Vehicle cabin area positioning system and vehicle cabin area control method

Abstract

The invention relates to a vehicle cabin area positioning system and a vehicle cabin area control method, and relates to the technical field of vehicle positioning. The system comprises a satellite positioning chip, an inertial measurement sensor, a wireless communication module, a vehicle cabin domain controller and a display screen. The satellite positioning chip is used for receiving a Beidou satellite positioning signal and sending basic geographic position information to the vehicle cabin domain controller; the inertial measurement sensor is used for collecting the acceleration and the angular velocity of the vehicle and estimating the motion state of the vehicle based on the acceleration and the angular velocity; the wireless communication module is used for determining auxiliary position information of the vehicle and sending the auxiliary position information to the vehicle cabin domain controller; the vehicle cabin domain controller is used for fusing and processing data output by the satellite positioning chip, the inertial measurement sensor and the wireless communication module and generating a final navigation positioning result of the vehicle; and the display screen is used for visually displaying the final navigation positioning result of the vehicle.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of vehicle positioning technology, and in particular to a vehicle cabin domain positioning system and a vehicle cabin domain control method. Background Art

[0002] As the large-scale application of the Beidou system enters a critical stage of marketization, industrialization, and internationalization, intelligent connected vehicles, as an important emerging application field, have an increasing demand for high-computing-power intelligent cockpit domain controllers.

[0003] Existing Beidou positioning systems for vehicle positioning typically focus on directly utilizing geographic location information provided by Beidou satellites. This approach relies on a Beidou receiver mounted on the vehicle to capture satellite signals and determine the vehicle's longitude, latitude, and altitude. To improve positioning accuracy, data from an inertial measurement unit (IMU) is sometimes combined through algorithmic fusion to compensate for position errors caused by unstable or temporary satellite signal loss.

[0004] However, the integration of such systems is relatively low, and in environments with poor satellite signal coverage, the vehicle positioning method is relatively simple and has poor accuracy. Summary of the Invention

[0005] The embodiments of the present application provide a vehicle cabin domain positioning system and a vehicle cabin domain control method, which can improve the accuracy of vehicle cabin domain positioning. The technical solution is as follows:

[0006] In one aspect, a vehicle cockpit domain positioning system is provided, the system comprising a satellite positioning chip, an inertial measurement sensor, a wireless communication module, a vehicle cockpit domain controller, and a display screen;

[0007] The vehicle cockpit domain controller is communicatively connected to the satellite positioning chip, the inertial measurement sensor, the wireless communication module and the display screen respectively;

[0008] The satellite positioning chip is used to receive Beidou satellite positioning signals and send basic geographic location information to the vehicle cockpit domain controller, where the basic geographic location information includes longitude, latitude and altitude;

[0009] The inertial measurement sensor is used to collect the acceleration and angular velocity of the vehicle and estimate the motion state of the vehicle based on the acceleration and the angular velocity, wherein the motion state includes position, velocity and heading angle;

[0010] The wireless communication module is used to determine auxiliary position information of the vehicle and send the auxiliary position information to the vehicle cabin domain controller, wherein the auxiliary position information is the position information of the vehicle in an indoor environment or a scenario with weak satellite signals;

[0011] The vehicle cockpit domain controller is configured to integrate and process data output by the satellite positioning chip, the inertial measurement sensor, and the wireless communication module to generate a final navigation positioning result for the vehicle, wherein the final navigation positioning result is the vehicle's current position information;

[0012] The display screen is used to visually display the final navigation positioning result of the vehicle.

[0013] In some embodiments, the inertial measurement sensor is used to:

[0014] Obtaining a basic body speed and a basic three-dimensional angular velocity of the vehicle;

[0015] performing correction compensation on a base body speed and a base three-dimensional angular velocity of the vehicle using pre-calibrated compensation parameters to obtain a corrected and compensated target body speed and target three-dimensional angular velocity, wherein the compensation parameters include an accelerometer bias and a gyroscope drift rate;

[0016] Inertial odometry calculation is performed based on the target vehicle body speed and the target three-dimensional angular velocity.

[0017] In some embodiments, the vehicle cockpit domain controller is further configured to:

[0018] Constructing a dead reckoning model based on the inertial mileage calculation result and a vehicle body CAN (Controller Area Network) signal, the dead reckoning model comprising a combination of one or more of a two-wheel differential model, an Ackermann steering model, and an inertial measurement geometry model;

[0019] The target vehicle body speed, the target three-dimensional angular velocity, and the basic geographic location information are input into a constructed position calculation model to obtain the current vehicle position output by the position calculation model.

[0020] In some embodiments, the vehicle cockpit domain controller is further configured to:

[0021] DR filtering is performed on the current vehicle position output by the position estimation model to obtain a first position estimation value.

[0022] In some embodiments, the vehicle cockpit domain controller is further configured to:

[0023] Real-time detection of the quality of the Beidou satellite positioning signal;

[0024] When the signal strength of the Beidou satellite positioning signal meets a preset condition, a local filtering operation is performed on the Beidou satellite positioning signal to obtain filtered Beidou position information.

[0025] In some embodiments, the vehicle cockpit domain controller is further configured to:

[0026] Based on the first position estimate and the filtered Beidou position signal, a fusion process is performed through a main filtering algorithm to obtain a final navigation positioning result.

[0027] In some embodiments, the satellite positioning chip is further used to:

[0028] After the vehicle is started and the Beidou signal state is stable, initial positioning information of the vehicle is obtained, where the initial positioning information includes the position of the starting point and the heading angle of the vehicle.

[0029] In some embodiments, the wireless communication module is used to:

[0030] Acquiring positioning assistance data, the positioning assistance data including signal strengths of Bluetooth beacons and / or wireless access points in the vicinity of the vehicle, physical addresses of beacons and / or access points of the wireless access points, and estimated distances between the vehicle and the nearby Bluetooth beacons and / or wireless access points;

[0031] Based on the positioning assistance data, as well as the positions of Bluetooth beacons and wireless access points, auxiliary position information of the vehicle is determined using multilateration.

[0032] In some embodiments, the wireless communication module is used to:

[0033] The auxiliary position information of the vehicle is sent to the vehicle cockpit domain controller in a specified data frame format.

