Vehicle positioning method

Abstract

The application discloses a vehicle positioning method, which comprises the following steps: judging the stability of a current satellite positioning signal; determining a vehicle position based on the current satellite positioning signal as a target position in the case that the current satellite positioning signal is located in a signal stable area, wherein the target position is a final required current geographical position of a host vehicle; selecting a target positioning point from a preset driving distance range of a latest driving in the case that the current satellite positioning signal is located in a signal unstable area or a signal free area; determining an initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm; determining an algorithm positioning error of the corresponding initial position according to an error curve of each target positioning algorithm and a target driving distance; and selecting the initial position with the minimum algorithm positioning error as the target position. The application can improve the positioning accuracy of the vehicle.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automobiles, in particular to a vehicle positioning method. BACKGROUND

[0002] With the rapid development of the national economy and the gradual improvement of people's living standards, the number of vehicles is increasing, and intelligent driving technology is becoming more and more abundant. Vehicle positioning is an important part of the field of intelligent driving. In order to realize vehicle positioning, the commonly used positioning method at present is RTK (Real-time kinematic, real-time dynamic) differential positioning. RTK differential positioning is a differential method for real-time processing of carrier phase observations of two measurement stations. The carrier phase collected by the reference station is sent to the user receiver for difference calculation of coordinates. This is a new commonly used satellite positioning measurement method. Previous static, fast static and dynamic measurements all need to be calculated after the event to obtain centimeter-level accuracy. RTK is a measurement method that can obtain centimeter-level positioning accuracy in the field in real time. It uses a carrier phase dynamic real-time differential method and is a major milestone in the application of GPS (Global Positioning System, Global Positioning System). Its appearance brings new measurement principles and methods to engineering lofting, topographic mapping and various control measurements, greatly improving work efficiency.

[0003] However, when the vehicle drives to a special scene such as an overpass or a tunnel, the satellite positioning signal will be very unstable, and even completely no signal, thereby causing the problem of low positioning accuracy or being unable to position. SUMMARY

[0004] The present application provides a vehicle positioning method, which can solve the problem of low positioning accuracy or being unable to position caused by unstable or no satellite positioning signal in the related art.

[0005] The specific technical solutions are as follows:

[0006] The present application provides a vehicle positioning method, which comprises:

[0007] judging the stability of the current satellite positioning signal;

[0008] In the case that the current satellite positioning signal is located in a signal stable area, the vehicle position positioned based on the current satellite positioning signal is determined as a target position, wherein the target position is the final required current geographical position of the ego vehicle.

[0009] In a case that the current satellite positioning signal is located in a signal unstable area or a signal free area, a target positioning point is selected from a preset driving distance range of a latest driving, an initial position corresponding to each target positioning algorithm is determined based on the target positioning point and each target positioning algorithm, an algorithm positioning error of the corresponding initial position is determined according to an error curve corresponding to each target positioning algorithm and a target driving distance, and the initial position with the minimum algorithm positioning error is selected as the target position,

[0010] The target positioning algorithm is a non-satellite positioning algorithm, the error curve is a curve about a mapping relationship between a driving distance and an algorithm positioning error generated in a positioning process in a signal stable area, and the target driving distance is a driving distance of the ego vehicle from a starting time corresponding to the target positioning point to a to-be-positioned time.

[0011] In an embodiment, judging the stability of the current satellite positioning signal includes:

[0012] In a case that a number of satellite searchings in N positioning periods is greater than a preset satellite searching threshold, and all satellite positioning errors are less than a first positioning error threshold, it is determined that the current satellite positioning signal is located in a signal stable area, where N≧2.

[0013] In a case that the number of satellite searchings in the N positioning periods is less than the preset satellite searching threshold, or the number of satellite searchings in at least N-1 positioning periods in the N positioning periods is greater than the preset satellite searching threshold and satellite positioning errors of at least two positioning periods are greater than the first preset positioning error threshold, it is determined that the current satellite positioning signal is located in a signal unstable area, where 2≦M≦N-2.

[0014] In a case that the number of satellite searchings in at least N-1 positioning periods in the N positioning periods is less than the preset satellite searching threshold, or all satellite positioning errors are greater than the first positioning error threshold, it is determined that the current satellite positioning signal is located in a signal free area.

[0015] In an embodiment, the target positioning algorithm includes at least one of an inertial navigation positioning algorithm, a wheel rotation number positioning algorithm, a high-precision map positioning algorithm, and a lane matching positioning algorithm.

[0016] When the target positioning algorithm comprises the inertial navigation positioning algorithm, determining the initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm comprises: calculating a self-vehicle driving track according to the target positioning point and target inertial navigation information, and taking a track point corresponding to a to-be-positioned time in the self-vehicle driving track as the initial position corresponding to the inertial navigation positioning algorithm, wherein the target inertial navigation information comprises inertial navigation information in a self-vehicle driving process from a starting time corresponding to the target positioning point to the to-be-positioned time.

[0017] When the target positioning algorithm comprises the wheel rotation number positioning algorithm, determining the initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm comprises: calculating the target driving distance based on a wheel average radius and a target wheel rotation number, and determining a position in the self-vehicle driving track at a distance of the target driving distance from the target positioning point as the initial position corresponding to the wheel rotation number positioning algorithm, wherein the target wheel rotation number is a wheel rotation number of the self-vehicle from a starting time corresponding to the target positioning point to a to-be-positioned time.

[0018] When the target positioning algorithm comprises the high-precision map positioning algorithm, determining the initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm comprises: determining a target road currently located by the self-vehicle according to a preset road recognition algorithm, obtaining a preset center line on the target road in a high-precision map, and determining a position on the preset center line at the target driving distance from the target positioning point according to the self-vehicle driving track as the initial position corresponding to the high-precision map positioning algorithm, wherein the preset center line comprises a road center line of the target road and / or a lane center line of the target road.

[0019] When the target positioning algorithm comprises the lane matching positioning algorithm, determining the initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm comprises: determining a target lane currently located by the self-vehicle according to a preset lane recognition algorithm, when the preset center line only comprises the road center line of the target road, determining a position obtained by translating the initial position corresponding to the high-precision map positioning algorithm to a lane center line of the target lane as the initial position corresponding to the lane matching positioning algorithm, or when the preset center line comprises the lane center line of the target road, determining the initial position on the lane center line of the target lane corresponding to the high-precision map positioning algorithm as the initial position corresponding to the lane matching positioning algorithm.

[0020] In an embodiment, the target inertial navigation information comprises at least one of a driving distance in a driving process from the target positioning point as a starting position, an inertial measurement unit (IMU) gyro inertial navigation angle, a vehicle speed, and a driving time length from the target positioning point.

[0021] The calculating the ego vehicle driving trajectory according to the target positioning point and the target inertial navigation information comprises:

[0022] The calculating the ego vehicle driving trajectory according to the first formula or the second formula;

[0023] The first formula is

[0024]

[0025] The P is t (x, y) is the position coordinates of the trajectory point when the driving time length is t, the P1(x, y) is the position coordinates of the target positioning point, and the δD is the difference between the driving distance in the kth driving distance statistical period and the driving distance in the nth driving distance statistical period. k The kth driving distance statistical period, the n is the nth driving distance statistical period, and the δθ is the difference between the IMU gyro inertial navigation angle at the end time and the IMU gyro inertial navigation angle at the start time in the kth driving distance statistical period.

[0026] The second formula is

[0027] The P t (x, y) = P1(x, y) + ∫∫v(x, y, t)dθdt

[0028] The v(x, y, t) is the vehicle speed when the driving time length is t, and the θ is the IMU gyro inertial navigation angle.

[0029] In an embodiment, before the calculating the target driving distance based on the average wheel radius and the target wheel rotation number, the method further comprises:

[0030] In the current average wheel radius correction period, when the ego vehicle is driving in the signal stable area, two positioning points satisfying the preset distance requirement and having a satellite positioning error less than a second positioning error threshold are acquired.

[0031] The average wheel radius is calculated according to the distance between the two positioning points, the driving time length between the two positioning points, and the wheel rotation speed.

[0032] In an embodiment, the target positioning point comprises at least one of a positioning point calculated based on a satellite positioning signal, a positioning point calculated based on a roadside device assisted positioning algorithm, and a positioning point calculated based on an other vehicle assisted positioning algorithm.

