Vehicle passing control method and device, equipment and storage medium
By collecting and verifying specific color channels in traffic light areas to identify traffic light colors, the problem of inaccurate traffic control for autonomous vehicles has been solved, achieving higher accuracy in traffic control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- FOSS (HANGZHOU) INTELLIGENT TECH CO LTD
- Filing Date
- 2025-12-22
- Publication Date
- 2026-04-21
AI Technical Summary
The current method of autonomous vehicles relying on the color of images to determine whether to proceed when recognizing traffic lights is not accurate enough, resulting in insufficient accuracy in traffic control.
By acquiring image frames of the area in front of the vehicle, the traffic light area is extracted and its accuracy is verified. The traffic light color is identified using a specific color channel of the traffic light area, and the traffic light color and position are combined to control the passage of vehicles.
It improves the accuracy of traffic control for autonomous vehicles, ensuring that vehicles pass reasonably according to traffic light colors and locations, and reducing misjudgments.
Smart Images
Figure CN121905010A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of autonomous driving technology, and in particular to a vehicle traffic control method, device, equipment and storage medium. Background Technology
[0002] With the rapid development of artificial intelligence technology, autonomous driving has become a core direction for future transportation. In autonomous driving systems, environmental perception is the foundation for vehicle decision-making and planning. Among these, the accurate recognition and understanding of traffic lights directly relates to vehicle safety and compliance with traffic regulations, making it a crucial element of autonomous driving technology. Currently, the forward-looking vision systems of autonomous vehicles rely solely on the color of traffic lights to determine whether to proceed. However, since the colors in captured images are influenced by numerous factors, relying on the colors of traffic lights in photographs to determine whether to proceed is inaccurate. Therefore, improving the accuracy of traffic control for autonomous vehicles has become an urgent problem to be solved. Summary of the Invention
[0003] The main objective of this application is to provide a vehicle traffic control method, device, equipment, and storage medium, which aims to solve the technical problem of how to improve the accuracy of traffic control for autonomous vehicles.
[0004] To achieve the above objectives, this application provides a vehicle traffic control method, which includes the following steps: Acquire the frontal image frame corresponding to the current vehicle, and extract the traffic light area from each of the frontal image frames; The accuracy of the traffic light area is verified based on the traffic light information corresponding to the traffic light area, and the accuracy verification result is obtained. If the accuracy verification result is that the accuracy verification is passed, the traffic light color is identified according to the specific color channel of the traffic light area; Traffic control is performed on the current vehicle based on the traffic light color and the corresponding color position.
[0005] Optionally, the step of acquiring the vehicle-front image frame corresponding to the current vehicle and extracting the traffic light region from each of the vehicle-front image frames includes: Acquire frontal image frames of the current vehicle within a preset time period, and extract candidate regions from each of the frontal image frames; Determine the brightness channel corresponding to each candidate region, and determine the average brightness of each candidate region based on the brightness channel; A luminance signal is generated based on the average luminance, and a Fourier transform is performed on the luminance signal to obtain a frequency domain signal; The traffic light region in each of the vehicle's forward image frames is determined based on the power spectral density corresponding to the frequency domain signal.
[0006] Optionally, determining the traffic light region in each of the vehicle's forward image frames based on the power spectral density corresponding to the frequency domain signal includes: Calculate the power spectral density corresponding to the frequency domain signal, and select the maximum functional spectrum from the functional spectral density based on the target frequency band; Calculate the average power corresponding to the frequency domain signal; The candidate region is determined to be a true value based on the maximum functional spectrum, the average power, and the signal-to-noise ratio threshold. If so, the candidate region is taken as the traffic light region in each of the vehicle's front image frames.
[0007] Optionally, the step of verifying the accuracy of the traffic light area based on the traffic light information corresponding to the traffic light area includes: The traffic light area is segmented by brightness, and candidate bounding boxes are determined based on the segmented areas; Determine the traffic light information corresponding to the traffic light area, wherein the traffic light information includes: spatial location information, visual feature information, and positional relationship; The accuracy of the traffic light region is verified based on the number of candidate bounding boxes and the traffic light information.
[0008] Optionally, controlling the passage of the current vehicle based on the traffic light color and the corresponding color position includes: If the traffic light color and the corresponding color position meet the preset standard, control the current vehicle to proceed according to the traffic light color; If the traffic light color and its corresponding position do not conform to a preset standard, determine the traffic flow information corresponding to the current vehicle, and control the passage of the current vehicle based on the traffic flow information.
[0009] Optionally, the step of controlling the passage of the current vehicle based on the traffic flow information includes: Logical detection is performed on the traffic flow direction in the traffic flow information and the preset correlation to obtain the detection result; A consistency check is performed between the traffic light color and the traffic flow status in the traffic flow information to obtain the check result; If the detection result is "detection passed" and the inspection result is "inspection passed", the current vehicle is controlled to proceed according to the traffic light color.
[0010] Optionally, after performing a consistency check on the traffic light color and the traffic flow status in the traffic flow information, and obtaining the check result, the method further includes: Determine the traffic flow status in the traffic flow information, wherein the traffic flow status includes vertical traffic flow status and perpendicular traffic flow status; If the traffic light color is abnormal, the intersection scene where the current vehicle is located is monitored, and the confidence level corresponding to the intersection scene is determined based on the vertical traffic flow state and the cross-sectional traffic flow state. Based on the confidence level, determine whether the current vehicle meets the passage standards, and obtain the judgment result; Based on the judgment result, traffic control is applied to the current vehicle.
