Vehicle anomaly handling method and apparatus, device and storage medium
By receiving abnormal messages from the planning system, determining the type of abnormality of the autonomous vehicle, and executing corresponding processing actions, the abnormal problems that occur during the planning and driving process of the autonomous vehicle are resolved, the timeliness of processing and service reliability are improved, and safe driving is ensured.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- BEIJING VOYAGER TECH CO LTD
- Filing Date
- 2025-11-04
- Publication Date
- 2026-06-04
AI Technical Summary
Anomalies in autonomous vehicles during planning and operation can lead to impediments or collision risks, affecting service reliability and safety.
By receiving abnormal messages from the planning system, the system can determine the lateral deviation between the planned trajectory and the driving trajectory, identify the type of abnormality, and execute corresponding processing actions, such as reducing speed, pulling over, or requesting assistance, to handle the abnormality of the autonomous vehicle.
This improves the timeliness and reliability of autonomous vehicles in handling anomalies, ensuring safe driving and a better user experience.
Smart Images
Figure CN2025132407_04062026_PF_FP_ABST
Abstract
Description
Methods, devices, equipment, and storage media for handling vehicle malfunctions
[0001] This application claims priority to Chinese Patent Application No. 202411747434.8, filed on November 29, 2024, entitled "Method, Apparatus, Device and Storage Medium for Handling Vehicle Abnormalities", the entire contents of which are incorporated herein by reference. Technical Field
[0002] The exemplary embodiments disclosed herein generally relate to the field of computers, and particularly to methods, apparatus, devices, and computer-readable storage media for handling vehicle anomalies. Background Technology
[0003] Autonomous driving is a technology that uses computers to replace or assist human drivers in planning the vehicle's trajectory and controlling the vehicle to reach a designated destination. With advancements in autonomous driving technology, some vehicles based on autonomous driving capabilities (also known as autonomous vehicles) are able to provide travel services to users. Summary of the Invention
[0004] In a first aspect of this disclosure, a method for handling vehicle anomalies is provided. The method includes: receiving a message associated with a planning system of an autonomous vehicle, the message indicating an anomaly in the planning system; in response to determining that lateral offset information between the planned trajectory and the driving trajectory of the autonomous vehicle within a preset time period meets preset conditions, determining that the planning system of the autonomous vehicle is associated with a first anomaly type, the lateral offset information indicating the direction of offset of the driving trajectory relative to the planned trajectory; and performing a first set of actions corresponding to the first anomaly type, the first set of actions including at least reducing the driving speed of the autonomous vehicle.
[0005] In a second aspect of this disclosure, an apparatus for handling vehicle anomalies is provided. The apparatus includes: a message receiving module configured to receive a message associated with a planning system of an autonomous vehicle, the message indicating an anomaly in the planning system; a type determination module configured to, in response to determining that lateral offset information between the planned trajectory and the driving trajectory of the autonomous vehicle within a preset time period meets preset conditions, determine that the planning system of the autonomous vehicle is associated with a first anomaly type, the lateral offset information indicating the direction of offset of the driving trajectory relative to the planned trajectory; and an action execution module configured to execute a first set of actions corresponding to the first anomaly type, the first set of actions including at least reducing the driving speed of the autonomous vehicle.
[0006] In a third aspect of this disclosure, an electronic device is provided. The device includes at least one processing unit; and at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit. When executed by the at least one processing unit, the instructions cause the device to perform the method of the first aspect.
[0007] In a fourth aspect of this disclosure, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program that can be executed by a processor to implement the method of the first aspect.
[0008] In a fifth aspect of this disclosure, a computer program product is provided. The computer program product includes computer-executable instructions that, when executed by a processor, implement the method according to a first aspect of this disclosure.