[0034] On the other hand, a vehicle cockpit domain positioning method is provided, the method being performed by the vehicle cockpit domain positioning system, the method comprising:

[0035] Receive Beidou satellite positioning signals through the satellite positioning chip and send basic geographic location information to the vehicle cockpit domain controller, where the basic geographic location information includes longitude, latitude and altitude;

[0036] collecting the acceleration and angular velocity of the vehicle through the inertial measurement sensor, and estimating the motion state of the vehicle based on the acceleration and the angular velocity, the motion state including position, velocity and heading angle;

[0037] Determining auxiliary position information of the vehicle through the wireless communication module and sending the auxiliary position information to the vehicle cabin domain controller, wherein the auxiliary position information is position information of the vehicle in an indoor environment or a scenario with weak satellite signals;

[0038] The vehicle cockpit domain controller fuses and processes the data output by the satellite positioning chip, the inertial measurement sensor, and the wireless communication module to generate final position information of the vehicle;

[0039] The final position information of the vehicle is visually displayed on the display screen.

[0040] The technical solution provided by this application may have the following beneficial effects:

[0041] The satellite positioning chip provides high-precision vehicle geographic location information, the inertial measurement sensor estimates the vehicle's motion state by integrating acceleration and angular velocity, and the wireless communication module provides auxiliary positioning information for the vehicle when the satellite signal is weak. The vehicle cabin domain controller adopts a multi-sensor fusion algorithm, combining the advantages of each module. By integrating multi-source data from the satellite positioning chip, inertial measurement sensor and wireless communication module, it improves the vehicle's positioning accuracy in complex environments, thereby effectively suppressing the impact of single sensor errors, improving the real-time and stability of the vehicle positioning system, and achieving high-precision and continuous navigation positioning effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0043] Figure 1 This is a system diagram of an application environment of a vehicle cockpit domain positioning system involved in one embodiment of the present application;

[0044] Figure 2 This is a structural diagram of a vehicle cabin domain positioning system provided by one embodiment of the present application;

[0045] Figure 3 This is a flow chart of a vehicle cabin domain positioning method provided by an embodiment of the present application;

[0046] Figure 4 This is a technical schematic diagram of an intelligent cockpit domain controller of a Beidou positioning system provided by one embodiment of the present application;

[0047] Figure 5 This is a workflow diagram of the Beidou positioning system provided by one embodiment of the present application;

[0048] Figure 6 It is a schematic diagram of a navigation algorithm provided by an embodiment of the present application. DETAILED DESCRIPTION

[0049] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0050] like Figure 1 As shown, Figure 1 This is a system diagram of the vehicle cockpit domain positioning system application environment involved in one embodiment of the present application. Figure 1 As shown, Figure 1 The vehicle 100 is equipped with a vehicle cabin domain positioning system 10. The vehicle cabin domain positioning system 10 can receive Beidou satellite positioning signals and determine the vehicle's current position information based on the Beidou satellite positioning signals.

[0051] like Figure 2 As shown, Figure 2 This is a structural diagram of a vehicle cockpit domain positioning system provided by one embodiment of the present application. The system includes a satellite positioning chip 22, an inertial measurement sensor 23, a wireless communication module 24, a vehicle cockpit domain controller 21, and a display screen 25;

[0052] The vehicle cabin domain controller 21 is respectively connected to the satellite positioning chip 22, the inertial measurement sensor 23, the wireless communication module 24 and the display screen 25;

[0053] The satellite positioning chip 22 is used to receive Beidou satellite positioning signals and send basic geographic location information to the vehicle cockpit domain controller 21. The basic geographic location information includes longitude, latitude and altitude;

[0054] An inertial measurement sensor 23 is used to collect the acceleration and angular velocity of the vehicle and estimate the vehicle's motion state based on the acceleration and angular velocity, where the motion state includes position, velocity, and heading angle;

[0055] The wireless communication module 24 is used to determine the auxiliary position information of the vehicle and send the auxiliary position information to the vehicle cabin domain controller 21. The auxiliary position information is the position information of the vehicle in an indoor environment or in a scene with weak satellite signals;

[0056] The vehicle cockpit domain controller 21 is used to integrate and process the data output by the satellite positioning chip 22, the inertial measurement sensor 23 and the wireless communication module 24 to generate the final navigation positioning result of the vehicle. The final navigation positioning result is the vehicle's current position information;

[0057] The display screen 25 is used to visually display the final navigation positioning result of the vehicle.

[0058] Among them, the above-mentioned satellite positioning chip refers to a hardware module that can receive signals from the global navigation satellite system, and in this application it can be a positioning chip that supports the Beidou system.

[0059] In an embodiment of the present application, the satellite positioning chip can receive the L1 frequency band signal transmitted by the Beidou satellite through an antenna, and use the triangulation principle (i.e., the distance from multiple satellites to the receiver) to calculate the three-dimensional coordinates (longitude, latitude and altitude) as the basic geographic location information of the vehicle.

[0060] The inertial measurement sensor is a sensor including an accelerometer and a gyroscope, and is used to measure the linear acceleration and angular velocity of an object.

[0061] In an embodiment of the present application, the inertial measurement sensor can obtain velocity by integrating acceleration, and then obtain displacement by integrating velocity, and at the same time, combine with the gyroscope to measure the change in heading angle to perform track calculation.

[0062] The wireless communication module is a hardware device with short-range communication capabilities, which is used to obtain information about surrounding beacons or access points to assist in positioning.

[0063] In an embodiment of the present application, the wireless communication module scans the signal strength of surrounding Bluetooth beacons or Wi-Fi access points, estimates the distance based on the position of the Bluetooth beacon or Wi-Fi access point and the signal attenuation model, and then calculates the auxiliary position through multilateration.

[0064] Among them, the above-mentioned vehicle cockpit domain controller is the central control unit in the vehicle responsible for centrally processing cockpit-related functions.

[0065] In an embodiment of the present application, the vehicle cabin domain controller runs an embedded operating system, integrates a multi-sensor fusion algorithm, performs weighted fusion on data from the satellite positioning chip, inertial measurement sensor and wireless communication module, and outputs the optimal estimated position information as the vehicle's current position information.

[0066] The display screen is part of the in-vehicle infotainment system and is used to visually display the positioning results to the driver or passengers.

