A signal lamp adaptive control method and device, electronic equipment and medium

Abstract

This application relates to the field of monitoring data processing technology, and in particular to a traffic light adaptive control method, device, electronic device, and medium. The method includes acquiring a digital image of the area to be moved within the current cycle; determining the area waiting score of the area to be moved based on each vehicle image and each vehicle's waiting score; determining the adjustment duration corresponding to the area to be moved based on the area waiting score and a first mapping relationship; acquiring the actual traffic light duration corresponding to the area to be moved in the current cycle; determining the target traffic light duration based on the adjustment duration; and determining the traffic light duration allocation strategy for the next cycle corresponding to the area to be moved based on the target traffic light duration. The actual traffic light duration is the traffic light duration allocation strategy corresponding to the area to be moved within the current cycle. This application can improve the adaptability of the traffic light duration allocation strategy to the actual road traffic flow situation, thereby improving traffic speed.

Description

Technical Field

[0001] This application relates to the field of monitoring data processing technology, and in particular to a traffic light adaptive control method, device, electronic device and medium. Background Technology

[0002] With the acceleration of urbanization and the improvement of people's living standards, the demand for transportation is constantly increasing. As a convenient and free mode of transportation, automobiles can meet people's travel needs. However, with the increase in the number of vehicles, road congestion is becoming increasingly serious. To improve the current road congestion situation, related technologies generally adopt the method of adjusting the duration of traffic lights within a cycle according to time periods, separating conflicting traffic flows in time. For example, during peak hours, the flow of both vehicles and pedestrians is large. At this time, the duration of the green light in each cycle can be increased to increase the passage capacity of vehicles and pedestrians and alleviate traffic congestion. During off-peak hours, the flow of vehicles and pedestrians is relatively small. At this time, the duration of the green light in each cycle can be reduced, i.e., the duration of the red light in each cycle can be reduced, to reduce the waiting time of vehicles and pedestrians and improve traffic efficiency.

[0003] However, the method of adjusting traffic light duration in different time periods can only extend or shorten the duration of road traffic lights within certain fixed time periods. It cannot adapt to the random changes in traffic flow on the road, which may affect traffic efficiency due to the low adaptability of the traffic light duration allocation strategy to the actual road traffic conditions. Summary of the Invention

[0004] To improve the adaptability of traffic light duration allocation strategies to actual road traffic flow conditions and thus increase traffic speed, this application provides a traffic light adaptive control method, device, electronic device, and medium.

[0005] Firstly, this application provides a traffic light adaptive control method, which adopts the following technical solution:

[0006] An adaptive control method for traffic lights, comprising:

[0007] Acquire the area digital image corresponding to the area to be moved within the current period. The area digital image contains an image of each vehicle and a waiting score for each vehicle. The area to be moved is a monitoring area waiting to pass. The area to be moved corresponds to at least one monitoring area. The traffic light equipment corresponding to each monitoring area in the area to be moved is different. The traffic light equipment corresponding to each monitoring area in the area to be moved adopts the same traffic light duration allocation strategy.

[0008] Based on the digital image of the region, determine the regional waiting score of the region to be moved;

[0009] Based on the regional waiting score and the first mapping relationship, the adjustment duration corresponding to the region to be moved is determined, wherein the first mapping relationship is the mapping relationship between the regional waiting score and the adjustment duration;

[0010] The actual traffic light duration corresponding to the area to be moved in the current cycle is obtained, the target traffic light duration is determined according to the adjusted duration, and the traffic light duration allocation strategy for the next cycle corresponding to the area to be moved is determined based on the target traffic light duration. The actual traffic light duration is the traffic light duration allocation strategy for the area to be moved in the current cycle.

[0011] By adopting the above technical solution, the waiting score of each vehicle in the waiting area can be determined through regional digital images. The waiting scores displayed in the regional digital images allow for a more intuitive view of the driving situation of each vehicle on the road. Adjusting the allocation duration of traffic lights encountered by vehicles during their journey based on the waiting scores of all vehicles can improve the adaptability of the traffic light allocation duration to the actual road traffic flow, thereby improving traffic speed.

[0012] In one possible implementation, the process of generating the digital image of the region includes:

[0013] Obtain the on-site image of the area to be moved within the current period, and identify at least one license plate number contained in the on-site image of the area;

[0014] Obtain road image information within a first preset time period, and determine the vehicle driving image corresponding to each license plate number from the road image information;

[0015] Based on the vehicle driving images, determine the driving information corresponding to each license plate number within the first preset time period, and based on the driving information corresponding to each license plate number, determine the first waiting score corresponding to each license plate number. The driving information includes the average driving speed and the waiting time.

[0016] Obtain the movement route information corresponding to each license plate number, and determine the second waiting score corresponding to each license plate number based on the movement route information and the area to be moved;

[0017] Based on the first and second waiting scores of each license plate number, the waiting score corresponding to each license plate number is determined, and each license plate number is bound to the corresponding waiting score to form number binding information;

[0018] The number binding information is overlaid with the road image information to form the digital image of the area.

[0019] By adopting the above technical solution, the driving speed, waiting time, and driving route of vehicles during the driving process are analyzed to digitally monitor and manage the status of different vehicles during the driving process. Through unified digital information, it is convenient to manage different vehicles in a unified manner. By overlaying data, the number binding information is bound to the road image information, so that relevant monitoring personnel can directly view the driving status of each vehicle by viewing the road image, thereby facilitating the direct adjustment of the traffic light allocation duration.

[0020] In one possible implementation, determining the second waiting score corresponding to each license plate number based on the travel route information and the area to be moved includes:

[0021] Determine the destination location corresponding to each license plate number based on the described movement route;

[0022] Based on the distance between the area to be moved and each destination location, determine the distance score corresponding to each license plate number;

[0023] Based on the movement route information, the area to be moved, and each destination location, determine the number of traffic lights to be passed for each license plate number, and determine the traffic light score for each license plate number based on the number of traffic lights to be passed for each license plate number.

[0024] The second waiting score for each license plate number is determined based on the distance score and traffic light score corresponding to each license plate number.

[0025] By adopting the above technical solution, the waiting score for each vehicle is determined by the distance between each vehicle and the destination and the number of traffic lights to pass. This allows for a more comprehensive assessment of each vehicle's driving needs and driving status, thereby improving the compatibility between the traffic light duration allocation strategy and the actual traffic flow, and ultimately enhancing road traffic efficiency and safety.

[0026] In one possible implementation, the method further includes:

[0027] Based on the on-site images of the area, determine the vehicle waiting images corresponding to the area to be moved;

[0028] Identify the waiting area of ​​each vehicle in the vehicle waiting image, and determine the area interval between adjacent waiting areas based on each waiting area;

[0029] Each region interval is compared with a preset standard interval to determine the number of abnormal intervals, wherein the abnormal intervals are region intervals that are lower than the preset standard interval;

[0030] An interval score is determined based on the number of abnormal intervals, and the region waiting score is updated based on the interval score.

[0031] By adopting the above technical solution, the vehicle density in the area to be moved can be reflected by calculating the interval between each vehicle. The signal light allocation duration can be adjusted according to the vehicle density, which can improve the adaptability of the signal light allocation duration to the actual road conditions and reduce the probability of traffic congestion at road intersections.

