Maintenance judgment method and device and vehicle

Abstract

The invention provides an overhaul judgment method and device, a vehicle, electronic equipment and a computer program product, and relates to the technical field of driving safety, the method can be based on driving data of the vehicle, and the driving data is obtained by counting braking behaviors of the vehicle in the over-speed-limit driving process; and determining whether a driver of the vehicle has a fierce driving behavior, if the driver of the vehicle has the fierce driving behavior, recording target driving data, and determining whether brake equipment of the vehicle needs to be overhauled according to the target driving data. Through the arrangement, whether the braking equipment of the vehicle needs to be overhauled or not can be determined according to the intense driving condition of a driver, then the braking failure risk of the braking equipment is reduced, and driving safety is improved.

Description

Technical Field

[0001] The present application relates to the technical field of driving safety, and particularly relates to an overhaul determination method, device and vehicle. Background Art

[0002] Once a vehicle's braking equipment fails, for example, there is a phenomenon of brake disc crack or crack penetration, it will affect the braking performance of the vehicle and increase the risk of braking failure. Therefore, how to detect in advance the risk of braking failure of the braking equipment and determine whether the braking equipment needs to be overhauled has become a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0003] In view of this, the present application provides an overhaul determination method, device, vehicle, electronic device and computer program product, and this method can detect in advance the risk of braking failure of the braking equipment and determine whether the braking equipment needs to be overhauled.

[0004] The technical solutions proposed by the present application are specifically as follows:

[0005] In a first aspect, an embodiment of the present application provides an overhaul determination method, including:

[0006] Based on the driving data of the vehicle, determine whether the driver of the vehicle has aggressive driving behavior, where the driving data is obtained by statistically analyzing the braking behavior of the vehicle during overspeed driving;

[0007] If the driver of the vehicle has aggressive driving behavior, record the target driving data;

[0008] According to the target driving data, determine whether the braking equipment of the vehicle needs to be overhauled.

[0009] Further, in the above method, the determining whether the driver of the vehicle has aggressive driving behavior based on the driving data of the vehicle includes:

[0010] When it is detected that the driving speed is greater than the set speed, determine that the vehicle is overspeed driving;

[0011] Detect the number of times the vehicle brakes during the overspeed driving;

[0012] If the number of times the vehicle brakes during the overspeed driving reaches the set number of times, determine that the driver of the vehicle has aggressive driving behavior.

[0013] It can be seen that, due to frequent speeding and braking operations during aggressive driving, by judging the scenario of the vehicle driving over the speed limit and further detecting the number of braking operations in this scenario, the speeding and braking operations are data-associated to avoid misjudgment caused by accidental speeding or braking operations, and improve the accuracy of aggressive driving behavior judgment.

[0014] Further, in the above-mentioned method, if the number of braking operations of the vehicle during the process of driving over the speed limit reaches a set number, it is determined that the driver of the vehicle has aggressive driving behavior, including:

[0015] Obtain the detection period set for the vehicle for the aggressive driving behavior;

[0016] Within the detection period, if the number of braking operations of the vehicle during the process of driving over the speed limit reaches the set number, record that the driver of the vehicle has dangerous driving behavior;

[0017] Determine that the driver of the vehicle has aggressive driving behavior by counting the number of times the driver of the vehicle has dangerous driving behavior during the process of speeding.

[0018] It can be seen that considering that aggressive driving may occur intermittently, that is, aggressive driving within a certain period of time and normal driving within a certain period of time. At this time, in order to improve the certainty of aggressive driving behavior judgment; by configuring the detection period, avoid counting the braking behavior during normal driving into aggressive driving; further implement the statistical process of aggressive driving behavior into the statistical process of fine-grained dangerous driving behavior, and combine the recording process of the detection period to avoid abnormal recording during normal driving and improve the accuracy of aggressive driving behavior judgment.

[0019] Further, in the above-mentioned method, the method further includes:

[0020] Obtain the set speed of the corresponding driving section of the vehicle;

[0021] Compare the driving speed of the vehicle with the set speed to determine the overspeed ratio information;

[0022] Configure the set number based on the overspeed ratio information.

[0023] It can be seen that since the essence of aggressive driving is the braking loss brought by the braking behavior during speeding, the greater the speed in this process, the greater the kinetic energy of the vehicle, and the greater the kinetic energy that the braking behavior needs to offset, and thus the greater the braking loss; therefore, for the judgment process of dangerous driving behavior, combining the overspeed ratio information corresponding to the overspeed process can better reflect the representativeness of the set number for braking loss and improve the accuracy of dangerous driving behavior recording.

[0024] Further, in the method described above, the method further includes:

[0025] Controlling the vehicle to perform environmental perception to obtain road condition information of the vehicle's location;

[0026] Adjusting at least one of the set speed and the set number according to the road condition information.

[0027] It can be seen that since the potential safety hazards caused by the vehicle speeding on roads with different road conditions are different. For example, the more rugged the road surface, the greater the loss during braking at the same speed. Therefore, by enabling the vehicle to perform environmental perception to determine road condition information, dynamically adjusting the set speed of the road section, and dynamically adjusting the set number of brakings, the set speed and the set number are dynamically configured from the perspective of vehicle loss, improving the effectiveness of the set speed and the set number, and improving the accuracy of the statistics of aggressive driving behaviors.

[0028] Further, in the method described above, it further includes:

[0029] If the braking device of the vehicle needs to be repaired, determining the available duration of the braking device;

[0030] Determining the repair deadline of the braking device according to the available duration, and outputting a repair reminder message including the repair deadline.

[0031] It can be seen that since the braking device is crucial for the safe driving of the vehicle and is a necessary device for vehicle driving, by judging the available duration of the braking device and outputting a repair reminder message including the repair deadline, the user can intuitively know the status of the vehicle's braking device, avoid driving when the braking device is abnormal, and improve the safety of vehicle driving.

[0032] Further, in the method described above, the step of if the braking device of the vehicle needs to be repaired, determining the available duration of the braking device includes:

[0033] Inputting the target driving data into a pre-trained available duration prediction model, so that the available duration prediction model outputs a prediction result according to the target driving data; the prediction result is the available duration of the braking device;

[0034] The available duration prediction model is trained with the driving data of sample vehicles under different driving road conditions as training samples and with the goal of predicting the available duration of the braking devices of the sample vehicles.

[0035] It can be seen that since the available duration of the braking device is related to the safe driving of the vehicle, by accurately predicting the available duration through the available duration prediction model and using the driving data of the sample vehicle under different driving road conditions as training samples, the prediction process of the available duration under different road conditions becomes more accurate.

[0036] Further, in the above method, the determining the overhaul deadline of the braking device according to the available duration includes:

[0037] If the available duration is greater than or equal to the remaining duration of the current maintenance cycle, determine the overhaul deadline as the end time of the current maintenance cycle; if the available duration is less than the remaining duration of the current maintenance cycle, determine the overhaul deadline as the end time of the available duration.

[0038] It can be seen that since the state of the braking device can be restored through maintenance, the remaining duration of the maintenance cycle can be monitored in real time, so as to determine the corresponding overhaul deadline and improve the timeliness of the braking device maintenance.

