Automatic emergency braking system key parameter verification method based on miniature sand table experiment platform

Abstract

The invention provides an automatic emergency braking system key parameter verification method based on a miniature sand table experiment platform. The automatic emergency braking system key parameter verification method comprises the steps that to-be-verified key parameters of an automatic emergency braking system and a vehicle control instruction are determined; the to-be-verified key parameter comprises any one of communication delay, communication packet loss rate, image resolution and perception precision; based on the miniature sand table experiment platform, according to the to-be-verified key parameters and the vehicle control instruction, controlling the miniature vehicle to perform simulated driving in the sand table platform, and obtaining actual driving data of the miniature vehicle in the simulated driving process; obtaining a verification result of the to-be-verified key parameter based on the actual driving data and pre-stored simulation driving data; wherein the actual driving data comprises the collision time of the miniature vehicle and the front obstacle. According to the method, the key parameters of the automatic emergency braking system are verified through the miniature sand table experiment platform, and accurate, safe and efficient verification of the key parameters of the automatic emergency braking system is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle testing, and in particular to a key parameter verification method of an automatic emergency braking system based on a miniature sandbox experimental platform. Background Art

[0002] As a key component of advanced driver assistance systems (ADAS), the Autonomous Emergency Braking system (AEB) is designed to reduce the occurrence of traffic accidents or mitigate their severity by detecting obstacles ahead and automatically applying braking force in the event of a potential collision.

[0003] In order to ensure the reliability and effectiveness of the AEB system, it must be rigorously tested and verified in a variety of actual traffic scenarios. Although existing technologies provide a series of safety performance requirements and test methods such as simulation tests and real vehicle road tests, they fail to provide specific reference values ​​or optimization suggestions for the key indicator parameters of the data processing module in the automatic emergency braking system. This means that when manufacturers develop new automatic emergency braking systems, they need to design and implement a series of complex experiments to test and verify the optimal configuration of these key parameters to ensure the efficient operation of the system.

[0004] However, the existing test verification process is not only costly but also slow to iterate, and cannot meet the needs of the rapidly developing automotive industry for new automatic emergency braking systems. In addition, due to the lack of standardized guidelines, different manufacturers may adopt different test verification strategies, which may lead to uneven performance of products on the market and affect the overall level of road traffic safety.

[0005] Therefore, how to solve the problems of high cost, high safety risk and limitations of existing automatic emergency braking system key parameter verification methods is an important issue that needs to be urgently solved in the field of vehicle testing. Summary of the invention

[0006] The present invention provides a key parameter verification method for an automatic emergency braking system based on a miniature sandbox experimental platform, so as to overcome the defects of the existing key parameter verification method for an automatic emergency braking system, such as high cost, high safety risk and limitations, and realize accurate, safe and efficient verification of the key parameters of the automatic emergency braking system.

[0007] On the one hand, the present invention provides a method for verifying key parameters of an automatic emergency braking system based on a scaled sand table experiment platform. The scaled sand table experiment platform includes scaled vehicles and a sand table platform, and is connected to the automatic emergency braking system through a wireless communication network. The method includes: determining the key parameters to be verified of the automatic emergency braking system and vehicle control instructions; wherein, the key parameters to be verified include any one of communication delay, communication packet loss rate, image resolution, and perception accuracy; based on the scaled sand table experiment platform, according to the key parameters to be verified and vehicle control instructions, controlling the scaled vehicle to perform simulated driving on the sand table platform, and obtaining the actual driving data of the scaled vehicle during the simulated driving; based on the actual driving data and pre-stored simulation driving data, obtaining the verification result of the key parameters to be verified; wherein, the actual driving data includes the collision time between the scaled vehicle and the obstacle in front, and the simulation driving data includes the simulated collision time between the scaled vehicle and the obstacle in front.

[0008] Further, the determining the key parameters to be verified of the automatic emergency braking system and vehicle control instructions includes: obtaining the current operating state information and environmental state information of the scaled vehicle in the scaled sand table experiment platform; generating vehicle control instructions according to the current operating state information and environmental state information of the scaled vehicle; wherein, the current operating state information includes pose information and speed information; the environmental state information includes traffic signal state information, street lamp state information, and lifting rod state information; the vehicle control instructions include the expected turning angle and expected speed of the scaled vehicle.

[0009] It is characterized in that one or more scaled vehicles are included in the scaled sand table experiment platform, and the scaled vehicles are distinguished by different color block designs; correspondingly, the step of obtaining the current operating state information of the scaled vehicle in the scaled sand table experiment platform specifically includes: obtaining the global image of the sand table platform and the scaled vehicle; performing color space conversion on the global image to obtain an HSV image; performing binaryzation according to the H value of the pixel points in the HSV image to obtain an initial binaryzation image; performing convex polygon fitting on the initial binaryzation image and calculating the minimum bounding rectangle of the convex polygon; in the case where the aspect ratio of the minimum bounding rectangle is within a set interval and the area of the minimum bounding rectangle is greater than a set area, taking the minimum bounding rectangle as the color block area on the top of the scaled vehicle to obtain the pose information of the scaled vehicle, and the pose information includes the position of the scaled vehicle.

[0010] Further, the step of obtaining the current operating state information of the scaled vehicle in the scaled sand table experiment platform specifically includes: obtaining the position of the scaled vehicle in adjacent frame global images; performing differential processing on the positions of the scaled vehicle in adjacent frame global images to obtain the change in the center point coordinates of the scaled vehicle; obtaining the speed information of the scaled vehicle according to the change in the center point coordinates of the scaled vehicle.

[0011] Further, obtaining the verification result of the to-be-verified key parameter based on the actual driving data and the pre-stored simulated driving data includes: when the difference between the collision time and the simulated collision time is less than or equal to a set threshold, determining the verification result of the to-be-verified key parameter as qualified; when the difference between the collision time and the simulated collision time is greater than the set threshold, determining the verification result of the to-be-verified key parameter as unqualified.