[0067] In an embodiment of the present application, the display screen is connected to the vehicle cockpit domain controller through a specific interface, and the location information sent by the vehicle cockpit domain controller is received and displayed on the digital map.

[0068] In an embodiment of the present application, the satellite positioning chip provides high-precision geographic location information of the vehicle, the inertial measurement sensor estimates the vehicle's motion state by integrating acceleration and angular velocity, and the wireless communication module provides auxiliary positioning information of the vehicle when the satellite signal is weak. The vehicle cabin domain controller adopts a multi-sensor fusion algorithm, combining the advantages of each module, and improving the positioning accuracy of the vehicle in complex environments by integrating multi-source data from the satellite positioning chip, inertial measurement sensor and wireless communication module, thereby effectively suppressing the influence of single sensor errors, improving the real-time and stability of the vehicle positioning system, and achieving high-precision and continuous navigation positioning effects.

[0069] Based on any one or more of the above embodiments, in a possible implementation, the inertial measurement sensor is used to obtain a basic body speed and a basic three-dimensional angular velocity of the vehicle;

[0070] Correction compensation is performed on the vehicle's base body speed and base three-dimensional angular velocity using pre-calibrated compensation parameters to obtain a corrected target body speed and target three-dimensional angular velocity. The compensation parameters include accelerometer bias and gyroscope drift rate.

[0071] Inertial odometry calculation is performed based on the target vehicle body speed and target three-dimensional angular velocity.

[0072] The basic vehicle body speed refers to the speed of the vehicle relative to the ground during driving.

[0073] The basic three-dimensional angular velocity refers to the rate at which the vehicle rotates around its three main axes (such as the front and rear axes, the left and right axes, and the axis perpendicular to the bottom surface of the vehicle).

[0074] In the embodiment of the present application, the accelerometer calculates the vehicle body speed by sensing the linear acceleration of the vehicle in various directions; the gyroscope is used to detect the angular velocity generated when the vehicle rotates around each axis.

[0075] In the embodiments of this application, calibration and compensation is the process of correcting the base vehicle velocity and three-dimensional angular velocity measured by the inertial measurement sensor. The purpose of calibration and compensation is to reduce the position estimation bias caused by sensor errors. Compensation parameters include accelerometer bias (i.e., the deviation of the output value when there is no acceleration) and gyroscope drift (the degree to which the output value gradually deviates from the true value after long-term use).

[0076] In the embodiment of the present application, the inertial measurement odometer calculation estimates the distance moved by the vehicle and the process of posture change based on the calibrated target vehicle body speed and target three-dimensional angular velocity combined with the time interval.

[0077] In an embodiment of the present application, the inertial measurement sensor accumulates the continuous target vehicle body speed over a period of time through a numerical integration method to obtain the displacement; for posture changes, it is necessary to perform an integration operation on the three-dimensional angular velocity to update the vehicle's posture matrix.

[0078] In the embodiment of the present application, by applying compensation parameters, the deviation between the target vehicle body speed and the target three-dimensional angular velocity can be effectively reduced, and the accuracy of the inertial measurement mileage calculation result can be effectively improved.

[0079] Based on any one or more of the above embodiments, in one possible implementation, the vehicle cockpit domain controller is further configured to construct a dead reckoning model based on the result of inertial measurement odometer calculation and the vehicle body CAN signal, where the dead reckoning model includes a combination of one or more of a two-wheel differential model, an Ackermann steering model, and an inertial measurement geometry model.

[0080] The target vehicle body speed, target three-dimensional angular velocity, and basic geographic location information are input into the constructed position calculation model to obtain the current vehicle position output by the position calculation model.

[0081] The vehicle body CAN signal is real-time status information transmitted on the vehicle's internal controller area network bus, including but not limited to the vehicle's wheel speed, steering angle, gear position, and braking status.

[0082] The position estimation model is a mathematical model based on the vehicle kinematics principle, which is used to predict or estimate the position of the vehicle at a certain moment.

[0083] The two-wheel differential model uses the speed difference between the left and right wheels to estimate the turning radius and heading angle.

[0084] The Ackerman steering model is used to consider the geometric relationship between the front wheel steering angle and the vehicle's trajectory.

[0085] The above-mentioned inertial measurement geometric model can be combined with the data of the inertial measurement sensor (such as acceleration and angular velocity) to perform spatial coordinate transformation and estimate the vehicle posture.

[0086] In this embodiment, the vehicle cockpit domain controller receives the calibrated target vehicle body speed and three-dimensional angular velocity data, and simultaneously obtains the left and right wheel speed information provided by the wheel speed sensor, the front wheel steering angle output by the steering wheel angle sensor, and other key parameters such as gear position and brake status through the CAN bus. The vehicle cockpit domain controller selects an appropriate model based on the current vehicle driving state and environmental conditions. For example, when driving at low speeds and with a significant wheel speed difference, the two-wheel differential model is used to estimate the turning radius and heading angle change based on the difference in left and right wheel speeds. The Ackerman steering model is selected for complex turning conditions on urban roads, and the relationship between the front wheel angle and wheelbase is used to establish a vehicle trajectory prediction equation. When the GNSS (Global Navigation Satellite System) signal is lost, the inertial measurement geometry model is selected to perform an integration operation based on the acceleration and angular velocity measured by the inertial measurement sensor to derive the vehicle's displacement and attitude change. After completing the construction of the position calculation model, the vehicle cockpit domain controller uses the target vehicle body speed, target three-dimensional angular velocity and basic geographic location information provided by the satellite positioning chip as input variables of the position calculation model, and substitutes them into the above position calculation model for recursive calculation.

[0087] In an embodiment of the present application, after the vehicle cockpit domain controller integrates the position calculation model with the inertial measurement data and satellite positioning information, it can effectively improve the positioning accuracy and robustness of the vehicle cockpit domain controller in complex environments, reduce the error accumulation problem during long-term operation, and thus achieve a more stable, continuous and high-precision vehicle positioning effect.

[0088] Based on any one or more of the above embodiments, in a possible implementation, the vehicle cockpit domain controller is further used to perform DR filtering processing on the current vehicle position output by the position estimation model to obtain a first position estimate value.