[0039] In a second aspect, an embodiment of the present application provides an overhaul determination device, including:

[0040] A first determination unit, configured to determine whether there is an intense driving behavior of the driver of the vehicle based on the driving data of the vehicle, where the driving data is obtained by statistically analyzing the braking behavior of the vehicle during overspeed driving;

[0041] A recording unit, configured to record the target driving data if there is an intense driving behavior of the driver of the vehicle;

[0042] A second determination unit, configured to determine whether the braking device of the vehicle needs to be overhauled according to the target driving data.

[0043] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0044] A memory and a processor; wherein, the memory is used to store a program; the processor is configured to implement the method described in any one of the above by running the program in the memory.

[0045] In a fourth aspect, an embodiment of the present application provides a vehicle, including:

[0046] An overhaul judgment device, where the overhaul judgment device is configured to be able to implement the method described in any one of the above.

[0047] Fifth aspect, an embodiment of the present application provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the method described in any one of the above is implemented. Optionally, the computer program can be stored in a readable storage medium or cloud of a computer device; the processor of the computer device reads the computer program from the readable storage medium or cloud.

[0048] The overhaul determination method proposed in this application can determine whether there is aggressive driving behavior of the vehicle driver based on the driving data of the vehicle, and the driving data is obtained by statistically analyzing the braking behavior of the vehicle during overspeed driving; if there is aggressive driving behavior of the vehicle driver, the target driving data is recorded; then, based on the target driving data, it is determined whether the braking device of the vehicle needs to be overhauled. With this setting, since aggressive driving refers to overly radical vehicle control in driving behavior, which is a behavior that increases the accident risk or vehicle wear, and the braking behavior of the vehicle during overspeed driving is statistically determined for vehicle wear, this is because the kinetic energy of the vehicle is relatively large during overspeed, and the corresponding braking behavior will cause greater wear to the braking device. Therefore, through the simulation process of the wear of the braking device caused by aggressive driving, it can be determined whether the braking device of the vehicle needs to be overhauled, thereby reducing the risk of braking failure of the braking device and reducing the accident risk brought by aggressive driving, and improving driving safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0050] Figure 1 is a flowchart of an overhaul determination method provided by an embodiment of the present application.

[0051] Figure 2 is a flowchart of detecting the aggressive driving behavior of the driver provided by an embodiment of the present application.

[0052] Figure 3 is a structural diagram of an overhaul determination method device provided by an embodiment of the present application.

[0053] Figure 4 is a structural diagram of an electronic device provided by an embodiment of the present application.

[0054] Figure 5 is a structural diagram of a vehicle provided by an embodiment of the present application. Detailed implementation mode

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts shall fall within the protection scope of the present application.

[0056] The braking equipment of a vehicle is one of the key components to ensure driving safety, and the stability and reliability of its performance are directly related to the safety of drivers, passengers, and other pedestrians and vehicles on the road. Once a failure occurs in the braking equipment of a vehicle, such as the appearance of cracks or through cracks in the brake disc, it will affect the braking performance of the vehicle, increase the risk of braking failure, and threaten the safety of drivers, passengers, and other pedestrians and vehicles on the road.

[0057] Therefore, how to detect the risk of braking failure of the braking equipment in advance and accurately determine whether it needs to be repaired has become an important technical problem that needs to be solved urgently by those skilled in the art.

[0058] Generally, the maintenance configuration for the braking equipment is carried out during the vehicle maintenance process, that is, maintenance reminders are given based on fixed dates or mileage; however, due to different driving habits of users during the driving process, the impacts on the vehicle caused by different driving habits are also different; at this time, the process of giving maintenance reminders based on fixed dates or mileage may not match the actual vehicle condition, resulting in untimely vehicle maintenance reminders, which may cause abnormalities in the braking equipment, affect the braking performance of the vehicle, and increase the risk of braking failure.

[0059] Based on this, the present application proposes an overhaul determination method, device, vehicle, electronic device, and computer program product. This technical solution determines whether the braking equipment of the vehicle needs to be overhauled according to the situation of the driver's intense driving, achieving the effect of reducing the risk of braking failure of the braking equipment and improving driving safety.

[0060] An overhaul determination method is proposed in the embodiments of the present application. This method can be executed by an electronic device, which can be any device with data and instruction processing functions, such as various types of user terminals such as laptop computers, tablet computers, desktop computers, in-vehicle devices, mobile devices (such as mobile phones, personal digital assistants, dedicated messaging devices), or any combination of any two or more of these electronic devices, or a server.

[0061] See Figure 1 As shown, the method includes:

[0062] S101. Based on the driving data of the vehicle, determine whether the driver of the vehicle has aggressive driving behavior; if the driver of the vehicle has aggressive driving behavior, execute S102; if the driver of the vehicle does not have aggressive driving behavior, repeat S101.

[0063] The above-mentioned vehicle driving data refers to data that can characterize the vehicle's driving status. These data are collected in real time through vehicle sensors, electronic control units (ECUs) and software programs, and stored in vehicle computers or cloud servers. More specifically, the vehicle's driving data includes the vehicle's speed, braking status and mileage.

[0064] The above-mentioned violent driving behavior refers to the behavior performed by the driver of the vehicle during driving that may affect the service life of the brake equipment and damage the brake equipment. The brake equipment refers to the equipment in the vehicle that executes deceleration or parking commands, including brake discs, etc. For example, the driver's frequent braking behavior at high speed will cause the brake disc to be damaged because it cannot dissipate heat in a short time.

[0065] It is understandable that, considering that aggressive driving behavior may affect the service life of the braking equipment and damage the braking equipment, the impact of aggressive driving behavior on the braking equipment is that when the vehicle is speeding, the higher the speed, the greater the vehicle's kinetic energy, the greater the kinetic energy that needs to be offset during the braking process, and the greater the corresponding loss of the braking equipment. Therefore, the driving data used to determine whether there is an aggressive driving behavior can be obtained by statistically analyzing the vehicle's braking behavior during overspeeding.

[0066] Specifically, aggressive driving behavior may include sudden acceleration / deceleration, that is, slamming on the accelerator or brake in a short period of time, resulting in a sudden change in vehicle speed (such as accelerating from 0 to 100 km / h in a very short time or locking the tires during sudden braking). High-speed cornering or lane changing, that is, cornering at a speed significantly higher than the safe speed limit, or frequent and large-scale rapid lane changes (such as "snake driving"). Continuous high-speed driving, that is, keeping the engine in the red line area (close to the maximum speed) for a long time, which is often seen in manual transmission models for forced downshifting to overtake. Speeding, that is, significantly exceeding the prescribed speed on speed-limited roads (for example, speeding by more than 50% in urban areas). Frequently following vehicles too closely, that is, driving closely to the vehicle in front, resulting in repeated emergency braking (which can easily lead to rear-end collisions).

[0067] After the vehicle trip ends, the driving data of the trip can be retrieved from the on-vehicle computer or the cloud server, and then the driving data of the trip can be analyzed to determine whether there is any aggressive driving behavior by the driver during the trip, and further determine whether the braking equipment of the vehicle needs to be repaired. It should be noted that the amount of driving data directly retrieved from the on-vehicle computer or the cloud server is generally large. To reduce the amount of data and improve the analysis speed of aggressive driving behavior, data extraction can be performed every first set time period, and the extracted data is composed of the driving data of the vehicle. Among them, the first set time period can be set according to the actual situation, such as set to 1S or 10S, etc., and this embodiment does not make a limitation.

