CN113447033A - Lane-level map matching method and system - Google Patents
Lane-level map matching method and system Download PDFInfo
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- CN113447033A CN113447033A CN202110532902.XA CN202110532902A CN113447033A CN 113447033 A CN113447033 A CN 113447033A CN 202110532902 A CN202110532902 A CN 202110532902A CN 113447033 A CN113447033 A CN 113447033A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
- G01C21/3804—Creation or updating of map data
- G01C21/3807—Creation or updating of map data characterised by the type of data
- G01C21/3815—Road data
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
- G01C21/30—Map- or contour-matching
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
- G01C21/3804—Creation or updating of map data
- G01C21/3833—Creation or updating of map data characterised by the source of data
- G01C21/3848—Data obtained from both position sensors and additional sensors
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Abstract
The invention discloses a lane-level map matching method, which comprises the following steps: acquiring positioning data and road basic data of a vehicle; carrying out data preprocessing on the positioning data of the vehicle; drawing a high-precision map according to the road basic data, and matching the lane where the vehicle is located according to the preprocessed vehicle positioning data and the high-precision map; and determining the vertical projection of the positioning position of the vehicle on the center line of the lane where the vehicle is positioned as the matching position of the vehicle on the lane. The invention solves the problems that the traditional road map matching method adopts positioning data to perform position projection on a road connecting line, so that lane information cannot be distinguished, and correction of lane-level positioning data cannot be realized, and improves the lane matching precision.
Description
Technical Field
The invention relates to the technical field of positioning navigation and Internet of vehicles, in particular to a lane-level map matching method and system.
Background
With the rapid development of computers, information technologies and electronic technologies, intelligent traffic systems have come into play, vehicles and roads are considered comprehensively, and various high-tech systems are used as the core of the current traffic field. The vehicle positioning technology is an important part of an intelligent traffic system, and accurate and complete expression of vehicle positions on an electronic map is a premise for realizing applications such as traffic guidance, traffic jam judgment, traffic control and control, vehicle monitoring and the like. Due to errors in the positioning device, the vehicle cannot be accurately positioned into the driving road in general. By using the map matching method, the driving track of the vehicle and the road network in the electronic map database can be analyzed and compared, and the route most similar to the driving track is found out on the map, so that the actual positioning data is mapped to the visual digital map.
The traditional road map matching method mainly adopts a common precision electronic map to match conventional precision positioning data. In this case, a road topology network is constructed for the road sections between the intersections, and the intersection nodes and the road links are respectively regarded as a whole. When map matching is carried out, the road to be matched is selected according to the principles of the shortest distance and the like, and the positioning data is vertically projected on a road connecting line, so that the map matching is realized. The common electronic map data and the positioning data cannot distinguish lane information, and a vehicle cannot be positioned in a specific lane by a traditional map matching method, so that the requirements of refined vehicle positioning, traffic control and road traffic information service cannot be met.
Therefore, how to distinguish the lane information and correct the lane-level positioning data becomes an urgent problem to be solved in the field.
Disclosure of Invention
The invention aims to provide a lane-level map matching method and a lane-level map matching system, which are used for solving the problems that the traditional road map matching method adopts positioning data to perform position projection on a road connecting line, so that lane information cannot be distinguished, and correction of lane-level positioning data cannot be realized.
In order to achieve the above object, the present invention provides a lane-level map matching method, including:
acquiring positioning data and road basic data of a vehicle; the positioning data comprises real-time position information and operation condition data;
carrying out data preprocessing on the positioning data of the vehicle to obtain preprocessed vehicle positioning data;
drawing a high-precision map according to the road basic data, wherein the map position error of the high-precision map is within centimeter level, and the lane can be effectively distinguished;
matching the lane where the vehicle is located according to the preprocessed vehicle positioning data and the high-precision map;
and determining the vertical projection of the positioning position of the vehicle on the center line of the lane where the vehicle is positioned as the matching position of the vehicle on the lane.
Optionally, the acquiring of the positioning data and the road basic data of the vehicle specifically includes:
acquiring real-time position information in a vehicle running process, which is acquired by Beidou submicron-grade high-precision positioning equipment, wherein the real-time position information comprises UTC time, longitude hemisphere, latitude hemisphere, vehicle running speed and direction angle; wherein, the UTC time is the sampling time of the real-time position information; longitude, latitude, longitude hemisphere and latitude hemisphere are position information of the vehicle, and are accurate to sub-meter error; the vehicle running speed is estimated by using Beidou positioning information; the direction angle is an included angle between the driving direction of the vehicle and the positive north direction;
acquiring operation condition data of a vehicle CAN bus acquired by a vehicle-mounted automatic diagnosis system, wherein the operation condition data comprises vehicle speed, engine rotating speed and steering angle of a steering wheel; the vehicle speed is the driving speed acquired by a vehicle-mounted computer system; the steering angle of the steering wheel is the steering angle of the vehicle, when the steering wheel is in the positive direction, the angle is 0, the left-turning angle of the steering wheel is a negative value, and the right-turning angle of the steering wheel is a positive value;
and acquiring road basic data acquired by the RTK equipment, wherein the road basic data is accurate to centimeter-level errors.
