Autonomous driving method and system, controller, electronic device and computer storage medium

Abstract

An autonomous driving method, an auxiliary controller, a main controller, an autonomous driving system, an electronic device, and a computer-readable storage medium, which relate to the field of autonomous driving technology. The method is used in an auxiliary controller, and includes a step of acquiring state monitoring information that is information obtained by monitoring the operating state of the main controller, and a step of controlling the operating state of an autonomous vehicle when an operating abnormality of the main controller is determined based on the state monitoring information.

Description

Cross-reference to related documents

[0001] This application claims priority from Chinese Patent Application No. 202210434520.8 filed on April 24, 2022, the contents of which are incorporated herein by reference. [Technical Field]

[0002] The present application relates to the field of autonomous driving technology, and specifically to an autonomous driving method, an auxiliary controller, a main controller, an autonomous driving system, an electronic device, and a computer-readable storage medium. [Background technology]

[0003] Autonomous vehicles (self-driving automobiles), also known as driverless vehicles, are smart vehicles that achieve unmanned driving through computer systems. Autonomous vehicles rely on the coordination of multiple systems, including artificial intelligence, visual calculations, radar, monitoring devices, and global positioning systems, to achieve safe and autonomous driving in unmanned operation. The safety of autonomous vehicles and safe response control in the event of a malfunction are key indicators for autonomous vehicles. Summary of the Invention [Problem to be solved by the invention]

[0004] During the operation test process, the autonomous vehicle may encounter various out-of-control problems, such as ineffective braking, poor turning timing, and / or ignoring traffic lights, etc. These out-of-control problems of the autonomous vehicle directly threaten the personal safety of the test personnel inside the vehicle and the safety of the equipment and property, thereby reducing the practicality of the autonomous vehicle. [Means for solving the problem]

[0005] The autonomous driving method provided by the present application includes a step of acquiring status monitoring information, which is used by the auxiliary controller and is information obtained by monitoring the operating status of the main controller, and a step of controlling the operating status of the autonomous vehicle when an operating abnormality in the main controller is confirmed based on the status monitoring information.

[0006] The autonomous driving method provided by the present application includes a step of being used by a main controller to generate status monitoring information, and a step of transmitting the status monitoring information to an auxiliary controller so that the auxiliary controller controls the driving status of the autonomous vehicle in a situation where an operational abnormality of the main controller is determined based on the status monitoring information.

[0007] The auxiliary controller provided by the present application includes an acquisition module arranged to acquire status monitoring information, which is information obtained by monitoring the operating status of the main controller, and a determination module arranged to control the operating status of the autonomous vehicle when an operating abnormality of the main controller is determined based on the status monitoring information.

[0008] The main controller provided by the present application includes a generating module configured to generate status monitoring information, and a transmitting module configured to transmit the status monitoring information to an auxiliary controller, thereby controlling the operating status of the autonomous vehicle in a situation where the auxiliary controller determines an operating abnormality in the main controller based on the status monitoring information.

[0009] The autonomous driving system provided by the present application includes a main controller, an auxiliary controller, an execution device, and a data sensing component, all of which are communicatively connected, wherein the auxiliary controller is configured to execute the autonomous driving method used in the auxiliary controller, the main controller is configured to execute the autonomous driving method used in the main controller, the execution device is configured to obtain control information sent by the main controller or the auxiliary controller, and maintain or change the driving state of the autonomous vehicle based on the control information, and the data sensing component is configured to feed back sensing information to the main controller or the auxiliary controller, so that the main controller or the auxiliary controller determines state monitoring information of the autonomous vehicle based on the sensing information.

[0010] The present application provides an electronic device including at least one processor and a memory having at least one computer program stored therein, the at least one computer program causing the at least one processor to realize the above-described autonomous driving method when executed by the at least one processor.

[0011] The present application provides a computer-readable storage medium having a computer program stored therein, the computer program realizing the above-described autonomous driving method when executed by a processor.

[0012] These and other aspects of the present application and how they are implemented are described in more detail in the Brief Description of the Drawings, Detailed Description and Claims. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is a flow diagram of the autonomous driving method provided by the present application. [Figure 2] FIG. 2 is a structural schematic diagram of the autonomous driving system provided by the present application. [Figure 3] FIG. 3 is a flow diagram of the auxiliary controller's judgment method for the main controller's status provided by this application. [Figure 4] FIG. 4 is a flow diagram of the auxiliary controller's judgment method for the main controller's intercepted information provided in this application. [Figure 5] FIG. 5 is a flow diagram of the autonomous driving method provided by the present application. [Figure 6] FIG. 6 is a composition structure diagram of the auxiliary controller provided in this specification. [Figure 7] FIG. 7 is a composition structure diagram of the main controller provided in this specification. [Figure 8] Figure 8 is a structural diagram of the autonomous driving system provided by the present application. [Figure 9] Figure 9 is a structural diagram of the autonomous driving system provided by the present application. [Figure 10] FIG. 10 is a structural diagram of an exemplary hardware architecture of a computer device capable of implementing the autonomous driving method and apparatus according to the present application. DETAILED DESCRIPTION OF THE INVENTION

[0014] In order to make the purpose, technical solution and advantages of the present application clearer, the present application will be described in detail below in conjunction with the drawings, whereby, unless contradictory, each example / embodiment and each feature in the example / embodiment in the present application can be arbitrarily combined with each other.