[0068] In addition, during the driving process of the vehicle, the driving data of the vehicle can be retrieved from the on-vehicle computer or the cloud server in real time, and the driving data can be analyzed in real time to determine whether there is any aggressive driving behavior by the driver, and further determine whether the braking equipment of the vehicle needs to be repaired. In some embodiments, the driving data of the vehicle can be retrieved from the on-vehicle computer or the cloud server every second set time period, and the retrieved data is composed of the driving data of the vehicle. Among them, the second set time period can also be set according to the actual situation, such as set to 1S or 10S, etc., and this embodiment does not make a limitation.

[0069] It should also be noted that the reporting period of the in-vehicle braking signal is 10 milliseconds, while the acquisition period of the cloud periodic data is 1 second. Therefore, there is a probability of data loss. To ensure the accuracy of the algorithm, the acquisition scheme of the cloud data can be modified to report once when the signal transmission changes.

[0070] Furthermore, based on the driving data of the vehicle, it can be determined whether there is any aggressive driving behavior by the driver of the vehicle. Specifically, if it is determined according to the driving data of the vehicle that a brake signal is frequently received when the speed of the vehicle is greater than the set speed, it is determined that the driver has the behavior of frequently braking when driving at a high speed, then it can be further determined that the driver of the vehicle has aggressive driving behavior. Among them, the set speed can be set according to the actual situation, such as set to 120 km / h, and this embodiment does not make a limitation.

[0071] If the driver of the vehicle has aggressive driving behavior, then S102 can be executed to record the target driving data, so as to determine whether the braking equipment of the vehicle needs to be repaired according to the target driving data; if the driver of the vehicle does not have aggressive driving behavior, then S101 can be repeatedly executed to continue monitoring the aggressive driving behavior.

[0072] S102. Record the target driving data.

[0073] The above-mentioned target driving data includes at least one of the occurrence time of aggressive driving behavior and the vehicle mileage data when the aggressive driving behavior occurs. The occurrence time of the aggressive driving behavior refers to the specific time corresponding to the occurrence of the aggressive driving behavior; the vehicle mileage data when the aggressive driving behavior occurs refers to the mileage data of the vehicle when the aggressive driving behavior occurs. This mileage data can be the mileage data of the vehicle after the last brake equipment overhaul, and this embodiment does not make a limitation.

[0074] In some embodiments, the target driving data may further include weather conditions, road surface conditions, etc. when the aggressive driving behavior occurs, and this embodiment does not make a limitation. Among them, the above-mentioned weather conditions include different weather conditions such as rain, snow, fog, etc., and the road surface conditions include different road surface conditions such as dry, slippery, icy, etc.

[0075] In addition, it should be noted that the target driving data includes the target driving data corresponding to each aggressive driving behavior of the vehicle after the last brake equipment overhaul.

[0076] S103. Determine whether the brake equipment of the vehicle needs to be overhauled according to the target driving data.

[0077] In this embodiment, it is possible to further determine whether the brake equipment of the vehicle needs to be overhauled according to the target driving data.

[0078] Specifically, a brake equipment detection model can be trained in advance, and the target driving data and the corresponding driving road conditions are input into the pre-trained brake equipment detection model, so that the brake equipment detection model outputs a prediction result according to the target driving data. The prediction result includes whether the brake equipment of the vehicle needs to be overhauled.

[0079] Among them, the brake equipment detection model is trained with the driving data of sample vehicles under different driving road conditions as training samples, with the goal of predicting whether the brake equipment of the sample vehicles needs to be overhauled.

[0080] Specifically, the driving data of a large number of sample vehicles can be obtained. The sample vehicles are vehicles using the same brake equipment as the above-mentioned vehicle, and the sample vehicles have not been repaired for the brake equipment. According to the description of the above embodiment, it is determined whether the drivers of the sample vehicles have performed aggressive driving behaviors based on the driving data of the sample vehicles, and the corresponding target driving data when the aggressive driving behaviors occur is extracted as training samples. Then, relevant experts or staff evaluate the brake equipment of the sample vehicles to determine whether the brake equipment needs to be overhauled, and the evaluation result is used as a training label.

[0081] During the training process, the training samples are input into the braking device detection model, and the prediction results output by the braking device detection model are obtained. By comparing the prediction results of the braking device detection model with the training labels, the loss value of the braking device detection model is determined. With the goal of reducing the loss of the braking device detection model, the parameters of the braking device detection model are adjusted until the braking device detection model meets the training requirements. The above-mentioned braking device detection model can be trained based on any neural network model or based on a pre-trained model. For example, it can be a pre-trained large model similar to ChatGPT.

[0082] The target driving data is input into the trained braking device detection model to enable the braking device detection model to predict whether the braking device of the vehicle needs to be repaired. If repair is required, a reminder message can be output, such as prompt words or audio like "There is a safety risk with the braking device, please repair it in time", and the fault light of the braking device can also be turned on. This embodiment does not make any limitations.

[0083] In the above embodiment, based on the driving data of the vehicle, it can be determined whether the driver of the vehicle has aggressive driving behavior. The driving data is obtained by statistically analyzing the braking behavior of the vehicle during overspeed driving. If the driver of the vehicle has aggressive driving behavior, the target driving data is recorded. Then, based on the target driving data, it is determined whether the braking device of the vehicle needs to be repaired. With such a setting, since aggressive driving refers to overly radical vehicle control in driving behavior, which is a behavior that increases the accident risk or vehicle wear, and the vehicle wear is determined by statistically analyzing the braking behavior of the vehicle during overspeed driving. This is because the kinetic energy of the vehicle is relatively large during overspeed, and the corresponding braking behavior will cause greater wear to the braking device. Therefore, through the simulation process of the wear of the braking device caused by aggressive driving, it can be determined whether the braking device of the vehicle needs to be repaired, thereby reducing the risk of braking failure of the braking device and reducing the accident risk brought by aggressive driving, and improving driving safety.

[0084] As an alternative implementation, as Figure 2 shown, in another embodiment of the present application, it is disclosed that the driving data in the above embodiment includes the driving speed and the number of braking times of the vehicle. The steps in the above embodiment are based on the driving data of the vehicle to determine whether the driver of the vehicle has aggressive driving behavior, which may specifically include the following steps:

[0085] S201. When it is detected that the driving speed is greater than the set speed, it is determined that the vehicle is driving overspeed.

[0086] The above set speed can be set according to the actual situation. For example, it can be set to 120 km / h. This embodiment does not make any limitations.

[0087] In an embodiment of the present application, when it is detected that the driving speed of the vehicle is greater than the set speed, it indicates that the driving speed of the vehicle is relatively fast and the vehicle is in a state of exceeding the speed limit. Frequent braking in such a driving state may damage the braking equipment.

