Optimization method and device for brake control in vehicle cruising process, equipment and medium

Abstract

The invention provides an optimization method, device and equipment for brake control in the vehicle cruising process and a medium, and relates to the technical field of vehicle control. The optimization method comprises the steps that multi-source sensor data collected by a plurality of sensors installed on a main vehicle are obtained; identifying the current driving condition of the host vehicle based on the multi-source sensor data, wherein the driving condition at least comprises a vehicle cut-in condition; and under the condition that the vehicle cut-in working condition is recognized, a braking control strategy corresponding to the vehicle cut-in working condition is executed, so that the electronic stability control system conducts braking operation on the main vehicle based on the braking control strategy. According to the method, the key working condition of vehicle cut-in is introduced and recognized, and therefore the braking strategy of the electronic stability control system is optimized.

Description

Technical Field

[0001] This invention relates to the field of vehicle control technology, and in particular to an optimization method, device, equipment and medium for braking control during vehicle cruise. Background Technology

[0002] With the rapid development of intelligent driving technology, autonomous driving systems are playing an increasingly important role in vehicle control and safety. In existing technologies, autonomous driving systems typically rely on various sensors (such as cameras, radar, lidar, etc.) to acquire information about the surrounding environment and use algorithms to perform real-time analysis and decision-making to achieve functions such as automatic braking, steering, and acceleration of the vehicle.

[0003] In common autonomous driving systems, braking strategies are primarily based on the detection and distance assessment of obstacles ahead. When the system detects an obstacle or vehicle ahead, it calculates the collision risk based on relative speed and distance and triggers corresponding braking operations. However, this conventional braking strategy is typically designed for scenarios involving obstacles traveling in a straight line or relatively stationary obstacles ahead.

[0004] In actual driving, vehicles frequently encounter complex scenarios such as "vehicles cutting in," such as a vehicle in an adjacent lane suddenly changing lanes and entering in front of the vehicle, or a vehicle at an intersection suddenly cutting into the vehicle's path. These scenarios typically occur in sensor blind spots or at the edge of detection range, and due to the dynamic changes of the cutting vehicle, conventional braking strategies often cannot respond in time. Therefore, in special blind spot conditions, existing technologies lack effective braking strategies for complex scenarios such as "vehicles cutting in," which can easily lead to braking delays or insufficient braking, increasing the risk of collisions. Summary of the Invention

[0005] In view of this, the purpose of the present invention is to provide an optimization method, device, equipment and medium for braking control during vehicle cruise, which introduces and identifies the key operating condition of "vehicle cut-in", thereby optimizing the braking strategy of the electronic stability control system.

[0006] In a first aspect, the present invention provides an optimization method for braking control during vehicle cruising, comprising: Acquire multi-source sensor data collected by multiple sensors installed on the main vehicle; The current driving condition of the main vehicle is identified based on multi-source sensor data, and the driving condition includes at least the vehicle entry condition; When a vehicle is detected to be entering a braking situation, the braking control strategy corresponding to the vehicle entering the braking situation is executed, so that the electronic stability control system can brake the main vehicle based on the braking control strategy.

[0007] In one implementation, identifying the current driving condition of the main vehicle based on multi-source sensor data includes: Based on multi-source sensor data, when a target vehicle in an adjacent lane is identified to exhibit lane-changing behavior and the main vehicle exhibits driving state disturbance characteristics, the current driving condition of the main vehicle is determined as the vehicle entry condition.

[0008] In one implementation, the multi-source sensor data includes at least: radar sensor data, camera data, wheel speed sensor data, and yaw rate sensor data; based on the multi-source sensor data, identifying a target vehicle in an adjacent lane exhibiting lane-changing behavior characteristics and the main vehicle exhibiting driving state disturbance characteristics includes: Perform the following operations within the preset time window: Based on radar sensor data, it is determined whether a target vehicle in an adjacent lane is moving in front of the main vehicle at a lateral relative speed greater than a first preset threshold; based on camera data, it is determined whether the target vehicle's turn signal is active; and based on wheel speed sensor data, it is determined whether the relative speed difference between the main vehicle and the target vehicle is greater than a second preset threshold; if all the determination results are yes, it is determined that the target vehicle has lane-changing behavior characteristics. Based on yaw rate sensor data, it is determined whether the main vehicle has a lateral movement trend; if the determination result is yes, it is determined that the main vehicle has driving state disturbance characteristics.

