Vehicle test field measuring system

Abstract

The invention discloses a vehicle test field measurement system, which comprises a vehicle end, a field end and a rear end, and is characterized in that a vehicle-mounted positioning module outputs vehicle self-positioning information through a vehicle-mounted communication module; the field end comprises a plurality of positioning assemblies, and each positioning assembly comprises a base, a capture positioning module, an edge calculation module and a communication module. The capturing and positioning module is used for outputting field end positioning information acquired by the image positioning unit, the ultra-wideband positioning unit, the laser radar positioning unit, the millimeter-wave radar positioning unit and the pseudo-satellite base station positioning unit, and the edge calculation module acquires a preset weight coefficient based on environmental parameters; the edge calculation module adopts an extended Kalman filtering method to determine vehicle capture positioning information based on a preset weight coefficient and the field end positioning information; and the rear end evaluates the vehicle-mounted positioning module according to the vehicle capture positioning information and the vehicle self-positioning information.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent driving vehicle development test system, and in particular to a vehicle test field measurement system. Background Art

[0002] As the functions of automobiles become more and more abundant, the demand for closed-field testing of modern automobiles, especially self-driving cars, is gradually increasing. Real-time measurement and recording of test process data are of great significance for test operation and data analysis. At present, the method for measuring the motion state of test vehicles in automobile test fields is usually to install measurement sensors on each vehicle to obtain the vehicle's position, speed, posture and other status information. Since a large number of sensors need to be installed on each vehicle, the vehicle load and temperature will change. For tests with strict requirements on the vehicle state environment, this method will cause the vehicle state to be "distorted" and cannot meet the test requirements; at the same time, with the increase in the number of test vehicles running in the field, the cost and maintenance pressure of test equipment will inevitably increase sharply. Single-vehicle positioning and simple combination of GPS+RTK base station fusion positioning methods are highly dependent on the environment. They do not consider the use requirements in bad weather and bad environments. The measurement system cannot achieve stable measurement all day and all day, which is often the environment that modern automobiles, especially intelligent connected vehicles, need to be tested and verified. In addition, as the functions of automobiles are gradually enriched, the number and danger of automobile tests are increasing, and the current test fields generally lack real-time intelligent monitoring and measurement facilities for the running vehicle status and global operation status.

[0003] The problems of the existing test field measurement system are as follows: First, if the vehicles running in the test field want to achieve high-precision positioning and effectively perceive the surrounding environment information, a large number of sensors need to be arranged on each vehicle, resulting in excessively high cost of the measurement system, excessive weight of the measurement equipment, and difficulty in transmitting test information to the outside, which is not conducive to large-scale use. Secondly, the single vehicle-side sensor positioning method collects limited information, and it is difficult to obtain clear and sufficiently in-depth multi-vehicle collaborative test information. At present, for tests that require multi-vehicle collaborative testing (such as AEB tests, Cut-in tests, and ACC tests), the usual practice is to arrange communication equipment on the vehicles that communicate with each other, and to equip each vehicle with a dedicated person to communicate information. This approach is generally not suitable for information coordination of more than three vehicles, and equipment and personnel will be added to each vehicle, resulting in changes in the load on the vehicle, etc., and tests with high requirements for load, electromagnetics, etc. cannot meet the test standards. Thirdly, existing test vehicles, especially autonomous driving test vehicles, often need to be inspected for performance in bad weather and extreme environments, but existing measurement systems are usually unable to or do not consider working in bad environments such as thunderstorms, cloudy days, low temperatures, strong backlight, etc. Therefore, it is urgent to ensure that the measurement system can be used normally in the above environments and achieve stable positioning and communication all day and all day. In addition, the test site usually has rain shelter equipment, which requires ash holes, mud, and salinity tests, so there are generally metal awnings. At present, the single-vehicle on-board measurement system cannot achieve accurate and stable positioning under the awning; and the single platform or sensor vehicle-side positioning has limited positioning capabilities and cannot achieve stable and reliable positioning. At the same time, in terms of computing power, the existing single-vehicle test system is limited by the computing processing power and on-board power of the single vehicle, making it difficult to synchronously track and monitor the vehicle's operating status, and difficult to make timely diagnosis of the vehicle's health status, resulting in large mileage deviations in confirming test failure events, and difficulty in timely detection of early failure signs and early failure events. Summary of the invention