[0012] Further, the step of obtaining the actual driving data of the scaled vehicle during the simulated driving process specifically includes: using a camera configured on the scaled vehicle to obtain a target image in front of the scaled vehicle; performing target detection on the target image to obtain the upper and lower limits of the abscissa and the upper and lower limits of the ordinate of the front obstacle in the target image; calculating the relative distance from the front obstacle to the camera according to the height, downward deflection angle, and focal length of the camera that captured the target image, as well as the upper and lower limits of the abscissa and the upper and lower limits of the ordinate; calculating the collision time according to the relative distance and the relative speed between the front obstacle and the scaled vehicle in the current operating state to obtain the actual driving data.

[0013] Further, after obtaining the actual driving data of the scaled vehicle during the simulated driving process, it includes: when the collision time is less than the first set threshold and greater than or equal to the second set threshold, sending a first prompt message for warning danger to the scaled vehicle; when the collision time is less than the second set threshold and greater than or equal to the third set threshold, sending a second prompt message for partial braking to the scaled vehicle; when the collision time is less than the third set threshold, sending a third prompt message for full braking to the scaled vehicle.

[0014] Second aspect, the present invention further provides a device for verifying key parameters of an automatic emergency braking system based on a scaled-down sand table experiment platform. The scaled-down sand table experiment platform includes a scaled-down vehicle and a sand table platform, and is connected to the automatic emergency braking system through a wireless communication network. The device includes: a key parameter to be verified and vehicle control instruction determination module, configured to determine the key parameter to be verified of the automatic emergency braking system and the vehicle control instruction; wherein, the key parameter to be verified includes any one of communication delay, communication packet loss rate, image resolution, and perception accuracy; a simulated driving module of the scaled-down vehicle in the scaled-down sand table experiment platform, configured to control the scaled-down vehicle to perform simulated driving on the sand table platform based on the scaled-down sand table experiment platform, according to the key parameter to be verified and the vehicle control instruction, and obtain the actual driving data of the scaled-down vehicle during the simulated driving; a verification result acquisition module for the key parameter to be verified, configured to obtain the verification result of the key parameter to be verified based on the actual driving data and the pre-stored simulated driving data; wherein, the actual driving data includes the collision time between the scaled-down vehicle and the obstacle in front, and the simulated driving data includes the simulated collision time between the scaled-down vehicle and the obstacle in front.

[0015] Third aspect, an automatic emergency braking system key parameter verification system based on a scaled-down sand table experiment platform includes: a scaled-down sand table experiment platform, including a physical sand table platform in the physical space and a twin sand table platform in the information space; wherein, the physical sand table platform includes a scaled-down vehicle and a sand table platform, and the sand table platform includes a structured road, a variety of roadside devices, and a workstation; the twin sand table platform is obtained by reconstructing the scene through three-dimensional modeling based on the physical sand table platform, and is used to reflect the real-time operation state of the physical sand table platform; a computing server, including an automatic emergency braking system control unit, wirelessly connected to the scaled-down sand table experiment platform, and configured to execute the method for verifying key parameters of the automatic emergency braking system based on the scaled-down sand table experiment platform as described above.

[0016] Fourth aspect, the present invention further provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the method for verifying key parameters of the automatic emergency braking system based on the scaled-down sand table experiment platform as described in any one of the above.

[0017] The method for verifying key parameters of an automatic emergency braking system based on a micro - scale sand table experimental platform provided by the present invention determines the key parameters to be verified of the automatic emergency braking system and vehicle control instructions; among them, the key parameters to be verified include any one of communication delay, communication packet loss rate, image resolution, and perception accuracy; based on the micro - scale sand table experimental platform, according to the key parameters to be verified and vehicle control instructions, the micro - scale vehicle is controlled to perform simulated driving on the sand table platform, and the actual driving data of the micro - scale vehicle during the simulated driving process is collected; based on the actual driving data and pre - stored simulation driving data, the verification result of the key parameters to be verified is obtained; among them, the actual driving data includes the collision time between the micro - scale vehicle and the obstacle in front, and the simulation driving data includes the simulated collision time between the micro - scale vehicle and the obstacle in front. This method realizes accurate, safe, and efficient verification of the key parameters of the automatic emergency braking system by using the micro - scale sand table experimental platform for verifying the key parameters of the automatic emergency braking system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0019] Figure 1 It is a system schematic diagram of a system for verifying key parameters of an automatic emergency braking system based on a micro - scale sand table experimental platform provided by an embodiment of the present invention.

[0020] Figure 2 It is a flowchart of a method for verifying key parameters of an automatic emergency braking system based on a micro - scale sand table experimental platform provided by an embodiment of the present invention.

[0021] Figure 3 It is a structural schematic diagram of a device for verifying key parameters of an automatic emergency braking system based on a micro - scale sand table experimental platform provided by an embodiment of the present invention.

[0022] Figure 4 It is a physical structure schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0023] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0024] It is easy to understand that before elaborating on the method for verifying key parameters of the automatic emergency braking system based on the scaled-down sand table experimental platform provided by the embodiments of the present invention, a verification system for implementing this verification method is first described herein.

[0025] Figure 1 Fig. shows a system schematic diagram of a verification system for key parameters of an automatic emergency braking system based on a scaled-down sand table experimental platform provided by an embodiment of the present invention.

[0026] As Figure 1 shown, the system includes: a scaled-down sand table experimental platform, including a physical sand table platform in the physical space and a twin sand table platform in the information space; wherein, the physical sand table platform includes a scaled-down vehicle and a sand table platform, and the sand table platform includes a structured road, a variety of roadside devices, multiple cameras, and a workstation; the twin sand table platform is obtained by reconstructing the scene through three-dimensional modeling based on the physical sand table platform, and is used to reflect the real-time operating state of the physical sand table platform; a computing server, including an automatic emergency braking system control unit, wirelessly connected to the scaled-down sand table experimental platform, and used to execute the method for verifying key parameters of the automatic emergency braking system based on the scaled-down sand table experimental platform.

