Vehicle lane changing early warning processing method, device and equipment and medium

Abstract

The invention relates to the field of vehicle control, in particular to a vehicle lane changing early warning processing method and device, equipment and a medium. According to the method, the collision risk quantitative data of the adjacent vehicles during turning is detected firstly, then the risk type is analyzed, and finally the intervention strategy is matched, so that the real collision risk and the risk-free scene can be accurately distinguished. In the special scene that the vehicle turns at a low speed, the situation that alarm is not needed can be recognized, the situation that sound-light alarm is triggered when an adjacent vehicle enters an alarm area is avoided, interference to a driver is reduced, the driving experience is improved, and the problem that an L2-level lane changing auxiliary function lacks a targeted alarm suppression strategy is effectively solved.

Description

Technical Field

[0001] This invention relates to the field of vehicle control, and specifically to a method, device, equipment, and medium for processing vehicle lane change warnings. Background Technology

[0002] In the application of Lane Change Assist (LCA) function in L2 level vehicles, when the vehicle is in the second lane to turn left or right at a traffic light intersection and turns with the turn signal on, due to the limitation of the millimeter-wave radar installation position and the influence of the target vehicle's driving trajectory, vehicles in the first lane to the left or the first lane to the right are likely to enter the LCA alarm area, triggering a level 2 alarm (exterior rearview mirror lights flashing and buzzer warning).

[0003] However, in such scenarios, the vehicle turns at a low speed, and the driver has sufficient ability to make safe driving judgments, so there is no need for LCA alarm intervention. The existing LCA function is based on a positive triggering strategy of "the target enters the alarm range and the conditions are met, and it is triggered", which lacks an alarm suppression mechanism for such special scenarios. As a result, the sound and light alarms interfere with the driver and passengers and affect the driving experience, failing to reflect the humanized design of assisted driving. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method, apparatus, device and medium for processing vehicle lane change warning, in order to solve the problem that the L2 level LCA function, in the special scenario of the vehicle turning at low speed, will trigger unnecessary audible and visual alarms, interfere with normal driving and affect the user experience due to the lack of a targeted alarm suppression strategy.

[0005] In a first aspect, embodiments of the present invention provide a method for processing vehicle lane change warnings, the method comprising:

[0006] When the lane change assist function of the vehicle is activated and the warning conditions corresponding to the lane change assist function are met, the collision risk quantification data between the vehicle and adjacent vehicles during the turning process is detected.

[0007] The collision risk quantification data is used to analyze the risk type corresponding to the adjacent vehicles;

[0008] Obtain the intervention strategy corresponding to the risk type, and perform corresponding handling operations on the lane change assist function based on the intervention strategy.

[0009] Furthermore, the step of analyzing the risk type corresponding to adjacent vehicles using the collision risk quantification data includes:

[0010] From the collision risk quantification data, obtain the lateral distance between each adjacent vehicle, the first duration corresponding to the lateral distance, the lateral movement data, and the second duration corresponding to the lateral movement data;

[0011] The first vehicle whose lateral distance is less than a preset distance and whose first duration is greater than a first threshold is obtained from the adjacent vehicles, and the risk type corresponding to the first vehicle is determined to be a collision risk type.

[0012] The second vehicle whose lateral motion data is greater than a preset threshold and whose second duration is less than a second threshold is obtained from the other vehicles in the adjacent vehicles (excluding the first vehicle), and the risk type corresponding to the second vehicle is determined to be a collision risk type.

[0013] The risk type corresponding to the other vehicles among the adjacent vehicles, excluding the first and second vehicles, is the no-collision risk type.

[0014] Furthermore, the step of performing corresponding actions on the lane change assist function based on the intervention strategy includes:

[0015] If the risk type is a non-collision risk type, then control the vehicle's lane change assist function to enter a suppressed state.

[0016] Furthermore, the control of the vehicle's lane change assist function to enter a suppressed state includes:

[0017] The system detects the driver's driving status in the vehicle and the environmental information of the vehicle's driving environment.

[0018] Analyze the driving state and the environmental information to determine the suppression intensity;

[0019] The lane change assist function of the vehicle is controlled to enter a suppressed state according to the suppression intensity.

[0020] Furthermore, the analysis of the driving state and the environmental information to determine the suppression intensity includes:

[0021] The driver's engagement index is calculated based on the driving state;

[0022] The uncertainty coefficient of the driving environment is calculated based on the environmental information;

[0023] The influence score is calculated using the participation index and the uncertainty coefficient, and the suppression intensity is determined using the score range in which the influence score falls.

[0024] Furthermore, the step of performing corresponding actions on the lane change assist function based on the intervention strategy includes:

[0025] If the risk type is a collision risk type, detect whether the driver has pressed the accelerator pedal.

[0026] If a stampede occurs, the lane change assist function of the vehicle is controlled to enter a suppressed state; or, if no stampede occurs, a warning prompt is executed on the first and second vehicles corresponding to the collision risk type, the first and second vehicles are detected to see if they respond to the warning prompt, the detection result is obtained, and the lane change assist function is handled accordingly based on the detection result.

