Method for determining work cycle of traffic signal lamp and electronic equipment

Abstract

The embodiment of the invention provides a method for determining the work cycle of a traffic signal lamp and electronic equipment. The method comprises the following steps: acquiring the driving state of a vehicle in a target area; wherein the target area comprises a lane controlled by a traffic signal lamp, and the driving state comprises movement or stop; based on the driving state of the vehicle, determining the lighting working state of the traffic signal lamp; and determining the working period of the traffic signal lamp based on the lighting working state of the traffic signal lamp.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular, to a method for determining the working cycle of a traffic signal and an electronic device. Background Art

[0002] In the vehicle networking intelligent road system, an important application scenario of V2X technology is vehicle green wave speed guidance. In this scenario, the working cycle of the traffic signals at intersections is provided through the Signal Phase and Timing (SPAT) messages broadcast by V2X technology. Vehicles supporting V2X technology can achieve green wave speed by receiving SPAT messages and combining their own location information, so as to guide vehicles to pass through intersections quickly and safely, optimize traffic flow, and reduce traffic jams.

[0003] The working cycle of traffic signals is the basis for realizing green wave speed guidance. How to conveniently obtain the working cycle of traffic signals is a problem that each roadside device needs to solve. In related technologies, roadside devices directly access the intersection signal machine through a wired connection method to obtain the pulse signals of traffic signals, and calculate the working cycle of traffic signals through the pulse signals.

[0004] However, the method of wired access to the signal machine requires an additional construction step in engineering implementation, resulting in high costs. At multi-lane intersections, the roadside device and the signal machine are on both sides or opposite sides of the road, with a relatively long distance, which further increases the construction difficulty and cost. Summary of the Invention

[0005] The purpose of the embodiments of this application is to provide a method for determining the working cycle of a traffic signal and an electronic device, which can at least solve the problem of high cost of obtaining the working cycle of traffic signals.

[0006] In a first aspect, the embodiments of this application provide a method for determining the working cycle of a traffic signal, including: obtaining the driving state of vehicles in a target area; where the target area includes lanes controlled by traffic signals, and the driving state includes moving or stopping; determining the lighting working state of the traffic signal based on the driving state of the vehicles; and determining the working cycle of the traffic signal based on the lighting working state of the traffic signal.

[0007] In a second aspect, the embodiments of this application provide an electronic device, including: a memory, a processor, and computer executable instructions stored on the memory and executable on the processor, where the computer executable instructions, when executed by the processor, implement the steps of the method described in the first aspect.

[0008] In a third aspect, an embodiment of the present application provides a computer-readable storage medium for storing computer-executable instructions, which, when executed by a processor, implement the steps of the method described in the first aspect.

[0009] In an embodiment of the present application, the driving state of a vehicle in a lane controlled by a traffic signal is obtained, the lighting working state of the traffic signal is determined based on the driving state of the vehicle, and the working cycle of the traffic signal can be determined based on the lighting working state of the traffic signal, without the need to be wired to access a signal machine, which is convenient for cost reduction. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments described in the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0011] Figure 1 FIG. shows a schematic flowchart of a method for determining the working cycle of a traffic signal provided by an embodiment of the present application;

[0012] Figure 2 FIG. shows a schematic flowchart of a method for determining the working cycle of a traffic signal provided by an embodiment of the present application;

[0013] Figure 3 FIG. shows a schematic flowchart of a method for determining the working cycle of a traffic signal provided by an embodiment of the present application;

[0014] Figure 4 FIG. shows a specific application schematic diagram of a method for determining the working cycle of a traffic signal provided by an embodiment of the present application;

[0015] Figure 5 FIG. shows a schematic structural diagram of a device for determining the working cycle of a traffic signal provided by an embodiment of the present application;

[0016] Figure 6 FIG. is a schematic hardware structure diagram of an electronic device for executing the method for determining the working cycle of a traffic signal provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] To enable those skilled in the art to better understand the technical solutions in this application, the following will clearly and completely describe the technical solutions in the embodiments of this application in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this application.

