Vehicle control method and device, electronic equipment and storage medium

Abstract

Embodiments of the present disclosure disclose a vehicle control method and device, electronic equipment and storage medium, the method comprising: determining whether a minimum safety system condition is met when a preset level of failure occurs in an automatic driving system of a vehicle; if yes, determining whether the preset level of failure is a failure of a positioning module and / or a perception module in the automatic driving system; if yes, determining whether the vehicle is currently driving on a straight road; if yes, or the preset level of failure is not a failure of the positioning module and / or the perception module in the automatic driving system, determining a first longitudinal brake acceleration based on a preset acceleration change rate constraint curve; determining a target longitudinal brake acceleration according to the first longitudinal brake acceleration and a second longitudinal brake acceleration output by a planning module in the automatic driving system; and controlling the vehicle brake according to the target longitudinal brake acceleration. The present disclosure improves the safety and smoothness of the vehicle during braking.

Description

Technical Field

[0001] This disclosure relates to the field of autonomous driving technology, and in particular to a vehicle control method, device, electronic device, and storage medium. Background Technology

[0002] In autonomous driving, vehicle fault handling capability is a crucial and fundamental ability. This capability ensures vehicle safety when a malfunction occurs. Specifically, in the event of a serious malfunction, immediate stopping is necessary to guarantee safety.

[0003] Currently, common approaches include direct braking or converting the autonomous driving system to a minimum safety level. However, converting the autonomous driving system to a minimum safety level can affect the normal operation of the entire system, leading to more potential dangers, and it also fails to consider braking smoothness. Direct braking also neglects braking smoothness and can easily cause a chain reaction of dangerous accidents due to sudden braking, such as the dangerous accident involving a large semi-trailer truck where the trailer folds over due to sudden braking. Summary of the Invention

[0004] To address or at least partially address the aforementioned technical problems, this disclosure provides a vehicle control method, apparatus, electronic device, and storage medium that improve vehicle safety and braking smoothness.

[0005] In a first aspect, embodiments of this disclosure provide a vehicle control method, the method comprising:

[0006] When it is determined that the vehicle's autonomous driving system has a preset level of fault, it is determined whether the vehicle meets the conditions for establishing a minimum safety system.

[0007] If the vehicle meets the conditions for establishing a minimum safety system, then determine whether the preset level of fault is a fault of the positioning module and / or perception module in the autonomous driving system.

[0008] If the preset level of fault is a fault of the positioning module and / or the sensing module, then determine whether the vehicle is currently traveling on a straight road;

[0009] If the vehicle is currently traveling on a straight road, or if the fault of the preset level is not a fault of the positioning module and / or perception module in the autonomous driving system, then the first longitudinal braking acceleration is determined based on the preset acceleration change rate constraint curve.

[0010] The target longitudinal braking acceleration is determined based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system.

[0011] The vehicle braking is controlled based on the target longitudinal braking acceleration.

[0012] Secondly, embodiments of this disclosure also provide a vehicle control device, the device comprising:

[0013] The first determining module is used to determine whether the vehicle meets the conditions for establishing a minimum safety system when it is determined that the vehicle's automatic driving system has a preset level of fault.

[0014] The second determining module is used to determine whether the preset level of fault is a fault of the positioning module and / or perception module in the autonomous driving system if the vehicle meets the conditions for the establishment of the minimum safety system.

[0015] The third determining module is used to determine whether the vehicle is currently traveling on a straight road if the preset level of fault is a fault of the positioning module and / or the sensing module.

[0016] The fourth determining module is used to determine the first longitudinal braking acceleration based on a preset acceleration change rate constraint curve if the vehicle is currently traveling on a straight road, or if the preset level of fault is not a fault of the positioning module and / or perception module in the autonomous driving system.

[0017] The fifth determining module is used to determine the target longitudinal braking acceleration based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system;

[0018] A braking module is used to control the vehicle braking based on the target longitudinal braking acceleration.

