Vehicle control method, vehicle-mounted device, vehicle, and storage medium
By displaying augmented reality images on the vehicle's screen and calculating the driving trajectory using beacon and sensor data, the problem of motion sickness caused by the conflict between visual and vestibular perception on spiral roads has been solved, achieving a safe and comfortable driving experience.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GUANGZHOU AUTOMOBILE GROUP CO LTD
- Filing Date
- 2026-05-08
- Publication Date
- 2026-07-14
AI Technical Summary
When a vehicle travels on a spiral road, passengers may experience motion sickness due to a conflict between visual and vestibular perception, which can affect driving safety.
By acquiring multi-source data, including beacon locations, sensor data, and map information, the vehicle's trajectory is calculated, augmented reality images are generated and displayed on the screen, providing navigation elements for visual guidance.
It effectively relieves motion sickness symptoms, reduces the illusion of being lost in a maze and anxiety through accurate visual guidance, and improves driving safety.
Smart Images
Figure CN122379558A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of intelligent driving technology, specifically to a vehicle control method, on-board equipment, vehicle, and storage medium. Background Technology
[0002] As a vehicle enters or exits a spiral parking lot, it needs to travel along a fixed curvature for an extended period. The enclosed environment inside the vehicle obstructs external views, preventing passengers' visual system from perceiving the vehicle's actual movement relative to the ground. However, the vestibular system located in the ear can sensitively detect this movement, creating a conflict between visual information and vestibular perception. This sensory discrepancy can easily cause passengers to experience a sense of disorientation and disorientation, leading to motion sickness symptoms such as dizziness and nausea.
[0003] If motion sickness cannot be effectively resolved, it will affect driving safety. Summary of the Invention
[0004] This application provides a vehicle control method, an in-vehicle device, a vehicle, and a storage medium, which can solve the technical problem of motion sickness caused by sensory conflict when a vehicle is traveling on a spiral road.
[0005] On one hand, this application provides a vehicle control method, the method comprising: when the vehicle is traveling on a spiral road, acquiring multi-source data, the multi-source data including a map of the spiral road, beacon positions corresponding to beacons set on the spiral road, and sensor data of the vehicle, the sensor data including an environmental image and dynamic parameters of the vehicle; determining the vehicle's driving trajectory data based on the beacon positions and the dynamic parameters; and fusing the map, the driving trajectory data, and the environmental image to generate an augmented reality image for display on the vehicle's display screen, the augmented reality image including navigation elements for providing visual guidance to the user.
[0006] In some embodiments of this application, the dynamic parameters include initial yaw rate and initial lateral acceleration. Determining the vehicle's trajectory data based on the beacon position and the dynamic parameters includes: performing a tightly coupled fusion operation on the beacon position, the initial yaw rate, and the initial lateral acceleration to obtain the vehicle's standard yaw rate, standard lateral acceleration, and vehicle attitude; determining the vehicle position based on the beacon position; determining the vehicle speed using multiple beacon positions and the acquisition time corresponding to each beacon position; and obtaining the trajectory data based on the standard yaw rate, the standard lateral acceleration, the vehicle attitude, the vehicle position, and the vehicle speed.
[0007] In some embodiments of this application, the method for generating the augmented reality image includes: generating the navigation element in a preset virtual coordinate space based on the map and the vehicle position; determining the motion state of the vehicle according to the vehicle posture and the vehicle speed; determining the transformation matrix of the navigation element according to the motion state, the standard yaw rate and the standard lateral acceleration; and rendering the navigation element onto the environment image using the transformation matrix to obtain the augmented reality image.
[0008] In some embodiments of this application, generating navigation elements in a preset virtual coordinate space based on the map and the vehicle location includes: determining the remaining distance data of the vehicle based on the map and the vehicle location; and generating lane lines aligned with the spiral lane, text information for displaying the remaining distance data, and directional markers for indicating the exit of the spiral lane in the virtual coordinate space based on the map and the vehicle location.
[0009] In some embodiments of this application, the multi-source data further includes ambient light intensity, and the method further includes: determining the scene mode corresponding to the vehicle based on the current remaining distance data, the scene mode being used to indicate the position of the vehicle relative to the spiral lane; determining the desired light intensity and target color temperature based on the scene marker corresponding to the scene mode using a preset mapping relationship; determining the target brightness based on the reference ambient light intensity, the current ambient light intensity, and the desired light intensity; and adjusting the display parameters of the display screen based on the target brightness and the target color temperature.
[0010] In some embodiments of this application, the transformation matrix includes rotation parameters and translation parameters. Determining the transformation matrix of the navigation element based on the motion state, the standard yaw rate, and the standard lateral acceleration includes: determining a first proportionality coefficient corresponding to the rotation parameter and a second proportionality coefficient corresponding to the translation parameter based on the motion state using a preset correspondence; determining the rotation parameter based on the standard yaw rate and the first proportionality coefficient; and determining the translation parameter based on the standard lateral acceleration and the second proportionality coefficient.
[0011] In some embodiments of this application, the step of rendering the navigation element onto the environment image using the transformation matrix to obtain an augmented reality image includes: according to the transformation matrix and the calibration parameters of the sensor that acquires the environment image, performing perspective matching of the navigation element from the virtual coordinate space to the coordinate space corresponding to the environment image to obtain a navigation element layer, and fusing and overlaying the navigation element layer with the environment image to obtain the augmented reality image.
[0012] On the other hand, this application provides an in-vehicle device, the in-vehicle device including: a processor, a memory; and an application program, wherein the application program is stored in the memory and configured to be executed by the processor to implement the vehicle control method.
[0013] On the other hand, this application provides a vehicle that includes the aforementioned on-board equipment.
[0014] On the other hand, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor of an in-vehicle device, implements the vehicle control method.
[0015] In the vehicle control scheme provided in this application embodiment, beacon location provides vehicle position reference, and sensor data reflects vehicle motion status and ambient lighting conditions in real time. Therefore, by fusing beacon location and sensor data, continuous and smooth vehicle trajectory data can be accurately calculated. Based on the vehicle's trajectory data, the vehicle's position and motion can be accurately determined. Based on the spiral road map, the total number of spiral road loops, lane gradient, and exit coordinates can be accurately determined. Therefore, by combining the map and trajectory data with environmental images, an augmented reality image is generated. This augmented reality image integrates navigation elements with the environmental image of the real road view. Displaying the augmented reality image on the vehicle's screen provides users with intuitive visual guidance that fits the real scene, enabling users to form a clear and definite understanding of their own position and travel progress. This reduces the psychological and visual "being lost" illusion and the resulting anxiety caused by unknown environment, repetitive paths, or disorientation, effectively alleviating motion sickness symptoms such as dizziness and nausea. Attached Figure Description
[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and are configured together with the description to explain the principles of this disclosure.
