Vehicle malfunction processing method, apparatus, equipment, and storage medium

Abstract

Embodiments of this disclosure relate to a method, apparatus, device, and storage medium for handling vehicle malfunctions. [Solution] The method presented herein includes receiving a message associated with the autonomous vehicle's planning system, the message indicating an anomaly in the planning system, and determining that the lateral offset information between the autonomous vehicle's planned trajectory and driving trajectory within a preset time period satisfies a preset condition, thereby determining that the autonomous vehicle's planning system is associated with a first anomaly type, the lateral offset information indicating that the driving trajectory is offset relative to the planned trajectory, and executing a first set of actions corresponding to the first anomaly type, the first set of actions including at least reducing the autonomous vehicle's speed. Thus, embodiments of the present disclosure can determine the anomaly type of the autonomous vehicle, execute corresponding processing actions based on this anomaly type, and improve the timeliness of processing and the reliability of services when responding to anomalies in the autonomous vehicle.

Description

Technical Field

[0001] Exemplary embodiments of the present disclosure generally relate to the field of computers, and particularly to a method, apparatus, device, and computer-readable storage medium for handling vehicle anomalies.

Background Art

[0002] Autopilot is a technology that plans the movement trajectory of a vehicle by using a computer instead of a human driver or assisting the human driver, and controls the vehicle to reach a specified destination. With the progress of autopilot technology, some vehicles (also referred to as autonomous vehicles) based on autopilot capabilities can provide mobility services to users.

Summary of the Invention

[0003] According to a first aspect of the present disclosure, a method for handling vehicle anomalies is provided. The method includes receiving a message associated with a planning system of an autonomous vehicle, where the message indicates that there is an anomaly in the planning system, and in response to determining that the lateral offset information within a preset time period between the planned trajectory and the driving trajectory of the autonomous vehicle meets a preset condition, determining that the planning system of the autonomous vehicle is associated with a first type of anomaly, where the lateral offset information indicates the offset direction of the driving trajectory with respect to the planned trajectory, and executing a first set of operations corresponding to the first type of anomaly, the first set of operations including at least reducing the driving speed of the autonomous vehicle.

[0004] A second aspect of the present disclosure provides a vehicle anomaly processing device. The device includes a message receiving module that receives a message associated with a planning system of an autonomous vehicle, the message being configured to indicate an anomaly in the planning system; a type determination module that determines that the planning system of an autonomous vehicle is associated with a first anomaly type in response to the determination that lateral offset information between the planned trajectory and the driving trajectory of the autonomous vehicle within a preset time period satisfies a preset condition, the lateral offset information being configured to indicate the offset direction of the driving trajectory relative to the planned trajectory; and an action execution module that performs a first set of actions corresponding to the first anomaly type, the first set of actions being configured to at least include reducing the driving speed of the autonomous vehicle.

[0005] A third aspect of the present disclosure provides an electronic device comprising at least one processing unit and at least one memory, the memory of which is coupled to at least one processing unit and stores instructions to be executed by at least one processing unit. When the instructions are executed by at least one processing unit, the device causes the device to perform the method of the first aspect.

[0006] A fourth aspect of this disclosure provides a computer-readable storage medium on which a computer program is stored, and which is executed by a processor to implement the method of the first aspect.

[0007] According to a fifth aspect of this disclosure, a computer program product is provided. The computer program product comprises computer executable instructions, which, when executed by a processor, implement the method of the first aspect of this disclosure.

[0008] It should be understood that the content described in this section is not intended to limit any or any significant features of the embodiments of this disclosure, nor is it used to limit the scope of this disclosure. Other features of this disclosure will be readily apparent from the following description. [Brief explanation of the drawing]

[0009] The above and other features, advantages, and aspects of each embodiment of the present disclosure will become more apparent with reference to the drawings and the detailed description below. In the drawings, identical or similar reference numerals represent identical or similar elements.

[0010] [Figure 1] A schematic diagram of an exemplary environment in which embodiments of this disclosure can be implemented is shown.

[0011] [Figure 2] A flowchart illustrating an exemplary vehicle malfunction processing process according to some embodiments of this disclosure is shown.

