Control method, system and device of driving equipment, storage medium and electronic equipment

Abstract

The application provides a driving device control method, system, device, storage medium and electronic device. First, driving state data of the driving device in a driving process is acquired, and the number of times that the driving device is in an aggressive driving state in the driving process is determined according to the driving state data. Then, the aggressive degree value of the driving device is determined according to the number of times that the driving device is in the aggressive driving state. When it is monitored that a target pedal in the driving device is stepped on, the stepping intensity of the target pedal is determined, and the target control force corresponding to the stepping intensity of the target pedal in the aggressive driving state corresponding to the aggressive degree value of the driving device is determined according to the aggressive degree value and the standard control force corresponding to the stepping intensity. Then, the control signal is determined according to the target control force, and the driving device is controlled according to the control signal.

Description

Technical Field

[0001] This application relates to the field of intelligent driving, and more particularly to a control method, system, device, storage medium, and electronic device for a driving device. Background Technology

[0002] In recent years, the new energy vehicle industry has developed rapidly. Compared with traditional fuel vehicles, new energy vehicles have stronger acceleration performance, but at the same time, they also have a higher probability of safety accidents.

[0003] Currently, the control systems of new energy vehicles can apply control force based on the depth to which a specified pedal is pressed. However, current control systems do not take into account the user's individual preferences, which can lead to significant safety hazards. For example, when a user drives aggressively, the corresponding control force is also greater, thus greatly reducing safety during driving.

[0004] Therefore, how to adjust the control force to enhance safety during driving is an urgent problem to be solved. Summary of the Invention

[0005] This application provides a control method, system, device, storage medium, and electronic device for driving equipment to partially solve the aforementioned problems existing in the prior art.

[0006] The technical solution adopted in this application is as follows: This application provides a control method for a driving device, including: Acquire driving status data of the driving equipment during driving; Based on the driving status data, determine the number of times the driving device is in an aggressive driving state during driving; The degree of aggression for the driving device is determined based on the number of times the driving device is in an aggressive driving state; When the target pedal in the driving device is detected to be pressed, the pedal travel of the target pedal is determined; Based on the relationship between the aggression level value, the pedal travel, and the control force of the driving device, a target control force corresponding to the current aggression level value and the current pedal travel of the driving device is determined; The driving device is controlled according to the target control force.

[0007] Optionally, the aggressive driving state includes a rapid acceleration driving state and a rapid deceleration driving state; The degree of aggression for the driving device is determined based on the number of times the driving device is in an aggressive driving state, specifically including: The degree of rapid acceleration of the driving device is determined based on the number of times the driving device is in a state of rapid acceleration, and the degree of rapid deceleration of the driving device is determined based on the number of times the driving device is in a state of rapid deceleration. The aggressiveness value of the driving device is determined based on the rapid acceleration value and the rapid deceleration value.

[0008] Optionally, the degree of rapid acceleration of the driving device is determined based on the number of times the driving device is in a state of rapid acceleration, and the degree of rapid deceleration of the driving device is determined based on the number of times the driving device is in a state of rapid deceleration, specifically including: The number of times the driving device was in a rapid acceleration state and the number of times it was in a rapid deceleration state are sent to the cloud platform. The cloud platform then determines a rapid acceleration state sequence based on the number of times the driving device was in a rapid acceleration state and the number of times other driving devices were in a rapid acceleration state. It also determines a rapid deceleration state sequence based on the number of times the driving device was in a rapid deceleration state and the number of times other driving devices were in a rapid deceleration state. Finally, the cloud platform determines the degree of rapid acceleration and the degree of rapid deceleration of the driving device based on the rapid acceleration state sequence.

[0009] Optionally, a rapid acceleration driving state sequence is determined based on the number of times the driving device is in a rapid acceleration driving state and the number of times other driving devices are in a rapid acceleration driving state, specifically including: The average number of times the driving device was in a state of rapid acceleration and the average number of times the other driving devices were in a state of rapid acceleration was determined as the first average number. Based on the difference between the number of times the driving device is in a rapid acceleration state and the first average number of times, and the difference between the number of times the other driving devices are in a rapid acceleration state and the first average number of times, the driving device and the other driving devices included in the cloud platform are sorted in sequence to obtain a rapid acceleration state sequence.

[0010] Optionally, a sequence of rapid deceleration states is determined based on the number of times the driving device is in a rapid deceleration state and the number of times the other driving devices are in a rapid deceleration state, specifically including: The average number of times the driving device was in a state of rapid deceleration and the average number of times the other driving devices were in a state of rapid deceleration is determined as the second average number; Based on the difference between the number of times the driving device was in a rapid deceleration state and the second average number of times, and the difference between the number of times the other driving devices were in a rapid deceleration state and the second average number of times, the driving device and the other driving devices were sorted in sequence to obtain a rapid deceleration state sequence.

