US20200333143A9 - Gps-based area recognition in vehicles - Google Patents
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- US20200333143A9 US20200333143A9 US15/458,451 US201715458451A US2020333143A9 US 20200333143 A9 US20200333143 A9 US 20200333143A9 US 201715458451 A US201715458451 A US 201715458451A US 2020333143 A9 US2020333143 A9 US 2020333143A9
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- 238000012360 testing method Methods 0.000 claims abstract description 30
- 238000000034 method Methods 0.000 claims abstract description 25
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000006073 displacement reaction Methods 0.000 claims description 4
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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
- G01C21/32—Structuring or formatting of map data
-
- 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
- G01C21/3863—Structures of map data
- G01C21/3867—Geometry of map features, e.g. shape points, polygons or for simplified maps
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- 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
- G01C21/34—Route searching; Route guidance
- G01C21/3453—Special cost functions, i.e. other than distance or default speed limit of road segments
- G01C21/3469—Fuel consumption; Energy use; Emission aspects
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
-
- 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
Definitions
- the disclosure relates to a method for determining the current geoposition of a vehicle, and digital maps, which in each case represent a geographic area on the earth.
- driver assistance systems in modern motor vehicles operate in dependence on the environment in which the vehicle is currently located, and the functional accuracy and availability of such driver assistance systems can be improved by information from a navigation system, for example by information regarding in which state or other geographic area the motor vehicle is currently located in order to provide for a country- or area-specific system behavior.
- a motor vehicle contains a navigation system that matches the geoposition of the vehicle continuously to a digital map
- area information for driver assistance systems can also be easily obtained, namely as an area code, e.g. a country identifier, for the road currently traveled.
- Global Positioning System calculates the current vehicle position very accurately in geocoordinates, that is to say as absolute position and much more accurately than is actually necessary for supporting driver assistance systems.
- Navigation systems are frequently not part of the standard equipment of motor vehicles and even if this is the case, the driver should keep the ability of deactivating the navigation.
- the disclosure is based on the object of determining in a vehicle, with as little expenditure as possible but with adequate accuracy, in which geographic area the vehicle is currently located in order to safeguard the performance and availability of driver assistance systems if no navigation system is available in the vehicle or if it is currently not in operation.
- a boundary precheck is initially performed, wherein candidate area polygons are selected that are located in the vicinity of the current vehicle position.
- the selected candidate area polygons are then successively subjected to a PIP (“Point-In-Polygon”) test in order to determine whether the current vehicle position is located in one of the corresponding areas.
- PIP Point-In-Polygon
- an initial variable is supplied, which specifies whether the vehicle is currently located in an area and possibly in which of the areas the vehicle is currently located.
- GNSS global navigation satellite systems
- eCall automatic emergency call system for motor vehicles
- GNSS devices supply only the absolute geoposition as pure numerical values, it is possible by means of the disclosure to obtain area information from them with minimum storage and computing expenditure, which is accurate enough for driver assistance systems.
- the method according to the disclosure only needs a minimal set of geographic map data with correspondingly little storage requirement and can be performed as software, which can run on a so-called “Embedded Platform”.
- the computing times are predeterminable and less than in the case of an accurate position determination.
- the method according to the disclosure is significantly more accurate than mere position estimations but faster by a multiple and more resource-saving than usual navigation systems.
- the latter is also caused by the fact that only the relative positions of vehicle and area polygons have to be determined for the disclosure.
- the method according to the disclosure is to a certain degree related to so-called geofencing algorithms, which trigger an action when an imagined boundary on the earth is crossed.
- the algorithms used for this purpose have no predetermined computing times, however, and do not need as little storage space and cannot be implemented as simply as the present disclosure.
- the boundary precheck is performed by greater or less than comparisons of the values of a first coordinate of the current vehicle position with the maximum or minimum coordinate values, respectively, of the area polygons contained in the digital maps with respect to the first coordinate and by greater or less than comparisons of the values of a second coordinate, orthogonal to the first coordinate, of the current vehicle position with the maximum or minimum coordinate values, respectively, of the area polygons with respect to the second coordinate.
- the PIP tests are performed without point of intersection calculations by means of greater or less than comparisons of coordinate values after a suitable coordinate displacement that significantly reduces the computing expenditure.
- the candidate area polygons selected by means of the boundary precheck are subdivided into smaller part-polygons by superimposing parallel strips. Furthermore, by means of a binary search, a strip is determined into which the current vehicle position falls and the part-polygons falling into the strip determined are then subjected to the PIP tests. This lowers the computing expenditure even more.