[0019] Thirdly, embodiments of this disclosure also provide an electronic device, the electronic device comprising: one or more processors; a storage device for storing one or more programs; and when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the vehicle control method as described above.

[0020] Fourthly, embodiments of this disclosure also provide a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the vehicle control method as described above.

[0021] This disclosure provides a vehicle control method that, when a preset level of fault occurs in the vehicle's autonomous driving system, determines whether the vehicle meets the conditions for establishing a minimum safety system; if the vehicle meets the conditions for establishing a minimum safety system, it determines whether the preset level fault is a fault of the positioning module and / or perception module in the autonomous driving system; if the preset level fault is a fault of the positioning module and / or perception module, it determines whether the vehicle is currently traveling on a straight road; if the vehicle is currently traveling on a straight road, or if the preset level fault is not a fault of the positioning module and / or perception module in the autonomous driving system, it determines a first longitudinal braking acceleration based on a preset acceleration change rate constraint curve; a target longitudinal braking acceleration is determined based on the first longitudinal braking acceleration and a second longitudinal braking acceleration output by the planning module in the autonomous driving system; and the technical means of controlling the vehicle braking based on the target longitudinal braking acceleration improves vehicle safety and braking smoothness. Attached Figure Description

[0022] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and the originals and elements are not necessarily drawn to scale.

[0023] Figure 1 This is a flowchart of a vehicle control method according to an embodiment of the present disclosure;

[0024] Figure 2 This is a schematic diagram of a fault transmission and processing embodiment of the present disclosure;

[0025] Figure 3 This is a schematic diagram showing the placement of a key lidar and a key camera in an embodiment of this disclosure;

[0026] Figure 4 This is a schematic diagram of a constraint curve with a fixed rate of change of acceleration according to an embodiment of this disclosure;

[0027] Figure 5 This is a schematic diagram of a constraint curve for a decreasing rate of acceleration in an embodiment of this disclosure;

[0028] Figure 6 This is a schematic diagram of a constraint curve for the rate of change of acceleration based on the Kuznets curve, as described in an embodiment of this disclosure.

[0029] Figure 7 This is a schematic diagram illustrating the actual braking effect when there are no obstacles in an embodiment of this disclosure;

[0030] Figure 8This is a schematic diagram illustrating the actual braking effect when there is an obstacle in an embodiment of this disclosure;

[0031] Figure 9 This is a schematic diagram illustrating the actual braking effect when approaching an obstacle in an embodiment of this disclosure;

[0032] Figure 10 This is a flowchart of a vehicle control method according to an embodiment of the present disclosure;

[0033] Figure 11 This is a schematic diagram of the structure of a vehicle control device according to an embodiment of the present disclosure;

[0034] Figure 12 This is a schematic diagram of the structure of an electronic device according to an embodiment of this disclosure. Detailed Implementation

[0035] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0036] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0037] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0038] Figure 1 This is a flowchart illustrating a vehicle control method according to an embodiment of this disclosure. The method can be executed by a vehicle control device, which can be implemented in software and / or hardware, and can be configured in an electronic device. Figure 1 As shown, the method may specifically include the following steps:

[0039] S110. When it is determined that the vehicle's automatic driving system has a preset level of fault, determine whether the vehicle meets the conditions for establishing a minimum safety system.

[0040] The fault levels for autonomous driving systems are currently divided into five categories: E1, E2, E3, E4, and E5. When an autonomous driving system experiences an E1 level fault, the response is to issue a warning to alert relevant personnel. For an E2 level fault, the response is to keep the autonomous vehicle moving at a low speed to ensure safety. For an E3 level fault, the response is to pull over to the side of the road. For an E4 level fault, the response is to brake slowly until a stop. For an E5 level fault, the response is to brake abruptly to a stop. The technical solutions in this disclosure address the response measures for E4 and E5 level faults in autonomous driving systems, aiming to improve braking smoothness while ensuring the safety of the autonomous vehicle. In other words, the preset fault levels include faults requiring immediate stopping.

