JPS6312096A - Recognition of current location for vehicle - Google Patents

Abstract

(57) [Summary] This bulletin contains application data before electronic filing, so abstract data is not recorded.

Description

DETAILED DESCRIPTION OF THE INVENTION The present invention relates to a method for recognizing the current location of a vehicle in an on-vehicle navigation device.

1. In recent years, there has been research into in-vehicle navigation devices that guide a vehicle to a predetermined destination by storing map information in a memory, reading the map information from the memory, and having a recognition device recognize the map information along with the vehicle's current location. , has been developed.

Such navigation devices detect the vehicle's travel distance, direction, etc. based on the output of a travel distance sensor, direction sensor, etc. mounted on the vehicle, and estimate the vehicle's current location, which changes from moment to moment, based on this. , the current location is recognized on the map recognized on the display.

In this case, it is preferable that the current location is always recognized on the road on the map, but due to sensor accuracy, calculation errors, map accuracy, etc., the current location may deviate from the road in recognition, especially as the distance traveled becomes longer. It will end up being put away.

1 and Natsumi 1 The present invention has been made in view of the above-mentioned points, and an object of the present invention is to provide a method for recognizing the current location of a vehicle that can always accurately recognize the current location of the vehicle.

The method for recognizing the current location of a vehicle according to the present invention digitizes each position on the road on the map and stores it as map data, and each time it is detected that the vehicle has traveled a certain distance based on the output of the mileage sensor, The present invention is characterized in that a position on the road that is a certain distance away from the previously detected position on the road is detected based on map data, and this detected position is recognized as the current location.

Real - 11 pieces Embodiments of the present invention will be described below with reference to the drawings.

FIG. 1 is a block diagram showing the configuration of an in-vehicle navigation device according to the present invention. In the figure, 1 is a geomagnetic sensor for outputting vehicle azimuth data based on geomagnetism, 2 is an angular velocity sensor for detecting the angular velocity of the vehicle,
3 is a mileage sensor for detecting the distance traveled by the vehicle;
4 is GP3 (Global Positioning) for detecting the current location of the vehicle from latitude and longitude information, etc.
System) device, and each of these sensors (devices)
The output of is supplied to the system controller 5.

The system controller 5 sequentially receives the outputs of the sensors (devices) 1 to 4 from an interface 6 that performs A/D (analog/digital) conversion, etc., and an interface 6 that processes various image data. A CPU (central processing circuit) that calculates the amount of movement of the vehicle, etc. based on the sent output data of each sensor (device) 1 to 4.
7 and a ROM (read-only) in which various processing programs and other necessary information for the CPU 7 are written in advance.
Memory) 8, RAM (Random Access Memory) 9 in which information necessary for executing programs is written and read, and so-called CD-ROMs, IC cards, etc., which are digitized (numerical). A recording medium 10 on which map information is recorded, and a v-RAM (Video
o RAM) etc.') Luk7Fic memory 11,
Graphic data such as a map sent from the CPU 7 is drawn in the graphic memory 11 and CR as an image.
It is composed of a graphic controller 13 that controls the display on a display 12 such as a T. The input device 14 consists of a keyboard or the like, and various commands and the like are issued to the system controller 5 by the user's keystrokes.

Map information is recorded on the recording medium 10, and its data structure will be explained below.

First, as shown in Figure 2 (A), let's take a look at Japan's plan, for example,
6384 (=214) [Divide into m1 square meshes, and one mesh at this time is called a territory. The territory is Territory No. (TX.

Ty), and each territory is assigned a territory number based on, for example, the lower left territory in the figure. Territory No. is the current location (Crntx.

CrntV). Territory is the largest management unit in this data structure. The entire structure of the map data file is shown in Figure 2 (B).
As shown in Figure 2 (C), the D file contains the territory number, the start address in the file for (TX, TV), the latitude of the bottom left of the territory (real number), and the longitude of the bottom left of the territory (real number). , geomagnetic declination (real number), and other data are written for each territory.