[0032] In one possible implementation, the method further includes:

[0033] Based on the vehicle waiting image, determine the vehicle dispersion degree of each vehicle in the vehicle waiting image, and based on the dispersion degree of each vehicle, determine the discrete influence value of the area to be moved.

[0034] When the vehicle dispersion in the area to be moved is higher than a preset dispersion, the vehicle information corresponding to each license plate number in the area to be moved is identified, and the vehicle signal includes the vehicle model and vehicle type.

[0035] Based on the vehicle information corresponding to each license plate number, the average startup time is determined, and the startup impact value is determined based on the average startup time.

[0036] The regional waiting score is updated based on the discrete influence value and the initiation influence value.

[0037] By adopting the above technical solution, and by analyzing the discrete situation of vehicles during the waiting process and the start time of each vehicle, the predetermined traffic light allocation duration can be adjusted, which facilitates the improvement of the adaptability of the traffic light allocation duration to the actual road conditions.

[0038] In one possible implementation, determining the discrete influence value of the area to be moved based on the discreteness of each vehicle includes:

[0039] Based on the degree of dispersion of each vehicle and the second mapping relationship, the discrete influence value of each vehicle is determined. Based on the discrete influence value of each vehicle, the first discrete influence value corresponding to the area to be moved is determined. The second mapping relationship is the mapping relationship between the degree of dispersion and the discrete influence value of the vehicle.

[0040] The waiting position of each vehicle is determined based on the vehicle waiting image, and at least one straight route is determined based on the waiting position of each vehicle, wherein the distance between edge points corresponding to vehicles in the straight route does not exceed a preset threshold.

[0041] Based on the number of direct routes and the third mapping relationship, the second discrete influence value corresponding to the area to be moved is determined, wherein the third mapping relationship is the mapping relationship between the number of routes and the discrete influence value;

[0042] The final discrete influence value of the region to be moved is determined based on the first discrete influence value and the second discrete influence value corresponding to the region to be moved.

[0043] By adopting the above technical solution, the dispersion between vehicles in the area to be moved will affect the speed of the vehicles when passing through the traffic lights. The greater the dispersion, the longer the time required to pass through the traffic lights. In addition, since the vehicles travel faster on a relatively standardized moving route, limiting the straight route according to the preset threshold helps to improve the accuracy of determining the straight route. By jointly determining the dispersion influence value by the dispersion and the straight route, the accuracy of determining the dispersion influence value can be improved.

[0044] In one possible implementation, the method further includes:

[0045] Identify the green light passage duration included in the signal duration allocation strategy for the next cycle. When the green light passage duration is higher than the preset passage duration, obtain the supplementary area image corresponding to the intersection within the second preset time period.

[0046] The corresponding supplementation rate is determined based on the supplementation area image. When the supplementation rate is higher than the preset standard rate, the green light passage duration included in the duration allocation strategy is adjusted to the preset passage duration.

[0047] By adopting the above technical solution, the time allocation strategy is restricted by the corresponding supplementary rate of the intersection. Without affecting the normal driving of the intersection, the corresponding passage time is reasonably adjusted. By simultaneously analyzing the traffic flow conditions of the current road segment and the intersection, the traffic light allocation time is optimized in a coordinated manner, which facilitates the improvement of the rationality of the traffic light allocation time and thus improves the traffic speed.

[0048] Secondly, this application provides a traffic light adaptive control device, which adopts the following technical solution:

[0049] An adaptive control device for traffic lights, comprising:

[0050] The regional digital image acquisition module is used to acquire the regional digital image corresponding to the area to be moved within the current period. The regional digital image contains an image of each vehicle and a waiting score for each vehicle. The area to be moved is a monitoring area waiting to pass. The area to be moved corresponds to at least one monitoring area. The traffic light equipment corresponding to each monitoring area in the area to be moved is different. The traffic light equipment corresponding to each monitoring area in the area to be moved adopts the same traffic light duration allocation strategy.

[0051] The waiting weight value determination module is used to determine the regional waiting score of the area to be moved based on each vehicle image and each vehicle's waiting score;

[0052] The adjustment duration determination module is used to determine the adjustment duration corresponding to the region to be moved based on the region waiting score and the first mapping relationship, wherein the first mapping relationship is the mapping relationship between the region waiting score and the adjustment duration;

[0053] The target traffic light duration determination module is used to obtain the actual traffic light duration corresponding to the area to be moved in the current cycle, determine the target traffic light duration based on the adjustment duration, and determine the traffic light duration allocation strategy for the next cycle corresponding to the area to be moved based on the target traffic light duration. The actual traffic light duration is the traffic light duration allocation strategy for the area to be moved in the current cycle.

[0054] By adopting the above technical solution, the waiting score of each vehicle in the waiting area can be determined through regional digital images. The waiting scores displayed in the regional digital images allow for a more intuitive view of the driving situation of each vehicle on the road. Adjusting the allocation duration of traffic lights encountered by vehicles during their journey based on the waiting scores of all vehicles can improve the adaptability of the traffic light allocation duration to the actual road traffic flow, thereby improving traffic speed.

[0055] In one possible implementation, the device further includes:

[0056] The license plate number recognition module is used to acquire the on-site image of the area to be moved within the current period, and to recognize at least one license plate number contained in the on-site image of the area;

[0057] The vehicle driving image determination module is used to acquire road image information within a first preset time period and determine the vehicle driving image corresponding to each license plate number from the road image information;

[0058] The module for determining the first waiting score is used to determine the driving information corresponding to each license plate number within the first preset time period based on the vehicle driving image, and to determine the first waiting score corresponding to each license plate number based on the driving information corresponding to each license plate number. The driving information includes the average driving speed and the waiting time.

[0059] The second waiting score determination module is used to obtain the movement route information corresponding to each license plate number, and determine the second waiting score corresponding to each license plate number based on the movement route information and the area to be moved;

[0060] The number binding information module is used to determine the waiting score corresponding to each license plate number based on the first waiting score and the second waiting score of each license plate number, and bind each license plate number with the corresponding waiting score to form number binding information;

[0061] The information overlay module is used to overlay the number binding information with the road image information to form the digital image of the area.

[0062] In one possible implementation, the module for determining the second waiting score, when determining the second waiting score for each license plate number based on the travel route information and the area to be moved, is specifically used for:

[0063] Determine the destination location corresponding to each license plate number based on the described movement route;

[0064] Based on the distance between the area to be moved and each destination location, determine the distance score corresponding to each license plate number;

[0065] Based on the movement route information, the area to be moved, and each destination location, determine the number of traffic lights to be passed for each license plate number, and determine the traffic light score for each license plate number based on the number of traffic lights to be passed for each license plate number.

[0066] The second waiting score for each license plate number is determined based on the distance score and traffic light score corresponding to each license plate number.

[0067] In one possible implementation, the device further includes:

[0068] The vehicle waiting image determination module is used to determine the vehicle waiting image corresponding to the area to be moved based on the on-site image of the area.

[0069] A region interval determination module is used to identify the waiting area of ​​each vehicle in the vehicle waiting image and determine the region interval between adjacent waiting areas based on each waiting area;

[0070] The module for determining the number of abnormal intervals is used to compare each regional interval with a preset standard interval to determine the number of abnormal intervals, wherein the abnormal intervals are regional intervals that are lower than the preset standard intervals.

