WO2022089241A1 - 一种汽车定位的方法及装置 - Google Patents

一种汽车定位的方法及装置 Download PDF

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Publication number
WO2022089241A1
WO2022089241A1 PCT/CN2021/124445 CN2021124445W WO2022089241A1 WO 2022089241 A1 WO2022089241 A1 WO 2022089241A1 CN 2021124445 W CN2021124445 W CN 2021124445W WO 2022089241 A1 WO2022089241 A1 WO 2022089241A1
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vehicle
information
positioning
surrounding
yaw
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PCT/CN2021/124445
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English (en)
French (fr)
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陈超越
胡伟龙
王舜垚
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华为技术有限公司
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Priority to EP21884969.3A priority Critical patent/EP4215873A4/en
Publication of WO2022089241A1 publication Critical patent/WO2022089241A1/zh
Priority to US18/299,723 priority patent/US20230251095A1/en

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
    • G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/13—Receivers
    • G01S19/14—Receivers specially adapted for specific applications
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/393—Trajectory determination or predictive tracking, e.g. Kalman filtering
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/396—Determining accuracy or reliability of position or pseudorange measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/48—Determining position by combining or switching between position solutions derived from the satellite radio beacon positioning system and position solutions derived from a further system
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
    • G01S5/0009—Transmission of position information to remote stations
    • G01S5/0072—Transmission between mobile stations, e.g. anti-collision systems

Definitions

  • the present application relates to the technical field of automatic driving, and in particular, to a method and device for positioning an automobile.
  • Vehicle positioning technology is an important foundation and key technology for autonomous driving functions. The loss of positioning will cause the unmanned vehicle to fail to operate normally, which may lead to major accidents.
  • GPS Global Positioning System
  • IMU Inertial Measuring Unit
  • SLAM real-time localization and mapping
  • the above methods are greatly affected by the external environment, especially in some special scenarios, such as the GPS failure in the tunnel and the reduction of visual and laser features, the IMU loses most of the constraints, resulting in deviations in the positioning results, and it is difficult to achieve the global positioning of the vehicle.
  • the embodiments of the present application provide a method and device for vehicle positioning, which can use the vehicle information of surrounding vehicles to calculate the global positioning information of the vehicle to be located when the GPS fails or the vehicle sensor of the vehicle to be located is faulty, so as to improve the performance in special scenarios. It can improve the accuracy of the vehicle positioning results and improve the robustness of the vehicle positioning system.
  • an embodiment of the present application provides a method for positioning a vehicle, including:
  • the GPS positioning covariance of the vehicle to be positioned when the GPS positioning covariance is less than or equal to the preset positioning covariance threshold, obtain the initial positioning information of the vehicle to be positioned and the vehicle information of the surrounding vehicles, and the surrounding vehicles are the same as the vehicle to be positioned.
  • the vehicle information includes distance information and vehicle speed information; according to the initial positioning information of the vehicle to be located and the vehicle information of the surrounding vehicles, the first positioning calculation result of the surrounding vehicles is determined; according to the first positioning calculation result, A second positioning estimation result of the vehicle to be positioned is determined.
  • the vehicle to be located may be a vehicle whose GPS fails in environments such as tunnels, residential areas, and underground parking lots, and needs to be located, or a vehicle whose sensor fails, so it is impossible to obtain the surrounding environment information for positioning.
  • the vehicle sensor can be a vehicle sensor such as lidar, ultrasonic radar, etc.
  • Devices for acquiring vehicle information of surrounding vehicles may be on-board cameras, millimeter-wave radar sensors, and vehicle-to-everything (V2X) broadcast communicators and other devices.
  • the device that determines the result of the positioning calculation may be a vehicle terminal, a server or a cloud and other devices.
  • the above method can calculate the positioning information of the vehicle to be positioned by obtaining the information of the surrounding vehicles when the GPS fails or the vehicle sensor fails and the vehicle cannot be positioned, which can effectively reduce the possibility of the vehicle causing a safety accident due to the loss of positioning, and improve the vehicle positioning.
  • the accuracy of the positioning results can be calculated.
  • the vehicle information of the surrounding vehicles further includes identification information of the surrounding vehicles, orientation information of the surrounding vehicles, and angle difference information between the surrounding vehicles and the vehicle to be positioned, and the orientation information includes the yaw of the surrounding vehicles.
  • determining the first positioning estimation result of the surrounding vehicles according to the initial positioning information of the vehicle to be positioned and the vehicle information of the surrounding vehicles includes: establishing a vehicle tracking table according to the vehicle information of the surrounding vehicles; The tracking table and the initial positioning information of the vehicle to be located are used to obtain the initial positioning information of the surrounding vehicles through the initial positioning calculation algorithm; according to the initial positioning information of the surrounding vehicles and the vehicle information of the surrounding vehicles, the first positioning calculation result is obtained through the first positioning calculation algorithm.
  • the initial positioning information of the surrounding vehicles includes first initial positioning coordinates (x i_t0 , y i_t0 , z i_t0 , yaw i_t0 , pitch i_t0 , roll i_t0 ), and the initial positioning information of the vehicle to be positioned includes the first Two initial positioning coordinates (x t0 , y t0 , z t0 , yaw t0 , pitch t0 , roll t0 ), the initial positioning calculation algorithm includes:
  • x i_t0 x t0 +lx i_t0 ;
  • y i_t0 y t0 +ly i_t0 ;
  • yaw i_t0 yaw t0 +lyaw i_t0 ;
  • pitch i_t0 pitch t0 ;
  • x i_t0 , y i_t0 , z i_t0 , yaw i_t0 , pitch i_t0 and roll i_t0 respectively represent the coordinate information of the surrounding vehicle with serial number i in the direction of the preset x-coordinate axis at the initial time t 0 , and the preset y-coordinate axis Coordinate information in the direction, coordinate information in the direction of the preset z coordinate axis, yaw angle information, pitch angle information and roll angle information, x t0 , y t0 , z t0 , yaw t0 , pltch t0 and roll t0 respectively Represents the coordinate information of the vehicle to be positioned in the direction of the preset x -coordinate axis, the coordinate information in the direction of the preset y-coordinate axis, the coordinate information in the direction of the preset z-coordinate axis, the
  • the first positioning estimation result includes first positioning estimation coordinates (x i_t , y i_t , z i_t , yaw i_t , pitch i_t , roll i_t ), and the first positioning estimation algorithm includes:
  • yaw i_t yaw i_t- ⁇ t +yawrate i_t * ⁇ t;
  • pitch i_t pitch i_t- ⁇ t ;
  • roll i_t roll i_t- ⁇ t ;
  • x i_t x i_t- ⁇ t +v i_t *cosyaw i_t * ⁇ t;
  • y i_t y i_t- ⁇ t +v i_t *sinyaw i_t * ⁇ t;
  • x i_t , y i_t , z i_t , yaw i_t , pitch i_t and roll i_t respectively represent the coordinate information of the surrounding vehicle with serial number i in the preset x-coordinate axis direction at time t, in the preset y-coordinate axis direction coordinate information, coordinate information in the direction of the preset z coordinate axis, yaw angle information, pitch angle information and roll angle information, x i_t- ⁇ t , y i_t- ⁇ t , z i_t- ⁇ t , yaw i_t- ⁇ t , pitch i_t- ⁇ t and roll i_t- ⁇ t respectively represent the coordinate information of the surrounding vehicle with serial number i in the preset x-coordinate axis direction at time t- ⁇ t, the coordinate information in the preset y-coordinate axis direction, and the preset z coordinate information.
  • yawrate i_t represents the yaw rate information of the surrounding vehicle with serial number i at time t
  • ⁇ t is the preset time interval
  • v i_t represents The speed information of the surrounding vehicle with serial number i at time t.
  • the above method obtains the first positioning calculation result of the surrounding vehicles by obtaining the vehicle information of the surrounding vehicles, so that the positioning information of the surrounding vehicles can be calculated and obtained under the GPS failure environment, which can be used as the basic information for calculating the positioning results of the vehicles to be located, thereby improving the positioning. Robustness of the system.
  • determining the second positioning calculation result of the vehicle to be positioned according to the first positioning calculation result including: acquiring information on the angle difference between the surrounding vehicle and the vehicle to be positioned, the difference between the surrounding vehicle and the vehicle to be positioned The horizontal distance information between the two, and the longitudinal distance information between the surrounding vehicles and the vehicle to be located; combined with the first positioning calculation result, the second positioning calculation algorithm is used to obtain the second positioning calculation result.
  • the second positioning estimation result includes second positioning estimation coordinates (x t , y t , z t , yaw t , pitch t , roll t ), and the second positioning estimation algorithm includes:
  • x t x i_t -lx i_t ;
  • yaw t yaw i_t -lyaw i_t ;
  • pitch t pitch i_t ;
  • x t , y t , z t , yaw t , pitch t and roll t respectively represent the coordinate information of the vehicle to be positioned in the direction of the preset x-coordinate axis and the coordinate information in the direction of the preset y-coordinate axis at time t , coordinate information, yaw angle information, pitch angle information and roll angle information in the direction of the preset z coordinate axis, x i_t , y i_t , z i_t , yaw i_t , pitch i_t and roll i_t respectively represent the serial number i
  • the above method obtains the information of the angle difference between the surrounding vehicles and the vehicle to be located, and the distance information between the surrounding vehicles and the vehicle to be located, and obtains the positioning calculation result of the vehicle to be located through the second positioning calculation algorithm.
  • calculating the positioning information of the vehicle to be positioned based on the vehicle information of the surrounding vehicles is beneficial to reduce the positioning error of the vehicle to be positioned and realize the global positioning of the vehicle to be positioned.
  • the method before determining the first positioning estimation result of the surrounding vehicles according to the initial positioning information of the vehicle to be positioned and the vehicle information of the surrounding vehicles, the method further includes: judging whether the GPS positioning covariance is greater than a preset value The positioning covariance threshold, if yes, execute the determination of the first positioning estimation result of the surrounding vehicles according to the initial positioning information of the vehicle to be positioned and the vehicle information of the surrounding vehicles.
  • the vehicle positioning method provided by the embodiment of the present application is enabled, so that the GPS positioning covariance can be used in the GPS positioning method.
  • the positioning system is constrained by the vehicle information of the surrounding vehicles, effectively preventing the harm caused by the loss of GPS positioning, and improving the accuracy of the positioning results of the vehicles to be located. .
  • N vehicles in the surrounding vehicles correspond to N first positioning estimation results
  • the second positioning of the vehicle to be positioned is determined according to the first positioning estimation results
  • the calculation results include: respectively determining N second positioning calculation results corresponding to the vehicle to be positioned according to the N first positioning calculation results, calculating the mean value of the positioning results of the N second positioning calculation results, and using the mean value of the positioning results as the final value of the vehicle to be positioned.
  • the second positioning calculation result of when the number N of surrounding vehicles is greater than 1, N vehicles in the surrounding vehicles correspond to N first positioning estimation results, and the second positioning of the vehicle to be positioned is determined according to the first positioning estimation results
  • the calculation results include: respectively determining N second positioning calculation results corresponding to the vehicle to be positioned according to the N first positioning calculation results, calculating the mean value of the positioning results of the N second positioning calculation results, and using the mean value of the positioning results as the final value of the vehicle to be positioned.
  • the second positioning calculation result of the vehicle to be positioned relative to each surrounding vehicle is calculated, and the positioning result of the vehicle to be positioned is calculated by taking the average value of the second positioning calculation result. Further processing is performed to reduce the error of the positioning result of the vehicle to be located, so as to realize the global positioning of the vehicle to be located.
  • the method further includes: obtaining a GPS positioning result and an inertial measurement unit IMU estimation result; according to the GPS positioning result and the IMU estimation result, combined with the second positioning estimation result, through the extended Kalman filter (Extended Kalman filter).
  • Extended Kalman filter Extended Kalman filter
  • KalmanFilter referred to as EKF
  • the above method uses the EKF to fuse the positioning results of the GPS positioning results, the IMU estimation results and the second positioning estimation results, so that when the IMU loses its positioning constraints, the IMU can be constrained by the vehicle information of the surrounding vehicles to improve the accuracy of the positioning results. and the robustness of the positioning system.
  • an embodiment of the present application provides a vehicle positioning device, including:
  • the positioning covariance acquisition module is used to acquire the GPS positioning covariance of the vehicle to be located;
  • the vehicle information acquisition module is used to acquire the initial positioning of the vehicle to be located when the GPS positioning covariance is less than or equal to a preset positioning covariance threshold information and vehicle information of surrounding vehicles, the surrounding vehicles are vehicles whose distance from the vehicle to be located is less than the preset distance threshold, and the vehicle information includes distance information and vehicle speed information;
  • the first positioning calculation module is used for the initial positioning information of the vehicle to be located and
  • the vehicle information of the surrounding vehicles determines the first location estimation result of the surrounding vehicles;
  • the second location estimation module is used for determining the second location estimation result of the vehicle to be located according to the first location estimation result.
  • the vehicle to be located may be a vehicle that needs to be located due to GPS failure in environments such as tunnels, residential areas, and underground parking lots, or a vehicle that cannot be located by acquiring surrounding environment information due to a malfunction of the vehicle sensor.