[0088] In a possible scenario, considering that the process of aggressive driving may occur intermittently, that is, aggressive driving within a certain period of time and normal driving within a certain period of time. At this time, in order to avoid counting the braking times during normal driving into aggressive driving, the determination of aggressive driving can be based on the detection period. Among them, for the driving behavior within each detection period, fine-grained dangerous driving behaviors are used for identification. That is, first obtain the detection period set by the vehicle for aggressive driving behaviors; then within the detection period, if the number of brakings during the vehicle's overspeed driving reaches the set number, it is recorded that the driver of the vehicle has dangerous driving behavior; and by counting the number of times the driver of the vehicle has dangerous driving behavior during overspeed driving, it is determined that the driver of the vehicle has aggressive driving behavior.

[0089] It can be understood that the dangerous driving behavior is a judgment of the driving behavior within a single detection period and is a risk prediction parameter; while the aggressive driving behavior is a judgment of the overall driving process, which is determined by the number of times of dangerous driving behavior, that is, the behavior judgment obtained through the accumulation of risk prediction parameters, realizing the process of judging aggressive driving behavior from a fine-grained perspective and improving the accuracy of behavior judgment.

[0090] Exemplarily, the detection period is 1 hour, the overspeed is 120 km / h, and the set number of brakings is 1. Then when it is detected that the vehicle speed exceeds 120 km / h, the process of judging dangerous driving behavior based on the detection period (1 hour) starts. If the speed during braking within this period exceeds 120 km / h, it reaches the set number and is counted as 1 dangerous driving. If during the subsequent driving of the vehicle, the number of times of dangerous driving behavior reaches 10, it is determined that the driver of the vehicle has aggressive driving behavior.

[0091] It can be seen that by configuring the detection period, the braking behavior during normal driving is avoided from being counted into aggressive driving; further, the statistical process of aggressive driving behavior is implemented into the statistical process of fine-grained dangerous driving behavior, combined with the recording process of the detection period, avoiding abnormal records during normal driving and improving the accuracy of judging aggressive driving behavior.

[0092] In another possible scenario, since the essence of aggressive driving is the braking loss caused by the braking behavior during speeding, the greater the speed during this process, the greater the kinetic energy of the vehicle, and the greater the kinetic energy that the braking behavior needs to offset, and thus the greater the braking loss. Therefore, for the set number of times corresponding to braking, it can be dynamically set according to the degree of speeding. First, obtain the set speed of the vehicle for the corresponding driving section; then compare the driving speed of the vehicle with the set speed to determine the speeding ratio information; and configure the set number of times based on the speeding ratio information.

[0093] Exemplarily, in the first scenario, the set speed of the vehicle for the corresponding driving section is 100 km / h, and the driving speed of the vehicle is 120 km / h. At this time, the speeding ratio information is (120 - 100) / 100 = 20%, so the set number of times can be set to 5 times; in contrast, in the second scenario, the set speed of the vehicle for the corresponding driving section is 100 km / h, and the driving speed of the vehicle is 150 km / h. At this time, the speeding ratio information is (150 - 100) / 100 = 50%, so the set number of times can be set to 1 time; that is, in the second scenario, the speeding ratio is 50%, and the braking process is larger than 20% in the first scenario, that is, the equipment loss caused by a single braking process is larger than that in the first scenario. Therefore, the set number of times is set less to balance the numerical values of the judgment of dangerous driving behaviors in different speeding scenarios.

[0094] It can be seen that for the judgment process of dangerous driving behaviors, by combining the speeding ratio information corresponding to the speeding process, the representativeness of the set number of times for braking loss can be better reflected, and the accuracy of the record of dangerous driving behaviors can be improved.

[0095] Furthermore, considering that during the driving process of the vehicle on different road conditions, different road conditions will have different impacts on the vehicle due to the speeding or braking process. Therefore, the set speed and the set number of times can be configured specifically in combination with environmental perception, that is, control the vehicle to perform environmental perception to obtain the road condition information of the vehicle; and adjust at least one of the set speed and the set number of times according to the road condition information.

[0096] Specifically, for the judgment process of a vehicle exceeding the speed limit in combination with road conditions, it can be dynamically set in combination with the road conditions of the vehicle. For example, the speed limit on urban roads (congested / uncongested) can be 40 - 60 km / h (specifically according to road section signs). For highways, the speed limit can be 100 - 120 km / h (the overtaking lane may have a higher speed, but it must comply with regulations). For mountainous / curved road sections, the speed limit for curves is usually 30 - 50 km / h (according to the curve radius and warning signs). For rainy / snowy / slippery road surfaces, the recommended speed is reduced to 50% - 70% of the dry road surface speed (for example, if the dry speed limit is 60 km / h, the speed limit on rainy days is 30 - 40 km / h). For school / residential areas, the speed limit can be 20 - 30 km / h; specific road condition scenarios depend on the actual road configuration.

[0097] Furthermore, for the judgment of driving road conditions, it can be carried out through data from a variety of sensors. For example, sensing devices such as cameras, radars, and lidar are used to detect the surrounding environment, such as road type, traffic signs, obstacles, etc. In addition, GPS and map data can provide location information to help the vehicle know the current road type, such as highways, urban roads, etc. Weather sensors, such as rain sensors or temperature sensors, can detect weather conditions, such as rainy or snowy weather, so as to judge whether the road condition is slippery. In addition, the vehicle can process the above data. For example, a camera can identify road signs and lane lines to judge whether it is driving on a highway or entering a school area. Radars and lidar can detect the distance and speed of surrounding vehicles, as well as obstacles on the road. GPS combined with a high-precision map can provide information such as the curvature and slope of the road to help the vehicle understand the current road condition structure.

[0098] In addition, vehicle dynamics data can also be used for road condition judgment, such as wheel speed, acceleration, steering angle, etc., to judge whether the vehicle is skidding or encountering other handling problems, so as to infer whether the road condition is complex, such as a slippery road surface or a rough road. Or road condition judgment can be carried out through the vehicle's communication system, such as V2X (vehicle-to-everything), which can receive information from other vehicles or infrastructure, such as an accident or construction area ahead, etc., so as to ensure the accuracy of road condition judgment.

[0099] Furthermore, for the judgment process of a vehicle exceeding the speed limit, it can also be carried out in combination with the vehicle's environmental perception, that is, comprehensively judged in combination with the speeds of the vehicles around the vehicle, so as to avoid the inability to judge aggressive driving in scenarios without road signs or speed limits.

[0100] Specifically, for the process of judging vehicle over - speed driving by combining vehicle environmental perception, the set speed is determined based on the average speed of surrounding vehicles in the vehicle's environment. That is, the vehicle's radar sensing device is used to measure the vehicle speeds of surrounding vehicles, so as to obtain the average speed of surrounding vehicles, and the over - speed standard is set based on the average speed. For example, if the speeds of surrounding vehicles are 50 km / h, 60 km / h, and 70 km / h, the set speed is then (50 + 60 + 70) / 3 * 1.5 = 90 km / h. That is, when the vehicle's driving speed is greater than 90 km / h, it is determined that the vehicle is over - speed driving.

