A method, apparatus and device for monitoring start-up time of an autonomous driving system

Abstract

The application discloses a starting time monitoring method, device and equipment of an automatic driving system, the method comprises the following steps: in response to a received starting instruction, obtaining a current starting time point when each function module is started respectively; when the initialization of each function module is completed, obtaining an initialization completion time point respectively; calculating the difference between the initialization completion time point and the current starting time point to obtain a starting time; and determining a target fault module from the multiple function modules according to the comparison result of the starting time and a preset starting time range. Therefore, the selection of the target fault module is accurately performed through the difference calculation between the initialization completion time point and the current starting time point, and the problem information of a single function module can be conveniently collected comprehensively, and the fault of the automatic driving system can be timely investigated.

Description

Technical Field

[0001] This invention relates to the field of system monitoring technology, and in particular to a method, apparatus and device for monitoring the start-up time of an autonomous driving system. Background Technology

[0002] With the continuous development of artificial intelligence technology, autonomous driving technology has become a focus of attention across all sectors of society. At the same time, as vehicles are an important means of transportation in our lives, people have higher requirements for their performance stability and driving safety.

[0003] In autonomous driving systems, the system startup status is often related to user experience. When the system starts slowly, users may be dissatisfied with the startup process. However, from the user's perspective, they can only know that the system started slowly. Specific system problem information can only be collected manually. Since there are many components required for various functions in autonomous driving systems, manual collection cannot comprehensively collect the information needed to troubleshoot problems, which can easily lead to untimely troubleshooting of autonomous driving system faults. Summary of the Invention

[0004] This invention provides a method, apparatus, and device for monitoring the startup time of an autonomous driving system, which solves the technical problem that in the prior art, startup problem information of autonomous driving systems can only be collected manually. Since there are many components required for various functions in an autonomous driving system, manual collection cannot comprehensively collect the information needed to troubleshoot problems, which easily leads to untimely troubleshooting of autonomous driving system faults.

[0005] The first aspect of this invention provides a method for monitoring the startup time of an autonomous driving system. The autonomous driving system includes multiple functional modules, and the method includes:

[0006] In response to the received startup command, obtain the current startup time point when each of the aforementioned functional modules is started;

[0007] When each of the aforementioned functional modules completes initialization, the initialization completion time point is obtained respectively;

[0008] Calculate the difference between the initialization completion time and the current startup time to obtain the startup time;

[0009] Based on the comparison between the startup time and the preset startup time range, the target fault module is determined from the multiple functional modules.

[0010] Optionally, the step of determining the target fault module from the plurality of functional modules based on the comparison result between the startup time and a preset startup time range includes:

[0011] Compare each startup time with the preset startup time range of each functional module;

[0012] If a single startup time is not within the corresponding startup time range, then the functional module is identified as the target fault module.

[0013] If multiple startup times are not within the corresponding startup time range, then the target fault module is determined from the multiple functional modules.

[0014] Optionally, the method further includes:

[0015] If each startup time is within its corresponding startup time range, then all functional modules are considered to be functioning normally.

[0016] Optionally, the step of determining the target fault module from the multiple functional modules if multiple startup times are not within the corresponding startup time range includes:

[0017] If multiple startup times are not within the corresponding startup time range, the corresponding functional modules will be designated as pending functional modules.

[0018] Determine whether there are module dependencies among the various undetermined functional modules;

[0019] If only the module dependency relationship exists, sort the undetermined functional modules according to the module dependency relationship to obtain a module sequence;

[0020] Calculate the difference between the startup times of each module in reverse order according to the module sequence to obtain the dependency-free startup time of each undetermined functional module.

[0021] Select the pending functional module with the longest dependency-free startup time as the target fault module;

[0022] If none of the aforementioned module dependencies exist, the pending functional module corresponding to the longest startup time is selected as the target fault module.

[0023] Optionally, the method further includes:

[0024] If some of the module dependencies exist, then select the first functional module with the longest startup time from the undetermined functional modules that do not have the module dependencies.

[0025] Jump to execute the step of sorting each of the undetermined functional modules according to the module dependency relationship to obtain a module sequence, and take the target fault module as the second functional module;

[0026] If the startup time of the first functional module is greater than the startup time of the second functional module, then the first functional module is determined as the target fault module.

