CN115265557B - Map matching positioning and deviation line judging method - Google Patents
Map matching positioning and deviation line judging method Download PDFInfo
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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
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- G—PHYSICS
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Abstract
The invention discloses a map matching positioning and deviation line judging method, and belongs to the field of intelligent traffic. The method comprises the following steps: traversing a reference route of a map to be detected by using a sliding window, extracting peak distances of all road sections, and forming map discrete features; meanwhile, aiming at turning conditions, turning characteristics of all road sections are advanced; then, respectively extracting real-time discrete features and turning features of the vehicle from the real-time running actual road of the vehicle; the location of the vehicle is determined based on the discrete features and the turning features matching the vehicle travel trajectory to the map road. Finally, the real-time discrete characteristics of the vehicle are utilized to judge whether the vehicle deviates from the designated route. Under the condition of no satellite navigation measurement, the invention only uses the trajectory of the odometer and the low-cost gyroscope for driving in a short time when the vehicle turns, extracts the key characteristics of the actual driving trajectory and the map route, performs matching and vehicle position correction, and has the characteristics of low cost and full-automatic positioning.
Description
Technical Field
The invention belongs to the field of intelligent traffic, and relates to a map matching positioning and deviation line judging method.
Background
The vehicle positioning technology has important significance in the field of intelligent transportation and location-based services.
The existing vehicle positioning is mainly based on satellite navigation, and under the condition that satellite navigation signals cannot be effectively received by urban building groups, valleys or tunnels, the satellite navigation system cannot realize effective positioning, so that difficulties are caused to the development of vehicle monitoring, position service and other works.
The vehicle positioning technology based on map matching utilizes the determined shape of the vehicle running road and the actual running track of the vehicle to match, and can realize autonomous positioning under the condition of no satellite navigation.
The existing map matching algorithm is matched with the turning condition of the route in the map according to the turning position and the turning angle of the vehicle in the running process, so that the matching can be truly completed under the simple condition of urban intersections and the like, but an effective matching method is lacking in the condition of no fixed-shape turning in road sections.
In the case where there is no clear intersection such as a suburban road, the non-intersection turning road characteristics cannot be used for effective matching, and long-time error accumulation occurs in calculation of the vehicle mileage and speed sensor by the odometer or the like, so that autonomous positioning accuracy is significantly lowered. Furthermore, without satellite positioning, there is a complexity in algorithm design to determine if the vehicle deviates from a specified route due to the lack of a direct positioning reference.
Disclosure of Invention
Aiming at the defects of the autonomous positioning method for map matching of the vehicle, the invention provides a method for map matching positioning and deviation line judgment, which is used for extracting discrete and integral features of road shapes so as to realize the expression of key shapes of the road, extracting the same features of real-time running tracks of the vehicle on the basis, and realizing the vehicle matching positioning by utilizing any turning on the basis of the design of a matching algorithm. According to the method, satellite navigation data are not utilized, and the deviation route judgment can be realized only by using whether the road characteristics extracted in the designated section are matched with the vehicle running track characteristics or not; the invention can be realized by only using the vehicle odometer and the low-cost rate gyroscope, and has the advantages of low cost, simple operation and the like.
The map matching positioning and deviation line judging method is realized by the following steps:
Step one, traversing a route track by using a sliding window with a specified length according to a map reference route track to be tested, setting the distance direction from a road section inner point to a reference straight line by taking a road section origin-destination connecting line vector as a reference according to the route shape in each sliding window, and extracting the peak value distance to form discrete features in the road section.
Step two, setting a sliding window with a specified track length according to the turning condition of the map reference route, and setting indexes such as a turning angle algebraic sum, a turning angle absolute value sum, a turning road section length and the like in the window to form turning characteristics of the road section route.
And thirdly, on the actual road corresponding to the map reference route track, the vehicle runs in real time, and the discrete feature and the turning feature are extracted from the track of the vehicle running in real time according to the extraction method of the discrete feature and the turning feature of the map route.
And step four, matching the actual running route of the vehicle with the map reference route by utilizing the real-time discrete features and turning features of each road section of the vehicle and the discrete features and turning features of each road section of the map to determine the position of the vehicle.
And fifthly, on the basis of map matching and positioning, judging whether the vehicle deviates from a specified route or not by utilizing real-time discrete features of the vehicle.