[0089] The DR filter mentioned above refers to the Dead Reckoning (DR) filter, a filtering method that fuses continuous position calculation results with historical state information. It is often used to enhance vehicle positioning stability when GNSS signals are unavailable. Its core is to use filtering algorithms (such as Kalman filtering and extended Kalman filtering (EKF)) to perform weighted averaging and prediction correction on continuous position sequences, thereby reducing error accumulation.

[0090] Among them, the above-mentioned first position estimation value refers to the optimized vehicle position information output after DR filtering processing, which has higher stability and lower error accumulation rate compared with the original position estimation result.

[0091] In some embodiments, the first position estimate is structured data including fields such as timestamp, coordinates, heading angle, and confidence level.

[0092] In an embodiment of the present application, the current position output by the position estimation model has uncertainty due to factors such as sensor errors and modeling deviations. Direct use may cause positioning drift. By performing DR filtering on the position information, DR filtering can combine the continuity and dynamic constraints of vehicle motion and has good robustness to sudden errors, thereby improving the positioning accuracy and continuity of the vehicle cabin domain positioning system in complex environments, and ultimately achieving more reliable high-precision positioning output.

[0093] Based on any one or more of the above embodiments, in a possible implementation, the vehicle cockpit domain controller is further used to detect the quality of the Beidou satellite positioning signal in real time;

[0094] When the signal strength of the Beidou satellite positioning signal meets the preset conditions, a local filtering operation is performed on the Beidou satellite positioning signal to obtain the filtered Beidou position information.

[0095] Among them, the above-mentioned preset conditions refer to the signal quality judgment standards set by the vehicle cabin domain controller according to actual application requirements. For example, the signal strength of the Beidou satellite positioning signal is higher than a certain signal strength threshold.

[0096] The above-mentioned local filtering operation is a preliminary filtering process performed on the GNSS raw observation data level, the purpose of which is to remove noise, suppress instantaneous errors, and improve the stability of single positioning results.

[0097] Among them, the above-mentioned filtered Beidou position information is the optimized vehicle position data output after local filtering processing. The filtered Beidou position information can include longitude, latitude, altitude, heading angle, and speed.

[0098] In an embodiment of the present application, when the Beidou satellite positioning signal meets the preset conditions, the vehicle cabin domain controller enables the local filtering algorithm, and the filtering input is the position coordinates (latitude and longitude), speed, and timestamp (PVT) output by the original GNSS, and the output is the optimized Beidou position information.

[0099] In an embodiment of the present application, when the signal strength of the Beidou satellite positioning signal meets the preset conditions, it indicates that the received data has a high degree of credibility. At this time, local filtering is performed on the Beidou satellite positioning signal, which can effectively remove noise, further improve the purity of the position information, and effectively improve the accuracy of the Beidou position information.

[0100] Based on any one or more of the above embodiments, in a possible implementation, the vehicle cabin domain controller is further used to perform fusion processing through a main filtering algorithm based on the first position estimate and the filtered Beidou position signal to obtain a final navigation positioning result.

[0101] Among them, the above-mentioned main filtering algorithm is responsible for weighted fusion of the data output by the satellite positioning chip, inertial measurement sensor and wireless communication module, and outputting the optimal estimated state.

[0102] In one possible implementation, the vehicle cockpit domain controller is further used to perform multi-source data fusion processing through a main filtering algorithm based on the first position estimate and the filtered Beidou position signal to obtain a final navigation positioning result.

[0103] Among them, the main filtering algorithm integrates the GNSS information output by the satellite positioning chip, the motion status data collected by the inertial measurement unit, and the auxiliary positioning information provided by the wireless communication module, and dynamically adjusts the weighting coefficients of each input according to the real-time confidence of different sensors to achieve the output of the optimal estimation state.

[0104] Furthermore, during the weighted fusion process, weights are assigned based on factors including, but not limited to, GNSS signal strength and the number of visible satellites, gyroscope and accelerometer noise levels, wireless communication module signal latency and packet loss rate, and consistency errors in historical positioning trajectories. By quantitatively evaluating these influencing factors and feeding them into a pre-trained machine learning model (e.g., a neural network or random forest), the model outputs a dynamic weight allocation strategy for different sensor channels, enabling more accurate position fusion calculations.

[0105] Preferably, the machine learning model is trained with a large amount of real road test data, covering a variety of typical application scenarios (e.g., high-speed driving, densely built-up areas in urban areas, and underground garages). The machine learning model can also integrate an online learning mechanism and has the ability to adaptively adjust weight parameters according to actual operating conditions.

[0106] Among them, the above-mentioned final navigation and positioning result refers to the optimal vehicle position estimate output by the main filtering algorithm after fusing multi-source positioning data. The final navigation and positioning result has high precision, high stability and high continuity, and can be used for navigation display, path planning, parking guidance and other functions.

[0107] In this embodiment, the vehicle cabin domain controller performs time synchronization and coordinate uniform conversion on the first position estimate value and the filtered Beidou position signal, inputs the converted first position estimate value and Beidou position signal into the main filtering algorithm, and obtains the final navigation positioning result output by the main filtering algorithm.

[0108] In an embodiment of the present application, by combining the first position estimate with the filtered Beidou position signal and applying the main filtering algorithm for data fusion processing, the final navigation positioning result of the vehicle is accurately calculated, thereby improving the accuracy of the vehicle navigation positioning.

[0109] Based on any one or more of the above embodiments, in a possible implementation method, the vehicle cabin domain controller and the satellite positioning chip are also used to obtain the vehicle's initial positioning information after the vehicle is started and the Beidou signal status is stable. The initial positioning information includes the position of the vehicle's starting point and the heading angle.

[0110] Among them, the above-mentioned stable Beidou signal status means that the satellite positioning chip has successfully captured a sufficient number of Beidou satellite signals and can continuously output high-quality positioning data.

[0111] The initial positioning information refers to the exact location of the vehicle at the beginning of the trip.

[0112] The starting point refers to the geographical coordinates of the vehicle at the start of the trip.

[0113] The heading angle refers to the angle of the vehicle's forward direction relative to true north, and is used to describe the vehicle's attitude direction.

[0114] In an embodiment of the present application, after the vehicle is started and the Beidou signal status is stable, the satellite positioning chip obtains the vehicle's initial positioning information (including the position and heading angle of the starting point), effectively ensuring the accuracy of the vehicle's initial positioning information.

