Unmanned vehicle state monitoring and analyzing system

Abstract

The invention relates to an unmanned vehicle state monitoring and analysis system. The unmanned vehicle state monitoring and analysis system comprises a data analysis module and a plurality of data acquisition modules in communication connection with the data analysis module. Each data acquisition module is used for acquiring state information of the corresponding unmanned vehicle; the data analysis module obtains the state information, collected by the data collection module, of the unmanned vehicle, and completes unmanned vehicle motion control ability analysis, unmanned vehicle environment perception ability analysis and unmanned vehicle planning ability analysis based on the state information. According to the unmanned vehicle state monitoring and analysis system, the data acquisition module at the vehicle end and the data analysis module at the cloud end are integrated, the system achieves centralized real-time monitoring and analysis of the motion state and the safety condition of the networking unmanned vehicle, the testing efficiency of the unmanned vehicle system can be improved, and the safety of the unmanned vehicle during testing can be better guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field, and in particular to an unmanned vehicle state monitoring and analysis system. Background Art

[0002] Unmanned vehicles, also known as driverless cars or self-driving cars, are intelligent vehicles that can use a variety of sensor technologies to sense the environment and status of the vehicle, and plan appropriate paths and control the vehicle's driving through advanced computing and control systems. In recent years, with the advancement of related technologies for autonomous driving, the optimization of the policy environment and the expansion of the market scale, the autonomous driving industry has made great progress, and the development of autonomous driving technology is in a stage of rapid growth and continuous breakthroughs. However, the development of autonomous driving also faces a series of challenges. How to ensure the safety of unmanned vehicle operation and testing and how to effectively improve the efficiency of unmanned vehicle testing are two key challenges.

[0003] With the advancement of autonomous driving technology, countries are actively promoting the practical application of unmanned vehicles to improve traffic safety, efficiency and reduce environmental pollution. Unmanned vehicles need to undergo rigorous testing before they are put into formal use. How to ensure the safety of the testing process and improve the testing efficiency are two key issues in unmanned vehicle testing.

[0004] The current methods to improve the safety of unmanned vehicle operation and testing are mainly focused on how to improve the performance of various autonomous driving algorithms and sensors. However, when it comes to the operation of unmanned vehicle networks, simply improving the performance of a single machine from a single machine perspective cannot completely solve the problem. Literature shows that in some cases, there are still risk factors in the global environment. In other words, ensuring that all drones in the system recognize the risks they face is not a strong constraint on system safety. In order to systematically evaluate the safety and operating efficiency of the system, it is necessary to make a layout from the overall perspective of the system. Summary of the invention

[0005] In order to improve the test efficiency and runtime safety of existing unmanned vehicle systems and to make up for the deficiencies in system safety and test parameter acquisition when relying solely on a single unmanned vehicle, the present application provides an unmanned vehicle status monitoring and analysis system.

[0006] The unmanned vehicle status monitoring and analysis system of the present application includes a data analysis module and a plurality of data acquisition modules that are in communication with the data analysis module; each data acquisition module is used to obtain the status information of the corresponding unmanned vehicle; The data analysis module obtains the status information of the unmanned vehicle collected by the data collection module, and completes the unmanned vehicle motion control capability analysis, the unmanned vehicle environmental perception capability analysis and the unmanned vehicle planning capability analysis based on the status information.

[0007] Preferably, it also includes a remote communication module, which includes multiple ad hoc network radio stations; each data acquisition module is communicatively connected to one ad hoc network radio station, and the data analysis module is communicatively connected to one ad hoc network radio station.

[0008] Preferably, the status information collected by the data acquisition module includes at least the real-time latitude and longitude, heading, speed, acceleration, pitch angle, tilt angle, timestamp, perception grid map, perceived target position, perceived target size, perceived target type, global planning results, local planning results, on-board video information, remaining fuel / battery level, fault type, and operating mode of the unmanned vehicle.

[0009] Preferably, the unmanned vehicle motion control capability analysis of the data analysis module includes: Analysis of the longitudinal control capability of unmanned vehicles and indicators to measure the longitudinal control capability of unmanned vehicles ,

[0010] Among them, Indicates unmanned vehicle Time speed, Indicates unmanned vehicle Always plan your speed. Indicates the total number of moments; and / or, Analysis of the lateral control capability of unmanned vehicles and indicators to measure the lateral control capability of unmanned vehicles ,

[0011] in, Indicates unmanned vehicle Time longitude, Indicates unmanned vehicle Time latitude, Indicates unmanned vehicle Always plan your longitude, Indicates unmanned vehicle Always plan your latitude, Indicates the total number of moments, , ; and / or, The control stability analysis of the unmanned vehicle is to evaluate the stability of the unmanned vehicle based on the changes in the acceleration and heading angle of the unmanned vehicle. Indicates unmanned vehicle Time acceleration, Indicates unmanned vehicle Time direction, Indicates the total number of moments, an indicator to measure the control stability of the unmanned vehicle , .