[0071] The first update module is used to determine the interval score based on the number of abnormal intervals, and update the region waiting score based on the interval score.

[0072] In one possible implementation, the device further includes:

[0073] The discrete influence value determination module is used to determine the vehicle discreteness of each vehicle in the vehicle waiting image based on the vehicle waiting image, and to determine the discrete influence value of the area to be moved based on the discreteness of each vehicle.

[0074] The vehicle information identification module is used to identify the vehicle information corresponding to each license plate number in the area to be moved when the vehicle dispersion in the area to be moved is higher than a preset dispersion. The vehicle signal includes the vehicle model and vehicle type.

[0075] The module for determining the startup impact value is used to determine the average startup time based on the vehicle information corresponding to each license plate number, and to determine the startup impact value based on the average startup time.

[0076] The second update module is used to update the regional waiting score based on the discrete influence value and the start-up influence value.

[0077] In one possible implementation, the discrete impact value determination module, when determining the discrete impact value of the area to be moved based on the discreteness of each vehicle, is specifically used for:

[0078] Based on the degree of dispersion of each vehicle and the second mapping relationship, the discrete influence value of each vehicle is determined. Based on the discrete influence value of each vehicle, the first discrete influence value corresponding to the area to be moved is determined. The second mapping relationship is the mapping relationship between the degree of dispersion and the discrete influence value of the vehicle.

[0079] The waiting position of each vehicle is determined based on the vehicle waiting image, and at least one straight route is determined based on the waiting position of each vehicle, wherein the distance between edge points corresponding to vehicles in the straight route does not exceed a preset threshold.

[0080] Based on the number of direct routes and the third mapping relationship, the second discrete influence value corresponding to the area to be moved is determined, wherein the third mapping relationship is the mapping relationship between the number of routes and the discrete influence value;

[0081] The final discrete influence value of the region to be moved is determined based on the first discrete influence value and the second discrete influence value corresponding to the region to be moved.

[0082] In one possible implementation, the device further includes:

[0083] The passage duration judgment module is used to identify the green light passage duration included in the signal duration allocation strategy of the next cycle. When the green light passage duration is higher than the preset passage duration, the module obtains the supplementary area image of the intersection within the second preset time period.

[0084] The duration adjustment module is used to determine the corresponding supplementation rate based on the supplementation area image. When the supplementation rate is higher than the preset standard rate, the green light passage duration included in the duration allocation strategy is adjusted to the preset passage duration.

[0085] Thirdly, this application provides an electronic device that adopts the following technical solution:

[0086] An electronic device comprising:

[0087] At least one processor;

[0088] Memory;

[0089] At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: execute the above-described traffic light adaptive control method.

[0090] Fourthly, this application provides a computer-readable storage medium, which adopts the following technical solution:

[0091] A computer-readable storage medium includes: a computer program stored thereon that can be loaded by a processor and execute the above-described traffic light adaptive control method.

[0092] In summary, this application includes at least one of the following beneficial technical effects:

[0093] 1. By using regional digital images, the waiting score of each vehicle in the waiting area can be determined. The waiting scores displayed in the regional digital images provide a more intuitive view of the driving situation of each vehicle on the road. Adjusting the allocation duration of traffic lights encountered by vehicles during their journey based on the waiting scores of all vehicles can improve the adaptability of the traffic light allocation duration to the actual road traffic flow, thereby improving traffic speed.

[0094] 2. By analyzing the vehicle's speed, waiting time, and route during operation, the system enables digital monitoring and management of different vehicles' status during operation. Unified digital information facilitates unified management of different vehicles. By overlaying data, the system binds the vehicle's registration number with road image information, allowing monitoring personnel to directly view the driving status of each vehicle through road images, thereby facilitating direct adjustment of traffic light durations. Attached Figure Description

[0095] Figure 1 This is a schematic diagram of a road intersection according to an embodiment of this application;

[0096] Figure 2 This is a flowchart illustrating an adaptive control method for traffic lights according to an embodiment of this application.

[0097] Figure 3 This is a flowchart illustrating a method for generating a regional digital image according to an embodiment of this application;

[0098] Figure 4This is a schematic diagram of a vehicle spacing area in an embodiment of this application;

[0099] Figure 5 This is a schematic diagram of a vehicle arrangement in an embodiment of this application;

[0100] Figure 6 This is a schematic diagram of the structure of a traffic light adaptive control device according to an embodiment of this application;

[0101] Figure 7 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0102] The following is in conjunction with the appendix Figure 1-7 This application will be described in further detail.

[0103] After reading this specification, those skilled in the art may make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they fall within the scope of the claims of this application.

[0104] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0105] For ease of understanding, in this embodiment, each cycle includes the duration of a green traffic light and the duration of a red traffic light. The current cycle is the cycle of the traffic light corresponding to the area to be moved at the current moment, such as... Figure 1As shown, there is a crossroads, which can be a road intersection within a park. The crossroads has multiple monitoring areas, where the area to be moved is at least one monitoring area on the same road. The traffic light equipment corresponding to the area to be moved is different, but the different traffic light equipment uses the same traffic light duration allocation strategy. The number of monitoring areas included in the area to be moved is not specifically limited in this embodiment. When the traffic light corresponding to the current cycle is red, vehicles in the area to be moved are waiting to pass. Therefore, as time goes on, vehicles may gradually enter the area to be moved. By analyzing each vehicle in the area to be moved during the red light counting period, the traffic light duration corresponding to when the area to be moved begins to allow passage can be determined. For example, the green light lasts for 25 seconds in the current cycle, and the red light also lasts for 25 seconds. During the red light's timing, the vehicles continuously entering the waiting area are analyzed to determine the light allocation duration for the next cycle. The light allocation duration for the next cycle may be the same as or different from the current cycle. That is, the green light's duration for the next cycle may be 25 seconds, higher, or lower than 25 seconds. However, within the same cycle, the green light's duration and the red light's duration are the same.

[0106] Specifically, this application provides a traffic light adaptive control method executed by an electronic device, which can be a server or a terminal device. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing cloud computing services. The terminal device can be a smartphone, tablet, laptop, desktop computer, etc., but is not limited to these. The terminal device and the server can be directly or indirectly connected via wired or wireless communication, and this application does not impose any limitations on this connection.

[0107] refer to Figure 2 , Figure 2 This is a flowchart illustrating an adaptive traffic light control method according to an embodiment of this application. The method includes steps S210-S240, wherein:

[0108] Step S210: Obtain the area digital image corresponding to the area to be moved within the current period. The area digital image contains the image of each vehicle and the waiting score of each vehicle. The area to be moved is the monitoring area waiting to pass. The area to be moved corresponds to at least one monitoring area. The traffic light equipment corresponding to each monitoring area in the area to be moved is different. The traffic light equipment corresponding to each monitoring area in the area to be moved adopts the same traffic light duration allocation strategy.

[0109] Specifically, one cycle consists of one red light duration and one green light duration. The area to be moved is the current location of the vehicle that needs to move in the next cycle within the park, such as... Figure 1 The shaded area is shown. The area digital image is an area image with digital information, including the waiting score for each vehicle. The waiting score for each vehicle can be directly viewed through the area digital image. The display format of the waiting score in the area digital image can be bordered text or plain text. The specific display format is not specifically limited in this application and can be set by relevant technical personnel, as long as it is possible to view the waiting score corresponding to each vehicle based on the area digital image.