[0041] Different modules of an autonomous driving system (such as perception, planning, control, camera, and localization modules) generate fault messages based on the severity of their own malfunctions. Therefore, it is not necessary to focus on the overall severity of the autonomous driving system's malfunctions. This approach offers the advantages of loose coupling and robustness in handling and managing malfunctions throughout the entire autonomous driving system. Figure 2 The diagram illustrates a fault transmission and handling process. Different modules of the autonomous driving system periodically generate heartbeat information, which includes the fault level of the module. When the fault level is a preset level, the heartbeat information is transmitted to the fault handling module via a data bus.

[0042] In some implementations, determining whether the vehicle meets the conditions for establishing a minimum safety system includes:

[0043] If at least one key LiDAR and at least one key camera of the vehicle are functioning normally, and the autonomous driving system is not currently in a pure motion estimation state, then the vehicle is determined to meet the conditions for establishing a minimum safety system; wherein, the LiDAR capable of scanning the area in front of the vehicle is a key LiDAR, and the camera capable of capturing images of the area in front of the vehicle is a key camera. For example, refer to... Figure 3 The diagram shows the placement of key LiDAR and key cameras, where Lidar-1, Lidar-2, and Lidar-3 represent key LiDARs; and Camera-1, Camera-2, and Camera-3 represent key cameras. The minimum safety system is the smallest unit that ensures the safe operation of an autonomous vehicle.

[0044] In some implementations, to further ensure the safety of autonomous vehicles, when a preset level of fault is determined in the vehicle's autonomous driving system, the method further includes disabling the obstacle avoidance function of the autonomous driving system. Specifically, the planning module of the autonomous driving system plans a route based on perception data and positioning data, and the planning results are divided into longitudinal planning and lateral planning. Lateral planning considers obstacles ahead and accelerates to avoid them. To increase safety, the acceleration and obstacle avoidance function of lateral planning is canceled in the event of a severe fault, while longitudinal planning becomes a plan for safe stopping.

[0045] S120. If the vehicle meets the conditions for establishing a minimum safety system, then determine whether the fault of the preset level is a fault of the positioning module and / or perception module in the autonomous driving system.

[0046] Specifically, the source of the heartbeat information can be used to determine which module of the autonomous driving system is at fault according to the preset level of fault.

[0047] S130. If the preset level of fault is a fault of the positioning module and / or the sensing module, then determine whether the vehicle is currently traveling on a straight road.

[0048] Determining whether the vehicle is currently traveling on a straight road includes:

[0049] The distance between the vehicle's current position and a reference position is determined, where the reference position is a road location with a road curvature greater than a first threshold; if the distance is greater than a preset safety distance, it is determined that the vehicle is currently traveling on a straight road; wherein, the preset safety distance y = speed. 2 / 2×acc+b, where speed represents the current vehicle speed, acc represents the average of the first longitudinal braking acceleration, and b represents the second threshold, i.e., the reserved safety distance threshold (when the vehicle chassis performs braking, there are strong / weak braking situations; when braking is strong, the vehicle has strong braking force and can quickly decelerate, at which time b is generally a negative value; when braking is weak or in a normal response, b is generally a positive value. b is a threshold introduced to ensure that the autonomous vehicle can brake safely and smoothly before reaching the curve, and the value of b varies for different vehicle models). The first threshold is a set value, and the reference position is essentially a road position with a road curvature greater than the first threshold: the reference position is a position on the curve. Specifically, the curvature of different planned path segments can be calculated according to the plane curvature formula. To prevent the autonomous vehicle from entering the curve during braking, this embodiment designs a preset safety distance. When the distance between the vehicle's current position and the reference position is less than the preset safety distance, the system determines that the autonomous vehicle is currently driving on the curve. To improve safety, the technical solution of this embodiment will not be adopted when the autonomous vehicle is driving on a curve and the positioning module and / or perception module malfunctions, in order to prevent the vehicle from hitting the edge of the road during braking.

