Combined driving assistance function hand torque processing method, device, equipment and medium

Abstract

The embodiment of the invention provides a combined driving assistance function hand torque processing method and device, equipment and a medium, and relates to the technical field of vehicles. The method comprises the steps that it is determined that a current combined driving assistance function is in an activated state, and vehicle motion state information and an original hand torque signal are obtained in real time; determining that a lateral collision event occurs based on the vehicle motion state information; filtering the original hand torque signal to obtain an effective hand torque representing the real intention of the driver; and executing a corresponding vehicle control strategy based on a comparison result of the effective hand torque and a preset takeover threshold value. The method provided by the invention effectively solves the problem that the driving safety is affected due to misjudgment of the hand torque processing under the abnormal working condition in the related technology.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, and in particular to a method, device, equipment and medium for handling hand torque in combination driving assistance functions. Background Technology

[0002] With the development of intelligent driving technology, combined driver assistance functions (such as Lane Centering Cruise Control (LCC) and Navigation Assist (NOA)) have been widely applied in mass-produced vehicles. During the operation of these functions, the system needs to continuously monitor the torque applied by the driver to the steering wheel, using this as the core basis for determining whether the driver intends to take over actively. The accurate identification and processing of torque signals directly affects the smooth and safe transfer of human-machine control, and is fundamental to ensuring the normal operation of the driver assistance system and the user experience.

[0003] In related technologies, the handling of hand torque is mainly optimized for normal driving scenarios or known disturbances (such as road bumps), generally neglecting the abnormal condition of a side collision or scrape. When a side collision occurs, the huge impact force is transmitted to the torque sensor through the steering mechanism, generating a strong interference signal that is not the driver's intention. Existing solutions cannot effectively distinguish between this signal distortion caused by the collision impact and the real driver's intention to take over, which can easily lead to misjudgment and cause the combined driving assistance functions to deactivate unexpectedly. This can cause the vehicle to lose necessary lateral control in critical scenarios, potentially leading to secondary accidents and seriously threatening driving safety. Summary of the Invention

[0004] This application provides a method, device, equipment, and medium for handling hand torque under combined driving assistance functions, in order to solve the problem that hand torque handling under abnormal working conditions in related technologies is prone to misjudgment and affects driving safety.

[0005] In a first aspect, this application provides a method for handling hand torque in a combined driving assistance function, the method comprising the following steps:

[0006] Determine that the current combination of driving assistance functions is active, and acquire vehicle motion status information and raw hand torque signals in real time;

[0007] Based on vehicle motion state information, a side collision event is determined to have occurred;

[0008] The original hand torque signal is filtered to obtain the effective hand torque that represents the driver's true intention;

[0009] Based on the comparison between the effective hand torque and the preset takeover threshold, the corresponding vehicle control strategy is executed.

[0010] In one embodiment of this disclosure, the vehicle motion state information includes lateral acceleration and yaw rate from an inertial measurement unit and four-wheel speed information from a wheel speed meter; based on the vehicle motion state information, determining that a side collision event has occurred includes: performing a fusion analysis on the lateral acceleration, yaw rate and four-wheel speed information, and based on the analysis results, determining that there is a dynamic response that conforms to the characteristics of a side collision.

[0011] In one embodiment of this disclosure, lateral acceleration, yaw rate, and four-wheel speed information are fused and analyzed. Based on the analysis results, a dynamic response that meets the characteristics of a side collision is determined, including: determining whether the amplitude of the lateral acceleration exceeds a first dynamic threshold; determining whether the amplitude of the yaw rate exceeds a second dynamic threshold; analyzing the four-wheel speed information to determine whether a wheel speed characteristic indicating unilateral obstruction occurs; and determining that a side collision event has occurred when the lateral acceleration, yaw rate, and wheel speed characteristics all meet their respective judgment conditions.

[0012] In one embodiment of this disclosure, the original hand torque signal is filtered to obtain an effective hand torque that represents the driver's true intention. This includes filtering the interference torque component in the original hand torque signal generated by the collision impact transmitted through the steering mechanism based on a filtering algorithm. The filtering process includes attenuation processing or elimination processing. The filtering algorithm is an algorithm that models and compensates for the interference torque component based on the feature parameters of the side collision event, or an algorithm that smooths the original hand torque signal within a preset time window.

[0013] In one embodiment of this disclosure, based on the comparison result of the effective hand torque and the preset takeover threshold, a corresponding vehicle control strategy is executed, including: if the effective hand torque is greater than the preset takeover threshold, the combined driving assistance function is disengaged; if the effective hand torque is not greater than the preset takeover threshold, the combined driving assistance function is controlled to maintain lateral control of the current lane and a safe parking procedure is executed.

[0014] In one embodiment of this disclosure, executing a safe parking procedure includes: controlling the vehicle to maintain its movement along the current lane; while maintaining lateral control, initiating longitudinal deceleration control of the vehicle and monitoring the vehicle's stopping status; and ending the safe parking procedure when the vehicle is detected to have come to a complete stop.

[0015] In one embodiment of this disclosure, the method further includes: acquiring the vehicle's current driving state parameters and road environment parameters; and calculating and updating the value of a preset takeover threshold based on the driving state parameters and road environment parameters.

[0016] Secondly, embodiments of this disclosure provide a combined driving assistance function hand torque processing device, the combined driving assistance function hand torque processing device comprising:

[0017] The acquisition module is used to determine whether the current combined driving assistance function is active and to acquire vehicle motion status information and raw hand torque signal in real time;

[0018] The analysis module is used to determine whether a side collision event has occurred based on vehicle motion state information;

[0019] The processing module is used to filter the raw hand torque signal to obtain the effective hand torque that represents the driver's true intention;

[0020] The execution module is used to execute the corresponding vehicle control strategy based on the comparison result between the effective hand torque and the preset takeover threshold.

[0021] Optionally, the acquisition module is specifically used to acquire vehicle motion state information including lateral acceleration and yaw rate from the inertial measurement unit and four-wheel speed information from the wheel speed meter.