[0018] Figure 1 FIG. 1 shows a schematic flow chart of a method for determining the working cycle of a traffic signal provided by an embodiment of this application. This method can be executed by an electronic device (such as a roadside device). In other words, the method can be executed by software or hardware installed in the electronic device. As Figure 1 shown, this method can include the following steps.

[0019] S102: Obtain the driving states of vehicles in the target area; wherein, the target area includes the lanes controlled by traffic signals, and the driving states include moving or stopped.

[0020] In some embodiments, the driving states of vehicles in the target area can be obtained in the following ways: vehicles report autonomously; sensing devices such as cameras on the vehicles identify and report the vehicles around themselves and share the identified vehicle information; intelligent devices on roadside pedestrians, including but not limited to mobile phones, smart glasses, drones, etc., sense and identify the data of vehicles on the lane.

[0021] Optionally, the target area includes the area within a target distance in front of the stop line in the lanes controlled by traffic signals. In some embodiments, when there are multiple vehicles in the area within the target distance in front of the stop line, the driving state of the vehicle closest to the stop line can be obtained.

[0022] In other embodiments, the method further includes: when no vehicles are detected in the target area, determining the lit working state of the traffic signal based on at least one of the following:

[0023] 1) The driving states of vehicles in the oncoming lane of the lane. Generally, at an intersection, the lit working state of the traffic signal in the oncoming lane is the same as that of the traffic signal in the local lane.

[0024] 2) The driving state of vehicles in the lateral lane perpendicular to the said lane. Generally, at an intersection, the lighting working state of the traffic signal in the lane perpendicular to the lane on this side is different from that of the traffic signal in the lane on this side. For example, when the traffic light of the lane on this side is green, the traffic light perpendicular to the lane on this side is red; when the traffic light of the lane on this side is red, the traffic light perpendicular to the lane on this side is green.

[0025] S104: Based on the driving state of the vehicle, determine the lighting working state of the traffic signal.

[0026] The traffic signal mentioned in each embodiment of this application can be a traffic light, and the lighting working state of the traffic signal can include, for example, red light and green light.

[0027] In this step, when the driving state of the vehicle is moving, determine that the lighting working state of the traffic signal is green; when the driving state of the vehicle is stopped, determine that the lighting working state of the traffic signal is red.

[0028] Since the lighting time of the yellow light is short, and when the yellow light is on, some vehicles may accelerate through while some vehicles may stop, this embodiment may not consider the yellow light. By determining the working cycle of the traffic signal multiple times through subsequent embodiments and then averaging, the accuracy of the obtained working cycle of the traffic signal can be improved.

[0029] S106: Based on the lighting working state of the traffic signal, determine the working cycle of the traffic signal.

[0030] The working cycle of the traffic signal can include the cycle of the green light, can also include the cycle of the red light, and can also include the total cycle (for example, the duration between the start time of this green light and the start time of the next green light).

[0031] Optionally, S104 continuously determines the lighting working state of the traffic signal at a first time interval, and the duration of the first time interval is, for example, 1 second. This step of determining the working cycle of the traffic signal based on the lighting working state of the traffic signal includes: determining whether the currently determined lighting working state is the same as the previously determined lighting working state (this step can also be continuously executed at the above first time interval); when the currently determined lighting working state is the same as the previously determined lighting working state, perform an operation of cumulative addition by one with the first time interval as the step; when the currently determined lighting working state is different from the previously determined lighting working state, determine the working cycle of the traffic signal based on the accumulated first time interval.

[0032] Optionally, performing S102 to S106 multiple times can obtain multiple working cycles. As Figure 2 shown, the method further includes the following steps.

[0033] S108: Filter the determined multiple working cycles to remove values with large errors; use the average value of the filtered multiple working cycles as the working cycle of the traffic signal, thereby improving the accuracy of the obtained working cycle of the traffic signal.

[0034] Optionally, as Figure 3 shown, based on any of the above embodiments, the following steps may further be included.

[0035] S110: When the errors of the continuously determined multiple working cycles are less than the first threshold condition, but the errors of the multiple working cycles and the multiple working cycles continuously determined before the first time period are greater than the second threshold condition, it is determined that the working cycle of the traffic signal has changed, and the average value of the multiple working cycles with errors less than the first threshold condition is used as the working cycle of the traffic signal.

