Electronic mechanical brake pre-braking method and device, electronic equipment and storage medium

Abstract

The application discloses an electromechanical brake pre-braking method and device, electronic equipment and a storage medium, and relates to the technical field of vehicle control. The method comprises the following steps: collecting driver behavior signals and vehicle environment signals; inputting the collected signals into an intention prediction model to output a braking intention probability and an expected braking intensity; when the braking intention probability exceeds a preset threshold, performing a corresponding pre-braking action according to the expected braking intensity; and if no actual braking operation is detected within a preset time after the pre-braking trigger, the pre-braking action is cancelled. The technical effect of shortening the braking response time, improving the pre-braking prediction accuracy and the working condition adaptability, and balancing the braking safety and the driving smoothness is achieved.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and in particular to an electromechanical braking pre-braking method, device, electronic device, and storage medium. Background Technology

[0002] Electromechanical braking systems have been gradually applied to vehicle braking due to their compact structure and controllable response. However, in actual working conditions, there is an inherent gap between the brake pads and the brake disc. After the driver presses the brake pedal, the gap must be eliminated before effective braking force can be established, resulting in a brake free travel. This causes a delay in braking response, which affects the driver's braking experience and also reduces the safe braking distance in emergency situations.

[0003] Existing pre-braking schemes mostly rely on a single pedal signal or front radar data to trigger pre-braking. The driver's intention recognition dimension is limited, making it difficult to accurately predict the timing and intensity of braking. This can easily lead to problems such as delayed or false pre-braking triggering. They cannot match different braking needs to execute differentiated pre-braking actions, and there is no timely cancellation mechanism after false triggering. This can easily cause unnecessary interference to normal driving, affecting the smoothness of vehicle driving and the driving experience. Summary of the Invention

[0004] This application provides an electromechanical pre-braking method, device, electronic device, and storage medium. It can solve the problems in the prior art such as delayed braking response due to brake free travel, insufficient matching between pre-braking trigger timing and intensity due to limited braking intent recognition dimensions, and the lack of a cancellation mechanism after mis-triggered braking, which affects driving smoothness.

[0005] According to a first aspect of this application, an electromechanical braking pre-braking method is provided, comprising: Collect driver behavior signals and vehicle environmental signals; The collected signals are input into the intention prediction model, which outputs the braking intention probability and the expected braking intensity. When the probability of braking intent exceeds a preset threshold, a corresponding pre-braking action is performed according to the expected braking intensity. If no actual braking operation is detected within a preset time after the pre-braking is triggered, the pre-braking action is cancelled.

[0006] According to a second aspect of this application, an electromechanical pre-braking device is provided, comprising: The data acquisition module is configured to collect driver behavior signals and vehicle environmental signals; The output module is configured to input the collected signals into the intention prediction model and output the braking intention probability and expected braking intensity. The execution module is configured to perform a corresponding pre-braking action based on the expected braking intensity when the probability of the braking intention exceeds a preset threshold. The cancellation module is configured to cancel the pre-braking action if no actual braking operation is detected within a preset time after the pre-braking is triggered.

[0007] According to a third aspect of this application, an electronic device is provided, comprising: At least one processor; and memory that is communicatively connected to at least one processor; The memory stores instructions that can be executed by at least one processor, which are executed by at least one processor to enable the at least one processor to perform the electromechanical braking pre-braking method described in the first aspect above.

[0008] According to a fourth aspect of this application, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause a computer to execute the electromechanical braking pre-braking method described in the first aspect above.

[0009] According to a fifth aspect of this application, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the electromechanical braking pre-braking method as described in the first aspect above.

