CN115131966A - A method for identifying key nodes in road network considering the operation characteristics of intersections - Google Patents
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Abstract
Description
技术领域technical field
本发明公开了一种考虑交叉口运行特性的路网关键节点识别方法，属于智能交通技术领域。The invention discloses a road network key node identification method considering the operation characteristics of the intersection, and belongs to the technical field of intelligent transportation.
背景技术Background technique
在城市交通系统中，由于交通出行的分散性和潮汐性、交通需求分布的不均匀性、供需资源的不匹配性等内外部因素，城市路网中不同的交叉口往往具有不同的重要性。若随机面向部分非关键节点采用交通管控优化措施，无法在网络层面实现交通运行效果有效改善；若面向路网某些关键节点进行针对性地交通管控优化，如交通需求管理、增设车道、增加通行权等，通常可以提升网络全局交通流的运行效率。与此同时，关键节点的识别为拥堵溯源、瓶颈路段挖掘等研究提供理论支撑。因此，作为影响城市交通运行效率的重要因素之一，城市路网关键节点的识别具有重要的理论价值和现实意义。In the urban traffic system, due to internal and external factors such as the dispersion and tidal nature of traffic travel, the uneven distribution of traffic demand, and the mismatch of supply and demand resources, different intersections in the urban road network often have different importance. If the traffic control optimization measures are randomly adopted for some non-critical nodes, the traffic operation effect cannot be effectively improved at the network level. It can usually improve the operation efficiency of the global traffic flow of the network. At the same time, the identification of key nodes provides theoretical support for researches such as congestion tracing and bottleneck road mining. Therefore, as one of the important factors affecting the efficiency of urban traffic operation, the identification of key nodes in urban road network has important theoretical value and practical significance.
当前，随着大数据、移动互联等新一代信息技术的发展，交通信息的采集方式也在发生日新月异的变化。交叉口车辆检测可以提供该交叉口通行车辆的车牌号、检测时间、通行车道等信息，为路网关键节点的识别提供了数据基础。At present, with the development of new-generation information technologies such as big data and mobile Internet, the collection methods of traffic information are also changing rapidly. Intersection vehicle detection can provide information such as the license plate number, detection time, and traffic lane of vehicles passing at the intersection, which provides a data basis for the identification of key nodes in the road network.
目前路网关键节点的识别方法主要基于复杂网络理论，将城市路网抽象为节点和边的集合，并通过网络静态拓扑结构，实现路网关键点边的识别。同时，部分研究基于网络渗流理论，通过网络性能相变过程识别路网关键节点。此外，少量研究基于网络可靠性评价指标，将对交通网络可靠性影响最大的节点定义为关键节点。但是，上述方法均缺乏考虑网络交通流的运行特性，网络静态拓扑结构并非影响节点关键性的唯一因素，路网关键节点的识别应结合交叉口多维运行特性，如动态交通流特性、信号控制特性等进行综合考量。At present, the identification method of key nodes in road network is mainly based on complex network theory, which abstracts the urban road network into a collection of nodes and edges, and realizes the identification of key points and edges in the road network through the static topology of the network. At the same time, some studies are based on the network seepage theory, and identify the key nodes of the road network through the phase transition process of the network performance. In addition, a few studies have defined the nodes that will have the greatest impact on the reliability of the transportation network as key nodes based on network reliability evaluation indicators. However, all of the above methods lack consideration of the operational characteristics of network traffic flow. The static topology of the network is not the only factor that affects the criticality of nodes. The identification of key nodes in the road network should be combined with the multi-dimensional operational characteristics of intersections, such as dynamic traffic flow characteristics and signal control characteristics. etc. for comprehensive consideration.
因此，本方法综合考虑交叉口多维度的运行特性，包括：静态拓扑特性、动态交通流特性、信号控制特性、供需水平时变特性等，通过客观加权评价方法建立节点关键性的量化评价模型，从而实现路网关键节点的识别。Therefore, this method comprehensively considers the multi-dimensional operation characteristics of the intersection, including: static topology characteristics, dynamic traffic flow characteristics, signal control characteristics, time-varying characteristics of supply and demand levels, etc. In order to realize the identification of key nodes in the road network.