[0036] In this embodiment, for a traffic signal with a variable working cycle, when several consecutive calculated working cycles are basically the same (such as the error is less than the first threshold condition), but there is a large deviation from the previous several working cycles (such as the error is greater than the second threshold condition), it can be considered that the working cycle of the current traffic signal has changed, and the average value of the latest determined several working cycles is used as the working cycle of the traffic signal to improve the accuracy.

[0037] Optionally, each of the above embodiments further includes the following steps: performing green wave vehicle speed guidance based on the working cycle of the traffic signal. This embodiment can be applied to the vehicle networking intelligent transportation system and the green wave vehicle speed guidance application scenario.

[0038] For example, in this embodiment, the corresponding relationship between the working cycle of the traffic signal and the current time can be determined, and at the same time, the position, direction, and speed of the vehicles at the intersection are combined for green wave vehicle speed guidance. For example, a reminder is sent to the vehicles in front of the vehicle stop line. For example, it is reminded that the current green light will end in 10 seconds, which is convenient for the driver to determine whether to stop in advance or accelerate through the intersection in combination with the vehicle position and speed; or for example, it is reminded that the current red light will end in 5 seconds, which is convenient for the driver to control the vehicle in time to prepare to pass through the intersection and improve the traffic efficiency.

[0039] Optionally, each of the above embodiments further includes the following steps: determining a control direction of the traffic signal based on a direction of the lane within the target area, where the control direction includes going straight, turning left, or turning right. This embodiment combines the working cycle and the control direction of the traffic signal to obtain complete traffic signal information, facilitating the guidance of the green wave vehicle speed.

[0040] The method for determining the working cycle of a traffic signal provided by an embodiment of the present application obtains the driving state of vehicles in a lane controlled by the traffic signal, determines the lighting working state of the traffic signal based on the driving state of the vehicles, and can determine the working cycle of the traffic signal based on the lighting working state of the traffic signal without wired access to a signal machine, facilitating cost reduction.

[0041] The method for determining the working cycle of a traffic signal provided by an embodiment of the present application is beneficial to reducing the deployment cost of v2x roadside equipment RSU. In the past, spat messages relied on accessing a signal machine to obtain traffic light data. Using this method can eliminate the engineering implementation of accessing the traffic light signal machine and can also implement the deployment of v2x devices at intersections without the support of a traffic light signal machine.

[0042] In each of the above embodiments, the obtaining of the driving state of vehicles in the target area includes: obtaining vehicle big data, where the vehicle big data includes longitude and latitude information of the vehicles and the driving state; obtaining map data, where the map data includes longitude and latitude information of the target area; and obtaining the driving state of vehicles in the target area based on the map data and the vehicle big data.

[0043] The method for determining the working cycle of a traffic signal provided by an embodiment of the present application can obtain vehicle big data through methods such as vehicles reporting independently; cameras on vehicles identifying and reporting; intelligent devices on roadside pedestrians identifying and reporting, etc. Compared with the method of identifying the working cycle of traffic signals through images, it does not have the problem that cameras cannot be reused with other functions caused by deploying cameras next to each traffic signal, and the cost is relatively low.

[0044] Optionally, the target area includes an area within a target distance in front of a stop line in a lane controlled by the traffic signal, and the obtaining of the driving state of vehicles in the target area includes: when there are multiple vehicles in the area within the target distance in front of the stop line, obtaining the driving state of the vehicle closest to the stop line.

[0045] Optionally, the map data includes the longitude and latitude information of the lane and the stop line. Obtaining the driving states of the vehicles in the target area based on the map data and the vehicle big data includes: determining the vehicles located in the lane based on the longitude and latitude information of the lane and the longitude and latitude information of the vehicles in the vehicle big data; determining the vehicle closest to the stop line based on the longitude and latitude information of the vehicles located in the lane and the longitude and latitude information of the stop line; and taking the driving state of the vehicle closest to the stop line as the driving state of the vehicles in the target area.