[0011] Optionally, the aggressiveness value of the driving device is determined based on the rapid acceleration value and the rapid deceleration value, specifically including: Determine the weights for rapid acceleration and rapid deceleration; The acceleration and deceleration values ​​are weighted according to the acceleration weight and deceleration weight to obtain the aggressiveness value of the driving device.

[0012] Optionally, based on the relationship between the aggression level value, the pedal travel, and the control force of the driving device, a target control force corresponding to the current aggression level value and the current pedal travel of the driving device is determined, specifically including: The control force corresponding to the pedal travel at a preset maximum level of aggression is determined as the maximum control force corresponding to the pedaling force, and the standard control force corresponding to the pedal travel is determined based on the relationship between the pedal travel and the control force of the driving device. Based on the maximum control force and the standard control force, a target control force corresponding to the current aggressiveness value of the driving device and the current pedal travel is determined.

[0013] Optionally, based on the maximum control force and the standard control force, a target control force corresponding to the current aggressiveness value of the driving device and the current pedal travel is determined, specifically including: Determine the difference between the maximum control force and the standard control force; Based on the difference and the current aggression level, a target control force corresponding to the current aggression level of the driving device and the current pedal travel is determined.

[0014] Optionally, based on the driving status data, the number of times the driving device is in an aggressive driving state during driving is determined, specifically including: Based on the driving status data, determine the probability distribution of the acceleration value of the driving device during driving; Based on the probability distribution, determine the driving acceleration threshold; Based on the driving acceleration threshold and the driving status data, determine the number of times the driving device is in an aggressive driving state during driving.

[0015] This application provides a control system for a driving device, the system including sensors, a vehicle control unit, an on-board communication unit, and a brake controller installed on the driving device; The sensor is used to collect driving status data of the driving device during driving; The vehicle control unit is used to receive the driving status data collected by the sensor, and determine the number of times the driving device is in an aggressive driving state during driving based on the driving status data; The vehicle communication unit is used to send the number of times the driving device is in an aggressive driving state during driving, as determined by the vehicle control unit, to the cloud platform, so that the cloud platform can determine the degree of aggression for the driving device based on the number of times the driving device is in an aggressive driving state, and return it to the driving device. The brake controller is used to determine the pedal travel of the target pedal when it is detected that the target pedal in the driving device is pressed, and to determine the target control force corresponding to the current aggression value and the current pedal travel of the driving device based on the relationship between the aggression value, the pedal travel and the control force of the driving device, and to control the driving device according to the target control force.

[0016] This application provides a control device for a driving system, including: Acquisition module: Used to acquire driving status data of the driving equipment during driving; First determining module: used to determine the number of times the driving device is in an aggressive driving state during driving based on the driving state data; The second determining module is used to determine the degree of aggression of the driving device based on the number of times the driving device is in an aggressive driving state. Monitoring module: used to determine the pedal travel of the target pedal when the target pedal in the driving device is detected to be pressed; The third determining module is used to determine the target control force corresponding to the current aggressiveness value and the current pedal travel of the driving device based on the relationship between the aggressiveness value, the pedal travel and the control force of the driving device. Control module: Used to control the driving equipment according to the target control force.

[0017] This application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the control method of the driving device described above.

[0018] This application provides an electronic device, including a memory, a processor, and a device stored on the memory. A computer program that can run on a processor, wherein the processor executes the program to implement the control method of the driving device described above.

[0019] The above-mentioned technical solution adopted in this application can achieve the following beneficial effects: The control method for the driving device provided in this application first acquires driving state data of the driving device during operation, and determines the number of times the driving device is in an aggressive driving state during operation based on the driving state data. Then, based on the number of times the driving device is in an aggressive driving state, an aggressiveness value for the driving device is determined. When a target pedal in the driving device is detected to be pressed, the pressing force of the target pedal is determined, and based on the aggressiveness value and the standard control force corresponding to the pressing force, a target control force corresponding to the pressing force in the aggressive driving state corresponding to the aggressiveness value is determined. Finally, a control signal is determined based on the target control force, and the driving device is controlled according to the control signal.

