Multi-critical-path-oriented variable-bandwidth green wave coordination method and system for trunk road

Abstract

The invention relates to the technical field of traffic signal control, and discloses an arterial road variable bandwidth green wave coordination method and system for multiple critical paths, and the method comprises the following steps: obtaining real-time arterial road structure data, intersection signal timing parameters and critical path information; inputting the collected data into a pre-constructed trunk road green wave optimization model, solving the trunk road green wave optimization model, outputting optimized signal control parameters, and coordinating green waves according to the optimized signal control parameters; the trunk road green wave optimization model comprises an objective function and constraint conditions; and obtaining a target function of the trunk road green wave optimization model by taking the weighted sum of the green wave bandwidth of the maximized key path as a target. The method can be applied to an urban trunk road scene, green wave bands are provided for multiple key paths, the green wave bands can be flexibly changed in different road sections, and the traffic flow passing efficiency of the urban trunk road is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic signal control, and in particular to a trunk road variable bandwidth coordinated green wave method and system for multiple critical paths. Background Art

[0002] As a core means of optimizing urban traffic signals, arterial green wave coordinated control can significantly improve the efficiency of continuous traffic on arterial roads and reduce parking delays and energy consumption by coordinating the phase difference of signals at adjacent intersections. Its importance has been widely verified in theoretical research and engineering practice. As a classic green wave coordination algorithm, traditional two-way coordination models (such as MAXBAND and MULTIBAND) construct bandwidth maximization objective functions, optimize and adjust parameters such as phase difference, and design two-way through traffic green waves, thus achieving coordinated control of two-way traffic on arterial roads. They have shown good adaptability in actual road networks in Europe, America and Asia, and have become a basic method in the field of traffic control. However, with the complexity of urban traffic flow, the limitations of traditional two-way models have gradually emerged. This model mainly focuses on through traffic on arterial roads, but pays insufficient attention to the needs and characteristics of other directions such as left-turn traffic, which may lead to the problem of left-turn traffic overflow in actual traffic flow, thus interfering with the smooth travel of through traffic.

[0003] In order to coordinate the paths of turning traffic, some scholars have proposed the concept of multi-path coordinated green waves, which provides independent green waves for all key paths of traffic on the main road. However, most of the existing multi-path coordinated green wave models use a fixed green wave bandwidth, which makes the green wave bandwidth limited by the minimum green light duration of each intersection, which limits the green wave bandwidth to a certain extent. In addition, the existing multi-path models lack the coordinated optimization of signal cycle and green wave speed. Summary of the invention

[0004] In view of the shortcomings of the prior art, the present invention provides a method and system for coordinated green waves with variable bandwidth for trunk roads with multiple critical paths, which can be applied to urban trunk road scenarios, provide green waves for multiple paths, and improve the traffic efficiency of urban trunk roads.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] In a first aspect, the present invention proposes a trunk variable bandwidth coordinated green wave method for multiple critical paths, comprising:

[0007] Obtain real-time trunk road structure data, intersection signal timing parameters and critical path information;

[0008] Input the real-time trunk road structure data, intersection signal timing parameters and key path information into the pre-built trunk road green wave optimization model, solve the trunk road green wave optimization model, output the optimized signal control parameters, and coordinate the green wave according to the optimized signal control parameters; wherein the optimized signal control parameters include common period, coordinated phase difference, phase sequence and green wave speed;

[0009] The trunk green wave optimization model includes an objective function and constraints; the objective function of the trunk green wave optimization model is obtained with the goal of maximizing the weighted sum of the green wave bandwidths of the critical path; the constraints of the trunk green wave optimization model include green wave bandwidth constraints, cyclic integer constraints, green wave connectivity constraints, common period constraints, green wave speed constraints and phase sequence constraints.

[0010] The trunk road structure data includes the number of intersections and the length of road sections. This type of data is static data and can be obtained through high-precision maps and input into the trunk road green wave optimization model in advance as known parameters.

