A global traffic flow optimization method, device, equipment and storage medium

Abstract

The application provides a global traffic flow optimization method, device and equipment and a storage medium. The method comprises the following steps: acquiring a topological road network diagram of an optimization area, wherein the topological road network diagram comprises a first road section, a second road section with a lower importance degree than the first road section, and a third road section with a lower importance degree than the second road section; constructing a target function for determining optimal vehicle flow of each road section in an optimization road section set, wherein the optimization road section set comprises each first road section or a road section obtained by connecting each first road section in series, and each second road section; regarding each third road section as an artificial congestion point road section, and constructing a constraint condition for each road section in the optimization road section set and each third road section; solving the target function in combination with the constraint condition to obtain the optimal vehicle flow of each road section in the optimization road section set; and adjusting vehicle flow of the optimization area according to the optimal vehicle flow of each road section in the optimization road section set. The global traffic flow optimization method provided by the application has good optimization effect.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to a global traffic flow optimization method, apparatus, device, and storage medium. Background Technology

[0002] With the rapid construction and development of urban transportation, the increasing travel demand of urban residents during morning and evening rush hours has gradually exceeded the vehicle carrying capacity of some main roads. Prolonged lane congestion has increased the travel burden of residents. Therefore, how to optimize the overall traffic flow has become an urgent problem to be solved. Summary of the Invention

[0003] In view of this, the present invention provides a global traffic flow optimization method, apparatus, device, and storage medium for optimizing the global traffic flow in an optimization area. The technical solution is as follows:

[0004] A global traffic flow optimization method includes:

[0005] Obtain the topology network map of the optimized area, wherein the topology network map includes intersections represented by nodes and road segments represented by lines connecting the nodes. The topology network map includes a first type of road segment, a second type of road segment with a lower importance than the first type of road segment, and a third type of road segment with a lower importance than the second type of road segment.

[0006] Construct an objective function to determine the optimal traffic flow for each road segment in the optimized road segment set, wherein the optimized road segment set includes each first type of road segment or a road segment connecting each first type of road segment, and each second type of road segment;

[0007] Each of the third type of road segments is considered as an artificial congestion point, and constraints are constructed for each road segment in the optimized road segment set and each of the third type of road segments.

[0008] By solving the objective function in conjunction with the aforementioned constraints, the optimal traffic flow for each road segment in the optimized road segment set is obtained.

[0009] Based on the optimal traffic flow of each road segment in the optimized road segment set, the traffic flow in the optimized area is adjusted.

[0010] Optionally, the objective function for determining the optimal traffic flow for each road segment in the optimized road segment set includes:

[0011] Determine the weights corresponding to each road segment in the optimized road segment set. If the optimized road segment set includes each first type of road segment, the weight corresponding to each first type of road segment is greater than the weight corresponding to each second type of road segment. If the optimized road segment set includes a road segment that connects each first type of road segment, the weight corresponding to the road segment that connects each first type of road segment is greater than the weight corresponding to each second type of road segment.

[0012] Construct an objective function with the traffic flow of each road segment in the optimized road segment set as the independent variable. The objective function is to minimize the sum of the weighted delay times of each road segment in the optimized road segment set. The weighted delay time of a road segment is obtained by weighting the overall average delay time determined based on the traffic flow of that road segment with the weight corresponding to that road segment.

[0013] Optionally, the constraints include:

[0014] For each road segment in the optimized road segment set: the traffic flow of the road segment is less than or equal to the maximum traffic flow that the road segment can carry; the overall average delay time of the road segment is less than or equal to the maximum acceptable delay time of the road segment;

[0015] For each third type of road segment: the traffic volume of the road segment is less than or equal to the maximum traffic volume that the road segment can carry; the overall average delay time of the road segment is greater than or equal to the minimum delay time that the road segment can cause congestion;

[0016] The sum of the weights corresponding to each road segment in the optimized road segment set is 1;

[0017] The sum of the traffic flow of each road segment in the optimized road segment set and the traffic flow of each third type of road segment is less than or equal to the maximum traffic flow that the optimized area can carry.

[0018] Optionally, determining the weights corresponding to each road segment in the optimized road segment set includes:

[0019] For each road segment in the optimized road segment set, the traffic flow data of that road segment during peak hours is obtained, and the overall average delay time of that road segment is determined based on the traffic flow data of that road segment during peak hours, so as to obtain the overall average delay time of each road segment in the optimized road segment set.

[0020] Based on the overall average delay time of each road segment in the optimized road segment set, the weights corresponding to each road segment in the optimized road segment set are determined.

[0021] Optionally, determining the weight corresponding to each segment in the optimized road segment set based on the overall average delay time of each segment in the optimized road segment set includes:

[0022] Based on the overall average delay time of each road segment in the optimized road segment set, the weights corresponding to each road segment in the optimized road segment set are generated using the hierarchical analysis model.

[0023] The weights are adjusted so that the weight of each first road segment in the optimized road segment set, or the weight of the road segment connecting all the first road segments, is greater than the weight of each second road segment in the optimized road segment set. The final weights of each road segment in the optimized road segment set are obtained after the adjustment.

[0024] Optionally, determining the overall average delay time of the road segment based on traffic flow data during peak hours includes:

[0025] Based on the traffic flow data of the lanes in this road segment during peak hours, determine the average delay time of the lanes in this road segment;

[0026] The overall average delay time for the road segment is determined based on the traffic flow data of the lanes during peak hours and the average delay time of the lanes in the road segment.

[0027] Optionally, the step of allocating traffic flow in the optimized area based on the optimal traffic flow of each road segment in the optimized road segment set includes:

[0028] Based on the optimal traffic flow of each road segment in the optimized road segment set, the green light ratio of each intersection in the topological road network map is determined;

[0029] Based on the green light ratio of each intersection in the topological road network map, the traffic lights at each intersection in the optimized area are controlled to allocate traffic flow in the optimized area.

[0030] Optionally, determining the green light ratio of each intersection in the topological road network map based on the optimal traffic flow of each road segment in the optimized road segment set includes:

[0031] For each intersection in the topological road network map, the green ratio of the intersection is predicted based on the optimal traffic flow of each road segment related to the intersection in the optimized road segment set and using a pre-trained green ratio prediction model.

