A control strategy method, device, storage medium and vehicle

Abstract

The application discloses a vehicle speed control method and device, a storage medium and a vehicle, and relates to the technical field of automatic driving control, and comprises the following steps: determining a driving behavior type of a user according to historical driving data of the user; determining an optimal vehicle speed and a vehicle speed control starting point according to current road information, vehicle condition information, weather information and the driving behavior type; determining a vehicle speed control strategy according to the optimal vehicle speed and a current driving vehicle speed; and controlling the current driving vehicle speed according to the vehicle speed control starting point and the vehicle speed control strategy. The application has high matching degrees for all road conditions, conforms to the driving behavior habits of users, can be compatible with multiple working conditions such as an empty vehicle, a full load, different tires, high and low adhesion road surfaces, can work stably in all scenes, can reduce the occupation of vehicle machine resources through layered calculation and on-demand triggering, can improve system fluency, and can realize linear smooth acceleration and deceleration without sudden braking and jerk.

Description

Technical Field

[0001] This invention relates to the field of autonomous driving control technology, and in particular to vehicle speed control methods, vehicle speed control devices, storage media, and vehicles. Background Technology

[0002] Current autonomous driving and adaptive cruise control technologies generally rely on road speed limits, distance to the vehicle ahead, and traffic signals as core control criteria, failing to establish a three-dimensional, scenario-based decision-making system that integrates road geometry, vehicle status, and weather conditions. However, the current scenario-based decision-making system has significant shortcomings: First, the vehicle's speed control logic is simplistic, failing to consider factors such as road slope, curvature, inclination, vehicle weight, tire friction, and weather conditions. Speed ​​control is unreasonable when cornering, going uphill or downhill, or on slippery surfaces, resulting in poor ride smoothness. Furthermore, the optimal deceleration starting position is not calculated in advance, leading to inaccurate acceleration and deceleration timing. Deceleration is only implemented near speed limit changes or curves, easily causing sudden braking and jerking, resulting in insufficient safety and comfort.

[0003] Secondly, using the same set of control parameters for empty, fully loaded, dry, wet, slippery, and icy / snowy roads lacks the ability to adapt to load and road conditions, easily leading to insufficient braking distance, vehicle skidding, and the risk of tilting. It only executes control commands in one direction, without collecting user facial expressions, body language, or voice feedback, lacking user perception and iteration mechanisms, making it impossible to optimize control strategies, resulting in a rigid experience that doesn't align with user habits.

[0004] Furthermore, the system only provides text or simple voice prompts, lacking multimodal confirmation and satisfaction perception, resulting in a poor human-computer interaction experience. It also lacks hierarchical computing logic, continuing high-frequency routing during computationally demanding periods such as vehicle start-up, turning, and lane changes, leading to unreasonable system resource consumption and potential system lag. Summary of the Invention

[0005] The purpose of this invention is to provide a vehicle speed control method, vehicle speed control device, electronic device, storage medium, and vehicle, which at least solves the following technical problems: the lack of integration of road, vehicle condition, and weather information in autonomous driving speed control; inaccurate acceleration and deceleration timing; unstable braking or acceleration; strong driving jerks; safety issues related to incompatible control strategies under different loads, tires, and weather conditions; lack of user feedback, self-learning, and the inability to iteratively optimize control strategies; limited interaction in vehicle speed control and inability to perceive user satisfaction and driving expectations; and high computational power consumption and unsmooth system operation in vehicle speed control algorithms.

[0006] This invention provides the following solution: According to one aspect of the present invention, a vehicle speed control method is provided, comprising: Determine the user's driving behavior type based on their historical driving data; Based on current road information, vehicle condition information, weather information, and the driving behavior type, determine the optimal vehicle speed and the starting point for vehicle speed control; Based on the optimal vehicle speed and the current vehicle speed, a vehicle speed control strategy is determined; The current driving speed is controlled according to the vehicle speed control start point and the vehicle speed control strategy.