[0033] In an embodiment, when the target positioning point comprises a positioning point calculated by a roadside device-based auxiliary positioning algorithm, before selecting the target positioning point within a preset driving distance range from the latest driving, the method further comprises: calculating the position coordinates of the target positioning point based on the roadside device-based auxiliary positioning algorithm;

[0034] The calculating of the position coordinates of the target positioning point based on the roadside device-based auxiliary positioning algorithm comprises:

[0035] receiving a regional high-precision map and regional high-precision auxiliary positioning data within the range of the regional high-precision map sent by the roadside device, wherein the regional high-precision auxiliary positioning data comprises at least one auxiliary positioning subzone, the auxiliary positioning subzone comprises external feature information of an auxiliary positioning reference object with unique identifiable features, a lane reference point for perceiving a relative position relationship with the auxiliary positioning reference object, and a relative position relationship between the auxiliary positioning reference object and the lane reference point;

[0036] In the process of driving based on the regional high-precision map, if it is determined that the ego vehicle enters an auxiliary positioning subzone, it is judged whether a target auxiliary positioning reference object is detected according to the external feature information, the lane reference point, and the relative position relationship, wherein the target auxiliary positioning reference object is an auxiliary positioning reference object in the auxiliary positioning subzone where the ego vehicle is currently located;

[0037] In the case where it is determined that the target auxiliary positioning reference object is detected, a body coordinate system is converted into a north-south positive coordinate system with the target auxiliary positioning reference object as the origin, wherein the horizontal axis positive direction of the north-south positive coordinate system is the positive east direction, and the vertical axis positive direction is the positive north direction;

[0038] According to the relative position relationship between the ego vehicle and the target auxiliary positioning reference object and the mapping relationship between the north-south positive coordinate system and the geographic coordinate system, the position coordinates of the target positioning point are determined.

[0039] In an embodiment, when the target positioning point comprises a positioning point calculated by an auxiliary positioning algorithm based on other vehicles, before selecting the target positioning point within a preset driving distance range from the latest driving, the method further comprises: calculating the position coordinates of the target positioning point based on the auxiliary positioning algorithm based on other vehicles;

[0040] The calculating of the position coordinates of the target positioning point based on the auxiliary positioning algorithm based on other vehicles comprises:

[0041] detecting relative position information between the ego vehicle and a target neighboring vehicle, and obtaining positioning information of the target neighboring vehicle based on vehicle-to-everything (V2X) technology, wherein the positioning information comprises a neighboring vehicle positioning position and a neighboring vehicle positioning error;

[0042] In a case that the adjacent vehicle positioning error is less than a third positioning error threshold, a position coordinate of the target positioning point is calculated according to the relative position information and the adjacent vehicle positioning position.

[0043] In an embodiment, the relative position information comprises a position coordinate of the target adjacent vehicle, a distance between the ego vehicle and the target adjacent vehicle, and an included angle between a line connecting the ego vehicle and the target adjacent vehicle and a road direction.

[0044] The calculating of the position coordinate of the target positioning point according to the relative position information and the adjacent vehicle positioning position comprises:

[0045] The position coordinate P of the target positioning point is calculated according to a third formula A (x,y), wherein the third formula is P A (x,y) = P B (x,y) - (L cos α, L sin α), P B (x,y) is the position coordinate of the target adjacent vehicle, the L is the distance between the ego vehicle and the target adjacent vehicle, and the α is the included angle.

[0046] In an embodiment, before the algorithm positioning error of each initial position is determined according to the error curve corresponding to each target positioning algorithm and the target driving distance, the method further comprises: generating the error curve corresponding to each target positioning algorithm.

[0047] The generating of the error curve corresponding to each target positioning algorithm comprises:

[0048] When the ego vehicle is driving in the signal stable area, a plurality of driving distance subranges are obtained from a preset driving distance range of historical driving;

[0049] In each driving distance sub-range, a positioning point with a satellite positioning error less than a fourth positioning error threshold is selected as a starting position;

[0050] A positioning position of the ego vehicle corresponding to each starting position is calculated according to each starting position and a target positioning algorithm respectively, wherein the positioning position of the ego vehicle is a positioning position at a latest time corresponding to the preset driving distance range of historical driving;

[0051] An algorithm positioning error between each positioning position of the ego vehicle and a true position is calculated respectively, wherein the true position is a position where a positioning point with a satellite positioning error less than a fourth positioning error threshold is located in a preset driving distance range of historical driving;

[0052] A driving distance of each starting position of the ego vehicle corresponding to a starting time to the latest time is determined.

[0053] The error curve corresponding to the target positioning algorithm is generated according to a mapping relationship between an algorithm positioning error and a driving distance.

[0054] In a second aspect, the embodiments of the present application provide a vehicle positioning device, which comprises:

[0055] A judging unit is configured to judge stability of a current satellite positioning signal.

[0056] A first determining unit is configured to determine a vehicle position positioned based on the current satellite positioning signal as a target position in a case that the current satellite positioning signal is located in a signal stable area, wherein the target position is a final required current geographical position of the ego vehicle.

[0057] A selecting unit is configured to select a target positioning point from a preset driving distance range of a latest driving in a case that the current satellite positioning signal is located in a signal unstable area or a signal free area.

[0058] A second determining unit is configured to determine an initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm, wherein the target positioning algorithm is a non-satellite positioning algorithm.

[0059] A third determining unit is configured to determine an algorithm positioning error of the corresponding initial position according to an error curve corresponding to each target positioning algorithm and a target driving distance, wherein the error curve is an error curve about a mapping relationship between a driving distance and an algorithm positioning error generated in a positioning process in the signal stable area, and the target driving distance is a driving distance of the ego vehicle from a starting time corresponding to the target positioning point to a to-be-positioned time.

[0060] A selecting unit is configured to select the initial position with the minimum algorithm positioning error as the target position.

[0061] In an embodiment, the judging unit comprises:

[0062] A first determining module is configured to determine that the current satellite positioning signal is located in the signal stable area in a case that a number of satellites searched for in N positioning periods is greater than a preset satellite searching threshold, and all satellite positioning errors are less than a first positioning error threshold, wherein N≧2.

[0063] A second determining module is configured to determine that the current satellite positioning signal is located in the signal unstable area in a case that a number of satellites searched for in M positioning periods of the N positioning periods is less than the preset satellite searching threshold, or a number of satellites searched for in N-1 positioning periods of the N positioning periods is greater than the preset satellite searching threshold and satellite positioning errors of at least two positioning periods are greater than the first preset positioning error threshold, wherein 2≦M≦N-2.

[0064] The third determination module is configured to determine that the current satellite positioning signal is located in a signal-free area when there are at least N-1 positioning cycles in which the number of satellite search is less than the preset satellite search threshold, or all satellite positioning errors are greater than the first positioning error threshold.

[0065] In an embodiment, the target positioning algorithm includes at least one of an inertial navigation positioning algorithm, a wheel rotation positioning algorithm, a high-definition map positioning algorithm, and a lane matching positioning algorithm.

[0066] The second determination unit includes:

[0067] The first determination module is configured to, when the target positioning algorithm includes the inertial navigation positioning algorithm, calculate a self-vehicle driving trajectory according to the target positioning point and target inertial navigation information, and take a trajectory point corresponding to a to-be-positioned time in the self-vehicle driving trajectory as an initial position corresponding to the inertial navigation positioning algorithm, wherein the target inertial navigation information includes inertial navigation information in a self-vehicle driving process from a start time corresponding to the target positioning point to the to-be-positioned time.

[0068] The second determination module is configured to, when the target positioning algorithm includes the wheel rotation positioning algorithm, calculate the target driving distance based on a wheel average radius and a target wheel rotation, and determine a position at a distance of the target driving distance from the target positioning point in the self-vehicle driving trajectory as an initial position corresponding to the wheel rotation positioning algorithm, wherein the target wheel rotation is a wheel rotation of the self-vehicle from a start time corresponding to the target positioning point to a to-be-positioned time.

[0069] The third determination module is configured to, when the target positioning algorithm includes the high-definition map positioning algorithm, determine a target road on which the self-vehicle is currently located according to a preset road recognition algorithm, obtain a preset center line on the target road in a high-definition map, and determine a position at a distance of the target driving distance from the target positioning point and on the preset center line in the self-vehicle driving trajectory as an initial position corresponding to the high-definition map positioning algorithm, wherein the preset center line includes a road center line of the target road and / or a lane center line of the target road.

[0070] A fourth determining module is configured to determine a target lane in which the ego vehicle currently locates according to a preset lane recognition algorithm when the target positioning algorithm comprises the lane matching positioning algorithm, and determine an initial position corresponding to the lane matching positioning algorithm as a position obtained after the initial position corresponding to the high-definition map positioning algorithm is translated to a lane center line of the target lane when the preset center line only comprises a road center line of the target road, or as an initial position on the lane center line of the target lane corresponding to the high-definition map positioning algorithm when the preset center line comprises a lane center line of the target road.

[0071] In an implementation, the target inertial navigation information comprises at least one of a driving distance in a driving process starting from the target positioning point, an inertial measurement unit (IMU) gyro inertial navigation angle, a vehicle speed, and a driving duration starting from the target positioning point.

[0072] A first determining module is specifically configured to:

[0073] calculate the driving trajectory of the ego vehicle according to the first formula or the second formula.