[0012] Preferably, the unmanned vehicle environment perception capability analysis of the data analysis module includes: Analysis of target recognition capabilities of unmanned vehicles, and indicators to measure target recognition capabilities of unmanned vehicles ,

[0013] in, Indicates The perceived target location, Indicates The perceived target length, Indicates The perceived target width, Indicates The perceived target height, Indicates Perception target type, using Indicates The real position of the perceived target, Indicates The real length of the perceived target, Indicates The real width of the perceived target, Indicates The real height of the perceived target, Indicates The real type of the perceived target, Represents the total number of recognized targets. and Same ,when and Different ; and / or, Analysis of the efficiency of autonomous vehicle perception and mapping, and the index to measure the efficiency of autonomous vehicle perception and mapping ,

[0014] in, Indicates the moment when the data analysis module receives the first perception grid map. Indicates the time when the data analysis module receives the last perception grid map. From the beginning to the end of the counting, a total of a perception grid map; and / or, Unmanned vehicle perception and mapping quality assessment and analysis function, an indicator to measure the quality of unmanned vehicle perception and mapping ,

[0015] in, Indicates the resolution of the perceptual raster map; Preferably, the unmanned vehicle global path planning efficiency analysis of the data analysis module includes: Analysis of the efficiency of global path planning for unmanned vehicles, and indicators to measure the efficiency of global path planning ,

[0016] in, represents the length of the global trajectory, Indicates the time consumption of global planning. and / or, Safety analysis of local path planning for unmanned vehicles, and indicators to measure the safety of local path planning ,

[0017] in, Indicates The minimum distance between a local path and an obstacle, Indicates The distance between the local path and the boundary of the traversable area at the minimum distance between the local path and the obstacle, Indicates The length of the local path, Indicates the reference value of the distance between the local path and the obstacle, and is an indicator to measure the safety of local path planning. ; and / or, Analysis of the smoothness of planned trajectories of unmanned vehicles, and indicators to measure the smoothness of planned trajectories ,

[0018] in, Indicates The local path The curvature of a point.

[0019] This application provides an unmanned vehicle status monitoring and analysis system that integrates a vehicle-side data acquisition module and a cloud-based data analysis module. The data analysis module completes tasks such as unmanned vehicle motion control capability analysis, unmanned vehicle environmental perception capability analysis, and unmanned vehicle planning capability analysis by acquiring the unmanned vehicle status information collected by the data acquisition module. This system realizes centralized real-time monitoring and analysis of the motion status and safety status of networked unmanned vehicles, which can improve the test efficiency of the unmanned vehicle system and better ensure the safety of unmanned vehicle testing. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a network diagram of the unmanned vehicle status monitoring and analysis system of the present invention; Figure 2 A schematic diagram of an embodiment of the unmanned vehicle state monitoring and analysis system of the present invention; Figure 3 It is a schematic diagram of the arrangement of the data acquisition module 1 in the unmanned vehicle state monitoring and analysis system of the present invention; Figure 4 It is a schematic diagram of the operation of the unmanned vehicle state monitoring and analysis system of the present invention; Figure 5 Schematic diagram of the functional architecture of the data analysis module 2 in the unmanned vehicle status monitoring and analysis system of the present invention.

[0021] In the figure: 1: Data acquisition module; 2: Data analysis module; 3: Remote communication module; 31: Self-organizing network radio station. DETAILED DESCRIPTION

[0022] The present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. In this specification, the size ratios in the drawings do not represent the actual size ratios, but are only used to reflect the relative position relationship and connection relationship between the components. Components with the same name or the same number represent similar or identical structures and are only for illustrative purposes.