[0012] [Figure 3] The following are schematic diagrams illustrating exemplary vehicle malfunction processing processes according to some embodiments of this disclosure.

[0013] [Figure 4] The following are schematic block diagrams illustrating exemplary vehicle malfunction processing according to some embodiments of this disclosure.

[0014] [Figure 5] Block diagrams of electronic devices according to multiple embodiments that can realize this disclosure are shown. [Modes for carrying out the invention]

[0015] Embodiments of this disclosure will be described in more detail below with reference to the drawings. While the drawings illustrate several embodiments of this disclosure, it should be understood that this disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein. Conversely, providing these embodiments should lead to a more detailed and complete understanding of this disclosure. It should be understood that the drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0016] The titles of any sections / subsections provided herein are not limiting. This specification provides a general overview of various embodiments, and any type of embodiment may be included in any section / subsection. Furthermore, embodiments described in any section / subsection may be combined with any other embodiments described in the same section / subsection and / or different sections / subsections.

[0017] In the description of embodiments of this disclosure, “including” and similar terms should be understood as “including, but not limited to.” The term “based on” should be understood as “based at least in part.” The term “one embodiment” or “this embodiment” should be understood as “at least one embodiment.” The term “several embodiments” should be understood as “at least several embodiments.” Other explicit and implicit definitions may also be included below. Terms such as “first,” “second,” etc., may refer to different objects or the same object. Other explicit and implicit definitions may also be included below.

[0018] Embodiments of this disclosure may include user data, data acquisition and / or use, etc. All of these aspects are subject to applicable laws and regulations and related provisions. In embodiments of this disclosure, all data collection, acquisition, processing, modification, transfer, and use are carried out on the premise that the user is aware of and acknowledges them. Accordingly, when implementing each embodiment of this disclosure, it is necessary to notify the user of the type of data or information that may be relevant, the scope of use, and the usage scenarios in an appropriate manner in accordance with applicable laws and regulations, and to obtain the user's permission. 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 to this.

[0019] Any solutions in this specification and its embodiments relating to the processing of personal information are based on a lawful foundation (e.g., obtaining the consent of the data subject and being necessary to perform a contract) and are processed only within the scope of the provisions or agreements. Users may refuse the processing of personal information other than that essential for basic functions, and this will not affect their use of those basic functions.

[0020] According to conventional approaches, autonomous vehicles may experience control and planning anomalies (PNC anomalies) in several scenarios, potentially preventing them from continuing their journey or creating collision risks, thus impacting the normal operation of autonomous vehicles.

[0021] Embodiments of the present disclosure propose a method for handling vehicle anomalies. This method includes receiving a message associated with the planning system of an autonomous vehicle, the message indicating that there is an anomaly in the planning system, determining that the planning system of the autonomous vehicle is associated with a first anomaly type in response to the determination that lateral offset information between the planned trajectory and the driving trajectory of the autonomous vehicle within a preset time period satisfies a preset condition, the lateral offset information indicating that the driving trajectory is offset in the direction 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.

[0022] Thus, the embodiments of the present disclosure can determine different types of abnormalities of the autonomous vehicle, execute corresponding processing operations based on these types of abnormalities, and enhance the timeliness of the processing and the reliability of the service when dealing with abnormalities of the autonomous vehicle.

[0023] Hereinafter, with reference to the drawings, each exemplary implementation of this solution will be described in more detail. Exemplary environment

[0024] FIG. 1 shows a schematic diagram of an exemplary environment 100 in which embodiments of the present disclosure can be implemented. As shown, the environment 100 can include a vehicle 110. The vehicle 110 may be an autonomous vehicle, that is, a vehicle having autonomous driving capabilities (or driverless capabilities), and is also referred to as a driverless vehicle, an autonomous driving vehicle, etc.

[0025] In some scenarios, the vehicle 110 may be assigned to provide mobility services to a user. For example, the user can obtain mobility services provided by the vehicle 110 via a mobility application. In some scenarios, the vehicle 110 may also be referred to as a driverless taxi, or a robotaxi. While the vehicle 110 provides mobility services to the user, a safety operator can be arranged in the vehicle 110. The safety operator can, for example, take over the vehicle 110 under sudden circumstances. Alternatively, the vehicle 110 may be in a driverless control state.

