Simulation method and simulation device for driving assistance system, driving assistance system, and vehicle

Abstract

The invention provides a simulation method and a simulation device of a driving assistance system, the driving assistance system and a vehicle. The simulation method is used for simulating a driving control function in a driving assistance system and comprises the steps that actual test data of a target vehicle are acquired, and the actual test data comprise driving parameters of the target vehicle; recharging the actual test data into the simulation model with the driving control function for simulation; wherein the driving parameters are processed by the simulation model, so that the simulation vehicle in the simulation model continues to drive forwards according to the speed and the direction of the target vehicle at the first moment starting from the first moment, and the first moment is the moment, recorded in the actual test data, of triggering the driving control function by the target vehicle. The problem that the triggering rate of the driving control function of the simulated vehicle is low when actual test data is adopted for recharge simulation is solved.

Description

Technical Field

[0001] The present disclosure relates to the field of driving assistance technology, and in particular to a simulation method and a simulation device for a driving assistance system, a driving assistance system, and a vehicle. Background Art

[0002] The performance test of vehicle driving control function is usually completed using the re-injection simulation method. Re-injection simulation refers to injecting the actual driving data of the collected vehicle into the simulation system to simulate and drive the simulated vehicle to drive in the simulation system, so as to make driving decisions such as deceleration and turning.

[0003] However, the above-mentioned recharge simulation method has a problem of low trigger rate in the actual test of driving control function. In other words, the simulated vehicle cannot make driving decisions such as deceleration and turning during driving. Summary of the invention

[0004] In view of this, the embodiments of the present disclosure are dedicated to providing a simulation method, a simulation device, a driving assistance system and a vehicle for a driving assistance system.

[0005] In a first aspect, an embodiment of the present disclosure provides a simulation method for a driving assistance system, wherein the simulation method is used to simulate a driving control function in the driving assistance system, and the simulation method comprises: obtaining actual test data of a target vehicle, wherein the actual test data comprises driving parameters of the target vehicle; and injecting the actual test data back into a simulation model of the driving control function for simulation; wherein the simulation model processes the driving parameters so that, starting from a first moment, the simulated vehicle in the simulation model continues to travel forward at the speed and direction of the target vehicle at the first moment, wherein the first moment is the moment when the target vehicle triggers the driving control function recorded in the actual test data.

[0006] As a possible implementation, the driving parameters include one or more of the following: longitudinal speed parameters, lateral angle parameters, and the simulation model processes the driving parameters including: changing the longitudinal speed parameters of the simulated vehicle so that the simulated vehicle continues to move forward from the first moment at the speed of the target vehicle at the first moment; and / or changing the lateral angle parameters of the simulated vehicle so that the simulated vehicle continues to move forward from the first moment at the direction of the target vehicle at the first moment.

[0007] As a possible implementation manner, the longitudinal speed parameter includes a longitudinal acceleration, and the changing of the longitudinal speed parameter of the simulated vehicle includes: removing the longitudinal acceleration of the simulated vehicle at the first moment.

[0008] As a possible implementation manner, the lateral angle parameter includes a steering wheel angle, and changing the lateral angle parameter of the simulated vehicle includes: removing the steering wheel angle of the simulated vehicle at the first moment.

[0009] As a possible implementation manner, removing the steering wheel angle of the simulated vehicle at the first moment includes: if the steering wheel angle of the target vehicle at the first moment is greater than a first threshold, removing the steering wheel angle of the simulated vehicle at the first moment.

[0010] As a possible implementation manner, the first threshold is greater than or equal to 10 degrees.

[0011] In a second aspect, an embodiment of the present disclosure provides a simulation device of a driving assistance system, wherein the simulation device is used to simulate a driving control function in the driving assistance system, and the simulation device includes: an acquisition module, used to acquire actual test data of a target vehicle, wherein the actual test data includes driving parameters of the target vehicle; a simulation module, used to inject the actual test data back into a simulation model of the driving control function for simulation; wherein the simulation model processes the driving parameters so that, starting from a first moment, the simulated vehicle in the simulation model continues to travel forward at the speed and direction of the target vehicle at the first moment, wherein the first moment is the moment when the target vehicle triggers the driving control function recorded in the actual test data.

[0012] In a third aspect, an embodiment of the present disclosure provides a simulation device for a driving assistance system, wherein the simulation device is used to simulate a driving control function in the driving assistance system, and the simulation device comprises: a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the computer program is executed by the processor, the steps of any simulation method in the first aspect are implemented.

[0013] In a fourth aspect, an embodiment of the present disclosure provides a driving assistance system, wherein a driving control function in the driving assistance system is implemented by any simulation method in the first aspect.

[0014] In a fifth aspect, an embodiment of the present disclosure provides a vehicle, the vehicle comprising a driving assistance system, wherein a driving control function in the driving assistance system is implemented by any simulation method in the first aspect.

[0015] The disclosed embodiment processes the driving parameters in the actual test data so that the simulated vehicle continues to travel forward at the speed and direction at the triggering moment of the driving control function of the target vehicle, thereby avoiding the influence of the driving parameters of the target vehicle on the triggering of the driving control function of the simulated vehicle, thereby improving the trigger rate when the driving control function in the driving assistance system is re-injected simulated using the actual test data. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The figure is a flow chart of the simulation method of the driving assistance system provided by the embodiment of the present disclosure.

[0017] Figure 2 Shown is a schematic diagram of a simulation process of a driving assistance system provided by an embodiment of the present disclosure.