[0027] Specifically, the scaled-down sand table test platform consists of a physical sand table platform in the physical space and a twin sand table platform in the information space. The physical sand table platform in the physical space is mainly composed of a structured road, roadside devices, a workstation, and a scaled-down vehicle. Among them, the roadside devices and the scaled-down vehicle are the main traffic elements considered.

[0028] The roadside devices all belong to information unidirectional transmission devices, mainly including street lights, traffic lights, parking lot lifting rods, and cameras with full-area coverage. They are connected to the workstation through wired or serial ports. The workstation can adjust the states of roadside devices such as street lights, traffic lights, and parking lot lifting rods through serial communication. In addition, through wired connection, the workstation can read images taken by the global cameras at a rate not lower than 10 fps, and then calculate relevant state information of the scaled-down vehicle based on the images.

[0029] In a specific embodiment, the sand table includes typical and rich road scenes such as intersections, roundabouts, parking lots, and bus stops, and can be used to simulate various typical urban traffic scenes. Among them, the length of the sand table is 9 m, the width is 5 m, the sand table road is composed of strictly structured roads, the single-lane width is 240 mm, and there are road structures such as two-way four-lane and two-way two-lane. The road yellow lines and green belts restrict the driving direction, and it is stipulated that the counterclockwise direction outside the yellow line near the edge of the sand table is the driving direction.

[0030] Meanwhile, 11 traffic lights and 73 street lights are deployed on the side of the sand table road, and 3 motor-controlled lifting rods are deployed at the entrance of the parking lot and on the green belt on the side of the center line parallel to the short axis. The traffic lights, street lights, and lifting rods communicate with the workstation responsible for overall information through serial ports. The workstation can change the real-time start and stop status by issuing serial port instructions, and each device can be independently controlled.

[0031] Four cameras are deployed on the ceiling about 2.1m above the sand table plane. They are connected to the workstation through USB cables, achieving full coverage of the observation of the sand table plane. Among them, there is a certain overlapping area between each camera, and the width of the overlapping area is greater than or equal to the vehicle length. This deployment method ensures that the vehicle can be seamlessly detected even when crossing the camera boundary during driving.

[0032] The miniature vehicle belongs to the type of device with two-way information transmission. It is connected to the workstation through a local wireless network. The miniature vehicle can convert its own real-time motor speed into real-time speed and actively report it to the workstation; the workstation monitors the real-time running status of the miniature vehicle and sends the desired front wheel angle and desired vehicle speed to the miniature vehicle. Under the condition of not exceeding the allowed threshold range, the miniature vehicle can quickly complete the response.

[0033] In a specific embodiment, the miniature vehicle adopted in this embodiment weighs 1.4 kg, and its length, width, and height are 200 mm, 180 mm, and 130 mm respectively. The wheelbase is 140 mm, and the wheel diameter is 60 mm. The miniature vehicle is equipped with a camera with a resolution of 640×480 and a single-line lidar. In addition, the miniature vehicle is also equipped with an IMU (Inertial Measurement Unit).

[0034] The miniature vehicle communicates with the sand table workstation through a local wireless network, obtains the motor speed, converts it into the real-time speed of the miniature vehicle and reports it. Generally, the maximum speed of the miniature vehicle can reach 1 m / s, and the battery can continuously supply power for about 3.5 hours. In terms of on-vehicle computing power, the upper computer of the miniature vehicle is a Raspberry Pi 4B with Ubuntu1804 installed, and the lower computer main control chip is STM32F103RBT6. The CPU of the upper computer is a 64-bit quad-core processor with a main frequency of 1.5 GHz, with 2G of memory and 16G of storage. Based on the on-vehicle sensing devices and computing units, the miniature vehicle can complete on-vehicle environment perception with a certain accuracy.

[0035] The twin sandbox platform in the cyber space is mainly composed of the one-to-one twins (twin miniature vehicles) of the roadside equipment and miniature vehicles in the physical space and virtual vehicles. The twins complete the scene reconstruction based on real-time communication through 3D modeling and interface design, so that they can reflect the real-time operation status of the corresponding physical elements. Virtual vehicles are used to represent physical miniature vehicles through similar dynamics and kinematics modeling.

[0036] This embodiment can complete the modeling of information space based on the game engine Unity3D, and adjust the corresponding state parameters of the twin body by obtaining the real-time operating status of each traffic element in the physical space to achieve real-time state mapping. For virtual vehicles, their information flow interaction is similar to that of miniature vehicles in the physical space. By reporting their real-time state information, including but not limited to speed, position and direction, to the host running Unity (i.e. Figure 1 The Unity host in the image processing unit sends the desired front wheel steering angle and speed instructions to it.

[0037] Compute Server (i.e. Figure 1 The cloud-based Java server in the middle establishes connections with workstations in the physical space and Unity hosts in the information space to obtain the real-time status of each traffic element in the physical space and the virtual vehicle in the information space, and aligns and encapsulates all status information through time synchronization and predetermined protocols.

[0038] It is worth mentioning that, unlike the cloud of the intelligent connected vehicle cloud control system, the cloud described in this embodiment integrates complete status data of the information space and the physical space, and opens it to the outside through certain protocols. For external programs, they can obtain real-time status data of the system by establishing a connection with the cloud to realize corresponding applications.

[0039] according to Figure 1 It can be seen that the automatic emergency braking system key parameter verification system based on the miniature sandbox experimental platform provided in this embodiment can provide the vehicle status data to the external controller, and under the premise of ensuring safety, it can also apply the converted external control instructions to the miniature vehicle end. For the external controller, it receives the real-time status data of the miniature vehicle, generates the control instructions of the miniature vehicle after calculation, without having to pay attention to the specific implementation details inside the system.

