A method and system for coordinated green wave with variable bandwidth on trunk roads with multiple critical paths

Abstract

The present invention relates to the field of traffic signal control technology, and discloses a method and system for coordinating green waves with variable bandwidth on arterial roads for multiple critical paths. The method comprises the following steps: acquiring real-time arterial road structure data, intersection signal timing parameters, and critical path information; inputting the acquired data into a pre-built arterial green wave optimization model, solving the arterial green wave optimization model, outputting optimized signal control parameters, and coordinating green waves based on the optimized signal control parameters; the arterial green wave optimization model comprises an objective function and constraints; and the objective function of the arterial green wave optimization model is obtained with the goal of maximizing the weighted sum of the green wave bandwidths of the critical paths. The present invention can be applied to urban arterial road scenarios, providing green wave bands for multiple critical paths, and the green wave bandwidths can be flexibly varied in different road sections, thereby improving the traffic efficiency of urban arterial roads.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic signal control, and in particular to a method and system for coordinating green waves with variable bandwidth on arterial roads with multiple critical paths. Background Art

[0002] Green wave coordination control on arterial roads, a core approach to urban traffic signal optimization, significantly improves the efficiency of continuous vehicle traffic on arterial roads and reduces parking delays and energy consumption by coordinating signal phase differences at adjacent intersections. Its importance has been widely validated in theoretical research and engineering practice. Traditional two-way coordination models (such as MAXBAND and MULTIBAND), as classic green wave coordination algorithms, construct a bandwidth maximization objective function and design two-way green waves for through-traffic by optimizing parameters such as phase differences. These models achieve coordinated control of two-way traffic on arterial roads. These models have demonstrated excellent adaptability in real-world road networks across Europe, America, and Asia, becoming a foundational approach in traffic control. However, with the increasing complexity of urban traffic flows, the limitations of traditional two-way models have become increasingly apparent. These models primarily focus on through-traffic on arterial roads, while paying insufficient attention to the needs and characteristics of traffic in other directions, such as left-turning traffic. This can lead to overflow of left-turning traffic, disrupting the smooth flow of through-traffic traffic in real-world traffic.

[0003] To balance the coordination of turning traffic paths, some researchers have proposed the concept of multipath coordinated green waves, which provides independent green waves for all critical paths on arterial roads. However, most existing multipath coordinated green wave models use a fixed green wave bandwidth, which is limited by the minimum green light duration at each intersection, thus restricting the green wave bandwidth to a certain extent. Furthermore, existing multipath models lack the coordinated optimization of signal cycles and green wave speeds. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a method and system for coordinated green waves with variable bandwidth for trunk roads with multiple critical paths. The method 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 road 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 real-time arterial road structure data, intersection signal timing parameters, and critical path information into a pre-built arterial green wave optimization model, solve the arterial green wave optimization model, output optimized signal control parameters, and coordinate green waves based on 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 road green wave optimization model includes an objective function 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.

[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 the path in the target trunk road where the flow rate is greater than a preset threshold (preferably, the top five paths in terms of flow rate are directly selected 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 (10 minutes to 60 minutes). The top five paths in terms of path flow rate are selected. The method for obtaining critical path information is existing technology.

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

[0014] At the intersection, the critical 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;

[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 green wave bands of sub-paths 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 road green wave optimization model is for:

[0018] ;

[0019] in, Upward critical path Passing the intersection of traffic, Refers to the downstream critical path Passing the intersection Traffic volume; Upward critical path At the intersection Green wave bandwidth on Refers to the downstream critical path At the intersection Green wave bandwidth on ; The number indicating 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 of Refers to the downstream critical path At the starting intersection Green band offset; Upward critical path At the end intersection Green band offset, Refers to the downstream critical path At the end intersection Green band offset; Critical Path At the intersection The maximum coordination time that can be obtained; Refers to the set of upstream critical paths, Refers to the set of downstream critical paths; Indicates the total number of intersections in the arterial road (i.e., the number of intersections in the arterial road structure data).

[0026] The cyclic integer constraint is expressed as:

[0027] ;

[0028] ;

[0029] in, Intersection 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 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 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, Refers to the downstream critical path of vehicles at the intersection The travel time required for the downstream section to operate at the 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 End intersection A multiple of the period, Represents the downstream critical path End intersection multiples of the period; Upward critical path At the intersection The queue clearing time, Refers to the downstream critical path At the intersection How long it takes for the queue to be cleared?

