A signal light flexible timing method and system based on vehicle-road collaboration

Abstract

The present invention provides a signal light flexible timing method and system based on vehicle-road collaboration, and relates to the technical field of traffic optimization. The method includes: collecting the number of queued vehicles in each lane in the monitoring area, wherein the monitoring area is bounded; introducing adjustment variables, and determining the signal light cycle length based on the number of queued vehicles, wherein the signal light cycle length is the time it takes for the signal light to go from the beginning of one phase to the beginning of the next same phase, wherein the beginning of the phase is when the signal light allows vehicles in the controlled lane to pass; combining the number of queued vehicles in each lane, calculating the distribution ratio of the signal light cycle length in each phase; taking the sum of the number of queued vehicles in each lane within a signal light cycle length as the minimum as the goal, optimizing the adjustment variables, and outputting the target adjustment variables; combining the distribution ratio and the target adjustment variables, and allocating the signal light cycle length to the corresponding lane. Improve traffic efficiency and reduce the probability of traffic jams.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic optimization, and in particular to a method and system for flexible timing of traffic lights based on vehicle-road collaboration. Background Art

[0002] Traffic lights are one of the traffic control devices, usually used at intersections or other places where traffic control is required. Traffic lights use different colors of lights such as red, yellow, and green to indicate when vehicles and pedestrians should stop or pass. They are an important tool for traffic management, which can help regulate traffic flow and reduce traffic accidents. Traffic light timing refers to the reasonable planning and arrangement of traffic light opening hours according to road traffic conditions and vehicle traffic needs. This includes determining the length of the traffic light cycle, the duration of each phase, the phase switching order, etc., to ensure smooth traffic flow and traffic safety.

[0003] The current traffic light timing technology is still at the fixed timing stage. The timing of the traffic lights installed at an intersection often requires the collection of long-term vehicle traffic information first, and then the timing of each state of the traffic lights is set manually. With the continuous changes in the local economy and population, the load rate of the same intersection will fluctuate dynamically, which makes it impossible for the fixed traffic light timing technology to be dynamically adaptively adjusted, leading to traffic jams and even traffic paralysis in severe cases. Summary of the invention

[0004] In order to solve the problem that the existing signal light timing technology is still at the fixed timing stage, the timing of the signal light installed at an intersection often requires the collection of long-term vehicle traffic information first, and then the timing of each state of the signal light is set manually. With the continuous changes in local economy and population, the load rate of the same traffic intersection will dynamically fluctuate, which makes it impossible for the fixed signal light timing technology to be dynamically adaptively adjusted, thus causing traffic jams and even traffic paralysis in severe cases. The present invention provides a signal light flexible timing method and system based on vehicle-road collaboration.

[0005] The technical solution provided by the embodiment of the present invention is as follows:

[0006] First aspect

[0007] An embodiment of the present invention provides a signal light flexible timing method based on vehicle-road collaboration, including:

[0008] S1: Collect the number of queued vehicles in each lane in the monitoring area, where the monitoring area is bounded;

[0009] S2: Introduce a regulating variable to determine the length of the signal light cycle based on the number of vehicles in the queue, wherein the length of the signal light cycle is the time from the beginning of one phase to the beginning of the next same phase of the signal light, wherein the beginning of the phase is when the signal light allows vehicles in the controlled lane to pass;

[0010] S3: Calculate the distribution ratio of the signal light cycle length in each phase based on the number of queued vehicles in each lane;

[0011] S4: Taking the minimum sum of the number of queued vehicles in each lane within the length of a traffic light cycle as the goal, optimize the adjustment variables and output the target adjustment variables;

[0012] S5: Allocate the signal light cycle length to the corresponding lane in combination with the allocation ratio and the target adjustment variable.

[0013] Second aspect

[0014] An embodiment of the present invention provides a signal light flexible timing system based on vehicle-road collaboration, including:

[0015] processor;

[0016] A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method for flexible timing of traffic lights based on vehicle-road collaboration as described in the first aspect is implemented.

[0017] The third aspect

[0018] An embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the method for flexible timing of traffic lights based on vehicle-road collaboration as described in the first aspect is implemented.