[0011] The intersection signal timing parameters include the intersection phase structure, green-to-signal ratio and signal cycle, and the intersection signal timing parameters can be obtained through each intersection signal controller.

[0012] The critical path refers to a path in the target trunk road whose flow rate is greater than a preset threshold (preferably, the top five paths in terms of flow rate are directly taken as the critical paths). The critical path is obtained by fusing vehicle trajectory data and vehicle license plate recognition data to obtain the trunk road OD matrix for a period of time (10min~60min), and taking the top five paths in terms of path flow rate. The method for obtaining critical path information is an existing technology.

[0013] In combination with the first aspect, further, the method for constructing the trunk road green wave optimization model is:

[0014] The key path is broken into several sub-paths at the intersection, and the green wave attributes required by each sub-path are clarified, wherein the green wave attributes include straight-straight green wave, straight-left turn green wave, left turn-straight green wave, and left turn-left turn green wave;

[0015] Taking subpath as the basic modeling unit, green wave bandwidth constraints, cyclic integer constraints, common period constraints, green wave speed constraints and phase sequence constraints are constructed to form subpath green wave bands;

[0016] Green wave connectivity constraints are used to constrain the sub-path green wave bands under the same path to be connected to form a complete critical path green wave.

[0017] In combination with the first aspect, further, the objective function of the trunk green wave optimization model is for:

[0018] ;

[0019] in, Upward critical path Passing the intersection of traffic, Downward critical path Passing the intersection Traffic volume; Upward critical path At the intersection The green wave bandwidth on Downward critical path At the intersection Green wave bandwidth on The number representing the critical path; Indicates the number of the intersection;

[0020] The green wave bandwidth constraint is expressed as:

[0021] ;

[0022] ;

[0023] ;

[0024] ;

[0025] in, Upward critical path At the starting intersection The green band offset, Downward critical path At the starting intersection Green band offset of Upward critical path At the end of the intersection Green band offset, Downward critical path At the end of the intersection Green band offset; Critical Path At the intersection The maximum coordination time that can be obtained; Refers to the upstream critical path set, Refers to the set of downstream critical paths; Represents the total number of intersections in the arterial road (i.e., the number of intersections in the arterial road structure data).

[0026] The loop integer constraint is expressed as:

[0027] ;

[0028] ;

[0029] in, Point to the intersection The phase difference; Critical Path At the starting intersection The length of the red light on the left side of the green wave band; Critical Path At the end of the intersection The length of the red light on the left side of the green wave band; Critical Path At the starting intersection The duration of the red light on the right side of the green wave band; Critical Path At the end of the intersection The duration of the red light on the right side of the green wave band; Upward critical path of vehicles at the intersection The travel time required for the downstream section to run at the green wave speed, Downward critical path of vehicles at the intersection The travel time required for the downstream section to operate at green wave speed; Indicates the upward critical path Upper starting intersection The multiple of the period is a positive integer; Represents the downstream critical path Upper starting intersection The multiple of the period is a positive integer; Indicates the upward critical path Upper end intersection The multiple of the period, Represents the downstream critical path Upper end intersection multiples of the period; Upward critical path At the intersection The queue clearing time, Downward critical path At the intersection The queue clearing time;

[0030] The green wave connectivity constraint is expressed as:

[0031] ;

[0032] ;

[0033] In combination with the first aspect, further, the common period constraint is expressed as:

[0034] ;

[0035] in, Indicates the maximum common cycle duration; Indicates the minimum common cycle duration; Indicates the reciprocal of the common period length.

[0036] The present invention adds a common period constraint and allows the period to change, thereby increasing the solution space of the optimization model and being able to increase the green wave bandwidth.

[0037] In combination with the first aspect, further, the green wave speed constraint is expressed as:

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] in, Indicates intersection The distance to the downstream intersection (i.e., the length of the road segment in the arterial road structure data); Indicates the maximum green wave speed; represents the minimum green wave speed; Indicates the upward critical path At the intersection Green wave speed; Represents the downstream critical path At the intersection Green wave speed.

