Intelligent vehicle tail door control method based on interaction of laser ToF sensor and multi-state projection lamp

Abstract

The invention relates to the technical field of intelligent control, in particular to a vehicle tail gate intelligent control method based on interaction of a laser ToF sensor and a multi-state projection lamp, which comprises the following steps: detecting an acceleration direction and a distance measurement trend to generate an unstable identifier, correcting distance measurement to construct a stable area, classifying a direction control pattern and judging the trend. The echo intensity is analyzed, a reflection signal is output, and a tailgate control scheme is triggered according to conditions. According to the method, the disturbance sensing precision in the static state is improved through linkage recognition of the acceleration significant direction and the distance measurement trend slope, the distance measurement continuity and the anti-jamming capability are enhanced by combining the disturbance section difference amplitude and the direction included angle cosine weighted substitution point, and vector direction classification is matched with image change trend analysis; the recognition accuracy of the user operation direction is improved, light intensity difference trend and region stability judgment is introduced, the reflection recognition robustness is enhanced, accurate response of a control instruction is ensured, and the safety and reliability of tail gate interaction are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control, and particularly to an intelligent control method for a vehicle tailgate based on the interaction between a laser ToF sensor and a multi-state projection lamp. Background Art

[0002] The technical field of intelligent control includes various methods and devices that collect environmental data using information sensing devices and dynamically adjust and manage the operating state of a system or device through logical processing. The core content of this technical field lies in realizing human-computer interaction, automatic execution, and precise regulation through the linkage among sensors, actuators, and control logic, and it is widely applied in scenarios such as transportation, intelligent manufacturing, and home automation. Its development is closely integrated with related subsystems such as the Internet of Things, embedded systems, sensing and recognition technologies, etc., systematically realizing intelligent monitoring, recognition, and command control of physical objects, and constructing an operating mechanism based on a perception and response closed-loop.

[0003] Among them, the intelligent control method for a vehicle tailgate based on the interaction between a laser ToF sensor and a multi-state projection lamp refers to obtaining distance information of the rear vehicle space area through a laser time-of-flight sensor, and combining with a projection lamp to achieve visual prompts and interactive intention guidance. When a driver or passenger approaches the rear of the vehicle, the laser ToF sensor is used to continuously monitor the positional relationship between the target and the vehicle in real time, and based on this distance data, it is judged whether to trigger the tailgate opening control logic; in addition, the multi-state projection lamp is used to display different interactive state signals to guide the user to complete the tailgate control intention, so as to complete the interactive opening control of the rear tailgate by combining optical recognition and spatial ranging.

[0004] The prior art mostly relies on the static matching relationship between the laser ranging value and the interactive distance threshold in tailgate control, lacking the comprehensive analysis ability based on data trends and dynamic feature evolution. In actual use, the system has poor ability to distinguish external disturbances from real user interactions, and is easily interfered by non-human factors such as objects passing by, environmental vibrations, and light changes, resulting in a decrease in recognition accuracy. Since it fails to combine the ranging continuity trend and multi-angle direction judgment means, and only judges interactive actions through a fixed distance difference, it is unable to accurately recognize the user's intention in non-typical user actions or non-standard angle approach scenarios, and the interactive experience lacks flexibility and adaptability. In a changing environment, such as in the case of complex light reflection or multipath interference in space, the existing solutions are unable to evaluate the stability of reflected signals, resulting in frequent errors in the optical recognition link. The lack of corresponding judgment between the fine-grained direction classification of the behavior trajectory and the projection feedback response also limits the user's visual guidance effect and interactive efficiency, and the overall intelligent recognition level and environmental adaptation ability are limited. Summary of the Invention

[0005] The object of the present invention is to solve the disadvantages existing in the prior art, and to propose an intelligent control method for a vehicle tailgate based on the interaction between a laser ToF sensor and a multi-state projection lamp.

[0006] To achieve the above object, the present invention adopts the following technical solutions: An intelligent control method for a vehicle tailgate based on the interaction between a laser ToF sensor and a multi-state projection lamp, comprising the following steps: S1: Detect the three-axis data of the tail acceleration sensor, screen the fluctuation direction, call the direction laser ranging value, make a trend judgment with the slopes of the previous two times. If it continuously rises unidirectionally and crosses the interference boundary, generate an inertial direction instability flag; S2: Call the ranging values in the area of the inertial direction instability flag, analyze the difference between sampling points and the direction inconsistency, identify the disturbance section, calculate the weighted mean of the cosine of the included angle to replace the abnormal section, and generate a stable ranging section; S3: Construct a direction vector based on the stable ranging section, classify it according to the forward, lateral, and symmetric directions, control the tail projection to switch patterns, and make continuous trend judgments on the contour density, center trajectory, and pattern matching degree, then generate a behavior trajectory recognition state; S4: Call the area indicated by the behavior trajectory recognition state, obtain the initial and delayed laser echo, judge the change trend of their intensity difference, compare it with the previous cycle, analyze the center stability, and output an optical reflection confirmation signal; S5: Compare the ranging in the area of the optical reflection confirmation signal with the ground reference, judge whether it can be triggered, and detect whether the projection flashes and whether the user leaves the pattern, to obtain an intelligent control scheme for the vehicle tailgate.