[0009] It should be understood that the content described in this content section is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description
[0010] 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. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:
[0011] Figure 1 shows a schematic diagram of an example environment in which embodiments of the present disclosure may be implemented;
[0012] Figure 2 shows a flowchart of an example vehicle anomaly handling process according to some embodiments of the present disclosure;
[0013] Figure 3 illustrates a schematic diagram of an example vehicle anomaly handling process according to some embodiments of the present disclosure;
[0014] Figure 4 shows a schematic structural block diagram of example vehicle anomaly handling according to some embodiments of the present disclosure; and
[0015] Figure 5 shows a block diagram of an electronic device capable of implementing several embodiments of the present disclosure. Detailed Implementation
[0016] 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.
[0017] It should be noted that the headings of any section / subsection provided herein are not limiting. Various embodiments are described throughout this document, and embodiments of any type may be included under any section / subsection. Furthermore, embodiments described in any section / subsection may be combined in any way with any other embodiments described in the same section / subsection and / or different sections / subsections.
[0018] In the description of embodiments of this disclosure, the term "comprising" and similar terms should be understood as open-ended inclusion, i.e., "including but not limited to". The term "based on" should be understood as "at least partially based on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The term "some embodiments" should be understood as "at least some embodiments". Other explicit and implicit definitions may also be included below. The terms "first", "second", etc., may refer to different or the same objects. Other explicit and implicit definitions may also be included below.
[0019] The embodiments of this disclosure may involve user data, data acquisition, and / or use. All of these aspects comply with applicable laws, regulations, and relevant provisions. In the embodiments of this disclosure, all data collection, acquisition, processing, manipulation, forwarding, and use are conducted with the user's knowledge and confirmation. Accordingly, in implementing the embodiments of this disclosure, the type, scope of use, and usage scenarios of any data or information that may be involved should be communicated to the user and their authorization obtained in accordance with relevant laws and regulations through appropriate means. The specific methods of notification and / or authorization may vary depending on the actual situation and application scenario, and the scope of this disclosure is not limited in this respect.
[0020] In this specification and the embodiments, any processing of personal information will be carried out only under the premise of legality (such as obtaining the consent of the personal information subject, or being necessary for the performance of a contract), and will only be carried out within the scope stipulated or agreed upon. A user's refusal to process personal information other than that necessary for basic functions will not affect the user's use of basic functions.
[0021] According to traditional solutions, autonomous vehicles may experience control and planning anomalies (PNC anomalies) in certain scenarios, which may cause the autonomous vehicle to be unable to continue to pass or to be at risk of collision, thereby affecting the normal service of the autonomous vehicle.
[0022] Embodiments of this disclosure propose a vehicle anomaly handling scheme. According to this scheme, a message associated with the autonomous vehicle's planning system can be received, indicating an anomaly in the planning system; in response to determining that the lateral offset information between the autonomous vehicle's planned trajectory and its driving trajectory within a preset time period meets preset conditions, the autonomous vehicle's planning system is determined to be associated with a first anomaly type, the lateral offset information indicating the offset direction of the driving trajectory relative to the planned trajectory; and a first set of actions corresponding to the first anomaly type is executed, the first set of actions including at least reducing the autonomous vehicle's driving speed.
[0023] In this way, the embodiments of this disclosure can determine the anomaly type of the autonomous vehicle and perform corresponding processing actions based on the anomaly type, thereby improving the timeliness of the autonomous vehicle in dealing with anomalies and the reliability of the service.
[0024] The following section provides a detailed description of various example implementations of this scheme, with reference to the accompanying drawings.
[0025] Example Environment
[0026] Figure 1 illustrates a schematic diagram of an example environment 100 in which embodiments of the present disclosure can be implemented. As shown, environment 100 may include a vehicle 110. Vehicle 110 may be an autonomous vehicle, which is a vehicle with autonomous driving capability (or driverless capability), also known as a driverless car, autonomous driving vehicle, etc.
[0027] In some scenarios, vehicle 110 can be assigned to provide travel services to users. For example, users can obtain travel services provided by vehicle 110 through a travel application. In some scenarios, vehicle 110 may also be called a driverless taxi or robotaxi. During the process of vehicle 110 providing travel services to users, vehicle 110 may be equipped with a safety operator. The safety operator can, for example, take over vehicle 110 in case of an emergency. Alternatively, vehicle 110 may also be in an unmanned state.
