Lane departure warning methods, control devices and systems

Abstract

A lane departure warning method, control device, and system are disclosed. The lane departure warning method includes: acquiring wheel speed information and lane line information; and executing a lane departure warning function based on the wheel speed information and the lane line information. This solution can infer the current road surface smoothness based on the wheel speed information, and then reasonably determine the lane departure warning intensity threshold according to different road surface conditions, thereby improving the identifiability of the lane departure warning function and enhancing the safety and user experience of the LDW (Lane Departure Warning) function.

Description

Technical Field

[0001] This article relates to, but is not limited to, intelligent driving technology, and in particular to a lane departure warning method, control device, and system. Background Technology

[0002] Advanced Driver Assistance Systems (ADAS) include Lane Departure Warning (LDW) functions that issue alerts to prevent the vehicle from drifting out of its lane, such as by emitting vibrations through the steering wheel. Currently, the LDW function uses the same vibration amplitude regardless of road conditions. Therefore, in poor road conditions, the LDW warning intensity may be difficult for the driver to perceive due to road surface variations, thus affecting user safety and experience. Summary of the Invention

[0003] This application provides a lane departure warning method, control device, and system that can combine lane line information and wheel speed information to perform the lane departure warning function, thereby improving the safety and user experience of the LDW function.

[0004] This application provides a lane departure warning method, including: acquiring wheel speed information and lane line information; and executing a lane departure warning function based on the wheel speed information and the lane line information.

[0005] The lane departure warning method provided in this application combines wheel speed information and lane line information to execute the lane departure warning function (i.e., LDW function), issuing a timely warning when the vehicle is about to deviate from the lane to prevent it from doing so. Therefore, lane line information and wheel speed information can jointly serve as the control basis for the lane departure warning function. Since wheel speed information reflects wheel vibration and indirectly reflects the smoothness of the current road surface, the smoothness of the current road can be inferred based on the wheel speed information during the execution of the lane departure warning function. This allows for adjustment of the alarm intensity based on the current road smoothness, preventing users from not feeling the alarm due to poor road conditions. In this way, the execution of the lane departure warning function comprehensively considers lane line information and road surface smoothness, thereby improving the safety and user experience of the lane departure warning function.

[0006] Furthermore, compared to using accelerometers to infer road surface smoothness, this embodiment infers the current road surface smoothness using wheel speed information, that is, by using the signals from wheel speed sensors. Since accelerometers are mounted on the vehicle body and are relatively far from the ground, they detect vehicle body vibrations other than steering wheel vibrations, making them susceptible to interference. Wheel speed sensors, being the closest sensors to the ground, have a significant advantage over other sensors when monitoring road surface conditions, being less affected by interference from other factors, and therefore providing higher accuracy in inferring road surface smoothness.

[0007] In one exemplary embodiment, the step of executing the lane departure warning function based on the wheel speed information and the lane line information includes: determining the lane departure warning intensity based on the wheel speed information; and executing the lane departure warning function based on the lane line information and the lane departure warning intensity.

[0008] In one exemplary embodiment, determining the lane departure alarm intensity based on the wheel speed information includes: determining the vibration level of the wheel based on the wheel speed information; determining the road surface smoothness level based on the vibration level of the wheel; and determining the lane departure alarm intensity based on the road surface smoothness level.

[0009] In one exemplary embodiment, determining the road surface smoothness grade based on the vibration level of the wheel includes: determining a road surface smoothness grade reference value based on the vibration level of the wheel; and determining the road surface smoothness grade based on the road surface smoothness grade reference value.

[0010] In one exemplary embodiment, determining the road surface smoothness level based on the road surface smoothness level reference value includes: determining whether the road surface smoothness level reference value has been continuously set for a certain duration; determining the road surface smoothness level reference value as a new road surface smoothness level based on the fact that the road surface smoothness level reference value has been continuously set for a certain duration; and continuing to use the previously determined road surface smoothness level based on the fact that the road surface smoothness level reference value has not been continuously set for a certain duration.

[0011] In one exemplary embodiment, determining the lane departure alarm intensity based on the road surface smoothness level includes: determining lane departure alarm intensity adjustment information based on the road surface smoothness level; and determining the lane departure alarm intensity based on the lane departure alarm intensity adjustment information.

[0012] In one exemplary embodiment, the lane departure warning intensity adjustment information is: an updated value of the lane departure warning intensity; determining the lane departure warning intensity based on the lane departure warning intensity adjustment information includes: determining the updated value of the lane departure warning intensity as the lane departure warning intensity; or, the lane departure warning intensity adjustment information is: a lane departure warning intensity coefficient; determining the lane departure warning intensity based on the lane departure warning intensity adjustment information includes: determining the lane departure warning intensity by multiplying the lane departure warning intensity baseline value by the lane departure warning intensity coefficient.

[0013] In one exemplary embodiment, determining the lane departure alarm intensity adjustment information based on the road surface smoothness level includes: determining the lane departure alarm intensity adjustment information corresponding to the road surface smoothness level based on the mapping relationship between the road surface smoothness level and the lane departure alarm intensity adjustment information.

[0014] In one exemplary embodiment, the road surface smoothness level is negatively correlated with road surface smoothness, the wheel vibration level is negatively correlated with road surface smoothness, the lane departure alarm intensity is positively correlated with the road surface smoothness level, and the lane departure alarm intensity adjustment information is positively correlated with the lane departure alarm intensity.

[0015] In one exemplary embodiment, the road surface smoothness level includes: Level 1, Level 2, and Level 3, wherein Level 1 road surface smoothness is better than Level 2 road surface smoothness, and Level 2 road surface smoothness is better than Level 3 road surface smoothness; the lane departure warning intensity adjustment information includes: first adjustment information, second adjustment information, and third adjustment information, wherein the first adjustment information < the second adjustment information < the third adjustment information; in the mapping relationship between the road surface smoothness level and the lane departure warning intensity adjustment information: when the road surface smoothness level is Level 1, the lane departure warning intensity adjustment information is equal to the first adjustment information; when the road surface smoothness level is Level 2, the lane departure warning intensity adjustment information is equal to the second adjustment information; and when the road surface smoothness level is Level 3, the lane departure warning intensity adjustment information is equal to the third adjustment information.

[0016] In one exemplary embodiment, determining the vibration level of the wheel based on the wheel speed information includes: filtering the wheel speed information; and determining the vibration level of the wheel based on the result of the filtering process.

