A forward collision warning processing device and method for intelligent networked vehicles

Abstract

The application relates to the field of intelligent networked automobile active safety technology, and particularly discloses a front collision early warning processing device and method for an intelligent networked automobile, which is characterized in that: the system is provided with high and low front collision early warning processing devices at the front bumper of the vehicle through multi-height sensor layout and dynamic parameter adjustment technology, and is integrated with multi-source sensing modules such as a camera, a laser radar and an infrared sensor. The high-position device is responsible for long-distance wide-area detection, and the low-position device is responsible for strengthening close-range accurate sensing; the initial detection parameters are matched in real time in combination with the thick fog visibility parameters, so that a three-dimensional detection network of 'far and near cooperation and environment adaptation' is formed. The layout effectively solves the problem that a traditional single-height sensor is easily disturbed in complex weather, significantly improves the target detection reliability in a thick fog environment, and reduces the collision risk caused by low visibility.

Description

Technical Field

[0001] This invention relates to the field of active safety technology for intelligent connected vehicles, specifically to a forward collision warning processing device and method for intelligent connected vehicles. Background Technology

[0002] In the field of active safety for intelligent connected vehicles, forward collision warning systems, as a core protective technology, have evolved from basic obstacle detection to all-scenario adaptive protection. Existing technologies generally employ multi-sensor fusion solutions, utilizing the collaborative work of millimeter-wave radar, visual sensors, and lidar to achieve real-time perception of vehicles, pedestrians, and road signs ahead. These systems, relying on dynamic safe distance models and collision time algorithms, can trigger audible and visual warnings under potential collision risks and coordinate with automatic emergency braking systems to provide the driver with a critical reaction window.

[0003] For example, Chinese invention patent CN112918473B discloses a rear-end collision warning decision-making method based on evidence networks, including step S1: collecting current data of rear-end vehicles according to the CAN bus, step S2: processing, detecting, calibrating, calculating and classifying the data collected in step S1, step S3: identifying targets based on the data processed in step S2, and estimating the vehicle state, step S4: using the extracted feature information of the measured object to provide a decision basis for rear-end collision warning and conduct vehicle collision hazard assessment, step S5: comparing the hazard assessment results of step S4 with the knowledge base in the display installed in the vehicle to make a collision avoidance decision.

[0004] For example, Chinese invention patent CN108099906B provides a collision warning system and a vehicle for installation on a car, belonging to the field of automotive technology. The collision warning system includes a camera and a processor, wherein: the processor is electrically connected to the camera; the camera is used to acquire obstacle images and send the acquired obstacle images to the processor; the processor is used to determine the estimated collision duration based on multiple frames of obstacle images using a dynamic image processing algorithm; if the estimated collision duration is less than or equal to a preset value, an alarm command is sent to an alarm component electrically connected to the processor, causing the alarm component to issue an alarm signal.

[0005] However, in the process of implementing the embodiments of this application, it was discovered that the above-mentioned technology has at least the following technical problems: the core sensor of the existing intelligent connected vehicle forward collision warning technology relies on only a single operating mode, which is easily affected by environmental factors such as severe weather, strong glare, or dirt obstruction. This leads to a significant decrease in sensor performance or even complete failure, resulting in the failure to detect obstacles ahead and significantly increasing the risk of collision accidents. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides a forward collision warning processing device and method for intelligent connected vehicles, which can effectively solve the problems mentioned in the background technology.

[0007] To achieve the above objectives, the present invention provides the following technical solution: The first aspect of the present invention provides a forward collision warning processing method for intelligent connected vehicles, comprising: S1. marking the road segment in which the intelligent connected vehicle is traveling as the target road segment, collecting and analyzing the fog visibility parameters of the target road segment, obtaining the visibility range of the target road segment based on the fog visibility parameters of the target road segment, thereby obtaining the initial detection parameters of the intelligent connected vehicle.

[0008] S2. Obtain and analyze the detection process parameters of the intelligent connected vehicle, determine whether to update the initial detection parameters of the intelligent connected vehicle, obtain the updated detection process parameters of the intelligent connected vehicle, and thus determine whether to switch the configuration of the forward collision warning processing device of the intelligent connected vehicle.

[0009] S3. Acquire the detection results of the forward collision warning processing equipment of the intelligent connected vehicle in real time, compare them with the actual safe distance, and determine whether to issue a collision warning.

[0010] A second aspect of the present invention provides a forward collision warning processing device for intelligent connected vehicles, comprising: a high-position visual radar sensor, a low-position visual radar sensor, and an infrared sensor; the high-position visual radar sensor refers to the forward collision warning processing device deployed at a higher position in the intelligent connected vehicle, including a camera and an electromagnetic wave radar, integrating visual perception and radar detection functions; the low-position visual radar sensor refers to the forward collision warning processing device deployed at a higher position in the intelligent connected vehicle, including a camera and an electromagnetic wave radar, integrating visual perception and radar detection functions; the infrared sensor refers to the sensor deployed at a key position in the forward collision warning processing device of the intelligent connected vehicle, achieving accurate detection by detecting infrared reflection signals emitted by objects within the detection range.

[0011] A collision warning database is used to store parameters for a forward collision warning processing device and method for intelligent connected vehicles.

[0012] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects:

[0013] (1) This invention provides a forward collision warning processing device and method for intelligent connected vehicles. Through multi-height sensor layout and dynamic parameter adjustment technology, this invention deploys high-level and low-level forward collision warning processing devices at the vehicle bumper, integrating multi-source sensing modules such as cameras, lidar, and infrared sensors. The high-level device is responsible for long-distance wide-area detection, while the low-level device enhances close-range precise perception. Combined with fog visibility parameters, the initial detection parameters are matched in real time, forming a three-dimensional detection network that is "coordinated between near and far distances and adaptable to different environments." This layout effectively solves the problem of traditional single-height sensors being susceptible to interference in complex weather conditions, significantly improves the reliability of target detection in foggy environments, and reduces the risk of collisions due to low visibility.

[0014] (2) This invention is based on a collision time prediction and graded early warning mechanism. By acquiring the distance to obstacles ahead in real time and calculating the predicted collision time (TTC), it dynamically divides the warning levels into multiple levels. The system triggers a progressive warning from pop-up prompts to audible and visual alarms based on the TTC threshold, avoiding the problem of frequent false alarms in traditional fixed threshold warnings. At the same time, by combining the correction algorithm of detection efficiency coefficient and benchmark safe distance, the actual safe distance is recalculated after adjusting the sensor parameters a second time, realizing a closed-loop control of "prediction-evaluation-correction". This mechanism enables the early warning system to respond to sudden risks in a timely manner, while reducing ineffective interference to the driver, improving the accuracy of collision warnings and user trust.