[0020] As can be seen from the above method, during the control of the driving equipment, the aggression level of the driving equipment can be determined based on driving status data. Furthermore, the driving equipment can be controlled by combining various factors reflected in the user's driving process based on the aggression level value. That is, the above method can identify the driver's driving habits based on the aggression level value of the driving equipment without increasing hardware costs, and significantly improve the braking characteristics of the driving equipment based on the identified driving habits. Therefore, it avoids the significant safety hazards caused by current control systems that do not consider the user's individual characteristics, thus greatly enhancing the safety of the driving equipment during driving. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart illustrating a control method for a driving device provided in this application; Figure 2 A schematic diagram illustrating the probability distribution of acceleration values ​​of a driving device during driving, as provided in this application; Figure 3 This application provides a schematic diagram of a process for obtaining the aggression level value of a driving device; Figure 4 A schematic diagram of a control method for a driving device provided in this application; Figure 5A schematic diagram illustrating the control of the driving equipment through the control system of the driving equipment provided in this application; Figure 6 A schematic diagram illustrating how a brake controller, provided in this application, performs driving equipment control; Figure 7 A schematic diagram of a control device for a driving device provided in this application; Figure 8 A corresponding to the present application Figure 1 A schematic diagram of the driving equipment. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] Currently, the control systems of new energy vehicles can apply control force based on the depth to which a specified pedal is depressed. However, current control systems do not consider the individual user's preferences, leading to significant safety hazards during driving. Therefore, this application provides a control method for a driving device to address this problem. The control method for the driving device provided in this application will be described in detail below.

[0024] In this application, the driving status data acquired during the control process of the driving device is obtained with the user's authorization. Furthermore, the subsequent use of driving status data from other driving devices to determine the aggression level is also done with the authorization of the users of those other driving devices. Therefore, all data used in this application is obtained in compliance with the relevant data protection laws and regulations of the country where the application is located, and with the authorization of the respective driving device's owner.

[0025] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0026] Figure 1 The flowchart of a control method for a driving device provided in this application includes the following steps: S101: Acquire driving status data of the driving equipment during driving.

[0027] S102: Based on the driving status data, determine the number of times the driving device is in an aggressive driving state during driving.

[0028] In a specific embodiment of this application, the driving device can first acquire driving status data during the driving process. This data can be collected by various sensors, including inertial measurement units (IMUs), lidar, millimeter-wave radar, and Global Navigation Satellite System (GNSS). The acquired driving status data may include information such as driving speed, driving acceleration, and steering angle.

[0029] After acquiring the aforementioned driving status data, the driving device can determine the number of times it entered an aggressive driving state during operation. To ensure real-time data acquisition, the driving device can first acquire driving status data using short-period sampling. This short-period data can then be used to determine a driving acceleration threshold, which in turn can be used to determine the number of times the driving device entered an aggressive driving state. For example, the driving status data can be sampled every 20ms or 50ms to determine the driving acceleration threshold.

[0030] Specifically, the driving device can determine the probability distribution of acceleration values ​​during driving based on driving state data acquired under short-period sampling. This probability distribution reflects the driving device's various acceleration values ​​over a certain period of time. For any given acceleration value, if the driving device has used that acceleration value more frequently or for a longer duration in the past period, the probability corresponding to that acceleration value in the probability distribution will be higher.

[0031] Once the probability distribution described above is determined, the driving device can determine the driving acceleration threshold based on this distribution. Furthermore, based on the driving acceleration threshold and driving state data, the number of times the driving device enters an aggressive driving state during operation can be determined. The probability distribution of the driving device's acceleration values ​​during operation can be found in [reference needed]. Figure 2 .

[0032] Figure 2 This is a schematic diagram illustrating the probability distribution of acceleration values ​​of a driving device during driving, as provided in this application.

[0033] Depend on Figure 2As can be seen, it can represent the probability distribution of the acceleration values ​​of the driving device during operation. The horizontal axis represents the acceleration values ​​of the driving device, where positive acceleration indicates that the driving device is accelerating, and negative acceleration indicates that the driving device is decelerating. The vertical axis represents the probability value of the driving device moving at the corresponding acceleration. Therefore, after determining... Figure 2 After illustrating the probability distribution, the acceleration value at which the acceleration value is less than a set probability (e.g., 5%, which can be adjusted according to actual needs) can be used as the driving acceleration threshold. From Figure 2 As can be seen from this, the determined driving acceleration threshold can actually be divided into rapid acceleration threshold and rapid deceleration threshold.

[0034] After determining the aforementioned driving acceleration threshold, the driving device can continue to collect driving status data during the driving process through various sensors. The data collection method can differ from the short-period collection method described above. For example, the driving device can collect driving status data using a long-period collection method (e.g., collecting driving status data every 10 seconds). After collecting the driving status data, the determined driving acceleration threshold can be used to determine the number of times the driving device entered an aggressive driving state during the driving process.

[0035] Specifically, when the acceleration contained in the driving status data of the driving device is not within the range of rapid deceleration threshold to rapid acceleration threshold, the driving device can be marked as being in an aggressive driving state, and the number of times the driving device is in an aggressive driving state during driving can be counted.

[0036] S103: Determine the degree of aggression for the driving device based on the number of times the driving device is in an aggressive driving state.