[0017] In one exemplary embodiment, the wheel speed information is the average of the wheel speed information of multiple wheels of the vehicle.

[0018] This application also provides a lane departure warning control device, including a processor and a memory storing a computer program. When the processor executes the computer program, it implements the steps of the lane departure warning method as described in any of the above embodiments.

[0019] This application embodiment also provides a lane departure warning system, characterized in that it includes: a driving environment condition detection device, configured to detect driving environment conditions; a wheel speed detection device, configured to detect wheel speed; and a lane departure warning control device, configured to obtain lane line information and wheel speed information based on the detection results of the driving environment condition detection device and the wheel speed detection device, and to execute a lane departure warning function based on the lane line information and the wheel speed information.

[0020] In one exemplary embodiment, the lane departure warning control device includes: a road surface smoothness level determination module, configured to determine the road surface smoothness level based on the wheel speed information; and a lane departure warning control module, configured to determine the lane departure warning intensity based on the road surface smoothness level, and to execute the lane departure warning function based on the lane line information and the lane departure warning intensity.

[0021] Other features and advantages of this application will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the application. Other advantages of this application can be realized and obtained by means of the solutions described in the description and the accompanying drawings. Attached Figure Description

[0022] The accompanying drawings are used to provide an understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0023] Figure 1 This is a flowchart illustrating a driver hands-off detection method provided in one embodiment of this application.

[0024] Figure 2 This is a schematic diagram comparing the driver's hand torque signal and the LDW alarm torque when driving on a good road;

[0025] Figure 3 This is a schematic diagram comparing the driver's hand torque signal and the LDW alarm torque when driving on a bad road.

[0026] Figure 4 This is a schematic diagram comparing the filtered wheel speed signal with the road surface smoothness grade.

[0027] Figure 5 This is a schematic diagram showing the relationship between the degree of wheel vibration and the road surface smoothness level.

[0028] Figure 6 This is a schematic diagram of the structure of a lane departure warning control device provided in one embodiment of this application;

[0029] Figure 7 A schematic diagram of a vehicle provided in one embodiment of this application;

[0030] Figure 8 A schematic diagram of a vehicle provided in one embodiment of this application;

[0031] Figure 9 This is a schematic diagram of a lane departure warning system provided in one embodiment of this application.

[0032] 101 Turn signal switch, 102 Accelerator pedal sensor, 103 Brake pedal sensor, 104 Steering angle sensor, 105 Hand torque sensor, 106 Vehicle speed sensor, 107 Radar sensor, 108 Camera sensor, 109 Yaw rate sensor, 110 Longitudinal acceleration sensor, 111 Lateral acceleration sensor, 112 Right front wheel speed sensor, 113 Left front wheel speed sensor, 114 Right rear wheel speed sensor, 115 Left rear wheel speed sensor;

[0033] 1071 First radar sensor, 1072 Second radar sensor, 1073 Third radar sensor, 1074 Fourth radar sensor, 1075 Fifth radar sensor, 1076 Sixth radar sensor, 1081 First camera sensor, 1082 Second camera sensor, 1083 Third camera sensor.

[0034] 200 Driving assistance control device, 201 Lane departure warning control device, 2011 Lane departure warning control module, 2021 Low-pass filter processing module, 2022 High-pass filter processing module, 2023 Calculation module, 2024 Road surface smoothness level determination module, 205 Processor, 206 Memory.

[0035] 301 Engine ECU, 311 Engine, 302 Brake ECU, 312 Brake System, 303 Steering ECU, 313 Steering System, 304 Information Display ECU, 314 Information Display Device;

[0036] 400 Driving Environment Condition Detection Device. Detailed Implementation

[0037] This application describes several embodiments, but these descriptions are exemplary and not restrictive, and it will be apparent to those skilled in the art that many more embodiments and implementations are possible within the scope of the embodiments described herein. Although many possible combinations of features are shown in the drawings and discussed in the detailed description, many other combinations of the disclosed features are also possible. Unless specifically limited, any feature or element of any embodiment may be used in combination with, or may replace, any feature or element of any other embodiment.

[0038] This application includes and contemplates combinations of features and elements known to those skilled in the art. The embodiments, features, and elements disclosed in this application may also be combined with any conventional features or elements to form a unique inventive scheme as defined by the claims. Any feature or element of any embodiment may also be combined with features or elements from other inventive schemes to form another unique inventive scheme as defined by the claims. Therefore, it should be understood that any feature shown and / or discussed in this application may be implemented individually or in any suitable combination. Therefore, the embodiments are not limited except by the limitations imposed by the appended claims and their equivalents. Furthermore, various modifications and changes may be made within the scope of the appended claims.

[0039] Furthermore, in describing representative embodiments, the specification may have presented methods and / or processes as a specific sequence of steps. However, the method or process should not be limited to the specific order of steps described herein, to the extent that it does not depend on such a specific order. As will be understood by those skilled in the art, other sequences of steps are also possible. Therefore, the specific order of steps set forth in the specification should not be construed as a limitation of the claims. Moreover, the claims concerning the method and / or process should not be limited to the steps performed in the written order, and those skilled in the art will readily understand that these orders can be varied and still remain within the spirit and scope of the embodiments of this application.

[0040] Currently, the LDW (Lane Departure Warning) function uses the same vibration amplitude regardless of road conditions. If the LDW vibration alarm intensity is increased on a smooth road surface, the sudden alarm may be perceived by the driver as sudden and could even be mistaken for a malfunction. Furthermore, camera recognition is not 100% accurate; misidentification of lane lines can lead to a very poor driving experience, and drivers may even disable the LDW function, rendering this safety feature ineffective. On rough roads, the LDW alarm intensity may be difficult for the driver to perceive due to road surface conditions, thus impacting user safety and overall experience.

[0041] The lane departure warning method provided in this application embodiment can infer road conditions based on wheel speed information, and then adjust the alarm intensity of LDW in combination with road conditions. This can reduce misunderstandings or unpleasant experiences caused to drivers by the LDW function, and help improve the safety and user experience of the LDW function.

[0042] The following is a detailed explanation with reference to the accompanying drawings.

[0043] like Figure 1 As shown in the figure, this application provides a lane departure warning method, including:

[0044] Step S10: Obtain wheel speed information and lane line information;

[0045] Step S20: Execute the lane departure warning function based on wheel speed information and lane line information.