[0043] The present invention adds a green wave speed constraint, allowing the green wave speeds of different paths to vary in different sections, thereby increasing the solution space of the optimization model and being able to increase the green wave bandwidth.

[0044] The phase order constraint is expressed as:

[0045] ;

[0046] ;

[0047] ;

[0048] ;

[0049] ;

[0050] ;

[0051] ;

[0052] ;

[0053] ;

[0054] ;

[0055] in, is a binary variable, indicating the intersection Phase and Phase The position relationship, 1 represents the phase exist Previously, 0 represented the phase exist after; , , Both represent phase; Indicates intersection Phase and Phase The position relationship, 1 represents the phase exist Previously, 0 represented the phase exist After that; by the same token , , , The meaning of the characters will not be repeated here; Indicates intersection Phase Green light duration; is a binary variable representing the critical path Is it possible to Phase Get the green light, 1 means yes, 0 means no, similarly, The definition of is no longer repeated; Represents a sufficiently large positive number, with a lower limit of 10000.

[0056] In combination with the first aspect, further, the common cycle, coordinated phase difference, phase sequence and green wave speed are determined according to the output result of the trunk green wave optimization model; the common cycle duration is 1 / z; the phase difference Indicates intersection The time difference between the initial moment and the time when the green light of the straight phase in the main road direction is turned on, the phase difference Divide by z to convert to phase difference in seconds; when the solution is , and , then the phase sequence of phase 1 is 1; in the solution, when , , or , , or , , , then the phase sequence of phase 1 is 2; in the solution, when , , or , , or , , , then the phase sequence of phase 1 is 3; in the solution, when , , , then the phase sequence of phase 1 is 4; the phase sequence refers to the order in which the phases are turned on when executed, and if the phase sequence is 1, the phase is executed first.

[0057] In a second aspect, the present invention provides a trunk variable bandwidth coordinated green wave system for multiple critical paths, comprising:

[0058] A data acquisition module configured to acquire real-time trunk road structure data, intersection signal timing parameters and critical path information;

[0059] The optimization module is configured to input real-time trunk road structure data, intersection signal timing parameters and key path information into a pre-built trunk road green wave optimization model, solve the trunk road green wave optimization model, output optimized signal control parameters, and coordinate green waves according to the optimized signal control parameters; wherein the optimized signal control parameters include common period, coordinated phase difference, phase sequence and green wave speed;

[0060] The trunk green wave optimization model includes an objective function and constraints; the objective function of the trunk green wave optimization model is obtained with the goal of maximizing the weighted sum of the green wave bandwidths of the critical path; the constraints of the trunk green wave optimization model include green wave bandwidth constraints, cyclic integer constraints, green wave connectivity constraints, common period constraints, green wave speed constraints and phase sequence constraints.

[0061] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-mentioned trunk road variable bandwidth coordinated green wave method for multiple critical paths.

[0062] In a fourth aspect, the present invention provides a computer device, comprising:

[0063] Memory for storing computer programs;

[0064] The processor is used to execute the computer program to implement the steps of the above-mentioned trunk road variable bandwidth coordinated green wave method for multiple critical paths.

[0065] In a fifth aspect, the present invention provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned trunk road variable bandwidth coordinated green wave method for multiple critical paths.

[0066] Compared with the prior art, the present invention provides a trunk road variable bandwidth coordinated green wave method and system for multiple critical paths, which has the following beneficial effects:

[0067] (1) The present invention determines the coordination control scheme as solving the optimization model, and then determines the common period, coordination phase difference, phase sequence and green wave speed according to the output results, so that the green wave bandwidth is flexible and variable, which can further make full use of green light resources, increase the green wave bandwidth, enable more vehicles to participate in the coordination, and thus improve traffic efficiency.

[0068] (2) The present invention takes urban trunk roads as the research object (it can be applied to ordinary trunk roads (3-8 intersections) and is not limited to long trunk roads (more than 8 intersections)), and establishes a variable green wave optimization model for multiple paths. The model can simultaneously optimize the phase difference, signal period, phase sequence and green wave speed. In terms of phase structure, the stage flow phase structure is adopted, which is more in line with China's actual situation.