[0015] (3) This invention uses dense fog visibility parameter processing and detection efficiency optimization technology to divide the visibility of the target road section into high / medium / low visibility ranges and adjust the sensor working mode accordingly (such as high-position device single operation, high and low position device collaboration, infrared sensor triggering). By continuously monitoring the detection efficiency coefficient and comparing it with the threshold, dynamic optimization of primary adjustment (increasing frame rate / power) and secondary adjustment (switching to detection parameters in higher visibility ranges) is achieved. This technology enables the system to maintain high-efficiency detection capability in low visibility environments such as dense fog, avoids missed detections or misjudgments caused by sensor performance degradation, and significantly enhances driving safety in complex weather conditions;

[0016] (4) This invention constructs a closed-loop adjustment system and a safety distance correction mechanism based on "detection-evaluation-optimization". The detection performance is continuously evaluated through multi-source sensor data fusion. The corrected safety distance is obtained by multiplying the detection performance coefficient after secondary adjustment with the baseline safety distance, thus achieving dynamic calibration of the safety distance. This closed-loop system enables the system to adapt to environmental changes (such as sudden drops in visibility or temporary sensor malfunctions), accurately determine the actual safety distance threshold, reduce trajectory deviations caused by model fixation, and improve the environmental adaptability of forward collision warning. Attached Figure Description

[0017] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the method steps of the present invention;

[0019] Figure 2 This is a flowchart of the dynamic configuration method for adaptive detection parameters of environmental visibility in the target highway section according to the present invention.

[0020] Figure 3 This is a flowchart of the dynamic parameter adaptive optimization method based on detection performance feedback of the present invention;

[0021] Figure 4 This is a flowchart of the optimization and dynamic switching method for device configuration of the present invention;

[0022] Figure 5 Flowchart of the dynamic switching determination method for the forward warning collision processing device of the present invention;

[0023] Figure 6 This is a flowchart of the multi-level collision warning dynamic response and braking control method of the present invention. Detailed Implementation

[0024] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0025] The first aspect of this invention provides a forward collision warning processing device for intelligent connected vehicles, comprising: a high-position visual radar sensor, a low-position visual radar sensor, and an infrared sensor; the high-position visual radar sensor refers to the forward collision warning processing device deployed at a higher position in the intelligent connected vehicle, including a camera and an electromagnetic wave radar, integrating visual perception and radar detection functions; the low-position visual radar sensor refers to the forward collision warning processing device deployed at a higher position in the intelligent connected vehicle, including a camera and an electromagnetic wave radar, integrating visual perception and radar detection functions; the infrared sensor refers to the sensor deployed at a key position in the forward collision warning processing device of the intelligent connected vehicle, achieving accurate detection by detecting infrared reflection signals emitted by objects within the detection range.

[0026] Reference Figure 1As shown, the second aspect of the present invention provides a forward collision warning processing method for intelligent connected vehicles, comprising: S1. marking the road segment in which the intelligent connected vehicle is traveling as a target road segment, collecting and analyzing the fog visibility parameters of the target road segment, obtaining the visibility range of the target road segment based on the fog visibility parameters of the target road segment, thereby obtaining the initial detection parameters of the intelligent connected vehicle; S2. acquiring and analyzing the detection process parameters of the intelligent connected vehicle, determining whether to update the initial detection parameters of the intelligent connected vehicle, acquiring the updated detection process parameters of the intelligent connected vehicle, thereby determining whether to switch the configuration of the forward collision warning processing device of the intelligent connected vehicle; S3. acquiring the detection results of the forward collision warning processing device of the intelligent connected vehicle in real time, comparing them with the actual safe distance, and determining whether to issue a collision warning.

[0027] Reference Figure 2 As shown, the system first starts by setting initial detection parameters and marking the currently monitored highway section. Then, it collects three key parameters in real time: fog droplet concentration, ambient light contrast, and light transmittance, calculating the Environmental Visibility Index (VI) as a classification criterion. Subsequently, the system makes dynamic decisions based on the VI value's range: when the VI is in the high visibility range, the environment is marked and the first initial detection parameter is activated, with only the high-position sensor operating at a preset frame rate and power; if the VI is in the medium visibility range, the system switches to the second initial detection parameter, simultaneously activating both high and low-position sensors to operate with standard parameters; when the VI is detected to be in the low visibility range, the system immediately triggers a risk warning mechanism, configures the third initial detection parameter, and improves target detection reliability in low-visibility scenarios through multi-modal sensor fusion. The entire process, through a closed-loop design of environmental perception, parameter calculation, classification decision-making, and equipment control, achieves dynamic matching of detection resources and visibility conditions, effectively balancing detection accuracy and system energy consumption.

[0028] Specifically, the visibility range of a target highway segment is obtained based on the visibility parameters of dense fog. The specific analysis process is as follows: The visibility parameters of the target highway segment include the fog droplet concentration, the ambient light contrast, and the light transmittance. The fog droplet concentration refers to the number of fog droplets contained in a unit volume of air within the target highway segment. The ambient light contrast refers to the degree of brightness difference between obstacles within the detection range of the forward collision warning equipment and its background environment. The light transmittance refers to the ratio of transmitted light intensity to incident light intensity when light passes through the environment of the target highway segment, reflecting the attenuation ability of dense fog on light. Among these parameters, the fog droplet concentration can be directly monitored by a fog droplet spectrometer, the ambient light contrast can be analyzed by a high dynamic range camera in conjunction with an image brightness analyzer, and the light transmittance can be directly monitored by a transmissive visibility meter.

[0029] It should be explained that ambient light contrast can be obtained through analysis using a high dynamic range (HDR) camera in conjunction with an image brightness analyzer. The HDR camera first captures image data containing complete details of both the extreme bright and dark areas of a scene through multiple exposures or special sensor technology. This image data is then imported into the image brightness analyzer. The analyzer applies preset calibration parameters to accurately convert the image data into a brightness distribution map that reflects the actual physical brightness. The user or software selects the key areas to be compared in the map, and the analyzer automatically calculates the ratio of the brightness values ​​representing those areas, yielding an accurate ambient light contrast result.

[0030] By introducing fusion coefficients to quantify the influence of the ratios of the defined droplet concentration to the target highway section's droplet concentration, the ratios of the target highway section's ambient light contrast to the defined ambient light contrast, and the ratios of the target highway section's light transmittance to the defined light transmittance on the environmental visibility index of the target highway section, these fusion terms are aggregated to derive the environmental visibility index of the target highway section. The specific expression is as follows:

[0031] ;

[0032] In the formula, VI is the environmental visibility index of the target highway section, N is the fog droplet concentration of the target highway section, C is the ambient light contrast of the target highway section, T is the light transmittance of the target highway section, N_max is the preset boundary fog droplet concentration in the collision warning database, C_min is the preset boundary ambient light contrast in the collision warning database, T_min is the preset boundary light transmittance in the collision warning database, k1 is the fusion coefficient corresponding to the preset fog droplet concentration in the collision warning database, k2 is the fusion coefficient corresponding to the preset ambient light contrast in the collision warning database, and k3 is the fusion coefficient corresponding to the preset light transmittance in the collision warning database.

[0033] The environmental visibility index of the target highway section mentioned above is a quantitative indicator of the visibility of the current target highway section, used to characterize the environmental visibility of the target highway section under dense fog conditions.