[0032] The green ratio prediction model is trained using multiple training traffic flow data and the green ratio corresponding to each of the multiple training traffic flow data. Each training traffic flow data is the historical traffic flow data of each road segment related to an intersection.

[0033] A global traffic flow optimization device includes: a topology road network map acquisition module, an objective function construction module, a constraint condition construction module, an optimal traffic flow determination module, and a traffic flow allocation module;

[0034] The topology network map acquisition module is used to acquire the topology network map of the optimized area. The topology network map includes intersections represented by nodes and road segments represented by lines connecting the nodes. The topology network map includes a first type of road segment, a second type of road segment with a lower importance than the first type of road segment, and a third type of road segment with a lower importance than the second type of road segment.

[0035] The objective function construction module is used to construct an objective function for determining the optimal traffic flow of each road segment in the optimized road segment set, wherein the optimized road segment set includes each first type of road segment or a road segment that connects each first type of road segment, and each second type of road segment;

[0036] The constraint construction module is used to construct constraint conditions for each road segment and each third type of road segment, treating each third type of road segment as an artificial congestion point.

[0037] The optimal traffic flow determination module is used to solve the objective function in combination with the constraints to obtain the optimal traffic flow of each road segment in the optimized road segment set.

[0038] The traffic flow allocation module is used to allocate traffic flow in the optimized area based on the optimal traffic flow of each road segment in the optimized road segment set.

[0039] Optionally, the objective function construction module includes: a weight determination submodule and an objective function construction submodule;

[0040] The weight determination submodule is used to determine the weight corresponding to each road segment in the optimized road segment set. If the optimized road segment set includes each first type of road segment, the weight corresponding to each first type of road segment is greater than the weight corresponding to each second type of road segment. If the optimized road segment set includes a road segment that connects each first type of road segment, the weight corresponding to the road segment that connects each first type of road segment is greater than the weight corresponding to each second type of road segment.

[0041] The objective function construction submodule is used to construct an objective function with the traffic flow of each road segment in the optimized road segment set as the independent variable. The objective function is to minimize the sum of the weighted delay times of each road segment in the optimized road segment set. The weighted delay time of a road segment is obtained by weighting the overall average delay time determined based on the traffic flow of the road segment with the weight corresponding to that road segment.

[0042] Optionally, the traffic flow allocation module includes: a green ratio determination submodule and a traffic flow allocation submodule;

[0043] The green ratio determination submodule is used to determine the green ratio of each intersection in the topological road network map based on the optimal traffic flow of each road segment in the optimized road segment set.

[0044] The traffic flow allocation submodule is used to control the traffic lights at each intersection in the optimization area according to the green light ratio of each intersection in the topological road network map, so as to allocate the traffic flow in the optimization area.

[0045] A global traffic flow optimization device includes: a memory and a processor;

[0046] The memory is used to store programs;

[0047] The processor is configured to execute the program to implement each step of the global traffic flow optimization method described above.

[0048] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the global traffic flow optimization method described in any of the preceding claims.

[0049] The global traffic flow optimization method, apparatus, device, and storage medium provided by this invention first obtains a topological road network map of the optimization area (the topological road network map includes a first type of road segment, a second type of road segment with a lower importance than the first type of road segment, and a third type of road segment with a lower importance than the second type of road segment). Then, an objective function is constructed to determine the optimal traffic flow of each road segment in the optimized road segment set (the optimized road segment set includes each first type of road segment or a road segment connecting each first type of road segment, and each second type of road segment). Next, each third type of road segment is treated as an artificial congestion point, and constraints are constructed for each road segment and each third type of road segment in the optimized road segment set. Then, the objective function is solved in combination with the constraints to obtain the optimal traffic flow of each road segment in the optimized road segment set. Finally, based on the optimal traffic flow of each road segment in the optimized road segment set, the traffic flow in the optimization area is allocated to achieve the optimization of the global traffic flow in the optimization area. The global traffic flow optimization method provided by this invention can determine the optimal traffic flow configuration scheme for the optimization area, and adjust the traffic flow in the optimization area according to the optimal traffic flow configuration scheme, which can maximize the smoothness of the more important road sections in the optimization area. The global traffic flow optimization method provided by this invention has a good optimization effect. Attached Figure Description

[0050] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0051] Figure 1 A flowchart illustrating the global traffic flow optimization method provided in this embodiment of the invention;

[0052] Figure 2 This is an example of a topological road network diagram of a region provided in an embodiment of the present invention;

[0053] Figure 3 A flowchart illustrating the process of constructing an objective function for determining the optimal traffic flow of each road segment in an optimized road segment set, provided in an embodiment of the present invention.

[0054] Figure 4 This is a flowchart illustrating the process of allocating traffic flow in an optimized area based on the optimal traffic flow of each road segment in the optimized road segment set, as provided in an embodiment of the present invention.

[0055] Figure 5 An example of an intersection provided in an embodiment of the present invention;

[0056] Figure 6 This is an example of a traffic light timing scheme provided in an embodiment of the present invention;

[0057] Figure 7 This is a schematic diagram of the global traffic flow optimization device provided in an embodiment of the present invention;

[0058] Figure 8 This is a schematic diagram of the global traffic flow optimization device provided in an embodiment of the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0060] In order to optimize the global traffic flow in the optimization area, the inventors of this case conducted research. The initial idea was to construct a mixed integer linear programming model, determine the global traffic flow optimization scheme based on the constructed model, and optimize the global traffic flow in the optimization area based on the global traffic flow optimization scheme.

[0061] The constructed model includes an objective function and constraints. The objective function aims to maximize the capacity of the intersection. The constraints mainly include constraints related to lane channelization, flow distribution, and signal timing. Lane channelization constraints mainly introduce binary variables to indicate whether traffic flow is allowed in the approach direction. Secondly, they constrain internal conflicts between different turning traffic flows in the same approach direction. Flow distribution constraints mainly ensure that the traffic flow of multiple permitted lanes follows queuing theory, i.e., equal saturation. Signal timing constraints constrain the range of values ​​for each green light duration and need to ensure that conflicting traffic flows are separated by the signal phase sequence.