Optionally, data preprocessing is performed on the positioning data of the vehicle to obtain preprocessed vehicle positioning data, and the method specifically includes:
removing a plurality of repeated real-time position information in the real-time position information, and only keeping one piece of real-time position information;
eliminating speed error data which are larger than a maximum speed threshold value in the operation condition data, and performing speed compensation on a time period corresponding to the eliminated speed error data by using historical speed data and a smoothing method; the maximum speed threshold is set according to the road speed limit and the operation condition data;
when the real-time position information is not received within the sampling time, determining that the positioning data of the sampling time is missing; when the continuous positioning data is not lost more than the preset times, compensating the lost positioning data by utilizing real-time position information obtained by adjacent two sections of sampling time, wherein the speed and position coordinates in the compensated positioning data are calculated as follows:
vi＝2vi-1-vi-2 (1)
wherein (x)i,yi,vi) To compensate for the longitude, latitude, and velocity of the point, (x)i-1,yi-1,vi-1)、(xi-2,yi-2,vi-2) Respectively the longitude, latitude and speed of the first two sampling points;
calculating the average speed of the vehicle from the current sampling moment to the previous sampling moment; and eliminating the positioning data with the average speed of the vehicle being greater than the set maximum running speed, and compensating the position coordinates in the positioning data with the time content corresponding to the eliminated positioning data, wherein the calculation formulas of the position coordinates in the compensated positioning data are shown in the formulas (2) and (3).
Optionally, when the continuous positioning data is missing for more than a preset number of times, it is determined as an equipment fault or a communication fault, no compensation is performed, and a data exception or fault prompt message is sent.
Optionally, matching the lane where the vehicle is located according to the preprocessed vehicle positioning data and the high-precision map specifically includes:
performing two-dimensional coordinate projection on the real-time position information in the high-precision map to obtain a vehicle projection position;
determining a lane where the vehicle is located according to the vehicle projection position and lane line position information;
calculating the distance from the positioning point of the vehicle to the center line of the lane;
judging whether the distance is smaller than a first distance threshold value or not to obtain a first judgment result; the first distance threshold is less than half of a lane width;
when the first judgment result shows that the lane is the matched lane, determining that the lane is the matched lane in which the vehicle is located;
when the first judgment result shows that the vehicle is not the vehicle, acquiring the positioning data of continuous N sampling moments before the current sampling moment of the vehicle, wherein in a positioning data sequence of the real-time N continuous sampling moments, the distance from the first sampling moment to the center line of the lane is smaller than a second distance threshold; wherein the second distance threshold is a sufficiently small distance from the lane centerline, and the second distance threshold is much smaller than the first distance threshold;
using formulas
Calculating the average direction angle of the historical track by using a formula
Calculating average radial velocity usingFormula (II)
Calculating an average tangential velocity; wherein beta is an included angle between the advancing direction of the road lane and the positive north direction,
representing the included angle between the vehicle advancing direction and the lane line;
using formulas
Calculating the transverse movement distance L of the vehicle;
judging whether the transverse movement distance of the vehicle is greater than half of the lane width, if so, determining that the vehicle crosses the lane line and has lane changing behavior, and determining that the adjacent lane is the lane where the matched vehicle is located; and if the vehicle does not cross the lane line, determining that the current lane is the lane where the matched vehicle is located.
The present invention also provides a lane-level map matching system, the system comprising:
the data acquisition module is used for acquiring positioning data and road basic data of the vehicle; the positioning data comprises real-time position information and operation condition data;
the data preprocessing module is used for preprocessing the positioning data of the vehicle to obtain preprocessed vehicle positioning data; the system is also used for drawing a high-precision map according to the road basic data, the map position error of the high-precision map is within centimeter level, and the traffic lanes can be effectively distinguished;
the lane matching module is used for matching a lane where the vehicle is located according to the preprocessed vehicle positioning data and the high-precision map;
and the vehicle projection matching module is used for determining the vertical projection of the positioning position of the vehicle on the center line of the lane where the vehicle is positioned as the matching position of the vehicle on the lane.
