Intelligent cabin test method, device and system for cooperative automatic driving, and storage medium

Abstract

The embodiment of the invention provides an intelligent cabin test method, device and system for collaborative automatic driving, and a storage medium, and relates to the technical field of automatic driving. The method comprises the steps of simulating automatic driving task starting to generate simulation scene data according to a collected offline data set related to automatic driving; controlling the intelligent cockpit to render the simulation scene data according to the corresponding application; synchronizing a user event in the intelligent cabin and the domain controller, and obtaining an abnormal log of the application and corresponding problem scene data in the domain controller; and generating a test report according to the abnormal log and the problem scene data. According to the method, a complex driving scene can be efficiently simulated in a safe and controllable environment, the test safety, the scene authenticity and the execution efficiency are balanced, and the stability verification effect of intelligent cabin application is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent transportation, in particular, to a method, device and system for testing an intelligent cockpit in cooperation with automatic driving, and a storage medium. BACKGROUND

[0002] At present, with the rapid development of automatic driving technology, the application stability of an intelligent cockpit, as a core carrier for human-computer interaction, has become a key element for ensuring driving safety and user experience. In the cooperative working mode of an automatic driving domain controller and an intelligent cockpit, the cockpit application needs to respond to complex driving scenarios (such as path planning, environment perception, event warning, etc.) in real time, and ensure the fluency of interface rendering, data synchronization and user operation. Therefore, how to verify the stability of the intelligent cockpit application under the demand of multi-scene and high concurrency interaction has become a technical problem to be solved in the industry.

[0003] The related art mainly adopts two testing schemes: one is automatic driving full-scene testing based on real vehicle environment, which triggers the interaction logic of the cockpit application through real road driving, and injects random user events (such as touch and swipe) by using a Monkey testing tool; the other is static simulation testing independent of the domain controller, which generates fixed scene data by using a simulation tool to verify the basic functions of the application. The former relies on a real vehicle to perform an automatic driving task in a high-precision map coverage area, and the latter reduces the testing complexity by simplifying the scene.

[0004] In the process of implementing the embodiments of the present disclosure, it is found that at least the following problems exist in the related art:

[0005] Although real vehicle testing can cover real road conditions, random event injection can easily cause vehicle misjudgment, especially in high-risk scenarios such as construction and accidents, which poses a safety hazard. The static testing independent of the real vehicle lacks the real-time decision-making of the domain controller and the multi-sensor data synchronization capability, and it is difficult to reproduce the diversity of dynamic driving scenarios, resulting in insufficient testing coverage. Therefore, using the related art cannot efficiently simulate complex driving scenarios in a safe and controllable environment, so it is difficult to balance testing safety, scene authenticity and execution efficiency, resulting in poor stability verification effect of the intelligent cockpit application. SUMMARY

[0006] The embodiments of the present application provide a method, device and system for testing an intelligent cockpit in cooperation with automatic driving, and a storage medium.

[0007] In a first aspect, the embodiments of the present application provide a method for testing an intelligent cockpit in cooperation with automatic driving, comprising:

[0008] The domain controller generates simulated scene data by simulating an automatic driving task according to the collected offline data set related to automatic driving;

[0009] The intelligent cockpit renders the simulation scenario data according to the corresponding application;

[0010] The intelligent cockpit and the domain controller synchronize user events, and obtain abnormal logs of the application and corresponding problem scenario data in the domain controller;

[0011] According to the abnormal logs and the problem scenario data, a test report is generated.

[0012] In an optional embodiment of the present application, the domain controller generates simulation scenario data according to the collected offline data set related to automatic driving to start simulation, including:

[0013] The offline data set related to automatic driving is collected;

[0014] The interface of the domain controller is called through an automated script, and the offline data set is loaded in the domain controller;

[0015] The domain controller parses the offline data set to generate simulation sensor signals and automatic driving decision instructions.

[0016] In an optional embodiment of the present application, the intelligent cockpit renders the simulation scenario data according to the corresponding application, including:

[0017] The domain controller sends the simulation scenario data to the intelligent cockpit;

[0018] The application of the intelligent cockpit updates the map interface, the ego vehicle trajectory and / or the event warning information based on the received scenario data.

[0019] In an optional embodiment of the present application, the intelligent cockpit and the domain controller synchronize user events, including:

[0020] Random user events are generated in the intelligent cockpit using a Monkey tool, and preset user events are inserted through a Python script;

[0021] The intelligent cockpit synchronizes the random user events and the preset user events to the domain controller through a communication link.