[0026] As shown in FIG. 1, the vehicle 110 may be associated with an electronic device 120. The electronic device 120 may be integrated inside the vehicle 110, or may be connected to the vehicle 110 via a network. As an example, the electronic device 120 can arrange an abnormality processing module of the vehicle 110 to control the vehicle 110 to execute corresponding operations based on different types of abnormalities.

[0027] As shown in Figure 1, the electronic device 120 can also establish a communication connection 140 with the planning system 130. For example, the communication connection 140 can be established by wire or wireless. The communication connection 140 may include, but is not limited to, Bluetooth® connections, mobile network connections, general-purpose serial bus connections, wireless fidelity guaranteed connections, etc., and embodiments of the disclosure are not limited in this respect. In embodiments of the disclosure, the electronic device 120 and the planning system 130 can achieve signaling interaction through the communication connection 140 between them.

[0028] In some embodiments, the planning system 130 can acquire the user's mobility request and plan the trajectory of the vehicle 110. Furthermore, the planning system 130 can also send a message to the electronic device 120 indicating that there is an anomaly in the planning system and requesting a corresponding anomaly handling action.

[0029] The structure and function of Environment 100 are described for illustrative purposes only and should be understood as not to imply any limitations on the scope of this disclosure. Exemplary process

[0030] Figure 2 shows a flowchart illustrating an exemplary vehicle malfunction processing process according to some embodiments of the present disclosure. Process 200 can be implemented in the electronic device 120. Process 200 will now be described with reference to Figure 1.

[0031] In some embodiments, the electronic device 120 can plan a global route corresponding to a 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 sensing, real-time response, and vehicle control, enabling the autonomous vehicle to travel safely along the planned route.

[0032] Furthermore, to cope with complex and ever-changing traffic conditions, the electronic device 120 can also perform local planning using the planning system, making real-time adjustments according to traffic conditions, thereby enabling the autonomous vehicle to avoid obstacles. For example, the electronic device 120 can use the planning system to plan the next route based on preset distances. In this way, the two systems work together to ensure that the autonomous vehicle can reach its destination efficiently and safely from the starting point of the target journey. The following describes the process by which the autonomous vehicle's planning system handles planning anomalies that occur in the vehicle when performing local planning.

[0033] As shown in Figure 2, in block 210, the electronic device 120 receives a message indicating that there is an anomaly in the planning system associated with the autonomous vehicle's planning system.

[0034] To facilitate understanding, the vehicle anomaly handling process will be explained with reference to Figure 3, as shown in Figure 3, in block 310, a PNC anomaly may occur in the planning system before or during the autonomous vehicle's journey. In some embodiments, such PNC anomalies can be classified into, for example, three types: First anomaly type: The autonomous vehicle may exhibit an "S-shaped" trajectory while in motion, thereby posing a safety risk to the vehicle. Second anomaly type: The autonomous vehicle's planning system may fail to plan without having a subsequent planned trajectory, potentially causing traffic congestion. Third anomaly type: The trajectory may become empty while the autonomous vehicle is in motion, preventing the vehicle from following the planned trajectory, increasing safety risks and potentially affecting driving efficiency.

[0035] In some embodiments, messages received by the electronic device 120 related to the autonomous vehicle planning system may be, for example, messages related to the PNC anomalies described above. In block 311, the electronic device 120 can detect PNC anomalies such as a first anomaly type, a second anomaly type, and a third anomaly type.

[0036] In some embodiments, the electronic device 120 can also generate fault codes corresponding to PNC exception types. For example, the electronic device 120 can generate fault codes corresponding to a second and a third abnormality type, such as a second fault code and a third fault code.

[0037] Furthermore, in block 312, the electronic device 120 reports PNC anomaly types that generate fault codes to a monitoring system, and the PNC anomaly types that generate fault codes can be monitored through this monitoring system. In some embodiments, such a monitoring system may be, for example, a system having a communication connection with the electronic device 120.