The territory file is the most important file in this data structure, and various map data and data necessary for map drawing are written therein. In FIG. 3A, the navigation I'D and section table are files for searching roads and intersections in navigation, the picture ID is a file for display management, and the data from road section data to intersection data is actual map data. The map data is
As shown in Figure 3 (B), it has a hierarchical structure, with the bottom layer being polygon data for rivers, oceans, lakes, etc., and the top layer being roads, etc.
Line data such as railways, etc., above that is character data such as various marks, above that is character data such as place names, and the top layer is intersection data. The intersection data on the top layer is data used for intersection drawing, which will be described later, and is not displayed on the display.

Next, as shown in FIG. 4(A), one territory is divided into, for example, 256, and the resulting 1024
(2”) [m] It is called a square mesh unit.

This unit is similarly managed by unit No. (NX, NV), and its (7) No.

(Nx, Ny> is the current location (Crntx, Crnty
). A unit is an intermediate management unit, and map information is recorded in this unit, and a collection of 256 units constitutes a territory file. Maps are drawn based on this unit, so it can be called the basic unit of drawing. The navigation ID file contains the unit f'JO as shown in FIG. 4(B).

Line start address, intersection start address, road section start address in the (Nx, Ny) file,
Data such as the intersection start address is written for each unit.

Furthermore, as shown in FIG. 5(A), one unit is divided into, for example, 16 parts, resulting in 256 (28
) [m] square mesh is called a section. This section is similarly managed by section No. (Sx, Sy), and the current location (Crntx) is
, Crnty). A section is the smallest management unit, and information on line segments (roads, etc. are expressed by connecting line segments) and intersections within this area is shown in Figure 5 (B).
As shown in (C), a sixth section table is added as a section table.
As shown in Figures (A) and (B) and Figures 7 (A) and (B), it is registered in the territory file as section data.

Furthermore, as shown in FIG. 3(A), the territory file includes a file called picture ID for display management. In this embodiment, the scale of the map data is set to three types, for example, 1/25,000, 1/50,000, and 1/100,000, and the actual map data is set to 2.5, which is the largest scale. I only have one in a million. The map of each scale is divided into areas as shown in each figure (A) of FIGS. 8 to 10, and this area is area No. <Anx.

AnV)T" managed. Area No., (ArlX
, And) is the current location (Crntx, Crnty
). If the scale is 1/25,000, area N
o, and unit number are the same, and in the case of 1/50,000, one area is equivalent to 4 unit files, and 10
In the case of 1/10,000, one area will have 16 units. In addition, the picture ID for each scale includes figures 8 to 1.
As shown in each figure (B) of Figure 0, the start addresses and data sizes of polygons, lines, characters, and character data necessary to display a map of that scale are recorded.

Next, polygon data and line data will be explained. The polygon data and line data are shown in Figure 11 (A>
As shown in FIG. 12(A), it is represented by a connected vector (line segment) represented by a starting point and an ending point. Here, if you represent a map at 1/50,000 or 1/100,000 using map data at the largest scale of 2°/50,000, the distance between the start and end points will shrink, so as far as you can see on the display, all points will be In some cases, it may not be necessary to display the . Taking this into consideration, the information that can be omitted visually when displayed on a display is shown in Figure 11 (
B) and as shown in FIG. 12(B), each thinning bit of polygon and line data is entered in advance. Then, by checking the thinning bits when displaying each scale and removing the points containing information in the thinning bits as necessary, the line segments to be displayed (muku1
~ le) can be reduced in number.

Furthermore, as shown in FIG. 13(A), serial numbers (x n, yn) are assigned to all intersections within one unit. By the way, intersections include orthogonal type, Y-junction,
There are various types of intersections, such as five-way intersections, but especially at intersections where there are multiple passages with similar directions, when passing through this intersection, the sensor accuracy, total error, map accuracy, etc. may result in incorrect road selection, and the display may not show up. There is a possibility that the road on which the current location is displayed does not match the road on which the driver is actually driving. Therefore, for such intersections, the 13th
As shown in Figure (B), difficulty level data indicating the difficulty level of the intersection is stored in the difficulty level bit in the intersection data. When passing through an intersection, by performing processing based on this difficulty level data, it is possible to prevent the wrong road from being selected. The processing will be explained later.