[0007] Preferably, determining the user's driving behavior type based on the user's historical driving data includes: Based on the user's historical driving data, determine the user's normal driving speed preference, speed control timing preference, and speed control smoothness preference for each driving scenario; Based on the preferred normal driving speed, the preferred timing of speed control, and the preferred smoothness of speed control, and combined with the corresponding judgment weights, the driving behavior type is determined, and the correspondence between the driving behavior type and the driving scenario is determined. Based on the current driving scenario and the corresponding relationship, the user's current driving behavior type is determined.

[0008] Preferably, determining the optimal vehicle speed and speed control starting point based on current road information, vehicle condition information, weather information, and the user's driving behavior type includes: Determine the driving behavior coefficient based on the driving behavior type; Based on the road information, vehicle condition information, and weather information, determine the basic speed limit, gradient correction coefficient, curvature correction coefficient, inclination correction coefficient, and weather correction coefficient. The optimal vehicle speed is determined based on the base speed limit, the slope correction coefficient, the curvature correction coefficient, the tilt correction coefficient, the driving behavior coefficient, and the weather correction coefficient. The tire friction coefficient and load correction coefficient are determined based on the vehicle condition information, and the vehicle speed control starting point is determined based on the tire friction coefficient, the load correction coefficient, and the road information.

[0009] Preferably, determining the vehicle speed control strategy based on the optimal vehicle speed and the current vehicle speed includes: In response to the optimal vehicle speed being greater than the sum of the current vehicle speed and the set error, an acceleration control strategy is determined; or In response to the optimal vehicle speed being less than the difference between the current vehicle speed and the set error, a deceleration control strategy is determined; or In response to the absolute value of the optimal vehicle speed and the current vehicle speed being less than or equal to the set error, a vehicle speed maintenance control strategy is determined.

[0010] Preferably, controlling the current vehicle speed based on the vehicle speed control start point and the vehicle speed control strategy includes: The acceleration is controlled within a preset acceleration threshold, and the acceleration control strategy is executed based on the vehicle speed control start point. or The deceleration is controlled within a preset deceleration threshold, and the deceleration control strategy is executed based on the vehicle speed control start point. or The vehicle speed fluctuation range is controlled within a set error range, and a speed maintenance control strategy is implemented.

[0011] Preferably, after controlling the current vehicle speed based on the vehicle speed control start point and the vehicle speed control strategy, the method further includes: The user's status is determined based on their facial expressions, body language, voice feedback, and operation commands. If the user's status is satisfactory, the determination parameters for the driving behavior type are fixed. If the user's state is unsatisfied, adjust the judgment weight of the driving behavior type, redetermine the optimal vehicle speed and the vehicle speed control start point, until the user's state is satisfied, and then solidify the judgment parameters of the driving behavior type.

[0012] Preferably, the method further includes: The system provides users with feedback on the vehicle speed control start point and the vehicle speed control strategy via voice.

[0013] According to a second aspect of the present invention, a control strategy device is provided, comprising: The determination module is used to determine the user's driving behavior type based on the user's historical driving data; The vehicle speed determination module is used to determine the optimal vehicle speed and the starting point of vehicle speed control based on the current road information, vehicle condition information, weather information and the driving behavior type. The strategy determination module is used to determine the vehicle speed control strategy based on the optimal vehicle speed and the current vehicle speed; The vehicle speed control module is used to control the current driving speed according to the vehicle speed control start point and the vehicle speed control strategy.

[0014] According to three aspects of the present invention, an electronic device is provided, comprising: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of the vehicle speed control method.

[0015] According to four aspects of the present invention, a computer-readable storage medium is provided, comprising: storing a computer program executable by an electronic device, wherein when the computer program is run on the electronic device, the electronic device performs the steps of a vehicle speed control method.

[0016] According to five aspects of the present invention, a vehicle is provided, comprising: Electronic equipment used to implement vehicle speed control methods; The processor runs a program, and when the program runs, it executes the steps of the vehicle speed control method based on data output from the electronic device. Storage medium used to store programs that, when running, execute steps of a vehicle speed control method based on data output from electronic devices.

