Redundancy fusion unmanned driving domain control method and controller

Abstract

The invention relates to a redundancy fusion unmanned driving domain control method and a controller, and relates to the technical field of unmanned driving control, and the method comprises the steps that a domain control system is powered and started, and the domain control system comprises an SOC system and an MCU system; when the SOC system is started to control the vehicle to run, indicating the MUC system and the SOC system to perform data communication and sending a preset self-checking protocol signal to the SOC system; self-inspection is carried out to determine whether the SOC system is abnormal or not, and if yes, the MUC system is indicated to take over vehicle control; instructing the MUC system to communicate with a preset 5G-V2X module so as to collect fault information of the domain control system and a vehicle position and upload the fault information and the vehicle position to a preset storage terminal; analyzing according to the domain control system fault information to determine a system fault type, and matching a corresponding fault removal mode; and planning a maintenance path according to the vehicle position, and sending an on-site maintenance prompt. According to the invention, after the main intelligent system of the unmanned vehicle fails, other secondary systems can be kept controllable.

Description

Technical Field

[0001] The present application relates to the field of unmanned driving control technology, and in particular to a redundant fusion unmanned driving domain control method and controller. Background Art

[0002] With the development of intelligent driving technology, driverless vehicles are gradually entering people's lives, such as driverless delivery vehicles, driverless street sweepers, etc. These vehicles are gradually driving from closed parks to public roads, which puts higher requirements on the stability of the driverless driving system.

[0003] In related technologies, unmanned driving systems are composed of multiple functional domain systems, including intelligent control systems, high-precision positioning systems, communication systems, gateway systems and other high-level intelligent driving systems, which control all aspects of unmanned driving. However, in current unmanned driving systems, most control systems are in the industrial field, and electronic products in different functional domains are interconnected by cables, and cannot perform downgraded functions.

[0004] Regarding the above-mentioned related technologies, when the main control system fails, the functions of the remaining interconnected systems fail, which is not conducive to improving the controllability of the unmanned vehicle. Summary of the invention

[0005] In order to ensure that the remaining secondary systems of an unmanned vehicle can remain controllable after the main intelligent system of the unmanned vehicle fails, the present application provides a redundant fusion unmanned driving domain control method.

[0006] In the first aspect, the present application provides a redundant fusion unmanned driving domain control method, which adopts the following technical solution:

[0007] A redundant fusion unmanned driving domain control method, comprising:

[0008] Step 1, powering on and starting a domain control system integrating multiple functions, wherein the domain control system includes a primary SOC system and a secondary MCU system;

[0009] Step 2: When the SOC system starts to control the vehicle's driving, the MUC system is instructed to communicate data with the SOC system and a preset self-test protocol signal is sent to the SOC system;

[0010] Step 3, performing a self-check according to the self-check protocol signal to determine whether the SOC system is abnormal, and if so, instructing the MUC system to take over vehicle control;

[0011] Step 4: Instruct the MUC system to communicate with the preset 5G-V2X module to collect domain control system fault information and vehicle location and upload them to the preset storage terminal;

[0012] Step 5: Analyze the fault information of the domain control system to determine the system fault type, and match the fault elimination method corresponding to the system fault type;

[0013] Step 6: Plan a maintenance route based on the vehicle location using a preset planning method and issue an on-site maintenance reminder.

[0014] By adopting the above technical solution, when the SOC system responsible for handling driving control in the domain control system fails, the secondary MUC system is instructed to take over the control of the vehicle, so that other systems except the system that caused the fault can remain controllable, thereby facilitating the analysis of the location and fault information of the unmanned vehicle, and planning of maintenance routes and search for troubleshooting methods, so that relevant personnel can quickly reach the location of the faulty vehicle during on-site troubleshooting.

[0015] Optionally, sending a preset self-test protocol signal to the SOC system includes:

[0016] Collecting power supply parameters of the SOC system of the unmanned vehicle, wherein the power supply parameters include power supply voltage and power supply temperature;

[0017] Calculating according to the power supply voltage, the power supply temperature and a preset weight value calculation method to determine the voltage weight value and the temperature weight value;

[0018] If the voltage weight value is greater than the temperature weight value, the voltage self-test protocol data is determined according to the voltage weight value match;

[0019] If the temperature weight value is greater than the voltage weight value, the corresponding temperature self-test protocol data is matched according to the temperature weight value;

[0020] The voltage self-test protocol data or the temperature self-test protocol data is marked, and a self-test protocol signal is sent.