[0034] The above definition of fog droplet concentration represents the maximum critical allowable value of fog droplet concentration; the above definition of ambient light contrast represents the minimum critical allowable value of ambient light contrast; the above definition of light transmittance represents the minimum critical allowable value of light transmittance.

[0035] The fusion coefficient corresponding to the aforementioned droplet concentration represents the degree of influence of the ratio between the defined droplet concentration and the droplet concentration of the target highway section on the environmental visibility index of the target highway section. It is preset in the collision warning database and has a value range of (0, 1]. The fusion coefficient corresponding to the aforementioned ambient light contrast represents the degree of influence of the ratio between the ambient light contrast of the target highway section and the defined ambient light contrast on the environmental visibility index of the target highway section. It is preset in the collision warning database and has a value range of (0, 1). The fusion coefficient corresponding to the aforementioned light transmittance represents the degree of influence of the ratio between the light transmittance of the target highway section and the defined light transmittance on the environmental visibility index of the target highway section. It is preset in the collision warning database and has a value range of (0, 1).

[0036] It should be explained that an increase in fog droplet concentration leads to an increase in the number of fog droplets in the target road section's environment, enhancing light absorption and scattering, and decreasing light transmittance. Consequently, the ratio of light transmittance in the target road section to the defined light transmittance decreases, resulting in a lower environmental visibility index. Simultaneously, the ratio of defined fog droplet concentration to fog droplet concentration in the target road section also decreases, leading to a lower environmental visibility index. On the other hand, an increase in ambient light contrast makes obstacle identification on the target road section more accurate. This leads to an increase in the ratio of ambient light contrast in the target road section to the defined ambient light contrast, resulting in an increase in the environmental visibility index. In summary, fog droplet concentration affects light transmittance, which in turn affects the environmental visibility index. Furthermore, fog droplet concentration, ambient light contrast, and light transmittance all directly influence the environmental visibility index.

[0037] If the environmental visibility index of the target highway segment falls within the preset high environmental visibility index range in the collision warning database, then the environment of the target highway segment will be marked as a high visibility environment.

[0038] If the environmental visibility index of the target highway segment falls within the preset medium environmental visibility index range in the collision warning database, then the environment of the target highway segment will be marked as medium visibility environment.

[0039] If the environmental visibility index of the target highway section falls within the preset low environmental visibility index range in the collision warning database, the environment of the target highway section will be marked as a low visibility environment, and a risk warning will be issued.

[0040] It should be explained that if the target highway section has low visibility, the current environmental visibility index of the target highway section is low, and there is a risk of collision caused by the environment, a risk warning will be issued.

[0041] Furthermore, the initial detection parameters of the intelligent connected vehicle are obtained. The specific acquisition process is as follows: if the environment of the target road section is highly visible, the high-position visual radar sensor of the intelligent connected vehicle is turned on and captures the detection image at a preset frame rate. At the same time, it transmits electromagnetic wave radar at a preset power. The preset frame rate and preset power of the high-position visual radar sensor in the high visibility environment are marked as the first initial detection parameters of the intelligent connected vehicle, and the high-position visual radar sensor turned on in the high visibility environment is marked as the first forward collision warning processing device configuration.

[0042] The preset frame rate of the aforementioned high-position visual radar is the preset frame rate of the high-position visual radar sensor in the collision warning database; the preset power of the aforementioned high-position visual radar is the preset power of the high-position visual radar sensor in the collision warning database.

[0043] If the target highway section has medium visibility, the high-position visual radar sensor of the intelligent connected vehicle is activated and the frame rate is increased to capture the detection image. At the same time, it emits electromagnetic wave radar with increased power. The low-position visual radar sensor is activated and captures the detection image at a preset frame rate. At the same time, it emits electromagnetic wave radar with a preset power. The preset frame rate and preset power of the high-position visual radar sensor and the preset frame rate and preset power of the low-position visual radar sensor in the medium visibility environment are marked as the second initial detection parameters of the intelligent connected vehicle. The high-position visual radar sensor and the second visual radar sensor activated in the medium visibility environment are marked as the configuration of the second forward collision warning processing device.

[0044] The aforementioned increase in frame rate is obtained by subtracting the environmental visibility index of the target road segment from the minimum value of the high-position environmental visibility index range, multiplied by the preset frame rate of the high-position visual radar, and then adding the preset frame rate of the high-position visual radar; the aforementioned increase in power is obtained by subtracting the environmental visibility index of the target road segment from the preset power of the high-position visual radar, multiplied by the preset power of the high-position visual radar, from the minimum value of the high-position environmental visibility index range, and then adding the preset power of the high-position visual radar.

[0045] The preset frame rate of the aforementioned low-position visual radar sensor is the preset frame rate of the low-position visual radar sensor in the collision warning database; the preset power of the aforementioned low-position visual radar sensor is the preset power of the low-position visual radar sensor in the collision warning database.

[0046] If the target highway section has low visibility, the high-position visual radar sensor of the intelligent connected vehicle is activated and captures the detection image at the maximum frame rate, while simultaneously emitting electromagnetic wave radar at the maximum power. The low-position visual radar sensor is activated and captures the detection image at the maximum frame rate, while simultaneously emitting electromagnetic wave radar at the maximum power. The infrared sensor is activated and receives infrared reflection signals at a preset response band. The preset frame rate and preset power of the high-position visual radar sensor and the preset frame rate and preset power of the low-position visual radar sensor are marked as the second initial detection parameters of the intelligent connected vehicle, and the preset response band of the infrared sensor is marked as the third initial detection parameters of the intelligent connected vehicle. The high-position visual radar sensor, the low-position visual radar sensor, and the infrared sensor activated in the low-visibility environment are marked as the third forward collision warning processing device configuration.

[0047] The aforementioned maximum frame rate is the maximum frame rate of the visual sensor preset in the collision warning database; the aforementioned maximum power is the maximum power of the radar sensor preset in the collision warning database.

[0048] It should be noted that the only difference between high-position visual radar sensors and low-position visual radar sensors is their deployment location.

[0049] The aforementioned preset response bands are the response band frequencies of infrared sensors preset in the collision warning database.

[0050] Reference Figure 3 The system calculates the target position deviation between the visual sensor and the radar, the difference in electromagnetic echo intensity, and the current environmental visibility index (VI). These are weighted to generate a detection effectiveness coefficient (DEI) as an evaluation metric. When the DEI falls below a preset threshold, the system triggers differentiated optimization strategies based on the current visibility level: in high-visibility scenarios, only the frame rate and transmission power of the high-position sensor are increased to enhance long-range detection capabilities; in medium-visibility scenarios, the operating parameters of both high and low-position sensors are simultaneously optimized to expand the monitoring coverage; in low-visibility scenarios, the operating frequency of the infrared module is further increased, and target recognition accuracy in complex environments is improved through multi-band signal fusion. If the DEI meets the threshold requirements, the existing parameter configuration is maintained to ensure system stability. This mechanism, through closed-loop control of "monitoring-evaluation-decision-execution," achieves precise matching of detection resources with the dynamic environment, effectively improving the reliability of the early warning system under all operating conditions.