The invention has the advantages and positive effects that:
(1) The invention provides a map matching positioning and deviation line judging method, which is simple and easy to implement and low in cost, and can realize the matching of any turning road sections by extracting road section characteristics, and the key reference positioning points are determined by utilizing the road characteristics while the turning road sections are matched, so that the autonomous positioning accuracy of the vehicle is improved by the key point matching;
(2) The invention relates to a map matching positioning and deviation line judging method, which is a judging method for judging whether a vehicle deviates from a specified line or not based on track and road matching characteristics, and has universality;
(3) According to the map matching positioning and deviation line judging method, the measurement precision of the low-precision inertial device is considered, the autonomous positioning function can be realized by using the odometer and the low-cost inertial device, and the positioning precision is ensured; the operation is simple, and the popularization and the use are easy.
Drawings
FIG. 1 is a flow chart of a map matching location and deviation route determination method of the present invention;
FIG. 2 is a schematic diagram of a feature extraction area of a current road segment trajectory to be measured according to the present invention;
FIG. 3 is a schematic illustration of the definition of the trace points in the upper and lower half planes of the present invention;
Fig. 4 is a definition of the turning angle of the present invention.
Detailed Description
The technical scheme of the invention is described below with reference to the accompanying drawings.
The invention discloses a map matching positioning and deviation line judging method, which comprises the steps of extracting track discrete features of road sections of a map route and actual running road sections of a vehicle and extracting turning features; matching the vehicle running track based on the discrete features with the map road; matching the vehicle running track based on the turning characteristics with a map road; and determining that the vehicle is off-course. The invention only utilizes the odometer and the low-cost gyroscope to extract the key characteristic parameter information of the actual running track and the geometric shape of the route on the basis of the calculation of the short-time running track of the vehicle turning, designs the road section matching and vehicle position correction algorithm based on the characteristic parameters, and can continuously position the vehicle under the condition of not having satellite navigation measurement. Meanwhile, a deviation route judging method without accurate position of the vehicle is designed based on discrete characteristics of roads and running tracks. The method has the characteristics of low cost and full-automatic positioning, has the capability of independently completing navigation positioning and judging whether the vehicle runs according to a plan, and can meet the application requirements of special vehicles and special environments with limited satellite navigation.
As shown in fig. 1, the method comprises the following steps:
step one: extracting discrete features of a route to be detected on a map;
The method comprises the following steps: traversing the track of the route to be tested on the map by using sliding windows with specified lengths, setting the distance direction from the point in the road section to the reference straight line by taking the line vector of the origin and destination points of the road section as a reference for the shape of the route in each sliding window, and extracting the peak value distance to form the discrete feature in the road section.
Firstly, selecting a reference road section;
As shown in fig. 2, for the current path track AB traversed by the sliding window, the path starting from the point a is integrated, and if the integrated length of the path between AB is equal to the set path length L d, the path section AB is taken as the reference path section. A is taken as a starting point B as an end point, and a connecting line between the AB is taken as a reference straight line.
Then, extracting the distance from each track point on the road section to a reference line AB under a space three-dimensional coordinate system, and extracting the peak value distance as a discrete feature;
and taking the map coordinate system as a reference, if the map route is longitude and latitude coordinates, converting the map route into plane rectangular coordinates or space three-dimensional coordinates by using a UTM (universal time-series) coordinate conversion method, and then carrying out subsequent feature calculation.
1) Judging the relative position of the track point C;
And taking the AB vector as a reference direction, B' as a point on the extension line along the BA direction, and defining the angular position reached by the AB rotating by less than 180 degrees along the anticlockwise direction as an upper half plane and the angular position reached by the AB rotating by less than 180 degrees along the clockwise direction as a lower half plane.