[0115] Based on any one or more of the foregoing embodiments, in one possible implementation, the wireless communication module is configured to obtain positioning assistance data, where the positioning assistance data includes signal strengths of Bluetooth beacons and / or wireless access points in the vicinity of the vehicle, beacons of wireless access points and / or physical addresses of access points, and estimated distances between the vehicle and the nearby Bluetooth and wireless access points;

[0116] Based on the positioning assistance data, as well as the positions of Bluetooth beacons and wireless access points, multilateration is used to determine the vehicle's auxiliary position information.

[0117] The above-mentioned multilateration method is a geometric method for estimating the target position based on the distance relationship between multiple known reference points and the target point.

[0118] The wireless communication module draws multiple virtual circles on a two-dimensional plane with each beacon or access point as the center and the estimated distance from the beacon to the vehicle as the radius. By calculating the intersection point or optimal approach point of the circles, the coordinate position of the vehicle is determined, thereby achieving auxiliary positioning of the vehicle and determining the auxiliary position information of the vehicle.

[0119] In an embodiment of the present application, positioning auxiliary data such as the signal strength, physical address and estimated distance of Bluetooth beacons or wireless access points around the vehicle are obtained through a wireless communication module, and combined with the known geographical location information of the beacons and access points, the auxiliary position information of the vehicle is calculated using multilateral measurement, thereby achieving high-availability positioning of the vehicle in complex environments where GPS (Global Positioning System) signals are limited or unavailable, thereby improving the accuracy of determining the auxiliary position information of the vehicle.

[0120] Based on any one or more of the above embodiments, in a possible implementation manner, the wireless communication module is used to send the auxiliary position information of the vehicle to the vehicle cabin domain controller in a specified data frame format.

[0121] The data frame format specified above refers to a standardized data structure defined to ensure communication efficiency and compatibility. It is used to describe the content, sequence, unit, and encoding method of auxiliary location information. Common formats include custom binary protocols, JSON, XML, and Protobuf.

[0122] In an embodiment of the present application, the wireless communication module sends the vehicle's auxiliary location information to the vehicle cabin domain controller in a preset data frame format, ensuring the standardization of the auxiliary location information sent and ensuring efficient and standardized transmission of the vehicle's auxiliary location information.

[0123] like Figure 3 As shown, Figure 3 This is a flow chart of a vehicle cockpit domain positioning method provided by an embodiment of the present application. The vehicle cockpit domain positioning method can be executed by a vehicle cockpit domain positioning system. For example, the vehicle control system can be the above-mentioned Figure 1 The vehicle cockpit domain positioning system 10 is shown. The vehicle cockpit domain positioning method includes steps 310, 320, 330, 340 and 350, which are specifically as follows.

[0124] Step 310: Receive Beidou satellite positioning signals through the satellite positioning chip and send basic geographic location information to the vehicle cabin domain controller. The basic geographic location information includes longitude, latitude and altitude.

[0125] Step 320: The acceleration and angular velocity of the vehicle are collected by an inertial measurement sensor, and the motion state of the vehicle is estimated based on the acceleration and angular velocity. The motion state includes position, velocity, and heading angle.

[0126] Step 330: Determine the auxiliary location information of the vehicle through the wireless communication module and send the auxiliary location information to the vehicle cabin domain controller. The auxiliary location information is the location information of the vehicle in an indoor environment or a scenario with weak satellite signals.

[0127] Step 340: The vehicle cockpit domain controller integrates and processes the data output by the satellite positioning chip, inertial measurement sensor and wireless communication module to generate the final position information of the vehicle.

[0128] Step 350: Visually display the final position information of the vehicle on the display screen.

[0129] In an embodiment of the present application, the satellite positioning chip provides high-precision geographic location information of the vehicle, the inertial measurement sensor estimates the vehicle's motion state by integrating acceleration and angular velocity, and the wireless communication module provides auxiliary positioning information of the vehicle when the satellite signal is weak. The vehicle cabin domain controller adopts a multi-sensor fusion algorithm, combining the advantages of each module, and improving the positioning accuracy of the vehicle in complex environments by integrating multi-source data from the satellite positioning chip, inertial measurement sensor and wireless communication module, thereby effectively suppressing the influence of single sensor errors, improving the real-time and stability of the vehicle positioning system, and achieving high-precision and continuous navigation positioning effects.

[0130] For example, based on Figures 2 to 3 Corresponding to any one or more embodiments, the embodiments of the present application propose a system auxiliary device for quickly analyzing and solving problems of the vehicle function controller.

[0131] The purpose of this embodiment is to provide an intelligent cockpit domain controller based on the Beidou positioning system and its application method. By integrating a single Beidou positioning chip into the intelligent cockpit domain controller and building a complete system-level solution around the Beidou positioning location information, the accuracy and reliability of positioning are improved.

[0132] To achieve the above objectives, this embodiment adopts the following technical solutions:

[0133] 1. Integrate a single Beidou positioning chip into the intelligent cockpit domain controller to achieve real-time acquisition of vehicle location information.

[0134] 2. Leveraging the cockpit controller's built-in inertial measurement sensor to connect and obtain vehicle information, combined with multi-sensor fusion positioning algorithms, map data, external camera visual signals and other information, the accuracy and reliability of positioning are improved.

[0135] 3. Provide users with rich location-based functions based on their needs, such as navigation, traffic query, and surrounding service recommendations.

[0136] The Beidou positioning system-based intelligent cockpit domain controller and its application method, provided in this embodiment, integrates a single Beidou positioning chip into the intelligent cockpit domain controller and builds a complete system-level solution based on Beidou positioning information. This improves positioning accuracy and reliability, meeting users' needs for precise navigation. It provides a rich set of location-based functions, enhancing the user's driving experience. By optimizing key hardware technologies, the overall performance indicators of the cockpit domain controller product are improved.

[0137] This embodiment provides an intelligent cockpit domain controller based on the Beidou positioning system, including a single Beidou positioning chip, an inertial measurement sensor, a BT+WiFi module, an intelligent cockpit domain controller, a display screen, a camera, and a CAN bus.