[0101] Among them, for the process of the vehicle perceiving the speeds of surrounding vehicles, it can be executed by multiple sensors. For example, a radar uses the Doppler effect to detect the relative speed of a target by transmitting radio waves and analyzing the frequency change of the reflected signal; a camera combines computer vision algorithms to track the displacement of adjacent vehicles in consecutive images and estimates the actual speed in combination with the time difference; a lidar emits laser pulses and measures the reflection time difference to accurately calculate the rate of distance change; in addition, an in - vehicle communication system (such as V2V) can directly receive the real - time speed data sent by surrounding vehicles through a wireless network. These pieces of information are integrated by data fusion technology to eliminate the errors of a single sensor, and finally generate accurate speeds of surrounding vehicles in the in - vehicle system.

[0102] It can be seen that by combining vehicle environmental perception to judge vehicle over - speed driving, it is possible to avoid losing judgment data on aggressive driving in unmarked sections and improve the accuracy of aggressive driving judgment.

[0103] S202. Detect the number of times the vehicle brakes during over - speed driving.

[0104] During this over - speed driving process, detect the number of times the driver brakes. It should be noted that if the vehicle's driving speed is greater than the set speed, it means the vehicle is over - speed driving, and the number of times the vehicle brakes during this over - speed driving process can be continuously detected; if the vehicle's driving speed drops below the set speed, it means the over - speed driving of the vehicle ends, and the detection of the number of braking times is no longer carried out. When the vehicle's driving speed is greater than the set speed next time, it means the vehicle enters a new round of over - speed driving, and it is necessary to start detecting the number of times the vehicle brakes during this over - speed driving process again.

[0105] S203. Detect whether the number of braking times reaches the set number; if the number of braking times reaches the set number, it is determined that the driver of the vehicle has aggressive driving behavior; if the number of braking times does not reach the set number, re - execute S201.

[0106] If the number of times the vehicle brakes during this over - speed driving process reaches the set number, it can be determined that the driver of the vehicle has aggressive driving behavior.

[0107] If the number of times the vehicle brakes during this overspeed driving does not reach the set number of times, it means that the vehicle driver does not have aggressive driving behavior, and S201 can be re-executed to monitor the vehicle's overspeed driving behavior.

[0108] In a possible scenario, the process of determining whether the number of braking times reaches the set number of times can be based on the road conditions where the vehicle is located. For example, in a congested section, the number of normal braking times of the vehicle is relatively large. Therefore, in order to avoid misjudgment of aggressive driving behavior in such scenarios, a dynamic configuration process of the set number of times is required. For example, for a congested section, the set number of times is 20 times, and for a green wave section, the set number of times is 10 times, so as to achieve differential braking judgment and improve the adaptability of the braking times data in different scenarios.

[0109] Specifically, for the configuration process of the set number of braking times based on the driving road conditions, the process of environmental perception can refer to the description in S201 above and will not be elaborated here. For the configuration process of the set number of times, since the flatness or slipperiness of the road conditions will affect the braking process. For example, the more rugged the road surface, the more longitudinal jitter will be brought during braking, which will cause additional equipment wear to the braking equipment. At this time, a smaller number of braking times should be configured to balance the vehicle wear corresponding to aggressive driving behavior under different road conditions. For example, the preset set number of braking times is 5 times, and the environmental perception shows that the road condition information is a gravel section. At this time, the ground is not flat, and the equipment wear caused by the braking process is larger than that on a flat section. Therefore, the set number of braking times can be adjusted to 3 times, that is, less than the preset set number of braking times, so as to balance the vehicle wear corresponding to aggressive driving behavior under different road conditions and improve the accuracy of subsequent vehicle maintenance reminders.

[0110] It can be seen that since the potential safety hazards caused by the vehicle overspeed driving on roads with different road conditions are different. For example, the more rugged the road surface, the greater the wear caused by braking at the same speed. Therefore, by enabling the vehicle to perform environmental perception to determine the road condition information, dynamically adjusting the set speed of the section, and dynamically adjusting the set number of braking times, the set speed and the set number of times are dynamically configured from the perspective of vehicle wear, improving the effectiveness of the set speed and the set number of times, and improving the accuracy of aggressive driving behavior statistics.

[0111] In the above embodiments, since speeding and braking operations often occur during aggressive driving, by judging the scenario of the vehicle exceeding the speed limit and further detecting the number of braking operations in this scenario, the speeding and braking operations are data-associated to avoid misjudgment caused by occasional speeding or braking operations, and improve the accuracy of aggressive driving behavior judgment. That is, by analyzing the driving speed and the number of braking operations of the vehicle, it is quickly determined whether the driver of the vehicle has aggressive driving behavior, and then whether the braking device of the vehicle needs to be repaired is determined according to the situation of the driver's aggressive driving, reducing the risk of braking failure of the braking device.

[0112] As an alternative implementation, since the braking device is related to the safe driving of the vehicle and is a necessary device for vehicle driving, considering that aggressive driving will cause wear and tear on the braking device, it is necessary to detect the available duration of the braking device. Therefore, in another embodiment of the present application, the method of the above embodiment specifically may include the following steps:

[0113] If the braking device of the vehicle needs to be repaired, determine the available duration of the braking device; determine the repair deadline of the braking device according to the available duration, and output a repair reminder message including the repair deadline.

[0114] If it is determined that the braking device of the vehicle needs to be repaired, the available duration of the braking device can be determined first, so as to calculate the repair deadline of the braking device according to the available duration of the braking device, and output a repair reminder message including the repair deadline, thereby reminding the vehicle owner to repair the braking device before the repair deadline. For example: when it is determined that the braking device of the vehicle needs to be repaired, the available duration of the braking device is determined to be 10 days. Further, the repair deadline of the braking device (if the current date is January 1st, the repair deadline is January 10th) is calculated according to the available duration of the braking device (10 days), and a repair reminder message including the repair deadline is output. The repair reminder message can be prompted through the in-vehicle terminal or the user terminal associated with the vehicle.

[0115] In some embodiments, the repair reminder message may include "There is a risk of failure of the braking device. Please repair it before X year X month X day" or "Please repair the braking device before X year X month X day", etc. This embodiment does not make any limitations.

[0116] The repair reminder message can be displayed on the central control screen of the vehicle or sent to the terminal devices such as the vehicle owner's mobile phone and watch through the wireless network. This embodiment also does not make any limitations.

[0117] With such a setting, by judging the available duration of the braking device and outputting a maintenance reminder message including the maintenance deadline, the user can intuitively know the status of the braking device of the vehicle, avoid driving when the braking device is abnormal, and improve the driving safety of the vehicle; moreover, the vehicle owner can choose a suitable time to maintain the braking device before the maintenance deadline, so that the vehicle owner can freely arrange the maintenance time on the basis of ensuring driving safety and improve the convenience of using the vehicle by the vehicle owner.

[0118] In some embodiments, the available duration prediction model can be trained in advance, and the target driving data is input into the pre-trained available duration prediction model, so that the available duration prediction model outputs a prediction result according to the target driving data; the prediction result is the available duration of the braking device.

[0119] Among them, the available duration prediction model is trained with the driving data of sample vehicles under different driving road conditions as training samples and with the goal of predicting the available duration of the braking devices of the sample vehicles.