[0110] The process of generating a regional digital image specifically includes steps Sa1-Sa6, such as... Figure 3 As shown, where:

[0111] Step Sa1: Obtain the on-site image of the area to be moved within the current period, and identify at least one license plate number contained in the on-site image of the area.

[0112] Specifically, the area scene image can be acquired by an image acquisition device set in the area to be moved and then uploaded to an electronic device. The specific acquisition method is not specifically limited in this embodiment. When identifying license plate numbers contained in the area scene image, the area scene image can be directly imported into a trained license plate feature recognition model. The license plate feature recognition model is obtained after training with a large amount of sample data, which includes images of license plate numbers and corresponding manual labels. Since the traffic light allocation duration needs to be adjusted only when there are vehicles in the area to be moved, the area scene image must contain at least one vehicle. When there are no vehicles in the area to be moved, the electronic device controls the corresponding image acquisition device not to acquire images. Since there is at least one vehicle in the area to be moved, at least one license plate number can be identified in the corresponding area scene image. The obtained license plate number is that of a vehicle located in the straight lane of the area to be moved.

[0113] Step Sa2: Obtain road image information within the first preset time period, and determine the vehicle driving image corresponding to each license plate number from the road image information.

[0114] Specifically, the first preset time period is a period of time preceding the current moment, which can be 5 minutes or 8 minutes prior to the current moment. The specific duration of the first preset time period is not specifically limited in this embodiment and can be set by relevant technical personnel. Road image information is collected by multiple image acquisition devices installed in the park and uploaded to an electronic device. The road image information includes image information corresponding to each road in the park within the first preset time period. From the road map information, all vehicles traveling within the park during the first preset time period, as well as the roads traveled by each vehicle, can be identified. The vehicle driving image corresponding to each license plate number is a complete driving image of the vehicle corresponding to each license plate number within the first preset time period.

[0115] Step Sa3: Determine the driving information corresponding to each license plate number within the first preset time period based on the vehicle driving image, and determine the first waiting score corresponding to each license plate number based on the driving information corresponding to each license plate number. The driving information includes the average driving speed and the waiting time.

[0116] Specifically, when determining the average speed of a vehicle based on its driving image, the traffic light markers in the image are first identified. The image is then divided into at least one road segment based on these markers. The vehicle's speed in each road segment is determined by the time it appears at each marker and the path length of that segment. The average speed across all at least one road segment is calculated to obtain the vehicle's average speed. The waiting time is the total time the vehicle spends waiting at traffic lights within a first preset time interval. To determine the waiting time, the image shows the traffic light status and the corresponding duration at each marker. Traffic light statuses include red and green. The waiting time corresponding to the license plate number can be determined based on the traffic light status and its corresponding duration.

[0117] When determining the first waiting score corresponding to a license plate number, it can be determined jointly based on the average driving speed and the periodic waiting time. Specifically, the speed score corresponding to the average driving speed can be determined based on the speed mapping relationship, and the time score corresponding to the periodic waiting time can be determined based on the time mapping relationship. The speed mapping relationship includes scores corresponding to different average driving speeds, and the time mapping relationship includes scores corresponding to different periodic waiting times. The specific content of the speed mapping relationship and the time mapping relationship is not specifically limited in this embodiment of the application, and can be set by relevant technical personnel.

[0118] Step Sa4: Obtain the movement route information corresponding to each license plate number, and determine the second waiting score corresponding to each license plate number based on the movement route information and the area to be moved.

[0119] Specifically, the movement route information corresponding to each license plate number is used to characterize the target route of each vehicle within the park, including the starting position and destination. This movement route information can be uploaded to an electronic device by the driver when the vehicle enters the park, or it can be pre-entered by relevant staff. The method of obtaining the movement route information is not specifically limited in this embodiment. Based on the movement route information, the destination of each vehicle can be determined. Then, based on the distance between the destination and the area to be moved, a second waiting score is determined for each vehicle. By calculating the distance between each vehicle and its destination, the driving demand and driving status of each vehicle can be analyzed. Different distances correspond to different second waiting scores, and the mapping relationship between the distance and the second waiting score is not specifically limited in this embodiment.

[0120] Step Sa5: Based on the first and second waiting scores of each license plate number, determine the waiting score corresponding to each license plate number, and bind each license plate number with the corresponding waiting score to form number binding information.

[0121] Specifically, the final waiting score for a license plate number is the sum of the first waiting score and the second waiting score. By establishing a binding relationship between the license plate number and the waiting score, the corresponding waiting score can be viewed directly when the license plate number is identified.

[0122] Step Sa6: Overlay the number binding information with the road image information to form a regional digital image.

[0123] Specifically, image processing software or programming libraries can be used to overlay and synthesize the number binding information with the road image to form a regional digital image. When overlaying the number binding information onto the road image, parameters such as the position, size, and color of the number binding information on the road image can be adjusted to ensure that it can be clearly displayed on the road image. The specific adjustment method is not specifically limited in this application embodiment and can be set by relevant technical personnel.

[0124] Step S220: Determine the area waiting score of the area to be moved based on each vehicle image and each vehicle's waiting score.

[0125] Specifically, the waiting weight value of the area to be moved is the weighted average of the waiting scores of all vehicles in the area. This can be achieved by first identifying all waiting scores from the digital image of the area, and then using the average calculation formula to determine the area waiting score of the area to be moved. Alternatively, based on the waiting score of each vehicle, a preset number of vehicles can be selected from multiple vehicles, and the average of the waiting scores of the selected vehicles can be calculated. The result of this calculation is then determined as the area waiting score corresponding to the area to be moved. The specific method for determining the area waiting score is not specifically limited in this embodiment of the application and can be set and selected by relevant technical personnel.

[0126] Step S230: Based on the regional waiting score and the first mapping relationship, determine the adjustment duration corresponding to the region to be moved. The first mapping relationship is the mapping relationship between the regional waiting score and the adjustment duration.

[0127] Specifically, different waiting weight values ​​correspond to different adjustment durations. The first mapping relationship includes different regional waiting scores and the adjustment duration can be -2s, +2s, +3s, etc. The specific content of the first mapping relationship is not specifically limited in this application embodiment, but can be set by relevant technical personnel.

[0128] Step S240: Obtain the actual traffic light duration corresponding to the area to be moved in the current week, determine the target traffic light duration based on the adjusted duration, and determine the traffic light duration allocation strategy for the next cycle corresponding to the area to be moved based on the target traffic light duration. The actual traffic light duration is the traffic light duration allocation strategy for the area to be moved in the current cycle.

[0129] Specifically, the target traffic light duration = actual traffic light duration + adjustment duration, where the actual traffic light duration is the duration the traffic light is currently displaying within the current cycle. If the actual traffic light duration for the current cycle is 25 seconds and the adjustment duration is -2 seconds, then the target traffic light duration = 25 - 2 = 23 seconds. Based on the target traffic light duration, a traffic light duration allocation strategy for the next cycle is generated, and the corresponding traffic lights are controlled to illuminate and switch according to this strategy. The target traffic light duration for the next cycle may or may not be the same as the actual traffic light duration for the current cycle.