[0009] In one embodiment, the multi-source sensor data further includes steering wheel angle sensor data and brake pedal position sensor data; executing the braking control strategy corresponding to the vehicle engagement condition includes: Apply automatic braking force to the main vehicle; After applying automatic braking force, the driver's intention and its corresponding intensity are identified based on steering wheel angle sensor data and brake pedal position sensor data, and the target braking force is determined based on the automatic braking force, the driver's intention and its corresponding intensity. Apply the target braking force to the main vehicle.

[0010] In one implementation, identifying the driver's intention and its corresponding intensity based on steering wheel angle sensor data and brake pedal position sensor data includes: Upon receiving data from the steering wheel angle sensor and the brake pedal position sensor, the driver's intention is determined to be an active braking intention; Based on data from the brake pedal position sensor, the active braking force, braking duration, and brake pedal opening change rate are determined to determine the intensity of the driver's intention, which is divided into slight deceleration and emergency braking.

[0011] In one implementation, determining the target braking force based on the automatic braking force, the driver's intention, and the corresponding intensity of that intention includes: When the intended braking intensity is emergency braking, the active braking force and the automatic braking force are fused together to obtain the target braking force; When the intention intensity is slight deceleration, if the active braking force is higher than the automatic braking force, the active braking force will be used as the target braking force; if the active braking force is lower than the automatic braking force, the automatic braking force will be used as the target braking force.

[0012] In one implementation, the electronic stability control system performs braking operations on the main vehicle based on a braking control strategy, including: The electronic stability control system applies longitudinal coordinated braking and / or yaw stability correction to the vehicle based on the target braking force.

[0013] Secondly, the present invention also provides an optimization device for braking control during vehicle cruising, comprising: The data acquisition module is used to acquire multi-source sensor data collected by multiple sensors installed on the main vehicle; The driving condition identification module is used to identify the current driving condition of the main vehicle based on multi-source sensor data. The driving condition includes at least the vehicle entry condition. The braking control module is used to execute the braking control strategy corresponding to the vehicle entry condition when the vehicle entry condition is detected, so as to perform braking operation on the main vehicle through the electronic stability control system based on the braking control strategy.

[0014] Thirdly, the present invention also provides an electronic device including a processor and a memory, the memory storing computer-executable instructions executable by the processor, the processor executing the computer-executable instructions to implement any of the methods provided in the first aspect.

[0015] Fourthly, the present invention also provides a computer-readable storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement any of the methods provided in the first aspect.

[0016] This invention provides an optimization method, apparatus, device, and medium for braking control during vehicle cruise. First, it acquires multi-source sensor data collected by multiple sensors installed on the main vehicle. Then, based on the multi-source sensor data, it identifies the current driving condition of the main vehicle, including at least a vehicle entry situation. Finally, upon identifying a vehicle entry situation, it executes the braking control strategy corresponding to that situation, thereby enabling the electronic stability control system to brake the main vehicle based on the braking control strategy. By identifying the specific condition of "vehicle entry," the electronic stability control system can more accurately determine the driver's avoidance intention and the dynamic change trend of the vehicle, and promptly activate the matching braking control strategy in this scenario. Compared to conventional response modes, this invention effectively enhances the vehicle's driving stability and safety under sudden disturbances, avoiding the risk of loss of control due to external disturbances, thus achieving more scenario-adaptive intelligent stability control.

[0017] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention are realized and obtained in accordance with the structures particularly pointed out in the description, claims and drawings.

[0018] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0019] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 A flowchart illustrating an optimization method for braking control during vehicle cruise provided in an embodiment of the present invention; Figure 2 A flowchart illustrating an optimization method for braking control during vehicle cruise under vehicle engagement conditions, provided in an embodiment of the present invention. Figure 3 A schematic diagram of the structure of an optimization device for braking control during vehicle cruise provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. 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.

[0022] Currently, existing vehicle braking control systems still have several problems in terms of driver operation and automatic function coordination. First, when systems such as Adaptive Cruise Control (ACC) or Automatic Emergency Braking (AEB) are triggered, if the driver simultaneously brakes, the system's braking force may overlap or conflict with the driver's input due to insufficient accuracy in recognizing the driver's intent, resulting in insufficient or excessive total braking force, affecting safety and control stability. Second, when switching between different driving conditions, the braking force distribution strategy changes abruptly, causing discontinuous brake pedal feedback and a degraded driving experience. Furthermore, existing systems lack the ability to accurately identify complex traffic scenarios such as "vehicle entry," and do not have targeted braking response strategies, making it difficult to achieve coordinated optimization of safety and comfort.