发明内容SUMMARY OF THE INVENTION
1.发明目的1. Purpose of the invention
本发明面向城市道路网络，基于交叉口检测数据解析不同维度的运行特性，结合客观加权评价方法，建立节点关键性的量化评价模型，提出一种考虑交叉口运行特性的路网关键节点识别方法，实现城市道路网络中关键节点的识别。The invention faces the urban road network, analyzes the operation characteristics of different dimensions based on the intersection detection data, combines the objective weighted evaluation method, establishes a quantitative evaluation model of node criticality, and proposes a road network key node identification method considering the operation characteristics of the intersection. Realize the identification of key nodes in the urban road network.
2.本发明所采用的技术方案2. The technical solution adopted in the present invention
本发明提出的考虑交叉口运行特性的路网关键节点识别方法，可以通过以下步骤实现：The method for identifying key nodes in the road network that considers the operating characteristics of the intersection proposed by the present invention can be implemented through the following steps:
(1)解析交叉口静态拓扑特性。将城市路网抽象为复杂网络，计算不同交叉口在静态拓扑结构方面的特性。(1) Analyze the static topology characteristics of the intersection. The urban road network is abstracted into a complex network, and the characteristics of different intersections in terms of static topology are calculated.
(2)解析交叉口动态交通流特性。基于交叉口检测数据，计算不同交叉口在交通流参数方面的特性。(2) Analyze the dynamic traffic flow characteristics of the intersection. Based on the intersection detection data, the characteristics of different intersections in terms of traffic flow parameters are calculated.
(3)解析交叉口信号控制特性。基于交叉口信号控制方案，计算不同交叉口在信号控制参数方面的特性。(3) Analyze the signal control characteristics of the intersection. Based on the intersection signal control scheme, the characteristics of different intersections in terms of signal control parameters are calculated.
(4)解析交叉口供需水平时变特性。将研究时段切割，计算不同交叉口供需水平随时间的波动特性。(4) Analyze the time-varying characteristics of the supply and demand level of the intersection. The study period is cut to calculate the fluctuation characteristics of supply and demand levels at different intersections over time.
(5)客观加权评价。基于客观评价方法进行参数加权，综合分析交叉口不同运行特性在网络层面对节点关键性的影响。(5) Objective weighted evaluation. Based on the objective evaluation method, the parameters are weighted, and the influence of different operation characteristics of the intersection on the criticality of the node at the network level is comprehensively analyzed.
(6)建立节点关键性量化评价模型。基于量化评价模型，实现路网关键节点识别。(6) Establish a quantitative evaluation model of node criticality. Based on the quantitative evaluation model, the identification of key nodes in the road network is realized.
(7)关键节点地图匹配。通过关键节点ID实现地图匹配，分析关键节点的空间分布特征。(7) Key node map matching. Map matching is achieved through key node IDs, and the spatial distribution characteristics of key nodes are analyzed.
所述步骤(1)具体为：将城市路网抽象为复杂网络G＝(V,E)，计算节点度与节点介数中心性表征节点的静态拓扑特性。节点度反映了该节点的局部影响能力，节点介数中心性反映了节点在静态网络结构中的全局关联能力。交叉口i的节点度D(i)和节点介数值B(i)的计算方式为The step (1) is as follows: abstracting the urban road network into a complex network G=(V, E), and calculating the node degree and node betweenness centrality to represent the static topology characteristics of the nodes. The node degree reflects the local influence ability of the node, and the node betweenness centrality reflects the global association ability of the node in the static network structure. The node degree D(i) and the node betweenness value B(i) of intersection i are calculated as
其中，Γi表示交叉口i的邻接交叉口集合，ρij＝1表示交叉口i与其邻接交叉口j相连接，否则，ρij＝0，Nuw表示连接任意两个不相邻交叉口u和w的最短路径数量，Nuw(j)表示交叉口u和交叉口w之间的最短路径中经过交叉口i的最短路径数量。Among them, Γ i represents the adjacent intersection set of intersection i, ρ ij =1 indicates that intersection i and its adjacent intersection j are connected, otherwise, ρ ij =0, N uw indicates that any two non-adjacent intersections u are connected and the number of shortest paths of w, Nuw (j) represents the number of shortest paths passing through intersection i among the shortest paths between intersection u and intersection w.