[0046] The lane departure warning method provided in this application combines wheel speed information and lane line information to execute the lane departure warning function (i.e., LDW function), issuing a timely warning when the vehicle is about to deviate from the lane to prevent it from doing so. Therefore, lane line information and wheel speed information can jointly serve as the control basis for the lane departure warning function. Since wheel speed information reflects wheel vibration and indirectly reflects the smoothness of the current road surface, the smoothness of the current road can be inferred based on the wheel speed information during the execution of the lane departure warning function. This allows for adjustment of the alarm intensity based on the current road smoothness, preventing users from not feeling the alarm due to poor road conditions. In this way, the execution of the lane departure warning function comprehensively considers lane line information and road surface smoothness, thereby improving the safety and user experience of the lane departure warning function.

[0047] Furthermore, compared to using accelerometers to infer road surface smoothness, this embodiment infers the current road surface smoothness using wheel speed information, that is, by using the signals from wheel speed sensors. Since accelerometers are mounted on the vehicle body and are relatively far from the ground, they detect vehicle body vibrations other than steering wheel vibrations, making them susceptible to interference. Wheel speed sensors, being the closest sensors to the ground, have a significant advantage over other sensors when monitoring road surface conditions, being less affected by interference from other factors, and therefore providing higher accuracy in inferring road surface smoothness.

[0048] In this embodiment, the lane departure warning intensity can be characterized by the vibration amplitude and frequency of the steering wheel, the volume and frequency of the alarm sound, the brightness and frequency of the alarm lights, etc.

[0049] In one exemplary embodiment, a lane departure warning function is executed based on wheel speed information and lane line information, including:

[0050] The intensity of the lane departure warning is determined based on wheel speed information.

[0051] The lane departure warning function is activated based on lane line information and lane departure warning intensity.

[0052] Research has revealed that the difference between the hand torque caused by road vibration and the LDW vibration alarm torque is significant when driving on different road surfaces. Figure 2 This diagram illustrates the comparison between the hand torque caused by road vibration when driving on a good road and the LDW vibration alarm torque. The line on the left side, with regular fluctuations and large amplitude, represents the LDW vibration alarm torque. The line throughout the image, with irregular fluctuations and relatively small amplitude, represents the hand torque caused by road vibration. Figure 3 This diagram compares the hand torque caused by road vibrations when driving on rough roads with the LDW vibration alarm torque. The line on the left side, characterized by regular fluctuations and large amplitude, represents the LDW vibration alarm torque. The line throughout the image, exhibiting irregular fluctuations, represents the hand torque caused by road vibrations. Figure 2 It can be seen that the difference between the hand torque caused by road vibration and the LDW vibration alarm torque is quite significant. Therefore, the driver can clearly perceive the LDW vibration alarm, but the intensity may be too high, leading the driver to mistakenly believe that the vehicle has malfunctioned. Figure 3 It can be seen that the difference between the hand torque caused by road vibration and the LDW vibration alarm torque is small, so the driver can hardly detect the LDW vibration alarm.

[0053] Therefore, when driving on good roads, the LDW alarm intensity can be set relatively low to improve the driver's experience. Conversely, when driving on bad roads, the LDW alarm intensity needs to be relatively high to be clearly perceived by the driver.

[0054] Therefore, this solution first determines the lane departure warning intensity based on the wheel speed information to ensure that the determined lane departure warning intensity matches the road conditions reflected by the wheel speed information, and then executes the lane departure warning function based on the lane line information and the lane departure warning intensity.

[0055] The system can determine the vehicle's position in the current lane based on lane marking information, thereby identifying whether the vehicle is about to deviate from the lane and issuing a timely warning.

[0056] Based on wheel speed information, the smoothness of the current road surface can be inferred, and then the lane departure warning intensity can be determined based on the smoothness of the current road surface. This ensures that the final output warning intensity matches the current road conditions, so as to avoid the warning intensity being difficult for the driver to perceive due to poor road conditions, thereby improving the safety of the LDW function.

[0057] In one exemplary embodiment, determining the lane departure warning intensity based on wheel speed information includes:

[0058] The degree of wheel vibration is determined based on wheel speed information;

[0059] The road surface smoothness grade is determined based on the degree of vibration of the wheels;

[0060] The lane departure warning intensity is determined based on the road surface smoothness level.

[0061] During vehicle operation, the wheels vibrate due to the unevenness of the road surface, which in turn affects the signal from the wheel speed sensor. Therefore, by analyzing the signals from the wheel speed sensor at different times, the vibration spectrum of the wheel can be obtained. In other words, the vibration spectrum of the wheel can be derived from the wheel speed information, thereby determining the degree of wheel vibration at different times.

[0062] The degree of wheel vibration is closely related to the road surface smoothness, and the intensity of the lane departure warning is also closely related to the road surface smoothness. Therefore, the road surface smoothness level can be determined first by the degree of wheel vibration, and then the lane departure warning intensity can be determined based on the road surface smoothness level. The logic is simple, clear and reasonable.

[0063] The specific method for determining the degree of wheel vibration based on the signal from the wheel speed sensor is based on the same principle as the conventional method for determining the degree of vehicle body vibration using the signal from the acceleration sensor, and will not be described in detail here.

[0064] In one exemplary embodiment, determining the road surface smoothness level based on the degree of wheel vibration includes:

[0065] The reference value for the road surface smoothness grade is determined based on the degree of vibration of the wheels;

[0066] The road surface smoothness grade is determined based on the reference value for road surface smoothness grade.

[0067] Since the vibration level of wheels varies at different times, directly determining the road surface smoothness level based on wheel vibration would cause the road surface smoothness level to also change constantly, resulting in constantly changing lane departure warning intensity. This would complicate the programming and increase the failure rate.

[0068] Furthermore, it is unreasonable to directly determine road conditions based on the degree of wheel vibration at a single moment. For example, when a wheel goes over obstacles such as a manhole cover, speed bump, or small stone, the degree of wheel vibration will change suddenly. It is obviously unreasonable to conclude that the road conditions are poor based on this.

[0069] Therefore, this scheme first determines the reference value of road surface smoothness grade based on the vibration level of the wheels, and then determines the road surface smoothness grade based on the reference value of road surface smoothness grade, which helps to improve the accuracy of road surface condition prediction.

[0070] In one exemplary embodiment, determining the road surface smoothness grade based on a road surface smoothness grade reference value includes:

[0071] Determine whether the reference value for road surface smoothness level has been continuously set for the specified duration;

[0072] Based on the fact that the reference value for road surface smoothness grade has been continuously set for a certain period of time, the reference value for road surface smoothness grade is determined as the new road surface smoothness grade.