[0027] Furthermore, the step of performing corresponding processing operations on the lane change assist function based on the detection results includes:

[0028] If the detection result indicates that both the first vehicle and the second vehicle responded to the warning prompt, then it is analyzed whether the first vehicle and the second vehicle are still at risk of collision after responding to the warning prompt. If they are not at risk of collision, then the lane change assist function is controlled to enter the monitoring state; or, if they are still at risk of collision, then the lane change assist function is controlled to enter the warning state, and a reminder operation is performed on the driver of the vehicle through the lane change assist function; or...

[0029] If the detection result indicates that neither the first vehicle nor the second vehicle responds to the warning prompt, then the lane change assist function is controlled to enter the warning state.

[0030] Secondly, embodiments of the present invention provide a vehicle lane change warning suppression device, the device comprising:

[0031] The detection module is used to detect the collision risk quantification data between the vehicle and adjacent vehicles during the turning process when the vehicle's lane change assist function is activated and the warning conditions corresponding to the lane change assist function are met.

[0032] The analysis module is used to analyze the risk type corresponding to the adjacent vehicles using the collision risk quantification data;

[0033] The execution module is used to obtain the intervention strategy corresponding to the risk type, and to perform corresponding handling operations on the lane change assist function based on the intervention strategy.

[0034] Thirdly, embodiments of the present invention provide a computer device, including: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the method described in the first aspect or any corresponding embodiment thereof.

[0035] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing computer instructions that cause a computer to perform the method described in the first aspect or any of its corresponding embodiments.

[0036] This application first detects and quantifies the collision risk data of adjacent vehicles during a turn, then analyzes the risk type, and finally matches intervention strategies. This allows for accurate differentiation between real collision risks and risk-free scenarios. In the special scenario of a vehicle turning at low speed, it can identify situations where no alarm is needed, avoiding triggering audible and visual alarms when adjacent vehicles enter the alarm zone. This reduces driver interference, improves the driving experience, and effectively solves the problem of the lack of targeted alarm suppression strategies in L2-level lane change assist functions. Attached Figure Description

[0037] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0038] Figure 1 This is a flowchart illustrating a method for processing vehicle lane change warning according to some embodiments of the present invention;

[0039] Figure 2 This is a flowchart illustrating another method for processing lane change warnings for vehicles according to some embodiments of the present invention.

[0040] Figure 3 This is a structural block diagram of a vehicle lane change warning processing device according to an embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] According to embodiments of the present invention, a method, apparatus, device, and medium for processing vehicle lane change warning are provided. It should be noted that the steps shown in the flowcharts in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0044] This embodiment provides a method for processing vehicle lane change warnings. Figure 1 This is a flowchart of a vehicle lane change warning processing method according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0045] Step S101: When the vehicle's lane change assist function is activated and the warning conditions corresponding to the lane change assist function are met, detect the collision risk quantification data between adjacent vehicles during the turning process.

[0046] In this embodiment, when the forward-facing camera detects a traffic light at an intersection, or when the surround-view camera detects a reversing turn at an intersection, the lane change assist function (LCA) will automatically activate, and then the system will detect whether the vehicle meets the alarm conditions corresponding to the LCA function.

[0047] When the vehicle's Lane Change Assist (LCA) function is activated and the warning conditions are met (such as the driver activating the turn signal, the vehicle speed being within the effective operating range of 20-120 km / h, and the steering wheel angle being greater than 5°), the collision risk quantification data detection process will be initiated. This process relies on the vehicle's multi-sensor fusion system, including millimeter-wave radar, surround-view cameras, and ultrasonic radar, to monitor adjacent vehicles in real time during the vehicle's turning process.

[0048] Specifically, the millimeter-wave radar is responsible for collecting the lateral distance between adjacent vehicles and the vehicle itself (i.e., the straight-line distance between the two vehicles perpendicular to the direction of travel of the vehicle itself), and continuously sampling and recording the trend of the distance change, while accumulating the first duration when the lateral distance is within a certain range (such as the duration when the lateral distance is less than 2 meters); the surround-view camera tracks the movement trajectory of adjacent vehicles through image recognition technology, and calculates the lateral motion data (including lateral velocity and lateral acceleration) by combining the inter-frame difference algorithm, that is, the movement speed and rate of change of the adjacent vehicles relative to the vehicle itself in the lateral direction, and simultaneously records the second duration when the lateral motion data exceeds a preset benchmark value (such as the duration when the lateral velocity is greater than 0.5 m / s).

[0049] The data collected by the sensors undergoes filtering (such as Kalman filtering) to eliminate noise interference and ensure the accuracy of quantitative indicators such as lateral distance, first duration, lateral motion data, and second duration. Furthermore, the detection range is dynamically adjusted based on the vehicle's turning radius (calculated using a steering wheel angle sensor and vehicle speed). For example, in sharp turns, the lateral monitoring width is reduced to avoid mistakenly including vehicles traveling normally in the oncoming lane within the monitoring range. This ultimately forms a structured collision risk quantification dataset, providing a data foundation for subsequent risk type analysis.