[0011] Furthermore, to achieve the above objectives, this application also provides a vehicle traffic control device, the vehicle traffic control device comprising: The traffic light region extraction module is used to collect the front image frame corresponding to the current vehicle and extract the traffic light region in each of the front image frames. The accuracy verification module is used to verify the accuracy of the traffic light area based on the traffic light information corresponding to the traffic light area, and obtain the accuracy verification result. A traffic light color recognition module is used to identify the traffic light color based on a specific color channel of the traffic light area when the accuracy verification result is that the accuracy verification is passed. The vehicle passage control module is used to control the passage of the current vehicle based on the traffic light color and the corresponding color position.
[0012] In addition, to achieve the above objectives, this application also proposes a vehicle traffic control device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the vehicle traffic control method as described above.
[0013] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the vehicle traffic control method described above.
[0014] This application acquires image frames of the vehicle's front view corresponding to the current vehicle, extracts the traffic light region from each image frame, and then verifies the accuracy of the traffic light region based on the traffic light information corresponding to that region. If the accuracy verification is successful, the traffic light color is identified based on a specific color channel of the traffic light region, and then the current vehicle's passage is controlled based on the traffic light color and its corresponding position. This application first extracts the traffic light region from each image frame of the vehicle's front view, enabling the extraction of the traffic light region containing the traffic lights from the entire image. Then, it verifies the accuracy of the traffic light region based on the traffic light information. If the accuracy verification is successful, the traffic light color is accurately identified based on a specific color channel of the traffic light region, and then the current vehicle's passage is controlled based on the traffic light color and its corresponding position. This improves the accuracy of passage control for autonomous vehicles by considering the relative positions and colors of various traffic lights. Attached Figure Description
[0015] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 This is a flowchart illustrating the first embodiment of the vehicle traffic control method of this application; Figure 2 This is a schematic diagram of the traffic light arrangement according to an embodiment of the vehicle traffic control method of this application; Figure 3 This is a flowchart illustrating the second embodiment of the vehicle traffic control method of this application; Figure 4 This is a flowchart illustrating the third embodiment of the vehicle traffic control method of this application; Figure 5 This is a schematic diagram illustrating a traffic control process based on traffic flow information, according to an embodiment of the vehicle traffic control method of this application. Figure 6 This is a schematic flowchart illustrating vehicle traffic control in the event of abnormal traffic light colors, according to an embodiment of the vehicle traffic control method of this application. Figure 7 This is a schematic diagram of the overall process of an embodiment of the vehicle traffic control method of this application; Figure 8This is a structural block diagram of the first embodiment of the vehicle access control device of this application; Figure 9 This is a schematic diagram of the structure of a vehicle access control device in the hardware operating environment involved in the embodiments of this application.
[0018] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation
[0019] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.
[0020] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.
[0021] It should be noted that the executing entity of this application can be a computing service device with data processing, network communication and program execution functions, such as a vehicle controller, cloud, or other device for controlling vehicle passage.
[0022] Based on this, the embodiments of this application provide a vehicle traffic control method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the vehicle traffic control method of this application.
[0023] In this embodiment, the vehicle traffic control method includes the following steps: Step S10: Acquire the frontal image frame corresponding to the current vehicle, and extract the traffic light area from each of the frontal image frames.
[0024] Understandably, the current vehicle refers to a vehicle with autonomous driving capabilities, which can collect the corresponding frontal image frames of the current vehicle. This can be done through the forward-facing camera on the current vehicle. For example, it can collect continuous frontal images of the vehicle within five or ten seconds to form continuous frontal image frames.
[0025] It should be understood that determining whether a vehicle is in a special scenario where traffic lights are prone to misidentification is crucial. For example, if we need to identify such scenarios, such as sunset, dusty weather, or smoggy weather, we can utilize data from the image signal processing algorithm (ISP algorithm) module. For instance, the automatic white balance algorithm (AWB algorithm) in the ISP module can output the color temperature of the current environment, estimating the current color temperature scene and roughly determining if it's a sunset scene. The automatic exposure algorithm (AE exposure algorithm) in the ISP module can output the brightness of the current environment, estimating the current ambient brightness and determining whether it's daytime or nighttime. The sharpness module in the ISP module can output the sharpness of the current image based on the current environment. Therefore, this embodiment can determine whether the current scene is a special scenario through image signal processing algorithms.
[0026] In practice, the traffic light region can be directly extracted from each vehicle's forward image frame, or it can be extracted only when the current scene is a special scenario. The traffic light region refers to the area in the image ahead of the vehicle that contains traffic lights.
[0027] Step S20: Verify the accuracy of the traffic light area based on the traffic light information corresponding to the traffic light area, and obtain the accuracy verification result.
[0028] Understandably, the traffic light information corresponding to the traffic light area can include spatial location, positional relationship, etc. The spatial location can include the height position of the traffic light, such as the distance from the ground, and can also include the horizontal position of the traffic light, such as being located directly in front of the lane or at the entrance of the intersection. The positional relationship can include the positional relationship of red, green and yellow lights, such as red light, yellow light and green light arranged in sequence.
[0029] In a specific implementation, the accuracy of the traffic light area can be verified based on the traffic light information. In one feasible embodiment, when the traffic light information meets the general standard, the traffic light area can be determined to be accurate, and the accuracy verification result is that the accuracy verification is passed.
[0030] Further, in this embodiment, step S20 includes: performing brightness segmentation on the traffic light area and determining candidate bounding boxes based on the segmented area; determining the traffic light information corresponding to the traffic light area, the traffic light information including: spatial location information, visual feature information, and positional relationship; and verifying the accuracy of the traffic light area based on the number of bounding boxes of the candidate bounding boxes and the traffic light information.