[0138] A single Beidou positioning chip receives and processes signals from Beidou satellites, providing basic geographic location information; the inertial measurement sensor estimates the vehicle's acceleration and angular velocity by measuring the vehicle's acceleration and angular velocity (the inertial measurement sensor uses a built-in accelerometer and gyroscope to measure the vehicle's acceleration and angular velocity on three orthogonal coordinate axes in real time. The accelerometer obtains acceleration data in the longitudinal, lateral, and vertical directions of the vehicle, and obtains the velocity component in the corresponding direction through integration; the gyroscope measures the vehicle's angular velocity around these three axes, and also obtains the vehicle's attitude angle through integration. Combining velocity vector and attitude information, and using the Kalman filter algorithm for fusion processing, can effectively compensate for sensor errors. The final output is high-precision position, speed and heading angle information) of the vehicle's motion status; the BT+WiFi module is used for indoor positioning or to provide auxiliary positioning functions in environments with weak satellite signals; the intelligent cockpit domain controller processes data from each unit and executes d (the input data of the fusion algorithm includes the longitude, latitude, altitude and other geographic coordinate information provided by the Beidou positioning chip, the position, speed and heading angle information estimated by the inertial measurement sensor, and the indoor positioning or auxiliary positioning data of the BT+WiFi network. The output data is more accurate longitude, latitude, altitude, as well as precise position information such as the vehicle's driving direction and speed). Output the final precise location information; the display screen presents the processed location information to the user in the form of graphics or text; the camera transmits image data in real time (mainly a color visual image of the vehicle's surroundings captured by the camera, including scene images in various directions such as the front, rear, and sides of the vehicle, with a certain resolution, for assisted driving functions), and the intelligent cockpit domain controller receives and processes the image data for assisted driving functions; the CAN bus is responsible for transmitting data and instructions between the intelligent cockpit domain controller and other vehicle systems. By integrating a single Beidou positioning chip in the intelligent cockpit domain controller and building a complete system-level solution around the Beidou positioning location information, the accuracy and reliability of positioning are improved.

[0139] Please refer to Figure 4, Figure 4 This is a technical schematic diagram of the intelligent cockpit domain controller of the Beidou positioning system provided by an embodiment of the present application. Figure 4 As shown in the figure, the intelligent cockpit domain controller based on the Beidou positioning system includes: 1. Single Beidou positioning chip; 2. Inertial measurement sensor; 3. BT+Wi-Fi module; 4. Intelligent cockpit domain controller; 5. Display; 6. Camera; 7. CAN bus. These components are interconnected through hardware interfaces and data communication protocols, forming a complete system architecture.

[0140] The single Beidou positioning chip 1, as the core of the system, is responsible for receiving and processing signals from Beidou satellites, providing basic geographic location information, and inputting it to the intelligent cockpit domain controller 4. It is the basic data source for the entire positioning system.

[0141] Inertial measurement sensor 2 works in conjunction with single Beidou positioning chip 1 to estimate the vehicle's motion state by measuring its acceleration and angular velocity, helping to improve positioning accuracy and stability. This information is then fed into the intelligent cockpit domain controller 4. The inertial measurement sensor can also provide temporary position information when satellite signals are unstable or temporarily lost.

[0142] The BT+WiFi module 3 has the function of automatically detecting the communication environment, especially in scenarios where indoor positioning or satellite signals are weak, and can intelligently select the best signal source. It receives location information from other devices or networks and provides auxiliary positioning functions (specific data information includes the signal strength of nearby Bluetooth beacons and / or WiFi access points, the MAC (Media Access Control) address of the beacon or access point, and the estimated relative distance to these signal sources. The module scans the surrounding Bluetooth and WiFi signals, collects the above data, and uses multilateral measurement to combine the location information of Bluetooth beacons and WiFi hotspots to calculate the relative position of the vehicle indoors or the precise position in an environment with weak satellite signals. This data is transmitted to the smart cockpit domain controller in a specific data frame format, and the controller integrates it with other positioning data to optimize the positioning results) and transmits this information to the smart cockpit domain controller 4. In addition, the BT+WiFi module 3 can also be used for communication and data transmission with other devices to ensure that the system can obtain accurate and stable location information in various environments.

[0143] The intelligent cockpit domain controller 4 serves as the system's control center, integrating the functions of all the aforementioned units and coordinating and managing them. It processes data from each unit, executes a fusion algorithm, and outputs the final, precise location information (displayed graphically, with an icon visually identifying the vehicle's current location on the display's map interface and displaying the vehicle's direction of travel, indicated by an arrow pointing in that direction) to the display screen 5.

[0144] The display screen 5 presents the location information processed by the intelligent cockpit domain controller 4 to the user in the form of graphics or text, providing intuitive navigation and information display functions.

[0145] The camera 6 is connected to the smart cockpit domain controller 4 to transmit image data in real time. After receiving the image data from the camera 6, the smart cockpit domain controller 4 performs image processing (including grayscale conversion (converting color images to grayscale images to reduce data volume and computational complexity) and filtering (such as Gaussian filtering to remove image noise and make the image clearer). Feature extraction is then performed, such as edge detection and shape recognition (recognizing the outline shape of vehicles and pedestrians). Target classification and recognition are then performed using deep learning algorithms, such as using convolutional neural network models to recognize traffic signs (speed limit, no parking, etc.) and detect pedestrians and vehicles (determining their position, size, and motion status). These image analysis results are used for assisted driving functions, such as triggering the lane keeping assist system's reminder or automatic correction function when a vehicle is detected to have deviated from the lane; promptly reminding the driver of relevant information after recognizing a traffic sign; and warning of potential collision risks when a pedestrian is detected, thereby improving driving safety and convenience) and analysis, and are used for assisted driving functions such as lane keeping assist, traffic sign recognition, and pedestrian detection.

[0146] The CAN bus 7 serves as a communication network between different electronic control units inside the vehicle. It is responsible for transmitting data and instructions between the intelligent cockpit domain controller 4 and other vehicle systems, ensuring that the electronic systems of the entire vehicle work in coordination.

[0147] Please refer to Figure 5 , Figure 5 This is a workflow diagram of the Beidou positioning system provided by an embodiment of the present application.