[0015] Currently, control of an autonomous vehicle is mainly achieved by the above-mentioned modules: a fault warning module detects vehicle status information to determine whether an abnormality has occurred in the operating status of the autonomous vehicle's main control module; when it is determined that an abnormality has occurred in the operating status of the main control module, an auxiliary control module obtains the fault scenario in which the autonomous vehicle is located and the fault problem that has occurred; and the auxiliary control module controls the driving status of the autonomous vehicle in accordance with a control policy determined based on the fault scenario and the fault problem.

[0016] However, in the above control method, the main control module and the auxiliary control module are not completely separated, and the auxiliary control module does not have complete control functions for the autonomous vehicle. Such an independent detection module and auxiliary control module cannot ensure the safe driving of the autonomous vehicle, and the autonomous vehicle is prone to out-of-control problems during driving, threatening the safety of the testers inside the vehicle and reducing the practicality of the autonomous vehicle.

[0017] In light of the above problems, the present application provides an autonomous driving method, an auxiliary controller, a main controller, an autonomous driving system, an electronic device, and a computer-readable storage medium, which, when an operational abnormality of the main controller of an autonomous vehicle is confirmed, uses the auxiliary controller to completely replace the main controller, allowing the auxiliary controller to continue to control the driving state of the autonomous vehicle, thereby reducing the occurrence rate of various out-of-control problems of the autonomous vehicle and reducing the probability of traffic accidents occurring during the driving process of the autonomous vehicle.

[0018] 1 is a flow diagram of the autonomous driving method provided by the present application, which can be used in an auxiliary controller. As shown in FIG. 1, the autonomous driving method of the present application may include, but is not limited to, the following steps S101 and S102:

[0019] Step S101: Obtain status monitoring information.

[0020] The status monitoring information is information obtained by monitoring the operating status of the main controller.

[0021] Step S102: Control the driving state of the autonomous vehicle when an operational abnormality of the main controller is confirmed based on the state monitoring information.

[0022] In the autonomous driving method provided by the present application, the main controller obtains state monitoring information that the main controller uses to control the driving of the autonomous vehicle, thereby enabling real-time monitoring of the main controller and obtaining the main controller's control status for the autonomous vehicle. When an abnormal operation of the main controller is determined based on the state monitoring information, the abnormal status occurring in the main controller is detected in a timely manner and dealt with promptly in the main controller, using the current auxiliary controller to replace the main controller and allowing the auxiliary controller to continue to control the driving status of the autonomous vehicle, thereby reducing the occurrence rate of various out-of-control problems of the autonomous vehicle (e.g., ineffective braking, control information errors, etc.) and reducing the probability of traffic accidents occurring during the driving process of the autonomous vehicle, thereby improving the personal safety of testers in the autonomous vehicle and ensuring the safe and effective driving of the autonomous vehicle.

[0023] 2 is a structural schematic diagram of the autonomous driving system provided in the present application. As shown in FIG. 2, the autonomous driving system includes, but is not limited to, a main controller 201 and an auxiliary controller 202 that are communicatively connected.

[0024] For example, the main controller 201 and the auxiliary controller 202 may be connected using wired or wireless connection technologies. Wired connection technologies include, but are not limited to, connection modes based on bus technology and proprietary wired communication protocols. Wireless connection technologies include, but are not limited to, connection modes based on TCP / IP and short-range wireless communication technologies (e.g., Wi-Fi technology, Vehicle To Everything (V2X) technology, Bluetooth® communication protocol, Near Link technology, etc.).

[0025] The auxiliary controller 202 monitors the main controller 201 by acquiring status monitoring information (e.g., heartbeat messages) sent by the main controller 201 at regular intervals, and acquires the status monitoring information that controls the operation of the autonomous vehicle.

[0026] For example, in order to realize real-time monitoring of the main controller 201 by the auxiliary controller 202 and accurately monitor the operating status of the main controller 201, the main controller 201 can also periodically send a heartbeat message to the auxiliary controller 202, so that the auxiliary controller 202 can determine the operating status of the main controller 201 based on the received heartbeat message.

[0027] For example, if the auxiliary controller 202 does not receive a heartbeat message sent by the main controller 201 within one or more preset time periods, or if the heartbeat message received by the auxiliary controller 202 within one or more preset time periods contains abnormal information (e.g., detected information that is not in a preset format, or a parameter in the heartbeat message is an abnormal value), it indicates that the main controller 201 is in an abnormal operating state. If the auxiliary controller 202 receives a heartbeat message sent by the main controller 201 within one or more preset time periods and all the heartbeat messages contain normal information, it indicates that the main controller 201 is in a normal operating state.

[0028] When the auxiliary controller 202 determines that the main controller 201 is malfunctioning, it can further perform emergency danger avoidance operations (e.g., stopping the vehicle on the shoulder of the road and / or applying emergency braking) on ​​the autonomous vehicle, thereby reducing the rate of traffic accidents involving the autonomous vehicle.

[0029] In some embodiments, the auxiliary controller 202 may send control information to the main controller 201, and the main controller 201 may stop controlling the autonomous vehicle based on the control information, and completely transfer the control authority over the autonomous vehicle to the auxiliary controller 202, thereby ensuring that the auxiliary controller 202 can accurately control the autonomous vehicle, reducing the probability of the autonomous vehicle causing a traffic accident, and improving the driving safety of the vehicle.

[0030] 3 is a flow diagram of the auxiliary controller's determination method for the main controller's status provided in the present application. As shown in FIG. 3, the auxiliary controller's determination method for the main controller's status includes, but is not limited to, the following steps S301 and S302:

[0031] In step S301, it is determined whether the main controller is operating abnormally based on the status monitoring information.

[0032] The status monitoring information includes intercepted information within a predetermined period, and may include, for example, heartbeat messages and / or periodically reported status information.