[0074] The first formula is

[0075]

[0076] The P t (x, y) is a position coordinate of a trajectory point when the driving duration is t, the P1(x, y) is a position coordinate of the target positioning point, and the δD k is a driving distance in a kth driving distance statistical period, the n is an nth driving distance statistical period, and the δθ is a difference between an IMU gyro inertial navigation angle at a cutoff time and an IMU gyro inertial navigation angle at a start time of the kth driving distance statistical period.

[0077] The second formula is

[0078] P t (x, y) = P1(x, y) + ∫∫v(x, y, t)dθdt

[0079] The v(x, y, t) is a vehicle speed when the driving duration is t, and the θ is an IMU gyro inertial navigation angle.

[0080] In an implementation, the second determining module is further configured to, before calculating the target driving distance based on the average wheel radius and the target wheel rotation number, acquire two positioning points that meet a preset distance requirement and have a satellite positioning error less than a second positioning error threshold during the self vehicle is driving in the signal stable area in a current average wheel radius correction period; and calculate the average wheel radius according to a distance between the two positioning points, a driving time length between the two positioning points, and a wheel rotation speed.

[0081] In an implementation, the target positioning point comprises at least one of a positioning point calculated based on a satellite positioning signal, a positioning point calculated based on an auxiliary positioning algorithm of a roadside device, and a positioning point calculated based on an auxiliary positioning algorithm of another vehicle.

[0082] In an implementation, the apparatus further comprises:

[0083] a first positioning unit configured to calculate a position coordinate of a target positioning point based on an auxiliary positioning algorithm of a roadside device;

[0084] The first positioning unit comprises:

[0085] a receiving module configured to receive a regional high-precision map and regional high-precision auxiliary positioning data within a range of the regional high-precision map sent by a roadside device, wherein the regional high-precision auxiliary positioning data comprises at least one auxiliary positioning subzone, the auxiliary positioning subzone comprises external feature information of an auxiliary positioning reference object having a unique identifiable feature, a lane reference point for sensing a relative position relationship with the auxiliary positioning reference object, and a relative position relationship between the auxiliary positioning reference object and the lane reference point.

[0086] a judging module configured to, during driving based on the regional high-precision map, if it is determined that the self vehicle enters an auxiliary positioning subzone, judge whether a target auxiliary positioning reference object is detected according to the external feature information, the lane reference point, and the relative position relationship, wherein the target auxiliary positioning reference object is an auxiliary positioning reference object in the auxiliary positioning subzone where the self vehicle is currently located.

[0087] a converting module configured to, if it is determined that the target auxiliary positioning reference object is detected, convert a vehicle body coordinate system into a north-south positive coordinate system with the target auxiliary positioning reference object as an origin, wherein a horizontal axis positive direction of the north-south positive coordinate system is a positive east direction, and a vertical axis positive direction is a positive north direction.

[0088] a fifth determining module configured to determine a position coordinate of the target positioning point according to a relative position relationship between the self vehicle and the target auxiliary positioning reference object, and a mapping relationship between the north-south positive coordinate system and a geographic coordinate system.

[0089] In an implementation, the apparatus further comprises:

[0090] a second positioning unit configured to calculate the position coordinates of the target positioning point based on an assisted positioning algorithm of the roadside device;

[0091] The second positioning unit comprises:

[0092] a detection module configured to detect relative position information of the ego vehicle and the target neighboring vehicle;

[0093] a first acquisition module configured to acquire positioning information of the target neighboring vehicle based on a vehicle-to-everything (V2X) technology, wherein the positioning information comprises a neighboring vehicle positioning position and a neighboring vehicle positioning error;

[0094] a first calculation module configured to calculate the position coordinates of the target positioning point according to the relative position information and the neighboring vehicle positioning position when the neighboring vehicle positioning error is less than a third positioning error threshold.

[0095] In an implementation, the relative position information comprises position coordinates of the target neighboring vehicle, a distance between the ego vehicle and the target neighboring vehicle, and an included angle formed by a line connecting the ego vehicle and the target neighboring vehicle and a road direction;

[0096] The first calculation module is configured to calculate the position coordinates P A (x,y) of the target positioning point according to a third formula, wherein the third formula is P A (x,y) = P B (x,y) - (L cos α, L sin α), P B (x,y) is the position coordinates of the target neighboring vehicle, L is the distance between the ego vehicle and the target neighboring vehicle, and α is the included angle.

[0097] In an implementation, the apparatus further comprises:

[0098] a generation unit configured to generate an error curve corresponding to each target positioning algorithm before determining an algorithm positioning error of a corresponding initial position according to the error curve and a target driving distance corresponding to each target positioning algorithm;

[0099] The generation unit comprises:

[0100] a second acquisition module configured to acquire a plurality of driving distance sub-ranges from a preset driving distance range of historical driving when the ego vehicle is driving in a signal stable area;

[0101] a selection module configured to select a positioning point with a satellite positioning error less than a fourth positioning error threshold as a starting position in each driving distance sub-range;

[0102] The second calculation module is configured to calculate a self-vehicle positioning position corresponding to each starting position according to each starting position and a target positioning algorithm respectively, wherein the self-vehicle positioning position is a positioning position corresponding to a latest time in a preset driving distance range of historical driving, calculate an algorithm positioning error between each self-vehicle positioning position and a true position respectively, wherein the true position is a position of a positioning point with a latest satellite positioning error less than a fourth positioning error threshold in the preset driving distance range of historical driving, and determine a driving distance of each starting position corresponding to a starting time of the self-vehicle to the latest time.

[0103] The generation module is configured to generate an error curve corresponding to the target positioning algorithm according to a mapping relationship between the algorithm positioning error and the driving distance.

[0104] In a third aspect, another embodiment of the present application provides a storage medium having stored executable instructions, which, when executed by a processor, cause the processor to implement the method according to any of the embodiments of the first aspect.

[0105] In a fourth aspect, another embodiment of the present application provides a vehicle, which comprises:

[0106] one or more processors;

[0107] a storage device configured to store one or more programs,

[0108] wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method according to any of the embodiments of the first aspect.

[0109] As can be seen from the above, the vehicle positioning method provided by the embodiments of the present application can directly determine the vehicle position based on the current satellite positioning signal as the target position in the case that the current satellite positioning signal is located in the signal stable area, and can calculate the positioning result (i.e., the initial position) corresponding to each target positioning algorithm by means of at least one target positioning algorithm (non-satellite positioning algorithm) and target positioning point in the case that the current satellite positioning signal is located in the signal unstable area or the signal-free area, and determine the algorithm positioning error of the corresponding initial position according to the error curve corresponding to each target positioning algorithm and the target driving distance, and finally select the initial position with the minimum algorithm positioning error as the target position, so that high-precision positioning results can be obtained regardless of whether the current satellite positioning signal is stable.

[0110] The technical effects that can be achieved by the embodiments of the present application include but are not limited to the following points:

[0111] 1. The embodiments of the present application can quickly and accurately determine the stability of the current satellite positioning signal in combination with the number of searched satellites and the satellite positioning error.

[0112] 2. In order to improve the accuracy of the average radius of the wheel, two positioning points meeting the preset distance requirement and having a satellite positioning error less than the second positioning error threshold can be obtained when the ego vehicle is driving in the signal stable area, and the average radius of the wheel can be calculated according to the distance between the two positioning points, the driving time length between the two positioning points and the wheel speed, so as to realize periodic updating of the average radius of the wheel.

[0113] 3. In the case that the current satellite positioning signal is located in the signal unstable area or the signal-free area, auxiliary positioning can be performed based on the roadside equipment or other vehicles to obtain the target positioning point, thereby improving the accuracy of the target positioning point.

[0114] Of course, implementing any product or method of the present application does not necessarily require all the advantages described above to be achieved at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0115] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application. Those skilled in the art can also obtain other drawings according to these drawings without creative labor.

[0116] Figure 1 A flowchart of a vehicle positioning method provided by an embodiment of the present application;

[0117] Figure 2 An example diagram of positioning results of multiple positioning algorithms provided by an embodiment of the present application;

[0118] Figure 3 An example diagram of auxiliary positioning based on other vehicles provided by an embodiment of the present application;

[0119] Figure 4a An error calculation schematic diagram in the signal stable area provided by an embodiment of the present application;

[0120] Figure 4b An error calculation schematic diagram in the signal unstable area provided by an embodiment of the present application

[0121] Figure 4c An error calculation schematic diagram in the signal-free area provided by an embodiment of the present application;

[0122] Figure 5 A block diagram of a vehicle positioning device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0123] With reference to the drawings and the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all the other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of the present application.

[0124] It should be noted that the terms "comprising" and "having" and any variations thereof in the embodiments of the present application and the drawings are intended to cover the inclusions without exclusivity. For example, the processes, methods, systems, products or devices including a series of steps or units are not limited to the listed steps or units, but can optionally further include steps or units not listed or can optionally further include other steps or units inherent to these processes, methods, products or devices.

[0125] Figure 1 A flowchart of a vehicle positioning method provided by the embodiments of the present application is shown, the method is applied to a ego vehicle, and the method comprises the following steps of:

[0126] S110: judging the stability of the current satellite positioning signal.

