JPH10185601A - Position detection device - Google Patents

Abstract

(57) [Summary] The present invention uses, as road map data, data that stores the coordinates of the starting point of a link constituting a road, and limits the estimated vehicle position caused by a vehicle position error and a road map error. the outer circumference of the error range E, links the within the scope E + U which added the length L _max of the longest ones of the links in the road map data, determine the link start coordinates of link exists, the determined Is adopted as a candidate for a map matching target link. [Effect] The number of links as candidates can be reduced, and a reduction in processing time as a whole can be expected.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a position detecting device for detecting the position of a vehicle traveling on a road on a map.

[0002]

2. Description of the Related Art Conventionally, in order to detect the position of a vehicle running on a road, a distance sensor, a direction sensor, and a processing device for performing necessary processing on output signals from both sensors have been provided. Autonomous navigation has been proposed in which the current position data of the vehicle is obtained while integrating the distance change amount and azimuth change amount caused by running of the vehicle, but the distance sensor and the azimuth sensor necessarily have There is a problem that the errors in the current position data are accumulated as the running continues, and the errors included in the obtained current position data are also accumulated.

In consideration of such problems and on the premise that a vehicle travels on a road, a current position data obtained based on the autonomous navigation and a road stored in a map memory in advance are used. Comparing with the map data, the deviation amount (distance difference and azimuth difference) of the current position data from the road is calculated as a cumulative error, and the current position data is corrected for the cumulative error. A map matching process has been proposed in which the current position data is made to match the road map data (see Japanese Patent Application Laid-Open No. 61-56910, etc.).

At the time of executing the map matching process, in order to reduce the amount of calculation required for the process, the directions of the roads stored in the map memory are classified, and the roads having the directions belonging to the classification are grouped for each classification. A proposal has been made to search for a relevant road from a group of roads in which the detected azimuth of the vehicle and the azimuth of the road are similar when specifying the target candidate road (see Japanese Patent Application Laid-Open No. 1-260312).

According to this method, the number of candidate roads can be reduced, so that the efficiency of map-map matching and the required time can be reduced. However, actually, when performing the map matching process, that is, when performing the map matching between the detected direction of the vehicle and the direction of the road, the target road is not limited and is within a certain range (for example, the estimated position of the vehicle). Selected from roads within the surrounding error range).

Conventionally, when a target road is selected from the roads in the "fixed range", whether a vector (hereinafter, referred to as "link") representing the road is included in the "fixed range" You must decide whether or not. That is,
A line segment is determined from the start and end coordinates of the link, and if even a part of the line segment is within a “certain range”, it is determined that the line segment is within the “certain range” and the line segment is If it does not fall within the “fixed range” at all, it is determined that it is outside the “fixed range”.

FIG. 10 is a diagram for explaining this determination method. FIG. 10 (a) shows a link outside the “fixed range”, and FIGS. 10 (b) to 10 (e) show a link Link within "range".

[0008]

However, with this method alone, there is a drawback in that it takes a long time to determine whether or not it is within a “certain range”. Therefore, there is a demand to reduce the number of links to be determined as much as possible. In view of the above, the present invention reduces the matching processing time by selecting an optimal one as a candidate road limiting condition when performing a map matching process based on the position and orientation of a vehicle obtained by autonomous navigation, satellite positioning navigation, or the like. It is an object of the present invention to realize a position detecting device that can be shortened.

[0009]

The position detecting apparatus according to the present invention uses, as road map data, data storing the coordinates of the starting point of a link constituting a road, and it is used for errors in vehicle position and road map errors. by the outer periphery of the range E of the limit error of the vehicle estimated position resulting range added length L _max of the longest ones of the links in the road map data E +
In U, there is provided a link selecting means for obtaining a link having the coordinates of the link start end, and the link obtained by the link selecting means is adopted as a candidate for a map matching target link (claim 1). .

According to the above configuration, before selecting a link to be subjected to map matching, a link having the coordinates of the start end of the link within the range E + U is selected and adopted as a candidate for a link to be subjected to map matching. The number of candidate links can be reduced. In addition, since it is only necessary to make a simple determination as to whether or not the coordinates of the link start end are within the range E + U, the increase in the determination time is minimized. Therefore, it is possible to expect a reduction in the overall processing time due to a decrease in the number of candidate links rather than an increase in the determination time.

According to the second aspect of the present invention, the "coordinates at the beginning of the link" are only replaced by "coordinates at the end of the link", and the substance of the invention is the same as that of the first aspect.

[0012]

Embodiments of the present invention will be described below in detail with reference to the accompanying drawings. FIG. 1 is a block diagram showing one embodiment of the position detecting device of the present invention. The position detection device includes a traveling distance detection unit 1 and a traveling direction detection unit 2
And a road map memory 3 in which road map data of a predetermined range is stored in advance, a traveling distance detection signal and a traveling direction detection signal output from the detection units 1 and 2, and a road stored in the road map memory 3. An estimated position calculating unit 4 that calculates an estimated position based on the map data and the evaluation data output from the matching evaluation unit 6; and a road map data stored in the road map memory 3 and the estimated position calculating unit 4. A target link extraction unit 5 that extracts a target link by using the output position data as an input, and a matching evaluation that evaluates a predetermined magnitude relationship with respect to the target link extracted by the target link extraction unit 5 and outputs a current position. 6.