[0010] This application solves the problems in the prior art, such as delayed braking response due to brake travel, insufficient matching between pre-braking timing and intensity due to limited braking intent recognition dimensions, and lack of cancellation mechanism after false triggering, by collecting driver behavior signals and vehicle environmental signals and outputting braking intent probability and expected braking intensity through an intent prediction model. Furthermore, it cancels the pre-braking action if no actual braking operation is detected within a preset time after the pre-braking is triggered. Thus, it achieves the technical effects of shortening braking response time, improving the accuracy and adaptability of pre-braking prediction, and balancing braking safety and driving smoothness.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0012] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A schematic flowchart illustrating an electromechanical braking pre-braking method provided in an embodiment of this application; Figure 2 This is a schematic diagram of the structure of an electromechanical pre-braking device provided in an embodiment of this application. Detailed Implementation

[0014] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of this application, including various details to aid understanding. These should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0015] The following description, with reference to the accompanying drawings, describes an electromechanical braking pre-braking method, apparatus, electronic device, and storage medium according to embodiments of this application.

[0016] Figure 1 This is a schematic flowchart of an electromechanical braking pre-braking method provided in an embodiment of this application.

[0017] like Figure 1 As shown, the method includes the following steps: Step 101: Collect driver behavior signals and vehicle environmental signals.

[0018] In some embodiments, this step performs a signal acquisition operation, simultaneously acquiring driver behavior signals and vehicle environmental signals. These two types of signals together constitute the basic data source for braking intention recognition.

[0019] Driver behavior signals include accelerator pedal signals, brake pedal signals, steering wheel angle signals, and driver eye gaze area signals. The accelerator pedal signal acquires the pedal position and rate of change of position; the brake pedal signal acquires the pedal position, rate of change of position, and contact switch status; the steering wheel angle signal acquires the real-time steering angle value and corresponding angular velocity; and the driver eye gaze area signal is acquired by a Driver State Monitoring (DSM) camera, which captures the driver's gaze distribution area in real time.

[0020] The vehicle environment signals include the distance to the vehicle in front and the relative speed. The vehicle-mounted millimeter-wave radar continuously detects the target vehicle in front and outputs the distance between the vehicle and the vehicle in front in real time, as well as the relative speed between the two vehicles.

[0021] By collecting driver operation characteristics and vehicle driving environment information from multiple dimensions, it is possible to comprehensively cover key representation quantities related to braking intention, ensuring the integrity and real-time nature of the collected data, and providing reliable data support for the accurate identification of braking intention.

[0022] Step 102: Input the collected signal into the intention prediction model and output the braking intention probability and expected braking intensity.

[0023] In some embodiments, this step involves aligning the collected driver behavior signals with the vehicle environment signals in a time sequence, then inputting them into the intention prediction model for inference calculation, and outputting the braking intention probability and expected braking intensity.

[0024] The intention prediction model employs a Transformer temporal model, using a continuous signal sequence from the past 2 seconds as input. It utilizes a self-attention mechanism to analyze the temporal correlation and trends between multi-source signals, extracting feature information reflecting the driver's braking tendency. The model outputs a braking intention probability ranging from 0 to 1, representing the likelihood of the driver performing an imminent braking operation. The expected braking intensity is categorized into light, medium, and heavy levels, representing the driver's expected braking force. This model can be trained and iterated in the cloud based on massive amounts of driving data and deployed to the vehicle via over-the-air (OTA) updates.

[0025] By relying on the Transformer time series model to process multi-dimensional time series signals, it can fully explore the correlation features and change patterns between signals, realize the accurate identification of braking intention and the graded prediction of braking intensity, and output results with both quantitative probability and intensity level, providing accurate decision-making basis for subsequent braking control.

[0026] Step 103: When the probability of the braking intention exceeds a preset threshold, perform the corresponding pre-braking action according to the expected braking intensity.

[0027] In some embodiments, this step is a pre-braking triggering and execution phase. The system compares the braking intention probability output by the intention prediction model with a preset threshold in real time. The preset threshold for the braking intention probability is 0.7. When the braking intention probability exceeds the preset threshold, it is determined that the driver has a clear braking tendency, and the pre-braking execution process is then initiated.

