WO2022193940A1 - 车辆测速方法、装置、车载计算机设备和存储介质 - Google Patents

车辆测速方法、装置、车载计算机设备和存储介质 Download PDF

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Publication number
WO2022193940A1
WO2022193940A1 PCT/CN2022/078561 CN2022078561W WO2022193940A1 WO 2022193940 A1 WO2022193940 A1 WO 2022193940A1 CN 2022078561 W CN2022078561 W CN 2022078561W WO 2022193940 A1 WO2022193940 A1 WO 2022193940A1
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Prior art keywords
vehicle
velocity
angle
sideslip angle
speed
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PCT/CN2022/078561
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English (en)
French (fr)
Inventor
林长宏
屈孝志
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北京航迹科技有限公司
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Publication of WO2022193940A1 publication Critical patent/WO2022193940A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P3/00—Measuring linear or angular speed; Measuring differences of linear or angular speeds

Definitions

  • the present disclosure relates to the technical field of vehicle speed measurement, and in particular, to a vehicle speed measurement method, device, vehicle-mounted computer equipment, storage medium, and computer program product.
  • Unmanned vehicles referred to as unmanned vehicles for short, mainly rely on the intelligent pilot system based on the computer system in the vehicle to achieve the purpose of unmanned driving.
  • the driving strategy of the unmanned vehicle needs to be modified according to the speed of the unmanned vehicle. Therefore, the accuracy of the speed of the unmanned vehicle is very important for the unmanned vehicle.
  • the speed measured by the vehicle-mounted speed measuring device is generally determined as the speed of the center of mass of the vehicle, that is, the speed of the vehicle.
  • the on-board speed measuring device is often not installed at the center of mass of the vehicle body; on the other hand, as shown in Figure 1, the vehicle is simplified as a two-wheeled vehicle, wherein the filling area between A and B on the vehicle is Represents the rear wheel, and the filled area between B and C represents the front wheel.
  • the vehicle rotates around the instantaneous center point O, and the magnitude and direction of the instantaneous speeds at points A, B, and C on the vehicle are different. Therefore, it can be seen that, The speed measured by the on-board speed measuring device cannot be directly used as the speed of the center of mass of the vehicle.
  • Embodiments of the present disclosure provide a vehicle speed measurement method, device, vehicle-mounted computer equipment, storage medium, and computer program product, which can improve the accuracy of the vehicle's center of mass speed.
  • an embodiment of the present disclosure provides a vehicle speed measurement method, the method comprising:
  • the initial centroid velocity is filtered and denoised to obtain the optimized centroid velocity.
  • an embodiment of the present disclosure provides a vehicle speed measuring device, the device comprising:
  • an acquisition module for acquiring the sideslip angle of the vehicle, where the sideslip angle is the angle between the speed direction of the vehicle and the driving direction of the vehicle;
  • the centroid velocity determination module is used to obtain the initial centroid velocity of the vehicle according to the velocity measurement value and the sideslip angle measured by the on-board velocity measuring device;
  • the optimization module is used to filter and denoise the initial centroid velocity to obtain the optimized centroid velocity.
  • an embodiment of the present disclosure provides an in-vehicle computer device, the in-vehicle computer device includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the method shown in the first aspect when the processor executes the computer program .
  • an embodiment of the present disclosure provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the steps of the method shown in the first aspect above.
  • an embodiment of the present disclosure provides a computer program product, including a computer program, which implements the steps of the method shown in the first aspect above when the computer program is executed by a processor.
  • the vehicle speed measurement method, device, vehicle-mounted computer device, storage medium, and computer program product provided by the embodiments of the present disclosure can improve the accuracy of vehicle speed.
  • the vehicle speed measurement method obtains the initial centroid velocity of the vehicle based on the speed measurement value and the sideslip angle measured by the vehicle-mounted speed measurement device, and corrects the speed measurement value measured by the vehicle-mounted speed measurement device through the sideslip angle to obtain the corrected initial centroid velocity, Compared with the method in which the velocity measurement value is directly used as the centroid velocity in the prior art, the accuracy of the initial centroid velocity is improved. Further, the optimized centroid velocity is obtained by filtering and denoising the initial centroid velocity, which further improves the performance. The accuracy of the center of mass velocity improves the accuracy of the vehicle speed.
  • FIG. 1 is a schematic diagram of a vehicle provided by the prior art
  • Fig. 2 is the internal structure diagram of in-vehicle computer equipment in one embodiment
  • FIG. 3 is a schematic flowchart of a vehicle speed measurement method in one embodiment
  • FIG. 4 is a schematic flowchart of a method for obtaining the sideslip angle of a vehicle in one embodiment
  • FIG. 5 is a schematic diagram of velocity decomposition in a simplified vehicle model in one embodiment
  • FIG. 6 is a schematic flowchart of a vehicle speed measurement method in another embodiment
  • FIG. 7 is a structural block diagram of a vehicle speed measuring device in one embodiment.
  • Unmanned vehicles mainly rely on the computer-based intelligent driver in the vehicle to achieve the purpose of unmanned driving.
  • the method of multi-sensor fusion is generally used to collect the surrounding environment information of the unmanned vehicle, and the driving strategy of the unmanned vehicle is adjusted according to the fusion results of the multi-sensor data.
  • a four-wheeled vehicle can generally be simplified into a two-wheeled vehicle model similar to a bicycle.
  • the vertical motion in the vehicle model is ignored, and the vehicle motion is described only according to the acceleration of the vehicle along the vehicle body and the steering angle of the front wheels.
  • the on-board speed measuring device can measure the speed at its location, and use the measured vehicle speed as the vehicle center of mass velocity, and perform subsequent multi-sensor data fusion based on the vehicle speed measured by the on-board speed measuring device.
  • the vehicle speed measured by the device is not the real vehicle centroid speed. Due to the difference between the vehicle speed measured by the on-board speed measuring device and the real vehicle centroid speed, the subsequent multi-sensor data based on the vehicle speed measured by the on-board speed measuring device is generated. Fusion can introduce systematic biases that reduce the positioning accuracy of autonomous vehicles.
  • an embodiment of the present disclosure provides a vehicle velocity measurement method.
  • the method obtains the initial centroid velocity of the vehicle based on the velocity measurement value and the sideslip angle measured by the vehicle velocity measurement device, and measures the vehicle velocity through the sideslip angle.
  • the velocity measurement value measured by the device is corrected to obtain the corrected initial centroid velocity, which improves the accuracy of the initial centroid velocity compared to the method of directly using the velocity measurement value as the centroid velocity in the prior art.
  • the centroid velocity is filtered and denoised to obtain the optimized centroid velocity, which further improves the accuracy of the centroid velocity and the vehicle velocity.