[0069] (3) The present invention expands the modeling object from the traditional two-way straight path to multiple paths, and can provide green wave belts for multiple key paths in the trunk road at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 This is a flow chart of a trunk coordination method according to Embodiment 1 of the present invention;

[0071] Figure 2 This is a schematic diagram of the geometric layout of the trunk road in Example 1 of the present invention;

[0072] Figure 3 This is a schematic diagram of the key path in Example 1 of the present invention;

[0073] Figure 4This is a schematic diagram of the green wave bandwidth result in Example 1 of the present invention. DETAILED DESCRIPTION

[0074] The technical solution of the present invention is described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. The embodiments of the present invention and the technical features in the embodiments may be combined with each other unless there is a conflict.

[0075] The term "and / or" is only a description of the association relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " generally indicates that the related objects are in an "or" relationship.

[0076] Example 1

[0077] like Figure 1 As shown, this embodiment proposes a trunk variable bandwidth coordinated green wave method for multiple critical paths, and the method includes the following steps:

[0078] Obtain real-time trunk road structure data, intersection signal timing parameters and critical path information;

[0079] Input the real-time trunk road structure data, intersection signal timing parameters and key path information into the pre-built trunk road green wave optimization model, solve the trunk road green wave optimization model, output the optimized signal control parameters, and coordinate the green wave according to the optimized signal control parameters; wherein the optimized information control parameters include common period, coordinated phase difference, phase sequence and green wave speed;

[0080] The trunk road green wave optimization model includes objective functions and constraints. The objective function of the trunk road green wave optimization model is obtained with the goal of maximizing the weighted sum of the green wave bandwidths of the critical path. The constraints of the trunk road green wave optimization model include green wave bandwidth constraints, cyclic integer constraints, green wave connectivity constraints, common period constraints, green wave speed constraints and phase sequence constraints.

[0081] Among them, the main road structure data includes the number of intersections and the length of road sections. This type of data is static data and can be obtained through high-precision maps and input into the main road green wave optimization model in advance as known parameters.

[0082] The intersection signal timing parameters include the intersection phase structure, green-to-signal ratio and signal cycle. The intersection signal timing parameters can be obtained through the signal controllers at each intersection.

[0083] The critical path refers to the path in the target trunk road where the flow rate is greater than the preset threshold (preferably, the top five paths in terms of flow rate are directly taken as the critical paths). The critical path is obtained by fusing the vehicle trajectory data and the vehicle license plate recognition data to obtain the trunk road OD matrix for a period of time (10min~60min), and the top five paths in terms of path flow rate are taken. The method for obtaining the critical path information is the existing technology.

[0084] In a specific embodiment of the present embodiment, Python is used to call a solver to solve the optimization model and output a common signal period, a phase difference, a phase sequence, and a green wave speed solution.

[0085] In a specific implementation of this embodiment, the method for constructing the trunk road green wave optimization model is:

[0086] At the intersection, the key path is broken into several sub-paths, and the green wave attributes required for each sub-path are clarified. The green wave attributes include straight-straight green wave, straight-left turn green wave, left turn-straight green wave, and left turn-left turn green wave;

[0087] Taking subpath as the basic modeling unit, green wave bandwidth constraints, cyclic integer constraints, common period constraints, green wave speed constraints and phase sequence constraints are constructed to form subpath green wave bands;

[0088] Green wave connectivity constraints are used to constrain the sub-path green wave bands under the same path to be connected to form a complete critical path green wave.

[0089] In a specific embodiment of this embodiment, the objective function of the trunk green wave optimization model is for:

[0090] ;

[0091] in, Upward critical path Passing the intersection of traffic, Downward critical path Passing the intersection Traffic volume; Upward critical path At the intersection The green wave bandwidth on Downward critical path At the intersection Green wave bandwidth on The number representing the critical path; Indicates the number of the intersection.