[0028] As shown in Figure 1, vehicle 110 can also be associated with electronic device 120. Electronic device 120 can be integrated inside vehicle 110 or connected to vehicle 110 via a network. As an example, electronic device 120 can be deployed with an exception handling module of vehicle 110 to control vehicle 110 to perform corresponding actions based on different types of exceptions.
[0029] As shown in Figure 1, the electronic device 120 can also establish a communication connection 140 with the planning system 130. As an example, the communication connection 140 can be established via wired or wireless means. The communication connection 140 may include, but is not limited to, Bluetooth connections, mobile network connections, Universal Serial Bus connections, Wi-Fi connections, etc., and the embodiments of this disclosure are not limited in this respect. In the embodiments of this disclosure, the electronic device 120 and the planning system 130 can achieve signaling interaction through the communication connection 140 between them.
[0030] In some embodiments, the planning system 130 can acquire a user's travel request and plan the trajectory of the vehicle 110. Furthermore, the planning system 130 can also send a message to the electronic device 120 to indicate that an anomaly has occurred in the planning system and request corresponding anomaly handling actions.
[0031] It should be understood that the structure and function of environment 100 are described for illustrative purposes only and do not imply any limitation on the scope of this disclosure.
[0032] Example process
[0033] Figure 2 shows a flowchart of an example vehicle anomaly handling process 200 according to some embodiments of the present disclosure. Process 200 can be implemented at electronic device 120. Process 200 is described below with reference to Figure 1.
[0034] In some embodiments, the electronic device 120 can plan a global route corresponding to the target journey based on the autonomous vehicle's planning system. Such a planning system can be used, for example, to plan the autonomous vehicle's route, navigation, obstacle avoidance, environmental perception, real-time response, and vehicle control, thereby enabling the autonomous vehicle to travel safely along the planned route.
[0035] Furthermore, to cope with complex and ever-changing traffic conditions, the electronic device 120 can also utilize a planning system for local planning, making real-time adjustments based on traffic conditions to achieve obstacle avoidance for the autonomous vehicle. As an example, the electronic device 120 can use the planning system to plan the next route segment based on a preset distance. In this way, through the collaborative work of both, it can be ensured that the autonomous vehicle can efficiently and safely reach its destination from the starting point of the target journey. The following section will describe the process by which the autonomous vehicle's planning system handles planning anomalies during local planning.
[0036] As shown in Figure 2, in box 210, electronic device 120 receives a message associated with the autonomous vehicle's planning system, indicating that there is an anomaly in the planning system.
[0037] To facilitate understanding, the handling process of vehicle anomalies will be described below with reference to Figure 3. As shown in Figure 3, in box 310, the planning system may encounter PNC anomalies before or during the autonomous vehicle's operation. In some embodiments, such PNC anomalies can be categorized into three types: The first type of anomaly is that the autonomous vehicle may exhibit an "S-shaped" trajectory during operation, leading to safety risks. The second type of anomaly is that the autonomous vehicle's planning system may fail to plan a trajectory, resulting in no subsequent planned trajectory and causing traffic congestion. The third type of anomaly is that the autonomous vehicle may have an empty trajectory during operation, preventing the vehicle from following the planned trajectory, increasing safety risks, and affecting driving efficiency.
[0038] In some embodiments, the message received by the electronic device 120 in connection with the autonomous vehicle's planning system may be, for example, a message associated with the aforementioned PNC anomaly. In block 311, the electronic device 120 may detect the PNC anomaly, such as a first anomaly type, a second anomaly type, and a third anomaly type.
[0039] In some embodiments, the electronic device 120 may also generate fault codes corresponding to PNC anomaly types. As an example, the electronic device 120 may generate fault codes corresponding to a second anomaly type and a third anomaly type, such as a second fault code and a third fault code.