[0031] It should be understood that the traffic light area can be segmented by brightness, the brightness channels can be extracted, and binarization can be performed using an adaptive thresholding method (such as the Otsu algorithm) or a fixed high threshold (such as brightness value > 200) to obtain a mask of the bright area, i.e., the area after brightness segmentation. Then, contour search is performed on the binary mask. For each contour, its area, roundness (4π * area / perimeter 2), and aspect ratio of the circumscribed rectangle are calculated. Contours with moderate area and roundness close to 1 or aspect ratio close to 1 (for circular lights) are retained to generate candidate bounding boxes. Typically, there are 3 candidate bounding boxes, namely red light, green light, and yellow light. The number of candidate bounding boxes can also be 4, namely red light, green light, yellow light, and countdown light.
[0032] Understandably, traffic light information corresponding to a traffic light area can also be determined. This information includes spatial location information, visual characteristics, and positional relationships, all of which are stipulated by national standards. According to the national standard GB14886-2016 "Specifications for the Installation and Setting of Road Traffic Signal Lights," traffic light information has the following characteristics: a) Spatial location: Height: Usually installed at a height of 5.5 to 7 meters, located in the upper half of the image, often against a sky background, rarely appearing on the ground or at vehicle height; Horizontal location: Located directly in front of the lane or at the entrance of an intersection. For multi-lane roads, it is often installed opposite the intersection (cantilever type) or directly above (gantry type). b) Visual characteristics: High brightness: As an active light source, its brightness is much higher than the surrounding environment, especially at night, at dusk, or in tunnels; Specific shape: The lamp body itself is usually circular or arrow-shaped, and the entire lamp housing (backplate) is usually a black rectangle or circle, forming a "T" or "L" shape with the support rod; Color: Under normal lighting conditions, its color is a highly saturated red, yellow, and green. c. Positional relationship: Red and yellow lights almost always appear in a fixed arrangement to form a light group; Repetition: At a large intersection, there may be multiple identical light groups (main lights, auxiliary lights) in the same direction, and there will also be corresponding light groups in the perpendicular direction.
[0033] In practical implementation, based on the strong prior knowledge of the stable and unchanging spacebar position relationship mandated by the national standard (GB14886-2016), the corresponding national standard rules are: Vertical: top - red, middle - yellow, bottom - green; Horizontal: left - red, middle - yellow, right - green (corresponding to the road center to the roadside from left to right). The relative positions of the traffic lights are fixed, refer to... Figure 2 , Figure 2 This is a schematic diagram of the traffic light layout according to an embodiment of the vehicle traffic control method of this application. Figure 2 The image on the left is a schematic diagram of a horizontal arrangement of traffic lights. Figure 2The image on the right is a schematic diagram of a vertical arrangement of traffic lights. The relative positions of these traffic lights are fixed. For example, when there are 3 candidate bounding boxes, in the case of vertical traffic lights, the first light cannot be yellow. If a yellow light is detected, the traffic light area is directly judged to be incorrect. In the case of horizontal traffic lights, the first light on the left must be red, and the traffic light area is accurately determined.
[0034] Additionally, if there are four candidate bounding boxes, a countdown timer is typically used. The countdown timer and the circular traffic light display are quite different. The countdown timer shows a constantly changing number, while the circular traffic light remains a circle. Distinguishing between the two is relatively easy.
[0035] Step S30: If the accuracy verification result is that the accuracy verification is passed, the traffic light color is identified according to the specific color channel of the traffic light area.
[0036] Understandably, if the accuracy verification result is passed, it indicates that there are red and green traffic lights in the traffic light area. At this time, the traffic light color can be identified according to the specific color channel of the traffic light area. The traffic light color can include red, green, and yellow.
[0037] In practical implementation, if the white balance of the image is sometimes faulty, resulting in an overall orange tint, it will also affect the actual captured traffic light color. This embodiment addresses this by recognizing a key characteristic: the response of a true red light in the R channel is significantly higher than that in the G and B channels. Conversely, the response of a true yellow light in the R and G channels is significantly higher than that in the B channel. This relative relationship still exists. We can use this characteristic, rather than simply defining a threshold, to determine whether something is red. Because other modules in the system, such as white balance, may also occasionally malfunction, this approach can be used to make judgments in such cases. Therefore, this embodiment can identify the true traffic light color based on the response of the traffic light area in the R, G, and B channels.
[0038] Step S40: Control the passage of the current vehicle according to the traffic light color and the corresponding color position.
[0039] It should be understood that the position of the illuminated traffic light color within the entire traffic light system can be used to determine whether a vehicle can proceed normally. For example, if the currently detected traffic light color is red and the color position is the first one, then it is considered that the traffic light color and color position are consistent, and the current vehicle can be controlled to proceed normally.
[0040] This embodiment acquires image frames of the vehicle's front view corresponding to the current vehicle, extracts the traffic light region from each image frame, and then verifies the accuracy of the traffic light region based on the traffic light information corresponding to that region. If the accuracy verification is successful, the traffic light color is identified based on a specific color channel of the traffic light region, and then the current vehicle's passage is controlled based on the traffic light color and its corresponding position. This embodiment first extracts the traffic light region from each image frame of the vehicle's front view, enabling the extraction of the traffic light region containing the traffic lights from the entire image. Then, it verifies the accuracy of the traffic light region based on the traffic light information. If the accuracy verification is successful, the traffic light color is accurately identified based on a specific color channel of the traffic light region, and then the current vehicle's passage is controlled based on the traffic light color and its corresponding position. This improves the accuracy of passage control for autonomous vehicles by considering the relative positions and colors of various traffic lights.