[0027] If the startup time of the first functional module is less than the startup time of the second functional module, then the second functional module is determined as the target fault module.

[0028] If the startup time of the first functional module is equal to the startup time of the second functional module, then the first functional module and the second functional module are identified as target fault modules.

[0029] Optionally, the method further includes:

[0030] When the current start time is obtained, the vehicle number to which the autonomous driving system belongs is recorded;

[0031] A log file is constructed using the current startup time and the vehicle number;

[0032] When the initialization completion time is obtained, the initial completion time is recorded in the log file to obtain the target log file.

[0033] Optionally, the method further includes:

[0034] Once the target faulty module is identified, the vehicle number and module version number corresponding to the target faulty module are extracted from the target log file.

[0035] Extract the initialization completion time point corresponding to the target fault module as the event occurrence time point;

[0036] Using the vehicle number and module version number corresponding to the target fault module, as well as the time point of the event, a work order task is created and forwarded to the responsible terminal corresponding to the target fault module.

[0037] Optionally, the method further includes:

[0038] When the terminal in charge receives the repair completion information for the target fault module, the update function module carried by the repair completion information is obtained;

[0039] By replacing the target faulty module with the updated function module, an updated autonomous driving system is obtained.

[0040] The steps involve jumping to execute the startup command received in the response and obtaining the current startup time point when each of the functional modules is started.

[0041] A second aspect of the present invention provides a device for monitoring the start-up time of an autonomous driving system. The autonomous driving system includes multiple functional modules, and the device includes:

[0042] The response module is used to respond to the received startup command and obtain the current startup time point when each of the functional modules is started.

[0043] The initialization completion time point acquisition module is used to acquire the initialization completion time point when each of the aforementioned functional modules completes initialization.

[0044] The startup time calculation module is used to calculate the difference between the initialization completion time and the current startup time to obtain the startup time;

[0045] The target fault module determination module is used to determine the target fault module from among the multiple functional modules based on the comparison result between the startup time and the preset startup time range.

[0046] A third aspect of the present invention provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of monitoring the start-up time of the autonomous driving system as described in any of the first aspects of the present invention.

[0047] As can be seen from the above technical solutions, the present invention has the following advantages:

[0048] In response to the received start command, the system obtains the current start time of each functional module. When each functional module completes initialization, it obtains the initialization completion time. The difference between the initialization completion time and the current start time is calculated to obtain the start time. Based on the comparison between the start time and a preset start time range, the target faulty module is determined from multiple functional modules. Thus, by calculating the difference between the initialization completion time and the current start time, the target faulty module can be accurately selected, facilitating the comprehensive collection of problem information for individual functional modules and enabling timely troubleshooting of faults in the autonomous driving system. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a flowchart of the steps of a startup time monitoring method for an autonomous driving system provided in Embodiment 1 of the present invention;

[0051] Figure 2 This is a flowchart of the steps of a startup time monitoring method for an autonomous driving system provided in Embodiment 2 of the present invention;

[0052] Figure 3 This is a structural block diagram of a startup time monitoring device for an autonomous driving system provided in Embodiment 3 of the present invention. Detailed Implementation

[0053] This invention provides a method, apparatus, and device for monitoring the startup time of an autonomous driving system, which addresses the technical problem that in the prior art, startup information of autonomous driving systems can only be collected manually. However, since autonomous driving systems require numerous components for various functions, manual collection cannot comprehensively gather the information needed to troubleshoot problems, easily leading to untimely fault diagnosis of autonomous driving systems.

[0054] To make the objectives, features, and advantages of this invention more apparent and understandable, the technical solutions of the embodiments of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0055] Please see Figure 1 , Figure 1 The flowchart illustrates the steps of a startup time monitoring method for an autonomous driving system provided in Embodiment 1 of the present invention.

[0056] This invention provides a method for monitoring the startup time of an autonomous driving system. The autonomous driving system includes multiple functional modules, and the method includes:

[0057] Step 101: In response to the received startup command, obtain the current startup time point when each functional module is started;

[0058] A start command is a command used to start an autonomous driving system. It triggers the start of various functional modules to achieve the overall start of the autonomous driving system, including but not limited to commands generated by triggering physical buttons or virtual buttons.