[0023] Based on this, the present invention provides an optimization method, device, equipment and medium for braking control during vehicle cruise, which introduces and identifies the key operating condition of "vehicle cutting in", thereby optimizing the braking strategy of the electronic stability control system.

[0024] To facilitate understanding of this embodiment, a detailed description of an optimization method for braking control during vehicle cruise, as disclosed in this embodiment of the invention, will be provided first. (See [link to relevant documentation]). Figure 1 The diagram shows a flowchart of an optimization method for braking control during vehicle cruise. The method mainly includes the following steps S102 to S106: Step S102: Obtain multi-source sensor data collected by multiple sensors installed on the main vehicle.

[0025] The multi-source sensor data includes radar sensor data, camera data, wheel speed sensor data, yaw rate sensor data, steering wheel angle sensor data, and brake pedal position sensor data.

[0026] Step S104: Identify the current driving condition of the main vehicle based on multi-source sensor data.

[0027] The driving conditions include at least the vehicle entry condition, which is a driving scenario where a target vehicle in an adjacent lane crosses the lane line and enters the driving lane of the main vehicle, and that target vehicle becomes a potential collision target of the main vehicle. In addition, the driving conditions may also include normal cruise braking conditions and automatic emergency braking conditions.

[0028] In one example, radar sensor data, camera data, wheel speed sensor data, and yaw rate sensor data can be used to identify whether the current driving condition of the main vehicle is a vehicle entry condition.

[0029] Step S106: When a vehicle entry condition is detected, the braking control strategy corresponding to the vehicle entry condition is executed so that the electronic stability control system can brake the main vehicle based on the braking control strategy.

[0030] In one example, automatic braking force is first applied to the main vehicle. After the automatic braking force is applied, the driver's intention and its corresponding intensity are identified based on steering wheel angle sensor data and brake pedal position sensor data. Based on the automatic braking force, the driver's intention and its corresponding intensity, the target braking force is determined, such as using the automatic braking force or active braking force as the target braking force, or using the superposition result of the automatic braking force and active braking force as the target braking force. Then, the target braking force is applied to the main vehicle through the electronic stability control system (ESC).

[0031] The braking control optimization method provided in this invention during vehicle cruise can more accurately judge the driver's avoidance intention and the dynamic change trend of the vehicle by identifying the specific working condition of "vehicle cutting in". In this scenario, the matching braking control strategy is activated in time. Compared with the conventional response mode, this invention effectively enhances the driving stability and safety of the vehicle under sudden interference, avoids the risk of loss of control caused by external disturbances, and thus achieves more scenario-adaptive intelligent stability control.

[0032] For ease of understanding, this embodiment of the invention provides a specific implementation of an optimization method for braking control during vehicle cruise.

[0033] The core of this invention lies in introducing a "vehicle entry" condition recognition module to construct a more refined braking control decision tree, thereby achieving accurate responses to driver intentions and system requirements. Specifically, it includes a condition recognition module, a braking influencing factor analysis module, and a braking control decision and execution module.

[0034] 1) Driving Condition Recognition Module: This module is the decision-making center of the entire control strategy, responsible for real-time monitoring and judgment of the driving scenario the vehicle is in. When the system is in cruise mode, it continuously analyzes data from the vehicle radar, camera, vehicle speed sensor, and brake pedal sensor to identify the following three key driving conditions: Operating Condition A: Normal Cruise Control (ACC): The system smoothly controls the vehicle to decelerate or follow the vehicle ahead based on the preset following distance and the speed of the vehicle in front.

[0035] Condition B: Automatic Emergency Braking (AEB): The system detects a collision risk ahead and needs to take immediate emergency braking measures to avoid danger.

[0036] Condition C: Vehicle Cut-in Condition (New): The system detects that a vehicle cuts into the vehicle's path from the side, or a vehicle in front suddenly changes lanes, requiring avoidance or deceleration.

[0037] 2) Braking Influence Factor Analysis Module: Once the ESC system is detected as needing to intervene in braking, this module will immediately activate to quantitatively analyze the following three key factors to distinguish the driver's braking intentions: Pressure comparison: Compare the magnitudes of active braking pressure and automatic braking pressure.

[0038] Duration: Determines whether the duration of the driver's active braking pressure exceeds a preset threshold.

[0039] Rate of change: Monitors the rate of change of brake pedal opening to determine the urgency of the driver's braking.

[0040] 3) Braking control decision and execution module: Based on the identified operating conditions and analyzed braking influencing factors, this module will execute different braking control strategies to achieve the optimal braking effect.