[0017] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.
[0018] Figure 1 This is an application scenario diagram of a vehicle control method provided in an embodiment of this application.
[0019] Figure 2 This is a flowchart of a vehicle control method provided in an embodiment of this application.
[0020] Figure 3 This is a flowchart of a method for determining a transformation matrix provided in an embodiment of this application.
[0021] Figure 4 This is a flowchart of a vehicle control method provided in another embodiment of this application.
[0022] Figure 5 This is a schematic diagram of a vehicle control method provided in an embodiment of this application.
[0023] Figure 6 This is a schematic diagram of the structure of a vehicle-mounted device provided in an embodiment of this application. Detailed Implementation
[0024] It should be noted that in this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and drawings of this application are used to distinguish similar objects, not to describe a specific order or sequence.
[0025] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner. Unless otherwise specified, the following embodiments and features described herein can be combined with each other.
[0026] As a vehicle enters or exits a spiral parking lot, it needs to travel along a fixed curvature for an extended period. The enclosed environment inside the vehicle obstructs external views, preventing passengers' visual system from perceiving the vehicle's actual movement relative to the ground. However, the vestibular system located in the ear can sensitively detect this movement, creating a conflict between visual information and vestibular perception. This sensory discrepancy can easily cause passengers to experience a sense of disorientation and disorientation, leading to motion sickness symptoms such as dizziness and nausea.
[0027] If motion sickness cannot be effectively resolved, it will affect driving safety.
[0028] To address the aforementioned technical problems, this application provides a vehicle control method that effectively alleviates dizziness and anxiety caused by spiral roads by displaying augmented reality images on the vehicle's display screen.
[0029] like Figure 1 The diagram shown is an application scenario diagram of a vehicle control method provided in an embodiment of this application.
[0030] In this embodiment, the vehicle control method can be applied to the on-board device 10. The on-board device 10 can be installed in the vehicle 100; for example, the on-board device 10 can be an on-board terminal in the vehicle 100. The vehicle 100 can be a car, but is not limited to a conventional car, a pure electric vehicle, or a hybrid car. Furthermore, the vehicle control method provided in this embodiment can also be applied to other types of motor vehicles or non-motor vehicles.
[0031] The vehicle 100 may also include a perception system 11, which is communicatively connected to the on-board equipment 10. The perception system 11 may include various sensors, such as vision sensors, distance sensors, inertial measurement units (IMUs), temperature sensors, wheel speed sensors, etc. The vision sensor may be a camera, etc., and the distance sensor may be a lidar, millimeter-wave radar, ultrasonic radar, etc.
[0032] The above-mentioned vehicle-mounted equipment 10 and sensing system 11 are merely examples. In actual applications, the vehicle 100 may include more or fewer components, and this application does not impose any specific limitations on this.
[0033] In other embodiments of this application, the vehicle control method provided in this application can be applied to one or more electronic devices. The electronic devices can be communicatively connected to the vehicle; for example, the electronic devices can be computers, mobile phones, laptops, servers, etc., wherein the server can be a cloud server or a server cluster. This application does not limit the type of electronic device.
[0034] To more clearly illustrate the vehicle control method provided in the embodiments of this application, the following description will take an in-vehicle device as an example.
[0035] like Figure 2 The diagram shown is a flowchart of a vehicle control method according to an embodiment of this application. Depending on different needs, the order of the steps in this flowchart can be adjusted according to actual requirements, and some steps can be omitted. The method is applied to in-vehicle equipment, such as... Figure 6 The vehicle-mounted device 10 is shown. The method includes the following steps: S11: When the vehicle is traveling on the spiral lane, acquire multi-source data, including a map of the spiral lane, the beacon positions corresponding to the beacons set on the spiral lane, and sensor data of the vehicle, including environmental images and vehicle dynamic parameters.
[0036] The timing of execution of the vehicle control method in this application embodiment can be flexible and diverse. For example, the on-board device can execute the vehicle control method in this application embodiment in response to the activation signal of the anti-motion sickness mode, or the on-board device can execute the vehicle control method in this application embodiment when it detects that the vehicle has entered or exited a spiral lane.
[0037] The activation signal for the anti-motion sickness mode can be generated by the user's touch operation of the activation control. This application does not restrict the location of the activation control. Alternatively, the in-vehicle device can generate the activation signal when it detects that the vehicle is traveling on a spiral road, confirms the user's legal identity, and obtains the user's historical data on motion sickness tendencies. The in-vehicle device can identify the user and obtain the user's historical data on motion sickness tendencies through an in-vehicle camera, a user's mobile terminal (e.g., a mobile phone), or a wearable device (e.g., a smartwatch). The above methods for triggering the activation signal of the anti-motion sickness mode are merely examples and are not limited to these in practical applications.
[0038] In some embodiments, a spiral lane can be a spiral-shaped driving path within a parking lot, or it can be any other driving path outside of a parking lot that has a similar spiral shape. Taking a parking lot as an example, the scenario of a vehicle driving in a spiral lane can correspond to both exiting the parking lot and entering the parking lot; in practical applications, it is not limited to these two scenarios.
[0039] In some embodiments, the beacon, also known as a positioning beacon, can be a roadside unit (RSU) deployed on a spiral roadway, capable of broadcasting high-precision positioning signals or responding to data acquisition requests from onboard equipment by directionally transmitting high-precision positioning signals. For example, the beacon can employ technologies such as Ultra-Wideband Beacon (UWB) and Radio Frequency Identification (RFID) to generate, broadcast, or transmit positioning signals. The positioning signal can include the beacon's location; for example, it can include beacon coordinate information. Onboard equipment can receive the beacon's positioning signal through a UWB / RFID receiving module and determine the beacon's location from the beacon coordinate information within the positioning signal. Each beacon location can have a corresponding acquisition time, facilitating the subsequent determination of the vehicle's driving trajectory data based on the beacon location and the corresponding acquisition time. The acquisition time can be recorded by the receiving module upon receiving the positioning signal.
[0040] In other embodiments, the on-board equipment can determine the vehicle's trajectory data based on the beacon location and the corresponding transmission time, wherein the transmission time can be the time when the roadside unit sends the positioning signal.