[0023] The present application provides an unmanned vehicle status monitoring and analysis system. Figure 1 : is a schematic diagram of the system composition of the unmanned vehicle status monitoring and analysis system. The unmanned vehicle monitoring and analysis system is mainly used in a combination system with multiple unmanned vehicles. It includes a data analysis module 2 and a plurality of data acquisition modules 1 that are communicatively connected to the data analysis module 2. The data analysis module 2 is placed on the server side, and each data acquisition module 1 corresponds to a single unmanned vehicle. The data acquisition module 1 is communicatively connected to the corresponding unmanned vehicle to obtain various status information of the unmanned vehicle corresponding to it. In an actual embodiment, the data acquisition module 1 can be set on the unmanned vehicle to obtain information from the unmanned vehicle through Ethernet interconnection, or it can be not set on the unmanned vehicle, but communicated with the unmanned vehicle via wireless communication. The data analysis module 2 receives the information from the data acquisition module 1 and performs real-time monitoring and analysis on the operating status of the unmanned vehicle according to various status information of the unmanned vehicle to obtain corresponding results.

[0024] Figure 2This is a schematic diagram of an embodiment of the unmanned vehicle status monitoring and analysis system of the present application. Each data acquisition module 1 and the data analysis module 2 communicate with each other through a remote communication module 3. The remote communication module 3 is a communication system composed of multiple self-organizing network radio stations 31. In the path between each data acquisition module 1 and the data analysis module 2, communication is achieved through the relay of multiple self-organizing network radio stations 31. In this embodiment, the data analysis module 2 on the server side and each data acquisition module 1 are correspondingly deployed with one self-organizing network radio station 31. In the communication process between each data acquisition module 1 and the data analysis module 2, communication is achieved through at least the aforementioned two self-organizing network radio stations 31.

[0025] The state acquisition module 1 includes a battery and a data acquisition board, and has the ability to self-power, collect data, and send data. The self-organizing network radio is interconnected with the state acquisition module, and the collected unmanned vehicle state information is forwarded externally via the self-organizing network radio. The information collected by the data acquisition module 1 from the unmanned vehicle should at least include the unmanned vehicle's real-time latitude and longitude, heading, speed, acceleration, pitch angle, tilt angle, timestamp, perception grid map, perception target position, perception target size, perception target type, global planning results, local planning results, vehicle-mounted video information, remaining fuel / power, fault type, and operating mode.

[0026] like Figure 3 As shown, multiple data acquisition modules 1 are deployed on different unmanned vehicles, and real-time status monitoring and analysis of multiple unmanned vehicles are realized at the same time. The upper limit of the number of data acquisition modules 1 deployed is determined by the bandwidth of wireless data transmission and the amount of data collected. Figure 4 As shown, in one embodiment of the present application, the number of data acquisition modules 1 is set to no more than 8. The number of ad hoc network radio stations included in the remote communication module 3 is determined by the number of data acquisition modules 1 and data analysis modules 2. One ad hoc network radio station is deployed at each data acquisition module 1, and one ad hoc network radio station is deployed at each data analysis module 2.

[0027] Figure 5 This is a functional architecture diagram of the data analysis module 2. The functions of the data analysis module 2 include real-time situation display of the unmanned vehicle, analysis and evaluation of the unmanned vehicle's motion control capability, analysis and evaluation of the unmanned vehicle's environmental perception capability, and analysis and evaluation of the unmanned vehicle's planning capability.

[0028] The real-time situation display function of the unmanned vehicle of the data analysis module 2 includes: video display function, which displays the on-board video information, and has the functions of storing videos, playing back videos, and playing videos at double speeds; real-time health status monitoring function, which displays the chassis status feedback information such as the remaining power / fuel amount, operating mode, and fault type of the unmanned vehicle; high-precision map display function, which displays the high-precision map of the unmanned vehicle operating area, and the position, speed, heading, actual operating trajectory, and planned trajectory of the unmanned vehicle can be displayed in real time on the high-precision map. By clicking on the actual operating trajectory point, the status information of the unmanned vehicle at the trajectory point can be displayed; grid map display function, which displays the unmanned vehicle grid map, which integrates the perception result information of the on-board perception sensor, and includes the passable area information and obstacle information.

[0029] The unmanned vehicle motion control capability analysis and evaluation functions of the data analysis module 2 include: The unmanned vehicle longitudinal control capability analysis and evaluation function evaluates the unmanned vehicle longitudinal control capability based on the actual speed information and speed planning information of the unmanned vehicle. Indicates unmanned vehicle Time speed, Indicates unmanned vehicle Always plan your speed. Indicates the total number of moments, an indicator to measure the longitudinal control capability of the unmanned vehicle , according to the formula

[0030] Calculated.