[0028] The system matches the corresponding pre-braking action based on the expected braking intensity output by the model. For light braking prediction, the drive redundant motor pushes the brake pads to the critical contact position, where the gap between the brake pads and the brake disc is 0.05mm, thus eliminating the inherent clearance of the braking system in advance. For medium or heavy braking prediction, the drive redundant motor pushes the brake pads to make slight contact with the brake disc. The braking force generated under slight contact is less than 50N, and a corresponding pedal reaction force is established at the brake pedal to provide operational feedback to the driver.

[0029] Precise pre-braking is achieved by using threshold determination, and differentiated pre-braking actions are executed by combining braking intensity classification. This can adapt to different levels of braking demand, effectively shorten the braking free travel and response time, while avoiding excessive braking intervention and balancing braking response speed and vehicle ride smoothness.

[0030] Step 104: If no actual braking operation is detected within a preset time after the pre-braking is triggered, the pre-braking action is cancelled.

[0031] In some embodiments, this step is a fault-tolerant cancellation step for pre-braking. After the pre-braking action is triggered, the system synchronously starts timing, with a preset time set to 500ms. During the timing period, the system continuously monitors the driver's actual braking operation, determining whether the driver has performed a valid braking action by observing changes in the brake pedal position and the status of the contact switch. If no actual braking operation is detected by the time the preset time expires, it is determined that the pre-braking was falsely triggered, and the system immediately performs a cancellation operation, controlling the redundant motor to reverse and reset, causing the brake pads to return to the initial standby gap position, while simultaneously releasing the established pedal reaction force, allowing the braking system to fully return to the normal standby state.

[0032] By setting a time-limited cancellation mechanism, the pre-braking state can be terminated in time when the braking intention is misjudged, avoiding continuous interference with normal driving caused by erroneous pre-braking actions. While retaining the acceleration effect of pre-braking, it effectively improves the smoothness of vehicle driving and the driving experience.

[0033] Compared with related technologies, this embodiment collects driver behavior signals and vehicle environmental signals; inputs the collected signals into an intention prediction model, and outputs the braking intention probability and expected braking intensity; when the braking intention probability exceeds a preset threshold, a corresponding pre-braking action is executed according to the expected braking intensity; if no actual braking operation is detected within a preset time after the pre-braking is triggered, the pre-braking action is revoked. This can solve the problems in the prior art, such as braking response delay due to brake free travel, insufficient matching degree between pre-braking triggering timing and intensity due to limited braking intention recognition dimensions, and lack of cancellation mechanism after false triggering affecting driving smoothness. It achieves the technical effects of shortening braking response time, improving the accuracy and adaptability of pre-braking prediction, and balancing braking safety and driving smoothness.

[0034] As a specific implementation of this application, based on the basic solution, the driver behavior signal is further defined to include accelerator pedal signal, brake pedal signal, steering wheel angle signal and driver eye gaze area signal.

[0035] Specifically, in this particular implementation, the collected driver behavior signals include accelerator pedal signals, brake pedal signals, steering wheel angle signals, and driver eye gaze area signals. A behavior feature collection system is constructed from two dimensions: driver operation actions and visual attention, fully covering the typical behavioral representations before and after the braking intention is generated.

[0036] The accelerator pedal signal acquires the real-time position value and rate of change of the pedal, which can intuitively reflect the driver's adjustment trend of the vehicle's power output. A rapid drop in the pedal position usually corresponds to the driver's tendency to decelerate by releasing the accelerator, and is one of the precursor indicators of braking intention. The brake pedal signal acquires the pedal position, rate of change of position, and contact switch status. The contact switch can accurately capture the initial contact action between the driver's foot and the brake pedal, and can detect the initial stage of braking operation before the pedal travel occurs. The steering wheel angle signal acquires the real-time angle value and rotation angular velocity to identify the driver's steering operation status, help determine the current driving condition of the vehicle, and provide a reference for the contextual recognition of braking intention. The driver's eye gaze area signal is acquired by the DMS camera, which captures the driver's gaze distribution area in real time, reflecting the driver's attention allocation and observation status, and can help predict the timing of the driver's braking decision.