[0041] In some embodiments, the map can be acquired in real time or pre-acquired, and this application embodiment does not limit this. Exemplarily, the vehicle-mounted device can communicate with beacons positioned on the spiral lane and acquire the spiral lane map from the beacons; alternatively, the vehicle-mounted device can communicate with a server and acquire the spiral lane map from the server; or the vehicle-mounted device can read the spiral lane map from the vehicle's local storage device. The vehicle-mounted device can establish communication connections with beacons and servers through a communication module. For example, the communication module can be a Vehicle-to-Everything (V2X) communication module. Exemplarily, the vehicle-mounted device can attempt to connect with a roadside unit inside the parking lot through the V2X communication module to confirm that the parking lot supports Infrastructure-to-Pedestrian (I2P) services and download or receive a high-precision map of the spiral lane from the roadside unit. The above examples of map acquisition methods are merely illustrative, and practical applications are not limited to these.
[0042] In some embodiments, sensor data can be acquired through sensors, such as inertial measurement units (IMUs), vision sensors (e.g., cameras), wheel speed sensors, light sensors, etc.
[0043] The dynamic parameters in the sensor data can be obtained by inertial measurement unit (IMU) measurement, and these dynamic parameters include, but are not limited to, yaw rate ω. can With lateral acceleration a lat_can For example, an inertial measurement unit may include an accelerometer and a gyroscope, and a yaw rate ω. can With lateral acceleration a lat_can The acceleration measured by the accelerometer and the angular velocity measured by the gyroscope can be calculated. In addition to dynamic parameters, sensor data can also include other data. For example, sensor data can also include environmental images acquired by a vision sensor, vehicle speed acquired by a wheel speed sensor, and ambient light intensity acquired by a light sensor. Each sensor data point can have a corresponding acquisition time (e.g., a timestamp).
[0044] For ease of distinction, the yaw rate ω obtained by the inertial measurement unit will be used in the following text. can This is called the initial yaw rate ω. can The lateral acceleration a obtained by the inertial measurement unit lat_can This is called the initial lateral acceleration a. lat_can .
[0045] In some embodiments, the in-vehicle device can connect to sensors on the vehicle to acquire sensor data. For example, the in-vehicle device can connect to the in-vehicle sensors via a Controller Area Network Bus (CANBus) bus, and the in-vehicle device can acquire sensor data via the CANBus bus.
[0046] The examples of multi-source data above are merely illustrative; in practical applications, multi-source data can also include other types of data. For instance, multi-source data can also include environmental point cloud data acquired by LiDAR, etc.
[0047] S12, based on the beacon location and the vehicle's dynamic parameters, determines the vehicle's trajectory data.
[0048] In some embodiments, the vehicle-mounted device determines the vehicle's driving trajectory data based on the beacon position and the vehicle's dynamic parameters, including: performing a tightly coupled fusion operation on the beacon position, initial yaw rate, and initial lateral acceleration to obtain the vehicle's standard yaw rate, standard lateral acceleration, and vehicle attitude; determining the vehicle position based on the beacon position; determining the vehicle speed using multiple beacon positions and the acquisition time corresponding to each beacon position; and obtaining the driving trajectory data based on the standard yaw rate, standard lateral acceleration, vehicle attitude, vehicle position, and vehicle speed.
[0049] In some embodiments, the calculation of driving trajectory data can be periodic, and the on-board equipment can determine the vehicle's driving trajectory data based on beacon positions and sensor data, according to a preset sampling period or sampling time.
[0050] In some embodiments, the on-board device can utilize a fusion algorithm to perform tightly coupled fusion calculations on the beacon position, initial yaw rate, and initial lateral acceleration to obtain the vehicle's standard yaw rate, standard lateral acceleration, and vehicle attitude. For example, the fusion algorithm can be an Extended Kalman Filter (EKF) algorithm or a factor graph optimization algorithm; the specific type of fusion algorithm is not limited in the embodiments of this application.
[0051] In some embodiments, the on-board device is based on the initial yaw rate ω can and initial lateral acceleration a lat_can The standard yaw rate ω is determined by using fusion algorithms such as extended Kalman filtering or factor graph optimization. fused and standard lateral acceleration a lat_fused The methods can be found in relevant technologies, or in the following description of methods for predicting vehicle attitude.
[0052] In some embodiments, vehicle attitude can be represented using attitude angles, such as pitch angle, roll angle, and yaw angle, where the yaw angle is also called the yaw angle. Taking the extended Kalman filter algorithm as an example, the on-board device can determine the acceleration measured by the accelerometer and the angular velocity measured by the gyroscope based on the initial yaw rate and initial lateral acceleration. Using the extended Kalman filter algorithm, the attitude angle is calculated as the observed value based on the acceleration measured by the accelerometer, and the attitude angle at the current moment is predicted as the predicted value based on the angular velocity measured by the gyroscope. The observed value and the predicted value are compared, and then the optimal Kalman gain is calculated based on the uncertainty of each of the observed value and the predicted value. The Kalman gain is used to correct the predicted value, and finally the optimal estimate of the vehicle attitude is obtained. The method of determining the vehicle attitude using the Kalman filter algorithm based on the acceleration measured by the accelerometer and the angular velocity measured by the gyroscope can refer to the relevant process of the Kalman filter algorithm in related technologies.
[0053] The acceleration measured by the accelerometer is also called triaxial acceleration, which can include the acceleration of the vehicle in the three coordinate axes of the corresponding coordinate system. The pitch and roll angles can be calculated as observed values based on the acceleration measured by the accelerometer. For example, the method for determining the pitch and roll angles based on the acceleration measured by the accelerometer can refer to the following formulas (1)~(2): (1) (2) in, This represents the roll angle, and atan2 represents the two-parameter arctangent function. This represents the vehicle's acceleration in the y-axis direction. This represents the vehicle's acceleration in the z-axis direction. Indicates pitch angle, This represents the vehicle's acceleration in the x-axis direction.
[0054] Among them, the angular velocity measured by the gyroscope is also called the three-axis angular velocity, which can include the angular velocity of the vehicle in the three coordinate axes of the corresponding coordinate system. For example, the method of predicting the attitude angle at the current moment based on the angular velocity measured by the gyroscope can refer to the following formulas (3) to (5): (3) (4) (5) in, express The roll angle at any moment, express The roll angle at any moment, This represents the angular velocity of the vehicle in the x-axis direction. Indicates the sampling time or sampling period. express The pitch angle at any moment, express The pitch angle at any moment, This represents the angular velocity of the vehicle in the y-axis direction. express The lateral angle at any moment, express The lateral angle at any moment, This represents the angular velocity of the vehicle in the z-axis direction.