[0040] Furthermore, in block 312, the electronic device 120 can report the PNC anomaly type that generates the fault code to a monitoring system, and monitor the PNC anomaly type that generates the fault code through the monitoring system. In some embodiments, such a monitoring system may be, for example, a system that has a communication connection with the electronic device 120.
[0041] In box 313, the electronic device 120 can also report the PNC anomaly type that generates the fault code to a server (or cloud). Such a server can be, for example, a server that has a communication connection with the electronic device 120, and the server can display anomaly information for the PNC anomaly type that generates the fault code, so that it is convenient for the user to view.
[0042] Furthermore, in box 314, the electronic device 120 can also classify the detected PNC anomalies, that is, the electronic device 120 can determine whether the detected PNC anomaly is a first anomaly type, a second anomaly type, or a third anomaly type. The judgment and response of the three anomaly types will be introduced below.
[0043] Returning to Figure 2, in box 220, the electronic device 120 determines that the lateral offset information between the planned trajectory and the driving trajectory of the autonomous vehicle within a preset time period meets the preset conditions, and determines that the planning system of the autonomous vehicle is associated with the first anomaly type. The lateral offset information indicates the offset direction of the driving trajectory relative to the planned trajectory.
[0044] In other embodiments, such lateral offset information can also indicate the offset distance of the driving trajectory relative to the planned trajectory.
[0045] To determine the positional relationship between the planned trajectory and the actual driving trajectory of an autonomous vehicle within a preset time period, in some embodiments, the electronic device 120 can determine a first set of positions for the planned trajectory and a second set of positions for the driving trajectory, and the first and second sets of positions can be associated with the preset time period. Further, the electronic device 120 can determine a set of lateral offset directions of the first set of positions relative to the second set of positions.
[0046] In some embodiments, such lateral deviation may be caused by factors such as sudden steering wheel turns or problems with the autonomous vehicle's control system, resulting in a deviation between the autonomous vehicle's planned trajectory and its actual driving trajectory.
[0047] In some embodiments, such a set of lateral offset directions can refer to whether the planned trajectory of the autonomous vehicle within a preset time period is located to the left or right of the driving trajectory, or it can be represented by the change in the positive or negative sign of the planned trajectory of the autonomous vehicle relative to the driving trajectory within a preset time period. As an example, the planned trajectory of the autonomous vehicle within a preset time period exhibits an "S-shape".
[0048] Furthermore, in response to a set of changes in lateral offset directions exceeding a preset level, the electronic device 120 can determine that the lateral offset information meets the preset conditions. Such a degree of change indicates the number of times the lateral offset direction changes in adjacent time periods.
[0049] In some embodiments, adjacent moments within such a preset time period may include, for example, moment 1, moment 2, moment 3, and moment 4. The electronic device 120 determines that at moment 1, the planned trajectory of the autonomous vehicle is located to the left of the driving trajectory; at moment 2, the planned trajectory of the autonomous vehicle is located to the right of the driving trajectory; at moment 3, the planned trajectory of the autonomous vehicle is located to the left of the driving trajectory; and at moment 4, the planned trajectory of the autonomous vehicle is again located to the right of the driving trajectory. That is, the position of the planned trajectory of the autonomous vehicle relative to the driving trajectory is constantly changing, and the number of directional changes within the preset time period is greater than a preset number. Therefore, the electronic device 120 can determine that the lateral offset information of the autonomous vehicle meets a preset condition.
[0050] It is understood that the above is merely an exemplary illustration under ideal conditions, and this disclosure is not intended to limit the number of times the direction can change.
[0051] In other embodiments, the electronic device 120 may also determine, in response to determining adjacent moments within a preset time period, that the positive and negative signs of the planned trajectory change repeatedly relative to the driving trajectory, in order to determine that the lateral offset information meets preset conditions.
[0052] In some other embodiments, the electronic device 120 may also determine that the severity of a set of lateral offsets is greater than a preset level, and may determine that the lateral offset information meets the preset conditions. Such severity may be determined based on acceleration or offset distance.
