Roadside unit deployment method and device based on intersection node hierarchical activation mechanism

Abstract

The present invention discloses a method and device for deploying roadside units (RSUs) based on a hierarchical activation mechanism for intersection nodes. The method includes: using traffic time series analysis technology to quantify the flow fluctuation values ​​of each road; screening sub-regions with significant flow fluctuations as priority deployment areas; establishing a weighted graph model, storing intersection location information as node attributes, and storing road type and road flow fluctuations as edge attributes, and identifying intersections where candidate RSUs are deployed as nodes to be activated; calculating edge weights and node weights, setting a threshold to be activated based on the statistical results of the node weights, and obtaining a first-layer set of nodes to be activated based on the node weights and the threshold to be activated; iteratively activating the remaining inactivated nodes to obtain a second-layer set of nodes to be activated; and outputting all nodes to be activated as activated nodes to obtain a final RSU deployment plan. The present invention achieves an optimal balance between the number of RSUs deployed and monitoring coverage, significantly reducing deployment costs.

Description

Technical Field

[0001] The present invention relates to the field of vehicle-road collaboration technology, and in particular to a roadside unit deployment method and device based on a hierarchical activation mechanism of intersection nodes. Background Art

[0002] With the rapid development of urbanization and the national economy, the number of cars on the road continues to rise, and traffic congestion is becoming increasingly serious. Roadside units (RSUs), as infrastructure components that collect and analyze traffic data within a self-organizing vehicle network, are key to achieving smart roads and vehicle-road collaboration. In urban road planning, the high cost of RSUs makes it impossible to deploy them at every intersection. Therefore, a deployment strategy that balances deployment costs and traffic coverage requirements is crucial.

[0003] Traditional deployment strategies often involve evenly placing RSUs at fixed intervals along the road. This approach lacks accurate analysis of actual traffic flow and demand, potentially leading to under- or over-coverage on roads with uneven vehicle density. This can result in too few or too many RSUs, leading to poor cost-effectiveness. Summary of the Invention

[0004] The present invention aims to provide a roadside unit deployment method and device based on a hierarchical activation mechanism of intersection nodes to address the shortcomings of existing methods, improve the coverage and traffic monitoring capabilities of roadside units, minimize the number of deployments, and reduce costs.

[0005] In order to solve the above technical problems, the present invention is implemented through the following technical solutions:

[0006] A roadside unit deployment method based on a hierarchical activation mechanism of intersection nodes, characterized by comprising:

[0007] S1, based on the urban road network structure and vehicle GPS travel trajectory, uses traffic time series analysis technology to quantify the traffic fluctuation value of each road;

[0008] S2, based on the traffic fluctuation values ​​of each road, selecting sub-regions with significant traffic fluctuations as priority deployment areas, and pre-processing the road network data within the priority deployment areas;

[0009] S3: A weighted graph model is established for the pre-processed priority deployment area, where the intersection location information is stored as node attributes, the road type and road traffic fluctuation are stored as edge attributes, and the intersections of the candidate roadside units are identified as nodes to be activated.

[0010] S4, using multi-attribute weighting and node degree to respectively calculate the edge weights and node weights of the weighted graph model, then setting an adaptive threshold to be activated based on the statistical results of the weights of all nodes in the priority deployment area, and determining the partial order relationship between the node weights and the threshold to be activated to obtain a first-layer set of nodes to be activated;

[0011] S5, iteratively activate the remaining inactivated nodes, verify whether they meet the conditions for being directly connected to the nodes to be activated through the neighborhood influence function, and obtain the second layer of nodes to be activated, until all nodes in the priority deployment area are to be activated or can be covered by the nodes to be activated;

[0012] S6: Output all nodes to be activated as activated nodes to obtain the final roadside unit deployment plan.

[0013] An embodiment of the present invention further provides a roadside unit deployment device based on an intersection node hierarchical activation mechanism, comprising:

[0014] The data acquisition unit is used to quantify the traffic fluctuation value of each road using traffic time series analysis technology based on the urban road network structure and vehicle GPS travel trajectory;

[0015] A road network preprocessing unit is used to screen out sub-areas with significant traffic fluctuations as priority deployment areas based on the traffic fluctuation values ​​of each road, and preprocess the road network data in the priority deployment areas;

[0016] The road network topology unit is used to establish a weighted graph model for the pre-processed priority deployment area, store the intersection location information as node attributes, store the road type and road traffic fluctuation as edge attributes, and identify the intersection of the candidate deployment roadside unit as a node to be activated;

[0017] The first layer of to-be-activated units is configured to calculate the edge weights and node weights of the weighted graph model using multi-attribute weighting and node degree, and then set an adaptive to-be-activated threshold based on the statistical results of the weights of all nodes in the priority deployment area. The first layer of to-be-activated node set is determined by determining the partial order relationship between the node weights and the to-be-activated threshold.