[0007] As a further solution of the present invention, the inertial direction instability flag includes the main direction of acceleration change, the trend of the slope of the ranging value change, and the interference determination boundary judgment. The stable ranging section includes the replacement point of the disturbance section, the weighted mean of the cosine value of the direction included angle, and the analysis result of the continuous ranging difference. The behavior trajectory recognition state includes the classification of the moving vector direction, the edge density distribution of the projection area, the feature of the center point offset trajectory, and the pattern matching trend judgment. The optical reflection confirmation signal includes the difference in reflected light intensity, the fluctuation trend of the light intensity difference, and the standard deviation of the sampling stability in the central area. The intelligent control scheme for the vehicle tailgate includes the determination of the difference between the laser ranging and the ground, the flashing state of the tail projection, and the detection of the user's leaving action.

[0008] As a further solution of the present invention, the specific steps of S1 are as follows: S101: Detect the acceleration output in three directions at the tail of the vehicle when it is turned off, calculate the direction change amplitude, identify the amplitude direction, and generate a direction amplitude comparison value; S102: Call the three ranging values in the direction of the direction amplitude comparison value, calculate the slope of the adjacent ranging values, and generate a direction ranging slope result; S103: Based on the direction ranging slope result, determine whether the slope continuously increases and compare it with the interference determination boundary line. If the condition is met, generate an inertial direction instability flag.

[0009] As a further solution of the present invention, the specific formula for the slope of adjacent ranging values is as follows: ; where represents the ranging value slope between the i-th and the (i + 1)-th ranging, represents the i-th ranging value, represents the (i + 1)-th ranging value, represents the independent value of each measurement point, represents the average value of the measurement points, represents the total number of points.

[0010] As a further solution of the present invention, the specific steps of S2 are as follows: S201: Call the continuous ranging values in the area pointed to by the inertial direction instability flag, and sequentially calculate the ranging difference amplitude between adjacent sampling points in the paragraph to obtain a paragraph difference amplitude sequence; S202: According to the paragraph difference amplitude sequence, screen the paragraph sampling points with difference amplitudes within the perturbation range and inconsistent direction changes, and establish a perturbation sampling point set; S203: Call the ranging values at the time points before and after each point in the perturbation sampling point set, calculate the cosine of the direction angle, and weighted average to generate a stable ranging section.

[0011] As a further solution of the present invention, the specific steps of S3 are as follows: S301: Based on the direction vector sequence in the stable ranging section, classify it into forward, lateral, and symmetric directions according to the angle range, and generate a direction classification label set; S302: Call the direction classification label set to send a switching instruction to the projection device, collect continuous data on the edge density, center offset, and pattern matching of the area, and generate an area projection trend sequence; S303: According to the area projection trend sequence, determine whether the three trends exceed the set boundary line within a continuous period. If the condition is met, generate a behavior trajectory recognition status.

[0012] As a further solution of the present invention, the specific steps of S4 are as follows: S401: Call the area of the behavior trajectory recognition status, obtain the current initial and delayed reflected light intensities and determine whether the difference increases, and generate an increasing trend of the light intensity difference; S402: Based on the increasing trend of the light intensity difference, shrink the sampling angle, extract the central continuous sampling points, and calculate the sampling fluctuation value of the central continuous sampling points to generate a sampling fluctuation result; S403: Determine whether it is lower than the stable threshold result according to the sampling fluctuation result, and establish an optical reflection confirmation signal.

[0013] As a further solution of the present invention, the calculation formula for the sampling fluctuation value of the central continuous sampling points is: ; Wherein, represents the sampling fluctuation value of the central continuous sampling points, represents the light intensity value of the th sampling point, represents the average value of the light intensity values of all sampling points within the central continuous sampling section, represents the angle value corresponding to the th sampling point, represents the average value of all angle values within the central continuous sampling section, is the sampling point serial number, is the starting index of the central continuous sampling section, is the length of the continuous sampling section.

[0014] As a further solution of the present invention, the specific steps of S5 are as follows: S501: Compare the ranging value in the area covered by the optical reflection confirmation signal with the current ground reference distance, calculate the ranging difference index, and determine whether it is in the trigger interval to generate a ranging difference status; S502: According to the ranging difference status, identify whether the current tail projection is in a flashing state, and at the same time detect whether the user has a leaving action in this state to obtain an interactive behavior compliance identifier; S503: Invoke the interactive behavior compliance identifier to determine whether all three states are satisfied. If all are established, send a tailgate action execution signaling to generate a vehicle tailgate intelligent control solution.