[0022] Optionally, the analysis module is specifically used to perform fusion analysis on the information of lateral acceleration, yaw rate and four-wheel speed, and based on the analysis results, determine whether there is a dynamic response that conforms to the characteristics of a side collision.

[0023] Optionally, the analysis module is specifically used to: determine whether the amplitude of the lateral acceleration exceeds a first dynamic threshold; determine whether the amplitude of the yaw rate exceeds a second dynamic threshold; analyze the wheel speed information of the four wheels to determine whether a wheel speed characteristic indicating unilateral obstruction occurs; and determine that a side collision event has occurred when the lateral acceleration, yaw rate, and wheel speed characteristics all meet their respective judgment conditions.

[0024] Optionally, the processing module is specifically used to filter the interference torque component generated by the collision impact transmitted through the steering mechanism in the original hand torque signal based on the filtering algorithm. The filtering process includes attenuation processing or elimination processing. If the filtering algorithm is an algorithm that models and compensates the interference torque component based on the feature parameters of the side collision event, or an algorithm that smooths the original hand torque signal within a preset time window.

[0025] Optionally, the execution module is specifically used to: if the effective hand torque is greater than the preset takeover threshold, exit the combined driving assistance function; if the effective hand torque is not greater than the preset takeover threshold, control the combined driving assistance function to maintain lateral control of the current lane and execute the safe parking procedure.

[0026] Optionally, the execution module is specifically used to control the vehicle to keep driving along the current lane; while maintaining lateral control, initiate longitudinal deceleration control of the vehicle and monitor the vehicle's stopping status; and when the vehicle is detected to have come to a complete stop, end the safe parking process.

[0027] Optionally, the execution module is also used to obtain the vehicle's current driving status parameters and road environment parameters; and to calculate and update the value of the preset takeover threshold based on the driving status parameters and road environment parameters.

[0028] Thirdly, embodiments of this application provide a control device, including: a memory and a processor;

[0029] The memory stores instructions that the computer executes;

[0030] The processor executes computer execution instructions stored in memory, causing the processor to perform a hand torque processing method for implementing a combined driving assistance function as described in the first aspect of this disclosure.

[0031] Fourthly, embodiments of this disclosure also provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the combined driving assistance function hand torque processing method as described in the first aspect of this disclosure.

[0032] Fifthly, embodiments of this disclosure also provide a computer program product comprising computer execution instructions, which, when executed by a processor, are used to implement the combined driving assistance function hand torque processing method as described in the first aspect of this disclosure.

[0033] The combined driving assistance function hand torque processing method, device, equipment, and medium provided in this disclosure identify lateral collision events in real time based on the vehicle's motion state when the combined driving assistance function is activated, and selectively filter the collected raw hand torque signals accordingly. Finally, based on the purified effective hand torque decision control strategy, the strong interference signal components generated by mechanical impact transmission are effectively removed. This allows for accurate differentiation between collision interference and the driver's true operating intention, fundamentally avoiding unexpected exit of the assistance function and loss of lateral control due to misjudgment. Consequently, the accuracy of hand torque recognition and the reliability of system decision-making are significantly improved, providing key technical guarantees for maintaining vehicle stability and preventing secondary accidents in critical scenarios of accidental collisions. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0035] Figure 1 This diagram illustrates an application scenario of the combined driving assistance function hand torque processing method, apparatus, equipment, and medium provided in this embodiment of the disclosure.

[0036] Figure 2A flowchart of a combined driving assistance function hand torque processing method provided in one embodiment of this disclosure;

[0037] Figure 3 A flowchart illustrating a combined driving assistance function hand torque processing method provided in yet another embodiment of this disclosure;

[0038] Figure 4 A schematic diagram of the combined driving assistance function hand torque processing device provided in yet another embodiment of this disclosure;

[0039] Figure 5 This is a schematic diagram of the structure of a control device provided in yet another embodiment of this disclosure.

[0040] The accompanying drawings have illustrated specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to specific embodiments. Detailed Implementation

[0041] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0042] In integrated driver assistance systems, real-time and accurate interpretation of the driver's steering wheel torque is crucial for determining whether the driver intends to take over the vehicle and for achieving a smooth handover of control. The core challenge lies in the fact that the steering wheel torque signal is highly susceptible to interference from external physical stimuli not generated by the driver. Especially during lateral scrapes or collisions, the resulting immense impact force is directly transmitted to the steering wheel torque sensor through mechanical components such as wheels, steering linkages, and racks, generating high-amplitude, transiently changing interference signals. This interference can be difficult to distinguish from the actual smooth driving intentions of the driver, making it challenging for the recognition algorithm to differentiate between them.

[0043] In related technologies, the handling of hand torque mainly focuses on optimization under normal driving scenarios, or only suppresses known, weak, and persistent disturbances such as road bumps. These solutions fail to identify the high-risk disturbance source of side collisions. Because their underlying design does not include the ability to perceive and distinguish such sudden, strong impact events, they are essentially unable to distinguish between collision impact signals and driver takeover signals. In the event of a side collision, they will inevitably face the risk of misjudgment, and thus cannot avoid the occurrence of vehicle loss of control.

[0044] The combined driving assistance function hand torque processing method, device, equipment and medium provided in this application actively senses and determines the occurrence of a side collision event, and uses this as a key scenario input; then, under the trigger of this scenario, it performs special filtering processing on the hand torque signal to eliminate the collision impact component in order to extract the true driving intention; finally, it makes a reliable control decision based on the purified signal. Thus, side collisions are clearly identified as interference sources that need to be independently identified and specifically processed. Through an event-driven signal purification strategy, accurate identification of intentions under extreme interference is achieved.

[0045] Figure 1 This is a schematic diagram illustrating the application scenarios of the combined driving assistance function hand torque processing method, device, equipment, and medium provided in this application, such as... Figure 1 As shown, during vehicle operation, the vehicle control system 100 automatically collects vehicle status data and environmental data 110, and when it is determined that the vehicle is experiencing an abnormal lateral impact, it controls the vehicle's driving status according to the corresponding control strategy 120.

[0046] It should be noted that, Figure 1 The scenario shown includes an on-board control system, vehicle status data and environmental data. The control strategy is only illustrated by one or a specific number of examples, but this disclosure is not limited to this. That is to say, the number of on-board control systems, vehicle status data and environmental data, and control strategies can be arbitrary.