  • the application environment of the vehicle speed measurement method provided by the embodiments of the present disclosure may include a vehicle, on which a vehicle-mounted speed measurement device and a vehicle-mounted computer device are provided, wherein the vehicle-mounted speed measurement device is installed on the vehicle and is used to measure the vehicle speed and measure the speed of the vehicle.
  • the measured speed value is sent to the on-board computer device, and the on-board computer device can be used to implement the vehicle testing method provided by the embodiment of the present disclosure.
  • the internal structure of the in-vehicle computer equipment is shown in FIG. 2 , and the in-vehicle computer equipment includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the on-board computer equipment is used to provide computing and control capabilities.
  • the memory of the in-vehicle computer equipment includes a non-volatile storage medium and an internal memory.
  • the nonvolatile storage medium stores an operating system, a computer program, and a database.
  • the internal memory provides an environment for the execution of the operating system and computer programs in the non-volatile storage medium.
  • the database of the in-vehicle computer equipment is used to store preset data related to the vehicle speed measurement method provided by the present disclosure.
  • the network interface of the computer device is used to communicate with an external terminal through a network connection.
  • the computer program when executed by a processor, implements a vehicle testing method.
  • a vehicle speed measurement method is provided. The method is applied to the vehicle shown in FIG. 1 and includes the following steps:
  • Step 301 acquiring the sideslip angle of the vehicle.
  • the sideslip angle is the angle between the speed direction of the vehicle and the direction of travel of the vehicle.
  • the sideslip angle of the vehicle refers to the included angle between the direction of the speed of the vehicle and the traveling direction of the vehicle when the vehicle is turning, such as the angle ⁇ shown in FIG. 4 .
  • the position offset of the vehicle-mounted speed measuring device and the position of the center of mass of the vehicle can be measured, and then the position coordinates of the center of mass of the vehicle can be obtained through the preset rotation matrix and the position offset, and then the direction of the speed of the center of mass of the vehicle can be determined; Perform azimuth transformation on the vehicle heading data to obtain the driving direction of the vehicle.
  • the direction of the speed of the center of mass of the vehicle can be expressed by the heading angle of the center of mass of the vehicle, and the driving direction of the vehicle can be expressed by the heading angle of the vehicle, and then the direction based on the speed of the vehicle can be used. Calculate the sideslip angle of the vehicle with the direction of travel of the vehicle.
  • Step 302 Obtain the initial centroid velocity of the vehicle according to the measured velocity value and the sideslip angle measured by the vehicle-mounted velocity measuring device.
  • the speed compensation coefficient may be obtained based on the sideslip angle, and then the initial centroid speed of the vehicle may be obtained based on the speed compensation coefficient and the speed measurement value measured by the vehicle-mounted speed measuring device.
  • the process of obtaining the speed compensation coefficient based on the sideslip angle may include: determining the speed compensation coefficient based on a ratio of a sine value to a cosine value of the sideslip angle.
  • the process of obtaining the speed compensation coefficient based on the sideslip angle may further include: obtaining the target sideslip angle based on the product of the sideslip angle and a preset coefficient, and then based on the cosine value of the sideslip angle and the cosine value of the target sideslip angle. The ratio of determines the speed compensation coefficient.
  • the process of obtaining the initial centroid speed of the vehicle based on the speed compensation coefficient and the speed measurement value measured by the vehicle-mounted speed measuring device may include: taking the product of the speed compensation coefficient and the speed measurement value measured by the vehicle-mounted speed measuring device as the initial centroid of the vehicle. speed.
  • Step 303 Perform filtering and denoising processing on the initial centroid velocity to obtain an optimized centroid velocity.
  • filtering and denoising processing may be performed on the initial centroid velocity based on a filter to obtain an optimized centroid velocity.
  • the initial centroid velocity of the vehicle is obtained based on the speed measurement value measured by the vehicle-mounted speed measurement device and the sideslip angle, and the speed measurement value measured by the vehicle-mounted speed measurement device is corrected by the sideslip angle, and the correction is obtained.
  • the accuracy of the initial centroid velocity is improved.
  • the optimized centroid velocity is obtained by filtering and denoising the initial centroid velocity. The centroid velocity further improves the accuracy of the centroid velocity and improves the accuracy of the vehicle velocity.
  • an embodiment of the present disclosure provides a method for determining the vehicle position, the method comprising:
  • the position measurement value of the vehicle is obtained, and the initial centroid velocity and position measurement value are filtered and denoised to obtain the optimized centroid velocity and the optimized vehicle position.
  • the position measurement value of the vehicle may be obtained based on GNSS (English: Global Navigation Satellite System, Chinese: Global Navigation Satellite System) or Lidar (English: light detection and ranging, Chinese: light detection and ranging) measurement.
  • GNSS Global Navigation Satellite System
  • Lidar Terms: light detection and ranging
  • Chinese light detection and ranging
  • the purpose of taking the influence of the vehicle's speed into consideration in the process of optimizing the position measurement value of the vehicle is achieved. , thereby improving the accuracy of the vehicle position.
  • FIG. 4 which shows another method for obtaining the sideslip angle of a vehicle, the method includes:
  • Step 401 obtaining the steering wheel angle of the vehicle.
  • the steering wheel angle ⁇ s of the vehicle can be obtained by measuring the sensor.
  • Step 402 Calculate the steering angle of the front wheels of the vehicle according to the steering wheel angle.
  • the front wheel steering angle ⁇ f can be calculated based on the steering wheel angle, the gear ratio ⁇ steer-gear and the mathematical expression.
  • Step 403 Obtain the sideslip angle of the vehicle according to the steering angle of the front wheels.
  • FIG. 5 is a schematic diagram of the speed decomposition in the simplified vehicle model, in which the on-board speed measuring device is installed at the location of the IMU in Figure 5, and the center of mass of the vehicle is simplified as the geometric center of the vehicle, which is marked with center.
  • l f is the distance from the center of the vehicle to the front axle
  • l r is the distance from the center of the vehicle to the rear axle
  • ⁇ f is the steering angle of the front wheel
  • ⁇ is the sideslip angle of the vehicle.
  • ⁇ is the heading angle of the vehicle
  • v is the speed of the vehicle. It can be seen that different positions of the vehicle have different speed magnitudes and directions.
  • the process of obtaining the sideslip angle ⁇ of the vehicle by the on-board computer equipment may be: calling a pre-set sideslip angle calculation model, and calculating the steering angle of the front wheels, the distance from the center of the vehicle to the front axle, and the center of the vehicle. The distance from the position to the rear axle is input into the sideslip angle calculation model to obtain the sideslip angle ⁇ of the vehicle.