[0148] The workflow of a method for applying a smart cockpit domain controller based on the Beidou positioning system begins with designing a hardware interface between a single Beidou positioning chip 1 and a smart cockpit domain controller 4 to ensure stable data transmission and processing. Simultaneously, hardware interfaces are designed and integrated with other key components, including the BT+WiFi module 3, display 5, camera 6, and CAN bus 7, to ensure seamless collaboration between these components.

[0149] The inertial measurement sensor 2 built into the cockpit controller 4 acquires real-time vehicle attitude information, which is crucial for improving positioning accuracy and stability. Combining the position information provided by the Beidou positioning chip 1 with attitude information acquired by the inertial measurement sensor 2, and location information received from other devices or networks by the BT+WiFi module 3, an advanced multi-sensor fusion positioning algorithm accurately calculates the vehicle's position, significantly improving positioning accuracy and stability, especially in environments with limited signals or severe interference.

[0150] The processed location information is transmitted to the smart cockpit's display screen 5, enabling the display of location-based functions and services. For example, it can display information such as the vehicle's current location, driving trajectory, and surrounding service facilities, providing the driver with convenient navigation and information services. Furthermore, the camera 6 captures information about the vehicle's interior and exterior environments, combining this information with location information to provide users with a richer interactive experience and services.

[0151] By integrating a single Beidou positioning chip, BT+WiFi module, display, camera, CAN bus, and other components into the smart cockpit domain controller, and focusing on Beidou positioning information, a complete system-level solution was built. This included hardware design, software development, and algorithm optimization, aiming to improve positioning accuracy and reliability while meeting other functional requirements of the smart cockpit.

[0152] Please refer to Figure 6 , Figure 6 It is a schematic diagram of a navigation algorithm provided by an embodiment of the present application.

[0153] A navigation algorithm process for an intelligent cockpit domain controller based on the Beidou positioning system. The Beidou positioning + inertial measurement combined navigation algorithms complement each other to meet the requirements of positioning accuracy and stability. When the Beidou positioning signal is good, centimeter-level positioning can be provided. However, in scenarios where the Beidou positioning signal is weak, such as urban canyons, tunnels, and mountainous areas, the satellite positioning signal update frequency is low (only 10Hz, with a delay of 100ms), resulting in delayed navigation position and large errors, which is insufficient to support real-time position updates, and its positioning accuracy will be greatly reduced. However, inertial measurement sensors (update frequency > 100Hz, delay < 10ms) can accurately position even in complex working environments or extreme motion conditions.

[0154] This embodiment achieves a complementary effect through the combination of Beidou positioning and inertial measurement, greatly improving the accuracy of the positioning system.

[0155] like Figure 6 As shown, this navigation algorithm includes step S1-1, step S1-2, and step S2, which are specifically as follows.

[0156] Step S1-1: The Beidou satellite positioning signal sends the vehicle position, speed and heading. After receiving the above information, the intelligent cockpit domain controller performs local filtering of the positioning signal.

[0157] Step S1-2: The CAN bus sends the vehicle body speed and three-dimensional angular velocity to the intelligent cockpit domain controller, which performs inertial measurement mileage calculation and then further performs DR local filtering.

[0158] Step S2: The intelligent cockpit domain controller obtains the data after local filtering and DR local filtering, and obtains the navigation positioning result output through main filtering.

[0159] 1. When the vehicle is started and the Beidou positioning chip is operating normally, and the Beidou positioning signal status stabilizes, it will be initialized (first reading the initial geographic location information provided by the Beidou chip, including longitude, latitude, and altitude, to determine the vehicle's starting position; simultaneously obtaining the vehicle's initial attitude. Assuming the vehicle is stationary, the initial heading angle is determined by the steering wheel angle sensor or GIS data based on the initial position. The initialization result determines the precise position and heading angle of the vehicle's starting point, providing a reference for subsequent navigation and positioning). The dead reckoning status, including position and heading angle, will be displayed.

[0160] 2. During vehicle driving, the CAN bus will output the vehicle body speed and the three-dimensional angular velocity information of the gyroscope.

[0161] 3. The inertial measurement sensor acquires the vehicle speed and three-dimensional angular velocity output from the CAN bus and calculates the inertial measurement mileage. This calculation method integrates the vehicle speed to obtain the displacement increment, and combines the three-dimensional angular velocity changes to infer the vehicle's motion trajectory. Simultaneously, the raw data is corrected and compensated using pre-calibrated parameters. These correction parameters include the accelerometer's zero bias and the gyroscope's drift rate. By eliminating these deviations through a compensation algorithm, the corrected results show more precise vehicle motion parameters, effectively improving positioning accuracy.

[0162] Velocity integration method: The vehicle body velocity (UCAN) output by the CAN bus is integrated over time and combined with the gyroscope angular velocity (Wx, Wy, Wz) to correct the velocity offset caused by the change in vehicle body posture. The formula is:

[0163] Δs=∫t0t1(vCAN·cos(θ)-a·Δt)dt

[0164] Where θ is the heading angle, and a is the lateral acceleration (calculated by the gyroscope angular velocity and vehicle speed).

[0165] At the same time, these raw data are corrected and compensated using pre-calibrated parameters (the correction parameters include the zero bias of the accelerometer (such as the zero bias of the X axis is 0.01m / s 2) and the drift rate of the gyroscope (e.g., the drift rate around the Z axis is 0.02° / s)) to eliminate deviations that may be caused by sensor errors, environmental factors, etc.

[0166] 4. Based on the inertial measurement mileage calculation results and combined with the vehicle body CAN signal, some basic models (such as the two-wheel differential model, Ackerman steering model, inertial measurement geometry model, and Kalman filter model) are established (the intelligent cockpit domain controller establishes the model and estimates the position. The input data is the mileage calculation result of the inertial measurement sensor and the vehicle body CAN signal, and the output is the vehicle's current precise position. The model training process includes data acquisition, preprocessing, model construction and optimization, and model verification. Driving data under different working conditions are collected, and multiple models are constructed after preprocessing. The model parameters are determined through the optimization algorithm. Finally, the model accuracy is verified to ensure reliable estimation of the vehicle position). The specific position of the vehicle at the current moment is estimated (input: IMU-corrected acceleration / angular velocity, CAN speed / steering wheel angle, Beidou position / speed; output: real-time position (latitude and longitude, elevation), velocity vector, heading angle, and state confidence).