[0015] As a further solution of the present invention, the specific calculation formula for the ranging difference index is: ; Wherein, represents the ranging difference index, represents the real-time ranging value corresponding to the current optical reflection confirmation signal, represents the current ground reference distance, represents the ranging value collected for the kth time within the current cycle, represents the average value of all ranging values within the current cycle, represents the total number of current ranging samplings, represents the average ranging value finally output in the previous cycle, is the ranging serial number in the sum of squared differences.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In the present invention, through the linkage recognition of the significant acceleration direction and the slope of the ranging trend, the disturbance perception accuracy in the static state is improved. By combining the difference amplitude of the disturbance segment and the cosine-weighted substitution point of the direction angle, the ranging continuity and anti-interference ability are enhanced. The vector direction classification is combined with the analysis of the image change trend to improve the recognition accuracy of the user operation direction. The trend of the light intensity difference and the judgment of the regional stability are introduced to enhance the robustness of the reflection recognition, ensure the accurate response of the control instruction, and effectively improve the safety and reliability of the tailgate interaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following-described drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0018] Figure 1 It is a schematic diagram of the step flow of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The following will describe the technical solutions in the present invention with reference to the drawings.

[0020] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as "exemplary" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Exactly speaking, the use of the word "example" is intended to present concepts in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two.

[0021] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, their intended meanings are the same.

[0022] In the embodiments of the present invention, sometimes subscripts such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, their intended meanings are the same.

[0023] In order to make the technical problems to be solved, technical solutions and advantages of the present invention clearer, the following will be described in detail with reference to the drawings and specific embodiments.

[0024] Please refer to Figure 1 , a vehicle tailgate intelligent control method based on the interaction between a laser ToF sensor and a multi-state projection lamp, comprising the following steps: S1: Detect the output values of the acceleration induction at the tail of the vehicle in three directions when the vehicle is turned off, identify the direction with a significant change amplitude among the three directions, call the current ranging value of the laser ranging device in the direction, and judge the continuity of the change slope of the ranging value and the previous two acquisition sequences in the same direction. If the slope trend shows a continuous one-way increase and exceeds the interference determination boundary, generate an inertial direction instability identifier; S2: Call the continuous ranging values of the area indicated by the inertial direction instability identifier, perform adjacent difference amplitude analysis on the paragraphs constructed by the sampling points in the sequence, screen the points with inconsistent direction changes in the paragraph difference amplitude interval as the disturbance segments, extract the ranging data at the same positions in the time points before and after the disturbance segments, calculate the cosine values of the direction angles of the three groups of data, and generate a stable ranging section by constructing an alternative point through weighted mean; S3: Based on the moving direction vector sequence constructed in the stable ranging section, classify all vectors into forward, lateral or symmetric directions, then send a light map switching instruction to the tail projection, and respectively judge the trend persistence of the contour edge density, the center point offset trajectory, and the coverage pattern matching degree of the projection area. If all three consecutive detection periods meet the set boundary, generate a behavior trajectory recognition status; S4: Call the area indicated by the behavior trajectory recognition status, obtain the initial reflected light and the delayed reflected light intensities at the current moment through laser emission, perform a determination operation on the continuous change amplitude of the intensity difference between the two, and compare the result with the light intensity difference in the same area in the previous cycle. If the continuous fluctuation shows a positive increase and exceeds the reflection difference threshold, shrink the sampling angle of the area, and perform a standard deviation determination on the fluctuation stability of the continuous acquisition points in the central area, and output an optical reflection confirmation signal; S5: Judge the difference between the laser ranging value within the area covered by the optical reflection confirmation signal and the recorded ground reference distance, verify whether the ranging meets the trigger condition, identify whether the tail projection is currently in a flashing state, and detect whether the user has left during the state. If all three of the above judgments meet the current interaction logic, output a tailgate action execution signaling to obtain a vehicle tailgate intelligent control solution.

[0025] The inertial direction instability identification includes the main direction of acceleration change, the trend of the slope of the ranging value change, and the judgment of the interference determination boundary. The stable ranging section includes the disturbance section replacement point, the weighted average value of the cosine value of the direction angle, and the analysis result of the continuous ranging difference. The behavior trajectory recognition state includes the classification of the moving vector direction, the edge density distribution of the projection area, the central point offset trajectory feature, and the pattern matching trend judgment. The optical reflection confirmation signal includes the difference in reflected light intensity, the fluctuation trend of the light intensity difference, and the standard deviation of the sampling stability in the central area. The intelligent control scheme for the vehicle tailgate includes the determination of the difference between laser ranging and the ground, the flashing state of the tail projection, and the detection of the user's leaving action.