[0047] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0048] Figure 2 This is a flowchart illustrating the combined driving assistance function hand torque processing method provided in the embodiments of this application. The following is a summary of the process. Figure 2 The main process of the hand torque handling method for combined driving assistance functions is explained below:

[0049] S201. Determine that the current combined driving assistance function is active, and obtain vehicle motion status information and raw hand torque signal in real time.

[0050] Specifically, in this embodiment of the combined driving assistance function hand torque processing method, the executing entity is a system and an on-board processor capable of acquiring driver operation signals and on-board sensor signals and performing analysis and judgment. For ease of explanation, it will be referred to as the system below.

[0051] When a vehicle activates a combination of driver assistance functions such as lane centering cruise control or navigation assist, the system enters a standby state that requires continuous monitoring of the driver's interaction intentions.

[0052] The activation state here not only means that the function switch is turned on, but also that the system's lateral control subsystem (such as active steering assist) is automatically adjusting the vehicle's driving trajectory based on perceived environmental information (such as lane lines).

[0053] In this state, the system needs to continuously perceive the driver's intentions to ensure safe and smooth human-machine co-driving.

[0054] Therefore, the system needs to collect two types of key real-time data streams in parallel.

[0055] The first category is vehicle motion state information, which directly reflects the instantaneous dynamic behavior of the vehicle in three-dimensional space. This type of information usually does not rely on the interpretation of the environment, but rather comes from the sensors on the vehicle itself.

[0056] For example, the system can read raw data periodically reported by the inertial measurement unit from the vehicle network (such as the CAN bus), which directly encodes the vehicle's motion changes in the lateral and vertical axes.

[0057] At the same time, the system will also obtain the instantaneous rotational speed of each wheel from the wheel speed sensor array. This data can reflect the interaction state between the wheel and the ground and is an important basis for judging whether the vehicle has experienced unexpected lateral slippage or unilateral obstruction.

[0058] The second type of data is the raw hand torque signal, which comes directly from the torque sensor integrated into the steering column. This sensor measures the net effect of the force applied by the driver's hand to the steering wheel in an attempt to rotate it, combined with the torques from the steering system's motor assist, road feedback, and other factors. Therefore, this signal is a mixture of multiple physical processes, including the driver's explicit intention to operate the steering wheel, as well as excitations from road unevenness, internal friction within the steering system, and, crucially, often overlooked—the force transmitted from external collision impacts through the suspension and steering tie rods.

[0059] The system can acquire this raw, unprocessed torque signal in real time from the electric power steering controller, serving as a starting point for analyzing the driver's intentions.

[0060] To enable accurate subsequent analysis, the system needs to ensure that these multi-source heterogeneous data are aligned and synchronized in time.

[0061] One possible approach is to assign a high-precision timestamp to all incoming data and perform data fusion preprocessing based on this timestamp. This ensures that the lateral acceleration, wheel speed, and hand torque values ​​used in any decision cycle correspond to the vehicle state at the same physical moment, thereby avoiding analytical errors caused by signal delays.

[0062] S202. Based on the vehicle motion state information, determine that a side collision event has occurred.

[0063] Specifically, based on the obtained data, the system needs to detect and identify the unique dynamic characteristics caused by a specific external event such as a side collision or scrape.

[0064] Therefore, the system is required to be able to distinguish between normal driving maneuvers (such as lane changes and swerving) and abnormal collision impacts.

[0065] The principle is that a typical side collision will produce a set of highly correlated anomalous features in the vehicle's dynamic response in a very short time.

[0066] The system detects whether the vehicle is experiencing an abnormal change in lateral force by continuously monitoring lateral acceleration signals from the IMU (Inertial Measurement Unit).

[0067] When driving calmly, lateral acceleration usually fluctuates slightly around zero. However, when a vehicle is hit from the side, the vehicle body will generate a significant acceleration pulse with a very steep rise in the direction of impact.

[0068] The system can set a dynamic reference baseline based on the vehicle's normal maneuverability. Any lateral acceleration change that significantly exceeds this baseline within a short period of time will be marked as a potential anomalous event.

[0069] Since the sudden change in lateral acceleration alone may not be enough to rule out driver-initiated actions such as emergency obstacle avoidance, yaw rate also needs to be introduced as key supporting evidence.

[0070] If the impact force of a collision does not pass through the vehicle's center of gravity, it will generate a torque that causes the vehicle to rotate around its vertical axis, resulting in a sudden surge in yaw rate, the direction of which is related to the location of the collision.

[0071] The system can determine whether a collision has occurred by analyzing the coupling relationship between the lateral acceleration pulse and the yaw rate pulse in terms of timing and direction.

[0072] For example, when a vehicle is struck on the left, it typically generates a lateral acceleration to the right (the vehicle is pushed to the right) and a clockwise yaw rate (the front of the vehicle tends to swing to the right). This specific coupling pattern is an important criterion for distinguishing between passive collisions and active steering.

[0073] Based on this, in order to further confirm the source and severity of the impact, the system can also simultaneously analyze the wheel speed information of all four wheels.

[0074] In the event of a side collision, the impact is highly likely to directly affect one or more wheels. This can cause the wheel speed of the struck wheel to drop sharply at the moment of impact (due to drag), or result in a sustained speed difference with the opposite wheel over the following seconds due to rim deformation or tire depressurization. Therefore, the system calculates the wheel speed difference between the left and right wheels on the same axle in real time and correlates it with the aforementioned acceleration and angular velocity events in a time sequence.

[0075] A strongly correlated combination of events—namely, abnormal pulses of lateral acceleration and yaw rate accompanied by abnormal wheel speed on a specific side—can point to a side collision event with a very high degree of confidence.

[0076] S203. Filter the original hand torque signal to obtain the effective hand torque that represents the driver's true intention.

[0077] Specifically, once the system confirms a side collision, it needs to filter the hand torque signal. This is because the impact force of the collision is transmitted to the torque sensor through a clear physical path (i.e., from the wheel to the drive system, all the way to the steering structure), forming a strong, transient, and non-driver-generated interference signal (i.e., the interference torque component).