Optionally, the data acquisition module specifically includes:
the Beidou submillimeter-level high-precision positioning equipment is used for acquiring real-time position information in the running process of a vehicle, and the real-time position information comprises UTC time, longitude, a longitude hemisphere, latitude, a latitude hemisphere, vehicle running speed and a direction angle; wherein, the UTC time is the sampling time of the real-time position information; longitude, latitude, longitude hemisphere and latitude hemisphere are position information of the vehicle, and are accurate to sub-meter error; the vehicle running speed is estimated by using Beidou positioning information; the direction angle is an included angle between the driving direction of the vehicle and the positive north direction;
the vehicle-mounted automatic diagnosis system is used for acquiring the operation condition data of the vehicle CAN bus, wherein the operation condition data comprises the vehicle speed, the engine rotating speed and the steering angle of a steering wheel; the vehicle speed is the driving speed acquired by a vehicle-mounted computer system; the steering angle of the steering wheel is the steering angle of the vehicle, when the steering wheel is in the positive direction, the angle is 0, the left-turning angle of the steering wheel is a negative value, and the right-turning angle of the steering wheel is a positive value;
and the RTK equipment is used for acquiring road basic data, and the road basic data is accurate to centimeter-level errors.
Optionally, the data preprocessing module specifically includes:
the redundant data removing unit is used for removing a plurality of repeated real-time position information in the real-time position information and only keeping one piece of real-time position information;
the speed error data removing and compensating unit is used for removing the speed error data which is larger than the maximum speed threshold value in the operation working condition data, and performing speed compensation on the time section corresponding to the removed speed error data by using historical speed data and adopting a smoothing method; the maximum speed threshold is set according to the road speed limit and the operation condition data;
the data missing compensation unit is used for determining that the positioning data of the sampling time is missing when the real-time position information is not received in the sampling time; when the continuous positioning data is not lost more than the preset times, compensating the lost positioning data by utilizing real-time position information obtained by adjacent two sections of sampling time, wherein the speed and position coordinates in the compensated positioning data are calculated as follows:
vi＝2vi-1-vi-2 (1)
wherein (x)i,yi,vi) To compensate for the longitude, latitude, and velocity of the point, (x)i-1,yi-1,vi-1)、(xi-2,yi-2,vi-2) Respectively the longitude, latitude and speed of the first two sampling points;
the positioning error data eliminating and compensating unit is used for calculating the average speed of the vehicle from the current sampling moment to the previous sampling moment; and eliminating the positioning data with the average speed of the vehicle being greater than the set maximum running speed, and compensating the position coordinates in the positioning data with the time content corresponding to the eliminated positioning data, wherein the calculation formulas of the position coordinates in the compensated positioning data are shown in the formulas (2) and (3).
Optionally, the lane matching module specifically includes:
the coordinate projection unit is used for carrying out two-dimensional coordinate projection on the real-time position information in the high-precision map to obtain a vehicle projection position;
the positioning lane unit is used for determining a lane where the vehicle is located according to the vehicle projection position and lane line position information;
the distance calculation unit is used for calculating the distance from the positioning point of the vehicle to the center line of the lane;
the first lane judging unit is used for judging whether the distance is smaller than a first distance threshold value or not to obtain a first judgment result; the first distance threshold is less than half of a lane width;
when the first judgment result shows that the lane is the matched lane, determining that the lane is the matched lane in which the vehicle is located;
when the first judgment result shows that the vehicle is not the vehicle, acquiring the positioning data of continuous N sampling moments before the current sampling moment of the vehicle, wherein in a positioning data sequence of the real-time N continuous sampling moments, the distance from the first sampling moment to the center line of the lane is smaller than a second distance threshold; wherein the second distance threshold is a sufficiently small distance from the lane centerline, and the second distance threshold is much smaller than the first distance threshold;
a second lane discriminating unit for using the formula
Calculating the average direction angle of the historical track by using a formula
Calculating the average radial velocity using the formula
Calculating an average tangential velocity; wherein beta is an included angle between the advancing direction of the road lane and the positive north direction,
representing the included angle between the vehicle advancing direction and the lane line;
using formulas
Calculating the transverse movement distance L of the vehicle;
judging whether the transverse movement distance of the vehicle is greater than half of the lane width, if so, determining that the vehicle crosses the lane line and has lane changing behavior, and determining that the adjacent lane is the lane where the matched vehicle is located; and if the vehicle does not cross the lane line, determining that the current lane is the lane where the matched vehicle is located.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the lane-level map matching method and the lane-level map matching system provided by the invention utilize high-precision positioning equipment to acquire continuous real-time position information and running condition data of the vehicle in real time, select the lane where the vehicle is located, and perform vertical projection map matching according to the selected lane. The invention provides a feasible map matching method for lane-level positioning, can effectively reduce the vehicle position drift phenomenon caused by positioning errors, and has important significance for the application in the fields of lane-level vehicle navigation, fine traffic management and control and the like.