[0026] The specific steps of S1 are as follows: S101: Detect the acceleration output in three directions at the tail of the vehicle in the off state, calculate the direction change amplitude, identify the amplitude direction, and generate a direction amplitude comparison value; When the vehicle is off and stationary, the acceleration sensors on the X, Y, and Z axes at the tail collect data at a fixed frequency. For example, the X-axis records 10 acceleration values per second for 5 seconds, obtaining a total of 50 groups of data. After caching, the maximum and minimum values in each direction are extracted. If the highest value in the X-axis data segment is 0.25g and the lowest is -0.05g, the range is 0.25g - (-0.05g) = 0.30g. The range of the Y-axis is 0.10g, and the range of the Z-axis is 0.03g. By comparing the range values of the three axes, the ranges of the X, Y, and Z axes are sorted in descending order as 0.30g > 0.10g > 0.03g. The X-axis corresponding to the maximum range is taken as the main change direction. Divide the range of each axis by the minimum range of 0.03g to obtain the X-axis coefficient of 0.30 / 0.03 = 10, the Y-axis coefficient of 0.10 / 0.03 ≈ 3.33, and the Z-axis coefficient of 1. After normalization, a direction amplitude comparison value of X:Y:Z = 10:3.3:1 is generated. For example, when the vehicle is parked on a bumpy road and a vehicle frequently passes behind, the vibration amplitude of the X-axis far exceeds other directions, and the comparison value directly reflects the dominance of the X-axis.

[0027] S102: Call the three ranging values in the direction of the direction amplitude comparison value, calculate the slope of adjacent ranging values, and generate a direction ranging slope result; The specific formula for the slope of adjacent ranging values is as follows: ; Among them, represents the ranging value slope between the i-th and the (i + 1)-th ranging, represents the i-th ranging value, represents the (i + 1)-th ranging value, represents the independent value of each measurement point, represents the average value of the measurement points, represents the total number of points; Parameter acquisition and value setting: Distance measurement value and : No. Secondary distance measurement value rice; No. Secondary distance measurement value rice.

[0028] Measuring point data : mW, mW, mW, mW, mW.

[0029] average value : ; Calculation steps: Calculate the absolute value of the distance difference: ; Calculate the sum of squared differences of the measured point data: ; ; ; Compute the square root of the sum of squared differences: ; Substitute into the formula to calculate : ; Result description: The result shows that the change value of the direction ranging slope is about 0.0058, which means that in two consecutive ranging measurements, the change degree of the direction ranging slope is small and the ranging data stability is high. This value can be used to evaluate the stability and consistency of ranging data and assist in judging abnormal fluctuations or environmental interference during the measurement process.

[0030] S103: Based on the direction ranging slope result, determine whether the slope continues to increase, and compare it with the interference determination boundary. If the conditions are met, generate an inertial direction instability flag; Take the slope sequences at three consecutive time points K1 = 0.1 m / s, K2 = 0.2 m / s, K3 = 0.3 m / s, and verify whether K3 > K2 > K1 (0.3 > 0.2 > 0.1 holds). Calculate the adjacent slope differences ΔK1 = 0.2 - 0.1 = 0.1, ΔK2 = 0.3 - 0.2 = 0.1. The setting basis for the interference determination boundary ΔK_min = 0.05 is as follows: By statistically analyzing 200 sets of experimental data on the slope fluctuations caused by environmental interferences (such as wind force and minute ground vibrations), the maximum change amount does not exceed 0.05. Therefore, when the actual differences ΔK1 and ΔK2 both exceed 0.05, it is determined as an effective increase. Currently, ΔK1 = 0.1 > 0.05 and ΔK2 = 0.1 > 0.05, generating an inertial direction instability identifier. For example, when the vehicle continues to accelerate and slide after being impacted by an external force, the slope difference exceeds the interference tolerance, triggering an alarm.

[0031] The specific steps of S2 are as follows: S201: Call the continuous ranging values in the area pointed to by the inertial direction instability identifier, and sequentially calculate the ranging difference amplitudes between adjacent sampling points in the paragraph to obtain the paragraph difference amplitude sequence; Based on the time period pointed to by the inertial direction instability identifier (such as from t1 to t5), extract the ranging values of 5 consecutive sampling points in this area D1 = 1.5 m, D2 = 1.3 m, D3 = 1.0 m, D4 = 0.6 m, D5 = 0.3 m. Calculate the adjacent point differences ΔD1 = D2 - D1 = -0.2 m, ΔD2 = D3 - D2 = -0.3 m, ΔD3 = D4 - D3 = -0.4 m, ΔD4 = D5 - D4 = -0.3 m in sequence. Take the absolute values of each difference to obtain the paragraph difference amplitude sequence [0.2, 0.3, 0.4, 0.3]. For example, when the vehicle's ranging value continuously decreases during the landslide process, the difference amplitude reflects the severity of the displacement change. When the amplitude exceeds 0.1 m, it is determined as an effective displacement. If the difference amplitude is lower than 0.1 m (such as ΔD = 0.05 m) in a certain case, it is regarded as noise interference and excluded.