[0053] In this way, electronic device 120 can more efficiently determine that the autonomous vehicle's planning system is associated with the first anomaly type, improve the timeliness of the autonomous vehicle's response to anomalies, and thus enhance the user experience.
[0054] Returning to Figure 2, in box 230, electronic device 120 performs a first set of actions corresponding to the first anomaly type, the first set of actions including at least reducing the driving speed of the autonomous vehicle.
[0055] Referring again to Figure 3, in box 315, in response to determining that the autonomous vehicle's planning system is associated with a first anomaly type, electronic device 120 can execute the corresponding first set of actions, such as reducing the autonomous vehicle's speed and correcting its pose information, thereby allowing the autonomous vehicle to return to normal. Further, in box 316, in response to the autonomous vehicle returning to normal, electronic device 120 can determine that the PNC anomaly of the first anomaly type has been processed.
[0056] The detection and response to the second type of anomaly in autonomous vehicles will be described below.
[0057] In some embodiments, in response to the failure of the autonomous vehicle to replan the global route based on the initial route-finding information, the electronic device 120 may determine that the autonomous vehicle's planning system is associated with a second anomaly type.
[0058] In some embodiments, the electronic device 120 may determine the initial target starting point for initial routing as initial routing information. Such initial routing information may also include other content. It is understood that this disclosure is only illustrative using the initial target starting point for initial routing as an example.
[0059] In some embodiments, the electronic device 120 may initiate initial route finding based on the autonomous vehicle when the distance between the autonomous vehicle and the target starting point is a preset distance. In some embodiments, the electronic device 120 may clear the cache of the autonomous vehicle's route planning system and re-initiate route finding based on the autonomous vehicle when the autonomous vehicle fails to replan the global route based on the initial route finding information. Further, if the electronic device 120 determines that the autonomous vehicle's route planning system is associated with a second anomaly type when the autonomous vehicle repeats the above process multiple times at the preset distance.
[0060] Referring again to Figure 3, in box 317, in response to determining that the autonomous vehicle's planning system is associated with a second anomaly type, electronic device 120 can execute a second set of actions corresponding to the second anomaly type. The second set of actions includes at least triggering the autonomous vehicle to pull over. In some embodiments, in response to the autonomous vehicle completing its pullover, electronic device 120 can send a target message corresponding to the second anomaly type to a remote device. This target message may indicate a test order request associated with the autonomous vehicle. Further, the remote device can generate and send a corresponding test order to the autonomous vehicle to remotely switch orders for that autonomous vehicle.
[0061] In box 318, in response to the autonomous vehicle receiving the test order, electronic device 120 can plan a global route based on the test order to determine whether the anomaly has been resolved. Further, in box 319, in response to the autonomous vehicle failing to plan a global route based on the test order, electronic device 120 can generate a rescue request to request offline assistance.
[0062] Furthermore, in box 316, after the electronic device 120 responds to determining whether the anomaly has been resolved or generating a rescue request, it can determine that the PNC anomaly of the second anomaly type has been processed.
[0063] The detection and response to the third type of anomaly in autonomous vehicles will be described below.
[0064] In some embodiments, the electronic device 120 determines that the autonomous vehicle's planning system is associated with a third anomaly type in response to the autonomous vehicle's control system not receiving the planned trajectory. For example, the electronic device 120 responds to the planning system successfully planning a trajectory, but due to communication connection issues between the planning system and the control system, the autonomous vehicle's control system fails to receive the planned trajectory, resulting in an empty driving trajectory for the autonomous vehicle. Therefore, the electronic device 120 can determine that the autonomous vehicle's planning system is associated with a third anomaly type.
[0065] Referring again to Figure 3, in box 320, electronic device 120, in response to determining that the autonomous vehicle's planning system is associated with a third anomaly type, can execute a third set of actions corresponding to the third anomaly type. The third set of actions includes at least triggering the autonomous vehicle to stop in the current lane.