[0120] Specifically, the driving data of a large number of sample vehicles can be obtained, where the sample vehicles are vehicles using the same braking device as the above-mentioned vehicle and have not been repaired for the braking device. According to the description of the above embodiments, based on the driving data of the sample vehicles, it is determined whether the drivers of the sample vehicles have performed aggressive driving behaviors, and the target driving data corresponding to the occurrence of aggressive driving behaviors is extracted as training samples. Then, relevant experts or staff evaluate the braking devices of the sample vehicles to determine the available duration of the braking devices, and use the available duration as training labels.

[0121] During the training process, the training samples are input into the available duration prediction model, and the prediction results output by the available duration prediction model are obtained. By comparing the prediction results of the available duration prediction model with the training labels, the loss value of the available duration prediction model is determined. With the goal of reducing the loss of the available duration prediction model, the parameters of the available duration prediction model are adjusted until the available duration prediction model meets the training requirements. The above-mentioned available duration prediction model can be trained based on any neural network model or based on a pre-trained model, such as a pre-trained large model similar to ChatGPT.

[0122] The target driving data is input into the pre-trained available duration prediction model, so that the available duration prediction model predicts the available duration of the vehicle.

[0123] In this way, based on the duration prediction model, the available duration of the vehicle can be predicted quickly and accurately, so as to determine the maintenance deadline of the braking device according to the available duration of the braking device.

[0124] In some embodiments, the deadline of the available duration is directly used as the maintenance deadline.

[0125] In some other embodiments, if the available duration is greater than or equal to the remaining duration of the current maintenance cycle, the overhaul cut-off time is determined to be the end time of the current maintenance cycle; if the available duration is less than the remaining duration of the current maintenance cycle, the overhaul cut-off time is determined to be the cut-off time of the available duration.

[0126] Specifically, since vehicles need to be maintained regularly, in order to save the time of vehicle owners and avoid the owners going to the repair point for vehicle repair and maintenance multiple times, when the available duration is greater than or equal to the remaining duration of the current maintenance cycle, the overhaul cut-off time is determined to be the end time of the current maintenance cycle, so that the vehicle owner can overhaul the braking equipment while performing vehicle maintenance, saving time.

[0127] For example, if the predicted available duration is one and a half years and the remaining duration of the current maintenance cycle is one year, the overhaul cut-off time can be determined to be one year later. The braking equipment can be overhauled while the vehicle owner performs vehicle maintenance, and the vehicle owner does not need to go to the repair point for vehicle repair and maintenance multiple times, saving the vehicle owner's time.

[0128] If the available duration is less than the remaining duration of the current maintenance cycle, in order to ensure driving safety, the overhaul cut-off time is determined to be the cut-off time of the available duration to remind the vehicle owner to maintain the braking equipment in time.

[0129] In a possible scenario, the above overhaul judgment method can also be applied to the review of vehicle historical overhaul data. That is, first obtain the vehicle's historical driving data, then determine the predicted overhaul date according to the historical driving data with reference to the above overhaul judgment method, and then compare it with the vehicle's historical overhaul data to determine the rationality of the overhaul node configuration.

[0130] Furthermore, since the historical overhaul data can be obtained by triggering overhauls based on fixed mileage or time, or can be obtained by triggering overhauls in combination with relevant monitoring algorithms. That is, the monitoring algorithms for triggering vehicle overhaul and maintenance usually make comprehensive judgments based on multi-dimensional data, including driving mileage, time period, real-time sensor monitoring (such as oil life, brake pad wear, tire pressure, etc.), on-board diagnostic system (OBD) fault codes, driving behavior patterns (such as the frequency of hard acceleration / braking), and environmental factors (such as extreme temperature or road conditions). By analyzing the data through preset threshold rules or machine learning models, the algorithm will automatically trigger maintenance reminders or fault warnings when detecting that key indicators exceed the safe range, reach the maintenance cycle, or predict potential fault risks. Therefore, combining the overhaul judgment method provided in this embodiment can optimize the existing monitoring algorithms, thereby further improving the accuracy of vehicle overhaul judgment.

[0131] The above maintenance judgment method is implemented using VB (Visual Basic) code, which is convenient for embedding tables containing vehicle condition data. It can also be implemented using Python or other languages.

[0132] Corresponding to the above maintenance judgment method, an embodiment of the present application also discloses a maintenance judgment device. Refer to Figure 3 As shown, the device includes:

[0133] A first determination unit 100, configured to determine whether a driver of the vehicle has aggressive driving behavior based on driving data of the vehicle;

[0134] A recording unit 110, configured to record target driving data if the driver of the vehicle has aggressive driving behavior; wherein, the target driving data includes at least one of the occurrence time of the aggressive driving behavior and the vehicle mileage data when the aggressive driving behavior occurs;

[0135] A second determination unit 120, configured to determine whether the braking device of the vehicle needs maintenance according to the target driving data.

[0136] As an optional implementation manner, in another embodiment of the present application, it is disclosed that the first determination unit 100 in the above embodiment, when determining whether the driver of the vehicle has aggressive driving behavior based on the driving data of the vehicle as described in claim 1,

[0137] when it is detected that the driving speed is greater than the set speed, determine that the vehicle is speeding;

[0138] detect the number of times the vehicle brakes during the speeding;

[0139] if the number of times the vehicle brakes during the speeding reaches the set number of times, determine that the driver of the vehicle has aggressive driving behavior.

[0140] As an optional implementation manner, in another embodiment of the present application, it is disclosed that the first determination unit 100 in the above embodiment, when determining that the driver of the vehicle has aggressive driving behavior if the number of times the vehicle brakes during the speeding reaches the set number of times,

[0141] obtain the detection period set for the vehicle for the aggressive driving behavior;

[0142] within the detection period, if the number of times the vehicle brakes during the speeding reaches the set number of times, record that the driver of the vehicle has dangerous driving behavior;

[0143] By counting the number of dangerous driving behaviors of the driver of the vehicle during speeding, it is determined that the driver of the vehicle has aggressive driving behavior.

[0144] As an alternative implementation, in another embodiment of the present application, it is disclosed that the first determination unit 100 of the above embodiment is further configured to:

[0145] Obtain the set speed of the corresponding driving section of the vehicle;

[0146] Compare the driving speed of the vehicle with the set speed to determine the overspeed ratio information;

[0147] Configure the set number of times based on the overspeed ratio information.

[0148] As an alternative implementation, in another embodiment of the present application, it is disclosed that the first determination unit 100 of the above embodiment is further configured to:

[0149] Control the vehicle to perform environmental perception to obtain the road condition information of the vehicle;

[0150] Adjust at least one of the set speed and the set number of times according to the road condition information.

[0151] As an alternative implementation, in another embodiment of the present application, it is disclosed that the device of the above embodiment further includes:

[0152] A third determination unit, configured to determine the available duration of the braking device if the braking device of the vehicle needs to be repaired;

[0153] An output unit, configured to determine the repair deadline of the braking device according to the available duration and output a repair reminder message including the repair deadline.

[0154] As an alternative implementation, in another embodiment of the present application, it is disclosed that when the third determination unit of the above embodiment determines the available duration of the braking device if the braking device of the vehicle needs to be repaired, it is specifically configured to:

[0155] When it is detected that the driving speed is greater than the set speed, it is determined that the vehicle is overspeed;

[0156] Detect the number of times the vehicle brakes during the overspeed driving;

[0157] If the number of times the vehicle brakes during the overspeed driving reaches the set number of times, it is determined that the driver of the vehicle has aggressive driving behavior.