[0127] In actual application, the stability of the current satellite positioning signal can be predicted using historical data, the stability of the current satellite positioning signal can be judged in real time, and the real-time judgment result can be used to correct the historical judgment result. When there is no corresponding stability judgment result in the historical data, the stability judgment result can be added to the historical data. The ego vehicle can send correction information to the server to correct the historical data, and the correction information comprises a target position, a stability judgment result corresponding to the modified target position and a stability judgment result before modification. For example, the historical data indicates that the current geographic area where the ego vehicle is located is a signal stable area, but the real-time judgment result indicates that the current geographic area is a signal unstable area. Therefore, the ego vehicle can report the correction information of the stability judgment result to the server. The ego vehicle can send stability increase information to the server to correct the historical data, and the stability increase information comprises a target position and a stability judgment result corresponding to the target position.

[0128] The method for real-time determination of the stability of the current satellite positioning signal includes: if the number of satellite searches within N positioning cycles is above a preset satellite search threshold and all satellite positioning errors are less than a first positioning error threshold, the current satellite positioning signal is determined to be in a stable signal region, where N ≥ 2; if there are M positioning cycles within N positioning cycles where the number of satellite searches is less than the preset satellite search threshold, or if there are at least N-1 positioning cycles within N positioning cycles where the number of satellite searches is above the preset satellite search threshold and at least two positioning cycles where the satellite positioning error is greater than the first preset positioning error threshold, the current satellite positioning signal is determined to be in an unstable signal region, where 2 ≤ M ≤ N-2; if there are at least N-1 positioning cycles within N positioning cycles where the number of satellite searches is less than the preset satellite search threshold, or if all satellite positioning errors are greater than the first positioning error threshold, the current satellite positioning signal is determined to be in a no-signal region. N, the preset satellite search threshold, and the first positioning error threshold can be determined based on practical experience in satellite positioning.

[0129] Assuming one positioning cycle is 1 second, N is 10, the preset satellite search threshold is 3, and the first positioning error threshold is 3 meters, then if the number of satellites searched within 10 seconds is 3 or more, and the positioning error of all satellites is less than 3 meters, the current satellite positioning signal is determined to be in a stable signal zone. If there are 2-8 positioning cycles within 10 seconds with fewer than 3 satellites searched, or if there are at least 9 seconds within 10 seconds with more than 3 satellites searched and at least 2 seconds with a positioning error greater than 3 meters, the current satellite positioning signal is determined to be in an unstable signal zone. If there are at least 9 seconds within 10 seconds with fewer than 3 satellites searched, or if the positioning error of all satellites is greater than 3 meters, the current satellite positioning signal is determined to be in a no-signal zone.

[0130] It should be added that the satellite positioning methods involved in the embodiments of this application include, but are not limited to, RTK (Real-time kinematic) differential positioning.

[0131] S120: When the current satellite positioning signal is located in a stable signal area, the vehicle position located based on the current satellite positioning signal will be determined as the target position.

[0132] The target location is the vehicle's final required current geographical location. When the current satellite positioning signal is in a stable signal area, the satellite positioning accuracy is high, so the vehicle's position based on the current satellite positioning signal can be directly determined as the target location.

[0133] S130: In the case that the current satellite positioning signal is located in the signal unstable area or the signal free area, a target positioning point is selected from a preset driving distance range of the latest driving, an initial position corresponding to each target positioning algorithm is determined based on the target positioning point and each target positioning algorithm, an algorithm positioning error of the corresponding initial position is determined according to an error curve of each target positioning algorithm and a target driving distance, and the initial position with the minimum algorithm positioning error is selected as the target position.

[0134] The target positioning algorithm is a non-satellite positioning algorithm, including at least one of an inertial navigation positioning algorithm, a wheel rotation number positioning algorithm, a high-precision map positioning algorithm and a lane matching positioning algorithm. The error curve is a curve about the mapping relationship between the driving distance and the algorithm positioning error generated in the positioning process in the signal stable area. The target driving distance is the driving distance of the ego vehicle from the starting time corresponding to the target positioning point to the to-be-positioned time.

[0135] The above various target positioning algorithms will be described below. Figure 2 The method for obtaining the initial position of each target positioning algorithm will be described below.

[0136] (A1) Inertial navigation positioning algorithm

[0137] The ego vehicle driving trajectory is calculated according to the target positioning point and the target inertial navigation information, and the trajectory point corresponding to the to-be-positioned time in the ego vehicle driving trajectory is taken as the initial position corresponding to the inertial navigation positioning algorithm, for example Figure 2 The circle position is the initial position corresponding to the inertial navigation positioning algorithm. The target inertial navigation information includes the inertial navigation information in the driving process of the ego vehicle from the starting time corresponding to the target positioning point to the to-be-positioned time. The inertial navigation information includes the driving distance and the IMU (Inertial Measurement Unit, inertial measurement unit) gyroscope inertial navigation rotation angle in the driving process from the target positioning point as the starting position, or the inertial navigation information includes the IMU gyroscope inertial navigation rotation angle, the vehicle speed and the driving time length from the target positioning point.

[0138] The position coordinates P(x, y) of the trajectory point in the ego vehicle driving trajectory when the driving time length is t can be calculated using the first formula or the second formula t .

[0139] The first formula is:

[0140]

[0141] wherein P1(x, y) is the position coordinates of the target positioning point, δD kDk is the driving distance in the kth driving distance statistical period, n is the nth driving distance statistical period, and δθ is the difference between the IMU gyro inertial navigation angle at the end time and the start time of the kth driving distance statistical period. The value of the driving distance statistical period is set according to actual needs.

[0142] The second formula is:

[0143] P t (x, y) = P1(x, y) + ∫∫v(x, y, t)dθdt

[0144] where P1(x, y) is the position coordinates of the target positioning point, v(x, y, t) is the vehicle speed when the driving time is t, and θ is the IMU gyro inertial navigation angle. Wherein,

[0145]

[0146] where D t (x, y) is the driving distance when the driving time is t.

[0147] (A2) Wheel revolution positioning algorithm

[0148] The target driving distance is calculated based on the average wheel radius and the target wheel revolution, and the position in the vehicle driving trajectory that is a distance of the target driving distance from the target positioning point is determined as the initial position corresponding to the wheel revolution positioning algorithm, for example Figure 2 The position of the gray box is the initial position corresponding to the wheel revolution positioning algorithm, wherein the target wheel revolution is the wheel revolution of the ego vehicle from the start time corresponding to the target positioning point to the to-be-positioned time.

[0149] The target driving distance = target wheel revolution * 2π * average wheel radius. Since the average wheel radius changes slightly with each day of vehicle driving, in order to improve the accuracy of the target driving distance, the accuracy of the average wheel radius needs to be improved first. A wheel average radius correction period can be set, for example, 1 day, and the average wheel radius is updated every time a new wheel average radius correction period is entered, and the updated average wheel radius is used in the wheel average radius correction period.

[0150] In an embodiment, the updating method of the average wheel radius comprises: in the current wheel average radius correction period, when the ego vehicle is driving in the signal stable area, two positioning points satisfying the preset distance requirement and the satellite positioning error being less than a second positioning error threshold are acquired; and the average wheel radius is calculated according to the distance between the two positioning points, the driving time between the two positioning points, and the wheel rotation speed.

[0151] The preset distance requirement and the second positioning error threshold can be determined according to actual experience, for example, the preset distance requirement is 500 meters, and the second positioning error threshold is 1 meter.

[0152] The average wheel radius calculation formula is

[0153]

[0154] wherein, R is the average wheel radius, I is the distance between two positioning points, and t' is the driving time length between two positioning points.

[0155] (A3) High-precision map positioning algorithm

[0156] According to the preset road recognition algorithm, the target road where the ego vehicle is currently located is determined, and a preset center line on the target road in the high-precision map is obtained. According to the driving trajectory of the ego vehicle, the position on the preset center line with a target driving distance from the target positioning point is determined as the initial position corresponding to the high-precision map positioning algorithm.

[0157] The preset center line includes the road center line of the target road and / or the lane center line of the target road. The preset road recognition algorithm includes an algorithm for recognizing a road based on satellite positioning, an algorithm for recognizing a road based on inertial navigation positioning, or an algorithm for recognizing a road based on navigation planning path. The high-precision map can be a regional high-precision map or a global high-precision map. As shown in Figure 2 , the target road where the ego vehicle is located has three lanes. If the accuracy of the high-precision map is relatively high, the preset center line includes the road center line of the target road and the three lane center lines of the target road, so that four initial positions can be obtained based on the high-precision map positioning algorithm. Among them, the solid white triangular position is the initial position on the lane center line, and the black triangular position is the initial position on the road lane line.