[0019] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0020] (1) In the present invention, according to the number of queued vehicles in the bounded monitoring area, the signal light cycle length with a limited duration related to the number of queued vehicles is determined, so that the waiting time of the lane with small traffic volume can be well taken into account while maximizing the traffic efficiency of the lane with large traffic volume. In addition, in the case of multiple lanes, the allocation ratio in each phase is determined, that is, the green light duration of each lane allocated to the signal light cycle length. This allocation method can be applied to all existing intersections. For both single lanes and multiple lanes, sufficient signal light cycle length can be reasonably allocated to adjust traffic efficiency and reduce the waiting time of each vehicle at the intersection. By dynamically adjusting the timing scheme of the signal light, the traffic flow can be effectively optimized, traffic congestion can be reduced, and road traffic efficiency can be improved. The cycle length and phase sequence of the signal light can be adjusted according to the changes in traffic flow and different road conditions to achieve more efficient traffic management and vehicle passage and reduce the cost of manual intervention.

[0021] (2) In the present invention, adjustment variables are introduced, and the goal is to minimize the sum of the number of queued vehicles in each lane within a signal light cycle. The adjustment variables are optimized, and each lane is merged. Considering the overall situation, the sum of the number of queued vehicles within a signal light cycle is minimized, which further optimizes the overall traffic efficiency, avoids traffic jams, and releases the upper limit of vehicle traffic under the inherent road to the greatest extent. In addition, this signal light timing method is independent at each intersection. Even if its associated signal light fails, the signal light timing method can timely adjust the signal light cycle length by itself, can cope with complex and changeable traffic flow changes, can efficiently cope with changes in traffic flow, and increase traffic anti-interference ability. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 A flowchart of a signal light flexible timing method based on vehicle-road collaboration provided by an embodiment of the present invention;

[0024] Figure 2 A schematic diagram of the structure of a traffic light flexible timing system based on vehicle-road collaboration provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0025] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0026] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0027] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0028] In the embodiments of the present invention, sometimes the subscripts such as W 1 It may be mistakenly written as a non-subscript form such as W1. When the difference is not emphasized, the meanings they express are the same.

[0029] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0030] Reference Manual Attached Figure 1 , showing a flow chart of a traffic light flexible timing method based on vehicle-road collaboration provided in an embodiment of the present invention.

[0031] S1: Collect the number of queued vehicles in each lane in the monitoring area, where the monitoring area is bounded.

[0032] Among them, the monitoring area refers to a specific area of ​​the intersection controlled by the traffic light, which includes the parking line of the lane and the vehicle driving area within the field of view of the signal light. The vehicle information collected in this area can be used as input data for the signal light control system to optimize the timing plan of the signal light to improve traffic efficiency and reduce congestion. Specifically, the number of queued vehicles in the monitoring area can be collected by the video collector. The monitoring area is bounded and only a limited area of ​​the lane is covered by the sensor. Therefore, the measured queue length will be bounded, so the maximum cycle time, that is, the length of the signal light cycle, will also be bounded. Even if the measured value, that is, the number of queued vehicles in the monitoring area, is saturated, it will limit the number of vehicles passing through the controller within a signal light cycle. Such a setting ensures that the lane is in line with the actual situation. On the one hand, the waiting time of each lane can be maintained within a stable and bounded time range. On the other hand, it can also avoid the problem of too long waiting time in the non-passing lane, which greatly improves the traffic efficiency of the intersection and reduces the occurrence of congestion.

[0033] S2: Introduce a regulating variable to determine the length of the signal light cycle based on the number of vehicles in the queue, where the length of the signal light cycle is the time it takes for the signal light to start from the beginning of one phase to the beginning of the next same phase, where the beginning of a phase is when the signal light allows vehicles in the controlled lane to pass.

[0034] Among them, the adjustment variable refers to a parameter or variable that can be adjusted according to specific conditions or requirements. Here, the adjustment variable is used to dynamically determine the length of the signal light cycle according to the number of vehicles in the queue. The value of the adjustment variable may be adjusted according to the changes in real-time traffic conditions to achieve effective control of traffic flow. The adjustment variable is used to dynamically adjust the length of the signal light cycle according to the vehicle queue situation to achieve more flexible and effective traffic control. The signal light cycle length refers to the length of time from the beginning of one phase to the beginning of the next same phase. In signal light control, a complete cycle includes the sum of the durations of all phases. The adjustment of the signal light cycle length can affect the control of traffic flow and the smoothness of vehicle traffic. Phase refers to the different states or stages of the signal light in a cycle, usually including different states such as red light, yellow light, and green light. Each phase has a corresponding duration, which is used to control the passage of vehicles and pedestrians. Here, the start of the phase refers to the moment when the signal light allows vehicles in the controlled lane to pass.