[0018] Figure 3 Shown is a schematic diagram of a simulation process of a driving assistance system provided by another embodiment of the present disclosure.

[0019] Figure 4 Shown is a schematic diagram of the structure of a simulation device for a driving assistance system provided in one embodiment of the present disclosure.

[0020] Figure 5 Shown is a schematic structural diagram of a simulation device for a driving assistance system provided in another embodiment of the present disclosure.

[0021] Figure 6 Shown is a schematic diagram of the structure of a driving assistance system provided by an embodiment of the present disclosure.

[0022] Figure 7 Shown is a schematic diagram of the structure of a transportation vehicle provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0024] The driver assistance system is an important update applied to modern transportation. It aims to provide instant assistance and support to the driver by monitoring the driving status of the vehicle and the surrounding environment in real time through intelligent sensors and advanced algorithms. Such systems usually integrate multiple functions, such as emergency braking, lane keeping, cruise control, etc., which can help drivers avoid potential dangers at critical moments and improve driving safety.

[0025] For example, Advanced Driver Assistance Systems (ADAS) can obtain environmental data through sensors such as cameras and radars, and then process and analyze the environmental data through software and hardware systems to identify and judge traffic conditions such as road conditions, sea conditions, and weather conditions, thereby providing information and driving assistance to drivers. When potential danger is predicted, ADAS will warn the driver and can even take active intervention measures such as emergency braking.

[0026] The functions of the driving assistance system can be generally divided into two categories: driving control functions and non-driving control functions. Non-driving control functions focus on providing information and warnings to drivers to enhance safety and convenience. For example, the Forward Collision Warning (FCW) function warns the driver of potential collision risks in advance by detecting traffic conditions ahead, allowing the driver to take timely action. Another example is the Blind Spot Detection (BSD) function, which can warn the driver when other vehicles are detected in the blind spot, thereby reducing the risk of lane change accidents.

[0027] The driving control function of the driving assistance system can control the driving of the vehicle, for example, the speed and direction of the vehicle. In other words, the driving control function of the driving assistance system can assist the driver in better controlling the vehicle. It should be noted that in addition to controlling the driving of the vehicle, the driving control function of the driving assistance system may have other auxiliary functions (such as a warning function), which is not limited in the embodiments of the present disclosure.

[0028] The embodiments of the present application do not limit the driving control functions of the driving assistance system. For example, the driving control functions may include the Autonomous Emergency Braking (AEB) function, the Lane Keeping Assist (LKA) function, the Adaptive Cruise Control (ACC) function, and the Automatic Parking Assist (APA) function. It should be noted that in addition to the driving control functions listed above, other driving control functions that can control the driving of vehicles introduced in future driving assistance systems (such as ADAS) also fall within the scope of protection of the present disclosure.

[0029] Among them, the AEB function can detect the traffic status ahead through sensors (such as radar and cameras). When it is judged that the vehicle is about to get too close to the obstacle ahead and there is a risk of collision, the AEB function will first alert the driver through an alarm. If the driver does not respond in time, the AEB function will automatically apply braking such as deceleration or lateral avoidance to help reduce the severity of the collision or even completely avoid the accident.

[0030] The LKA function can identify lane markings through a camera and warn the driver or perform driving control when the vehicle unintentionally deviates from the lane. The LKA function usually includes sub-functions such as Lane Departure Warning (LDW), Lane Departure Prevention (LDP) and Lane Centering Control (LCC). These functions can remind the driver through sound, visual or steering wheel vibration, or automatically make slight steering adjustments, such as automatically adjusting the steering wheel, to help the driver keep the vehicle in the center of the lane (or correct its course when a ship is detected to have deviated from its course, or correct its course when a flying vehicle is detected to have deviated from its flight path).

[0031] The ACC function monitors the traffic conditions ahead through radar or camera, automatically controls the accelerator and brake to adjust the driving speed and maintain a safe distance, thereby reducing the driver's operating burden and improving safety.

[0032] In addition, the APA function can identify suitable parking spaces through ultrasonic sensors or cameras installed around the vehicle body, and automatically control the vehicle's steering, acceleration and braking to achieve precise and safe parking.

[0033] In the development and testing process of the driving assistance system, commonly used testing methods include the re-injection simulation method. The re-injection simulation method involves injecting the actual driving data of a vehicle (such as a vehicle) into a simulation environment to verify and optimize the performance of the driving assistance system. Specifically, the actual collected driving data (sensor data, camera images, GPS information, environmental data, etc.) is input into the simulation system, so that the simulated vehicle equipped with the driving assistance system function to be tested in the simulation system can simulate the driving process of the real vehicle and trigger the corresponding driving assistance function under the drive of the driving data, thereby completing the performance verification and optimization of the driving assistance system. This process simulates the real-world driving scene, allowing engineers and other relevant personnel to conduct detailed analysis and verification of the performance of the driving assistance system in a controlled environment.

[0034] More specifically, in the testing of driver assistance systems, re-injection simulation can be used to detect the triggering of driving control functions under specific conditions, such as emergency braking, lane keeping, adaptive cruise control, and automatic parking, so as to make necessary adjustments and optimizations to the driving control functions. This method not only improves the safety of testing, but also greatly saves the time and cost of real vehicle testing, allowing the development and testing team to quickly iterate and improve the driving control functions of the driver assistance system.