[0051] Specifically, the determination of whether to update the initial detection parameters of the intelligent connected vehicle involves the following process: acquiring and analyzing the detection process parameters of the intelligent connected vehicle, including the visual radar detection deviation value, the electromagnetic wave radar echo difference value, and the environmental visibility index of the target road section; the visual radar detection deviation value is the deviation between the visual detection result and the radar detection result of the intelligent connected vehicle's visual radar sensor during detection; the electromagnetic wave radar echo difference value is the absolute difference between the amplitude of the electromagnetic wave radar echo formed after the electromagnetic wave radar emitted by the intelligent connected vehicle's visual radar sensor is detected and reflected, and the amplitude of the electromagnetic wave radar echo is a preset value; wherein the visual radar detection result deviation value is obtained through monitoring and calculation by the visual radar sensor, and the electromagnetic wave radar echo difference value is obtained through the radar sensor signal processing module.

[0052] It should be explained that the visual radar detection deviation value of intelligent connected vehicles is calculated by multiplying the absolute value of the difference between the obstacle distance detected by the visual radar sensor and the obstacle distance detected by the radar, along with the corresponding fusion coefficient, and then multiplying the absolute value of the difference between the relative speed of the obstacle detected by the visual radar and the relative speed of the obstacle detected by the radar, along with the corresponding fusion coefficient.

[0053] The above detection results include the distance to obstacles and the relative speed of obstacles within the target highway section.

[0054] It needs to be explained that the visual radar detection deviation value of intelligent connected vehicles is used to characterize the degree of measurement difference between the visual sensor and the radar sensor when the visual radar sensor is detecting an obstacle. By introducing fusion coefficients, the absolute values ​​of the difference between the distance of the obstacle detected by the visual sensor and the distance of the obstacle detected by the radar sensor, and the absolute values ​​of the difference between the relative velocity of the obstacle detected by the visual sensor and the relative velocity of the obstacle detected by the radar sensor, are quantified to influence the visual radar sensor detection deviation value of the intelligent connected vehicle. By coupling these influence values, the visual radar sensor deviation value of the intelligent connected vehicle is obtained, and the specific expression is as follows:

[0055] ;

[0056] In the formula, E is the visual radar detection deviation value of the intelligent connected vehicle, D1 is the obstacle distance detected by the visual sensor, D2 is the obstacle distance detected by the radar sensor, V1 is the relative speed of the obstacle detected by the visual sensor, V2 is the relative speed of the obstacle detected by the radar sensor, kz1 is the fusion coefficient corresponding to the obstacle distance preset in the collision warning database, and kz2 is the fusion coefficient corresponding to the obstacle relative speed preset in the collision warning database.

[0057] The obstacle distance detected by the aforementioned visual sensor is calculated by extracting features of the obstacle ahead using image recognition technology and combining this with imaging principles to determine the straight-line distance between the obstacle and the intelligent connected vehicle. The obstacle distance detected by the aforementioned radar sensor refers to the spatial distance between the obstacle and the intelligent connected vehicle calculated by the radar sensor based on the echo propagation time and electromagnetic wave propagation speed after emitting electromagnetic wave signals and receiving the echoes reflected from the obstacle. The relative speed of the obstacle detected by the aforementioned visual sensor refers to the speed of the obstacle relative to the intelligent connected vehicle calculated by the visual sensor through continuous frame image analysis of obstacle position changes and combining this with the speed of the intelligent connected vehicle itself, based on the trajectory. The relative speed of the obstacle detected by the aforementioned radar sensor refers to the speed of the obstacle relative to the intelligent connected vehicle calculated by the radar sensor through analysis of the Doppler frequency offset of the reflected echoes and combining this with the Doppler effect formula.

[0058] The aforementioned preset electromagnetic radar echo is the defined electromagnetic radar echo in the collision warning database, which is the minimum allowable benchmark value for electromagnetic radar echoes.

[0059] By introducing weighted contribution coefficients, the proportional relationships between the visual radar detection deviation value and the intelligent connected vehicle's visual radar detection deviation value, the proportional relationships between the electromagnetic wave radar echo difference value and the intelligent connected vehicle's electromagnetic wave radar echo difference value, and the proportional relationships between the environmental visibility index of the target highway section and the defined environmental visibility index are quantified to determine the weighted contribution of each weighted contribution to the detection efficiency coefficient of the intelligent connected vehicle. The contribution of each weight is then aggregated to derive the detection efficiency coefficient of the intelligent connected vehicle, as specifically expressed as:

[0060] ;

[0061] In the formula, DEI is the detection efficiency coefficient of the intelligent connected vehicle, E is the visual radar detection deviation value of the intelligent connected vehicle, L is the electromagnetic wave radar echo difference value of the intelligent connected vehicle, VI is the environmental visibility index of the target highway section, E_max is the preset defined visual radar detection deviation value in the collision warning database, L_max is the preset defined electromagnetic wave radar echo difference value in the collision warning database, VI_min is the preset defined environmental visibility index in the collision warning database, kx1 is the weight contribution coefficient corresponding to the preset visual radar detection deviation value in the collision warning database, kx2 is the weight contribution coefficient corresponding to the preset electromagnetic wave radar echo difference value in the collision warning database, and kx3 is the weight contribution coefficient corresponding to the preset environmental visibility index in the collision warning database.

[0062] The aforementioned detection efficiency coefficient of intelligent connected vehicles is a quantitative indicator of the detection capability of intelligent connected vehicle forward collision warning processing equipment within the target highway section under a preset configuration. It is used to characterize the detection efficiency of intelligent connected vehicles within the target highway section.

[0063] The above definition of visual radar detection deviation value represents the maximum critical allowable value of visual radar detection deviation value; the above definition of electromagnetic wave radar echo difference value represents the maximum critical allowable value of electromagnetic wave radar echo difference value; the above definition of environmental visibility index represents the minimum critical allowable value of environmental visibility index.

[0064] The weighted contribution coefficient corresponding to the aforementioned visual radar detection deviation value represents the proportional relationship between the defined visual radar detection deviation value and the visual radar detection deviation value of the intelligent connected vehicle. It is a preset value in the collision warning database and its range is (0, 1). The weighted contribution coefficient corresponding to the aforementioned electromagnetic wave radar echo difference value represents the weighted contribution of the proportional relationship between the defined electromagnetic wave radar echo difference value and the electromagnetic wave radar echo difference value of the intelligent connected vehicle to the detection efficiency coefficient of the intelligent connected vehicle. It is a preset value in the collision warning database and its range is (0, 1). The weighted contribution coefficient corresponding to the aforementioned environmental visibility index represents the weighted contribution of the proportional relationship between the environmental visibility index of the target road section and the defined environmental visibility index to the detection efficiency coefficient of the intelligent connected vehicle. It is a preset value in the collision warning database and its range is (0, 1).