- the geographic areas are preferably administrative or similar areas that change only in exceptional cases. For this reason, no frequent updating of the digital maps is required.
- the method according to the disclosure is particularly suitable for vehicles, particularly motor vehicles, wherein a receiver for a global navigation satellite system supplying the geoposition data, but no navigation system, is installed and that have at least one driver assistance system.
- FIG. 1 shows a block diagram of a method for determining in which geographic area a vehicle is currently located
- FIG. 2 shows a drawing for explaining the delimitation block in FIG. 1 ;
- FIG. 3 shows a drawing for explaining the PIP test block in FIG. 1 ;
- FIG. 4 shows a drawing for explaining the strip/binary search block in FIG. 1 ;
- FIG. 5 shows a flowchart of the method for determining in which geographic area the vehicle is currently located.
- GPS-based area recognition The system described in the text which follows is called GPS-based area recognition.
- a GNSS receiver installed in a motor vehicle supplies raw data, which specify the geographic coordinates of the vehicle as its GPS position or generally geoposition.
- raw data specify the geographic coordinates of the vehicle as its GPS position or generally geoposition.
- a digital map is stored in the vehicle which exclusively represents coherent geographic and/or administrative areas on the earth as more or less gaplessly adjoining polygons that represent relevant area boundaries or are approximated to these.
- the geoposition data On the basis of the geoposition data, it is determined at regular time intervals such as, e.g. every pair of seconds, in which of the geographic or administrative areas the vehicle is currently located.
- the area recognition method shown in an overview in FIG. 1 is performed by means of hardware and software present in the vehicle.
- a boundary precheck is performed in a block 1 , by which means, among all stored area polygons, those are selected, which, due to their vicinity to the current vehicle position, are candidates for an area in which the vehicle is currently located.
- the candidate area polygons identified in block 1 are successively subjected to a Point-In-Polygon test (PIP test) in block 3 in order to find out whether the current vehicle position is located in the tested area and the area determined as currently fitting, or an identifier of it, is the initial variable supplied to a driver assistance system of the motor vehicle.
- PIP test Point-In-Polygon test
- each candidate area polygon identified in block 1 is firstly subdivided in block 2 , by superimposing many parallel strips, which extend along a predetermined coordinate axis, into smaller part-polygons.
- a binary search an algorithm known in the prior art which very efficiently finds an element sought in a list, that strip is determined into which the current vehicle position falls.
- the part-polygons of all candidate area polygons, falling into the respective strips, are then successively subjected to a PIP test in block 1 in order to find out whether the current vehicle position is located in the part-polygon checked.
- the boundary precheck in block 1 of FIG. 1 is performed since the number of areas to be distinguished is normally high.
- a fitting rectangular boundary box 5 a, 5 b, 5 c, 5 d, 5 e the coordinates of which are e.g. simply given by the smallest and largest x or y coordinates of the corresponding area polygon 4 a, 4 b, 4 c, 4 d, 4 e in an x-y coordinate system is drawn around each area polygon, wherein here only five area polygons 4 a, 4 b, 4 c, 4 d, 4 e are represented.
- All area polygons which belong to a boundary box into which the geoposition of the vehicle falls are candidate polygons, i.e. possible candidates for an area in which the vehicle is currently located. All other area polygons do not need to be checked further.
- the PIP test in block 3 of FIG. 1 is an optimized so-called ray method for checking whether a point is located inside or outside a polygon.
- ray method a test ray is drawn in an arbitrary direction from a point to be tested and it is counted how often the test ray intersects the edges of the polygon. If the number of points of intersection of the test ray with the polygon edges is odd, the point is located inside the polygon and otherwise outside of it.
- the corresponding decision rule can be written as:
- FIG. 3 illustrates an example of a corresponding PIP test with respect to a point p that is within a polygon P, and with respect to a point p′ that is outside the polygon P.
- Exemplary test rays emanating from points p and p′ are drawn as S and S′, and their points of intersection with the polygon edges as small circles.
- the most extensive computing steps in the ray method are the calculations of the points of intersection.
- the optimized ray method proposed here operates without point of intersection calculations by using improved greater or less than comparisons of coordinate values as described in the text which follows.
- the coordinate system is displaced in such a way that the current position of the vehicle is at the origin.