[0055] In other embodiments, the onboard device may also calculate the standard yaw rate ω based on the vehicle attitude predicted by the fusion algorithm. fused and standard lateral acceleration a lat_fused .
[0056] In some embodiments, the on-board equipment can determine the vehicle's position within a unit of time based on multiple beacon locations. Displacement within So as to facilitate the calculation of displacement With unit time Determine vehicle speed For example, vehicle speed. .
[0057] In some embodiments, the on-board device can determine the vehicle's position based on the beacon location using a positioning algorithm. For example, the positioning algorithm could be a Time Difference of Arrival (TDOA) algorithm or an Angle of Arrival (AOA) algorithm. The on-board device can calculate the vehicle's three-dimensional coordinates P(x, y, z) as its position based on the beacon location using algorithms such as TDOA and AOA.
[0058] In this embodiment, the beacon location can provide a vehicle position reference, and the sensor data can reflect the vehicle's motion status and ambient lighting conditions in real time. Therefore, by fusing the beacon location and sensor data, the vehicle's continuous and smooth driving trajectory data can be accurately calculated.
[0059] S13, based on map, driving trajectory data and environmental images, merges and generates augmented reality images, which include navigation elements to provide visual guidance to users.
[0060] In some embodiments of this application, the vehicle-mounted device generates augmented reality images by fusing maps, driving trajectory data, and environmental images, including: generating navigation elements in a preset virtual coordinate space based on the map and vehicle position; determining the vehicle's motion state based on the vehicle's posture and speed; determining the transformation matrix of the navigation elements based on the motion state, standard yaw rate, and standard lateral acceleration; and rendering the navigation elements onto the environmental image using the transformation matrix to obtain the augmented reality image.
[0061] In some embodiments, the virtual coordinate space may be a three-dimensional coordinate space composed of a custom-defined virtual coordinate system.
[0062] In some embodiments of this application, the in-vehicle device generates navigation elements in a preset virtual coordinate space based on a map and the vehicle's location, including: determining the remaining distance data of the vehicle based on the map and the vehicle's location; and generating lane lines aligned with the spiral lane, text information for indicating the remaining distance data, and directional markers for indicating the exit of the spiral lane in the virtual coordinate space based on the map and the vehicle's location.
[0063] For example, the on-board device can determine information such as the total number of lane loops, lane gradient, and exit coordinates based on a map of the spiral lane. The on-board device can then determine the remaining distance based on the total number of lane loops, lane gradient, and vehicle position. For example, the parking lot depth can be calculated based on the total number of lane loops and lane gradient, and the remaining distance can be determined based on the parking lot depth and the Z-coordinate of the vehicle position.
[0064] Lane lines can be virtual 3D curves. Lane lines can conform to the centerline or boundary line of a spiral lane, presenting a continuous spatial spiral curve, and can be represented using highlight colors such as yellow or white. To enhance the three-dimensional effect, lane lines can be slightly thicker and inclined with the lane's slope, making them visually appear to conform to the ground.
[0065] The remaining distance data can reflect the remaining distance or the number of laps remaining. For example, the remaining distance data could be "1.2 laps" or "300 meters". Text information is used to indicate the remaining distance data; for example, the text information could be "1.2 laps remaining" or "300 meters remaining". Directional indicators can be three-dimensional arrows used to indicate the exit direction of the spiral track.
[0066] In some embodiments, the in-vehicle device can dynamically adjust and update lane lines, text information, and directional signs based on the vehicle's location.
[0067] In the embodiments of this application, the lane lines, prompt text, and directional markings described above are only some examples of navigation elements. In practical applications, navigation elements may also include more static and dynamic vector graphics and text to provide users with more comprehensive visual guidance. For example, navigation elements may also include text information indicating the vehicle's current driving progress, such as "Loop 2, 350 meters from the exit".
[0068] In this embodiment, the vehicle's trajectory data accurately reflects its movement. Based on the spiral lane map, information such as the total number of lane loops, lane gradient, and exit coordinates is determined. Therefore, based on the map and trajectory data, navigation elements providing visual guidance to the user can be accurately generated in the virtual coordinate space. These navigation elements intuitively display the vehicle's current position, exit direction, and remaining distance, allowing the user to have a clear and definite understanding of their location and travel progress. This reduces the psychological and visual illusion of being lost due to unknown environment, repetitive paths, or disorientation, as well as the resulting anxiety, effectively alleviating motion sickness symptoms such as dizziness and nausea.
[0069] In some embodiments of this application, the on-board device can determine the vehicle's motion state based on the vehicle's attitude and speed using preset motion state determination rules. These motion states include, but are not limited to: constant speed hovering, accelerating uphill, decelerating downhill, decelerating into a curve, and decelerating out of a curve. The examples of motion states given above are merely illustrations, and are not limited to these in practical applications.
[0070] The motion state determination rules can include the vehicle motion state corresponding to changes in vehicle attitude and vehicle speed. For example, if the vehicle speed is stable and the yaw angle ψ changes continuously and uniformly, the vehicle can be determined to be in a uniform turning state; or if the vehicle speed continues to increase while the pitch angle θ remains positive (the front of the car tilts up), the vehicle can be determined to be in an accelerating uphill state; or if the vehicle speed continues to decrease while the pitch angle θ is negative (the front of the car tilts down), the vehicle can be determined to be in a decelerating downhill state; or if the vehicle speed decreases while the rate of change of the yaw angle ψ changes, the vehicle can be determined to be in a decelerating entering or exiting a curve.
[0071] In this embodiment, the vehicle's motion state can be accurately determined based on the vehicle's attitude and speed, so that the transformation matrix of the navigation element can be accurately determined based on the motion state in the following text.
[0072] In some embodiments of this application, the vehicle-mounted device determines the transformation matrix of the navigation element based on the motion state, standard yaw rate, and standard lateral acceleration. This transformation matrix not only represents the transformation relationship between the virtual coordinate system corresponding to the virtual coordinate space and the world coordinate system corresponding to the vehicle, but also accurately describes the dynamic pose transformation of the navigation element in visual space caused by the vehicle's real-time yaw and lateral movements. The method for determining the transformation matrix can be found below. Figure 3 Explanation.
[0073] In some embodiments of this application, the vehicle-mounted device uses the transformation matrix corresponding to the navigation element to render the navigation element onto the environment image to obtain an augmented reality image. This includes: according to the transformation matrix and the calibration parameters of the sensor that acquires the environment image, the navigation element is perspective-matched from the virtual coordinate space to the coordinate space corresponding to the environment image to obtain a navigation element layer, and the navigation element layer is fused and superimposed with the environment image to obtain an augmented reality (AR) image.