[0032] S202: According to the paragraph difference amplitude sequence, screen the paragraph sampling points with difference amplitudes within the disturbance interval and inconsistent directions, and establish a disturbance sampling point set; Set the lower limit of the disturbance interval to 0.15 meters and the upper limit to 0.45 meters (by statistically analyzing 100 sets of environmental interference data, 95% of the interference amplitudes are between 0.05 - 0.15 meters, and the true displacement amplitude is usually greater than 0.15 meters). Traverse the sequence of paragraph difference amplitudes [0.2, 0.3, 0.4, 0.3], filter out the points with amplitude values within the range of 0.15 - 0.45 meters (all meet the criteria), check the consistency of the direction changes of each point. For example, ΔD1 to ΔD4 are all negative changes (the difference signs are consistent), which is determined to be in the same direction and not added to the disturbance set. If there are some alternating difference signs (such as the sequence ΔD1 = -0.2, ΔD2 = +0.3, ΔD3 = -0.4), then filter out the points with inconsistent signs (such as the second point ΔD2 = +0.3 has the opposite direction to the previous point ΔD1 = -0.2), and add such points to the disturbance sampling point set. For example, when the vehicle is pushed and pulled by intermittent external forces, resulting in a sudden change in the direction of the ranging value, the set records such abnormal points.

[0033] S203: Call the ranging values at the time points before and after each point in the disturbance sampling point set, calculate the cosine of the direction angle, and calculate the weighted mean to generate a stable ranging section; For the sampling points in the disturbance set (such as the third point D3 = 1.0 meter), call the ranging values of the two points before and after it (D1 = 1.5 meters, D2 = 1.3 meters, D4 = 0.6 meters, D5 = 0.3 meters), construct the front vector (D2 - D1 = -0.2 meters, D3 - D2 = -0.3 meters) and the rear vector (D4 - D3 = -0.4 meters, D5 - D4 = -0.3 meters), and calculate the cosine of the direction angle between the front vector and the rear vector: The average change of the front vector is (-0.2 - 0.3) / 2 = -0.25 meters, and the average change of the rear vector is (-0.4 - 0.3) / 2 = -0.35 meters. When the directions of the two are the same, the cosine value is 1, and when they are opposite, it is -1. Here, since both are negative, the cosine value is 1, and the weighted mean is (1 × 0.6 + 1 × 0.4) = 1 (the weights are assigned 0.6 and 0.4 according to the proximity of time). If the weighted mean of the cosine value exceeds the threshold of 0.8 (based on the fact that the proportion of consistent stable movement directions in the experimental data is more than 85%), then it is determined that the directions before and after this point are stable, and the range of 2 seconds before and after such points (such as t1 to t5) is marked as a stable ranging section. For example, when the vehicle resumes directional sliding after a short disturbance, the stable section is used for subsequent trajectory prediction.

[0034] The specific steps of S3 are as follows: S301: Based on the sequence of direction vectors in the stable ranging section, classify them into forward, lateral, and symmetric directions according to the angle range to generate a direction classification label set; Extract three consecutive direction vectors V1 = (-0.25 m / s), V2 = (-0.30 m / s), and V3 = (-0.28 m / s) from the stable ranging section, calculate the angles between adjacent vectors. For example, the angle θ1 between V1 and V2 is 0° (because they have the same direction), the angle θ2 between V2 and V3 is 5°. Set the forward classification range as 0° ≤ θ < 30°, the lateral range as 60° ≤ θ < 120°, and the symmetric direction range as 150° ≤ θ ≤ 180°. If an angle is 85°, it is classified as lateral; if it is 170°, it is classified as the symmetric direction. If all current angles are less than 30°, it is classified as forward, generating a direction classification label set [forward, forward, forward]. For example, when a vehicle reverses in a straight line, the angles between the direction vectors continuously remain less than 30°, and the label set reflects the consistency of the movement direction.

[0035] S302: Call the direction classification label set to send a switching instruction to the projection device, collect continuous data on the edge density, center offset, and pattern matching of the area, and generate a regional projection trend sequence; According to the label set [forward, forward, forward], send an instruction to the projection device to switch to the parallel beam projection mode. The number of edge pixels in the projection area (edge density) is 120 points, the center point coordinate offset is (0.1 m, 0.0 m), and the pattern matching similarity is 85% (compared with the preset reverse trajectory template). The data for three consecutive cycles are: in cycle 1, the edge density is 120, the center offset is 0.1 m, and the matching degree is 85%; in cycle 2, the edge density is 150, the center offset is 0.2 m, and the matching degree is 80%; in cycle 3, the edge density is 180, the center offset is 0.3 m, and the matching degree is 75%. Generate a regional projection trend sequence [edge density: +60, center offset: +0.2 m, matching degree: -10%]. For example, when a vehicle reverses, the projection area expands, resulting in an increase in the edge density, and the center point gradually deviates from the reference.