Next, regarding the display of map data, a case will be described in which, for example, a V-RAM is used as the graphic memory 11. As shown in FIG. 14(A), the display configuration is a 512 (dot) x 512 (dot) V-RAM.
The screen above is divided into 16 areas, and each area has an independent 1
Display multiple maps. One area is one unit of 128 (dots) x 128 (dots), and one
By dividing into 6 areas, 1 area is 32 (dots) x 32
(dot) (Figure 14 (B), (
(See C). The actual in-vehicle display has 256 (dots)
A 56 (dot) area (encircled by a thick line) is displayed, and this area moves on the V-RAM to express the movement of the vehicle's current location.

Next, the basic procedure executed by CPLJ7 will be explained according to the flowchart of FIG. 15.

The CPU 7 first initializes the program to execute it (step 81), and then determines whether the current location of the vehicle has been set (step 82). If the current location has not been set, a current location setting routine is executed (step S3), for example, the current location is manually set using the keys on the input device 14. Next, the mileage is set to zero (step S4), and it is then determined whether there is any key input from the input device 14 (step 85).

If there is no key personnel available, a map of the area around the current location is displayed on the display 12, and the current location of the vehicle and its direction are displayed on this map using, for example, a vehicle mark, and when the vehicle moves, the map scrolls as the vehicle moves. Furthermore, when the vehicle position is about to exceed the range of the map data currently on the graphic memory 11, the necessary map data is read out from the recording medium 10 and displayed on the display 12 (step 36).

If there is key human power, the current location is reset (step S7) and sensor correction (step S8) according to the input data.
, destination setting (step 89), and map enlargement/reduction (step 810) routines are executed.

In addition, the CPU 7 receives an interrupt from the timer, and the 16th
As shown in the figure, a process is performed to constantly calculate the direction of the vehicle based on the output data of the geomagnetic sensor 1 and the angular velocity sensor 2 at regular time intervals (steps 811 and 512).

Furthermore, when data is input from the mileage sensor 3, the CPtJ7 performs interrupt processing by the mileage sensor. In this interrupt process, as shown in FIG. 17, the current location is calculated from the travel distance and direction (step 513), right turn or left turn is determined (step 514), and turning into the road (step 514) is performed.
step 515), intersection pull-in (step 816),
Retraction based on mileage (step 517) is performed. Note that each process in steps 313 to 817 will be explained in detail later.

In addition, the latitude and longitude data obtained from the GPS device 4 are
As shown in FIG. 18, the data is processed by a GPS data reception interrupt, and the coordinates are converted as current location data (step 818).

The travel distance of the vehicle is determined from the output of the travel distance sensor 3. As this distance sensor 3, for example, one configured to calculate the distance traveled by integrating the distance of one revolution from the number of rotations of the car's so-called speedometer cable (637 revolutions/km according to the JIS standard) is used. However,
It is inevitable that errors will occur in the travel distance obtained due to the accuracy of the sensor 3. In addition, not only the VI degree of the sensor 3, but also the accuracy of the map, changes in tire air pressure, slips, etc. are factors that cause errors in the travel distance. Therefore, unless the travel distance is corrected frequently, it will not be possible to accurately determine the distance.

Therefore, by calculating the distance correction coefficient rs from the actual measured distance obtained from the output of the mileage sensor 3 and the distance obtained from the map data, and performing distance correction using this correction coefficient rs, the mileage can always be accurately determined. It can be detected.

Further, the direction of the vehicle is determined from the output of the geomagnetic sensor 1. This azimuth detection method is described in Japanese Patent Application No. 60-282341 filed by the present applicant and others.

The north indicated by this geomagnetic sensor 1 is magnetic north, not map north. Therefore, if the magnetic north is deviated from the map north, the estimated current location P+ obtained from the output of the geomagnetic sensor 1 when traveling a certain distance from the reference position will be different from the actual current location P2, as shown in Figure 19. , a deviation will occur. Therefore, it is necessary to convert the orientation determined by the geomagnetic sensor '1 into a map orientation.

As shown in FIG. 20, this conversion work is performed using a rotation angle determined by two-dimensional geometric coordinate conversion, that is, an orientation correction coefficient θS. This azimuth correction coefficient θS varies depending on the region, and the mounting error that occurs when the geomagnetic sensor 1 is attached to the vehicle body also varies depending on the error. This direction correction coefficient θS
As shown in FIG. 21, the coefficient can be set to zero and the vehicle travels between two points whose positions are known, and can be determined from the error between the current location and the arrival point determined by inertial navigation.