[0059] A functional module refers to a collection of program elements, such as data descriptions and executable statements, used to implement the various functions of an autonomous driving system. These functional modules may have dependencies on each other, meaning that the startup or implementation of a later functional module depends on the startup of an earlier functional module.

[0060] In this embodiment of the invention, when the autonomous driving system receives a start command, it indicates that the start status of the autonomous driving system needs to be monitored. All functional modules can be started, and the start time of each functional module can be obtained as the current start time point corresponding to each functional module.

[0061] Step 102: When each functional module completes initialization, obtain the initialization completion time point respectively;

[0062] After a functional module is started, it needs to be initialized to wake up the various components inside the module. When the initialization of each functional module is complete, it means that the functional module is ready to start and can directly implement its functions. The current time is taken as the initialization completion time point for each functional module.

[0063] It should be noted that, in the specific implementation, a recording module can be set up within the autonomous driving system to monitor its startup in real time, so as to obtain the initialization completion time and current startup time of the functional module.

[0064] Step 103: Calculate the difference between the initialization completion time and the current startup time to obtain the startup time;

[0065] In this embodiment, the difference between the initialization completion time and the current startup time is calculated to obtain the startup time. It should be noted that the initialization completion time and the current startup time are usually expressed in hours, minutes and seconds. Therefore, after the startup time is calculated, it can be converted into seconds, microseconds or other uniform units for convenient subsequent calculations.

[0066] Step 104: Based on the comparison between the startup time and the preset startup time range, determine the target fault module from multiple functional modules.

[0067] In an autonomous driving system, each functional module has different functional logic and varying degrees of complexity, thus each module has a pre-defined startup time range. Therefore, after obtaining the startup time, the startup time and startup time range of each functional module can be compared. By determining whether the startup time falls within the startup time range, the target faulty module can be identified from among multiple functional modules.

[0068] It should be noted that there should be at least one target faulty module. When multiple functional modules that are outside the startup time range appear at the same time, they can be further filtered according to their startup time to reduce the difficulty of subsequent module repair.

[0069] In this embodiment of the invention, in response to the received start command, the current start time of each functional module is obtained. When each functional module completes initialization, the initialization completion time is obtained, and the difference between the initialization completion time and the current start time is calculated to obtain the start time. Based on the comparison between the start time and a preset start time range, the target faulty module is determined from multiple functional modules. Thus, by calculating the difference between the initialization completion time and the current start time, the target faulty module can be accurately selected, facilitating the comprehensive collection of problem information for individual functional modules and enabling timely troubleshooting of faults in the autonomous driving system.

[0070] Please see Figure 2 , Figure 2 This is a flowchart illustrating the steps of a startup time monitoring method for an autonomous driving system provided in Embodiment 2 of the present invention.

[0071] This invention provides a method for monitoring the startup time of an autonomous driving system. The autonomous driving system includes multiple functional modules, and the method includes:

[0072] Step 201: In response to the received startup command, obtain the current startup time point when each functional module is started;

[0073] Step 202: When each functional module completes initialization, obtain the initialization completion time point respectively;

[0074] Step 203: Calculate the difference between the initialization completion time and the current startup time to obtain the startup time;

[0075] In this embodiment of the invention, the specific implementation process of steps 201-203 is similar to that of steps 101-103, and will not be repeated here.

[0076] Step 204: Compare each startup time with the preset startup time range of each functional module;

[0077] After obtaining the startup time corresponding to each functional module, in order to determine whether the startup of the functional module is normal, each startup time can be compared with the preset startup time range of each functional module.

[0078] It should be noted that the startup time range can be constructed by taking the average of the startup times of various functional modules within a historical period as the median of the range, and then assigning a certain error time as the endpoint values. However, the startup time range may be different or the same for different functional modules. For functional modules with module dependencies, the startup time range of subsequent functional modules needs to take into account the startup time of the preceding functional modules they depend on when setting the startup time range.

[0079] Step 205: If a single startup time is not within the corresponding startup time range, then the functional module is identified as the target fault module.