[0041] For Condition A, Normal Cruise Control (ACC): In this condition, the system prioritizes driving comfort and executes the automatic braking strategy of Adaptive Cruise Control (ACC). When the driver presses the brake pedal, the system determines the braking intention based on the rate of change of pedal opening: if the rate of change exceeds a preset threshold (e.g., 50–70 mm / s), it is considered an emergency deceleration intention, and the system will combine the automatic braking force with the braking force actively applied by the driver to achieve coordinated braking; if it does not exceed the threshold, the system compares the current automatic braking force with the braking force requested by the driver. When the latter is greater, the system exits the automatic braking mode and the driver takes full control of the braking.

[0042] For Condition B, Automatic Emergency Braking (AEB): In this condition, the system prioritizes collision avoidance, and the automatic braking command has the highest priority. The system first triggers automatic emergency braking based on the obstacle detection results ahead. If the driver depresses the brake pedal during this process, the system will compare the braking force applied by the driver with the system's automatic braking force in real time and determine whether the driver is actively intervening. Only when the driver's braking force is continuously greater than the automatic braking force and the duration exceeds a preset threshold (e.g., 400–600 ms) will the system determine it as a valid takeover request and exit automatic braking mode; otherwise, automatic braking continues to ensure the timeliness and reliability of the braking response.

[0043] For scenario C, the vehicle cutting-in scenario: In the event that a nearby vehicle suddenly cuts into the vehicle's path, the system initiates automatic braking to achieve safe avoidance, prioritizing the restoration of longitudinal clearance. When the system detects that the driver has pressed the brake pedal, it analyzes the driver's braking intention in real time: if the brake pedal opening change rate is high and reaches a preset depth, it is determined to be an emergency braking intention, and the system will superimpose the automatic braking force and the driver's requested braking force to achieve a coordinated response; if the change rate is low and the braking force increases slowly, it is considered a slight deceleration intention, and the system dynamically adjusts the control assignment based on the relationship between the automatic and driver braking forces, prioritizing the continuity and smoothness of the braking process. This strategy ensures risk avoidance capabilities while also taking into account driving comfort and natural human-machine collaboration.

[0044] Based on this, the embodiments of the present invention take the vehicle entry condition as an example, see... Figure 2 The flowchart shown is an optimization method for braking control during vehicle cruise under vehicle engagement conditions, including: (a) Identification of vehicle entry conditions.

[0045] In one implementation, when, based on multi-source sensor data, a target vehicle in an adjacent lane is identified as exhibiting lane-changing behavior characteristics and the main vehicle exhibits driving state disturbance characteristics, the current driving condition of the main vehicle is determined as the vehicle entry condition. Specifically, the following operations are performed within a preset time window: (1.1) Based on radar sensor data, determine whether the target vehicle in the adjacent lane is moving in front of the main vehicle at a lateral relative speed greater than a first preset threshold; and based on camera data, determine whether the turn signal of the target vehicle is active; and based on wheel speed sensor data, determine whether the relative speed difference between the main vehicle and the target vehicle is greater than a second preset threshold; if the determination results are all yes, determine that the target vehicle has lane-changing behavior characteristics. (1.2) Based on the yaw rate sensor data, determine whether the main vehicle has a lateral movement trend; if the determination result is yes, determine that the main vehicle has driving state disturbance characteristics.

[0046] In practical applications, the system adopts a multi-sensor fusion scheme to monitor the surrounding traffic environment and the vehicle's status in real time, and comprehensively judge whether there is a sudden driving situation of "vehicle cutting in", so as to provide a decision basis for the subsequent activation of braking control strategy and parameter adjustment. Specifically, the system continuously collects data from multiple onboard sensors: Radar sensors are used to obtain the relative distance, relative speed, and relative acceleration between the vehicle ahead and the vehicle itself. Cameras are used to monitor the lateral displacement trajectories of vehicles in adjacent lanes and identify their turn signal status to predict lane change intentions. Wheel speed sensors are used to detect the rotational speed signals of the four wheels of the vehicle, and combined with filtering processing, calculate the actual driving speed of the vehicle and compare it with the speed of the vehicle in front. Yaw rate sensor is used to sense the vehicle's rotational motion around the vertical axis and help determine whether there is a change in the vehicle's attitude caused by avoidance. Steering wheel angle sensor is used to acquire the driver's steering operation behavior and reflect their intention to adjust the path; Brake pedal position sensor is used to capture in real time the start time of the driver's braking action, pedal opening and its rate of change, in order to identify the intensity of braking intent.