[0017] The above solution achieves the following beneficial technical effects: This invention determines the optimal vehicle speed and speed control start point by using current road information, vehicle condition information, weather information, and the type of driving behavior. It has a high degree of matching across all road conditions, conforms to the user's driving habits, and is compatible with various working conditions such as empty vehicle, fully loaded vehicle, different tires, and uneven road surfaces, and works stably in all scenarios.

[0018] This invention controls the current vehicle speed by describing the vehicle speed control start point and vehicle speed control strategy. It performs layered calculations and triggers on demand, reducing the consumption of vehicle system resources, improving system smoothness, and also achieving linear and smooth acceleration and deceleration without sudden braking or jerking. Attached Figure Description

[0019] Figure 1 This is a flowchart of a vehicle speed control method provided by one or more embodiments of the present invention.

[0020] Figure 2 This is a schematic diagram of a vehicle speed control framework provided in a specific embodiment of the present invention.

[0021] Figure 3 This is a structural diagram of a vehicle speed control device provided in one or more embodiments of the present invention.

[0022] Figure 4 This is a block diagram of an electronic device structure for a vehicle speed control method provided in one or more embodiments of the present invention. Detailed Implementation

[0023] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Figure 1 This is a flowchart of a vehicle speed control method provided by one or more embodiments of the present invention.

[0025] like Figure 1 The speed control methods shown include: Step S1: Determine the user's driving behavior type based on the user's historical driving data.

[0026] Among them, driving behavior types include aggressive, stable, and conservative.

[0027] Furthermore, based on users' historical driving data, the system determines users' preferred normal driving speed, speed control timing, and speed control smoothness for each driving scenario. Based on these preferences, along with their corresponding weights, the system determines the driving behavior type and the correspondence between driving behavior types and driving scenarios.

[0028] If a user's historical driving speed is higher than the first percentage threshold of the predicted optimal speed, then the user's driving behavior type is determined to be aggressive in this driving scenario.

[0029] If a user's historical driving speed is lower than the second percentage threshold of the predicted optimal speed, then the user's driving behavior type is determined to be robust in this driving scenario.

[0030] If the percentage difference between a user's historical driving speed and the predicted optimal speed falls between the first percentage threshold and the second percentage threshold, then the user's driving behavior type is determined to be stable in this driving scenario.

[0031] The first percentage threshold can be 5%, and the second percentage threshold can be 3%.

[0032] Step S2: Determine the optimal vehicle speed and the starting point for vehicle speed control based on the current road information, vehicle condition information, weather information, and driving behavior type.

[0033] The current road information includes the following: Road surface slope (uphill or downhill, unit: °); Road curvature (related to curve radius, unit: m) - ¹); Road surface inclination (superelevation, unit: °); Current road speed limit (V_limit_cur); The speed limit for the next road segment (V_limit_next).

[0034] The current vehicle condition information includes the following: Current vehicle speed (V_cur); Gross vehicle weight (including load capacity, in meters). Tire-road friction coefficient (f); The vehicle's current power and braking status.

[0035] The current weather information includes the following: Weather type (cloud data): Sunny, Light rain, Moderate rain, Heavy rain, Light snow, Moderate snow, Heavy snow, Icy Road surface condition (visual recognition): dry, slippery, snow-covered, icy.

[0036] Furthermore, by combining the above road information, vehicle condition information, weather information, and driving behavior type, the optimal vehicle speed and the starting point for vehicle speed control are determined.

[0037] Step S3: Determine the vehicle speed control strategy based on the optimal vehicle speed and the current vehicle speed.

[0038] The vehicle speed control strategy includes acceleration control strategy, deceleration control strategy, and speed maintenance control strategy.

[0039] Furthermore, if the optimal vehicle speed is greater than the sum of the current vehicle speed and the set error, an acceleration control strategy is determined, i.e., V_opt > V_cur + 1 km / h, corresponding to a smooth acceleration strategy. Here, V_opt represents the optimal vehicle speed, V_cur represents the current vehicle speed, and the set error can be 1 km / h.