[0050] The road curvature can be determined by the following formula:

[0051]

[0052] Where K represents the road curvature, y = f(x) represents the road curve, y″ is the second derivative, and y′ is the first derivative.

[0053] S140. If the vehicle is currently traveling on a straight road, or if the fault of the preset level is not a fault of the positioning module and / or perception module in the autonomous driving system, then the first longitudinal braking acceleration is determined based on the preset acceleration change rate constraint curve.

[0054] For example, the preset acceleration rate of change constraint curve includes:

[0055] Any one of the following: a constraint curve with a fixed rate of change of acceleration, a constraint curve with a decreasing rate of change of acceleration, or a constraint curve with a rate of change of acceleration based on the Kuznets curve.

[0056] The constraint curve for a fixed rate of change of acceleration can be referenced as follows: Figure 4 As shown, the constraint curve for the rate of change of decreasing acceleration can be referenced as follows: Figure 5 As shown, the constraint curve for the rate of change of acceleration based on the Kuznets curve can be referenced as follows: Figure 6 As shown, smoothness during braking can be improved by constraining the rate of change of acceleration to achieve a smoother transition.

[0057] Furthermore, the slope of the preset acceleration rate of change constraint curve needs to be less than a preset threshold. This preset threshold can be set according to the specific vehicle type. For example, for autonomous logistics vehicles, the preset threshold can be larger, while for autonomous passenger vehicles, the preset threshold should be smaller.

[0058] S150. Determine the target longitudinal braking acceleration based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system.

[0059] Based on the above implementation steps, it can be determined that when the autonomous driving system experiences a preset level of fault, the autonomous driving system remains operational and does not exit the autonomous driving mode to switch to the minimum safety system. Therefore, the planning module of the autonomous driving system continues to execute planning logic and output planning results, which include the second longitudinal braking acceleration. Furthermore, when the autonomous driving system experiences a serious fault, the planning result output by the planning module is not necessarily the planning result for the vehicle to slow down and stop. Therefore, in order to ensure safety and smoothness during braking, it is necessary to determine the final target longitudinal braking acceleration based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system.

[0060] In some implementations, determining the target longitudinal braking acceleration based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system includes: comparing the magnitudes of the first longitudinal braking acceleration and the second longitudinal braking acceleration; and determining the larger one as the target longitudinal braking acceleration.

[0061] S160. Control the vehicle braking according to the target longitudinal braking acceleration.

[0062] By controlling the vehicle's braking according to the target longitudinal braking acceleration, not only can safety be guaranteed, but braking smoothness can also be taken into account.

[0063] For example, see references to Figures 7-9 The diagram illustrating the actual braking effect compares the magnitudes of the first and second longitudinal braking accelerations at each time t, and determines the larger one as the target longitudinal braking acceleration. Figure 7 The illustrated scenario is that, in the absence of obstacles, the actual braking effect curve 710 is closer to the first longitudinal braking acceleration curve 720. Figure 8The illustrated scenario is that when there is an obstacle, the actual braking (target longitudinal braking acceleration) effect curve 810 is closer to the first longitudinal braking acceleration curve 820 before time t1, and after time t1, the actual braking effect curve 810 is closer to the second longitudinal braking acceleration curve 830. Here, t1 is the time corresponding to the intersection of the first longitudinal braking acceleration curve 820 and the second longitudinal braking acceleration curve 830. Figure 9 The illustrated scenario is that when the distance to the obstacle is relatively close, the actual braking effect curve 910 is closer to the second longitudinal braking acceleration curve 930, and 920 represents the first longitudinal braking acceleration curve.

[0064] Furthermore, if the vehicle does not meet the conditions for establishing the minimum safety system, or if the preset level of fault is a fault of the positioning module and / or perception module in the autonomous driving system but the vehicle is not currently traveling on a straight road, then the vehicle braking is controlled according to the preset braking acceleration.