- the test ray can then be defined as the positive x axis of a cartesian x-y coordinate system. Extensive point of intersection calculations can be avoided since it is not necessary to know the precise point of intersection, but only whether the polygon edge intersects the positive half of the x axis. This can be performed in three simple steps as described in the text which follows.
- An inside/outside condition can be formulated as follows:
- the above calculation can be performed, instead of in a cartesian x-y coordinate system, also in a polar coordinate system.
- the optional binary strip search in Block 3 of FIG. 1 is particularly suitable for cases in which the individual area polygons of a polygon map have very many or a very different number of edges.
- the area polygons or at least those having very many edges are subdivided into smaller part-polygons, which in each case contain approximately the same number of polygon edges and are here called strips or bins.
- one polygon P is split into smaller part-polygons by five strips B 1 to B 5 .
- edges contained in an individual strip are interpreted and treated as independent polygons.
- area polygons which naturally have different sizes and shapes, are scaled to polygons of approximately the same size.
- the performance of the PIP tests on smaller pieces can be administered better and the computing time is less dependent on the polygon size and shape.
- the strip Before performing the PIP tests or point of intersection tests, the strip must be determined into which the current vehicle position falls. This can be done by a so-called binary search, which reduces the complexity O (n) when testing n strips in chronological order to O (log n).
- the second exemplary embodiment of the method for determining in which geographic area a vehicle is currently located is also shown as a flowchart in FIG. 5 .
- the method can then be started cyclically and begins in each case with step S 1 , to perform a boundary precheck as in block 1 of FIG. 1 and enter candidate polygons determined into a list.
- step S 2 If it is found in step S 2 that the list of candidate polygons is empty, the result of the method is output in step S 3 that the current vehicle position is not located in any area of the digital map, and the method ends. Otherwise, an entry is read out of the list of candidate polygons in step S 4 and by means of the binary strip search, a search is conducted for a strip for the current vehicle position by means of the binary strip search in block 2 of FIG. 1 .
- step S 5 it is checked whether there is a corresponding strip, and if not, it is effected in step S 6 that in step S 4 , the next entry, if present, is read out of the list of candidate polygons and supplied to step S 5 .
- step S 5 If a strip has been found in step S 5 , the part polygon contained therein is subjected to the PIP test in block 3 of FIG. 1 in step S 7 . If it is found in step S 8 that the current vehicle position is not in the part polygon, it returns to step S 6 and if it is there, an area code is output as a result in the method in step S 9 that is allocated to the area polygon in which the part-polygon is located.
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Abstract
Description
- This application claims foreign priority benefits under 35 U.S.C. §119(a)-(d) to DE 10 2016 204 823.6 filed Mar. 23, 2016, which is hereby incorporated by reference in its entirety.
- The disclosure relates to a method for determining the current geoposition of a vehicle, and digital maps, which in each case represent a geographic area on the earth.
- Some of the various driver assistance systems in modern motor vehicles operate in dependence on the environment in which the vehicle is currently located, and the functional accuracy and availability of such driver assistance systems can be improved by information from a navigation system, for example by information regarding in which state or other geographic area the motor vehicle is currently located in order to provide for a country- or area-specific system behavior.
- If a motor vehicle contains a navigation system that matches the geoposition of the vehicle continuously to a digital map, area information for driver assistance systems can also be easily obtained, namely as an area code, e.g. a country identifier, for the road currently traveled.
- Navigation systems that utilize GPS (“Global Positioning System”) data calculate the current vehicle position very accurately in geocoordinates, that is to say as absolute position and much more accurately than is actually necessary for supporting driver assistance systems.
- Navigation systems are frequently not part of the standard equipment of motor vehicles and even if this is the case, the driver should keep the ability of deactivating the navigation.
- The disclosure is based on the object of determining in a vehicle, with as little expenditure as possible but with adequate accuracy, in which geographic area the vehicle is currently located in order to safeguard the performance and availability of driver assistance systems if no navigation system is available in the vehicle or if it is currently not in operation.
- According to the disclosure, a boundary precheck is initially performed, wherein candidate area polygons are selected that are located in the vicinity of the current vehicle position. The selected candidate area polygons are then successively subjected to a PIP (“Point-In-Polygon”) test in order to determine whether the current vehicle position is located in one of the corresponding areas. To at least one driver assistance system of the vehicle, an initial variable is supplied, which specifies whether the vehicle is currently located in an area and possibly in which of the areas the vehicle is currently located.