[0073] Since the reference value for road surface smoothness grade has not been continuously set for a certain duration, the previously determined road surface smoothness grade will continue to be used.

[0074] Because wheel speed sensor signal changes are affected not only by road surface smoothness but also by other factors, such as instantaneous vibrations when passing over manhole covers, speed bumps, or small stones, causing significant instantaneous changes in the wheel speed sensor signal, which are unrelated to road surface smoothness, the road surface smoothness rating reference value is often misclassified as a value indicating poor road surface smoothness (i.e., poor road condition) due to the greater degree of wheel vibration. Directly determining this road surface smoothness rating reference value as the actual road surface smoothness rating will inevitably lead to misjudgment.

[0075] If the vibration is caused by road surface conditions, the wheels will continue to vibrate at a roughly equivalent intensity for a period of time. Therefore, the road surface smoothness rating reference value corresponding to the wheel vibration intensity will also remain unchanged for a set period. In this case, the road surface smoothness rating reference value corresponds to the road surface smoothness, so it is reasonable to determine the road surface smoothness rating reference value as the new road surface smoothness rating.

[0076] If the reference value for road surface smoothness grade is not continuously set for a certain duration, it indicates that the wheel vibration is instantaneous and not caused by road surface smoothness. Therefore, it can be determined that the road surface smoothness has not changed, the road surface smoothness grade remains unchanged, and the previously determined road surface smoothness grade continues to be used.

[0077] exist Figure 4 In the diagram, "extended time" indicates that when the road surface smoothness reference value reaches the level indicated by "2" in the diagram (i.e., Figure 5 The third level in the middle, Figure 4 0 in Figure 5 Level 1 in Figure 4 The 1 in the middle corresponds to Figure 5 If the road surface smoothness level is 2 (as indicated by the diagram) and has persisted for a period of time, then the road surface smoothness level can be determined to be 2.

[0078] The duration can be set as needed, such as 10s, 30s, 1min, 5min, 10min, etc.

[0079] At the factory setting, the road surface smoothness grade can be set to the baseline value, which represents the smoothness grade under good road conditions. During subsequent use, the road surface smoothness grade can be adjusted based on changes in road surface smoothness to improve the accuracy of the predicted smoothness grade.

[0080] In one exemplary embodiment, determining the lane departure warning intensity based on the road surface smoothness level includes:

[0081] The lane departure warning intensity adjustment information is determined based on the road surface smoothness level;

[0082] The lane departure warning intensity is determined based on the lane departure warning intensity adjustment information.

[0083] The intensity of the lane departure warning can be adjusted in different ways as needed. For example, it can be determined directly by searching or calculated. Calculation methods can also be varied, such as addition / subtraction or multiplication.

[0084] Therefore, determining the lane departure warning intensity adjustment information based on the degree of wheel vibration, and then determining the lane departure warning intensity based on the lane departure warning intensity adjustment information, can have a variety of implementation methods, making it easy to choose the appropriate method according to needs.

[0085] In one exemplary embodiment, the lane departure warning intensity adjustment information is an updated value of the lane departure warning intensity. Determining the lane departure warning intensity based on the lane departure warning intensity adjustment information includes: determining the updated value of the lane departure warning intensity as the lane departure warning intensity.

[0086] When the lane departure warning intensity adjustment information is the updated value of the lane departure warning intensity, the system does not need to perform calculations and can directly determine the updated value of the lane departure warning intensity as the lane departure warning intensity. This solution eliminates the calculation step, thus simplifying the logic and the electronic control program.

[0087] In another exemplary embodiment, the lane departure warning intensity adjustment information is: a lane departure warning intensity coefficient. Determining the lane departure warning intensity based on the lane departure warning intensity adjustment information includes: multiplying the lane departure warning intensity baseline value by the lane departure warning intensity coefficient to determine the lane departure warning intensity.

[0088] When the lane departure warning intensity adjustment information is the lane departure warning intensity coefficient, the system can obtain the lane departure warning intensity through a simple multiplication calculation. Since the lane departure warning intensity coefficient is usually relatively small, it helps to reduce the system's storage space requirements.

[0089] In one exemplary embodiment, determining lane departure warning intensity adjustment information based on road surface smoothness level includes:

[0090] Based on the mapping relationship between road surface smoothness level and lane departure alarm intensity adjustment information, determine the lane departure alarm intensity adjustment information corresponding to the road surface smoothness level.

[0091] In this way, the mapping relationship between road surface smoothness level and lane departure alarm intensity adjustment information can be directly stored in the system. Of course, it can also be placed on the network, and the lane departure alarm intensity adjustment information can be determined directly by searching.

[0092] In one exemplary embodiment, the road surface smoothness level is negatively correlated with the road surface smoothness, the wheel vibration level is negatively correlated with the road surface smoothness, the lane departure alarm intensity is positively correlated with the road surface smoothness level, and the lane departure alarm intensity adjustment information is positively correlated with the lane departure alarm intensity.

[0093] Road surface smoothness grade is negatively correlated with road surface smoothness, meaning that a higher smoothness grade indicates a poorer road surface smoothness and a worse road condition; conversely, a lower smoothness grade indicates a better road surface smoothness and a better road condition. Similarly, wheel vibration intensity is also negatively correlated with road surface smoothness, meaning that more intense wheel vibration indicates a poorer road surface smoothness and a worse road condition; and less intense wheel vibration indicates a better road surface smoothness and a better road condition. Therefore, the correlation between wheel vibration intensity and road surface smoothness grade is as follows: a higher smoothness grade corresponds to more intense wheel vibration, and a lower smoothness grade corresponds to less intense wheel vibration.

[0094] Lane departure warning intensity is positively correlated with road surface smoothness level, meaning that the higher the road surface smoothness level, the stronger the lane departure warning intensity; and the lower the road surface smoothness level, the weaker the lane departure warning intensity. Lane departure warning intensity adjustment information is also positively correlated with lane departure warning intensity, meaning that the stronger the lane departure warning intensity, the larger the adjustment information; and the weaker the lane departure warning intensity, the smaller the adjustment information. Therefore, the correspondence between lane departure warning intensity adjustment information and road surface smoothness level can be established: the higher the road surface smoothness level, the larger the adjustment information; and the lower the road surface smoothness level, the smaller the adjustment information. This mapping relationship can be established through experiments, experience summarization, etc., and stored in the system, or it can be placed on the network.