[0033] In addition, under normal conditions, the main controller is responsible for controlling the driving state of the autonomous vehicle, and the auxiliary controller is configured to monitor the operating state of the main controller. In the main control process, the main controller periodically transmits intercepted information to the auxiliary controller, allowing the auxiliary controller to monitor the operating state of the main controller at intervals of an intercepting period (e.g., 1 second or 5 seconds). If the intercepted information received by the auxiliary controller is abnormal, or if the auxiliary controller does not receive intercepted information within a preset period, the main controller is determined to be operating abnormally.

[0034] In some embodiments, the status monitoring information may further include a real-time data processing amount. By monitoring the real-time data processing amount of data processed by the main controller in real time, it is possible to determine whether the main controller is operating overloaded, thereby determining whether the main controller is operating abnormally and improving the accuracy of determining the operating status of the main controller.

[0035] For example, if it is determined that the real-time data processing volume of the main controller exceeds its maximum data processing load threshold, it indicates that the main controller is operating abnormally and processing needs to be performed on the main controller, for example, step S302 is executed. If it is determined that the real-time data processing volume of the main controller is smaller than its maximum data processing load threshold, it indicates that the main controller is operating normally.

[0036] If an operational abnormality of the main controller is confirmed, step S302 is executed. If it is determined that the main controller is operating normally, step S301 is continued, and the main controller continues to control the operating state of the autonomous vehicle.

[0037] Step S302: Control the driving state of the autonomous vehicle using the auxiliary controller instead of the main controller.

[0038] For example, the auxiliary controller immediately takes over as the main controller, realizing the control function of the auxiliary controller for the driving state of the autonomous vehicle.

[0039] In the autonomous driving method provided by the present application, determining whether the main controller is operating abnormally through status monitoring information enables real-time monitoring of the main controller and timely detection of possible malfunctions in the main controller. When a malfunction in the main controller is determined, using the auxiliary controller to control the driving state of the autonomous vehicle instead of the main controller allows the auxiliary controller to fully exercise its control function, achieving complete control of the autonomous vehicle, reducing the risk of loss of control of the autonomous vehicle due to a malfunction of the main controller, and reducing the probability of a traffic accident occurring during the driving of the autonomous vehicle, thereby improving the personal safety of testers in the autonomous vehicle and ensuring the safe and efficient driving of the autonomous vehicle.

[0040] In some embodiments, the step of determining an operational abnormality of the main controller in a situation where intercepted information is not received within a preset period includes the steps of accumulating the number of abnormalities in which intercepted information is not received within a preset period and obtaining the accumulated number of abnormalities, and determining an operational abnormality of the main controller in a situation where it is determined that the accumulated number of abnormalities exceeds a preset number threshold.

[0041] In some embodiments, the autonomous driving method further includes a step of initializing the number of abnormalities when intercepted information is received within a predetermined period and the intercepted information is normal information, before determining that the cumulative number of abnormalities exceeds a predetermined number threshold and determining that the main controller is operating abnormally.

[0042] The preset period may include preset time interval values ​​such as 1 second, 2 seconds, etc. The above preset period is merely described as an example and can be specifically set according to actual needs. Other preset periods not described are also within the scope of protection of the present application and will not be mentioned again here.

[0043] For example, Figure 4 is a flow diagram of the auxiliary controller's judgment method for the main controller's intercepted information provided in the present application. As shown in Figure 4, the auxiliary controller's judgment method for the main controller's intercepted information includes, but is not limited to, the following steps S401 to S405:

[0044] Step S401: The auxiliary controller determines whether it has received the intercepted information sent by the main controller.

[0045] The intercepted information may include heartbeat messages and / or periodically reported status information, etc.

[0046] For example, a state counter can be used to provide monitoring for intercepted information sent by the main controller.

[0047] If the intercepted information is not received within a preset period, step S402 is executed. If the intercepted information is received within a preset period and is normal, step S405 is executed.

[0048] In step S402, the auxiliary controller accumulates the abnormal number of times when the intercepted information is not received, and obtains the accumulated abnormal number.

[0049] The abnormal count can be accumulated using an arithmetic progression, for example, the abnormal count can be accumulated based on a preset accumulation value (e.g., 1 or 2) for each abnormal count, thereby ensuring that the abnormal count after accumulation exhibits regular changes.

[0050] Step S403: The auxiliary controller determines whether the accumulated abnormality count exceeds a preset count threshold.

[0051] For example, the preset number threshold may be set to a value such as 3 or 5 times, thereby setting the monitoring tolerance of the main controller.

[0052] If it is determined that the accumulated abnormal count exceeds the preset threshold (for example, the accumulated abnormal count is equal to or greater than the preset threshold), step S404 is executed. If it is determined that the accumulated abnormal count does not exceed the preset threshold (for example, the accumulated abnormal count is less than the preset threshold), step S401 is executed again to continue monitoring the intercepted information transmitted by the main controller.

[0053] Step S404: The auxiliary controller determines whether the main controller is operating abnormally.

[0054] After step S404 is completed, the flow ends.

[0055] In step S405, the number of abnormalities is initialized.

[0056] For example, the abnormal count of the state counter is initialized to an initial preset value (for example, the initial preset value is 0).

[0057] After completing the execution of step S405, the process returns to step S401 and continues to monitor the intercepted information transmitted by the main controller.

[0058] In this judgment method, the auxiliary controller monitors and judges the intercepted messages sent by the main controller to determine whether the main controller is operating abnormally, thereby enabling accurate monitoring of the main controller and reducing the rate at which autonomous vehicles become unable to operate due to a malfunction in the main controller.