[0021] By adopting the above technical solution, the power supply parameters of the SOC system of the unmanned vehicle are analyzed, so as to calculate the voltage weight value and temperature weight value that affect the stable operation of the SOC system, and conduct comparative analysis to understand the current factors affecting the power supply stability of the SOC system, and match the corresponding self-test protocol data to perform self-test on the SOC system to improve the detection reliability of the self-test protocol data.

[0022] Optionally, when the power supply voltage, the power supply temperature and the preset weight value calculation method are calculated, the following formula is used for calculation:

[0023]

[0024] Among them, Q u Represents the voltage weight value, Δx tIt represents the rate of change of the power supply voltage value per unit time of duration t, δ represents the reference voltage weight coefficient, Δy t It represents the rate of change of the power supply temperature value per unit time of duration t, and γ represents the reference temperature weight coefficient.

[0025] By adopting the above technical solution, based on the change rate of the power supply voltage and the power supply temperature in unit time, it can be known whether the power supply voltage and the power supply temperature have undergone drastic changes in unit time, and the corresponding self-test protocol data can be matched according to the corresponding weight value, so that the self-test protocol data used in different temperature change or voltage change states can better meet the detection needs.

[0026] Optionally, the collection of domain control system fault information includes:

[0027] Collect and analyze the operating status of the control system to determine the abnormal system function of the faulty system;

[0028] If the abnormal system function belongs to the preset irreplaceable system function type, the faulty system will be marked and a fault type analysis prompt will be issued;

[0029] If the abnormal system function belongs to the replaceable system function type, the corresponding backup system in the preset expansion system is matched;

[0030] Instructs the domain control system and standby system to connect and issue troubleshooting prompts.

[0031] By adopting the above technical solution, the domain control system fault information is analyzed to find out whether the specific system that caused the fault in the integrated domain control system has a replacement system, so as to enable the backup system to replace it, so that the unmanned vehicle can automatically eliminate the fault and maintain normal operation.

[0032] Optionally, the preset planning method includes:

[0033] Analyze the preset moving path and vehicle position of the unmanned vehicle when it is working to determine the minimum moving path with the shortest path;

[0034] Collect and analyze panoramic images of the process of the unmanned vehicle moving along a preset moving path to the vehicle position to determine path obstacle parameters;

[0035] The path obstacle parameters are compared with the minimum moving path to determine the maintenance path that avoids the obstacles corresponding to the path obstacle parameters on the minimum moving path.

[0036] By adopting the above technical solution,

[0037] Optionally, when determining the maintenance path for avoiding the obstacle corresponding to the path obstacle parameter on the minimum moving path, it also includes:

[0038] Instruct the preset 5G-V2X module to collect traffic information on the minimum moving path according to a preset period;

[0039] Analyze traffic information based on road conditions to determine the location of traffic obstacles;

[0040] Compare and analyze the location of traffic obstacles and the minimum moving path to determine the temporary adjustment path and issue a temporary adjustment prompt;

[0041] adjusting the minimum moving path based on the temporary adjustment prompt and the temporary adjustment path;

[0042] The adjusted minimum moving path is updated as the maintenance path, and the temporary adjustment prompt is obtained again.

[0043] By adopting the above technical solution, after the maintenance path is determined, the traffic information on the minimum moving path is analyzed, and the minimum moving path is adjusted according to the analysis of the location of the traffic obstacles where the obstacles exist, thereby forming a new maintenance path, so that the maintenance path can avoid the areas where obstacles exist in time.

[0044] Optionally, determining the location of traffic obstructions includes:

[0045] Collect regional images of traffic obstacle locations for analysis to determine the status of traffic obstacles;

[0046] Analyze whether the traffic obstacle status is consistent with the preset obstacle clearing status within the preset preparation time range;

[0047] If they are consistent, the mark of the traffic obstacle location will be cancelled;

[0048] If there is any inconsistency, the location of the traffic obstacle will be marked and a temporary route adjustment prompt will be issued.