所述步骤(2)具体为：基于交叉口检测数据，计算交叉口交通量和交叉口平均车速表征节点的动态交通流特性。交叉口交通量反映了交通出行主体对于节点的交通需求，交叉口平均车速反映了节点的车流通行时间。交叉口i的交通量N(i)和平均车速V(i)的计算方式为The step (2) is specifically: based on the intersection detection data, calculating the intersection traffic volume and the intersection average vehicle speed to characterize the dynamic traffic flow characteristics of the node. The traffic volume at the intersection reflects the traffic demand of the traffic travel subjects for the node, and the average speed of the intersection reflects the traffic flow time of the node. The traffic volume N(i) and the average vehicle speed V(i) at intersection i are calculated as
N(i)＝∑en(e) (3)N(i)=∑ e n(e) (3)
其中，n(e)表示进口道e的交通量，θ表示交叉口i的进口道与出口道数量之和，v(a)表示交叉口i各进口道、出口道的车辆平均车速。Among them, n(e) represents the traffic volume of entrance e, θ represents the sum of the number of entrances and exits of intersection i, and v(a) represents the average vehicle speed of each entrance and exit of intersection i.
所述步骤(3)具体为：基于交叉口信号控制方案，计算交叉口饱和度表征节点的信号控制特性。饱和度是交叉口信号控制的重要参数，反映了节点的交通供需情况。交叉口i的饱和度α(i)的计算方式为The step (3) is specifically: based on the signal control scheme of the intersection, calculating the signal control characteristic of the node representing the saturation degree of the intersection. Saturation is an important parameter in intersection signal control, reflecting the traffic supply and demand of nodes. The saturation α(i) of intersection i is calculated as
其中，Q表示交叉口i的关键车道流量，λ表示此车道所对应的绿信比，S表示此车道所对应的饱和流率。Among them, Q represents the critical lane flow at intersection i, λ represents the green signal ratio corresponding to this lane, and S represents the saturated flow rate corresponding to this lane.
所述步骤(4)具体为：将研究时段切割，计算不同时段间的交叉口饱和度标准差表征节点供需水平时变特性。交叉口饱和度标准差反映了节点随时间变化的交通供需波动，其计算方式为The step (4) is specifically as follows: cutting the research period and calculating the standard deviation of the intersection saturation between different periods to represent the time-varying characteristics of the supply and demand level of the node. The standard deviation of intersection saturation reflects the fluctuation of traffic supply and demand at nodes over time, and is calculated as
其中，n表示样本总数，xt表示交叉口i的饱和度序列，μ表示饱和度样本均值。where n represents the total number of samples, x t represents the saturation sequence of intersection i, and μ represents the saturation sample mean.
所述步骤(5)具体为：基于客观评价方法——CRITIC方法，分析交叉口不同运行特性间的变异性和相关性，其中，变异性以标准差的形式表征，相关性以相关系数的形式表征。最终，获取交叉口不同运行特性所呈现的客观信息量，并依此进行参数加权，综合分析不同运行特性对节点关键性的影响。此步骤中，信息量Cn及客观权重ωn的计算方式为The step (5) is specifically: based on the objective evaluation method - the CRITIC method, analyze the variability and correlation between different operating characteristics of the intersection, wherein the variability is represented in the form of standard deviation, and the correlation is in the form of correlation coefficient. characterization. Finally, the objective information presented by different operating characteristics of the intersection is obtained, and the parameters are weighted accordingly, and the impact of different operating characteristics on the criticality of the node is comprehensively analyzed. In this step, the calculation method of the information amount C n and the objective weight ω n is:
其中，Sn为运行特性n的标准差。rmn表示运行特性m和n之间的相关系数。当信息量Cn越大，运行特性n在整个评价指标体系中的作用越大，其权重就越高。Among them, Sn is the standard deviation of the running characteristic n . r mn represents the correlation coefficient between the operating characteristics m and n. When the amount of information C n is larger, the function of the operation characteristic n in the whole evaluation index system is larger, and its weight is higher.