[0065] General overview, references as follows Figure 10 The flowchart of a vehicle control method shown includes: the autonomous driving system starts working; each module of the autonomous driving system reports faults; the autonomous driving system plans a path and acceleration for autonomous driving; it determines whether the reported fault is a fault of a preset level; if so, it further determines whether the conditions for establishing a minimum safety system are met, and simultaneously cancels the obstacle avoidance function in the autonomous driving system; if it is not a fault of a preset level, it is processed according to the handling logic of a non-serious fault (this disclosure does not limit it); if the conditions for establishing a minimum safety system are met, it further determines whether it is a fault of the perception module and / or the positioning module; if it is not a fault of the minimum safety system, it directly controls the vehicle to brake according to a preset braking acceleration; if it is a fault of the perception module and / or the positioning module, it further determines whether the vehicle is currently traveling straight; if it is not traveling straight, it controls the vehicle to brake according to a preset braking acceleration; if it is traveling straight, it plans a first longitudinal braking acceleration and determines a target longitudinal braking acceleration based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system.

[0066] By using the above solution, safe and smooth parking can be achieved in the event of a serious malfunction. This not only ensures the normal operation of the automatic driving system but also improves safety and achieves smooth parking, reducing the potential harm to passengers caused by sudden braking in the event of a malfunction.

[0067] In summary, this disclosure proposes a method for enhancing the safety and smoothing the stopping of autonomous vehicles based on a minimum safety system in the event of a severe fault. This method addresses the issues of low safety and uneven braking when handling severe faults, while also achieving the most ideal braking result by balancing smoothness and safety.

[0068] Specifically, this disclosure categorizes faults into two types for handling, allowing for different decisions between different fault categories. The minimum safety system of this disclosure is the smallest unit that does not affect the safe operation of the autonomous vehicle. It utilizes various braking methods with smooth braking acceleration to meet the different smoothness and safety requirements of various vehicle models.

[0069] The vehicle-related parameters disclosed in this invention (such as preset acceleration rate of change constraint curves; for passenger-carrying autonomous vehicles, these curves are typically Kuznets curve-based, while for logistics vehicles, they are usually fixed-rate-of-acceleration constraint curves) can be obtained through data analysis. Furthermore, these parameters can be analyzed and set according to different scenarios, allowing for application to various vehicle models and scenarios, thus offering high flexibility. For example, it can be applied to different autonomous vehicles (such as trucks, buses, delivery vehicles, and sweepers), and can handle severe faults without affecting the operation of the autonomous driving system.

[0070] Figure 11 This is a schematic diagram of the structure of a vehicle control device according to an embodiment of this disclosure. Figure 11 As shown: The device includes: a first determining module 1110, a second determining module 1120, a third determining module 1130, a fourth determining module 1140, a fifth determining module 1150, and a braking module 1160.

[0071] The system comprises the following modules: a first determining module 1110, used to determine whether the vehicle meets the minimum safety system establishment conditions when a preset level of fault is detected in the vehicle's autonomous driving system; a second determining module 1120, used to determine whether the preset level fault is a fault of the positioning module and / or perception module in the autonomous driving system if the vehicle meets the minimum safety system establishment conditions; a third determining module 1130, used to determine whether the vehicle is currently traveling on a straight road if the preset level fault is a fault of the positioning module and / or perception module; a fourth determining module 1140, used to determine a first longitudinal braking acceleration based on a preset acceleration change rate constraint curve if the vehicle is currently traveling on a straight road, or if the preset level fault is not a fault of the positioning module and / or perception module in the autonomous driving system; a fifth determining module 1150, used to determine a target longitudinal braking acceleration based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system; and a braking module 1160, used to control the vehicle braking based on the target longitudinal braking acceleration.

[0072] Furthermore, the first determining module 1110 is specifically used to: determine that the vehicle meets the conditions for establishing a minimum safety system if at least one key lidar and at least one key camera of the vehicle are functioning normally and the autonomous driving system is not currently in a pure motion estimation state; wherein, the lidar that can scan the area in front of the vehicle is a key lidar, and the camera that can capture images of the area in front of the vehicle is a key camera.