[0158] As an alternative implementation, in another embodiment of the present application, it is disclosed that the output unit in the above embodiment, when determining the overhaul deadline of the braking device according to the available duration, specifically is used for:

[0159] If the available duration is greater than or equal to the remaining duration of the current maintenance cycle, determine the overhaul deadline as the end time of the current maintenance cycle; if the available duration is less than the remaining duration of the current maintenance cycle, determine the overhaul deadline as the end time of the available duration.

[0160] Specifically, the device provided in this embodiment belongs to the same inventive concept as the method provided in the above embodiment of the present application, can execute the method provided in any of the above embodiments of the present application, and has the corresponding functional modules and beneficial effects for executing the method. For technical details not described in detail in this embodiment, reference can be made to the specific processing content of the method provided in the above embodiment of the present application, which will not be elaborated here.

[0161] The functions implemented by the above units can be respectively implemented by the same or different processors, which is not limited in the embodiments of the present application.

[0162] It should be understood that the units in the above device can be implemented in the form of a processor calling software. For example, the device includes a processor, the processor is connected to a memory, and instructions are stored in the memory. The processor calls the instructions stored in the memory to implement any of the above methods or the functions of each unit of the device. The processor can be a general-purpose processor, such as a CPU or a microprocessor, etc., and the memory can be a memory inside or outside the device. Alternatively, the units in the device can be implemented in the form of a hardware circuit. By designing the hardware circuit, some or all of the unit functions can be implemented. The hardware circuit can be understood as one or more processors. For example, in one implementation, the hardware circuit is an ASIC, and some or all of the above unit functions are implemented by designing the logical relationship of the components in the circuit. Another example is that in another implementation, the hardware circuit can be implemented by a PLD. Taking an FPGA as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured through a configuration file to implement some or all of the above unit functions. All units of the above device can be all implemented in the form of a processor calling software, or all implemented in the form of a hardware circuit, or some implemented in the form of a processor calling software and the remaining part implemented in the form of a hardware circuit.

[0163] In an embodiment of the present application, a processor is a circuit with signal processing capabilities. In one implementation, the processor can be a circuit with the ability to read and execute instructions, such as a CPU, microprocessor, GPU, or DSP, etc.; in another implementation, the processor can implement certain functions through the logical relationship of a hardware circuit, and the logical relationship of this hardware circuit is fixed or can be reconfigured. For example, the processor is a hardware circuit implemented by an ASIC or PLD, such as an FPGA, etc. In a reconfigurable hardware circuit, the process of the processor loading a configuration document to implement the configuration of the hardware circuit can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as a type of ASIC, such as an NPU, TPU, DPU, etc.

[0164] It can be seen that each unit in the above device can be one or more processors (or processing circuits) configured to implement the above method. For example: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0165] In addition, each unit in the above device can be integrated in whole or in part, or can be independently implemented. In one implementation, these units are integrated together and implemented in the form of an SOC. The SOC can include at least one processor for implementing any of the above methods or implementing the functions of each unit of the device. The types of the at least one processor can be different. For example, it includes a CPU and an FPGA, a CPU and an artificial intelligence processor, a CPU and a GPU, etc.

[0166] An embodiment of the present application also proposes a control device, which includes a processor and an interface circuit. The processor in the control device is connected to the input / output component through the interface circuit of the control device.

[0167] The input / output component specifically refers to a hardware component that enables a user to input information and output information to the user. For example, it can be a microphone, keyboard, handwriting board, touch screen, display, speaker, printer, etc.

[0168] The above interface circuit can be any interface circuit capable of implementing data communication functions. For example, it can be a USB interface circuit, a Type-C interface circuit, a serial port circuit, a PCIE circuit, etc.

[0169] The processor in the control device is a circuit with signal processing capabilities. By executing any of the overhaul determination methods introduced in the above embodiments, it reduces the risk of braking failure of the braking device and improves driving safety. The specific implementation manner of the processor can refer to the above processor implementation manner, and the embodiments of the present application do not make strict limitations.

[0170] When the control device is applied to a device with a human-computer interaction function, the input and output components of the control device may be input components and output components on the device, such as a microphone, a keyboard, a handwriting tablet, a touch screen, a display, an audio player, etc. At the same time, the processor of the control device may be a CPU or GPU, etc. provided by the device, and the interface circuit of the control device may be an interface circuit between the information input component of the device and a processor such as a CPU or GPU.

[0171] Corresponding to the above-mentioned maintenance determination method, the embodiment of the present application also discloses an electronic device, see Figure 4 As shown, the electronic device includes:

[0172] Memory 200 and processor 210;

[0173] The memory 200 is connected to the processor 210 and is used to store programs;

[0174] The processor 210 is used to implement the maintenance determination method disclosed in any of the above embodiments by running the program stored in the memory 200.

[0175] Specifically, the electronic device may further include: a bus, a communication interface 220 , an input device 230 and an output device 240 .

[0176] The processor 210, the memory 200, the communication interface 220, the input device 230 and the output device 240 are connected to each other via a bus.

[0177] A bus may include a pathway that transfers information between components of a computer system.

[0178] The processor 210 may be a general-purpose processor, such as a general-purpose central processing unit (CPU), a microprocessor, etc., or an application-specific integrated circuit (ASIC), or one or more integrated circuits for controlling the execution of the program of the present application. It may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0179] The processor 210 may include a main processor, and may also include a baseband chip, a modem, and the like.

[0180] The program for implementing the technical solution of this application is stored in the memory 200. The operating system and other key services can also be stored. Specifically, the program can include program code, and the program code includes computer operation instructions. More specifically, the memory 200 can include a read-only memory (ROM), other types of static storage devices that can store static information and instructions, a random access memory (RAM), other types of dynamic storage devices that can store information and instructions, a disk memory, a flash memory, and so on.

[0181] The input device 230 can include devices for receiving data and information input by the user, such as a keyboard, a mouse, a camera, a scanner, a light pen, a voice input device, a touch screen, a pedometer, or a gravity sensor, etc.

[0182] The output device 240 can include devices for allowing information to be output to the user, such as a display screen, a printer, a speaker, etc.

[0183] The communication interface 220 can include any device such as a transceiver for communicating with other devices or communication networks, such as Ethernet, a radio access network (RAN), a wireless local area network (WLAN), etc.

[0184] The processor 210 executes the program stored in the memory 200 and calls other devices, and can be used to implement each step of the overhaul determination method provided in the above embodiments of this application.

[0185] Another embodiment of this application also proposes a vehicle. Refer to Figure 5 As shown, the vehicle includes an overhaul judgment device 300, and the overhaul judgment device 300 is configured to be able to implement the overhaul determination method disclosed in any of the above embodiments.

[0186] The overhaul judgment device 300 can be set on the center console of the vehicle, or set at any position such as the engine compartment of the vehicle. The overhaul judgment device 300 can be an electronic device embedded in the vehicle's electronic control unit (ECU), or a processing chip independently set from the ECU. Or, the overhaul judgment device 300 can also be one or more ECUs specifically used to determine whether the braking device of the vehicle needs to be overhauled.