[0158] (A4) Lane matching positioning algorithm

[0159] According to the preset lane recognition algorithm, the target lane where the ego vehicle is currently located is determined. When the preset center line only includes the road center line of the target road, the position obtained after translating the initial position corresponding to the high-precision map positioning algorithm to the lane center line of the target lane is determined as the initial position corresponding to the lane matching positioning algorithm, or when the preset center line includes the lane center line of the target road, the initial position on the lane center line of the target lane corresponding to the high-precision map positioning algorithm is determined as the initial position corresponding to the lane matching positioning algorithm. The direction of translation is the vertical direction of the lane center line, as shown in Figure 2 , for example, Figure 2 , the lowermost lane in the figure is the target lane, and the white triangular position of the dashed line is the initial position corresponding to the lane matching positioning algorithm. In addition, the five-point star position is the satellite positioning position.

[0160] In an embodiment, the target positioning point can be one or multiple. The target positioning point includes at least one of a positioning point calculated based on a satellite positioning signal, a positioning point calculated based on a roadside device-based auxiliary positioning algorithm, and a positioning point calculated based on an auxiliary positioning algorithm of other vehicles. The positioning error of all selected target positioning points is less than a fifth positioning error threshold. Specifically, in the case that the current satellite positioning signal is located in a signal unstable area, the target positioning point can include all of the above three kinds of positioning points, as long as the positioning error requirement is met. In the case that the current satellite positioning signal is located in a signal unstable area, the target positioning point can include a positioning point calculated based on a roadside device-based auxiliary positioning algorithm and a positioning point calculated based on an auxiliary positioning algorithm of other vehicles, as long as the positioning error requirement is met. The fifth positioning error threshold is determined according to actual experience, for example, it can be 1 meter.

[0161] The method of calculating the position coordinates of the target positioning point based on the roadside device-based auxiliary positioning algorithm and the method of calculating the position coordinates of the target positioning point based on the auxiliary positioning algorithm of other vehicles are described below respectively:

[0162] (B1) Calculating the position coordinates of the target positioning point based on the roadside device-based auxiliary positioning algorithm

[0163] The regional high-precision map and the regional high-precision auxiliary positioning data within the range of the regional high-precision map sent by the roadside device are received, wherein the regional high-precision auxiliary positioning data includes at least one auxiliary positioning partition, the auxiliary positioning partition includes the external feature information of the auxiliary positioning reference object with unique identifiable features, the lane reference point for perceiving the relative position relationship with the auxiliary positioning reference object, and the relative position relationship between the auxiliary positioning reference object and the lane reference point; in the process of driving based on the regional high-precision map, if it is determined that the ego vehicle enters an auxiliary positioning partition, it is judged whether the target auxiliary positioning reference object is detected according to the external feature information, the lane reference point, and the relative position relationship, wherein the target auxiliary positioning reference object is the auxiliary positioning reference object of the auxiliary positioning partition where the ego vehicle is currently located; in the case that it is determined that the target auxiliary positioning reference object is detected, the body coordinate system is converted into a north-south positive coordinate system with the target auxiliary positioning reference object as the origin, wherein the horizontal axis positive direction of the north-south positive coordinate system is the positive east direction, and the vertical axis positive direction is the positive north direction; the relative position relationship between the ego vehicle and the target auxiliary positioning reference object, and the mapping relationship between the north-south positive coordinate system and the geographic coordinate system are used to determine the position coordinates of the target positioning point.

[0164] The regional high-precision map includes data identification, basic elements, and extended elements. The data identification includes regional identification and regional high-precision map version number; the basic elements include road, lane, and intersection data (including lane lines, road edge lines, zebra crossings, and other basic information); and the extended elements include road medians, road sides, on-road ground objects or buildings, facilities, signboards, and road surface signs. The data identification is the unique code of the regional high-precision map. The basic elements are basic elements for describing lanes, lane lines, and road networks. The extended elements are adjacent ground objects other than the basic elements. The basic elements are necessary road information for navigation and driving decisions (including lane-level path selection), while the extended elements are not necessary information but are optional spatial elements for high-precision assisted driving.

[0165] The external feature information includes the length, height, and width of the auxiliary positioning reference object and the text or graphic content displayed on the auxiliary positioning reference object. The lane reference point for sensing the relative position relationship with the auxiliary positioning reference object is a reference point selected on a lane near the auxiliary positioning reference object, such as a lane line or a lane center line. The relative position relationship between the auxiliary positioning reference object and the lane reference point includes the distance between the auxiliary positioning reference object and the lane reference point, the included angle between the line connecting the auxiliary positioning reference object and the lane reference point and the lane line or the lane center line of the lane where the lane reference point is located, and the like. The regional high-precision auxiliary positioning data further includes data description, which includes the data packet identification and version number of the regional high-precision auxiliary positioning data and the data identification of the matching regional high-precision map. The regional high-precision auxiliary positioning data is matched with the regional high-precision map, which means that the regional high-precision auxiliary positioning data is within the range of the region described by the regional high-precision map.

[0166] The positioning error calculation method of the roadside device-based auxiliary positioning algorithm includes: when the regional high-precision auxiliary positioning data further includes the actual position coordinates of the target auxiliary positioning reference object, obtaining the actual position coordinates of the target auxiliary positioning reference object from the regional high-precision auxiliary positioning data; according to the relative position relationship between the target auxiliary positioning reference object recorded in the regional high-precision auxiliary positioning data and the lane reference point corresponding to the target auxiliary positioning reference object, and the distance traveled by the vehicle from the last auxiliary positioning point to the detection of the target auxiliary positioning reference object, determining the actual distance between the vehicle and the target auxiliary positioning reference object, and the actual included angle between the line connecting the vehicle and the target auxiliary positioning reference object and the driving direction of the vehicle; taking the position coordinates of the target auxiliary positioning reference object detected by the vehicle as the measured position coordinates, and obtaining the measured distance between the vehicle and the target auxiliary positioning reference object, and the measured included angle between the line connecting the vehicle and the target auxiliary positioning reference object and the driving direction of the vehicle from the relative position relationship between the vehicle and the target auxiliary positioning reference object detected by the vehicle; taking the absolute value of the difference between the measured position coordinates and the actual position coordinates as the position coordinate error δr of the target auxiliary positioning reference object; taking the absolute value of the difference between the measured distance and the actual distance as the distance measurement error δL' when the vehicle measures the distance between the vehicle and the target auxiliary positioning reference object; taking the absolute value of the difference between the measured included angle and the actual included angle as the angle measurement error δθ' when the vehicle measures the included angle between the line connecting the vehicle and the target auxiliary positioning reference object and the driving direction of the vehicle; calculating the longitudinal error according to the longitudinal error formula δr+δL'+L'δθ'ctgθ', wherein L' represents the minimum distance between the measured distance and the actual distance, and θ' represents the included angle between the line connecting the vehicle and the target auxiliary positioning reference object and the driving direction of the vehicle corresponding to L'; calculating the lateral error according to the lateral error formula δr+Lδθ'; and determining the positioning error corresponding to the latitude and longitude coordinates according to the longitudinal error and the lateral error.

[0167] (B2) calculating the position coordinates of the target positioning point based on the auxiliary positioning algorithm of other vehicles

[0168] detecting the relative position information between the ego vehicle and the target neighboring vehicle, and obtaining the positioning information of the target neighboring vehicle based on the vehicle wireless communication technology V2X, wherein the positioning information includes the neighboring vehicle positioning position and the neighboring vehicle positioning error; in the case that the neighboring vehicle positioning error is less than a third positioning error threshold, calculating the position coordinates of the target positioning point according to the relative position information and the neighboring vehicle positioning position.

[0169] wherein the relative position information includes the position coordinates of the target neighboring vehicle, the distance between the ego vehicle and the target neighboring vehicle, and the included angle formed by the line connecting the ego vehicle and the target neighboring vehicle and the road direction. The position coordinates P A (x,y) of the target positioning point are calculated according to a third formula P A (x,y) = PB (x, y) - (L cos a, L sin a), P B (x, y) is the position coordinate of the target neighboring vehicle, L is the distance between the ego vehicle and the target neighboring vehicle, and a is the included angle. In addition, the neighboring vehicle positioning error is the positioning error of the target positioning point, and the third positioning error threshold is determined according to actual experience, for example, can be 1 meter. The embodiment of the present application does not limit the establishment method of the coordinate system, for example, as shown in Figure 3 the vehicle driving direction can be taken as the positive direction of the x axis, and the direction perpendicular to the x axis and pointing to the target neighboring vehicle can be taken as the positive direction of the y axis.