[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 length; Indicates the minimum common cycle length; Indicates the reciprocal of the public cycle length.

[0036] The present invention adds a common period constraint and allows the period to vary, thereby increasing the solution space of the optimization model and enabling the green wave bandwidth to be increased.

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

[0038] ;

[0039] ;

[0040] ;

[0041] ;

[0042] in, Indicates an 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; Indicates 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 enabling an increase in 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 representing the intersection Phase and phase Positional relationship, 1 represents the phase exist Previously, 0 represented phase exist after; , , Both represent phase; Indicates an intersection Phase and phase Positional relationship, 1 represents the phase exist Previously, 0 represented phase exist Afterwards; by the same token 、 、 、 The meaning of the characters will not be repeated here; Indicates an intersection Phase Green light duration; is a binary variable representing the critical path Is it possible at the intersection 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] Combined with the first aspect, further, according to the output result of the trunk green wave optimization model, the common cycle, coordinated phase difference, phase sequence and green wave speed are determined; the common cycle duration is 1 / z; the phase difference Indicates an 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 it into 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 during execution, and if the phase sequence is 1, the phase is executed first.

[0057] In a second aspect, the present invention provides a trunk road 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] An optimization module is configured to input real-time arterial road structure data, intersection signal timing parameters, and critical path information into a pre-built arterial green wave optimization model, solve the arterial green wave optimization model, output optimized signal control parameters, and coordinate green waves based on the optimized signal control parameters; wherein the optimized signal control parameters include a common period, a coordinated phase difference, a phase sequence, and a green wave speed;

[0060] The trunk road green wave optimization model includes an objective function 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.

[0061] In a third aspect, the present invention provides 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 road variable bandwidth coordinated green wave method for multiple critical paths are implemented.

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

[0063] Memory for storing computer programs;

[0064] The processor is configured 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, comprising 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 existing technology, 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 coordinated control scheme as solving the optimization model, and then determines the common period, coordinated 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) This 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 Schematic diagram of the process of the 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 results 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. In the absence of conflict, the embodiments of the present invention and the technical features in the embodiments can be combined with each other.

[0075] The term "and / or" simply describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can mean: A exists alone, A and B exist simultaneously, or B exists alone. Additionally, the character " / " generally indicates an "or" relationship between the related objects.

[0076] Example 1

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

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

[0079] Real-time arterial road structure data, intersection signal timing parameters, and critical path information are input into a pre-built arterial green wave optimization model. The arterial green wave optimization model is solved and optimized signal control parameters are output. Green waves are coordinated based on the optimized signal control parameters. The optimized signal control parameters include common period, coordinated phase difference, phase sequence, and green wave speed.

[0080] The trunk road green wave optimization model includes an objective function 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 paths. 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] Intersection signal timing parameters include intersection phase structure, green-to-signal ratio, and signal cycle. Intersection signal timing parameters can be obtained through the signal controllers at each intersection.

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

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

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

[0086] At intersections, the critical path is broken into several sub-paths, and the required green wave attributes of each sub-path are clearly defined. 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, Refers to the downstream critical path Passing the intersection Traffic volume; Upward critical path At the intersection Green wave bandwidth on Refers to the downstream critical path At the intersection Green wave bandwidth on ; The number indicating the critical path; Indicates the intersection number.

[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 of Refers to the downstream critical path At the starting intersection Green band offset; Upward critical path At the end intersection Green band offset, Refers to the downstream critical path At the end intersection Green band offset; Critical Path At the intersection The maximum coordination time that can be obtained; Refers to the set of upstream critical paths, Refers to the set of downstream critical paths; Indicates 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, Intersection Phase difference; Refers to the 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 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; Refers to the critical path At the end 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, Refers to the downstream critical path of vehicles at the intersection The travel time required for the downstream section to operate at the 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 End intersection A multiple of the period, Represents the downstream critical path End intersection multiples of the period; Upward critical path At the intersection The queue clearing time, Refers to the downstream critical path At the intersection How long does it take to clear the queue?