[0049] By adopting the above technical solution, the status of the traffic obstacle location is analyzed, so that the traffic obstacle status is detected within the preset preparation time. When the traffic obstacle at the traffic obstacle location is cleared, the traffic obstacle location is unmarked to reduce the work of re-planning the maintenance path, which helps to improve the reliability of maintenance path planning.

[0050] In the second aspect, the present application provides a redundant fusion unmanned driving domain controller, which adopts the following technical solution:

[0051] A redundant fusion unmanned driving domain controller, comprising:

[0052] The domain control module integrates multiple control systems and performs driving control, including the main SOC system and the secondary MCU system;

[0053] Self-check analysis module, when the SOC system starts to control the vehicle driving, instructs the MUC system to communicate data with the SOC system and sends a preset self-check protocol signal to the SOC system;

[0054] Perform self-check according to the self-check protocol signal to determine whether the SOC system is abnormal, and if so, instruct the MUC system to take over vehicle control;

[0055] The maintenance interaction module instructs the MUC system to communicate with the preset 5G-V2X module to collect domain control system fault information and vehicle location and upload them to the preset storage terminal;

[0056] Analyze the fault information of the domain control system to determine the system fault type and match the fault elimination method corresponding to the system fault type;

[0057] Plan the maintenance route according to the vehicle location using a preset planning method and issue on-site maintenance reminders;

[0058] A memory for storing a program of any one of the redundant fusion unmanned driving domain controllers;

[0059] The program in the processor and the memory can be loaded and executed by the processor to realize any redundant fusion unmanned driving domain controller.

[0060] By adopting the above technical solution, when the SOC system fails, the MUC system takes over the control, so that when the integrated domain control system partially fails, the remaining systems that have not failed can maintain normal operation, so that the vehicle can collect fault information and provide convenience for fault inspection and repair.

[0061] In summary, the present application includes at least one of the following beneficial technical effects:

[0062] 1. When the SOC system responsible for handling driving control in the domain control system fails, the secondary MUC system is instructed to take over the control of the vehicle, so that other systems except the fault can remain controllable, which is convenient for analyzing the location and fault information of the unmanned vehicle, planning the maintenance path and finding the troubleshooting method, so that when performing on-site troubleshooting, relevant personnel can quickly reach the location of the faulty vehicle;

[0063] 2. Analyze the power supply parameters of the SOC system of the unmanned vehicle, so as to calculate the voltage weight value and temperature weight value that affect the stable operation of the SOC system, and conduct comparative analysis to understand the current factors affecting the power supply stability of the SOC system, and match the corresponding self-test protocol data to perform self-test on the SOC system to improve the detection reliability of the self-test protocol data;

[0064] 3. After analyzing the panoramic image on the minimum moving path to obtain the obstacle parameters, avoidance analysis is performed to plan a maintenance path that can avoid obstacles, so that when performing on-site maintenance, the vehicle can drive according to the maintenance path and avoid the obstacle section on the minimum moving path, thereby improving the overall maintenance efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 It is a method flow chart of steps S100 to S105 in this application.

[0066] Figure 2 It is a method flow chart of steps S200 to S204 in this application.

[0067] Figure 3 It is a method flow chart of steps S300 to S303 in this application.

[0068] Figure 4 It is a method flow chart of steps S400 to S402 in this application.

[0069] Figure 5 It is a method flow chart of steps S500 to S504 in this application.

[0070] Figure 6 It is a method flow chart of steps S600 to S603 in this application. DETAILED DESCRIPTION

[0071] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-6 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0072] The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings.

[0073] The embodiment of the present application discloses a redundant fusion unmanned driving domain control method, which sends a self-check protocol signal after the domain control system is started, and performs self-check on the main SOC system in the domain control system. When an abnormal fault occurs in the SCO system, the MCU system is instructed to take over the control of the unmanned vehicle, so that after the unmanned vehicle fails, the remaining control systems can maintain stable operation, so as to facilitate the collection of fault information and provide corresponding troubleshooting methods for subsequent on-site maintenance.