[0065] It should be explained that an increase in visual radar detection deviation leads to a decrease in the ratio between the defined visual radar detection deviation and the visual radar detection deviation of the intelligent connected vehicle, thus reducing the detection efficiency coefficient of the intelligent connected vehicle. Similarly, an increase in electromagnetic radar echo difference leads to a decrease in the ratio between the defined electromagnetic radar echo difference and the electromagnetic radar echo difference of the intelligent connected vehicle, further reducing the detection efficiency coefficient. On the other hand, an increase in the environmental visibility index leads to an increase in the ratio between the environmental visibility index of the target road section and the defined environmental visibility index, thus increasing the detection efficiency coefficient of the intelligent connected vehicle. In summary, visual radar detection deviation, electromagnetic radar echo difference, and environmental visibility index directly affect the detection efficiency coefficient. Specifically, visual radar detection deviation and electromagnetic radar echo difference are negatively correlated with the detection efficiency coefficient, while the environmental visibility index is positively correlated with the detection efficiency coefficient.

[0066] The detection efficiency coefficient of the intelligent connected vehicle is compared with the detection efficiency threshold. If the detection efficiency coefficient of the intelligent connected vehicle is less than the detection efficiency threshold, the initial detection parameters of the intelligent connected vehicle are updated. If the detection efficiency coefficient of the intelligent connected vehicle is greater than or equal to the detection efficiency threshold, the initial detection parameters of the intelligent connected vehicle are not updated.

[0067] The aforementioned detection effectiveness threshold refers to the minimum critical allowable value of the detection effectiveness coefficient preset in the collision warning database.

[0068] Reference Figure 4 As shown, when the initial detection effectiveness coefficient (DEI) fails to meet the threshold requirement, the system optimizes or maintains parameters based on the visibility level, and then immediately recalculates the DEI for effectiveness verification. If the updated DEI is still below the threshold, a device configuration reconfiguration mechanism is triggered: in high visibility scenarios, it automatically switches to medium visibility configuration; in medium visibility scenarios, it upgrades to low visibility configuration; and in low visibility scenarios, it forces all sensors to run at maximum performance mode and activates anomaly warnings. If the verification passes, the current optimized configuration is maintained and runs stably. This mechanism, by introducing an iterative verification step, effectively avoids the local optimum problem that may be caused by a single optimization. Combined with the hierarchical configuration reconfiguration strategy, it not only ensures system stability under normal operating conditions but also achieves a leap in detection performance under extreme environments, significantly improving the early warning system's adaptability to complex dynamic scenarios.

[0069] Furthermore, the initial detection parameters of the intelligent connected vehicle are updated. The specific update process is as follows: If the environment of the target highway section has high visibility, the frame rate amplification factor and the power amplification factor of the high-position visual radar sensor are matched based on the detection efficiency coefficient and detection efficiency threshold of the intelligent connected vehicle. The frame rate of the high-position visual radar sensor is increased and adjusted by the frame rate amplification factor, and the power of the high-position visual radar sensor is increased and adjusted by the power amplification factor, thereby updating the initial detection parameters of the intelligent connected vehicle.

[0070] It needs to be explained that the high-position visual radar sensor frame rate amplification coefficient is matched, the preset high-position visual radar sensor frame rate amplification rule in the collision warning database is called, the detection efficiency coefficient of the intelligent connected vehicle is input, and the high-position visual radar sensor frame rate amplification coefficient is mapped and output.

[0071] It needs to be explained that the process involves matching the power amplification coefficient of the high-position visual radar sensor, calling the preset power amplification rules of the high-position visual radar sensor in the collision warning database, inputting the detection efficiency coefficient of the intelligent connected vehicle, mapping and outputting the power amplification coefficient of the high-position visual radar sensor.

[0072] It should be explained that the frame rate amplification factor of the high-position visual radar sensor is multiplied by the preset frame rate of the high-position visual radar sensor to increase and adjust the frame rate of the high-position visual radar sensor; the power amplification factor of the high-position visual radar sensor is multiplied by the preset power of the high-position visual radar sensor to increase and adjust the power of the high-position visual radar sensor.

[0073] If the target highway section has medium visibility, based on the detection efficiency coefficient and detection efficiency threshold of the intelligent connected vehicle, the frame rate amplification coefficient, power amplification coefficient, frame rate amplification coefficient, and power amplification coefficient of the low-position visual radar sensor are matched. The frame rate of the high-position visual radar sensor is increased and adjusted by the frame rate amplification coefficient, and the power of the low-position visual radar sensor is increased and adjusted by the power amplification coefficient, thereby updating the initial detection parameters of the intelligent connected vehicle.

[0074] It needs to be explained that the low-position visual radar sensor frame rate amplification coefficient is matched, the preset low-position visual radar sensor frame rate amplification rules in the collision warning database are called, the detection efficiency coefficient of the intelligent connected vehicle is input, and the low-position visual radar sensor frame rate amplification coefficient is mapped and output.

[0075] It needs to be explained that the process involves matching the power amplification coefficient of the low-position visual radar sensor, calling the preset power amplification rules of the low-position visual radar sensor in the collision warning database, inputting the detection efficiency coefficient of the intelligent connected vehicle, mapping and outputting the power amplification coefficient of the low-position visual radar sensor.

[0076] It should be explained that the frame rate amplification factor of the low-position visual radar sensor is multiplied by the preset frame rate of the low-position visual radar sensor to increase and adjust the frame rate of the low-position visual radar sensor; the power amplification factor of the low-position visual radar sensor is multiplied by the preset power of the low-position visual radar sensor to increase and adjust the power of the low-position visual radar sensor.

[0077] If the target highway section has low visibility, based on the detection efficiency coefficient and detection efficiency threshold of the intelligent connected vehicle, the following factors are matched: frame rate amplification factor for the high-position visual radar sensor, power amplification factor for the high-position visual radar sensor, frame rate amplification factor for the low-position visual radar sensor, power amplification factor for the low-position visual radar sensor, and frequency amplification factor for the infrared sensor response band. The frame rate of the high-position visual radar sensor is increased and adjusted using the frame rate amplification factor, the power of the low-position visual radar sensor is increased and adjusted using the power amplification factor, and the frequency of the infrared sensor response band is increased and adjusted using the frequency amplification factor, thereby updating the initial detection parameters of the intelligent connected vehicle.

[0078] It needs to be explained that the process involves matching the frequency amplification coefficient of the infrared sensor response band, calling the preset frequency amplification rules of the infrared sensor response band in the collision warning database, inputting the detection efficiency coefficient of the intelligent connected vehicle, mapping and outputting the frequency amplification coefficient of the infrared sensor response band.

[0079] It should be explained that the frequency amplification factor of the infrared sensor response band is multiplied by the preset response band of the infrared sensor to increase and adjust the frequency of the infrared sensor response band.