[0041] refer to Figure 3 , Figure 3 This is a flowchart illustrating the second embodiment of the vehicle traffic control method of this application.
[0042] Based on the first embodiment described above, in this embodiment, step S10 includes: Step S101: Acquire the frontal image frames of the current vehicle within a preset time period, and extract the candidate regions from each of the frontal image frames.
[0043] Understandably, the preset time period can be a continuous 5 seconds or 10 seconds. In this embodiment, the forward-facing camera of the current vehicle can capture continuous image frames of the vehicle's front within the preset time period and extract candidate regions from these image frames. Candidate regions can be areas in the image frames containing traffic or similar elements. In one feasible embodiment, traffic lights appear sequentially, typically changing from green to yellow and then to red. Therefore, for the target detection module, a short, preset video sequence can be input, and a 3D convolutional network can be used to learn the temporal pattern of traffic light changes. This can effectively filter out momentary misidentifications. This embodiment can use MobileNetV3 to perform end-to-end target detection on each image frame of the vehicle's front. This model can detect, classify (color + shape), and determine the state (on / off), i.e., identify candidate regions in each image frame of the vehicle's front.
[0044] Step S102: Determine the brightness channel corresponding to each candidate region, and determine the average brightness of each candidate region based on the brightness channel.
[0045] It should be understood that LED traffic lights typically flicker at high frequencies above 100Hz, which is imperceptible to the human eye (the human eye perceives it as constantly lit), but cameras can capture this flickering. Identifying this characteristic allows traffic lights to be distinguished from static red signs, vehicle taillights, and other interfering lights. Specifically, a time-domain Fourier transform is performed on candidate regions to analyze their spectral characteristics. If it exhibits the characteristic high-frequency flickering pattern of LED lights, it can be identified; otherwise, it is considered interference.
[0046] In a specific implementation, in order to identify the accurate traffic light area, this embodiment can first determine the brightness channel corresponding to each candidate area. In a series of vehicle front image frames I_t(x,y), the candidate area of each frame can be converted into HSV or Lab color space, the brightness channel L(x,y) can be extracted, and the average brightness of all pixels in the candidate area can be calculated.
[0047] Step S103: Generate a luminance signal based on the average luminance, and perform a Fourier transform on the luminance signal to obtain a frequency domain signal.
[0048] Understandably, a luminance signal S(t) can be generated based on the average luminance of the candidate regions in each frame of the image in front of the vehicle, where S(t) = mean(L(x,y,t)), t = 0, 1, 2, ..., N-1, t represents the t-th frame, and N is the total number of frames in the image in front of the vehicle. Next, the slow changing trends (such as overall illumination changes) that may exist in the luminance signal are eliminated, resulting in the eliminated signal S_detrended(t) = S(t) - mean(s). Then, a window function is applied to the signal to reduce spectral leakage, resulting in the preprocessed signal S_window(t) = S_detrended(t) * w(t), where w(t) is the window function.
[0049] In a practical implementation, the preprocessed signal can be subjected to Fourier transform (FFT) to transform it from the time domain to the frequency domain, resulting in a frequency domain signal F(k) = FFT(S_window(t)), where k = 0, 1, 2, 3, ..., N-1, corresponding to different frequencies.
[0050] Step S104: Determine the traffic light region in each of the vehicle front image frames based on the power spectral density corresponding to the frequency domain signal.
[0051] It should be understood that in order to analyze the frequency energy distribution of the frequency domain signal, the power spectral density P(k) = |F(k)|2 / N is calculated. This represents the power (energy) of each frequency component, which is the main basis for finding the peak. Then, the traffic light area in the image frame in front of each vehicle is determined based on the power spectral density.
[0052] Furthermore, in order to accurately determine the traffic light region in each vehicle's forward image frame, in this embodiment, step S104 includes: calculating the power spectral density corresponding to the frequency domain signal, and selecting the maximum functional spectrum from the functional spectral density based on the target frequency band; calculating the average power corresponding to the frequency domain signal; determining whether the candidate region is a true value based on the maximum functional spectrum, the average power, and the signal-to-noise ratio threshold; if so, then using the candidate region as the traffic light region in each vehicle's forward image frame.
[0053] Understandably, the index k of the Fourier Transform (FFT) can be converted into the actual physical frequency f, f(k) = k * (FrameRate / N), where FrameRate is the camera's frame rate, such as 30fps. The target frequency band can be customized; for example, if the target frequency band is 90-120Hz, the search window is defined as [90Hz, 120Hz]. Based on the target frequency band, the maximum functional spectrum p_max is selected from the functional spectral density.
[0054] It should be understood that the average power p_mean of the frequency domain signal can be calculated over the entire frequency range, and a signal-to-noise ratio threshold SNR_th can be set. The judgment formula is: is_LED = (p_max>SNR_th * p_mean). If is_LED is true, the candidate region is directly used as the traffic light region.
[0055] This embodiment acquires image frames of the vehicle ahead within a preset time period, extracts candidate regions from each image frame, determines the brightness channel corresponding to each candidate region, determines the average brightness of each candidate region based on the brightness channel, generates a brightness signal based on the average brightness, performs a Fourier transform on the brightness signal to obtain a frequency domain signal, and then determines the traffic light region in each image frame based on the power spectral density corresponding to the frequency domain signal.
[0056] refer to Figure 4 , Figure 4 This is a flowchart illustrating the third embodiment of the vehicle traffic control method of this application.
[0057] Based on the above embodiments, in this embodiment, step S40 includes: Step S401: If the traffic light color and the corresponding color position meet the preset standard, control the current vehicle to pass according to the traffic light color.