[0059] In some embodiments, in step S101, the main controller obtaining state monitoring information for controlling autonomous vehicle operation includes receiving sensing information and determining the state monitoring information based on the sensing information.

[0060] The sensing information is information fed back by the first data sensing component or information fed back by the second data sensing component. The state monitoring information includes at least one of driving speed information, driving angle information, and position information of the autonomous vehicle.

[0061] The second data sensing component may have the same function as the first data sensing component. In a situation where a failure occurs in the first data sensing component, the second data sensing component can be used instead of the first data sensing component to sense environmental information around the autonomous vehicle, vehicle status information, spatial information where the vehicle is located, etc.

[0062] For example, the first data sensing component and / or the second data sensing component may be implemented using different types of sensors, such as a speed sensor, an angle sensor, a positioning component, etc. Implementing the data sensing components using different types of sensors allows the main controller and / or the auxiliary controller to obtain multiple types of sensing information of different dimensions, thereby enriching state monitoring information, and using the state monitoring information to determine the driving status of the autonomous vehicle may improve the accuracy of the determination.

[0063] In some embodiments, the autonomous driving method further includes, after performing control over the driving state of the autonomous vehicle in step S102, acquiring auxiliary sensing information, and updating state monitoring information of the autonomous vehicle based on the auxiliary sensing information.

[0064] The auxiliary sensing information is information fed back by an auxiliary sensing component. The auxiliary sensing component is a component configured to assist the first data sensing component or the second data sensing component in sensing an environmental factor. For example, the auxiliary sensing component may include a weather sensor (e.g., a rain sensor), a temperature sensor, etc.

[0065] Obtaining auxiliary sensing information fed back by the auxiliary sensing component and using the auxiliary sensing information to update the state monitoring information of the autonomous vehicle allows the state monitoring information to more accurately represent the ambient environment information of the autonomous vehicle, allowing the auxiliary controller to more accurately control the autonomous vehicle and improving control accuracy.

[0066] In some embodiments, the sensed information includes at least one of environmental image information, spatial information in which the vehicle is located, vehicle status information, and communication information.

[0067] Representing the sensing information through different dimensions of information allows the auxiliary controller or the main controller to obtain diversified information, so that the state monitoring information of the autonomous vehicle can be accurately determined based on the sensing information, and the autonomous vehicle can be accurately controlled, thereby improving the driving accuracy of the autonomous vehicle.

[0068] In some embodiments, the control of the driving state of the autonomous vehicle in step S102 includes: disconnecting the main controller's control of the autonomous vehicle according to a preemptive method; and controlling the driving state of the autonomous vehicle based on the hazard avoidance information.

[0069] The risk avoidance information is determined from abnormal operation information (e.g., failure information or operation error information) of the main controller and / or sensing information fed back from a data sensing component (e.g., a first data sensing component or a second data sensing component). The preemptive approach allows the main controller or the auxiliary controller to obtain control of the autonomous vehicle through a competitive approach. For example, when a failure occurs in the main controller, the auxiliary controller seizes the position of controller for the autonomous vehicle and cuts off the main controller's control over the autonomous vehicle, so that the autonomous vehicle is under the control of only one controller (i.e., the auxiliary controller), ensuring the driving safety of the autonomous vehicle.

[0070] The risk avoidance information allows the auxiliary controller to clarify how to control the autonomous vehicle, thereby avoiding potentially dangerous situations (such as potential collisions between vehicles), thereby enabling the auxiliary controller to more accurately control the driving state of the autonomous vehicle.

[0071] For example, the auxiliary controller may promptly activate an airbag on a seat based on the danger avoidance information to ensure the safety of passengers in the vehicle, or may control the autonomous vehicle to stop on the shoulder based on the danger avoidance information to avoid other vehicles that may collide with the autonomous vehicle, thereby improving the accuracy of the autonomous vehicle's response to dangerous situations.

[0072] In some embodiments, the step of controlling the driving state of the autonomous vehicle based on the hazard avoidance information includes the steps of generating a control command based on the hazard avoidance information, and sending the control command to an actuator so that the actuator controls the driving state of the autonomous vehicle based on the control command.

[0073] An actuator is communicatively coupled to each of the auxiliary controller and the main controller, and may be at least one of a power system component, a turning system component, and a braking system component.

[0074] By sending a control command to the actuator, the actuator can clarify any risks that may exist based on the control command, thereby avoiding those risks (e.g., avoiding obstacles, etc.), thereby improving the driving safety of the self-driving vehicle.

[0075] In some embodiments, the auxiliary controller includes an auxiliary actuator and the main controller includes a main actuator, wherein cutting off control of the main controller over the autonomous vehicle based on the preemptive strategy includes cutting off control of the main actuator over the autonomous vehicle based on the preemptive strategy, and controlling the operating state of the autonomous vehicle based on the hazard avoidance information includes controlling the auxiliary actuator to control the operating state of the autonomous vehicle based on the hazard avoidance information.

[0076] The auxiliary actuator and the main actuator are configured to control the driving state of the autonomous vehicle to change or maintain the driving state of the autonomous vehicle. The main controller may further include a first data sensing component, and the auxiliary controller may further include a second data sensing component, where different data sensing components sense the surrounding environment information of the autonomous vehicle of different controllers, and generate danger avoidance information based on the acquired sensing information, so that the autonomous vehicle can avoid possible hazards using the danger avoidance information.