[0038] In block 313, the electronic device 120 may be, for example, a server having a communication connection with the electronic device 120, and may report PNC anomaly types that generate fault codes to the server (or cloud) in a way that allows for the formation of an anomaly information display for the PNC anomaly types that generate fault codes, making it easier for users to view.

[0039] Furthermore, in block 314, the electronic device 120 can also classify and process the detected PNC anomaly; that is, the electronic device 120 can determine whether the detected PNC anomaly is of type 1, type 2, or type 3. The determination and response for the three anomaly types are described below.

[0040] Returning to Figure 2, in block 220, in response to the determination that the lateral offset information between the autonomous vehicle's planned trajectory and its driving trajectory within a preset time period satisfies the preset conditions, it is determined that the autonomous vehicle's planning system is associated with the first anomaly type, and the lateral offset information indicates the direction in which the driving trajectory is offset from the planned trajectory.

[0041] In another embodiment, such lateral offset information can also indicate the offset distance of the travel trajectory relative to the planned trajectory.

[0042] In some embodiments, to determine the positional relationship between the planned trajectory and the actual driving trajectory of an autonomous vehicle within a preset time period, the electronic device 120 can determine a first set of positions in the planned trajectory and a second set of positions in the driving trajectory, and the first and second sets of positions can be associated with a preset time period. Furthermore, the electronic device 120 can determine a set of lateral offset directions for the first set of positions relative to the second set of positions.

[0043] In some embodiments, such lateral offset can be caused by, for example, a sudden movement of the autonomous vehicle's steering wheel or a problem occurring in the autonomous vehicle's control system, resulting in a deviation between the autonomous vehicle's planned trajectory and its actual trajectory.

[0044] In some embodiments, such a set of lateral offset directions can indicate whether the autonomous vehicle's planned trajectory within a preset time period is located to the left or right of the travel trajectory, or whether the planned trajectory within a preset time period exhibits a change in positive or negative sign compared to the travel trajectory. For example, the autonomous vehicle's planned trajectory exhibits an "S-shape" within a preset time period.

[0045] Furthermore, the electronic device 120 can determine that the lateral offset information satisfies a preset condition in response to the fact that the degree of change in a set of lateral offset directions is greater than a preset degree, and such degree of change indicates the number of times the lateral offset direction changes in adjacent time points.

[0046] In some embodiments, adjacent times within such a preset time period may include, for example, time 1, time 2, time 3, and time 4. In response to its determination at time 1, the electronic device 120 determines that the autonomous vehicle's planned trajectory is located to the left of the driving trajectory, the autonomous vehicle's planned trajectory at time 2 is located to the right of the driving trajectory, the autonomous vehicle's planned trajectory at time 3 is located to the left of the driving trajectory, and the autonomous vehicle's planned trajectory at time 4 is located to the right of the driving trajectory. That is, the autonomous vehicle's planned trajectory is always changing more than the position of the driving trajectory, and since the number of directional changes within the preset time period is greater than the preset number, the electronic device 120 can determine that the lateral offset information of the autonomous vehicle satisfies the preset conditions.

[0047] The above is merely an illustrative description of an ideal state, and it should be understood that this disclosure is not intended to limit the number of changes in that direction.

[0048] In another embodiment, the electronic device 120 can also determine that the lateral offset information satisfies a preset condition in response to the autonomous vehicle determining that the sign of the planned trajectory repeatedly changes in relation to the travel trajectory at adjacent times within a preset time period.

[0049] In yet another embodiment, the electronic device 120 may also determine that the abruptness of a set of lateral offsets is greater than a preset value and determine that the lateral offset information satisfies a preset condition, such abruptness may be determined based on acceleration or offset distance.

[0050] In this way, the electronic device 120 can more efficiently determine that the autonomous vehicle's planning system is related to the first type of anomaly, thereby improving the timeliness of the autonomous vehicle's response to anomalies and, consequently, the user experience.

[0051] Returning to Figure 2, in block 230, a first set of actions corresponding to the first abnormality type is performed, and this first set of actions includes at least reducing the autonomous vehicle's speed.