[0018] The second layer of to-be-activated units is used to iteratively activate the remaining inactivated nodes. The neighborhood influence function is used to verify whether they meet the conditions for being directly connected to the to-be-activated nodes. This results in a second layer of to-be-activated node sets, which are obtained until all nodes in the priority deployment area are to be activated or can be covered by the to-be-activated nodes.

[0019] The intersection deployment unit is used to output all nodes to be activated as activated nodes to obtain the final roadside unit deployment plan.

[0020] The present invention also provides a roadside unit deployment device based on the intersection node hierarchical activation mechanism, which includes a processor and a memory, wherein the memory stores a computer program, and the computer program can be executed by the processor to implement a roadside unit deployment method based on the intersection node hierarchical activation mechanism as described above.

[0021] The present invention also provides a computer-readable storage medium, which stores computer-readable instructions. When the computer-readable instructions are executed by the processor of the device where the computer-readable storage medium is located, the roadside unit deployment method based on the intersection node hierarchical activation mechanism as described above is implemented.

[0022] In summary, compared with the prior art, the present invention has the following beneficial effects:

[0023] The present invention calculates road traffic fluctuations by analyzing vehicle-mounted GPS trajectory data, selects high-fluctuation areas as priority deployment areas, adopts a weighted graph model and partial order relationship judgment method, introduces adaptive thresholds to be activated and neighborhood influence functions, and deploys roadside units in layers and grades. Specifically, the present invention integrates attributes such as intersection location, road type, and traffic fluctuations into the topology graph, prioritizes the activation of high-value nodes through weight calculation and threshold setting to be activated, and ensures that unactivated nodes can be covered by nodes to be activated, ultimately forming an efficient and low-cost roadside unit deployment solution. The present invention can accurately locate traffic demand hotspots, optimize resource allocation, and adaptively adjust deployment in combination with dynamic traffic data, significantly improving the communication efficiency, coverage capability, and economy of the vehicle-road cooperative system. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 FIG2 is a flow chart of a roadside unit deployment method based on a hierarchical activation mechanism of intersection nodes provided in the first embodiment of the present invention;

[0026] Figure 2 FIG2 is a schematic diagram of a roadside unit deployment method based on a hierarchical activation mechanism of intersection nodes provided in a first embodiment of the present invention;

[0027] Figure 3 FIG2 is a result diagram of a roadside unit deployment method based on a hierarchical activation mechanism of intersection nodes provided by the first embodiment of the present invention;

[0028] Figure 4 Shown is a schematic diagram of a roadside unit deployment device based on an intersection node hierarchical activation mechanism provided by the second embodiment of the present invention. DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0030] In order to better understand the technical solution of the present invention, the embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0031] It should be understood that the embodiments described are only a portion of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative work are within the scope of protection of the present invention.

[0032] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The singular forms "a", "an", "the" and "the" used in the embodiments of the present invention and the appended claims are also intended to include plural forms unless the context clearly indicates otherwise.

[0033] It should be understood that the term "and / or" as used herein is merely a description of the relationship between associated objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Furthermore, the character " / " in this document generally indicates that the associated objects are in an "or" relationship.

[0034] The word "if," as used herein, may be interpreted as "at the time of" or "when" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if (stated condition or event) is detected" may be interpreted as "when it is determined" or "in response to the determination" or "when detecting (stated condition or event)" or "in response to detecting (stated condition or event)," depending on the context.

[0035] The "first" and "second" mentioned in the embodiments are merely used to distinguish similar objects and do not represent a specific ordering of the objects. It is understood that the specific order or precedence of "first" and "second" can be interchanged where appropriate. It should be understood that the objects distinguished by "first" and "second" can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein.

[0036] The present invention is further described in detail below with reference to the accompanying drawings and specific embodiments:

[0037] Example 1

[0038] Embodiment 1 of the present invention provides a roadside unit deployment method based on a hierarchical activation mechanism of intersection nodes, which can be implemented by a roadside unit deployment device based on a hierarchical activation mechanism of intersection nodes (hereinafter referred to as a deployment device), and in particular, executed by one or more processors in the deployment device.