[0046] To illustrate in detail the method for determining the working cycle of the traffic signal provided in the embodiments of the present application, the following will be described with reference to a specific embodiment. As Figure 4 shown, the method may include the following steps.

[0047] Step 1: Obtain vehicle big data.

[0048] In this embodiment, vehicle big data can be obtained through roadside sensing technology.

[0049] Vehicle big data is obtained through roadside sensing technology by deploying sensing modules at intersections, including but not limited to video cameras, lidar, millimeter-wave radars, infrared radars, etc., to sense the vehicles driving on the road. The sensed data is sent to a computing platform, including but not limited to an edge computing module, a roadside computing unit (RCU), a cloud platform, etc., and vehicle big data is obtained by using, but not limited to, ai large model technology to identify the driving vehicles.

[0050] In addition, methods for obtaining vehicle big data include, but are not limited to, vehicles autonomously reporting their own data. Sensing devices such as cameras on vehicles identify the vehicles around themselves and sharing the identified vehicle information is also a source of vehicle big data. Even the intelligent devices on roadside pedestrians, including but not limited to mobile phones, smart glasses, drones, etc., sensing and identifying the data of the vehicles on the lane can also be a source of big data.

[0051] Vehicle big data includes, but is not limited to, the longitude and latitude information of the vehicle, speed, direction angle, acceleration, and other vehicle driving states.

[0052] Step 2: Locate the vehicle in combination with map data.

[0053] The sources of map data include, but are not limited to, v2x map, etc.

[0054] The map data includes the longitude and latitude information of the lane and the lane stop line. Combining the longitude and latitude of the vehicles in the vehicle big data, the distance between two points of longitude and latitude is calculated using mathematical operations to locate the vehicle on the lane and calculate the distance between the vehicle and the lane stop line.

[0055] Step 3: Determine the traffic light status based on the vehicle behavior at the intersection.

[0056] Select the driving status of the vehicles in front of the stop line at the intersection lane to determine the traffic light status.

[0057] First, filter out several vehicles closest to the stop line based on the distance between the vehicle and the stop line. Vehicles that are too far from the stop line can also be filtered out.

[0058] Based on the speed parameter of the vehicle big data, the driving status of the vehicle can be determined, such as moving or stopped. If the vehicle is stopped, it indicates that the traffic light status of the current lane is red; if the vehicle is moving, it indicates that the traffic light status of the current lane is green.

[0059] If there are several vehicles in the area in front of the stop line, the vehicle closest to the stop line can be used as a reference base point. The closest distance here can be a very short distance, not exceeding 1 meter. It means the vehicle is in front of the stop line or just beyond the stop line. The vehicles within this distance are considered to be the ones that can best represent the traffic light status. If this vehicle is stopped, even if several vehicles behind are moving, the current traffic light will be judged as red.

[0060] The above is an ideal situation. If there are no vehicles in the current lane, the vehicle big data of the oncoming lane can be considered for reference because the traffic light status of the two opposite lanes is the same. Another method is to refer to the vehicle big data of the lateral lane perpendicular to the current lane, but note that the traffic light status of the lateral lane and the current lane is opposite.

[0061] Step 4: Calculate the working cycle of the traffic light.

[0062] Continuously use the vehicle big data to determine the traffic light status at a fixed interval (the first time interval). If the traffic light status is the same in two consecutive times, add the interval time until the traffic light status is different in two consecutive times. The accumulated interval time is the cycle time of the traffic light.

[0063] The time unit of the traffic light is seconds. To obtain a more accurate traffic light cycle time, the first time interval for the vehicle big data to determine the traffic light status should be less than or equal to 1 second, which can be 100 milliseconds, 200 milliseconds or 500 milliseconds.

[0064] Considering that the behavior of each vehicle passing through the traffic light varies, with some vehicles starting faster and some slower during each traffic light conversion, there will be a certain deviation in the calculated cycle time of each traffic light. To reduce the deviation, the average value of the calculated cycle times of multiple traffic lights can be obtained. The more times the cycle time of the traffic light is averaged, which can be 10 times, 20 times, 50 times, or 100 times, the more accurate the average value will be and the closer it will be to the actual cycle time of the traffic light in reality. Before calculating the average value, a filtering process also needs to be performed on each cycle time to filter out values with too large errors, so as to ensure the accuracy of the final average value.