[0031] The lateral control capability of the unmanned vehicle is analyzed and evaluated based on the operating position information and path planning information of the unmanned vehicle. Indicates unmanned vehicle Time longitude, Indicates unmanned vehicle Time latitude, Indicates unmanned vehicle Always plan your longitude, Indicates unmanned vehicle Always plan your latitude, Indicates the total number of moments, an indicator to measure the lateral control capability of the unmanned vehicle , according to the formula

[0032] Calculated, among which , ; The control stability assessment of the unmanned vehicle is to assess the stability of the unmanned vehicle based on the changes in the acceleration and heading angle of the unmanned vehicle. Indicates unmanned vehicle Time acceleration, Indicates unmanned vehicle Time direction, Indicates the total number of moments, an indicator to measure the control stability of the unmanned vehicle , according to the formula

[0033] Calculated.

[0034] The unmanned vehicle environmental perception capability analysis and evaluation functions of the data analysis module 2 include: The target recognition capability evaluation function of the unmanned vehicle evaluates the target recognition accuracy of the unmanned vehicle based on the perceived target position, perceived target size, perceived target type, perceived target true position, perceived target true size, and perceived target true type. Indicates The perceived target location, Indicates The perceived target length, Indicates The perceived target width, Indicates The perceived target height, Indicates Perception target type, using Indicates The real position of the perceived target, Indicates The real length of the perceived target, Indicates The real width of the perceived target, Indicates The real height of the perceived target, Indicates The real type of the perceived target, Indicates the total number of recognized targets, an indicator to measure the target recognition capability of the unmanned vehicle , according to the formula

[0035] Calculated, among which The meaning is that when and Same ,when and Different .

[0036] The unmanned vehicle perception mapping efficiency evaluation function evaluates the mapping efficiency of the unmanned vehicle perception system based on the perception grid map generation frequency. Indicates the time when the online data analysis module receives the first perception grid map, Indicates the time when the online data analysis module receives the last perception grid map. From the start to the end of the counting, a total of A perception grid map, an indicator to measure the efficiency of perception mapping for unmanned vehicles , according to the formula

[0037] Calculated.

[0038] The unmanned vehicle perception mapping quality assessment function evaluates the unmanned vehicle perception mapping quality based on the perception grid map resolution and the unmanned vehicle target recognition capability. Indicates the resolution of the perception grid map, an indicator to measure the quality of the perception map of the unmanned vehicle , according to the formula Calculated.

[0039] The unmanned vehicle planning capability analysis and evaluation functions of data analysis module 2 include: The unmanned vehicle global path planning efficiency evaluation function evaluates the global path planning efficiency of the unmanned vehicle based on the global planning path length and the time taken to complete the global path planning. represents the length of the global trajectory, Indicates the time consumption of global planning and is an indicator to measure the efficiency of global path planning , according to the formula Calculations show that, under the same conditions, the shorter the global trajectory and the shorter the planning time, the higher the surface global path planning efficiency.

[0040] The safety assessment function of the local path planning of the unmanned vehicle is used to assess the safety of the local path planning of the unmanned vehicle based on the minimum distance between the local path and obstacles, the minimum distance between the local path and the boundary of the passable area, and the length of the local path. Indicates The minimum distance between a local path and an obstacle, Indicates The distance between the local path and the boundary of the traversable area at the minimum distance between the local path and the obstacle, Indicates The length of the local path, Indicates the reference value of the distance between the local path and the obstacle, and is an indicator to measure the safety of local path planning. , according to the formula

[0041] Calculated.

[0042] The function of evaluating the smoothness of the planned trajectory of the unmanned vehicle is to evaluate the smoothness of the trajectory planning based on the average curvature of the local path. Indicates The local path The curvature of each point is used as an indicator to measure the smoothness of the planned trajectory. , according to the formula

[0043] Calculated.

[0044] This system solution improves the safety of the unmanned vehicle operation and testing process through real-time monitoring of the unmanned vehicle's operating status, and improves the efficiency of unmanned vehicle testing through analysis and evaluation of some of the unmanned vehicle's autonomous capabilities. From the perspective of real-time status monitoring, it intuitively displays the real-time operating status of the unmanned vehicle in front of the staff, ensuring that the operating status of the unmanned vehicle can be controlled at all times and problems can be discovered in a timely manner, ultimately achieving the goal of ensuring the safe operation of the unmanned vehicle.

[0045] The above content only describes the preferred implementation mode of the present invention, and does not limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solution of the present invention by ordinary technicians in this field should fall within the protection scope determined by the claims of the present invention.