[0170] In an embodiment, before using the error curve, it is also necessary to generate the error curve corresponding to each target positioning algorithm. The process of generating the error curve corresponding to each target positioning algorithm is described below:

[0171] When the ego vehicle is driving in the signal stable area, a plurality of driving distance sub-ranges are obtained from the preset driving distance range of the historical driving; a positioning point with a satellite positioning error less than a fourth positioning error threshold is selected as a starting position in each driving distance sub-range; the positioning position of the ego vehicle corresponding to each starting position is calculated according to each starting position and the target positioning algorithm respectively, wherein the positioning position of the ego vehicle is the positioning position at the latest time corresponding to the preset driving distance range of the historical driving; the algorithm positioning error between each positioning position of the ego vehicle and the true position is calculated respectively, wherein the true position is the position of the positioning point with the satellite positioning error less than the fourth positioning error threshold in the preset driving distance range of the historical driving; the driving distance from the starting time corresponding to each starting position of the ego vehicle to the latest time is determined; and the error curve corresponding to the target positioning algorithm is generated according to the mapping relationship between the algorithm positioning error and the driving distance. The plurality of driving distance sub-ranges have no intersection and are continuous. In order to improve the accuracy and smoothness of the error curve, the steps before "generating the error curve corresponding to the target positioning algorithm according to the mapping relationship between the algorithm positioning error and the driving distance" can be repeatedly executed to obtain more algorithm positioning errors and driving distances, and the average value of the algorithm positioning error and the average value of the driving distance are calculated to obtain the error curve corresponding to the target positioning algorithm according to the mapping relationship between the average value of the algorithm positioning error and the average value of the driving distance. The fourth positioning error threshold is determined according to actual experience, for example, can be 1 meter.

[0172] For example, assuming that the preset driving distance range of historical driving is 1000 meters, a plurality of driving distance subranges (500, 1000], (200, 500], (100, 200] are obtained therefrom, and one positioning point with a satellite positioning error less than the fourth positioning error threshold is selected as a starting position in each of the three driving distance subranges, which are starting position 1, starting position 2, and starting position 3, respectively. A position where the last positioning point within 100 meters with a satellite positioning error less than the fourth positioning error threshold is located is selected as the true position. According to the calculation method of each target positioning algorithm, the self-vehicle positioning position corresponding to each starting position is calculated according to each starting position and the target positioning algorithm, and the algorithm positioning error between each self-vehicle positioning position and the true position is calculated, for example, E1, E2, and E3 in turn. The driving distance from the starting time corresponding to each starting position to the latest time is determined, for example, the driving distances corresponding to starting positions 1-3 are D1, D1, and D3, respectively. According to the mapping relationship between the algorithm positioning error and the driving distance, the error curve corresponding to the target positioning algorithm, i.e., the D-E curve, is generated.

[0173] The following will be described respectively for different error changes:

[0174] As shown in FIG. 1, Figure 4a When the vehicle is within 100-1000 meters from the current time point, it drives in the signal stable area, and the RTK positioning error range is small. For the upper half of the figure (i.e., the area above the largest rectangular frame), the dotted circle represents the RTK positioning error range, the black triangle in the RTK positioning point represents the reference positioning point with the smallest RTK positioning error (almost 0), and the white triangle is the actual RTK positioning point. When the vehicle is within 100-1000 meters from the current time point, the RTK positioning error is small, and the vehicle drives in the signal stable area. When it is within 100, the vehicle starts to enter the signal unstable area. During the driving of the vehicle in the signal stable area, the error curve corresponding to each target positioning algorithm can be calculated, Figure 4a For example, starting from starting point 1, an error curve can be calculated. Starting from starting points 2 and 3, an error curve can be calculated, respectively, for subsequent use when the vehicle enters the non-signal stable area. When the vehicle is in the signal unstable area from starting point 4 to the current time point, the RTK positioning position is no longer directly used as the position of the current time point, but the target positioning algorithm can be used to calculate the position of the current time point, and the error curve calculated before can be used to calculate the error of the position. Therefore, the error change from starting point 4 to the current time point is represented by a dotted line.

[0175] As shown in FIG. 2, Figure 4bAs shown in the figure, according to the change of the dotted circle in the upper half of the figure, it can be seen that the RTK positioning error changes greatly, and the vehicle is in the signal unstable area. In the driving process in this area, the RTK positioning points with low positioning error can be obtained at 200-1000 meters. Therefore, the error relative to the RTK positioning can be seen when the corresponding position is calculated using the target positioning algorithm in this range. When the distance is less than 200 meters, the RTK positioning error is large, so the positioning error of this time can be determined by referring to the error curve corresponding to the target positioning algorithm generated before, that is, the dotted part is part of the error curve corresponding to the target positioning algorithm generated before.

[0176] As shown in the figure, Figure 4c As shown in the figure, according to the change of the dotted circle in the upper half of the figure, it can be seen that there is basically no RTK signal within 1000, so auxiliary positioning is needed. Between the starting point 3 and the starting point 4, auxiliary positioning has been performed, so the error relative to the auxiliary positioning can be seen when the corresponding position is calculated using the target positioning algorithm in this range. From the starting point 4 to the current time point, since there is no positioning information, the positioning error of this time can be determined by referring to the error curve corresponding to the target positioning algorithm generated before, that is, the dotted part is part of the error curve corresponding to the target positioning algorithm generated before.

[0177] It should be noted that the first positioning error threshold, the second positioning error threshold, the third positioning error threshold, the fourth positioning error threshold, and the fifth positioning error threshold can be the same or different, and the specific values are determined according to the actual situation.

[0178] Based on the above method embodiment, another embodiment of the present application further provides a vehicle positioning device, as shown in the figure, Figure 5 The device comprises:

[0179] A judgment unit 21 is configured to judge the stability of the current satellite positioning signal.

[0180] A first determination unit 22 is configured to determine the vehicle position positioned based on the current satellite positioning signal as a target position in a case where the current satellite positioning signal is located in a signal stable area, wherein the target position is the final required current geographical position of the ego vehicle.

[0181] A selection unit 23 is configured to select a target positioning point from a preset driving distance range of the most recent driving in a case where the current satellite positioning signal is located in a signal unstable area or a signal free area.

[0182] A second determination unit 24 is configured to determine an initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm in at least one target positioning algorithm, wherein the target positioning algorithm is a positioning algorithm other than satellite positioning.

[0183] The third determining unit 25 is configured to determine an algorithm positioning error of the initial position according to an error curve corresponding to each target positioning algorithm and a target driving distance, wherein the error curve is an error curve about a mapping relationship between a driving distance and an algorithm positioning error generated in a positioning process in a signal stable area, and the target driving distance is a driving distance of the ego vehicle from a starting time corresponding to the target positioning point to a to-be-positioned time;

[0184] The selecting unit 26 is configured to select the initial position with the minimum algorithm positioning error as the target position.

[0185] In an embodiment, the judging unit 21 comprises:

[0186] The first determining module is configured to determine that the current satellite positioning signal is located in the signal stable area when the number of satellites in the N positioning periods is greater than the preset satellite number threshold and all satellite positioning errors are less than the first positioning error threshold, wherein N≧2.

[0187] The second determining module is configured to determine that the current satellite positioning signal is located in the signal unstable area when there are M positioning periods with the number of satellites less than the preset satellite number threshold in the N positioning periods, or there are at least N-1 positioning periods with the number of satellites greater than the preset satellite number threshold and at least two positioning periods with satellite positioning errors greater than the first preset positioning error threshold in the N positioning periods, wherein 2≦M≦N-2.

[0188] The third determining module is configured to determine that the current satellite positioning signal is located in the signal-free area when there are at least N-1 positioning periods with the number of satellites less than the preset satellite number threshold, or all satellite positioning errors are greater than the first positioning error threshold.

[0189] In an embodiment, the target positioning algorithm comprises at least one of an inertial navigation positioning algorithm, a wheel rotation number positioning algorithm, a high-precision map positioning algorithm, and a lane matching positioning algorithm.

[0190] The second determining unit 24 comprises:

[0191] The first determining module is configured to, when the target positioning algorithm comprises the inertial navigation positioning algorithm, calculate an ego vehicle driving track according to the target positioning point and target inertial navigation information, and take a track point corresponding to the to-be-positioned time in the ego vehicle driving track as the initial position corresponding to the inertial navigation positioning algorithm, wherein the target inertial navigation information comprises inertial navigation information in an ego vehicle driving process from a starting time corresponding to the target positioning point to the to-be-positioned time.

[0192] the second determining module is configured to, when the target positioning algorithm comprises the wheel rotation positioning algorithm, calculate the target driving distance based on a wheel average radius and a target wheel rotation number, and determine a position corresponding to the target driving distance from the target positioning point in the ego vehicle driving trajectory as an initial position corresponding to the wheel rotation positioning algorithm, wherein the target wheel rotation number is a wheel rotation number of the ego vehicle from a starting time corresponding to the target positioning point to a to-be-positioned time;

[0193] the third determining module is configured to, when the target positioning algorithm comprises the high-definition map positioning algorithm, determine a target road currently located by the ego vehicle according to a preset road recognition algorithm, acquire a preset center line on the target road in a high-definition map, and determine a position corresponding to the target driving distance from the target positioning point and located on the preset center line according to the ego vehicle driving trajectory as an initial position corresponding to the high-definition map positioning algorithm, wherein the preset center line comprises a road center line of the target road and / or a lane center line of the target road;

[0194] the fourth determining module is configured to, when the target positioning algorithm comprises the lane matching positioning algorithm, determine a target lane currently located by the ego vehicle according to a preset lane recognition algorithm, and when the preset center line only comprises the road center line of the target road, determine a position obtained by translating the initial position corresponding to the high-definition map positioning algorithm to a lane center line of the target lane as an initial position corresponding to the lane matching positioning algorithm, or when the preset center line comprises the lane center line of the target road, determine the initial position on the lane center line of the target lane corresponding to the high-definition map positioning algorithm as the initial position corresponding to the lane matching positioning algorithm.