[0036] S303: Determine whether all three trends in the regional projection trend sequence exceed the set boundaries within consecutive cycles. If satisfied, generate a behavior trajectory recognition status; Set the trend boundary line as the edge density change threshold ±50 (based on the maximum density fluctuation of ±40 during normal operation in historical data), the center offset threshold ±0.35 meters (allowing a maximum offset of 20% of the width according to the vehicle body width of 1.8 meters), the pattern matching threshold decline rate ≤15% (the lowest tolerance value for effective matching in experimental statistics is 70%). Check the edge density change +60 (exceeding +50), center offset +0.3 meters (not exceeding 0.35 meters), and matching degree decline of 10% (not exceeding 15%) in the trend sequence. If any one of the three items exceeds the limit, a determination is triggered. Currently, only the edge density exceeds the limit, not meeting the condition that all three items exceed the limit. If the subsequent cycle data is edge density +70, center offset +0.4 meters, and matching degree -20%, then all three items exceed the limit, generating a behavior trajectory recognition status. For example, when the projection parameters are completely out of bounds during vehicle out-of-control, it is determined as an abnormal movement behavior.

[0037] The specific steps of S4 are as follows: S401: Call the behavior trajectory recognition status area, obtain the current initial and delayed reflected light intensities, and determine whether the difference is increasing to generate an increasing trend of the light intensity difference; Based on the time period (t1 to t3) marked by the behavior trajectory recognition status, call the initial reflected light intensity data (I1 = 500 lux at time t1, I2 = 520 lux at time t2, I3 = 550 lux at time t3) and the delayed reflected light intensity data (D1 = 480 lux at time t1, D2 = 500 lux at time t2, D3 = 520 lux at time t3) within this area, calculate the light intensity difference ΔI1 = I1 - D1 = 20 lux, ΔI2 = I2 - D2 = 20 lux, ΔI3 = I3 - D3 = 30 lux at each time point, and determine whether the difference is increasing: Check ΔI1 ≤ ΔI2 ≤ ΔI3 (20 ≤ 20 ≤ 30 does not meet the strict increasing condition). If there are at least two consecutive increases (such as ΔI1 = 20 → ΔI2 = 25 → ΔI3 = 30), then generate an increasing trend of the light intensity difference. For example, when there is water accumulation behind the vehicle causing reflection delay and the difference gradually increases from 20 lux to 30 lux, it is determined as an increasing trend. Set the increasing determination condition as the adjacent difference increase amplitude ≥ 5 lux (based on the maximum environmental interference fluctuation of ±3 lux in historical data, and an actual change exceeding 5 lux is regarded as an effective trend). Currently, ΔI3 - ΔI2 = 10 lux ≥ 5, meeting the condition.

[0038] S402: Based on the increasing trend of the light intensity difference, shrink the sampling angle, extract the central continuous sampling points, calculate the sampling fluctuation value of the central continuous sampling points, and generate a sampling fluctuation result; The calculation formula for the sampling fluctuation value of the central continuous sampling points: ; Among them, represents the sampling fluctuation value of the central continuous sampling points, represents the light intensity value of the th sampling point, represents the average value of the light intensity values of all sampling points within the central continuous sampling section, represents the th sampling point corresponding angle value, represents the average value of all angle values within the central continuous sampling section, is the sampling point serial number, is the starting index of the central continuous sampling section, is the length of the continuous sampling section; Parameter acquisition and numerical setting: Number of sampling points : Sampling point serial number : Light intensity value : ; ; ; ; ; Angle value : ; ; ; ; ; Calculation steps: Calculate the average light intensity : ; Calculate the average angle : ; Calculate the total light intensity difference : ; ; ; ; ; Calculate the total light intensity deviation : ; ; ; ; ; ; Calculate the sum of squares of angular deviations : ; ; ; ; ; ; Calculate the square root of the sum of squares of angular deviations: ; Substitute into the formula for calculation : ; This result indicates that the sampling fluctuation value of the central continuous sampling points is approximately 0.1215, representing the degree of fluctuation of the light intensity change in this area. This value can be used to evaluate the uniformity of the light intensity distribution, assist in judging the stability of the light source or the response consistency of the detection system.

[0039] S403: According to the sampling fluctuation result, judge whether it is lower than the stable threshold result, and establish an optical reflection confirmation signal; Set the stable threshold to 3 lux. If the sampling fluctuation result is 2.05 lux, judge that 2.05 < 3, and establish an optical reflection confirmation signal. For example, when the vehicle is driving on a stable road surface, the reflection fluctuation is controlled, and the signal is marked as valid. If the fluctuation result is 4 lux (such as when water splashes from the tires on a rainy day causing chaotic reflections), then 4 ≥ 3, and no confirmation signal is generated. The threshold is set based on: statistically analyzing the fluctuation data of 100 groups of normal driving scenarios, 98% of the fluctuation values ≤ 2.5 lux, so the threshold is set to 3 lux to cover the 2σ (standard deviation 1.2 lux) range to ensure the error tolerance rate. For example, when the fluctuation value is 2.8 lux, it is still lower than the threshold, triggering the confirmation signal for subsequent response of the control module.