By correcting the direction using this direction correction coefficient θS, the direction of the vehicle can always be accurately detected.

The method for calculating the distance correction coefficient rs and the direction correction coefficient θS is described in Japanese Patent Application No. 60-282344 by the present applicant.

Next, the mileage sensor 3 executed by CPLJ7
The interrupt processing procedure will be explained according to the flowchart of FIG. 22. The estimated current location is calculated at any time based on the output data of the mileage sensor 3, and this routine is called at a predetermined timing as the current location recognition routine.

First, the CPU 7 determines whether or not the unit distance 10 has been run (step 520). Here, the unit distance refers to a certain distance actually traveled by the vehicle, for example, 20 [m]
is set to . Then, this routine is executed every certain distance traveled, and first, the relationship with the map data, that is, the distance 11ijm to the nearest line segment, the angle θn between the line segment and the north of the map, etc., as shown in FIG. 23, are determined. Furthermore, if there are two or more line segments approximately equidistant, this is indicated with a flag (
Step $21). In addition, the presence or absence of nearby intersections may also be determined here. Subsequently, the distance ρm is a preset threshold value j! It is determined whether or not th has been exceeded (step 522). If not, the error valve ρ visit is corrected, assuming that the current location is near the haboso line segment (step 523). This error amount βm is calculated as follows:
This is due to detection errors in map data, digitization errors in map data, etc.

This correction is done in order to recognize the current location next time.
This is because it is necessary to cancel those errors. Thereafter, the process proceeds to a pattern pull-in routine to be described later.

On the other hand, if the distance @fJra exceeds the threshold N th , then it is determined whether the vehicle has made a curve (turn right or left) (step 524). The curve detection method will be described separately later. If the curve does not occur, the difference between the vehicle's traveling direction θ obtained from the output data of the geomagnetic sensor 1 and the line segment angle θn is compared with a set reference value θth (step 525). If 1θ-θnl>θth, the process proceeds to the pattern pull-in routine without doing anything. Examples of this case include, for example, when the vehicle is heading toward the end of a crossroads, or when the vehicle is driving on a road that is not stored as map data. Next, it is determined whether there is a more difficult intersection with a smaller angle, such as a Y-junction, in the vicinity (step 826). If there is a Y-junction nearby, for example, there is a possibility that the vehicle will be drawn into a road different from the one on which it is currently running, so the process proceeds to the pattern drawing routine without doing anything.

Data indicating the difficulty level of the intersection is inserted into the difficulty level bit of the intersection data in advance as shown in FIG. 13(B) when converting the map into numerical values, so the CPU 7
All you have to do is check this bit.

If the above two conditions do not apply, it is determined that an error has occurred in the sensor or the like and the road data is starting to deviate from the road data. In this case, the current location is corrected, that is, it is included in the road data (step 527).

As shown in Fig. 24, the new estimated point Pcpd of the current location is the point that intersects with the perpendicular line drawn to the nearest neighbor from the current estimated point Pcp calculated from the relative relationship from the previous estimated point Pppd obtained from the sensor output. and change the display etc. The distance lll1 and the coordinates of the current estimated point Pcp (
X m, Y m) are the correction values at that point,
It is stored for use in the pattern pull-in routine described in Section 3.

If it is determined in step 824 that the vehicle has curved, the intersection pull-in routine is entered. First, the travel distance gc from the point previously recognized as an intersection is calculated, and this travel distance Il! tg
C multiplied by a constant value aC is set as an intersection detection threshold N cth (step 828). The constant value aC is a value related to the accuracy of the mileage sensor 3, and is, for example, 0.05.
The value shall be approximately.

The distance ρC from the current location PCD to each intersection is calculated from the intersection data included as map data (step 829), and it is determined whether there is an intersection where Jc<ρCth (step 530).

In step 830, it is also determined whether the distance is within a certain distance I11 range (for example, about several hundred meters). Here, if no intersection exists, the process proceeds to a pattern pull-in routine. Further, if it is determined that there are a plurality of nearby intersections and the distances pc to the intersections are about the same and that the nearby intersections cannot be specified (step 531), the process proceeds to the pattern pull-in routine.