[0039] In this embodiment, the deployment device may be an electronic device equipped with a processor, which carries a computer program of the roadside unit deployment method based on the intersection node hierarchical activation mechanism and the computer program can be executed, such as a computer, a smart phone, a smart tablet, a workstation, etc., which is not limited here.

[0040] like Figure 1 As shown, a roadside unit deployment method based on the intersection node hierarchical activation mechanism includes steps S1 to S6.

[0041] S1, based on the urban road network structure and vehicle GPS travel trajectory, uses traffic time series analysis technology to quantify the traffic fluctuation value of each road.

[0042] like Figure 2 Specifically, the calculation method of the traffic fluctuation value of the road is as follows:

[0043]

[0044]

[0045] in, It's a road Traffic fluctuations, For the The flow rate of a time period, For the road The average flow rate, is the number of time periods in a day, and are the minimum and maximum values ​​of traffic fluctuations on all roads in the area, is the normalized road traffic fluctuation.

[0046] S2: Based on the traffic fluctuation values ​​of each road, select sub-areas with significant traffic fluctuations as priority deployment areas, and pre-process the road network data in the priority deployment areas.

[0047] Specifically, step S2 includes:

[0048] S21, select the area of ​​interest from the real road network as the experimental area.

[0049]

[0050] in, represents the experimental area, Represents each latitude and longitude coordinate point in the road data.

[0051] S22, for each road in the road network data If its geometry and the study area If the road intersects, the road remains in the study area.

[0052]

[0053] Among them, R represents the original road network data set, r is a road in the road network data, is the cropped road network data set.

[0054] S23, integrating the intersections that are too close to each other into one intersection. Specifically, the calculation model for determining whether the intersections are too close is:

[0055]

[0056] in, represents the set of all intersections identified by analyzing the road network, Indicates an intersection and intersections The distance between Represents the minimum distance threshold, which is selected based on the actual deployment scenario and the discreteness of the intersection distribution in the road network. Represents the set of intersections resulting from applying the distance constraint.

[0057] S3, establishes a weighted graph model for the preprocessed priority deployment area, stores the intersection location information as node attributes, and stores the road type and road traffic fluctuation as edge attributes, and identifies the intersection of the candidate deployment roadside unit as a node to be activated.

[0058] Specifically, step S3 includes:

[0059] S31, create an empty weighted undirected graph and an empty set of nodes to be activated A ,in is a set of nodes, where is the set of edges, W is a weight set.

[0060] S32, each node Contains the following properties:

[0061]

[0062] in, Represents the node unique identifier, Represents longitude and latitude coordinates, Represents the node weight.

[0063] S33, each edge Contains the following properties:

[0064]

[0065] in, represents the unique identifier of the edge, Indicates the road type, including main road, first-level road, second-level road, third-level road, etc. Represents the weight of the edge.

[0066] S4, using multi-attribute weighting and node degree to respectively calculate the edge weights and node weights of the weighted graph model, and then setting an adaptive threshold to be activated based on the statistical results of the weights of all nodes in the priority deployment area, and obtaining the first layer of the set of nodes to be activated by judging the partial order relationship between the node weights and the threshold to be activated.

[0067] Specifically, step S4 includes:

[0068] S41, based on road traffic fluctuations and road types, the edge weight is calculated as follows:

[0069]

[0070] in, 、 Represents the adjustment coefficient, which is used to flexibly adjust the relative importance of traffic fluctuations and road types in weight calculation. It is generally set is 7, is 3. is the normalized flow fluctuation, represents the road type weight function. Due to its importance in the transportation network, the weight of the main road is set to 1, the weight of the first-class road is 0.8, the weight of the second-class road is 0.5, and the weight of the third-class road is 0.1.

[0071] S42, after obtaining the edge weight, the formula for calculating the node weight is:

[0072]

[0073] in, deg(v i ) Representation node The degree of the node is the number of edges connected to it. With node The set of connected edges, Represents the sum of the edge weights connected to this node.