[0004] In order to solve at least one aspect of the above problems, the present invention provides a vehicle test field measurement system, including: a vehicle end, a field end and a back end, the vehicle end includes a vehicle-mounted positioning module and a vehicle-mounted communication module, and the vehicle-mounted positioning module outputs the vehicle self-positioning information through the vehicle-mounted communication module; the field end includes multiple groups of positioning components, and the multiple groups of positioning components are respectively arranged at multiple preset positions of the test field, and each group of the multiple groups of positioning components includes a base, a capture positioning module, an edge computing module and a communication module, the base includes a fixed base and a mounting bracket, the capture positioning module, the edge computing module and the communication module are respectively fixedly connected to the mounting bracket, and the capture positioning module includes an image positioning unit, an ultra-wideband positioning unit, a laser radar positioning unit, a millimeter wave Radar positioning unit, pseudo-satellite base station positioning unit, the capture and positioning module is used to output the field-side positioning information obtained by the image positioning unit, the ultra-wideband positioning unit, the laser radar positioning unit, the millimeter-wave radar positioning unit, and the pseudo-satellite base station positioning unit, the edge computing module obtains the preset weight coefficient based on the environmental parameters, and the preset weight coefficient corresponds one-to-one with the field-side positioning information output by the capture and positioning module, and the edge computing module uses the extended Kalman filtering method to determine the vehicle capture positioning information based on the preset weight coefficient and the field-side positioning information; the back end is respectively communicated with the vehicle end and multiple groups of the positioning components, and the back end is used to output test instructions, and the back end evaluates the vehicle-mounted positioning module according to the vehicle capture positioning information and the vehicle self-positioning information.

[0005] Preferably, the image positioning unit comprises a first image collector and a second image collector, and the first image collector and the second image collector are respectively arranged at a first height and a second height of the mounting bracket.

[0006] Preferably, the field end also includes an auxiliary positioning component, which includes an aircraft, the capture and positioning module, the edge computing module and the communication unit. The capture and positioning module, the edge computing module and the communication module are respectively fixedly connected to the aircraft or connected through a controlled gimbal.

[0007] Preferably, the aircraft is started in response to an auxiliary positioning instruction output by the back end, and the auxiliary positioning instruction includes preset trajectory information of the aircraft.

[0008] Preferably, the image positioning unit collects field-end images, and identifies the oil leakage status and vehicle body appearance status of the vehicle based on the field-end images.

[0009] Preferably, the edge computing module receives the field-end image through the image positioning unit, the edge computing module determines environmental parameters based on the field-end image, and adjusts the preset weight coefficient based on the environmental parameters.

[0010] Preferably, the edge computing module calculates the vehicle capture speed based on the vehicle capture positioning information.

[0011] Preferably, the field-side positioning information also includes field-side obstacle position information and field-side obstacle classification information.

[0012] The vehicle test field measurement system of the embodiment of the present invention has the following beneficial effects: by building a vehicle-field-backstage measurement system of the automobile test field, the cost of single-vehicle intelligent positioning can be reduced, and reliable, stable and high-precision positioning can be achieved around the clock through multi-modal (image, sound, radar) sensor fusion positioning, while improving test efficiency and reducing test risks; by using appropriate sensors installed in appropriate locations, the health status of running vehicles can be monitored, and global monitoring and measurement of the vehicle operating status can be performed in the background, which can effectively improve the operating efficiency and safety of the test field. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In order to better understand the above and other purposes, features, advantages and functions of the present invention, reference may be made to the embodiments shown in the accompanying drawings. The same reference numerals in the accompanying drawings refer to the same components. It should be understood by those skilled in the art that the accompanying drawings are intended to schematically illustrate the preferred embodiments of the present invention and have no limiting effect on the scope of the present invention, and the components in the drawings are not drawn to scale.

