CN109345434B - Method for evaluating design safety of external roads in open type community - Google Patents

Abstract

The invention discloses a method for safety evaluation of road design inside and outside an open community, comprising the following steps: (1) division of investigation areas and data collection; (2) screening of research objects; (3) road network shape division and discrimination; ( 4) Construction of traffic safety analysis model; (5) Traffic safety evaluation. The beneficial effects of the invention are as follows: by screening the areas with similar road network characteristics and land use characteristics as open residential areas as research objects, the full Bayesian spatial hierarchical model is used to study the influence of road design on residential areas with different road network forms. , on the basis of the random error term, a random effect term that considers the spatial correlation of cells is introduced, and the spatial convergence effect of cells is considered. In addition, the model quantitatively analyzes and classifies the traffic safety level after the community opening, which provides a scientific and effective method for the traffic safety risk identification and traffic safety level evaluation of the community opening.

Description

A method for safety evaluation of road design inside and outside open community

technical field

The invention relates to the technical field of road traffic, in particular to a method for safety evaluation of road design inside and outside an open community.

Background technique

With the rapid development of my country's national economy and the acceleration of urbanization, the problem of traffic congestion in some cities is becoming more and more serious. The unreasonable structure of my country's urban traffic network is the main reason that this problem cannot be effectively solved. For a long time, due to the limitation of planning thinking and management system, there are many large closed communities in our cities. These communities hinder the formation of urban microcirculation road network to a certain extent, cut urban traffic, and increase the pressure on urban road network. It is the key to solve the traffic congestion on the main roads of the city, promote the residential block system and gradually open the completed residential quarters and unit compounds. The biggest problem faced in the process of implementing the open community is how to ensure the road traffic safety of the open community.

Different from the mature research foundation of open block road network safety planning in foreign countries, the concept of open block is still in the promotion stage in my country. Whether in the field of scientific research or patent application, research based on open communities often uses topology theory and traffic flow theory to analyze road network reliability, accessibility, and traffic congestion. In terms of road network safety evaluation, especially However, there is still a lack of research involving the safety evaluation of road design inside and outside open communities. Aiming at the contradiction between actual social demand and insufficient theoretical research, the present invention proposes a method for safety evaluation of road design inside and outside an open community.

SUMMARY OF THE INVENTION

In order to solve the above-mentioned existing problems, the present invention provides a method for safety evaluation of road design inside and outside an open community, which can quantitatively analyze the safety level of road design inside and outside an open community, and classify its traffic safety level into grades. In order to achieve this purpose, the present invention provides a method for safety evaluation of road design inside and outside an open community, comprising the following steps:

(1) Division of the survey area and data collection: The main road and the secondary road are used as the boundary to divide the area, and the area with an area greater ^than 0.5km2 is selected as the survey area, and the main road, secondary road and branch road are used as the roads in the survey area. The edges of the network, road intersections and end points of dead ends are used as nodes for data collection, including the proportion of residential land pr , the density of road network _dr , the _proportion of major roads P _A , the proportion of secondary roads P _S , and the number of edges in the network E , the number of nodes N, the degree k _n of the node n, the distance d _ij between the nodes i and j, the number of the shortest paths between the nodes k _ij , the degree of connection of the road network c, the speed limit v _L of the road section, the length of the road section l, the external road strip of the community number C _E , number of accidents A, traffic volume q;

(2) Screening of research objects: Introduce screening indicators, and select the survey area that meets the proportion of residential land greater than 25%, the road network density is 8-12km/km ² , and the degree of connection is greater than 1.6 as the research object, that is, the traffic safety analysis area. And use the data obtained in (1) to calculate the road network characteristic variables of each traffic safety analysis area and its adjacent survey areas, including the number of shortest paths k _inj between nodes i and j crossing node n, and the betweenness centrality B _n , close to centrality C _n , grid coefficient M;

(3) Road network morphology division and discrimination: the main road proportion P _A , the secondary road proportion P _S , the betweenness centrality B _n , the closeness centrality C _n , and the grid coefficient M are used as clustering variables, and K-means is used to cluster The class method divides the road network morphology of all traffic safety analysis areas and their adjacent survey areas into g classes, denoted as R _f (f=1,2,3,...,g). According to the clustering results, the road network shape is determined by Bayesian discriminant analysis. The network shape with the highest _{discriminant score} is the road network shape in the area. Constant term, s _k represents the clustering variable coefficient, X _k represents the clustering variable, and the corresponding discriminant function is:

(4) Evaluation model selection and parameter calibration: The accident rate of the traffic analysis area is used as the dependent variable, and the full Bayesian spatial hierarchical model is used for traffic safety analysis, where I represents the total number of survey areas adjacent to the traffic analysis area, N _f (f=1,2,3,...,g) represents the number of R _f -type survey areas adjacent to the traffic analysis area, C _E represents the number of external roads, K represents the set of road segments in the survey area, and _VL represents the traffic Analyze the total average speed limit difference between the residential area and the adjacent survey area, α is a constant term, ε _i is a random error term, u _i is a random effect term of spatial correlation, β _n is a regression vector coefficient, and for different types of roads The traffic analysis community in the form of network establishes the traffic safety analysis model respectively;

个单位作为上下控制限，将小区内外部道路设计的交通安全水平划分为四级：Ⅰ，Ⅱ，Ⅲ，Ⅳ。(5) Traffic safety evaluation: Divide the road network shape of the community, use the model of the corresponding road network shape to quantitatively analyze the traffic safety level after the community is opened, and obtain the total distribution of expected accident rates in all communities. According to the characteristics of the model , take the expected accident rate μ as the center line, and translate up and down respectively

Each unit is used as the upper and lower control limits, and the traffic safety level of road design inside and outside the community is divided into four levels: Ⅰ, Ⅱ, Ⅲ, Ⅳ.

In a further improvement of the present invention, the degree k _n of node n in step (1) refers to the number of edges adjacent to node n in the survey area, and the degree of connectivity refers to the ratio of the number of road connections to the number of road nodes in the survey area.

The present invention is a method for the safety evaluation of road design inside and outside an open community. By selecting an area with similar land use properties to the existing closed community as the research object, the full Bayesian spatial hierarchical model is used to study the effect of road design on different road networks. On the basis of the random error term, a random effect term that considers the spatial correlation of the cells is introduced, and the spatial convergence effect of open cells is considered. In addition, the model quantitatively analyzes and classifies the traffic safety level of the existing closed community after opening, which provides a scientific and effective method for the traffic safety risk identification and traffic safety level evaluation of the open community.

Description of drawings

FIG. 1 is a schematic diagram of the classification of traffic safety analysis results and safety evaluation levels according to the present invention.

FIG. 2 is a schematic flow chart of the method of the present invention.

Detailed ways

The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments:

The invention provides a method for safety evaluation of road design inside and outside an open community, which can quantitatively analyze the safety level of road design inside and outside the open community, and classify its traffic safety level.

As shown in Figures 1 and 2, a method for determining the impact of a fixed-point speedometer on an expressway on the number of traffic accidents includes the following steps:

(1) Division of survey areas and data collection: through the investigation and collection of road network information and land use information by the local traffic department and the traffic police station, the main road and the secondary road are used as the boundary to divide the area, and the area with an area greater than 0.5km ² is selected. as an investigation area. The main roads, secondary roads and branch roads are used as the edges of the road network in the survey area, and the road intersections and the end points of the dead ends are used as nodes for data collection, including the proportion of residential land _{pr , the density of road network dr ,} and the proportion of main roads P _A , the proportion of secondary roads P _S , the number of edges of the network E, the number of nodes N, the degree k _n of node n, the distance d _ij between nodes i and j, the number of shortest paths between nodes k _ij , the degree of road network connection c, The speed limit v _L of the road section, the length of the road section l, the number of external roads C _E of the community, the number of accidents A, and the traffic volume q.

(2) Screening of research objects: Introduce screening indicators, and select the survey area that meets the proportion of residential land is greater than 25%, the road network density is 8-12km/km ² , and the degree of connection is greater than 1.6 as the research object, that is, the traffic safety analysis area. And use the data obtained in (1) to calculate the road network characteristic variables of each traffic safety analysis area and its adjacent survey areas, including the number of shortest paths k _inj between nodes i and j crossing node n, and the betweenness centrality B _n , close to centrality C _n , grid coefficient M.