[0040] To accommodate the access of external controllers with different requirements, three types of vehicle control modes are opened in the cloud in this embodiment. The parameters and meanings corresponding to each vehicle control mode are as follows: (1) Desired front wheel angle and speed; (2) Waypoints. A waypoint is the desired position of the scaled vehicle. Generally, waypoints are often discrete points on the center line of the road, and the set of waypoints forms the desired trajectory of the scaled vehicle over a period of time. To enable the scaled vehicle to reach the position indicated by the waypoint while satisfying the road geometry constraints, waypoints usually include information such as coordinates and reference speed; (3) Map nodes. The map nodes referred to in this embodiment are large-scale diversion or confluence points of vehicle queues, usually referring to the starting and ending points of lanes on structured roads. To enable the scaled vehicle to reach the position indicated by the map node at the minimum cost while satisfying the road geometry constraints, map nodes usually include information such as numbers, coordinates, and the numbers of the downstream nodes connected to them.

[0041] While ensuring the driving safety of the vehicle, the above three vehicle control modes open to the outside also provide a certain degree of flexibility, capable of meeting the vehicle control requirements of different external controllers.

[0042] According to Figure 1 It can also be seen that in addition to external controllers, human-computer interaction devices can also be applied to external inputs. To realize the input of human intention, this embodiment can capture the behavior of the wearer through a Hololens device and convert the behavior of the wearer into the corresponding intention input based on the preset behavior / logic correspondence. Similarly, to realize the visualization of the information space, the established model can be projected into the three-dimensional space in the form of a hologram based on the Hololens device, providing the wearer with a three-dimensional immersive viewing perspective.

[0043] To implement HDV simulation and provide the driver with a first-person driving perspective, based on a driving simulator, this embodiment updates the parameters of each model by obtaining the real-time operating state of the scene and provides the driver with a first-person driving perspective; at the same time, by collecting the driver's input control information, including throttle opening information, gear information, steering wheel angle information, etc., and feeding it back to the scaled vehicle in the system, thereby simulating human driving of a car.

[0044] In this embodiment, the key parameter verification system of the automatic emergency braking system based on the micro-scale sand table experimental platform includes a micro-scale sand table experimental platform and a computing server. The micro-scale sand table experimental platform includes a physical sand table platform in the physical space and a twin sand table platform in the information space. Among them, the physical sand table platform includes a micro-scale vehicle and a sand table platform, and the sand table platform includes a structured road, various roadside devices, and a workstation. The twin sand table platform is obtained by reconstructing the scene through three-dimensional modeling based on the physical sand table platform, and is used to reflect the real-time operation state of the physical sand table platform. The computing server includes an automatic emergency braking system control unit, which is wirelessly connected to the micro-scale sand table experimental platform and is used to execute the key parameter verification method of the automatic emergency braking system based on the micro-scale sand table experimental platform. This system effectively improves the safety, efficiency, and controllability of the key parameter verification of the automatic emergency braking system.

[0045] Further, based on the key parameter verification system of the automatic emergency braking system based on the micro-scale sand table experimental platform provided in the above embodiment, the key parameter verification method of the automatic emergency braking system based on the micro-scale sand table experimental platform is executed. Specifically, Figure 2 FIG. shows a schematic flow chart of the key parameter verification method of the automatic emergency braking system based on the micro-scale sand table experimental platform provided in the embodiment of the present invention.

[0046] As Figure 2 shown, the method includes steps S210-S230, and the following will elaborate on steps S210-S230 and related steps.

[0047] S210, determine the key parameter to be verified of the automatic emergency braking system and the vehicle control instruction; wherein, the key parameter to be verified includes any one of communication delay, communication packet loss rate, image resolution, and perception accuracy.

[0048] It should be noted that the key parameter verification method of the automatic emergency braking system based on the micro-scale sand table experimental platform provided in the embodiment of the present invention takes the computing server in the system as the execution entity.

[0049] It is easy to understand that based on the key parameter verification system of the automatic emergency braking system based on the micro-scale sand table experimental platform provided in the above embodiment, by obtaining the current operation state information and environmental state information of the micro-scale vehicle in the micro-scale sand table experimental platform, the computing server can generate corresponding vehicle control instructions. At the same time, the computing server will also determine the key parameters of the automatic emergency braking system to be verified currently, that is, the key parameters to be verified.

[0050] Specifically, through the cameras with global coverage in the scaled sand table experiment platform, the state information of the entire sand table platform and the scaled vehicles can be captured, including but not limited to road network structure information, lane geometry information, the correspondence information between lane IDs and colors, and the overall global image. Based on these perceived state information, the pose information and speed information of the scaled vehicles, that is, the current running state information of the scaled vehicles, can be calculated through the vehicle detection and state output algorithm.

[0051] Meanwhile, the start-stop state information of traffic lights, street lights, and parking lot lifting poles can be obtained from the workstation. For this information, the edge cloud (cloud computing model) method can be used for integration to obtain the integrated environment information, that is, the environmental state information.

[0052] Subsequently, according to the current running state information of the scaled vehicles and the environmental state information, the desired front wheel angle and speed of the scaled vehicles can be determined, thereby generating corresponding vehicle control instructions.

[0053] It should be noted that since this embodiment verifies the key parameters of the automatic emergency braking system, when the scaled vehicles are driving in simulation according to the vehicle control instructions, the automatic emergency braking system should be triggered.

[0054] In addition, the key parameters to be verified for the automatic emergency braking system in this embodiment include but are not limited to communication delay, communication packet loss rate, image resolution, and perception accuracy. However, when verifying the key parameters of the automatic emergency braking system, only one of the communication delay, communication packet loss rate, image resolution, and perception accuracy is selected to be changed each time. That is to say, the key parameters to be verified such as communication delay, communication packet loss rate, image resolution, and perception accuracy are in an "or" relationship during verification, rather than an "and" relationship.

[0055] Among them, the type of the key parameters to be verified can be determined according to actual requirements / situations, and no specific limitation is made here. The values of the key parameters to be verified are obtained according to the predetermined simulation test algorithm.