[0077] By using the preemptive approach to cut off control of the main actuator for the autonomous vehicle, the occurrence rate of situations in which the autonomous vehicle becomes uncontrollable due to a failure of the main actuator can be reduced; furthermore, based on the risk avoidance information, the auxiliary controller can control the auxiliary actuator to complete accurate control of the autonomous vehicle, thereby improving the driving safety of the autonomous vehicle.

[0078] 5 is a flow diagram of the autonomous driving method provided by the present application. The autonomous driving method can be used in a main controller. As shown in FIG. 5, the autonomous driving method of the present application may include, but is not limited to, the following steps S501 and S502:

[0079] In step S501, status monitoring information is generated.

[0080] The status monitoring information includes at least one of the driving speed of the autonomous vehicle, the driving angle, and the driving route of the autonomous vehicle.

[0081] By monitoring different dimensions of state information of an autonomous vehicle, state monitoring information such as driving speed information, driving angle information, and position information of the autonomous vehicle can be obtained, and the state monitoring information can indicate the driving status of the autonomous vehicle, enabling control of the autonomous vehicle and monitoring of the driving status of the autonomous vehicle, thereby ensuring stable operation of the autonomous vehicle.

[0082] Step S502: Send the state monitoring information to the auxiliary controller, so that the auxiliary controller controls the driving state of the autonomous vehicle when it determines that the main controller is operating abnormally based on the state monitoring information.

[0083] The status monitoring information is transmitted to the auxiliary controller at preset intervals, so that the auxiliary controller periodically monitors the main controller. The auxiliary controller analyzes the received status monitoring information, and if an operational abnormality in the main controller is determined, the auxiliary controller can control the operating status of the autonomous vehicle in place of the main controller.

[0084] For example, when the auxiliary controller receives a garbled heartbeat message sent by the main controller at regular intervals, or does not receive a heartbeat message sent by the main controller within a certain preset period, and it is determined that the main controller has an abnormality in connection, controlling the driving state of the autonomous vehicle with the auxiliary controller instead of the main controller can reduce the occurrence rate of various uncontrollable problems of the autonomous vehicle (e.g., ineffective braking, control information errors, etc.) and reduce the probability of traffic accidents occurring when the autonomous vehicle is driving.

[0085] Using the auxiliary controller to replace the main controller may include using the auxiliary controller to complete all of the control functions of the main controller and turning off the main controller, or using the auxiliary controller to assist the main controller and jointly complete the control of the autonomous vehicle, compensating for the main controller's deficiencies in independent control of the autonomous vehicle, thereby achieving precise control of the autonomous vehicle.

[0086] The autonomous driving method provided by the present application for use in a main controller controls the driving state of an autonomous vehicle, generates state monitoring information, and uses the state monitoring information to indicate the driving situation of the autonomous vehicle. This facilitates the main controller to perform stable control of the autonomous vehicle in real time, and sends the state monitoring information to an auxiliary controller, so that the auxiliary controller can control the driving state of the autonomous vehicle on behalf of the main controller when an operational abnormality of the main controller is determined based on the state monitoring information. This reduces the occurrence of various out-of-control problems in the autonomous vehicle and reduces the probability of traffic accidents occurring when the autonomous vehicle is traveling.

[0087] In some embodiments, the autonomous driving method includes a step of stopping control of the driving state of the autonomous vehicle and a step of generating alarm information in a situation where it is determined that a failure has occurred in the main controller after transmitting state monitoring information to the auxiliary controller in step S502.

[0088] The alarm information is intended to notify the control terminal of the autonomous vehicle that an abnormality exists in the autonomous vehicle.

[0089] For example, in a situation where the auxiliary controller detects that a malfunction has occurred in the main controller, the main controller receives shutdown information sent by the auxiliary controller, which is intended to notify the main controller to stop operation. This allows the auxiliary controller to completely control the autonomous vehicle in place of the main controller, thereby reducing the rate at which autonomous vehicles cause traffic accidents due to abnormalities in the main controller.

[0090] In addition, before the main controller stops operating, it sends the generated alarm information to the server, allowing the server to know that a fault has occurred in the main controller of the autonomous vehicle, and have the server transfer the alarm information to the control terminal of the autonomous vehicle, obtain intervention information voluntarily input by the control terminal of the autonomous vehicle, reduce the rate at which the autonomous vehicle becomes uncontrollable, and improve the driving safety of the autonomous vehicle.

[0091] 6 is a structural diagram of the auxiliary controller provided in the present application. As shown in FIG. 6, the auxiliary controller 600 includes, but is not limited to, an acquisition module 601 and a determination module 602.

[0092] The acquisition module 601 is arranged to acquire status monitoring information, which is information obtained by monitoring the operating status of the main controller.

[0093] The determination module 602 is configured to control the driving state of the autonomous vehicle when an operation abnormality of the main controller is determined based on the state monitoring information.

[0094] In the auxiliary controller provided by the present application, an acquisition module 601 acquires status monitoring information, which is information obtained by monitoring the operating status of the main controller, and can monitor the main controller in real time to obtain the control status of the main controller for the autonomous vehicle. When an operating abnormality of the main controller is determined based on the status monitoring information, a determination module 602 detects an abnormality in the main controller in a timely manner and promptly handles the main controller, using the current auxiliary controller to take the place of the main controller and allow the auxiliary controller to continue to control the operating status of the autonomous vehicle, thereby reducing the occurrence of various out-of-control problems in the autonomous vehicle and reducing the probability of traffic accidents during the driving process of the autonomous vehicle, thereby improving the personal safety of testers in the autonomous vehicle and ensuring the safe and effective driving of the autonomous vehicle.