As shown in fig. 3, α 1 is the angle of the AB vector relative to the horizontal axis in rectangular coordinates, if C is any point in the coordinate system and the deflection angle of the AC vector is defined as α 2 in the case where the value interval of the AB deflection angle is [ -pi, pi ], the condition for determining that C is in the upper half plane is:
when alpha 1 is more than or equal to 0, the judgment condition that the C point is positioned on the upper half plane is as follows:
When alpha 1 is less than 0, the judgment condition that the C point is positioned on the upper half plane is as follows:
α2∈[α1,π+α1]
2) Calculating the distance d from the C point to the AB line segment c
If the C point is located on the upper half plane
If the C point is located in the lower half plane
(K A,YA) is the coordinates of point A; (X C,YC) is the coordinates of point C;
3) Recording the peak value and position of the distance from C point to line segment AB
The arc length of the AC segment of the actual route is denoted by l AC, the local extremum is recorded for d c, and the following discrete feature vectors within the AB segment are composed:
(lAC1,dc1),(lAC2,dc2),(lAC3,dc3),…(lAC,dcn),(lACmax,dcmax),(lACmin,dcmin)
Wherein (l ACn,dcn) represents the position and specific distance value of the nth extremum, and the sign of d cn represents the positive half plane or the negative half plane of the C point, (l ACmax,dcmax) is the position and specific distance value of the maximum distance point from the AB line segment in the positive half plane road segment, (l ACmin,dcmin) is the position and specific distance value of the maximum distance point from the AB line segment in the negative half plane, and (l ACmax,dcmax)、(lACmin,dcmin) does not appear repeatedly in the previous n local extremums.
In use, the number of n is related to the set road segment length L d, where n may be set to 3 in the case of L < 1000 meters. In practical use, the upper limit of n can be set, and when the number of the local extremum is greater than n, the extremum information of the first n is reserved except the global extremum of the upper half and the lower half.
Step two, extracting turning characteristics of a route to be detected on the map;
The method comprises the following steps: setting a sliding window with a specified track length according to the turning condition of the route, setting a turning angle algebraic sum, a turning angle absolute value sum, a turning road section length and other indexes in the window, and forming characteristic parameters of the turning shape of the route to be tested.
The specific process of counting the turning characteristic parameters of the route in the designated route length L a is as follows:
1) Definition of the turning angle symbol
Referring to the defined mode of the satellite navigation system, the rotational angular rate of the vehicle is positive in the clockwise direction and negative in the counterclockwise direction.
2) Calculating turning angle information
The calculation step length L a-step is set, the step length L a-step is taken as the route stepping distance, the included angle between the adjacent two start and stop point vectors is calculated, as shown in fig. 4, the vector deflection angle from the road segment P k+1Pk+2 to the road segment P k+2Pk+3 is denoted by a k+2, and the angle is positive value when a k+2 rotates clockwise.
3) Determining the start and end points of a turn
The turning angle determination threshold value alpha threshold is set, and if the turning angle of the continuous L steps L a-ste step road segment vector is smaller than the threshold value alpha threshold, the turning is considered to be finished or the route is not turned. This example sets α threshold, L and L a-step to 3 degrees, 3 and 5 meters, respectively. The turning ending point is taken as the ending point of the last step L a-ste, and the turning starting point is taken as the starting point of the first L a-ste road section exceeding the threshold alpha threshold.
4) Calculating turning characteristic value
After obtaining the turning starting point and the turning ending point, if m turning sections are provided, and the turning starting point is k, the turning characteristic value comprises the following contents:
① Absolute value sum of turning angles
Alpha k+i is the k+i turning angle value;
② Algebraic sum of turning angles
③ Distance of turning
Lsum＝mLa-st
④ Turning starting position
Trj start is the starting point position of the whole mileage turn;
(X start,Ystart) is the coordinate position of the turn start;
⑤ End position of turning
Trj end is the end position of the whole mileage turn;
(X end,Yend) is the end point coordinate position of the turn;
⑥ Critical turning angle position
Setting the end point of L a-step with the included angle of |alpha key | with the turning end direction as the key angle position,
Trj key is the key turning position of the whole range;
(X key,Ykey) is the coordinate location of the critical turn;
and thirdly, the vehicle runs in real time according to the actual road of the map route to be measured, and the real-time running track of the vehicle which is terminated at the current moment is subjected to feature extraction according to the map route discrete and turning feature extraction method to form discrete and turning feature parameter description.
The real-time track characteristic calculation is realized by using the measurement data of the odometer and the gyroscope, and the specific calculation process is as follows:
1) Vehicle position recursion
Dead reckoning is carried out by using a vehicle odometer and a rate gyroscope, and all other important parameters for matching are relative change data in a road section except for a turning position for resetting the position of the vehicle in discrete features and turning features, so that the dead reckoning does not require an accurate initial course, and the requirements of matching positioning and deviation route judgment can be met as long as the accumulated error of the gyroscope in the running time of the road section is smaller.