[0078] This interference signal will severely affect the original hand torque reading, causing it to fluctuate violently and irregularly in a short period of time, completely masking the real, smooth steering or corrective torque that the driver may be applying.

[0079] The goal of filtering is to separate and remove the noise caused by the collision from the mixed original signal as much as possible, thereby restoring the effective hand torque that can represent the driver's actual hand input signal.

[0080] Therefore, the system can utilize the collision event features identified in the previous step (such as the precise time of the impact and the estimated impact intensity and direction) as prior knowledge.

[0081] One approach is to construct an event-triggered transient filter. For example, the system can set a time window starting from the moment of the collision. Within this window, the system determines that the high-frequency, rapidly changing components in the hand torque signal mainly originate from the impact. By applying an adaptively weighted low-pass filter or a specially designed impact response filter, the system can significantly attenuate the high-frequency energy of the signal within this time window, retaining relatively low-frequency and slowly varying components, the latter being more likely to correspond to the driver's instinctive steering response after shock.

[0082] Another approach is compensation based on parameter estimation. For example, the system can pre-define a simplified dynamic model (such as a first- or second-order transfer function) describing the transmission of impact force from the wheel to the steering wheel torque sensor.

[0083] When a collision event is detected, the system uses the measured vehicle motion response (such as the amplitude of lateral acceleration) to estimate the magnitude of the disturbance force acting on the steering mechanism, and then uses a model to calculate the theoretical disturbance torque value that the disturbance force should produce on the torque sensor.

[0084] Finally, the system subtracts this estimated interference torque from the original hand torque signal to obtain the purified effective hand torque. This process is essentially a real-time, targeted filtering and correction of the sensor signal.

[0085] S204. Based on the comparison result between the effective hand torque and the preset takeover threshold, execute the corresponding vehicle control strategy.

[0086] Specifically, after obtaining the filtered effective hand torque, the system has a reliable foundation for determining the driver's current intention. At this point, the system needs to compare the calculated effective hand torque value with a preset takeover threshold to determine whether the driver intentionally and explicitly requests to take over lateral control of the vehicle. This determination can be based on whether the effective hand torque value reaches the minimum steady-state torque level required. This distinguishes it from ordinary grip torque or slight adjustments.

[0087] The comparison results guide the system to two distinct security control paths.

[0088] The first scenario is when the filtered effective hand torque consistently exceeds the takeover threshold. This indicates that the driver, after the collision, not only remained conscious but was also actively and forcefully applying steering input, attempting to regain control of the vehicle. In this case, the system should respect the driver's explicit intention and execute the normal disengagement procedure. This means that the combined driver assistance functions (especially the lateral control portion) will smoothly and orderly disengage, returning full control of the steering wheel and the responsibility for determining the vehicle's lateral trajectory to the driver. During the disengagement process, the system ensures a smooth transition of steering assist, preventing sudden transfer of control that could lead to vehicle instability.

[0089] In another scenario, the filtered effective hand torque consistently does not exceed the takeover threshold. This could indicate that the driver was temporarily incapacitated during the collision, in shock and unable to react, or believed the impact was minor and did not require intervention. However, if the system misjudges and disengages due to unfiltered interference, causing the vehicle to lose its automatic lateral control capability, it is highly likely to veer off the lane without the driver's conscious control, potentially leading to a secondary accident.

[0090] Therefore, the system will not disengage at this time, but will actively adopt control strategies to maintain vehicle safety. For example, it can enhance the lane keeping function, applying precise corrective torque through the steering system based on lane line information perceived by the front camera, to ensure that the vehicle stays stably in the center of the current lane and avoids deviation caused by collision inertia or the driver's unconscious release of the steering wheel.

[0091] At the same time, the system can also initiate a gentle but firm longitudinal deceleration control, such as automatically reducing drive torque and applying moderate braking to smoothly decelerate the vehicle until it comes to a complete stop within the lane.

[0092] Throughout the process, the system acts as a substitute driver, decisively taking over and executing the most conservative and safest sequence of actions—"keeping the lane and stopping safely"—when the driver may be temporarily "absent," ensuring the safety of the occupants.

[0093] The combined driving assistance function hand torque processing method provided in this application identifies lateral collision events in real time based on the vehicle's motion state when the combined driving assistance function is activated, and accordingly filters the collected raw hand torque signals. Finally, based on the purified effective hand torque, a decision control strategy is formulated. This effectively removes strong interference signal components generated by mechanical impact transmission, thereby accurately distinguishing collision interference from the driver's true operating intention. This fundamentally avoids unexpected exit of the assistance function and loss of lateral control due to misjudgment, and significantly improves the accuracy of hand torque recognition and the reliability of system decision-making. It provides key technical support for maintaining vehicle stability and preventing secondary accidents in critical scenarios of accidental collisions.

[0094] Figure 3 Another embodiment of the present disclosure provides a method for handling hand torque in a combined driving assistance function. Figure 2 Based on the illustrated embodiment, the following is combined with Figure 3 The implementation process of the hand torque processing method for combined driving assistance functions is explained in detail, which includes the following steps:

[0095] S301. Determine that the current combined driving assistance function is active, and obtain vehicle motion status information and raw hand torque signal in real time.

[0096] Specifically, before triggering the hand torque processing, the system first needs to confirm that the advanced driver assistance system, such as lane centering cruise or navigation-assisted driving, is in normal working mode.

[0097] In this mode, the system's lateral control function is activated, which is responsible for automatically adjusting the steering to maintain the lane based on environmental perception results.

[0098] Confirming activation is a prerequisite for all subsequent processing logic, ensuring that the system is in a state where it needs to monitor the driver's intentions.

[0099] Next, the system collects two types of key signals in real time from the vehicle bus network in parallel: the motion state information of the vehicle body and the original hand torque signal.

[0100] The latter is generated by a torque sensor mounted on the steering column and reported via the electric power steering controller. This signal is the vector sum of all torque components on the steering wheel, including the driver's actively applied torque, the output torque of the power steering motor, the road feedback torque, and the disturbance torque transmitted to the steering wheel by external impacts (such as collisions) through the mechanical structure.