[0095] In one exemplary embodiment, such as Figure 5 As shown, road surface smoothness grades include: Grade 1, Grade 2 and Grade 3. Grade 1 road surface smoothness is better than Grade 2 road surface smoothness, and Grade 2 road surface smoothness is better than Grade 3 road surface smoothness.

[0096] The lane departure warning intensity adjustment information includes: first adjustment information, second adjustment information, and third adjustment information, with the first adjustment information < second adjustment information < third adjustment information.

[0097] In the mapping relationship between road surface smoothness grade and lane departure warning intensity adjustment information:

[0098] When the road surface smoothness level is Level 1, the lane departure alarm intensity adjustment information is equal to the first adjustment information;

[0099] When the road surface smoothness level is level two, the lane departure alarm intensity adjustment information is equal to the second adjustment information;

[0100] When the road surface smoothness level is three, the lane departure alarm intensity adjustment information is equal to the third adjustment information.

[0101] This plan classifies road surface smoothness into three levels: Level 1 has the best road surface smoothness and is considered a good road; Level 2 has the next best road surface smoothness and is considered a slightly bad road; and Level 3 has the worst road surface smoothness and is considered a severely bad road.

[0102] Correspondingly, the lane departure warning intensity adjustment information is also divided into three levels: the first adjustment information corresponds to the first level of road surface smoothness, the second adjustment information corresponds to the second level of road surface smoothness, and the third adjustment information corresponds to the third level of road surface smoothness.

[0103] Since the vibration level of a vehicle's wheels cannot remain constant during driving, even under the same road surface smoothness level, the vibration level will fluctuate. Therefore, the vibration level of the wheels can be divided into three ranges based on the road surface smoothness level: when it is less than the first vibration level, the road surface smoothness level is Level 1, and the corresponding lane departure warning intensity adjustment information is the first adjustment information; when it is between the first and second vibration levels (the second vibration level is greater than the first vibration level), the road surface smoothness level is Level 2, and the corresponding lane departure warning intensity adjustment information is the second adjustment information; when it is greater than the second vibration level, the road surface smoothness level is Level 3, and the corresponding lane departure warning intensity adjustment information is the third adjustment information.

[0104] For example (such as) Figure 5 As shown): When the lane departure alarm intensity adjustment information is the updated value of the lane departure alarm intensity: when the vibration level of the wheel is less than the first vibration level, the road surface smoothness level is level one, and the lane departure alarm intensity can be recorded as Kon; when the vibration level of the wheel is between the first vibration level and the second vibration level, the road surface smoothness level is level two, and the lane departure alarm intensity can be recorded as Kon1; when the vibration level of the wheel is greater than the second vibration level, the road surface smoothness level is level three, and the lane departure alarm intensity can be recorded as Kon2, then Kon < Kon1 < Kon2.

[0105] The above division method can basically meet the usage requirements, and the electronic control program is relatively simple and not complicated.

[0106] Of course, the classification of road surface smoothness level, wheel vibration level, and lane departure warning intensity adjustment information is not limited to the above methods. It can also be divided into two levels, four levels, or even more levels as needed.

[0107] In one exemplary embodiment, determining the degree of wheel vibration based on wheel speed information includes:

[0108] Filter the wheel speed information;

[0109] The degree of wheel vibration is determined based on the results of the filtering process.

[0110] Filtering wheel speed information, that is, filtering the signals from wheel speed sensors, can filter out interference signals, which helps to improve the accuracy of subsequent road condition predictions.

[0111] In one exemplary embodiment, filtering the wheel speed information includes:

[0112] The wheel speed information is processed by low-pass filtering and high-pass filtering.

[0113] By setting the corresponding cutoff frequency during these two filtering processes, excessively high and low frequencies can be filtered out, thus filtering out the road surface frequencies of bad roads, or in other words, filtering out frequency components that are comparable to the LDW vibration alarm frequency. This makes it easier to accurately determine the degree of wheel vibration, and thus accurately determine the lane departure alarm intensity corresponding to the road surface smoothness level.

[0114] In one example, the wheel speed information is processed by low-pass filtering and high-pass filtering in sequence, with the cutoff frequency of the low-pass filtering being higher than that of the high-pass filtering.

[0115] In another example, the wheel speed information is processed by high-pass filtering and low-pass filtering in sequence, with the cutoff frequency of the high-pass filtering being lower than that of the low-pass filtering.

[0116] The cutoff frequencies for low-pass and high-pass filtering can be reasonably set based on the conventional road surface frequency.

[0117] In one exemplary embodiment, the wheel speed information is the average of the wheel speed information of multiple wheels of the vehicle.

[0118] This helps prevent misjudging poor road conditions due to a single wheel passing over a manhole cover or small stone, and improves the accuracy of subsequent judgments.

[0119] As for which wheel speed values ​​to use, the selection can be made reasonably based on factors such as the vehicle's drive system and specific structure.

[0120] In one example, the wheel speed information is the average of the wheel speed information of the left front wheel and the left rear wheel.

[0121] In another example, the wheel speed information is the average of the wheel speed information of the right front wheel and the right rear wheel.

[0122] In yet another example, the wheel speed information is the average of the wheel speed information of the left front wheel and the right front wheel.

[0123] In yet another example, the wheel speed information is the average of the wheel speed information of the left and right wheels and the right rear wheel.

[0124] like Figure 6 As shown, this application embodiment also provides a lane departure warning control device 201, including a processor 205 and a memory 206 storing a computer program. When the processor 205 executes the computer program, it implements the steps of any of the lane departure warning methods in the above embodiments, and thus has all the above-mentioned beneficial effects, which will not be repeated here.

[0125] Processor 205 may be an integrated circuit chip with signal processing capabilities. The aforementioned processor 205 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application-Specific Integrated Circuit (ASIC), an On-Premises Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor.

[0126] This application also provides a lane departure warning system, including: a driving environment condition detection device, a wheel speed detection device, and a lane departure warning control device 201.

[0127] The driving environment condition detection device is set to detect the driving environment condition.

[0128] The wheel speed detection device is set to detect the wheel speed.

[0129] The lane departure warning control device 201 is configured to: obtain lane line information and wheel speed information based on the detection results of the driving environment condition detection device and the wheel speed detection device, and execute the lane departure warning function based on the lane line information and wheel speed information.