[0056] Communication delay refers to the time required for the information to be completely received at the receiving end from the sending end during the network data transmission process, which can be controlled by using a network emulator or built-in tools of the operating system. Communication packet loss rate refers to the proportion of data packets that fail to reach the destination successfully in the total sent data packets during the network data transmission process, which can be controlled by using a network emulator. Image resolution refers to the number of pixels contained in an image. A higher resolution means that the image contains more details and information, which can be controlled by changing the performance parameters of the camera. Perception accuracy refers to the accuracy of the perception model used to detect and predict the state of the scaled vehicles, which can be controlled by changing the model parameters of the perception model.

[0057] Specifically, the control of communication delay / communication packet loss rate mainly aims at the scenario of unreliable communication. By relying on the camera to detect the distance between the scaled vehicle and the obstacle in front (such as the vehicle ahead), there is a time delay in the position. This time delay makes the inter-vehicle distance received by the automatic emergency braking system larger than the actual inter-vehicle distance. As a result, the actual alarm and braking time lags behind the theoretical alarm and braking time, causing the minimum relative distance to continuously decrease, which may lead to a collision between the host vehicle and the vehicle ahead.

[0058] In addition, in the communication network, data transmission usually has burstiness, that is, after one data is lost during the transmission process, the probability of the next data being lost is greater than the probability of successful transmission. Therefore, packet loss may occur. The control of image resolution mainly considers detecting the distance between the scaled vehicle and the forward obstacle through the camera. So the camera resolution will affect the automatic emergency braking performance of the system. The control of the perception accuracy of the perception model mainly considers that the accuracy of detecting the relative distance between the scaled vehicle and the obstacle in front based on the camera in the system will directly affect the output accuracy of the system.

[0059] After determining the key parameters to be verified for the automatic emergency braking system and the vehicle control instructions, the computing server will transmit the key parameters to be verified and the vehicle control instructions to the scaled sand table experiment platform to execute step S220.

[0060] S220. Based on the scaled sand table experiment platform, according to the key parameters to be verified and the vehicle control instructions, control the scaled vehicle to perform simulated driving on the sand table platform, and obtain the actual driving data of the scaled vehicle during the simulated driving process.

[0061] It is easy to understand that after receiving the key parameters to be verified, the value of the key parameters to be verified is controlled / adjusted, such as increasing the communication delay, increasing the communication packet loss rate, reducing the image resolution, or reducing the perception accuracy of the perception model, etc.

[0062] After adjusting the key parameters to be verified, according to the vehicle control instructions, adjust the front wheel angle of the scaled vehicle with the desired angle as the target, and adjust the speed of the scaled vehicle with the desired speed as the target, thereby controlling the scaled vehicle to perform simulated driving on the sand table platform. At the same time, based on the cameras with global coverage and various installed sensor devices, collect the actual driving data of the scaled vehicle during the entire simulated driving process. The actual driving data here includes the collision time between the scaled vehicle and the obstacle in front.

[0063] After collecting the actual driving data of the scaled vehicle during the simulated driving process, transmit the actual driving data to the computing server to execute step S230.

[0064] S230. Obtain the verification result of the key parameter to be verified based on the actual driving data and the pre-stored simulated driving data. Among them, the actual driving data includes the collision time between the scaled vehicle and the obstacle ahead, and the simulated driving data includes the simulated collision time between the scaled vehicle and the obstacle ahead.

[0065] It is easy to understand that the simulated driving data corresponding to the key parameter to be verified is pre-stored in the system, and the simulated driving data includes the simulated collision time between the scaled vehicle and the obstacle ahead. After obtaining the actual driving data (including the collision time) of the key parameter to be verified, compare the actual driving data with the corresponding simulated driving data, and thus the verification result of the key parameter to be verified can be obtained.

[0066] Specifically, calculate the difference between the collision time obtained in the verification process and the simulated collision time obtained in the simulation test process. If the difference between the two is less than or equal to the set threshold, it means that the verification result of the current key parameter to be verified is qualified; otherwise, if the difference between the two is greater than the set threshold, it means that the verification result of the current key parameter to be verified is unqualified and the simulation test process needs to be adjusted again.

[0067] Among them, the set threshold can be adjusted according to the actual situation and is not specifically limited here.

[0068] It is worth mentioning that this embodiment verifies the key parameters of the automatic emergency braking system, but this embodiment also verifies the simulation test algorithm for determining the key parameters to be verified. If the simulation test method is accurate and effective, the key parameters to be verified determined by it must be verified to be qualified; otherwise, if the simulation test method has poor effects, the key parameters to be verified determined by it will cause the automatic emergency braking system to be unable to complete emergency braking or have poor emergency braking effects.

[0069] In this embodiment, determine the key parameter to be verified of the automatic emergency braking system and the vehicle control instruction. Among them, the key parameter to be verified includes any one of communication delay, communication packet loss rate, image resolution, and perception accuracy. Based on the scaled sand table experiment platform, according to the key parameter to be verified and the vehicle control instruction, control the scaled vehicle to perform simulated driving on the sand table platform, and collect the actual driving data of the scaled vehicle during the simulated driving process. Obtain the verification result of the key parameter to be verified based on the actual driving data and the pre-stored simulated driving data. Among them, the actual driving data includes the collision time between the scaled vehicle and the obstacle ahead, and the simulated driving data includes the simulated collision time between the scaled vehicle and the obstacle ahead. This method realizes the accurate, safe, and efficient verification of the key parameters of the automatic emergency braking system by using the scaled sand table experiment platform to verify the key parameters of the automatic emergency braking system.

[0070] Based on the above embodiments, further, the process of obtaining the current operating state information of the scaled vehicle will be described in detail below.

[0071] It is easy to understand that the current operating state information of the scaled vehicle includes pose information and speed information. Therefore, this embodiment mainly describes in detail the process of obtaining pose information and speed information.

[0072] To achieve the state perception of the scaled vehicle, real-time perception of the scaled vehicle is realized based on the global camera and the color block design on the top of the scaled vehicle. Its essence is an image processing algorithm, that is, the detection and state perception of the vehicle are realized by detecting different color block combinations of different scaled vehicles.

[0073] In a specific embodiment, the process of obtaining the pose information of the scaled vehicle is described in detail.