所述步骤(6)具体为：建立节点关键性量化评价模型为The step (6) is specifically as follows: establishing a quantitative evaluation model of node criticality as follows:
Ki＝∑ωn·Fi (9)K i =∑ω n ·Fi ( 9)
其中，Fi为交叉口不同运行特性，包括D(i)，B(i)，N(i)，V(i)，α(i)，σ(i)，并基于此量化评价模型，实现路网关键节点识别。Among them, F i is the different running characteristics of the intersection, including D(i), B(i), N(i), V(i), α(i), σ(i). Based on this quantitative evaluation model, the realization of Identification of key nodes in the road network.
所述步骤(7)具体为：基于上述量化评价模型识别关键节点，并通过关键节点ID实现地图匹配，分析关键节点的空间分布特征。The step (7) is specifically: identifying key nodes based on the above-mentioned quantitative evaluation model, implementing map matching through key node IDs, and analyzing the spatial distribution characteristics of key nodes.
3.本发明所产生的技术效果3. Technical effect produced by the present invention
本发明基于交叉口检测数据解析不同维度的运行特性，结合客观加权评价方法，建立节点关键性的量化评价模型，提出一种考虑交叉口运行特性的路网关键节点识别方法，实现城市道路网络中关键节点的识别。本发明具有以下优点：The invention analyzes the operation characteristics of different dimensions based on the intersection detection data, and combines the objective weighted evaluation method to establish a quantitative evaluation model of node criticality, and proposes a road network key node identification method considering the intersection operation characteristics. Identification of key nodes. The present invention has the following advantages:
(1)本发明综合分析了交叉口在不同维度的运行特性，并将不同特性融合至节点关键性量化评价模型中，具有识别精度高、效率快、可应用和可推广性强等优点；(1) The present invention comprehensively analyzes the operation characteristics of the intersection in different dimensions, and integrates the different characteristics into the node criticality quantitative evaluation model, which has the advantages of high recognition accuracy, fast efficiency, strong applicability and generalizability;
(2)本发明为面向城市路网关键节点的信号控制优化提供了理论依据；(2) The present invention provides a theoretical basis for signal control optimization for key nodes of urban road network;
(3)本发明为交通拥堵溯源开拓了研究思路。(3) The present invention develops a research idea for tracing the source of traffic congestion.
4.附图说明4. Description of drawings
此处所说明的附图用来提供对本申请的进一步理解，构成本申请的一部分，本申请的示意性实施例及其说明用于解释本申请，并不构成对本申请的不当限定。在附图中：The drawings described herein are used to provide further understanding of the present application and constitute a part of the present application. The schematic embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation of the present application. In the attached image:
图1为本发明的方法流程图。FIG. 1 is a flow chart of the method of the present invention.
图2为验证数据覆盖范围空间分布示意图。Figure 2 is a schematic diagram of the spatial distribution of verification data coverage.
图3为各交叉口节点度分布示意图。Figure 3 is a schematic diagram of the degree distribution of each intersection node.
图4为各交叉口节点介数值分布示意图。Figure 4 is a schematic diagram of the distribution of betweenness values of nodes at each intersection.
图5为各交叉口交通量分布示意图。Figure 5 is a schematic diagram of the traffic volume distribution at each intersection.
图6为各交叉口平均车速分布示意图。FIG. 6 is a schematic diagram of the average vehicle speed distribution at each intersection.
图7为各交叉口饱和度分布示意图。FIG. 7 is a schematic diagram of the distribution of saturation at each intersection.
图8为各交叉口饱和度标准差分布示意图。FIG. 8 is a schematic diagram of the distribution of the standard deviation of saturation at each intersection.
图9为交叉口不同运行特性客观权重。Figure 9 shows the objective weights of different operating characteristics of the intersection.