By adopting the calculation method, the true value of the course does not need to be concerned, and the road section characteristic extraction can be calculated on the basis of the existing course; assuming that the initial heading of the vehicle is Yaw ini, continuously calculating the track coordinates according to the odometer speed v od, the gyroscope angular rate Yaw rate and the measurement interval T as follows:
(X real(t)、Yreal (t)) is the actual track coordinate of the vehicle at the moment t, and Yaw (t) is the heading of the vehicle at the moment t.
2) Discrete feature computation
The calculation content is the same as the method in the first step, and is calculated according to the same parameters as the L d、La-step and the like in the road discrete feature extraction part.
In order to reduce invalid feature data in the case of approximate straight line sections, local extreme points with a distance of less than 5 meters from a line section are ignored in the calculation process, and discrete feature descriptions are only arranged at the positions of the turning sections with the valid amplitude larger than a threshold value.
The real-time discrete features are described as:
(lRC1,dRc1),(lRC2,dRc2),(lRC3,dRc3),…(lRCn,dRcn),(lRCm,dRcmax),(lRCmin,dRcmin)
3) Turning feature calculation
The turning characteristic calculation method is the same as that in the second step, and turning characteristics are calculated according to the same parameters, so that turning characteristic description ending at the current moment is obtained
αRsum_abs,αRsum,LRsum,trjRstart,trjRkey,(XRkey,YRkey)
And step four, matching the actual driving route with the map reference route by utilizing the real-time discrete feature and turning feature of the vehicle and the discrete feature and turning feature of the map under the matching methods of different discrete parameters and turning characteristic parameters, and determining the position of the vehicle.
The map matching positioning is to match road sections with turns, the discrete features and the turning features of the road sections are designed for the turns of the routes, and a matching mode of combining the discrete features and the turning features is adopted to ensure the map matching reliability;
the specific matching method is as follows:
1) Discrete feature matching
And taking the real-time discrete features of the vehicle as indexes, and searching and matching in the map route discrete features. Under the condition that the road is determined and the range of the mileage error can be determined, discrete feature search matching is carried out along the road in the determined range of the mileage, and the matching method is as follows:
① Pretreatment of road discrete features
And sequentially adjusting the discrete features of the map route according to the running direction of the vehicle, and if the advancing direction is the same as the extraction direction of the discrete features of the map route, not performing any adjustment. If the advancing direction is opposite to the extraction direction of the discrete features of the map route and the road is a bidirectional route with the same shape, reversing the distance sign, recalculating the arc length L d-lCi of the ith local feature point according to the reverse running, and sequentially adjusting the non-global distance extreme points according to the arc length value; the positions of the global extreme points are also treated the same.
② Local extremum point coarse matching
The map route discrete feature description is searched for within the range of possible vehicle mileage. Taking the fact that the driving direction is the same as the extraction direction of the discrete features of the map route as an example, regarding the ith local distance extreme point, if the following conditions are met at the same time, the real-time discrete features i of the vehicle are considered to be successfully matched with the discrete features j of the map route.
|lRCi-lACj|＜lerror
|dRci-dcj|＜derror
And l error、derror is an arc length error threshold value and a point-to-origin-destination line segment distance error threshold value respectively.
And matching the position and the amplitude value in the characteristic road section by adopting the same parameters for the global distance extremum discrete characteristic, and if all the real-time discrete characteristics of the vehicles can be matched with the map route discrete characteristics of a certain road section, considering the map road section as a feasible matching road section.
Under the condition that the real-time discrete feature i of the vehicle is successfully matched with the discrete feature j of the map route, the statistical index of the matching error is as follows:
③ Road segment matching optimization
In practical situations, according to the given l error、derror, a plurality of adjacent road segments meet the matching condition, and the matching Error l、Errord corresponding to different road segments is utilized to select the optimal matching result, as described below, the road segment with the minimum comprehensive Error is the optimal matching road segment.
min(0.7Errorl+0.3Errord)
2) Turning feature matching
① Turning feature pretreatment
Because the map route turning feature extraction has directivity, when the actual running direction of the vehicle is opposite to the map route turning extraction direction, the map route turning feature needs to be preprocessed, and the processing content comprises two parts: the algebraic sum sign of the turning angle is inverted and the turning position is aligned, wherein the turning position is realigned, and the turning starting position and the turning ending position are adjusted by considering the running direction of the vehicle.