[0047] The aforementioned multi-source information, after being time-synchronized and weighted by confidence, is input into the operating condition recognition module to achieve accurate and robust recognition of "vehicle entry" events.

[0048] The operating condition identification logic is as follows: The system uses multi-source sensor information and preset collaborative judgment rules to identify whether a "vehicle cutting in" situation has occurred. Specifically, the identification conditions include the following: Condition 1: The radar sensor detects that a target vehicle in an adjacent lane is moving toward the lane where the vehicle is located at a lateral relative speed greater than a first preset threshold, and its trajectory is expected to enter the driving area in front of the vehicle within a predetermined distance. Condition 2: The camera detects that the target vehicle's turn signal is active, which helps to confirm that it has a clear intention to change lanes; Condition 3: The relative speed difference between this vehicle and the vehicle in front exceeds the second preset threshold, indicating that there is a risk that more forceful intervention measures need to be taken; Condition 4: The yaw rate sensor detects a slight yaw tendency in the vehicle that is not actively caused by the driver, reflecting that external traffic behavior has disturbed the vehicle's driving stability.

[0049] When the above conditions are met simultaneously within a preset time window, or successively in a time sequence that conforms to traffic patterns, the system determines that it is currently in a "vehicle entry" condition and triggers the corresponding braking control optimization process to enter the cooperative braking force distribution stage.

[0050] (ii) Arbitration between braking intention and demand.

[0051] The system determines a unified braking control objective by comprehensively assessing the driver's braking intention and the system's automatic braking requirements. Specifically, the system first quantifies the intensity of the driver's braking intention based on brake pedal opening, rate of change, and vehicle dynamic response; simultaneously, it assesses the required automatic braking intensity based on forward traffic situation analysis. Subsequently, it sets an appropriate safety margin based on the risk level of the "vehicle cutting in" scenario to ensure hazard avoidance capabilities. Finally, the system weighted and integrates the braking force requested by the driver and the braking force required by the system to generate a coordinated and consistent collaborative braking strategy. This achieves a smooth transition and reasonable distribution of braking force, ensuring active safety while avoiding driving discomfort caused by sudden changes in braking force, thus improving the naturalness and reliability of human-machine collaboration.

[0052] In one implementation, an automatic braking force is first applied to the main vehicle. After the automatic braking force is applied, the driver's intention and its corresponding intensity are identified based on steering wheel angle sensor data and brake pedal position sensor data. Based on the automatic braking force, the driver's intention, and its corresponding intensity, a target braking force is determined, thereby applying the target braking force to the main vehicle. The process of identifying the driver's intention and its corresponding intensity is as follows: (2.1) Upon receiving steering wheel angle sensor data and brake pedal position sensor data, determine that the driver’s intention is an active braking intention.

[0053] (2.2) Based on the brake pedal position sensor data, determine the active braking force, braking duration data and brake pedal opening change rate data, in order to determine the intensity of the driver's intention, which is divided into slight deceleration and emergency braking.

[0054] In one instance, when the intended braking intensity is emergency braking, the active braking force and the automatic braking force are fused together to obtain the target braking force.

[0055] Specifically, the system activates a braking force fusion mechanism: it superimposes the automatic braking force with the braking force actively applied by the driver, prioritizes retaining the larger component of the two, and appropriately supplements the output of the other component while ensuring that the total braking force is not lower than the higher one, so as to accelerate the braking response speed and make full use of the existing braking capacity.

[0056] In another example, when the intention intensity is slight deceleration, if the active braking force is higher than the automatic braking force, the active braking force is used as the target braking force; if the active braking force is lower than the automatic braking force, the automatic braking force is used as the target braking force.

[0057] Specifically, the system compares and judges the two: if the active braking force applied by the driver is greater than the automatic braking force output by the system, it is determined that the driver has a stronger intention to decelerate, the system exits automatic braking control, and uses the active braking force as the target braking force, with the vehicle braking system responding to the driver's operation first; conversely, if the active braking force is less than the automatic braking force, the system maintains its current automatic braking state and continues to use the automatic braking force as the target braking force to ensure the continuity and stability of speed adjustment during cruising.

[0058] This mechanism enables a smooth transfer of control in low-intensity braking scenarios, respecting the driver's intentions while avoiding deceleration fluctuations caused by braking force switching, thus improving driving comfort and the naturalness of human-machine collaboration.

[0059] (III) Coordination and execution of ESC braking force.