[0080] In one example of the present invention, if there is only a single startup time that is not within the startup time range corresponding to its functional module, it indicates that the startup delay of the autonomous driving system may be due to the slow startup of that functional module. In this case, the functional module can be identified as the target fault module, and the staff responsible for the terminal can be notified to carry out maintenance and updates.

[0081] It should be noted that if the startup of the autonomous driving system is still delayed after updating and modifying this functional module, it may be due to a problem with the hardware device that carries the autonomous driving system. In this case, the vehicle to which it belongs can be retrieved for further physical inspection.

[0082] Step 206: If multiple startup times are not within the corresponding startup time range, then the target fault module is determined from the multiple functional modules.

[0083] In another embodiment of the present invention, if there are multiple startup times that are not within the startup time range corresponding to their functional modules, it indicates that there may be multiple functional module failures, and further investigation is needed to determine whether this situation is caused by module dependency.

[0084] Optionally, step 206 may include the following sub-steps S11-S16:

[0085] S11. If there are multiple startup times that are not within the corresponding startup time range, then the corresponding functional modules will be designated as pending functional modules.

[0086] S12. Determine if there are module dependencies between the pending functional modules;

[0087] S13. If only module dependencies exist, sort the undetermined functional modules according to the module dependencies to obtain the module sequence;

[0088] S14. Calculate the difference between each startup time in reverse order of the module sequence to obtain the dependency-free startup time corresponding to each undetermined functional module.

[0089] S15. Select the pending functional module corresponding to the longest dependency-free startup time as the target fault module.

[0090] S16. If there are no module dependencies, the pending functional module corresponding to the longest startup time is selected as the target fault module.

[0091] In this embodiment, if multiple startup times are outside the startup time range of their respective functional modules, these functional modules can be filtered out as pending functional modules. Further, the existence of module dependencies between these pending functional modules is determined according to their operational logic. If module dependencies exist between all pending functional modules, it indicates that all pending functional modules reside on the same operational logic. In this case, the pending functional modules can be sorted according to their module dependencies to obtain a module sequence. Then, the differences between each pending functional module are calculated in reverse order according to this module sequence to determine the dependency-free startup time corresponding to each pending functional module, thus achieving dependency-free startup of functional modules.

[0092] After determining the dependency-free startup time of each pending functional module, due to the overall module dependency relationship, there will inevitably be cases where the startup time of some or all pending functional modules will time out. In this case, for ease of operation, the pending functional module corresponding to the longest dependency-free startup time can be directly selected as the target fault module.

[0093] Furthermore, if there are no module dependencies between all pending functional modules, it indicates that each pending functional module belongs to a different functional implementation, and there is no need to remove the dependencies between functional modules. In this case, the pending functional module with the longest startup time can be directly selected as the target fault module.

[0094] Furthermore, step 206 also includes the following sub-steps S21-S25:

[0095] S21. If some modules have module dependencies, select the first functional module with the longest startup time from the undetermined functional modules that do not have module dependencies.

[0096] S22. Jump to execute the step of sorting each pending functional module according to the module dependency relationship to obtain the module sequence, and take the target fault module as the second functional module;

[0097] S23. If the startup time of the first functional module is greater than the startup time of the second functional module, then the first functional module is determined as the target fault module.

[0098] S24. If the startup time of the first functional module is less than the startup time of the second functional module, then the second functional module is determined as the target fault module.

[0099] S25. If the startup time of the first functional module is equal to the startup time of the second functional module, then the first functional module and the second functional module are identified as the target fault modules.

[0100] In this embodiment, if there are module dependencies, multiple functions may fail. The first functional module with the longest startup time is selected from the pending functional modules that do not have module dependencies.

[0101] Simultaneously, steps S13-S16 are executed to obtain the target fault module with which there is a dependency as the second functional module. The startup time of the first functional module and the startup time of the second functional module are further compared to determine the target fault module.

[0102] Step 207: If each startup time is within the corresponding startup time range, then all functional modules are determined to be normal.

[0103] In this embodiment of the invention, if all startup times are within the startup time range corresponding to the functional modules, then all functional modules are determined to be normal, and the autonomous driving system is determined to be in a normal startup state.