[0066] Further, in box 321, in response to the autonomous vehicle completing its stop within the current lane, electronic device 120 can determine whether the planning system has returned to normal within a preset time period (e.g., 5 seconds). As an example, electronic device 120 can determine whether the planning system has returned to normal within the preset time period based on the autonomous vehicle repeatedly initiating planning requests. Further, in box 319, in response to the planning system not returning to normal, electronic device 120 generates a rescue request to request offline assistance.
[0067] Furthermore, in box 316, after the electronic device 120 determines that the planning system has returned to normal or generated a rescue request within a preset time period, it can determine that the PNC anomaly of the third anomaly type has been handled.
[0068] During autonomous vehicle operation or PNC anomaly, electronic device 120 can detect point clouds around the autonomous vehicle. If, during this process, electronic device 120 detects a collision risk with a certain point cloud, it can trigger the autonomous vehicle to brake immediately to ensure the safety of the autonomous vehicle.
[0069] In this way, the embodiments of this disclosure can determine the anomaly type of the autonomous vehicle and perform corresponding processing actions based on the anomaly type, thereby improving the timeliness of the autonomous vehicle in dealing with anomalies and the reliability of the service.
[0070] Example devices and equipment
[0071] Embodiments of this disclosure also provide corresponding apparatus for implementing the methods or processes described above. Figure 4 shows a schematic structural block diagram of an example apparatus 400 for handling vehicle anomalies according to certain embodiments of this disclosure. Apparatus 400 may be implemented as or included in electronic device 120. The various modules / components in apparatus 400 may be implemented by hardware, software, firmware, or any combination thereof.
[0072] As shown in Figure 4, the device 400 includes a message receiving module 410, configured to receive a message associated with the planning system of the autonomous vehicle, the message indicating that the planning system has an anomaly; a type determination module 420, configured to determine that the planning system of the autonomous vehicle is associated with a first anomaly type in response to determining that the lateral offset information between the planned trajectory and the driving trajectory of the autonomous vehicle within a preset time period meets preset conditions, the lateral offset information indicating the offset direction of the driving trajectory relative to the planned trajectory; and an action execution module 430, configured to execute a first set of actions corresponding to the first anomaly type, the first set of actions including at least reducing the driving speed of the autonomous vehicle.
[0073] In some embodiments, the apparatus 400 further includes a first processing module configured to, in response to the failure of the autonomous vehicle to replan the global route based on the initial route-finding information, determine that the autonomous vehicle's planning system is associated with a second anomaly type; and execute a second set of actions corresponding to the second anomaly type, the second set of actions including at least triggering the autonomous vehicle to pull over.
[0074] In some embodiments, the apparatus 400 further includes a second processing module configured to send a target message corresponding to a second anomaly type to a remote device; receive a test order associated with the autonomous vehicle from the remote device; and generate a rescue request in response to the autonomous vehicle's failure to plan a global route based on the test order.
[0075] In some embodiments, the device 400 further includes a third processing module configured to, in response to the autonomous vehicle's control system not receiving a planned trajectory, determine that the autonomous vehicle's planning system is associated with a third anomaly type; and execute a third set of actions corresponding to the third anomaly type, the third set of actions including at least triggering the autonomous vehicle to stop in the current lane.
[0076] In some embodiments, the device 400 further includes a fourth processing module configured to determine whether the planning system has returned to normal within a preset time period in response to the autonomous vehicle completing a stop in the current lane; and to generate a rescue request in response to the planning system not returning to normal.
[0077] In some embodiments, the apparatus 400 further includes a fifth processing module configured to generate a fault code corresponding to the anomaly.
[0078] In some embodiments, the device 400 further includes a sixth processing module configured to determine a first set of positions of the planned trajectory and a second set of positions of the driving trajectory, the first set of positions and the second set of positions being associated with a preset time period; determine a set of lateral offset directions of the first set of positions relative to the second set of positions; and determine, based on the set of lateral offset directions, whether the lateral offset information meets preset conditions.
[0079] In some embodiments, the sixth processing module is further configured to determine that the lateral offset information meets a preset condition in response to a set of lateral offset directions changing to a degree greater than a preset degree, wherein the degree of change indicates the number of times the lateral offset direction changes in adjacent time periods.