[0062] The inventors of this case, through research on the aforementioned global traffic flow optimization method, discovered that the method has many shortcomings. For example, the lack of a precise definition of the minimum constraint in the setting of constraints leads to an insufficiently precise solution range, and the optimization degree for key road segments is insufficient. These shortcomings result in the poor performance of the aforementioned global traffic flow optimization method. Given the unsatisfactory performance of the aforementioned global traffic flow optimization method, the inventors of this case continued their research and, through continuous efforts, finally proposed a global traffic flow optimization method with better performance.

[0063] The global traffic flow optimization method provided by this invention can be applied to electronic devices with data processing capabilities. These electronic devices can be user-side terminals, such as smartphones, PCs, laptops, tablets, and handheld computers. The electronic devices can also be servers, which can be a single server, a server cluster composed of multiple servers, or a cloud computing server center. The server can include processors, memory, and network interfaces. The aforementioned terminals or servers can optimize the global traffic flow in the optimization area according to the global traffic flow optimization method provided by this invention.

[0064] Those skilled in the art should understand that the above-described terminals and servers are merely examples, and other existing or future terminals or servers that are applicable to this invention should also be included within the scope of protection of this invention, and are hereby incorporated by reference.

[0065] The global traffic flow optimization method provided by the present invention will be described in the following embodiments.

[0066] Please see Figure 1 The diagram illustrates a flowchart of the global traffic flow optimization method provided in an embodiment of the present invention, which may include:

[0067] Step S101: Obtain the topology network map of the optimized area.

[0068] The topology diagram includes intersections represented by nodes and road segments represented by lines connecting the nodes.

[0069] The topological road network map includes three types of road segments: Type 1, Type 2, and Type 3. The importance of Type 2 road segments is lower than that of Type 1, and the importance of Type 3 road segments is lower than that of Type 2. In other words, Type 1 road segments are the most important and require special attention; Type 2 road segments are the next most important and are considered general; and Type 3 road segments are the least important. It should be noted that road segments with a greater impact on traffic in the optimized area are of higher importance.

[0070] Optionally, when obtaining the topological road network map of the optimized area, the Intersection Continuity Decision (ICN) method from the dual method can be used to present the urban road network topology. Then, intersections are selected as nodes, and lines are connected between the selected nodes according to the direction of the road segments between intersections, thereby obtaining the topological road network map. Please refer to [link to relevant documentation]. Figure 2 This shows an example of a topological road network diagram for a region.

[0071] Step S102: Construct an objective function to determine the optimal traffic flow for each road segment in the optimized road segment set.

[0072] In one possible implementation, the optimized road segment set includes each type of road segment and each type of road segment.

[0073] In another possible implementation, the optimized road segment set includes road segments that connect the various first-type road segments, as well as various second-type road segments. In order to uniformly allocate traffic flow for each first-type road segment, the various first-type road segments in the topological road network map can be connected into continuous road segments.

[0074] It should be noted that when connecting the first type of road segments in the topological road network diagram into a continuous road segment, the third type of road segments in the topological road network diagram are treated as prohibited road segments, that is, only the second type of road segments are used to connect the first type of road segments.

[0075] It should also be noted that when connecting the various first-type road segments into a continuous road segment, the direction of traffic flow needs to be considered. If it is not possible to connect the various first-type road segments into a continuous road segment, then the various first-type road segments can be connected into multiple continuous road segments.

[0076] Optionally, a genetic algorithm can be used to connect the various first-type road segments in the topological road network diagram into a continuous road segment. The genetic algorithm is a type of randomized search algorithm based on natural genetic mechanisms and biological evolution theories such as natural selection. It uses genetic operations such as selection, crossover, and mutation to cultivate the computational process of the control mechanism, mathematically simulating the biological evolution process to some extent. Its characteristic is that it operates on the encoding of parameters rather than the parameters themselves. Furthermore, as a parallel algorithm, it is suitable for global search to some extent, and because it uses a random search process, it has virtually no requirements on the target function, only needing to utilize fitness information. When using a genetic algorithm to connect road segments, the shortest directed path connecting each first-type road segment can be found to form a coherent road segment.

[0077] In constructing the objective function, this invention only considers the road segments in the optimized road segment set and does not consider the third type of road segment. That is, it only uses the road segments in the optimized road segment set as optimized road segments to construct the objective function.

[0078] Step S103: Treat each third type of road segment as an artificial congestion point, and construct constraints for each road segment and each third type of road segment in the optimized road segment concentration.

[0079] When constructing the objective function, this invention only considers the road segments in the optimized road segment set. However, when constructing the constraints for the objective function, it considers a third type of road segment. That is, when constructing the constraints for the objective function, in addition to considering the road segments in the optimized road segment set, it also considers each third type of road segment as a man-made congestion point. Constraints are constructed for each road segment in the optimized road segment set and each third type of road segment.

[0080] The purpose of introducing artificially created congestion points into the constraints is to control certain road sections to be relatively more congested than important road sections, thereby maximizing the smooth flow of important road sections.

[0081] Step S104: Solve the objective function by combining the constraints to obtain the optimal traffic flow of each road segment in the optimized road segment set.

[0082] By combining the constraints, the traffic flow of each road segment is found to minimize the value of the objective function. This is the optimal traffic flow of each road segment in the optimized road segment set, which is the optimal traffic flow configuration for the specified area.

[0083] Step S105: Based on the optimal traffic flow of each road segment in the optimized road segment set, the traffic flow in the optimized area is adjusted.

[0084] Traffic flow in the optimized area is adjusted to ensure that the traffic flow in each road segment is at its optimal level.

[0085] The global traffic flow optimization method provided in this invention first obtains the topological road network map of the optimization area. Then, it constructs an objective function to determine the optimal traffic flow for each road segment in the optimized road segment set (which includes each first-type road segment or a road segment connecting the first-type road segments in the topological network map, and each second-type road segment). Next, it treats each third-type road segment as an artificial congestion point and constructs constraints for each road segment and each third-type road segment in the optimized road segment set. Then, it solves the objective function based on the constraints to obtain the optimal traffic flow for each road segment in the optimized road segment set. Finally, based on the optimal traffic flow for each road segment in the optimized road segment set, it allocates traffic flow in the optimization area to optimize the global traffic flow in the optimization area. The global traffic flow optimization method provided in this invention can determine the optimal traffic flow configuration scheme for the optimization area and allocate traffic flow in the optimization area according to the optimal traffic flow configuration scheme, which can maximize the smooth flow of more important road segments in the optimization area. The global traffic flow optimization method provided in this invention has a good optimization effect.