[0104] Optionally, the method further includes the following steps:

[0105] When the current start time is obtained, the vehicle number to which the autonomous driving system belongs is recorded;

[0106] A log file is constructed using the current startup time and vehicle number;

[0107] When the initialization completion time is obtained, the initial completion time is recorded in the log file to obtain the target log file.

[0108] In the specific implementation, to facilitate subsequent analysis, the vehicle number to which the autonomous driving system belongs can be recorded when the current startup time is obtained. The log file can then be constructed using the current startup time and the vehicle number. Specifically, the name, number, or identifier of the functional module can be used as the key, and the current time point can be used as the specific value for each line in the log file, until log records for all functional modules are generated.

[0109] When each module is initialized and its internal operation is ready, the ready time is recorded and saved to the log file of the running time, generating the target log file. In this way, the target log file saves the vehicle number, the start time of each module and the ready time.

[0110] Furthermore, the method also includes the following steps:

[0111] Once the target faulty module is identified, extract the vehicle number and module version number corresponding to the target faulty module from the target log file;

[0112] Extract the initialization completion time point corresponding to the target fault module as the event occurrence time point;

[0113] Using the vehicle number and module version number corresponding to the target fault module, as well as the time of the event, a work order task is created and forwarded to the terminal responsible for the target fault module.

[0114] After identifying the target faulty module, the vehicle number and module version number corresponding to that module can be extracted from the target log file. The corresponding initialization completion time can then be extracted as the event occurrence time to indicate the specific time of the system's delayed startup. The module version number can also be determined by parsing the log file; the first line of the log file will record the software version number. By reading key strings related to the version number, such as the branch or commit number, the software version can be identified.

[0115] After obtaining the vehicle number, module version number, and the time of the event, a work order can be created and forwarded to the terminal responsible for the target faulty module, so that technicians can perform the update and repair.

[0116] In the actual implementation, after reading the above-mentioned relevant information, the software version number, specific time, specific vehicle, specific module, and log file path are obtained. Then, a Jira work order is automatically created using Python and automatically forwarded to the terminal of the module manager.

[0117] In one example of the present invention, the method further includes the following steps:

[0118] When the terminal receives a repair completion message for the target faulty module, it retrieves the update function module carried in the repair completion message.

[0119] The updated autonomous driving system is obtained by replacing the target faulty module with the updated functional module;

[0120] Jump to execute the received startup command and retrieve the current startup time of each functional module.

[0121] In practice, technicians can repair the code or operational logic within the target faulty module from the responsible terminal. Upon completion of the repair and update, they upload the updated version of the target faulty module and repair completion information to the autonomous driving system. The autonomous driving system obtains the updated functional module carried by the repair completion information, uses this updated functional module to replace the target faulty module, updates the original autonomous driving system, and finally jumps to step 201 to continuously monitor the startup of the autonomous driving system until it is in a normal startup state.

[0122] In this embodiment of the invention, in response to the received start command, the current start time of each functional module is obtained. When each functional module completes initialization, the initialization completion time is obtained, and the difference between the initialization completion time and the current start time is calculated to obtain the start time. Based on the comparison between the start time and a preset start time range, the target faulty module is determined from multiple functional modules. Thus, by calculating the difference between the initialization completion time and the current start time, the target faulty module can be accurately selected, facilitating the comprehensive collection of problem information for individual functional modules and enabling timely troubleshooting of faults in the autonomous driving system.

[0123] Please see Figure 3 , Figure 3 This is a structural block diagram of a startup time monitoring device for an autonomous driving system provided in Embodiment 3 of the present invention.

[0124] This invention provides a device for monitoring the startup time of an autonomous driving system. The autonomous driving system includes multiple functional modules, and the device includes:

[0125] The response module 301 is used to respond to the received start command and obtain the current start time point when each functional module is started.

[0126] The initialization completion time point acquisition module 302 is used to acquire the initialization completion time point when each functional module completes initialization.

[0127] The startup time calculation module 303 is used to calculate the difference between the initialization completion time and the current startup time to obtain the startup time;

[0128] The target fault module determination module 304 is used to determine the target fault module from multiple functional modules based on the comparison result between the startup time and the preset startup time range.

[0129] Optionally, the target fault module determination module 304 includes:

[0130] The comparison submodule is used to compare each startup time with the preset startup time range of each functional module.