[0065] For traffic lights with variable cycle times, if several consecutive calculated cycle times are basically the same but there is a large deviation from the previous several cycle times, it can be considered that the current cycle time of the traffic light has changed.

[0066] Step 5: Determine the control direction of the traffic light.

[0067] The direction of the traffic light is determined using the direction of the lane. Combining vehicle big data with map data, the vehicle is located in different lanes. If the vehicle in the straight lane is moving, the current traffic light is a straight green light. If the vehicle in the left-turn lane stops, the current traffic light is a left-turn red light, and this is used as the basis for judgment.

[0068] Step 6: Combine the cycle time and direction of the traffic light to obtain the complete traffic light information.

[0069] In the embodiment of the present application, the working cycle of the traffic light is obtained through the big data of the driving state of the vehicle. The driving state of the vehicles at the intersection can be recognized by roadside sensing technology or actively reported by the vehicles. Combining the intersection map information, by positioning the vehicle to the lane position provided by the map and using the lane turning information to define the direction of the current traffic light, the two can be combined to obtain the complete traffic light information, with a relatively low cost.

[0070] Figure 5 The structural schematic diagram of the traffic signal working cycle determination device 500 provided by the embodiment of the present application is shown. The device 500 includes the following modules.

[0071] The acquisition module 502 is used to acquire the driving state of the vehicles in the target area; wherein, the target area includes the lanes controlled by the traffic signal, and the driving state includes moving or stopping.

[0072] The first determination module 504 is used to determine the lighting working state of the traffic signal based on the driving state of the vehicle.

[0073] The second determination module 506 is configured to determine the working cycle of the traffic signal based on the lighting working state of the traffic signal.

[0074] In the embodiment of the present application, the driving state of the vehicles in the lane controlled by the traffic signal is obtained, the lighting working state of the traffic signal is determined based on the driving state of the vehicles, and the working cycle of the traffic signal can be determined based on the lighting working state of the traffic signal, without wired access to the signal machine, which is convenient for cost reduction.

[0075] Optionally, as an embodiment, the first determination module 504 is configured to continuously determine the lighting working state of the traffic signal at a first time interval; the second determination module 506 is configured to determine whether the lighting working state determined this time is the same as the lighting working state determined last time; when the lighting working state determined this time is the same as the lighting working state determined last time, perform an operation of cumulative addition by one with the first time interval as the step; when the lighting working state determined this time is different from the lighting working state determined last time, determine the working cycle of the traffic signal based on the accumulated first time interval.

[0076] Optionally, as an embodiment, the second determination module 506 is further configured to perform filtering processing on the determined multiple working cycles; use the average value of the multiple working cycles after filtering processing as the working cycle of the traffic signal.

[0077] Optionally, as an embodiment, the second determination module 506 is further configured to, when the error of the continuously determined multiple working cycles is less than the first threshold condition, but the error of the multiple working cycles and the multiple working cycles continuously determined before the first time period is greater than the second threshold condition, determine that the working cycle of the traffic signal has changed, and use the average value of the multiple working cycles with the error less than the first threshold condition as the working cycle of the traffic signal.

[0078] Optionally, as an embodiment, the acquisition module 502 is configured to acquire vehicle big data, where the vehicle big data includes the longitude and latitude information and driving state of the vehicle; acquire map data, where the map data includes the longitude and latitude information of the target area; and acquire the driving state of the vehicles in the target area based on the map data and the vehicle big data.

[0079] Optionally, as an embodiment, the target area includes an area within a target distance in front of the stop line in the lane controlled by the traffic signal, and the acquisition module 502 is configured to acquire the driving state of the vehicle closest to the stop line when there are multiple vehicles in the area within the target distance in front of the stop line.