[0035] It should be noted that the switching order of traffic lights from the beginning of one phase to the beginning of the next identical phase can be set by oneself, or the switching order can be in the conventional order without restriction, that is, any switching order will not affect the overall traffic efficiency, that is, the total travel time, which improves the adjustability and applicable scenarios of the method.

[0036] In a possible implementation, S2 specifically includes:

[0037] S201: Determine a preset total switching duration between the beginnings of each phase, wherein the switching duration between the beginnings of every two phases is equal.

[0038] It should be noted that those skilled in the art can set the size of the preset total switching duration according to actual needs, and the present invention does not limit this. Specifically, the preset total switching duration is an integer multiple of the switching duration between each two phase switches. This switching duration is actually what we usually understand as the yellow light duration, which can generally be set to 3 seconds or 5 seconds, or can be set to other durations according to actual needs. It is specifically used to clear the vehicles in the traffic area before the next phase starts, ensuring the orderliness and safety between phase switches. To ensure smooth transition of traffic to the next phase, only after the clearing time is over will the next phase be activated to allow new vehicles to pass. Such an arrangement helps to reduce the occurrence of traffic accidents and improve the efficiency of traffic flow.

[0039] S202: Determine the length of the signal light cycle by combining the adjustment variable and the total switching time:

[0040]

[0041] Among them, T(x(t k )) represents the length of the signal light cycle in the kth cycle, where t k represents the starting time of the kth cycle, x(t k ) indicates t k The number of queued vehicles in the monitoring area at any time, x i (t k ) represents the i-th lane t k The number of queued vehicles in the monitoring area at any time, T w represents the preset total switching time, κ represents the adjustment variable, i=1,2,…,n represents the i-th lane, n represents the maximum number of lanes, and the symbol Indicates rounding down.

[0042] Regardless of the selection of the adjustment variable, if the number of queued vehicles in the lane is greater than the number of queued vehicles in the lane in the previous cycle, the signal light cycle length will always be greater than the signal light cycle length when the number of queued vehicles is smaller, that is, the signal light cycle length will dynamically increase or decrease according to the number of queued vehicles in the lane. Therefore, when the demand is higher, the signal light cycle length will be longer, and when the demand is lower, the signal light cycle length will be shorter.

[0043] S3: Calculate the distribution ratio of the signal light cycle length in each phase based on the number of queued vehicles in each lane.

[0044] Specifically, first, it is necessary to collect data on the number of queued vehicles in each lane in the monitoring area. This can be achieved through vehicle detectors or other sensors to obtain real-time information on the number of queued vehicles. Next, based on the number of queued vehicles in each lane, calculate the proportion of the number of queued vehicles in each lane in each phase. This can be achieved by comparing and calculating the number of queued vehicles in each lane with the total number of queued vehicles. Finally, based on the allocation ratio of each phase, determine the allocation ratio of the signal light cycle length in each phase. This can be adjusted according to factors such as traffic flow and road congestion to achieve reasonable timing of traffic lights.

[0045] In general, according to the real-time vehicle queue situation, the timing scheme of the traffic lights is dynamically adjusted to optimize the traffic flow to the greatest extent and improve the road traffic efficiency. By reasonably allocating the various phases of the traffic light cycle length, the needs of traffic flow in different directions can be more effectively met, congestion can be reduced, and traffic efficiency can be improved.

[0046] In a possible implementation, the allocation ratio is calculated as follows:

[0047]

[0048] Among them, u j (x(t k )) represents the distribution ratio of the signal light cycle length in the jth phase in the kth cycle, l represents the total number of phases in a signal light cycle, It means that only one lane among all lanes is open to traffic in the jth phase.

[0049] S4: With the goal of minimizing the sum of the number of queued vehicles in each lane within the length of a traffic light cycle, optimize the adjustment variables and output the target adjustment variables.

[0050] It should be noted that the process is to optimize the adjustment variables to minimize the sum of the number of vehicles queuing in each lane within the signal cycle. From a local perspective, this method minimizes the number of vehicles queuing in each lane within a single cycle by adjusting parameters such as the signal cycle length, thereby reducing local traffic congestion and improving vehicle traffic efficiency. From a global perspective, this method optimizes the signal timing scheme to make the overall traffic flow more reasonably distributed and controlled, thereby reducing overall traffic congestion, improving road traffic efficiency, and helping to improve the overall operation of the transportation system.