[0035] However, in the above process, the actual driving data injected into the simulation system may include driving behavior data such as vehicle speed, steering wheel angle, ship speed, heading, and airspeed and heading of flying vehicles, so that the simulated vehicle does not trigger its driving control function under certain conditions, but instead performs corresponding driving controls including emergency braking, lane keeping, adaptive cruise control and automatic parking according to the existing driving behavior (data), resulting in a low trigger rate of the driving control function of the simulated vehicle and poor development and testing performance of the driving assistance system.

[0036] For example, a pure re-injection simulation method is used in the vehicle's AEB function test, that is, the re-injection simulation is performed directly based on the actual road test data (i.e., driving data, such as sensor data including environmental monitoring, and road test data including vehicle speed or steering wheel angle, etc.). In this case, the speed of the simulated vehicle's AEB function is consistent with that of the shadow vehicle (actual vehicle) when it is triggered. Therefore, the simulated vehicle may decelerate longitudinally with the shadow vehicle after the AEB function is triggered, resulting in the failure to trigger the simulated vehicle's own AEB function; or, because the shadow vehicle's own triggering time is short, the simulated vehicle has already performed lateral avoidance with the shadow vehicle within a short time after the AEB function is triggered, resulting in the failure to trigger the simulated vehicle's AEB function.

[0037] For another example, in the LKA function test of a ship, the ship driving data collected during the actual voyage (such as speed, heading, and environmental data such as ocean currents and wind speed) is injected into the simulation system. In this way, when the LKA function of the simulated ship is triggered, the heading angle is consistent with that of the shadow ship (the actual ship). Therefore, after the LKA function is triggered, the simulated ship may adjust its lateral heading along with the shadow ship, causing the LKA function of the simulated ship to fail to be triggered.

[0038] For another example, in the ACC function test of an aircraft, the data collected during the actual flight (position, climate, speed, attitude, etc.) are fed back for simulation. Since the ACC function of the simulated aircraft is consistent with the speed of the actual aircraft when it is triggered, the simulated aircraft may decelerate longitudinally with the actual aircraft after the ACC function adaptive deceleration is triggered, resulting in the failure to trigger the ACC function.

[0039] For another example, in the APA function test of the vehicle, the actual parking data of the vehicle in the actual road test (such as sensor data, vehicle speed and steering wheel angle, etc.) is injected into the simulation system. Since the running state of the simulated vehicle is the same as that of the shadow vehicle when the APA function is triggered, the simulated vehicle may park like the shadow vehicle after the APA function is triggered (including longitudinal acceleration or deceleration, and / or lateral steering wheel angle, etc.), resulting in the failure to trigger the APA function of the simulated vehicle.

[0040] It should be understood that the above examples are only for illustration and are not intended to limit the application scenarios of the driving control function. For example, the AEB function can be applied to other vehicles such as ships and aircraft, in addition to vehicles. The same is true for the ACC function, LKA function and APA function, which will not be elaborated here.

[0041] In view of the problem of low trigger rate when using actual test data to simulate the driving control function, the embodiment of the present disclosure proposes a simulation method. The method processes the driving parameters in the actual test data during the re-injection simulation, so that the simulated vehicle starts from the triggering moment of the driving control function of the target vehicle and continues to move forward at the speed and direction of the triggering moment, so as to avoid the influence of the driving parameters of the target vehicle on the triggering of the driving control function of the simulated vehicle, thereby improving the trigger rate when using actual test data to simulate the driving control function in the driving assistance system. The simulation method proposed in the embodiment of the present disclosure can be applied to the re-injection simulation of the driving assistance system, including but not limited to any of the driving control functions mentioned above.

[0042] Figure 1 The following is a flow chart of the simulation method provided by the embodiment of the present disclosure. It should be understood that Figure 1 This is for illustration only and any Figure 1 Simple improvements to the simulation method based on this method fall within the scope of protection of this disclosure. Figure 1 As shown, in step S110, actual test data of the target vehicle is obtained.

[0043] The target vehicle refers to a physical vehicle. The actual test data collected by the target vehicle can be used by the simulated vehicle in the simulation model, that is, the simulated vehicle can use the actual test data collected by the target vehicle to perform simulation (i.e., re-injection simulation) to test and / or optimize the performance of the driving control function. Therefore, in some embodiments, the target vehicle can also be referred to or understood as a physical vehicle, an actual vehicle, a shadow vehicle of a simulated vehicle, etc.

[0044] In the simulation method provided in the embodiment of the present disclosure, the target vehicle can be equipped with high-quality sensors and data recording equipment to ensure that its driving parameters such as speed, position and driving direction, as well as environmental parameters such as traffic conditions, can be accurately collected, thereby providing real simulation test data and providing accurate environmental input for the simulation model to ensure the authenticity and complexity of the simulation environment, so that the simulation test of the driving control function is closer to the actual driving scenario.

[0045] The embodiments of the present disclosure do not limit the implementation method of the driving control function of the target vehicle. In some embodiments, the driving control function of the target vehicle can be manually triggered by the driver. For example, when the driver of the vehicle finds an obstacle ahead while driving on the road, he can manually brake to achieve emergency braking. For another example, the driver of the vehicle can also brake in time to avoid the obstacle when the AEB function issues a roadblock warning.