[0058] Understandably, if the traffic light color and its corresponding position meet the preset standards, for example, if the traffic light color is red and the corresponding position is the first one in the traffic light, it means that it meets the preset standards. At this time, the current vehicle can be controlled to pass according to the traffic light color. When the traffic light color is green, it can pass normally.
[0059] Step S402: If the traffic light color and the corresponding color position do not conform to the preset standard, determine the traffic flow information corresponding to the current vehicle, and control the passage of the current vehicle according to the traffic flow information.
[0060] It should be understood that when the traffic light color and its corresponding position do not conform to preset standards, traffic flow information corresponding to the current vehicle can be obtained based on data from cameras and radar around the vehicle. This traffic flow information comes from data from an independent vehicle detection and tracking model, including: vehicle ID, position, speed, acceleration, and lane ID. This information, combined with the traffic light color and traffic flow information, is then used to control the passage of the current vehicle.
[0061] Furthermore, in order to effectively combine traffic flow information to control the passage of current vehicles, in this embodiment, the step of controlling the passage of current vehicles based on the traffic flow information includes: performing logical detection on the traffic flow direction in the traffic flow information and a preset association relationship to obtain a detection result; performing a consistency check on the traffic light color and the traffic flow state in the traffic flow information to obtain a check result; and controlling the current vehicle to pass according to the traffic light color when the detection result is a pass and the check result is a pass.
[0062] Understandably, during the logic conflict detection process, the perceived traffic light status can be checked for fundamental logical errors based on the intersection's physical topology. A conflict topology table is constructed, which is a pre-defined association in a high-precision map, defining all conflicting traffic flow directions at the intersection. For example, {this lane - straight ahead, perpendicular lane - straight ahead}, {this lane - left turn, perpendicular lane - straight ahead}, and {this lane - straight ahead, perpendicular lane - left turn} can all be considered logical conflict situations. If the traffic flow direction of the current vehicle's current lane is straight ahead, and the traffic flow direction of the perpendicular lane is also straight ahead, then the logic detection result is a failure.
[0063] It should be understood that during the consistency check process, the actual behavior of traffic participants can be used as the ground situation to verify the correctness of the traffic light color. If the traffic light color is "green" but the traffic flow status of the corresponding lane is "stopped", the consistency check will fail; if the traffic light color is "red" but the traffic flow status of the corresponding lane is "going", the consistency check will fail.
[0064] In the specific implementation, refer to Figure 5 , Figure 5 This is a schematic diagram illustrating a traffic control process based on traffic flow information, according to an embodiment of the vehicle traffic control method of this application. Figure 5 As shown, logical conflict detection can be performed based on traffic flow direction and preset associations. If a conflict occurs, a logical conflict alarm is triggered. If no conflict occurs, the logical detection result is "detection passed". Consistency checks can also be performed based on traffic light status and traffic light color. If an inconsistency occurs, a traffic flow inconsistency alarm is triggered. If no inconsistency occurs, the consistency check result is "check passed". Then, a comprehensive decision is made by the safety decision-maker. If both rule one and rule two pass, the current vehicle is controlled to pass normally, that is, the current vehicle is controlled to pass according to the traffic light color. If either rule is triggered, a downgrade strategy is executed to wait conservatively or request takeover or other measures.
[0065] In addition, under the failure mode (traffic light malfunction), the decision-making basis depends entirely on the traffic flow perception results. The game strategy is as follows: Follow through: If there is a vehicle in front of you crossing the intersection in your direction, follow at a low speed; Give way cautiously: If there is continuous traffic flow in the perpendicular direction and there is no trend of deceleration, wait; Proactively pass through: If there are no vehicles in your direction and vehicles in the perpendicular direction are obviously slowing down or stopping at the intersection, judge it as giving way and pass decisively; Conservatively wait: If the scene continues to be chaotic, wait for manual intervention.
[0066] The vehicle light (circular light) processing channel's function is to accurately identify the color status of circular light groups. Technical implementation includes: National standard layout judgment: Candidate frames for the same light group are sorted by y-coordinate (vertical) or x-coordinate (horizontal). The layout is determined based on the number and relative positions of the sorted frames. Status classification (national standard driven): Brightness confirmation: Determines which light in the group is lit (highest brightness). Position mapping: Maps the position of the lit light (top / middle / bottom or left / middle / right) to national standard rules to directly determine the light color. (Based on the strong prior knowledge of the stable and unchanging spacebar position relationship mandated in the national standard (GB14886-2016), the corresponding national standard rules are: Vertical: Top - Red, Middle - Yellow, Bottom - Green; Horizontal: Left - Red, Middle - Yellow, Right - Green (from left to right corresponding to the road center to the roadside)). In actual judgment, the direction of the light pole and the spatial distribution of the candidate area can be used to determine whether the light group is installed vertically or horizontally. Then, by referring to our national standard rules, it can be determined which signal light is lit.
[0067] For example, under the setting sun, the top light of a vertical light group is lit, but its color is orange-toned. Based on color judgment, the probability of it being red or yellow is about the same. However, the algorithm prioritizes the national standard rule of "red above," classifying it as a red light, which effectively solves the problem of color deviation misjudgment. Color auxiliary verification: The HSV color value of the lit area is calculated and checked for consistency with the national standard judgment result. If the difference is too large, a low confidence level is recorded.