[0051] In a possible implementation, the adjustment variables are optimized by using an improved simulated annealing algorithm.

[0052] Among them, the improved simulated annealing algorithm is an optimization algorithm based on simulating the annealing process of metals in nature, which is used to solve optimization problems. The algorithm simulates the behavior of metals gradually decreasing in temperature during the annealing process, so that the system can jump out of the local optimal solution during the search process and is more likely to find the global optimal solution. In the improved simulated annealing algorithm, an initial temperature is usually set first, and then the temperature is gradually reduced according to a certain strategy. At each temperature, the algorithm explores the solution space by the probability of accepting a differential solution. The probability of accepting a differential solution depends on the difference in the objective function between the current solution and the new solution and the current temperature. As the temperature decreases, the probability of accepting a differential solution gradually decreases, making the system more inclined to accept a better solution.

[0053] The advantage of the improved simulated annealing algorithm is that it has certain randomness and adaptability. Randomness enables the algorithm to jump out of the local optimal solution during the search process, while adaptability enables the algorithm to adopt different strategies at different stages of the search, thereby exploring the solution space more effectively. This makes the improved simulated annealing algorithm have good robustness and global search capabilities when solving complex optimization problems. The process of optimizing the adjustment variables using the improved simulated annealing algorithm. The algorithm effectively avoids the problem of falling into the local optimal solution by introducing mechanisms such as randomness, adaptive cooling strategy and multiple iterations.

[0054] S4 specifically includes:

[0055] S401: Determine the following formula as the objective function:

[0056]

[0057] Where X represents the sum of the number of vehicles in the queue, x i represents the number of queued vehicles in the i-th lane.

[0058] S402: Setting cycle parameters, wherein the cycle parameters include an initial temperature, an end temperature, and a temperature decay rate.

[0059] The temperature decay rate can be set to a value less than 1, usually between 0.8 and 0.99. A smaller decay rate means that the temperature drops more slowly, the search process is more gentle, and it is conducive to a more comprehensive exploration of the solution space. A larger decay rate means that the temperature drops faster, the search process is faster, and it is conducive to faster convergence to the optimal solution. Optionally, the temperature decay rate is set to 0.92 here to increase the search speed and complete the optimization as soon as possible.

[0060] S403: Setting the initial temperature as the current temperature.

[0061] S404: Setting the optional parameter space of the adjustment variable according to the length of the traffic light cycle.

[0062] In a possible implementation manner, the optional parameter space is specifically:

[0063] [κ min , κ max ]

[0064]

[0065] κ min =T w

[0066] Among them, κ min , κ max represent the minimum and maximum adjustment variables, respectively.

[0067] Among them, the determination of the optional parameter space is related to the preset total switching time. Since the switching time between each two bits is generally 3 to 5, the optional parameter space set in this way can ensure that the signal light cycle length is within a reasonable range and can effectively control the traffic flow. The setting of the optional parameter space ensures that the controlled signal light cycle length will not deviate from the actual situation due to abnormal values ​​of the adjustment variables, such as waiting for too long. The setting of the optional parameter space ensures that the optimization process is meaningful. On the other hand, it also avoids the problem of traffic paralysis caused by the optimization process, and optimizes in accordance with the actual situation.

[0068] S405: randomly generating a first adjustment variable in the parameter space, and collecting the sum of the number of vehicles in the queue under the first adjustment variable, that is, determining the objective function value.

[0069] S406: Randomly generate a second adjustment variable, and calculate the acceptance probability of the second adjustment variable based on the Metropolis criterion.

[0070] In a possible implementation, the acceptance probability is specifically:

[0071]

[0072] Among them, P 接受 represents the acceptance probability, ΔX represents the difference between the objective function under the second adjustment variable and the first adjustment variable, T 当前 Represents the current temperature, and exp() represents the natural exponential function.