[0074] Reference Figure 1 The method flow of the redundant fusion unmanned driving domain control method includes the following steps:

[0075] Step S100: powering and starting a domain control system integrating multiple functions, wherein the domain control system includes a primary SOC system and a secondary MCU system;

[0076] SOC system stands for system-on-chip or system on chip. It integrates the main systems of multiple control functions into the SOC system for unified management, and helps to reduce the space occupied by the equipment and reduce the external cables used for connection. The integrated functions include panoramic camera system, high-precision navigation module, 5G-V2X module, WiFi Bluetooth module, signal deserialization module, laser radar system and other control systems. The secondary MCU system is a microcontroller, microcontroller and ultrasonic radar control system, vehicle control unit, power control system, etc.

[0077] The domain control system connects the SOC system and the MCU system. When the domain control system is powered on and started, it means that the unmanned vehicle is operating under the control of the domain control system.

[0078] Step S101: When the SOC system starts to control the vehicle driving, the MUC system is instructed to communicate data with the SOC system and a preset self-test protocol signal is sent to the SOC system;

[0079] When the SOC system controls the vehicle's driving, the MUC system and the SOC system communicate data so that the SOC system and the MUC system can cooperate with each other to complete the stable driving control of the vehicle. At the same time, a self-test protocol signal is sent to the SOC system to facilitate fault detection of the SOC according to the self-test protocol signal.

[0080] Step S102: Perform a self-check according to the self-check protocol signal to determine whether the SOC system is abnormal. If so, instruct the MUC system to take over vehicle control;

[0081] After receiving the self-test protocol signal, the corresponding self-test data is matched and sent to the SOC system. After receiving the corresponding data, the SOC system performs self-test. For example, after the panoramic camera system receives the self-test data corresponding to the self-test protocol signal, it performs corresponding image capture and transmission signal acquisition, thereby analyzing whether there is an abnormal image capture or transmission signal, and then knowing whether the panoramic camera system has an abnormality. If the main system for the stable driving control of the unmanned vehicle fails, it means that it is not conducive to the stable driving and operation of the unmanned vehicle at this time, and the MCU system is instructed to take over the vehicle control.

[0082] Step S103: instructing the MUC system to communicate with the preset 5G-V2X module to collect domain control system fault information and vehicle location and upload them to a preset storage terminal;

[0083] The 5G-V2X module is a vehicle wireless communication module used for 5G communication on unmanned vehicles. The system fault information indicates the system that has a fault on the domain control system. The specific faulty system can be determined through self-test. The vehicle position indicates the coordinate position of the unmanned vehicle, which can be determined through positioning by a high-precision navigation module. After the MUC system and the 5G-V2X module are connected and interoperable, the collected system fault information and vehicle position can be sent and uploaded to the storage terminal through the 5G-V2X module for storage, where the storage terminal is a pre-set data storage cloud.

[0084] Step S104: Analyze the fault information of the domain control system to determine the system fault type, and match the fault elimination method corresponding to the system fault type;

[0085] The fault type indicates the type of fault that occurs in the system, including system fault type and hardware fault type. System fault type can be troubleshooted by online maintenance of the system, while hardware fault requires on-site maintenance to troubleshoot.

[0086] The storage terminal stores a fault information analysis database, which stores different system fault types and fault troubleshooting methods corresponding to the system fault types. When the corresponding fault type is input, the corresponding fault troubleshooting method is automatically matched and output.

[0087] Step S105: Plan a maintenance route according to the vehicle location using a preset planning method, and issue an on-site maintenance prompt.

[0088] The planning method is a pre-set path planning method, which can collect the shortest moving path according to the vehicle position and form a method with the shortest distance path. The specific planning steps will be further explained later. After the maintenance path is planned, the corresponding on-site maintenance prompt will be issued to prompt the staff to reach the vehicle position for maintenance according to the maintenance path.