Under the condition that the extraction direction of the map features is opposite to the actual running direction of the vehicle, the pretreatment can also adopt a mode of inverting the turning algebra and the sign of the real-time turning features and adjusting the initial and final positions.
For a single-line with opposite driving directions and large route shape difference, the single-line is used as two independent roads to be processed in the turning characteristic extraction process, and pretreatment is not needed.
② Turning feature coarse matching
The route turn characterization is searched for within the range of possible vehicle range. Turning characteristic matching is performed on the turning angle absolute value sum, the turning angle algebraic sum and the turning distance, and the case where the driving direction is consistent with the map route turning characteristic extraction direction is taken as an example for explanation.
|αRsum_abs-αsum_abs|＜α_abserror
|αRsum-αsum|＜α_sumerror
|LRsum-Csum|＜L_sumerror
Alpha_abs error、α_sumerror and L_sum error are the error of the absolute sum of the turning angles, the error of the algebraic sum of the turning angles and the error of the turning distance, respectively; the setting may be made according to the actual situation, and in the case of a turning distance of about 200 meters, the present embodiment is set to 10 degrees, and 10 meters with reference to the reference.
If all three conditions are satisfied, the rough matching is considered to be successful.
③ Optimization of turn matching
In practical situations, a plurality of adjacent road segments meeting the constraint condition of alpha abs error、α_sumerror、L_sumerror exist, the matching errors of the adjacent road segments are compared in order to determine the optimal matching road segments, and a specific calculation method of the matching errors is as follows, and the road segment with the smallest matching error is selected as the optimal turning matching road segment.
3) Optimal matching decision
Ideally, for a given actual road segment, the map route discrete feature and turning feature are optimized simultaneously, and the matching reliability is considered to be 100%. However, due to the influence of the measurement precision of the sensor or the precision of the map, the situation that the two optimally matched road sections are inconsistent can occur, and in the situation, discrete features are taken as main references, but the matching reliability is reduced to 75%.
4) Vehicle position adjustment
After the discrete feature and turning feature matching is completed, the vehicle position correction can be performed using the following rules:
① Discrete maximum distance accurate matching correction
When the following two conditions are satisfied simultaneously, the vehicle position is corrected using the discrete maximum distance position.
And taking the position corresponding to l RCmax or l Cmin as the coordinate of the real-time track passing through the global distance extreme point of the road section.
② Critical cornering angle position correction
In case the discrete maximum distance exact match is not met, the coordinates at the real-time trajectory critical turning angle position are reset with the critical turning position correction, i.e. with the same |α key | parameter at the map route critical turning angle position.
(XRkey,YRkey)＝(Xkey,Ykey)
And fifthly, on the basis of map matching and positioning, judging whether the vehicle deviates from a specified route or not by utilizing the discrete characteristics of the actual running track of the vehicle.
When the vehicle runs on a known route and the initial positioning is accurate, the invention designs a method for judging whether the vehicle deviates from the route or not under the satellite-free navigation condition based on the relative motion trail of the odometer and the gyroscope.
The use of only an odometer and a gyroscope on a long straight road cannot determine whether the vehicle is off-road, and therefore the determination calculation is designed for a turning road section. Under the condition that the vehicle runs on a known road and is effectively positioned by means of map matching and the like, the vehicle deviation route judgment can be realized by utilizing discrete features, the vehicle continuously slides by taking L d as a window in the range of possible mileage of the vehicle, and the vehicle deviation from a preset route is judged if any of the following conditions are met:
|dRcmax-dcmax|＞doff
|dRcmin-dcmin|＞doff
d off is a threshold value that determines whether the vehicle is off-course, typically taking a value of 10 meters.