[0046] In other embodiments, the driving control function module equipped in the target vehicle can be actively triggered to control the driving of the target vehicle without the need for manual triggering by the driver under certain conditions. For example, when a courier drone flies over a city, its ACC function can actively sense buildings and wind speed, adjust the flight speed in real time to avoid obstacles and maintain an efficient and safe flight state by optimizing the route. For another example, when a helicopter equipped with the ACC function suddenly detects an obstacle ahead while flying at low altitude and the driver does not brake in time, the ACC function system immediately issues an alarm and automatically decelerates to avoid collision and ensure flight safety.

[0047] The disclosed embodiments do not limit the type of target vehicle. In some embodiments, the target vehicle may be a smart driving vehicle specifically used for test data collection. Smart driving vehicles are equipped with various sensors (such as lidar, camera, ultrasonic sensor, GPS), which can obtain surrounding environment information in real time, and can record a large amount of data (such as motion status, surrounding environment, traffic conditions) at a high frequency.

[0048] For example, using an intelligent driving data collection vehicle as the target vehicle can obtain information about the surrounding environment in real time during driving, and can also record a large amount of data including speed, steering wheel angle, road conditions, etc. at a high frequency.

[0049] In other embodiments, the target vehicle may also be a vehicle that has passed the design and testing phase and has officially entered the market and is mass-produced. For example, a mass-produced vehicle can collect real and diverse data in an actual driving environment, including driving behavior, vehicle dynamics, environmental conditions, etc. These data provide rich inputs for the re-injection simulation, making the simulation results closer to reality.

[0050] The disclosed embodiments do not limit the type of target vehicle. In some embodiments, a vehicle can be used as the target vehicle, for example, data (including sensor data, driving behavior data, etc.) of the vehicle during actual road driving can provide actual test data for the simulated vehicle in the simulation model.

[0051] Since the navigation data of the ship under different sea conditions (including data such as the ship's position, speed, heading and surrounding environment) can be used to test the driving control function of the ship's driving assistance system in the recharge simulation, in other embodiments, the ship can also be used as a target vehicle.

[0052] In some other embodiments, an aircraft may be used as a target vehicle. For example, the performance of the flight (driving) control system may be evaluated based on the re-injection simulation by collecting data of the aircraft in actual flight, such as speed, attitude, and external environment such as wind speed or wind direction.

[0053] It should be understood that the types of target vehicles listed above are merely illustrative and do not constitute a limitation on the types of target vehicles. Any vehicle that can provide actual test data and apply it to the re-injection simulation to test its driving control function can be used as a target vehicle.

[0054] Actual test data refers to detailed information about vehicle performance, status, and surrounding environment collected by various sensors, data recording devices, and monitoring systems during the actual operation of the target vehicle. In the disclosed embodiment, the actual test data includes driving parameters and environmental parameters.

[0055] The driving parameters are a series of dynamic data generated by the target vehicle during driving, which reflect the vehicle's motion state and performance. In the disclosed embodiment, in order to describe the driving control performance of the target vehicle and the simulated vehicle in more detail, based on the running trajectory of the target vehicle on the two-dimensional plane, the driving parameters may further include longitudinal speed parameters and lateral angle parameters.

[0056] The longitudinal speed parameter refers to the dynamic data generated when the target vehicle is traveling along its main driving direction, such as the speed and acceleration generated when the vehicle is traveling forward.

[0057] The lateral angle parameter refers to the dynamic data generated when the target vehicle has a rotation angle on a plane relative to its main driving direction, which can be used to indicate the lateral (i.e., sideways) deflection of the target vehicle. For example, the angle between the projection of the vehicle's forward direction on the ground and the north direction (or other reference directions, such as the center angle of the road), that is, the heading angle (Heading Angle); another example is the lateral offset or slippage of a ship relative to its longitudinal axis (centerline of the hull) during navigation, that is, the sideslip angle (Sideslip Angle); another example is the yaw angle, that is, the rotation angle of the vehicle around its vertical axis (Z axis), that is, the deflection of the vehicle's head relative to its initial or desired direction. Among them, compared with the heading angle, the yaw angle focuses more on the dynamic rotation of the vehicle body.

[0058] In addition to driving parameters, in the embodiments of the present disclosure, the actual test data also includes environmental parameters. Environmental parameters refer to external environmental information related to the actual operation of the target vehicle in a specific scenario. In some embodiments, environmental parameters may include road conditions, such as road surface type, roughness, and friction coefficient. In other embodiments, environmental parameters may also include traffic conditions, such as traffic density, flow, etc. In some other embodiments, environmental parameters may also include meteorological parameters, such as temperature, humidity, wind speed, and precipitation. The embodiments of the present disclosure do not limit the specific content of the environmental parameters. As long as it is external environmental information that affects the driving control function of the target vehicle, it is within the scope of the present disclosure.

[0059] The disclosed embodiments do not limit the source of actual test data. In some embodiments, the actual test data may come from a variety of sensors of the target vehicle. For example, real-time position data is obtained based on GPS, and the velocity, acceleration components, and environmental parameters recorded by cameras and radars in two or three dimensions are obtained by an inertial measurement unit (IMU). In other embodiments, the actual test data may also come from external data sources. For example, road and traffic data may also be obtained through road sensors and traffic detection systems.

[0060] Based on the unlimited source of actual test data, the embodiments of the present disclosure do not limit the method of obtaining actual test data. In some embodiments, the actual test data can be collected by various sensors carried by the target vehicle and stored or transmitted through a related (e.g., vehicle-mounted) computing platform. In other embodiments, real-time and historical data can also be obtained through cooperation with meteorological services and traffic management departments.