[0040] The specific steps of S5 are as follows: S501: Compare the ranging value in the area covered by the optical reflection confirmation signal with the current ground reference distance, calculate the ranging difference index, and judge whether it is in the triggering interval to generate a ranging difference status; The specific formula for the ranging difference index is: ; Wherein, represents the ranging difference index, represents the real-time ranging value corresponding to the current optical reflection confirmation signal, represents the current ground reference distance, represents the ranging value collected for the kth time within the current period, represents the average value of all ranging values within the current period, represents the total number of current ranging samples, represents the average ranging value finally output in the previous period, is the ranging serial number in the sum of squared differences; Parameter acquisition and value setting: Real-time ranging value : ; Ground reference distance : ; Ranging values within the current period : ; ; ; ; ; Therefore, the total number of current ranging samples is: ; Average ranging value within the current period : ; Average ranging value in the previous period : ; Calculation steps: Calculate : ; Calculate : ; Calculate : ; Calculate : ; ; ; ; ; ; ; Substitute into the formula for calculation : ; The result shows that the ranging difference index is approximately 0.004376, indicating the degree of difference between the current ranging value, the ground reference distance, and the historical ranging data. This value can be used to determine whether it is within the trigger range, thereby generating a ranging difference status.

[0041] S502: According to the ranging difference status, identify whether the current tail projection is in a flashing state, and at the same time detect whether the user makes a leaving action in this state to obtain an interaction behavior compliance flag; Detect the tail projection state. If the projection flashing frequency is 4 times per second (the set threshold ≥ 3 times / second is the flashing state), and at the same time judge the user's action through the in-vehicle pressure sensor and camera data: the value of the pressure sensor drops from 70 kg to 0 kg (for 2 seconds continuously), and the camera detects that the user moves from the driver's seat to the outside area of the vehicle (the coordinate change exceeds 2 meters), it is determined that the user makes a leaving action, and an interaction behavior compliance flag is generated (flashing state "yes", leaving action "yes"). For example, after the user gets out of the car, the projection continues to flash and there is no load in the vehicle. If the projection frequency is 2 times per second (below the threshold) or the user does not leave the seat (the pressure remains at 70 kg), the flag does not hold.

[0042] S503: Invoke the interaction behavior compliance flag, judge whether all three states are satisfied. If all are established, send a tailgate action execution signal to generate a vehicle tailgate intelligent control scheme; Verify the three states: the ranging difference status is "effectively triggered", the projection flashing state is "yes", and the user leaving action is "yes". If all three are satisfied simultaneously (for example, ΔD = 0.2 meters is within the trigger range, the projection frequency is 4 times per second, and the user leaves the seat), send an opening instruction to the tailgate control module to generate a vehicle tailgate intelligent control scheme. If any one of them is not satisfied (such as the user does not leave or the ranging difference is invalid), the instruction is not triggered. Set the condition verification order as: first detect the ranging difference, then verify the projection state, and finally judge the user's action. For example, when the user stays in the car on a rainy day (the pressure is not cleared), even if the first two are satisfied, the tailgate opening is still blocked.

[0043] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims described above.

Claims

1. A vehicle tailgate intelligent control method based on the interaction between a laser ToF sensor and a multi-state projection lamp, characterized in that: The following steps are involved: S1: Detect the three-axis data of the tail acceleration sensor, select the fluctuation direction, call the direction laser ranging value, and make a trend judgment with the previous two slopes. If it continues to rise in one direction and crosses the interference boundary, an inertial direction instability mark is generated; S2: calling the ranging value of the unstable identification area of ​​the inertial direction, analyzing the sampling point difference and the direction inconsistency, identifying the disturbance segment, calculating the weighted mean of the angle cosine to replace the abnormal segment, and generating a stable ranging segment; S3: constructing a direction vector based on the stable ranging section, classifying it into forward, sideways, and symmetrical, controlling the tail projection switching pattern, making a continuous trend judgment on the contour density, center trajectory, and pattern matching, and generating a behavior trajectory recognition state; S4: calling the area shown in the behavior trajectory recognition state, obtaining the initial and delayed laser echoes, determining the intensity difference change trend, comparing with the previous cycle, analyzing the center stability, and outputting an optical reflection confirmation signal; S5: Compare the optical reflection confirmation signal area distance measurement with the ground reference to determine whether it can be triggered, and detect whether the projection flickers and whether the user leaves the pattern to obtain the vehicle tailgate intelligent control solution.

2. The vehicle tailgate intelligent control method based on the interaction between the laser ToF sensor and the multi-state projection lamp according to claim 1 is characterized in that: The inertial direction instability indicator includes the main direction of acceleration change, the slope trend of the ranging value change, and the interference judgment limit judgment; the stable ranging section includes the disturbance section replacement point, the weighted mean of the cosine value of the direction angle, and the continuous ranging difference analysis result; the behavior trajectory recognition state includes the movement vector direction classification, the projection area edge density distribution, the center point offset trajectory characteristics, and the pattern matching trend judgment; the optical reflection confirmation signal includes the reflected light intensity difference, the light intensity difference fluctuation trend, and the central area sampling stability standard deviation; the vehicle tailgate intelligent control solution includes the laser ranging and ground difference judgment, the tail projection flashing state, and the user leaving action detection.