[0074] The calibration parameters can include extrinsic and intrinsic parameters. Extrinsic parameters can be the transformation relationship between the camera coordinate system and the world coordinate system of the sensor that acquires the environmental image, while intrinsic parameters can be the transformation relationship between the camera coordinate system and the pixel coordinate system of the environmental image.
[0075] In some embodiments, the coordinate space corresponding to the environmental image can be determined by the pixel coordinate system of the environmental image. Navigation elements can be transformed from the world coordinate system to the pixel coordinate system according to calibration parameters to obtain a navigation element layer. Through rendering, the in-vehicle device can blend and overlay the navigation element layer with the environmental image to obtain an augmented reality image.
[0076] In some embodiments, the environmental image can be a 360-degree panoramic image, and multiple consecutive environmental images can constitute a real-time video stream. Accordingly, multiple augmented reality images generated by continuous rendering constitute an AR navigation video.
[0077] In other embodiments of this application, the in-vehicle device can transform navigation elements from a virtual coordinate system to a world coordinate system according to a transformation matrix, so that the visual representation of the navigation elements is synchronized with the vehicle's movement. For example, when the vehicle turns right at a specific angular velocity, the lane lines will also simulate a rightward flow effect, and their speed will match the severity of the vehicle's turn.
[0078] In this embodiment, navigation elements are rendered onto the environmental image based on the transformation matrix and the calibration parameters corresponding to the environmental image. This allows for dynamic adjustment of the flow speed, curvature, and position of the displayed navigation elements (such as lane lines), ensuring that the visual representation of the navigation elements in the augmented reality image is synchronized with the vehicle's movement. This effectively reduces the conflict between visual and vestibular sensations, thereby mitigating dizziness that may occur in scenarios involving continuous circular motion, such as spiral lanes.
[0079] S14 displays augmented reality images on the vehicle's display screen.
[0080] In some embodiments, the display screen may be a head-up display (HUD), or it may be a vehicle central control screen, digital instrument panel, streaming media rearview mirror, multimedia entertainment display screen, or other display screens such as a full LCD instrument panel. This application does not limit the specific type of display screen.
[0081] In some embodiments, the in-vehicle device can display multiple consecutive augmented reality images on a screen to enable the playback of AR navigation videos.
[0082] In this embodiment, augmented reality images are integrated with navigation elements and environmental images of the real road view. The augmented reality images are displayed on the screen, which can provide users with intuitive visual guidance integrated into the real scene. This eliminates the need for users to repeatedly refer to maps or memorize abstract instructions, thereby significantly reducing cognitive load and shortening decision-making time. In complex scenarios such as spiral lanes, a more relaxed and efficient driving experience can be achieved.
[0083] In some embodiments of this application, the vehicle-mounted device can communicate with a server, which may be a cloud server; this application does not limit this. The vehicle-mounted device can send driving trajectory data to the server, enabling the server to analyze the traffic efficiency bottlenecks of the spiral lane at different time periods based on the driving trajectory data of multiple vehicles, obtain analysis results, generate or optimize a global parking lot scheduling strategy based on the analysis results, and optimize and update the spiral lane map based on the analysis results to improve map accuracy.
[0084] The parking lot global scheduling strategy can indicate the deployment location and number of beacons and parking spaces in the parking lot. The server can communicate with the beacons and send the parking lot global scheduling strategy and optimized map to the management equipment of the beacons or spiral lanes.
[0085] In this embodiment, by using the server to analyze the vehicle's driving trajectory data, the traffic flow scheduling and parking space allocation of the parking lot can be dynamically optimized to obtain a global parking lot scheduling strategy. Based on the global parking lot scheduling strategy, the ineffective driving and waiting time of vehicles in the lanes can be reduced, thereby improving the overall operating efficiency of the parking lot.
[0086] In some embodiments of this application, the in-vehicle device can send the acquired multi-source data and the user's historical motion sickness tendency data to the server, so that the server can recommend personalized visual compensation intensity parameters for the vehicle based on the feature analysis of the historical motion sickness tendency data and multi-source data.
[0087] For example, visual compensation intensity parameters include, but are not limited to: yaw rate gain coefficient, lateral acceleration gain coefficient, target brightness value or compensation gain, color temperature adjustment coefficient, motion blur suppression intensity, etc.
[0088] Among them, the yaw rate gain coefficient can be used to control the speed at which navigation elements such as virtual lane lines flow laterally as the vehicle turns. The higher the yaw rate gain coefficient, the stronger the sense of flow, which is used to match vestibular perception and alleviate dizziness caused by sensory conflict.
[0089] The lateral acceleration gain coefficient can control the longitudinal stretching or lateral translation effect of navigation elements when the vehicle accelerates or decelerates or is subjected to centrifugal force, making the visual image more consistent with the inertial force felt by the body.
[0090] The target brightness value / compensation gain can be used to automatically adjust the overall brightness of the display based on ambient light (such as the strong light when driving out of an underground parking lot), ensuring that information is clearly visible and not dazzling under any lighting conditions.
[0091] The color temperature adjustment coefficient can be used to dynamically adjust the hue of the displayed content (such as leaning towards blue or yellow) based on the ambient light color temperature (such as the warm yellow light in a tunnel versus the cool white light outdoors), reducing visual fatigue and improving readability and realism.
[0092] Motion blur suppression can stabilize the displayed content on the screen by using reverse displacement or image interpolation algorithms when the vehicle is bumpy or shaking, reducing blur and ensuring sharp display.
[0093] Contrast enhancement factor can be used to increase the difference in brightness between the displayed content and the dark areas under poor visibility conditions such as low light or haze, making the outlines clearer and the details easier to distinguish.
[0094] In the vehicle control scheme provided in this application embodiment, beacon location provides vehicle position reference, and sensor data reflects vehicle motion status and ambient lighting conditions in real time. Therefore, by fusing beacon location and sensor data, continuous and smooth vehicle trajectory data can be accurately calculated. Based on the vehicle's trajectory data, the vehicle's position and motion can be accurately determined. Based on the spiral road map, the total number of spiral road loops, lane gradient, and exit coordinates can be accurately determined. Therefore, by combining the map and trajectory data with environmental images, an augmented reality image is generated. This augmented reality image integrates navigation elements with the environmental image of the real road view. Displaying the augmented reality image on the vehicle's screen provides users with intuitive visual guidance that fits the real scene, enabling users to form a clear and definite understanding of their own position and travel progress. This reduces the psychological and visual "being lost" illusion and the resulting anxiety caused by unknown environment, repetitive paths, or disorientation, effectively alleviating motion sickness symptoms such as dizziness and nausea.