[0131] The first determination submodule is used to determine the functional module as the target fault module if there is a single startup time that is not within the corresponding startup time range;

[0132] The second determination submodule is used to determine the target fault module from multiple functional modules if there are multiple startup times that are not within the corresponding startup time range.

[0133] Optionally, the target fault module determination module 304 further includes:

[0134] The system normality determination submodule is used to determine that all functional modules are normal if all startup times are within the corresponding startup time range.

[0135] Optionally, the second determining submodule is specifically used for:

[0136] If multiple startup times are not within the corresponding startup time range, the corresponding functional modules will be designated as pending functional modules.

[0137] Determine if there are module dependencies among the pending functional modules;

[0138] If only module dependencies exist, sort the undetermined functional modules according to the module dependencies to obtain a module sequence;

[0139] Calculate the difference between the startup times of each module in reverse order of the module sequence to obtain the dependency-free startup time of each pending functional module.

[0140] Select the pending functional module with the longest dependency-free startup time as the target fault module;

[0141] If there are no module dependencies, the pending functional module corresponding to the longest startup time is selected as the target fault module.

[0142] Optionally, the second determining submodule is further used for:

[0143] If some modules have module dependencies, then select the first functional module with the longest startup time from the undetermined functional modules that do not have module dependencies.

[0144] The jump execution steps sort each pending functional module according to the module dependency relationship to obtain the module sequence, and the target fault module is used as the second functional module;

[0145] If the startup time of the first functional module is greater than the startup time of the second functional module, then the first functional module is determined as the target fault module.

[0146] If the startup time of the first functional module is less than the startup time of the second functional module, then the second functional module is identified as the target fault module.

[0147] If the startup time of the first functional module is equal to the startup time of the second functional module, then the first functional module and the second functional module are identified as the target fault modules.

[0148] Optionally, the device further includes:

[0149] The vehicle number recording module is used to record the vehicle number to which the autonomous driving system belongs when the current start time is obtained;

[0150] The log file construction module is used to construct log files using the current startup time and vehicle number.

[0151] The target log file generation module is used to record the initial completion time in the log file when the initialization completion time is obtained, thus obtaining the target log file.

[0152] Optionally, the device further includes:

[0153] The information extraction module is used to extract the vehicle number and module version number corresponding to the target fault module from the target log file after the target fault module is identified.

[0154] The event occurrence time extraction module is used to extract the initialization completion time point corresponding to the target fault module as the event occurrence time point;

[0155] The work order creation and forwarding module is used to create a work order task and forward it to the responsible terminal corresponding to the target fault module using the vehicle number and module version number corresponding to the target fault module, as well as the time of the event.

[0156] Optionally, the device further includes:

[0157] The module update module is used to obtain the update function module carried in the repair completion information when it receives the repair completion information for the target faulty module from the terminal responsible for the repair completion information.

[0158] The system update module is used to replace the target faulty module with an update function module to obtain an updated autonomous driving system.

[0159] The loop module is used to jump to execute the response to the received startup command and obtain the steps at the current startup time point when each functional module is started.

[0160] This invention provides an electronic device, including a memory and a processor. The memory stores a computer program, which, when executed by the processor, causes the processor to perform the steps of monitoring the startup time of an autonomous driving system as described in any embodiment of this invention.

[0161] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, modules, and sub-modules described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0162] In the several embodiments provided by this invention, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0163] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0164] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0165] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for monitoring the startup time of an autonomous driving system, characterized in that, The autonomous driving system includes multiple functional modules, and the method includes: In response to the received startup command, obtain the current startup time point when each of the aforementioned functional modules is started; When each of the aforementioned functional modules completes initialization, the initialization completion time point is obtained respectively; Calculate the difference between the initialization completion time and the current startup time to obtain the startup time; Based on the comparison between the startup time and the preset startup time range, the target fault module is determined from the multiple functional modules; The step of determining the target fault module from among the multiple functional modules based on the comparison result between the startup time and the preset startup time range includes: Compare each startup time with the preset startup time range of each functional module; If a single startup time is not within the corresponding startup time range, then the functional module is identified as the target fault module. If multiple startup times are not within the corresponding startup time range, then the target fault module is determined from the multiple functional modules; The step of determining the target fault module from the multiple functional modules if multiple startup times are not within the corresponding startup time range includes: If multiple startup times are not within the corresponding startup time range, the corresponding functional modules will be designated as pending functional modules. Determine whether there are module dependencies among the various undetermined functional modules; If only the module dependency relationship exists, sort the undetermined functional modules according to the module dependency relationship to obtain a module sequence; Calculate the difference between the startup times of each module in reverse order according to the module sequence to obtain the dependency-free startup time of each undetermined functional module. Select the pending functional module with the longest dependency-free startup time as the target fault module; If none of the aforementioned module dependencies exist, the pending functional module corresponding to the longest startup time is selected as the target fault module.