[0074] The steps of obtaining the current operating state information of the scaled vehicle in the scaled sand table experiment platform specifically include: obtaining the global image of the sand table platform and the scaled vehicle; performing color space conversion on the global image to obtain an HSV image; performing binarization according to the H value of the pixel points in the HSV image to obtain a binarized image; performing convex polygon fitting on the binarized image and calculating the minimum bounding rectangle of the convex polygon; when the aspect ratio of the minimum bounding rectangle is within a set interval and the area of the minimum bounding rectangle is greater than a set area, taking the minimum bounding rectangle as the color block area on the top of the scaled vehicle to obtain the pose information of the scaled vehicle, and the pose information includes the position of the scaled vehicle.

[0075] Specifically, the perception of the pose information of the scaled vehicle can be realized based on a single-frame global image, and the following steps are required: color space conversion, edge extraction and graphic filtering, and coordinate and orientation calculation output.

[0076] Color space is one of the ways to describe colors. By abstractly representing colors in a high-dimensional space, colors correspond one-to-one with points in the color space, making the description of colors more intuitive. Since the global image collected by the global camera is based on the RGB color space, it needs to be converted to the HSV color space during subsequent processing. For the color value of any pixel point in the global image, convert it from RGB to the HSV color space to obtain an HSV image.

[0077] To extract the information of miniature vehicles, i.e., the color patch combination information at the top of each vehicle, from an image represented in the HSV color space (HSV image), the colors at the rear side, front side, and middle of the miniature vehicle are searched in the HSV image in sequence. During the search process, the main parameter is the H value of the pixel points in the HSV image, and the HSV image is converted into the required initial binary image based on the H value of the pixel points. Due to the possible presence of colors to be detected and noise in the scene background, the initial binary image often contains multiple regions to be screened. To screen out the target vehicle from multiple regions to be screened, the regions to be screened need to be filtered.

[0078] During filtering, first, convex polygon fitting is performed on the initial binary image at the pixel level, then the minimum bounding rectangle of the convex polygon is calculated, and finally, screening is performed based on the geometric features of the minimum bounding rectangle. Considering that the imaging diagram of the designed rectangular color patch may be deformed and the geometric parameters of the minimum bounding rectangle may fluctuate as the distance between the miniature vehicle and the global camera changes during the driving process of the miniature vehicle. For the result of whether the region to be screened is the target color patch, when the aspect ratio of the minimum bounding rectangle is within a certain range and the area is greater than the threshold, it is determined that the region to be selected is the color patch region at the top of the vehicle, and thus the pose information of the miniature vehicle, including the position and orientation of the miniature vehicle, can be determined.

[0079] In another specific embodiment, the process of obtaining the speed information of the miniature vehicle is described in detail.

[0080] It is easy to understand that there are two schemes for obtaining the real-time running speed of the miniature vehicle. One is to perform differencing on the positions of the miniature vehicle in adjacent frames of the global image to obtain the change in the center point coordinates of the miniature vehicle; the other is based on the communication between the miniature vehicle and the sand table workstation, and the miniature vehicle converts its own motor speed into the real-time speed and reports it.

[0081] In the scheme where the miniature vehicle actively reports its speed, the upper computer of the miniature vehicle is a Raspberry Pi 4B with the Ubuntu18.04 system installed, and the lower computer main control chip is an STM32. The Raspberry Pi and the sand table host are located in the same local area network and communicate wirelessly. The sand table host sends the desired speed and front wheel angle to the Raspberry Pi at a frequency of 20Hz, and the Raspberry Pi sends the desired speed and front wheel angle commands to the lower computer based on serial communication at a frequency of 120Hz. The lower computer sends the corresponding control commands to the execution device of the miniature vehicle at a frequency of 20Hz. The vehicle obtains the states of mechanical devices such as the motor, such as the rotational speed, and then converts it into the corresponding vehicle speed, and finally reports the estimated vehicle speed to the sand table host at a frequency of 20Hz based on wireless communication.

[0082] In this embodiment, the key parameters to be verified of the automatic emergency braking system and the vehicle control instructions are determined; wherein, the key parameters to be verified include any one of communication delay, communication packet loss rate, image resolution, and perception accuracy; based on the micro-scale sand table experiment platform, according to the key parameters to be verified and the vehicle control instructions, the micro-scale vehicle is controlled to perform simulated driving on the sand table platform, and the actual driving data of the micro-scale vehicle during the simulated driving is collected; based on the actual driving data and the pre-stored simulated driving data, the verification result of the key parameters to be verified is obtained; wherein, the actual driving data includes the collision time between the micro-scale vehicle and the obstacle in front, and the simulated driving data includes the simulated collision time between the micro-scale vehicle and the obstacle in front. This method realizes accurate, safe, and efficient verification of the key parameters of the automatic emergency braking system by using the micro-scale sand table experiment platform to verify the key parameters of the automatic emergency braking system.

[0083] In some embodiments, it specifically includes: the step of obtaining the actual driving data of the micro-scale vehicle during the simulated driving, specifically including: using the camera configured on the micro-scale vehicle to obtain the target image in front of the micro-scale vehicle; performing target detection on the target image to obtain the upper and lower limits of the abscissa and the upper and lower limits of the ordinate of the obstacle in front in the target image; according to the height, downward deviation angle, and focal length of the camera that captures the target image, and the upper and lower limits of the abscissa and the upper and lower limits of the ordinate, calculate the relative distance from the obstacle in front to the camera; calculate the collision time according to the relative distance and the relative speed of the obstacle in front and the micro-scale vehicle in the current running state to obtain the actual driving data.

[0084] In some other embodiments, if the collision time is less than the first set threshold and greater than or equal to the second set threshold, a first prompt message warning of danger is sent to the micro-scale vehicle; if the collision time is less than the second set threshold and greater than or equal to the third set threshold, a second prompt message for partial braking is sent to the micro-scale vehicle; if the collision time is less than the third set threshold, a third prompt message for full braking is sent to the micro-scale vehicle.