  • the faulty vehicle sensor can be a vehicle sensor such as lidar, ultrasonic radar, etc.
  • the device for acquiring vehicle information of surrounding vehicles may be a vehicle-mounted camera, a millimeter-wave radar, and a vehicle to everything (V2X) communication module and other devices.
  • the device that determines the result of the positioning calculation may be a vehicle terminal, a server or a cloud and other devices.
  • the above-mentioned device can calculate the positioning information of the vehicle to be located by obtaining the information of the surrounding vehicles when the GPS fails or the vehicle sensor fails and the vehicle cannot be located, which can effectively reduce the possibility of a safety accident caused by the loss of the vehicle's positioning, and improve the performance of the vehicle.
  • the accuracy of the positioning results can be calculated.
  • the vehicle information of the surrounding vehicles further includes identification information of the surrounding vehicles, orientation information of the surrounding vehicles, and angle difference information between the surrounding vehicles and the vehicle to be positioned, and the orientation information includes the surrounding vehicles.
  • the distance information includes the lateral distance information between the surrounding vehicle and the vehicle to be positioned, and the longitudinal distance between the surrounding vehicle and the vehicle to be positioned Information;
  • vehicle speed information includes vehicle speed information of surrounding vehicles and yaw rate information of surrounding vehicles.
  • the first positioning calculation module includes: a vehicle tracking table establishment unit, used for establishing a vehicle tracking table according to vehicle information of surrounding vehicles; an initial positioning calculation unit, used for according to the vehicle tracking table and the to-be-located table.
  • the initial positioning information of the vehicle is obtained through the initial positioning calculation algorithm to obtain the initial positioning information of the surrounding vehicles; the first positioning calculation unit is used to obtain the first positioning calculation algorithm according to the initial positioning information of the surrounding vehicles and the vehicle information of the surrounding vehicles. Location estimation result.
  • the initial positioning information of the surrounding vehicles includes first initial positioning coordinates (x i_t0 , y i_t0 , z i_t0 , yaw i_t0 , pitch i_t0 , roll i_t0 ), and the initial positioning information of the vehicle to be positioned includes the first Two initial positioning coordinates (x t0 , y t0 , z t0 , yaw t0 , pitch t0 , roll t0 ), the initial positioning calculation algorithm includes:
  • x i_t0 x t0 +lx i_t0 ;
  • y i_t0 y t0 +ly i_t0 ;
  • yaw i_t0 yaw t0 +lyaw i_t0 ;
  • pitch i_t0 pitch t0 ;
  • x i_t0 , y i_t0 , z i_t0 , yaw i_t0 , pitch i_t0 and roll i_t0 respectively represent the coordinate information of the surrounding vehicle with serial number i in the direction of the preset x-coordinate axis at the initial time t 0
  • the preset y-coordinate axis Coordinate information in the direction, coordinate information in the direction of the preset z coordinate axis, yaw angle information, pitch angle information and roll angle information, x t0 , y t0 , z t0 , yaw t0 , pitch t0 and roll t0 respectively Represents the coordinate information of the vehicle to be positioned in the direction of the preset x -coordinate axis, the coordinate information in the direction of the preset y-coordinate axis, the coordinate information in the direction of the preset z-coordinate axis, the y
  • the first positioning estimation result includes first positioning estimation coordinates (x i_t , y i_t , z i_t , yaw i_t , pitch i_t , roll i_t ), and the first positioning estimation algorithm includes:
  • yaw i_t yaw i_t- ⁇ t +yawrate i_t * ⁇ t;
  • pitch i_t pitch i_t- ⁇ t ;
  • roll i_t roll i_t- ⁇ t ;
  • x i_t x i_t- ⁇ t +v i_t *cosyaw i_t * ⁇ t;
  • y i_t y i_t- ⁇ t +v i_t *sinyaw i_t * ⁇ t;
  • x i_t , y i_t , z i_t , yaw i_t , pitch i_t and roll i_t respectively represent the coordinate information of the surrounding vehicle with serial number i in the preset x-coordinate axis direction at time t, in the preset y-coordinate axis direction coordinate information, coordinate information in the direction of the preset z coordinate axis, yaw angle information, pitch angle information and roll angle information, x i_t- ⁇ t , y i_t- ⁇ t , z i_t- ⁇ t , yaw i_t- ⁇ t , pitch i_t- ⁇ t and roll i_t- ⁇ t respectively represent the coordinate information of the surrounding vehicle with serial number i in the preset x-coordinate axis direction at time t- ⁇ t, the coordinate information in the preset y-coordinate axis direction, and the preset z coordinate information.
  • yawrate i_t represents the yaw rate information of the surrounding vehicle with serial number i at time t
  • ⁇ t is the preset time interval
  • v i_t represents The speed information of the surrounding vehicle with serial number i at time t.
  • the above-mentioned device obtains the first positioning estimation result of the surrounding vehicles by obtaining the vehicle information of the surrounding vehicles, so that the positioning information of the surrounding vehicles can be calculated and obtained under the GPS failure environment, which can be used as the basic information for calculating the positioning results of the vehicles to be positioned, thereby improving the positioning. Robustness of the system.
  • the second location estimation module includes: an information acquisition unit, configured to acquire information on the angle difference between the surrounding vehicles and the vehicle to be located, the lateral distance information between the surrounding vehicles and the vehicle to be located, and Longitudinal distance information between the surrounding vehicles and the vehicle to be positioned; the second positioning calculation unit is used to obtain the second positioning calculation result through the second positioning calculation algorithm in combination with the first positioning calculation result.
  • the second positioning estimation result includes second positioning estimation coordinates (x t , y t , z t , yaw t , pitch t , roll t ), and the second positioning estimation algorithm includes:
  • x t x i_t -lx i_t ;
  • yaw t yaw i_t -lyaw i_t ;
  • pitch t pitch i_t ;
  • x t , y t , z t , yaw t , pitch t and roll t respectively represent the coordinate information of the vehicle to be positioned in the direction of the preset x-coordinate axis and the coordinate information in the direction of the preset y-coordinate axis at time t , coordinate information, yaw angle information, pitch angle information and roll angle information in the direction of the preset z coordinate axis, x i_t , y i_t , z i_t , yaw i_t , pitch i_t and roll i_t respectively represent the serial number i
  • the above device obtains the angular difference information between the surrounding vehicle and the vehicle to be positioned, and the distance information between the surrounding vehicle and the vehicle to be positioned, and obtains the positioning calculation result of the vehicle to be positioned through the second positioning calculation algorithm, which can realize During the operation of the vehicle, calculating the positioning information of the vehicle to be positioned based on the vehicle information of the surrounding vehicles is beneficial to reduce the positioning error of the vehicle to be positioned and realize the global positioning of the vehicle to be positioned.
  • the first positioning estimation module further includes: a positioning covariance judgment unit for judging whether the GPS positioning covariance is greater than a preset positioning covariance threshold; The initial positioning information and the vehicle information of the surrounding vehicles are used to determine the first positioning estimation result of the surrounding vehicles.
  • the above device by judging the magnitude relationship between the GPS positioning covariance and the preset positioning covariance threshold, enables the vehicle positioning method provided by the embodiment of the present application when the GPS positioning covariance is greater than the preset positioning covariance threshold, so that the GPS positioning covariance is greater than the preset positioning covariance threshold.
  • the positioning system is constrained by the vehicle information of the surrounding vehicles, effectively preventing the harm caused by the loss of GPS positioning, and improving the accuracy of the positioning results of the vehicles to be located. .
  • the second positioning estimation module includes: a positioning result mean value calculation unit for According to the N first positioning calculation results, respectively determine N second positioning calculation results corresponding to the vehicle to be positioned, calculate the average value of the positioning results of the N second positioning calculation results, and use the mean value of the positioning results as the final second positioning calculation of the vehicle to be positioned. result.
  • the above-mentioned device when the number of surrounding vehicles is greater than 1, calculates the second positioning calculation result of the vehicle to be positioned relative to each surrounding vehicle, and performs the positioning result of the vehicle to be positioned by taking the average value of the second positioning calculation result. Further processing is performed to reduce the error of the positioning result of the vehicle to be located, so as to realize the global positioning of the vehicle to be located.
  • the device further includes: a positioning result acquisition module for acquiring GPS positioning results and inertial measurement unit IMU estimation results; a positioning result fusion module for combining the GPS positioning results and IMU estimation results with For the second positioning calculation result, the final positioning result of the vehicle to be positioned is determined by extending the Kalman filter.
  • the above device uses the EKF to fuse the positioning results of the GPS positioning results, the IMU estimation results and the second positioning estimation results, so that when the IMU loses the positioning constraint, the IMU can be constrained by the vehicle information of the surrounding vehicles to improve the accuracy of the positioning results. and the robustness of the positioning system.
  • an embodiment of the present application provides an apparatus for positioning a vehicle, including a memory and a processor, where the memory is used to store a computer program, and the processor is used to call the computer program to execute the first aspect or any possibility of the first aspect method described in the implementation of .
  • an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program includes program instructions.
  • the program instructions When the program instructions are executed by the processor, the first The method described in the aspect or any one of the possible implementations of the first aspect.
  • FIG. 1 is a schematic flowchart of a method for positioning a vehicle according to an embodiment of the present application
  • FIG. 2 is a schematic diagram of a scene of a method for positioning a vehicle provided by an embodiment of the present application
  • FIG. 3 is a schematic flowchart of determining a first positioning estimation result provided by an embodiment of the present application.
  • FIG. 4 is a schematic flowchart of determining a second positioning estimation result provided by an embodiment of the present application.
  • FIG. 5 is a schematic flowchart of another vehicle positioning method provided by an embodiment of the present application.
  • FIG. 6 is a schematic diagram of the composition of a vehicle positioning device provided by an embodiment of the present application.
  • FIG. 7 is a schematic diagram of the composition of another vehicle positioning device provided by an embodiment of the present application.
  • FIG. 8 is a schematic diagram of the composition of an apparatus for positioning a vehicle provided by an embodiment of the present application.
  • the vehicle positioning method provided by the embodiments of the present application can be applied to scenarios such as GPS failure or vehicle sensor failure, and of course, can also be applied to a normal GPS or vehicle sensor scenario.
  • the method for locating a vehicle provided by the embodiment of the present application is described by taking the first scenario and the second scenario as an example.
  • Vehicle positioning technology provides an important foundation for the realization of automatic driving, and is a key technology in the field of automatic driving technology. At present, most of the vehicle positioning technology relies on GPS, but because the GPS signal will be blocked and reflected by the surrounding environment, in special scenarios, such as tunnels, residential quarters, underground garages and other scenarios, the GPS signal is weak, resulting in vehicle positioning. Ineffective problem.
  • Vehicle positioning technology provides an important foundation for the realization of automatic driving, and is a key technology in the field of automatic driving technology. Due to the problems of low update frequency and easy occlusion and reflection of GPS, it is difficult for a single GPS to accurately locate the vehicle in complex scenes. Therefore, various road information can be obtained through other vehicle sensors to realize the positioning of the vehicle. However, during the driving process of the car, when the vehicle sensor fails suddenly, the positioning result cannot be constrained, which affects the accuracy of the positioning result. For example, when the lidar sensor fails, the distance between the vehicle and surrounding obstacles cannot be determined. The distance is measured, causing the car positioning results to be affected.
  • the vehicle to be positioned can obtain the GPS positioning covariance of the vehicle to be positioned; when the GPS positioning covariance is less than or equal to the preset positioning covariance threshold, the initial positioning information of the vehicle to be positioned and Vehicle information of surrounding vehicles, the surrounding vehicles are vehicles whose distance from the vehicle to be located is less than the preset distance threshold, and the vehicle information includes distance information and vehicle speed information; according to the initial positioning information of the vehicle to be located and the vehicle information of the surrounding vehicles, determine the The first positioning calculation result; according to the first positioning calculation result, the second positioning calculation result of the vehicle to be positioned is determined. Obtain GPS positioning results and IMU estimation results; according to GPS positioning results and IMU estimation results, combined with the second positioning estimation results, perform positioning fusion through EKF to determine the final positioning result of the vehicle to be positioned.
  • the vehicle positioning method can obtain the initial positioning information of the vehicle to be located when the GPS is normal, and then when the GPS fails or the signal is poor, and/or the sensor of the vehicle to be located fails, By acquiring the vehicle information of the surrounding vehicles, combined with the initial positioning information of the vehicle to be located, the global positioning information of the vehicle to be located is calculated, which effectively improves the accuracy of the vehicle positioning result and the robustness of the vehicle positioning system.
  • Embodiment 1 and Embodiment 2 may be applied to the above-mentioned scenario 1 and scenario 2.
  • FIG. 1 is a schematic flowchart of a method for positioning a vehicle provided by an embodiment of the present application. As shown in Figure 1, the method for car positioning includes the following steps:
  • the vehicle to be located may be a vehicle that needs to be located due to GPS failure in environments such as tunnels, residential areas, and underground parking lots; it may also be a vehicle for which the vehicle sensor is faulty, so it is impossible to obtain the surrounding environment information for positioning.