[0130] In this embodiment of the application, the waiting score of each vehicle in the waiting area can be determined by the regional digital image. The waiting score displayed in the regional digital image can provide a more intuitive view of the driving situation of each vehicle on the road. Adjusting the allocation duration of traffic lights encountered by vehicles during their journey based on the waiting scores of all vehicles can improve the adaptability of the traffic light allocation duration to the actual road traffic flow, thereby improving traffic speed.

[0131] Furthermore, to improve the adaptability of the traffic light duration allocation strategy to actual traffic flow, a second waiting score is determined for each license plate number based on the moving route information and the area to be moved. Specifically, this includes:

[0132] The destination location corresponding to each license plate number is determined based on the movement route; the distance score corresponding to each license plate number is determined based on the interval between the area to be moved and each destination location; the number of traffic lights to be passed for each license plate number is determined based on the movement route information, the area to be moved, and each destination location, and the traffic light score corresponding to each license plate number is determined based on the number of traffic lights to be passed for each license plate number; the second waiting score corresponding to each license plate number is determined based on the distance score and traffic light score corresponding to each license plate number.

[0133] Specifically, the destination corresponding to the license plate number is the vehicle's final destination. Keyword recognition can be performed on the movement route to determine the destination for each license plate number. When determining the distance between the moving area and each final destination, the area to be moved and each final destination can be imported into a pre-defined coordinate system to determine the coordinate points of the moving area and each final destination. Then, the distance between the moving area and each final destination is determined using the point-to-point distance calculation formula. It's worth noting that the distance between the moving area and the final destination may or may not be a straight line. When the distance is not a straight line, the route between the moving area and the final destination can be divided into multiple local straight-line distances, and the distance between the moving area and the final destination is calculated based on these local straight-line distances. Different distances correspond to different distance scores, which can be determined according to a distance score mapping relationship. This distance score mapping relationship includes distance scores corresponding to different distances. The specific content of the distance score mapping relationship is not specifically limited in this embodiment and can be set by relevant technical personnel.

[0134] Besides the distance between the area to be moved and the destination, the amount of traffic light data in the route to be traveled also affects the waiting score corresponding to the license plate number. The route to be traveled is the road between the area to be moved and the destination. When determining the number of traffic lights corresponding to each license plate number, road images can be collected by image acquisition devices set in the route to be traveled, and then the number of traffic lights that each license plate number needs to pass in the route to be traveled can be determined by analyzing the road images. Alternatively, it can be determined based on traffic light distribution data and the route to be traveled. The traffic light distribution data includes the location and number of traffic lights set in all routes. The method of determining the number of traffic lights is not specifically limited in this embodiment and can be set by relevant technical personnel. After determining the number of traffic lights corresponding to each license plate number, the traffic light score corresponding to each license plate number is determined according to the traffic light score mapping relationship. The traffic light score mapping relationship includes the traffic light scores corresponding to different numbers, and the specific content is not specifically limited in this embodiment.

[0135] The second waiting score is the sum of the distance score and the traffic light score. By determining the waiting score for each vehicle based on its distance from the destination and the number of traffic lights to pass, a more comprehensive assessment of each vehicle's driving needs and driving status can be achieved.

[0136] Furthermore, to further improve the adaptability of traffic light allocation durations to actual road conditions, the method also includes:

[0137] Based on the on-site images of the area, determine the vehicle waiting images corresponding to the area to be moved; identify the waiting area of ​​each vehicle in the vehicle waiting image, and determine the area interval between adjacent waiting areas based on each waiting area; compare each area interval with the preset standard interval to determine the number of abnormal intervals, and abnormal intervals are area intervals that are lower than the preset standard intervals; determine the interval score based on the number of abnormal intervals, and update the area waiting score based on the interval score.

[0138] Specifically, vehicle waiting images can be collected by drone equipment. Unlike road images, vehicle waiting images collected by drone equipment can identify the vehicle outline from above, i.e., the waiting area of ​​each vehicle. The waiting area is the area occupied by that vehicle. A trained edge feature recognition model can be used for identification. This model is trained with a large amount of edge sample data, which consists of vehicle images containing waiting areas and corresponding manual labels. The method for identifying waiting areas from vehicle waiting images is not specifically limited in this embodiment and can be set by relevant technical personnel, as long as the waiting areas contained in the vehicle waiting images can be identified.

[0139] The zone interval is the area between adjacent waiting areas in the same row of vehicles, such as... Figure 4 As shown, the specific preset standard interval distance is not specifically limited in this embodiment and can be set by relevant technical personnel. The regional interval is compared with the preset standard interval. When the regional interval is lower than the preset standard interval, it is determined to be an abnormal interval, and the number of abnormal intervals is counted. Different numbers of abnormal intervals correspond to different interval scores. When the regional interval between adjacent vehicles is too small, it may lead to traffic congestion. When the green light is on, vehicles may need a longer time to completely pass through the intersection, resulting in a higher probability of traffic delays and congestion. Therefore, when adjusting the traffic light duration, it is also necessary to analyze the regional intervals between vehicles. The more abnormal intervals there are, the higher the corresponding interval score. This can be determined according to the interval score mapping relationship, which includes the interval scores corresponding to different numbers of abnormal intervals. The specific content is not specifically limited in this embodiment. The interval score is added to the previous regional waiting score to obtain the updated regional waiting score.

[0140] Furthermore, by analyzing the dispersion of vehicles, the adaptability of traffic light timing to actual road conditions can be further improved. Based on this, the method includes:

[0141] Based on the vehicle waiting image, the vehicle dispersion of each vehicle in the waiting image is determined, and the discrete influence value of the area to be moved is determined based on the dispersion of each vehicle. When the vehicle dispersion of the area to be moved is higher than the preset dispersion, the vehicle information corresponding to each license plate number in the area to be moved is identified. The vehicle signal includes the vehicle model and vehicle type. Based on the vehicle information corresponding to each license plate number, the average start time is determined, and the start influence value is determined based on the average start time. The area waiting score is updated based on the discrete influence value and the start influence value.

[0142] Specifically, when traffic jams occur, vehicles typically travel at low speeds or may even come to a standstill, resulting in relatively small gaps between vehicles. This can lead to a chaotic arrangement of vehicles, such as... Figure 5 As shown, neatly arranged vehicles mean that there is a certain distance and order between them, with a low degree of dispersion. In this case, the vehicles move more orderly and stably, which can shorten the time it takes for vehicles to pass through traffic lights. Therefore, when adjusting the duration of traffic light allocation, it is also necessary to analyze and consider the degree of dispersion of vehicles.

[0143] When determining the vehicle dispersion based on a vehicle waiting image, the location of each vehicle can be identified and marked in the image to generate a vehicle position marking image. This image is then imported into a preset coordinate system for data fitting to obtain a data fitting curve. The dispersion of the corresponding vehicle in the waiting image is determined based on this curve. Since the area to be moved may correspond to multiple driving lanes, there may be one or more data fitting curves. The number of data fitting curves is not specifically limited in this embodiment. Different dispersion levels correspond to different discrete influence values. Higher dispersion levels indicate lower vehicle regularity during driving, and correspondingly higher discrete influence values. The correspondence between dispersion levels and discrete influence values ​​can be set by relevant technical personnel.