[0080] Reference Figure 5 As shown, the system first uses a preset baseline safety distance as the initial judgment threshold, then checks whether a device configuration switch has occurred in the current period. If a configuration change has occurred, a corrected safety distance is derived based on the latest calculated detection efficiency coefficient (DEI). This corrected value quantifies the actual detection reliability under the current configuration through the mapping relationship between the efficiency coefficient and sensor performance. The system further compares the corrected distance with the baseline distance. When the corrected value is less than the baseline value, it indicates that the current configuration can support a shorter critical safety distance. At this time, the actual safety distance threshold is updated to improve the warning sensitivity. If the corrected value is not less than the baseline value or no configuration switch has occurred, the original safety distance judgment standard is maintained. This mechanism dynamically links the device configuration status with the safety distance threshold, achieving a precise match between the warning judgment logic and the system's actual detection capability. This avoids an increase in false alarms due to configuration upgrades and can shorten the safety margin and improve road traffic efficiency under high-performance configurations, forming a closed-loop safety control at the "perception-decision-execution" level.

[0081] Furthermore, the determination of whether to switch the forward collision warning processing equipment configuration of the intelligent connected vehicle is as follows: After updating the initial detection parameters of the intelligent connected vehicle, the detection efficiency coefficient of the updated intelligent connected vehicle is obtained and compared with the detection efficiency threshold. If the detection efficiency coefficient of the updated intelligent connected vehicle is greater than or equal to the detection efficiency threshold, it is determined that the forward collision warning processing equipment configuration of the intelligent connected vehicle will not be switched; if the detection efficiency coefficient of the updated intelligent connected vehicle is less than the detection efficiency threshold, it is determined that the forward collision warning processing equipment configuration of the intelligent connected vehicle will be switched.

[0082] Specifically, the configuration of the forward collision warning processing equipment for intelligent connected vehicles is switched. The specific switching process is as follows: if it is determined that the configuration of the forward collision warning processing equipment for intelligent connected vehicles is to be switched, the environmental visibility index of the target highway section is obtained.

[0083] If the target highway section has high visibility, the configuration of the first forward collision warning processing device for the intelligent connected vehicle will be changed to the configuration of the second forward collision warning processing device.

[0084] If the environmental conditions of the target highway section are of medium visibility, the configuration of the second forward collision warning processing device of the intelligent connected vehicle will be changed to the configuration of the third forward collision warning processing device, and a risk warning will be issued.

[0085] It should be explained that the configuration of the second forward collision warning processing device in intelligent connected vehicles is changed to the configuration of the third forward collision warning processing device. However, due to the unchangeable objective attributes of the environment, the visibility level remains unchanged.

[0086] If the target highway section has low visibility, the maximum frame rate and maximum power of the high-position visual radar sensor, the maximum frame rate and maximum power of the low-position visual radar sensor, and the maximum frequency of the infrared sensor response band are matched based on the updated detection efficiency coefficient and detection efficiency threshold of the intelligent connected vehicle. The high-position visual radar sensor of the intelligent connected vehicle operates at the maximum frame rate and maximum power, the low-position visual radar sensor of the intelligent connected vehicle operates at the maximum frame rate and maximum power, and the infrared sensor of the intelligent connected vehicle receives infrared reflected signals at the maximum frequency response band and issues anomaly warnings.

[0087] It should be explained that when the target highway section has low visibility, if the detection effect of the forward collision warning processing device does not meet expectations, and the forward collision warning processing device has been configured to the highest performance level supported by the system, the system will automatically match the maximum frame rate, maximum power and maximum frequency of the forward collision warning processing device and run it.

[0088] Reference Figure 6As shown: First, the real-time distance between the vehicle and obstacles ahead is continuously acquired. When an obstacle is detected to enter the actual safe distance threshold range, a multi-level warning matching mechanism is immediately activated: the obstacle distance is compared with preset graded thresholds (Level 1 / Level 2 / Level 3 warning boundary distances), triggering different levels of warning responses accordingly—Level 1 warning is activated when the distance is between the safe distance and the Level 1 warning threshold, Level 2 warning is activated when it is between Level 1 and Level 2 warning thresholds, and Level 3 warning is activated when it is less than or equal to the Level 2 warning threshold; if the obstacle distance does not exceed the safe threshold, no warning is triggered. While the warning is active, the system continuously monitors changes in obstacle distance. If an increasing trend is detected, the warning level is downgraded from high to low until the warning is lifted; if the distance continues to decrease or remains at a dangerous value, emergency braking intervention is immediately triggered. This mechanism, through a four-order control logic of "distance threshold grading - dynamic warning response - trend reversal lifting - continuous braking in dangerous situations," constructs a safety protection system covering all scenarios, avoiding driving interference caused by frequent warnings while ensuring rapid response capabilities when collision risks escalate.

[0089] Specifically, the process for determining whether to issue a collision warning is as follows: obtain the baseline safety distance of the target road segment and mark the baseline safety distance of the target road segment as the actual safety distance.

[0090] The aforementioned baseline safe distance for the target highway segment refers to the minimum safe distance threshold preset in the collision warning database for the target highway segment, which is a benchmark parameter for measuring the safe driving space of the target highway segment.

[0091] After switching the forward collision warning processing equipment configuration of the intelligent connected vehicle, the detection efficiency coefficient of the switched intelligent connected vehicle is obtained. Based on the detection efficiency coefficient of the switched intelligent connected vehicle, the corrected safety distance of the target road segment is obtained and compared with the baseline safety distance of the target road segment.

[0092] If the corrected safety distance of the target highway segment is greater than or equal to the baseline safety distance of the target highway segment, the actual safety distance will not be updated.

[0093] If the corrected safety distance of the target highway segment is less than the baseline safety distance of the target highway segment, the actual safety distance is updated to the corrected safety distance of the target highway segment.

[0094] The forward collision warning processing equipment for intelligent connected vehicles obtains the distance between obstacles and the intelligent connected vehicle, marks it as the obstacle distance, and compares it with the actual safe distance. If the obstacle distance is greater than the actual safe distance, it is determined that no collision warning will be issued.

[0095] If the distance to the obstacle is less than or equal to the actual safe distance, a collision warning will be issued.

[0096] Specifically, collision warnings are issued, and the warning process involves: obtaining the distance to the obstacle and the actual safe distance, and then matching the collision warning level based on the obstacle distance and the actual safe distance.

[0097] If the distance to the obstacle is greater than the preset limit distance for a Level 1 collision warning in the collision warning database, but less than or equal to the actual safe distance, a Level 1 collision warning will be issued.

[0098] The defined distance corresponding to the Level 1 collision warning mentioned above refers to the shortest critical distance for triggering a Level 1 collision warning for a target highway segment preset in the collision warning database.

[0099] If the distance to the obstacle is greater than the preset boundary distance for a level 2 collision warning in the collision warning database, but less than or equal to the preset boundary distance for a level 1 collision warning in the collision warning database, a level 2 collision warning will be issued.

[0100] The defined distance corresponding to the above-mentioned Level 2 collision warning refers to the shortest critical distance for triggering a Level 2 collision warning for a target highway segment preset in the collision warning database.