[0085] Among them, the first set threshold, the second set threshold, and the third set threshold can be adjusted according to the actual situation, and no specific limitation is made here.

[0086] For example, in a specific embodiment, the first set threshold is 2.6 seconds, the second set threshold is 1.6 seconds, and the third set threshold is 0.6 seconds.

[0087] In addition, when the obstacle ahead is a vehicle, if the speed of the scaled-down vehicle is the same as that of the vehicle in front and the distance is relatively close, the collision time cannot be calculated. In this case, the safety distance model will determine whether full braking intervention is required. When the calculated relative distance from the obstacle ahead to the camera is less than the limit safety distance Hstop (usually 2 - 5 m), the vehicle AEBS intervenes and performs full braking.

[0088] Corresponding to the method for verifying key parameters of the automatic emergency braking system based on the scaled-down sand table experimental platform described in the above embodiments, the present invention further provides a device for verifying key parameters of the automatic emergency braking system based on the scaled-down sand table experimental platform.

[0089] Specifically, Figure 3 FIG. shows a schematic structural diagram of a device for verifying key parameters of the automatic emergency braking system based on the scaled-down sand table experimental platform provided by an embodiment of the present invention.

[0090] As Figure 3 shown, the device includes: a key parameter to be verified and vehicle control instruction determination module 310, configured to determine the key parameter to be verified of the automatic emergency braking system and the vehicle control instruction; wherein, the key parameter to be verified includes any one of communication delay, communication packet loss rate, image resolution, and perception accuracy; a scaled-down vehicle simulation driving module 320 in the scaled-down sand table experimental platform, configured to control the scaled-down vehicle to perform simulated driving on the sand table platform based on the scaled-down sand table experimental platform, according to the key parameter to be verified and the vehicle control instruction, and obtain the actual driving data of the scaled-down vehicle during the simulated driving; a verification result acquisition module 330 for the key parameter to be verified, configured to obtain the verification result of the key parameter to be verified based on the actual driving data and the pre-stored simulated driving data; wherein, the actual driving data includes the collision time between the scaled-down vehicle and the obstacle ahead, and the simulated driving data includes the simulated collision time between the scaled-down vehicle and the obstacle ahead.

[0091] In this embodiment, the key parameters to be verified and the vehicle control instruction determination module 310 determines the key parameters to be verified of the automatic emergency braking system and the vehicle control instruction; wherein, the key parameters to be verified include any one of communication delay, communication packet loss rate, image resolution, and sensing accuracy; the miniature vehicle simulation driving module 320 in the miniature sand table experiment platform controls the miniature vehicle to perform simulated driving on the sand table platform based on the miniature sand table experiment platform according to the key parameters to be verified and the vehicle control instruction, and obtains the actual driving data of the miniature vehicle during the simulated driving; the verification result acquisition module 330 of the key parameters to be verified obtains the verification result of the key parameters to be verified based on the actual driving data and the pre-stored simulation driving data; wherein, the actual driving data includes the collision time between the miniature vehicle and the obstacle in front, and the simulation driving data includes the simulated collision time between the miniature vehicle and the obstacle in front. This device realizes accurate, safe, and efficient verification of the key parameters of the automatic emergency braking system by using the miniature sand table experiment platform to verify the key parameters of the automatic emergency braking system.

[0092] It should be noted that the key parameter verification device of the automatic emergency braking system based on the miniature sand table experiment platform provided in the embodiments of the present invention can be correspondingly referred to the key parameter verification method of the automatic emergency braking system based on the miniature sand table experiment platform described in the above embodiments, and will not be elaborated here.

[0093] Figure 4 An example of the physical structure diagram of an electronic device is shown as Figure 4 As shown, the electronic device may include: a processor 410, a communication interface 420, a memory 430, and a communication bus 440. Among them, the processor 410, the communication interface 420, and the memory 430 complete mutual communication through the communication bus 440. The processor 410 can call the logical instructions in the memory 430 to execute the key parameter verification method of the automatic emergency braking system based on the miniature sand table experiment platform. The method includes: determining the key parameters to be verified of the automatic emergency braking system and the vehicle control instruction; wherein, the key parameters to be verified include any one of communication delay, communication packet loss rate, image resolution, and sensing accuracy; based on the miniature sand table experiment platform, according to the key parameters to be verified and the vehicle control instruction, controlling the miniature vehicle to perform simulated driving on the sand table platform, and obtaining the actual driving data of the miniature vehicle during the simulated driving; based on the actual driving data and the pre-stored simulation driving data, obtaining the verification result of the key parameters to be verified; wherein, the actual driving data includes the collision time between the miniature vehicle and the obstacle in front, and the simulation driving data includes the simulated collision time between the miniature vehicle and the obstacle in front.

[0094] In addition, when the logical instructions in the above-mentioned memory 430 are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0095] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative labor.

[0096] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on such an understanding, the technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium such as ROM / RAM, magnetic disks, optical discs, etc., and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments.

[0097] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments or equivalently replace some of the technical features. These modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of various embodiments of the present invention.

Claims

1. A method for verifying key parameters of an automatic emergency braking system based on a miniature sandbox experimental platform, characterized in that: The miniature sandbox experimental platform includes a miniature vehicle and a sandbox platform, which are connected to the automatic emergency braking system via a wireless communication network; The method comprises: Determining key parameters to be verified of the automatic emergency braking system and vehicle control instructions; wherein the key parameters to be verified include any one of communication delay, communication packet loss rate, image resolution and perception accuracy; Based on the miniature sandbox experimental platform, according to the key parameters to be verified and the vehicle control instructions, the miniature vehicle is controlled to perform simulated driving in the sandbox platform, and actual driving data of the miniature vehicle during the simulated driving process is obtained; Based on the actual driving data and the pre-stored simulated driving data, the verification result of the key parameter to be verified is obtained; wherein the actual driving data includes the collision time between the miniature vehicle and the obstacle ahead, and the simulated driving data includes the simulated collision time between the miniature vehicle and the obstacle ahead.