[0040] If the optimal vehicle speed is less than the difference between the current vehicle speed and the set error, a deceleration control strategy is determined, i.e., V_opt < V_cur – 1 km / h, which corresponds to a smooth deceleration strategy.

[0041] If the absolute value of the optimal vehicle speed and the current vehicle speed is less than or equal to the set error, a speed maintenance control strategy is determined, i.e., |V_opt – V_cur|≤1km / h, which corresponds to the speed maintenance strategy.

[0042] Step S4: Control the current vehicle speed according to the vehicle speed control start point and vehicle speed control strategy.

[0043] Figure 2 This is a schematic diagram of a vehicle speed control framework provided in a specific embodiment of the present invention. Figure 2 As shown, in conjunction with the above implementation of the vehicle speed control strategy, if the vehicle speed control strategy is determined to be an acceleration control strategy, the acceleration is controlled within a preset acceleration threshold (acceleration less than or equal to the preset acceleration threshold). Based on the starting point of vehicle speed control, the acceleration control strategy is executed. The preset acceleration threshold can be 0.2g, at which point there is no feeling of being pushed back into the seat during acceleration.

[0044] If the vehicle speed control strategy is determined to be a deceleration control strategy, the deceleration will be controlled within a preset deceleration threshold (deceleration less than or equal to the deceleration threshold). During the deceleration process, hydraulic braking will be gently intervened, and the deceleration control strategy will be executed based on the starting point of vehicle speed control. The preset deceleration threshold can be 0.25g.

[0045] If the vehicle speed control strategy is determined to be a speed maintenance strategy, the speed fluctuation range of the current driving speed is controlled within a set error range, and the speed maintenance strategy is executed. The set error range can be 1 km / h, or ±1 km / h.

[0046] The implementation method for determining the optimal vehicle speed and the starting point of vehicle speed control is as follows.

[0047] Based on the determined driving behavior type, the corresponding driving behavior coefficient is determined. For example, if the driving behavior type is aggressive, the corresponding driving behavior coefficient is 1.05; if the driving behavior type is moderate, the corresponding driving behavior coefficient is 1; and if the driving behavior type is conservative, the corresponding driving behavior coefficient is 0.95.

[0048] Furthermore, based on road information, vehicle condition information, and weather information, the basic speed limit, gradient correction factor, curvature correction factor, inclination correction factor, and weather correction factor are determined.

[0049] The base speed limit is V_base, where V_base = min(V_limit_cur, V_limit_next), V_limit_cur represents the speed limit of the current road segment, and V_limit_next represents the speed limit of the next road segment.

[0050] The slope correction factor is K_slope, K_slope=1–|slope|×0.12 (reduce power demand uphill and strictly control speed downhill).

[0051] The curvature correction factor is K_curve, K_curve = 1 – curvature × 0.18 (sharp bends significantly reduce vehicle speed).

[0052] The tilt correction factor is K_incline, K_incline=1–|inner and outer tilt deviation|×0.06 (appropriate speed reduction to prevent roll when tilt is insufficient).

[0053] The weather friction correction factor is K_weather.

[0054] The weather friction correction factor is determined based on the current road surface conditions.

[0055] For example, if the road surface is dry and the weather is sunny or drizzling, the corresponding weather friction correction factor is 1.00.

[0056] If the road surface is currently slippery, and the weather is sunny or light rain, the corresponding weather friction correction coefficient is 0.90; if the weather is moderate rain, the corresponding weather friction correction coefficient is 0.80; and if the weather is heavy rain, the corresponding weather friction correction coefficient is 0.70.

[0057] If there is snow on the road surface and the weather is light snow, the corresponding weather friction correction coefficient is 0.60; if the weather is moderate snow, the corresponding weather friction correction coefficient is 0.55; if the weather is heavy snow, the corresponding weather friction correction coefficient is 0.50.

[0058] If the road surface is currently icy, the corresponding weather friction correction factor is 0.40, regardless of the previous weather information.

[0059] Furthermore, according to the optimal vehicle speed calculation formula: V_opt = V_base × (K_slope) K_curve K_incline K_weather) H determines the current optimal vehicle speed.