[0052] Continuing with Figure 3, in block 315, the electronic device 120, in response to determining that the autonomous vehicle's planning system is associated with a first type of anomaly, can restore the autonomous vehicle to normal operation by performing a corresponding first set of actions, such as reducing the autonomous vehicle's speed and correcting the autonomous vehicle's position information. Furthermore, in block 316, in response to the autonomous vehicle's normal operation, the electronic device 120 can determine that the first type of PNC anomaly has been resolved.

[0053] The following describes the detection and response to the second type of anomaly in autonomous vehicles.

[0054] In some embodiments, the electronic device 120 determines that the autonomous vehicle's planning system is associated with a second anomaly type in response to the autonomous vehicle failing to replan the global route based on the initial route search information.

[0055] In some embodiments, the electronic device 120 can determine the target origin of the initial pathfinding information as initial pathfinding information, and such initial pathfinding information may include other content, and it should be understood that this disclosure only describes the target origin of the initial pathfinding as an example.

[0056] In some embodiments, the electronic device 120 can initiate an initial route search based on the autonomous vehicle in response to the autonomous vehicle's distance from the target origin being a preset distance. In some embodiments, the electronic device 120 can clear the cache of the autonomous vehicle planning system and restart route searching based on the autonomous vehicle in response to the autonomous vehicle failing to replan the global route based on the initial route search information. Furthermore, the electronic device 120 can determine that the autonomous vehicle's planning system is associated with a second anomaly type in response to the autonomous vehicle repeating the above process multiple times at a preset distance.

[0057] Continuing with reference to Figure 3, in block 317, the electronic device 120, in response to the autonomous vehicle's planning system determining that a second anomaly type is associated with the second anomaly type, performs a second set of actions corresponding to the second anomaly type, the second set of actions including at least triggering the autonomous vehicle to park on the curb. In some embodiments, the electronic device 120 may, in response to the autonomous vehicle completing the curb parking, send a target message to a remote device corresponding to the second anomaly type. This target message may indicate a test order request associated with the autonomous vehicle. Furthermore, the remote device may generate and send a corresponding test order to the autonomous vehicle so that the autonomous vehicle can remotely switch orders.

[0058] In block 318, the electronic device 120 can, in response to the autonomous vehicle receiving this test order, plan a global route based on the test order and determine whether the anomaly has been cleared. Furthermore, in block 319, the electronic device 120 can, in response to the autonomous vehicle failing to plan a global route based on the test order, generate a rescue request to request offline assistance.

[0059] Furthermore, in block 316, the electronic device 120 can determine whether the anomaly has been cleared or generate a rescue request, and then determine that the second type of PNC anomaly has been processed.

[0060] The following describes the detection and response to the third type of anomaly in autonomous vehicles.

[0061] 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 successfully planned a trajectory in response to the planning system, but the autonomous vehicle's driving trajectory became empty because the autonomous vehicle's control system did not receive the planned trajectory for reasons such as a communication failure between the planning system and the control system. This allows the electronic device 120 to determine that the autonomous vehicle's planning system is associated with a third anomaly type.

[0062] Continuing with reference to Figure 3, in block 320, the electronic device 120 can perform a third set of actions corresponding to the third anomaly type, which at least includes triggering the autonomous vehicle to park within its current lane in response to the autonomous vehicle's planning system determining that the third anomaly type is associated with it.

[0063] Furthermore, in block 321, the electronic device 120 can determine whether the planning system has successfully returned to normal within a preset time period (e.g., 5 seconds) in response to the autonomous vehicle completing parking within the current lane. For example, the electronic device 120 can determine whether the planning system has successfully returned to normal within a preset time period based on the autonomous vehicle repeatedly initiating planning requests within the preset time period. Furthermore, in block 319, the electronic device 120 generates a rescue request to request offline rescue in response to the planning system not having successfully returned to normal.

[0064] Furthermore, in block 316, the electronic device 120 can determine that a PNC anomaly of type 3 has been processed in response to the planning system determining that it has returned to normal operation within a preset time period or has generated a rescue request.