[0068] For example, at night, strong light causes camera glare, causing the system to incorrectly identify a red light in its direction as a green light. a) Main process perception: Incorrect output (Type: circular light, Status: green light). b) Post-hoc safety verification module activation: Rule 1 (Logical conflict): The system attempts to identify the traffic light in the perpendicular direction, but may fail due to glare; this rule is not triggered. Rule 2 (Traffic flow verification): The vehicle detection module detects that there are no moving vehicles ahead in this lane, while a vehicle in the perpendicular direction is rapidly crossing the intersection. This seriously contradicts the vehicle's perception that it can proceed straight on a green light. c) Decision and degradation: The system immediately triggers the highest alert for traffic flow inconsistency. The green light confidence level is downgraded to an extremely low level, controlling the vehicle to brake suddenly before the stop line and remain waiting instead of running the red light. At the same time, a strong takeover request is issued to the driver. This embodiment successfully avoided a serious traffic accident caused by a purely visual perception error through multi-source information verification.
[0069] Furthermore, to achieve vehicle traffic control in the event of traffic light color recognition anomalies, in this embodiment, after performing a consistency check on the traffic light color and the traffic flow state in the traffic flow information and obtaining the check result, the method further includes: determining the traffic flow state in the traffic flow information, wherein the traffic flow state includes vertical traffic flow state and perpendicular traffic flow state; if the traffic light color is abnormal, monitoring the intersection scene where the current vehicle is located, and determining the confidence level corresponding to the intersection scene based on the vertical traffic flow state and the perpendicular traffic flow state; judging whether the current vehicle meets the passage standards based on the confidence level, and obtaining a judgment result; and controlling the passage of the current vehicle according to the judgment result.
[0070] Understandably, the vertical and perpendicular traffic flow states can be determined. When there are vehicles or pedestrians crossing in the perpendicular direction, it can be determined that the current lane is not open for passage. However, when there are no vehicles or pedestrians crossing in the perpendicular direction, it is impossible to determine whether the current light is a "green light with no pedestrians" or a "red light with no pedestrians".
[0071] It should be understood that when the relative position of the traffic light area cannot be detected, i.e. when the traffic light color is abnormal, the current intersection scene of the vehicle can be monitored, including normal scene, empty intersection scene, etc., and the confidence level of the intersection scene can be determined based on the vertical traffic flow state and the vertical traffic flow state. For example, 80% confidence level is acceptable in normal scene, and may need to be increased to 95% in empty intersection scene. If the confidence level reaches the passage standard, the result of traffic light color recognition can be relied upon; if the confidence level of the current scene is relatively low, then it needs to be handled with caution, and is divided into two types: (1) a state that humans can take over, prompting humans to take over. (2) a state that humans cannot take over. First, make a short wait at the intersection (e.g., 0.5-1 second), while continuously sensing the traffic light. During this period, instantaneous recognition errors or traffic light state switching can be captured, and perhaps it can be recognized. Then, start slowly with an acceleration significantly lower than the normal value, a state of tentative creeping, while during the creeping process, the sensing system focuses on scanning the direction of conflict. In addition, during the entire passage process, the control system must be in a state of "ready to brake at any time". Once any moving object is detected in the conflict zone, the vehicle should be immediately braked. This approach can be applied in situations where traffic lights are obscured by smog or cameras are partially blocked.
[0072] In the specific implementation, refer to Figure 6 , Figure 6 This is a schematic flowchart illustrating vehicle traffic control in the event of abnormal traffic light colors, according to an embodiment of the vehicle traffic control method of this application. Figure 6 As shown, when the traffic light area cannot be detected in the image in front of the vehicle, i.e. when the traffic light color is abnormal, in order to determine whether the traffic flow meets the passage standard, the confidence level of the traffic flow meets the passage standard. If the confidence level is greater than the threshold, it can be determined that the passage standard is met. If it is met, the vehicle will proceed slowly or prompt human intervention and brake accordingly. If it is not met, the vehicle will stop at the intersection and wait or prompt human intervention.
[0073] In this embodiment, refer to Figure 7 , Figure 7 This is a schematic diagram of the overall process of an embodiment of the vehicle traffic control method of this application, as shown below. Figure 7 As shown, the system can determine whether it is a special scenario based on the input image of the vehicle in front. If so, it can initially identify the traffic light status and the relative position of the lit light, and determine whether it conforms to the relative position of the national standard. If the judgment results are consistent, normal communication is maintained. If the judgment results conflict, it combines traffic flow perception and uses the decision module to determine whether the traffic flow and traffic light position information are consistent. If not, an alarm is triggered, and the system either waits conservatively or combines high-precision map information for further judgment. If so, it proceeds based on traffic flow.
[0074] In this embodiment, when the traffic light color and its corresponding position meet a preset standard, the vehicle is controlled to proceed according to the traffic light color. If the traffic light color and its corresponding position do not meet the preset standard, the traffic flow information corresponding to the vehicle is determined, and the vehicle's passage is controlled based on this information. This embodiment can combine traffic light color and traffic flow information to jointly control the vehicle's passage when the traffic light color and its corresponding position do not meet the preset standard, thus improving the accuracy of passage control for autonomous vehicles.
[0075] Reference Figure 8 , Figure 8 This is a structural block diagram of the first embodiment of the vehicle traffic control device of this application.
[0076] like Figure 8 As shown, the vehicle traffic control device proposed in this application includes: The traffic light region extraction module 10 is used to collect the front image frame corresponding to the current vehicle and extract the traffic light region in each of the front image frames. Accuracy verification module 20 is used to verify the accuracy of the traffic light area based on the traffic light information corresponding to the traffic light area, and obtain the accuracy verification result; Traffic light color recognition module 30 is used to recognize the traffic light color according to a specific color channel of the traffic light area when the accuracy verification result is that the accuracy verification is passed. The vehicle passage control module 40 is used to control the passage of the current vehicle according to the traffic light color and the corresponding color position.