- The disclosure makes use of the circumstance that in most motor vehicles, at least one receiver for global navigation satellite systems (“GNSS”) is installed as standard, a device that can determine its own geographic position from the satellite signals. Such GPS or related position determining devices are even prescribed with the introduction of the automatic emergency call system for motor vehicles (“eCall”) and will not be easily deactivatable.
- Although GNSS devices supply only the absolute geoposition as pure numerical values, it is possible by means of the disclosure to obtain area information from them with minimum storage and computing expenditure, which is accurate enough for driver assistance systems.
- The method according to the disclosure only needs a minimal set of geographic map data with correspondingly little storage requirement and can be performed as software, which can run on a so-called “Embedded Platform”. The computing times are predeterminable and less than in the case of an accurate position determination.
- On the other hand, the method according to the disclosure is significantly more accurate than mere position estimations but faster by a multiple and more resource-saving than usual navigation systems. The latter is also caused by the fact that only the relative positions of vehicle and area polygons have to be determined for the disclosure.
- The method according to the disclosure is to a certain degree related to so-called geofencing algorithms, which trigger an action when an imagined boundary on the earth is crossed. The algorithms used for this purpose have no predetermined computing times, however, and do not need as little storage space and cannot be implemented as simply as the present disclosure.
- US 2001 024 203 A1, US 2012 123 677 A1 and US 2007 083 325 A1 disclose map display or movement devices wherein, however, other algorithms are used for polygon processing than in the case of the present disclosure. In addition, the disclosure does not require any map display devices.
- In a preferred embodiment of the present disclosure, the boundary precheck is performed by greater or less than comparisons of the values of a first coordinate of the current vehicle position with the maximum or minimum coordinate values, respectively, of the area polygons contained in the digital maps with respect to the first coordinate and by greater or less than comparisons of the values of a second coordinate, orthogonal to the first coordinate, of the current vehicle position with the maximum or minimum coordinate values, respectively, of the area polygons with respect to the second coordinate.
- In preferred embodiments, the PIP tests are performed without point of intersection calculations by means of greater or less than comparisons of coordinate values after a suitable coordinate displacement that significantly reduces the computing expenditure.
- In a development of the disclosure, the candidate area polygons selected by means of the boundary precheck are subdivided into smaller part-polygons by superimposing parallel strips. Furthermore, by means of a binary search, a strip is determined into which the current vehicle position falls and the part-polygons falling into the strip determined are then subjected to the PIP tests. This lowers the computing expenditure even more.
- The geographic areas are preferably administrative or similar areas that change only in exceptional cases. For this reason, no frequent updating of the digital maps is required.
- As described, the method according to the disclosure is particularly suitable for vehicles, particularly motor vehicles, wherein a receiver for a global navigation satellite system supplying the geoposition data, but no navigation system, is installed and that have at least one driver assistance system.
- A description of exemplary embodiments by means of the drawings follows, in which:
-
FIG. 1 shows a block diagram of a method for determining in which geographic area a vehicle is currently located; -
FIG. 2 shows a drawing for explaining the delimitation block inFIG. 1 ; -
FIG. 3 shows a drawing for explaining the PIP test block inFIG. 1 ; -
FIG. 4 shows a drawing for explaining the strip/binary search block inFIG. 1 ; and -
FIG. 5 shows a flowchart of the method for determining in which geographic area the vehicle is currently located. - As required, detailed embodiments of the present disclosure are disclosed herein; however, it is to be understood that the disclosed embodiments are merely exemplary of the disclosure that may be embodied in various and alternative forms. The figures are not necessarily to scale; some features may be exaggerated or minimized to show details of particular components. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting, but merely as a representative basis for teaching one skilled in the art to variously employ the present disclosure.
- The system described in the text which follows is called GPS-based area recognition.
- A GNSS receiver installed in a motor vehicle supplies raw data, which specify the geographic coordinates of the vehicle as its GPS position or generally geoposition. In addition, a digital map is stored in the vehicle which exclusively represents coherent geographic and/or administrative areas on the earth as more or less gaplessly adjoining polygons that represent relevant area boundaries or are approximated to these.
- On the basis of the geoposition data, it is determined at regular time intervals such as, e.g. every pair of seconds, in which of the geographic or administrative areas the vehicle is currently located.