[0037] By clearly defining the content of the four types of driver behavior signals collected, the pre-braking behavioral characteristics can be captured from multiple dimensions, enriching the input dimensions of intention recognition and effectively improving the accuracy and timeliness of braking intention prediction.

[0038] As a specific implementation of this application, based on the basic solution, the vehicle environment signal is further defined to include the distance to the vehicle in front and the relative speed.

[0039] Specifically, in this particular implementation, the collected vehicle environment signals include the distance to the vehicle in front and the relative speed. These two types of signals are obtained by the vehicle-mounted millimeter-wave radar continuously detecting the target vehicle in front, and are used to characterize the driving environment in front of the vehicle, providing environmental feature support for predicting braking intentions.

[0040] The distance to the vehicle in front is the real-time distance between the vehicle and the vehicle traveling in the same direction ahead. It directly reflects the spatial separation between the two vehicles. When the distance continues to decrease, it corresponds to the vehicle gradually approaching the vehicle in front, which is a typical environmental factor that triggers braking. The relative speed is the speed difference between the vehicle and the vehicle in front, which reflects the trend of the two vehicles approaching or moving away. Combined with the distance to the vehicle in front, it can further quantify and assess the driving safety margin, and help determine the objective environmental conditions under which the driver will perform braking operations.

[0041] By clearly defining two types of environmental signals—distance to the vehicle ahead and relative speed—the risk level of the driving environment ahead can be quantified, supplementing the input features of the environmental dimension for braking intention recognition and improving the adaptability of the prediction results to actual driving conditions.

[0042] As a specific implementation of this application, based on the basic scheme, the intent prediction model is further defined as a Transformer time series model, with the signal sequence within the past 2 seconds as input.

[0043] Specifically, in this particular implementation, the intent prediction model adopts the Transformer time-series model, using the signal sequence within the past 2 seconds as input to complete the inference and recognition of braking intent.

[0044] The Transformer temporal model, leveraging a self-attention mechanism, fully exploits the correlation characteristics between multi-source signals and the evolution patterns of signals over time. It accurately captures the dynamic trends of driving operations and environmental parameters, demonstrating excellent extraction and fitting capabilities for temporal driving behavior features. The input signal sequence is composed of driver behavior signals and vehicle environmental signals sampled continuously over the past two seconds, aligned with timestamps. A fixed-duration input window balances feature completeness and real-time computation, ensuring inference efficiency when deployed on the vehicle. After performing multi-layer feature encoding and decoding on the input temporal signal sequence, the model outputs the braking intent probability and expected braking intensity level for the corresponding driving condition. The model can be trained and iterated in the cloud based on massive amounts of driving data and deployed on the vehicle via OTA (Over-The-Air) updates, enabling continuous optimization of prediction performance.

[0045] By adopting the Transformer timing model and setting a 2-second input timing window, the feature fusion capability and intent recognition accuracy of multi-source timing signals can be effectively improved, while ensuring the real-time performance of vehicle-side inference and providing stable and reliable model support for accurate prediction of braking intent.

[0046] As a specific implementation of this application, based on the basic solution, the step of performing the corresponding pre-braking action according to the expected braking intensity is further defined as follows: For light braking prediction, the redundant drive motor moves the brake pads to the critical contact position, which is the position where the gap between the brake pads and the brake disc is 0.05mm. For medium or heavy braking prediction, the redundant drive motor makes the brake pads slightly contact the brake disc and establishes pedal reaction force. The braking force generated when the brake pads slightly contact the brake disc is less than 50N.

[0047] Specifically, in this particular implementation, the pre-braking action is performed in stages according to the expected braking intensity, with a redundant motor acting as the power source to drive the braking mechanism to complete the corresponding action, adapting to different levels of braking requirements.