If a nearby intersection is specified, that intersection is selected as a new current location estimation point P cpd (step 532). At this time, distance 1C to the intersection and current location P
The coordinates of cp (X C, Y C) are stored as the amount of retraction. Furthermore, the estimated current location point pcpd is stored (updated) as a new recognized intersection. Thereby, when the current location of the vehicle deviates from the road on the map displayed on the display 12, the current location of the vehicle is forcibly placed on the intersection on the map, so-called intersection pull-in is performed.

Next, the distance and direction correction coefficients rs and θS are updated based on the coordinates of the intersection recognized last time, the sum of correction values therefrom, and the coordinates of the current location (step 533). In this way, if the distance and direction correction coefficients rs and θS are updated every time an intersection is recognized or when the distance between intersections is long, every time a certain distance ρp is traveled, the current location can be estimated with higher accuracy. becomes possible.

Next, pattern pull-in will be explained. This routine is executed after running a certain distance tliρpO. The distance tnjpo has a value of, for example, 1000 [m].

Note that if intersection recognition is performed in step S31, the travel distance is reset.

While traveling on a constant road 11iJ)po, the distance fltth to the nearest line segment is measured n-1)po/ρ0 [times], and n error correction amounts ei are stored as data. There is. Furthermore, for one measurement, the difference between the error correction amount eil in the previous measurement and the current error correction amount ei is calculated as a change fici (ei - ei-1).

When it is determined that you have run a certain distance 1 po (Step 8)
34), step 835) to calculate the variation in the value of C1 between changes, and then the deviation α6). Then, this value α is compared with a predetermined threshold αthh (step 5
37). This value α is determined by taking into account detection errors of each sensor, travel distance, and the like. If α>αthh, it is determined that pattern pull-in is not possible, and pattern pull-in is not performed. On the other hand, if α<αthh, it is further determined whether or not a pull-in is currently being carried out (step 838). If the pull-in is not being carried out, that is, if the current location is at a position outside of the road data, the nearest neighbor of the current location A withdrawal to the minutes is performed (step 539). Furthermore, step 540), α
<When αthfJ, the distance and direction correction coefficient rs
, θS are updated (step 541).

With the above method, it is possible to re-enter another road after driving off the road. In other words, if you drive on a road that has not been digitized and then drive on a digitized road again, that road will be recognized after you have traveled a certain distance, making it possible to accurately estimate your current location. Also, for a constant distance gpO, a longer distance j!
It is also possible to calculate the deviation for t and shorten the distance ρpO to improve accuracy and shorten the response time. The situation is shown in FIGS. 25(A) and 25(B).

In the above manner, the pull-in to the nearest intersection or the pull-in to the nearest-neighbor valve is performed. ) is required.

Searching for the nearest intersection or nearest line valve involves a lot of line segment and intersection data, that is, if the search area is wide, it takes time, and the current location, which changes from moment to moment, cannot be displayed smoothly. Become. However, in this embodiment, as is clear from the data structures shown in FIGS. 2 to 5, the search area from the current location is made as small as possible, and the data of line segments and intersections that fall into that area are managed. By having data (section data, section table), it is possible to search for line segments and intersections within the minimum unit section as a search area, thereby reducing the time required for the search. Hereinafter, the procedure executed by the CPU 7 to search for the nearest line valve and the nearest intersection from the current location will be explained according to the flowchart of FIG. 26.

First, the CPU 7 determines the current location (Crntx, Crnty
) to Territory No., (Tx, Ty), lnit N
O, (NX, NY), Section No., (Sx.

Sy) are determined (steps 850 to 552).

This can be determined by a simple calculation (division) since each area is divided into units of 2 degrees. Next, using the section as a search area, the line segment and intersection data existing in the section are loaded by referring to the section table and section data (steps 853 to 55).
5). Based on the loaded data, calculate the distance from the current location to all line segments in the search area (the length of the perpendicular to the line segment) and the distance to all intersections, and compare them to find the nearest neighbor valve. The nearest intersection point may be obtained (step 856). The speed of searching is proportional to the number of line segments and the number of intersections, but according to the search method based on the data structure described above, the search area (section) is small and the number of line segments to be calculated is proportional to the number of line segments and intersections. Since there are fewer intersections and intersections, high-speed searches are possible.