[0050] Step S102: Analyze the risk types of adjacent vehicles using collision risk quantification data.

[0051] In this embodiment of the application, collision risk quantification data is used to analyze the risk type corresponding to adjacent vehicles, including the following steps A1-A4:

[0052] Step A1: Obtain the lateral distance between each adjacent vehicle, the first duration corresponding to the lateral distance, the lateral motion data, and the second duration corresponding to the lateral motion data from the collision risk quantification data.

[0053] Step A2: Obtain the first vehicle from the adjacent vehicles whose lateral distance is less than a preset distance and whose first duration is greater than a first threshold, and determine the risk type corresponding to the first vehicle as a collision risk type.

[0054] Specifically, the lateral distance and initial duration of each adjacent vehicle are verified one by one. A preset distance threshold (e.g., 1.5 meters, dynamically adjustable based on vehicle type) and an initial duration threshold (e.g., 1 second) are used. A comparison algorithm filters out a set of vehicles that meet the criteria of "lateral distance < preset distance" and "initial duration > first threshold," and these vehicles are marked as the first vehicle. In the judgment logic, the lateral distance must consistently be less than the threshold for a set duration to avoid misjudgments due to instantaneous distance fluctuations (e.g., adjacent vehicles briefly changing lanes and then immediately moving away). For adjacent vehicles marked as the first vehicle, the system automatically categorizes their risk type as a collision risk type, as these vehicles are continuously in close proximity, posing a direct risk of intersection with the vehicle's turning trajectory.

[0055] Step A3: Obtain the second vehicle from the adjacent vehicles other than the first vehicle whose lateral motion data is greater than a preset threshold and whose second duration is less than the second threshold, and determine the risk type corresponding to the second vehicle as the collision risk type.

[0056] Specifically, after excluding adjacent vehicles already identified as the first vehicle, the system analyzes the lateral movement data and the second duration of the remaining vehicles. A preset lateral movement threshold is used (e.g., lateral velocity > 1 m / s or lateral acceleration > 0.8 m / s²). 2The system uses a second time threshold (e.g., 0.5 seconds) and a motion trend algorithm to filter out vehicles that meet the criteria of "lateral motion data > preset threshold" and "second duration < second threshold," marking them as the second vehicle. This logic targets vehicles that approach rapidly in the short term (e.g., adjacent vehicles suddenly accelerating into the system's trajectory). Although the distance is not sustained, the motion trend already poses a potential risk. The system classifies the risk type of the second vehicle as a collision risk type, ensuring timely response to dynamically approaching dangerous targets.

[0057] Step A4: Assign the risk type to the vehicles other than the first and second vehicles among the adjacent vehicles as the no-collision risk type.

[0058] Specifically, all adjacent vehicles are ultimately categorized. The remaining vehicles, neither labeled as the first nor the second vehicle, are uniformly classified as having no collision risk. These vehicles are characterized by: a lateral distance consistently greater than a preset distance, and lateral movement data not exceeding a threshold, or slight movement without a sustained approach trend. During the classification process, an elimination method is used to ensure no omissions, while edge data (such as lateral distances slightly higher than the preset value but close to the threshold) undergoes secondary verification to avoid misclassification as risk-free. The final classification result is: "First vehicle + Second vehicle = Collision risk type" and "Remaining = No collision risk type".

[0059] Step S103: Obtain the intervention strategy corresponding to the risk type, and perform corresponding handling operations on the lane change assist function based on the intervention strategy.

[0060] In this embodiment of the application, the lane change assist function is subjected to corresponding handling operations based on the intervention strategy, including: if the risk type is a no-collision risk type, then the lane change assist function of the vehicle is controlled to enter a suppressed state.

[0061] In this embodiment of the application, controlling the vehicle's lane change assist function to enter a suppressed state includes the following steps B1-B3:

[0062] Step B1: Detect the driver's driving status in the vehicle and the environmental information of the vehicle's driving environment.

[0063] Specifically, detecting the driver's driving status and environmental information of the vehicle's driving environment requires the collaborative work of a multi-dimensional sensor network and data acquisition system. Regarding the driver's driving status, the system primarily relies on the Driver Monitoring System (DMS) cameras to collect data on the driver's facial features and body movements, including gaze direction (using eye-tracking technology to determine whether the driver is focused on the road or deviating from it), blink frequency (less than 15 blinks per minute indicates fatigue), head posture (such as the head tilt angle caused by looking down at a phone), steering wheel operation frequency (no micro-adjustment within 10 seconds indicates distraction), and pedal operation reaction speed (the delay from perceiving a risk to pressing the pedal). Simultaneously, the steering wheel torque sensor and accelerator pedal travel sensor record the driver's force and frequency of vehicle control, comprehensively assessing the degree of active driving participation.