[0095] In some embodiments of this application, the vehicle-mounted device can determine the transformation matrix of navigation elements based on the motion state, standard yaw rate, and standard lateral acceleration, wherein the transformation matrix may include rotation parameters and translation parameters. For example... Figure 3 The diagram shown is a flowchart of a method for determining a transformation matrix according to an embodiment of this application, including the following steps: S131, Based on the vehicle's motion state, determine the first proportional coefficient and the second proportional coefficient using a preset correspondence.
[0096] In some embodiments, the preset correspondence may include the association between the motion state and the first proportional coefficient and the second proportional coefficient. Therefore, based on the preset correspondence, the vehicle-mounted device can quickly determine the first proportional coefficient corresponding to the rotation parameter and the second proportional coefficient corresponding to the translation parameter.
[0097] S132, determine the rotation parameters based on the standard yaw rate and the first proportional coefficient.
[0098] In some embodiments, the vehicle-mounted device can perform an integral calculation on the standard yaw rate, and determine the rotation angle based on the integral result and a first proportionality coefficient, and determine the rotation parameters based on the trigonometric function value of the rotation angle. The rotation parameters can be matrices, for example, matrices with a dimension of 2×2. For example, the calculation method for the rotation parameters can refer to the following formulas (6)~(7); (6) (7) in, Indicates rotation parameters, Indicates the rotation angle. Indicates the standard yaw rate. This represents the first proportionality coefficient.
[0099] S133, determine the translation parameters based on the standard lateral acceleration and the second proportionality coefficient.
[0100] In some embodiments, the on-board equipment can perform a double integral operation on the standard lateral acceleration, and determine the lateral translation distance based on the integral result and a second proportionality coefficient, and determine the longitudinal translation distance based on the lateral translation distance and the second proportionality coefficient, and determine the translation parameters based on the lateral translation distance and the longitudinal translation distance. The translation parameters can be a 3×1 vector. For example, the calculation method for the translation parameters can refer to the following formulas (8) to (10): (8) (9) (10) in, Indicates the lateral translation distance. Indicates standard lateral acceleration. This represents the second proportionality coefficient. This indicates the longitudinal translation distance.
[0101] In this embodiment, a first proportional coefficient and a second proportional coefficient are determined based on the vehicle's motion state. The first proportional coefficient is adapted to the rotational sensitivity requirements of the corresponding motion state, and the second proportional coefficient is adapted to the translational amplitude requirements of the corresponding motion state. Rotation parameters are calculated based on the first proportional coefficient and a standard yaw rate, ensuring that the rotation parameters accurately reflect the visual mapping intensity of changes in vehicle direction. These rotation parameters control the visual rotation of navigation elements, synchronizing them with the vehicle's steering. Translation parameters are calculated based on the second proportional coefficient and a standard lateral acceleration, ensuring that the translation parameters accurately reflect the visual offset of the vehicle's lateral movement. These translation parameters control the visual translation amplitude of navigation elements, synchronizing them with the vehicle's lateral movement.
[0102] S134, generate the transformation matrix based on the rotation and translation parameters.
[0103] In some embodiments, a 3×3 matrix can be generated as the transformation matrix based on the rotation and translation parameters. For example, the formula for the transformation matrix can be found in the following formula (11): (11) in, Represents the transformation matrix. Indicates the rotation angle. Indicates the lateral translation distance. This indicates the longitudinal translation distance.
[0104] In this embodiment, since the driving trajectory data corresponds to the world coordinate system, the vehicle's motion state is determined based on the vehicle's attitude and speed. A first proportional coefficient and a second proportional coefficient are determined based on the motion state. Rotation parameters are determined based on the standard yaw rate and the first proportional coefficient. Translation parameters are determined based on the standard lateral acceleration and the second proportional coefficient. A rotation matrix is determined based on the rotation parameters and the translation parameters. This transformation matrix not only represents the transformation relationship between the virtual coordinate system corresponding to the virtual coordinate space and the world coordinate system corresponding to the vehicle, but also accurately describes the dynamic pose changes of navigation elements in visual space caused by the vehicle's real-time yaw and lateral movements.
[0105] In some embodiments of this application, the in-vehicle device can adjust the display parameters of the screen based on ambient light intensity and the vehicle's remaining range data to avoid discomfort and interference to the human eye caused by sudden changes in light, making the visual transition natural and smooth, and improving driving comfort. Figure 4 The diagram shown is a flowchart of a vehicle control method provided in another embodiment of this application, including the following steps: S21, Based on the current remaining distance data, determine the scene mode corresponding to the vehicle.
[0106] In some embodiments, scene markers can be used to indicate the vehicle's position relative to the spiral lane. For example, a scene mode can include three phases: "in the tunnel," "about to exit," and "exited," where "in the tunnel" may represent that the vehicle is currently traveling within the spiral lane of the parking lot, "about to exit" may represent that the vehicle is currently approaching the exit of the spiral lane, and "exited" may represent that the vehicle has already left the spiral lane.
[0107] In this embodiment, by determining the scene marker corresponding to the vehicle based on the current remaining distance data, the current scene mode of the vehicle can be determined.
[0108] S22, based on the scene markers corresponding to the scene mode, determine the desired light intensity and target color temperature using a preset mapping relationship.
[0109] In some embodiments, the on-board device can determine the scene flag corresponding to a scene mode based on a comparison of remaining mileage data with a preset threshold range. The preset threshold range can be customized, and this embodiment does not limit this. For example, the preset threshold range can be 0 to 1. The scene flag corresponding to each scene mode can be customized.
[0110] For example, when the preset threshold range is 0~1, if the remaining distance data is within 0~1, it can be determined that the vehicle is approaching the parking lot exit, and the current scene flag for the vehicle can be "EXITING_SOON"; if the remaining distance data is greater than 1, it can be determined that the vehicle is currently traveling in the parking lot's spiral lane, and the current scene flag for the vehicle can be "IN_TUNNEL"; if the remaining distance data is less than 0, it can be determined that the vehicle has already left the parking lot, and the current scene flag for the vehicle can be "OUTSIDE". The above examples of scene modes and corresponding scene flags are only illustrations, and are not limited to these in actual applications.
[0111] For example, if the remaining distance data is "1.2 laps", and the preset threshold range is 0 to 1, since "1.2 laps" is greater than 1, it is determined that the vehicle is currently driving in the spiral lane of the parking lot, and the scene flag corresponding to the vehicle can be "IN_TUNNEL".