Claims (7)
1. The map matching positioning and deviation line judging method is characterized by comprising the following steps of:
Firstly, traversing a map reference route to be tested by using sliding windows, setting the distance direction from each point in a road section to a reference straight line by taking a road section origin-destination connecting line vector as a reference for the route in each sliding window, and extracting the peak value distance to form the discrete feature of the road section;
meanwhile, setting a turning angle algebraic sum, a turning angle absolute value sum and a turning road section length index in a sliding window according to the turning condition of the map reference route to form turning characteristics of the road section;
Then, the real-time discrete features and turning features are respectively extracted from the real-time running actual road of the vehicle in the same way;
Further, matching the actual running route of the vehicle with the map reference route by utilizing the real-time discrete features and turning features of each road section of the vehicle and the discrete features and turning features of each road section of the map to determine the position of the vehicle;
Finally, on the basis of map matching and positioning, judging whether the vehicle deviates from a specified route or not by utilizing real-time discrete features of the vehicle;
Based on the judgment of the odometer and the gyroscope, the vehicle deviation route judgment is realized by utilizing discrete features aiming at a turning road section, the vehicle continuously slides by taking the set road section length L d as a window in the mileage range of the vehicle, and if any of the following conditions is met, the vehicle deviation from a preset route is judged:
|dRcmax-dcmax|＞doff
|dRcmin-dcmin|＞doff
d off is a threshold value for determining whether the vehicle deviates from the route; d cmax is a distance value corresponding to a point with the largest distance from the reference line segment in the front half-plane road section on the map; d cmin is a distance value corresponding to a point with the maximum distance from the reference line segment in the negative half-plane road section; d Rcmax is a distance value corresponding to a point with the largest distance from the reference line segment in the front half-plane road section where the vehicle runs; d Rcmin is a distance value corresponding to a point with the maximum distance from the reference line segment in the negative half-plane section where the vehicle runs.
2. The map matching locating and deviating line determining method according to claim 1, wherein the map discrete feature obtaining process is as follows:
Recording the peak value and the position of the distance from the point C to the line segment AB on the road section aiming at the reference route taking the point A as the starting point B as the end point;
Let l AC denote the arc length of the AC segment of the actual route, d c be the distance from the point C to the line AB, record the local extremum obtained by the distance d c, and compose the following discrete feature vectors in the line AB:
(lAC1,dc1),(lAC2,dc2),(lAC3,dc3),…(lACn,dcn),(lACmax,dcmax),(lACmin,dcmin)
Wherein (l ACn,dcn) represents the position and specific distance value of the nth extremum, and the sign of d cn represents the positive half plane or the negative half plane of the C point, (l ACmax,dcmax) represents the position and specific distance value of the maximum distance point from the AB line segment in the positive half plane section, and (l ACmin,dcmin) represents the position and specific distance value of the maximum distance point from the AB line segment in the negative half plane section.
3. The map matching locating and deviating line determining method according to claim 1, wherein the map turning feature obtaining process is as follows:
① Absolute value sum of turning angles
Alpha k+i is the k+i turning angle value; m is the number of turning road sections; k is the starting point of the turn;
② Algebraic sum of turning angles
③ Length of turning distance
Lsum＝mLa-ste
L a-ste is the step size of the route step;
④ Turning starting position
Trj start is the starting point position of the whole mileage turn;
(X start,Ystart) is the coordinate position of the turn start;
⑤ End position of turning
Trj end is the end position of the whole mileage turn;
(X end,Yend) is the end point coordinate position of the turn;
⑥ Critical turning angle position
Setting the end point of L a-ste with the included angle of |alpha key | with the turning end direction as the key angle position,
Trj key is the key turning position of the whole range;
(X key,Ykey) is the coordinate location of the critical turn.
4. The map matching locating and off-course determination method of claim 1, wherein said vehicle real-time discrete features are:
(lRC1,dRc1),(lRC2,dRc),(lRC3,dRc3),…(lRCn,dRcn),(lRCmax,dRcmax),(lRCmin,dRcmin)
(l RCn,dRcn) represents the real-time position and specific distance value of the nth extreme vehicle; (l RCmax,dRcmax) is the position and specific distance value of the point with the largest distance from the reference line segment in the road section of the vehicle running positive half plane, and (l RCmin,dRcmin) is the position and specific distance value of the point with the largest distance from the reference line segment in the vehicle running negative half plane;
The turning characteristic of the vehicle is as follows:
αRsum_abs,αRsum,LRsum,trjRstart,trjRkey,(XRkey,YRkey)
Alpha Rsum_abs is the absolute value sum of the turning angles of the vehicles; alpha Rsum is the algebraic sum of the turning angles of the vehicle; l Rsum is the vehicle turning distance length; trj Rstart is the vehicle turn starting position; trj Rkey is the vehicle key turn angle position; (X Rkey,YRkey) is the coordinate position of the critical turn of the vehicle.