[0086] In another embodiment of the present invention, the specific implementation process of "step S102: constructing an objective function for determining the optimal traffic flow of each road segment in the optimized road segment set" and "step S103: treating each third type of road segment as an artificial congestion point and constructing constraint conditions for each road segment in the optimized road segment set and each third type of road segment" in the above embodiment will be described.

[0087] Please see Figure 3 The diagram illustrates a flowchart for constructing an objective function to determine the optimal traffic flow for each road segment in the optimized road segment set, which may include:

[0088] Step S301: Determine the weights corresponding to each road segment in the optimized road segment set.

[0089] If the optimized road segment set includes each first type of road segment and each second type of road segment, then the weight corresponding to each first type of road segment is greater than the weight corresponding to each second type of road segment. If the optimized road segment set includes a road segment that connects each first type of road segment and each second type of road segment, then the weight corresponding to the road segment that connects each first type of road segment is greater than the weight corresponding to each second type of road segment.

[0090] Specifically, the process of determining the weights of each road segment in the optimized road segment set may include:

[0091] Step a1: For each road segment in the optimized road segment set, obtain the traffic flow data of that road segment during peak hours, and determine the overall average delay time of that road segment based on the traffic flow data of that road segment during peak hours, so as to obtain the overall average delay time of each road segment in the optimized road segment set.

[0092] The process of determining the overall average delay time of a road segment based on traffic flow data during peak hours may include: determining the average delay time of each lane in the road segment based on traffic flow data during peak hours; and determining the overall average delay time of the road segment based on both traffic flow data of each lane in the road segment during peak hours and the average delay time of each lane in the road segment.

[0093] Optionally, optimize the average delay time of the i-th lane in the r-th road segment of the road segment set. It can be calculated using the following formula:

[0094]

[0095] Where C represents the duration of the traffic flow statistics cycle, B represents the analysis duration, and g ir y represents the effective green light time of the i-th lane in the r-th road segment of the optimized road segment set. ir s represents the flow rate ratio of the i-th lane in the r-th road segment of the optimized road segment set. irThis represents the saturation flow of the i-th lane in the r-th road segment of the optimized road segment set.

[0096] The overall average delay time d of the r-th road segment in the optimized road segment set r It can be calculated using the following formula:

[0097]

[0098] Where, q ir q represents the traffic flow of the i-th lane in the r-th road segment of the optimized road segment set. ir And the aforementioned y ir s ir g ir Data such as this can be obtained from the traffic management department's system.

[0099] Step a2: Determine the weight of each segment in the optimized road segment set based on the overall average delay time of each segment in the optimized road segment set.

[0100] Optionally, the process of determining the weights of each segment in the optimized road segment set based on the overall average delay time of each segment may include:

[0101] Step a21: Based on the overall average delay time of each road segment in the optimized road segment set, use the hierarchical analysis model to generate the weights corresponding to each road segment in the optimized road segment set.

[0102] This invention applies the Analytic Hierarchy Process (AHP) to determine the weights of each road segment in a road segment optimization set. The basic idea of ​​AHP is to hierarchically categorize the problem to be analyzed. Based on the nature of the problem and the overall goal to be achieved, the problem is decomposed into different constituent factors. These factors are then grouped and combined at different levels according to their interrelationships and hierarchical relationships to form a multi-level analytical structure model. This model allows for the comparison and ranking of the problems. The method used in AHP to construct the judgment matrix is ​​the consistent matrix method, which compares factors pairwise rather than all at once, employing a relative scale to minimize the difficulty of comparing factors with different properties.

[0103] Step a22: Adjust the generated weights with the goal of making the weight of each first road segment in the optimized road segment set, or the weight of the road segment connecting all the first road segments, greater than the weight of each second road segment in the optimized road segment set. After adjustment, the final weights corresponding to each road segment in the optimized road segment set are obtained.

[0104] Given that the first type of road segment is more important than the second type of road segment, this invention increases the optimization level of the more important road segments by making the weight corresponding to each first road segment, or the weight corresponding to the road segment connecting all the first type of road segments, greater than the weight corresponding to each second road segment.

[0105] Step S302: Construct an objective function with the traffic flow of each road segment in the optimized road segment set as the independent variable.

[0106] The objective function is to minimize the sum of weighted delay times of all road segments in the optimized road segment set. The weighted delay time of a road segment is obtained by weighting the overall average delay time determined based on the traffic flow of that road segment with the corresponding weight. The objective function can be expressed as:

[0107]

[0108] The first segment subset includes each of the first type of road segments, or it includes road segments that connect the first type of road segments. Let q represent the average delay time of the j-th lane in the k-th segment of the first segment subset. mjk This represents the traffic flow of the j-th lane in the k-th segment of the first segment subset. w represents the overall average delay time of the k-th segment in the first segment subset. mk This represents the weight of the k-th segment in the first segment subset. The second segment subset includes all second segments. Let q represent the average delay time of the j-th lane in the k-th segment of the second segment subset. njk This represents the traffic flow of the j-th lane in the k-th segment of the second segment subset. w represents the overall average delay time of the k-th segment in the second segment subset. nk This represents the weight corresponding to the k-th segment in the second segment subset.

[0109] After constructing the objective function, each of the third type of road segments is treated as an artificial congestion point, and constraints are constructed for each road segment in the optimization road segment set and each of the third type of road segments.

[0110] Specifically, the constraints for each road segment and each third type road segment in the optimized road segment set include: (1) For each road segment in the optimized road segment set: the traffic flow of the road segment is less than or equal to the maximum traffic flow that the road segment can carry; the overall average delay time of the road segment is less than or equal to the maximum delay time that the road segment can accept; (2) For each third type road segment: the traffic flow of the road segment is less than or equal to the maximum traffic flow that the road segment can carry; the overall average delay time of the road segment is greater than or equal to the minimum delay time that the road segment can cause congestion; (3) The sum of the weights corresponding to each road segment in the optimized road segment set is 1; (4) The sum of the traffic flow of each road segment in the optimized road segment set and the traffic flow of each third type road segment is less than or equal to the maximum traffic flow that the optimized area can carry.