[0077] This embodiment acquires image frames of the vehicle's front view corresponding to the current vehicle, extracts the traffic light region from each image frame, and then verifies the accuracy of the traffic light region based on the traffic light information corresponding to that region. If the accuracy verification is successful, the traffic light color is identified based on a specific color channel of the traffic light region, and then the current vehicle's passage is controlled based on the traffic light color and its corresponding position. This embodiment first extracts the traffic light region from each image frame of the vehicle's front view, enabling the extraction of the traffic light region containing the traffic lights from the entire image. Then, it verifies the accuracy of the traffic light region based on the traffic light information. If the accuracy verification is successful, the traffic light color is accurately identified based on a specific color channel of the traffic light region, and then the current vehicle's passage is controlled based on the traffic light color and its corresponding position. This improves the accuracy of passage control for autonomous vehicles by considering the relative positions and colors of various traffic lights.
[0078] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of this application. In practical applications, those skilled in the art can select some or all of it to achieve the purpose of this embodiment according to actual needs, and no restrictions are imposed here.
[0079] In addition, for technical details not described in detail in this embodiment, please refer to the vehicle traffic control method provided in any embodiment of this application, which will not be repeated here.
[0080] Based on the first embodiment of the vehicle traffic control device described in this application, a second embodiment of the vehicle traffic control device of this application is proposed.
[0081] In this embodiment, the traffic light region extraction module 10 is further configured to acquire image frames of the vehicle ahead within a preset time period, and extract candidate regions from each of the image frames; determine the brightness channel corresponding to each candidate region, and determine the average brightness of each candidate region based on the brightness channel; generate a brightness signal based on the average brightness, and perform a Fourier transform on the brightness signal to obtain a frequency domain signal; and determine the traffic light region in each of the image frames based on the power spectral density corresponding to the frequency domain signal.
[0082] Furthermore, the traffic light region extraction module 10 is also used to calculate the power spectral density corresponding to the frequency domain signal, and select the maximum functional spectrum from the functional spectral density based on the target frequency band; calculate the average power corresponding to the frequency domain signal; determine whether the candidate region is a true value based on the maximum functional spectrum, the average power and the signal-to-noise ratio threshold; if so, the candidate region is used as the traffic light region in each of the vehicle front image frames.
[0083] Furthermore, the accuracy verification module 20 is also used to perform brightness segmentation on the traffic light area and determine candidate bounding boxes based on the segmented area; determine the traffic light information corresponding to the traffic light area, the traffic light information including: spatial location information, visual feature information and positional relationship; and perform accuracy verification on the traffic light area based on the number of bounding boxes of the candidate bounding boxes and the traffic light information.
[0084] Furthermore, the vehicle passage control module 40 is also used to control the current vehicle to pass according to the traffic light color when the traffic light color and the corresponding color position meet the preset standard; and to determine the traffic flow information corresponding to the current vehicle when the traffic light color and the corresponding color position do not meet the preset standard, and to control the passage of the current vehicle according to the traffic flow information.
[0085] Furthermore, the vehicle passage control module 40 is also used to perform logical detection on the traffic flow direction in the traffic flow information and the preset association relationship to obtain the detection result; to perform consistency verification on the traffic light color and the traffic flow state in the traffic flow information to obtain the verification result; and to control the current vehicle to pass according to the traffic light color when the detection result is a successful detection and the verification result is a successful verification.
[0086] Furthermore, the vehicle passage control module 40 is also used to determine the traffic flow state in the traffic flow information, the traffic flow state including vertical traffic flow state and perpendicular traffic flow state; if the traffic light color is abnormal, the module monitors the intersection scene where the current vehicle is located, and determines the confidence level corresponding to the intersection scene based on the vertical traffic flow state and the perpendicular traffic flow state; based on the confidence level, the module judges whether the current vehicle meets the passage standards and obtains a judgment result; and performs passage control on the current vehicle according to the judgment result.
[0087] Other embodiments or specific implementations of the vehicle access control device of this application can be found in the above-described method embodiments, and will not be repeated here.
[0088] This application provides a vehicle access control device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the vehicle access control method in the above embodiment 1.
[0089] The following is for reference. Figure 9 The diagram illustrates a structural schematic of a vehicle access control device suitable for implementing embodiments of this application. The vehicle access control device in the embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital radio receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 9 The vehicle access control device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.
[0090] like Figure 9As shown, the vehicle access control device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the vehicle access control device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touchscreen, touchpad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), speaker, vibrator, etc.; storage devices 1003 including, for example, magnetic tape, hard disk, etc.; and communication devices 1009. Communication device 1009 allows the vehicle access control device to communicate wirelessly or wiredly with other devices to exchange data. Although the figures show vehicle access control devices with various systems, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.
[0091] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.
[0092] The vehicle access control device provided in this application, employing the vehicle access control method in the above embodiments, can solve the technical problem of how to improve the accuracy of access control for autonomous vehicles. Compared with the prior art, the beneficial effects of the vehicle access control device provided in this application are the same as those of the vehicle access control method provided in the above embodiments, and other technical features in this vehicle access control device are the same as those disclosed in the previous embodiment method, and will not be repeated here.
[0093] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.
[0094] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
[0095] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the vehicle traffic control method in the above embodiments.
[0096] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.
[0097] The aforementioned computer-readable storage medium may be included in the vehicle access control device; or it may exist independently and not be assembled into the vehicle access control device.