[0095] 7 is a structural diagram of the main controller provided by the present application. As shown in FIG. 7, the main controller 700 includes, but is not limited to, a generating module 701 and a sending module 702.

[0096] The generating module 701 is arranged to generate condition monitoring information.

[0097] The transmitting module 702 is configured to transmit the status monitoring information to the auxiliary controller, so that the auxiliary controller controls the driving status of the autonomous vehicle in a situation where the auxiliary controller determines an operational abnormality of the main controller based on the status monitoring information.

[0098] In the main controller provided by the present application, a generating module 701 generates state monitoring information, which indicates the driving status of the autonomous vehicle, thereby facilitating the main controller to perform stable control of the autonomous vehicle in real time. A transmitting module 702 transmits the state monitoring information to an auxiliary controller, which controls the driving status of the autonomous vehicle on behalf of the main controller when it determines an abnormality in the main controller based on the state monitoring information, thereby reducing the occurrence of various out-of-control problems in the autonomous vehicle and the probability of a traffic accident occurring during the driving process of the autonomous vehicle.

[0099] Figure 8 is a structural diagram of the autonomous driving system provided by the present application. As shown in Figure 8, the autonomous driving system includes, but is not limited to, the following devices:

[0100] 8, a main controller 801, an auxiliary controller 802, an execution device 803, and a data sensing component 804, all of which are communicatively coupled.

[0101] The main controller 801 is configured to execute the automatic driving method provided in this application and used by the main controller.

[0102] The auxiliary controller 802 is configured to implement the autonomous driving method provided herein for use with the auxiliary controller.

[0103] The execution device 803 is configured to obtain control information transmitted by the main controller 801 or the auxiliary controller 802, and maintain or change the driving state of the autonomous vehicle based on the control information.

[0104] The data sensing component 804 is configured to feed back sensing information to the main controller 801 or the auxiliary controller 802, so as to cause the main controller 801 or the auxiliary controller 802 to determine state monitoring information of the autonomous vehicle based on the sensing information.

[0105] The main controller 801 is connected to the auxiliary controller 802, the data sensing component 804, and the execution device 803. The main controller 801 is arranged to control the driving state of the autonomous vehicle in a normal state, for example, the main controller 801 controls the execution device 803 to perform operations such as running or stopping the autonomous vehicle, and / or receives sensing information transmitted by the data sensing component 804, and / or periodically transmits its own status monitoring information (e.g., heartbeat messages, etc.) to the auxiliary controller 802.

[0106] The auxiliary controller 802 is arranged to monitor the operating status of the main controller 801, and for example, checks whether the main controller 801 is operating normally by intercepting heartbeat messages periodically transmitted by the main controller 801. In the event of an abnormality in the main controller 801, the auxiliary controller 802 takes over the control function of the main controller 801 and controls the operation of the execution device 803 connected to the auxiliary controller 802. In addition, the auxiliary controller 802 realizes an auxiliary control function for the autonomous vehicle by acquiring sensing information transmitted by a data sensing module 804 connected to the auxiliary controller 802.

[0107] In some embodiments, the auxiliary controller 802 can only implement hazard avoidance maneuvers for the autonomous vehicle, such as controlling the autonomous vehicle (e.g., sending control signals to the execution device 803) to stop the vehicle on a safe shoulder, activating relevant alarm signals (e.g., hazard lights, etc.), and transmitting fault information to a server, etc., in a situation where the main controller is disabled.

[0108] The auxiliary controller 802 may be an automatic control system with relatively simple functions, and may only realize simple danger avoidance functions such as emergency braking and / or stopping on the shoulder of the road. The auxiliary controller 802 receives control commands input from the outside, and based on the control commands, performs control functions on the execution device 803, thereby controlling the driving state of the vehicle. The auxiliary controller 802 may be a device that can realize all the control functions of the main controller 801, and controls the autonomous vehicle instead of the main controller 801.

[0109] The execution device 803 is configured to receive control information transmitted by the main controller 801 or the auxiliary controller 802, thereby controlling the driving state of the autonomous vehicle. After the auxiliary controller 802 takes over control of the autonomous vehicle, the execution device 803 no longer receives control commands transmitted by the main controller 801. At this time, the execution device 803 controls the autonomous vehicle based on the control information received from the auxiliary controller 802, thereby improving the control accuracy of the autonomous vehicle. The execution device 803 includes at least one of a power system component, a turning system component, and a braking system component. The execution device 803 controls the autonomous vehicle and can change or maintain the driving state (e.g., direction of movement, driving speed, etc.) of the autonomous vehicle.

[0110] The data sensing component 804 is configured to sense the driving state information of the autonomous vehicle, the vehicle's external environment information, etc. The data sensing component 804 is communicatively connected to both the main controller 801 and the auxiliary controller 802, and provides the sensed information to the main controller 801 and the auxiliary controller 802, allowing the main controller 801 and the auxiliary controller 802 to determine autonomous vehicle state monitoring information based on the sensed information, thereby realizing the automatic control function for the autonomous vehicle.

[0111] The data sensing component 804 includes, but is not limited to, at least one of an external environment sensing device, a vehicle state sensing device, and a communication device.

[0112] For example, the external environment sensing device may include a camera and / or a radar, and the vehicle state sensing device includes at least one of a gyroscope, a tachometer, an accelerometer, a steering angle sensor, a Global Positioning System (GPS), and a Beidou device. The communication device can obtain at least one of communication information such as external communication information, electronic map information, and real-time traffic information.

[0113] The external environment sensing device can acquire environmental image information, and the vehicle state sensing device can acquire spatial information about the vehicle's location and vehicle state information.

