. At present, there are more qualitative analysis, less quantitative analysis, more manual observation and less automatic identification and collection of conflicts in the safety evaluation methods based on traffic conflict technology. Therefore, based on the application background of automatic discrimination and recording of traffic conflicts, a risk assessment model for signal-free intersections is established in this paper. Referring to the existing research results at home and abroad, this paper first systematically expounds the relationship between traffic conflicts and traffic accidents, and probes into the feasibility and rationality of using traffic conflicts to evaluate the safety of intersections. By analyzing the mechanism of conflict, the definition of traffic conflict suitable for machine automatic recognition is given, the factors influencing the severity of traffic conflict are analyzed, and the train of thought for evaluating the severity of conflict is given. Secondly, the paper uses the longest common subsequence algorithm to deal with the different length of trajectory and locus outliers. The traditional longest common subsequence algorithm is extended from the similarity comparison of nominal sequences to the comparison of the similarity degree of vehicle trajectories so as to achieve the extraction of typical trajectory patterns. A dynamic threshold method based on collision time and vehicle velocity is proposed to judge whether the two expected tracks are collision tracks, and to judge and identify the potential conflicts according to the type of the two vehicle tracks. The conditional probability of vehicle trajectory prediction and the collision time corresponding to the corresponding trajectory are taken as independent variables to describe the proximity between traffic conflicts and traffic accidents, and the severity of potential accidents is described by the two vehicle velocities that interact with each other. An evaluation model is established to measure the severity of traffic conflict. The automatic analysis model for evaluating the safety level of the whole intersection is established by applying it to the whole intersection. Finally, the microcosmic traffic flow simulation software VISSIM and the mathematical analysis software Matlab are used as simulation tools. Taking a T type unsignalized intersection as an example, the safety risk levels before and after the implementation of safety improvement measures are compared. The effectiveness of the improvement measures is evaluated. The results show that the model can be applied to the automatic evaluation of traffic safety at planar unsignalized intersections, and it is of great significance to improve the safety of intersections.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491
本文编号：2166295
[Abstract]:Intersection is an important part of road network and also a place where traffic accidents occur frequently. In order to improve the safety management level of intersections, a reasonable improvement scheme is put forward, and the effect before and after improvement is compared. The first step is to evaluate the traffic safety of intersections. Compared with the traditional accident evaluation method, the evaluation method based on traffic conflict technology (Traffic Conflict technique TCT has the characteristics of "large sample, short period, high confidence", so it is favored by researchers. At present, there are more qualitative analysis, less quantitative analysis, more manual observation and less automatic identification and collection of conflicts in the safety evaluation methods based on traffic conflict technology. Therefore, based on the application background of automatic discrimination and recording of traffic conflicts, a risk assessment model for signal-free intersections is established in this paper. Referring to the existing research results at home and abroad, this paper first systematically expounds the relationship between traffic conflicts and traffic accidents, and probes into the feasibility and rationality of using traffic conflicts to evaluate the safety of intersections. By analyzing the mechanism of conflict, the definition of traffic conflict suitable for machine automatic recognition is given, the factors influencing the severity of traffic conflict are analyzed, and the train of thought for evaluating the severity of conflict is given. Secondly, the paper uses the longest common subsequence algorithm to deal with the different length of trajectory and locus outliers. The traditional longest common subsequence algorithm is extended from the similarity comparison of nominal sequences to the comparison of the similarity degree of vehicle trajectories so as to achieve the extraction of typical trajectory patterns. A dynamic threshold method based on collision time and vehicle velocity is proposed to judge whether the two expected tracks are collision tracks, and to judge and identify the potential conflicts according to the type of the two vehicle tracks. The conditional probability of vehicle trajectory prediction and the collision time corresponding to the corresponding trajectory are taken as independent variables to describe the proximity between traffic conflicts and traffic accidents, and the severity of potential accidents is described by the two vehicle velocities that interact with each other. An evaluation model is established to measure the severity of traffic conflict. The automatic analysis model for evaluating the safety level of the whole intersection is established by applying it to the whole intersection. Finally, the microcosmic traffic flow simulation software VISSIM and the mathematical analysis software Matlab are used as simulation tools. Taking a T type unsignalized intersection as an example, the safety risk levels before and after the implementation of safety improvement measures are compared. The effectiveness of the improvement measures is evaluated. The results show that the model can be applied to the automatic evaluation of traffic safety at planar unsignalized intersections, and it is of great significance to improve the safety of intersections.
【学位授予单位】：南京理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：U491
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