[0111] The constraints for each road segment and each third type of road segment in the optimized road segment set can be expressed as:

[0112]

[0113] In equation (4) above, q m q represents the traffic flow of a segment within the first segment subset (including all segments of type 1, or segments connecting all segments of type 1). mmax The first sub-set of road segments represents the maximum traffic flow that the road segments can carry. Equation (4) above means that the traffic flow of each road segment in the first sub-set of road segments does not exceed the maximum traffic flow that the road segment can carry.

[0114] In equation (5) above, q n q represents the traffic flow of road segments within the second subset of road segments (including all second-type road segments). nmax The first subset of road segments represents the maximum traffic flow that the road segments in the second subset can carry. Equation (5) above means that the traffic flow of each road segment in the first subset does not exceed the maximum traffic flow that the road segment can carry.

[0115] In the above formula (6), q l q represents the traffic flow of road segments within the set of man-made congestion points (including all third-type road segments). lmax The above formula (6) indicates that the traffic flow of each road segment with concentrated man-made congestion points does not exceed the maximum traffic flow that the road segment can carry.

[0116] In the above formula (7) Let represent the overall average delay time of the road segments in the first road segment subset, and let a represent the maximum acceptable delay time of the road segments in the first road segment subset. The above formula (7) represents the range of the overall average delay time of the road segments in the first road segment subset, that is, the overall average delay time of each road segment in the first road segment subset does not exceed the maximum acceptable delay time of that road segment.

[0117] In the above formula (8) denoted as the overall average delay time of the road segments in the second road segment subset, b represents the maximum acceptable delay time of the road segments in the second road segment subset, and the above formula (8) represents the range of the overall average delay time of the road segments in the second road segment subset, that is, the overall average delay time of each road segment in the second road segment subset does not exceed the maximum acceptable delay time of that road segment.

[0118] In the above formula (9) The formula (9) represents the overall average delay time of the road segment with concentrated man-made congestion points, and c represents the minimum delay time that the road segment with concentrated man-made congestion points can cause congestion. The formula (9) represents the range of the overall average delay time of the road segment with concentrated man-made congestion points, that is, the overall average delay time of each road segment with concentrated man-made congestion points is not less than the minimum delay time that the road segment can cause congestion.

[0119] w in equation (10) above m w represents the weight of the segment in the first segment subset. n The weights of the segments in the second segment subset are represented by , and the above formula (10) means that the sum of the weights of each segment in the first segment subset and the weights of each segment in the second segment subset is 1.

[0120] In equation (11) above, Q represents the maximum traffic flow that the optimization area can carry. Equation (11) above means that the sum of the traffic flow of each road segment in the first road segment subset, the traffic flow of each road segment in the second road segment subset, and the traffic flow of each road segment in the man-made congestion point road segment subset does not exceed the maximum traffic flow that the optimization area can carry.

[0121] In another embodiment of the present invention, the specific implementation process of "step S105: allocating traffic flow in the optimization area according to the optimal traffic flow of each road segment in the optimization road segment set" in the above embodiment will be described.

[0122] Please see Figure 4 This diagram illustrates the process of allocating traffic flow in an optimized area based on the optimal traffic flow of each road segment in the optimized road segment set. This may include:

[0123] Step S401: Determine the green light ratio of each intersection in the topology network diagram based on the optimal traffic flow of each road segment in the optimized road segment set.

[0124] The green light ratio refers to the ratio of the effective green light time for each phase to the cycle of a traffic signal timing period. If λ represents the green light ratio, then:

[0125]

[0126] Among them, g eC represents the effective green light time and the traffic light cycle.

[0127] In the above formula, 0 < λ < 1. If the traffic light cycle C is determined, the effective green light time for each phase can be calculated using the green light ratio.

[0128] Optionally, the process of determining the green ratio of each intersection in the topological road network map based on the optimal traffic flow of each road segment in the optimized road segment set may include: for each intersection in the topological road network map, using the optimal traffic flow of each road segment related to the intersection in the optimized road segment set as the prediction basis, and using a pre-trained green ratio prediction model to predict the green ratio of the intersection.

[0129] The green ratio prediction model is trained using multiple training traffic flow data sets and the corresponding green ratios for each training traffic flow data set. Each training traffic flow data set consists of historical traffic flow data for various road segments related to an intersection. The training of the green ratio prediction model aims to ensure that the green ratio predicted from the training traffic flow data is consistent with the green ratio corresponding to the training traffic flow data set.

[0130] Optionally, the green signal ratio prediction model can adopt a neural network model. A neural network model is a computational model composed of a large number of nodes (or neurons) that are directly interconnected. Each node (except for the input node) represents a specific output function (or can be considered as an operation), called the activation function. The connection between each pair of nodes represents the proportion of the signal in the transmission (i.e., the proportion of the "memory value" of that node that is passed on), called the weight. The output of the network varies depending on the activation function and the weights, and is an approximation of a certain function or an approximate description of the mapping relationship.

[0131] Step S402: Based on the green light ratio of each intersection in the topology road network diagram, control the traffic lights at each intersection in the optimization area to adjust the traffic flow in the optimization area.

[0132] After determining the green light ratio at the intersection, the traffic light timing scheme for the intersection in the optimization area can be determined based on the determined green light ratio. Then, the traffic lights at the intersection can be controlled according to the traffic light timing scheme to control the average delay time of the intersection, ensuring it meets the optimal traffic flow obtained according to the objective function. This achieves the allocation of traffic flow in the optimization area, i.e., the optimization of the global traffic flow in the optimization area. Please refer to [link / reference]. Figure 6 This shows an example of a traffic light timing scheme, which is Figure 5 The traffic light timing scheme shown at the intersection Figure 6 In this diagram, G represents the green light duration, and A represents the yellow light duration. Figure 6 The phases in the diagram represent road segments; that is, the four phases in the diagram represent the four road segments of the intersection.