图10为前10位关键节点ID。Figure 10 shows the top 10 key node IDs.
图11为关键节点空间分布示意图。Figure 11 is a schematic diagram of the spatial distribution of key nodes.
5.具体实施方式5. Specific implementation
下面结合附图和实施实例对本发明进行详细说明，使得本领域技术人员参照说明书能够据以实施：The present invention will be described in detail below in conjunction with the accompanying drawings and implementation examples, so that those skilled in the art can implement it with reference to the description:
本发明提出的考虑交叉口运行特性的路网关键节点识别方法可以通过以下步骤来实现：The method for identifying key nodes in the road network that considers the operating characteristics of the intersection proposed by the present invention can be implemented through the following steps:
(1)解析交叉口静态拓扑特性。将城市路网抽象为复杂网络，计算不同交叉口在静态拓扑结构方面的特性。(1) Analyze the static topology characteristics of the intersection. The urban road network is abstracted into a complex network, and the characteristics of different intersections in terms of static topology are calculated.
(2)解析交叉口动态交通流特性。基于交叉口检测数据，计算不同交叉口在交通流参数方面的特性。(2) Analyze the dynamic traffic flow characteristics of the intersection. Based on the intersection detection data, the characteristics of different intersections in terms of traffic flow parameters are calculated.
(3)解析交叉口信号控制特性。基于交叉口信号控制方案，计算不同交叉口在信号控制参数方面的特性。(3) Analyze the signal control characteristics of the intersection. Based on the intersection signal control scheme, the characteristics of different intersections in terms of signal control parameters are calculated.
(4)解析交叉口供需水平时变特性。将研究时段切割，计算不同交叉口供需水平随时间的波动特性。(4) Analyze the time-varying characteristics of the supply and demand level of the intersection. The study period is cut to calculate the fluctuation characteristics of supply and demand levels at different intersections over time.
(5)客观加权评价。基于客观评价方法进行参数加权，综合分析交叉口不同运行特性在网络层面对节点关键性的影响。(5) Objective weighted evaluation. Based on the objective evaluation method, the parameters are weighted, and the influence of different operation characteristics of the intersection on the criticality of the node at the network level is comprehensively analyzed.
(6)建立节点关键性量化评价模型。基于量化评价模型，实现路网关键节点识别。(6) Establish a quantitative evaluation model of node criticality. Based on the quantitative evaluation model, the identification of key nodes in the road network is realized.
(7)关键节点地图匹配。通过关键节点ID实现地图匹配，分析关键节点的空间分布特征。(7) Key node map matching. Map matching is achieved through key node IDs, and the spatial distribution characteristics of key nodes are analyzed.
本实施例选用河北省保定市中心城区的交叉口检测数据集作为验证数据，覆盖120余个交叉口和200余条路段，具体空间分布如图2所示。其中，研究路段涵盖多种道路等级，包括：主干路、次干路、支路等。不同道路具有不同车道数，以双向四车道和双向六车道最为普遍。部分交叉口存在展宽现象。In this embodiment, the intersection detection data set in the central urban area of Baoding, Hebei Province is selected as the verification data, covering more than 120 intersections and more than 200 road sections, and the specific spatial distribution is shown in Figure 2. Among them, the research section covers a variety of road grades, including: arterial road, secondary arterial road, branch road, etc. Different roads have different numbers of lanes, two-way four-lane and two-way six-lane are the most common. There is a widening phenomenon at some intersections.
第(1)步：解析交叉口静态拓扑特性。Step (1): Analyze the static topology characteristics of the intersection.
通过式(1)和式(2)，获取研究路网中各交叉口节点度和节点介数值的分布，分别如图3、图4所示。Through formula (1) and formula (2), the distribution of node degree and node betweenness value of each intersection in the research road network is obtained, as shown in Figure 3 and Figure 4, respectively.
第(2)步：解析交叉口动态交通流特性。Step (2): Analyze the dynamic traffic flow characteristics of the intersection.