[0074] S43: Based on the weights of all nodes in the area, a threshold to be activated is set. The specific calculation method is:

[0075]

[0076] in, is the activation threshold, k For adaptive experience adjustment parameters, is the mean of the node weights, k The parameter is adjusted empirically (e.g., 1, 1.5, 2). The selection of this parameter needs to be determined based on the actual deployment scenario and the degree of discreteness of the weights in the road network. If the distribution of node weights in the road network is relatively dispersed, a larger k value to balance the influence of different nodes; on the contrary, if the weight distribution is relatively concentrated, a smaller k By adjusting k The value can set the activation threshold scientifically and reasonably according to the overall situation of the node weights in the area, providing an important reference for the subsequent deployment decisions of the roadside units.

[0077] S44, traverse the nodes in the sub-region and determine the partial order relationship between the node weight and the threshold to be activated. If , then add the node to the set of nodes to be activated A In the above example, all nodes with a value greater than the threshold to be activated are obtained, which is the first layer of nodes to be activated. .

[0078] S5, iteratively activate the remaining inactivated nodes, and verify whether they meet the conditions of being directly connected to the nodes to be activated through the neighborhood influence function, and obtain the second layer of nodes to be activated, until all nodes in the sub-region are ready for activation or can be covered by the nodes to be activated.

[0079] Specifically, step S5 includes:

[0080] S51, the activation state of the node is determined by the activation indicator function express:

[0081]

[0082] Initialize the node's activation state to 0.

[0083] S52, for all nodes , define its neighbor node set , the set represents All connected nodes:

[0084]

[0085] S53, neighborhood influence function:

[0086]

[0087] S54, each node Satisfy the conditions for activation, or have at least one neighbor node Pending activation.

[0088]

[0089] Where n is the total number of nodes, Aij represents the jth neighbor node of the i-th node in the set of nodes to be activated A. The meaning of the above formula is:

[0090] If for neighbor nodes Each node in , it is satisfied that it has not joined the set of nodes to be activated , and it is the same as the set of nodes to be activated Any node in No direct connection , then the node Set to be activated and added to the collection , obtain the second layer of node set to be activated.

[0091] S55, when all nodes satisfy (node already in the set of nodes to be activated), or and the set of nodes to be activated is connected to a node in Make (node can be covered by the node to be activated), the activation stops.

[0092] S6: Output all nodes to be activated as activated nodes to obtain the final roadside unit deployment plan.

[0093] The final result of the roadside unit deployment is as follows Figure 3 shown. Specifically, Figure 3 Lines of different colors represent roads of different levels. Red edges represent main roads, yellow edges represent first-level roads, green edges represent second-level roads, and blue edges represent third-level roads. Red circles represent activated nodes, i.e., road intersections where roadside units need to be deployed, and white circles represent inactivated nodes.

[0094] The embodiment of the present invention calculates road traffic fluctuations by analyzing vehicle-mounted GPS trajectory data, selects high-fluctuation areas as priority deployment areas, adopts a weighted graph model and partial order relationship judgment method, introduces adaptive thresholds to be activated and neighborhood influence functions, and deploys roadside units in layers and grades. Specifically, the present invention integrates attributes such as intersection location, road type, and traffic fluctuations into the topology graph, prioritizes the activation of high-value nodes through weight calculation and threshold setting to be activated, and ensures that unactivated nodes can be covered by nodes to be activated, ultimately forming an efficient and low-cost roadside unit deployment solution. The present invention can accurately locate traffic demand hotspots, optimize resource allocation, and adaptively adjust deployment in combination with dynamic traffic data, significantly improving the communication efficiency, coverage capability, and economy of the vehicle-road cooperative system.

[0095] Example 2

[0096] like Figure 4 As shown, an embodiment of the present invention provides a roadside unit deployment device based on an intersection node hierarchical activation mechanism, comprising:

[0097] The data acquisition unit 101 is used to quantify the traffic flow fluctuation value of each road using traffic time series analysis technology based on the urban road network structure and the vehicle GPS travel trajectory;

[0098] A road network preprocessing unit 102 is configured to select sub-regions with significant traffic fluctuations as priority deployment areas based on the traffic fluctuation values ​​of each road, and preprocess the road network data within the priority deployment areas;

[0099] The road network topology unit 103 is configured to establish a weighted graph model for the pre-processed priority deployment area, store the intersection location information as node attributes, store the road type and road traffic fluctuation as edge attributes, and identify the intersection of the candidate deployment roadside unit as a node to be activated;

[0100] The first layer to-be-activated unit 104 is configured to calculate the edge weights and node weights of the weighted graph model using multi-attribute weighting and node degree, and then set an adaptive threshold to be activated based on the statistical results of the weights of all nodes in the priority deployment area. The first layer of to-be-activated node set is determined by determining the partial order relationship between the node weights and the threshold to be activated.