[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 length; Indicates the minimum common cycle length; Indicates the reciprocal of the public cycle length.

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

[0109] ;

[0110] ;

[0111] ;

[0112] ;

[0113] in, Indicates an 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; Indicates 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 representing the intersection Phase and phase Positional relationship, 1 represents the phase exist Previously, 0 represented phase exist after; , , Both represent phase; Indicates an intersection Phase and phase Positional relationship, 1 represents the phase exist Previously, 0 represented phase exist Afterwards; by the same token 、 、 、 The meaning of the characters will not be repeated here; Indicates an intersection Phase Green light duration; is a binary variable representing the critical path Is it possible at the intersection 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 an 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 it into 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 during execution. If the phase sequence is 1, the phase is executed first.

[0127] Example 2

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

[0129] A main road with an east-west direction is known, such as Figure 2 As shown in Figure 2. Assume that vehicles are traveling from west to east in the upward direction and vice versa in the downward direction. The distance between adjacent intersections is as follows: Figure 2 The green signal ratio of each intersection is shown in Table 1. The key path information of the main road is shown in Table 2 and Figure 3 As shown in Figure 1, there are five critical paths, including two uplink paths and three downlink paths. The public signal period ranges from [80s, 160s]. The green wave speed ranges from [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 critical 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 was 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 road sections passed by the path. "-" in Table 3 indicates that no green wave band is generated by this model. The optimization model proposed in the present invention has obvious advantages over the MULTIBAND model in handling multiple critical path scenarios. On paths 1 to 4, the optimization model of the present invention achieved green wave bandwidths of 0.957, 0.437, 0.780 and 0.773, respectively. However, due to model limitations, the MULTIBAND model can only provide green waves for upward and downward straight traffic flows, with bandwidths of 1.498 and 0.80, respectively.

[0134]

[0135] Furthermore, as shown in Table 4, simulation results show that the optimization model of the present invention outperforms the MULTIBAND model. Specifically, under the optimization model of the present invention, average vehicle delays were reduced by 13.66% compared to the MULTIBAND model. In terms of the average number of stops, the optimization model of the present invention achieved a lower number of stops (1.05), compared to 1.24 for the MULTIBAND model. Furthermore, a comparison of average speeds further validated the effectiveness of the optimization model of the present invention. In summary, the optimization model of the present invention outperforms the MULTIBAND model in reducing average route flow delays, reducing the average number of stops, and increasing average travel speed.

[0136]

[0137] like Figure 4 As shown, the optimized signal control parameters output by the optimization model in this embodiment include the common signal period, intersection phase difference, phase sequence and green wave speed. The common signal period is 1 / z, that is, 140s; the phase differences of intersections 1-4 are 26s, 0s, 21 and 138s respectively. The phase sequences of intersections 1-4 are [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 Example 1, this example introduces a trunk road 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 arterial road structure data, intersection signal timing parameters, and critical path information into a pre-built arterial green wave optimization model, solve the arterial green wave optimization model, output optimized signal control parameters, and coordinate green waves based on the optimized signal control parameters. The optimized signal control parameters include common period, coordinated phase difference, phase sequence, and green wave speed.

[0142] The trunk road green wave optimization model includes an objective function 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 paths. 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 road 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 road 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. When the computer program is executed by a processor, the steps of the above-mentioned trunk road variable bandwidth coordinated green wave method for multiple critical paths are implemented.

[0149] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. 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 magnetic 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 flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, 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 flowcharts and / or block diagrams. 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 that can direct a computer or other programmable data processing device to work 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 The 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 operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function 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 are all protected by the present invention.