[0037] To more accurately determine the aggressive driving state of the driving equipment, multiple factors can be considered. Therefore, aggressive driving states can include rapid acceleration and rapid deceleration. The degree of rapid acceleration can be determined by the number of times the driving equipment enters a rapid acceleration state, and the degree of rapid deceleration can be determined by the number of times it enters a rapid deceleration state. Then, the degree of aggressiveness of the driving equipment can be determined based on the rapid acceleration and rapid deceleration values. The specific process for determining the degree of aggressiveness of the driving equipment can be found in [reference needed]. Figure 3 .

[0038] Figure 3 This application provides a schematic diagram of a process for obtaining the aggressiveness value of a driving device.

[0039] Depend on Figure 3As can be seen, the number of times the driving device was in a rapid acceleration state and the number of times it was in a rapid deceleration state can be sent to the cloud platform. The cloud platform can first determine the average of the number of times the driving device was in a rapid acceleration state with the number of times other driving devices were in a rapid acceleration state, as the first average. Then, the cloud platform can sort the driving device and other driving devices included in the cloud platform according to the difference between the number of times the driving device was in a rapid acceleration state and the first average, as well as the difference between the number of times other driving devices were in a rapid acceleration state and the first average, thereby obtaining the rapid acceleration state sequence.

[0040] The rapid acceleration driving state sequence can be sorted from smallest to largest by sorting the difference between the number of rapid accelerations of the current driving device and the average number of rapid accelerations, and the difference between the number of rapid accelerations of other driving devices included in the cloud platform and the average number of rapid accelerations, thus obtaining the rapid acceleration driving state sequence.

[0041] The cloud platform can divide the number of rapid accelerations into multiple ranges based on the sequence of rapid acceleration driving states. Each range corresponds to a different rapid acceleration level, and each rapid acceleration level corresponds to a rapid acceleration intensity value. Furthermore, the cloud platform can determine the range of rapid accelerations that the driving device's own rapid acceleration count falls into based on the number of rapid accelerations it has accumulated, and then determine the current rapid acceleration intensity value of the driving device based on the rapid acceleration level corresponding to that range.

[0042] Then, the cloud platform can determine the average number of times the driving device is in a state of rapid deceleration with the average number of times other driving devices are in a state of rapid deceleration, as the second average. The cloud platform can then sort the driving device and other driving devices included in the cloud platform according to the difference between the number of times the driving device is in a state of rapid deceleration and the second average, as well as the difference between the number of times other driving devices are in a state of rapid deceleration and the second average, thereby obtaining a sequence of rapid deceleration states.

[0043] The rapid deceleration driving state sequence can be sorted from smallest to largest by sorting the difference between the number of rapid decelerations of the current driving device and the average number of rapid decelerations, and the difference between the number of rapid decelerations of other driving devices included in the cloud platform and the average number of rapid decelerations, thus obtaining the rapid deceleration driving state sequence.

[0044] The cloud platform can divide the number of rapid decelerations into multiple ranges based on the sequence of rapid deceleration driving states. Each range corresponds to a different level of rapid deceleration, and each level of rapid deceleration corresponds to a value indicating the degree of rapid deceleration. Furthermore, the cloud platform can determine the range of rapid decelerations that the driving device's rapid decelerations fall into based on the number of rapid decelerations it experiences, and then determine the current degree of rapid deceleration of the driving device based on the corresponding level of rapid deceleration within that range.

[0045] Then, the cloud platform can determine the aggressiveness level of the driving equipment based on the rapid deceleration and rapid acceleration driving status values.

[0046] Specifically, the cloud platform can first determine the weights for rapid acceleration and rapid deceleration, and then weight the values ​​for rapid acceleration and rapid deceleration to obtain the aggressiveness value of the driving device. This aggressiveness value is then sent to the driving device. The specific aggressiveness value can be referenced by the following formula: Used to indicate the aggressiveness level of driving equipment. Used to indicate the degree of rapid acceleration. Used to indicate the degree of rapid deceleration. Used to represent acceleration weights, Used to represent the weight of rapid deceleration.

[0047] The acceleration weight can be determined based on actual needs.

[0048] As can be seen from the above formula, the aggressiveness value of the driving device is closely related to the rapid acceleration and rapid deceleration values. When the rapid acceleration and / or rapid deceleration values ​​are larger, the corresponding aggressiveness value is also larger, that is, the current user is more aggressive. When the rapid acceleration and / or rapid deceleration values ​​are smaller, the corresponding aggressiveness value is also smaller, that is, the current user is more stable.