[0022] In an optional embodiment of the present application, the abnormal logs of the application and the corresponding problem scenario data in the domain controller are obtained, including:

[0023] During the running of the application in the intelligent cockpit, application abnormal data is collected; wherein the application abnormal data includes ANR logs, Crash stack information and / or memory leak records;

[0024] According to the time stamp of the abnormal data, the problem scenario data is determined.

[0025] In an optional embodiment of the present application, the problem scenario data is determined according to the timestamp of the abnormal data, including:

[0026] According to the timestamp in the abnormal data and the timestamp of the simulation scenario data, the abnormal data is time-aligned with the corresponding simulation scenario data;

[0027] According to the time alignment result, a corresponding relationship between the abnormal data and the simulation scenario data is established, and the problem scenario data matching the abnormal data is screened out.

[0028] In an optional embodiment of the present application, a test report is generated according to the abnormal log and the problem scenario data, including:

[0029] A problem scenario description is generated according to the problem scenario data; and / or, the application log and the performance data of the domain controller are time-aligned according to the timestamp, a performance trend chart is generated, and an abnormal point is marked on the performance trend chart according to the timestamp of the abnormal log;

[0030] A test report is generated, the test report including the abnormal data and / or the performance trend chart and / or the problem scenario description; wherein the abnormal data includes the abnormal log and the corresponding problem scenario data.

[0031] A second aspect of an embodiment of the present application provides a smart cockpit testing device cooperating with automatic driving, including a processor and a memory storing program instructions, the processor being configured to execute the smart cockpit testing method cooperating with automatic driving of the first aspect of the present application when running the program instructions.

[0032] A third aspect of an embodiment of the present application provides a system, including:

[0033] A system body; and,

[0034] The smart cockpit testing device cooperating with automatic driving of the second aspect of the present application is installed in the system body.

[0035] A fourth aspect of an embodiment of the present application provides a computer readable storage medium storing program instructions, the program instructions being used to make a computer execute the method for traffic control of the first aspect of the present application when running.

[0036] The smart cockpit testing method and device, system and storage medium provided in the present application have the following beneficial effects:

[0037] The embodiment of the application controls the domain controller to simulate an automatic driving task to generate simulation scene data according to the collected offline data set related to automatic driving, controls the intelligent cockpit to render the simulation scene data according to the corresponding application, synchronizes the user event of the intelligent cockpit and the domain controller, obtains the abnormal log of the application and the corresponding problem scene data in the domain controller, and finally generates a test report according to the abnormal log and the problem scene data, so that the complex driving scene can be simulated efficiently in a safe and controllable environment, the test safety, scene authenticity and execution efficiency are balanced, and the stability verification effect of the intelligent cockpit application is improved. BRIEF DESCRIPTION OF DRAWINGS

[0038] The accompanying drawings, which are included to provide a further understanding of the application, constitute a part of the application and serve to explain the application together with the specification, but do not limit the application in any way. In the drawings:

[0039] Figure 1 is a schematic diagram of a smart cockpit test method for cooperative automatic driving provided by an embodiment of the application;

[0040] Figure 2 is a schematic diagram of another smart cockpit test method for cooperative automatic driving provided by an embodiment of the application;

[0041] Figure 3 is a schematic diagram of a smart cockpit test device for cooperative automatic driving provided by an embodiment of the application.

[0042] Reference signs:

[0043] 800: a smart cockpit test device for cooperative automatic driving; 801: a processor; 802: a memory; 803: a communication interface; and 804: a bus. DETAILED DESCRIPTION

[0044] In order to make the technical solutions and advantages in the embodiments of the application clearer, the exemplary embodiments of the application will be further described in detail below with reference to the drawings. Obviously, the described embodiments are only a part of the embodiments of the application, rather than all the embodiments. It should be noted that the embodiments in the application and the features in the embodiments can be combined with each other without conflict.