[0060] Furthermore, the tire friction coefficient and load correction coefficient are determined based on vehicle condition information, and the starting point for vehicle speed control is determined based on the tire friction coefficient, load correction coefficient, and road information.

[0061] Taking the vehicle speed control strategy as the deceleration control strategy as an example, the deceleration starting point is calculated based on the following implementation method.

[0062] The safe and smooth deceleration distance is S, where S = (V_cur² – V_opt²) / (2 × g × f × K_load), g represents the gravitational acceleration, taken as 9.81 m / s², f represents the tire friction coefficient (determined according to vehicle calibration), and K_load represents the load correction coefficient.

[0063] For example, when the vehicle is empty, the load correction factor is 1.00; when the vehicle is half-loaded, the load correction factor is 1.10; and when the vehicle is fully loaded, the load correction factor is 1.25.

[0064] In this embodiment, the user's state can also be determined based on the user's facial expressions, body movements, voice feedback, and operation commands, so as to determine the user's satisfaction level with the corresponding vehicle speed control result.

[0065] The user's facial expression can be one of tension, relaxation, satisfaction, or dissatisfaction. The user's body movements can be one or more of the following: sitting posture, gripping the armrest, leaning forward, or leaning back. The user's voice feedback can be "too fast," "too slow," "braking too suddenly," or "very smooth." The user's operation commands can be pressing the brake pedal, pressing the accelerator pedal, etc.

[0066] If the user's facial expression is relaxed or satisfied, there are no abnormal body movements, and the speech is positive, then it is determined to be positive feedback from the user, indicating that the user's state is satisfied. At this time, the judgment parameters for the driving behavior type are fixed.

[0067] If the user's facial expression is tense or dissatisfied, or exhibits abnormal body movements or negative speech, the user's state is determined to be dissatisfied. The judgment weight of the driving behavior type is adjusted, and the optimal vehicle speed and speed control start point are re-determined until the user's state is satisfied. The judgment parameters of the driving behavior type are then fixed.

[0068] Specifically, if the user's expression is tense, indicating the user's psychological state is that deceleration was too late, then the optimal speed is reduced and the deceleration distance S is increased. If the user's expression is dissatisfied, indicating the user's psychological state is also dissatisfied, the optimal speed and speed control starting point are adjusted based on body language and voice feedback. If the user's expression is relaxed or satisfied, indicating the user's psychological state is to remain unchanged, the optimal speed and speed control starting point are not adjusted.

[0069] If the user's body movement is leaning forward, indicating a psychological state of sudden braking or too late deceleration, then reduce the optimal speed and increase the deceleration distance S. If the user's body movement is gripping the steering wheel tightly, indicating a psychological state of too late deceleration, then reduce the optimal speed and increase the deceleration distance S.

[0070] If the user's voice feedback indicates a complaint about decelerating too early, the user's psychological state is determined to be that they are decelerating too early. Therefore, the optimal speed should be increased, and the deceleration distance S shortened. If the user's voice feedback indicates a complaint about decelerating too late, the optimal speed should be decreased, and the deceleration distance S lengthened.

[0071] If the user's command is to brake, and the user's psychological state is that deceleration is too late, then the optimal speed is reduced, and the deceleration distance S is increased. If the user's command is to accelerate, and the user's psychological state is that deceleration is too early, then the optimal speed is increased, and the deceleration distance S is shortened.

[0072] The deceleration distance S is extended or shortened by 10 meters each time until positive feedback from the user's state is detected; if negative psychological activity is detected, the distance is reduced to 5 meters. After three consecutive satisfactory responses, the parameters are fixed as a user-specific strategy.

[0073] For example, the user was dissatisfied when the deceleration started at 160 meters the first time, feeling that the deceleration was too early. The second time, the deceleration was reduced to 150 meters, but the user was still dissatisfied. The third time, the deceleration was reduced to 140 meters, and the user was satisfied, but negative feedback appeared, feeling that the deceleration was too early. The fourth time, the deceleration started at 145 meters, until the user had three consecutive negative feedbacks, and the user-specific parameters were fixed.