  • the vehicle sensor may be a vehicle sensor such as a lidar, an ultrasonic radar, or the like.
  • GPS positioning covariance can be used to represent the accuracy of the positioning results output by the vehicle positioning system. The lower the accuracy of the output positioning result.
  • the device for obtaining the initial positioning information of the vehicle to be positioned may be a vehicle-mounted GPS receiver, an inertial measurement unit IMU sensor, and other devices.
  • the device for obtaining vehicle information of surrounding vehicles may be a vehicle-mounted camera, a millimeter-wave radar, a V2X broadcast communicator, etc., wherein the vehicle-mounted camera may be a monocular camera, a binocular camera, a trinocular camera, a surround-view camera, etc., the embodiment of the present application Not limited.
  • the surrounding vehicles are vehicles whose distance from the vehicle to be located is less than a preset distance threshold, and the vehicle information includes distance information and vehicle speed information.
  • the preset distance threshold can be used to indicate the maximum distance between the surrounding vehicles and the vehicle to be located.
  • the vehicle to be located can be obtained through a V2X broadcast communicator and other devices Vehicle information of surrounding vehicles.
  • the vehicle information of the surrounding vehicles also includes the identification information of the surrounding vehicles, the orientation information of the surrounding vehicles, and the angle difference information between the surrounding vehicles and the vehicle to be positioned.
  • the orientation information includes the yaw angle information of the surrounding vehicles in the world coordinate system, the surrounding vehicles The pitch angle information of the vehicle and the roll angle information of the surrounding vehicles;
  • the distance information includes the lateral distance information between the surrounding vehicle and the vehicle to be positioned, and the longitudinal distance information between the surrounding vehicle and the vehicle to be positioned;
  • the vehicle speed information includes the surrounding vehicle Vehicle speed information and yaw rate information of surrounding vehicles.
  • the identification information of the surrounding vehicles may be information that uniquely identifies the vehicle, such as a license plate number, which is not limited in the embodiment of the present application.
  • the device for determining the first positioning estimation result may be a vehicle-mounted terminal, or a device such as a server or a cloud, which is not limited in this embodiment of the present application.
  • the method provided by this embodiment of the present application may further include: judging whether the GPS positioning covariance is greater than a preset positioning covariance threshold, and if so, executing the determination according to the initial positioning information of the vehicle to be positioned and the vehicle information of the surrounding vehicles.
  • the first location estimation result of surrounding vehicles may further include: judging whether the GPS positioning covariance is greater than a preset positioning covariance threshold, and if so, executing the determination according to the initial positioning information of the vehicle to be positioned and the vehicle information of the surrounding vehicles. The first location estimation result of surrounding vehicles.
  • FIG. 2 is a schematic diagram of a scene of a method for positioning a vehicle provided by an embodiment of the present application.
  • vehicle A is the vehicle to be located.
  • Vehicles B, C, and D are the same as the vehicle.
  • the distances between A are all less than the preset distance threshold; in addition, the four vehicles are equipped with V2X broadcast communicators, and vehicle A is also equipped with an on-board camera, millimeter-wave radar sensor, on-board GPS receiver and inertial measurement unit IMU .
  • scenario 1 the GPS positioning of A, B, C, and D is temporarily lost due to building blockage and other reasons.
  • vehicle A obtains the initial positioning information and surrounding information of the vehicle in step S102.
  • the vehicle information of vehicles B, C and D when it is detected that the GPS positioning covariance is greater than the preset positioning covariance threshold, that is, after the GPS positioning is lost, the steps described in S103 are started; When a fault occurs, the positioning of vehicle A is affected. At this time, vehicle A can obtain the initial positioning information of its own vehicle and the vehicle information of surrounding vehicles B, C and D in step S102. When it is detected that the GPS positioning covariance is greater than the preset value When the covariance threshold is located, that is, the vehicle sensor fails and the positioning is affected, the steps described in S103 are started.
  • FIG. 3 is a schematic flowchart of determining a first positioning estimation result provided by an embodiment of the present application.
  • the steps of S103 include:
  • the vehicle tracking table may include identification information of surrounding vehicles, acquisition time of vehicle information, initial positioning information, vehicle speed information, orientation information, distance information from the vehicle to be located, and a first positioning calculation result.
  • the identification information of the surrounding vehicles can be obtained through the on-board camera of the vehicle to be located; the speed information and orientation information of the surrounding vehicles can be obtained through the V2X broadcast communicator of the vehicle to be located; the distance information between the surrounding vehicles and the vehicle to be located is specific It includes lateral distance information and longitudinal distance information, which can be obtained through the millimeter-wave radar, V2X broadcast communicator and vehicle camera of the vehicle to be located.
  • the image data captured by the vehicle camera can determine the positional relationship between the surrounding vehicles and the vehicle to be located, such as Front, rear, left, right, etc.; the initial positioning information of the surrounding vehicles and the first positioning calculation result may be calculated by the on-board terminal, server, or cloud of the vehicle to be positioned, which is not limited in this embodiment of the present application.
  • the initial positioning information of the surrounding vehicles may be the first initial positioning coordinates (x i_t0 , y i_t0 , z i_t0 , yaw i_t0 , pitch i_t0 , roll i_t0 ), and the initial positioning information of the vehicle to be positioned may be is the second initial positioning coordinate (x t0 , y t0 , z t0 , yaw t0 , pitch t0 , roll t0 ), and the initial positioning calculation algorithm is:
  • x i_t0 x t0 +lx i_t0 ;
  • y i_t0 y t0 +ly i_t0 ;
  • yaw i_t0 yaw t0 +lyaw i_t0 ;
  • pitch i_t0 pitch t0 ;
  • x i_t0 , y i_t0 , z i_t0 , yaw i_t0 , pitch i_t0 and roll i_t0 respectively represent the coordinate information of the surrounding vehicle with serial number i in the direction of the preset x-coordinate axis at the initial time t 0
  • the preset y-coordinate axis Coordinate information in the direction, coordinate information in the direction of the preset z coordinate axis, yaw angle information, pitch angle information and roll angle information, x t0 , y t0 , z t0 , yaw t0 , pitch t0 and roll t0 respectively Represents the coordinate information of the vehicle to be positioned in the direction of the preset x -coordinate axis, the coordinate information in the direction of the preset y-coordinate axis, the coordinate information in the direction of the preset z-coordinate axis, the y
  • the above-mentioned x, y, and z may be three-dimensional Cartesian coordinates in the world coordinate system, and the geodetic Cartesian coordinates where the Cartesian coordinates are located may take a certain position as a fixed origin, such as the position where the vehicle to be positioned starts to perform step S103.
  • Position take the north direction as the x-axis direction, the east direction as the y-axis direction, and the vertical upward direction as the z-axis direction; the above x, y, and z can also represent the latitude, longitude and altitude of the vehicle's location high.
  • yaw is the angle at which the front of the vehicle rotates around the z-coordinate axis
  • pitch is used to represent the angle between the head of the vehicle and the ground level, that is, the angle at which the vehicle rotates around the y-coordinate axis
  • roll is the angle at which the vehicle rotates around the x-coordinate axis.
  • the first positioning estimation result includes first positioning estimation coordinates (x i_t , y i_t , z i_t , yaw i_t , pitch i_t , roll i_t ), and the first positioning estimation algorithm includes:
  • yaw i_t yaw i_t- ⁇ t +yawrate i_t * ⁇ t;
  • pitch i_t pitch i_t- ⁇ t ;
  • roll i_t roll i_t- ⁇ t ;
  • x i_t x i_t- ⁇ t +v i_t *cosyaw i_t * ⁇ t;
  • y i_t y i_t- ⁇ t +v i_t *sinyaw i_t * ⁇ t;
  • x i_t , y i_t , z i_t , yaw i_t , pitch i_t and roll i_t respectively represent the coordinate information of the surrounding vehicle with serial number i in the preset x-coordinate axis direction at time t, in the preset y-coordinate axis direction coordinate information, coordinate information in the direction of the preset z coordinate axis, yaw angle information, pitch angle information and roll angle information, x i_t- ⁇ t , y i_t- ⁇ t , z i_t- ⁇ t , yaw i_t- ⁇ t , pitch i_t- ⁇ t and roll i_t- ⁇ t respectively represent the coordinate information of the surrounding vehicle with serial number i in the preset x-coordinate axis direction at time t- ⁇ t, the coordinate information in the preset y-coordinate axis direction, and the preset z coordinate information.
  • yawrate i_t represents the yaw rate information of the surrounding vehicle with serial number i at time t
  • ⁇ t is the preset time interval
  • v i_t represents The speed information of the surrounding vehicle with serial number i at time t.
  • the yaw rate information and vehicle speed information of surrounding vehicles can be acquired through the V2X broadcast communicator.
  • the basic information for calculating the positioning result of the vehicle to be located it can solve the problem that vehicle positioning cannot be performed when the GPS of the surrounding vehicles is lost, thereby improving the robustness of the positioning system.
  • FIG. 4 is a schematic flowchart of determining a second positioning estimation result provided by an embodiment of the present application. As shown in FIG. 4, the steps of S104 include:
  • the angle difference information between the surrounding vehicles and the vehicle to be positioned can be obtained through the millimeter-wave radar of the vehicle to be positioned; the lateral distance information between the surrounding vehicle and the vehicle to be positioned, and the longitudinal distance between the surrounding vehicle and the vehicle to be positioned
  • the distance information can be obtained through the millimeter-wave radar of the vehicle to be located and the vehicle-mounted camera, wherein the millimeter-wave radar is used to measure the distance between the surrounding vehicle and the vehicle to be located, and the vehicle-mounted camera is used to capture the position between the surrounding vehicle and the vehicle to be located. relation.
  • the second positioning estimation result includes second positioning estimation coordinates (x t , y t , z t , yaw t , pitch t , roll t ), and the second positioning estimation algorithm includes:
  • x t x i_t -lx i_t ;
  • yaw t yaw i_t -lyaw i_t ;
  • pitch t pitch i_t ;
  • x t , y t , z t , yaw t , pitch t and roll t respectively represent the coordinate information of the vehicle to be positioned in the direction of the preset x-coordinate axis and the coordinate information in the direction of the preset y-coordinate axis at time t , coordinate information, yaw angle information, pitch angle information and roll angle information in the direction of the preset z coordinate axis, x i_t , y i_t , z i_t , yaw i_t , pitch i_t and roll i_t respectively represent the serial number i
  • the updated z value and vehicle pitch angle information can be obtained through a high-precision map, which is not limited in the embodiment of the present application.
  • step S103 through the first positioning calculation algorithm, the first positioning calculation result of the surrounding vehicle is determined, and on the basis of the first positioning calculation result, the distance and position between the surrounding vehicle and the vehicle to be positioned are combined relationship, as well as the angle difference information between the surrounding vehicles and the vehicle to be located, the position of the vehicle to be located can be inversely deduced through the second positioning calculation algorithm, that is, the second positioning calculation result.
  • the positional relationship between the surrounding vehicles and the vehicle to be positioned can determine the positive and negative of lx i_t and ly i_t ; for example, in the direction of the x-coordinate axis, when the surrounding vehicles are in the positive direction of the vehicle to be positioned, lx i_t takes a positive number On the contrary, when the surrounding vehicles are in the negative direction of the vehicle to be located, lx i_t takes a negative number; in the direction of the y coordinate axis, when the surrounding vehicles are in the positive direction of the vehicle to be located, ly i_t takes a positive number, otherwise when the surrounding vehicles are in the undetermined direction When the vehicle is in the negative direction, ly i_t takes a negative number.
  • N vehicles in the surrounding vehicles correspond to N first positioning estimation results.
  • the above method includes: respectively determining the to-be-located according to the N first positioning estimation results. For the N second positioning estimation results corresponding to the vehicle, the average value of the positioning results of the N second positioning estimation results is calculated, and the average value of the positioning results is used as the final second positioning estimation result of the vehicle to be positioned.
  • Embodiment 2 is a diagrammatic representation of Embodiment 1:
  • FIG. 5 is a schematic flowchart of another vehicle positioning method provided by an embodiment of the present application. As shown in FIG. 5 , compared with the first embodiment, steps S501 to S504 are the same as steps S101 to S104 of the first embodiment. After step S504, the method of the second embodiment further includes:
  • the second positioning calculation result calculated according to the method described in Embodiment 1 can be used as the positioning result of the vehicle to be positioned; it can also be used as the positioning constraint of the IMU.
  • the Kalman filter EKF By extending the Kalman filter EKF, the GPS positioning results, The IMU estimation result and the second positioning estimation result are fused to obtain the final positioning result of the vehicle to be positioned.
  • the EKF starts to perform the iteration of positioning information prediction and positioning information observation, and finally obtains the final positioning result of the vehicle to be positioned.
  • the positioning information observation can be used to perform weighted correction on the result of the positioning information prediction, so as to obtain the accuracy of the positioning result.
  • FIG. 6 is a schematic diagram of the composition of an apparatus for positioning a vehicle provided by an embodiment of the present application.