[0060] The electronic stability control system applies longitudinal coordinated braking and / or yaw stability correction to the vehicle based on the target braking force.

[0061] In practical applications, based on the results of the coordinated braking decision, the Electronic Stability Control (ESC) system independently adjusts the braking pressure of each wheel through its hydraulic control unit (HCU) to achieve precise braking force distribution and dynamic response.

[0062] The system executes a multi-dimensional braking force distribution strategy based on the vehicle's entry position, the relative speed difference between the vehicle and the vehicle in front, and the current vehicle motion state: (3.1) Longitudinal Cooperative Braking: In order to achieve smooth deceleration, the system outputs a basically balanced braking torque to the four wheels, so that the difference in braking force between the wheels is less than the preset threshold, suppressing the body yaw or pitch disturbance caused by uneven braking force on one side, and improving the longitudinal smoothness of the braking process. (3.2) Lateral stability correction: When the vehicle is detected to have understeer or oversteer tending, the system applies additional braking force to specific wheels (such as the outer rear wheel or the inner front wheel) to generate a corrective yaw moment that is opposite to the actual yaw rate deviation, to help the vehicle return to the expected driving trajectory. (3.3) Dynamic adjustment mechanism: Throughout the braking process, the system continuously monitors the driver's operating behavior (such as changes in brake pedal opening) and vehicle status feedback, and updates the braking force distribution command in real time to ensure the continuity, controllability and driving comfort of the braking response.

[0063] The above control strategy is executed in a closed loop by the ESC system, achieving an organic unity between safety intervention and human-machine coordination.

[0064] In summary, compared with the prior art, the core technical points of the embodiments of the present invention are reflected in: Added key operating condition identification dimension: For the first time, the high-frequency driving scenario of "vehicle entry" with significant safety impact has been incorporated into the operating condition decision system of the Electronic Stability Control (ESC) system, realizing targeted identification and response to such complex interaction scenarios, and filling the technical gap of the traditional ACC / AEB system's lack of strategy in such edge scenarios.

[0065] A hierarchical control logic with adaptive operating conditions is constructed: differentiated braking force fusion rules and control priority mechanisms are designed for different driving conditions (including normal cruise (ACC), emergency avoidance (AEB), and vehicle intrusion interference). The system can dynamically switch control modes according to the actual traffic situation, realizing the transformation from passive response to active coordination, and improving the intelligence level and scenario adaptability of braking control.

[0066] Based on this, the embodiments of the present invention have at least the following characteristics: Enhancing active safety: In high-risk situations such as Automatic Emergency Braking (AEB), the system assigns the highest priority to automatic braking force. Even if the driver fails to respond in time or the braking operation is insufficient, the system can still independently trigger sufficient braking force, effectively shortening the braking reaction time, reducing the probability of a collision, and enhancing the overall active safety performance of the vehicle.

[0067] Improved braking comfort: In conventional deceleration scenarios such as adaptive cruise control (ACC), the system identifies the intensity of the driver's braking intention and dynamically integrates manual and automatic braking force output to achieve smooth connection and gradual increase of braking force, suppress sudden deceleration, avoid vehicle "nodding" phenomenon, provide a near-linear longitudinal deceleration feel, and improve driving comfort.

[0068] Optimize the driving experience in complex scenarios: For typical traffic interference scenarios where a vehicle suddenly cuts into the lane, the system can flexibly adjust the control allocation strategy based on subtle characteristics of the driver's pedal behavior (such as the rate of pedal change). While ensuring necessary avoidance capabilities, it avoids sudden braking impacts caused by excessive system intervention, making the braking process more natural and controllable, and enhancing driving confidence and operational ease in human-machine collaboration.

[0069] Based on the foregoing embodiments, this invention provides an optimization device for braking control during vehicle cruise, see [link to previous embodiment]. Figure 3 The diagram shows a structural schematic of an optimization device for braking control during vehicle cruise. This device mainly includes the following parts: The data acquisition module 302 is used to acquire multi-source sensor data collected by multiple sensors installed on the main vehicle; The driving condition identification module 304 is used to identify the current driving condition of the main vehicle based on multi-source sensor data. The driving condition includes at least the vehicle entry condition. The braking control module 306 is used to execute the braking control strategy corresponding to the vehicle entry condition when the vehicle entry condition is detected, so as to perform braking operation on the main vehicle through the electronic stability control system based on the braking control strategy.