[0014] Figure 1 A structural block diagram of a vehicle test field measurement system according to an embodiment of the present invention is shown;

[0015] Figure 2 A schematic structural diagram of a positioning component of a vehicle proving ground measurement system according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0016] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0017] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0018] In order to at least partially solve one or more of the above-mentioned problems and other potential problems, an embodiment of the present disclosure proposes a vehicle test field measurement system, including: a vehicle end, a field end and a back end, the vehicle end includes a vehicle-mounted positioning module and a vehicle-mounted communication module, and the vehicle-mounted positioning module outputs vehicle self-positioning information through the vehicle-mounted communication module; the field end includes multiple groups of positioning components, and the multiple groups of positioning components are respectively arranged at multiple preset positions of the test field, each group of positioning components in the multiple groups of positioning components includes a base, a capture positioning module, an edge computing module and a communication module, the base includes a fixed base and a mounting bracket, the capture positioning module, the edge computing module and the communication module are respectively fixedly connected to the mounting bracket, and the capture positioning module includes an image positioning unit, an ultra-wideband positioning unit , laser radar positioning unit, millimeter wave radar positioning unit, pseudo satellite base station positioning unit, the capture and positioning module is used to output the field positioning information obtained by the image positioning unit, ultra-wideband positioning unit, laser radar positioning unit, millimeter wave radar positioning unit, and pseudo satellite base station positioning unit, the edge computing module obtains the preset weight coefficients based on the environmental parameters, and the preset weight coefficients correspond one by one to the field positioning information output by the capture and positioning module, and the edge computing module uses the extended Kalman filtering method to determine the vehicle capture positioning information based on the preset weight coefficients and the field positioning information; the back end is respectively communicated with the vehicle end and multiple groups of positioning components, the back end is used to output test instructions, and the back end evaluates the vehicle-mounted positioning module according to the vehicle capture positioning information and the vehicle self-positioning information.

[0019] Specifically, Figure 1As shown, the vehicle end is the on-board equipment and processing system of the test vehicle on the test field. The number of test vehicles running on the test field is determined according to the test requirements and the capacity of the test field, including one, two or more. Each test vehicle on the test field is equipped with the vehicle end of the vehicle test field measurement system. Among them, the vehicle-mounted positioning module adopts GNSS or a combination of GNSS and INS or other positioning methods such as radio. This module can realize self-positioning of the vehicle and send the vehicle self-positioning information to the vehicle-mounted communication module. The vehicle-mounted communication module is a T-BOX (Telematic-BOX) or OBU (On Board Unit) or other communication components. It has two main functions: on the one hand, it receives information from the vehicle-mounted positioning module and the vehicle bus, and sends the information to the field end; on the other hand, it can receive instructions from the field end or the back end, and send the instructions to the vehicle-end system so that the test vehicle completes the corresponding action.

[0020] The multiple groups of positioning components at the field end are respectively set at multiple preset positions of the test field, and the multiple groups of positioning components adopt the same configuration. The multiple preset positions can be determined according to specific test requirements, and the multiple groups of positioning components are respectively fixed at the corresponding preset positions through their respective bases.

[0021] like Figure 2 As shown, the fixed base of the base is used to fix the positioning component on the test field so that the positioning component remains stable during the vehicle test, and the mounting bracket is used to fix the capture positioning module and the communication module. The fixed base and the mounting bracket have sufficient rigidity to ensure that the dynamic deviation of the reference position of the capture positioning module, the edge computing module and the communication module is controllable. Each base has precise positioning information. The preset position corresponding to each base has a precise positioning target, so that each positioning unit of the capture positioning module can be accurately positioned again relative to the positioning information of the base.

[0022] The image positioning unit includes a camera, and the camera (CAM) is used to collect site images and use existing image recognition technology to determine the position information of the test vehicle relative to the base, and determine the image capture positioning information of the test vehicle based on the positioning information of the base.

[0023] The ultra-wideband positioning unit uses ultra-high precision wireless positioning technology UWB (ultra-wideband). The UWB is installed on the mounting bracket of the base. Each UWB communicates with the vehicle to obtain the distance information from the vehicle. The test vehicle can be positioned through multiple UWBs of multiple positioning components. The ultra-wideband positioning unit outputs ultra-wideband capture positioning information. Because UWB has the advantages of strong penetration, low power consumption, good anti-multipath effect, high security, and can provide precise positioning accuracy, it can provide reliable and stable positioning in strong backlight, cloudy days, thunderstorms, heavy fog, obstructions or tunnels.