[0101] The second layer of to-be-activated unit 105 is configured to iteratively activate the remaining inactivated nodes, verify whether they meet the condition of being directly connected to the to-be-activated nodes through the neighborhood influence function, and obtain the second layer of to-be-activated node set until all nodes in the priority deployment area are to be activated or can be covered by the to-be-activated nodes;

[0102] The intersection deployment unit 106 is used to output all nodes to be activated as activated nodes to obtain the final roadside unit deployment plan.

[0103] Example 3

[0104] An embodiment of the present invention provides a roadside unit deployment device based on a hierarchical intersection node activation mechanism, comprising a processor, a memory, and a computer program stored in the memory. The computer program can be executed by the processor to implement a roadside unit deployment method based on a hierarchical intersection node activation mechanism as described in Example 1.

[0105] Example 4

[0106] An embodiment of the present invention provides a computer-readable storage medium, which includes a stored computer program. When the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a roadside unit deployment method based on a hierarchical activation mechanism of intersection nodes as described in Example 1.

[0107] In the several embodiments provided in the embodiments of the present invention, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device and method embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of the devices, methods, and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or part of the code, which contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the boxes can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, as well as the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified functions or actions, or can be implemented using a combination of dedicated hardware and computer instructions.

[0108] In addition, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0109] If the functions are implemented in the form of software modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, electronic device, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks. It should be noted that, in this document, the terms "comprise," "include," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or device that includes a series of elements includes not only those elements but also other elements not explicitly listed, or also includes elements inherent to such process, method, article, or device. Without further constraints, an element defined by the phrase "comprises a..." does not preclude the existence of additional identical elements in the process, method, article or apparatus that includes the element.

[0110] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A roadside unit deployment method based on a hierarchical activation mechanism of intersection nodes, characterized in that: include: S1, based on the urban road network structure and vehicle GPS travel trajectory, uses traffic time series analysis technology to quantify the traffic fluctuation value of each road; S2, based on the traffic fluctuation values ​​of each road, selecting sub-regions with significant traffic fluctuations as priority deployment areas, and pre-processing the road network data within the priority deployment areas; S3: A weighted graph model is established for the pre-processed priority deployment area, where the intersection location information is stored as node attributes, the road type and road traffic fluctuation are stored as edge attributes, and the intersections of the candidate roadside units are identified as nodes to be activated. S4, using multi-attribute weighting and node degree to respectively calculate the edge weights and node weights of the weighted graph model, then setting an adaptive threshold to be activated based on the statistical results of the weights of all nodes in the priority deployment area, and determining the partial order relationship between the node weights and the threshold to be activated to obtain a first-layer set of nodes to be activated; S5, iteratively activate the remaining inactivated nodes, verify whether they meet the conditions for being directly connected to the nodes to be activated through the neighborhood influence function, and obtain the second layer of nodes to be activated, until all nodes in the priority deployment area are to be activated or can be covered by the nodes to be activated; S6: Output all nodes to be activated as activated nodes to obtain the final roadside unit deployment plan. The process of establishing the weighted graph model is as follows: Create an empty weighted undirected graph and an empty set of nodes to be activated A ,in is a set of nodes, where is the set of edges, W is the weight set; Each node Contains the following properties: in, Represents the node unique identifier, Represents longitude and latitude coordinates, represents the node weight; Each edge Contains the following properties: in, represents the unique identifier of the edge, Indicates the road type, including main road, primary road, secondary road, and tertiary road; represents the weight of the edge; then step S4 is specifically as follows: Based on the two edge attributes of road type and road traffic fluctuation, a multi-attribute weighting function is used to calculate the edge weights. The edge weights are then integrated and the node weights are calculated based on the node degrees. The edge weights and node weights are calculated as follows: in, 、 represents the adjustment coefficient; is the normalized flow fluctuation; represents the road type weight function; deg ( v i ) represents a node The degree of , that is, the number of edges connected to the node; With node The set of connected edges; Represents the sum of the edge weights connected to the node; By utilizing the numerical distribution characteristics of node weights in the priority deployment area, an adaptive mechanism for generating thresholds to be activated is developed to achieve dynamic response to road network environments of different scales and characteristics. The thresholds to be activated are calculated as follows: in, is the activation threshold, k For adaptive experience adjustment parameters, is the mean of the node weights; The nodes in the priority deployment area are traversed, and the partial order relationship between the node weight and the threshold to be activated is determined to obtain all nodes with a weight greater than the threshold to be activated, which is the first layer of the node set to be activated.