[0114] Figure 9 is a structural diagram of the autonomous driving system provided by the present application. As shown in Figure 9, the autonomous driving system includes, but is not limited to, the following devices:

[0115] 9A and 9B, a main controller 901, an auxiliary controller 902, a first data sensing component 903, a first execution device 904, a second data sensing component 905, and a second execution device 906, all of which are communicatively coupled.

[0116] The main controller 901 has the same functions as the main controller 801 shown in FIG. 8, and the auxiliary controller 902 has the same functions as the auxiliary controller 802 shown in FIG.

[0117] Both the first data sensing component 903 and the second data sensing component 905 can realize the function of the data sensing component 804 shown in Fig. 8. In addition, the auxiliary controller 902 can be connected to the first data sensing component 903 to obtain sensing information fed back by the first data sensing component 903, and can be connected to the second data sensing component 905 to obtain auxiliary sensing information fed back by the second data sensing component 905, which is used to update the status monitoring information of the autonomous vehicle, allowing the auxiliary controller 902 to obtain more accurate driving information of the autonomous vehicle.

[0118] In some embodiments, both the first data sensing component 903 and the second data sensing component 905 may be implemented using multiple different types of sensors to enrich the sensing of multiple different dimensions of information for the autonomous vehicle.

[0119] Both the first execution unit 904 and the second execution unit 906 can implement the functions of the execution unit 803 shown in FIG.

[0120] In some embodiments, the priority of the second execution device 906 is higher than the priority of the first execution device 904. When the second execution device 906 is enabled, the first execution device 904 is in a disabled state, i.e., the first execution device 904 ceases control over the autonomous vehicle, thereby allowing the second execution device 906 to take over complete control over the autonomous vehicle from the first execution device 904.

[0121] In the autonomous driving system provided by the present application, the second data sensing component 905 and the second execution device 906 enable the auxiliary controller 902 to obtain more detailed driving state information and sensing information during the driving process of the autonomous vehicle when the autonomous vehicle is controlled by the auxiliary controller 902, thereby assisting the auxiliary controller 902 to more effectively control the autonomous vehicle, reducing the occurrence rate of various uncontrollable problems of the autonomous vehicle (e.g., brake failure, control information error, etc.), reducing the probability of traffic accidents occurring during the driving process of the autonomous vehicle, and improving the accuracy of control of the autonomous vehicle.

[0122] It should be noted that the present application is not limited to the specific arrangements and processes described and illustrated above. For the sake of convenience and brevity, detailed descriptions of known methods will be omitted herein. The specific operation steps of the above-described systems, modules, and units can be referenced to the corresponding steps in the methods, and will not be repeated herein.

[0123] FIG. 10 is a structural diagram of an exemplary hardware architecture of a computer device capable of implementing the autonomous driving method and apparatus according to the present application.

[0124] 10, a computer device 1000 includes an input device 1001, an input interface 1002, a central processor 1003, a memory 1004, an output interface 1005, and an output device 1006. The input interface 1002, the central processor 1003, the memory 1004, and the output interface 1005 are interconnected via a bus 1007, and the input device 1001 and the output device 1006 are connected to the bus 1007 via the input interface 1002 and the output interface 1005, respectively, and are further connected to other components of the computer device 1000.

[0125] The input device 1001 receives input information from the outside and transmits the input information to the central processor 1003 via the input interface 1002. The central processor 1003 processes the input information based on computer-executable instructions stored in the memory 1004 to generate output information, stores the output information temporarily or permanently in the memory 1004, and then transmits the output information to the output device 1006 via the output interface 1005. The output device 1006 outputs the output information outside the computer device 1000 for use by a user.

[0126] In some embodiments, the computing device shown in FIG. 10 may be implemented as an electronic device, which may include a memory arranged to store a computer program and a processor arranged to execute the computer program stored in the memory to perform the above-described autonomous driving method.

[0127] In some embodiments, the computing device shown in FIG. 10 may be implemented as an autonomous driving system, which may include a memory arranged to store a computer program and a processor arranged to execute the autonomous driving method described above by executing the computer program stored in the memory.

[0128] The present application further provides a computer-readable storage medium having a computer program stored therein, which, when executed by a processor, realizes the above-described autonomous driving method.

[0129] The above description is merely an example of an embodiment of the present application and does not limit the scope of the claims of the present application. Generally, the embodiments of the present application can be implemented in hardware or dedicated circuits, software, logic, or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software executed by a controller, microprocessor, or other computing device, but the present application is not limited thereto.

[0130] Examples / embodiments of the present application may be implemented by executing computer program instructions by a data processor of a mobile device, e.g., in a processor entity, implemented by hardware, or by a combination of software and hardware. The computer program instructions may be assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.

[0131] Any logic flow block diagrams in the drawings may represent program steps, interconnected logic circuits, modules, and functions, or a combination of program steps, logic circuits, modules, and functions. Computer programs may be stored in memory. The memory may be of any type suitable for the local technology environment and may be implemented by any suitable data storage technology, including, but not limited to, read-only memory (ROM), random-access memory (RAM), optical memory devices and systems (digital versatile disks, DVDs, or CD disks), etc. Computer-readable storage media may include non-transitory storage media. Data processors may be of any type suitable for the local technology environment, including, but not limited to, general-purpose computers, special-purpose computers, microprocessors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable logic devices (FPGAs), and processors based on multi-core processor architectures.