[0073] According to the formula, a higher temperature will make the acceptance probability higher and easier to accept new parameter values, and we hope to minimize the objective function. If it is less than 0, the second adjustment variable will definitely be accepted. If ΔX is greater than or equal to 0, the acceptance probability is calculated according to the Metropolis criterion. In other words, when the temperature is higher, the acceptance probability is higher and it is easier to accept new parameter values, even if it causes the objective function value to increase. As the temperature gradually decreases, the acceptance probability tends to lower values, making it more difficult to accept new parameter values, especially when they cause the objective function value to increase. The core idea of ​​the Metropolis criterion is to perform a random search in the parameter space while retaining the better solution and controlling the search process through the temperature parameter.

[0074] S407: When the acceptance probability is greater than or equal to 1, the first adjustment variable is replaced by the second adjustment variable; otherwise, the process proceeds to S408.

[0075] Specifically, if ΔX is negative, that is, the new parameter value causes the objective function value to decrease, then the new parameter value will definitely be accepted. If ΔX is positive, that is, the new parameter value causes the objective function value to increase, then the acceptance probability is used to decide whether to accept it. If the acceptance probability is greater than or equal to 1, that is, The new parameter value will be accepted. Otherwise, the acceptance is determined based on the randomly generated probability, which is usually a value uniformly generated from the interval [0,1]. If this random number is less than the acceptance probability, the new parameter value is accepted. Otherwise, it is rejected. This is done to ensure the breadth of the solution space to a certain extent and prevent the algorithm from falling into the local optimal solution.

[0076] S408: Generate a random probability greater than 0 and less than 1. When the random probability is less than the acceptance probability, return to S406.

[0077] S409: Lower the current temperature and return to S405 until the current temperature is lower than the termination temperature.

[0078] S410: Select the second adjustment variable corresponding to the minimum sum of the number of vehicles in the queue as the target adjustment variable output.

[0079] Since the optimization process of the adjustment variable needs to be combined with the actual number of queued vehicles for variable adjustment, and the actual number of queued vehicles is very likely to have data cases, under the influence of data cases, the parameter optimization process is prone to fall into the local optimum. By using the improved simulated annealing algorithm and increasing the optimization range of the parameters, the parameter space can be explored more flexibly and the local optimal solution can be jumped out during the search process. The main reasons why the simulated annealing algorithm is not easy to fall into the local optimal solution due to data cases are as follows: Random nature: The simulated annealing algorithm accepts new solutions that are worse than the current solution by introducing randomness. In this way, even near the local optimal solution, there is still a certain probability of accepting the poor solution, so that the local optimal solution can be jumped out. Adaptive cooling strategy: The simulated annealing algorithm adopts a strategy of gradually lowering the temperature, which reduces the rate of change of the probability of accepting the poor solution over time, so that a larger gap can be accepted in the early stage, and it is more inclined to accept a better solution in the later stage. This adaptive cooling strategy is conducive to the algorithm to balance exploration and utilization during the search process. Jump out of the local optimal: The simulated annealing algorithm considers the temperature factor in the probability calculation of accepting the poor solution, so that there is a greater probability of accepting the poor solution in the initial stage, which helps to jump out of the local optimal solution. As the temperature decreases, the algorithm tends to accept better solutions, which helps converge to the global optimal solution. Multiple iterations: The simulated annealing algorithm usually performs multiple iterations, and each iteration searches near the current solution and increases the coverage of the search space by accepting poor solutions. Through multiple iterations, the algorithm has the opportunity to search for better solutions at different starting points and paths, thus avoiding falling into the local optimum.

[0080] In summary, the simulated annealing algorithm effectively avoids the problem of falling into the local optimal solution by introducing mechanisms such as randomness, adaptive cooling strategies and multiple iterations. It can explore the solution space more comprehensively during the search process, thereby finding a better solution.

[0081] S5: Allocate the signal light cycle length to the corresponding lane in combination with the allocation ratio and the target adjustment variable.

[0082] It is understandable that according to factors such as the number of queued vehicles in the lane and traffic flow, the timing scheme of the signal lights is dynamically adjusted to optimize traffic flow to the greatest extent and improve road traffic efficiency. By allocating the signal light cycle length to each lane, traffic flow can be more effectively controlled, congestion can be reduced, and traffic efficiency can be improved, thereby improving the operating status of the entire transportation system.

[0083] In a possible implementation, S5 specifically includes:

[0084] S501: Calculate the sum of allocation ratios under the target adjustment variable.