[0045] The embodiment of the application provides a system, which comprises a domain controller module, an intelligent cockpit module, a user event synchronization module, a data acquisition and analysis module and a test report generation module. The domain controller module is configured to load an offline data set related to automatic driving, analyze and generate simulation scene data, including simulation sensor signals and automatic driving decision instructions. The intelligent cockpit module is in communication connection with the domain controller module and is configured to receive the simulation scene data and render a map interface, a self-vehicle trajectory and event warning information in real time through a vehicle-mounted application. The user event synchronization module is configured to generate random user events and preset user events in the intelligent cockpit module and synchronize the events to the domain controller module through a communication link to trigger dynamic scene interaction. The data acquisition and analysis module is configured to acquire abnormal logs (including ANR logs, crash stack information and memory leakage records) generated in the process of running of the intelligent cockpit module and extract problem scene data in the domain controller module matched with the time stamps of the abnormal logs. The test report generation module is configured to associate the abnormal logs with the problem scene data and generate a test report containing problem scene description, performance trend chart and abnormal annotation. The system further comprises a processor in electrical connection with the modules and used for controlling the modules to perform the above actions.

[0046] In actual application, the domain controller module generates dynamic driving scenes (such as high-precision maps, V2X events and multi-vehicle interaction) based on the offline data set, the intelligent cockpit module synchronously renders an interface and responds to user events, forming a virtual test environment independent of a real vehicle. The user event synchronization module mixes event streams (random operations and preset logic) through a Monkey tool and script injection, ensuring consistency of interaction timing of the intelligent cockpit and the domain controller. The data acquisition and analysis module matches abnormal logs with scene data through time stamps, directly mapping problems such as crashes and lag to triggering scenes and code modules, realizing accurate root cause analysis. The whole process from scene loading, event injection to report generation is controlled by scripts, supporting offline data set loop playback and expansion, which can significantly improve test efficiency and scene coverage.

[0047] Figure 1 FIG. 1 is a schematic diagram of a method for testing an intelligent cockpit cooperating with automatic driving provided by the embodiment of the application, and any one of the following methods can be executed in the system or a server or a terminal device in communication connection with the system.

[0048] Based on the structure of the above system, as shown in FIG. 1, the embodiment of the application provides a method for testing an intelligent cockpit cooperating with automatic driving, comprising the following steps. Figure 1

[0049] S11, controlling the domain controller to generate simulation scene data according to the collected offline data set related to automatic driving.

[0050] ​S12, the intelligent cockpit renders the simulation scene data according to the corresponding application.

[0051] S13, the intelligent cockpit and the domain controller synchronize user events, and obtain abnormal logs of the application and corresponding problem scene data in the domain controller.

[0052] S14, a test report is generated according to the abnormal logs and the problem scene data.

[0053] In the embodiments of the present disclosure, the offline data set is various driving-related data collected in advance, including high-precision map data, sensor data, V2X event data, traffic condition data and / or vehicle trajectory data. The high-precision map data includes road shape, lane line, traffic sign, signal light, etc. The sensor data is from various sensors of the vehicle, such as three-dimensional information of the surrounding environment provided by the laser radar, the position and speed of other vehicles and obstacles perceived by the millimeter wave radar, lane lines, traffic signs and signal lights recognized by the camera, and high-precision positioning of RTK data. The V2X event data is the communication data between vehicles and infrastructure, including road construction reminders, accident reminders, bus stop reminders, etc. The vehicle trajectory data is the trajectory of the vehicle during driving, including speed, acceleration, driving direction, etc. The traffic condition data is real-time traffic condition information such as traffic flow and congestion. The system can record bag data through the ROS (Robot Operating System) system and perform disk writing. The bag file is a file format used to store time series data in ROS. Various sensor data, control instructions, etc. of the system during running can be recorded, which is convenient for subsequent offline analysis and playback. During the recording process, the rosbag tool stores the received data in the memory buffer according to the timestamp order. When the buffer is full, the data is written into the bag file on the disk.

[0054] By using the intelligent cockpit test method for cooperative automatic driving provided in the embodiments of the present application, the domain controller generates dynamic simulation scene data based on the offline data set, and synchronously controls the intelligent cockpit to render the scene and user events, so that diversified driving scenes can be reproduced in a safe workstation independent of the real vehicle environment, and the safety hazards caused by random event injection in real vehicle testing can be completely avoided. At the same time, by synchronously obtaining the abnormal logs of the intelligent cockpit application and the corresponding problem scene data of the domain controller, the association between the abnormality and the scene can be directly established, the specific scene and the interaction logic triggering the abnormality can be quickly located, and the problem analysis efficiency is improved. In addition, the scalability and the loop playback capability of the offline data set, combined with the dynamic synchronization mechanism of the simulation scene and the user events, effectively solve the core defects of the single test scene and the insufficient coverage in the prior art, and provide an efficient and safe closed-loop test scheme for the cooperative stability verification of the intelligent cockpit and the automatic driving system. Therefore, by using the scheme of the embodiments of the present application, complex driving scenes can be efficiently simulated in a safe and controllable environment, the test safety, the scene authenticity and the execution efficiency are balanced, and the stability verification effect of the intelligent cockpit application is improved.