[0130] The lane departure warning system provided in this application combines wheel speed information and lane line information to execute the lane departure warning function (i.e., LDW function), issuing a timely warning when the vehicle is about to deviate from the lane to prevent it from doing so. Therefore, lane line information and wheel speed information can jointly serve as the control basis for the lane departure warning function. Since wheel speed information reflects wheel vibration and indirectly reflects the smoothness of the current road surface, the smoothness of the current road can be inferred based on the wheel speed information during the execution of the lane departure warning function. This allows for adjustment of the alarm intensity based on the current road smoothness, preventing users from not feeling the alarm due to poor road conditions. In this way, the execution of the lane departure warning function comprehensively considers lane line information and road surface smoothness, thereby improving the safety and user experience of the lane departure warning function.

[0131] Furthermore, compared to using accelerometers to infer road surface smoothness, this embodiment infers the current road surface smoothness using wheel speed information, that is, by using the signals from wheel speed sensors. Since accelerometers are mounted on the vehicle body and are relatively far from the ground, they detect vehicle body vibrations other than steering wheel vibrations, making them susceptible to interference. Wheel speed sensors, being the closest sensors to the ground, have a significant advantage over other sensors when monitoring road surface conditions, being less affected by interference from other factors, and therefore providing higher accuracy in inferring road surface smoothness.

[0132] Among them, such as Figure 7 As shown, the driving environment condition detection device 400 includes, but is not limited to: radar sensor 107, camera sensor 108, lidar sensor, ultrasonic sensor, etc.

[0133] In one example, such as Figure 8 As shown, the driving environment condition detection device 400 includes: a first radar sensor 1071 for sensing the driving environment directly in front; a second radar sensor 1072 for sensing the driving environment on the right side in front; a third radar sensor 1073 for sensing the driving environment on the left side in front; a first camera sensor 1081 mainly for detecting the driving environment directly in front; a second camera sensor 1082 mainly for detecting the driving environment on the left side of the vehicle; a third camera sensor 1083 mainly for detecting the driving environment on the right side of the vehicle; a fourth radar sensor 1074 mainly for detecting the driving environment directly behind; a fifth radar sensor 1075 mainly for detecting the driving environment to the right rear; and a sixth radar sensor 1076 mainly for detecting the driving environment to the left rear.

[0134] As long as the driving environment can be detected, there are no requirements regarding the type of sensor (radar, lidar, ultrasonic sensors, camera sensors, etc.). Sensors for detecting the driving environment can detect and identify the speed, relative speed, position, angle, and size of three-dimensional objects around the vehicle.

[0135] As long as the driving environment ahead can be detected, the Lane Departure Warning (LDW) function can be guaranteed to be executed, and there are no requirements on the number of sensors.

[0136] Wheel speed detection devices include, but are not limited to: right front wheel speed sensor 112, left front wheel speed sensor 113, right rear wheel speed sensor 114, and left rear wheel speed sensor 115.

[0137] In one exemplary embodiment, the lane departure warning control device 201 includes a road surface smoothness level determination module 2024 and a lane departure warning control module 2011.

[0138] The road surface smoothness grade determination module 2024 is set to determine the road surface smoothness grade based on wheel speed information.

[0139] The lane departure warning control module 2011 is configured to: determine the lane departure warning intensity based on the road surface smoothness level, and execute the lane departure warning function based on lane line information and lane departure warning intensity.

[0140] This solution first determines the lane departure warning intensity based on wheel speed information, ensuring that the determined lane departure warning intensity matches the road conditions reflected by the wheel speed information. Then, it executes the lane departure warning function based on lane line information and lane departure warning intensity.

[0141] In one exemplary embodiment, the road surface smoothness level determination module 2024 includes a first determination module and a second determination module. The lane departure alarm control module 2011 includes a third determination module and a control module.

[0142] The first determining module is configured to determine the degree of wheel vibration based on wheel speed information.

[0143] The second determining module is set to determine the road surface smoothness level based on the degree of vibration of the wheels.

[0144] The third module is set to determine the lane departure alarm intensity based on the road surface smoothness level.

[0145] The control module is configured to execute the lane departure alarm function based on lane line information and lane departure alarm intensity.

[0146] In one exemplary embodiment, the second determining module includes: a first determining unit and a second determining unit.

[0147] The first determining unit is set as follows: determining the reference value of road surface smoothness level based on the vibration level of the wheels.

[0148] The second determining unit is set as follows: determine the road surface smoothness grade based on the road surface smoothness grade reference value.

[0149] In one exemplary embodiment, the second determining unit is configured as follows:

[0150] Determine whether the reference value for road surface smoothness level has been continuously set for the specified duration;

[0151] Based on the fact that the reference value for road surface smoothness grade has been continuously set for a certain period of time, the reference value for road surface smoothness grade is determined as the new road surface smoothness grade.

[0152] Since the reference value for road surface smoothness grade has not been continuously set for a certain duration, the previously determined road surface smoothness grade will continue to be used.

[0153] In one exemplary embodiment, the third determining module is configured to: determine lane departure alarm intensity adjustment information based on road surface smoothness level; and determine lane departure alarm intensity based on lane departure alarm intensity adjustment information.

[0154] In one exemplary embodiment, the lane departure warning intensity adjustment information is: the updated value of the lane departure warning intensity. The third determining module is configured to: determine the updated value of the lane departure warning intensity as the lane departure warning intensity.

[0155] In another exemplary embodiment, the lane departure warning intensity adjustment information is: lane departure warning intensity coefficient. The third determining module is configured to determine the lane departure warning intensity by multiplying the lane departure warning intensity benchmark value by the lane departure warning intensity coefficient.

[0156] In one exemplary embodiment, the third determining module is configured to: determine the lane departure alarm intensity adjustment information corresponding to the road surface smoothness level based on the mapping relationship between the road surface smoothness level and the lane departure alarm intensity adjustment information.

[0157] In one exemplary embodiment, the road surface smoothness level is negatively correlated with the road surface smoothness, the wheel vibration level is negatively correlated with the road surface smoothness, the lane departure alarm intensity is positively correlated with the road surface smoothness level, and the lane departure alarm intensity adjustment information is positively correlated with the lane departure alarm intensity.

[0158] In one exemplary embodiment, the road surface smoothness grades include: Grade 1, Grade 2, and Grade 3, wherein Grade 1 road surface smoothness is better than Grade 2 road surface smoothness, and Grade 2 road surface smoothness is better than Grade 3 road surface smoothness.

[0159] The lane departure warning intensity adjustment information includes: first adjustment information, second adjustment information, and third adjustment information, with the first adjustment information < second adjustment information < third adjustment information.