  • the vehicle positioning apparatus 600 provided in the embodiment of the present application may include:
  • a positioning covariance obtaining module 601, configured to obtain the GPS positioning covariance of the vehicle to be positioned
  • the vehicle information obtaining module 602 is configured to obtain initial positioning information of the vehicle to be positioned and vehicle information of surrounding vehicles when the GPS positioning covariance is less than or equal to a preset positioning covariance threshold, where the distance between the surrounding vehicles and the vehicle to be positioned is less than the preset distance Threshold vehicle, vehicle information includes distance information and vehicle speed information;
  • the first positioning estimation module 603 is configured to determine the first positioning estimation result of the surrounding vehicles according to the initial positioning information of the vehicle to be positioned and the vehicle information of the surrounding vehicles;
  • the second positioning estimation module 604 is configured to determine the second positioning estimation result of the vehicle to be positioned according to the first positioning estimation result.
  • the specific function implementation manners of the positioning covariance obtaining module 601 and the vehicle information obtaining module 602 may refer to steps S101-S102 in Embodiment 1 corresponding to FIG. 1 , which will not be repeated here.
  • the first positioning estimation module 603 includes:
  • the positioning covariance judging unit 6031 is configured to judge whether the GPS positioning covariance is greater than the preset positioning covariance threshold, and if so, execute step S103 in the first embodiment.
  • a vehicle tracking table establishment unit 6032 used for establishing a vehicle tracking table according to the vehicle information of surrounding vehicles
  • the initial positioning calculation unit 6033 is used to obtain the initial positioning information of the surrounding vehicles through the initial positioning calculation algorithm according to the vehicle tracking table and the initial positioning information of the vehicle to be positioned;
  • the first positioning estimation unit 6034 is configured to obtain a first positioning estimation result through a first positioning estimation algorithm according to the initial positioning information of the surrounding vehicles and the vehicle information of the surrounding vehicles.
  • step S103 in Embodiment 1 corresponding to FIG. 1 which will not be repeated here.
  • the second location estimation module 604 includes:
  • the information acquisition unit 6041 is used to acquire the angle difference information between the surrounding vehicles and the vehicle to be located, the lateral distance information between the surrounding vehicles and the vehicle to be located, and the longitudinal distance information between the surrounding vehicles and the vehicle to be located;
  • the second positioning calculation unit 6042 is configured to obtain the second positioning calculation result through the second positioning calculation algorithm in combination with the first positioning calculation result;
  • the positioning result mean value calculation unit 6043 is used to respectively determine N second positioning calculation results corresponding to the vehicle to be positioned according to the N first positioning calculation results, calculate the positioning result mean of the N second positioning calculation results, and use the positioning result mean as The final second positioning calculation result of the vehicle to be positioned.
  • step S104 for the specific function implementation manner of the second positioning estimation module 604, reference may be made to step S104 in the first embodiment corresponding to FIG. 1 , which will not be repeated here.
  • FIG. 7 is a schematic diagram of the composition of another vehicle positioning device provided by an embodiment of the present application.
  • the modules 701-704 are the same as the modules 601-604 in the apparatus 600.
  • the apparatus 700 may further include:
  • the positioning result obtaining module 705 is used to obtain the GPS positioning result and the inertial measurement unit IMU estimation result;
  • the positioning result fusion module 706 is configured to determine the final positioning result of the vehicle to be positioned by extending the Kalman filter according to the GPS positioning result and the IMU estimation result in combination with the second positioning estimation result.
  • the specific function implementation manner of the positioning result obtaining module 705 and the positioning result fusion module 706 may refer to steps S505-S506 in the second embodiment corresponding to FIG. 5 , which will not be repeated here.
  • FIG. 8 is a schematic diagram of the composition of an apparatus for positioning a vehicle provided by an embodiment of the present application.
  • the apparatus 800 for car positioning shown in FIG. 8 (the apparatus 800 may specifically be a computer device) includes a memory 801 , a processor 802 , a communication interface 803 and a bus 804 .
  • the memory 801 , the processor 802 , and the communication interface 803 are connected to each other through the bus 804 for communication.
  • the memory 801 may be a read only memory (Read Only Memory, ROM), a static storage device, a dynamic storage device, or a random access memory (Random Access Memory, RAM).
  • the memory 801 can store a program. When the program stored in the memory 801 is executed by the processor 802, the processor 802 and the communication interface 803 are used to execute each step of the method for vehicle positioning provided by the embodiments of the present application.
  • the processor 802 may adopt a general-purpose central processing unit (Central Processing Unit, CPU), a microprocessor, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a graphics processing unit (graphics processing unit, GPU) or one or more
  • the integrated circuit is used to execute the relevant program to realize the function required to be performed by the unit in the apparatus for positioning the vehicle of the embodiment of the present application, or to execute the method for positioning the vehicle of the method embodiment of the present application.
  • the processor 802 may also be an integrated circuit chip with signal processing capability. In the implementation process, each step of the method for positioning a vehicle of the present application can be completed by an integrated logic circuit of hardware in the processor 802 or instructions in the form of software.
  • the above-mentioned processor 802 may also be a general-purpose processor, a digital signal processor (Digital Signal Processing, DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (Field Programmable Gate Array, FPGA) or other programmable logic devices. , discrete gate or transistor logic devices, discrete hardware components.
  • a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
  • the steps of the method disclosed in conjunction with the embodiments of the present application may be directly embodied as executed by a hardware decoding processor, or executed by a combination of hardware and software modules in the decoding processor.
  • the software modules may be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other storage media mature in the art.
  • the storage medium is located in the memory 801, and the processor 802 reads the information in the memory 801 and, in combination with its hardware, completes the functions required to be performed by the units included in the vehicle positioning apparatus of the embodiment of the present application, or executes the car of the method embodiment of the present application. method of positioning.
  • the communication interface 803 uses a transceiving device such as, but not limited to, a transceiver to implement communication between the device 800 and other devices or a communication network.
  • a transceiving device such as, but not limited to, a transceiver to implement communication between the device 800 and other devices or a communication network.
  • Bus 804 may include a pathway for communicating information between various components of device 800 (eg, memory 801, processor 802, communication interface 803).
  • a computer-readable storage medium on which instructions are stored, and when the instructions are executed, the methods in the foregoing method embodiments are performed.
  • FIG. 8 It can be understood by those skilled in the art that, for the convenience of description, only one memory and a processor are shown in FIG. 8 . In an actual controller, there may be multiple processors and memories.
  • the memory may also be referred to as a storage medium or a storage device, etc., which is not limited in this embodiment of the present application.
  • the processor may be a central processing unit (Central Processing Unit, referred to as CPU), and the processor may also be other general-purpose processors, digital signal processors (Digital Signal Processing, referred to as DSP), Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • CPU Central Processing Unit
  • DSP Digital Signal Processing
  • ASIC Application Specific Integrated Circuit
  • FPGA Field-Programmable Gate Array
  • the memory mentioned in the embodiments of the present application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.
  • the non-volatile memory may be a read-only memory (Read-Only Memory, referred to as ROM), a programmable read-only memory (Programmable ROM, referred to as PROM), an erasable programmable read-only memory (Erasable PROM, referred to as EPROM) , Electrically Erasable Programmable Read-Only Memory (Electrically EPROM, EEPROM for short) or flash memory.
  • the volatile memory may be Random Access Memory (RAM for short), which is used as an external cache memory.
  • RAM Static Random Access Memory
  • DRAM Dynamic RAM
  • SDRAM Synchronous DRAM
  • DDR SDRAM double data rate synchronous dynamic random access memory
  • ESDRAM enhanced synchronous dynamic random access memory
  • SLDRAM synchronous connection dynamic random access memory
  • Direct Rambus RAM Direct Rambus RAM
  • the processor is a general-purpose processor, DSP, ASIC, FPGA or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components
  • the memory storage module
  • memory described herein is intended to include, but not be limited to, these and any other suitable types of memory.
  • the bus may also include a power bus, a control bus, a status signal bus, and the like.
  • the various buses are labeled as buses in the figure.
  • each step of the above-mentioned method can be completed by a hardware integrated logic circuit in a processor or an instruction in the form of software.
  • the steps of the methods disclosed in conjunction with the embodiments of the present application may be directly embodied as executed by a hardware processor, or executed by a combination of hardware and software modules in the processor.
  • the software modules may be located in random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers and other storage media mature in the art.
  • the storage medium is located in the memory, and the processor reads the information in the memory, and completes the steps of the above method in combination with its hardware. To avoid repetition, detailed description is omitted here.
  • the size of the sequence numbers of the above-mentioned processes does not mean the sequence of execution, and the execution sequence of each process should be determined by its functions and internal logic, rather than the implementation process of the embodiments of the present application. constitute any limitation.
  • the disclosed method and apparatus may be implemented in other manners.
  • the apparatus embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented.
  • the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the above-mentioned embodiments it may be implemented in whole or in part by software, hardware, firmware or any combination thereof.
  • software it can be implemented in whole or in part in the form of a computer program product.
  • the computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated.
  • the computer may be a general purpose computer, special purpose computer, computer network, or other programmable device.
  • the computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, for example, the computer instructions may be downloaded from a website site, computer, server, or data center Transmission to another website site, computer, server, or data center by wire (eg, coaxial cable, optical fiber, digital subscriber line) or wireless (eg, infrared, wireless, microwave, etc.).
  • the computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. that includes an integration of one or more available media.
  • the usable media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, DVDs), or semiconductor media (eg, solid state drives), and the like.