[0092] In a specific implementation of this embodiment, the green wave bandwidth constraint is expressed as:

[0093] ;

[0094] ;

[0095] ;

[0096] ;

[0097] in, Upward critical path At the starting intersection The green band offset, Downward critical path At the starting intersection Green band offset of Upward critical path At the end of the intersection Green band offset, Downward critical path At the end of the intersection Green band offset; Critical Path At the intersection The maximum coordination time that can be obtained; Refers to the upstream critical path set, Refers to the set of downstream critical paths; Represents the total number of intersections in the arterial road (i.e., the number of intersections in the arterial road structure data).

[0098] The cyclic integer constraint is expressed as:

[0099] ;

[0100] ;

[0101] in, Point to the intersection The phase difference; Critical Path At the starting intersection The length of the red light on the left side of the green wave band; Critical Path At the end of the intersection The length of the red light on the left side of the green wave band; Critical Path At the starting intersection The duration of the red light on the right side of the green wave band; Critical Path At the end of the intersection The duration of the red light on the right side of the green wave band; Upward critical path of vehicles at the intersection The travel time required for the downstream section to run at the green wave speed, Downward critical path of vehicles at the intersection The travel time required for the downstream section to operate at green wave speed; Indicates the upward critical path Upper starting intersection The multiple of the period is a positive integer; Represents the downstream critical path Upper starting intersection The multiple of the period is a positive integer; Indicates the upward critical path Upper end intersection The multiple of the period, Represents the downstream critical path Upper end intersection multiples of the period; Upward critical path At the intersection The queue clearing time, Downward critical path At the intersection The queue clearing time;

[0102] The green wave connectivity constraint is expressed as:

[0103] ;

[0104] ;

[0105] The common period constraint is expressed as:

[0106] ;

[0107] in, Indicates the maximum common cycle duration; Indicates the minimum common cycle duration; Indicates the reciprocal of the common period length.

[0108] The green wave speed constraint is expressed as:

[0109] ;

[0110] ;

[0111] ;

[0112] ;

[0113] in, Indicates intersection The distance to the downstream intersection (i.e., the length of the road segment in the arterial road structure data); Indicates the maximum green wave speed; represents the minimum green wave speed; Indicates the upward critical path At the intersection Green wave speed; Represents the downstream critical path At the intersection Green wave speed.

[0114] The phase order constraint is expressed as:

[0115] ;

[0116] ;

[0117] ;

[0118] ;

[0119] ;

[0120] ;

[0121] ;

[0122] ;

[0123] ;

[0124] ;

[0125] in, is a binary variable, indicating the intersection Phase and Phase The position relationship, 1 represents the phase exist Previously, 0 represented the phase exist after; , , Both represent phase; Indicates intersection Phase and Phase The position relationship, 1 represents the phase exist Previously, 0 represented the phase exist After that; by the same token , , , The meaning of the characters will not be repeated here; Indicates intersection Phase Green light duration; is a binary variable representing the critical path Is it possible to Phase Get the green light, 1 means yes, 0 means no, similarly, The definition of is no longer repeated; Represents a sufficiently large positive number, with a lower limit of 10000.

[0126] In a specific implementation of this embodiment, the common period, coordinated phase difference, phase sequence and green wave speed are determined according to the output results of the trunk green wave optimization model; the common period duration is 1 / z; the phase difference Indicates intersection The time difference between the initial moment and the time when the green light of the straight phase in the main road direction is turned on, the phase difference Divide by z to convert to phase difference in seconds; when the solution is , and , then the phase sequence of phase 1 is 1; in the solution, when , , or , , or , , , then the phase sequence of phase 1 is 2; in the solution, when , , or , , or , , , then the phase sequence of phase 1 is 3; in the solution, when , , , then the phase sequence of phase 1 is 4; the phase sequence refers to the order in which the phases are turned on when executed. If the phase sequence is 1, the phase is executed first.