[0080] Optionally, as an embodiment, the map data includes the longitude and latitude information of the lane and the stop line. The obtaining module 502 is configured to determine the vehicles located in the lane based on the longitude and latitude information of the lane and the longitude and latitude information of the vehicles in the vehicle big data; determine the vehicle closest to the stop line based on the longitude and latitude information of the vehicles located in the lane and the longitude and latitude information of the stop line; and use the driving state of the vehicle closest to the stop line as the driving state of the vehicles in the target area.

[0081] Optionally, as an embodiment, the first determining module 504 is further configured to, when no vehicle is detected in the target area, determine the lit working state of the traffic signal based on at least one of the following: the driving state of the vehicles in the oncoming lane of the lane; the driving state of the vehicles in the lateral lane perpendicular to the lane.

[0082] Optionally, as an embodiment, the second determining module 506 is further configured to determine the control direction of the traffic signal based on the direction of the lane in the target area, where the control direction includes straight, left turn, or right turn.

[0083] Optionally, as an embodiment, the device further includes a processing module configured to perform green wave vehicle speed guidance based on the working cycle of the traffic signal.

[0084] The device 500 provided in the embodiment of the present application can execute the various methods described in the foregoing method embodiments, and implement the functions and beneficial effects of the various methods described in the foregoing method embodiments, which will not be elaborated herein.

[0085] Figure 6 The figure shows a schematic hardware structure diagram of an electronic device provided in an embodiment of the present application. Referring to this figure, at the hardware level, the electronic device includes a processor, and optionally, an internal bus, a network interface, and a memory. Among them, the memory may include a memory, such as a high-speed random access memory (Random-Access Memory, RAM), and may also include a non-volatile memory, such as at least one disk memory, etc. Of course, the electronic device may also include other hardware required for other services.

[0086] The processor, network interface, and memory can be interconnected through an internal bus, which can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of simplicity, only a bidirectional arrow is used in the figure to represent it, but it does not mean that there is only one bus or one type of bus.

[0087] A memory for storing programs. Specifically, the program can include program code, and the program code includes computer operation instructions. The memory can include a memory and a non-volatile memory, and provide instructions and data to the processor.

[0088] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming a device for locating the target user at the logical level. The processor executes the program stored in the memory and is specifically used to execute: Figures 1-4 The method disclosed in the illustrated embodiment and implement the functions and beneficial effects of the various methods described in the foregoing method embodiments, which will not be elaborated herein.

[0089] The above as in this application Figures 1-4The method disclosed in the illustrated embodiments can be applied to or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above method can be completed by the integrated logic circuit in the hardware of the processor or instructions in software form. The above-mentioned processor can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of the hardware and software modules in the decoding processor. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory, and the processor reads the information in the memory and combines its hardware to complete the steps of the above method.

[0090] This electronic device can also execute the various methods described in the foregoing method embodiments and achieve the functions and beneficial effects of the various methods described in the foregoing method embodiments, which will not be elaborated here.

[0091] Of course, in addition to the software implementation, the electronic device of the present application does not exclude other implementation manners, such as a logic device or a combination of software and hardware, etc. That is to say, the execution subject of the following processing flow is not limited to each logic unit, and can also be hardware or a logic device.

[0092] The embodiments of the present application also propose a computer-readable storage medium. The computer-readable medium stores one or more programs. When the one or more programs are executed by an electronic device including a plurality of application programs, the electronic device is caused to execute Figures 1-4 the method disclosed in the illustrated embodiments and achieve the functions and beneficial effects of the various methods described in the foregoing method embodiments, which will not be elaborated here.

[0093] Among them, the computer-readable storage medium includes a read-only memory (ROM), a random access memory (RAM), a magnetic disk, an optical disc, or the like.

[0094] Furthermore, an embodiment of the present application also provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the following process is implemented: Figures 1-4 The method disclosed in the illustrated embodiment realizes the functions and beneficial effects of the various methods described in the foregoing method embodiments, and will not be elaborated herein.

[0095] In summary, the above are only the preferred embodiments of the present application and are not used to limit the protection scope of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0096] The systems, devices, modules, or units illustrated in the above embodiments can be specifically implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or any combination of these devices.