[0024] The LiDAR positioning unit uses LiDAR technology to install the LiDAR on the mounting bracket of the base. The LiDAR obtains the outline information of the test vehicle, as well as the distance and position information between the LiDAR and the test vehicle, and further outputs the positioning information captured by the LiDAR of the test vehicle in combination with the positioning information of the base. On the other hand, the LiDAR positioning unit can distinguish whether it is a vehicle, a person, an animal or a pile barrel within the monitoring range, and realizes classified positioning. Compared with the camera, the LiDAR can directly obtain the distance and position information between the LiDAR and the detected object.

[0025] The pseudo-satellite base station positioning unit includes a pseudo-satellite base station system (pGNSS) and a field-side communication module. The pseudo-satellite base station system broadcasts navigation message signals with the precise coordinates of the base station antenna itself to the test area. The test vehicle determines the positioning information of the test vehicle through the collected navigation message signals. For example, the GNSS system of the test vehicle determines the relative position of the test vehicle by receiving the navigation message signal, and further determines the positioning information of the test vehicle in combination with the coordinate information of the base. The test vehicle outputs the positioning information through the on-board communication module as pseudo-satellite base station capture positioning information, which is received by the field-side communication module and transmitted to the edge computing module. Moreover, the navigation message broadcasting of the precise position coordinates by the pseudo-satellite base station can enhance the positioning accuracy of the vehicle-side GNSS system and improve the positioning accuracy in severe weather.

[0026] The millimeter wave radar positioning unit uses millimeter wave radar positioning technology to install the millimeter wave radar (MRR) on the mounting bracket of the fixed base. The millimeter wave radar positioning unit can obtain information such as the distance, speed and posture of the test vehicle. Combined with the positioning information of the base, the millimeter wave radar capture positioning information of the test vehicle can be further determined. Since the millimeter wave radar has a strong ability to penetrate fog, smoke and dust, it has the characteristics of working all day and all weather (except heavy rainy days), and can be used in severe weather such as thunderstorms, cloudy days, and heavy fog.

[0027] The edge computing module is ECM (Edge Computing Machine), and its main functions are: calculating the data obtained by the perception sensor and sending it through the field communication module; calculating the data received by the field communication module, which includes vehicle-side data and back-end data; and receiving data from other ECMs.

[0028] The edge computing module obtains the field-side positioning information from the image positioning unit, the ultra-wideband positioning unit, the laser radar positioning unit, the millimeter-wave radar positioning unit, and the pseudo-satellite base station positioning unit respectively. The field-side positioning information includes the image capture positioning information, ultra-wideband capture positioning information, laser radar capture positioning information, millimeter-wave radar capture positioning information, and pseudo-satellite base station capture positioning information output by each positioning unit. The edge computing module obtains the preset weight coefficient based on the environmental parameters. For example, the preset weight coefficient includes k1, k2, k3, k4, and k5. The weight coefficient corresponding to the image capture positioning information is k1, the weight coefficient corresponding to the ultra-wideband capture positioning information is k2, the weight coefficient corresponding to the laser radar capture positioning information is k3, the weight coefficient corresponding to the millimeter-wave radar capture positioning information is k4, and the weight coefficient corresponding to the pseudo-satellite base station capture positioning information is k5. The edge computing module uses the extended Kalman filter method to determine the vehicle capture positioning information based on the preset weight coefficient and each field-side positioning information.