Claims

1. An unmanned vehicle status monitoring and analysis system, characterized in that: It comprises a data analysis module (2) and a plurality of data acquisition modules (1) which are in communication with the data analysis module (2); each data acquisition module (1) is used to obtain status information of a corresponding unmanned vehicle; The data analysis module (2) obtains the state information of the unmanned vehicle collected by the data collection module (1), and completes the unmanned vehicle motion control capability analysis, the unmanned vehicle environment perception capability analysis and the unmanned vehicle planning capability analysis based on the state information.

2. The unmanned vehicle status monitoring and analysis system according to claim 1, characterized in that: It also includes a remote communication module (3), which includes a plurality of ad hoc network radio stations (31); each data acquisition module (1) is communicatively connected to one ad hoc network radio station (31), and the data analysis module (2) is communicatively connected to one ad hoc network radio station (31).

3. The unmanned vehicle status monitoring and analysis system according to claim 1, characterized in that: The status information collected by the data collection module (1) at least includes the real-time latitude and longitude, heading, speed, acceleration, pitch angle, tilt angle, timestamp, perception grid map, perception target position, perception target size, perception target type, global planning results, local planning results, vehicle-mounted video information, remaining fuel / power, fault type, and operating mode of the unmanned vehicle.

4. The unmanned vehicle status monitoring and analysis system according to claim 3, characterized in that: The unmanned vehicle motion control capability analysis of the data analysis module (2) includes: Analysis of the longitudinal control capability of unmanned vehicles and indicators to measure the longitudinal control capability of unmanned vehicles , Among them, Indicates unmanned vehicle Time speed, Indicates unmanned vehicle Always plan your speed. Indicates the total number of moments; and / or, Analysis of the lateral control capability of unmanned vehicles and indicators to measure the lateral control capability of unmanned vehicles , in, Indicates unmanned vehicle Time longitude, Indicates unmanned vehicle Time latitude, Indicates unmanned vehicle Always plan your longitude, Indicates unmanned vehicle Always plan your latitude, Indicates the total number of moments, , ; and / or, The control stability analysis of the unmanned vehicle is to evaluate the stability of the unmanned vehicle based on the changes in the acceleration and heading angle of the unmanned vehicle. Indicates unmanned vehicle Time acceleration, Indicates unmanned vehicle Time direction, Indicates the total number of moments, an indicator to measure the control stability of the unmanned vehicle , 。 5. The unmanned vehicle status monitoring and analysis system according to claim 3, characterized in that: The analysis of the unmanned vehicle's environmental perception capability in the data analysis module (2) includes: Analysis of target recognition capabilities of unmanned vehicles, and indicators to measure target recognition capabilities of unmanned vehicles , in, Indicates The perceived target location, Indicates The perceived target length, Indicates The perceived target width, Indicates The perceived target height, Indicates Perception target type, using Indicates The real position of the perceived target, Indicates The real length of the perceived target, Indicates The real width of the perceived target, Indicates The real height of the perceived target, Indicates The real type of the perceived target, Represents the total number of recognized targets. and Same ,when and Different ; and / or, Analysis of the efficiency of autonomous vehicle perception and mapping, and the index to measure the efficiency of autonomous vehicle perception and mapping , in, represents the moment when the data analysis module (2) receives the first perception grid map, Indicates the time when the data analysis module (2) receives the last perception grid map. From the beginning to the end of the counting, a total of a perception grid map; and / or, Unmanned vehicle perception and mapping quality assessment and analysis function, an indicator to measure the quality of unmanned vehicle perception and mapping , in, Indicates the resolution of the perceptual raster map.

6. The unmanned vehicle status monitoring and analysis system according to claim 3, characterized in that: The unmanned vehicle global path planning efficiency analysis of the data analysis module (2) includes: Analysis of the efficiency of global path planning for unmanned vehicles, and indicators to measure the efficiency of global path planning , in, represents the length of the global trajectory, Indicates the time consumption of global planning. and / or, Safety analysis of local path planning for unmanned vehicles, and indicators to measure the safety of local path planning , in, Indicates The minimum distance between a local path and an obstacle, Indicates The distance between the local path and the boundary of the traversable area at the minimum distance between the local path and the obstacle, Indicates The length of the local path, Indicates the reference value of the distance between the local path and the obstacle, and is an indicator to measure the safety of local path planning. ; and / or, Analysis of the smoothness of planned trajectories of unmanned vehicles, and indicators to measure the smoothness of planned trajectories , in, Indicates The local path The curvature of a point.

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