[0048] For light braking anticipation, the system drives a redundant motor to output corresponding torque, pushing the brake pads towards the brake disc, ultimately positioning the brake pads at the critical contact position. The critical contact position is where the gap between the brake pads and the brake disc is 0.05mm. This position eliminates most of the inherent clearance of the braking system, leaving only a very small safety clearance. This significantly shortens the pressure build-up stroke for subsequent actual braking without generating additional driving drag resistance, making it suitable for light deceleration scenarios.

[0049] For medium or heavy braking prediction, the system drives a redundant motor to push the brake pads further forward, so that the brake pads make slight contact with the brake disc. The braking force generated under slight contact is less than 50N. At the same time, the pedal force feedback actuator establishes a corresponding pedal reaction force at the brake pedal, establishes the initial braking pressure base in advance, and transmits operation feedback to the driver. This allows the driver to directly enter the effective braking stage when pressing the pedal, further compressing the braking response time and adapting to medium and high intensity braking needs.

[0050] By setting differentiated pre-braking execution strategies in stages and matching different intensity of braking prediction results, it is possible to ensure the braking response acceleration effect while adapting to the braking needs under different operating conditions, avoiding driving interference caused by excessive pre-braking, and balancing braking response speed and vehicle driving smoothness.

[0051] As a specific implementation of this application, the preset time is further limited to 500ms based on the basic solution.

[0052] Specifically, in this particular implementation, the preset time for the cancellation determination after the pre-braking is triggered is set to 500ms. This duration serves as an effective waiting window for the pre-braking action, matching the normal action delay from the generation of the driver's braking intention to the actual pressing of the brake pedal.

[0053] Upon triggering the pre-braking action, the system simultaneously starts timing, continuously monitoring the brake pedal position and contact switch status within a 500ms timing period to identify the driver's actual braking operation. If a valid braking action is detected within this time, the pre-braking state is maintained and transitions into the formal braking process; if no actual braking operation is detected by the end of the timing period, it is determined that the prediction has deviated, and the pre-braking cancellation operation is immediately executed. The redundant motor is controlled to drive the brake pads to reset, releasing the pedal reaction force and restoring the braking system to its initial standby state. This timeframe covers the physiological reaction and operation time of the driver from generating the braking intention to completing the pedal action in normal driving scenarios, avoiding the false cancellation of pre-braking before normal braking, and also allows for rapid termination of intervention in case of prediction errors, shortening the duration of the false triggering state.

[0054] Setting the preset time to 500ms can effectively limit the duration of false triggering while ensuring the normal pre-braking activation window, balancing the response gain of pre-braking with driving smoothness, and improving the adaptability of the solution to operating conditions and the driving experience.

[0055] Figure 2 This is a schematic diagram of the structure of an electromechanical pre-braking device provided in an embodiment of this application, as shown below. Figure 2 As shown, it includes: The acquisition module 201 is configured to acquire driver behavior signals and vehicle environmental signals; Output module 202 is configured to input the collected signal into the intention prediction model and output the braking intention probability and expected braking intensity; The execution module 203 is configured to perform a corresponding pre-braking action based on the expected braking intensity when the probability of the braking intention exceeds a preset threshold. The cancellation module 204 is configured to cancel the pre-braking action if no actual braking operation is detected within a preset time after the pre-braking is triggered.

[0056] It should be noted that other corresponding descriptions of the functional units involved in the electromechanical pre-braking device provided in this embodiment can be found in [reference]. Figure 1 The corresponding descriptions in [the document] will not be repeated here.

[0057] Based on the above, Figure 1The embodiment illustrates an electromechanical braking pre-braking method. Correspondingly, this embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method. Figure 1 The above describes an electromechanical braking pre-braking method.