[0055] Optionally, the control domain controller simulates the automatic driving task to generate simulation scene data according to the collected offline data set related to automatic driving, including: collecting the offline data set related to automatic driving; calling the interface of the domain controller through an automated script to load the offline data set in the domain controller; controlling the domain controller to parse the offline data set to generate simulation sensor signals and automatic driving decision instructions.

[0056] In the embodiments of the present disclosure, a Python automation script can be written to call the HTTP interface of the domain controller and simulate login requests under different business modes. By sending HTTP requests containing different business mode parameters to the interface, the simulation login function is realized. For example, a POST request can be sent using the requests library, and the business mode parameters are carried in the request body, such as business_mode="mode1" and the like. The response data returned by the HTTP interface is parsed to obtain the task route information. The response data usually contains detailed information of the task route, such as the starting point, the ending point, the passing point, the road type and the like. By parsing these data, the key information of the task route is extracted to prepare for the subsequent scene data playback. After the task starts, the connection between the Android application device and the domain controller is established through the Python script. Socket communication or other suitable communication methods can be used to establish a data transmission channel between the device and the domain controller. The collected data set is started to be played back in a loop. The bag data file recorded and saved by the ROS system contains various sensor data, map information and V2X events, etc. After the Android application device and the domain controller are successfully connected, the script reads the bag data file and sends it to the domain controller. After the domain controller receives the data, it parses and generates simulation scene data for the intelligent cockpit application to render and process. During the running of the intelligent cockpit application, user events are synchronized and abnormal situations of the application are monitored. Random user events can be generated using the Monkey tool, and preset user events can be inserted through the Python script to simulate real user operations. At the same time, the user events are synchronized to the domain controller through the communication link to ensure that the domain controller can timely process these events and generate corresponding simulation scene data. During the test, abnormal data of the application, such as ANR logs, Crash stack information and memory leak records, etc. are collected, and the problem scene data is determined according to the time stamp of the abnormal data to generate a detailed test report.

[0057] In this way, by collecting offline datasets related to autonomous driving (such as high-precision maps, multi-sensor signals, and V2X event data), and using automated script calls to load data from the domain controller interface, real driving scene historical data can be directly reused without relying on real vehicle environments, avoiding the costs and safety risks of repeated real vehicle collection. Further, by analyzing offline datasets using the domain controller to generate simulated sensor signals and autonomous driving decision instructions, multi-source data interaction logic in complex driving scenarios (such as sudden accidents and road construction) can be dynamically reproduced, addressing the single-scene and dynamic decision-making deficiencies of static simulation testing. At the same time, the introduction of automated scripts ensures standardized execution of data loading and analysis, reducing process deviations caused by human intervention and improving testing efficiency and scenario coverage. Through precise playback and automated processing of offline data, a highly realistic virtual testing environment is constructed in the safety workstation, providing an efficient and controllable technical foundation for the collaborative verification of intelligent cockpits and autonomous driving systems.

[0058] Optionally, the control intelligent cockpit renders simulation scene data according to the corresponding application, including: controlling the domain controller to send simulation scene data to the intelligent cockpit; controlling the application of the intelligent cockpit to update the map interface, the ego vehicle trajectory, and / or the event warning information based on the received simulation scene data.

[0059] In this way, by controlling the domain controller to send simulation scene data to the intelligent cockpit and driving the intelligent cockpit application to update the map interface, ego vehicle trajectory, and event warning information in real time, the dynamic scene of the intelligent cockpit interface and the autonomous driving system can be highly synchronized, solving the problem of disconnection between interface rendering and domain controller decision data in traditional testing. Based on the precise simulation data generated by the domain controller, the intelligent cockpit can dynamically adjust the interface elements and event prompt logic, thereby reproducing the interaction complexity of real driving scenarios in a virtual environment, improving the authenticity and coverage of testing. At the same time, through the real-time rendering mechanism driven by data, the intelligent cockpit application can quickly respond to user events and scene changes, exposing potential problems such as interface lag and rendering delay, and providing a high-fidelity interactive environment for stability verification.