  • the steering angle of the front wheel is determined based on the steering wheel angle of the vehicle, and then the sideslip angle of the vehicle is obtained based on the steering angle of the front wheel, which improves the accuracy of the sideslip angle of the vehicle, thereby improving the determined initial center of mass velocity accuracy.
  • the sideslip angle includes the sideslip angle of the center of mass of the vehicle and the sideslip angle of the vehicle-mounted speed measuring device, wherein obtaining the sideslip angle of the vehicle according to the steering angle of the front wheels includes obtaining the center of mass of the vehicle
  • obtaining the sideslip angle of the vehicle according to the steering angle of the front wheels includes obtaining the center of mass of the vehicle
  • the in-vehicle computer device can obtain the first distance l 1 from the vehicle mass center of the vehicle to the front axle and the second distance l 2 from the vehicle mass center of the vehicle to the rear axle; according to the front wheel steering angle ⁇ f , the first distance l 1 and the second distance l 2 calculate the sideslip angle of the vehicle's center of mass.
  • the on-board computer equipment can calculate the sideslip angle ⁇ center of the center of mass of the vehicle based on the preset sideslip angle motion model
  • the third distance l3 from the vehicle-mounted speed measuring device to the front axle and the fourth distance l4 from the vehicle-mounted speed measuring device to the rear axle are obtained; according to the steering angle ⁇ f of the front wheel, the third distance l3 and the fourth distance l 4 Calculate the sideslip angle of the vehicle-mounted speed measuring device.
  • the vehicle-mounted computer equipment can calculate the sideslip angle ⁇ imu of the vehicle-mounted speed measuring device based on the preset sideslip angle motion model
  • the accuracy of the sideslip angle can be improved, paving the way for the subsequent acquisition of the initial center of mass velocity more accurately, and avoiding subsequent data processing.
  • the process introduces errors.
  • FIG. 6 another vehicle speed measurement method is provided, and the method includes:
  • Step 601 Obtain the sideslip angle of the vehicle mass center and the sideslip angle of the vehicle-mounted speed measuring device.
  • the sideslip angle ⁇ center of the center of mass of the vehicle and the sideslip angle ⁇ imu of the vehicle-mounted speed measuring device can be obtained with reference to the contents disclosed in the foregoing embodiments.
  • Step 602 Determine a correction coefficient according to the sideslip angle of the vehicle's center of mass and the sideslip angle of the vehicle-mounted speed measuring device.
  • the correction coefficient may be determined based on the ratio of the sideslip angle of the center of mass of the vehicle to the sideslip angle of the vehicle-mounted speed measuring device.
  • the correction coefficient may be determined based on the ratio of the cosine value of the sideslip angle of the center of mass of the vehicle to the cosine value of the sideslip angle of the vehicle-mounted speed measuring device.
  • Step 603 Obtain the initial centroid velocity of the vehicle according to the correction coefficient and the velocity measurement value.
  • the initial centroid velocity of the vehicle may be obtained according to the product of the correction coefficient and the velocity measurement value.
  • the accuracy of the correction coefficient is improved by separately obtaining the sideslip angle of the vehicle's center of mass and the sideslip angle of the vehicle-mounted speed measuring device, thereby improving the accuracy of the initial center-of-mass velocity and laying the groundwork for the subsequent optimization of the initial center-of-mass velocity.
  • Step 604 Perform filtering and denoising processing on the initial centroid velocity to obtain an optimized centroid velocity.
  • filtering and denoising processing is performed on the initial centroid velocity based on a preset Kalman filter to obtain an optimized centroid velocity.
  • the three dimensions are usually decoupled and estimated as three independent motions.
  • the velocity components in the three directions are estimated based on the equipment.
  • the azimuth angle of is decomposed into the three-axis coordinate system, however, this decomposition process introduces the error of the azimuth angle estimation into the velocity measurement, which brings additional error to the subsequent state estimation.
  • an embodiment of the present disclosure provides another optimization method, which includes:
  • Step A1 Determine the two-dimensional velocity component corresponding to the initial centroid velocity according to the sideslip angle and the heading angle of the vehicle.
  • the two-dimensional component of velocity includes a first velocity vector and a second velocity vector, and the first velocity vector is perpendicular to the direction of the second velocity vector.
  • the velocity component of the initial centroid velocity of the vehicle in the global coordinate system can be re-decomposed into a first velocity vector and a second velocity vector according to the sideslip angle and the heading angle, where the first velocity vector can represent for
  • the second velocity vector can be expressed as
  • Step A2 Input the two-dimensional component of velocity into the Kalman filter to obtain the optimized centroid velocity.
  • the velocity v can be expressed as a two-dimensional vector where v xy is v z is v xy and v z represent the vehicle's horizontal speed and vertical speed in the local coordinate system, respectively.
  • position p and attitude q are three-dimensional vectors defined in the global coordinate system
  • ⁇ p represents the error of position p
  • ⁇ q represents the error of attitude q
  • the acceleration bias a_b and gyro bias w_b are A three-dimensional vector defined in the vehicle body coordinate system
  • ⁇ a_b represents the error of the acceleration bias a_b
  • ⁇ w_b represents the error of the gyro bias w_b.
  • the global coordinate system is an absolute coordinate system independent of the motion of the vehicle body
  • the local coordinate system is a coordinate system that is relatively fixed to the vehicle body.
  • the left direction of the transverse axis and the upward direction of the vehicle body chassis plane are the three-dimensional positive directions of the coordinate system.
  • the three-dimensional component is changed to a two-dimensional component compared to the prior art, so it is necessary to redesign some parameters in the Kalman filter, and the redesign includes the redesign of the speed optimization model , and a redesign of the optimization model for location. Since the speed will have a direct impact on the position, when the component of the speed changes from a three-dimensional component to a two-dimensional component, the position component of the vehicle will also change accordingly.
  • the optimization models for the two parameters will be described below.
  • the error state at position p can be updated by the following formula:
  • R is the rotation matrix of the nominal state
  • Two-dimensional velocity vectors in the horizontal and vertical directions can be Converted into three-dimensional velocity components along the longitudinal, lateral and vertical directions of the vehicle body. According to the motion characteristics of the vehicle, the lateral velocity of the vehicle body can be ignored, so the velocity component in the horizontal direction of the vehicle body can be equal to the longitudinal velocity of the vehicle body.
  • the initial centroid velocity of the vehicle body is calculated based on the correction of the velocity measurement value of the vehicle-mounted velocity measuring device.
  • the Kalman filter is redesigned, and the horizontal speed measured by the combined inertial navigation equipment is directly used as the vehicle motion speed to avoid the additional error introduced by the three-axis speed decomposition. .