In addition, the invention provides a vehicle lane-level positioning method based on fusion of positioning equipment data and vehicle running data, which can effectively prevent the phenomenon of vehicle position error caused by positioning and inertial navigation equipment errors, greatly improve the positioning accuracy and has strong robustness.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of a lane-level map matching method according to an embodiment of the present invention;
FIG. 2 is a flow chart of lane matching according to the present invention;
FIG. 3 is a schematic diagram showing a distance relationship between a positioning point of a vehicle and a lane center line according to the present invention;
FIG. 4 is a schematic diagram of the lane-level matching of the vehicle according to the present invention;
fig. 5 is a block diagram of a lane-level map matching system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a lane-level map matching method and a lane-level map matching system, which are used for solving the problems that the traditional road map matching method adopts positioning data to perform position projection on a road connecting line, so that lane information cannot be distinguished, and correction of lane-level positioning data cannot be realized.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
As shown in fig. 1, the lane-level map matching method provided by the present embodiment includes:
step 101: acquiring positioning data and road basic data of a vehicle; the positioning data comprises real-time position information and operation condition data;
the acquisition of the positioning data of the vehicle and the road basic data in this step determines the accuracy of the whole lane matching. Therefore, the specific method for acquiring the positioning data and the road basic data of the vehicle in the embodiment may be as follows:
acquiring real-time position information in a vehicle running process, which is acquired by Beidou submicron-grade high-precision positioning equipment, wherein the real-time position information comprises UTC time, longitude hemisphere, latitude hemisphere, vehicle running speed and direction angle; wherein, the UTC time is the sampling time of the real-time position information; longitude, latitude, longitude hemisphere and latitude hemisphere are position information of the vehicle, and are accurate to sub-meter error; the vehicle running speed is estimated by using Beidou positioning information; the direction angle is an included angle between the driving direction of the vehicle and the positive north direction;
acquiring operation condition data of a vehicle CAN bus acquired by a vehicle-mounted automatic diagnosis system, wherein the operation condition data comprises vehicle speed, engine rotating speed and steering angle of a steering wheel; the vehicle speed is the driving speed acquired by a vehicle-mounted computer system; the steering angle of the steering wheel is the steering angle of the vehicle, when the steering wheel is in the positive direction, the angle is 0, the left-turning angle of the steering wheel is a negative value, and the right-turning angle of the steering wheel is a positive value;
and acquiring road basic data acquired by the RTK equipment, wherein the road basic data is accurate to centimeter-level errors. The error level can effectively distinguish lanes.
Step 102: carrying out data preprocessing on the positioning data of the vehicle to obtain preprocessed vehicle positioning data;
the step 102 may specifically include:
(1) and (3) redundant data elimination: in the actual acquisition process, a plurality of pieces of repeated positioning data acquired at the same time may appear, so that a plurality of pieces of repeated real-time position information in the real-time position information need to be removed, and only one piece of real-time position information is reserved.
(2) Speed error data culling and compensating: the wrong speed data may be deviation caused by instantaneous acquisition, so that a maximum speed threshold value can be set according to the road speed limit and the vehicle running condition data, the speed wrong data which are larger than the maximum speed threshold value in the running condition data are eliminated, and the historical speed data are utilized to perform speed compensation on the time period corresponding to the eliminated speed wrong data by adopting a smoothing method. To reduce the influence of erroneous data on the lane matching accuracy.
(3) And (3) positioning data missing compensation:
when the real-time position information is not received within the sampling time, determining that the positioning data of the sampling time is missing; when the continuous positioning data is missing for no more than 3 times, the missing positioning data is compensated by utilizing real-time position information obtained by adjacent two sampling time segments, and the speed and position coordinates in the compensated positioning data are calculated as follows:
vi＝2vi-1-vi-2 (1)
wherein (x)i,yi,vi) To compensate for the longitude, latitude, and velocity of the point, (x)i-1,yi-1,vi-1)、(xi-2,yi-2,vi-2) Respectively the longitude, latitude and speed of the first two sampling points;
and when the continuous positioning data is missing for more than 3 times, judging that the equipment fault or the communication fault occurs, not compensating, and prompting data abnormity by the system. Equipment maintenance work is started to avoid the impact of improper compensation on lane matching.
(4) Removing and compensating positioning error data:
and setting an effective range of the reserved route according to the historical data, judging that the reserved route is positioned wrongly if the reserved route exceeds the effective range, and rejecting wrong data and compensating. The determination method adopted in the present embodiment is as follows:
calculating the average speed of the vehicle from the current sampling moment to the previous sampling moment:
wherein the coordinates of the vehicle at the time T are
The coordinates of the vehicle at the previous moment T-T are
t is a GPS data receiving interval;
rejecting positioning data with the average speed of the vehicle being greater than a set maximum driving speed:
ΔvT＞V (5)
wherein, V is a driving speed threshold value (including a positioning error);
and (3) compensating the position coordinates in the positioning data of the time content corresponding to the elimination positioning data, wherein the calculation formulas of the position coordinates in the compensated positioning data are expressed by the formulas (2) and (3).