[0098] The aforementioned computer-readable storage medium carries one or more programs that, when executed by the vehicle traffic control device, cause the vehicle traffic control device to: acquire a forward image frame corresponding to the current vehicle and extract the traffic light region from each forward image frame; perform accuracy verification on the traffic light region based on the traffic light information corresponding to the traffic light region, and obtain an accuracy verification result; if the accuracy verification result is that the accuracy verification is passed, identify the traffic light color based on a specific color channel of the traffic light region; and perform traffic control on the current vehicle based on the traffic light color and the corresponding color position.
[0099] Computer program code for performing the operations of this application can be written in one or more programming languages or a combination thereof. These programming languages include object-oriented programming languages—such as Python, Java, Smalltalk, and C++—and conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).
[0100] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.
[0101] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.
[0102] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described vehicle traffic control method, and can solve the technical problem of how to improve the accuracy of traffic control for autonomous vehicles. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the vehicle traffic control method provided in the above embodiments, and will not be repeated here.
[0103] The above description is only a part of the embodiments of this application and does not limit the scope of protection of this application. All equivalent structural transformations made under the technical concept of this application and using the content of this application specification and drawings, or direct / indirect applications in other related technical fields, are included in the scope of protection of this application.
Claims
1. A vehicle traffic control method, characterized in that, The vehicle traffic control method includes the following steps: Acquire the frontal image frame corresponding to the current vehicle, and extract the traffic light area from each of the frontal image frames; The accuracy of the traffic light area is verified based on the traffic light information corresponding to the traffic light area, and the accuracy verification result is obtained. If the accuracy verification result is that the accuracy verification is passed, the traffic light color is identified according to the specific color channel of the traffic light area; Traffic control is performed on the current vehicle based on the traffic light color and the corresponding color position.
2. The vehicle traffic control method as described in claim 1, characterized in that, The step of acquiring the frontal image frame corresponding to the current vehicle and extracting the traffic light region from each of the frontal image frames includes: Acquire frontal image frames of the current vehicle within a preset time period, and extract candidate regions from each of the frontal image frames; Determine the brightness channel corresponding to each candidate region, and determine the average brightness of each candidate region based on the brightness channel; A luminance signal is generated based on the average luminance, and a Fourier transform is performed on the luminance signal to obtain a frequency domain signal; The traffic light region in each of the vehicle's forward image frames is determined based on the power spectral density corresponding to the frequency domain signal.
3. The vehicle traffic control method as described in claim 2, characterized in that, Determining the traffic light region in each of the vehicle's forward image frames based on the power spectral density corresponding to the frequency domain signal includes: Calculate the power spectral density corresponding to the frequency domain signal, and select the maximum functional spectrum from the functional spectral density based on the target frequency band; Calculate the average power corresponding to the frequency domain signal; The candidate region is determined to be a true value based on the maximum functional spectrum, the average power, and the signal-to-noise ratio threshold. If so, the candidate region is taken as the traffic light region in each of the vehicle's front image frames.
4. The vehicle traffic control method as described in claim 1, characterized in that, The step of verifying the accuracy of the traffic light area based on the traffic light information corresponding to the traffic light area includes: The traffic light area is segmented by brightness, and candidate bounding boxes are determined based on the segmented areas; Determine the traffic light information corresponding to the traffic light area, wherein the traffic light information includes: spatial location information, visual feature information, and positional relationship; The accuracy of the traffic light region is verified based on the number of candidate bounding boxes and the traffic light information.
5. The vehicle traffic control method according to any one of claims 1 to 4, characterized in that, The step of controlling the passage of the current vehicle based on the traffic light color and the corresponding color position includes: If the traffic light color and the corresponding color position meet the preset standard, control the current vehicle to proceed according to the traffic light color; If the traffic light color and its corresponding position do not conform to a preset standard, determine the traffic flow information corresponding to the current vehicle, and control the passage of the current vehicle based on the traffic flow information.
6. The vehicle traffic control method as described in claim 5, characterized in that, The step of controlling the passage of the current vehicle based on the traffic flow information includes: Logical detection is performed on the traffic flow direction in the traffic flow information and the preset correlation to obtain the detection result; A consistency check is performed between the traffic light color and the traffic flow status in the traffic flow information to obtain the check result; If the detection result is "detection passed" and the inspection result is "inspection passed", the current vehicle is controlled to proceed according to the traffic light color.
7. The vehicle traffic control method as described in claim 6, characterized in that, After performing a consistency check on the traffic light color and the traffic flow status in the traffic flow information, and obtaining the check result, the method further includes: Determine the traffic flow status in the traffic flow information, wherein the traffic flow status includes vertical traffic flow status and perpendicular traffic flow status; If the traffic light color is abnormal, the intersection scene where the current vehicle is located is monitored, and the confidence level corresponding to the intersection scene is determined based on the vertical traffic flow state and the cross-sectional traffic flow state. Based on the confidence level, determine whether the current vehicle meets the passage standards, and obtain the judgment result; Based on the judgment result, traffic control is applied to the current vehicle.
8. A vehicle passage control device, characterized in that, The vehicle access control device includes: The traffic light region extraction module is used to collect the front image frame corresponding to the current vehicle and extract the traffic light region in each of the front image frames. The accuracy verification module is used to verify the accuracy of the traffic light area based on the traffic light information corresponding to the traffic light area, and obtain the accuracy verification result. A traffic light color recognition module is used to identify the traffic light color based on a specific color channel of the traffic light area when the accuracy verification result is that the accuracy verification is passed. The vehicle passage control module is used to control the passage of the current vehicle based on the traffic light color and the corresponding color position.
9. A vehicle traffic control device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the vehicle traffic control method as described in any one of claims 1 to 7.
10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the vehicle traffic control method as described in any one of claims 1 to 7.