  • steps in the flowcharts of FIGS. 3 to 6 are sequentially displayed in accordance with the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, the execution of these steps is not strictly limited to the order, and these steps may be performed in other orders. Moreover, at least a part of the steps in FIG. 3 to FIG. 6 may include multiple steps or multiple stages. These steps or stages are not necessarily executed and completed at the same time, but may be executed at different times. The order of execution is also not necessarily sequential, but may be performed alternately or alternately with other steps or at least a portion of the steps or stages within the other steps.
  • a vehicle speed measurement device 700 comprising: an acquisition module 701 , a centroid velocity determination module 702 and an optimization module 703 , wherein:
  • the obtaining module 701 is used to obtain the sideslip angle of the vehicle, where the sideslip angle is the angle between the speed direction of the vehicle and the driving direction of the vehicle;
  • centroid velocity determination module 702 configured to obtain the initial centroid velocity of the vehicle according to the velocity measurement value and the sideslip angle measured by the vehicle-mounted velocity measuring device;
  • the optimization module 703 is used for filtering and denoising the initial centroid velocity to obtain the optimized centroid velocity.
  • the obtaining module 701 is specifically configured to: obtain the steering wheel angle of the vehicle; calculate the front wheel steering angle of the vehicle according to the steering wheel angle; and obtain the sideslip angle of the vehicle according to the front wheel steering angle.
  • the sideslip angle includes the sideslip angle of the center of mass of the vehicle and the sideslip angle of the vehicle-mounted speed measuring device
  • the acquiring module 701 is specifically configured to: acquire the first distance from the vehicle center of mass of the vehicle to the front axle and the vehicle's The second distance from the center of mass of the vehicle to the rear axle; obtain the third distance from the vehicle-mounted speed measuring device to the front axle and the fourth distance from the vehicle-mounted speed measuring device to the rear axle; Sideslip angle: Calculate the sideslip angle of the vehicle-mounted speed measuring device according to the steering angle of the front wheel, the third distance and the fourth distance.
  • the sideslip angle includes the sideslip angle of the vehicle's center of mass and the sideslip angle of the vehicle-mounted speed measuring device
  • the center of mass speed determination module 702 is specifically configured to: according to the sideslip angle of the vehicle's center of mass and the side-slip angle of the vehicle-mounted speed measuring device The slip angle determines the correction factor; the initial centroid velocity of the vehicle is obtained based on the correction factor and the speed measurement.
  • the centroid velocity determination module 702 is specifically configured to: determine the correction coefficient according to the ratio of the cosine value of the sideslip angle of the vehicle centroid to the cosine value of the sideslip angle of the vehicle-mounted speed measuring device.
  • the optimization module 703 is specifically configured to: perform filtering and denoising processing on the initial centroid velocity based on a preset Kalman filter to obtain an optimized centroid velocity.