[0065] During the process of the autonomous vehicle driving or when a PNC (Personal Nucleation Control) malfunction occurs, the electronic device 120 can detect point clouds around the autonomous vehicle. In this process, if the electronic device 120 detects a risk of collision with a point cloud, it can trigger the autonomous vehicle to stop immediately to ensure the safety of the autonomous vehicle.

[0066] Thus, the embodiments of this disclosure can determine the type of abnormality in an autonomous vehicle, execute corresponding processing operations based on this abnormality type, and improve the timeliness of processing and the reliability of services when dealing with an abnormality in an autonomous vehicle. Exemplary devices and equipment

[0067] Embodiments of this disclosure further provide corresponding apparatus for implementing the methods or processes described above. Figure 4 shows a schematic configuration block diagram for an exemplary vehicle malfunction processing apparatus 400 according to some embodiments of this disclosure. The apparatus 400 may be implemented in or included in the electronic equipment 120. Each module / component within the apparatus 400 may be implemented by hardware, software, firmware, or any combination thereof.

[0068] As shown in Figure 4, the device 400 includes a message receiving module 410 that receives messages associated with the autonomous vehicle's planning system, configured such that the messages indicate an anomaly in the planning system; a type determination module 420 that determines that the autonomous vehicle's planning system is associated with a first anomaly type in response to the determination that the lateral offset information between the autonomous vehicle's planned trajectory and its driving trajectory within a preset time period satisfies a preset condition, and is configured such that the lateral offset information indicates the direction in which the driving trajectory is offset relative to the planned trajectory; and an action execution module 430 that performs a first set of actions corresponding to the first anomaly type, the first set of actions being configured to at least include reducing the autonomous vehicle's driving speed.

[0069] In some embodiments, the device 400 includes a first processing module configured to perform a second set of actions corresponding to a second anomaly type in response to the autonomous vehicle's planning system determining that the autonomous vehicle's anomaly type is associated with the second anomaly type, and the second set of actions at least includes triggering the autonomous vehicle to park on the roadside.

[0070] In some embodiments, measure 400 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 related to the autonomous vehicle from the remote device, and generate a distress request in response to the autonomous vehicle failing to replan its global route based on the test order.

[0071] In some embodiments, the device 400 includes a third processing module configured to perform a third set of actions corresponding to the third anomaly type, which at least includes determining 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 a planned trajectory, and triggering the autonomous vehicle to park within its current lane.

[0072] In some embodiments, the device 400 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 having completed parking within the current lane, and to generate a rescue request in response to the planning system not having returned to normal.

[0073] In some embodiments, the device 400 further comprises a fifth processing module configured to generate fault codes corresponding to anomalies.

[0074] In some embodiments, the device 400 further comprises a sixth processing module configured to determine a first set of positions of a planned track and a second set of positions of a travel trajectory, wherein the first set of positions and the second set of positions are related within a preset time period, to determine a set of lateral offset information of the first set of positions relative to the second set of positions, and to determine whether the lateral offset information satisfies a preset condition based on a set of lateral offset directions.

[0075] In some embodiments, the sixth processing module can determine that the lateral offset information satisfies a preset condition in response to the degree of change in a set of lateral offset directions being greater than a preset degree, the degree of change being further configured to indicate the number of times the lateral offset direction has changed direction in adjacent time points.

[0076] In some embodiments, the first set of operations further includes correcting the attitude information of the autonomous vehicle.

[0077] The modules included in the 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 modules of the device 400 may be implemented at least partially by one or more hardware logic components. Examples of hardware logic components that can be used, but are not limited to, include field-programmable gate arrays (FPGAs), dedicated integrated circuits (ASICs), dedicated standards (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0078] Figure 5 shows a block diagram of an electronic device 500 in which one or more embodiments of the present disclosure are implemented. It should be understood that the electronic device 500 shown in Figure 5 is merely illustrative and should not constitute any limitation on the function and scope of the embodiments described herein. The electronic device 500 shown in Figure 5 can implement the electronic device 120 of Figure 1.

[0079] As shown in Figure 5, the electronic device 500 is in the form of a general-purpose electronic device. The components of the electronic device 500 may include, but are not limited to, one or more processors or processing units 510, memory 520, storage device 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 an actual or virtual processor and can perform various processes according to a program stored in 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.