- For this purpose, the area recognition method shown in an overview in
FIG. 1 is performed by means of hardware and software present in the vehicle. - By means of the geoposition data and the polygon map data as input variables, a boundary precheck is performed in a
block 1, by which means, among all stored area polygons, those are selected, which, due to their vicinity to the current vehicle position, are candidates for an area in which the vehicle is currently located. - In a first exemplary embodiment, the candidate area polygons identified in
block 1 are successively subjected to a Point-In-Polygon test (PIP test) inblock 3 in order to find out whether the current vehicle position is located in the tested area and the area determined as currently fitting, or an identifier of it, is the initial variable supplied to a driver assistance system of the motor vehicle. - In a second exemplary embodiment, each candidate area polygon identified in
block 1 is firstly subdivided inblock 2, by superimposing many parallel strips, which extend along a predetermined coordinate axis, into smaller part-polygons. By means of a binary search, an algorithm known in the prior art which very efficiently finds an element sought in a list, that strip is determined into which the current vehicle position falls. The part-polygons of all candidate area polygons, falling into the respective strips, are then successively subjected to a PIP test inblock 1 in order to find out whether the current vehicle position is located in the part-polygon checked. -
Blocks 1 to 3 will be described in greater detail in the text which follows. - The boundary precheck in
block 1 ofFIG. 1 is performed since the number of areas to be distinguished is normally high. As shown inFIG. 2 , a fittingrectangular boundary box corresponding area polygon area polygons - Thus, it is possible to check in the simplest way into which of the
boundary boxes area polygons area polygons - All area polygons which belong to a boundary box into which the geoposition of the vehicle falls are candidate polygons, i.e. possible candidates for an area in which the vehicle is currently located. All other area polygons do not need to be checked further.
- The PIP test in
block 3 ofFIG. 1 is an optimized so-called ray method for checking whether a point is located inside or outside a polygon. In the ray method, a test ray is drawn in an arbitrary direction from a point to be tested and it is counted how often the test ray intersects the edges of the polygon. If the number of points of intersection of the test ray with the polygon edges is odd, the point is located inside the polygon and otherwise outside of it. The corresponding decision rule can be written as: -
FIG. 3 illustrates an example of a corresponding PIP test with respect to a point p that is within a polygon P, and with respect to a point p′ that is outside the polygon P. Exemplary test rays emanating from points p and p′ are drawn as S and S′, and their points of intersection with the polygon edges as small circles. - The most extensive computing steps in the ray method are the calculations of the points of intersection. The optimized ray method proposed here operates without point of intersection calculations by using improved greater or less than comparisons of coordinate values as described in the text which follows.
- Firstly, the coordinate system is displaced in such a way that the current position of the vehicle is at the origin. The test ray can then be defined as the positive x axis of a cartesian x-y coordinate system. Extensive point of intersection calculations can be avoided since it is not necessary to know the precise point of intersection, but only whether the polygon edge intersects the positive half of the x axis. This can be performed in three simple steps as described in the text which follows.
- Let vi=(xi, yi) and vj=(xj, yj) be the displaced vertices of the checked polygon edge. An inside/outside condition can be formulated as follows:
- 1) Discard all edges that do not meet the following condition:
- sign (yi)≠sign (yj)
- 2a) Store the occurrence of a point of intersection if an edge meets the following condition:
- sign (xi)>0 && sign (xj)>0
- 2b) The edge is to be discarded if:
- sign (xi)<0 && sign (xj)<0
- 3) Also store the occurrence of a point of intersection for edges, wherein b is the y-axis section of the edge in the displaced coordinate system:
-
(x i *y i *b)<0 - With the greater or less than comparisons, the PIP test performed is very efficient. There only remains one division left over (in the calculation of b).
- The above calculation can be performed, instead of in a cartesian x-y coordinate system, also in a polar coordinate system.
- The optional binary strip search in
Block 3 ofFIG. 1 is particularly suitable for cases in which the individual area polygons of a polygon map have very many or a very different number of edges. For this purpose, the area polygons or at least those having very many edges are subdivided into smaller part-polygons, which in each case contain approximately the same number of polygon edges and are here called strips or bins. In the example shown inFIG. 4 , one polygon P is split into smaller part-polygons by five strips B1 to B5. - The edges contained in an individual strip are interpreted and treated as independent polygons. In this way, area polygons, which naturally have different sizes and shapes, are scaled to polygons of approximately the same size. The performance of the PIP tests on smaller pieces can be administered better and the computing time is less dependent on the polygon size and shape.