[0064] Environmental information for the driving environment is collected comprehensively through an onboard sensor matrix: millimeter-wave radar and lidar are responsible for detecting the distribution density, relative speed, and distance of surrounding vehicles; surround-view cameras identify road types (highways, urban arterial roads, rural roads), traffic signs (such as speed limits and lane change prohibitions), lane line integrity, and intersection complexity (presence of traffic lights and intersection type); rain sensors, light sensors, and atmospheric pressure sensors record weather conditions (sunny, rainy, foggy), light intensity (direct sunlight, backlight, low light at night), and visibility, respectively; GPS and high-precision map data provide real-time location information, along with regional traffic congestion index and accident-prone road section labels. All collected data is transmitted to the central processor via onboard Ethernet, and after filtering and spatiotemporal alignment processing, it forms a structured driving status dataset and environmental information dataset.

[0065] Step B2: Analyze the driving status and environmental information to determine the suppression intensity.

[0066] Specifically, the analysis of driving status and environmental information determines the intensity of inhibition, including: calculating the driver's participation index based on driving status; calculating the uncertainty coefficient of the driving environment based on environmental information; calculating the influence score using the participation index and uncertainty coefficient; and determining the intensity of inhibition using the score range in which the influence score falls.

[0067] First, the driver's participation index is calculated based on driving status: the percentage of time the driver's eyes are focused on the road (maximum score 30 points, ≥90% is full score), the frequency of active steering wheel micro-adjustments (maximum score 20 points, ≥2 times every 10 seconds is full score), the pedal operation response speed (maximum score 30 points, delay <0.5 seconds is full score), and the record of no dangerous operation (such as making or receiving phone calls, maximum score 20 points) are weighted and summed to obtain a participation index of 0-100 points. The higher the score, the stronger the driver's focus and willingness to actively control the vehicle.

[0068] Secondly, the uncertainty coefficient is calculated based on environmental information: from four dimensions, road complexity (3 points for intersections and 1 point for straight roads), traffic density (3 points for ≥3 vehicles per lane and 0 points for no vehicles), weather impact (3 points for heavy rain / fog and 0 points for clear weather), and lighting conditions (2 points for backlight / nighttime and 0 points for natural light), the uncertainty coefficient is accumulated according to a preset weight (4:3:2:1) to obtain an uncertainty coefficient of 0-10. The higher the value, the more difficult it is to predict the environmental risk.

[0069] Finally, the impact score is calculated using the participation index (weight 60%) and the uncertainty coefficient (weight 40%), with the formula: Impact Score = Participation Index × 0.6 - Uncertainty Coefficient × 10 × 0.4 (the coefficient is standardized to 0-40 points). The suppression intensity is determined based on the score range: ≥60 points corresponds to "high-intensity suppression" (completely turning off the audible and visual alarms, retaining only background monitoring); 30-59 points corresponds to "medium-intensity suppression" (turning off the buzzer alarm, retaining the flashing of the exterior rearview mirror lights); <30 points corresponds to "low-intensity suppression" (only reducing the alarm volume and light frequency, not turning off the core prompts). By dynamically adjusting the weights and thresholds, the suppression intensity is ensured to match the driver's ability and environmental risks, achieving humanized assistance.

[0070] Step B3: Control the vehicle's lane change assist function to enter the suppressed state according to the suppression intensity.

[0071] Specifically, when the condition is determined to be "high intensity suppression", a command is sent to the LCA function module to shut off the power supply circuit of the exterior rearview mirror warning light and the drive signal of the buzzer. At the same time, the active alarm triggering logic of the radar data is suspended, but the real-time monitoring of the sensor is retained (the data is only stored in the cache and does not trigger any prompts). At this time, the LCA icon on the instrument panel is displayed in gray, indicating that the function is in a suppressed state.

[0072] If it is "medium intensity suppression", only the audio output signal of the buzzer is cut off, the low-frequency flashing of the exterior rearview mirror warning light is maintained (the frequency is reduced from 2Hz to 0.5Hz), and the alarm trigger threshold is automatically increased by 20% (e.g., the lateral distance must be less than 80% of the original threshold to trigger); at the same time, a command is sent to the body control module to weaken the seat vibration warning (if equipped) to avoid causing significant interference to the driver.

[0073] For "low-intensity suppression," the buzzer volume is reduced (from 80 dB to 50 dB) by adjusting the PWM signal duty cycle, and the duration of the exterior rearview mirror light flashing is shortened (from 0.5 seconds to 0.2 seconds per flash). Simultaneously, slight steering wheel vibration feedback is retained (amplitude reduced by 50%), ensuring the driver perceives the risk without affecting normal operation. All suppression state transitions are synchronized in real-time to the instrument cluster display via the vehicle bus, displaying the current suppression level in text (e.g., "LCA Low-Intensity Suppression in Progress"). Furthermore, when driving conditions or environmental information change abruptly (e.g., driver distraction, worsening weather), the system can dynamically switch suppression intensity within 500 milliseconds, achieving a balance between safety and comfort.