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Abstract

一种汽车定位的方法及装置（600,700,800），方法包括：获取待定位车辆的全球定位系统GPS定位协方差（S101）；当GPS定位协方差小于等于预设定位协方差阈值时，获取待定位车辆的初始定位信息和周边车辆的车辆信息（S102）；根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果（S103）；根据第一定位推算结果，确定待定位车辆的第二定位推算结果（S104）。可以在GPS失效或车辆传感器出现故障的情况下，利用周边车辆的车辆信息计算待定位车辆的全局定位信息，提高在特殊场景中汽车定位结果的准确性，提升汽车定位系统的鲁棒性。

Description

一种汽车定位的方法及装置
本申请要求于2020年10月30日提交中国专利局、申请号为202011194287.8、发明名称为“一种汽车定位的方法及装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及自动驾驶技术领域，尤其涉及一种汽车的定位方法及装置。
背景技术
自动驾驶技术在车联网技术和人工智能技术的支持下，能够提高出行效率，并在一定程度上减少能源消耗、提升安全性，已成为一项完整、安全和有效的前沿科技。汽车定位技术是自动驾驶功能的重要基础和关键技术，定位的丢失会导致无人驾驶汽车无法正常运行，可能酿成重大事故。
目前，针对自动驾驶的定位问题，一般采用全球定位系统(Global Positioning System，简称GPS)和惯性测量单元(Inertial Measuring Unit，简称IMU)的组合定位来得到较高精度的定位结果，有时也会通过基于激光和视觉的即时定位与地图构建(simultaneous localization and mapping，简称SLAM)技术来对IMU进行约束，从而实现对汽车位置的修正。
然而，上述方法受外界环境影响较大，尤其在一些特殊场景中，如隧道中GPS失效且视觉及激光特征减少，IMU失去大部分约束，从而导致定位结果产生偏差，难以实现车辆的全局定位。
发明内容
本申请实施例提供一种汽车定位的方法及装置，可以在GPS失效或待定位车辆的车辆传感器出现故障的情况下，利用周边车辆的车辆信息计算待定位车辆的全局定位信息，提高在特殊场景中汽车定位结果的准确性，提升汽车定位系统的鲁棒性。
第一方面，本申请实施例提供了一种汽车定位的方法，包括：
获取待定位车辆的全球定位系统GPS定位协方差；当GPS定位协方差小于等于预设定位协方差阈值时，获取待定位车辆的初始定位信息和周边车辆的车辆信息，周边车辆为与待定位车辆距离小于预设距离阈值的车辆，车辆信息包括距离信息和车速信息；根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果；根据第一定位推算结果，确定待定位车辆的第二定位推算结果。
应理解，待定位车辆可以是在隧道、小区和地下停车场等环境中GPS失效，需要进行定位的车辆，也可以是车辆传感器出现故障，因此无法通过获取周边环境信息进行定位的车辆，出现故障的车辆传感器可以是激光雷达、超声波雷达等车辆传感器。获取周边车辆的车辆信息的设备可以是车载摄像头、毫米波雷达传感器和车辆无线通信技术(vehicle to everything，简称V2X)广播通信器等设备。确定定位推算结果的设备可以是车载终端，也可以是服务器或者云端等设备。
上述方法可以在GPS失效或车辆传感器出现故障、无法进行车辆定位时，通过获取周边车辆的信息计算出待定位车辆的定位信息，可以有效降低车辆因为定位丢失而引发安全事故的可能性，提高汽车定位结果的准确性。
在一个可选的实现方式中，周边车辆的车辆信息还包括周边车辆的标识信息、周边车辆的朝向信息，以及周边车辆和待定位车辆之间的角度差信息，朝向信息包括周边车辆的横摆角信息、周边车辆的俯仰角信息和周边车辆的横滚角信息；距离信息包括周边车辆与待定位车辆之间的横向距离信息，以及周边车辆与待定位车辆之间的纵向距离信息；车速信息包括周边车辆的车速信息和周边车辆的横摆角速度信息。
在一个可选的实现方式中，根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果，包括：根据周边车辆的车辆信息，建立车辆追踪表；根据车辆追踪表和待定位车辆的初始定位信息，通过初始定位推算算法得到周边车辆的初始定位信息；根据周边车辆的初始定位信息和周边车辆的车辆信息，通过第一定位推算算法得到第一定位推算结果。
在一个可选的实现方式中，周边车辆的初始定位信息包括第一初始定位坐标(x i_t0,y i_t0,z i_t0,yaw i_t0,pitch i_t0,roll i_t0)，待定位车辆的初始定位信息包括第二初始定位坐标(x t0,y t0,z t0,yaw t0,pitch t0,roll t0)，初始定位推算算法包括：
x i_t0＝x t0+lx i_t0；
y i_t0＝y t0+ly i_t0；
z i_t0＝z t0；
yaw i_t0＝yaw t0+lyaw i_t0；
pitch i_t0＝pitch t0；
roll i_t0＝roll t0；
其中，x i_t0、y i_t0、z i_t0、yaw i_t0、pitch i_t0和roll i_t0分别表示序号为i的周边车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x t0、y t0、z t0、yaw t0、pltch t0和roll t0分别表示待定位车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t0和ly i_t0分别表示序号为i的周边车辆与待定位车辆在初始时刻t 0的横向距离信息和纵向距离信息，lyaw i_t0表示序号为i的周边车辆与待定位车辆在初始时刻t 0的角度差信息。
在一个可选的实现方式中，第一定位推算结果包括第一定位推算坐标(x i_t,y i_t,z i_t,yaw i_t,pitch i_t,roll i_t)，第一定位推算算法包括：
yaw i_t＝yaw i_t-Δt+yawrate i_t*Δt；
pitch i_t＝pitch i_t-Δt；
roll i_t＝roll i_t-Δt；
x i_t＝x i_t-Δt+v i_t*cosyaw i_t*Δt；
y i_t＝y i_t-Δt+v i_t*sinyaw i_t*Δt；
z i_t＝z i_t-Δt；
其中，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t-Δt、y i_t-Δt、z i_t-Δt、yaw i_t-Δt、pitch i_t-Δt和roll i_t-Δt分别表示序号为i的周边车辆在t-Δt时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横滚角信息、俯仰角信息和横滚角信息，yawrate i_t表示序号为i的周边车辆在t时刻的横摆角速度信息，Δt为预设时间间隔，v i_t表示序号为i的周边车辆在t时刻的车速信息。
上述方法通过获取周边车辆的车辆信息，推算得到周边车辆的第一定位推算结果，可以 实现在GPS失效环境下计算得到周边车辆的定位信息，作为计算待定位车辆定位结果的基础信息，从而提高定位系统的鲁棒性。
在一个可选的实现方式中，根据第一定位推算结果，确定待定位车辆的第二定位推算结果，包括：获取周边车辆与待定位车辆之间的角度差信息、周边车辆与待定位车辆之间的横向距离信息，以及周边车辆与待定位车辆之间的纵向距离信息；结合第一定位推算结果，通过第二定位推算算法，得到第二定位推算结果。
在一个可选的实现方式中，第二定位推算结果包括第二定位推算坐标(x t,y t,z t,yaw t,pitch t,roll t)，第二定位推算算法包括：
x t＝x i_t-lx i_t；
y t＝y i_t-ly i_t；
z t＝z i_t；
yaw t＝yaw i_t-lyaw i_t；
pitch t＝pitch i_t；
roll t＝roll i_t；
其中，x t、y t、z t、yaw t、pitch t和roll t分别表示待定位车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t和ly i_t分别表示序号为i的周边车辆与待定位车辆在t时刻的横向距离信息和纵向距离信息,lyaw i_t表示所述序号为i的周边车辆与所述待定位车辆在t时刻的角度差信息。
上述方法，通过获取周边车辆与待定位车辆之间的角度差信息，以及周边车辆与待定位车辆之间的距离信息，通过第二定位推算算法计算得到待定位车辆的定位推算结果，可以实现在汽车运行过程中，基于周边车辆的车辆信息计算待定位车辆的定位信息，有利于减小待定位车辆的定位误差，实现对待定位车辆的全局定位。
在一个可选的实现方式中，在根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果之前，该方法还包括：判断GPS定位协方差是否大于预设定位协方差阈值，若是，则执行根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果。
上述方法，通过判断GPS定位协方差和预设定位协方差阈值的大小关系，在GPS定位协方差大于预设定位协方差阈值时，使能本申请实施例提供的汽车定位方法，从而可以在GPS失效或车辆传感器出现故障，导致定位结果准确性降低的情况下，通过周边车辆的车辆信息来对定位系统进行约束，有效防止因为GPS定位丢失引发的危害，并提高待定位车辆定位结果的准确性。
在一个可选的实现方式中，当周边车辆的数量N大于1时，周边车辆中的N台车辆对应N个第一定位推算结果，根据第一定位推算结果，确定待定位车辆的第二定位推算结果，包括：根据N个第一定位推算结果分别确定待定位车辆对应的N个第二定位推算结果，计算N个第二定位推算结果的定位结果均值，将定位结果均值作为待定位车辆最终的第二定位推算结果。
上述方法，在周边车辆的数量大于1时，计算出待定位车辆相对于每一辆周边车辆的第二定位推算结果，通过取第二定位推算结果平均值的方法，对待定位车辆的定位结果进行进一步处理，降低待定位车辆定位结果的误差，实现对待定位车辆的全局定位。
在一个可选的实现方式中，该方法还包括：获取GPS定位结果和惯性测量单元IMU推算 结果；根据GPS定位结果和IMU推算结果，结合第二定位推算结果，通过扩展卡尔曼滤波器(Extended KalmanFilter，简称EKF)，确定待定位车辆的最终定位结果。
上述方法通过EKF对GPS定位结果、IMU推算结果和第二定位推算结果进行定位结果融合，可以实现在IMU失去定位约束时，通过周边车辆的车辆信息对IMU进行定位约束，提高定位结果的准确性和定位系统的鲁棒性。
第二方面，本申请实施例提供了一种汽车定位的装置，包括：
定位协方差获取模块，用于获取待定位车辆的全球定位系统GPS定位协方差；车辆信息获取模块，用于当GPS定位协方差小于等于预设定位协方差阈值时，获取待定位车辆的初始定位信息和周边车辆的车辆信息，周边车辆为与待定位车辆距离小于预设距离阈值的车辆，车辆信息包括距离信息和车速信息；第一定位推算模块，用于根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果；第二定位推算模块，用于根据第一定位推算结果，确定待定位车辆的第二定位推算结果。
应理解，待定位车辆可以是在隧道、小区和地下停车场等环境中GPS失效，需要进行定位的车辆，也可以是车辆传感器出现故障，因此无法通过获取周边环境信息进行定位的车辆。出现故障的车辆传感器可以是激光雷达、超声波雷达等车辆传感器。获取周边车辆的车辆信息的设备可以是车载摄像头、毫米波雷达和车辆无线通信技术(vehicle to everything，简称V2X)通信模块等设备。确定定位推算结果的设备可以是车载终端，也可以是服务器或者云端等设备。
上述装置可以在GPS失效或车辆传感器出现故障、无法进行车辆定位时，通过获取周边车辆的信息计算出待定位车辆的定位信息，可以有效降低车辆因为定位丢失而引发安全事故的可能性，提高汽车定位结果的准确性。
在一个可选的实现方式中，周边车辆的车辆信息还包括周边车辆的标识信息、周边车辆的朝向信息，以及所述周边车辆和所述待定位车辆之间的角度差信息，朝向信息包括周边车辆的横摆角信息、周边车辆的俯仰角信息和周边车辆的横滚角信息；距离信息包括周边车辆与待定位车辆之间的横向距离信息，以及周边车辆与待定位车辆之间的纵向距离信息；车速信息包括周边车辆的车速信息和周边车辆的横摆角速度信息。
在一个可选的实现方式中，第一定位推算模块包括：车辆追踪表建立单元，用于根据周边车辆的车辆信息，建立车辆追踪表；初始定位计算单元，用于根据车辆追踪表和待定位车辆的初始定位信息，通过初始定位推算算法得到周边车辆的初始定位信息；第一定位推算单元，用于根据周边车辆的初始定位信息和周边车辆的车辆信息，通过第一定位推算算法得到第一定位推算结果。
在一个可选的实现方式中，周边车辆的初始定位信息包括第一初始定位坐标(x i_t0,y i_t0,z i_t0,yaw i_t0,pitch i_t0,roll i_t0)，待定位车辆的初始定位信息包括第二初始定位坐标(x t0,y t0,z t0,yaw t0,pitch t0,roll t0)，初始定位推算算法包括：
x i_t0＝x t0+lx i_t0；
y i_t0＝y t0+ly i_t0；
z i_t0＝z t0；
yaw i_t0＝yaw t0+lyaw i_t0；
pitch i_t0＝pitch t0；
roll i_t0＝roll t0；
其中，x i_t0、y i_t0、z i_t0、yaw i_t0、pitch i_t0和roll i_t0分别表示序号为i的周边车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐 标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x t0、y t0、z t0、yaw t0、pitch t0和roll t0分别表示待定位车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t0和ly i_t0分别表示序号为i的周边车辆与待定位车辆在初始时刻t 0的横向距离信息和纵向距离信息，lyaw i_t0表示所述序号为i的周边车辆与所述待定位车辆在初始时刻t 0的角度差信息。
在一个可选的实现方式中，第一定位推算结果包括第一定位推算坐标(x i_t,y i_t,z i_t,yaw i_t,pitch i_t,roll i_t)，第一定位推算算法包括：
yaw i_t＝yaw i_t-Δt+yawrate i_t*Δt；
pitch i_t＝pitch i_t-Δt；
roll i_t＝roll i_t-Δt；
x i_t＝x i_t-Δt+v i_t*cosyaw i_t*Δt；
y i_t＝y i_t-Δt+v i_t*sinyaw i_t*Δt；
z i_t＝z i_t-Δt；