[0061] The actual test data obtained based on one or more of the above acquisition methods can be used directly in the embodiments of the present disclosure, or can be processed and analyzed using data analysis tools to improve the reliability and accuracy of the data.

[0062] After obtaining the actual test data of the target vehicle, such as Figure 1 As shown, in step S120, the actual test data is fed back into the simulation model of the driving control function for simulation.

[0063] The simulation model simulates actual driving scenarios and target vehicle behaviors, allowing engineers and other relevant personnel to reproduce and analyze actual driving data in a virtual environment to evaluate and optimize the performance and safety of the driver assistance system while reducing the risks and costs of actual testing.

[0064] In the disclosed embodiment, the simulation model at least includes a dynamic model for simulating the physical movement of the target vehicle, such as speed, acceleration and steering response, and a control and decision model that reflects the core logic of the driving assistance system and performs the driving control function. In addition, in the disclosed embodiment, it can also include a sensor model for simulating the behavior of sensors such as cameras, lidars, and millimeter radar waves to generate perception data similar to the real world; an environmental model that covers roads (or routes), traffic, and weather, etc., to provide realistic background information; and a traffic flow model that simulates the dynamic behavior of surrounding vehicles and pedestrians to achieve the reproduction of complex traffic scenes.

[0065] In step S120, after the actual test data is fed back into the simulation model, the performance of the simulated vehicle in the virtual environment is observed, and the relevant data and test results are recorded. These test results are used to evaluate the performance of the driving control function in the driver assistance system, including whether it is responsive, response time, stability and safety. When the test results do not meet expectations, the driving control function may need further adjustment and optimization.

[0066] In the disclosed embodiment, the simulation model can process the driving parameters in the actual test data so that starting from the first moment, the simulated vehicle in the simulation model continues to move forward at the speed and direction of the target vehicle at the first moment.

[0067] The first moment refers to the moment when the target vehicle triggers the driving control function recorded in the actual test data, that is, the triggering moment. For example, in the AEB function test of the simulated vehicle, the first moment refers to the moment when the emergency braking function of the target vehicle is triggered.

[0068] It should be understood that, starting from the first moment, the simulated vehicle will continue to move forward according to the speed and direction of the target vehicle (or itself) at the first moment. For example, in the AEB function test, starting from the first moment, the simulated vehicle does not substantially decelerate according to the driving parameters of the target vehicle, and still moves forward according to the motion state of the target vehicle (or itself) at the first moment. For another example, in the AEB function test, starting from the first moment, the simulated vehicle does not turn according to the driving parameters of the target vehicle, and still moves forward according to the direction of the target vehicle (or itself) at the first moment.

[0069] In some embodiments, starting from the first moment, the simulated vehicle continues to travel forward at the speed and direction of the target vehicle at the first moment. It can also be understood that starting from the first moment, the simulated target vehicle no longer continues to travel according to the driving parameters of the target vehicle, but travels according to the driving parameters of the target vehicle at the first moment. In this way, the simulated vehicle and the target vehicle may separate after the first moment. For example, the target vehicle decelerates but does not turn after the first moment, while the simulated vehicle does not decelerate after the first moment, or does not decelerate but turns, or the deceleration of the two is inconsistent, etc.

[0070] It should be noted that the "starting from the first moment" mentioned in the embodiments of the present disclosure is not used to emphasize the length of a period of time after the first moment, but to emphasize that the simulated vehicle no longer maintains the same driving parameters as the target vehicle starting from the first moment. For example, a short period of time after the first moment, the simulated vehicle continues to move forward at the speed and direction of the target vehicle at the first moment, but the simulated vehicle will trigger the driving control function after this short period of time. In this case, the simulated vehicle will take measures such as deceleration and / or steering to control the driving, that is, the simulated vehicle will no longer continue to move forward at the speed and direction of the first moment after a short period of time, but will make its own driving decisions.

[0071] The determination of the first moment usually involves a series of conditions based on driving parameters and environmental parameters, and the first moment refers to the specific time point when the condition is met. The disclosed embodiments do not limit the specific conditions. In some embodiments, the condition may be that the speed reaches a certain value and the distance between the simulated vehicle and the obstacle is shortened to below a safety threshold. For example, the relevant department has set up an overspeed AEB function system for autonomous driving vehicles traveling on highways. When the actual speed of the vehicle exceeds the set maximum speed limit, such as 120 kilometers per hour, this moment is the first moment. In the re-injection simulation, once the speed of the simulated vehicle reaches or exceeds the threshold, the system will take emergency braking.

[0072] In other embodiments, the determination condition may also be any other parameter change related to driving behavior and safety. For example, in urban traffic, if the vehicle's sensor detects that the distance to the obstacle ahead is less than a safe distance, such as 3 meters at a driving speed of 30 kilometers per hour, then when the actual distance is shortened below this threshold, that moment is the trigger moment, that is, the first moment. In the simulation test, when the distance between the simulated vehicle and the obstacle ahead reaches or is less than 3 meters, the AEB function system will be triggered and emergency braking will be implemented to avoid or mitigate the collision.