By the way, when displaying map data at various scales in a navigation system, if you have map data at all scales, the display can be done easily and quickly, but the disadvantage is that the data size increases. There is. On the other hand, if you only have map data at the largest scale and want to represent other scales by simple reduction,
Although the data size is smaller, the disadvantage is that the display is slower.

In contrast, in this embodiment, as is clear from the data structure shown in FIGS. 8 to 10, in order to reduce the data size, only the map data of the largest scale is included, and in addition, map data of other scales are included. When displaying data, display management files and thinned data are used to speed up the display. Hereinafter, the procedure for enlarging/reducing the map executed by CP'tJ7 will be explained according to the flowchart of FIG. 27.

When the CPU 7 first determines that the scale to be displayed has been manually entered from the input device 9, (step 560),
Find the area number (AnX, And) corresponding to the scale from the current location (Cr'ntx, Crnty) (steps 861-563), then refer to the picture ID of that scale (steps 864-866), and obtain the start address and data. The map data is loaded depending on the size and drawn in each of the 16 areas on the V-RAM (step 567). In this way, the picture ID for display management makes it possible to refer to the identified map data to be displayed (as the scale becomes smaller, roads, place names, etc. to be displayed as hills are narrowed down to important ones). This makes it possible to achieve faster speeds.

Also, for polygon and line data, as explained in Figures 11 and 12, information to that effect is included in the thinning bits of points that can be omitted from display, so When drawing maps of 1/100,000 or 1/100,000,
The thinned out bits are checked (step 868), and the points targeted for thinning are drawn (step 569). In this way, when the map is reduced, the number of line segments to be displayed can be reduced by thinning out the points that can be visually omitted when displayed on the display. This makes it possible to achieve faster speeds.

In the above embodiment, a thinning bit 1- is provided for the polygon and line data, and information to that effect is entered in the thinning bit at points whose display can be omitted.
Plot polygon and line data at equal intervals, and when displaying, thin out data according to a predetermined rule (for example, skip 1 if the scale is 1/50,000, skip 4 if the scale is 1/100,000, etc.) The same effect can be obtained.

Next, step 32 in the flowchart of FIG.
The method for determining the curve (right turn/left turn) in No. 4 will be explained.

Basically, a right turn or a left turn is determined based on the output data of the azimuth sensor, for example, the geomagnetic sensor 1, and when a turn is detected, the intersection is pulled through the process from step 828 onwards. However, the geomagnetic sensor 1 is sensitive to external disturbances, and its output data will contain a large error when a large vehicle (for example, a truck or a bus) passes over a railroad crossing, a railway bridge, or a large vehicle (for example, a truck or bus) on its own weight side. If this data is used as it is to judge whether to turn right or left, the vehicle will mistakenly think that the vehicle has turned when it was traveling straight and will pull into the intersection even though it is not even an intersection, causing the current location to deviate from the correct location.

Therefore, in this embodiment, the radius of curvature and vehicle speed are included in the criteria to determine whether the vehicle has turned.
This makes it possible to accurately judge whether to turn right or left. Below, C.P.
The procedure of the right-turn/left-turn judgment method executed by tJ7 will be explained according to the flowchart of FIG. 28. First, the CPU 7 moves from a certain distance (for example, 15 [m
l)), when the vehicle faces over a certain angle (for example, 40 degrees), it is determined that the vehicle has made a curve (right or left turn).
step 370). However, when a curve is made, the radius of curvature R at that time is a constant value Rm, which is the minimum radius of rotation of the judgment criterion.
in (for example, 3.5 [ml) or less,
It is determined that the data is wrong, and it is not determined that the data is curved (step 571).

This is because the vehicle cannot turn below its minimum turning radius. Furthermore, if the vehicle speed S exceeds a certain maximum judgment standard speed Smax (for example, 40 [Km/h]), it is normally unthinkable to turn at an intersection. (Step 572).Furthermore, to determine whether to turn right or left, for example, if the bundle is azimuth 0 degrees, north is azimuth 90 degrees, west is azimuth 180 degrees, and south is azimuth 270 degrees, then the direction is increased or decreased. (Step 573).In other words, the direction in which the bearing increases is a left turn (Step 874), and the direction in which the bearing decreases is a right turn (Step 575).
It is possible to determine a left turn.