[0144] Since different types and models of vehicles have different speeds and accelerations during operation, considering vehicle type and model in traffic light timing schemes can better ensure road safety. However, because vehicle type and model have a relatively small impact on traffic congestion, analysis is only performed when the vehicle's compliance during operation is below a limit, i.e., the degree of discrete influence is below a preset degree of discreteness. The specific preset degree of discreteness is not specifically limited in this embodiment. Vehicle information can be retrieved from electronic devices based on license plate numbers, or obtained by feature recognition of images containing vehicles. The specific acquisition method is not specifically limited in this embodiment. Different vehicle models and types correspond to different vehicle start-up times. The start-up time can be determined according to a start-up time reference table, which contains the start-up times corresponding to different vehicle models and types. The average start-up time is the mean of the start-up times of all vehicles in the vehicle waiting image. Different average start-up times correspond to different start-up influence values; the longer the average start-up time, the higher the corresponding movement influence value. The correspondence between average start-up time and start-up influence value can be set by relevant technical personnel.

[0145] For details on how to update the waiting weight value based on discrete influence value and initiation influence value, please refer to the above implementation method of updating the waiting weight value based on interval score, which will not be elaborated here.

[0146] Furthermore, to improve the accuracy of determining discrete impact values, the determination of discrete impact values ​​for the area to be moved based on the discreteness of each vehicle specifically includes:

[0147] Based on the discreteness of each vehicle and the second mapping relationship, the discrete impact value of each vehicle is determined. Based on the discrete impact value of each vehicle, the first discrete impact value corresponding to the area to be moved is determined. The second mapping relationship is the mapping relationship between the discreteness and the discrete impact value of the vehicle. The waiting position of each vehicle is determined based on the vehicle waiting image, and based on the waiting position of each vehicle, at least one straight route is determined. The distance between edge points corresponding to vehicles in the straight route does not exceed a preset threshold. Based on the number of straight routes and the third mapping relationship, the second discrete impact value corresponding to the area to be moved is determined. The third mapping relationship is the mapping relationship between the number of routes and the discrete impact value. Based on the first and second discrete impact values ​​corresponding to the area to be moved, the final discrete impact value of the area to be moved is determined.

[0148] Specifically, the discrete impact value consists of two parts: a first discrete impact value and a second discrete impact value. The first discrete impact value corresponds to the degree of dispersion; the greater the degree of dispersion, the higher the first discrete impact value. The second discrete impact value corresponds to the impact value of the direct routes; the more direct routes there are, the higher the second discrete impact value. Direct routes are formed by the arrangement of vehicles and have a certain standardized channel, such as... Figure 5 As shown, due to the high degree of dispersion, vehicles may stop randomly more frequently, resulting in a direct route that may not match the prescribed number of lanes. However, due to the limited road width, the number of direct routes must not exceed a preset route threshold to ensure safe vehicle operation. When determining a direct route, the initial vehicles included in the initial direct route are first determined based on the waiting position of each vehicle. Then, by comparing the left and right edge coordinates of each initial vehicle, abnormal initial vehicles are removed. The direct route is then formed based on the edge coordinates of the remaining initial vehicles. The difference between the left and / or right edge coordinates of abnormal initial vehicles and the left and / or right edge coordinates of other vehicles in the current initial direct route must exceed a preset difference standard. For example… Figure 5 The initial straight route includes cars a, b, and c. After comparing the edge point coordinates of cars a, b, c, and d, car d is determined to be an abnormal initial vehicle. After removing car d, the final straight route is formed based on the edge point coordinates of cars a, b, and c.

[0149] The specific content of the second and third mapping relationships is not specifically limited in this embodiment of the application, and can be set by relevant technical personnel. The final discrete influence value is the sum of the first discrete influence value and the second discrete influence value.

[0150] To more rationally determine the duration of traffic light allocation, the method also includes:

[0151] Identify the green light passage duration included in the signal duration allocation strategy for the next cycle. When the green light passage duration is higher than the preset passage duration, obtain the supplementary area image corresponding to the intersection within the second preset time period. Determine the corresponding supplementary rate based on the supplementary area image. When the supplementary rate is higher than the preset standard rate, adjust the green light passage duration included in the duration allocation strategy to the preset passage duration.

[0152] Specifically, the signal duration allocation strategy includes the signal light passage duration for the next cycle. The specific preset passage duration is not specifically limited in this embodiment and can be set by relevant technical personnel. The second preset time period is a period before the start of the next cycle, and its specific duration is not specifically limited in this embodiment. Intersections where the road intersects with the current road, such as... Figure 2 As shown, the supplementary area is the corresponding area to be moved in the intersection. The image of the supplementary area can be acquired by an image acquisition device set at the intersection and then uploaded to an electronic device, or it can be acquired by a drone and then uploaded to an electronic device. The specific acquisition method is not specifically limited in this embodiment.

[0153] The replenishment rate is used to characterize the number of vehicles entering the replenishment area within a second preset time period. The more vehicles entering within the second preset time period, the higher the replenishment rate, meaning that the more vehicles are waiting to pass through the replenishment area within the second preset time period. The specific preset standard rate is not specifically limited in this embodiment and can be set by relevant technical personnel. When the replenishment rate is higher than the preset standard rate, it indicates that the number of vehicles waiting to pass through the replenishment area has reached a preset vehicle limit. In this case, the traffic light duration for the next cycle should be optimized and adjusted, i.e., the final passage duration should be controlled within the preset passage duration. If the replenishment rate within the two preset time periods is not higher than the preset standard rate, then when the green light passage duration is higher than the preset duration, no further adjustment is needed. By simultaneously analyzing the traffic flow conditions of the current road segment and intersections, the traffic light allocation duration can be optimized collaboratively, thereby improving the rationality of the traffic light allocation duration and thus facilitating a higher traffic speed.

[0154] The above embodiments describe a traffic light adaptive control method from the perspective of process flow. The following embodiments describe a traffic light adaptive control device from the perspective of virtual module or virtual unit. For details, please refer to the following embodiments.

[0155] This application provides a traffic light adaptive control device, such as... Figure 6 As shown, the device may specifically include: a regional digital image acquisition module 610, a waiting weight value determination module 620, an adjustment duration determination module 630, and a target traffic light duration determination module 640, wherein:

[0156] The regional digital image acquisition module 610 is used to acquire the regional digital image corresponding to the area to be moved within the current cycle. The regional digital image contains the image of each vehicle and the waiting score of each vehicle. The area to be moved is the monitoring area waiting to pass. The area to be moved corresponds to at least one monitoring area. The traffic light equipment corresponding to each monitoring area in the area to be moved is different. The traffic light equipment corresponding to each monitoring area in the area to be moved adopts the same traffic light duration allocation strategy.

[0157] The waiting weight value determination module 620 is used to determine the regional waiting score of the area to be moved based on each vehicle image and each vehicle's waiting score;

[0158] The adjustment duration determination module 630 is used to determine the adjustment duration corresponding to the region to be moved based on the region waiting score and the first mapping relationship. The first mapping relationship is the mapping relationship between the region waiting score and the adjustment duration.