其中，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t-Δt、y i_t-Δt、z i_t-Δt、yaw i_t-Δt、pitch i_t-Δt和roll i_t-Δt分别表示序号为i的周边车辆在t-Δt时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横滚角信息、俯仰角信息和横滚角信息，yawrate i_t表示序号为i的周边车辆在t时刻的横摆角速度信息，Δt为预设时间间隔，v i_t表示序号为i的周边车辆在t时刻的车速信息。
上述装置通过获取周边车辆的车辆信息，推算得到周边车辆的第一定位推算结果，可以实现在GPS失效环境下计算得到周边车辆的定位信息，作为计算待定位车辆定位结果的基础信息，从而提高定位系统的鲁棒性。
在一个可选的实现方式中，第二定位推算模块包括：信息获取单元，用于获取周边车辆与待定位车辆之间的角度差信息、周边车辆与待定位车辆之间的横向距离信息，以及周边车辆与待定位车辆之间的纵向距离信息；第二定位推算单元，用于结合第一定位推算结果，通过第二定位推算算法，得到第二定位推算结果。
在一个可选的实现方式中，第二定位推算结果包括第二定位推算坐标(x t,y t,z t,yaw t,pitch t,roll t)，第二定位推算算法包括：
x t＝x i_t-lx i_t；
y t＝y i_t-ly i_t；
z t＝z i_t；
yaw t＝yaw i_t-lyaw i_t；
pitch t＝pitch i_t；
roll t＝roll i_t；
其中，x t、y t、z t、yaw t、pitch t和roll t分别表示待定位车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t和ly i_t分别表示序号为i的周边车辆与待定位车辆在t时刻的横向距离信息和纵向距离信息,lyaw i_t表示所述序号为i的周边车辆与所述待定位车辆在t时刻的角度差信息。
上述装置，通过获取周边车辆与待定位车辆之间的角度差信息，以及周边车辆与待定位车辆之间的距离信息，通过第二定位推算算法计算得到待定位车辆的定位推算结果，可以实现在汽车运行过程中，基于周边车辆的车辆信息计算待定位车辆的定位信息，有利于减小待 定位车辆的定位误差，实现对待定位车辆的全局定位。
在一个可选的实现方式中，第一定位推算模块还包括：定位协方差判断单元，用于判断GPS定位协方差是否大于预设定位协方差阈值，若是，则执行根据所述待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果。
上述装置，通过判断GPS定位协方差和预设定位协方差阈值的大小关系，在GPS定位协方差大于预设定位协方差阈值时，使能本申请实施例提供的汽车定位方法，从而可以在GPS失效或车辆传感器出现故障，导致定位结果准确性降低的情况下，通过周边车辆的车辆信息来对定位系统进行约束，有效防止因为GPS定位丢失引发的危害，并提高待定位车辆定位结果的准确性。
在一个可选的实现方式中，当周边车辆的数量N大于1时，周边车辆中的N台车辆对应N个第一定位推算结果，第二定位推算模块包括：定位结果均值计算单元，用于根据N个第一定位推算结果分别确定待定位车辆对应的N个第二定位推算结果，计算N个第二定位推算结果的定位结果均值，将定位结果均值作为待定位车辆最终的第二定位推算结果。
上述装置，在周边车辆的数量大于1时，计算出待定位车辆相对于每一辆周边车辆的第二定位推算结果，通过取第二定位推算结果平均值的方法，对待定位车辆的定位结果进行进一步处理，降低待定位车辆定位结果的误差，实现对待定位车辆的全局定位。
在一个可选的实现方式中，该装置还包括：定位结果获取模块，用于获取GPS定位结果和惯性测量单元IMU推算结果；定位结果融合模块，用于根据GPS定位结果和IMU推算结果，结合第二定位推算结果，通过扩展卡尔曼滤波器，确定待定位车辆的最终定位结果。
上述装置通过EKF对GPS定位结果、IMU推算结果和第二定位推算结果进行定位结果融合，可以实现在IMU失去定位约束时，通过周边车辆的车辆信息对IMU进行定位约束，提高定位结果的准确性和定位系统的鲁棒性。
第三方面，本申请实施例提供了一种汽车定位的装置，包括存储器和处理器，存储器用于存储计算机程序，处理器用于调用计算机程序，以执行第一方面或第一方面任意一种可能的实现方式中所述的方法。
第四方面，本申请实施例提供了一种计算机可读存储介质，其特征在于，计算机可读存储介质存储有计算机程序，计算机程序包括程序指令，当程序指令被处理器执行时，执行第一方面或第一方面任意一种可能的实现方式中所述的方法。
附图说明
为了更清楚地说明本申请实施例或背景技术中的技术方案，下面将对本申请实施例或背景技术中所需要使用的附图进行说明。
图1是本申请实施例提供的一种汽车定位的方法的流程示意图；
图2是本申请实施例提供的一种汽车定位的方法的场景示意图；
图3是本申请实施例提供的一种确定第一定位推算结果的流程示意图；
图4是本申请实施例提供的一种确定第二定位推算结果的流程示意图；
图5是本申请实施例提供的另一种汽车定位的方法的流程示意图；
图6是本申请实施例提供的一种汽车定位的装置的组成示意图；
图7是本申请实施例提供的另一种汽车定位的装置的组成示意图；
图8是本申请实施例提供的一种汽车定位的装置的组成示意图。
具体实施方式
下面结合本申请实施例中的附图对本申请实施例进行描述。
本申请实施例提供的汽车定位方法可以应用在GPS失效或车辆传感器出现故障等场景，当然，也可以应用在GPS或车辆传感器正常的场景。下面，分别以场景一和场景二对本申请实施例提供的汽车定位的方法进行举例说明。
场景一：
汽车定位技术为自动驾驶的实现提供了重要基础，是自动驾驶技术领域中的一项关键技术，同时在一般的汽车导航系统中，也要基于汽车定位来实现出行路线规划。当前，汽车定位技术大多依赖GPS实现，但是由于GPS信号会受到周围环境的遮挡和反射，因此在特殊场景中，例如隧道、居民小区、地下车库等场景中，GPS信号较弱，从而出现车辆定位效果不佳的问题。
场景二：
汽车定位技术为自动驾驶的实现提供了重要基础，是自动驾驶技术领域中的一项关键技术，同时在一般的汽车导航系统中，也要基于汽车定位来实现出行路线规划。由于GPS存在更新频率较低、容易被遮挡反射等问题，在复杂场景下单一GPS难以实现对车辆的精确定位，因此可以通过其他车辆传感器，获取多种道路信息来实现对汽车的定位。然而，在汽车行驶过程中，当车辆传感器出现突发性故障时，无法对定位结果进行定位约束，影响定位结果的准确性，例如激光雷达传感器出现故障时，无法对车辆与周围障碍物之间的距离进行测量，导致汽车定位结果受到影响。
在场景一或场景二中，待定位车辆可以通过获取待定位车辆的全球定位系统GPS定位协方差；当GPS定位协方差小于等于预设定位协方差阈值时，获取待定位车辆的初始定位信息和周边车辆的车辆信息，周边车辆为与待定位车辆距离小于预设距离阈值的车辆，车辆信息包括距离信息和车速信息；根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果；根据第一定位推算结果，确定待定位车辆的第二定位推算结果。获取GPS定位结果和IMU推算结果；根据GPS定位结果和IMU推算结果，结合第二定位推算结果，通过EKF进行定位融合，确定待定位车辆的最终定位结果。
可见，本申请实施例提供的汽车定位的方法，可以在GPS正常时，获取待定位车辆的初始定位信息，然后在GPS失效或信号不佳，和/或待定位车辆传感器出现故障的情况下，通过获取周边车辆的车辆信息，结合待定位车辆的初始定位信息，计算得到待定位车辆的全局定位信息，有效提高汽车定位结果的准确性和汽车定位系统的鲁棒性。
下面详细描述本申请实施例涉及的方法。
需要说明的是，下述实施例一、实施例二可以应用于上述场景一和场景二中。
实施例一：
参见图1，图1是本申请实施例提供的一种汽车定位的方法的流程示意图。如图1所示，该汽车定位的方法包括如下步骤：
S101，获取待定位车辆的全球定位系统GPS定位协方差。
其中，待定位车辆可以是在隧道、小区和地下停车场等环境中GPS失效，需要进行定位的车辆；也可以是车辆传感器出现故障，因此无法通过获取周边环境信息进行定位的车辆， 出现故障的车辆传感器可以是激光雷达、超声波雷达等车辆传感器。
应理解，GPS定位协方差可用于表示车辆定位系统所输出的定位结果的准确性，GPS定位协方差越小，表示定位结果准确性越高，反之GPS定位协方差越大，表示车辆定位系统所输出的定位结果准确性越低。
S102，当GPS定位协方差小于等于预设定位协方差阈值时，获取待定位车辆的初始定位信息和周边车辆的车辆信息。
应理解，获取待定位车辆初始定位信息的设备可以是车载GPS接收机和惯性测量单元IMU传感器等设备。获取周边车辆的车辆信息的设备可以是车载摄像头、毫米波雷达和V2X广播通信器等设备，其中，车载摄像头可以是单目摄像头、双目摄像头、三目摄像头和环视摄像头等，本申请实施例不作限定。
周边车辆为与待定位车辆距离小于预设距离阈值的车辆，车辆信息包括距离信息和车速信息。预设距离阈值可以用于表示周边车辆与待定位车辆之间的最大距离，当周边车辆与待定位车辆之间的距离小于预设距离阈值时，待定位车辆可以通过V2X广播通信器等设备获取周边车辆的车辆信息。
周边车辆的车辆信息还包括周边车辆的标识信息、周边车辆的朝向信息，以及周边车辆和待定位车辆之间的角度差信息，朝向信息包括周边车辆在世界坐标系下的横摆角信息、周边车辆的俯仰角信息和周边车辆的横滚角信息；距离信息包括周边车辆与待定位车辆之间的横向距离信息，以及周边车辆与待定位车辆之间的纵向距离信息；车速信息包括周边车辆的车速信息和周边车辆的横摆角速度信息。应理解，周边车辆的标识信息可以是车牌号等唯一标识车辆的信息，本申请实施例不作限定。
S103，根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果。
其中，确定第一定位推算结果的设备可以是车载终端，也可以是服务器或者云端等设备，本申请实施例不作限定。
在步骤S103之前，本申请实施例提供的方法还可以包括，判断GPS定位协方差是否大于预设定位协方差阈值，若是，则执行根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果。
应理解，当GPS定位协方差大于预设定位协方差阈值时，表示此时车辆定位系统输出的定位结果与实际车辆位置不符，则开始执行S103所述的步骤。
参见图2，图2是本申请实施例提供的一种汽车定位的方法的场景示意图。如图2所示，车道上共行驶有四辆汽车，这四辆车均具有唯一标识信息，分别为A、B、C和D，车辆A为待定位车辆，车辆B、C和D与车辆A之间的距离均小于预设距离阈值；此外，这四辆车上均设置有V2X广播通信器，车辆A上还设置有车载摄像头、毫米波雷达传感器、车载GPS接收机和惯性测量单元IMU。在场景一中，由于建筑物遮挡等原因，A、B、C和D的GPS定位暂时丢失，此时，车辆A在GPS定位丢失之前，在步骤S102中获取到本车的初始定位信息和周边车辆B、C和D的车辆信息，当检测到GPS定位协方差大于预设定位协方差阈值时，即GPS定位丢失之后，开始执行S103所述的步骤；在场景二中，由于车辆A的传感器发生故障，车辆A的定位受到影响，此时，车辆A可以在步骤S102中获取到本车的初始定位信息和周边车辆B、C和D的车辆信息，当检测到GPS定位协方差大于预设定位协方差阈值时，即车辆传感器发生故障，定位受到影响之后，开始执行S103所述的步骤。
具体地，参见图3，图3为本申请实施例提供的一种确定第一定位推算结果的流程示意 图，如图3所示，S103的步骤包括：
S1031，根据周边车辆的车辆信息，建立车辆追踪表。
其中，车辆追踪表可以包括周边车辆的标识信息、车辆信息的获取时间、初始定位信息、车速信息、朝向信息、与待定位车辆之间的距离信息和第一定位推算结果。
应理解，周边车辆的标识信息可以通过待定位车辆的车载摄像头获取；周边车辆的车速信息和朝向信息可以通过待定位车辆的V2X广播通信器获取；周边车辆与待定位车辆之间的距离信息具体包括横向距离信息和纵向距离信息，可以通过待定位车辆的毫米波雷达、V2X广播通信器和车载摄像头获取，车载摄像头捕获到的图像数据可以判断周边车辆与待定位车辆之间的位置关系，如前、后、左、右等；周边车辆的初始定位信息和第一定位推算结果可以通过待定位车辆的车载终端、服务器或者云端等设备进行计算，本申请实施例不作限定。
S1032，根据车辆追踪表和待定位车辆的初始定位信息，通过初始定位推算算法得到周边车辆的初始定位信息。
在一个可选的实现方式中，周边车辆的初始定位信息可以是第一初始定位坐标(x i_t0,y i_t0,z i_t0,yaw i_t0,pitch i_t0,roll i_t0)，待定位车辆的初始定位信息可以是第二初始定位坐标(x t0,y t0,z t0,yaw t0,pitch t0,roll t0)，初始定位推算算法为：
x i_t0＝x t0+lx i_t0；
y i_t0＝y t0+ly i_t0；
z i_t0＝z t0；
yaw i_t0＝yaw t0+lyaw i_t0；
pitch i_t0＝pitch t0；
roll i_t0＝roll t0；
其中，x i_t0、y i_t0、z i_t0、yaw i_t0、pitch i_t0和roll i_t0分别表示序号为i的周边车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x t0、y t0、z t0、yaw t0、pitch t0和roll t0分别表示待定位车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t0和ly i_t0分别表示序号为i的周边车辆与待定位车辆在初始时刻t 0的横向距离信息和纵向距离信息，lyaw i_t0表示序号为i的周边车辆与待定位车辆在初始时刻t 0的角度差信息。
具体的，上述x、y、z可以是世界坐标系中的三维直角坐标，该直角坐标所在的大地直角坐标可以是以某一特定位置作为固定原点，比如待定位车辆开始执行步骤S103时所在的位置，以正北方向为x坐标轴方向，以正东方向为y坐标轴方向，以垂直向上方向为z坐标轴方向；上述x、y、z也可以表示车辆所在位置的纬度、经度和海拔高度。yaw为车辆车头围绕z坐标轴旋转的角度，pitch用于表示车辆车头与大地水平面之间的夹角，即车辆围绕y坐标轴旋转的角度，roll为车辆围绕x坐标轴旋转的角度。
S1033，根据周边车辆的初始定位信息和周边车辆的车辆信息，通过第一定位推算算法得到第一定位推算结果。
在一个可选的实现方式中，第一定位推算结果包括第一定位推算坐标(x i_t,y i_t,z i_t,yaw i_t,pitch i_t,roll i_t)，第一定位推算算法包括：
yaw i_t＝yaw i_t-Δt+yawrate i_t*Δt；
pitch i_t＝pitch i_t-Δt；
roll i_t＝roll i_t-Δt；
x i_t＝x i_t-Δt+v i_t*cosyaw i_t*Δt；
y i_t＝y i_t-Δt+v i_t*sinyaw i_t*Δt；
z i_t＝z i_t-Δt；
其中，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t-Δt、y i_t-Δt、z i_t-Δt、yaw i_t-Δt、pitch i_t-Δt和roll i_t-Δt分别表示序号为i的周边车辆在t-Δt时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横滚角信息、俯仰角信息和横滚角信息，yawrate i_t表示序号为i的周边车辆在t时刻的横摆角速度信息，Δt为预设时间间隔，v i_t表示序号为i的周边车辆在t时刻的车速信息。