[0101] Furthermore, the vehicle motion status information includes lateral acceleration and yaw rate from the inertial measurement unit, and four-wheel speed information from the wheel speed meter.

[0102] Specifically, inertial measurement units (IMUs) are typically fixed to the vehicle's body. The accelerometer's output along the vehicle's lateral direction is the lateral acceleration, which directly reflects the rate of change in the vehicle's motion caused by lateral forces (whether from driver steering, centrifugal force, or external collisions). The sign of this value indicates the direction of acceleration. The gyroscope's output around the vehicle's vertical axis is the yaw rate, which characterizes the rate of vehicle body torsion and is a core parameter for determining whether the vehicle is experiencing unexpected, violent rotational motion. IMU data is characterized by high frequency and low latency, enabling it to capture transient impacts.

[0103] Wheel speed sensors, also known as wheel speed meters, are installed at each wheel. Their signals are processed and provided by the anti-lock braking system (ABS) or a separate wheel speed module. Obtaining four-wheel wheel speed information means that the system needs to simultaneously and independently monitor the instantaneous angular velocities of the four wheels: front left, front right, rear left, and rear right.

[0104] In a side collision, the wheel on the impact side is highly likely to experience an abnormal change in wheel speed, distinct from the other wheels, due to direct physical obstruction. By comparing the wheel speed difference between the left and right wheels on the same axle, and monitoring sudden drops or abnormal fluctuations in the speed of individual wheels within a short period, the system can obtain direct evidence of the specific location and severity of the collision affecting the vehicle.

[0105] The fusion of wheel speed information and IMU information can effectively distinguish between yaw motion of the entire vehicle and obstruction of a single wheel, greatly improving the accuracy and robustness of event judgment.

[0106] S302. The information on lateral acceleration, yaw rate and four-wheel speed is fused and analyzed, and based on the analysis results, it is determined that there is a dynamic response that conforms to the characteristics of a side collision.

[0107] Specifically, the system utilizes the complementarity of information from multiple sensor sources and fuses it through specific logic or algorithms to identify the unique vehicle dynamic characteristics caused by a side collision.

[0108] The principle is that a real side collision will produce a set of abnormal responses in vehicle dynamics that are highly correlated in the time domain and different in characteristics from normal driving maneuvers (such as emergency obstacle avoidance or rapid lane change).

[0109] In some embodiments, the specific fusion analysis method includes the following steps:

[0110] Step A1: Determine whether the amplitude of the lateral acceleration exceeds the first dynamic threshold.

[0111] Specifically, the system continuously monitors lateral acceleration signals.

[0112] When driving calmly, the amplitude of lateral acceleration fluctuates slightly around zero.

[0113] When a vehicle is struck from the side, it will generate a large-amplitude acceleration pulse with a steep rise in a very short time.

[0114] The first dynamic threshold here is not a fixed value, but may be a critical value estimated based on the vehicle's current speed and the road surface adhesion coefficient, representing abnormally violent lateral motion.

[0115] For example, the system can calculate a theoretical maximum safe lateral acceleration reference value based on vehicle speed. Any peak value that exceeds this reference value by a certain percentage (e.g., 80%) within a short period of time (e.g., within 50 milliseconds) will be marked as a suspicious event, triggering further analysis (e.g., a judgment based on a combination of multiple values).

[0116] Step A2: Determine whether the amplitude of the yaw rate exceeds the second dynamic threshold.

[0117] Specifically, the system also monitors yaw rate. If the impact force does not pass through the vehicle's center of gravity, it will generate a torque that causes the vehicle to rotate, resulting in a sudden spike in yaw rate.

[0118] The setting logic for the second dynamic threshold is similar to that of the first dynamic threshold, and it is used to filter out abnormal, violent rotational movements caused by non-driver-initiated steering.

[0119] The system will determine whether the peak value of the yaw rate exceeds the safety limit set based on the vehicle's dynamic characteristics within a short period of time.

[0120] Step A3: Analyze the wheel speed information of the four wheels to determine whether there are wheel speed characteristics that indicate unilateral obstruction.

[0121] Specifically, since a side collision is likely to directly affect one or more wheels, the system can analyze the wheel speeds of all four wheels in real time to find two typical characteristics: first, at the moment of collision, the wheel speed of the wheel on the side that was hit may drop sharply (because it is subjected to huge lateral resistance); second, after the collision, due to tire depressurization, rim deformation or suspension damage, a speed difference may occur between the wheel on one side and the wheel on the other side.

[0122] To this end, the system calculates the wheel speed difference between the left and right wheels on the same axle and monitors whether it increases abnormally near the collision time point, and whether this abnormality persists for a period of time.

[0123] Step A4: When the lateral acceleration, yaw rate, and wheel speed characteristics all meet their respective judgment conditions, a side collision event is determined to have occurred.

[0124] Specifically, the system determines that a side collision event has occurred with high confidence only when the three judgment conditions corresponding to the above steps are simultaneously met within a similar time window (e.g., a predefined 200-millisecond time window).

[0125] This multi-condition joint judgment mechanism can effectively reduce false triggering caused by false alarms from a single sensor (such as sudden changes in wheel speed caused by driving over a large pothole) or aggressive driving operations (such as rapid and continuous lane changes), greatly improving the accuracy and reliability of collision detection.

[0126] The determination result will output the sign of the collision event, the approximate timestamp, and relevant parameters that can be used to characterize the impact intensity (such as the amount exceeding the threshold).

[0127] In some embodiments, after determining that a side collision event has occurred based on multi-sensor information, the system can also determine the severity level of the collision. This level can be determined based on a combination of factors, including the magnitude of exceeding thresholds in lateral acceleration and yaw rate, and the duration of abnormal wheel speed.

[0128] The system adaptively adjusts the strength of the subsequent hand torque filtering algorithm and the deceleration curve of the safe parking process according to different severity levels. For example, when it is determined to be a minor scratch, a weaker filtering and a gentler parking strategy are adopted, while when it is determined to be a serious collision, a strong filtering and an emergency braking strategy are adopted, thereby achieving a refined and adaptive response to different impact intensities.