[0074] This application embodiment detects the driver's driving state and vehicle environmental information, first calculating the driver's participation index and the uncertainty coefficient of the driving environment, then using both to calculate the influence score, and finally determining the suppression intensity to control the lane change assist function to enter the corresponding suppression state. This process can dynamically adjust the suppression level of the lane change assist function according to the driver's concentration, operational participation, and environmental factors such as road complexity, traffic density, and weather. When the driver is highly focused and the environment is simple, the suppression intensity can be reduced or even eliminated to ensure the effective operation of the assist function; when the driver is distracted and the environment is complex, the suppression intensity can be appropriately increased to avoid interference, reducing unnecessary alarm interference with driving, and providing effective assistance when necessary.

[0075] This embodiment provides a method for processing vehicle lane change warnings. Figure 2 This is a flowchart of a vehicle lane change warning processing method according to an embodiment of the present invention, such as... Figure 2 As shown, the process includes the following steps:

[0076] Step S201: When the vehicle's lane change assist function is activated and the warning conditions corresponding to the lane change assist function are met, detect the collision risk quantification data between adjacent vehicles during the turning process.

[0077] In this embodiment of the application, when the vehicle's forward-facing camera detects a traffic light at an intersection or the surround-view camera detects a reversing turn at an intersection, the lane change assist function will be automatically activated. Subsequently, the system will detect whether the vehicle meets the alarm conditions corresponding to this function (such as the driver turning on the turn signal, the vehicle speed being between 20-120 km / h, and the steering wheel angle being greater than 5°).

[0078] If the conditions are met, the collision risk quantification data detection process is initiated. This process relies on a multi-sensor fusion system, including millimeter-wave radar, surround-view cameras, and ultrasonic radar, to monitor adjacent vehicles in real time during the vehicle's turning process. The millimeter-wave radar collects and records the lateral distance between the vehicle and adjacent vehicles, as well as the first duration during which this distance is within a specific range. The surround-view camera calculates the lateral motion data (lateral velocity and lateral acceleration) of adjacent vehicles through image recognition and algorithms, as well as the second duration during which this data exceeds a preset benchmark value. At the same time, the data collected by the sensors is filtered to eliminate noise, and the detection range is dynamically adjusted according to the vehicle's turning radius. Finally, a structured collision risk quantification dataset is formed, providing a data foundation for subsequent risk type analysis.

[0079] Step S202: Analyze the risk types of adjacent vehicles using collision risk quantification data.

[0080] In this embodiment of the application, the lateral distance, first duration, lateral movement data and second duration of each adjacent vehicle and the vehicle itself are obtained from the collision risk quantification data; by verifying them one by one, vehicles whose lateral distance is less than a preset distance (e.g. 1.5 meters) and whose first duration is greater than a first threshold (e.g. 1 second) are selected as the first vehicle, because they are continuously close to the vehicle and have a direct intersection risk with the turning trajectory of the vehicle itself, they are determined to be collision risk types.

[0081] From the remaining vehicles excluding the first vehicle, select those with lateral motion data greater than a preset threshold (e.g., lateral velocity > 1 m / s or lateral acceleration > 0.8 m / s²). 2 Vehicles whose duration is less than the second threshold (e.g., 0.5 seconds) are classified as the second vehicle because their short-term rapid approach poses a potential risk and are also classified as collision risk type. Finally, all other vehicles except the first and second vehicles are classified as no-collision risk type. These vehicles have sufficient lateral distance and no obvious approach trend. The classification is made by elimination and edge data secondary verification to ensure accuracy, and finally a complete classification result is formed.

[0082] Step S203: Obtain the intervention strategy corresponding to the risk type, and perform corresponding handling operations on the lane change assist function based on the intervention strategy.

[0083] In this embodiment of the application, the lane change assist function is subjected to corresponding handling operations based on the intervention strategy, including the following steps C1-C2:

[0084] Step C1: If the risk type is collision risk, detect whether the driver has pressed the accelerator pedal.

[0085] Once the risk type of an adjacent vehicle is determined to be a collision risk, a detection process for the driver's accelerator pedal depressing behavior is initiated. This process relies on the vehicle's accelerator pedal position sensor, which can collect real-time data on the displacement and pressure changes of the accelerator pedal. The sensor samples the accelerator pedal state at a high frequency (typically above 100Hz), converts the collected analog signals into digital signals, and transmits them to the vehicle's electronic control unit (ECU) via the vehicle's CAN bus. The ECU has a pre-set algorithm for determining accelerator pedal depressing behavior, which analyzes the sensor data in real time.

[0086] For example, if the displacement of the accelerator pedal exceeds a preset threshold (e.g., 10% of the pedal travel), or if the rate of pressure change reaches a certain value within a short period (e.g., within 0.1 seconds), the system will determine that the driver has pressed the accelerator pedal. Simultaneously, to ensure accuracy, the system will also cross-validate the detection by incorporating information such as the vehicle's current driving status, including vehicle speed and engine speed. If the vehicle is stationary, even a slight displacement of the accelerator pedal may not be recognized as a valid pressing action, thus avoiding misjudgments due to sensor errors or driver accidental touches.