[0049] It should be noted that the method described above is primarily accomplished through a cloud platform. Specifically, the cloud platform determines the appropriate level of aggression for each driving device by aggregating the number of times each device has been in an aggressive driving state. However, besides this method, driving devices can also determine their own appropriate level of aggression. Specifically, the cloud platform can send the number of times other driving devices have been in aggressive driving states to the driving device. During this transmission, the cloud platform can only send the specific number of times, without sending the device information or user information of the other driving devices. In this case, the driving device only receives the number of times other driving devices have been in aggressive driving states, without obtaining the specific user information. Based on this, the driving device can determine its own appropriate level of aggression by using its own number of times in aggressive driving states and the number of times other driving devices have been in aggressive driving states, through a similar method.

[0050] S104: When it is detected that the target pedal in the driving device is pressed, the pedal travel of the target pedal is determined.

[0051] S105: Based on the relationship between the aggression level value, the pedal travel, and the control force of the driving device, determine the target control force corresponding to the current aggression level value and the current pedal travel of the driving device.

[0052] During the operation of the driving equipment, when the driving equipment detects that the target pedal is pressed, the pedal travel of the target pedal can be determined. The pedal travel of the target pedal can be obtained by using a sensor.

[0053] Then, the driving device can determine the target control force corresponding to the current aggressiveness value and current pedal travel based on the relationship between the aggressiveness value, pedal travel, and the control force of the driving device. The driving device can have a pre-defined relationship between different pedal travels and different control forces, which can be calibrated during the testing process. The driving device can then use this relationship to determine the control force corresponding to the current pedal travel, which serves as the standard control force. The standard control force can be understood as the control force corresponding to the lowest aggressiveness (the driving device is in an aggressive driving state 0 times, i.e., a normal driving state).

[0054] Simultaneously, the driving device can determine the control force corresponding to the current pedal travel at a preset maximum aggression level, and use this control force as the maximum control force corresponding to the current pedal travel. Then, it can determine the difference between the maximum control force and the standard control force, and based on this difference and the current aggression level, further determine the target control force corresponding to the current aggression level of the driving device and the current pedal travel, such as... Figure 4 As shown.

[0055] Figure 4 This is a schematic diagram of a control method for a driving device provided in this application.

[0056] Figure 4 The curves showing the relationship between brake pedal travel and braking force at corresponding aggressiveness levels are presented. Figure 4 As can be seen, the aggression level value can range from 0 to 1. An aggression level value of 0 indicates that the driving device has been in an aggressive driving state 0 times (i.e., normal driving), while an aggression level value of 1 indicates that the driving device is at its maximum aggression level. The driving device can determine the standard control force corresponding to the current brake pedal travel when the aggression level value is 0. Furthermore, it can be determined that when the aggression level is 1, the maximum control force corresponding to the current brake pedal travel is [value missing]. and determine the standard control force. and maximum control The difference between the target control force and the standard control force. When the aggression level is 0.5, the target control force is equal to the standard control force. The difference is the standard control force. and maximum control 0.5 times the difference.

[0057] In addition, after determining the standard control force and maximum control After calculating the difference, for the case where the aggression level is 0.5, the target control force can also be determined by the standard control force. The result is obtained by summing the difference with 0.5 times the difference.

[0058] It should be noted that the target pedal mentioned in the above process can also be the accelerator pedal. Therefore, the driving device can also determine the target traction force (i.e., target control force) corresponding to the current pedal travel under the aggressive driving state corresponding to the current aggressive level value based on the determined aggression level value and the standard traction force (i.e., standard control force) corresponding to the pedal travel, and then control the driving device based on the target traction force.

[0059] S106: Control the driving device according to the target control force.

[0060] After determining the target control force, the driving equipment can determine the control signal and control the driving equipment according to the control signal.

[0061] Therefore, it can be seen that the method in this application, during the control of the driving device, can determine the aggression level of the driving device based on driving status data. Furthermore, it can combine the various factors reflected in the user's driving process by the aggression level value to control the driving device, avoiding the situation where current control systems of new energy vehicles can only apply control force based on the depth of a specified pedal being pressed. That is, the method in this application can identify the driver's driving habits based on the aggression level of the driving device without increasing hardware costs, and significantly improve the braking characteristics of the driving device based on the identified driving habits. Therefore, it greatly increases the accuracy of driving device control and the safety of the driving device during operation.

[0062] Furthermore, by controlling itself through the degree of aggression, the driving equipment can significantly reduce the occurrence of rapid acceleration or deceleration, thereby further reducing energy loss caused by rapid acceleration or deceleration and lowering the operating cost of the driving equipment.

[0063] This application also provides a control system for a driving device. This system may include sensors installed on the driving device, a vehicle control unit, an onboard communication unit, and a brake controller. Therefore, the control methods described above can actually be implemented by various units and controllers within this system. The process of implementing the above control methods through this system is as follows: Figure 5 As shown.