[0133] Optionally, in addition to controlling the traffic lights at intersections according to the signal timing scheme to adjust the traffic flow in the optimized area, road guidance information can also be pushed to the map APP based on the determined optimal traffic flow of each road segment. The information push is combined with the signal timing to make the traffic flow configuration of the designated area reach the optimal traffic flow configuration as much as possible.

[0134] This invention also provides a global traffic flow optimization device. The global traffic flow optimization device provided in this invention will be described below. The global traffic flow optimization device described below can be referred to in correspondence with the global traffic flow optimization method described above.

[0135] Please see Figure 7 The diagram shows a schematic of the global traffic flow optimization device provided in an embodiment of the present invention. The global traffic flow optimization device may include: a topology road network map acquisition module 701, an objective function construction module 702, a constraint condition construction module 703, an optimal traffic flow determination module 704, and a traffic flow allocation module 705.

[0136] The topology network map acquisition module 701 is used to acquire the topology network map of the optimized area.

[0137] The topology network diagram includes intersections represented by nodes and road segments represented by lines connecting the nodes. The topology network diagram includes a first type of road segment, a second type of road segment with a lower importance than the first type of road segment, and a third type of road segment with a lower importance than the second type of road segment.

[0138] Objective function construction module 702 is used to construct an objective function for determining the optimal traffic flow for each road segment in the optimization road segment set.

[0139] The optimized road segment set includes each of the first type of road segment or the road segment connecting each of the first type of road segment, as well as each of the second type of road segment.

[0140] The constraint construction module 703 is used to construct constraint conditions for each road segment and each third type of road segment in the optimized road segment set, taking each third type of road segment as an artificial congestion point.

[0141] The optimal traffic flow determination module 704 is used to solve the objective function in combination with the constraints to obtain the optimal traffic flow of each road segment in the optimized road segment set.

[0142] The traffic flow allocation module 705 is used to allocate traffic flow in the optimized area based on the optimal traffic flow of each road segment in the optimized road segment set.

[0143] Optionally, the objective function construction module 702 may include a weight determination submodule and an objective function construction submodule.

[0144] The weight determination submodule is used to determine the weights corresponding to each road segment in the optimized road segment set.

[0145] Wherein, if the optimized road segment set includes each of the first type of road segments, then the weight corresponding to each of the first type of road segments is greater than the weight corresponding to each of the second type of road segments respectively; if the optimized road segment set includes a road segment that connects each of the first type of road segments, then the weight corresponding to the road segment that connects each of the first type of road segments is greater than the weight corresponding to each of the second type of road segments respectively.

[0146] The objective function construction submodule is used to construct an objective function with the traffic flow of each road segment in the optimized road segment set as the independent variable.

[0147] The objective function is to minimize the sum of the weighted delay times of each road segment in the optimized road segment set. The weighted delay time of a road segment is obtained by weighting the overall average delay time determined based on the traffic flow of the road segment with the weight corresponding to that road segment.

[0148] Optionally, the constraint construction module 703 is used to treat each third type of road segment as an artificially created congestion point, and the constraint conditions constructed for each road segment and each third type of road segment in the optimized road segment set include:

[0149] For each road segment in the optimized road segment set: the traffic flow of the road segment is less than or equal to the maximum traffic flow that the road segment can carry; the overall average delay time of the road segment is less than or equal to the maximum acceptable delay time of the road segment;

[0150] For each third type of road segment: the traffic volume of the road segment is less than or equal to the maximum traffic volume that the road segment can carry; the overall average delay time of the road segment is greater than or equal to the minimum delay time that the road segment can cause congestion;

[0151] The sum of the weights corresponding to each road segment in the optimized road segment set is 1;

[0152] The sum of the traffic flow of each road segment in the optimized road segment set and the traffic flow of each third type of road segment is less than or equal to the maximum traffic flow that the optimized area can carry.

[0153] Optionally, when determining the weights corresponding to each road segment in the optimized road segment set, the weight determination submodule is specifically used for:

[0154] For each road segment in the optimized road segment set, the traffic flow data of that road segment during peak hours is obtained, and the overall average delay time of that road segment is determined based on the traffic flow data of that road segment during peak hours, so as to obtain the overall average delay time of each road segment in the optimized road segment set.

[0155] Based on the overall average delay time of each road segment in the optimized road segment set, the weights corresponding to each road segment in the optimized road segment set are determined.

[0156] Optionally, when determining the weights corresponding to each segment in the optimized road segment set based on the overall average delay time of each segment in the optimized road segment set, the weight determination submodule is specifically used for:

[0157] Based on the overall average delay time of each road segment in the optimized road segment set, the weights corresponding to each road segment in the optimized road segment set are generated using the hierarchical analysis model.

[0158] The weights are adjusted so that the weight of each first road segment in the optimized road segment set, or the weight of the road segment connecting all the first road segments, is greater than the weight of each second road segment in the optimized road segment set. The final weights of each road segment in the optimized road segment set are obtained after the adjustment.

[0159] The optional weight determination submodule, when determining the overall average delay time of a road segment based on peak-hour traffic flow data, is specifically used for:

[0160] Based on the traffic flow data of the lanes in this road segment during peak hours, determine the average delay time of the lanes in this road segment;

[0161] The overall average delay time for the road segment is determined based on the traffic flow data of the lanes during peak hours and the average delay time of the lanes in the road segment.

[0162] Optionally, the traffic flow allocation module 705 may include: a green ratio determination submodule and a traffic flow allocation submodule.

[0163] The green ratio determination submodule is used to determine the green ratio of each intersection in the topological road network map based on the optimal traffic flow of each road segment in the optimized road segment set.

[0164] The traffic flow allocation submodule is used to control the traffic lights at each intersection in the optimization area according to the green light ratio of each intersection in the topological road network map, so as to allocate the traffic flow in the optimization area.

[0165] Optionally, when determining the green ratio of each intersection in the topological road network map based on the optimal traffic flow of each road segment in the optimized road segment set, the green ratio determination submodule is specifically used for:

[0166] For each intersection in the topological road network map, the green ratio of the intersection is predicted based on the optimal traffic flow of each road segment related to the intersection in the optimized road segment set and using a pre-trained green ratio prediction model.