[0073] Furthermore, the third determining module 1130 is specifically used to: determine the distance between the current position of the vehicle and a reference position, wherein the reference position is a road position where the road curvature is greater than a first threshold; if the distance is greater than a preset safety distance, then determine that the vehicle is currently traveling on a straight road; wherein the preset safety distance y = speed 2 / 2×acc+b, where speed represents the current speed of the vehicle, acc represents the average value of the first longitudinal braking acceleration, and b represents the second threshold.

[0074] Furthermore, it also includes a control module for disabling the obstacle avoidance function of the autonomous driving system when a preset level of fault is determined to occur in the vehicle's autonomous driving system; wherein the preset level of fault includes faults that require immediate stopping.

[0075] Furthermore, the preset acceleration rate of change constraint curve includes:

[0076] Any one of the following: a constraint curve with a fixed rate of change of acceleration, a constraint curve with a decreasing rate of change of acceleration, or a constraint curve with a rate of change of acceleration based on the Kuznets curve.

[0077] Furthermore, the fifth determining module 1150 is specifically used to: compare the magnitudes of the first longitudinal braking acceleration and the second longitudinal braking acceleration; and determine the larger one as the target longitudinal braking acceleration.

[0078] Furthermore, the control module is also configured to: if the vehicle does not meet the conditions for establishing the minimum safety system, or if the preset level of fault is a fault of the positioning module and / or perception module in the autonomous driving system but the vehicle is not currently traveling on a straight road, then control the vehicle to brake according to the preset braking acceleration.

[0079] The vehicle control device provided in this disclosure embodiment can execute the steps in the vehicle control method provided in this disclosure method embodiment, and can obtain the same beneficial effects, which will not be repeated here.

[0080] Figure 12 This is a schematic diagram of the structure of an electronic device according to an embodiment of this disclosure. See below for details. Figure 12 It shows a schematic diagram of a structure suitable for implementing the electronic device 500 in the embodiments of this disclosure. Figure 12 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0081] like Figure 12 As shown, the electronic device 500 may include a processing device 501, a ROM 502, a RAM 503, a bus 504, an input / output (I / O) interface 505, an input device 506, an output device 507, a storage device 508, and a communication device 509. The processing device (e.g., a central processing unit, a graphics processor, etc.) 501 can perform various appropriate actions and processes to implement the methods of the embodiments described herein, based on a program stored in the read-only memory (ROM) 502 or a program loaded from the storage device 508 into the random access memory (RAM) 503. The RAM 503 also stores various programs and data required for the operation of the electronic device 500. The processing device 501, ROM 502, and RAM 503 are interconnected via the bus 504. The input / output (I / O) interface 505 is also connected to the bus 504.

[0082] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a non-transitory computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts, thereby implementing the vehicle control method as described above. In such embodiments, the computer program can be downloaded and installed from a network via a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, it performs the functions defined in the methods of embodiments of this disclosure.

[0083] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0084] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to: determine whether the vehicle meets the minimum safety system establishment conditions when a preset level of fault is determined in the vehicle's autonomous driving system; if the vehicle meets the minimum safety system establishment conditions, determine whether the preset level fault is a fault of the positioning module and / or perception module in the autonomous driving system; if the preset level fault is a fault of the positioning module and / or perception module, determine whether the vehicle is currently traveling on a straight road; if the vehicle is currently traveling on a straight road, or if the preset level fault is not a fault of the positioning module and / or perception module in the autonomous driving system, determine a first longitudinal braking acceleration based on a preset acceleration change rate constraint curve; determine a target longitudinal braking acceleration based on the first longitudinal braking acceleration and a second longitudinal braking acceleration output by the planning module in the autonomous driving system; and control the vehicle braking based on the target longitudinal braking acceleration.

[0085] Optionally, when one or more of the above-described procedures are executed by the electronic device, the electronic device may also perform other steps described in the above embodiments.