3. The vehicle tailgate intelligent control method based on the interaction between the laser ToF sensor and the multi-state projection lamp according to claim 1 is characterized in that: The specific steps of S1 are: S101: Detect the acceleration output of the rear end in three directions when the vehicle is turned off, calculate the direction change amplitude, identify the amplitude direction, and generate a direction amplitude comparison value; S102: calling three ranging values ​​of the direction amplitude comparison value direction, calculating the slope of adjacent ranging values, and generating a direction ranging slope result; S103: Based on the direction ranging slope result, determine whether the slope continues to increase, and compare it with the interference determination boundary. If the conditions are met, generate an inertial direction instability flag.

4. The vehicle tailgate intelligent control method based on the interaction between the laser ToF sensor and the multi-state projection lamp according to claim 3 is characterized in that: The adjacent distance value slope calculation formula is specifically: ； in, Represents the slope of the distance measurement between the i-th and i+1-th distance measurement, represents the i-th distance measurement value, represents the i+1th distance measurement value, represents the independent value of each measurement point, represents the average value of the measurement points, Represents the total number of points.

5. The vehicle tailgate intelligent control method based on the interaction between the laser ToF sensor and the multi-state projection lamp according to claim 1 is characterized in that: The specific steps of S2 are: S201: calling the continuous distance measurement values ​​of the area indicated by the inertial direction instability mark, and sequentially calculating the distance measurement difference amplitudes of adjacent sampling points in the paragraph to obtain a paragraph difference amplitude sequence; S202: selecting paragraph sampling points whose difference amplitudes are within the disturbance interval and whose direction changes are inconsistent according to the paragraph difference amplitude sequence, and establishing a disturbance sampling point set; S203: calling the ranging values ​​of the time points before and after each point in the disturbance sampling point set, calculating the cosine of the direction angle, and taking a weighted average to generate a stable ranging section.

6. The vehicle tailgate intelligent control method based on the interaction between the laser ToF sensor and the multi-state projection lamp according to claim 1 is characterized in that: The specific steps of S3 are: S301: Based on the direction vector sequence in the stable ranging section, the direction is classified into forward, sideways and symmetric directions according to the angle range, and a direction classification label set is generated; S302: calling the direction classification label set to issue a switching instruction to the projection device, collecting continuous data of regional edge density, center offset, and pattern matching, and generating a regional projection trend sequence; S303: judging whether the three trends all exceed the set boundaries in a continuous period according to the regional projection trend sequence, and generating a behavior trajectory recognition state if they are satisfied.

7. The vehicle tailgate intelligent control method based on the interaction between the laser ToF sensor and the multi-state projection lamp according to claim 1 is characterized in that: The specific steps of S4 are: S401: calling the behavior trajectory recognition state area, obtaining the current initial and delayed reflected light intensities and determining whether the difference is increasing, and generating an increasing trend of the light intensity difference; S402: shrinking the sampling angle based on the increasing trend of the light intensity difference, extracting the central continuous sampling points, calculating the sampling fluctuation values ​​of the central continuous sampling points, and generating the sampling fluctuation results; S403: According to the sampling fluctuation result, determine whether it is lower than the stable threshold result, and establish an optical reflection confirmation signal.

8. The vehicle tailgate intelligent control method based on the interaction between the laser ToF sensor and the multi-state projection lamp according to claim 7 is characterized in that: The calculation formula of the sampling fluctuation value of the central continuous sampling point is: ； in, Represents the sampling fluctuation value of the central continuous sampling point, Representative The light intensity value of the sampling point, Represents the average light intensity value of all sampling points in the central continuous sampling section. Representative The angle value corresponding to the sampling point, Represents the average value of all angle values ​​in the central continuous sampling segment, is the sampling point number, is the starting index of the central continuous sampling segment, is the length of the continuous sampling segment.

9. The vehicle tailgate intelligent control method based on the interaction between the laser ToF sensor and the multi-state projection lamp according to claim 1 is characterized in that: The specific steps of S5 are: S501: Compare the distance measurement value of the area covered by the optical reflection confirmation signal with the current ground reference distance, calculate the distance measurement difference index, determine whether it is in the trigger interval, and generate the distance measurement difference state; S502: According to the state of the distance measurement difference, it is identified whether the tail projection is currently in a flashing state, and whether the user leaves the state, and an interaction behavior compliance mark is obtained; S503: Call the interactive behavior compliance flag to determine whether all three states are met. If all are met, a tailgate action execution signaling is issued to generate a vehicle tailgate intelligent control solution.

10. The vehicle tailgate intelligent control method based on the interaction between the laser ToF sensor and the multi-state projection lamp according to claim 9, characterized in that: The distance measurement difference index calculation formula is specifically: ； in, represents the ranging difference index, Represents the real-time distance measurement value corresponding to the current optical reflection confirmation signal. Represents the current ground reference distance, Represents the kth collected distance value in the current cycle, Represents the average value of all ranging values ​​in the current cycle, Represents the total number of current ranging sampling times, Represents the average distance measurement value finally output in the previous cycle, is the ranging number in the sum of squared differences.

Images