应理解，周边车辆的横摆角速度信息和车速信息可以通过V2X广播通信器获取。
步骤S1031-步骤S1033，可以在获取到待定位车辆的初始定位信息的基础上，通过利用周边车辆的车辆信息，结合初始定位推算算法和第一定位推算算法，计算得到周边车辆的第一定位推算结果，作为计算待定位车辆定位结果的基础信息，可以解决在周边车辆GPS丢失的情况下，无法进行车辆定位的问题，进而提升定位系统的鲁棒性。
S104，根据第一定位推算结果，确定待定位车辆的第二定位推算结果。
具体地，参见图4，图4为本申请实施例提供的一种确定第二定位推算结果的流程示意图，如图4所示，S104的步骤包括：
S1041，获取周边车辆与待定位车辆之间的角度差信息、周边车辆与待定位车辆之间的横向距离信息，以及周边车辆与待定位车辆之间的纵向距离信息。
应理解，周边车辆与待定位车辆之间的角度差信息可以通过待定位车辆的毫米波雷达获取；周边车辆与待定位车辆之间的横向距离信息，以及周边车辆与待定位车辆之间的纵向距离信息可以通过待定位车辆的毫米波雷达和车载摄像机获取，其中，毫米波雷达用于测量周边车辆与待定位车辆之间的距离，车载摄像机用于捕获周边车辆与待定位车辆之间的位置关系。
S1042，结合第一定位推算结果，通过第二定位推算算法，得到第二定位推算结果。
在一个可选的实现方式中，第二定位推算结果包括第二定位推算坐标(x t,y t,z t,yaw t,pitch t,roll t)，第二定位推算算法包括：
x t＝x i_t-lx i_t；
y t＝y i_t-ly i_t；
z t＝z i_t；
yaw t＝yaw i_t-lyaw i_t；
pitch t＝pitch i_t；
roll t＝roll i_t；
其中，x t、y t、z t、yaw t、pitch t和roll t分别表示待定位车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t和ly i_t分别表示序号为i的周边车辆与待定位车辆在t时刻的横向距离信息和纵向距离信息,lyaw i_t表示所述序号为i的周边车辆与所述待定位车辆在t时刻的角度差信息。
应理解，在一个可选的实现方式种，当车辆处于上坡或下坡路段时，可以通过高精度地图获取更新后的z值和车辆俯仰角信息，本申请实施例不作限定。
应理解，在步骤S103中，通过第一定位推算算法，确定了周边车辆的第一定位推算结果，在此第一定位推算结果的基础上，结合周边车辆与待定位车辆之间的距离、位置关系，以及周边车辆与待定位车辆之间的角度差信息，可以通过第二定位推算算法反推出待定位车辆的位置，即第二定位推算结果。其中，周边车辆与待定位车辆之间的位置关系可以确定lx i_t和ly i_t 的正负；例如，在x坐标轴方向上，当周边车辆在待定位车辆的正方向时，lx i_t取正数，反之当周边车辆在待定位车辆的负方向时，lx i_t取负数；在y坐标轴方向上，当周边车辆在待定位车辆的正方向时，ly i_t取正数，反之当周边车辆在待定位车辆的负方向时，ly i_t取负数。
进一步地，当周边车辆的数量N大于1时，周边车辆中的N台车辆对应N个第一定位推算结果，在步骤S1042之后，上述方法包括：根据N个第一定位推算结果分别确定待定位车辆对应的N个第二定位推算结果，计算N个第二定位推算结果的定位结果均值，将定位结果均值作为待定位车辆最终的第二定位推算结果。
实施例二：
参见图5，图5是本申请实施例提供的另一种汽车定位的方法的流程示意图。如图5所示，和实施例一相比，步骤S501-步骤S504与实施例一种的步骤S101-S104相同，在步骤S504之后，实施例二所述的方法还包括：
S505，获取GPS定位结果和惯性测量单元IMU推算结果。
S506，根据GPS定位结果和IMU推算结果，结合第二定位推算结果，通过扩展卡尔曼滤波器，确定待定位车辆的最终定位结果。
应理解，根据实施例一所述的方法计算得到的第二定位推算结果，可以作为待定位车辆的定位结果；也可以作为IMU的定位约束，通过扩展卡尔曼滤波器EKF，对GPS定位结果、IMU推算结果和第二定位推算结果进行定位结果融合，得到待定位车辆的最终定位结果。
在一个可选的实现方式中，EKF在经过车辆定位信息初始化后，开始进行定位信息预测和定位信息观测的迭代，最终获得待定位车辆的最终定位结果。其中，定位信息观测可以用于对定位信息预测的结果进行加权修正，得到定位结果的准确性。
下面结合附图介绍本申请实施例涉及的装置。
参见图6，图6是本申请实施例提供的一种汽车定位的装置的组成示意图。如图6所示，本申请实施例提供的汽车定位的装置600可以包括：
定位协方差获取模块601，用于获取待定位车辆的全球定位系统GPS定位协方差；
车辆信息获取模块602，用于当GPS定位协方差小于等于预设定位协方差阈值时，获取待定位车辆的初始定位信息和周边车辆的车辆信息，周边车辆为与待定位车辆距离小于预设距离阈值的车辆，车辆信息包括距离信息和车速信息；
第一定位推算模块603，用于根据待定位车辆的初始定位信息和周边车辆的车辆信息，确定周边车辆的第一定位推算结果；
第二定位推算模块604，用于根据第一定位推算结果，确定待定位车辆的第二定位推算结果。
其中，定位协方差获取模块601和车辆信息获取模块602的具体功能实现方式可以参见图1对应的实施例一中的步骤S101-S102，这里不再进行赘述。
进一步地，第一定位推算模块603包括：
定位协方差判断单元6031，用于判断GPS定位协方差是否大于预设定位协方差阈值，若是，则执行实施例一中的步骤S103。
车辆追踪表建立单元6032，用于根据周边车辆的车辆信息，建立车辆追踪表；
初始定位计算单元6033，用于根据车辆追踪表和待定位车辆的初始定位信息，通过初始定位推算算法得到周边车辆的初始定位信息；
第一定位推算单元6034，用于根据周边车辆的初始定位信息和周边车辆的车辆信息，通过第一定位推算算法得到第一定位推算结果。
其中，第一定位推算模块603的具体功能实现方式可以参见图1对应的实施例一中的步骤S103，这里不再进行赘述。
进一步地，第二定位推算模块604包括：
信息获取单元6041，用于获取周边车辆与待定位车辆之间的角度差信息、周边车辆与待定位车辆之间的横向距离信息，以及周边车辆与待定位车辆之间的纵向距离信息；
第二定位推算单元6042，用于结合第一定位推算结果，通过第二定位推算算法，得到第二定位推算结果；
定位结果均值计算单元6043，用于根据N个第一定位推算结果分别确定待定位车辆对应的N个第二定位推算结果，计算N个第二定位推算结果的定位结果均值，将定位结果均值作为待定位车辆最终的第二定位推算结果。
其中，第二定位推算模块604的具体功能实现方式可以参见图1对应的实施例一中的步骤S104，这里不再进行赘述。
参见图7，图7是本申请实施例提供的另一种汽车定位的装置的组成示意图。如图7所示，与装置600相比，模块701-704与装置600中的模块601-604相同，除此之外，装置700还可以包括：
定位结果获取模块705，用于获取GPS定位结果和惯性测量单元IMU推算结果；
定位结果融合模块706，用于根据所述GPS定位结果和所述IMU推算结果，结合所述第二定位推算结果，通过扩展卡尔曼滤波器，确定所述待定位车辆的最终定位结果。
其中，定位结果获取模块705和定位结果融合模块706的具体功能实现方式可以参见图5对应的实施例二中的步骤S505-S506，这里不再进行赘述。
参见图8，图8是本申请实施例提供的一种汽车定位的装置的组成示意图。图8所示的汽车定位的装置800(该装置800具体可以是一种计算机设备)包括存储器801、处理器802、通信接口803以及总线804。其中，存储器801、处理器802、通信接口803通过总线804实现彼此之间的通信连接。
存储器801可以是只读存储器(Read Only Memory，ROM)，静态存储设备，动态存储设备或者随机存取存储器(Random Access Memory，RAM)。存储器801可以存储程序，当存储器801中存储的程序被处理器802执行时，处理器802和通信接口803用于执行本申请实施例提供的汽车定位的方法的各个步骤。
处理器802可以采用通用的中央处理器(Central Processing Unit，CPU)，微处理器，应用专用集成电路(Application Specific Integrated Circuit，ASIC)，图形处理器(graphics processing unit，GPU)或者一个或多个集成电路，用于执行相关程序，以实现本申请实施例的汽车定位的装置中的单元所需执行的功能，或者执行本申请方法实施例的汽车定位的方法。
处理器802还可以是一种集成电路芯片，具有信号的处理能力。在实现过程中，本申请的汽车定位的方法的各个步骤可以通过处理器802中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器802还可以是通用处理器、数字信号处理器(Digital Signal Processing，DSP)、专用集成电路(ASIC)、现成可编程门阵列(Field Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或 者执行本申请实施例中的公开的各方法、步骤及逻辑框图。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。结合本申请实施例所公开的方法的步骤可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器801，处理器802读取存储器801中的信息，结合其硬件完成本申请实施例的汽车定位的装置中包括的单元所需执行的功能，或者执行本申请方法实施例的汽车定位的方法。
通信接口803使用例如但不限于收发器一类的收发装置，来实现装置800与其他设备或通信网络之间的通信。
总线804可包括在装置800各个部件(例如，存储器801、处理器802、通信接口803)之间传送信息的通路。
上述各个功能器件的具体实现可以参见上述实施例中相关描述，本申请实施例不再赘述。
作为本实施例的另一种形式，提供一种计算机可读存储介质，其上存储有指令，该指令被执行时执行上述方法实施例中的方法。
本领域技术人员可以理解，为了便于说明，图8中仅示出了一个存储器和处理器。在实际的控制器中，可以存在多个处理器和存储器。存储器也可以称为存储介质或者存储设备等，本申请实施例对此不做限制。
应理解，在本申请实施例中，处理器可以是中央处理单元(Central Processing Unit，简称CPU)，该处理器还可以是其他通用处理器、数字信号处理器(Digital Signal Processing，简称DSP)、专用集成电路(Application Specific Integrated Circuit，简称ASIC)、现成可编程门阵列(Field－Programmable Gate Array，简称FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。
还应理解，本申请实施例中提及的存储器可以是易失性存储器或非易失性存储器，或可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(Read-Only Memory，简称ROM)、可编程只读存储器(Programmable ROM，简称PROM)、可擦除可编程只读存储器(Erasable PROM，简称EPROM)、电可擦除可编程只读存储器(Electrically EPROM，简称EEPROM)或闪存。易失性存储器可以是随机存取存储器(Random Access Memory，简称RAM)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的RAM可用，例如静态随机存取存储器(Static RAM，简称SRAM)、动态随机存取存储器(Dynamic RAM，简称DRAM)、同步动态随机存取存储器(Synchronous DRAM，简称SDRAM)、双倍数据速率同步动态随机存取存储器(Double Data Rate SDRAM，简称DDR SDRAM)、增强型同步动态随机存取存储器(Enhanced SDRAM，简称ESDRAM)、同步连接动态随机存取存储器(Synchlink DRAM，简称SLDRAM)和直接内存总线随机存取存储器(Direct Rambus RAM，简称DR RAM)。
需要说明的是，当处理器为通用处理器、DSP、ASIC、FPGA或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件时，存储器(存储模块)集成在处理器中。
应注意，本文描述的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
该总线除包括数据总线之外，还可以包括电源总线、控制总线和状态信号总线等。但是为了清楚说明起见，在图中将各种总线都标为总线。
还应理解，本文中涉及的第一、第二、第三、第四以及各种数字编号仅为描述方便进行的区分，并不用来限制本申请的范围。
应理解，本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三 种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
在实现过程中，上述方法的各步骤可以通过处理器中的硬件的集成逻辑电路或者软件形式的指令完成。结合本申请实施例所公开的方法的步骤可以直接体现为硬件处理器执行完成，或者用处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器，处理器读取存储器中的信息，结合其硬件完成上述方法的步骤。为避免重复，这里不再详细描述。
在本申请的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各种说明性逻辑块(illustrative logical block，简称ILB)和步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
在本申请所提供的几个实施例中，应该理解到，所揭露的方法和装置，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
在上述实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。所述计算机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所述计算机程序指令时，全部或部分地产生按照本申请实施例所述的流程或功能。所述计算机可以是通用计算机、专用计算机、计算机网络、或者其他可编程装置。所述计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，所述计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线)或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质，(例如，软盘、硬盘、磁带)、光介质(例如，DVD)、或者半导体介质(例如固态硬盘)等。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。

Claims (22)

  1. 一种汽车定位的方法，其特征在于，包括：
    获取待定位车辆的全球定位系统GPS定位协方差；