[0187] The maintenance judgment device 300 provided in this embodiment belongs to the same inventive concept as the maintenance judgment method provided in the above embodiments of the present application. It can execute the maintenance judgment methods provided in any of the above embodiments of the present application, and has the corresponding functional modules and beneficial effects for executing the above maintenance judgment methods. For technical details not described in detail in this embodiment, reference may be made to the specific processing content of the maintenance judgment method provided in the above embodiments of the present application, which will not be elaborated here.

[0188] In addition to the above methods and devices, an embodiment of the present application may also be a computer program product, which includes a computer program. When the computer program is run by a processor, it can execute the maintenance judgment methods provided in any of the above embodiments of the present application. Optionally, the computer program may be stored in a readable storage medium or in the cloud of a computer device; the processor of the computer device reads the computer program from the readable storage medium or the cloud.

[0189] The computer program product can be written in any combination of one or more programming languages to write program code for performing the operations of the embodiments of the present application. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, executed as an independent software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0190] The above computer program product can be specifically implemented in a manner of hardware, software, or a combination thereof. In an alternative embodiment, the computer program product is specifically embodied as a computer storage medium. In another alternative embodiment, the computer program product is specifically embodied as a software product, such as a Software Development Kit (SDK), etc.

[0191] In addition, an embodiment of the present application may also be a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are run by a processor, the processor is caused to execute each step of the maintenance judgment method provided in the above embodiments.

[0192] The computer-readable storage medium may adopt any combination of one or more readable media. The readable media may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0193] Specifically, for the specific working content of each part of the above-mentioned electronic device, computer program product, and storage medium, as well as the specific processing content when the computer program on the computer program product or the above-mentioned storage medium is run by the processor, reference may be made to the content of each embodiment of the above-mentioned maintenance determination method, which will not be elaborated here.

[0194] For the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should be aware that this application is not limited by the described action sequence, because according to this application, certain steps may be performed in other sequences or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0195] It should be noted that the embodiments in this specification are all described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The same or similar parts among the embodiments may be referred to each other. For the device embodiments, since they are basically similar to the method embodiments, they are described relatively simply. For the relevant parts, reference may be made to the partial description of the method embodiments.

[0196] The steps in the method embodiments of this application may be adjusted, combined, and deleted according to actual needs. The technical features recorded in each embodiment may be replaced or combined.

[0197] The modules and sub-modules in the devices and terminals in the embodiments of this application may be combined, divided, and deleted according to actual needs.

[0198] In several embodiments provided by the present application, it should be understood that the disclosed terminals, devices, and methods can be implemented in other ways. For example, the terminal embodiments described above are merely illustrative. For example, the division of modules or sub-modules is only a logical function division. In actual implementation, there may be other division methods. For example, multiple sub-modules or modules can be combined or integrated into another module, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces, and the indirect coupling or communication connection of devices or modules can be in electrical, mechanical, or other forms.

[0199] The modules or sub-modules described as separate components may or may not be physically separated. The components as modules or sub-modules may or may not be physical modules or sub-modules, that is, they may be located in one place, or may be distributed to multiple network modules or sub-modules. Some or all of the modules or sub-modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0200] In addition, each functional module or sub-module in various embodiments of the present application can be integrated in a processing module, or each module or sub-module can exist physically alone, or two or more modules or sub-modules can be integrated in one module. The above-mentioned integrated modules or sub-modules can be implemented in the form of hardware or in the form of software functional modules or sub-modules.

[0201] Those skilled in the art can further realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, computer software, or a combination of the two. To clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described according to functions in the above description. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0202] The steps of the methods or algorithms described in combination with the embodiments disclosed in this article can be directly implemented by hardware, software units executed by a processor, or a combination of the two. The software units can be placed in a random access memory (RAM), memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium well-known in the technical field.

[0203] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the said element.

[0204] The foregoing description of the disclosed embodiments enables those skilled in the art to practice or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A maintenance determination method, characterized in that: include: Determining whether a driver of the vehicle has aggressive driving behavior based on driving data of the vehicle, wherein the driving data is obtained by collecting statistics on braking behavior of the vehicle during overspeed driving; If the driver of the vehicle has aggressive driving behavior, the target driving data is recorded; It is determined whether the braking equipment of the vehicle needs to be inspected or not according to the target driving data.

2. The method according to claim 1, characterized in that The determining, based on the driving data of the vehicle, whether the driver of the vehicle has aggressive driving behavior includes: When it is detected that the driving speed is greater than a set speed, determining that the vehicle is traveling over the speed limit; Detecting the number of times the vehicle brakes during the overspeeding process; If the number of braking operations of the vehicle during the overspeeding process reaches a set number, it is determined that the driver of the vehicle has an aggressive driving behavior.

3. The method according to claim 2, characterized in that If the number of braking times of the vehicle during the overspeeding process reaches a set number, it is determined that the driver of the vehicle has an aggressive driving behavior, including: Obtaining a detection cycle set for the vehicle for the intense driving behavior; During the detection period, if the number of braking of the vehicle during the overspeeding process reaches a set number, it is recorded that the driver of the vehicle has dangerous driving behavior; By counting the number of times the driver of the vehicle has dangerous driving behaviors during speeding, it is determined that the driver of the vehicle has aggressive driving behaviors.

4. The method according to claim 2, characterized in that: The method further comprises: Obtaining a set speed for the vehicle corresponding to the driving section; Comparing the running speed of the vehicle with the set speed to determine the overspeed ratio information; The set number of times is configured based on the overspeed ratio information.

5. The method according to claim 4, characterized in that The method further comprises: Controlling the vehicle to perform environmental perception to obtain road condition information of the vehicle; At least one of the set speed and the set number of times is adjusted according to the road condition information.

6. The method according to claim 1, characterized in that The method further comprises: If the braking device of the vehicle needs to be repaired, determining the useful life of the braking device; The maintenance deadline of the brake equipment is determined according to the available time, and maintenance reminder information including the maintenance deadline is output.

7. The method according to claim 6, characterized in that If the braking device of the vehicle needs to be repaired, determining the usable time of the braking device includes: Inputting the target driving data into a pre-trained available time prediction model, so that the available time prediction model outputs a prediction result according to the target driving data; the prediction result is the available time of the braking device; The available time prediction model is trained by using driving data of sample vehicles under different driving conditions as training samples and by aiming to predict the available time of the braking equipment of the sample vehicles.

8. The method according to claim 6, characterized in that Determining the maintenance deadline of the brake equipment according to the available time includes: If the available time is greater than or equal to the remaining time of the current maintenance cycle, the maintenance deadline is determined to be the end time of the current maintenance cycle.

9. A maintenance judgment device, characterized in that: include: A first determination unit is used to determine whether the driver of the vehicle has an aggressive driving behavior based on the driving data of the vehicle, wherein the driving data is obtained by collecting statistics on the braking behavior of the vehicle during the process of exceeding the speed limit; A recording unit, configured to record target driving data if the driver of the vehicle has aggressive driving behavior; The second determination unit is used to determine whether the braking equipment of the vehicle needs to be repaired according to the target driving data.

10. A vehicle, characterized in that: include: A maintenance judgment device, wherein the maintenance judgment device is configured to be able to implement the method according to any one of claims 1 to 8.

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