[0089] Reference Figure 2 , when sending a preset self-test protocol signal to the SOC system, it includes:

[0090] Step S200: collecting power supply parameters of the SOC system of the unmanned vehicle, wherein the power supply parameters include power supply voltage and power supply temperature;

[0091] When the MUC system controls the power supply system to supply power to the SOC system, it can learn whether the SOC system is in a stable operating state by collecting the power supply parameters of the SOC, wherein the collected power supply parameters include power supply voltage and power supply temperature.

[0092] Step S201: performing calculation according to the power supply voltage, the power supply temperature and a preset weight value calculation method to determine a voltage weight value and a temperature weight value;

[0093] The weight value calculation method is a weight calculation method used to calculate the voltage weight value and the temperature weight value. The specific calculation method is further explained in the subsequent steps. The purpose of calculating the temperature weight value and the voltage weight value is to analyze the impact weight of power supply temperature changes and power supply voltage changes on the normal operation of the SOC system, and perform corresponding self-test data matching.

[0094] Step S202: if the voltage weight value is greater than the temperature weight value, matching the voltage weight value to determine the voltage self-test protocol data;

[0095] After calculating the voltage weight value and the temperature weight value, by comparing the voltage weight value and the temperature weight value, the size relationship between the voltage weight value and the temperature weight value can be known. When the voltage weight value is greater than the temperature weight value, it means that the rate of change of the power supply voltage has changed significantly. Compared with the change of the power supply temperature, the stability of the power supply voltage needs to be tested accordingly. At this time, self-test is performed by matching the corresponding voltage self-test data.

[0096] Among them, a voltage self-test database is pre-established, different voltage weight values ​​are stored in the voltage self-test database, and voltage self-test data corresponding to different voltage weight values ​​are stored. When the corresponding voltage weight value is input, the corresponding voltage self-test data can be automatically matched and output, and the data is defined as voltage self-test protocol data. It should be noted that the larger the weight value, the smaller the matched voltage self-test protocol data. When the voltage self-test protocol data is smaller, the time required for the self-test process is shorter, which helps to improve the self-test efficiency.

[0097] Step S203: if the temperature weight value is greater than the voltage weight value, matching the corresponding temperature self-test protocol data according to the temperature weight value;

[0098] Similarly, when the temperature weight value is greater than the voltage weight value, it means that the power supply temperature in the SOC system is unstable. In this case, a power supply temperature self-test database is established in advance, and different temperature weight values ​​are stored in the power supply temperature self-test database. In addition, temperature self-test protocol data corresponding to different temperature weight values ​​are stored. When the temperature weight value is input, the corresponding temperature self-test protocol data can be matched to facilitate subsequent self-test calls.

[0099] Step S204: marking the voltage self-test protocol data or the temperature self-test protocol data, and sending a self-test protocol signal.

[0100] By marking the matched voltage self-test protocol data or temperature self-test protocol data and sending a self-test protocol signal to prompt a self-test, the fault information of the domain control system can be obtained.

[0101] Among them, when the power supply voltage, power supply temperature and the preset weight value calculation method are calculated, the following formula is used for calculation:

[0102]

[0103] Among them, Q u Represents the voltage weight value, Δx t It represents the rate of change of the power supply voltage value per unit time of duration t, δ represents the reference voltage weight coefficient, Δy t It represents the rate of change of the power supply temperature value per unit time of duration t, and γ represents the reference temperature weight coefficient.

[0104] Reference Figure 3 , when collecting domain control system fault information, it includes:

[0105] Step S300: collecting and analyzing the operating status of the control system to determine the abnormal system function of the faulty system;

[0106] The operation status of the domain control system indicates the working status of the system. When there is an operation fault in the control system, the control system is marked to know the control system with the fault, and the operation function of the faulty control system is queried and defined as an abnormal system function.

[0107] Step S301: If the abnormal system function belongs to a preset irreplaceable system function type, the faulty system is marked and a fault type analysis prompt is issued;

[0108] Different abnormal system functions have different function types, including replaceable function types and irreplaceable function types. By marking the corresponding systems in advance, it can be known whether the abnormal system function belongs to the irreplaceable system function type. If so, it means that it is difficult to repair the faulty system online, and a fault type analysis prompt is issued so that it can be known in advance when conducting on-site maintenance.