Claims

1. A trunk road variable bandwidth coordinated green wave method for multiple critical paths, characterized by: include: Obtain real-time trunk road structure data, intersection signal timing parameters and critical path information; Input real-time arterial road structure data, intersection signal timing parameters, and critical path information into a pre-built arterial green wave optimization model, solve the arterial green wave optimization model, output optimized signal control parameters, and coordinate green waves based on the optimized signal control parameters; The trunk road green wave optimization model includes an objective function and constraints. The objective function of the trunk road green wave optimization model is obtained by 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. The cyclic integer constraint is expressed as: ； ； in, Intersection Phase difference; Refers to the critical path At the starting intersection The length of the red light on the left side of the green wave band; Refers to the critical path At the end intersection The length of the red light on the left side of the green wave band; Refers to the critical path At the starting intersection The duration of the red light on the right side of the green wave band; Refers to the critical path At the end 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, Refers to the downstream critical path of vehicles at the intersection The travel time required for the downstream section to operate at the 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 End intersection A multiple of the period, Represents the downstream critical path End intersection multiples of the period; Upward critical path At the intersection The queue clearing time, Refers to the downstream critical path At the intersection How long does it take to clear the queue? Upward critical path At the starting intersection The green band offset of Refers to the downstream critical path At the starting intersection Green band offset; Upward critical path At the end intersection Green band offset, Refers to the downstream critical path At the end intersection Green band offset; Refers to the set of upstream critical paths, Refers to the set of downstream critical paths; Indicates the total number of intersections in the arterial road; The green wave connectivity constraint is expressed as: ； ； in, Upward critical path At the intersection Green wave bandwidth on Refers to the downstream critical path At the intersection Green wave bandwidth on.

2. The trunk road 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 as follows: At the intersection, the critical 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; 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 road variable bandwidth coordinated green wave method for multiple critical paths according to claim 1 is characterized by: The objective function of the trunk road green wave optimization model for: ； in, Upward critical path Passing the intersection of traffic, Refers to the downstream critical path Passing the intersection Traffic volume; The number indicating the critical path; Indicates the intersection number.

4. The trunk road 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, Refers to the critical path At the intersection The maximum coordination time that can be obtained.

5. The trunk road 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 length; Indicates the minimum common cycle length; Indicates the reciprocal of the public cycle length; The green wave speed constraint is expressed as: ； ； ； ； in, Indicates an intersection distance to downstream intersection; Indicates the maximum green wave speed; Indicates 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 representing the intersection Phase and phase Positional relationship, 1 represents the phase exist Previously, 0 represented phase exist after; , , Both represent phase; Indicates an intersection Phase and phase Positional relationship, 1 represents the phase exist Previously, 0 represented phase exist Afterwards; by the same token 、 、 、 The meaning of the characters will not be repeated here; Indicates an intersection Phase Green light duration; is a binary variable representing the critical path Is it possible at the intersection Phase Get the green light, 1 means yes, 0 means no; Represents a sufficiently large positive number, with a lower limit of 10000.

6. The trunk road 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 an 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 it into 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 during execution, 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 by: include: A data acquisition module configured to acquire real-time trunk road structure data, intersection signal timing parameters, and critical path information; An optimization module is configured to input real-time arterial road structure data, intersection signal timing parameters, and critical path information into a pre-built arterial green wave optimization model, solve the arterial green wave optimization model, output optimized signal control parameters, and coordinate green waves based on the optimized signal control parameters; wherein the optimized signal control parameters include a common period, a coordinated phase difference, a phase sequence, and a green wave speed; The trunk road green wave optimization model includes an objective function and constraints. The objective function of the trunk road green wave optimization model is obtained by 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. The cyclic integer constraint is expressed as: ； ； in, Intersection Phase difference; Refers to the critical path At the starting intersection The length of the red light on the left side of the green wave band; Refers to the critical path At the end intersection The length of the red light on the left side of the green wave band; Refers to the critical path At the starting intersection The duration of the red light on the right side of the green wave band; Refers to the critical path At the end 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, Refers to the downstream critical path of vehicles at the intersection The travel time required for the downstream section to operate at the 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 End intersection A multiple of the period, Represents the downstream critical path End intersection multiples of the period; Upward critical path At the intersection The queue clearing time, Refers to the downstream critical path At the intersection How long does it take to clear the queue? Upward critical path At the starting intersection The green band offset of Refers to the downstream critical path At the starting intersection Green band offset; Upward critical path At the end intersection Green band offset, Refers to the downstream critical path At the end intersection Green band offset; Refers to the set of upstream critical paths, Refers to the set of downstream critical paths; Indicates the total number of intersections in the arterial road; The green wave connectivity constraint is expressed as: ； ； in, Upward critical path At the intersection Green wave bandwidth on Refers to the downstream critical path At the intersection Green wave bandwidth on.

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 road 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 configured 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 according to any one of claims 1 to 6 are implemented.

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