[0060] Optionally, the intelligent cockpit and the domain controller synchronize user events, including: generating random user events in the intelligent cockpit using the Monkey tool, and inserting preset user events through a Python script; controlling the intelligent cockpit to synchronize the random user events and the preset user events to the domain controller through a communication link.

[0061] In the embodiments of the present disclosure, first, the Monkey tool is used to continuously run on the intelligent cockpit device to generate a series of random user events. These events include but are not limited to sliding button operations, frequent switching between different tab pages in an application, operation simulation of fault type work order reporting, sliding operation of a map interface, frequent switching between 2D and 3D map views, and switching operation of different perspectives, etc. At the same time, in order to more realistically simulate the operation habits of users in the actual driving process, specific script logic can be used to insert background switching events into the random event stream generated by the Monkey tool according to a preset proportion, so that the intelligent cockpit application can remain stable in the multi-application switching scenario. In addition, the comprehensiveness and authenticity of the test are further improved in combination with the multi-application switching scenario. During the test, the intelligent cockpit application not only needs to handle random events from the Monkey tool, but also needs to cope with switching operations with other applications, which simulates various operations that users may perform during driving, such as switching between navigation applications and multimedia applications, etc.

[0062] In this way, the Monkey tool can generate events such as random touches, swipes, and button presses similar to real users, and the Python script can flexibly insert specific preset events according to test requirements, such as simulating specific driving scenario switching, fault reporting, etc. Therefore, by using the Monkey tool to generate random user events and inserting preset user events through the Python script in the intelligent cockpit, a variety of user operation scenarios can be simulated, making the entire test process more close to the complex situation in actual use. By controlling the intelligent cockpit to synchronize these random and preset user events to the domain controller through the communication link, the interaction timing consistency between the intelligent cockpit and the domain controller is achieved, ensuring that the domain controller can timely receive user events and make corresponding responses, thereby completing the interaction and verification of dynamic scenarios. The synchronization mechanism enables the interaction logic between the intelligent cockpit and the domain controller to be completely reproduced in the test environment independent of the real vehicle, making the test more realistic and comprehensive.

[0063] Based on the structure of the above system, as shown in Figure 2 The embodiments of the present disclosure provide a method for testing an intelligent cockpit in cooperation with automatic driving, comprising:

[0064] S11, controlling the domain controller to simulate an automatic driving task to generate simulation scene data according to the collected offline data set related to automatic driving.

[0065] S12, controlling the intelligent cockpit to render the simulation scene data according to the corresponding application.

[0066] S21, synchronizing user events between the intelligent cockpit and the domain controller, and collecting application exception data in the running process of the intelligent cockpit application; wherein the application exception data includes ANR log, Crash stack information and / or memory leakage record; determining problem scenario data according to the time stamp of the exception data.

[0067] S14, generating a test report according to the exception log and the problem scenario data.

[0068] The intelligent cockpit test method for cooperative automatic driving provided by the embodiment of the application, the ANR (application non-response) log, the Crash (crash) stack information and the memory leakage record and other exception data directly reflect the error state and system resource management problem of the application in the running time, therefore, by collecting the application exception data, the stability problem of the application that may occur in various complex scenarios can be comprehensively captured. According to the matching of the time stamp of the exception data and the time stamp of the simulation scenario data, the exception event can be accurately mapped to the corresponding simulation scenario, the corresponding relationship between the exception data and the problem scenario data is established, and the accurate positioning of the exception triggering scenario is realized.

[0069] Optionally, determining the problem scenario data according to the time stamp of the exception data includes: time aligning the exception data and the corresponding simulation scenario data according to the time stamp in the exception data and the time stamp of the simulation scenario data; establishing the corresponding relationship between the exception data and the simulation scenario data according to the time alignment result, and screening out the problem scenario data matched with the exception data.

[0070] In this way, in the intelligent cockpit application stability test process, the collected exception data contains the time stamp information, and the simulation scenario data is also recorded based on time sequence. By aligning the time stamp of the exception data and the time stamp of the simulation scenario data, the corresponding relationship between the two can be accurately established, so that the problem scenario data matched with the exception data can be accurately screened out. Through the time alignment technology, the system can match the specific time of the exception occurrence with the corresponding simulation scenario data, so as to determine the specific scenario of the intelligent cockpit when the exception occurs.