[0074] In this embodiment, the vehicle speed control start point and vehicle speed control strategy can be fed back to the user via voice.

[0075] The invention will be explained using a specific driving scenario as an example.

[0076] The vehicle is traveling at 80 km / h, with a sharp left turn 200 meters ahead. The input data includes a curvature of 0.22, a slope of 2°, a tilt deviation of 1°, a current speed limit of 80 km / h, a next speed limit of 60 km / h, a vehicle weight of 2.0 tons (fully loaded), a friction coefficient of 0.85, and a dry, sunny day. The driver is an aggressive type. The optimal speed is calculated as: V_opt = V_base × (K_slope) K_curve K_incline K_weather) H1 (1.05) = 54 km / h.

[0077] Further, the deceleration distance is calculated as follows: S = (V_cur² – V_opt²) / (2 × g × f × K_load); S = 135 meters.

[0078] Finally, the system initiates deceleration 135 meters from the curve, with a voice prompt: "Sharp curve ahead, slowing down smoothly for you." The vehicle decelerates linearly to 54 km / h, safely navigating the curve. Recognizing a relaxed user expression and no physical tension, the system determines satisfaction and fixes the parameters. If the user's voice indicates "a bit rushed," the system will reduce the deceleration and extend the stop (S) to 145 meters the next time. This continues until the user provides three consecutive negative feedbacks.

[0079] Figure 3 This is a structural diagram of a vehicle speed control device provided in one or more embodiments of the present invention.

[0080] like Figure 3 The control strategy device shown includes: a determination module, a vehicle speed determination module, a strategy determination module, and a vehicle speed control module.

[0081] The determination module is used to determine the user's driving behavior type based on the user's historical driving data; The vehicle speed determination module is used to determine the optimal vehicle speed and the starting point of vehicle speed control based on current road information, vehicle condition information, weather information, and driving behavior type. The strategy determination module is used to determine the vehicle speed control strategy based on the optimal vehicle speed and the current vehicle speed. The vehicle speed control module is used to control the current vehicle speed based on the vehicle speed control start point and vehicle speed control strategy.

[0082] The judgment module is used to determine the user's normal driving speed preference, speed control timing preference, and speed control smoothness preference for each driving scenario based on the user's historical driving data; based on the normal driving speed preference, speed control timing preference, and speed control smoothness preference, combined with the corresponding judgment weights, the driving behavior type is determined, and the correspondence between the driving behavior type and the driving scenario is determined; based on the current driving scenario and the correspondence, the user's current driving behavior type is determined.

[0083] The vehicle speed determination module is used to determine driving behavior coefficients based on driving behavior type; determine basic speed limits, slope correction coefficients, curvature correction coefficients, tilt correction coefficients, and weather correction coefficients based on road information, vehicle condition information, and weather information; determine the optimal vehicle speed based on the basic speed limits, slope correction coefficients, curvature correction coefficients, tilt correction coefficients, driving behavior coefficients, and weather correction coefficients; determine tire friction coefficients and load correction coefficients based on vehicle condition information; and determine the starting point for vehicle speed control based on the tire friction coefficients, load correction coefficients, and road information.

[0084] The strategy determination module is used to determine an acceleration control strategy in response to the sum of the optimal vehicle speed and the current vehicle speed and the set error; or, in response to the difference between the optimal vehicle speed and the current vehicle speed and the set error, to determine a deceleration control strategy; or, in response to the absolute value of the optimal vehicle speed and the current vehicle speed being less than or equal to the set error, to determine a speed maintenance control strategy.

[0085] The vehicle speed control module is used to control the acceleration within a preset acceleration threshold and execute an acceleration control strategy based on the vehicle speed control start point; or, to control the deceleration within a preset deceleration threshold and execute a deceleration control strategy based on the vehicle speed control start point; or, to control the vehicle speed fluctuation range within a set error range and execute a speed maintenance control strategy.