  • the optimization module 703 is specifically configured to: determine a two-dimensional velocity component corresponding to the initial centroid velocity according to the sideslip angle and the heading angle of the vehicle, wherein the velocity two-dimensional component includes a first velocity vector and a second velocity vector Velocity vector, the first velocity vector is perpendicular to the second velocity vector; the two-dimensional component of velocity is input into the Kalman filter to obtain the optimized centroid velocity.
  • the acquisition module 701 is specifically used to: acquire the position measurement value of the vehicle; the optimization module 703 is specifically used to: filter and denoise the initial centroid velocity and the position measurement value to obtain the optimized vehicle position .
  • Each module in the above-mentioned vehicle speed measuring device can be implemented in whole or in part by software, hardware and combinations thereof.
  • the above modules may be embedded in or independent of the processor in the shared vehicle in the form of hardware, and may also be stored in the memory of the shared vehicle in the form of software, so that the processor can call and execute operations corresponding to the above modules.
  • non-transitory computer-readable storage medium including instructions
  • the non-transitory computer-readable storage medium may be ROM, random access memory (RAM), CD-ROM , tapes, floppy disks and optical data storage devices.
  • a computer program is stored on the storage medium, and when the computer program is executed by the processor, the above method is implemented.
  • a program product in one embodiment of the present disclosure, includes a computer program, and when the computer program is executed by a processor, the above method can be implemented.
  • the program product includes one or more computer instructions. When these computer instructions are loaded and executed on a computer, some or all of the above methods can be implemented in whole or in part according to the processes or functions described in the embodiments of the present disclosure.
  • any reference to memory, storage, database, or other media used in the various embodiments provided by the embodiments of the present disclosure may include at least one of non-volatile and volatile memory.
  • Non-volatile memory may include read-only memory (Read-Only Memory, ROM), magnetic tape, floppy disk, flash memory, or optical memory, and the like.
  • Volatile memory may include random access memory (RAM) or external cache memory.
  • the RAM may be in various forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

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Abstract

一种车辆测速方法，涉及车辆测速技术领域。该车辆测速方法基于车载测速装置测得的速度测量值和侧滑角获取车辆的初始质心速度（302），通过侧滑角对车载测速装置测得的速度测量值进行修正（602），得到修正后的初始质心速度（603），相比于现有技术中直接将速度测量值作为质心速度的方式提高了初始质心速度的准确性，通过对初始质心速度进行滤波去噪处理，得到优化后的质心速度（604），进一步提高了质心速度的准确性，提高了车辆速度的精度。还提供一种车辆测速装置、车载计算机设备、存储介质以及计算机程序产品。

Description

车辆测速方法、装置、车载计算机设备和存储介质
交叉引用
本申请要求于2021年3月18日提交的中国专利申请No.202110305030.3的优先权，其全部内容通过引用结合于此。
技术领域
本公开涉及车辆测速技术领域，特别是涉及一种车辆测速方法、装置、车载计算机设备、存储介质以及计算机程序产品。
背景技术
无人驾驶车辆，简称无人车，主要依靠车内的以计算机系统为主的智能驾驶仪来实现无人驾驶的目的。无人车在行驶的过程中，需要根据无人车的速度来修改车辆驾驶策略，因此，无人车的速度的准确性对无人车而言非常重要。
现有技术中，一般是将车载测速装置测得的速度确定为车辆质心的速度，即车辆的速度。然而，一方面车载测速装置常常不是安装于车体的质心位置；另一方面，如图1所示，图1中将车辆简化为两轮车，其中，车辆上A和B之间的填充区域表示后车轮，B和C之间的填充区域表示前车轮，此时，车辆围绕瞬时中心O点旋转，车辆上A、B和C三点的瞬时速度的大小和方向都不相同，因此可知，车载测速装置测得的速度并不能直接作为车辆质心的速度。
因此，基于现有技术确定的车辆质心的速度不准确。
发明内容
本公开实施例提供一种车辆测速方法、装置、车载计算机设备、存储介质以及计算机程序产品，可以提高车辆的质心速度的准确性。
第一方面，本公开实施例提供一种车辆测速方法，该方法包括：
获取车辆的侧滑角，侧滑角为车辆的速度方向与车辆的行驶方向之间的夹角；
根据车载测速装置测得的速度测量值和侧滑角获取车辆的初始质心速度；
对初始质心速度进行滤波去噪处理，得到优化后的质心速度。