[0085] S502: The product of the allocation ratio and the length of the signal light cycle is taken as the duration allocated to the corresponding lane:

[0086] T i =T(x(t k )) 目标 ×u j (x(t k )) 目标

[0087] Among them, T i represents the duration allocated to the i-th lane, u j (x(t k )) 目标 represents the allocation ratio under the target adjustment variable, T(x(t k )) 目标 Indicates the length of the traffic light cycle at the target manipulated variable.

[0088] In a possible implementation, it further includes:

[0089] S6: Calculate the average number of queued vehicles in each lane within the preset time length under the allocated time length. When the average number of queued vehicles is greater than the preset average number of queued vehicles, execute step S4 to re-optimize the adjustment variables.

[0090] It should be noted that those skilled in the art can set the preset duration and the average value of the preset number of queuing vehicles according to actual needs, and the present invention is not limited thereto.

[0091] It should be noted that step S6 describes an iterative process for checking whether the average number of vehicles queuing on the lane exceeds the preset value after the current signal light cycle length is allocated to each lane. If it is found that it exceeds the preset value, step S4 is re-executed to re-optimize the adjustment variable to adjust the signal light cycle length so that the average number of vehicles queuing on the lane does not exceed the preset value. This process dynamically adjusts the signal light timing plan to maintain the smoothness of road traffic and avoid traffic congestion.

[0092] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0093] (1) In the present invention, according to the number of queued vehicles in the bounded monitoring area, the signal light cycle length with a limited duration related to the number of queued vehicles is determined, so that the waiting time of the lane with small traffic volume can be well taken into account while maximizing the traffic efficiency of the lane with large traffic volume. In addition, in the case of multiple lanes, the allocation ratio in each phase is determined, that is, the green light duration of each lane allocated to the signal light cycle length. This allocation method can be applied to all existing intersections. For both single lanes and multiple lanes, sufficient signal light cycle length can be reasonably allocated to adjust traffic efficiency and reduce the waiting time of each vehicle at the intersection. By dynamically adjusting the timing scheme of the signal light, the traffic flow can be effectively optimized, traffic congestion can be reduced, and road traffic efficiency can be improved. The cycle length and phase sequence of the signal light can be adjusted according to the changes in traffic flow and different road conditions to achieve more efficient traffic management and vehicle passage and reduce the cost of manual intervention.

[0094] (2) In the present invention, adjustment variables are introduced, and the goal is to minimize the sum of the number of queued vehicles in each lane within a signal light cycle. The adjustment variables are optimized, and each lane is merged. Considering the overall situation, the sum of the number of queued vehicles within a signal light cycle is minimized, which further optimizes the overall traffic efficiency, avoids traffic jams, and releases the upper limit of vehicle traffic under the inherent road to the greatest extent. In addition, this signal light timing method is independent at each intersection. Even if its associated signal light fails, the signal light timing method can timely adjust the signal light cycle length by itself, can cope with complex and changeable traffic flow changes, can efficiently cope with changes in traffic flow, and increase traffic anti-interference ability.

[0095] Reference Manual Attached Figure 2 , showing a structural schematic diagram of a traffic light flexible timing system based on vehicle-road collaboration provided by the present invention.

[0096] The present invention further provides a signal light flexible timing system 20 based on vehicle-road collaboration, which is applied to the above-mentioned signal light flexible timing method based on vehicle-road collaboration, and comprises:

[0097] Processor 201.

[0098] The memory 202 stores computer-readable instructions. When the computer-readable instructions are executed by the processor 201, a traffic light flexible timing method based on vehicle-road collaboration as in the method embodiment is implemented.

[0099] The flexible signal light timing system 20 based on vehicle-road collaboration provided by the present invention can execute the above-mentioned flexible signal light timing method based on vehicle-road collaboration and achieve the same or similar technical effects. To avoid repetition, the present invention will not go into details.

[0100] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0101] (1) In the present invention, according to the number of queued vehicles in the bounded monitoring area, the signal light cycle length with a limited duration related to the number of queued vehicles is determined, so that the waiting time of the lane with small traffic volume can be well taken into account while maximizing the traffic efficiency of the lane with large traffic volume. In addition, in the case of multiple lanes, the allocation ratio in each phase is determined, that is, the green light duration of each lane allocated to the signal light cycle length. This allocation method can be applied to all existing intersections. For both single lanes and multiple lanes, sufficient signal light cycle length can be reasonably allocated to adjust traffic efficiency and reduce the waiting time of each vehicle at the intersection. By dynamically adjusting the timing scheme of the signal light, the traffic flow can be effectively optimized, traffic congestion can be reduced, and road traffic efficiency can be improved. The cycle length and phase sequence of the signal light can be adjusted according to the changes in traffic flow and different road conditions to achieve more efficient traffic management and vehicle passage and reduce the cost of manual intervention.