[0127] Example 2

[0128] This embodiment further illustrates the scheme and effect of the present invention through specific application examples.

[0129] A main road with an east-west direction is known, such as Figure 2 Assume that vehicles travel from west to east in the upward direction, and vice versa in the downward direction. The spacing between adjacent intersections is as follows: Figure 2 The green signal ratio of each intersection is shown in Table 1. The key path information in the main road is shown in Table 2 and Figure 3 As shown in the figure, there are five key paths, including two uplink paths and three downlink paths. The value range of the public signal period is [80s, 160s]. The value range of the green wave speed is [40km / h, 60km / h].

[0130]

[0131]

[0132] like Figure 3 As shown, Python is used to call the solver to solve the optimization model, solve the common cycle, phase difference and phase sequence scheme of the main road intersection, the key path coordination scheme and the green wave bandwidth as shown in Figure 3 shown.

[0133] In order to verify the superiority of the optimization model proposed in the present invention, the MULTIBAND model is used as a comparison model. Table 3 shows the green wave bandwidth results of the critical paths under the two models, where the green wave bandwidth is expressed as the sum of the green wave bandwidths of all sections passed by the path. "-" in Table 3 indicates that no green wave band is generated in this model. The optimization model proposed in the present invention has obvious advantages over the MULTIBAND model in dealing with multiple critical path scenarios. On paths 1 to 4, the optimization model of the present invention achieves green wave bandwidths of 0.957, 0.437, 0.780 and 0.773, respectively. However, due to the limitations of the model, the MULTIBAND model can only provide green waves for upward and downward straight traffic, with bandwidths of 1.498 and 0.80, respectively.

[0134]

[0135] Furthermore, the simulation results are shown in Table 4, and the optimization model of the present invention is superior to the MULTIBAND model. Specifically, under the optimization model of the present invention, the average delay of the vehicle is reduced by 13.66% compared with the MULTIBAND model. In terms of the average number of stops, the optimization model of the present invention achieves a lower number of stops (1.05 times), compared with 1.24 times for the MULTIBAND model. In addition, the effectiveness of the optimization model of the present invention is further verified by comparing the average speed. In summary, the optimization model of the present invention is superior to the MULTIBAND model in reducing the average path flow delay, reducing the average number of stops, and increasing the average driving speed.

[0136]

[0137] like Figure 4 As shown, the optimized signal control parameters output by the optimization model in this embodiment include each common signal cycle, intersection phase difference, phase sequence and green wave speed. The common signal cycle is 1 / z, that is, 140s; the phase difference of intersections 1-4 is 26s, 0s, 21 and 138s respectively. The phase sequence of intersections 1-4 is [3-4-2-1], [4-2-3-1], [2-4-3-1] and [1-4-2-3] respectively. The green wave speeds of path 1 in sections 1-3 are 56km / h, 50km / h and 48km / h respectively; the green wave speeds of path 2 in section 1 are 45km / h respectively; the green wave speeds of path 3 in section 3 are 50km / h respectively; the green wave speeds of path 4 in sections 1-3 are 48km / h, 52km / h and 52km / h respectively; the green wave speed of path 5 in section 1-2 is 50km / h.

[0138] Example 3

[0139] Based on the same inventive concept as that of Example 1, this embodiment introduces a trunk variable bandwidth coordinated green wave system for multiple critical paths, including:

[0140] A data acquisition module configured to acquire real-time trunk road structure data, intersection signal timing parameters and critical path information;

[0141] The optimization module is configured to input real-time trunk road structure data, intersection signal timing parameters and key path information into a pre-built trunk road green wave optimization model, solve the trunk road green wave optimization model, output optimized signal control parameters, and coordinate the green wave according to the optimized signal control parameters; wherein the optimized information control parameters include common period, coordinated phase difference, phase sequence and green wave speed;

[0142] The trunk road green wave optimization model includes objective functions and constraints. The objective function of the trunk road green wave optimization model is obtained with the goal of maximizing the weighted sum of the green wave bandwidths of the critical path. The constraints of the trunk road green wave optimization model include green wave bandwidth constraints, cyclic integer constraints, green wave connectivity constraints, common period constraints, green wave speed constraints and phase sequence constraints.