[0132] By way of illustrative and non-limiting examples, the above provides a detailed description of exemplary embodiments / embodiments of the present application. However, when considered in conjunction with the drawings and claims, various modifications and adjustments to the above embodiments will be apparent to those skilled in the art, but do not depart from the scope of the present application. Therefore, the appropriate scope of the present application is determined based on the claims.

Claims

1. An automatic driving method for use in an auxiliary controller, comprising: acquiring status monitoring information that is information obtained by monitoring the operating status of the main controller; and controlling the driving state of the autonomous vehicle in a situation where an operational abnormality of the main controller is determined based on the state monitoring information, The status monitoring information includes intercepted information within a predetermined period, The step of determining an operation abnormality of the main controller in a situation where the intercepted information is not received within the predetermined period, a step of accumulating an abnormal number of times when the intercepted information is not received within the predetermined period and acquiring the accumulated abnormal number; a step of initializing the abnormal count when the intercepted information is received within the predetermined period and the intercepted information is normal information; determining that the main controller is operating abnormally when it is determined that the accumulated abnormality count exceeds a predetermined threshold count; Contains Autonomous driving method.

2. The step of determining an operational abnormality of the main controller based on the status monitoring information comprises: Further comprising: determining an operation abnormality of the main controller when the received intercepted information is abnormal information. The automatic driving method according to claim 1.

3. The step of acquiring status monitoring information includes: receiving sensed information, the sensed information being feedback from a first data sensing component or feedback from a second data sensing component; determining the condition monitoring information based on the sensing information; The state monitoring information includes at least one of driving speed information of the autonomous vehicle, driving angle information of the vehicle, and position information. The automatic driving method according to claim 1.

4. After the step of controlling the driving state of the autonomous vehicle, a step of obtaining auxiliary sensing information, which is information fed back by an auxiliary sensing component; and updating the status monitoring information based on the auxiliary sensing information. The automatic driving method according to claim 3.

5. The sensing information includes at least one of environmental image information, spatial information where the vehicle is located, vehicle status information, and communication information. The automatic driving method according to claim 3.

6. The step of controlling the driving state of the autonomous vehicle includes: disconnecting the main controller's control of the autonomous vehicle based on a preemption policy; and controlling the driving state of the autonomous vehicle based on danger avoidance information determined from at least one of the operation abnormality information of the main controller and the sensing information fed back by a data sensing component. The automatic driving method according to claim 1.

7. The step of controlling the driving state of the autonomously driven vehicle based on the danger avoidance information includes: generating a control command based on the risk avoidance information; transmitting the control command to an actuator so that the actuator controls the driving state of the autonomous vehicle based on the control command; The actuators are communicatively connected to the main controller and the auxiliary controller, respectively. The automatic driving method according to claim 6.

8. the auxiliary controller includes an auxiliary actuator, the main controller includes a main actuator, and the auxiliary actuator and the main actuator are both configured to control an operating state of the autonomous vehicle; the step of disconnecting the main controller's control of the autonomous vehicle based on a preemption policy includes disconnecting the main actuator's control of the autonomous vehicle based on the preemption policy; The step of controlling the driving state of the autonomous vehicle based on the danger avoidance information includes a step of controlling the auxiliary actuator to control the driving state of the autonomous vehicle based on the danger avoidance information. The automatic driving method according to claim 6.

9. an acquisition module arranged to acquire status monitoring information, which is information obtained by monitoring the operating status of the main controller; a determination module configured to control an operating state of the autonomous vehicle when an operation abnormality of the main controller is determined based on the state monitoring information; The status monitoring information includes intercepted information within a predetermined period, the determination module is configured to control a state of the autonomous vehicle when the main controller determines an operation abnormality based on the state monitoring information; Accumulating the abnormal number of times that the intercepted information is not received within the predetermined period, and obtaining the accumulated abnormal number of times; When the intercepted information is received within the predetermined period and the intercepted information is normal information, the abnormal count is initialized; When it is determined that the cumulative number of abnormalities exceeds a predetermined threshold, it is determined that an operation abnormality has occurred in the main controller. Auxiliary controller.

10. a main controller, an auxiliary controller, an execution device, and a data sensing component communicatively connected thereto; The auxiliary controller is arranged to carry out the method for automated driving according to any one of claims 1 to 8. the execution device is configured to acquire control information transmitted by the main controller or the auxiliary controller, and to maintain or change the driving state of the autonomously driven vehicle based on the control information; The data sensing component is configured to feed back sensing information to the main controller or the auxiliary controller, so that the main controller or the auxiliary controller determines state monitoring information of the autonomous vehicle based on the sensing information. Autonomous driving system.

11. at least one processor; and a memory in which at least one computer program is stored, the at least one computer program causing the at least one processor to implement the autonomous driving method according to any one of claims 1 to 8 when the at least one computer program is executed by the at least one processor. electronic equipment.

12. A computer program is stored in the vehicle, and when the computer program is executed by a processor, the automatic driving method according to any one of claims 1 to 8 is realized. A computer-readable storage medium.

13. An automatic driving method for use in an auxiliary controller, comprising: acquiring status monitoring information that is information obtained by monitoring the operating status of the main controller; and controlling the driving state of the autonomous vehicle in a situation where an operational abnormality of the main controller is determined based on the state monitoring information, The step of acquiring status monitoring information includes: receiving sensed information, the sensed information being feedback from a first data sensing component or feedback from a second data sensing component; determining the condition monitoring information based on the sensing information; Further, after the step of controlling the driving state of the autonomous vehicle, a step of obtaining auxiliary sensing information, which is information fed back by an auxiliary sensing component; updating the status monitoring information based on the auxiliary sensing information. Autonomous driving method.

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