[0080] The electronic device 500 typically includes multiple computer storage media. Such media may be any available media accessible to the electronic device 500, and may include, but are not limited to, volatile media, non-volatile media, removable media, and non-removable media. Memory 520 may be volatile memory (e.g., registers, caches, random access memory (RAM)), non-volatile memory (e.g., read-only memory (ROM), electro-erasable programmable read-only memory (EEPROM), flash memory, or any combination thereof). Storage media 530 may be removable media and non-removable media, and may include machine-readable media such as flash drives, disks, or any other media, which can be used to store information and / or data and can be accessed within the electronic device 500.

[0081] The electronic device 500 may further include additional removable / non-removable, volatile / non-volatile storage media. Not shown in Figure 5, it may provide disk drives for reading from or writing to removable, non-volatile disks (e.g., “floppy disks”). In these cases, each driver may be connected to a bus (not shown) by one or more data media interfaces. The memory 520 may include a computer program product 525 having one or more program modules, which are arranged to perform various methods or operations of various embodiments of the present disclosure.

[0082] The communication unit 540 enables communication with other electronic devices via a communication medium. Furthermore, the functions of the components of the electronic device 500 can be realized by a single computing cluster or multiple computer devices, and these computer devices can communicate via a communication connection. Therefore, the electronic device 500 can operate in a network environment using logical connections with one or more other servers, network personal computers (PCs), or other network nodes.

[0083] The input device 550 may be one or more input devices such as a mouse, keyboard, or trackball. The output device 560 may be one or more output devices such as a display, speaker, or printer. The electronic device 500 may also communicate with one or more external devices (not shown) such as a storage device or display device via the communication unit 540 as needed, communicate with one or more devices that allow the user to interact with the electronic device 500, or communicate with any device (e.g., a network card or modem) that allows the electronic device 500 to communicate with one or more other electronic devices. Such communication can be performed via an input / output (I / O) interface (not shown).

[0084] According to exemplary embodiments of the present disclosure, a computer-readable storage medium is provided which stores computer-executable instructions that, when executed by a processor, implement the above-described method. According to exemplary embodiments of the present disclosure, a computer program product is further provided which is tangibly stored on a non-transient computer-readable medium and comprises computer-executable instructions that, when executed by a processor, implement the above-described method.

[0085] Here, various aspects of this disclosure will be described with reference to flowcharts and / or block diagrams of the methods, apparatus, devices, and computer program products realized by this disclosure. It should be understood that each block in the flowcharts and / or block diagrams, and each combination of blocks in the flowcharts and / or block diagrams, can be realized by computer-readable program instructions.

[0086] These computer-readable program instructions can be provided to the processing units of a general-purpose computer, a dedicated computer, or other programmable data processing device, and so a machine can be manufactured that generates a device that implements the functions / operations defined in one or more blocks of a flowchart and / or block diagram when these instructions are executed by the processing units of a computer or other programmable data processing device. These computer-readable program instructions may be stored in a computer-readable storage medium, and these instructions cause a computer, a programmable data processing device, and / or other device to operate in a particular way, and so a computer-readable medium storing the instructions includes a product containing instructions that implement various modes of the functions / operations defined in one or more blocks of a flowchart and / or block diagram.

[0087] Computer-readable program instructions can be loaded into a computer, other programmable data processing device, or other device, which can then execute a series of operational steps to generate a computer-implemented process. Thus, instructions executed on a computer, other programmable data processing device, or other device can implement functions / operations defined in one or more blocks of a flowchart and / or block diagram.

[0088] The flowcharts and block diagrams in the drawings illustrate the implementable architectures, functions, and operations of several implemented systems, methods, and computer program products relating to this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, program segment, or part of an instruction containing one or more executable instructions for implementing a given logical function. The functions shown in a block may occur in an order different from the order shown in the drawing, or they may be implemented as a switch. For example, two consecutive blocks may actually be executed essentially in parallel, or they may be executed in reverse order depending on the functions they relate to. Note also that each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, may be implemented in a dedicated hardware-based system that performs a given function or operation, or in a combination of dedicated hardware and computer instructions.