Step 103: drawing a high-precision map according to the road basic data, wherein the map position error of the high-precision map is within centimeter level, and the lane can be effectively distinguished;
step 104: matching the lane where the vehicle is located according to the preprocessed vehicle positioning data and the high-precision map;
as shown in fig. 2, the flow of step 104 is specifically as follows:
step 1: recognizing the lane: performing two-dimensional coordinate projection on the real-time position information in the high-precision map to obtain a vehicle projection position; determining a lane where the vehicle is located according to the vehicle projection position and lane line position information; that is, when the real-time positioning coordinates of the vehicle are located between two lane lines of the lane, it is determined that the positioning point of the vehicle at the time belongs to the lane.
Step 2: calculating the distance from the positioning point to the center line of the lane: and making a perpendicular line perpendicular to the lane direction through the positioning point, and calculating the distance d from the positioning point to the center line of the lane according to the coordinates of the positioning point and the basic geographic position information of the lane, as shown in fig. 3.
Step 3: judging the lane to be matched for one time: setting a first distance threshold
dLIs the lane width. If it is
Determining the lane where the vehicle is located as the matched lane where the vehicle is located; if it is
Step4 is executed to perform secondary judgment of the lane to be matched.
Step 4: and (3) secondary judgment of the lane to be matched:
(1) reading historical running track data of the vehicle: reading data of continuous N sampling points before the current sampling point of the vehicle,including the position coordinates (x) of the vehiclei,yi) Angle of orientation alphaiVelocity vi. In a positioning data sequence of real-time N continuous sampling moments, reading the distance d from the center line of a lane at the first sampling moment1Less than a second distance threshold
Namely, it is
Wherein the content of the first and second substances,
is a sufficiently small distance from the center line of the lane, and
(2) calculating the average direction angle, the average radial speed and the average tangential speed of the historical track:
the average direction angle of the historical travel track is calculated as shown in formula (6), the average radial velocity is calculated as shown in formula (7), and the average tangential velocity is calculated as shown in formula (8).
Wherein beta is an included angle between the advancing direction of the road lane and the positive north direction,
representing the angle of the vehicle's direction of travel with the lane line.
(3) Judging the state of crossing lane lines:
calculating the lateral movement distance of the vehicle as shown in formula (9):
when in use
And judging that the vehicle does not cross the lane line and still runs on the lane, namely the lane is the lane to be matched.
When in use
And judging that the vehicle crosses the lane line, the lane changing behavior exists, and the lane to be matched is an adjacent lane.
The lane matching method is simple and accurate in lane matching by converting the positioning points of the vehicles and matching the lane according to the distance between the positioning points and the center line of the lane and the size relationship between the first distance threshold and the second distance threshold.
Step 105: and determining the vertical projection of the positioning position of the vehicle on the center line of the lane where the vehicle is positioned as the matching position of the vehicle on the lane, as shown in fig. 4.
The lane-level map matching method provided by the embodiment utilizes the integration of the high-precision positioning data of the vehicle and the direction information of the vehicle, realizes the accurate lane identification and position matching under the high-precision map aiming at the lane-level positioning requirement, and provides reliable support for upper-layer traffic application technologies such as lane-level positioning, vehicle path navigation and accurate traffic management and control.
As shown in fig. 5, the present embodiment further provides a system corresponding to the lane-level map matching method described above, the system including:
the data acquisition module is used for acquiring positioning data and road basic data of the vehicle; the positioning data comprises real-time position information and operation condition data;
the data preprocessing module is used for preprocessing the positioning data of the vehicle to obtain preprocessed vehicle positioning data; the system is also used for drawing a high-precision map according to the road basic data, the map position error of the high-precision map is within centimeter level, and the traffic lanes can be effectively distinguished;
the lane matching module is used for matching a lane where the vehicle is located according to the preprocessed vehicle positioning data and the high-precision map;
and the vehicle projection matching module is used for determining the vertical projection of the positioning position of the vehicle on the center line of the lane where the vehicle is positioned as the matching position of the vehicle on the lane.
Specifically, the data acquisition module specifically includes:
the Beidou submillimeter-level high-precision positioning equipment is used for acquiring real-time position information in the running process of a vehicle, and the real-time position information comprises UTC time, longitude, a longitude hemisphere, latitude, a latitude hemisphere, vehicle running speed and a direction angle; wherein, the UTC time is the sampling time of the real-time position information; longitude, latitude, longitude hemisphere and latitude hemisphere are position information of the vehicle, and are accurate to sub-meter error; the vehicle running speed is estimated by using Beidou positioning information; the direction angle is an included angle between the driving direction of the vehicle and the positive north direction;
the vehicle-mounted automatic diagnosis system is used for acquiring the operation condition data of the vehicle CAN bus, wherein the operation condition data comprises the vehicle speed, the engine rotating speed and the steering angle of a steering wheel; the vehicle speed is the driving speed acquired by a vehicle-mounted computer system; the steering angle of the steering wheel is the steering angle of the vehicle, when the steering wheel is in the positive direction, the angle is 0, the left-turning angle of the steering wheel is a negative value, and the right-turning angle of the steering wheel is a positive value;
and the RTK equipment is used for acquiring road basic data, and the road basic data is accurate to centimeter-level errors.