[0167] The green ratio prediction model is trained using multiple training traffic flow data and the green ratio corresponding to each of the multiple training traffic flow data. Each training traffic flow data is the historical traffic flow data of each road segment related to an intersection.

[0168] The global traffic flow optimization device provided in this embodiment of the invention first acquires the topological road network map of the optimization area, then constructs an objective function to determine the optimal traffic flow of each road segment in the optimized road segment set (the optimized road segment set includes each first type of road segment in the topological network map or road segments connecting each first type of road segment, and each second type of road segment). Next, each third type of road segment is treated as an artificial congestion point, and constraints are constructed for each road segment and each third type of road segment in the optimized road segment set. Then, the objective function is solved in combination with the constraints to obtain the optimal traffic flow of each road segment in the optimized road segment set. Finally, based on the optimal traffic flow of each road segment in the optimized road segment set, the traffic flow in the optimization area is allocated to achieve global traffic flow optimization in the optimization area. The global traffic flow optimization device provided in this embodiment of the invention can determine the optimal traffic flow configuration scheme for the optimization area, and allocate the traffic flow in the optimization area according to the optimal traffic flow configuration scheme, which can maximize the smoothness of the more important road segments in the optimization area. The global traffic flow optimization device provided by this invention has a good optimization effect.

[0169] This invention also provides a global traffic flow optimization device; please refer to [link / reference]. Figure 8 The diagram shows the structure of the global traffic flow optimization device, which may include: a processor 801, a communication interface 802, a memory 803, and a communication bus 804.

[0170] In this embodiment of the invention, the number of processor 801, communication interface 802, memory 803, and communication bus 808 is at least one, and processor 801, communication interface 802, and memory 803 communicate with each other through communication bus 804.

[0171] The processor 801 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.

[0172] The memory 803 may include high-speed RAM, or it may also include non-volatile memory, such as at least one disk storage device;

[0173] The memory stores a program, which the processor can call. The program is used for:

[0174] Obtain the topology network map of the optimized area, wherein the topology network map includes intersections represented by nodes and road segments represented by lines connecting the nodes. The topology network map includes a first type of road segment, a second type of road segment with a lower importance than the first type of road segment, and a third type of road segment with a lower importance than the second type of road segment.

[0175] Construct an objective function to determine the optimal traffic flow for each road segment in the optimized road segment set, wherein the optimized road segment set includes each first type of road segment or a road segment connecting each first type of road segment, and each second type of road segment;

[0176] Each of the third type of road segments is considered as an artificial congestion point, and constraints are constructed for each road segment in the optimized road segment set and each of the third type of road segments.

[0177] By solving the objective function in conjunction with the aforementioned constraints, the optimal traffic flow for each road segment in the optimized road segment set is obtained.

[0178] Based on the optimal traffic flow of each road segment in the optimized road segment set, the traffic flow in the optimized area is adjusted.

[0179] Optionally, the refined and extended functions of the program can be found in the description above.

[0180] This invention also provides a readable storage medium that stores a program suitable for execution by a processor, the program being used for:

[0181] Obtain the topology network map of the optimized area, wherein the topology network map includes intersections represented by nodes and road segments represented by lines connecting the nodes. The topology network map includes a first type of road segment, a second type of road segment with a lower importance than the first type of road segment, and a third type of road segment with a lower importance than the second type of road segment.

[0182] Construct an objective function to determine the optimal traffic flow for each road segment in the optimized road segment set, wherein the optimized road segment set includes each first type of road segment or a road segment connecting each first type of road segment, and each second type of road segment;

[0183] Each of the third type of road segments is considered as an artificial congestion point, and constraints are constructed for each road segment in the optimized road segment set and each of the third type of road segments.

[0184] By solving the objective function in conjunction with the aforementioned constraints, the optimal traffic flow for each road segment in the optimized road segment set is obtained.

[0185] Based on the optimal traffic flow of each road segment in the optimized road segment set, the traffic flow in the optimized area is adjusted.

[0186] Optionally, the refined and extended functions of the program can be found in the description above.

[0187] Finally, it should be noted that in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0188] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0189] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A global traffic flow optimization method, characterized in that, include: Obtain the topology road network map of the optimized area, wherein the topology road network map includes intersections represented by nodes and road segments represented by lines connecting the nodes. The topology road network map includes a first type of road segment, a second type of road segment with a lower importance than the first type of road segment, and a third type of road segment with a lower importance than the second type of road segment. Construct an objective function to determine the optimal traffic flow for each road segment in the optimized road segment set, wherein the optimized road segment set includes each first type of road segment or a road segment connecting each first type of road segment, and each second type of road segment. The objective function is to minimize the sum of the weighted delay times of each road segment in the optimized road segment set, and the weight corresponding to each first type of road segment or the weight corresponding to the road segment connecting each first type of road segment is greater than the weight corresponding to each second type of road segment. Each of the third type of road segments is considered as an artificial congestion point, and constraints are constructed for each road segment in the optimized road segment set and each of the third type of road segments. By solving the objective function in conjunction with the aforementioned constraints, the optimal traffic flow for each road segment in the optimized road segment set is obtained. Based on the optimal traffic flow of each road segment in the optimized road segment set, the traffic flow in the optimized area is adjusted; The constraints include: For each road segment in the optimized road segment set: the traffic flow of the road segment is less than or equal to the maximum traffic flow that the road segment can carry; the overall average delay time of the road segment is less than or equal to the maximum acceptable delay time of the road segment; For each third type of road segment: the traffic volume of the road segment is less than or equal to the maximum traffic volume that the road segment can carry; the overall average delay time of the road segment is greater than or equal to the minimum delay time that the road segment can cause congestion; The sum of the weights corresponding to each road segment in the optimized road segment set is 1; The sum of the traffic flow of each road segment in the optimized road segment set and the traffic flow of each third type of road segment is less than or equal to the maximum traffic flow that the optimized area can carry.