(3) Road network morphology division and discrimination: the main road proportion P _A , the secondary road proportion P _S , the betweenness centrality B _n , the closeness centrality C _n , and the grid coefficient M are used as clustering variables, and K-means is used to cluster The class method divides the road network morphology of all traffic safety analysis areas and their adjacent survey areas into g classes, denoted as R _f (f=1,2,3,...,g). According to the clustering results, the road network shape is determined by Bayesian discriminant analysis. The network shape with the highest _{discriminant score} is the road network shape in the area. Constant term, s _k represents the clustering variable coefficient, X _k represents the clustering variable, and the corresponding discriminant function is:

(4) Evaluation model selection and parameter calibration: With the accident rate of the traffic analysis area as the dependent variable, a full Bayesian spatial hierarchical model is used to analyze traffic safety. I represents the total number of survey areas adjacent to the traffic analysis area, N _f (f=1, 2, 3, ..., g) represents the number of R _f category survey areas adjacent to the traffic analysis area, C _E represents the external access The number of bars, K represents the road segment set in the survey area, _VL represents the total average speed limit difference between the traffic analysis area and the adjacent survey area, α is a constant term, ε _i represents a random error term, and u _i represents the randomness of spatial correlation. Effect term, β _n is the regression vector coefficient. Traffic safety analysis models are established for traffic analysis communities with different types of road network forms.

个单位作为上下控制限，将小区内外部道路设计的交通安全水平划分为四级：Ⅰ，Ⅱ，Ⅲ，Ⅳ。(5) Traffic safety evaluation: Divide the road network shape of the community, use the model of the corresponding road network shape to quantitatively analyze the traffic safety level after the community is opened, and obtain the total distribution of expected accident rates in all communities. According to the characteristics of the model, take the expected accident rate μ as the center line, and translate upward and downward respectively

Each unit is used as the upper and lower control limits, and the traffic safety level of road design inside and outside the community is divided into four levels: Ⅰ, Ⅱ, Ⅲ, Ⅳ.

The present invention is described below with specific examples.

1) Division of survey area and data collection: The local traffic department and the traffic police bureau investigate and collect road network information and land use information, take the main road and the secondary road as the boundary to divide the area, and select the area with an area greater ^than 0.5km2 as the area. The survey area, the sample number of each survey area is _zi . The main road, secondary road and branch road are used as the edge of the road network in the survey area, and the road intersection and the end point of the dead end are used as nodes to collect data. The relevant data of each survey area are shown in Table 1-1.

Table 1-1 Statistics of data collection in the survey area

2) Screening of research objects: Introduce screening indicators, and select the survey areas that satisfy the proportion of residential land greater than 25%, the road network density is 8-12km/km ² , and the ratio of the number of road connections to the number of road nodes is greater than 1.6 as the research object. That is, the traffic safety analysis area.

3) Division of road network morphology: the main road proportion P _A , the secondary road proportion P _S , the betweenness centrality B _n , the closeness centrality C _n , and the grid coefficient M are used as clustering variables, and the K-means clustering method is used. The road network morphology of all traffic safety analysis areas and their adjacent survey areas is divided into g categories, denoted as R _f (f = 1, 2, 3, ..., g). According to the clustering results, the road network shape is determined by Bayesian discriminant analysis, and the network shape with the highest discrimination score is the road network shape in the area.

4) Construction of traffic safety analysis model: Based on the division results of road network forms, count the number of survey areas of various road network forms adjacent to the traffic safety analysis area, and obtain the traffic safety analysis area according to the data in Table 1-1 Table 1-2 of the independent variable data of the traffic safety analysis model, with the accident rate of the traffic analysis area as the dependent variable, and using the data in Table 1-2, the full Bayesian spatial hierarchical model is used to analyze the traffic with different road network forms. The analysis area establishes the traffic safety analysis model respectively.