第二方面，本公开实施例提供一种车辆测速装置，该装置包括：
获取模块，用于获取车辆的侧滑角，侧滑角为车辆的速度方向与车辆的行驶方向之间的夹角；
质心速度确定模块，用于根据车载测速装置测得的速度测量值和侧滑角获取车辆的初始质心速度；
优化模块，用于对初始质心速度进行滤波去噪处理，得到优化后的质心速度。
第三方面，本公开实施例提供一种车载计算机设备，车载计算机设备包括存储器以及处理器，该存储器存储有计算机程序，该处理器执行该计算机程序时实现上述第一方面所示的方法的步骤。
第四方面，本公开实施例提供一种存储介质，其上存储有计算机程序，该计算机程序被处理器执行时实现上述第一方面所示的方法的步骤。
第五方面，本公开实施例提供一种计算机程序产品，包括计算机程序，该计算机程序被处理器执行时实现上述第一方面所示的方法的步骤。
本公开实施例提供的车辆测速方法、装置、车载计算机设备、存储介质以及计算机程序产品，可以提高车辆速度的精度。该车辆测速方法基于车载测速装置测得的速度测量值和侧滑角获取车辆的初始质心速度，通过 侧滑角对车载测速装置测得的速度测量值进行修正，得到修正后的初始质心速度，相比于现有技术中直接将速度测量值作为质心速度的方式提高了初始质心速度的准确性，进一步的，通过对初始质心速度进行滤波去噪处理，得到优化后的质心速度，进一步提高了质心速度的准确性，提高了车辆速度的精度。
附图说明
图1为现有技术提供的车辆示意图；
图2为一个实施例中车载计算机设备的内部结构图；
图3为一个实施例中车辆测速方法的流程示意图；
图4为一个实施例中一种获取车辆的侧滑角的方法的流程示意图；
图5为一个实施例中简化后的车辆模型中的速度分解示意图；
图6为另一个实施例中车辆测速方法的流程示意图；
图7为一个实施例中车辆测速装置的结构框图。
具体实施方式
为了使本公开实施例的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本公开实施例进行进一步详细说明。应当理解，此处描述的具体实施例仅仅用以解释本公开实施例，并不用于限定本公开实施例。
首先，在具体介绍本公开实施例的技术方案之前，先对本公开实施例基于的技术背景或者技术演进脉络进行介绍。
无人车主要依靠车内的以计算机系统为主的智能驾驶仪来实现无人驾驶的目的。为了提高无人车的驾驶性能，一般采用多传感器融合的方式来采集无人车周边环境信息，并根据多传感器数据的融合结果来调整无人车的驾驶策略。
现有技术中，四轮车的前面两个车轮具有相同的转向角度和转向速度，后面两个车轮也是如此，因此一般可以将四轮车简化为与自行车类似的两轮车模型，该两轮车模型中垂直方向的运动被忽略，仅根据车辆沿车体朝向的加速度和前轮的转向角度描述车辆的运动情况。车载测速装置测量可以测量其所在的位置处的速度，并将测得的车辆速度作为车辆质心速度，并基于车载测速装置测量到的车辆速度进行后续的多传感器数据融合。然而，一方面，车辆在转弯的情况下，车辆上的不同位置处的瞬时速度的大小和方向都不相同；另一方面，由于车载测速装置常常不是安装于车体的质心位置，因此车载测速装置测量到的车辆速度并不是真实的车辆质心速度，由于车载测速装置测量到的车辆速度与真实的车辆质心速度之间存在差异，导致基于车载测速装置测量到的车辆速度进行后续的多传感器数据融合会带来系统性的偏差，从而降低无人车的定位精度。
为了提高车辆质心速度的精度，本公开实施例提供了一种车辆测速方法，该方法基于车载测速装置测得的速度测量值和侧滑角获取车辆的初始质心速度，通过侧滑角对车载测速装置测得的速度测量值进行修正，得到修正后的初始质心速度，相比于现有技术中直接将速度测量值作为质心速度的方式提高了初始质心速度的准确性，进一步的，通过对初始质心速度进行滤波去噪处理，得到优化后的质心速度，进一步提高了质心速度的准确性，提高了车辆速度的精度。
下面结合本公开实施例所应用的场景，对本公开实施例涉及的技术方案进行介绍。
本公开实施例提供的车辆测速方法的应用环境可以包括车辆，该车辆上设置有车载测速装置和车载计算机设备，其中，该车载测速装置安装于车辆上，用于测量车辆速度，并将测得的速度测量值发送给该车载计算机设备，该车载计算机设备可以用于实现本公开实施例提供的车辆测试方 法。
其中，该车载计算机设备的内部结构如图2所示，该车载计算机设备包括通过系统总线连接的处理器、存储器和网络接口。其中，该车载计算机设备的处理器用于提供计算和控制能力。该车载计算机设备的存储器包括非易失性存储介质、内存储器。该非易失性存储介质存储有操作系统、计算机程序和数据库。该内存储器为非易失性存储介质中的操作系统和计算机程序的运行提供环境。该车载计算机设备的数据库用于存储与本公开提供的车辆测速方法相关的预设数据。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机程序被处理器执行时以实现一种车辆测试方法。
在一个实施例中，如图3所示，提供了一种车辆测速方法，该方法应用于图1所示的车辆中，包括以下步骤：
步骤301，获取车辆的侧滑角。
侧滑角为车辆的速度方向与车辆的行驶方向之间的夹角。
本公开实施例中，车辆的侧滑角是指车辆在转弯时车辆的速度的方向与车辆的行驶方向之间的夹角，如图4所示的β角。
本公开实施例中，可以通过测量车载测速装置与车辆质心位置的位置偏移，然后通过预设的旋转矩阵和该位置偏移得到车辆质心的位置坐标，进而确定车辆质心的速度的方向；通过对车辆航向数据进行方位变换，得到车辆的行驶方向，可选的，车辆质心的速度的方向可以使用车辆质心航向角表示，车辆的行驶方向可以使用车辆航向角表示，然后基于车辆的速度的方向与车辆的行驶方向计算车辆的侧滑角。
步骤302，根据车载测速装置测得的速度测量值和侧滑角获取车辆的初始质心速度。
本公开实施例中，可以基于侧滑角获取速度补偿系数，然后基于速 度补偿系数和车载测速装置测得的速度测量值得到车辆的初始质心速度。
可选的，基于侧滑角获取速度补偿系数的过程可以包括：基于侧滑角的正弦值与余弦值的比值确定该速度补偿系数。
可选的，基于侧滑角获取速度补偿系数的过程还可以包括：基于侧滑角与预设系数的乘积得到目标侧滑角，然后基于侧滑角的余弦值与目标侧滑角的余弦值的比值确定该速度补偿系数。
可选的，基于速度补偿系数和车载测速装置测得的速度测量值得到车辆的初始质心速度的过程可以包括：将速度补偿系数和车载测速装置测得的速度测量值的乘积作为辆的初始质心速度。
步骤303，对初始质心速度进行滤波去噪处理，得到优化后的质心速度。
可选的，本公开实施例中，可以基于滤波器对初始质心速度进行滤波去噪处理，得到优化后的质心速度。
本公开实施例提供的车辆测速方法，基于车载测速装置测得的速度测量值和侧滑角获取车辆的初始质心速度，通过侧滑角对车载测速装置测得的速度测量值进行修正，得到修正后的初始质心速度，相比于现有技术中直接将速度测量值作为质心速度的方式提高了初始质心速度的准确性，进一步的，通过对初始质心速度进行滤波去噪处理，得到优化后的质心速度，进一步提高了质心速度的准确性，提高了车辆速度的精度。
在实际应用中，在得到车辆速度之后，可以基于车辆速度确定车辆的位置。由于通过测量得到的车辆的位置测量值是存在误差的，因此直接根据车辆的位置测量进行车辆定位，会导致车辆定位结果不准确。为了提高车辆定位结果的准确性，本公开实施例提供了一种确定车辆位置的方法，该方法包括：
获取车辆的位置测量值，对初始质心速度和位置测量值进行滤波去 噪处理，得到优化后的质心速度和优化后的车辆位置。
其中，车辆的位置测量值可以是基于GNSS(英文：Global Navigation Satellite System，中文：全球导航卫星系统)或者基于Lidar(英文：light detection and ranging，中文：光探测和测距)测量得到的。
本公开实施例中，通过对初始质心速度和位置测量值同时进行滤波去噪处理的方式，实现了在对车辆的位置测量值进行优化的过程中，将车辆的速度的影响考虑在内的目的，从而提高了车辆位置的准确性。
在本公开的另一个实施例中，如图4所示，其示出了另一种获取车辆的侧滑角的方法，该方法包括：
步骤401，获取车辆的方向盘转角。
本公开实施例中，车辆的方向盘转角δ s可以通过传感器测量得到。
步骤402，根据方向盘转角计算车辆的前轮转向角。
本公开实施例中，方向盘转角δ s与前轮转向角δ f之间具有固定的传动比γ steer-gear，根据该方向盘转角δ s和传动比γ steer-gear可以计算得到前轮转向角δ f。
可选的，
Figure PCTCN2022078561-appb-000001