[0129] S303. Based on the filtering algorithm, the interference torque component generated by the collision impact transmitted through the steering mechanism in the original hand torque signal is filtered.

[0130] The filtering process includes attenuation or elimination. The filtering algorithm is either an algorithm that models and compensates for the interference torque component based on the characteristic parameters of the side collision event, or an algorithm that smooths the original hand torque signal within a preset time window.

[0131] Specifically, once a side collision is confirmed, the system immediately initiates a dedicated filtering procedure for the hand torque signal. This step aims to address the core issue of separating and removing the strong, transient disruptive torque generated by the collision impact as it is transmitted to the torque sensor via a mechanical path from the original signal, thereby extracting the torque component that reflects the driver's true intentions.

[0132] Specifically, filtering can be physically manifested in two main ways: attenuation or removal. Attenuation aims to reduce the amplitude influence of interference components, while removal attempts to directly subtract the estimated interference components from the signal.

[0133] To achieve the above processing, this embodiment provides two filtering algorithms. However, those skilled in the art should understand that in practical applications, other methods capable of achieving the same effect can also be used, and no limitations are imposed here.

[0134] Modeling and compensation algorithm based on event feature parameters: The principle of this algorithm is to first model and estimate the collision interference, and then perform compensation.

[0135] The system utilizes the collision event characteristic parameters obtained in S302 (such as the precise time of impact, estimated impact intensity, or direction) as known inputs. A simplified physical model or transfer function describing the transmission of the impact force from the point of application to the steering wheel torque sensor can be preset.

[0136] For example, it can be modeled as a second-order system with specific attenuation and delay characteristics. When a collision occurs, the system uses this model and event parameters to estimate the theoretical waveform of the disturbance torque in real time. Finally, the estimated disturbance waveform is subtracted from the original hand torque signal to obtain the compensated effective hand torque. Thus, interference cancellation is achieved directly from a physical mechanism perspective.

[0137] Smoothing filtering algorithm based on preset time window: The principle of this algorithm is to smooth the signal in the time domain based on statistical characteristics.

[0138] The system sets a fixed or adaptive preset time window (e.g., 300-500 milliseconds) starting from the moment the collision event is detected. The algorithm assumes that within this time window, the high-frequency, large-amplitude fluctuations in the hand torque signal are mainly caused by the collision impact.

[0139] Therefore, within this time window, the system applies a powerful smoothing filter, such as a moving average filter or a low-pass filter, to the original signal. This filter has a low cutoff frequency to remove high-frequency noise representing the impact, while retaining signal components representing steady-state or low-frequency corrective torques that the driver may be applying. After the time window ends, the filter strength returns to normal. Thus, signal filtering is achieved through signal processing, with low dependence on the physical model.

[0140] In some embodiments, the hand torque filtering algorithm is calibrated and associated with the specific model or parameters of the vehicle steering system.

[0141] When the system applies the modeling compensation algorithm, the parameters of the transfer function model (such as stiffness and damping coefficient) used are not fixed values, but are dynamically loaded according to the steering system characteristics of the vehicle model in the vehicle configuration database.

[0142] This allows the same algorithm to be adapted to vehicles with different steering structures, ensuring the accuracy of collision interference torque estimation and improving the platform applicability and reliability of the solution.

[0143] S304. If the effective hand torque is greater than the preset takeover threshold, the combined driving assistance function will be deactivated.

[0144] Specifically, after obtaining the filtered effective hand torque, the system compares it with a preset takeover threshold. This threshold represents the minimum steady-state torque level that the system requires to determine if the driver has actively taken over control of the vehicle. It is typically determined through vehicle calibration tests to distinguish it from unintentional grip torque or minor corrections.

[0145] If the comparison result shows that the effective hand torque is consistently greater than (or exceeds) the threshold within a specific time integral, it indicates that the driver maintained a clear sense of control and a clear willingness to take over after experiencing a collision.

[0146] At this point, the system should follow the "driver priority" principle and execute an orderly exit procedure. That is, the combined driver assistance functions (especially the lateral control part) will smoothly release control of the steering wheel, completely returning the responsibility for the vehicle's lateral trajectory decision-making and execution to the driver.

[0147] The system exit process must ensure a smooth transition of power steering to avoid sudden loss of control that could lead to vehicle instability and ensure a safe handover.

[0148] In some embodiments, the takeover threshold is not limited to a preset fixed value, but can be dynamically updated according to actual conditions. In this case, the steps include:

[0149] Step B1: Obtain the vehicle's current driving status parameters and road environment parameters.

[0150] Specifically, the system first needs to acquire the key parameters that determine the threshold adjustment. These driving state parameters may include the vehicle's real-time speed, long-term statistical values ​​of lateral acceleration (used to assess current road curvature or driving style), etc. Road environment parameters can be derived from the perception results of onboard sensors, such as determining the current road type (highway, city, curve) through a forward-facing camera or map data, lane width, or the presence of construction zones. These parameters reflect the complexity of the driving task and the demands on the driver's attention.

[0151] Step B2: Calculate and update the preset takeover threshold value based on driving status parameters and road environment parameters.

[0152] Specifically, in the implementation, the system can have a built-in threshold calculation function or mapping table to realize the conversion of the takeover threshold.

[0153] For example, when a vehicle is traveling at a high speed on a straight, wide highway, the system can appropriately increase the takeover threshold, because at this time, the driver's slight grip or corrective torque does not necessarily mean a strong intention to take over, and increasing the threshold can reduce false triggering.

[0154] Conversely, when the system detects that the vehicle is going through a sharp bend or at a complex urban intersection, the takeover threshold can be appropriately lowered, making the system more sensitive to the driver's intentions and making it easier for the driver to take over when needed.

[0155] Through this dynamic adjustment, the system can achieve a better balance between security and user experience in different scenarios.

[0156] S305. If the effective hand torque is not greater than the preset takeover threshold, the combined driving assistance function is controlled to maintain lateral control of the current lane and execute the safe parking procedure.