[0070] The vehicle cruise braking control optimization device provided in this embodiment of the invention can more accurately judge the driver's avoidance intention and the dynamic change trend of the vehicle by identifying the specific working condition of "vehicle cutting in". In this scenario, the matching braking control strategy is activated in time. Compared with the conventional response mode, the present invention effectively enhances the driving stability and safety of the vehicle under sudden interference, avoids the risk of loss of control caused by external disturbances, and thus achieves more scenario-adaptive intelligent stability control.

[0071] In one embodiment, the operating condition identification module 304 is specifically used for: Based on multi-source sensor data, when a target vehicle in an adjacent lane is identified to exhibit lane-changing behavior and the main vehicle exhibits driving state disturbance characteristics, the current driving condition of the main vehicle is determined as the vehicle entry condition.

[0072] In one embodiment, the multi-source sensor data includes at least: radar sensor data, camera data, wheel speed sensor data, and yaw rate sensor data; the working condition identification module 304 is specifically used for: Perform the following operations within the preset time window: Based on radar sensor data, it is determined whether a target vehicle in an adjacent lane is moving in front of the main vehicle at a lateral relative speed greater than a first preset threshold; based on camera data, it is determined whether the target vehicle's turn signal is active; and based on wheel speed sensor data, it is determined whether the relative speed difference between the main vehicle and the target vehicle is greater than a second preset threshold; if all the determination results are yes, it is determined that the target vehicle has lane-changing behavior characteristics. Based on yaw rate sensor data, it is determined whether the main vehicle has a lateral movement trend; if the determination result is yes, it is determined that the main vehicle has driving state disturbance characteristics.

[0073] In one embodiment, the multi-source sensor data further includes steering wheel angle sensor data and brake pedal position sensor data; the brake control module 306 is specifically used for: Apply automatic braking force to the main vehicle; After applying automatic braking force, the driver's intention and its corresponding intensity are identified based on steering wheel angle sensor data and brake pedal position sensor data, and the target braking force is determined based on the automatic braking force, the driver's intention and its corresponding intensity. Apply the target braking force to the main vehicle.

[0074] In one embodiment, the braking control module 306 is specifically used for: Upon receiving data from the steering wheel angle sensor and the brake pedal position sensor, the driver's intention is determined to be an active braking intention; Based on data from the brake pedal position sensor, the active braking force, braking duration, and brake pedal opening change rate are determined to determine the intensity of the driver's intention, which is divided into slight deceleration and emergency braking.

[0075] In one embodiment, the braking control module 306 is specifically used for: When the intended braking intensity is emergency braking, the active braking force and the automatic braking force are fused together to obtain the target braking force; When the intention intensity is slight deceleration, if the active braking force is higher than the automatic braking force, the active braking force will be used as the target braking force; if the active braking force is lower than the automatic braking force, the automatic braking force will be used as the target braking force.

[0076] In one embodiment, the braking control module 306 is specifically used for: The electronic stability control system applies longitudinal coordinated braking and / or yaw stability correction to the vehicle based on the target braking force.

[0077] The device provided in this embodiment of the invention has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0078] This invention provides an electronic device, specifically, the electronic device includes a processor and a memory; the memory stores a computer program, which, when run by the processor, executes the method described in any of the above embodiments.

[0079] Figure 4 The present invention provides a schematic diagram of the structure of an electronic device 100, which includes a processor 40, a memory 41, a bus 42 and a communication interface 43. The processor 40, the communication interface 43 and the memory 41 are connected through the bus 42. The processor 40 is used to execute executable modules, such as computer programs, stored in the memory 41.

[0080] The memory 41 may include high-speed random access memory (RAM) or non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 43 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc.

[0081] Bus 42 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 4 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0082] The memory 41 is used to store programs. After receiving an execution instruction, the processor 40 executes the program. The method executed by the device for defining the flow process disclosed in any of the foregoing embodiments of the present invention can be applied to the processor 40 or implemented by the processor 40.

[0083] Processor 40 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 40 or by instructions in software form. Processor 40 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 41. The processor 40 reads the information in memory 41 and, in conjunction with its hardware, completes the steps of the above method.

[0084] The computer program product of the readable storage medium provided in the embodiments of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the foregoing method embodiments. For specific implementation, please refer to the foregoing method embodiments, which will not be repeated here.

[0085] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0086] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for optimizing brake control in a vehicle cruise process, characterized by, The method comprises: acquiring multi-source sensor data collected by a plurality of sensors installed on a host vehicle; identifying a driving condition in which the host vehicle currently locates based on the multi-source sensor data, wherein the driving condition at least comprises a vehicle cut-in condition; in a case where the vehicle cut-in condition is identified, performing a brake control strategy corresponding to the vehicle cut-in condition to brake the host vehicle based on the brake control strategy by an electronic stability control system.