[0143] Example 4

[0144] Based on the same inventive concept as other embodiments, this embodiment introduces a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the steps of the above-mentioned trunk variable bandwidth coordinated green wave method for multiple critical paths are implemented.

[0145] Example 5

[0146] Based on the same inventive concept as other embodiments, this embodiment introduces a computer device, including: a memory for storing a computer program; a processor for executing the computer program to implement the steps of the above-mentioned trunk variable bandwidth coordinated green wave method for multiple critical paths.

[0147] Example 6

[0148] Based on the same inventive concept as other embodiments, this embodiment introduces a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned trunk road variable bandwidth coordinated green wave method for multiple critical paths.

[0149] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0150] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0151] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0152] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0153] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Ordinary technicians in this field can also make many forms under the guidance of the present invention, which all fall within the protection of the present invention.

Claims

1. A trunk variable bandwidth coordinated green wave method for multiple critical paths, characterized in that: include: Obtain real-time trunk road structure data, intersection signal timing parameters and critical path information; Input the real-time trunk road structure data, intersection signal timing parameters and key path information into the pre-built trunk road green wave optimization model, solve the trunk road green wave optimization model, output the optimized signal control parameters, and coordinate the green wave according to the optimized signal control parameters; The trunk green wave optimization model includes an objective function and constraints; the objective function of the trunk green wave optimization model is obtained with the goal of maximizing the weighted sum of the green wave bandwidths of the critical path; the constraints of the trunk green wave optimization model include green wave bandwidth constraints, cyclic integer constraints, green wave connectivity constraints, common period constraints, green wave speed constraints and phase sequence constraints.

2. The trunk variable bandwidth coordinated green wave method for multiple critical paths according to claim 1 is characterized in that: The construction method of the trunk road green wave optimization model is: The key path is broken into several sub-paths at the intersection, and the green wave attributes required by each sub-path are clarified, wherein the green wave attributes include straight-straight green wave, straight-left turn green wave, left turn-straight green wave, and left turn-left turn green wave; Taking subpath as the basic modeling unit, green wave bandwidth constraints, cyclic integer constraints, common period constraints, green wave speed constraints and phase sequence constraints are constructed to form subpath green wave bands; Green wave connectivity constraints are used to constrain the sub-path green wave bands under the same path to be connected to form a complete critical path green wave.

3. The trunk variable bandwidth coordinated green wave method for multiple critical paths according to claim 1 is characterized by: The objective function of the trunk green wave optimization model for: ； in, Upward critical path Passing the intersection of traffic, Downward critical path Passing the intersection Traffic volume; Upward critical path At the intersection The green wave bandwidth on Downward critical path At the intersection Green wave bandwidth on The number representing the critical path; Indicates the number of the intersection.