[0080] In some embodiments, the first set of actions also includes correcting the pose information of the autonomous vehicle.
[0081] The modules included in device 400 can be implemented in various ways, including software, hardware, firmware, or any combination thereof. In some embodiments, one or more units can be implemented using software and / or firmware, such as machine-executable instructions stored on a storage medium. In addition to or as an alternative to machine-executable instructions, some or all of the modules in device 400 can be implemented at least partially by one or more hardware logic components. By way of example, and not limitation, exemplary types of hardware logic components that can be used include field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.
[0082] Figure 5 shows a block diagram of an electronic device 500 in which one or more embodiments of the present disclosure may be implemented. It should be understood that the electronic device 500 shown in Figure 5 is merely exemplary and should not constitute any limitation on the functionality and scope of the embodiments described herein. The electronic device 500 shown in Figure 5 can be used to implement the electronic device 120 of Figure 1.
[0083] As shown in Figure 5, the electronic device 500 is in the form of a general-purpose electronic device. Components of the electronic device 500 may include, but are not limited to, one or more processors or processing units 510, memory 520, storage devices 530, one or more communication units 540, one or more input devices 550, and one or more output devices 560. The processing unit 510 may be a physical or virtual processor and is capable of performing various processes according to programs stored in the memory 520. In a multiprocessor system, multiple processing units execute computer-executable instructions in parallel to improve the parallel processing capability of the electronic device 500.
[0084] Electronic device 500 typically includes multiple computer storage media. Such media can be any accessible media that is accessible to electronic device 500, including but not limited to volatile and non-volatile media, removable and non-removable media. Memory 520 can be volatile memory (e.g., registers, cache, random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory), or some combination thereof. Storage device 530 can be removable or non-removable media and can include machine-readable media, such as flash drives, disks, or any other media that can be used to store information and / or data and can be accessed within electronic device 500.
[0085] Electronic device 500 may further include additional removable / non-removable, volatile / non-volatile storage media. Although not shown in FIG. 5, disk drives for reading from or writing to removable, non-volatile disks (e.g., "floppy disks") and optical disk drives for reading from or writing to removable, non-volatile optical disks may be provided. In these cases, each drive may be connected to a bus (not shown) via one or more data media interfaces. Memory 520 may include computer program product 525 having one or more program modules configured to perform various methods or actions of various embodiments of the present disclosure.
[0086] Communication unit 540 enables communication with other electronic devices via a communication medium. Additionally, the functionality of components of electronic device 500 can be implemented using a single computing cluster or multiple computing machines capable of communicating via communication connections. Therefore, electronic device 500 can operate in a networked environment using logical connections to one or more other servers, network personal computers (PCs), or another network node.
[0087] Input device 550 can be one or more input devices, such as a mouse, keyboard, trackball, etc. Output device 560 can be one or more output devices, such as a monitor, speaker, printer, etc. Electronic device 500 can also communicate with one or more external devices (not shown) via communication unit 540 as needed. These external devices include storage devices, display devices, etc., and can communicate with one or more devices that enable user interaction with electronic device 500, or with any device that enables electronic device 500 to communicate with one or more other electronic devices (e.g., network card, modem, etc.). Such communication can be performed via input / output (I / O) interface (not shown).
[0088] According to an exemplary implementation of this disclosure, a computer-readable storage medium is provided that stores computer-executable instructions thereon, wherein the computer-executable instructions are executed by a processor to implement the methods described above. According to an exemplary implementation of this disclosure, a computer program product is also provided, which is tangibly stored on a non-transitory computer-readable medium and includes computer-executable instructions, which are executed by a processor to implement the methods described above.
[0089] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatuses, devices, and computer program products implemented according to this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.
[0090] These computer-readable program instructions can be provided to a processing unit of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processing unit of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.
[0091] Computer-readable program instructions can be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions that execute on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.
[0092] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.