[0087] Step C2: If a stamping action occurs, the lane change assist function of the vehicle is controlled to enter a suppressed state; or, if no stamping action occurs, a warning prompt operation is performed on the first and second vehicles corresponding to the collision risk type, the first and second vehicles are detected to see if they respond to the warning prompt operation, the detection result is obtained, and the corresponding handling operation is performed on the lane change assist function according to the detection result.

[0088] If the system detects that the driver has pressed the accelerator pedal, the lane change assist function will enter a suppressed state. In this state, the triggering mechanism of the exterior rearview mirror warning lights and buzzer will be temporarily disabled, and no more audible and visual warnings will be issued to the driver. At the same time, the current suppressed state will be fed back to the vehicle's instrument system, indicating to the driver through the instrument display or indicator lights that the lane change assist function has entered the suppressed state, allowing the driver to understand the working status of the vehicle's assistance system.

[0089] In this embodiment, if no driver is detected pressing the accelerator pedal, a warning prompt is issued to the first and second vehicles corresponding to the collision risk type. The warning prompt includes activating the exterior rearview mirror warning light, causing it to flash at a specific frequency (e.g., twice per second), while simultaneously triggering a buzzer to emit a continuous beeping sound (volume and frequency can be adjusted according to vehicle design). After the warning prompt is issued, the reactions of the first and second vehicles are continuously monitored using onboard sensors (e.g., millimeter-wave radar, cameras, etc.) to detect whether they respond to the warning prompt. The detection results mainly include whether the target vehicle decelerates or changes its trajectory to move away from the vehicle. If the target vehicle responds to the warning prompt (e.g., significantly decelerates or avoids it), the lane change assist function is controlled to maintain the current warning state, or the warning intensity is adjusted according to subsequent changes in the target vehicle's state; if the target vehicle does not respond to the warning prompt, the warning measures are further strengthened.

[0090] Specifically, based on the test results, corresponding actions will be taken to adjust the lane change assist function, including:

[0091] If the detection results show that both the first and second vehicles responded to the warning prompt, then it is analyzed whether the first and second vehicles are still in a collision risk type after responding to the warning prompt. If they are not in a collision risk type, then the lane change assist function is controlled to enter the monitoring state; or, if they are still in a collision risk type, then the lane change assist function is controlled to enter the warning state, and a reminder operation is performed on the driver of the vehicle through the lane change assist function.

[0092] First, real-time data of the two vehicles is re-collected using millimeter-wave radar and surround-view cameras, including lateral distance, lateral movement data, and corresponding durations, and compared with the thresholds used in the initial assessment. For example, if the first vehicle was initially identified as a collision risk due to a lateral distance <1.5 meters for more than 1 second, and after the response its lateral distance increases to 2 meters for 0.5 seconds, the system will determine that it has moved out of the collision risk range; if the second vehicle was initially marked due to a lateral speed >1 m / s for 0.3 seconds (less than the 0.5-second threshold), and after the response its lateral speed decreases to 0.3 m / s for 1 second without exceeding the threshold, it will also be determined as a non-collision risk vehicle.

[0093] For vehicles deemed "not of a collision risk type," the system sends a state switching command to the Lane Change Assist (LCA) module, controlling it to transition from warning mode to monitoring mode. In monitoring mode, the LCA continues to track adjacent vehicles in real time using sensors, but only triggers a warning when the collision risk conditions are met again. Simultaneously, the instrument panel displays "LCA monitoring in progress" to alert the driver. During this process, the sensor sampling frequency is reduced from 100Hz during warning to 50Hz to lower system power consumption, while retaining a fast wake-up mechanism to ensure that the system can re-enter warning mode within 0.2 seconds if the risk recurs.

[0094] If the secondary assessment results indicate that either the first or second vehicle still poses a collision risk (e.g., the lateral distance of the first vehicle briefly increases to 1.6 meters and then decreases to 1.4 meters for more than 1 second, or the lateral acceleration of the second vehicle briefly decreases and then exceeds 0.8 m / s² again). 2 The system then controls the LCA to enter enhanced warning mode. At this time, in addition to retaining the high-frequency flashing (3Hz) of the exterior rearview mirror lights and the buzzer alarm (80 dB), new steering wheel vibration feedback (0.5mm amplitude, 5Hz frequency) and seat side pulse alerts (once every 0.5 seconds) are added, enhancing the warning effect through multi-sensory stimulation. Simultaneously, the instrument panel dynamically displays the target vehicle's location icon and the text "Risk not eliminated, do not change lanes," and recommends appropriate actions based on vehicle speed data (e.g., "Recommended to reduce speed to below 30km / h").