[0195] In an implementation manner, the target inertial navigation information comprises at least one of a driving distance in a driving process starting from the target positioning point, an inertial measurement unit (IMU) gyroscope inertial navigation rotation angle, a vehicle speed, and a driving time length starting from the target positioning point.

[0196] The first determining module is specifically configured to:

[0197] calculate the ego vehicle driving trajectory according to the first formula or the second formula;

[0198] wherein the first formula is

[0199]

[0200] wherein the P t (x, y) is a position coordinate of a trajectory point when the driving time length is t, P1(x, y) is a position coordinate of the target positioning point, and δD kThe driving distance in the kth driving distance statistical period, n is the nth driving distance statistical period, and δθ is the difference between the IMU gyro inertial navigation angle of the end time and the start time of the kth driving distance statistical period.

[0201] The second formula is

[0202] P t (x, y) = P1(x, y) + ∫∫v(x, y, t)dθdt

[0203] Wherein, v(x, y, t) is the vehicle speed when the driving time is t, and θ is the IMU gyro inertial navigation angle.

[0204] In an embodiment, the second determining module is further configured to, before calculating the target driving distance based on the average wheel radius and the target wheel rotation number, acquire two positioning points meeting the preset distance requirement and having a satellite positioning error less than a second positioning error threshold during the self vehicle driving in the signal stable area in the current average wheel radius correction period; and calculate the average wheel radius according to the distance between the two positioning points, the driving time between the two positioning points, and the wheel rotation speed.

[0205] In an embodiment, the target positioning point includes at least one of a positioning point calculated based on a satellite positioning signal, a positioning point calculated based on an auxiliary positioning algorithm of a roadside device, and a positioning point calculated based on an auxiliary positioning algorithm of another vehicle.

[0206] In an embodiment, the apparatus further comprises:

[0207] A first positioning unit configured to calculate the position coordinates of the target positioning point based on an auxiliary positioning algorithm of a roadside device.

[0208] The first positioning unit comprises:

[0209] A receiving module configured to receive a regional high-precision map and regional high-precision auxiliary positioning data within the range of the regional high-precision map sent by a roadside device, wherein the regional high-precision auxiliary positioning data comprises at least one auxiliary positioning subzone, the auxiliary positioning subzone comprises the external feature information of an auxiliary positioning reference object having a unique identifiable feature, a lane reference point for sensing the relative position relationship with the auxiliary positioning reference object, and the relative position relationship between the auxiliary positioning reference object and the lane reference point.

[0210] a judging module, configured to, in a process of driving based on the high-precision regional map, determine whether a target auxiliary positioning reference object is detected according to the external feature information, the lane reference point and the relative position relationship if it is determined that the ego vehicle enters an auxiliary positioning subzone, wherein the target auxiliary positioning reference object is an auxiliary positioning reference object of the auxiliary positioning subzone where the ego vehicle is currently located;

[0211] a converting module, configured to, in a case where it is determined that the target auxiliary positioning reference object is detected, convert a vehicle body coordinate system into a north-south positive coordinate system with the target auxiliary positioning reference object as an origin, wherein a horizontal axis positive direction of the north-south positive coordinate system is a positive east direction and a vertical axis positive direction is a positive north direction;

[0212] a fifth determining module, configured to determine a position coordinate of the target positioning point according to a relative position relationship between the ego vehicle and the target auxiliary positioning reference object and a mapping relationship between the north-south positive coordinate system and a geographic coordinate system.

[0213] In an implementation manner, the device further includes:

[0214] a second positioning unit, configured to calculate a position coordinate of the target positioning point based on an auxiliary positioning algorithm of a roadside device;

[0215] the second positioning unit includes:

[0216] a detecting module, configured to detect relative position information between the ego vehicle and a target neighboring vehicle;

[0217] a first acquiring module, configured to acquire positioning information of the target neighboring vehicle based on a vehicle-to-everything (V2X) technology, wherein the positioning information includes a neighboring vehicle positioning position and a neighboring vehicle positioning error;

[0218] a first calculating module, configured to, in a case where the neighboring vehicle positioning error is less than a third positioning error threshold, calculate a position coordinate of the target positioning point according to the relative position information and the neighboring vehicle positioning position.

[0219] In an implementation manner, the relative position information includes a position coordinate of the target neighboring vehicle, a distance between the ego vehicle and the target neighboring vehicle and an included angle formed by a line connecting the ego vehicle and the target neighboring vehicle and a road direction;

[0220] the first calculating module is configured to calculate the position coordinate P A (x,y) of the target positioning point according to a third formula P A (x,y) = P B (x,y) - (L cos α, L sin α), P B(x, y) is a position coordinate of the target adjacent vehicle, the L is a distance between the ego vehicle and the target adjacent vehicle, and the a is the included angle.

[0221] In an implementation, the apparatus further includes:

[0222] The generating unit is configured to generate an error curve corresponding to each target positioning algorithm before determining an algorithm positioning error of a corresponding initial position according to the error curve and a target driving distance of each target positioning algorithm.

[0223] The generating unit includes:

[0224] The second obtaining module is configured to obtain a plurality of driving distance sub-ranges from a preset driving distance range of the historical driving when the ego vehicle is driving in the signal stable area.

[0225] The selecting module is configured to select a positioning point with a satellite positioning error less than a fourth positioning error threshold as a starting position in each driving distance sub-range.

[0226] The second calculating module is configured to calculate an ego vehicle positioning position corresponding to each starting position according to each starting position and a target positioning algorithm respectively, wherein the ego vehicle positioning position is a positioning position at a latest time corresponding to the preset driving distance range of the historical driving, calculate an algorithm positioning error between each ego vehicle positioning position and a true position respectively, wherein the true position is a position of a positioning point with a satellite positioning error less than the fourth positioning error threshold in the preset driving distance range of the historical driving for the last time, and determine a driving distance of the ego vehicle from a starting time corresponding to each starting position to the latest time.

[0227] The generating module is configured to generate an error curve corresponding to the target positioning algorithm according to a mapping relationship between the algorithm positioning error and the driving distance.

[0228] Based on the above method embodiments, another embodiment of the present application provides a storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to implement the method described above.

[0229] Based on the above method embodiments, another embodiment of the present application provides a vehicle, which includes:

[0230] One or more processors;

[0231] A storage device configured to store one or more programs,

[0232] When the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any of the above embodiments.

[0233] The system and device embodiments correspond to the method embodiments and have the same technical effects as the method embodiments. For details, refer to the method embodiments. The device embodiments are based on the method embodiments, and for details, refer to the method embodiments, which will not be described herein again. Those skilled in the art can understand that the accompanying drawings are only schematic diagrams of an embodiment, and the modules or flows in the accompanying drawings are not necessarily required for implementing the present application.

[0234] Those skilled in the art can understand that the modules in the device in the embodiments can be distributed in the device in the embodiments as described in the embodiments, or can be correspondingly changed and located in one or more devices different from the embodiments. The modules in the above embodiments can be combined into one module, or can be further split into multiple sub-modules.

[0235] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some technical features. Such modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A vehicle positioning method, characterized in that, The method includes: Determine the stability of the current satellite positioning signal; If the current satellite positioning signal is located in a stable signal area, the vehicle position located based on the current satellite positioning signal is determined as the target position, wherein the target position is the final required current geographical location of the vehicle; When the current satellite positioning signal is located in an unstable or no-signal area, a target positioning point is selected from the nearest preset travel distance range. Based on the target positioning point and each of the at least one target positioning algorithm, an initial position is determined for each algorithm. The algorithm positioning error for the corresponding initial position is determined according to the error curve of each algorithm and the target travel distance. The initial position with the smallest algorithm positioning error is selected as the target position. The target positioning algorithm is a non-satellite positioning algorithm, the error curve is a curve generated during the positioning process in the signal stable area that maps the driving distance to the algorithm positioning error, and the target driving distance is the driving distance of the vehicle from the start time corresponding to the target positioning point to the time to be positioned. Before determining the algorithm positioning error of the corresponding initial position based on the error curve and target driving distance for each target positioning algorithm, the method further includes: generating the error curve for each target positioning algorithm; The error curves for each target localization algorithm include: When the vehicle is driving in a signal-stable area, it obtains multiple sub-ranges of driving distance from a preset range of historical driving distances; Within each driving distance sub-range, a positioning point with a satellite positioning error less than the fourth positioning error threshold is selected as the starting position; The vehicle positioning position corresponding to each starting position is calculated based on each starting position and target positioning algorithm, wherein the vehicle positioning position is the latest positioning position corresponding to a preset driving distance range in the history; Calculate the algorithmic positioning error between each vehicle's location and its actual location, where the actual location is the location of the point where the satellite positioning error is less than the fourth positioning error threshold within the preset driving distance range of the historical driving. Determine the distance traveled from the starting time to the latest time for each starting position of the vehicle; An error curve corresponding to the target positioning algorithm is generated based on the mapping relationship between the algorithm positioning error and the driving distance.