[0093] Various implementations of this disclosure have been described above. The foregoing description is exemplary and not exhaustive, nor is it limited to the disclosed implementations. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described implementations. The terminology used herein is chosen to best explain the principles, practical applications, or improvements to technology in the market, or to enable others skilled in the art to understand the various implementations disclosed herein.
Claims
1. A method for handling vehicle malfunctions, comprising: A message associated with the autonomous vehicle's planning system is received, indicating that the planning system is malfunctioning; In response to determining that the lateral offset information between the planned trajectory and the driving trajectory of the autonomous vehicle within a preset time period meets a preset condition, the planning system of the autonomous vehicle is determined to be associated with a first anomaly type, wherein the lateral offset information indicates the offset direction of the driving trajectory relative to the planned trajectory; as well as Perform a first set of actions corresponding to the first anomaly type, the first set of actions including at least reducing the driving speed of the autonomous vehicle.
2. The method according to claim 1, further comprising: In response to the failure of the autonomous vehicle to replan the global route based on the initial route-finding information, it is determined that the planning system of the autonomous vehicle is associated with a second anomaly type; as well as Execute a second set of actions corresponding to the second anomaly type, the second set of actions including at least triggering the autonomous vehicle to pull over.
3. The method according to claim 2, further comprising: Send a target message corresponding to the second anomaly type to the remote device; Receive test orders associated with the autonomous vehicle from remote devices; as well as In response to the failure of the autonomous vehicle to plan a global route based on the test order, a rescue request is generated.
4. The method according to claim 1, further comprising: In response to the autonomous vehicle's control system not receiving the planned trajectory, it is determined that the autonomous vehicle's planning system is associated with a third anomaly type; as well as Execute a third set of actions corresponding to the third anomaly type, the third set of actions including at least triggering the autonomous vehicle to stop in the current lane.
5. The method according to claim 4, further comprising: In response to the autonomous vehicle completing a stop in the current lane, determine whether the planning system has returned to normal within a preset time period; as well as In response to the planning system failing to return to normal, a rescue request is generated.
6. The method according to claim 2 or 4, further comprising: Generate a fault code corresponding to the anomaly.
7. The method according to claim 1, further comprising: Determine a first set of positions for the planned trajectory and a second set of positions for the driving trajectory, wherein the first set of positions and the second set of positions are associated with the preset time period; Determine a set of lateral offset directions of the first set of positions relative to the second set of positions; as well as Based on the set of lateral offset directions, determine whether the lateral offset information meets the preset conditions.
8. The method according to claim 7, wherein determining whether the lateral offset information satisfies the preset condition based on the set of lateral offset directions includes: In response to the fact that the degree of change of the set of lateral offset directions is greater than a preset degree, it is determined that the lateral offset information meets the preset condition, wherein the degree of change indicates the number of times the lateral offset direction changes in adjacent time periods.
9. The method according to claim 1, wherein the first set of actions further includes correcting the pose information of the autonomous vehicle.
10. A device for handling vehicle malfunctions, comprising: The message receiving module is configured to receive a message associated with the planning system of the autonomous vehicle, the message indicating that the planning system has an anomaly; The type determination module is configured to determine that the planning system of the autonomous vehicle is associated with a first anomaly type in response to determining that the lateral offset information between the planned trajectory and the driving trajectory of the autonomous vehicle within a preset time period meets a preset condition, wherein the lateral offset information indicates the offset direction of the driving trajectory relative to the planned trajectory. as well as The action execution module is configured to execute a first set of actions corresponding to the first exception type, wherein the first set of actions includes at least reducing the driving speed of the autonomous vehicle.
11. An electronic device, comprising: At least one processing unit; as well as At least one memory, coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions causing the electronic device to perform the method according to any one of claims 1 to 9 when executed by the at least one processing unit.
12. A computer-readable storage medium having a computer program stored thereon, the computer program being executable by a processor to implement the method according to any one of claims 1 to 9.
13. A computer program product comprising computer-executable instructions, wherein the computer-executable instructions, when executed by a processor, implement the method according to any one of claims 1 to 9.