[0097] Computer-readable media includes both permanent and non-permanent, removable and non-removable media and can be implemented by any method or technology for storing information. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory media such as modulated data signals and carrier waves.

[0098] It should also be noted that the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed, or further includes elements inherent to such process, method, commodity or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, commodity or device including the said element.

[0099] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for the relevant parts, reference can be made to the partial description of the method embodiment.

Claims

1. A method for determining the working cycle of a traffic signal, comprising: Obtaining the driving state of vehicles in a target area; wherein, the target area includes lanes controlled by the traffic signal, and the driving state includes moving or stopping; Determining the lighting working state of the traffic signal based on the driving state of the vehicles; Determining the working cycle of the traffic signal based on the lighting working state of the traffic signal.

2. The method according to claim 1, wherein, The determining the lighting working state of the traffic signal includes: continuously determining the lighting working state of the traffic signal at a first time interval; the determining the working cycle of the traffic signal based on the lighting working state of the traffic signal includes: Determining whether the lighting working state determined this time is the same as the lighting working state determined last time; In the case where the lighting working state determined this time is the same as the lighting working state determined last time, performing an operation of cumulative addition by one with the first time interval as the step; in the case where the lighting working state determined this time is different from the lighting working state determined last time, determining the working cycle of the traffic signal based on the accumulated first time interval.

3. The method according to claim 1, wherein The method further includes: Performing filtering processing on the determined multiple working cycles; Taking the average value of the multiple filtered working cycles as the working cycle of the traffic signal.

4. The method according to claim 1, wherein The method further includes: In the case where the error of multiple continuously determined working cycles is less than a first threshold condition, but the error of multiple working cycles and multiple working cycles continuously determined before a first time period is greater than a second threshold condition, it is determined that the working cycle of the traffic signal has changed, and the average value of multiple working cycles with an error less than the first threshold condition is taken as the working cycle of the traffic signal.

5. The method according to any one of claims 1 to 4, wherein, The obtaining the driving state of vehicles in the target area includes: Obtaining vehicle big data, where the vehicle big data includes the longitude and latitude information of the vehicle and the driving state; Obtaining map data, where the map data includes the longitude and latitude information of the target area; Obtaining the driving state of vehicles in the target area based on the map data and the vehicle big data.

6. The method according to claim 5, wherein The target area includes an area within a target distance in front of a stop line in a lane controlled by the traffic signal, and the obtaining the driving state of vehicles in the target area includes: In the case where there are multiple vehicles in the area within the target distance in front of the stop line, obtaining the driving state of the vehicle closest to the stop line.

7. The method according to claim 6, wherein, The map data contains the longitude and latitude information of the lane and the stop line, and the obtaining the driving state of vehicles in the target area based on the map data and the vehicle big data includes: Determining the vehicles located in the lane based on the longitude and latitude information of the lane and the longitude and latitude information of the vehicles in the vehicle big data; Determining the vehicle closest to the stop line based on the longitude and latitude information of the vehicles located in the lane and the longitude and latitude information of the stop line; Taking the driving state of the vehicle closest to the stop line as the driving state of the vehicles in the target area.

8. The method according to claim 1, wherein, The method further includes: when no vehicle is detected in the target area, determining the lighting working state of the traffic signal based on at least one of the following: The driving state of the vehicles in the oncoming lane of the lane; The driving state of the vehicles in the lateral lane perpendicular to the lane.

9. The method according to claim 1, wherein The method further includes: Determining the control direction of the traffic signal based on the direction of the lane in the target area, where the control direction includes going straight, turning left, or turning right.

10. The method according to claim 1, wherein The method further includes: Performing a green wave vehicle speed guidance based on the working cycle of the traffic signal.

11. An electronic device, comprising: A processor; And A memory arranged to store computer-executable instructions, which when executed use the processor to execute the steps of the method according to any one of claims 1-10.

12. A computer-readable medium, where the computer-readable medium stores one or more programs, and when the one or more programs are executed by an electronic device including a plurality of application programs, the electronic device is caused to execute the steps of the method according to any one of claims 1-10.

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