[0159] The target traffic light duration determination module 640 is used to obtain the actual traffic light duration corresponding to the area to be moved in the current week, determine the target traffic light duration based on the adjusted duration, and determine the traffic light duration allocation strategy for the next cycle corresponding to the area to be moved based on the target traffic light duration. The actual traffic light duration is the traffic light duration allocation strategy for the area to be moved in the current cycle.

[0160] In one possible implementation, the device further includes:

[0161] The license plate number recognition module is used to acquire the on-site image of the area to be moved within the current period, and to identify at least one license plate number contained in the on-site image of the area;

[0162] The vehicle driving image determination module is used to acquire road image information within a first preset time period and determine the vehicle driving image corresponding to each license plate number from the road image information;

[0163] The module for determining the first waiting score is used to determine the driving information corresponding to each license plate number within a first preset time period based on the vehicle driving image, and to determine the first waiting score corresponding to each license plate number based on the driving information corresponding to each license plate number. The driving information includes the average driving speed and the waiting time.

[0164] The module for determining the second waiting score is used to obtain the movement route information corresponding to each license plate number, and determine the second waiting score corresponding to each license plate number based on the movement route information and the area to be moved.

[0165] The number binding information module is used to determine the waiting score corresponding to each license plate number based on the first waiting score and the second waiting score of each license plate number, and bind each license plate number with the corresponding waiting score to form number binding information;

[0166] The information overlay module is used to overlay number binding information with road image information to form a regional digital image.

[0167] In one possible implementation, the module for determining the second waiting score, when determining the second waiting score for each license plate number based on the travel route information and the area to be traveled, is specifically used for:

[0168] Determine the destination location corresponding to each license plate number based on the movement route;

[0169] The distance score for each license plate number is determined based on the distance between the area to be moved and each destination location.

[0170] Based on the movement route information, the area to be moved, and each destination location, determine the number of traffic lights to be passed for each license plate number, and determine the traffic light score for each license plate number based on the number of traffic lights to be passed for each license plate number.

[0171] The second waiting score for each license plate number is determined based on the distance score and traffic light score corresponding to each license plate number.

[0172] In one possible implementation, the device further includes:

[0173] The vehicle waiting image determination module is used to determine the vehicle waiting image corresponding to the area to be moved based on the on-site image of the area.

[0174] The area interval determination module is used to identify the waiting area of ​​each vehicle in the vehicle waiting image and determine the area interval between adjacent waiting areas based on each waiting area;

[0175] The module for determining the number of abnormal intervals is used to compare each regional interval with a preset standard interval to determine the number of abnormal intervals. Abnormal intervals are regional intervals that are lower than the preset standard interval.

[0176] The first update module is used to determine the interval score based on the number of abnormal intervals, and update the region waiting score based on the interval score.

[0177] In one possible implementation, the device further includes:

[0178] The discrete impact value determination module is used to determine the degree of vehicle discreteness for each vehicle in the vehicle waiting image, and to determine the discrete impact value of the area to be moved based on the degree of discreteness of each vehicle.

[0179] The vehicle information identification module is used to identify the vehicle information corresponding to each license plate number in the area to be moved when the vehicle dispersion in the area to be moved is higher than the preset dispersion. The vehicle signal includes the vehicle model and vehicle type.

[0180] The module for determining the startup impact value is used to determine the average startup time based on the vehicle information corresponding to each license plate number, and to determine the startup impact value based on the average startup time.

[0181] The second update module is used to update the regional waiting score based on the discrete influence value and the starting influence value.

[0182] In one possible implementation, the discrete impact value determination module, when determining the discrete impact value of the area to be moved based on the discreteness of each vehicle, is specifically used for:

[0183] Based on the degree of dispersion of each vehicle and the second mapping relationship, the discrete influence value of each vehicle is determined. Based on the discrete influence value of each vehicle, the first discrete influence value corresponding to the area to be moved is determined. The second mapping relationship is the mapping relationship between the degree of dispersion and the discrete influence value of the vehicle.

[0184] The waiting position of each vehicle is determined based on the vehicle waiting image, and at least one straight route is determined based on the waiting position of each vehicle. The distance between edge points corresponding to vehicles in the straight route does not exceed a preset threshold.

[0185] Based on the number of direct routes and the third mapping relationship, the second discrete impact value corresponding to the area to be moved is determined, wherein the third mapping relationship is the mapping relationship between the number of routes and the discrete impact value;

[0186] The final discrete influence value of the region to be moved is determined based on the first discrete influence value and the second discrete influence value corresponding to the region to be moved.

[0187] In one possible implementation, the device further includes:

[0188] The passage duration judgment module is used to identify the green light passage duration included in the signal duration allocation strategy of the next cycle. When the green light passage duration is higher than the preset passage duration, the supplementary area image corresponding to the intersection within the second preset time period is obtained.

[0189] The duration adjustment module is used to determine the corresponding supplementation rate based on the supplementation area image. When the supplementation rate is higher than the preset standard rate, the green light passage duration included in the duration allocation strategy is adjusted to the preset passage duration.

[0190] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the traffic light adaptive control device described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0191] This application provides an electronic device, such as... Figure 7 As shown, Figure 7 The illustrated electronic device 700 includes a processor 701 and a memory 703. The processor 701 and the memory 703 are connected, for example, via a bus 702. Optionally, the electronic device 700 may also include a transceiver 704. It should be noted that in practical applications, the transceiver 704 is not limited to one type, and the structure of this electronic device 700 does not constitute a limitation on the embodiments of this application.

[0192] Processor 701 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 701 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0193] Bus 702 may include a pathway for transmitting information between the aforementioned components. Bus 702 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 702 can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 7 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0194] The memory 703 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0195] The memory 703 is used to store application code that executes the solution of this application, and its execution is controlled by the processor 701. The processor 701 is used to execute the application code stored in the memory 703 to implement the content shown in the foregoing method embodiments.

[0196] Electronic devices include, but are not limited to: mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and in-vehicle terminals (such as in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Servers can also be included. Figure 7 The electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0197] This application provides a computer-readable storage medium storing a computer program that, when run on a computer, enables the computer to execute the corresponding content in the aforementioned method embodiments.

[0198] It should be understood that although the steps in the flowcharts of the accompanying figures are shown sequentially as indicated by the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the accompanying figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the sub-steps or stages of other steps.