[0029] The edge computing module includes multiple sets of preset weight coefficients, which correspond to different environmental parameters. For example, the environmental parameters include sunny days, cloudy days, fog, haze, thunderstorms, heavy rain, snowy days, etc., and each environmental parameter corresponds to a set of preset weight coefficients. It can be understood by those skilled in the art that due to the different characteristics and applicable scenarios of the above-mentioned sensors such as cameras, lidars and millimeter-wave radars, the accuracy of the positioning information of the test vehicle output by them in different scenarios will be deviated. Therefore, in the strong backlight scene in the early morning of winter, the ultra-wideband positioning unit, the millimeter-wave radar positioning unit, and the pseudo-satellite base station positioning unit are usually given higher weight coefficients (that is, k2, k4, and k5 are all greater than k1 and k3), and in the scene with strong snow and fog, the millimeter-wave radar positioning unit will be given a higher weight coefficient (that is, k4 is greater than k1, k2, k3, and k5). In some embodiments, the edge computing module obtains environmental parameters through the field end and determines the corresponding preset weight coefficients based on the environmental parameters.

[0030] The preset weight coefficients are obtained by calibration, that is, the preset weight coefficients are calibrated under the outdoor weather conditions corresponding to the environmental parameters. In another embodiment, in order to quickly obtain the sensor weight coefficients, the default weight coefficients under standard scenes (such as thunderstorms, strong backlight, foggy days, etc.) are first calibrated, and in actual use, the weight coefficients are first set to the default weight coefficients under the standard scene, and then the online perturbation optimization method is used to quickly obtain the better weight coefficients in actual use, so as to ensure that the system can output more accurate position accuracy in various application environments.

[0031] The communication module at the field end is usually a road side unit (RSU) or other communication modules with equivalent functions to achieve communication with the vehicle end and the back end.

[0032] The backend is the background control system of the test field. The backend is connected to the test vehicle in communication, and the backend is connected to each positioning component of the field end in communication. The backend controls the test vehicle to perform the test operation by outputting the test instruction. In some embodiments, the backend outputs the test instruction through the field end, and the backend determines the instruction transfer positioning component based on the captured positioning information of the test vehicle obtained through the field end. The instruction transfer positioning component is the positioning device whose coordinates are closest to the test vehicle among the multiple positioning components of the field end. The backend outputs the test instruction through the instruction transfer positioning component, and the test instruction is used to control the test vehicle to perform the test operation.

[0033] The back end receives the vehicle self-positioning information through the test vehicle, and the back end receives the vehicle capture positioning information corresponding to the test vehicle through the field end. The back end evaluates the positioning status of the on-board positioning module based on the deviation between the vehicle self-positioning information and the vehicle capture positioning information. When the deviation between the vehicle self-positioning information and the vehicle capture positioning information is within the preset distance threshold, the on-board positioning module is in a normal state; when the deviation between the vehicle self-positioning information and the vehicle capture positioning information is greater than the preset distance threshold, the on-board positioning module is in an abnormal state. In the positioning function test, the on-board positioning module of the test vehicle can be evaluated through the back end all day and all weather to verify the positioning function of the on-board positioning module of the test vehicle; on the other hand, the abnormal function status of the on-board positioning module of the test vehicle under extreme weather conditions can be timely warned. By setting up a positioning component on the field end, the on-board load of the test vehicle can be reduced.

[0034] like Figure 1 As shown, the vehicle side, the field side and the back end are connected through a communication link, wherein the communication link between the vehicle side and the field side is a wireless link, including but not limited to wireless links such as PC5, Wifi, 5G, etc.; the communication link between the field side and the back end can be a wired link or a wireless link; the vehicle side and the back end can be connected through a wireless link, including but not limited to wireless links such as 5g; no matter what form of communication, the information transmission requirements must be guaranteed first. The working mode of the field side true value measurement system of the entire test field is as follows: the vehicle side collects the vehicle position, speed, and posture information, and sends the information to the field side or the end through the vehicle-mounted communication module, and the system is composed of a lightweight sensor group and a communication module; at the same time, the vehicle side can receive command information from the field side or the back end and complete the corresponding action. The field side system has a built-in edge computing system, which uses multi-modal (such as image, radio, laser, sound, vibration, etc.) sensor fusion technology to perform stable, reliable, all-weather, high-precision positioning of the vehicle, and also has the function of vehicle health monitoring. The back end receives data from the field side and the vehicle side, performs data calculation, and has monitoring, management, and overall scheduling functions.