[0157] Specifically, when the filtered effective hand torque is not greater than (i.e. less than or equal to) the preset takeover threshold, it indicates that the driver has not demonstrated a clear and forceful intention to take over. This may be due to the driver being temporarily incapacitated during the collision, being in a state of shock and unable to react in time, or subjectively judging that the collision was minor and did not require intervention.

[0158] At this point, the safety fallback strategy provided by this solution is needed to prevent the vehicle from losing control due to a system misjudgment and exit.

[0159] Specifically, the system will not disengage from the driver assistance function at this time; instead, it will enhance its control role.

[0160] First, the system controls the combined driving assistance functions to maintain lateral control of the current lane. This means that the lane keeping module will be activated to a higher priority or stronger intervention mode. Based on the clear lane lines perceived by the front camera, the system applies the necessary corrective torque through the steering system to ensure that the vehicle stays stably in the center of the current lane, effectively counteracting vehicle deviation that may be caused by collision inertia or the driver's unconscious release of the steering wheel.

[0161] In some embodiments, while maintaining lateral control of the current lane using the combined driving assistance functions, the system provides the driver with clear takeover status prompts and system action notifications through the human-machine interface. The prompts not only indicate that a collision event has been detected, but also clearly explain that the system is currently in "automatically maintaining the lane and safely stopping" mode, and continuously display the progress of the safe stopping process (e.g., "decelerating" or "about to stop"). This helps to calm the driver in emergency situations, reduce panic-induced misoperations due to misunderstanding of system behavior, and enhance trust and collaboration in human-machine co-driving.

[0162] In parallel, the system also executes a safe parking procedure to ensure maximum vehicle safety.

[0163] In some embodiments, the safe parking process includes the following steps:

[0164] Step C1: Control the vehicle to keep driving in the current lane.

[0165] Specifically, during deceleration, the system continuously runs an enhanced lane-keeping algorithm to ensure that the vehicle remains within its lane throughout the entire deceleration to stop trajectory, avoiding collisions with vehicles in adjacent lanes or roadside obstacles.

[0166] Step C2: While maintaining lateral control, initiate longitudinal deceleration control of the vehicle and monitor the vehicle's stationary status.

[0167] Specifically, the system coordinates and controls the powertrain and braking system to initiate a smooth but firm longitudinal deceleration. The deceleration curve is carefully designed, typically including an initial slow deceleration phase with a small absolute value of acceleration, and a slow braking phase near a stop (at which point the absolute value of acceleration may decrease further), to avoid causing discomfort to the occupants or the risk of rear-end collisions.

[0168] The system monitors the vehicle's actual deceleration, speed, and estimated distance to complete stop in real time throughout the entire process.

[0169] Step C3: When the vehicle is detected to have come to a complete stop, the safe parking process ends.

[0170] Specifically, when the system confirms through information such as wheel speed that the vehicle speed has dropped to zero and remained stable (for example, for 1 second), it determines that the vehicle has come to a safe stop.

[0171] At this point, the safe parking process is complete. The system can automatically engage the parking gear, illuminate the hazard warning lights, and simultaneously notify the driver and passengers via the human-machine interface that "the vehicle has automatically and safely stopped due to the detection of a collision event."

[0172] Thus, the system successfully completed the hazard avoidance task in the event that the driver might be "absent," minimizing the occurrence of secondary accidents.

[0173] In some embodiments, when executing the safe stopping procedure, the system first uses onboard sensors (such as millimeter-wave radar and ultrasonic radar) to quickly scan the traffic environment behind and to the sides of the lane before initiating longitudinal deceleration control. If a rapidly approaching vehicle is detected from behind, the system dynamically adjusts its deceleration strategy, such as maintaining the current speed or only slightly decelerating in the initial stage, and simultaneously activating hazard warning lights to prioritize avoiding the risk of being rear-ended; once a safe distance is established behind, the system proceeds to a complete stop. This incorporates surrounding traffic participants into the decision-making loop, further enhancing the overall safety of the evasive maneuver.

[0174] The combined driving assistance function hand torque processing method provided in this disclosure significantly improves the accuracy and reliability of collision event recognition by using multi-condition fusion judgment based on IMU lateral acceleration, yaw rate, and four-wheel wheel speed information. Furthermore, by employing a dedicated filtering algorithm based on modeling compensation or time window smoothing, it can accurately remove strong interference components generated by the collision impact in the original hand torque signal, thus obtaining a pure and effective hand torque. Finally, by combining a dynamically adjusted takeover threshold with a safe stopping procedure including lane keeping and longitudinal deceleration, vehicle safety is ensured. Therefore, it effectively solves the problem of easily misjudging hand torque under collision conditions, greatly improving the accuracy of driver intent recognition and automatically executing the highest safety level of lane-keeping stability stopping when the driver does not actively take over, effectively eliminating the risk of secondary collisions caused by system erroneous exit, and achieving a significant leap in safety.

[0175] Figure 4 This is a schematic diagram of the structure of a combined driving assistance function hand torque processing device provided in one embodiment of this disclosure. Figure 4 As shown, the combined driving assistance function hand torque processing device 400 includes:

[0176] The acquisition module 410 is used to determine that the current combined driving assistance function is active, and to acquire vehicle motion status information and raw hand torque signal in real time;

[0177] Analysis module 420 is used to determine that a side collision event has occurred based on vehicle motion state information;

[0178] The processing module 430 is used to filter the original hand torque signal to obtain an effective hand torque that represents the driver's true intention.

[0179] The execution module 440 is used to execute the corresponding vehicle control strategy based on the comparison result between the effective hand torque and the preset takeover threshold.

[0180] Optionally, the acquisition module 410 is specifically used to acquire vehicle motion state information including lateral acceleration and yaw rate from the inertial measurement unit and four-wheel wheel speed information from the wheel speed meter.

[0181] Optionally, the analysis module 420 is specifically used to perform fusion analysis on the lateral acceleration, yaw rate and four-wheel speed information, and based on the analysis results, determine the existence of a dynamic response that conforms to the characteristics of a side collision.