The data preprocessing module specifically comprises:
the redundant data removing unit is used for removing a plurality of repeated real-time position information in the real-time position information and only keeping one piece of real-time position information;
the speed error data removing and compensating unit is used for removing the speed error data which is larger than the maximum speed threshold value in the operation working condition data, and performing speed compensation on the time section corresponding to the removed speed error data by using historical speed data and adopting a smoothing method; the maximum speed threshold is set according to the road speed limit and the operation condition data;
the data missing compensation unit is used for determining that the positioning data of the sampling time is missing when the real-time position information is not received in the sampling time; when the continuous positioning data is not lost more than the preset times, compensating the lost positioning data by utilizing real-time position information obtained by adjacent two sections of sampling time, wherein the speed and position coordinates in the compensated positioning data are calculated as follows:
vi＝2vi-1-vi-2 (1)
wherein (x)i,yi,vi) To compensate for the longitude, latitude, and velocity of the point, (x)i-1,yi-1,vi-1)、(xi-2,yi-2,vi-2) Respectively the longitude, latitude and speed of the first two sampling points;
the positioning error data eliminating and compensating unit is used for calculating the average speed of the vehicle from the current sampling moment to the previous sampling moment; and eliminating the positioning data with the average speed of the vehicle being greater than the set maximum running speed, and compensating the position coordinates in the positioning data with the time content corresponding to the eliminated positioning data, wherein the calculation formulas of the position coordinates in the compensated positioning data are shown in the formulas (2) and (3).
The lane matching module specifically comprises:
the coordinate projection unit is used for carrying out two-dimensional coordinate projection on the real-time position information in the high-precision map to obtain a vehicle projection position;
the positioning lane unit is used for determining a lane where the vehicle is located according to the vehicle projection position and lane line position information;
the distance calculation unit is used for calculating the distance from the positioning point of the vehicle to the center line of the lane;
the first lane judging unit is used for judging whether the distance is smaller than a first distance threshold value or not to obtain a first judgment result; the first distance threshold is less than half of a lane width;
when the first judgment result shows that the lane is the matched lane, determining that the lane is the matched lane in which the vehicle is located;
when the first judgment result shows that the vehicle is not the vehicle, acquiring the positioning data of continuous N sampling moments before the current sampling moment of the vehicle, wherein in a positioning data sequence of the real-time N continuous sampling moments, the distance from the first sampling moment to the center line of the lane is smaller than a second distance threshold; wherein the second distance threshold is a sufficiently small distance from the lane centerline, and the second distance threshold is much smaller than the first distance threshold;
a second lane discriminating unit for using the formula
Calculating the average direction angle of the historical track by using a formula
Calculating the average radial velocity using the formula
Calculating an average tangential velocity; wherein beta is an included angle between the advancing direction of the road lane and the positive north direction,
representing the included angle between the vehicle advancing direction and the lane line;
using formulas
Calculating the transverse movement distance L of the vehicle;
judging whether the transverse movement distance of the vehicle is greater than half of the lane width, if so, determining that the vehicle crosses the lane line and has lane changing behavior, and determining that the adjacent lane is the lane where the matched vehicle is located; and if the vehicle does not cross the lane line, determining that the current lane is the lane where the matched vehicle is located.
For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (9)
1. A lane-level map matching method, the method comprising:
acquiring positioning data and road basic data of a vehicle; the positioning data comprises real-time position information and operation condition data;
carrying out data preprocessing on the positioning data of the vehicle to obtain preprocessed vehicle positioning data;
drawing a high-precision map according to the road basic data, wherein the map position error of the high-precision map is within centimeter level, and the lane can be effectively distinguished;
matching the lane where the vehicle is located according to the preprocessed vehicle positioning data and the high-precision map;
and determining the vertical projection of the positioning position of the vehicle on the center line of the lane where the vehicle is positioned as the matching position of the vehicle on the lane.