[0109] Step S302: if the abnormal system function belongs to the replaceable system function type, then match the corresponding backup system in the preset extended system;

[0110] When the abnormal system function belongs to the type of replaceable system function, it means that remote fault repair can be performed through the network. At this time, it is replaced by matching the backup system so that the unmanned vehicle can work again. The expansion system is a pre-set expansion storage system that stores multiple backup systems. Different backup systems can replace different control systems in the domain control system to work.

[0111] Step S303: instruct the domain control system to connect with the backup system and issue a troubleshooting prompt.

[0112] After matching the corresponding backup system, the domain control system is instructed to connect with the backup system and send an exclusion prompt signal to let the unmanned vehicle know that it can drive and operate normally.

[0113] Reference Figure 4 , the preset planning method includes:

[0114] Step S400: Analyze the preset moving path and vehicle position of the unmanned vehicle when it is working to determine the shortest minimum moving path;

[0115] The preset moving path is a path pre-formed when the unmanned vehicle is operating. By comparing and intercepting the vehicle position with the preset moving path, the shortest path from the initial position to the current vehicle position of the unmanned vehicle can be obtained. This path is defined as the minimum moving path for subsequent further analysis.

[0116] Step S401: collecting and analyzing a panoramic image of the process of the unmanned vehicle moving along a preset moving path to the vehicle position to determine path obstacle parameters;

[0117] When the unmanned vehicle reaches the vehicle position along the preset moving path, it collects panoramic images of the path along the way, analyzes the obstacle characteristics of the panoramic image during the collection process, marks the road obstacle areas obtained by the analysis, and defines the corresponding coordinates of all obstacle areas as path obstacle parameters.

[0118] Step S402: Compare the path obstacle parameters with the minimum moving path to determine a maintenance path that avoids the obstacles corresponding to the path obstacle parameters on the minimum moving path.

[0119] By comparing the obstacle area and the minimum moving path of the obstacle parameters, the overlapping area of ​​the obstacle area on the minimum moving path can be obtained, so as to regenerate a path to avoid the obstacle, and define the path as the maintenance path so that subsequent personnel can arrive at the vehicle for on-site maintenance.

[0120] Reference Figure 5, when determining the maintenance path that avoids the obstacles corresponding to the path obstacle parameters on the minimum moving path, it also includes:

[0121] Step S500: instructing a preset 5G-V2X module to collect traffic information on the minimum moving path according to a preset period;

[0122] The 5G-V2X module collects traffic information on the minimum moving path at a periodic frequency, which can reduce working energy consumption. The specific collection cycle is set by the staff according to needs. Traffic information refers to the traffic congestion on the minimum moving path. The purpose of collecting traffic information is to call it for subsequent analysis of traffic obstacles.

[0123] Step S501: Analyze the traffic information to determine the location of the traffic obstacle;

[0124] By analyzing the traffic information, we can know the traffic congestion situation on the minimum moving path, and by periodic collection, we can know the changes in traffic congestion after a period of time. Each time the traffic information is collected, the congested section is marked and defined as the traffic obstacle location.

[0125] Step S502: comparing and analyzing the traffic obstacle location and the minimum moving path to determine a temporary adjustment path, and issuing a temporary adjustment prompt;

[0126] By comparing the traffic obstacle position and the minimum moving path, the overlapping area on the traffic obstacle position and the minimum moving path can be obtained, and a temporary adjustment path to avoid the overlapping area is generated, and a temporary adjustment prompt signal is issued.

[0127] Step S503: adjusting the minimum moving path based on the temporary adjustment prompt and the temporary adjustment path;

[0128] Step S504: updating the adjusted minimum moving path to the maintenance path, and reacquiring a temporary adjustment prompt.

[0129] A new path is generated by comparing and replacing the adjustment path with the minimum moving path, and the newly generated path is updated as the maintenance path, so that obstacles on the road and traffic jams can be avoided when the vehicle position is reached according to the maintenance path.