5. The map matching positioning and deviation route determination method according to claim 2 or 4, wherein the matching of the actual driving route of the vehicle with the map reference route discrete feature is specifically:
① Pretreatment of road discrete features
Sequentially adjusting the discrete features of the map route according to the running direction of the vehicle, and not adjusting if the advancing direction is the same as the extraction direction of the discrete features of the map route; if the advancing direction is opposite to the extraction direction of the discrete features of the map route and the road is a bidirectional route with the same shape, reversing the distance sign, recalculating the arc length of each local feature point according to the reverse running, and sequentially adjusting the non-global distance extreme points according to the arc length value; the positions of the global extreme points are treated the same;
② Local extremum point coarse matching
Aiming at the fact that the driving direction is the same as the extraction direction of the discrete features of the map route, regarding the ith local distance extreme point, if the following conditions are met at the same time, the real-time discrete features i of the vehicle are considered to be successfully matched with the discrete features j of the map route:
|lRCi-lACj|＜lerror
|dRci-dcj|＜derror
l error、derror is the arc length error threshold and the point-to-origin-destination point segment distance error threshold respectively;
The same parameters are adopted for the global distance extremum discrete features to match the position and the amplitude in the feature road section, and if all the real-time discrete features of the vehicles can be matched with the map route discrete features of a certain road section, the map road section is considered as a feasible matching road section;
Under the condition that the real-time discrete feature i of the vehicle is successfully matched with the discrete feature j of the map route, the statistical index of the matching error is as follows:
③ Road segment matching optimization
The road section with the minimum comprehensive error is the optimal matching road section: min (0.7 Error l+0.3Errord).
6. The map matching positioning and deviation route determination method according to claim 2 or 4, wherein the matching of the turning characteristics of the actual driving route of the vehicle and the map reference route is specifically:
① Turning feature pretreatment
When the actual running direction of the vehicle is opposite to the map route turning extraction direction, preprocessing map route turning characteristics: the algebraic sum sign of the turning angle is reversed and the turning positions are aligned; wherein the turn position realignment is an adjustment of the turn start and end positions;
For a single-line with opposite driving directions and larger route shape difference, the single-line is used as two independent roads to be processed in the turning characteristic extraction process, and pretreatment is not needed;
② Turning feature coarse matching
Aiming at the condition that the running direction is consistent with the extraction direction of turning features of the map route, the absolute value sum of turning angles, algebraic sum of turning angles and turning distances are matched, and the formula is as follows:
|αRsum_abs-αsum_abs|＜α_abserror
|αRsum-αsum|＜α_sumerror
|LRsum-Lsum|＜L_sumerror
Alpha_abs error、α_sumerror and L_sum error are the error of the absolute sum of the turning angles, the error of the algebraic sum of the turning angles and the error of the turning distance, respectively;
if all three conditions are met, the rough matching is considered to be successful;
③ Optimization of turn matching
Selecting the road section with the smallest matching error as the optimal turning matching road section:
for an actual road section, the discrete feature and the turning feature of the map route are optimized at the same time, otherwise, the discrete feature is taken as a main reference, and the matching reliability is reduced to 75%.
7. The map matching positioning and deviation route determination method according to claim 2 or 4, wherein after the matching of the actual driving route of the vehicle with the discrete feature and the turning feature of the map reference route is completed, determining the vehicle position specifically comprises:
① Discrete maximum distance accurate matching correction
Correcting the vehicle position using the discrete maximum distance position when the following two conditions are simultaneously satisfied:
Taking the position corresponding to l RCmax or l Cmin as the coordinate of the extreme point of the global distance of the real-time track passing road section;
② Critical cornering angle position correction
Under the condition that the discrete maximum distance accurate matching is not met, the coordinates at the real-time track key turning angle position are reset by the key turning position correction, namely under the same |alpha key | parameter, with the map route key turning angle position:
(XRkey,YRkey)＝(Xkey,Ykey)。
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