[0102] (2) In the present invention, adjustment variables are introduced, and the goal is to minimize the sum of the number of queued vehicles in each lane within a signal light cycle. The adjustment variables are optimized, and each lane is merged. Considering the overall situation, the sum of the number of queued vehicles within a signal light cycle is minimized, which further optimizes the overall traffic efficiency, avoids traffic jams, and releases the upper limit of vehicle traffic under the inherent road to the greatest extent. In addition, this signal light timing method is independent at each intersection. Even if its associated signal light fails, the signal light timing method can timely adjust the signal light cycle length by itself, can cope with complex and changeable traffic flow changes, can efficiently cope with changes in traffic flow, and increase traffic anti-interference ability.

[0103] It should be understood that the processor in the embodiment of the present invention may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0104] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0105] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0106] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0107] In the present invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0108] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0109] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0110] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0111] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0112] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0113] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0114] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0115] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the flexible timing method for traffic lights based on vehicle-road collaboration as described in the method embodiment.

[0116] A computer-readable storage medium provided by the present invention can implement the steps and effects of the flexible timing method of traffic lights based on vehicle-road collaboration in the above-mentioned method embodiment. To avoid repetition, the present invention will not go into details.

[0117] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0118] (1) In the present invention, according to the number of queued vehicles in the bounded monitoring area, the signal light cycle length with a limited duration related to the number of queued vehicles is determined, so that the waiting time of the lane with small traffic volume can be well taken into account while maximizing the traffic efficiency of the lane with large traffic volume. In addition, in the case of multiple lanes, the allocation ratio in each phase is determined, that is, the green light duration of each lane allocated to the signal light cycle length. This allocation method can be applied to all existing intersections. For both single lanes and multiple lanes, sufficient signal light cycle length can be reasonably allocated to adjust traffic efficiency and reduce the waiting time of each vehicle at the intersection. By dynamically adjusting the timing scheme of the signal light, the traffic flow can be effectively optimized, traffic congestion can be reduced, and road traffic efficiency can be improved. The cycle length and phase sequence of the signal light can be adjusted according to the changes in traffic flow and different road conditions to achieve more efficient traffic management and vehicle passage and reduce the cost of manual intervention.

[0119] (2) In the present invention, adjustment variables are introduced, and the goal is to minimize the sum of the number of queued vehicles in each lane within a signal light cycle. The adjustment variables are optimized, and each lane is merged. Considering the overall situation, the sum of the number of queued vehicles within a signal light cycle is minimized, which further optimizes the overall traffic efficiency, avoids traffic jams, and releases the upper limit of vehicle traffic under the inherent road to the greatest extent. In addition, this signal light timing method is independent at each intersection. Even if its associated signal light fails, the signal light timing method can timely adjust the signal light cycle length by itself, can cope with complex and changeable traffic flow changes, can efficiently cope with changes in traffic flow, and increase traffic anti-interference ability.

[0120] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0121] There are a few points to note:

[0122] (1) The drawings of the embodiments of the present invention only relate to the structures related to the embodiments of the present invention, and other structures may refer to the general design.

[0123] (2) For the sake of clarity, in the drawings used to describe the embodiments of the present invention, the thickness of the layers or regions is exaggerated or reduced, that is, these drawings are not drawn according to the actual scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being "on" or "under" another element, the element may be "directly" "on" or "under" the other element or there may be intermediate elements.

[0124] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to obtain new embodiments.