[0130] Reference Figure 6 , when determining the location of traffic obstacles, include:

[0131] Step S600: collecting and analyzing regional images of the traffic obstacle location to determine the state of the traffic obstacle;

[0132] When determining the location of a traffic obstacle, by collecting regional images for analysis, it can be determined whether the traffic at the current traffic obstacle location is still in a blocked state, and this state is defined as a traffic obstacle state.

[0133] Step S601: analyzing whether the traffic obstacle state is consistent with the preset obstacle clearing state within the preset preparation time range;

[0134] The preparation time range indicates the interval of preparation time before the on-site maintenance personnel depart. By analyzing whether the traffic obstacle status and obstacle clearing status are consistent within the preparation time range, it can be determined whether there is still traffic congestion at the traffic obstacle location.

[0135] Step S602: If they are consistent, cancel the mark of the traffic obstacle location;

[0136] If the traffic obstacle state is consistent with the preset obstacle clearing state, it means that the traffic congestion at the traffic obstacle location is resolved and there is no traffic obstacle at this time. Then the mark of the traffic obstacle location is cancelled to improve the accuracy and reliability of path planning to avoid obstacles.

[0137] Step S603: If not consistent, mark the traffic obstacle location and issue a temporary route adjustment prompt.

[0138] If the traffic obstacle status is inconsistent with the preset obstacle clearing status, it means that the traffic obstacle still exists at this time, and there is no need to cancel the mark of the traffic obstacle position. At this time, a temporary path adjustment prompt is issued to facilitate the corresponding path adjustment.

[0139] Based on the same inventive concept, an embodiment of the present invention provides a redundant fusion unmanned driving domain controller, including:

[0140] The domain control module integrates multiple control systems and performs driving control, including the main SOC system and the secondary MCU system;

[0141] Self-check analysis module, when the SOC system starts to control the vehicle driving, instructs the MUC system to communicate data with the SOC system and sends a preset self-check protocol signal to the SOC system;

[0142] Perform self-check according to the self-check protocol signal to determine whether the SOC system is abnormal, and if so, instruct the MUC system to take over vehicle control;

[0143] The maintenance interaction module instructs the MUC system to communicate with the preset 5G-V2X module to collect domain control system fault information and vehicle location and upload them to the preset storage terminal;

[0144] Analyze the fault information of the domain control system to determine the system fault type and match the fault elimination method corresponding to the system fault type;

[0145] Plan the maintenance route according to the vehicle location using a preset planning method and issue on-site maintenance reminders;

[0146] A memory for storing a program of any one of the redundant fusion unmanned driving domain controllers;

[0147] The program in the processor and the memory can be loaded and executed by the processor to realize any redundant fusion unmanned driving domain controller.

[0148] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0149] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded by a processor and execute a redundancy fusion unmanned driving domain control method.

[0150] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0151] Based on the same inventive concept, an embodiment of the present invention provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed by a redundant fusion unmanned driving domain controller.

[0152] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0153] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A redundant fusion unmanned driving domain control method, characterized in that: include: Step 1, powering on and starting a domain control system integrating multiple functions, wherein the domain control system includes a primary SOC system and a secondary MCU system; Step 2: When the SOC system starts to control the vehicle's driving, the MUC system is instructed to communicate data with the SOC system and a preset self-test protocol signal is sent to the SOC system; Step 3, performing a self-check according to the self-check protocol signal to determine whether the SOC system is abnormal, and if so, instructing the MUC system to take over vehicle control; Step 4: Instruct the MUC system to communicate with the preset 5G-V2X module to collect domain control system fault information and vehicle location and upload them to the preset storage terminal; Step 5: Analyze the fault information of the domain control system to determine the system fault type, and match the fault elimination method corresponding to the system fault type; Step 6: Plan a maintenance route based on the vehicle location using a preset planning method and issue an on-site maintenance reminder.

2. The redundant fusion unmanned driving domain control method according to claim 1 is characterized in that: Sending a preset self-test protocol signal to the SOC system includes: Collecting power supply parameters of the SOC system of the unmanned vehicle, wherein the power supply parameters include power supply voltage and power supply temperature; Calculating according to the power supply voltage, the power supply temperature and a preset weight value calculation method to determine the voltage weight value and the temperature weight value; If the voltage weight value is greater than the temperature weight value, the voltage self-test protocol data is determined according to the voltage weight value match; If the temperature weight value is greater than the voltage weight value, the corresponding temperature self-test protocol data is matched according to the temperature weight value; The voltage self-test protocol data or the temperature self-test protocol data is marked, and a self-test protocol signal is sent.