2. A roadside unit deployment method based on intersection node hierarchical activation mechanism according to claim 1, characterized in that: The calculation method of the road traffic fluctuation value is: in, It's a road The flow fluctuation value, For the The flow rate of a time period, For the road The average flow rate, is the number of time periods in a day, and are the minimum and maximum traffic fluctuation values ​​of all roads in the area, is the normalized road traffic fluctuation value.

3. A roadside unit deployment method based on intersection node hierarchical activation mechanism according to claim 1, characterized in that: Preprocessing the road network data in the priority deployment area is specifically performed as follows: Perform intersection identification on the road information in the road network of the priority deployment area. A road intersection will generate two or more intersection points. Remove duplicate intersection points at the same intersection: in, represents the region of interest, Represents each latitude and longitude coordinate point in the road data, , are the minimum and maximum values ​​of the coordinate point in the x direction, , are the minimum and maximum values ​​of the coordinate point in the y direction respectively; For each road in the road network data If its geometry With area of ​​interest If they intersect, the road will remain in the study area; Among them, R represents the original road network data set, r is a road in the road network data, is the cropped road network data set; Intersections that are too close to each other are merged into one intersection. The calculation model for determining whether intersections are too close is: in, represents the set of all intersections identified by analyzing the road network, Indicates an intersection and intersections The distance between Indicates the minimum distance threshold, used to determine whether the intersections are too close. Represents the set of intersections resulting from applying the distance constraint.

4. A roadside unit deployment method based on intersection node hierarchical activation mechanism according to claim 1, characterized in that: The specific process of obtaining the second-layer nodes to be activated is as follows: The activation state of a node is determined by the activation indicator function express: Initialize the node's activation state to 0; For all nodes , define its neighbor node set , the set represents All connected nodes: Neighborhood influence function: Each node Satisfy the conditions for activation, or have at least one neighbor node To be activated; Where n is the total number of nodes, Aij represents the jth neighbor node of the i-th node in the set of nodes to be activated A. The meaning of the above formula is: If for neighbor nodes Each node in , it is satisfied that it has not joined the set of nodes to be activated , and it is the same as the set of nodes to be activated Any node in No direct connection , then the node Set to be activated and added to the set of nodes to be activated , obtain the second layer of node set to be activated; When all nodes satisfy ,or and the set of nodes to be activated is connected to a node in Make , the activation stops.

5. A roadside unit deployment method based on intersection node hierarchical activation mechanism according to claim 1, characterized in that: Output all the nodes to be activated in the first and second layers as activated nodes, which is the final roadside unit deployment plan.

6. A roadside unit deployment device based on an intersection node hierarchical activation mechanism, used to implement a roadside unit deployment method based on an intersection node hierarchical activation mechanism according to any one of claims 1 to 5, characterized in that: include: The data acquisition unit is used to quantify the traffic fluctuation value of each road using traffic time series analysis technology based on the urban road network structure and vehicle GPS travel trajectory; A road network preprocessing unit is used to screen out sub-areas with significant traffic fluctuations as priority deployment areas based on the traffic fluctuation values ​​of each road, and preprocess the road network data in the priority deployment areas; The road network topology unit is used to establish a weighted graph model for the pre-processed priority deployment area, store the intersection location information as node attributes, store the road type and road traffic fluctuation as edge attributes, and identify the intersection of the candidate deployment roadside unit as a node to be activated; The first layer of to-be-activated units is configured to calculate the edge weights and node weights of the weighted graph model using multi-attribute weighting and node degree, and then set an adaptive to-be-activated threshold based on the statistical results of the weights of all nodes in the priority deployment area. The first layer of to-be-activated node set is determined by determining the partial order relationship between the node weights and the to-be-activated threshold. The second layer of to-be-activated units is used to iteratively activate the remaining inactivated nodes. The neighborhood influence function is used to verify whether they meet the conditions for being directly connected to the to-be-activated nodes. This results in a second layer of to-be-activated node sets, which are obtained until all nodes in the priority deployment area are to be activated or can be covered by the to-be-activated nodes. The intersection deployment unit is used to output all nodes to be activated as activated nodes to obtain the final roadside unit deployment plan.

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