2. The method of optimizing vehicle cruise braking control according to claim 1, wherein, The identifying of the driving condition in which the host vehicle currently locates based on the multi-source sensor data comprises: in a case where it is identified based on the multi-source sensor data that a target vehicle in a neighboring lane has a lane-changing behavior feature and the host vehicle has a driving state disturbance feature, determining that the host vehicle currently locates in the vehicle cut-in condition.

3. The method of optimizing vehicle cruise braking control according to claim 2, wherein, The multi-source sensor data at least comprises radar sensor data, camera data, wheel speed sensor data and yaw rate sensor data; and in a case where it is identified based on the multi-source sensor data that the target vehicle in the neighboring lane has the lane-changing behavior feature and the host vehicle has the driving state disturbance feature, the identifying comprises: in a preset time window, performing the following operations: based on the radar sensor data, judging whether the target vehicle in the neighboring lane moves towards a front of the host vehicle at a lateral relative speed greater than a first preset threshold; and based on the camera data, judging whether a turn signal of the target vehicle is in an activated state; and based on the wheel speed sensor data, judging whether a relative speed difference between the host vehicle and the target vehicle is greater than a second preset threshold; in a case where the judgment results are all yes, determining that the target vehicle has the lane-changing behavior feature; based on the yaw rate sensor data, judging whether the host vehicle has a lateral motion trend; in a case where the judgment result is yes, determining that the host vehicle has the driving state disturbance feature.

4. The method of optimizing vehicle cruise control braking according to claim 1, wherein The multi-source sensor data further comprises steering wheel angle sensor data and brake pedal position sensor data; The performing of the brake control strategy corresponding to the vehicle cut-in condition comprises: applying an automatic brake force to the host vehicle; after the automatic brake force is applied, identifying a driver intention and a corresponding intention strength based on the steering wheel angle sensor data and the brake pedal position sensor data, and determining a target brake force according to the automatic brake force, the driver intention and the corresponding intention strength; applying the target brake force to the host vehicle.

5. The method of optimizing vehicle cruise braking control according to claim 4, wherein, The identifying of the driver intention and the corresponding intention strength based on the steering wheel angle sensor data and the brake pedal position sensor data comprises: in a case where the steering wheel angle sensor data and the brake pedal position sensor data are received, determining that the driver intention is an active brake intention; determining an active brake force, brake duration data and brake pedal opening rate change data according to the brake pedal position sensor data, so as to determine the intention strength corresponding to the driver intention, wherein the intention strength is divided into slight deceleration and emergency brake.

6. The method of optimizing vehicle cruise braking control according to claim 5, wherein, The determining of the target brake force according to the automatic brake force, the driver intention and the corresponding intention strength comprises: In a case where the intention intensity is the emergency braking, the active braking force and the automatic braking force are fused to obtain a target braking force; In a case where the intention intensity is the slight deceleration, if the active braking force is higher than the automatic braking force, the active braking force is taken as the target braking force, and if the active braking force is lower than the automatic braking force, the automatic braking force is taken as the target braking force.

7. The method of claim 4, wherein, The braking operation on the host vehicle is performed by an electronic stability control system based on the braking control strategy, including: The vehicle is subjected to longitudinal cooperative braking and / or yaw stability correction by the electronic stability control system based on the target braking force.

8. An optimization device for braking control during vehicle cruising, characterized in that, The method comprises: a data acquisition module configured to acquire multi-source sensor data collected by a plurality of sensors installed on the host vehicle; a working condition identification module configured to identify a driving working condition currently experienced by the host vehicle based on the multi-source sensor data, the driving working condition at least including a vehicle cut-in working condition; a braking control module configured to, in a case where the vehicle cut-in working condition is identified, execute a braking control strategy corresponding to the vehicle cut-in working condition, so as to perform the braking operation on the host vehicle by the electronic stability control system based on the braking control strategy.

9. An electronic device, comprising: The computer readable storage medium stores computer executable instructions, and the computer executable instructions, when invoked and executed by the processor, cause the processor to implement the method according to any one of claims 1 to 7.

10. A computer readable storage medium characterized by, The computer readable storage medium stores computer executable instructions, and the computer executable instructions, when invoked and executed by the processor, cause the processor to implement the method according to any one of claims 1 to 7.

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