[0167] 5. To improve accuracy, the calculated position also needs to be subjected to DR filtering to remove noise interference, making the final position more accurate and reliable (the inertial measurement sensor is only responsible for data acquisition (such as the original output of the IMU), while model building, calculation and filtering (steps 4 and 5) are all performed by the intelligent cockpit domain controller because it needs to integrate multi-source information such as Beidou and CAN and complete complex calculations).

[0168] 6. In addition, the quality or confidence of the positioning signal from the Beidou satellite system is monitored in real time. If the signal strength is found to be sufficiently good and continuous and reliable, further local filtering operations are performed on the signal and combined with the position estimate obtained by the previous DR filtering method. The overall positioning result is then optimized by combining the main filtering technology and outputting the final navigation position. If the signal is found to be weak or discontinuous, the final navigation position is based solely on the position estimate obtained by the DR filtering method.

[0169] Those skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, which may be a read-only memory, a disk, or an optical disk, etc.

[0170] Those skilled in the art will appreciate that in one or more of the above examples, the functions described in the embodiments of the present application can be implemented using hardware, software, firmware, or any combination thereof. When implemented using software, these functions can be stored in a computer-readable medium or transmitted as one or more instructions or codes on a computer-readable medium. Computer-readable media include computer storage media and communication media, wherein communication media include any media that facilitates the transmission of computer programs from one place to another. The storage medium can be any available medium that can be accessed by a general-purpose or special-purpose computer.

[0171] The above description is merely an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A vehicle cockpit positioning system, characterized in that: The system includes a satellite positioning chip, an inertial measurement sensor, a wireless communication module, a vehicle cabin domain controller, and a display screen; The vehicle cockpit domain controller is communicatively connected to the satellite positioning chip, the inertial measurement sensor, the wireless communication module and the display screen respectively; The satellite positioning chip is used to receive Beidou satellite positioning signals and send basic geographic location information to the vehicle cockpit domain controller, where the basic geographic location information includes longitude, latitude and altitude; The inertial measurement sensor is used to collect the acceleration and angular velocity of the vehicle and estimate the motion state of the vehicle based on the acceleration and the angular velocity, wherein the motion state includes position, velocity and heading angle; The wireless communication module is used to determine auxiliary position information of the vehicle and send the auxiliary position information to the vehicle cabin domain controller, wherein the auxiliary position information is the position information of the vehicle in an indoor environment or a scenario with weak satellite signals; The vehicle cockpit domain controller is configured to integrate and process data output by the satellite positioning chip, the inertial measurement sensor, and the wireless communication module to generate a final navigation positioning result for the vehicle, wherein the final navigation positioning result is the vehicle's current position information; The display screen is used to visually display the final navigation positioning result of the vehicle.

2. The system according to claim 1, wherein: The inertial measurement sensor is used to: Obtaining a basic body speed and a basic three-dimensional angular velocity of the vehicle; performing correction compensation on a base body speed and a base three-dimensional angular velocity of the vehicle using pre-calibrated compensation parameters to obtain a corrected and compensated target body speed and target three-dimensional angular velocity, wherein the compensation parameters include an accelerometer bias and a gyroscope drift rate; Inertial odometry calculation is performed based on the target vehicle body speed and the target three-dimensional angular velocity.

3. The system according to claim 2, characterized in that The vehicle cockpit domain controller is further used to: Constructing a position estimation model based on the result of the inertial measurement mileage calculation and the vehicle body CAN signal, wherein the position estimation model includes a combination of one or more of a two-wheel differential model, an Ackermann steering model, and an inertial measurement geometry model; The target vehicle body speed, the target three-dimensional angular velocity, and the basic geographic location information are input into a constructed position calculation model to obtain the current vehicle position output by the position calculation model.

4. The system according to claim 3, characterized in that The vehicle cockpit domain controller is further used to: DR filtering is performed on the current vehicle position output by the position estimation model to obtain a first position estimation value.

5. The system according to claim 4, characterized in that The vehicle cockpit domain controller is further used to: Real-time detection of the quality of the Beidou satellite positioning signal; When the signal strength of the Beidou satellite positioning signal meets a preset condition, a local filtering operation is performed on the Beidou satellite positioning signal to obtain filtered Beidou position information.

6. The system according to claim 5, characterized in that The vehicle cockpit domain controller is further used to: Based on the first position estimate and the filtered Beidou position signal, a fusion process is performed through a main filtering algorithm to obtain a final navigation positioning result.

7. The system according to claim 1, wherein: The satellite positioning chip is also used to: After the vehicle is started and the Beidou signal state is stable, initial positioning information of the vehicle is obtained, where the initial positioning information includes the position of the starting point and the heading angle of the vehicle.

8. The system according to claim 1, wherein: The wireless communication module is used to: Acquiring positioning assistance data, the positioning assistance data including signal strengths of Bluetooth beacons and / or wireless access points in the vicinity of the vehicle, physical addresses of beacons and / or access points of the wireless access points, and estimated distances between the vehicle and the nearby Bluetooth beacons and / or wireless access points; Based on the positioning assistance data, as well as the positions of Bluetooth beacons and wireless access points, auxiliary position information of the vehicle is determined using multilateration.

9. The system according to claim 8, characterized in that The wireless communication module is used to: The auxiliary position information of the vehicle is sent to the vehicle cockpit domain controller in a specified data frame format.

10. A vehicle cabin positioning method, characterized in that: The method is performed by the vehicle cabin domain positioning system according to claim 1, and the method includes: Receive Beidou satellite positioning signals through the satellite positioning chip and send basic geographic location information to the vehicle cockpit domain controller, where the basic geographic location information includes longitude, latitude and altitude; collecting the acceleration and angular velocity of the vehicle through the inertial measurement sensor, and estimating the motion state of the vehicle based on the acceleration and the angular velocity, the motion state including position, velocity and heading angle; Determining auxiliary position information of the vehicle through the wireless communication module and sending the auxiliary position information to the vehicle cabin domain controller, wherein the auxiliary position information is position information of the vehicle in an indoor environment or a scenario with weak satellite signals; The vehicle cockpit domain controller fuses and processes the data output by the satellite positioning chip, the inertial measurement sensor, and the wireless communication module to generate final position information of the vehicle; The final position information of the vehicle is visually displayed on the display screen.

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