2. The key parameter verification method of the automatic emergency braking system based on the miniature sandbox experimental platform according to claim 1 is characterized in that: The step of determining key parameters to be verified of the automatic emergency braking system and the vehicle control instructions includes: Obtain the current operating status information and environmental status information of the miniature vehicle in the miniature sandbox experimental platform; Generate vehicle control instructions according to the current operating state information and environmental state information of the miniature vehicle; Among them, the current running state information includes posture information and speed information; the environmental state information includes signal light state information, street light state information and lifting pole state information; the vehicle control instruction includes the expected turning angle and expected speed of the miniature vehicle.

3. The key parameter verification method of the automatic emergency braking system based on the miniature sandbox experimental platform according to claim 2 is characterized in that: The miniature sandbox experimental platform includes one or more miniature vehicles, and the miniature vehicles are distinguished by different color block designs; Accordingly, the step of obtaining the current running status information of the miniature vehicle in the miniature sandbox experimental platform specifically includes: Get the global image of the sandbox platform and miniature vehicles; Performing color space conversion on the global image to obtain an HSV image; Binarize the image according to the H value of the pixel in the HSV image to obtain an initial binary image; Performing convex polygon fitting on the initial binary image, and calculating the minimum envelope rectangle of the convex polygon; When the aspect ratio of the minimum envelope rectangle is within a set range and the area of ​​the minimum envelope rectangle is greater than the set area, the minimum envelope rectangle is used as the color block area on the top of the miniature vehicle to obtain the posture information of the miniature vehicle, wherein the posture information includes the position of the miniature vehicle.

4. The key parameter verification method of the automatic emergency braking system based on the miniature sandbox experimental platform according to claim 2 is characterized in that: The steps of obtaining the current running status information of the miniature vehicle in the miniature sandbox experimental platform specifically include: Obtaining the position of the miniature vehicle in the global image of the adjacent frames; Perform differential processing on the position of the miniature vehicle in the global image of adjacent frames to obtain the change of the coordinates of the center point of the miniature vehicle; The speed information of the miniature vehicle is obtained according to the change of the coordinates of the center point of the miniature vehicle.

5. The key parameter verification method of the automatic emergency braking system based on the miniature sandbox experimental platform according to claim 1 is characterized in that: The obtaining the verification result of the key parameter to be verified based on the actual driving data and the pre-stored simulated driving data includes: When the difference between the collision time and the simulated collision time is less than or equal to a set threshold, determining the verification result of the key parameter to be verified as qualified; When the difference between the collision time and the simulated collision time is greater than a set threshold, the verification result of the key parameter to be verified is determined as verification failure.

6. The key parameter verification method of the automatic emergency braking system based on the miniature sandbox experimental platform according to claim 3 is characterized in that: The steps of obtaining actual driving data of the miniature vehicle during the simulated driving process specifically include: Using the camera configured on the miniature vehicle, the target image in front of the miniature vehicle is acquired; Performing target detection on the target image to obtain upper and lower limits of the horizontal coordinate and upper and lower limits of the vertical coordinate of the front obstacle in the target image; Calculate the relative distance from the front obstacle to the camera according to the height, downward deflection angle and focal length of the camera shooting the target image, as well as the upper and lower limits of the horizontal coordinate and the upper and lower limits of the vertical coordinate; The collision time is calculated according to the relative distance and the relative speed of the front obstacle and the miniature vehicle in the current running state to obtain the actual driving data.

7. The key parameter verification method of the automatic emergency braking system based on the miniature sandbox experimental platform according to claim 1 is characterized in that: After obtaining the actual driving data of the miniature vehicle during the simulated driving process, including: When the collision time is less than a first set threshold and greater than or equal to a second set threshold, a first warning message of danger is sent to the miniature vehicle; When the collision time is less than a second set threshold and greater than or equal to a third set threshold, a second prompt message of partial braking is sent to the miniature vehicle; When the collision time is less than a third set threshold, a third prompt message of full braking is sent to the miniature vehicle.

8. A device for verifying key parameters of an automatic emergency braking system based on a miniature sandbox experimental platform, characterized in that: The miniature sandbox experimental platform includes a miniature vehicle and a sandbox platform, which are connected to the automatic emergency braking system via a wireless communication network; The device comprises: A module for determining key parameters to be verified and vehicle control instructions, used to determine key parameters to be verified and vehicle control instructions of the automatic emergency braking system; wherein the key parameters to be verified include any one of communication delay, communication packet loss rate, image resolution and perception accuracy; A miniature vehicle simulation driving module in a miniature sandbox experimental platform is used to control the miniature vehicle to perform simulated driving in the sandbox platform based on the miniature sandbox experimental platform according to the key parameters to be verified and the vehicle control instructions, and obtain actual driving data of the miniature vehicle during the simulated driving process; The module for obtaining verification results of key parameters to be verified is used to obtain verification results of the key parameters to be verified based on actual driving data and pre-stored simulated driving data; wherein the actual driving data includes the collision time between the miniature vehicle and the obstacle ahead, and the simulated driving data includes the simulated collision time between the miniature vehicle and the obstacle ahead.

9. An automatic emergency braking system key parameter verification system based on a miniature sandbox experimental platform, characterized in that: include: A miniature sandbox experimental platform, including a physical sandbox platform in physical space and a twin sandbox platform in information space; wherein the physical sandbox platform includes a miniature vehicle and a sandbox platform, and the sandbox platform includes a structured road, a variety of roadside equipment, and a workstation; the twin sandbox platform is obtained by reconstructing the scene through three-dimensional modeling based on the physical sandbox platform, and is used to reflect the real-time operation status of the physical sandbox platform; A computing server, including an automatic emergency braking system control unit, is wirelessly connected to a miniature sandbox experimental platform and is used to execute the automatic emergency braking system key parameter verification method based on a miniature sandbox experimental platform as described in any one of claims 1 to 7.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the key parameter verification method of the automatic emergency braking system based on the miniature sandbox experimental platform as described in any one of claims 1 to 7 is implemented.

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