2. The lane-level map matching method according to claim 1, wherein the acquiring of the positioning data and the road basic data of the vehicle specifically comprises:
acquiring real-time position information in a vehicle running process, which is acquired by Beidou submicron-grade high-precision positioning equipment, wherein the real-time position information comprises UTC time, longitude hemisphere, latitude hemisphere, vehicle running speed and direction angle; wherein, the UTC time is the sampling time of the real-time position information; longitude, latitude, longitude hemisphere and latitude hemisphere are position information of the vehicle, and are accurate to sub-meter error; the vehicle running speed is estimated by using Beidou positioning information; the direction angle is an included angle between the driving direction of the vehicle and the positive north direction;
acquiring operation condition data of a vehicle CAN bus acquired by a vehicle-mounted automatic diagnosis system, wherein the operation condition data comprises vehicle speed, engine rotating speed and steering angle of a steering wheel; the vehicle speed is the driving speed acquired by a vehicle-mounted computer system; the steering angle of the steering wheel is the steering angle of the vehicle, when the steering wheel is in the positive direction, the angle is 0, the left-turning angle of the steering wheel is a negative value, and the right-turning angle of the steering wheel is a positive value;
and acquiring road basic data acquired by the RTK equipment, wherein the road basic data is accurate to centimeter-level errors.
3. The lane-level map matching method according to claim 1, wherein the data preprocessing is performed on the positioning data of the vehicle to obtain preprocessed vehicle positioning data, and specifically comprises:
removing a plurality of repeated real-time position information in the real-time position information, and only keeping one piece of real-time position information;
eliminating speed error data which are larger than a maximum speed threshold value in the operation condition data, and performing speed compensation on a time period corresponding to the eliminated speed error data by using historical speed data and a smoothing method; the maximum speed threshold is set according to the road speed limit and the operation condition data;
when the real-time position information is not received within the sampling time, determining that the positioning data of the sampling time is missing; when the continuous positioning data is not lost more than the preset times, compensating the lost positioning data by utilizing real-time position information obtained by adjacent two sections of sampling time, wherein the speed and position coordinates in the compensated positioning data are calculated as follows:
vi＝2vi-1-vi-2 (1)
wherein (x)i,yi,vi) To compensate for the longitude, latitude, and velocity of the point, (x)i-1,yi-1,vi-1)、(xi-2,yi-2,vi-2) Respectively the longitude, latitude and speed of the first two sampling points;
calculating the average speed of the vehicle from the current sampling moment to the previous sampling moment; and eliminating the positioning data with the average speed of the vehicle being greater than the set maximum running speed, and compensating the position coordinates in the positioning data with the time content corresponding to the eliminated positioning data, wherein the calculation formulas of the position coordinates in the compensated positioning data are shown in the formulas (2) and (3).
4. The lane-level map matching method according to claim 3, wherein when the continuous lack of the positioning data exceeds a preset number, it is determined that there is an equipment failure or a communication failure, and no compensation is performed, and a data abnormality or failure prompt message is issued.
5. The lane-level map matching method according to claim 1, wherein the matching of the lane where the vehicle is located according to the preprocessed vehicle positioning data and the high-precision map specifically comprises:
performing two-dimensional coordinate projection on the real-time position information in the high-precision map to obtain a vehicle projection position;
determining a lane where the vehicle is located according to the vehicle projection position and lane line position information;
calculating the distance from the positioning point of the vehicle to the center line of the lane;
judging whether the distance is smaller than a first distance threshold value or not to obtain a first judgment result; the first distance threshold is less than half of a lane width;
when the first judgment result shows that the lane is the matched lane, determining that the lane is the matched lane in which the vehicle is located;
when the first judgment result shows that the vehicle is not the vehicle, acquiring the positioning data of continuous N sampling moments before the current sampling moment of the vehicle, wherein in a positioning data sequence of the real-time N continuous sampling moments, the distance from the first sampling moment to the center line of the lane is smaller than a second distance threshold; wherein the second distance threshold is a sufficiently small distance from the lane centerline, and the second distance threshold is much smaller than the first distance threshold;
using formulas
Calculating the average direction angle of the historical track by using a formula
Calculating the average radial velocity using the formula
Calculating an average tangential velocity; wherein beta is an included angle between the advancing direction of the road lane and the positive north direction,
representing the included angle between the vehicle advancing direction and the lane line;
using formulas
Calculating the transverse movement distance L of the vehicle;
judging whether the transverse movement distance of the vehicle is greater than half of the lane width, if so, determining that the vehicle crosses the lane line and has lane changing behavior, and determining that the adjacent lane is the lane where the matched vehicle is located; and if the vehicle does not cross the lane line, determining that the current lane is the lane where the matched vehicle is located.
6. A lane-level map matching system, the system comprising:
the data acquisition module is used for acquiring positioning data and road basic data of the vehicle; the positioning data comprises real-time position information and operation condition data;
the data preprocessing module is used for preprocessing the positioning data of the vehicle to obtain preprocessed vehicle positioning data; the system is also used for drawing a high-precision map according to the road basic data, the map position error of the high-precision map is within centimeter level, and the traffic lanes can be effectively distinguished;
the lane matching module is used for matching a lane where the vehicle is located according to the preprocessed vehicle positioning data and the high-precision map;
and the vehicle projection matching module is used for determining the vertical projection of the positioning position of the vehicle on the center line of the lane where the vehicle is positioned as the matching position of the vehicle on the lane.