[0125] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A flexible signal light timing method based on vehicle-road collaboration, characterized in that: include: S1: Collecting the number of queued vehicles in each lane in a monitoring area, wherein the monitoring area is bounded; S2: introducing a regulating variable to determine the length of a signal light cycle based on the number of vehicles in the queue, wherein the length of the signal light cycle is the time it takes for the signal light to go from the beginning of one phase to the beginning of the next same phase, wherein the beginning of the phase is when the signal light allows vehicles in the controlled lane to pass; S3: Calculate the distribution ratio of the signal light cycle length in each phase based on the number of queued vehicles in each lane; S4: Optimizing the adjustment variable with the goal of minimizing the sum of the number of queued vehicles in each lane within a traffic light cycle, and outputting the target adjustment variable; S5: combining the allocation ratio and the target adjustment variable, allocating the signal light cycle length to the corresponding lane; Wherein, the S2 specifically includes: S201: Determine a preset total switching duration between the start of each phase, wherein the switching duration between the start of every two phases is equal; S202: Determine the length of the signal light cycle by combining the adjustment variable and the total switching duration: Among them, T(x(t k )) represents the length of the signal light cycle in the kth cycle, where t k represents the starting time of the kth cycle, x(t k ) indicates t k The number of queued vehicles in the monitoring area at any time, x i (t k ) represents the i-th lane t k The number of queued vehicles in the monitoring area at any time, T w represents the preset total switching time, κ represents the adjustment variable, i=1,2,…,n represents the i-th lane, n represents the maximum number of lanes, and the symbol Indicates rounding down; The adjustment variables are optimized by improving the simulated annealing algorithm, and S4 specifically includes: S401: Determine the following formula as the objective function: Where X represents the sum of the number of vehicles in the queue, x i represents the number of queued vehicles in the i-th lane; S402: Setting cycle parameters, wherein the cycle parameters include an initial temperature, an end temperature, and a temperature decay rate; S403: setting the initial temperature to the current temperature; S404: Setting the optional parameter space of the adjustment variable according to the signal light cycle length; S405: randomly generating a first adjustment variable in the parameter space, and collecting the sum of the number of vehicles in the queue under the first adjustment variable, that is, determining the objective function value; S406: randomly generating a second adjustment variable, and calculating the acceptance probability of the second adjustment variable based on the Metropolis criterion; S407: if the acceptance probability is greater than or equal to 1, replace the first adjustment variable with the second adjustment variable; otherwise, proceed to S408; S408: Generate a random probability greater than 0 and less than 1, and when the random probability is less than the acceptance probability, return to S406; S409: lowering the current temperature, and returning to S405 until the current temperature is lower than the termination temperature; S410: Selecting a second adjustment variable corresponding to the minimum sum of the number of vehicles in the queue as the target adjustment variable output; The optional parameter space is specifically: [k min ,k max ] k min =T w Among them, κ min , κ max denote the minimum and maximum moderator variables, respectively; The acceptance probability is specifically: Among them, P 接受 represents the acceptance probability, ΔX represents the difference between the objective function under the second adjustment variable and the first adjustment variable, T 当前 Represents the current temperature, and exp() represents the natural exponential function.

2. The signal light flexible timing method based on vehicle-road collaboration according to claim 1 is characterized in that: The calculation method of the distribution ratio is specifically as follows: Among them, u j (x(t k )) represents the distribution ratio of the signal light cycle length in the jth phase in the kth cycle, l represents the total number of phases in a signal light cycle, It means that only one lane among all lanes is open to traffic in the jth phase.

3. The signal light flexible timing method based on vehicle-road collaboration according to claim 1 is characterized in that: The S5 specifically includes: S501: Calculate the distribution ratio and under the target adjustment variable; S502: Taking the product of the allocation ratio and the length of the signal light cycle as the duration allocated to the corresponding lane: T i =T(x(t k )) 目标 ×u j (x(t k )) 目标 Among them, T i represents the duration allocated to the i-th lane, u j (x(t k )) 目标 represents the allocation ratio under the target adjustment variable, T(x(t k )) 目标 Indicates the length of the traffic light cycle under the target manipulated variable.

4. The signal light flexible timing method based on vehicle-road collaboration according to claim 1 is characterized in that: Also includes: S6: Calculate the average number of queued vehicles in each lane within the preset time length under the allocated time length. When the average number of queued vehicles is greater than the preset average number of queued vehicles, execute step S4 to re-optimize the adjustment variable.

5. A flexible signal light timing system based on vehicle-road collaboration, characterized in that: include: processor; A memory having computer-readable instructions stored thereon, wherein when the computer-readable instructions are executed by the processor, the method for flexible timing of traffic lights based on vehicle-road collaboration as described in any one of claims 1 to 4 is implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the flexible timing method for traffic lights based on vehicle-road collaboration as described in any one of claims 1 to 4 is implemented.

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