[0160] In the mapping relationship between road surface smoothness grade and lane departure warning intensity adjustment information:

[0161] When the road surface smoothness level is Level 1, the lane departure alarm intensity adjustment information is equal to the first adjustment information;

[0162] When the road surface smoothness level is level two, the lane departure alarm intensity adjustment information is equal to the second adjustment information;

[0163] When the road surface smoothness level is three, the lane departure alarm intensity adjustment information is equal to the third adjustment information.

[0164] In one exemplary embodiment, the lane departure warning system further includes a filtering module configured to filter wheel speed information. A first determining module is configured to determine the degree of wheel vibration based on the filtered result.

[0165] In one exemplary embodiment, the filtering module includes a low-pass filtering module 2021 (i.e., LPF processing module 2021) and a high-pass filtering module 2022 (i.e., HPF processing module 2022). The low-pass processing module performs low-pass filtering on the wheel speed information, and the high-pass processing module performs high-pass filtering on the wheel speed information.

[0166] In one exemplary embodiment, the wheel speed information is the average of the wheel speed information of multiple wheels of the vehicle. The lane departure warning system also includes a calculation module 2023, which is configured to calculate the average of the wheel system information of multiple wheels.

[0167] like Figure 7 As shown, this application embodiment also provides a vehicle, including a driving assistance ECU 200 (i.e., a driving assistance control device). The driving assistance ECU 200 includes the lane departure warning control device 201 of any of the above embodiments, and thus has all the above-mentioned beneficial effects, which will not be repeated here.

[0168] The vehicle also includes a signal input system, a signal output system, and an execution system.

[0169] like Figure 7 As shown, the signal input system is configured to input signals to the lane departure warning control device 201 of the driver assistance system. The signal output system is configured to receive the output signals from the lane departure warning control device 201 and control the execution system to perform corresponding operations based on the output signals.

[0170] Among them, such as Figure 7 As shown, the signal input system may include: a turn signal switch 101 for detecting driver turn signal operation, an accelerator pedal sensor 102 for detecting driver accelerator operation, a brake pedal sensor 103 for detecting driver braking operation, a steering angle sensor 104 for detecting driver steering operation, a hand torque sensor 105 for detecting driver steering operation force, a vehicle speed sensor 106 for detecting vehicle speed, a yaw rate sensor 109 for detecting vehicle motion state, a longitudinal acceleration sensor 110, a lateral acceleration sensor 111, and wheel speed detection devices (including a right front wheel speed sensor 112, a left front wheel speed sensor 113, a right rear wheel speed sensor 114, and left and right wheel speed sensors 115) and a driving environment condition detection device 400 (such as a camera sensor 108 and a radar sensor 107 for detecting the surrounding environment).

[0171] The signal output system may include: engine ECU 301, brake ECU 302, steering ECU 303, and information display ECU 304.

[0172] The execution system may include: an engine 311, a braking system 312, a steering system 313, and an information display device 314. The engine ECU 301 controls the engine 311 based on output signals, primarily performing acceleration control. The braking ECU 302 controls the braking system 312, primarily performing deceleration control. The steering ECU 303 controls the steering system 313, primarily performing lateral steering control. The information display ECU 304 controls the information display device 314, primarily providing the driver with information on vehicle status and function control status.

[0173] In one specific embodiment, the wheel speed information is the average of the wheel speed information of the right front wheel and the right rear wheel. For example... Figure 9 As shown, the detection signals from the right front wheel speed sensor and the left front wheel speed sensor are summed and averaged by the calculation module 2023, then processed by the low-pass filter module 2021 and the high-pass filter module 2022 before being sent to the road surface smoothness level determination module 2024. The road surface smoothness level determination module 2024 determines the road surface smoothness level and then sends it to the lane departure warning control module 2011. The detection results from driving environment condition detection devices (such as camera sensors) are also sent to the lane departure warning control module 2011. The lane departure warning control module 2011 determines whether the vehicle is about to deviate from its lane based on lane line information; when it determines that the vehicle is about to deviate from its lane, it issues an alarm according to the lane departure warning intensity to remind the driver and prevent the vehicle from deviating from its lane.

[0174] The technical effects of the above embodiments can be understood by referring to the embodiments in the aforementioned lane departure warning method section, and will not be repeated here.

[0175] In summary, the lane departure warning method, lane departure warning control device, and lane departure warning system provided in this application can infer the current road surface smoothness based on wheel speed information, and then reasonably determine the lane departure warning intensity threshold according to different road surface conditions, thereby improving the identifiability of the lane departure warning function and enhancing the safety and user experience of the LDW function.

[0176] In any one or more of the exemplary embodiments described above, the described functionality may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software, the functionality may be stored as one or more instructions or code on or transmitted via a computer-readable medium and executed by a hardware-based processing unit. The computer-readable medium may comprise a computer-readable storage medium corresponding to a tangible medium such as a data storage medium, or a communication medium comprising any medium facilitating the transfer of a computer program from one place to another, for example, according to a communication protocol. In this manner, a computer-readable medium may generally correspond to a non-transitory tangible computer-readable storage medium or a communication medium such as a signal or carrier wave. The data storage medium may be any available medium accessible by one or more computers or one or more processors to retrieve instructions, code, and / or data structures for implementing the techniques described in this disclosure. Computer program products may comprise computer-readable media.

[0177] For example, and not as a limitation, such computer-readable storage media may include RAM, ROM, EEPROM, CD-ROM or other optical disc storage devices, magnetic disk storage devices or other magnetic storage devices, flash memory, or any other medium that can be used to store desired program code in the form of instructions or data structures and is accessible by a computer. Furthermore, any connection may also be referred to as a computer-readable medium. For example, if instructions are transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, radio, and microwave, then coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. However, it should be understood that computer-readable storage media and data storage media do not include connections, carrier waves, signals, or other transient media, but rather refer to non-transient tangible storage media. As used herein, disks and optical discs include compact optical discs (CDs), laser discs, optical discs, digital versatile discs (DVDs), floppy disks, or Blu-ray discs, where disks typically reproduce data magnetically, while optical discs use lasers to reproduce data optically. The above combinations should also be included within the scope of computer-readable media.

[0178] For example, instructions can be executed by one or more processors, such as one or more digital signal processors (DSPs), general-purpose microprocessors, application-specific integrated circuits (ASICs), field-programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuits. Therefore, the term "processor" as used herein can refer to any of the above-described structures or any other structures suitable for implementing the techniques described herein. Additionally, in some aspects, the functionality described herein can be provided within dedicated hardware and / or software modules configured for encoding and decoding, or incorporated into combined codecs. Furthermore, the techniques can be fully implemented in one or more circuit or logic elements.