[0035] In some embodiments, the image positioning unit includes a first image collector and a second image collector, and the first image collector and the second image collector are respectively arranged at a first height and a second height of the mounting bracket.

[0036] Specifically, the first image collector and the second image collector are cameras, which are respectively arranged at different heights of the mounting bracket. For example, the first height of the mounting bracket is 5-8m, and the second height of the mounting bracket is greater than 10m. Different effects can be achieved by installing the cameras at different positions. For example, Figure 2 As shown in CAM1, the camera is installed at a lower position, usually at a height of 5-8m, which can distinguish vehicles, people, animals or pile barrels within the monitoring range to achieve classification and positioning; Figure 2 As shown in CAM2, the camera is installed at a higher position, usually at a height of more than 10m, to achieve a larger monitoring range, and multiple groups of such cameras are used to monitor the entire field. On the other hand, by installing cameras at the curbs on both sides, the road surface of the test field can be photographed, and the health status of the vehicle can be judged by whether there is oil leakage on the road surface, or the appearance of the vehicle body can be photographed to determine whether there are safety hazards.

[0037] In some embodiments, the field end also includes an auxiliary positioning component, which includes an aircraft, a capture and positioning module, an edge computing module and a communication unit. The capture and positioning module, the edge computing module and the communication module are respectively fixedly connected to the aircraft.

[0038] Specifically, the auxiliary positioning component is connected to the vehicle end and the rear end respectively through the communication unit, and the capture and positioning module of the auxiliary positioning component includes an image positioning unit, an ultra-wideband positioning unit, a laser radar positioning unit, a millimeter-wave radar positioning unit, and a pseudo-satellite base station positioning unit. The capture and positioning module is used to output the field-side positioning information obtained by the image positioning unit, the ultra-wideband positioning unit, the laser radar positioning unit, the millimeter-wave radar positioning unit, and the pseudo-satellite base station positioning unit. The edge computing module of the auxiliary positioning component obtains a preset weight coefficient based on environmental parameters, and the preset weight coefficient corresponds to the field-side positioning information output by the capture and positioning module. The edge computing module uses an extended Kalman filtering method to determine the vehicle capture and positioning information based on the preset weight coefficient and the field-side positioning information. In another embodiment, the capture and positioning module, the edge computing module, and the communication module are connected to the aircraft separately or through a controlled gimbal.

[0039] Uninterrupted positioning services are provided through auxiliary positioning components. The auxiliary positioning components do not require fixed poles (light poles, etc.) on the roadside or facilities specifically used to place sensor modules and communication modules, which is conducive to the promotion and use of this method in public road tests.

[0040] In some embodiments, the aircraft is started in response to an auxiliary positioning instruction output by a rear end, and the auxiliary positioning instruction includes preset trajectory information of the aircraft.

[0041] Specifically, the aircraft is connected to a back end for communication, and receives auxiliary positioning instructions through the back end. The aircraft executes flight based on a preset trajectory in response to the received auxiliary positioning instructions.

[0042] In some embodiments, the image positioning unit collects field-end images and identifies the oil leakage status and vehicle body appearance status of the vehicle based on the field-end images.

[0043] Specifically, the image positioning unit includes an image processor, the field end image includes the vehicle body and the test field ground, and the image processor uses image recognition technology to identify the vehicle oil leakage status and vehicle body appearance status based on the field end image. This enables monitoring of the vehicle health status. The back end receives the vehicle health status through the field end to monitor the health status of multiple test vehicles in the test field.

[0044] In some embodiments, the edge computing module receives the field-end image through the image positioning unit, the edge computing module determines the environmental parameters based on the field-end image, and adjusts the preset weight coefficient based on the environmental parameters.

[0045] Specifically, the edge computing module also includes an environmental parameter model, which is obtained by training based on environmental image samples, for example, by extracting pixel features in image samples corresponding to each environmental parameter for training. The edge computing module uses the environmental parameter model to determine environmental parameters based on the field-side image, and further selects a corresponding preset weight coefficient from multiple groups of preset weight coefficients of the edge computing module based on the environmental parameters.