[0086] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0087] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

Claims

1. A vehicle control method, characterized in that, The method includes: When it is determined that the vehicle's autonomous driving system has a preset level of fault, it is determined whether the vehicle meets the conditions for establishing a minimum safety system. If the vehicle meets the conditions for establishing a minimum safety system, then determine whether the preset level of fault is a fault of the positioning module and / or perception module in the autonomous driving system. If the preset level of fault is a fault of the positioning module and / or the sensing module, then determine whether the vehicle is currently traveling on a straight road; If the vehicle is currently traveling on a straight road, or if the fault of the preset level is not a fault of the positioning module and / or perception module in the autonomous driving system, then the first longitudinal braking acceleration is determined based on the preset acceleration change rate constraint curve. The target longitudinal braking acceleration is determined based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system. The vehicle braking is controlled based on the target longitudinal braking acceleration.

2. The method according to claim 1, characterized in that, Determining whether the vehicle meets the conditions for establishing a minimum safety system includes: If at least one key lidar and at least one key camera of the vehicle are functioning normally, and the autonomous driving system is not currently in a pure motion estimation state, then the vehicle is determined to meet the conditions for the establishment of a minimum safety system. Among them, the key LiDAR is the LiDAR that can scan the area in front of the vehicle, and the key camera is the camera that can capture the area in front of the vehicle.

3. The method according to claim 1, characterized in that, Determining whether the vehicle is currently traveling on a straight road includes: Determine the distance between the vehicle's current position and a reference position, where the reference position is a road location with a road curvature greater than a first threshold; if the distance is greater than a preset safety distance, then determine that the vehicle is currently traveling on a straight road; Wherein, the preset safety distance y = speed 2 / 2×acc+b, where speed represents the current speed of the vehicle, acc represents the average value of the first longitudinal braking acceleration, and b represents the second threshold.

4. The method according to claim 1, characterized in that, When it is determined that the vehicle's autonomous driving system has experienced a preset level of malfunction, the method further includes: Disable the obstacle avoidance function of the automatic driving system; Among them, the preset level of fault includes faults that require immediate shutdown.

5. The method according to claim 1, characterized in that, The preset acceleration rate of change constraint curve includes: Any one of the following: a constraint curve with a fixed rate of change of acceleration, a constraint curve with a decreasing rate of change of acceleration, or a constraint curve with a rate of change of acceleration based on the Kuznets curve.

6. The method according to claim 1, characterized in that, Determining the target longitudinal braking acceleration based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system includes: Compare the magnitudes of the first longitudinal braking acceleration and the second longitudinal braking acceleration; The larger one is determined as the target longitudinal braking acceleration.

7. The method according to claim 1, characterized in that, If the vehicle does not meet the conditions for establishing the minimum safety system, or if the preset level of fault is a fault of the positioning module and / or perception module in the autonomous driving system but the vehicle is not currently traveling on a straight road, then the vehicle braking is controlled according to the preset braking acceleration.

8. A vehicle control device, characterized in that, include: The first determining module is used to determine whether the vehicle meets the conditions for establishing a minimum safety system when it is determined that the vehicle's automatic driving system has a preset level of fault. The second determining module is used to determine whether the preset level of fault is a fault of the positioning module and / or perception module in the autonomous driving system if the vehicle meets the conditions for the establishment of the minimum safety system. The third determining module is used to determine whether the vehicle is currently traveling on a straight road if the preset level of fault is a fault of the positioning module and / or the sensing module. The fourth determining module is used to determine the first longitudinal braking acceleration based on a preset acceleration change rate constraint curve if the vehicle is currently traveling on a straight road, or if the preset level of fault is not a fault of the positioning module and / or perception module in the autonomous driving system. The fifth determining module is used to determine the target longitudinal braking acceleration based on the first longitudinal braking acceleration and the second longitudinal braking acceleration output by the planning module in the autonomous driving system; A braking module is used to control the vehicle braking based on the target longitudinal braking acceleration.

9. An electronic device, characterized in that, The electronic device includes: One or more processors; Storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1-7.

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