[0095] In addition, it will continuously calculate the time to collision (TTC) between the two vehicles and its own vehicle. If the TTC is less than 3 seconds, it will send a request to the powertrain via the CAN bus to briefly reduce the engine output torque (by 10%), giving the driver time to react.

[0096] Alternatively, based on the detection results, corresponding actions can be taken to handle the lane change assist function, including: if the detection results show that the first vehicle and the second vehicle do not respond to the warning prompt, then the lane change assist function can be controlled to enter the warning state.

[0097] Specifically, if the detection results indicate that the first and second vehicles did not respond to the warning prompts, the system immediately activates the Lane Change Assist (LCA) function to enter warning mode. At this time, the LCA module activates a multi-level warning mechanism through the vehicle network: the exterior rearview mirror warning light upgrades from regular flashing (2Hz) to high-frequency flashing (4Hz), the buzzer switches to continuous sounding mode (volume increased to 85 decibels), the steering wheel vibrates with an amplitude of 0.8mm and a frequency of 6Hz, and the side airbag module triggers a pulse pressure warning (once every 0.3 seconds), enhancing the driver's perception through multi-dimensional sensory stimulation. The instrument panel simultaneously displays a red dynamic risk icon, marking the location of the target vehicle and displaying the text "Adjacent vehicle failed to yield, lane change prohibited." Simultaneously, the system calculates the Time to Collision (TTC) based on radar data. If the TTC is less than 2 seconds, the system automatically applies slight braking (deceleration of 5-8 km / h) through the ESP module to give the driver reaction time. In this state, LCA continuously updates the target vehicle data at a frequency of 100Hz until the target vehicle responds or the collision risk is eliminated, ensuring that the driver receives continuous and strong warnings in emergency scenarios.

[0098] This application's embodiments dynamically adjust the lane change assist function state based on the driver's accelerator pedal operation and the response of adjacent vehicles to the warning under different collision risk types, resulting in significant beneficial effects. When the driver presses the accelerator pedal, suppressing the assist function can avoid interference with active operation; when the accelerator pedal is not pressed, a warning is triggered first, and then the monitoring or warning state is switched according to whether adjacent vehicles respond and the risk status after the response. This not only provides timely reminders when the driver is unaware of the risk, but also reduces unnecessary intervention after the risk is eliminated, and strengthens the warning when adjacent vehicles do not respond, thereby accurately balancing assistance and interference, and improving driving safety and experience.

[0099] This embodiment also provides a vehicle lane change warning suppression device, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0100] This embodiment provides a vehicle lane change warning suppression device, such as... Figure 3 As shown, it includes:

[0101] The detection module 301 is used to detect the collision risk quantification data between adjacent vehicles during the turning process when the vehicle's lane change assist function is activated and the warning conditions corresponding to the lane change assist function are met.

[0102] Analysis module 302 is used to analyze the risk type of adjacent vehicles using collision risk quantification data;

[0103] The execution module 303 is used to obtain the intervention strategy corresponding to the risk type and perform corresponding handling operations on the lane change assist function based on the intervention strategy.

[0104] In this embodiment of the application, the analysis module 302 is used to obtain the lateral distance between each adjacent vehicle, the first duration corresponding to the lateral distance, the lateral movement data, and the second duration corresponding to the lateral movement data from the collision risk quantification data; to obtain the first vehicle from the adjacent vehicles whose lateral distance is less than a preset distance and whose first duration is greater than a first threshold, and to determine the risk type corresponding to the first vehicle as a collision risk type; to obtain the second vehicle from the other adjacent vehicles besides the first vehicle whose lateral movement data is greater than a preset threshold and whose second duration is less than a second threshold, and to determine the risk type corresponding to the second vehicle as a collision risk type; and to classify the risk type corresponding to the other adjacent vehicles besides the first and second vehicles as a no-collision-risk type.

[0105] In this embodiment of the application, the execution module 303 is used to control the vehicle's lane change assist function to enter a suppressed state if the risk type is a no-collision risk type.

[0106] In this embodiment of the application, the execution module 303 is used to detect the driving state of the driver in the vehicle and the environmental information of the driving environment in which the vehicle is located; analyze the driving state and environmental information to determine the suppression intensity; and control the lane change assist function of the vehicle to enter the suppression state according to the suppression intensity.

[0107] In this embodiment of the application, the execution module 303 is used to calculate the driver's participation index based on the driving state; calculate the uncertainty coefficient of the driving environment based on environmental information; calculate the influence score using the participation index and the uncertainty coefficient; and determine the suppression intensity using the score range where the influence score is located.

[0108] In this embodiment, the execution module 303 is used to detect whether the driver has pressed the accelerator pedal if the risk type is a collision risk type; if the pressing behavior occurs, the driver controls the lane change assist function of the vehicle to enter a suppressed state; or, if the pressing behavior does not occur, the driver performs a warning prompt operation on the first vehicle and the second vehicle corresponding to the collision risk type, detects whether the first vehicle and the second vehicle respond to the warning prompt operation, obtains the detection result, and performs corresponding handling operations on the lane change assist function according to the detection result.