2. The global traffic flow optimization method according to claim 1, characterized in that, The objective function for determining the optimal traffic flow for each road segment in the optimized road segment set includes: Determine the weight of each road segment in the optimized road segment set; Construct an objective function with the traffic flow of each road segment in the optimized road segment set as the independent variable. The weighted delay time of a road segment is obtained by weighting the overall average delay time determined based on the traffic flow of that road segment with the weight corresponding to that road segment.

3. The global traffic flow optimization method according to claim 2, characterized in that, Determining the weights corresponding to each road segment in the optimized road segment set includes: For each road segment in the optimized road segment set, the traffic flow data of that road segment during peak hours is obtained, and the overall average delay time of that road segment is determined based on the traffic flow data of that road segment during peak hours, so as to obtain the overall average delay time of each road segment in the optimized road segment set. Based on the overall average delay time of each road segment in the optimized road segment set, the weights corresponding to each road segment in the optimized road segment set are determined.

4. The global traffic flow optimization method according to claim 3, characterized in that, The step of determining the weight corresponding to each road segment in the optimized road segment set based on the overall average delay time of each road segment in the optimized road segment set includes: Based on the overall average delay time of each road segment in the optimized road segment set, the weights corresponding to each road segment in the optimized road segment set are generated using the hierarchical analysis model. The weights are adjusted so that the weight of each first road segment in the optimized road segment set, or the weight of the road segment connecting all the first road segments, is greater than the weight of each second road segment in the optimized road segment set. The final weights of each road segment in the optimized road segment set are obtained after the adjustment.

5. The global traffic flow optimization method according to claim 3, characterized in that, The determination of the overall average delay time for the road segment based on traffic flow data during peak hours includes: Based on the traffic flow data of the lanes in this road segment during peak hours, determine the average delay time of the lanes in this road segment; The overall average delay time for the road segment is determined based on the traffic flow data of the lanes during peak hours and the average delay time of the lanes in the road segment.

6. The global traffic flow optimization method according to any one of claims 1 to 5, characterized in that, The step of allocating traffic flow in the optimized area based on the optimal traffic flow of each road segment in the optimized road segment set includes: Based on the optimal traffic flow of each road segment in the optimized road segment set, the green light ratio of each intersection in the topological road network map is determined; Based on the green light ratio of each intersection in the topological road network diagram, the traffic lights at each intersection in the optimized area are controlled to allocate traffic flow in the optimized area.

7. The global traffic flow optimization method according to claim 6, characterized in that, The step of determining the green light ratio of each intersection in the topological road network map based on the optimal traffic flow of each road segment in the optimized road segment set includes: For each intersection in the topological road network map, the green ratio of the intersection is predicted based on the optimal traffic flow of each road segment related to the intersection in the optimized road segment set and using a pre-trained green ratio prediction model. The green ratio prediction model is trained using multiple training traffic flow data and the green ratio corresponding to each of the multiple training traffic flow data. Each training traffic flow data is the historical traffic flow data of each road segment related to an intersection.

8. A global traffic flow optimization device, characterized in that, include: The module includes a topology road network map acquisition module, an objective function construction module, a constraint condition construction module, an optimal traffic flow determination module, and a traffic flow allocation module. The topology road network map acquisition module is used to acquire the topology road network map of the optimization area. The topology road network map includes intersections represented by nodes and road segments represented by lines connecting the nodes. The topology road network map includes a first type of road segment, a second type of road segment with a lower importance than the first type of road segment, and a third type of road segment with a lower importance than the second type of road segment. The objective function construction module is used to construct an objective function for determining the optimal traffic flow of each road segment in the optimized road segment set. The optimized road segment set includes each first type of road segment or a road segment connecting each first type of road segment, and each second type of road segment. The objective function is to minimize the sum of the weighted delay times of each road segment in the optimized road segment set, and the weight corresponding to each first type of road segment or the weight corresponding to the road segment connecting each first type of road segment is greater than the weight corresponding to each second type of road segment. The constraint construction module is used to construct constraint conditions for each of the third type of road segments as artificial congestion road segments, and for each road segment and each of the third type of road segments in the optimized road segment set. The optimal traffic flow determination module is used to solve the objective function in combination with the constraints to obtain the optimal traffic flow of each road segment in the optimized road segment set. The traffic flow allocation module is used to allocate traffic flow in the optimized area based on the optimal traffic flow of each road segment in the optimized road segment set. The constraints include: For each road segment in the optimized road segment set: the traffic flow of the road segment is less than or equal to the maximum traffic flow that the road segment can carry; the overall average delay time of the road segment is less than or equal to the maximum acceptable delay time of the road segment; For each third type of road segment: the traffic volume of the road segment is less than or equal to the maximum traffic volume that the road segment can carry; the overall average delay time of the road segment is greater than or equal to the minimum delay time that the road segment can cause congestion; The sum of the weights corresponding to each road segment in the optimized road segment set is 1; The sum of the traffic flow of each road segment in the optimized road segment set and the traffic flow of each third type of road segment is less than or equal to the maximum traffic flow that the optimized area can carry.

9. The global traffic flow optimization device according to claim 8, characterized in that, The objective function construction module includes: a weight determination submodule and an objective function construction submodule; The weight determination submodule is used to determine the weight corresponding to each road segment in the optimized road segment set; The objective function construction submodule is used to construct an objective function with the traffic flow of each road segment in the optimized road segment set as the independent variable. The weighted delay time of a road segment is obtained by weighting the overall average delay time determined based on the traffic flow of the road segment with the weight corresponding to that road segment.

10. The global traffic flow optimization device according to claim 8, characterized in that, The traffic flow allocation module includes: a green ratio determination submodule and a traffic flow allocation submodule; The green ratio determination submodule is used to determine the green ratio of each intersection in the topological road network map based on the optimal traffic flow of each road segment in the optimized road segment set. The traffic flow allocation submodule is used to control the traffic lights at each intersection in the optimization area according to the green light ratio of each intersection in the topological road network map, so as to allocate the traffic flow in the optimization area.

11. A global traffic flow optimization device, characterized in that, include: Memory and processor; The memory is used to store programs; The processor is configured to execute the program to implement each step of the global traffic flow optimization method as described in any one of claims 1 to 7.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements each step of the global traffic flow optimization method as described in any one of claims 1 to 7.

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