4. The trunk variable bandwidth coordinated green wave method for multiple critical paths according to claim 1 is characterized by: The green wave bandwidth constraint is expressed as: ； ； ； ； in, Upward critical path At the starting intersection The green band offset, Downward critical path At the starting intersection Green band offset of Upward critical path At the end of the intersection Green band offset, Downward critical path At the end of the intersection Green band offset; Critical Path At the intersection The maximum coordination time that can be obtained; Refers to the upstream critical path set, Refers to the set of downstream critical paths; Indicates the total number of intersections in the arterial road; The loop integer constraint is expressed as: ； ； in, Point to the intersection The phase difference; Critical Path At the starting intersection The length of the red light on the left side of the green wave band; Critical Path At the end of the intersection The length of the red light on the left side of the green wave band; Critical Path At the starting intersection The duration of the red light on the right side of the green wave band; Critical Path At the end of the intersection The duration of the red light on the right side of the green wave band; Upward critical path of vehicles at the intersection The travel time required for the downstream section to run at the green wave speed, Downward critical path of vehicles at the intersection The travel time required for the downstream section to operate at green wave speed; Indicates the upward critical path Upper starting intersection The multiple of the period is a positive integer; Represents the downstream critical path Upper starting intersection The multiple of the period is a positive integer; Indicates the upward critical path Upper end intersection The multiple of the period, Represents the downstream critical path Upper end intersection multiples of the period; Upward critical path At the intersection The queue clearing time, Downward critical path At the intersection The queue clearing time; The green wave connectivity constraint is expressed as: ； 。 5. The trunk variable bandwidth coordinated green wave method for multiple critical paths according to claim 3 is characterized by: The common period constraint is expressed as: ； in, Indicates the maximum common cycle duration; Indicates the minimum common cycle duration; Indicates the reciprocal of the public cycle length; The green wave speed constraint is expressed as: ； ； ； ； in, Indicates intersection distance to downstream intersection; Indicates the maximum green wave speed; represents the minimum green wave speed; Indicates the upward critical path At the intersection Green wave speed; Represents the downstream critical path At the intersection Green wave speed; The phase order constraint is expressed as: ； ； ； ； ； ； ； ； ； ； in, is a binary variable, indicating the intersection Phase and Phase The position relationship, 1 represents the phase exist Previously, 0 represented the phase exist after; , , Both represent phase; Indicates intersection Phase and Phase The position relationship, 1 represents the phase exist Previously, 0 represented the phase exist Afterwards; by the same token , , , The meaning of the characters will not be repeated here; Indicates intersection Phase Green light duration; is a binary variable representing the critical path Is it possible to Phase Get the green light, 1 means yes, 0 means no, similarly, The definition of is no longer repeated; Represents a sufficiently large positive number with a lower limit of 10000.

6. The trunk variable bandwidth coordinated green wave method for multiple critical paths according to claim 5 is characterized by: The common cycle, coordinated phase difference, phase sequence and green wave speed are determined according to the output results of the trunk green wave optimization model; the common cycle duration is 1 / z; the phase difference Indicates intersection The time difference between the initial moment and the time when the green light of the straight phase in the main road direction is turned on, the phase difference Divide by z to convert to phase difference in seconds; when the solution is , and , then the phase sequence of phase 1 is 1; in the solution, when , , or , , or , , , then the phase sequence of phase 1 is 2; in the solution, when , , or , , or , , , then the phase sequence of phase 1 is 3; in the solution, when , , , then the phase sequence of phase 1 is 4; the phase sequence refers to the order in which the phases are turned on when executed, and if the phase sequence is 1, the phase is executed first.

7. A trunk road variable bandwidth coordinated green wave system for multiple critical paths, characterized in that: include: A data acquisition module configured to acquire real-time trunk road structure data, intersection signal timing parameters and critical path information; The optimization module is configured to input real-time trunk road structure data, intersection signal timing parameters and key path information into a pre-built trunk road green wave optimization model, solve the trunk road green wave optimization model, output optimized signal control parameters, and coordinate green waves according to the optimized signal control parameters; wherein the optimized signal control parameters include common period, coordinated phase difference, phase sequence and green wave speed; The trunk green wave optimization model includes an objective function and constraints; the objective function of the trunk green wave optimization model is obtained with the goal of maximizing the weighted sum of the green wave bandwidths of the critical path; the constraints of the trunk green wave optimization model include green wave bandwidth constraints, cyclic integer constraints, green wave connectivity constraints, common period constraints, green wave speed constraints and phase sequence constraints.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the trunk variable bandwidth coordinated green wave method for multiple critical paths described in any one of claims 1 to 6 are implemented.

9. A computer device, characterized in that: include: Memory for storing computer programs; A processor is used to execute the computer program to implement the steps of the trunk road variable bandwidth coordinated green wave method for multiple critical paths according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that: When the computer program is executed by a processor, the steps of the trunk road variable bandwidth coordinated green wave method for multiple critical paths described in any one of claims 1 to 6 are implemented.

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