[0064] Figure 5 This is a schematic diagram illustrating the control of the driving equipment through the control system of the driving equipment, as provided in this application.

[0065] exist Figure 5 In this system, the control of the driving equipment can be coordinated by sensors, vehicle control units, on-board communication units, and brake controllers. Sensors in this system can include devices such as GNSS, lidar, IMU, and cameras. The vehicle control unit is mainly used to analyze the collected driving status data; therefore, the vehicle control unit can specifically be a vehicle control unit (VCU). The on-board communication unit mainly sends the data analysis results from the vehicle control unit to the cloud platform; that is, the on-board communication unit is mainly used to send data to and receive data from the cloud platform. Therefore, the on-board communication unit can specifically be a telematics box (T-BOX). The brake controller, after determining the target control force, outputs the control force to complete the control of the driving equipment. The brake controller can specifically be an electromechanical brake (EMB).

[0066] Therefore, from Figure 5 It can be seen that during the driving process, the sensors on the driving device can send the driving status data collected by the driving device to the vehicle control unit. Then, the vehicle control unit can determine the number of times the driving device is in an aggressive driving state based on the received driving status data.

[0067] The vehicle control unit can send the number of times the driving equipment has entered an aggressive driving state during operation to the cloud platform via the onboard communication unit. The cloud platform can then determine the level of aggression based on the number of times the driving equipment has entered an aggressive state and return this level of aggression to the driving equipment. Specifically, the cloud platform can return the level of aggression to the driving equipment via Over-the-Air (OTA) technology. After receiving the level of aggression value from the cloud platform, the driving equipment can transmit it to the brake controller via methods such as Controller Area Network (CAN) bus or Local Interconnect Network (LIN) bus.

[0068] Once the aggressiveness of the driving device is determined, the brake controller detects that the target pedal in the driving device is pressed. It can determine the pedal travel of the target pedal, and based on the difference between the standard control force determined by the relationship between the pedal travel and the control force of the driving device and the maximum control force corresponding to the current pressing force under the preset maximum aggressiveness, as well as the current aggressiveness value, it can determine the target control force corresponding to the current aggressiveness value of the driving device and the current pedal travel, thereby controlling the driving device.

[0069] The brake controller also includes a wheel braking module, which is used to brake the driving equipment. Figure 6 As shown.

[0070] Figure 6 This is a schematic diagram of a brake controller used in this application to control driving equipment.

[0071] Depend on Figure 6 As can be seen, when the brake controller receives a position signal from a sensor located at the brake pedal position, it can process and analyze the signal to determine the pedal travel. Then, based on this pedal travel, the brake controller sends a braking request command to the wheel braking module of the driving device. The wheel braking module can then adjust the braking torque to brake the driving device.

[0072] The above describes a control method for a driving device through one or more embodiments. Based on the same concept, this application also provides a corresponding control device for a driving device, such as... Figure 7 As shown.

[0073] Figure 7 A schematic diagram of a control device for a driving device provided in this application includes: The acquisition module 701 is used to acquire driving status data of the driving equipment during driving; The first determining module 702 is used to determine the number of times the driving device is in an aggressive driving state during driving based on the driving state data; The second determining module 703 is used to determine the degree of aggression of the driving device based on the number of times the driving device is in an aggressive driving state; The monitoring module 704 is used to determine the pedal travel of the target pedal when it is detected that the target pedal in the driving device is being pressed. The third determining module 705 is used to determine the target control force corresponding to the current aggressiveness value and the current pedal travel of the driving device based on the relationship between the aggressiveness value, the pedal travel and the control force of the driving device. The control module 706 is used to control the driving device according to the target control force.

[0074] Optionally, the aggressive driving state includes a rapid acceleration driving state and a rapid deceleration driving state; The second determining module 703 is specifically used to determine the degree of rapid acceleration of the driving device based on the number of times the driving device is in a state of rapid acceleration, and to determine the degree of rapid deceleration of the driving device based on the number of times the driving device is in a state of rapid deceleration; and to determine the degree of aggression of the driving device based on the degree of rapid acceleration and the degree of rapid deceleration.

[0075] Optionally, the second determining module 703 is specifically used to send the number of times the driving device is in a rapid acceleration state and the number of times it is in a rapid deceleration state to the cloud platform, so that the cloud platform determines a rapid acceleration state sequence based on the number of times the driving device is in a rapid acceleration state and the number of times other driving devices are in a rapid acceleration state, and determines a rapid deceleration state sequence based on the number of times the driving device is in a rapid deceleration state and the number of times other driving devices are in a rapid deceleration state, and determines the rapid acceleration degree value of the driving device based on the rapid acceleration state sequence, and determines the rapid deceleration degree value of the driving device based on the rapid deceleration state sequence.