[0101] If the distance to the obstacle is less than or equal to the preset limit distance for a Level 2 collision warning in the collision warning database, a Level 3 collision warning will be issued.

[0102] In one specific embodiment, the forward collision warning processing device of the intelligent connected vehicle acquires the distance to the obstacle in real time. If the distance to the obstacle gradually increases, the collision warning level is gradually reduced until the collision warning is terminated; if the distance to the obstacle does not gradually increase, the intelligent connected vehicle performs emergency braking.

[0103] A second aspect of the present invention provides a forward collision warning processing device for intelligent connected vehicles, comprising: a high-position visual radar sensor, a low-position visual radar sensor, and an infrared sensor; the high-position visual radar sensor refers to the forward collision warning processing device deployed at a higher position in the intelligent connected vehicle, including a camera and an electromagnetic wave radar, integrating visual perception and radar detection functions; the low-position visual radar sensor refers to the forward collision warning processing device deployed at a higher position in the intelligent connected vehicle, including a camera and an electromagnetic wave radar, integrating visual perception and radar detection functions; the infrared sensor refers to the sensor deployed at a key position in the forward collision warning processing device of the intelligent connected vehicle, achieving accurate detection by detecting infrared reflection signals emitted by objects within the detection range.

[0104] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A forward collision warning processing method for intelligent connected vehicles, characterized in that, include: S1. Mark the road segment where the intelligent connected vehicle is traveling as the target road segment, collect and analyze the fog visibility parameters of the target road segment, obtain the visibility range of the target road segment based on the fog visibility parameters of the target road segment, and thus obtain the initial detection parameters of the intelligent connected vehicle. S2. Acquire and analyze the detection process parameters of the intelligent connected vehicle, determine whether to update the initial detection parameters of the intelligent connected vehicle. If it is determined that the initial detection parameters of the intelligent connected vehicle should be updated, the intelligent connected vehicle acquires the updated detection process parameters of the intelligent connected vehicle, thereby determining whether to switch the forward collision warning processing device configuration of the intelligent connected vehicle. If it is determined that the initial detection parameters of the intelligent connected vehicle should not be updated, the intelligent connected vehicle continues to perform detection with the initial detection parameters. The specific process for determining whether to update the initial detection parameters of the intelligent connected vehicle is as follows: Acquire and analyze the detection process parameters of intelligent connected vehicles, including the visual radar detection deviation value of intelligent connected vehicles, the electromagnetic wave radar echo difference value of intelligent connected vehicles, and the environmental visibility index of the target highway section. The detection efficiency coefficient of the intelligent connected vehicle is compared with the detection efficiency threshold. If the detection efficiency coefficient of the intelligent connected vehicle is less than the detection efficiency threshold, the initial detection parameters of the intelligent connected vehicle are updated. If the detection efficiency coefficient of the intelligent connected vehicle is greater than or equal to the detection efficiency threshold, the initial detection parameters of the intelligent connected vehicle are not updated. The detection efficiency threshold refers to the preset detection efficiency coefficient in the collision warning database; By introducing weighted contribution coefficients, the proportional relationship between the visual radar detection deviation value and the visual radar detection deviation value of the intelligent connected vehicle, the proportional relationship between the electromagnetic wave radar echo difference value and the electromagnetic wave radar echo difference value of the intelligent connected vehicle, and the proportional relationship between the environmental visibility index of the target highway section and the defined environmental visibility index are quantified to determine the weighted contribution of each weighted contribution to the detection efficiency coefficient of the intelligent connected vehicle. The detection efficiency coefficient of the intelligent connected vehicle is then obtained by aggregating the weighted contribution of each weight. S3. Acquire the detection results of the forward collision warning processing equipment of the intelligent connected vehicle in real time, compare them with the actual safe distance, and determine whether to issue a collision warning.

2. The forward collision warning processing method for intelligent connected vehicles according to claim 1, characterized in that: The process of obtaining the visibility range of the target highway segment based on the dense fog visibility parameter of the target highway segment is as follows: The dense fog visibility parameters of the target highway section include the fog droplet concentration of the target highway section, the ambient light contrast of the target highway section, and the light transmittance of the target highway section. If the environmental visibility index of the target highway segment falls within the preset high environmental visibility index range in the collision warning database, then the environment of the target highway segment will be marked as a high visibility environment. If the environmental visibility index of the target highway segment falls within the preset medium environmental visibility index range in the collision warning database, then the environment of the target highway segment will be marked as medium visibility environment. If the environmental visibility index of the target highway section falls within the preset low environmental visibility index range in the collision warning database, the environment of the target highway section will be marked as a low visibility environment, and a risk warning will be issued.

3. The forward collision warning processing method for intelligent connected vehicles according to claim 1, characterized in that: The specific process for obtaining the initial detection parameters of the intelligent connected vehicle is as follows: If the environment of the target highway section is highly visible, the high-position visual radar sensor of the intelligent connected vehicle is activated and captures the detection image at a preset frame rate. At the same time, it transmits electromagnetic wave radar at a preset power. The preset frame rate and preset power of the high-position visual radar sensor in the high visibility environment are marked as the first initial detection parameters of the intelligent connected vehicle. The high-position visual radar sensor activated in the high visibility environment is also marked as the first forward collision warning processing device configuration. If the environment of the target highway section is of medium visibility, the high-position visual radar sensor of the intelligent connected vehicle is activated and captures the detection image at a preset frame rate, while simultaneously emitting electromagnetic wave radar at a preset power. The low-position visual radar sensor is activated and captures the detection image at a preset frame rate, while simultaneously emitting electromagnetic wave radar at a preset power. The preset frame rate and preset power of the high-position visual radar sensor and the preset frame rate and preset power of the low-position visual radar sensor corresponding to the medium visibility environment are marked as the second initial detection parameters of the intelligent connected vehicle. The high-position visual radar sensor and the second visual radar sensor activated in the medium visibility environment are marked as the configuration of the second forward collision warning processing device. If the target highway section has low visibility, the high-position visual radar sensor of the intelligent connected vehicle is activated and captures the detection image at a preset frame rate, while simultaneously emitting electromagnetic wave radar at a preset power. The low-position visual radar sensor is activated and captures the detection image at a preset frame rate, while simultaneously emitting electromagnetic wave radar at a preset power. The infrared sensor is activated and receives infrared reflected signals at a preset response band. The preset frame rate and preset power of the high-position visual radar sensor and the preset frame rate and preset power of the low-position visual radar sensor are marked as the second initial detection parameters of the intelligent connected vehicle, and the preset response band of the infrared sensor is marked as the third initial detection parameters of the intelligent connected vehicle. The high-position visual radar sensor, the low-position visual radar sensor, and the infrared sensor activated in the low-visibility environment are marked as the third forward collision warning processing device configuration.