[0182] Optionally, the analysis module 420 is specifically used to: determine whether the amplitude of the lateral acceleration exceeds a first dynamic threshold; determine whether the amplitude of the yaw rate exceeds a second dynamic threshold; analyze the wheel speed information of the four wheels to determine whether a wheel speed characteristic indicating unilateral obstruction occurs; and determine that a side collision event has occurred when the lateral acceleration, yaw rate, and wheel speed characteristics all meet their respective judgment conditions.

[0183] Optionally, the processing module 430 is specifically used to filter the interference torque component generated by the collision impact transmitted through the steering mechanism in the original hand torque signal based on a filtering algorithm. The filtering process includes attenuation processing or elimination processing. If the filtering algorithm is an algorithm that models and compensates the interference torque component based on the feature parameters of the side collision event, or an algorithm that smooths the original hand torque signal within a preset time window.

[0184] Optionally, the execution module 440 is specifically used to: if the effective hand torque is greater than the preset takeover threshold, exit the combined driving assistance function; if the effective hand torque is not greater than the preset takeover threshold, control the combined driving assistance function to maintain lateral control of the current lane and execute the safe parking procedure.

[0185] Optionally, the execution module 440 is specifically used to control the vehicle to keep traveling along the current lane; while maintaining lateral control, initiate longitudinal deceleration control of the vehicle and monitor the vehicle's stopping status; and when the vehicle is detected to have come to a complete stop, end the safe parking process.

[0186] Optionally, the execution module 440 is further configured to acquire the vehicle's current driving status parameters and road environment parameters; and calculate and update the value of the preset takeover threshold based on the driving status parameters and road environment parameters.

[0187] In this embodiment, the combined driving assistance function hand torque processing device solves the problem in related technologies that hand torque processing under abnormal working conditions is prone to misjudgment and affects driving safety by combining various modules.

[0188] Figure 5 This is a schematic diagram of the structure of a control device provided in one embodiment of the present disclosure, as shown below. Figure 5 As shown, the control device 500 includes a memory 510 and a processor 520.

[0189] The memory 510 stores a computer program that can be executed by at least one processor 520. This computer program is executed by at least one processor 520 to enable the control device to implement the combined driving assistance function hand torque processing method provided in any of the above embodiments.

[0190] The memory 510 and the processor 520 can be connected via a bus 530.

[0191] The relevant explanations can be understood by referring to the corresponding descriptions and effects in the method embodiments, and will not be repeated here.

[0192] One embodiment of this disclosure provides a computer-readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the combined driving assistance function hand torque processing method provided in any of the above embodiments.

[0193] The computer-readable storage medium may be ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0194] One embodiment of this disclosure provides a computer program product comprising computer-executable instructions that, when executed by a processor, are used to implement the combined driving assistance function hand torque processing method provided in any of the above embodiments.

[0195] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0196] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments. The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification.

[0197] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0198] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for handling hand torque in a combination of driving assistance functions, characterized in that, Includes the following steps: Determine that the current combination of driving assistance functions is active, and acquire vehicle motion status information and raw hand torque signals in real time; Based on vehicle motion state information, a side collision event is determined to have occurred; The original hand torque signal is filtered to obtain an effective hand torque that represents the driver's true intention; Based on the comparison result between the effective hand torque and the preset takeover threshold, the corresponding vehicle control strategy is executed.

2. The method according to claim 1, characterized in that, The vehicle motion state information includes lateral acceleration and yaw rate from the inertial measurement unit and four-wheel speed information from the wheel speed meter; The determination of a side collision event based on vehicle motion state information includes: The lateral acceleration, yaw rate, and four-wheel speed information are fused and analyzed, and based on the analysis results, it is determined that there is a dynamic response that conforms to the characteristics of a side collision.

3. The method according to claim 2, characterized in that, The process involves fusing and analyzing the lateral acceleration, yaw rate, and four-wheel speed information, and based on the analysis results, determining the existence of a dynamic response consistent with side-impact characteristics, including: Determine whether the amplitude of the lateral acceleration exceeds a first dynamic threshold; Determine whether the amplitude of the yaw rate exceeds the second dynamic threshold; Analyze the wheel speed information of the four wheels to determine whether there are wheel speed characteristics that indicate unilateral obstruction; When the lateral acceleration, yaw rate, and wheel speed characteristics all meet their respective judgment conditions, the lateral collision event is determined to have occurred.

4. The method according to claim 1, characterized in that, The filtering process of the original hand torque signal to obtain an effective hand torque that represents the driver's true intention includes: Based on the filtering algorithm, the interference torque component generated by the collision impact transmitted through the steering mechanism in the original hand torque signal is filtered. The filtering process includes attenuation processing or elimination processing. The filtering algorithm is an algorithm that models and compensates the interference torque component based on the feature parameters of the side collision event, or an algorithm that smooths the original hand torque signal within a preset time window.

5. The method according to claim 4, characterized in that, The process of executing a corresponding vehicle control strategy based on the comparison result between the effective hand torque and the preset takeover threshold includes: If the effective hand torque is greater than the preset takeover threshold, then the combined driving assistance function is deactivated. If the effective hand torque is not greater than the preset takeover threshold, the combined driving assistance function is controlled to maintain lateral control of the current lane and execute a safe parking procedure.

6. The method according to claim 5, characterized in that, The execution of the safe parking procedure includes: Control the vehicle to maintain its current lane; While maintaining lateral control, initiate longitudinal deceleration control of the vehicle and monitor the vehicle's stationary status; The safe parking process ends when the vehicle is detected to have come to a complete stop.

7. The method according to any one of claims 1 to 6, characterized in that, The method further includes: Obtain the vehicle's current driving status parameters and road environment parameters; Based on the driving status parameters and road environment parameters, the value of the preset takeover threshold is calculated and updated.

8. A combined driving assistance function hand torque processing device, characterized in that, include: The acquisition module is used to determine whether the current combined driving assistance function is active and to acquire vehicle motion status information and raw hand torque signal in real time; The analysis module is used to determine whether a side collision event has occurred based on vehicle motion state information; The processing module is used to filter the original hand torque signal to obtain an effective hand torque that represents the driver's true intention. The execution module is used to execute the corresponding vehicle control strategy based on the comparison result between the effective hand torque and the preset takeover threshold.

9. A control device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1 to 7.

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