[0073] In the disclosed embodiment, the processing of driving parameters by the simulation model may include changing the driving parameters of the simulated vehicle, for example, changing the driving parameters of the simulated vehicle after the first moment. In some embodiments, changing the driving parameters of the simulated vehicle includes changing the longitudinal speed parameters of the simulated vehicle so that the simulated vehicle continues to move forward from the first moment at the speed of the target vehicle at the first moment. As an example, after the ACC function of the aircraft is triggered, the flight speed of the simulated aircraft is changed so that the simulated aircraft flies forward at the speed at the moment when the ACC function is triggered. As another example, Figure 2 As shown in FIG. 1 , before the AEB function of the vehicle is triggered (at time T0), the speed of the simulated vehicle (V0_n) is the same as the speed of the actual vehicle (V0_s), that is, V0_n=V0_s, and the motion states of the two are exactly the same, as shown in FIG. Figure 2 As shown in the figure, at time T0, the simulated vehicle and the actual vehicle completely overlap. Starting from the time when the AEB function is triggered (i.e., time T1), the actual vehicle decelerates and its speed is V1_s; while the simulated vehicle still maintains its (or the actual vehicle's) speed at time T1 (V1_n) and continues to move forward. In other words, starting from time T1, the speed of the simulated vehicle is greater than the speed of the actual vehicle (V1_n>V1_s), that is, Figure 2 As shown, from time T1, the simulated vehicle and the actual vehicle body begin to separate.

[0074] In other embodiments, changing the driving parameters of the simulated vehicle may include changing the lateral angle parameters of the simulated vehicle so that the simulated vehicle continues to travel forward in the direction of the target vehicle at the first moment from the first moment. As an example, after the LKA function of the ship is triggered, the course angle of the simulated ship is changed so that the simulated ship continues to sail forward according to the course angle at the moment when the LKA is triggered. As another example, Figure 3 As shown in FIG. 1 , before the AEB function of the vehicle is triggered (at time T0), the steering wheel angle (SW0_n) of the simulated vehicle is the same as the steering wheel angle (SW0_s) of the actual vehicle, that is, SW0_n=SW0_s, and the driving directions of the two are exactly the same, as shown in FIG. Figure 3As shown in the figure, at time T0, the simulated vehicle and the actual vehicle completely overlap. Starting from the moment the AEB function is triggered (i.e., time T1), the actual vehicle performs a turning (obstacle avoidance) operation, and its steering wheel angle is SW1_s; while the simulated vehicle does not perform a turning operation, and maintains its (or the actual vehicle's) driving direction at time T1 (SW1_n) and continues to move forward. In other words, starting from time T1, the steering wheel angle of the simulated vehicle is not equal to the steering wheel angle of the actual vehicle (SW1_n≠SW1_s), that is, Figure 3 As shown, from time T1, the simulated vehicle and the actual vehicle body begin to separate.

[0075] In some other embodiments, changing the driving parameters of the simulated vehicle may include changing the longitudinal speed parameters of the simulated vehicle so that the simulated vehicle continues to drive forward at the speed of the target vehicle at the first moment, and may also include changing the lateral angle parameters of the simulated vehicle so that the simulated vehicle continues to drive forward at the direction of the target vehicle at the first moment. For example, when the APA function of the vehicle is triggered, the speed and driving direction of the simulated vehicle are changed so that the simulated vehicle continues to drive forward at the speed and direction at the time when the APA function is triggered. For another example, when the AEB function of the vehicle is triggered, the speed and driving direction of the simulated vehicle are changed so that the simulated vehicle continues to drive forward at the speed and direction at the time when the AEB function is triggered.

[0076] In some embodiments, changing the longitudinal speed parameter of the simulated vehicle may be to remove the longitudinal acceleration of the simulated vehicle at the first moment, so that the simulated vehicle continues to travel forward at the speed at the first moment from the first moment, so as to avoid the influence of the longitudinal speed parameter on the triggering of the driving control function of the simulated vehicle, thereby improving the triggering rate when the driving control function in the driving assistance system is simulated by back injection using actual test data. As an example, the longitudinal acceleration of the simulated vehicle at the first moment may be removed, so that the simulated vehicle travels forward at a constant speed at the speed at the first moment from the first moment.

[0077] As another example, after removing the longitudinal acceleration of the simulated vehicle at the first moment, the driving speed of the simulated vehicle is allowed to fluctuate up and down with the speed at the first moment or the speed at a certain historical driving moment (during normal driving) as the baseline speed to simulate factors such as uneven roads, wind resistance changes, and slight driving operation adjustments in the real world. As a further example, while the vehicle maintains a baseline speed of 60 kilometers per hour after the first moment, a speed change of ±5 kilometers per hour is allowed to reflect slight acceleration or deceleration that may be encountered in actual driving.

[0078] In other embodiments, changing the longitudinal speed parameter of the simulated vehicle at the first moment may be changing the speed of the simulated vehicle at the first moment. For example, the speed of the simulated vehicle at the first moment may be modified to the average speed before the first moment (which may include the first moment or may not include the first moment), or to the average speed of a certain historical driving time period, or to the instantaneous speed at the first moment. In this way, the speed of the simulated vehicle is different from that of the target vehicle after the first moment, and the simulated vehicle can maintain its own speed to move forward, which is conducive to the simulation model triggering the driving control function.

[0079] Correspondingly, in the disclosed embodiment, changing the lateral angle parameter of the simulated vehicle at the first moment may be changing the steering wheel angle of the simulated vehicle at the first moment, so that the simulated vehicle continues to travel forward in the travel direction of the first moment from the first moment, so as to avoid the influence of the lateral angle parameter on the triggering of the driving control function of the simulated vehicle, thereby improving the triggering rate when the driving control function in the driving assistance system is simulated by the actual test data. In some embodiments, the steering wheel angle after the first moment can be modified to 0, that is, the steering wheel angle of the simulated vehicle after the first moment can be removed.