[0086] The vehicle speed control module is also used to determine the user's state based on the user's facial expressions, body movements, voice feedback, and operation commands. If the user's state is satisfied, the judgment parameters of the driving behavior type are fixed. If the user's state is dissatisfied, the judgment weight of the driving behavior type is adjusted, and the optimal vehicle speed and vehicle speed control starting point are re-determined until the user's state is satisfied, and the judgment parameters of the driving behavior type are fixed.

[0087] The vehicle speed control module is used to provide users with feedback on the starting point and speed control strategy based on voice commands.

[0088] Figure 4 This is a block diagram of an electronic device structure for a vehicle speed control method provided in one or more embodiments of the present invention.

[0089] like Figure 4 As shown, the present invention provides an electronic device, including: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of a vehicle speed control method.

[0090] The present invention also provides a computer-readable storage medium storing a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of a vehicle speed control method.

[0091] The present invention also provides a vehicle, comprising: Electronic equipment for implementing steps of a vehicle speed-based control method; The processor runs a program, and when the program runs, it executes the steps of the vehicle speed control method based on data output from the electronic device. Storage medium used to store programs that, when running, execute steps of a vehicle speed control method based on data output from electronic devices.

[0092] The communication bus mentioned in the above electronic devices can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0093] The electronic device comprises a hardware layer, an operating system layer running on top of the hardware layer, and an application layer running on the operating system. The hardware layer includes hardware such as a central processing unit (CPU), a memory management unit (MMU), and memory. The operating system can be any one or more computer operating systems that control the electronic device through processes, such as Linux, Unix, Android, iOS, or Windows. Furthermore, in this embodiment of the invention, the electronic device can be a smartphone, tablet computer, or other handheld device, or a desktop computer, portable computer, or other electronic device; there is no particular limitation in this embodiment.

[0094] In this embodiment of the invention, the executing entity for electronic device control can be an electronic device itself, or a functional module within an electronic device capable of calling and executing a program. The electronic device can obtain the firmware corresponding to the storage medium. This firmware is provided by the supplier, and different storage media may have the same or different firmware; no limitation is made here. After obtaining the firmware corresponding to the storage medium, the electronic device can write this firmware into the storage medium; specifically, it burns the firmware corresponding to the storage medium into the storage medium. The process of burning the firmware into the storage medium can be implemented using existing technology, and will not be elaborated upon in this embodiment of the invention.

[0095] Electronic devices can also obtain reset commands corresponding to the storage media. The reset commands corresponding to the storage media are provided by the supplier. The reset commands corresponding to different storage media can be the same or different, and no restrictions are imposed here.

[0096] At this time, the storage medium of the electronic device is a storage medium on which the corresponding firmware has been written. The electronic device can respond to the reset command corresponding to the storage medium on which the corresponding firmware has been written, thereby resetting the storage medium on which the corresponding firmware has been written according to the reset command. The process of resetting the storage medium according to the reset command can be implemented by existing technology and will not be described in detail in this embodiment of the invention.

[0097] For ease of description, the above apparatus is described by dividing it into various units and modules according to their functions. Of course, in implementing this invention, the functions of each unit and module can be implemented in one or more software and / or hardware.

[0098] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the meaning consistent with their meaning in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined.

[0099] For the sake of simplicity, the method embodiments are described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0100] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of the present invention.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A vehicle speed control method, characterized in that, include: Determine the user's driving behavior type based on their historical driving data; Based on current road information, vehicle condition information, weather information, and the driving behavior type, determine the optimal vehicle speed and the starting point for vehicle speed control; Based on the optimal vehicle speed and the current vehicle speed, a vehicle speed control strategy is determined; The current driving speed is controlled according to the vehicle speed control start point and the vehicle speed control strategy.

2. The vehicle speed control method according to claim 1, characterized in that, The process of determining the user's driving behavior type based on the user's historical driving data includes: Based on the user's historical driving data, determine the user's normal driving speed preference, speed control timing preference, and speed control smoothness preference for each driving scenario; Based on the preferred normal driving speed, the preferred timing of speed control, and the preferred smoothness of speed control, and combined with the corresponding judgment weights, the driving behavior type is determined, and the correspondence between the driving behavior type and the driving scenario is determined. Based on the current driving scenario and the corresponding relationship, the user's current driving behavior type is determined.