[0112] In some embodiments, the preset mapping relationship may include the association between scene markers and desired light intensity and target color temperature. Therefore, based on the preset mapping relationship, the vehicle-mounted device can quickly determine the desired light intensity and target color temperature.
[0113] In this embodiment, the desired light intensity and target color temperature are determined based on the scene markers and using a preset mapping relationship, so that the desired light intensity and target color temperature can match the current scene mode of the vehicle.
[0114] S23, determine the target brightness based on the baseline ambient light intensity, the current ambient light intensity, and the desired light intensity.
[0115] In some embodiments, the baseline ambient light intensity may be the underground ambient light intensity obtained by the vehicle before entering the spiral lane.
[0116] In some embodiments, the in-vehicle device can be based on a reference ambient light intensity. Current ambient light intensity and desired light intensity The target brightness is determined using a feedback control algorithm. For example, the feedback control algorithm can be a proportional-integral (PI) control algorithm, a proportional-integral-derivative (PID) control algorithm, a fuzzy control algorithm, etc.
[0117] For example, taking the PI control algorithm as an example, the calculation method for the target brightness can refer to the following formula (12): (12) in, Indicates the target brightness at the current moment. This indicates the target brightness at the previous moment. Indicates proportional gain. Indicates the current ambient light intensity. Indicates the desired light intensity. This represents the integral gain. At t=1 It can be zero.
[0118] In this embodiment, the target brightness is determined based on the baseline ambient light intensity, the current ambient light intensity, and the desired light intensity, so that the target brightness matches the vehicle's current scene mode.
[0119] S24, adjust the display parameters of the display screen according to the target brightness and target color temperature.
[0120] In some embodiments, the display parameters may be parameters such as backlight brightness, RGB color channel gain, and contrast. This application embodiment does not limit the specific type of display parameters. For more explanation of the display parameters, please refer to the explanation of the visual compensation intensity parameter above.
[0121] In this embodiment, based on the ambient light intensity and scene markers corresponding to the scene mode, the brightness and contrast of the display screen (such as HUD) are smoothly and automatically adjusted in scenes such as "underground-transition-ground" or "ground-transition-underground". This allows the user's visual system to adapt to the drastic changes in external light in advance and gradually, obtaining a seamless visual transition experience. This effectively avoids glare, brief visual blurring, and potential safety risks caused by sudden changes in light when driving out of the parking lot, thereby improving driving comfort and safety when leaving the parking lot.
[0122] For example, the display parameter adjustment strategies used in different scene modes can refer to the following: IN_TUNNEL (in tunnels / underground): The display brightness is maintained at the same level as the baseline ambient light intensity. A correspondingly low level ensures clear information without causing glare; EXITING_SOON (about to exit): anticipates changes in light intensity based on the current ambient light level. Brightness is increased slowly and linearly, allowing the user's eyes to adapt to the strong external light in advance. OUTSIDE: The brightness is quickly adjusted to a high-brightness mode that matches the strong external light environment, ensuring that the displayed content remains clearly visible in bright environments.
[0123] like Figure 5The diagram shown is a schematic of a vehicle control method provided in an embodiment of this application. Taking the scenario of a vehicle leaving a parking lot as an example, the execution process of this method can be summarized into four stages. Stage one is initialization and scene perception, which completes initialization through power-on self-test and acquires data such as the parking lot map and ambient light intensity; Stage two is data acquisition and fusion positioning, which obtains the yaw rate ω through data acquisition. can and acceleration a lat_can By combining sensor data and positioning signals transmitted from UWB beacons, and through data fusion and collaborative localization calculations, the vehicle's three-dimensional position, attitude, and fused yaw rate ω can be determined. fused , fusion lateral acceleration a lat_fused Equipped with driving trajectory data; in Phase 3, based on the fused yaw rate ω fused , fusion lateral acceleration a lat_fused Virtual navigation elements are generated from driving trajectory data. Visual-vestibular compensation calculations are performed to determine the dynamic transformation matrix corresponding to each virtual navigation element. Based on ambient light intensity and the current scene mode, the target brightness and color temperature are determined. In stage four, AR video frames for HUD display are dynamically rendered and synthesized based on the navigation elements and their transformation matrices. The HUD display parameters are adjusted according to the target brightness and color temperature, thus projecting a real-world AR navigation image onto the vehicle's windshield. When the vehicle leaves the parking lot, the driving data can be sent to the cloud, enabling the cloud to analyze and optimize the parking lot's overall operational strategy.
[0124] like Figure 6 The diagram shown is a structural schematic of an in-vehicle device provided in one embodiment of this application. The in-vehicle device 10 can be an in-vehicle device, a computer, a mobile phone, a tablet computer, a laptop computer, a server, or other devices. This application embodiment does not impose any restrictions on the specific type of the in-vehicle device 10.
[0125] exist Figure 6 The vehicle-mounted device 10 may include a communication module 101, a memory 102, a processor 103, an input / output (I / O) interface 104, and a bus 105. The processor 103 is coupled to the communication module 101, the memory 102, and the input / output interface 104 via the bus 105.
[0126] Communication module 101 may include a wired communication module and / or a wireless communication module. The wired communication module may provide one or more wired communication solutions such as Universal Serial Bus (USB) and Controller Area Network (CAN). The wireless communication module may provide one or more wireless communication solutions such as Wireless Fidelity (Wi-Fi), Bluetooth (BT), mobile communication networks, frequency modulation (FM), near field communication (NFC), and infrared (IR).
[0127] Memory 102 may include one or more random access memory (RAM) and one or more non-volatile memory (NVM). The RAM can be directly read and written by the processor 103, and can be used to store executable programs (e.g., machine instructions) of other running programs, as well as user and application data. The RAM may include static random-access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), etc.
[0128] Non-volatile memory can also store executable programs and user and application data, and can be pre-loaded into random access memory for direct reading and writing by the processor 103. Non-volatile memory can include disk storage devices and flash memory.
[0129] The memory 102 is used to store one or more computer programs. The one or more computer programs are configured to be executed by the processor 103. The one or more computer programs include multiple instructions that, when executed by the processor 103, can implement a vehicle control method executed on the vehicle-mounted device 10.
[0130] In other embodiments, such as Figure 6 The vehicle-mounted device 10 shown also includes an external memory interface for connecting to an external memory to expand the storage capacity of the vehicle-mounted device 10.