2. The method according to claim 1, characterized in that, Determining the stability of the current satellite positioning signal includes: If the number of satellite searches within N positioning cycles is above a preset satellite search threshold and all satellite positioning errors are less than a first positioning error threshold, then the current satellite positioning signal is determined to be in a signal stability region, wherein N≧2; If, within the N positioning cycles, there are M positioning cycles with a satellite search count less than the preset satellite search threshold, or if within the N positioning cycles, there are at least N-1 positioning cycles with a satellite search count greater than the preset satellite search threshold and at least two positioning cycles with a satellite positioning error greater than the first positioning error threshold, then the current satellite positioning signal is determined to be in a signal unstable region, where 2≦M≦N-2; If, within the N positioning cycles, the number of satellite searches is less than the preset satellite search threshold for at least N-1 positioning cycles, or if all satellite positioning errors are above the first positioning error threshold, then the current satellite positioning signal is determined to be in a no-signal area.

3. The method according to claim 1, characterized in that, The target localization algorithm includes at least one of the following: inertial navigation localization algorithm, wheel rotation number localization algorithm, high-precision map localization algorithm, and lane matching localization algorithm. When the target positioning algorithm includes the inertial navigation positioning algorithm, determining the initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm in at least one target positioning algorithm includes: calculating the vehicle's driving trajectory according to the target positioning point and the target inertial navigation information, and taking the trajectory point corresponding to the time to be positioned in the vehicle's driving trajectory as the initial position corresponding to the inertial navigation positioning algorithm, wherein the target inertial navigation information includes the inertial navigation information of the vehicle during the driving process from the start time corresponding to the target positioning point to the time to be positioned; When the target positioning algorithm includes the wheel rotation number positioning algorithm, determining the initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm in at least one target positioning algorithm includes: calculating the target driving distance based on the average wheel radius and the target wheel rotation number, and determining the position at the target driving distance from the target positioning point in the vehicle's driving trajectory as the initial position corresponding to the wheel rotation number positioning algorithm, wherein the target wheel rotation number is the number of wheel rotations of the vehicle from the start time corresponding to the target positioning point to the time to be positioned; When the target positioning algorithm includes the high-precision map positioning algorithm, determining the initial position corresponding to each target positioning algorithm based on the target positioning point and each target positioning algorithm in at least one target positioning algorithm includes: determining the target road where the vehicle is currently located according to a preset road recognition algorithm, obtaining a preset center line on the target road in the high-precision map, and determining the position located at the target driving distance from the target positioning point and on the preset center line according to the vehicle's driving trajectory as the initial position corresponding to the high-precision map positioning algorithm, wherein the preset center line includes the road center line of the target road and / or the lane center line of the target road; When the target positioning algorithm includes the lane matching positioning algorithm, determining the initial position corresponding to each target positioning algorithm based on the target positioning point and each of the at least one target positioning algorithms includes: determining the target lane where the vehicle is currently located according to a preset lane recognition algorithm; when the preset center line only includes the road center line of the target road, determining the position obtained by translating the initial position corresponding to the high-precision map positioning algorithm to the lane center line of the target lane as the initial position corresponding to the lane matching positioning algorithm; or, when the preset center line includes the lane center line of the target road, determining the initial position on the lane center line of the target lane corresponding to the high-precision map positioning algorithm as the initial position corresponding to the lane matching positioning algorithm.

4. The method according to claim 3, characterized in that, The target inertial navigation information includes at least one of the following: the distance traveled while continuing from the target positioning point as the starting position, the inertial navigation rotation angle of the inertial measurement unit (IMU) gyroscope, the vehicle speed, and the travel time from the target positioning point. Calculating the vehicle's trajectory based on the target positioning point and target inertial navigation information includes: Calculate the vehicle's trajectory according to either the first or second formula; Wherein, the first formula is Wherein, P t (x,y) represents the position coordinates of the trajectory point when the travel time is t, P1(x,y) represents the position coordinates of the target positioning point, and δD represents the position coordinates of the target positioning point. k The distance traveled in the k-th driving distance statistical period is n, where n is the n-th driving distance statistical period, and δθ is the difference between the IMU gyroscope inertial navigation angle at the end time and the start time of the k-th driving distance statistical period. The second formula is P t (x,y)=P1(x,y)+∫∫v(x,y,t)dθdt Wherein, v(x,y,t) is the vehicle speed when the driving time is t, and θ is the inertial navigation angle of the IMU gyroscope.

5. The method according to claim 3, characterized in that, Before calculating the target travel distance based on the average wheel radius and the target wheel revolutions, the method further includes: During this wheel average radius correction cycle, when the vehicle is driving in the signal stable area, it acquires two positioning points that meet the preset distance requirements and whose satellite positioning error is less than the second positioning error threshold. The average radius of the wheel is calculated based on the distance between the two positioning points, the travel time between the two positioning points, and the wheel speed.

6. The method according to claim 1, characterized in that, The target positioning point includes at least one of the following: a positioning point calculated based on satellite positioning signals, a positioning point calculated based on a roadside equipment-assisted positioning algorithm, and a positioning point calculated based on an auxiliary positioning algorithm of other vehicles.

7. The method according to claim 6, characterized in that, When the target positioning point includes a positioning point calculated by an auxiliary positioning algorithm based on roadside equipment, the method further includes: calculating the position coordinates of the target positioning point based on the auxiliary positioning algorithm based on roadside equipment before selecting the target positioning point from the nearest preset driving distance range; The location coordinates of the target positioning point are calculated using the roadside equipment-based assisted positioning algorithm, which includes: The system receives a high-precision map of the area sent by a roadside device and high-precision auxiliary positioning data of the area within the range of the high-precision map. The high-precision auxiliary positioning data of the area includes at least one auxiliary positioning partition. The auxiliary positioning partition includes external feature information of an auxiliary positioning reference with unique identifiable features, a lane reference point for sensing the relative positional relationship with the auxiliary positioning reference, and the relative positional relationship between the auxiliary positioning reference and the lane reference point. During driving based on the high-precision map of the area, if it is determined that the vehicle has entered an auxiliary positioning zone, then based on the external feature information, the lane reference point and the relative position relationship, it is determined whether a target auxiliary positioning reference object has been detected, wherein the target auxiliary positioning reference object is the auxiliary positioning reference object of the auxiliary positioning zone in which the vehicle is currently located. If the target auxiliary positioning reference is detected, the vehicle coordinate system is converted into a north-south positive coordinate system with the target auxiliary positioning reference as the origin. The positive direction of the horizontal axis of the north-south positive coordinate system is due east, and the positive direction of the vertical axis is due north. The position coordinates of the target positioning point are determined based on the relative positional relationship between the vehicle and the target auxiliary positioning reference, and the mapping relationship between the north-south positive coordinate system and the geographic coordinate system.

8. The method according to claim 6, characterized in that, When the target positioning point includes a positioning point calculated based on an auxiliary positioning algorithm of other vehicles, before selecting the target positioning point from the nearest preset driving distance range, the method further includes: calculating the position coordinates of the target positioning point based on an auxiliary positioning algorithm of other vehicles; The calculation of the target location coordinates using the assisted positioning algorithm based on other vehicles includes: The relative position information between the vehicle and the target neighboring vehicle is detected, and the positioning information of the target neighboring vehicle is obtained based on the vehicle-to-everything (V2X) wireless communication technology. The positioning information includes the neighboring vehicle's positioning position and the neighboring vehicle's positioning error. If the positioning error of the neighboring vehicle is less than the third positioning error threshold, the position coordinates of the target positioning point are calculated based on the relative position information and the positioning position of the neighboring vehicle.

9. The method according to claim 8, characterized in that, The relative position information includes the position coordinates of the target neighboring vehicle, the distance between the vehicle and the target neighboring vehicle, and the angle formed by the line connecting the vehicle and the target neighboring vehicle and the road direction; Calculating the position coordinates of the target location point based on the relative position information and the location of the adjacent vehicle includes: The position coordinates P of the target location point are calculated according to the third formula. A (x,y), where the third formula is P A (x,y)=P B (x,y)-(L cosα,L sinα), P B (x,y) are the position coordinates of the target neighboring vehicle, L is the distance between the vehicle and the target neighboring vehicle, and α is the included angle.

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