4. The forward collision warning processing method for intelligent connected vehicles according to claim 1, characterized in that: The specific update process for the initial detection parameters of the intelligent connected vehicle is as follows: If the target highway section has high visibility, the frame rate amplification factor and power amplification factor of the high-position visual radar sensor are matched based on the detection efficiency coefficient and detection efficiency threshold of the intelligent connected vehicle. The frame rate of the high-position visual radar sensor is increased and adjusted by the frame rate amplification factor, and the power of the high-position visual radar sensor is increased and adjusted by the power amplification factor, thereby updating the initial detection parameters of the intelligent connected vehicle. If the target highway section has medium visibility, based on the detection efficiency coefficient and detection efficiency threshold of the intelligent connected vehicle, the frame rate amplification coefficient, power amplification coefficient, frame rate amplification coefficient, and power amplification coefficient of the low-position visual radar sensor are matched. The frame rate of the high-position visual radar sensor is increased and adjusted by the frame rate amplification coefficient of the high-position visual radar sensor, and the power of the low-position visual radar sensor is increased and adjusted by the power amplification coefficient of the low-position visual radar sensor. The frame rate amplification coefficient and the power amplification coefficient of the low-position visual radar sensor are used to increase and adjust the frame rate and the power of the low-position visual radar sensor, thereby updating the initial detection parameters of the intelligent connected vehicle. If the target highway section has low visibility, based on the detection efficiency coefficient and detection efficiency threshold of the intelligent connected vehicle, the following factors are matched: frame rate amplification factor for the high-position visual radar sensor, power amplification factor for the high-position visual radar sensor, frame rate amplification factor for the low-position visual radar sensor, power amplification factor for the low-position visual radar sensor, and frequency amplification factor for the infrared sensor response band. The frame rate of the high-position visual radar sensor is increased and adjusted using the frame rate amplification factor, the power of the low-position visual radar sensor is increased and adjusted using the power amplification factor, and the frequency of the infrared sensor response band is increased and adjusted using the frequency amplification factor, thereby updating the initial detection parameters of the intelligent connected vehicle.

5. A forward collision warning processing method for intelligent connected vehicles according to claim 1, characterized in that: The specific process for determining whether to switch the configuration of the forward collision warning processing equipment for intelligent connected vehicles is as follows: After updating the initial detection parameters of the intelligent connected vehicle, the detection efficiency coefficient of the updated intelligent connected vehicle is obtained and compared with the detection efficiency threshold. If the detection efficiency coefficient of the updated intelligent connected vehicle is greater than or equal to the detection efficiency threshold, it is determined that the forward collision warning processing device configuration of the intelligent connected vehicle will not be switched. If the detection efficiency coefficient of the updated intelligent connected vehicle is less than the detection efficiency threshold, then the configuration of the forward collision warning processing equipment of the intelligent connected vehicle will be switched.

6. A forward collision warning processing method for intelligent connected vehicles according to claim 5, characterized in that: The specific switching process for the forward collision warning processing equipment configuration of the intelligent connected vehicle is as follows: If it is determined that the forward collision warning processing equipment configuration of the intelligent connected vehicle is to be switched, the environmental visibility index of the target highway section is obtained. If the environment of the target highway section is highly visible, the configuration of the first forward collision warning processing device of the intelligent connected vehicle is changed to the configuration of the second forward collision warning processing device. If the environmental conditions of the target highway section are of medium visibility, the configuration of the second forward collision warning processing device of the intelligent connected vehicle will be changed to the configuration of the third forward collision warning processing device, and a risk warning will be issued. If the target highway section has low visibility, the maximum frame rate and maximum power of the high-position visual radar sensor, the maximum frame rate and maximum power of the low-position visual radar sensor, and the maximum frequency of the infrared sensor response band are matched based on the updated detection efficiency coefficient and detection efficiency threshold of the intelligent connected vehicle. The high-position visual radar sensor of the intelligent connected vehicle operates at the maximum frame rate and maximum power, the low-position visual radar sensor of the intelligent connected vehicle operates at the maximum frame rate and maximum power, and the infrared sensor of the intelligent connected vehicle receives infrared reflected signals at the maximum frequency response band and issues anomaly warnings.

7. A forward collision warning processing method for intelligent connected vehicles according to claim 1, characterized in that: The specific process for determining whether to issue a collision warning is as follows: Obtain the baseline safety distance of the target highway segment and mark the baseline safety distance of the target highway segment as the actual safety distance; After switching the forward collision warning processing equipment configuration of the intelligent connected vehicle, the detection efficiency coefficient of the intelligent connected vehicle after the switch is obtained. Based on the detection efficiency coefficient of the intelligent connected vehicle after the switch, the corrected safety distance of the target road segment is obtained and compared with the baseline safety distance of the target road segment. If the corrected safety distance of the target highway segment is greater than or equal to the baseline safety distance of the target highway segment, the actual safety distance will not be updated. If the corrected safety distance of the target highway segment is less than the baseline safety distance of the target highway segment, the actual safety distance is updated to the corrected safety distance of the target highway segment. The forward collision warning processing equipment for intelligent connected vehicles obtains the distance between obstacles and the intelligent connected vehicle, marks it as the obstacle distance, and compares it with the actual safe distance. If the obstacle distance is greater than the actual safe distance, it is determined that no collision warning will be issued. If the distance to the obstacle is less than or equal to the actual safe distance, a collision warning will be issued.

8. A forward collision warning processing method for intelligent connected vehicles according to claim 7, characterized in that: The collision warning process is as follows: Obtain obstacle distance and actual safe distance, and match collision warning level based on obstacle distance and actual safe distance; If the distance to the obstacle is greater than the preset limit distance for a Level 1 collision warning in the collision warning database, but less than or equal to the actual safe distance, a Level 1 collision warning will be issued. If the distance to the obstacle is greater than the preset boundary distance for a level 2 collision warning in the collision warning database, but less than or equal to the preset boundary distance for a level 1 collision warning in the collision warning database, a level 2 collision warning will be issued. If the distance to the obstacle is less than or equal to the preset limit distance for a Level 2 collision warning in the collision warning database, a Level 3 collision warning will be issued. The forward collision warning processing equipment of intelligent connected vehicles obtains the distance to obstacles in real time. If the distance to obstacles gradually increases, the collision warning level is gradually reduced until the collision warning is terminated. If the distance to the obstacle does not gradually increase, the intelligent connected vehicle will apply emergency braking.

9. An apparatus for processing a forward collision warning for intelligent connected vehicles as described in any one of claims 1-8, characterized in that: include: High-position visual radar sensor, low-position visual radar sensor, infrared sensor; The high-position visual radar sensor refers to a forward collision warning processing device deployed at a higher position in an intelligent connected vehicle, including a camera and electromagnetic radar, and a sensor that integrates visual perception and radar detection functions. The low-position visual radar sensor refers to a forward collision warning processing device deployed at a higher position in an intelligent connected vehicle, including a camera and electromagnetic wave radar, a sensor that integrates visual perception and radar detection functions. The infrared sensor refers to a sensor deployed in a key position of the forward collision warning and processing equipment of an intelligent connected vehicle, which achieves accurate detection by detecting the infrared reflection signals emitted by objects within its detection range.

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