[0199] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A traffic light adaptive control method, characterized in that, include: Acquire the area digital image corresponding to the area to be moved within the current period. The area digital image contains an image of each vehicle and a waiting score for each vehicle. The area to be moved is a monitoring area waiting to pass. The area to be moved corresponds to at least one monitoring area. The traffic light equipment corresponding to each monitoring area in the area to be moved is different. The traffic light equipment corresponding to each monitoring area in the area to be moved adopts the same traffic light duration allocation strategy. Based on each vehicle image and each vehicle's waiting score, determine the area waiting score of the area to be moved; Based on the regional waiting score and the first mapping relationship, the adjustment duration corresponding to the region to be moved is determined, wherein the first mapping relationship is the mapping relationship between the regional waiting score and the adjustment duration; The actual traffic light duration corresponding to the area to be moved in the current cycle is obtained, the target traffic light duration is determined according to the adjustment duration, and the traffic light duration allocation strategy for the next cycle corresponding to the area to be moved is determined based on the target traffic light duration. The actual traffic light duration is the traffic light duration allocation strategy for the area to be moved in the current cycle. The process of generating the digital image of the region includes: Obtain the on-site image of the area to be moved within the current period, and identify at least one license plate number contained in the on-site image of the area; Obtain road image information within a first preset time period, and determine the vehicle driving image corresponding to each license plate number from the road image information; Based on the vehicle driving images, determine the driving information corresponding to each license plate number within the first preset time period, and based on the driving information corresponding to each license plate number, determine the first waiting score corresponding to each license plate number. The driving information includes the average driving speed and the waiting time. Obtain the movement route information corresponding to each license plate number, and determine the second waiting score corresponding to each license plate number based on the movement route information and the area to be moved; Based on the first and second waiting scores of each license plate number, the waiting score corresponding to each license plate number is determined, and each license plate number is bound to the corresponding waiting score to form number binding information; The number binding information is overlaid with the road image information to form the digital image of the area; The step of determining the second waiting score corresponding to each license plate number based on the movement route information and the area to be moved includes: Determine the destination location corresponding to each license plate number based on the described movement route; Based on the distance between the area to be moved and each destination location, determine the distance score corresponding to each license plate number; Based on the movement route information, the area to be moved, and each destination location, determine the number of traffic lights to be passed for each license plate number, and determine the traffic light score for each license plate number based on the number of traffic lights to be passed for each license plate number. The second waiting score for each license plate number is determined based on the distance score and traffic light score corresponding to each license plate number.

2. The adaptive control method for traffic lights according to claim 1, characterized in that, Also includes: Based on the on-site images of the area, determine the vehicle waiting images corresponding to the area to be moved; Identify the waiting area of ​​each vehicle in the vehicle waiting image, and determine the area interval between adjacent waiting areas based on each waiting area; Each region interval is compared with a preset standard interval to determine the number of abnormal intervals, wherein the abnormal intervals are region intervals that are lower than the preset standard interval; An interval score is determined based on the number of abnormal intervals, and the region waiting score is updated based on the interval score.

3. The traffic light adaptive control method according to claim 2, characterized in that, Also includes: Based on the vehicle waiting image, determine the vehicle dispersion degree of each vehicle in the vehicle waiting image, and based on the dispersion degree of each vehicle, determine the discrete influence value of the area to be moved. When the vehicle dispersion in the area to be moved is higher than a preset dispersion, the vehicle information corresponding to each license plate number in the area to be moved is identified, and the vehicle information includes the vehicle model and vehicle type. Based on the vehicle information corresponding to each license plate number, the average startup time is determined, and the startup impact value is determined based on the average startup time. The regional waiting score is updated based on the discrete influence value and the initiation influence value.

4. The adaptive control method for traffic lights according to claim 3, characterized in that, The determination of the discrete influence value of the area to be moved based on the discreteness of each vehicle includes: Based on the degree of dispersion of each vehicle and the second mapping relationship, the discrete influence value of each vehicle is determined. Based on the discrete influence value of each vehicle, the first discrete influence value corresponding to the area to be moved is determined. The second mapping relationship is the mapping relationship between the degree of dispersion and the discrete influence value of the vehicle. The waiting position of each vehicle is determined based on the vehicle waiting image, and at least one straight route is determined based on the waiting position of each vehicle, wherein the distance between edge points corresponding to vehicles in the straight route does not exceed a preset threshold. Based on the number of direct routes and the third mapping relationship, the second discrete influence value corresponding to the area to be moved is determined, wherein the third mapping relationship is the mapping relationship between the number of routes and the discrete influence value; The final discrete influence value of the region to be moved is determined based on the first discrete influence value and the second discrete influence value corresponding to the region to be moved.

5. The adaptive control method for traffic lights according to claim 1, characterized in that, Also includes: Identify the green light passage duration included in the signal duration allocation strategy for the next cycle. When the green light passage duration is higher than the preset passage duration, obtain the supplementary area image corresponding to the intersection within the second preset time period. The corresponding supplementation rate is determined based on the supplementation area image. When the supplementation rate is higher than the preset standard rate, the green light passage duration included in the duration allocation strategy is adjusted to the preset passage duration.

6. A traffic light adaptive control device, characterized in that, include: The regional digital image acquisition module is used to acquire the regional digital image corresponding to the area to be moved within the current period. The regional digital image contains an image of each vehicle and a waiting score for each vehicle. The area to be moved is a monitoring area waiting to pass. The area to be moved corresponds to at least one monitoring area. The traffic light equipment corresponding to each monitoring area in the area to be moved is different. The traffic light equipment corresponding to each monitoring area in the area to be moved adopts the same traffic light duration allocation strategy. The waiting weight value determination module is used to determine the regional waiting score of the area to be moved based on each vehicle image and each vehicle's waiting score; The adjustment duration determination module is used to determine the adjustment duration corresponding to the region to be moved based on the region waiting score and the first mapping relationship, wherein the first mapping relationship is the mapping relationship between the region waiting score and the adjustment duration; The target traffic light duration determination module is used to obtain the actual traffic light duration corresponding to the area to be moved in the current cycle, determine the target traffic light duration based on the adjustment duration, and determine the traffic light duration allocation strategy for the next cycle corresponding to the area to be moved based on the target traffic light duration. The actual traffic light duration is the traffic light duration allocation strategy for the area to be moved in the current cycle. The license plate number recognition module is used to acquire the on-site image of the area to be moved within the current period, and to recognize at least one license plate number contained in the on-site image of the area; The vehicle driving image determination module is used to acquire road image information within a first preset time period and determine the vehicle driving image corresponding to each license plate number from the road image information; The module for determining the first waiting score is used to determine the driving information corresponding to each license plate number within the first preset time period based on the vehicle driving image, and to determine the first waiting score corresponding to each license plate number based on the driving information corresponding to each license plate number. The driving information includes the average driving speed and the waiting time. The second waiting score determination module is used to obtain the movement route information corresponding to each license plate number, and determine the second waiting score corresponding to each license plate number based on the movement route information and the area to be moved; The number binding information module is used to determine the waiting score corresponding to each license plate number based on the first waiting score and the second waiting score of each license plate number, and bind each license plate number with the corresponding waiting score to form number binding information; An information overlay module is used to overlay the number binding information with the road image information to form a digital image of the area; When determining the second waiting score for each license plate number based on the travel route information and the area to be moved, the second waiting score determination module is specifically used for: Determine the destination location corresponding to each license plate number based on the described movement route; Based on the distance between the area to be moved and each destination location, determine the distance score corresponding to each license plate number; Based on the movement route information, the area to be moved, and each destination location, determine the number of traffic lights to be passed for each license plate number, and determine the traffic light score for each license plate number based on the number of traffic lights to be passed for each license plate number. The second waiting score for each license plate number is determined based on the distance score and traffic light score corresponding to each license plate number.

7. An electronic device, characterized in that, The electronic device includes: At least one processor; Memory; At least one application, wherein the at least one application is stored in memory and configured to be executed by at least one processor, the at least one application being configured to: perform a traffic light adaptive control method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, include: The system stores a computer program capable of being loaded by a processor and executed as described in any one of claims 1-5 for adaptive control of traffic lights.

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