[0131] Processor 103 may include one or more processing units, such as application processors (APs), modem processors, graphics processing units (GPUs), image signal processors (ISPs), controllers, video codecs, digital signal processors (DSPs), and / or neural network processing units (NPUs). These different processing units may be independent devices or integrated into one or more processors.
[0132] The processor 103 provides computing and control capabilities. For example, the processor 103 is used to execute computer programs stored in the memory 102 to implement the vehicle control method described above.
[0133] The input / output interface 104 is used to provide a channel for user input or output. For example, the input / output interface 104 can be used to connect various input / output devices, such as a mouse, keyboard, touch device, display screen, etc., so that users can enter information or visualize information.
[0134] Bus 105 is used at least to provide a channel for communication between the communication module 101, memory 102, processor 103, and input / output interface 104 in the vehicle device 10.
[0135] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the vehicle-mounted device 10. In other embodiments of this application, the vehicle-mounted device 10 may include more or fewer components than illustrated, or combine some components, or split some components, or have different component arrangements. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.
[0136] This application embodiment also provides a vehicle, including the aforementioned vehicle-mounted equipment, for example... Figure 6 The vehicle-mounted device 10 is described above. The vehicle can be a car, sedan, motorcycle, all-terrain vehicle, etc., and this application embodiment does not limit the specific type of vehicle.
[0137] This application also provides a computer-readable storage medium storing a computer program, which includes program instructions. When the program instructions are executed, the method implemented can refer to the methods in the above embodiments of this application.
[0138] The computer-readable storage medium can be the internal storage of the vehicle-mounted device described in the above embodiments, such as the hard drive or memory of the vehicle-mounted device. Alternatively, the computer-readable storage medium can be an external storage device of the vehicle-mounted device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card.
[0139] In some embodiments, a computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, etc.; and the data storage area may store data created based on the use of the in-vehicle device, etc.
[0140] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules is only a logical functional division, and other division methods may be used in actual implementation.
[0141] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.
[0142] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or in the form of hardware plus software functional modules.
[0143] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of this application is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be embraced within this application. No appended diagram markings in the claims should be construed as limiting the scope of the claims.
[0144] Furthermore, it is clear that the word "comprising" does not exclude other units or steps, and the singular does not exclude the plural. Multiple units or devices described in this application may also be implemented by a single unit or device through software or hardware. The terms "first," "second," etc., are used to indicate names and do not indicate any specific order.
[0145] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit it. Although this application has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of this application without departing from the spirit and scope of the technical solutions of this application.
Claims
1. A vehicle control method, characterized in that, The method includes: While the vehicle is traveling on the spiral track, multi-source data is acquired, including a map of the spiral track, beacon positions corresponding to the beacons set on the spiral track, and sensor data of the vehicle, including environmental images and dynamic parameters of the vehicle. Based on the beacon location and the dynamic parameters, the vehicle's trajectory data is determined; Based on the map, the driving trajectory data, and the environmental image, an augmented reality image is generated and displayed on the vehicle's display screen. The augmented reality image includes navigation elements, which are used to provide visual guidance to the user.
2. The vehicle control method according to claim 1, characterized in that, The dynamic parameters include the initial yaw rate and the initial lateral acceleration. The determination of the vehicle's trajectory data based on the beacon position and the dynamic parameters includes: The beacon position, the initial yaw rate, and the initial lateral acceleration are tightly coupled and fused to obtain the vehicle's standard yaw rate, standard lateral acceleration, and vehicle attitude. The vehicle's location is determined based on the beacon's position; The vehicle speed is determined by using multiple beacon locations and the acquisition time corresponding to each beacon location; The driving trajectory data is obtained based on the standard yaw rate, the standard lateral acceleration, the vehicle attitude, the vehicle position, and the vehicle speed.
3. The vehicle control method according to claim 2, characterized in that, The method for generating augmented reality images includes: Based on the map and the vehicle's location, the navigation elements are generated in a preset virtual coordinate space; The motion state of the vehicle is determined based on the vehicle's posture and speed. The transformation matrix of the navigation element is determined based on the motion state, the standard yaw rate, and the standard lateral acceleration. The navigation elements are rendered onto the environment image using the transformation matrix to obtain the augmented reality image.
4. The vehicle control method according to claim 3, characterized in that, The step of generating navigation elements in a preset virtual coordinate space based on the map and the vehicle's location includes: Based on the map and the vehicle's location, determine the vehicle's remaining distance data; Based on the map and the vehicle's location, in the virtual coordinate space, lane lines aligned with the spiral lane, text information indicating the remaining distance data, and directional markers indicating the exit of the spiral lane are generated.
5. The vehicle control method according to claim 4, characterized in that, The multi-source data also includes ambient light intensity, and the method further includes: Based on the current remaining distance data, the scene mode corresponding to the vehicle is determined, and the scene mode is used to indicate the position of the vehicle relative to the spiral lane; Based on the scene markers corresponding to the scene mode, the desired light intensity and target color temperature are determined using a preset mapping relationship; The target brightness is determined based on the baseline ambient light intensity, the current ambient light intensity, and the desired light intensity. The display parameters of the display screen are adjusted according to the target brightness and the target color temperature.
6. The vehicle control method according to claim 3, characterized in that, The transformation matrix includes rotation parameters and translation parameters. Determining the transformation matrix of the navigation element based on the motion state, the standard yaw rate, and the standard lateral acceleration includes: Based on the motion state, using a preset correspondence, determine the first proportional coefficient corresponding to the rotation parameter and the second proportional coefficient corresponding to the translation parameter; The rotation parameters are determined based on the standard yaw rate and the first proportionality coefficient; The translation parameters are determined based on the standard lateral acceleration and the second proportionality coefficient.
7. The vehicle control method according to claim 3, characterized in that, The step of rendering the navigation elements onto the environment image using the transformation matrix to obtain an augmented reality image includes: Based on the transformation matrix and the calibration parameters of the sensor that acquired the environmental image, the navigation elements are perspective-matched from the virtual coordinate space to the coordinate space corresponding to the environmental image to obtain a navigation element layer; The navigation element layer is merged and overlaid with the environment image to obtain the augmented reality image.
8. A vehicle-mounted device, characterized in that, The vehicle-mounted equipment includes: processor; The memory; and the application program, wherein the application program is stored in the memory and configured to be executed by the processor to implement the vehicle control method as described in any one of claims 1 to 7.
9. A vehicle, characterized in that, The vehicle includes the on-board equipment as described in claim 8.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor of an on-board device, implements the vehicle control method as described in any one of claims 1 to 7.