[0080] It should be understood that the embodiment of the present disclosure aims to change the driving parameters of the simulated vehicle after the first moment to avoid the influence of the driving parameters on the triggering of the driving control function in the re-injection simulation test. Therefore, the present disclosure does not limit its specific changing method. As long as it meets the above purpose, it is within the scope of the present disclosure.

[0081] In the disclosed embodiment, the driving parameters at the first moment can be changed based on the relevant algorithm. As an example, when the AEB function of the simulated vehicle is triggered, if the longitudinal acceleration of the simulated vehicle is not 0, its longitudinal acceleration is changed to 0. As another example, when the AEB function of the simulated vehicle is triggered, if the steering wheel angle of the simulated vehicle is greater than or equal to a first threshold value (for the setting of the first threshold value, see below), its steering wheel angle is changed to 0.

[0082] In the actual driving process, the change of the steering wheel angle may be caused by many factors. For example, the driver (or the driving assistance system) can change the driving direction of the vehicle or perform obstacle avoidance operations by turning the steering wheel. In response to the situation where the steering wheel angle of the target vehicle changes after the first moment, the embodiment of the present disclosure will change the steering wheel angle of the simulated vehicle at the first moment so that the simulated vehicle continues to move forward in the direction of the first moment.

[0083] However, based on the response to external conditions, such as lane keeping, crosswind or uneven road surface, the driver (or the driving assistance system) may need to correct the driving direction of the target vehicle by adjusting the steering wheel.

[0084] Generally, when the driver (or the driving assistance system) needs to change the direction of the vehicle, such as turning or avoiding obstacles, a large steering wheel operation will be performed, resulting in a large steering wheel angle. This steering angle is often larger than the steering angle when the driver (or the driving assistance system) makes fine adjustments to the vehicle.

[0085] As an example, when performing an obstacle avoidance maneuver, the driver may need to turn the steering wheel quickly and sharply to steer around a sudden obstacle. In contrast, the LKA function or LCC function may make smaller steering wheel adjustments to help the vehicle stay in the lane or center, and these adjustments are usually smaller and the resulting steering wheel angle is also smaller.

[0086] Based on this, in the simulation method proposed in the embodiment of the present disclosure, when the steering wheel angle of the target vehicle at the first moment is greater than or equal to the first threshold, the steering wheel angle of the simulated vehicle at the first moment is removed, thereby avoiding erroneous removal of the necessary steering wheel angle at the first moment.

[0087] According to relevant research and statistics, the distribution of steering wheel angles has certain regularities. For example, some studies have pointed out that when a vehicle is driving in a straight line on a macro scale, the driver will constantly make fine adjustments to maintain the vehicle's driving direction, and most of the steering wheel angles corresponding to these fine adjustments are within 10 degrees. This means that if the steering wheel angle exceeds this value, especially reaching 10 degrees, it may indicate that the driver is making a larger direction adjustment, such as an obstacle avoidance operation.

[0088] Based on this, in the disclosed embodiment, the first threshold value may be set to 10 degrees. When the steering wheel angle of the target vehicle at the first moment is less than the threshold value, it may be considered that the target vehicle is performing normal route keeping or slight direction adjustment, and it is not necessary to remove its steering wheel angle. When the steering wheel angle of the target vehicle at the first moment reaches or exceeds 10 degrees, it may be considered that the driver is performing an emergency obstacle avoidance operation, and at this time, it is necessary to remove its steering wheel angle.

[0089] For ease of understanding, the following takes the AEB function of a vehicle as an example to describe in detail the simulation method for improving the triggering rate of the emergency braking function in the driving assistance function proposed in the embodiment of the present disclosure.

[0090] Based on the high-quality sensors and data recording equipment configured in the intelligent driving data collection vehicle, driving parameters such as speed (including speed changes) and driving direction (including direction changes), as well as environmental parameters such as traffic conditions, are collected. In addition, data analysis tools are used to process and analyze the collected driving parameters. The analyzed and processed driving parameters are fed back to the simulation model.

[0091] In Test 1, the intelligent driving collection car decelerated in the driving direction at T1 based on AEB; while the simulation car did not decelerate at T1 because the deceleration parameters were erased. At T1, the body of the simulation car completely overlapped with that of the intelligent driving collection car, and after T1, the two bodies gradually separated. Specifically, the driving directions of the two were still the same, but the intelligent driving collection car was in front and the simulation car was behind.

[0092] In Test 2, the intelligent driving vehicle automatically turned the steering wheel to generate a steering wheel angle based on AEB at T2, and the driving direction of the vehicle changed accordingly (turning right after T2); while the simulation vehicle found that the steering wheel angle was greater than 10 degrees at T2, so the simulation vehicle erased the steering wheel angle parameter and its driving direction did not change. At T2, the vehicle body completely overlapped with the intelligent driving vehicle, and after T2, the two vehicle bodies gradually separated. Specifically, the two are basically consistent in the longitudinal direction, but in the lateral direction, the simulation vehicle is on the left and the intelligent driving vehicle is on the right.

[0093] The method embodiment of the present disclosure is described in detail above, and the device embodiment of the present disclosure is described in detail below. It should be understood that the description of the device embodiment corresponds to the description of the method embodiment, so what is not described in detail can be referred to in the previous method embodiment.