Note that the radius of curvature R is determined at a certain point a, as shown in FIG.
Let θ [radian] be the angle between the vehicle's direction at point A and the vehicle's direction at point A, which has traveled a certain distance 1jij from point a.Since ρ=R・θ, it can be obtained by transforming this equation. It can be determined from the following formula R=1/θ.

In addition, the current location is controlled so that it is always located on the road shown on the map displayed on the display by the intersection pull-in, etc. performed by the process according to the flow shown in Figure 22. However, for example, if the distance between intersections is long, During this time, small corrections are made to the current location, but due to distance errors due to sensor accuracy, calculation errors, map accuracy, etc., there may be a distance difference between the actual current location from the last intersection and the current location on the map. occurs, and the error increases as the distance between intersections increases. In such a case, if there are a plurality of intersections close to each other in the vicinity of the intersection where the vehicle should pull in next, there is a possibility that the vehicle will pull in at the wrong intersection. Therefore, in this embodiment, after the vehicle has traveled a certain distance between intersections, a so-called distance-based pull-in is performed. Hereinafter, the procedure will be explained according to the flowchart of FIG. 30.

First, initial values are set (step 580). As this initial value, a fixed current location is required, but this can be set by the user first, or the current location when pulling into a fixed point such as an intersection can be used, or if the current location has already been fixed, If you register the data in non-volatile memory, you only need to set it once. The travel distance is reset to zero at this confirmed current location (step 581), and while constantly monitoring whether the driver has turned at an intersection (step 582) or has run a certain distance (step 583), the travel distance is reset to zero based on the map data when the user has run a certain distance (step 583). A point at a certain distance from the point on the map where the zero was reset (previously detected position) is found, the current location is changed to that point, and the pull-in is performed (step 584). While driving a certain distance, the vehicle's current location is drawn on the road on the map displayed on the display by drawing a perpendicular line to the line segment closest to the top and drawing the line to the intersection (step 385). can be set. If it is detected that the vehicle has turned, the intersection pull-in is performed (step 886). This intersection lead-in is as described above.

In addition, the distance traveled can be effectively used to determine whether the vehicle has turned at an intersection. In other words, it is possible to determine a curved intersection from the map data based on the distance between the intersections and the travel distance.

As explained above, according to the present invention, each position on the road on the map is digitized and stored as map data, and the vehicle travels a certain distance based on the output of the travel distance sensor. Each time a situation is detected, a position on the road that is a certain distance away from the previously detected image n on the road is detected based on the map data, and this detected position is set as the current location. Even if the distance between them is long, the distance 1 due to sensor accuracy, calculation error, map accuracy, etc. Since the i error can be corrected every fixed distance, the current location of the vehicle can always be accurately recognized.

[Brief explanation of the drawing]

FIG. 1 is a block diagram showing the configuration of an in-vehicle navigation device according to the present invention, and FIGS. 2(A) to 13(C) to 13(
A) and (B) are diagrams showing the data structure of map information stored in the recording medium in FIG. 1, and FIGS. 14 (A) to (C)
15 to 1 are diagrams showing the screen configuration on V-RAM.
FIG. 8 is a flowchart showing the basic procedure executed by the CPU in FIG. 1, FIGS. 19 to 21 are diagrams showing how to obtain the direction correction coefficient θS, and FIG.
23 and 24 are diagrams showing the positional relationship between the current location on the map and the nearest line segment, and FIG. Figure 26 is a flowchart showing the procedure for searching for nearest line segments and intersections, Figure 27 is a flowchart showing the procedure for enlarging/reducing the map, and Figure 28 is a diagram showing how to make a right turn/left turn. Flowchart showing the procedure of the determination method, No. 29
The figure shows how to determine the radius of curvature, and FIG. 30 is a flowchart showing the procedure of the pull-in method based on travel distance. Explanation of symbols of main parts

Claims (1)

[Claims] Each position on the road on the map is digitized and stored as map data, and each time it is detected that a certain distance has been traveled based on the output of the mileage sensor, the previous location on the road is calculated based on the map data. A method for recognizing the current location of a vehicle, comprising: detecting a location on the road that is a certain distance away from the detected location, and recognizing this detected location as the current location.