[0046] In other embodiments, the edge computing module obtains preset weight coefficients based on environmental parameters input by the user through the back end. In other embodiments, the edge computing module includes multiple sets of preset weight coefficients. The edge computing module receives environmental parameters through the back end and determines the corresponding preset weight coefficients based on the environmental parameters. In some other embodiments, the back end includes a preset weight coefficient, and the back end outputs the corresponding preset weight coefficient based on the environmental parameters input by the user, and the edge computing module receives the preset weight coefficient through the back end.

[0047] In some embodiments, the edge computing module calculates the vehicle capture speed based on the vehicle capture positioning information.

[0048] Specifically, the edge computing module calculates the vehicle capture speed through the time domain distribution of the vehicle capture positioning information. That is, the vehicle travel distance is determined by two adjacent vehicle capture positioning information, and the vehicle travel time is determined according to the time interval of two adjacent vehicle capture positioning information, thereby calculating the vehicle capture speed.

[0049] In some embodiments, the field-side positioning information also includes field-side obstacle location information and field-side obstacle classification information.

[0050] Specifically, the edge computing module obtains the field-side image captured by the camera through the image positioning unit, and identifies the field-side obstacles and the location information of the field-side obstacles based on the field-side image.

[0051] The embodiments of the present disclosure have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The selection of terms used herein is intended to best explain the principles of the embodiments, practical applications, or technical improvements in the market, or to enable other persons of ordinary skill in the art to understand the present invention.

Claims

1. A vehicle testing field measurement system, characterized in that: include: The vehicle end includes a vehicle positioning module and a vehicle communication module, and the vehicle positioning module outputs vehicle self-positioning information through the vehicle communication module; A field end, wherein the field end includes a plurality of positioning components, and the plurality of positioning components are respectively arranged at a plurality of preset positions of the test field, each of the plurality of positioning components includes a base, a capture positioning module, an edge computing module and a communication module, the base includes a fixed base and a mounting bracket, the capture positioning module, the edge computing module and the communication module are respectively fixedly connected to the mounting bracket, the capture positioning module includes an image positioning unit, an ultra-wideband positioning unit, a laser radar positioning unit, a millimeter wave radar positioning unit, and a pseudo-satellite base station positioning unit, the capture positioning module is used to output the field end positioning information acquired by the image positioning unit, the ultra-wideband positioning unit, the laser radar positioning unit, the millimeter wave radar positioning unit, and the pseudo-satellite base station positioning unit, the edge computing module acquires a preset weight coefficient based on environmental parameters, the preset weight coefficients respectively correspond to the field end positioning information output by the capture positioning module, and the edge computing module uses an extended Kalman filtering method to determine the vehicle capture positioning information based on the preset weight coefficient and the field end positioning information; The back end is respectively connected to the vehicle end and multiple groups of the positioning components for communication, and the back end is used to output test instructions. The back end evaluates the vehicle-mounted positioning module according to the vehicle-captured positioning information and the vehicle-self-positioning information.

2. The system according to claim 1, characterized in that The image positioning unit includes a first image collector and a second image collector, and the first image collector and the second image collector are respectively arranged at a first height and a second height of the mounting bracket.

3. The system according to claim 2, characterized in that The field end also includes an auxiliary positioning component, which includes an aircraft, the capture and positioning module, the edge computing module and the communication unit. The capture and positioning module, the edge computing module and the communication module are respectively fixedly connected to the aircraft.

4. The system according to claim 3, characterized in that The aircraft is started in response to an auxiliary positioning instruction output by the back end, and the auxiliary positioning instruction includes preset trajectory information of the aircraft.

5. The system according to claim 4, characterized in that The image positioning unit collects field-end images and identifies the oil leakage state and vehicle body appearance state of the vehicle based on the field-end images.

6. The system according to claim 5, characterized in that The edge computing module receives the field-end image through the image positioning unit, determines environmental parameters based on the field-end image, and adjusts the preset weight coefficient based on the environmental parameters.

7. The system according to claim 6, characterized in that The edge computing module determines the vehicle capture speed and the vehicle capture posture based on the field end positioning information.

8. The system according to claim 1, characterized in that The field-side positioning information also includes field-side obstacle position information and field-side obstacle classification information.

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