    当所述GPS定位协方差小于等于预设定位协方差阈值时，获取所述待定位车辆的初始定位信息和周边车辆的车辆信息，所述周边车辆为与所述待定位车辆距离小于预设距离阈值的车辆，所述车辆信息包括距离信息和车速信息；
    根据所述待定位车辆的初始定位信息和所述周边车辆的车辆信息，确定所述周边车辆的第一定位推算结果；
    根据所述第一定位推算结果，确定所述待定位车辆的第二定位推算结果。
  2. 根据权利要求1所述的方法，其特征在于，所述周边车辆的车辆信息还包括所述周边车辆的标识信息、所述周边车辆的朝向信息，以及所述周边车辆和所述待定位车辆之间的角度差信息，所述朝向信息包括所述周边车辆的横摆角信息、所述周边车辆的俯仰角信息和所述周边车辆的横滚角信息；
    所述距离信息包括所述周边车辆与所述待定位车辆之间的横向距离信息，以及所述周边车辆与所述待定位车辆之间的纵向距离信息；
    所述车速信息包括所述周边车辆的车速信息和所述周边车辆的横摆角速度信息。
  3. 根据权利要求2所述的方法，其特征在于，所述根据所述待定位车辆的初始定位信息和所述周边车辆的车辆信息，确定所述周边车辆的第一定位推算结果，包括：
    根据所述周边车辆的车辆信息，建立车辆追踪表；
    根据所述车辆追踪表和所述待定位车辆的初始定位信息，通过初始定位推算算法得到所述周边车辆的初始定位信息；
    根据所述周边车辆的初始定位信息和所述周边车辆的车辆信息，通过第一定位推算算法得到所述第一定位推算结果。
  4. 根据权利要求3所述的方法，其特征在于，所述周边车辆的初始定位信息包括第一初始定位坐标(x i_t0,y i_t0,z i_t0,yaw i_t0,pitch i_t0,roll i_t0)，所述待定位车辆的初始定位信息包括第二初始定位坐标(x t0,y t0,z t0,yaw t0,pitch t0,roll t0)，所述初始定位推算算法包括：
    x i_t0＝x t0+lx i_t0；
    y i_t0＝y t0+ly i_t0；
    z i_t0＝z t0；
    yaw i_t0＝yaw t0+lyaw i_t0；
    pitch i_t0＝pitch t0；
    roll i_t0＝roll t0；
    其中，x i_t0、y i_t0、z i_t0、yaw i_t0、pitch i_t0和roll i_t0分别表示序号为i的周边车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x t0、y t0、z t0、yaw t0、pitch t0和roll t0分别表示所述待定位车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t0和ly i_t0分别表示所述序号为i的周边车辆与所述待定位车辆在初始时刻t 0的横向距离信息和纵向距离信息，lyaw i_t0表示所述序号为i的周边车辆与所述待定位车辆在初始时刻t 0的角度差信息。
  5. 根据权利要求3或4任一项所述的方法，其特征在于，所述第一定位推算结果包括第一定位推算坐标(x i_t,y i_t,z i_t,yaw i_t,pitch i_t,roll i_t)，所述第一定位推算算法包括：
    yaw i_t＝yaw i_t-Δt+yawrate i_t*Δt；
    pitch i_t＝pitch i_t-Δt；
    roll i_t＝roll i_t-Δt；
    x i_t＝x i_t-Δt+v i_t*cos yaw i_t*Δt；
    y i_t＝y i_t-Δt+v i_t*sin yaw i_t*Δt；
    z i_t＝z i_t-Δt；
    其中，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示所述序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t-Δt、y i_t-Δt、z i_t-Δt、yaw i_t-Δt、pitch i_t-Δt和roll i_t-Δt分别表示所述序号为i的周边车辆在t-Δt时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横滚角信息、俯仰角信息和横滚角信息，yawrate i_t表示所述序号为i的周边车辆在t时刻的横摆角速度信息，Δt为预设时间间隔，v i_t表示所述序号为i的周边车辆在t时刻的车速信息。
  6. 根据权利要求1-5任一项所述的方法，其特征在于，所述根据所述第一定位推算结果，确定所述待定位车辆的第二定位推算结果，包括：
    获取所述周边车辆与所述待定位车辆之间的角度差信息、所述周边车辆与所述待定位车辆之间的横向距离信息，以及所述周边车辆与所述待定位车辆之间的纵向距离信息；
    结合所述第一定位推算结果，通过第二定位推算算法，得到所述第二定位推算结果。
  7. 根据权利要求6所述的方法，其特征在于，所述第二定位推算结果包括第二定位推算坐标(x t,y t,z t,yaw t,pitch t,roll t)，所述第二定位推算算法包括：
    x t＝x i_t-lx i_t；
    y t＝y i_t-ly i_t；
    z t＝z i_t；
    yaw t＝yaw i_t-lyaw i_t；
    pitch t＝pitch i_t；
    roll t＝roll i_t；
    其中，x t、y t、z t、yaw t、pitch t和roll t分别表示所述待定位车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示所述序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t和ly i_t分别表示所述序号为i的周边车辆与所述待定位车辆在t时刻的横向距离信息和纵向距离信息,lyaw i_t表示所述序号为i的周边车辆与所述待定位车辆在t时刻的角度差信息。
  8. 根据权利要求1-7任一项所述的方法，其特征在于，在根据所述待定位车辆的初始定位信息和所述周边车辆的车辆信息，确定所述周边车辆的第一定位推算结果之前，所述方法还包括：
    判断所述GPS定位协方差是否大于所述预设定位协方差阈值，若是，则执行所述根据所述待定位车辆的初始定位信息和所述周边车辆的车辆信息，确定所述周边车辆的第一定位推算结果。
  9. 根据权利要求1-8任一项所述的方法，其特征在于，当所述周边车辆的数量N大于1时，所述周边车辆中的N台车辆对应N个第一定位推算结果，所述根据所述第一定位推算结果，确定所述待定位车辆的第二定位推算结果，包括：
    根据所述N个第一定位推算结果分别确定所述待定位车辆对应的N个第二定位推算结果，计算所述N个第二定位推算结果的定位结果均值，将所述定位结果均值作为所述待定位车辆最终的第二定位推算结果。
  10. 根据权利要求1-9任一项所述的方法，其特征在于，所述方法还包括：
    获取GPS定位结果和惯性测量单元IMU推算结果；
    根据所述GPS定位结果和所述IMU推算结果，结合所述第二定位推算结果，通过扩展卡尔曼滤波器，确定所述待定位车辆的最终定位结果。
  11. 一种汽车定位的装置，其特征在于，包括：
    定位协方差获取模块，用于获取待定位车辆的全球定位系统GPS定位协方差；
    车辆信息获取模块，用于当所述GPS定位协方差小于等于预设定位协方差阈值时，获取所述待定位车辆的初始定位信息和周边车辆的车辆信息，所述周边车辆为与所述待定位车辆距离小于预设距离阈值的车辆，所述车辆信息包括距离信息和车速信息；
    第一定位推算模块，用于根据所述待定位车辆的初始定位信息和所述周边车辆的车辆信息，确定所述周边车辆的第一定位推算结果；
    第二定位推算模块，用于根据所述第一定位推算结果，确定所述待定位车辆的第二定位推算结果。
  12. 根据权利要求11所述的方法，其特征在于，所述周边车辆的车辆信息还包括所述周边车辆的标识信息、所述周边车辆的朝向信息，以及所述周边车辆和所述待定位车辆之间的角度差信息，所述朝向信息包括所述周边车辆的横摆角信息、所述周边车辆的俯仰角信息和所述周边车辆的横滚角信息；
    所述距离信息包括所述周边车辆与所述待定位车辆之间的横向距离信息和所述周边车辆与所述待定位车辆之间的纵向距离信息；
    所述车速信息包括所述周边车辆的车速信息和所述周边车辆的横摆角速度信息。
  13. 根据权利要求12所述的装置，其特征在于，所述第一定位推算模块包括：
    车辆追踪表建立单元，用于根据所述周边车辆的车辆信息，建立车辆追踪表；
    初始定位计算单元，用于根据所述车辆追踪表和所述待定位车辆的初始定位信息，通过初始定位推算算法得到所述周边车辆的初始定位信息；
    第一定位推算单元，用于根据所述周边车辆的初始定位信息和所述周边车辆的车辆信息，通过第一定位推算算法得到所述第一定位推算结果。
  14. 根据权利要求13所述的装置，其特征在于，所述周边车辆的初始定位信息包括第一初始定位坐标(x i_t0,y i_t0,z i_t0,yaw i_t0,pitch i_t0,roll i_t0)，所述待定位车辆的初始定位信息包括第二初始定位坐标(x t0,y t0,z t0,yaw t0,pitch t0,roll t0)，所述初始定位推算算法包括：
    x i_t0＝x t0+lx i_t0；
    y i_t0＝y t0+ly i_t0；
    z i_t0＝z t0；
    yaw i_t0＝yaw t0+lyaw i_t0；
    pitch i_t0＝pitch t0；
    roll i_t0＝roll t0；
    其中，x i_t0、y i_t0、z i_t0、yaw i_t0、pitch i_t0和roll i_t0分别表示序号为i的周边车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x t0、y t0、z t0、yaw t0、pitch t0和roll t0分别表示所述待定位车辆在初始时刻t 0在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t0和ly i_t0分别表示所述序号为i的周边车辆与所述待定位车辆在初始时刻t 0的横向距离信息和纵向距离信息，lyaw i_t0表示所述序号为i的周边车辆与所述待定位车辆在初始时刻t 0的角度差信息。
  15. 根据权利要求13或14任一项所述的装置，其特征在于，所述第一定位推算结果包括第一定位推算坐标(x i_t,y i_t,z i_t,yaw i_t,pitch i_t,roll i_t)，所述第一定位推算算法包括：
    yaw i_t＝yaw i_t-Δt+yawrate i_t*Δt；
    pitch i_t＝pitch i_t-Δt；
    roll i_t＝roll i_t-Δt；
    x i_t＝x i_t-Δt+v i_t*cos yaw i_t*Δt；
    y i_t＝y i_t-Δt+v i_t*sin yaw i_t*Δt；
    z i_t＝z i_t-Δt；
    其中，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示所述序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t-Δt、y i_t-Δt、z i_t-Δt、yaw i_t-Δt、pitch i_t-Δt和roll i_t-Δt分别表示所述序号为i的周边车辆在t-Δt时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横滚角信息、俯仰角信息和横滚角信息，yawrate i_t表示所述序号为i的周边车辆在t时刻的横摆角速度信息，Δt为预设时间间隔，v i_t表示所述序号为i的周边车辆在t时刻的车速信息。
  16. 根据权利要求11-15任一项所述的装置，其特征在于，所述第二定位推算模块包括：
    信息获取单元，用于获取所述周边车辆与所述待定位车辆之间的角度差信息、所述周边车辆与所述待定位车辆之间的横向距离信息，以及所述周边车辆与所述待定位车辆之间的纵向距离信息；
    第二定位推算单元，用于结合所述第一定位推算结果，通过第二定位推算算法，得到所述第二定位推算结果。
  17. 根据权利要求16所述的装置，其特征在于，所述第二定位推算结果包括第二定位推算坐标(x t,y t,z t,yaw t,pitch t,roll t)，所述第二定位推算算法包括：
    x t＝x i_t-lx i_t；
    y t＝y i_t-ly i_t；
    z t＝z i_t；
    yaw t＝yaw i_t-lyaw i_t；
    pitch t＝pitch i_t；
    roll t＝roll i_t；
    其中，x t、y t、z t、yaw t、pitch t和roll t分别表示所述待定位车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，x i_t、y i_t、z i_t、yaw i_t、pitch i_t和roll i_t分别表示所述序号为i的周边车辆在t时刻在预设x坐标轴方向上的坐标信息、在预设y坐标轴方向上的坐标信息、在预设z坐标轴方向上的坐标信息、横摆角信息、俯仰角信息和横滚角信息，lx i_t和ly i_t分别表示所述序号为i的周边车辆与所述待定位车辆在t时刻的横向距离信息和纵向距离信息,lyaw i_t表示所述序号为i的周边车辆与所述待定位车辆在t时刻的角度差信息。
  18. 根据权利要求11-17任一项所述的装置，其特征在于，所述第一定位推算模块还包括：
    定位协方差判断单元，用于判断所述GPS定位协方差是否大于预设定位协方差阈值，若是，则执行所述根据所述待定位车辆的初始定位信息和所述周边车辆的车辆信息，确定所述周边车辆的第一定位推算结果。
  19. 根据权利要求11-18任一项所述的装置，其特征在于，当所述周边车辆的数量N大于1时，所述周边车辆中的N台车辆对应N个第一定位推算结果，所述第二定位推算模块包括：
    定位结果均值计算单元，用于根据所述N个第一定位推算结果分别确定所述待定位车辆对应的N个第二定位推算结果，计算所述N个第二定位推算结果的定位结果均值，将所述定位结果均值作为所述待定位车辆最终的第二定位推算结果。
  20. 根据权利要求11-19任一项所述的装置，其特征在于，所述装置还包括：
    定位结果获取模块，用于获取GPS定位结果和惯性测量单元IMU推算结果；
    定位结果融合模块，用于根据所述GPS定位结果和所述IMU推算结果，结合所述第二定位推算结果，通过扩展卡尔曼滤波器，确定所述待定位车辆的最终定位结果。
  21. 一种汽车定位的装置，其特征在于，包括存储器和处理器，所述存储器用于存储计算机程序，所述处理器用于调用所述计算机程序，以执行如权利要求1-10任一项所述的方法。
  22. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有计算机程序，所述计算机程序包括程序指令，当所述程序指令被处理器执行时，执行如权利要求1-10任一项所述的方法。
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