Table 1-2 Statistical table for the collection of the number of adjacent survey areas in the traffic safety analysis community

个单位作为上下控制限，将小区内外部道路设计的交通安全水平划分为四级：Ⅰ，Ⅱ，Ⅲ，Ⅳ。5) Traffic safety evaluation: Divide the road network shape of the community, use the model corresponding to the road network shape to quantitatively analyze the traffic safety level after opening, and obtain the total distribution of the expected accident rate of the whole community. Take the expected accident rate as the center line, and translate up and down respectively

Each unit is used as the upper and lower control limits, and the traffic safety level of road design inside and outside the community is divided into four levels: Ⅰ, Ⅱ, Ⅲ, Ⅳ.

Table 1-3 Classification of traffic safety levels

The above are only preferred embodiments of the present invention, and are not intended to limit the present invention in any other form, and any modifications or equivalent changes made according to the technical essence of the present invention still fall within the scope of protection of the present invention. .

Claims (2)

1. a method for the safety evaluation of road design inside and outside the open community, is characterized in that, comprises the steps: (1) Division of the survey area and data collection: The main road and the secondary road are used as the boundary to divide the area, and the area with an area greater ^than 0.5km2 is selected as the survey area, and the main road, secondary road and branch road are used as the roads in the survey area. The edges of the network, road intersections and end points of dead ends are used as nodes for data collection, including the proportion of residential land pr , the density of road network _dr , the _proportion of major roads P _A , the proportion of secondary roads P _S , and the number of edges in the network E , the number of nodes N, the degree k _n of the node n, the distance d _ij between the nodes i and j, the number of the shortest paths between the nodes k _ij , the degree of connection of the road network c, the speed limit v _L of the road section, the length of the road section l, the external road strip of the community number C _E , number of accidents A, traffic volume q; (2) Screening of research objects: Introduce screening indicators, and select the survey area that meets the proportion of residential land greater than 25%, the road network density is 8-12km/km ² , and the degree of connection is greater than 1.6 as the research object, that is, the traffic safety analysis area. And use the data obtained in (1) to calculate the road network characteristic variables of each traffic safety analysis area and its adjacent survey areas, including the number of shortest paths k _inj between nodes i and j crossing node n, and the betweenness centrality B _n , close to centrality C _n , grid coefficient M;

(3) Road network morphology division and discrimination: the main road proportion P _A , the secondary road proportion P _S , the betweenness centrality B _n , the closeness centrality C _n , and the grid coefficient M are used as clustering variables, and K-means is used to cluster The class method divides the road network morphology of all traffic safety analysis areas and their adjacent survey areas into g classes, denoted as R _f (f = 1, 2, 3, ..., g), according to the clustering results, through Bayesian The method of discriminant analysis is used to identify the road network shape. The network shape with the highest discriminant score is the road network shape in the area. S _f represents the discriminant score of the f-th type of road network shape, s _o represents a constant term, and s _k represents clustering. Variable coefficient, X _k represents the clustering variable, and the corresponding discriminant function is:

(4) Evaluation model selection and parameter calibration: The accident rate of the traffic analysis area is used as the dependent variable, and the full Bayesian spatial hierarchical model is used for traffic safety analysis, where I represents the total number of survey areas adjacent to the traffic analysis area, N _f (f=1,2,3,...,g) represents the number of R _f -type survey areas adjacent to the traffic analysis area, C _E represents the number of external roads, K represents the set of road segments in the survey area, and _VL represents the traffic Analyze the total average speed limit difference between the residential area and the adjacent survey area, α is a constant term, ε _i is a random error term, u _i is a random effect term of spatial correlation, β _n is a regression vector coefficient, and for different types of roads The traffic analysis community in the form of network establishes the traffic safety analysis model respectively;

(5) Traffic safety evaluation: Divide the road network shape of the community, use the model of the corresponding road network shape to quantitatively analyze the traffic safety level after the community is opened, and obtain the total distribution of expected accident rates in all communities. According to the characteristics of the model , take the expected accident rate μ as the center line, and translate up and down respectively

Each unit is used as the upper and lower control limits, and the traffic safety level of road design inside and outside the community is divided into four levels: Ⅰ, Ⅱ, Ⅲ, Ⅳ. 2. The method for safety evaluation of road design inside and outside an open cell according to claim 1, wherein: the degree k _n of node n in step (1) refers to the area adjacent to node n in the survey area. The number of edges and the degree of connectivity refers to the ratio of the number of road connections to the number of road nodes in the survey area.

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