[0076] Optionally, the second determining module 703 is specifically used to: determine the average number of times the driving device is in a rapid acceleration driving state and the number of times other driving devices are in a rapid acceleration driving state, as a first average number; and sort the driving device and other driving devices included in the cloud platform in sequence according to the difference between the number of times the driving device is in a rapid acceleration driving state and the first average number, and the difference between the number of times other driving devices are in a rapid acceleration driving state and the first average number, so as to obtain a rapid acceleration driving state sequence.

[0077] Optionally, the second determining module 703 is specifically used to: determine the average number of times the driving device is in a rapid deceleration state and the number of times the other driving devices are in a rapid deceleration state, as a second average number; and sort the driving device and the other driving devices in sequence according to the difference between the number of times the driving device is in a rapid deceleration state and the second average number, and the difference between the number of times the other driving devices are in a rapid deceleration state and the second average number, so as to obtain a rapid deceleration state sequence.

[0078] Optionally, the second determining module 703 is specifically used to determine the rapid acceleration weight and the rapid deceleration weight; and to weight the rapid acceleration degree value and the rapid deceleration degree value according to the rapid acceleration weight and the rapid deceleration weight to obtain the aggressiveness value of the driving device.

[0079] Optionally, the third determining module 705 is specifically used to: determine the control force corresponding to the pedal travel at a preset maximum aggressiveness level, as the maximum control force corresponding to the pedaling force; and determine the standard control force corresponding to the pedal travel based on the relationship between the pedal travel and the control force of the driving device; and determine the target control force corresponding to the current aggressiveness value of the driving device and the current pedal travel based on the maximum control force and the standard control force.

[0080] Optionally, the third determining module 705 is specifically used to determine the difference between the maximum control force and the standard control force; and based on the difference and the current aggression value, determine the target control force corresponding to the current aggression value of the driving device and the current pedal travel.

[0081] Optionally, the first determining module 702 is specifically used to: determine the probability distribution of the acceleration value of the driving device during driving based on the driving state data; determine the driving acceleration threshold based on the probability distribution; and determine the number of times the driving device is in an aggressive driving state during driving based on the driving acceleration threshold and the driving state data.

[0082] This application also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 A driving equipment control method is provided.

[0083] This application also provides Figure 8 The one shown corresponds to Figure 1 A schematic diagram of the driving equipment. (See attached diagram.) Figure 8 As shown, at the hardware level, this electronic device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above. Figure 1 The control method for the driving equipment.

[0084] Of course, in addition to software implementation, this application does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. In other words, the execution subject of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0085] In the 1990s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many methodological improvements today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that a methodological improvement cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0086] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0087] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0088] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0089] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0090] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0091] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0092] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0093] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0094] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0095] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0096] It should also be noted that 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. Without further limitation, 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 said element.

[0097] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0098] This application can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0099] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0100] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A control method for a driving device, characterized in that, include: The driving status data of the driving equipment during the driving process is obtained by using short-period sampling or long-period sampling methods; Based on the driving status data, determine the number of times the driving device is in an aggressive driving state during driving; The degree of aggression for the driving device is determined based on the number of times the driving device is in an aggressive driving state; When the target pedal in the driving device is detected to be pressed, the pedal travel of the target pedal is determined; The control force corresponding to the pedal travel at a preset maximum aggressive level is determined as the maximum control force corresponding to the current pedal force, and the standard control force corresponding to the pedal travel is determined based on the relationship between the pedal travel and the control force of the driving device. Based on the maximum control force and the standard control force, a target control force corresponding to the current aggressiveness value of the driving device and the current pedal travel is determined; The driving device is controlled according to the target control force.

2. The method as described in claim 1, characterized in that, The aggressive driving state includes rapid acceleration driving state and rapid deceleration driving state; The degree of aggression for the driving device is determined based on the number of times the driving device is in an aggressive driving state, specifically including: The degree of rapid acceleration of the driving device is determined based on the number of times the driving device is in a state of rapid acceleration, and the degree of rapid deceleration of the driving device is determined based on the number of times the driving device is in a state of rapid deceleration. The aggressiveness value of the driving device is determined based on the rapid acceleration value and the rapid deceleration value.

3. The method as described in claim 2, characterized in that, The degree of rapid acceleration of the driving device is determined based on the number of times the driving device is in a state of rapid acceleration, and the degree of rapid deceleration of the driving device is determined based on the number of times the driving device is in a state of rapid deceleration, specifically including: The number of times the driving device was in a rapid acceleration state and the number of times it was in a rapid deceleration state are sent to the cloud platform. The cloud platform then determines a rapid acceleration state sequence based on the number of times the driving device was in a rapid acceleration state and the number of times other driving devices were in a rapid acceleration state. It also determines a rapid deceleration state sequence based on the number of times the driving device was in a rapid deceleration state and the number of times other driving devices were in a rapid deceleration state. Finally, the cloud platform determines the degree of rapid acceleration and the degree of rapid deceleration of the driving device based on the rapid acceleration state sequence.