基于方向盘转角、传动比γ steer-gear以及该数学表达式可以计算得到前轮转向角δ f。
步骤403，根据前轮转向角获取车辆的侧滑角。
由于车辆的基本布局是前轮转向，而后轮固定不动，并且前轮在转向时两轮的偏差较小可以忽略不急，因此我们将车辆模型简化成两轮的模型。如图5所示，图5为简化后的车辆模型中的速度分解示意图，其中，车载测速装置安装在如图5中IMU所在位置，车辆质心简化为车辆的几何中心，用center标注。l f表示车辆中心位置到前轴的距离，l r表示车辆中心位置到后轴的距离，δ f为前轮转向角，β为车辆的侧滑角。Ψ是车辆的航向 角，v为车辆的速度。可以看出，车辆的不同位置具有不同的速度大小和方向。
结合图5示出的内容，车载计算机设备获取车辆的侧滑角β的过程可以是：调用预先设置有侧滑角运算模型，将前轮转向角、车辆中心位置到前轴的距离和车辆中心位置到后轴的距离输入到该侧滑角运算模型中，得到车辆的侧滑角β。
其中，该预设的侧滑角运算模型的数学表达式为：
Figure PCTCN2022078561-appb-000002
本公开实施例中，基于车辆的方向盘转角确定前轮转向角，然后基于前轮转向角获取车辆的侧滑角，提高了车辆的侧滑角的准确性，从而提高了确定出的初始质心速度的准确性。
在本公开的另一种可选的实现方式中，侧滑角包括车辆质心的侧滑角和车载测速装置的侧滑角，其中，根据前轮转向角获取车辆的侧滑角包括获取车辆质心的侧滑角和获取车载测速装置的侧滑角，下面对该两种侧滑角的获取过程分别进行说明：
第一，获取车辆质心的侧滑角。
本公开实施例中，车载计算机设备可以获取车辆的车辆质心到前轴的第一距离l 1和车辆的车辆质心到后轴的第二距离l 2；根据前轮转向角δ f、第一距离l 1和第二距离l 2计算车辆质心的侧滑角。
其中，车载计算机设备可以基于预设的侧滑角运动模型计算出车辆质心的侧滑角β center，
Figure PCTCN2022078561-appb-000003
第二，获取车载测速装置的侧滑角。
本公开实施例中，获取车载测速装置到前轴的第三距离l 3和车载测速装置到后轴的第四距离l 4；根据前轮转向角δ f、第三距离l 3和第四距离l 4计 算车载测速装置的侧滑角。
其中，车载计算机设备可以基于预设的侧滑角运动模型计算出车载测速装置的侧滑角β imu，
Figure PCTCN2022078561-appb-000004
本公开实施例中，通过分别获取车辆质心的侧滑角和车载测速装置的侧滑角可以提高侧滑角的精度，为后续更加精确地获取初始质心速度做好数据铺垫，避免给后续数据处理过程带来误差。
本公开实施例中，如图6所示，提供了另一种车辆测速方法，该方法包括：
步骤601，获取车辆质心的侧滑角和车载测速装置的侧滑角。
可以参考上述实施例公开的内容获取车辆质心的侧滑角β center和车载测速装置的侧滑角β imu。
步骤602，根据车辆质心的侧滑角和车载测速装置的侧滑角确定修正系数。
可选的，本公开实施例中，可以基于车辆质心的侧滑角与车载测速装置的侧滑角的比值确定修正系数。
可选的，本公开实施例中，可以基于车辆质心的侧滑角的余弦值与车载测速装置的侧滑角的余弦值的比值确定修正系数。
步骤603，根据修正系数和速度测量值获取车辆的初始质心速度。
可选的，本公开实施例中，可以根据修正系数和速度测量值的乘积得到车辆的初始质心速度。
本公开实施例中，通过分别获取车辆质心的侧滑角和车载测速装置的侧滑角提高修正系数的准确性，从而提高初始质心速度的准确性，为后续对初始质心速度进行优化进行数据铺垫。
步骤604，对初始质心速度进行滤波去噪处理，得到优化后的质心速度。
可选的，本公开实施例中，基于预设的卡尔曼滤波器对初始质心速度进行滤波去噪处理，得到优化后的质心速度。
现有技术中，在使用卡尔曼滤波器进行空间三维位置姿态估计的时候，通常会将三个维度解耦，视为三个独立的运动进行估计，该三个方向的速度分量是基于设备估计的方位角被分解到三轴坐标系上的，然而，此分解过程将方位角估计的误差引入了速度测量值中，从而给后续的状态估计带来额外的误差。
为了进一步提高优化后的质心速度的精度，本公开实施例提供另一种优化方法，该方法包括：
步骤A1，根据侧滑角和车辆的航向角确定初始质心速度对应的速度二维分量。其中，速度二维分量包括第一速度矢量和第二速度矢量，第一速度矢量与第二速度矢量方向垂直。
本公开实施例中，车辆的初始质心速度的速度在全局坐标系下的速度分量可以根据侧滑角和航向角重新分解为第一速度矢量和第二速度矢量，其中，第一速度矢量可以表示为
Figure PCTCN2022078561-appb-000005
第二速度矢量可以表示为
Figure PCTCN2022078561-appb-000006
步骤A2，将速度二维分量输入到卡尔曼滤波器中，得到优化后的质心速度。
其中，以误差状态卡尔曼滤波器(英文：Error State Kalman Filter，简称：ESKF)为例，可以定义的误差状态卡尔曼滤波器的误差状态(英文：Error State)如下公式所示
Figure PCTCN2022078561-appb-000007
其中，速度v可以表示为二维向量
Figure PCTCN2022078561-appb-000008
其中，v xy即
Figure PCTCN2022078561-appb-000009
v z即
Figure PCTCN2022078561-appb-000010
v xy和v z分别表示局部坐标系下车辆水平速度和竖直方向的速度。
Figure PCTCN2022078561-appb-000011
表示v xy的误差，
Figure PCTCN2022078561-appb-000012
表示v z的误差，位置p和姿态q是定义在全局坐标系下的三维向量，δ p表示位置p的误差，δ q表示姿态q的误差，而加速度偏置a_b和陀螺仪偏置w_b是定义在车体坐标系下的三维向量，δ a_b表示加速度偏置a_b的误差，δ w_b表示陀螺仪偏置w_b的误差。
其中，全局坐标系(UTM坐标系、墨卡托坐标系等)和局部坐标系。其中全局坐标系是独立于车体运动的绝对坐标系，局部坐标系是与车体相对固定的坐标系，如以车的几何中心为坐标原点，沿车体中轴向前的方向、车体横轴向左方向和车体底盘平面向上方向为坐标系的三维正方向。
由于本公开实施例中，相比于现有技术中的三维分量变为了二维分量，因此需要对卡尔曼滤波器中的部分参数进行重新设计，该重新设计包括对速度的优化模型的重新设计，以及对位置的优化模型的重新设计。由于速度会对位置产生直接影响，在速度的分量从三维分量变为二维分量的情况下，车辆的位置分量也相应地会发生变化，下面分别对该两种参数的优化模型进行说明。
第一，位置p的误差状态可以由如下公式更新：
δp←δp+(RR 1δv-R[R 1v]×δθ)Δt
其中R为名义状态的旋转矩阵
Figure PCTCN2022078561-appb-000013
可以将水平方向和竖直方向的二维速度向量
Figure PCTCN2022078561-appb-000014
转化成沿车体纵向、横向和竖直方向的三维速度分量。根据车辆的运动特性，车体横向的速度可以忽略不计，因此车体水平方向的速度分量可以等同于车体纵向的速度。
第二，速度v的误差状态可以由如下公式更新：
δv←δv+R 2(-δab)Δt+vi
其中
Figure PCTCN2022078561-appb-000015
表示将加速度在车体坐标系下的纵向、横向和竖直方向的三维加速度向量转化成沿水平方向和竖直方向的二维加速度向量，根据车辆的运动特性，车体横向的加速度产生的横向速度可以忽略不计，因此横向加速度被忽略不计。
本公开实施例中，通过在局部坐标下描述车辆的运动速度，可以直接与传感器测量的加速度进行计算，不需要借助车辆航向角将全局坐标系下的速度转换到局部坐标，减少了一次航向角测量误差的引入。
进一步的，本公开实施例中，一方面基于对车载速度测量设备的速度测量值进行修正，计算出车体的初始质心速度。另一方面，结合车辆主要做沿车体纵向运动的运动学特性，重新设计卡尔曼滤波器，将组合惯导设备测量的水平速度直接作为车辆运动速度，来避免三轴速度分解引入的额外误差。
应该理解的是，虽然图3至图6的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，图3至图6中的至少一部分步骤可以包括多个步骤或者多个阶段，这些步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤中的步骤或者阶段的至少一部分轮流或者交替地执行。