7. The lane-level map matching system of claim 6, wherein the data acquisition module specifically comprises:
the Beidou submillimeter-level high-precision positioning equipment is used for acquiring real-time position information in the running process of a vehicle, and the real-time position information comprises UTC time, longitude, a longitude hemisphere, latitude, a latitude hemisphere, vehicle running speed and a direction angle; wherein, the UTC time is the sampling time of the real-time position information; longitude, latitude, longitude hemisphere and latitude hemisphere are position information of the vehicle, and are accurate to sub-meter error; the vehicle running speed is estimated by using Beidou positioning information; the direction angle is an included angle between the driving direction of the vehicle and the positive north direction;
the vehicle-mounted automatic diagnosis system is used for acquiring the operation condition data of the vehicle CAN bus, wherein the operation condition data comprises the vehicle speed, the engine rotating speed and the steering angle of a steering wheel; the vehicle speed is the driving speed acquired by a vehicle-mounted computer system; the steering angle of the steering wheel is the steering angle of the vehicle, when the steering wheel is in the positive direction, the angle is 0, the left-turning angle of the steering wheel is a negative value, and the right-turning angle of the steering wheel is a positive value;
and the RTK equipment is used for acquiring road basic data, and the road basic data is accurate to centimeter-level errors.
8. The lane-level map matching system of claim 6, wherein the data preprocessing module specifically comprises:
the redundant data removing unit is used for removing a plurality of repeated real-time position information in the real-time position information and only keeping one piece of real-time position information;
the speed error data removing and compensating unit is used for removing the speed error data which is larger than the maximum speed threshold value in the operation working condition data, and performing speed compensation on the time section corresponding to the removed speed error data by using historical speed data and adopting a smoothing method; the maximum speed threshold is set according to the road speed limit and the operation condition data;
the data missing compensation unit is used for determining that the positioning data of the sampling time is missing when the real-time position information is not received in the sampling time; when the continuous positioning data is not lost more than the preset times, compensating the lost positioning data by utilizing real-time position information obtained by adjacent two sections of sampling time, wherein the speed and position coordinates in the compensated positioning data are calculated as follows:
vi＝2vi-1-vi-2 (1)
wherein (x)i,yi,vi) To compensate for the longitude, latitude, and velocity of the point, (x)i-1,yi-1,vi-1)、(xi-2,yi-2,vi-2) Respectively the longitude, latitude and speed of the first two sampling points;
the positioning error data eliminating and compensating unit is used for calculating the average speed of the vehicle from the current sampling moment to the previous sampling moment; and eliminating the positioning data with the average speed of the vehicle being greater than the set maximum running speed, and compensating the position coordinates in the positioning data with the time content corresponding to the eliminated positioning data, wherein the calculation formulas of the position coordinates in the compensated positioning data are shown in the formulas (2) and (3).
9. The lane-level map matching system of claim 6, wherein the lane matching module specifically comprises:
the coordinate projection unit is used for carrying out two-dimensional coordinate projection on the real-time position information in the high-precision map to obtain a vehicle projection position;
the positioning lane unit is used for determining a lane where the vehicle is located according to the vehicle projection position and lane line position information;
the distance calculation unit is used for calculating the distance from the positioning point of the vehicle to the center line of the lane;
the first lane judging unit is used for judging whether the distance is smaller than a first distance threshold value or not to obtain a first judgment result; the first distance threshold is less than half of a lane width;
when the first judgment result shows that the lane is the matched lane, determining that the lane is the matched lane in which the vehicle is located;
when the first judgment result shows that the vehicle is not the vehicle, acquiring the positioning data of continuous N sampling moments before the current sampling moment of the vehicle, wherein in a positioning data sequence of the real-time N continuous sampling moments, the distance from the first sampling moment to the center line of the lane is smaller than a second distance threshold; wherein the second distance threshold is a sufficiently small distance from the lane centerline, and the second distance threshold is much smaller than the first distance threshold;
a second lane discriminating unit for using the formula
Calculating the average direction angle of the historical track by using a formula
Calculating the average radial velocity using the formula
Calculating an average tangential velocity; wherein beta is an included angle between the advancing direction of the road lane and the positive north direction,
representing the included angle between the vehicle advancing direction and the lane line;
using formulas
Calculating the transverse movement distance L of the vehicle;
judging whether the transverse movement distance of the vehicle is greater than half of the lane width, if so, determining that the vehicle crosses the lane line and has lane changing behavior, and determining that the adjacent lane is the lane where the matched vehicle is located; and if the vehicle does not cross the lane line, determining that the current lane is the lane where the matched vehicle is located.
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