[0094] like Figure 4 FIG. 1 is a schematic diagram of a simulation device for a driving assistance system according to an embodiment of the present disclosure. Figure 4 As shown, the simulation device 400 includes an acquisition module 410, which is used to acquire actual test data of the target vehicle, and the actual test data includes driving parameters of the target vehicle; the simulation device 400 also includes a simulation module 420, which is used to feed the actual test data back into the simulation model of the driving control function for simulation; wherein, the simulation model 420 processes the driving parameters so that, starting from the first moment, the simulated vehicle in the simulation model continues to travel forward at the speed and direction of the target vehicle at the first moment, and the first moment is the moment when the target vehicle triggers the driving control function recorded in the actual test data.

[0095] like Figure 5 FIG. 1 is a schematic diagram of a simulation device for a driving assistance system according to an embodiment of the present disclosure. Figure 5As shown, the simulation device 500 includes: a memory 510 and a processor 520, the memory 510 stores a computer program that can be run on the processor 520, and the computer program is executed by the processor 510 to realize Figure 1 Steps of the simulation method.

[0096] like Figure 6 As shown in FIG. 1 , it is a schematic diagram of a driving assistance system according to an embodiment of the present disclosure. Figure 6 As shown, the driving control function in the driving assistance system 600 is implemented by the simulation device 400 .

[0097] like Figure 7 As shown in FIG. 1 , it is a schematic diagram of a transportation tool according to an embodiment of the present disclosure. Figure 7 As shown, vehicle 700 includes driving assistance system 600 .

[0098] It should be understood that in the embodiments of the present disclosure, "B corresponding to A" means that B is associated with A, and B can be determined according to A. However, it should also be understood that determining B according to A does not mean determining B only according to A, and B can also be determined according to A and / or other information.

[0099] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0100] It should be understood that in the various embodiments of the present disclosure, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present disclosure.

[0101] In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms. The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the scheme of this embodiment.

[0102] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0103] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center via wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that can be read by a computer or a data storage device such as a server or data center that includes one or more available media integrated therein. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a digital video disc (DVD)) or a semiconductor medium (e.g., a solid state disk (SSD), etc.).

[0104] The above is only a specific embodiment of the present disclosure, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A simulation method for a driving assistance system, characterized in that: The simulation method is used to simulate the driving control function in the driving assistance system, and the simulation method includes: Acquiring actual test data of a target vehicle, wherein the actual test data includes driving parameters of the target vehicle; Feeding the actual test data back into the simulation model of the driving control function for simulation; Among them, the simulation model processes the driving parameters so that starting from the first moment, the simulated vehicle in the simulation model continues to move forward at the speed and direction of the target vehicle at the first moment, and the first moment is the moment when the target vehicle triggers the driving control function recorded in the actual test data.

2. The method according to claim 1, characterized in that The driving parameters include one or more of the following: longitudinal speed parameters, lateral angle parameters, and the processing of the driving parameters by the simulation model includes: Changing the longitudinal speed parameter of the simulated vehicle so that the simulated vehicle continues to move forward from the first moment according to the speed of the target vehicle at the first moment; and / or The lateral angle parameter of the simulated vehicle is changed so that the simulated vehicle continues to move forward in the direction of the target vehicle at the first moment starting from the first moment.

3. The method according to claim 2, characterized in that The longitudinal velocity parameter includes a longitudinal acceleration, and the changing of the longitudinal velocity parameter of the simulated vehicle includes: The longitudinal acceleration of the simulated vehicle at the first moment is removed.

4. The method according to claim 2, characterized in that: The lateral angle parameter includes a steering wheel angle, and the changing of the lateral angle parameter of the simulated vehicle includes: The steering wheel angle of the simulated vehicle at the first moment is removed.

5. The method according to claim 4, characterized in that The removing the steering wheel angle of the simulated vehicle at the first moment includes: If the steering wheel angle of the target vehicle at the first moment is greater than or equal to a first threshold, the steering wheel angle of the simulated vehicle at the first moment is removed.

6. The method according to claim 5, characterized in that The first threshold is greater than or equal to 10 degrees.

7. A simulation device for a driving assistance system, characterized in that: The simulation device is used to simulate the driving control function in the driving assistance system, and the simulation device includes: An acquisition module, used for acquiring actual test data of a target vehicle, wherein the actual test data includes driving parameters of the target vehicle; A simulation module, used for feeding the actual test data back into the simulation model of the driving control function for simulation; Among them, the simulation model processes the driving parameters so that starting from the first moment, the simulated vehicle in the simulation model continues to move forward at the speed and direction of the target vehicle at the first moment, and the first moment is the moment when the target vehicle triggers the driving control function recorded in the actual test data.

8. A simulation device for a driving assistance system, characterized in that: The simulation device is used to simulate the driving control function in the driving assistance system, and the simulation device includes: a memory and a processor, the memory stores a computer program that can be run on the processor, and when the computer program is executed by the processor, the steps of the simulation method as described in any one of claims 1 to 6 are implemented.

9. A driving assistance system, characterized in that: The driving control function in the driving assistance system is implemented by the simulation method described in any one of claims 1-6.

10. A means of transport, characterized in that: The vehicle comprises a driving assistance system, and a driving control function in the driving assistance system is implemented by the simulation method according to any one of claims 1 to 6.

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