2. The method according to claim 1, characterized in that, The method further includes: If each startup time is within its corresponding startup time range, then all functional modules are considered to be functioning normally.

3. The method according to claim 1, characterized in that, The method further includes: If some of the module dependencies exist, then select the first functional module with the longest startup time from the undetermined functional modules that do not have the module dependencies. Jump to execute the step of sorting each of the undetermined functional modules according to the module dependency relationship to obtain a module sequence, and take the target fault module as the second functional module; If the startup time of the first functional module is greater than the startup time of the second functional module, then the first functional module is determined as the target fault module. If the startup time of the first functional module is less than the startup time of the second functional module, then the second functional module is determined as the target fault module. If the startup time of the first functional module is equal to the startup time of the second functional module, then the first functional module and the second functional module are identified as target fault modules.

4. The method according to any one of claims 1-3, characterized in that, The method further includes: When the current start time is obtained, the vehicle number to which the autonomous driving system belongs is recorded; A log file is constructed using the current startup time and the vehicle number; When the initialization completion time is obtained, the initialization completion time is recorded in the log file to obtain the target log file.

5. The method according to claim 4, characterized in that, The method further includes: Once the target faulty module is identified, the vehicle number and module version number corresponding to the target faulty module are extracted from the target log file. Extract the initialization completion time point corresponding to the target fault module as the event occurrence time point; Using the vehicle number and module version number corresponding to the target fault module, as well as the time point of the event, a work order task is created and forwarded to the responsible terminal corresponding to the target fault module.

6. The method according to claim 5, characterized in that, The method further includes: When the terminal in charge receives the repair completion information for the target fault module, the update function module carried by the repair completion information is obtained; By replacing the target faulty module with the updated function module, an updated autonomous driving system is obtained. The steps involve jumping to execute the startup command received in the response and obtaining the current startup time point when each of the functional modules is started.

7. A device for monitoring the start-up time of an autonomous driving system, characterized in that, The autonomous driving system includes multiple functional modules, and the device includes: The response module is used to respond to the received startup command and obtain the current startup time point when each of the functional modules is started. The initialization completion time point acquisition module is used to acquire the initialization completion time point when each of the aforementioned functional modules completes initialization. The startup time calculation module is used to calculate the difference between the initialization completion time and the current startup time to obtain the startup time; The target fault module determination module is used to determine the target fault module from among the multiple functional modules based on the comparison result between the startup time and the preset startup time range. The target fault determination module includes: The comparison submodule is used to compare each startup time with the preset startup time range of each functional module. The first determining submodule is used to determine the functional module as the target fault module if there is a single startup time that is not within the corresponding startup time range; The second determining submodule is used to determine the target fault module from the multiple functional modules if there are multiple startup times that are not within the corresponding startup time range; The second determining submodule is specifically used for: If multiple startup times are not within the corresponding startup time range, the corresponding functional modules will be designated as pending functional modules. Determine whether there are module dependencies among the various undetermined functional modules; If only the module dependency relationship exists, sort the undetermined functional modules according to the module dependency relationship to obtain a module sequence; Calculate the difference between the startup times of each module in reverse order according to the module sequence to obtain the dependency-free startup time of each undetermined functional module. Select the pending functional module with the longest dependency-free startup time as the target fault module; If none of the aforementioned module dependencies exist, the pending functional module corresponding to the longest startup time is selected as the target fault module.

8. An electronic device, characterized in that, The system includes a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor causes the processor to perform the steps of the startup time monitoring method for an autonomous driving system as described in any one of claims 1-6.

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