- Before performing the PIP tests or point of intersection tests, the strip must be determined into which the current vehicle position falls. This can be done by a so-called binary search, which reduces the complexity O (n) when testing n strips in chronological order to O (log n).
- The second exemplary embodiment of the method for determining in which geographic area a vehicle is currently located is also shown as a flowchart in
FIG. 5 . The method can then be started cyclically and begins in each case with step S1, to perform a boundary precheck as inblock 1 ofFIG. 1 and enter candidate polygons determined into a list. - If it is found in step S2 that the list of candidate polygons is empty, the result of the method is output in step S3 that the current vehicle position is not located in any area of the digital map, and the method ends. Otherwise, an entry is read out of the list of candidate polygons in step S4 and by means of the binary strip search, a search is conducted for a strip for the current vehicle position by means of the binary strip search in
block 2 ofFIG. 1 . - In step S5, it is checked whether there is a corresponding strip, and if not, it is effected in step S6 that in step S4, the next entry, if present, is read out of the list of candidate polygons and supplied to step S5.
- If a strip has been found in step S5, the part polygon contained therein is subjected to the PIP test in
block 3 ofFIG. 1 in step S7. If it is found in step S8 that the current vehicle position is not in the part polygon, it returns to step S6 and if it is there, an area code is output as a result in the method in step S9 that is allocated to the area polygon in which the part-polygon is located. - While exemplary embodiments are described above, it is not intended that these embodiments describe all possible forms of the disclosure. Rather, the words used in the specification are words of description rather than limitation, and it is understood that various changes may be made without departing from the spirit and scope of the disclosure. Additionally, the features of various implementing embodiments may be combined to form further embodiments of the disclosure.
Claims (20)
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Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
DE102016204823.6A DE102016204823A1 (en) | 2016-03-23 | 2016-03-23 | GPS-based area recognition in vehicles |
DE102016204823.6 | 2016-03-26 |
Publications (3)
Publication Number | Publication Date |
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US20170276490A1 US20170276490A1 (en) | 2017-09-28 |
US20200333143A9 true US20200333143A9 (en) | 2020-10-22 |
US10935384B2 US10935384B2 (en) | 2021-03-02 |
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US10593074B1 (en) * | 2016-03-16 | 2020-03-17 | Liberty Mutual Insurance Company | Interactive user interface for displaying geographic boundaries |
DE102019200494B4 (en) | 2019-01-16 | 2022-12-22 | Audi Ag | Motor vehicle with at least one radar sensor and method for operating a radar sensor in a motor vehicle |
CN109557942B (en) * | 2019-01-21 | 2021-10-26 | 梁晓龙 | Unmanned aerial vehicle geo-fencing algorithm for autonomous flight |
CN109918468A (en) * | 2019-03-21 | 2019-06-21 | 四川长虹电器股份有限公司 | Internet of things equipment position data region screening technique based on Mercator projection |
DE102020211392A1 (en) | 2020-03-26 | 2021-09-30 | Continental Teves Ag & Co. Ohg | Method for recording one's own position with regard to a boundary and electronic control system |
CN112857376A (en) * | 2021-01-12 | 2021-05-28 | 广州小鹏自动驾驶科技有限公司 | Vehicle road matching method and device |
CN115240401B (en) * | 2022-07-04 | 2024-04-09 | 一汽解放汽车有限公司 | Vehicle position determining method, device, equipment, medium and product |
CN115240429B (en) * | 2022-08-11 | 2023-02-14 | 深圳市城市交通规划设计研究中心股份有限公司 | Pedestrian and vehicle flow statistical method, electronic equipment and storage medium |
DE102022120808B3 (en) | 2022-08-17 | 2023-10-26 | Audi Aktiengesellschaft | Procedure for making an emergency call |
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JP3912476B2 (en) | 2000-03-21 | 2007-05-09 | アイシン・エィ・ダブリュ株式会社 | Map display device |
JP2007108257A (en) | 2005-10-11 | 2007-04-26 | Alpine Electronics Inc | Map mobile device |
SG171974A1 (en) | 2008-12-26 | 2011-07-28 | Jx Nippon Mining & Metals Corp | Flexible laminate and flexible electronic circuit substrate formed using the same |
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US10386844B2 (en) * | 2015-09-30 | 2019-08-20 | Deere & Company | System and method for using geo-fenced guidance lines |
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US20170276490A1 (en) | 2017-09-28 |
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