[0071] Optionally, generating a test report according to the exception log and the problem scenario data includes: generating a problem scenario description according to the problem scenario data; and / or, aligning the application log and the performance data of the domain controller according to the time stamp, generating a performance trend chart, and marking the exception point on the performance trend chart according to the time stamp of the exception log; generating a test report, the test report including the exception data and / or the performance trend chart and / or the problem scenario description; wherein the exception data includes the exception log and the corresponding problem scenario data.

[0072] In this way, the problem scenario data is generated to describe the abnormal occurrence scene, and the application log and the domain controller performance data are aligned according to the timestamp, a performance trend chart is generated, and an abnormal point is marked, so that the developer can quickly locate the problem source. The generated test report contains abnormal data, a performance trend chart and problem scenario description, which can provide comprehensive information for the developer, accelerate problem repair and ensure the stability of the intelligent cockpit application. Thus, the professional degree and reliability of the test process can be improved, and the development of the intelligent cockpit technology can be promoted.

[0073] In combination Figure 3 As shown in the accompanying drawings, the embodiment of the present application provides a kind of intelligent cockpit testing device 800 coordinated with automatic driving, including processor (processor) 801 and memory (memory) 802. Optionally, the device can also include communication interface (Communication Interface) 803 and bus 804. Wherein, processor 801, communication interface 803, memory 802 can complete mutual communication by bus 804. Communication interface 803 can be used for information transmission. Processor 801 can call the logic instruction in memory 802, to execute the intelligent cockpit testing method coordinated with automatic driving of above-mentioned embodiment.

[0074] In addition, the logic instruction in the above-mentioned memory 802 can be realized in the form of software function unit and sold or used as an independent product when, can be stored in a computer readable storage medium.

[0075] Memory 802 as a kind of computer readable storage medium, it can be used to store software program, computer executable program, such as the program instruction / module corresponding to the method in the embodiment of the present application. Processor 801 by running the program instruction / module stored in memory 802, thus executes functional application and data processing, i.e. realizes the intelligent cockpit testing method coordinated with automatic driving in above-mentioned embodiment.

[0076] Memory 802 can include storage program area and storage data area, wherein, storage program area can store operating system, at least one application required by functional application;Storage data area can store data created according to the use of terminal equipment and the like. In addition, memory 802 can include high-speed random access memory, and can also include nonvolatile memory.

[0077] The embodiment of the present application provides a system, comprising: a system body, and the cooperative automatic driving intelligent cockpit testing device 800. The cooperative automatic driving intelligent cockpit testing device 800 is installed in the system body. The installation relationship described herein is not limited to being placed in the system, and also includes installation connection with other components of the system, including but not limited to physical connection, electrical connection or signal transmission connection and the like. Those skilled in the art can understand that the cooperative automatic driving intelligent cockpit testing device 800 can be adapted to a feasible system body, and thus realize other feasible embodiments.

[0078] The embodiment of the present application provides a computer readable storage medium, which stores computer executable instructions, and the computer executable instructions are configured to execute the cooperative automatic driving intelligent cockpit testing method.

[0079] The technical scheme of the embodiment of the present application can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes one or more instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in the embodiment of the present application. The aforementioned storage medium can be a non-transitory storage medium, including a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0080] The technical scheme of the embodiment of the present application can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes one or more instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute all or part of the steps of the method described in the embodiment of the present application. The aforementioned storage medium can be a non-transitory storage medium, including a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0081] The above description and drawings are illustrative of embodiments of the application and are not to be construed as limiting the application. Other embodiments can include structural, logical, electrical, process, and other changes. The embodiments are merely examples of the many possible embodiments of the application. Unless explicitly stated otherwise, individual components and functions are optional and the order of operations can vary. Parts and features of some embodiments can be included or replaced in or by parts and features of other embodiments. Also, the phraseology and terminology used herein is for the purpose of description and should not be regarded as limiting. As used in the description of the embodiments and the claims, the article "a" is intended to include one or more articles, by use of "a" or "an," it is intended to include one or more embodiments. Also, as used in the description of the embodiments and the claims, the term "including" and variations thereof, means that existence of the features, integers, steps, operations, elements, and / or components noted are an option, and that not all of them are required, but that some embodiments can include, but not require, several of those specialties features, integers, steps, operations, elements, components, and / or combinations thereof. The phraseology and terminology used by present disclosure are not limited to any particular embodiment. Any use of "one embodiment," "an embodiment," "one example," "a / an example," and the like is intended to mean that a particular feature, structure, characteristic, and so on was included in at least one embodiment of the present disclosure and can include, but is not limited to, this or similar feature, structure, characteristic in other embodiments. Notably, such phrasing is not intended to imply that future implementations are only possible, for example, with one of the described examples. Any use of "exemplary" is intended to indicate that an example, or a feature of an example, is used to illustrate a particular implementation. Thus, if it is stated that an "exemplary embodiment" or "exemplary example" includes a particular feature, then it is intended that at least one embodiment of the present disclosure includes the particular feature, and it is also intended that other embodiments of the present disclosure can include the particular feature.