[0058] Based on the above, Figure 1 The embodiment illustrates an electromechanical braking pre-braking method. Correspondingly, this embodiment also provides a computer program product storing a computer program that, when executed by a processor, implements the aforementioned method. Figure 1 The above describes an electromechanical braking pre-braking method.

[0059] Based on this understanding, the technical solution of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as CD-ROM, USB flash drive, mobile hard drive, etc.) and includes several instructions to cause a computer device (such as personal computer, server, or network device, etc.) to execute the methods of various implementation scenarios of this application.

[0060] Based on the above, Figure 1 An electromechanical pre-braking method is shown, and Figure 2 To achieve the above objectives, the present application also provides an electronic device, such as a personal computer or a server, in the illustrated virtual device embodiment. This device includes a storage medium and a processor; the storage medium stores a computer program; the processor executes the computer program to implement the above-described virtual device. Figure 1 The above describes an electromechanical braking pre-braking method.

[0061] In some embodiments, the aforementioned physical device may further include a user interface, a network interface, a camera, radio frequency (RF) circuitry, sensors, audio circuitry, a Wi-Fi module, etc. The user interface may include a display screen, an input unit such as a keyboard, etc., and optionally, a USB interface, a card reader interface, etc. In some embodiments, the network interface may include a standard wired interface, a wireless interface (such as a Wi-Fi interface), etc.

[0062] The storage medium may also include an operating system and a network communication module. The operating system is a program that manages the hardware and software resources of the aforementioned physical device, supporting the operation of information processing programs and other software and / or programs. The network communication module is used to enable communication between the various components within the storage medium, as well as communication with other hardware and software in the information processing physical device.

[0063] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0064] The above are merely specific embodiments of this application, enabling those skilled in the art to understand or implement this 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 this application. Therefore, this application is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. An electromechanical braking pre-braking method, characterized in that, include: Collect driver behavior signals and vehicle environmental signals; The collected signals are input into the intention prediction model, which outputs the braking intention probability and the expected braking intensity. When the probability of braking intent exceeds a preset threshold, a corresponding pre-braking action is performed according to the expected braking intensity. If no actual braking operation is detected within a preset time after the pre-braking is triggered, the pre-braking action is cancelled.

2. The electromechanical braking pre-braking method according to claim 1, characterized in that, The driver behavior signals include accelerator pedal signals, brake pedal signals, steering wheel angle signals, and signals of the driver's eye gaze area.

3. The electromechanical braking pre-braking method according to claim 1, characterized in that, The vehicle environment signals include the distance to the vehicle in front and the relative speed.

4. The electromechanical braking pre-braking method according to claim 1, characterized in that, The intent prediction model is a Transformer time series model, which takes the signal sequence within the past 2 seconds as input.

5. The electromechanical braking pre-braking method according to claim 1, characterized in that, The step of performing the corresponding pre-braking action according to the expected braking intensity includes: For light braking prediction, the redundant drive motor moves the brake pads to the critical contact position, which is the position where the gap between the brake pads and the brake disc is 0.05mm. For medium or heavy braking prediction, the redundant drive motor makes the brake pads slightly contact the brake disc and establishes pedal reaction force. The braking force generated when the brake pads slightly contact the brake disc is less than 50N.

6. The electromechanical braking pre-braking method according to claim 1, characterized in that, The preset time is 500ms.

7. An electromechanical pre-braking device, characterized in that, include: The data acquisition module is configured to collect driver behavior signals and vehicle environmental signals; The output module is configured to input the collected signals into the intention prediction model and output the braking intention probability and expected braking intensity. The execution module is configured to perform a corresponding pre-braking action based on the expected braking intensity when the probability of the braking intention exceeds a preset threshold. The cancellation module is configured to cancel the pre-braking action if no actual braking operation is detected within a preset time after the pre-braking is triggered.

8. An electronic device, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the electromechanical braking pre-braking method according to any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the electromechanical braking pre-braking method according to any one of claims 1-6.

10. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the electromechanical braking pre-braking method according to any one of claims 1-6.

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