[0179] The technical solutions of the embodiments of this disclosure can be implemented in a wide variety of devices or equipment, including wireless mobile phones, integrated circuits (ICs), or a set of ICs (e.g., chipsets). Various components, modules, or units are described in the embodiments of this disclosure to emphasize functional aspects of a device configured to perform the described techniques, but they do not necessarily need to be implemented through different hardware units. Rather, as described above, the various units can be combined in codec hardware units or provided by a collection of interoperable hardware units (including one or more processors as described above) combined with suitable software and / or firmware.

Claims

1. A lane departure warning method, characterized in that, include: Obtain wheel speed information and lane marking information; The degree of wheel vibration is determined based on the wheel speed information. The reference value for the road surface smoothness grade is determined based on the degree of vibration of the wheels; The road surface smoothness grade is determined based on the aforementioned road surface smoothness grade reference value; The lane departure alarm intensity is determined based on the road surface smoothness level. The lane departure warning function is executed based on the lane line information and the lane departure warning intensity. The step of determining the road surface smoothness grade based on the road surface smoothness grade reference value includes: Determine whether the road surface smoothness grade reference value has been continuously set for the specified duration; Based on the fact that the road surface smoothness grade reference value has been continuously set for a certain period of time, the road surface smoothness grade reference value is determined as the new road surface smoothness grade; Since the reference value for road surface smoothness grade has not been continuously set for a certain duration, the previously determined road surface smoothness grade will continue to be used.

2. The lane departure warning method according to claim 1, characterized in that, The process of determining the lane departure warning intensity based on the road surface smoothness level includes: The lane departure alarm intensity adjustment information is determined based on the road surface smoothness level. The lane departure warning intensity is determined based on the lane departure warning intensity adjustment information.

3. The lane departure warning method according to claim 2, characterized in that, The lane departure warning intensity adjustment information is: the updated value of the lane departure warning intensity; determining the lane departure warning intensity based on the lane departure warning intensity adjustment information includes: determining the updated value of the lane departure warning intensity as the lane departure warning intensity; or The lane departure warning intensity adjustment information is: lane departure warning intensity coefficient; determining the lane departure warning intensity based on the lane departure warning intensity adjustment information includes: multiplying the lane departure warning intensity benchmark value by the lane departure warning intensity coefficient to determine the lane departure warning intensity.

4. The lane departure warning method according to claim 2, characterized in that, The process of determining the lane departure alarm intensity adjustment information based on the road surface smoothness level includes: Based on the mapping relationship between the road surface smoothness level and the lane departure alarm intensity adjustment information, the lane departure alarm intensity adjustment information corresponding to the road surface smoothness level is determined.

5. The lane departure warning method according to claim 4, characterized in that, The road surface smoothness grade is negatively correlated with the road surface smoothness, the wheel vibration level is negatively correlated with the road surface smoothness, the lane departure alarm intensity is positively correlated with the road surface smoothness grade, and the lane departure alarm intensity adjustment information is positively correlated with the lane departure alarm intensity.

6. The lane departure warning method according to claim 5, characterized in that, The road surface smoothness grades include: Grade 1, Grade 2 and Grade 3, wherein Grade 1 road surface smoothness is better than Grade 2 road surface smoothness, and Grade 2 road surface smoothness is better than Grade 3 road surface smoothness. The lane departure warning intensity adjustment information includes: first adjustment information, second adjustment information, and third adjustment information, wherein the first adjustment information < the second adjustment information < the third adjustment information; In the mapping relationship between the road surface smoothness level and the lane departure alarm intensity adjustment information: When the road surface smoothness level is Level 1, the lane departure alarm intensity adjustment information is equal to the first adjustment information; When the road surface smoothness level is level two, the lane departure alarm intensity adjustment information is equal to the second adjustment information; When the road surface smoothness level is three, the lane departure alarm intensity adjustment information is equal to the third adjustment information.

7. The lane departure warning method according to any one of claims 1 to 6, characterized in that, Determining the degree of wheel vibration based on the wheel speed information includes: The wheel speed information is filtered. The degree of vibration of the wheel is determined based on the results of the filtering process.

8. The lane departure warning method according to any one of claims 1 to 6, wherein the wheel speed information is the average value of the wheel speed information of multiple wheels of the vehicle.

9. A lane departure warning control device, characterized in that, It includes a processor and a memory storing a computer program, wherein the processor executes the computer program to implement the steps of the lane departure warning method as described in any one of claims 1 to 8.

10. A lane departure warning system, characterized in that, include: A driving environment condition detection device is configured to detect driving environment conditions. A wheel speed detection device is configured to detect wheel speed. and The lane departure warning control device is configured to obtain lane line information and wheel speed information based on the detection results of the driving environment condition detection device and the wheel speed detection device, and to execute the lane departure warning function based on the lane line information and wheel speed information. The lane departure alarm control device includes: a road surface smoothness level determination module and a lane departure alarm control module; The road surface smoothness grade determination module is configured to determine the road surface smoothness grade based on the wheel speed information. The lane departure alarm control module is configured to determine the lane departure alarm intensity based on the road surface smoothness level, and to execute the lane departure alarm function based on the lane line information and the lane departure alarm intensity. The road surface smoothness grade determination module includes: a first determination module and a second determination module; the lane departure alarm control module includes: a third determination module and a control module; The first determining module is configured to determine the degree of wheel vibration based on wheel speed information; The second determining module is configured to determine the road surface smoothness grade based on the vibration level of the wheel; the second determining module includes a first determining unit and a second determining unit, wherein the first determining unit is configured to determine a road surface smoothness grade reference value based on the vibration level of the wheel; and the second determining unit is configured to determine the road surface smoothness grade based on the road surface smoothness grade reference value. The third determining module is configured to determine the lane departure alarm intensity based on the road surface smoothness level; The control module is configured to execute the lane departure alarm function based on lane line information and lane departure alarm intensity. The second determining unit is configured to: determine whether the road surface smoothness grade reference value has been continuously set for a duration; determine the road surface smoothness grade reference value as a new road surface smoothness grade based on the fact that the road surface smoothness grade reference value has been continuously set for a duration; and continue to use the previously determined road surface smoothness grade based on the fact that the road surface smoothness grade reference value has not been continuously set for a duration.

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