[0089] While various implementations of this disclosure have been described above, these descriptions are illustrative, incomplete, and not limited to the various implementations disclosed. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the implementations described. The choice of terms used herein is intended to best describe the principle, practical use, or improvements in the technology in the market of each implementation, or to enable those skilled in the art to understand each embodiment disclosed herein.

Claims

1. Receiving a message associated with the planning system of an autonomous vehicle, wherein the message indicates an anomaly in the planning system, In response to the determination that the lateral offset information between the autonomous vehicle's planned trajectory and its driving trajectory within a preset time period satisfies the preset conditions, the autonomous vehicle's planning system is determined to be associated with a first anomaly type, and the lateral offset information indicates that the driving trajectory is offset in the direction relative to the planned trajectory. The system performs a first set of actions corresponding to the first abnormality type, the first set of actions including at least reducing the driving speed of the autonomous vehicle, How to handle vehicle malfunctions.

2. In response to the autonomous vehicle failing to replan the global route based on the initial route search information, the autonomous vehicle's planning system determines that it is associated with a second anomaly type, The system further includes performing a second set of actions corresponding to the second abnormality type, the second set of actions including at least triggering the autonomous vehicle to park on the roadside, The method according to claim 1.

3. Sending a target message corresponding to the second abnormality type to a remote device, Receiving test orders associated with the aforementioned autonomous vehicle from a remote device, The autonomous vehicle further includes generating a distress request in response to its failure to plan a global route based on the test order, The method according to claim 2.

4. In response to the fact that the control system of the autonomous vehicle has not received the planned trajectory, the planning system of the autonomous vehicle is determined to be associated with a third anomaly type, The system further includes performing a third set of actions corresponding to the third abnormality type, the third set of actions at least including triggering the autonomous vehicle to park within the current lane, The method according to claim 1.

5. In response to the autonomous vehicle completing parking within the current lane, the planning system determines whether it will return to normal within the preset time period. The further includes generating a distress request in response to the fact that the aforementioned planning system has not returned to normal, The method according to claim 4.

6. The further includes generating a fault code corresponding to the aforementioned anomaly, The method according to claim 2 or 4.

7. The positions of the first set of the planned trajectory and the second set of the travel trajectory are determined, and the positions of the first set and the second set of the travel trajectory are associated with the preset time period. Determine the lateral offset direction of one set of the first set of positions relative to the second set of positions, The further includes determining whether the lateral offset information satisfies the preset conditions based on the set of lateral offset directions, The method according to claim 1.

8. Determining whether the aforementioned lateral offset information satisfies the preset conditions based on the set of lateral offset directions is: In response to the degree of change in the lateral offset direction of the set being greater than a preset value, it is determined that the lateral offset information satisfies the preset condition, and the degree of change indicates the number of times the lateral offset direction changes occur at adjacent time points. The method according to claim 7.

9. The first set of operations further includes correcting the attitude information of the autonomous vehicle. The method according to claim 1.

10. A message receiving module that receives messages associated with the planning system of an autonomous vehicle, wherein the message is configured to indicate that there is an abnormality in the planning system, In response to the determination that the lateral offset information between the autonomous vehicle's planned trajectory and its driving trajectory within a preset time period satisfies the preset conditions, the autonomous vehicle's planning system is determined to be associated with a first anomaly type, and the lateral offset information is configured such that the driving trajectory indicates an offset direction relative to the planned trajectory, The system includes an action execution module that performs a first set of actions corresponding to the first abnormality type, wherein the first set of actions is configured to at least include reducing the driving speed of the autonomous vehicle. Vehicle malfunction processing unit.

11. At least one processing unit, An electronic device comprising at least one memory coupled to the at least one processing unit, wherein, when the instruction is executed by the at least one processing unit, the instruction causes the electronic device to perform the method according to any one of claims 1 to 9. electronic equipment.

12. When executed on a processor, a computer program that implements the method described in any one of claims 1 to 9 is stored. Computer-readable storage medium.

13. When executed by a processor, the computer includes a computer executable instruction that implements the method according to any one of claims 1 to 9. Computer program products.

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