通过式(3)和式(4)，获取研究路网中各交叉口交通量和平均车速的分布，分别如图5、图 6所示。Through equations (3) and (4), the distribution of traffic volume and average vehicle speed at each intersection in the research road network is obtained, as shown in Figure 5 and Figure 6, respectively.
第(3)步：解析交叉口信号控制特性。Step (3): Analyze the signal control characteristics of the intersection.
通过式(5)，获取研究路网中各交叉口饱和度的分布，如图7所示。Through formula (5), the distribution of saturation of each intersection in the research road network is obtained, as shown in Figure 7.
第(4)步：解析交叉口供需水平时变特性。Step (4): Analyze the time-varying characteristics of the level of supply and demand at the intersection.
通过式(6)，获取研究路网中各交叉口饱和度标准差的分布，如图8所示。By formula (6), the distribution of the standard deviation of the saturation of each intersection in the research road network is obtained, as shown in Figure 8.
第(5)步：客观加权评价。Step (5): Objective weighted evaluation.
基于客观评价法——CRITIC法，即式(7)和式(8)，依据不同运行特性对节点关键性影响水平的不同，为研究路网中交叉口不同运行特性赋以不同权重。经计算得到的交叉口不同运行特性客观权重如图9所示。Based on the objective evaluation method - CRITIC method, namely equations (7) and (8), according to the different levels of influence of different operating characteristics on the criticality of nodes, different weights are assigned to different operating characteristics of intersections in the research road network. The calculated objective weights of different running characteristics of the intersection are shown in Figure 9.
第(6)步：建立节点关键性量化评价模型。Step (6): Establish a quantitative evaluation model of node criticality.
经计算，在此研究路网中，所建立的节点关键性量化评价模型为After calculation, in this research road network, the established node criticality quantitative evaluation model is:
Ki＝0.13D(i)+0.15B(i)+0.18N(i)+0.16V(i)+0.23α(i)+0.16σ(i) (10)K i =0.13D(i)+0.15B(i)+0.18N(i)+0.16V(i)+0.23α(i)+0.16σ(i) (10)
第(7)步：关键节点地图匹配。Step (7): key node map matching.
依据第(6)步中的节点关键性量化评价模型，获取研究路网中各节点的关键性排序，其中前10位关键节点ID如图10所示，其空间分布如图11所示。According to the node criticality quantitative evaluation model in step (6), the criticality ranking of each node in the research road network is obtained. The top 10 key node IDs are shown in Figure 10, and their spatial distribution is shown in Figure 11.
上述实例为本发明较佳的实施方式，但是本发明的实施方式并不受上述实施例的限制，其他的任何未背离本发明的精神实质与原理下所作的改变、修饰、替代、组合、简化，均应为等效的置换方式，都包含在本发明的保护范围之内。The above examples are preferred embodiments of the present invention, but the embodiments of the present invention are not limited by the above examples, and any other changes, modifications, substitutions, combinations, and simplifications made without departing from the spirit and principle of the present invention , all should be equivalent replacement modes, and all are included in the protection scope of the present invention.
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| CN115878737A (en) * | 2022-10-26 | 2023-03-31 | 中国电子科技集团公司第五十四研究所 | Road network data-based intersection extraction and topological structure description method |
| CN116090268A (en) * | 2023-04-12 | 2023-05-09 | 四川省交通勘察设计研究院有限公司 | Method, device, equipment and medium for identifying junction node of highway traffic network |
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| CN115878737A (en) * | 2022-10-26 | 2023-03-31 | 中国电子科技集团公司第五十四研究所 | Road network data-based intersection extraction and topological structure description method |
| CN115878737B (en) * | 2022-10-26 | 2023-09-01 | 中国电子科技集团公司第五十四研究所 | Intersection extraction and topology structure description method based on road network data |
| CN116090268A (en) * | 2023-04-12 | 2023-05-09 | 四川省交通勘察设计研究院有限公司 | Method, device, equipment and medium for identifying junction node of highway traffic network |
| CN116090268B (en) * | 2023-04-12 | 2023-07-14 | 四川省交通勘察设计研究院有限公司 | Method, device, equipment and medium for identifying junction node of highway traffic network |
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