[0109] In this embodiment of the application, the execution module 303 is used to, if the detection result shows that the first vehicle and the second vehicle responded to the warning prompt operation, analyze whether the first vehicle and the second vehicle are still in a collision risk type after responding to the warning prompt operation. If they are not in a collision risk type, control the lane change assist function to enter the monitoring state; or, if they are still in a collision risk type, control the lane change assist function to enter the warning state and perform a reminder operation on the driver of the vehicle through the lane change assist function; or, if the detection result shows that the first vehicle and the second vehicle did not respond to the warning prompt operation, control the lane change assist function to enter the warning state.

[0110] Please see Figure 4 , Figure 4 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 4As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system).

[0111] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0112] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0113] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device as shown by a landing page for an app. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, which can be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0114] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0115] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0116] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0117] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for processing vehicle lane change warnings, characterized in that, The method includes: When the lane change assist function of the vehicle is activated and the warning conditions corresponding to the lane change assist function are met, the collision risk quantification data between the vehicle and adjacent vehicles during the turning process is detected. The collision risk quantification data is used to analyze the risk type corresponding to the adjacent vehicles; Obtain the intervention strategy corresponding to the risk type, and perform corresponding handling operations on the lane change assist function based on the intervention strategy.

2. The method according to claim 1, characterized in that, The analysis of the risk type corresponding to adjacent vehicles using the collision risk quantification data includes: From the collision risk quantification data, obtain the lateral distance between each adjacent vehicle, the first duration corresponding to the lateral distance, the lateral movement data, and the second duration corresponding to the lateral movement data; The first vehicle whose lateral distance is less than a preset distance and whose first duration is greater than a first threshold is obtained from the adjacent vehicles, and the risk type corresponding to the first vehicle is determined to be a collision risk type. The second vehicle whose lateral motion data is greater than a preset threshold and whose second duration is less than a second threshold is obtained from the other vehicles in the adjacent vehicles (excluding the first vehicle), and the risk type corresponding to the second vehicle is determined to be a collision risk type. The risk type corresponding to the other vehicles among the adjacent vehicles, excluding the first and second vehicles, is the no-collision risk type.

3. The method according to claim 2, characterized in that, The step of performing corresponding actions on the lane change assist function based on the intervention strategy includes: If the risk type is a non-collision risk type, then control the vehicle's lane change assist function to enter a suppressed state.

4. The method according to claim 3, characterized in that, The control of the vehicle's lane change assist function to enter a suppressed state includes: The system detects the driver's driving status in the vehicle and the environmental information of the vehicle's driving environment. Analyze the driving state and the environmental information to determine the suppression intensity; The lane change assist function of the vehicle is controlled to enter a suppressed state according to the suppression intensity.

5. The method according to claim 4, characterized in that, The analysis of the driving state and the environmental information to determine the suppression intensity includes: The driver's engagement index is calculated based on the driving state; The uncertainty coefficient of the driving environment is calculated based on the environmental information; The influence score is calculated using the participation index and the uncertainty coefficient, and the suppression intensity is determined using the score range in which the influence score falls.

6. The method according to claim 2, characterized in that, The step of performing corresponding actions on the lane change assist function based on the intervention strategy includes: If the risk type is a collision risk type, detect whether the driver has pressed the accelerator pedal. If a stampede occurs, the lane change assist function of the vehicle is controlled to enter a suppressed state; or, if no stampede occurs, a warning prompt is executed on the first and second vehicles corresponding to the collision risk type, the first and second vehicles are detected to see if they respond to the warning prompt, the detection result is obtained, and the lane change assist function is handled accordingly based on the detection result.

7. The method according to claim 6, characterized in that, The step of performing corresponding processing operations on the lane change assist function based on the detection results includes: If the detection result indicates that both the first vehicle and the second vehicle responded to the warning prompt, then it is analyzed whether the first vehicle and the second vehicle are still at risk of collision after responding to the warning prompt. If they are not at risk of collision, then the lane change assist function is controlled to enter the monitoring state; or, if they are still at risk of collision, then the lane change assist function is controlled to enter the warning state, and a reminder operation is performed on the driver of the vehicle through the lane change assist function; or... If the detection result indicates that neither the first vehicle nor the second vehicle responds to the warning prompt, then the lane change assist function is controlled to enter the warning state.

8. A vehicle lane change warning suppression device, characterized in that, The device includes: The detection module is used to detect the collision risk quantification data between the vehicle and adjacent vehicles during the turning process when the vehicle's lane change assist function is activated and the warning conditions corresponding to the lane change assist function are met. The analysis module is used to analyze the risk type corresponding to the adjacent vehicles using the collision risk quantification data; The execution module is used to obtain the intervention strategy corresponding to the risk type, and to perform corresponding handling operations on the lane change assist function based on the intervention strategy.

9. A computer device, characterized in that, include: A memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, the processor executing the computer instructions to perform the method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to perform the method of any one of claims 1 to 7.

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