[0082] Those skilled in the art can understand that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods for each specific application to realize the described functions, but such implementation should not be considered beyond the scope of the embodiments of the present application. The skilled person can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described systems, devices and units can refer to the corresponding processes in the foregoing method embodiments, which will not be described here.

[0083] The methods and products (including but not limited to devices and equipment) disclosed in the embodiments herein can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units may be merely 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. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms. 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 implement this embodiment according to actual needs. In addition, the functional units in the embodiments of this application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0084] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description; sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A test method for a smart cockpit cooperating with automatic driving, characterized in that, The method comprises the following steps: The domain controller generates simulation scenario data according to the collected offline data set related to automatic driving; The intelligent cockpit renders the simulation scenario data according to the corresponding application; The user events are synchronized between the intelligent cockpit and the domain controller, and the abnormal logs of the application and the corresponding problem scenario data in the domain controller are obtained; A test report is generated according to the abnormal logs and the problem scenario data.

2. The method of claim 1, wherein, The domain controller generates simulation scenario data according to the collected offline data set related to automatic driving, comprising: Collecting the offline data set related to automatic driving; Calling the interface of the domain controller through an automated script to load the offline data set in the domain controller; The domain controller parses the offline data set to generate simulation sensor signals and automatic driving decision instructions.

3. The method of claim 1, wherein, The intelligent cockpit renders the simulation scenario data according to the corresponding application, comprising: The domain controller sends the simulation scenario data to the intelligent cockpit; The application of the intelligent cockpit updates the map interface, the trajectory of the ego vehicle, and / or the event warning information based on the received simulation scenario data.

4. The method of claim 1, wherein, The user events are synchronized between the intelligent cockpit and the domain controller, comprising: Random user events are generated in the intelligent cockpit using the Monkey tool, and preset user events are inserted through a Python script; The intelligent cockpit synchronizes the random user events and the preset user events to the domain controller through a communication link.

5. The method of claim 1, wherein, The abnormal logs of the application and the corresponding problem scenario data in the domain controller are obtained, comprising: During the running of the application in the intelligent cockpit, application exception data is collected; wherein the application exception data includes ANR logs, Crash stack information, and / or memory leak records; The problem scenario data is determined according to the timestamp of the exception data.

6. The method of claim 5, wherein, The problem scenario data is determined according to the timestamp of the exception data, comprising: According to the timestamp in the exception data and the timestamp of the simulation scenario data, the exception data and the corresponding simulation scenario data are time-aligned; According to the time alignment result, the corresponding relationship between the exception data and the simulation scenario data is established, and the problem scenario data matching the exception data is screened out.

7. The method according to any one of claims 1 to 6, characterized in that, The test report is generated according to the abnormal logs and the problem scenario data, comprising: Problem scenario descriptions are generated according to the problem scenario data; and / or, the application logs and the performance data of the domain controller are time-aligned according to the timestamp, a performance trend chart is generated, and an abnormal point is marked on the performance trend chart according to the timestamp of the abnormal logs; The test report includes the exception data and / or the performance trend chart and / or the problem scenario description; wherein the exception data includes the abnormal logs and the corresponding problem scenario data.

8. A cooperative automatic driving intelligent cockpit testing device, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to execute the intelligent cockpit testing method for automatic driving collaboration when the program instructions are running.

9. A system, characterized by The method comprises the following steps: The system body; The intelligent cockpit testing device for automatic driving collaboration as claimed in claim 8 is installed in the system body.

10. A computer readable storage medium storing program instructions, wherein the program instructions comprise instructions for causing a computer to perform the method of any one of claims 1-9. The program instructions are used to make the computer execute the intelligent cockpit testing method for automatic driving collaboration when the program instructions are running.

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