3. The vehicle speed control method according to claim 2, characterized in that, After controlling the current vehicle speed according to the vehicle speed control start point and the vehicle speed control strategy, the method further includes: The user's status is determined based on their facial expressions, body language, voice feedback, and operation commands. If the user's status is satisfactory, the determination parameters for the driving behavior type are fixed. If the user's state is unsatisfied, adjust the judgment weight of the driving behavior type, redetermine the optimal vehicle speed and the vehicle speed control start point, until the user's state is satisfied, and then solidify the judgment parameters of the driving behavior type.

4. The vehicle speed control method according to claim 1, characterized in that, The process of determining the optimal vehicle speed and speed control start point based on current road information, vehicle condition information, weather information, and the user's driving behavior includes: Determine the driving behavior coefficient based on the driving behavior type; Based on the road information, vehicle condition information, and weather information, determine the basic speed limit, gradient correction coefficient, curvature correction coefficient, inclination correction coefficient, and weather correction coefficient. The optimal vehicle speed is determined based on the base speed limit, the slope correction coefficient, the curvature correction coefficient, the tilt correction coefficient, the driving behavior coefficient, and the weather correction coefficient. The tire friction coefficient and load correction coefficient are determined based on the vehicle condition information, and the vehicle speed control starting point is determined based on the tire friction coefficient, the load correction coefficient, and the road information.

5. The vehicle speed control method according to claim 1, characterized in that, The step of determining the vehicle speed control strategy based on the optimal vehicle speed and the current vehicle speed includes: In response to the optimal vehicle speed being greater than the sum of the current vehicle speed and the set error, an acceleration control strategy is determined; or In response to the optimal vehicle speed being less than the difference between the current vehicle speed and the set error, a deceleration control strategy is determined; or In response to the absolute value of the optimal vehicle speed and the current vehicle speed being less than or equal to the set error, a vehicle speed maintenance control strategy is determined.

6. The vehicle speed control method according to claim 5, characterized in that, The step of controlling the current vehicle speed based on the vehicle speed control start point and the vehicle speed control strategy includes: The acceleration is controlled within a preset acceleration threshold, and the acceleration control strategy is executed based on the vehicle speed control start point. or The deceleration is controlled within a preset deceleration threshold, and the deceleration control strategy is executed based on the vehicle speed control start point. or The vehicle speed fluctuation range is controlled within a set error range, and a speed maintenance control strategy is implemented.

7. The vehicle speed control method according to claim 1, characterized in that, The method further includes: The system provides users with feedback on the vehicle speed control start point and the vehicle speed control strategy via voice.

8. A vehicle speed control device, characterized in that, Controlling vehicle speed using the method according to any one of claims 1-7 includes: The determination module is used to determine the user's driving behavior type based on the user's historical driving data; The vehicle speed determination module is used to determine the optimal vehicle speed and the starting point of vehicle speed control based on the current road information, vehicle condition information, weather information and the driving behavior type. The strategy determination module is used to determine the vehicle speed control strategy based on the optimal vehicle speed and the current vehicle speed; The vehicle speed control module is used to control the current driving speed according to the vehicle speed control start point and the vehicle speed control strategy.

9. A computer-readable storage medium, characterized in that, The device stores a computer program executable by an electronic device, which, when run on the electronic device, causes the electronic device to perform the steps of the vehicle speed control method as described in any one of claims 1 to 7.

10. A vehicle, characterized in that, include: An electronic device for implementing the steps of the vehicle speed control method as described in any one of claims 1 to 7; A processor that runs a program that, when the program is running, performs the steps of the vehicle speed control method as described in any one of claims 1 to 7 from data output by the electronic device. A storage medium for storing a program that, when running, performs the steps of the vehicle speed control method as described in any one of claims 1 to 7 on data output from an electronic device.

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