4. The method as described in claim 3, characterized in that, Based on the number of times the driving device is in a rapid acceleration driving state and the number of times other driving devices are in a rapid acceleration driving state, a rapid acceleration driving state sequence is determined, specifically including: The average number of times the driving device was in a state of rapid acceleration and the average number of times the other driving devices were in a state of rapid acceleration was determined as the first average number. Based on the difference between the number of times the driving device is in a rapid acceleration state and the first average number of times, and the difference between the number of times the other driving devices are in a rapid acceleration state and the first average number of times, the driving device and the other driving devices included in the cloud platform are sorted in sequence to obtain a rapid acceleration state sequence.

5. The method as described in claim 3, characterized in that, Based on the number of times the driving device and other driving devices were in a state of rapid deceleration, a sequence of rapid deceleration states was determined, specifically including: The average number of times the driving device was in a state of rapid deceleration and the average number of times the other driving devices were in a state of rapid deceleration is determined as the second average number; Based on the difference between the number of times the driving device was in a rapid deceleration state and the second average number of times, and the difference between the number of times the other driving devices were in a rapid deceleration state and the second average number of times, the driving device and the other driving devices were sorted in sequence to obtain a rapid deceleration state sequence.

6. The method as described in claim 2, characterized in that, The aggressiveness value of the driving device is determined based on the acceleration and deceleration values, specifically including: Determine the weights for rapid acceleration and rapid deceleration; The acceleration and deceleration values ​​are weighted according to the acceleration weight and deceleration weight to obtain the aggressiveness value of the driving device.

7. The method as described in claim 1, characterized in that, Based on the maximum control force and the standard control force, a target control force corresponding to the current aggression level of the driving device and the current pedal travel is determined, specifically including: Determine the difference between the maximum control force and the standard control force; Based on the difference and the current aggression level, a target control force corresponding to the current aggression level of the driving device and the current pedal travel is determined.

8. The method as described in claim 1, characterized in that, Based on the driving status data, determine the number of times the driving device is in an aggressive driving state during driving, specifically including: Based on the driving status data, determine the probability distribution of the acceleration value of the driving device during driving; Based on the probability distribution, determine the driving acceleration threshold; Based on the driving acceleration threshold and the driving status data, determine the number of times the driving device is in an aggressive driving state during driving.

9. A control system for a driving device, characterized in that, The system includes sensors, a vehicle control unit, an onboard communication unit, and a brake controller installed on the driving equipment; The sensor is used to collect driving status data of the driving device during driving by means of short-period sampling or long-period sampling. The vehicle control unit is used to receive the driving status data collected by the sensor, and determine the number of times the driving device is in an aggressive driving state during driving based on the driving status data; The vehicle communication unit is used to send the number of times the driving device is in an aggressive driving state during driving, as determined by the vehicle control unit, to the cloud platform, so that the cloud platform can determine the degree of aggression for the driving device based on the number of times the driving device is in an aggressive driving state, and return it to the driving device. The brake controller is used to determine the pedal travel of the target pedal when it is detected that the target pedal in the driving device is pressed, determine the control force corresponding to the pedal travel at a preset maximum aggressive level as the maximum control force corresponding to the current pressing force, and determine the standard control force corresponding to the pedal travel based on the relationship between the pedal travel and the control force of the driving device. Based on the maximum control force and the standard control force, a target control force corresponding to the current aggressiveness value of the driving device and the current pedal travel is determined.

10. A control device for a driving system, characterized in that, include: Acquisition module: Used to acquire driving status data of the driving equipment during driving; First determining module: used to determine the number of times the driving device is in an aggressive driving state during driving based on the driving state data; The second determining module is used to determine the degree of aggression of the driving device based on the number of times the driving device is in an aggressive driving state. Monitoring module: used to determine the pedal travel of the target pedal when the target pedal in the driving device is detected to be pressed; The third determining module is used to determine the control force corresponding to the pedal travel at a preset maximum aggressive level, as the maximum control force corresponding to the current pedaling force, and to determine the standard control force corresponding to the pedal travel based on the relationship between the pedal travel and the control force of the driving device. Based on the maximum control force and the standard control force, a target control force corresponding to the current aggressiveness value of the driving device and the current pedal travel is determined; Control module: Used to control the driving equipment according to the target control force.

11. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method described in any one of claims 1 to 8.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method described in any one of claims 1 to 8.

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