3. The redundant fusion unmanned driving domain control method according to claim 2 is characterized in that: When the power supply voltage, power supply temperature and the preset weight value calculation method are calculated, the following formula is used for calculation: Among them, Q u Represents the voltage weight value, Δx t It represents the rate of change of the power supply voltage value per unit time of duration t, δ represents the reference voltage weight coefficient, Δy t It represents the rate of change of the power supply temperature value per unit time of duration t, and γ represents the reference temperature weight coefficient.

4. The redundant fusion unmanned driving domain control method according to claim 1 is characterized in that: The collection of domain control system fault information includes: Collect and analyze the operating status of the control system to determine the abnormal system function of the faulty system; If the abnormal system function belongs to the preset irreplaceable system function type, the faulty system will be marked and a fault type analysis prompt will be issued; If the abnormal system function belongs to the replaceable system function type, the corresponding backup system in the preset expansion system is matched; Instructs the domain control system and the standby system to connect and issues troubleshooting prompts.

5. The redundant fusion unmanned driving domain control method according to claim 1 is characterized in that: The preset planning method includes: Analyze the preset moving path and vehicle position of the unmanned vehicle when it is working to determine the minimum moving path with the shortest path; Collect and analyze panoramic images of the process of the unmanned vehicle moving along a preset moving path to the vehicle position to determine path obstacle parameters; The path obstacle parameters are compared with the minimum moving path to determine the maintenance path that avoids the obstacles corresponding to the path obstacle parameters on the minimum moving path.

6. The redundant fusion unmanned driving domain control method according to claim 5 is characterized in that: When determining the inspection path that avoids the obstacles corresponding to the path obstacle parameters on the minimum moving path, it also includes: Instruct the preset 5G-V2X module to collect traffic information on the minimum moving path according to a preset period; Analyze traffic information based on road conditions to determine the location of traffic obstacles; Compare and analyze the location of traffic obstacles and the minimum moving path to determine the temporary adjustment path and issue a temporary adjustment prompt; adjusting the minimum moving path based on the temporary adjustment prompt and the temporary adjustment path; The adjusted minimum moving path is updated as the maintenance path, and the temporary adjustment prompt is obtained again.

7. The redundant fusion unmanned driving domain control method according to claim 6 is characterized in that: Determining the location of traffic obstructions includes: Collect regional images of traffic obstacle locations for analysis to determine the status of traffic obstacles; Analyze whether the traffic obstacle status is consistent with the preset obstacle clearing status within the preset preparation time range; If they are consistent, the mark of the traffic obstacle location will be cancelled; If there is any inconsistency, the location of the traffic obstacle will be marked and a temporary route adjustment prompt will be issued.

8. A redundant fusion unmanned driving domain controller, characterized in that: include: The domain control module integrates multiple control systems and performs driving control, including the main SOC system and the secondary MCU system; Self-check analysis module, when the SOC system starts to control the vehicle driving, instructs the MUC system to communicate data with the SOC system and sends a preset self-check protocol signal to the SOC system; Perform self-check according to the self-check protocol signal to determine whether the SOC system is abnormal, and if so, instruct the MUC system to take over vehicle control; Maintenance interaction module, instructing the MUC system to communicate with the preset 5G-V2X module to collect domain control system fault information and vehicle location and upload them to the preset storage terminal; Analyze the fault information of the domain control system to determine the system fault type and match the fault elimination method corresponding to the system fault type; Plan the maintenance route according to the vehicle location using a preset planning method and issue on-site maintenance reminders; A memory for storing a program of a redundant fusion unmanned driving domain controller according to any one of claims 1 to 7; The program in the memory can be loaded and executed by the processor to realize the redundant fusion unmanned driving domain controller as claimed in any one of claims 1 to 7.

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