在一个实施例中，如图7所示，提供了一种车辆测速装置700，包括：获取模块701、质心速度确定模块702和优化模块703，其中：
获取模块701，用于获取车辆的侧滑角，侧滑角为车辆的速度方向与 车辆的行驶方向之间的夹角；
质心速度确定模块702，用于根据车载测速装置测得的速度测量值和侧滑角获取车辆的初始质心速度；
优化模块703，用于对初始质心速度进行滤波去噪处理，得到优化后的质心速度。
在本公开的一个实施例中，获取模块701具体用于：获取车辆的方向盘转角；根据方向盘转角计算车辆的前轮转向角；根据前轮转向角获取车辆的侧滑角。
在本公开的一个实施例中，侧滑角包括车辆质心的侧滑角和车载测速装置的侧滑角，获取模块701具体用于：获取车辆的车辆质心到前轴的第一距离和车辆的车辆质心到后轴的第二距离；获取车载测速装置到前轴的第三距离和车载测速装置到后轴的第四距离；根据前轮转向角、第一距离和第二距离计算车辆质心的侧滑角；根据前轮转向角、第三距离和第四距离计算车载测速装置的侧滑角。
在本公开的一个实施例中，侧滑角包括车辆质心的侧滑角和车载测速装置的侧滑角，质心速度确定模块702具体用于：根据车辆质心的侧滑角和车载测速装置的侧滑角确定修正系数；根据修正系数和速度测量值获取车辆的初始质心速度。
在本公开的一个实施例中，质心速度确定模块702具体用于：根据车辆质心的侧滑角的余弦值与车载测速装置的侧滑角的余弦值的比值确定修正系数。
在本公开的一个实施例中，优化模块703具体用于：基于预设的卡尔曼滤波器对初始质心速度进行滤波去噪处理，得到优化后的质心速度。
在本公开的一个实施例中，优化模块703具体用于：根据侧滑角和车辆的航向角确定初始质心速度对应的速度二维分量，其中，速度二维分 量包括第一速度矢量和第二速度矢量，第一速度矢量与第二速度矢量方向垂直；将速度二维分量输入到卡尔曼滤波器中，得到优化后的质心速度。
在本公开的一个实施例中，获取模块701具体用于：获取车辆的位置测量值；优化模块703具体用于：对初始质心速度和位置测量值进行滤波去噪处理，得到优化后的车辆位置。
关于车辆测速装置的具体限定可以参见上文中对于车辆测速方法的限定，在此不再赘述。上述车辆测速装置中的各个模块可全部或部分通过软件、硬件及其组合来实现。上述各模块可以以硬件形式内嵌于或独立于共享车辆中的处理器中，也可以以软件形式存储于共享车辆中的存储器中，以便于处理器调用执行以上各个模块对应的操作。
在本公开的一个实施例中，还提供了一种包括指令的非临时性计算机可读存储介质，该非临时性计算机可读存储介质可以是ROM、随机存取存储器(RAM)、CD-ROM、磁带、软盘和光数据存储设备等。该存储介质上存储有计算机程序，计算机程序被处理器执行时实现上述方法。
在本公开的一个实施例中，还提供了一种程序产品，该计算机程序产品包括计算机程序，该计算机程序被处理器执行时可以实现上述方法。该程序产品包括一个或多个计算机指令。在计算机上加载和执行这些计算机指令时，可以全部或部分地按照本公开实施例所述的流程或功能实现上述方法中的部分或者全部。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的计算机程序可存储于一非易失性计算机可读取存储介质中，该计算机程序在执行时，可包括如上述各方法的实施例的流程。其中，本公开实施例所提供的各实施例中所使用的对存储器、存储、数据库或其它介质的任何引用，均可包括非易失性和易失性存储器中的至少一种。非易失性存储器可包括只读存 储器(Read-Only Memory，ROM)、磁带、软盘、闪存或光存储器等。易失性存储器可包括随机存取存储器(Random Access Memory，RAM)或外部高速缓冲存储器。作为说明而非局限，RAM可以是多种形式，比如静态随机存取存储器(Static Random Access Memory，SRAM)或动态随机存取存储器(Dynamic Random Access Memory，DRAM)等。
以上实施例的各技术特征可以进行任意的组合，为使描述简洁，未对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本公开实施例的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本公开实施例构思的前提下，还可以做出若干变形和改进，这些都属于本公开实施例的保护范围。因此，本公开实施例专利的保护范围应以所附权利要求为准。

Claims (12)

  1. 一种车辆测速方法，其特征在于，所述方法包括：
    获取车辆的侧滑角，所述侧滑角为所述车辆的速度方向与所述车辆的行驶方向之间的夹角；
    根据车载测速装置测得的速度测量值和所述侧滑角获取所述车辆的初始质心速度；
    对所述初始质心速度进行滤波去噪处理，得到优化后的质心速度。
  2. 根据权利要求1所述的方法，其特征在于，所述获取车辆的侧滑角，包括：
    获取所述车辆的方向盘转角；
    根据所述方向盘转角计算所述车辆的前轮转向角；
    根据所述前轮转向角获取所述车辆的侧滑角。
  3. 根据权利要求2所述的方法，其特征在于，所述侧滑角包括车辆质心的侧滑角和所述车载测速装置的侧滑角，所述根据所述前轮转向角获取所述车辆的侧滑角，包括：
    获取所述车辆的车辆质心到前轴的第一距离和所述车辆的车辆质 心到后轴的第二距离；
    获取所述车载测速装置到所述前轴的第三距离和所述车载测速装置到所述后轴的第四距离；
    根据所述前轮转向角、所述第一距离和所述第二距离计算所述车辆质心的侧滑角；
    根据所述前轮转向角、所述第三距离和所述第四距离计算所述车载测速装置的侧滑角。
  4. 根据权利要求1-3任一项所述的方法，其特征在于，所述侧滑角包括车辆质心的侧滑角和所述车载测速装置的侧滑角，所述根据车载测速装置测得的速度测量值和所述侧滑角获取所述车辆的初始质心速度，包括：
    根据所述车辆质心的侧滑角和所述车载测速装置的侧滑角确定修正系数；
    根据所述修正系数和所述速度测量值获取所述车辆的初始质心速度。
  5. 根据权利要求4所述的方法，其特征在于，根据所述车辆质心的侧滑角和所述车载测速装置的侧滑角确定修正系数，包括：
    根据所述车辆质心的侧滑角的余弦值与所述车载测速装置的侧滑角的余弦值的比值确定所述修正系数。
  6. 根据权利要求1所述的方法，其特征在于，所述对所述初始质心速度进行滤波去噪处理，得到优化后的质心速度，包括：
    基于预设的卡尔曼滤波器对所述初始质心速度进行滤波去噪处理，得到优化后的所述质心速度。
  7. 根据权利要求6所述的方法，其特征在于，所述基于预设的卡尔曼滤波器对所述初始质心速度进行滤波去噪处理，得到优化后的所述质心速度，包括：
    根据所述侧滑角和所述车辆的航向角确定所述初始质心速度对应的速度二维分量，其中，所述速度二维分量包括第一速度矢量和第二速度矢量，所述第一速度矢量与所述第二速度矢量方向垂直；
    将所述速度二维分量输入到所述卡尔曼滤波器中，得到优化后的所述质心速度。
  8. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    获取车辆的位置测量值；
    对所述初始质心速度和所述位置测量值进行滤波去噪处理，得到优化后的车辆位置。
  9. 一种车辆测速装置，其特征在于，所述装置包括：
    获取模块，用于获取车辆的侧滑角，所述侧滑角为所述车辆的速度方向与所述车辆的行驶方向之间的夹角；
    质心速度确定模块，用于根据车载测速装置测得的速度测量值和所述侧滑角获取所述车辆的初始质心速度；
    优化模块，用于对所述初始质心速度进行滤波去噪处理，得到优化后的质心速度。
  10. 一种车载计算机设备，其特征在于，所述车载计算机设备包括存储器以及处理器，所述存储器存储有计算机程序，所述处理器执行所述计算机程序时实现权利要求1至8中任一项所述的方法的步骤。
  11. 一种存储介质，其上存储有计算机程序，其特征在于，所述计算机程序被处理器执行时实现权利要求1至8中任一项所述的方法的步骤。
  12. 一种计算机程序产品，包括计算机程序，其特征在于，所述计算机程序被处理器执行时实现权利要求1至8中任一项所述的方法的步骤。
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