More specifically, the running distance detecting section 1 has, for example, a magnetic sensor for detecting the rotation of the wheel, and counts the number of sine wave signals output from the magnetic sensor by a counter to thereby detect the running distance of the wheel. A so-called wheel speed sensor having a configuration in which a rotational speed is obtained, and a running distance per unit time is calculated by multiplying count data output from the counter by a predetermined constant indicating the outer circumference of the wheel by a multiplier. Any known configuration such as a vehicle speed sensor configured to calculate the running distance of the vehicle by calculating the running speed of the vehicle based on the Doppler shift or the like and integrating the calculated running distance may be used.

The traveling direction detecting section 2 can use, for example, a gyro that outputs rotation angle data per unit time. Examples of the gyro include a vibration gyro, an optical fiber gyro, and a differential wheel speed sensor. Further, a geomagnetic sensor for detecting a horizontal component of the geomagnetism can be used, and a combination of the geomagnetic sensor and the gyro can be employed.

The road map memory 3 stores road map data covering a predetermined range in advance, and includes a semiconductor memory, a cassette tape, a CD-ROM, and a DVD.
(Digital versatile disk) -ROM or the like can be used. The road map data is obtained by dividing a road map (including a highway national road, a motorway, a national road, a prefectural road, a municipal road, and other living roads) into a mesh shape, and coordinates and adjacent nodes of each mesh unit. Consists of a pointer to the node. A nationally closed network is formed for roads over national roads.

The mesh has a vertical and horizontal distance of about 1 km × 1.
Although it has a square shape of km, it is not limited to this size. A node is generally a coordinate position for specifying a road intersection or a bending point. A node representing an intersection is an intersection node, and a node representing a road bending point (excluding an intersection) is an interpolation point node. That.

FIG. 2 shows the structure of the road map data. Node coordinates are stored for each node in the mesh, and a pointer to a terminal node having the node as a start node is stored.
Although not shown, the actual number of nodes in the mesh is stored corresponding to the mesh. In the structure of FIG. 2, the coordinates of the start node are stored and the pointer to the end node is stored. On the contrary, the coordinates of the end node may be stored and the pointer to the start node may be stored. .

A link between the start node and the end node is a link, which is a directed line segment (including a broken line) along the shape of the road. Based on the distance data Δd output from the traveling distance detection unit 1 and the azimuth data θ output from the traveling direction detection unit 2, the estimated position calculation unit 4 calculates an east-west component Δx (= Δd × cos θ) of the distance. ) And the north-south direction component Δy (= Δd × sin θ), and adding the components Δx and Δy to the previous estimated position data (Px ′, Py ′), thereby obtaining the current estimated position data ( Px, Py) is calculated.

Further, a limit error corresponding to the amount of travel of the vehicle with respect to a range of a limit error (including a distance error, an azimuth error, and an error of a road map) which may be included in the previous estimated position data. By adding the increments of the above, the range of the marginal error that the current estimated position data may have is calculated. Since this marginal error range generally has an elliptical shape, it is conceivable to set the ellipse as it is when setting it on a road map. However, in this embodiment, a rectangular shape is set as shown in FIG. This is because the rectangular shape simplifies the determination as to whether or not it belongs to the marginal error range E. (If it is a rectangular shape, it is only necessary to determine the magnitude relationship of the coordinates. It has to be converted to a curve equation for determination).

It goes without saying that the limit error range E usually extends over a plurality of meshes.
In FIG. 3, a marginal error range E including the estimated position P of the vehicle and four adjacent meshes M ₁ , M ₂ ,
Depicts the M _3, M _4. The target link extraction unit 5 includes:
The link in the marginal error range E is extracted.

If all links in the mesh are targeted, the number is too large, and it is necessary to limit the links.
Therefore, in this embodiment, the target links are limited as follows. When limiting, the road map memory 3
_{Let Lmax be} the length of the longest link among the links constituting the road map data stored in. Then, a band U having a width _Lmax is formed in contact with the outer periphery of the marginal error range E. Further, a link having a start node is searched for in the range E + U thus created. This search may be performed based on the node coordinates of the road map data (FIG. 2). Subsequently, a line segment is determined from the start coordinates and the end coordinates of the link with respect to the link searched as described above,
It is determined whether or not a part of the line segment falls within the marginal error range E (see FIG. 10).

FIG. 4 illustrates some links (represented by arrows in the figure) whose starting node falls within the range E + U. FIG. 5 illustrates a link whose starting end node does not fall within the range E + U. The advantage of this determination method will be described. Let N be the number of links for which it is determined whether or not they are within the marginal error range E. First, the coordinates of the start node are read, and the coordinates of the start node are set in the range E.
It is determined whether or not it is within + U. The read time of the coordinates of the start node per link is t _a , the range E
Assuming that the determination time as to whether or not it is within + U is t _b , the determination time T _{a + b} for all links is T _{a + b} = N (t _a + t _b ). At this time T _{a + b} , it is possible to narrow down links to be determined as to whether or not they are within the marginal error range E. The number of links is reduced from N to (1-α) by narrowing down.
It is assumed that the number has decreased to N (α is a decrease rate).

Then, it is determined whether or not the processing time per link is within the marginal error range E where the processing time per link is the largest for the narrowed down links. Assuming that the processing time per link is t _c , the determination time T _c for the narrowed links is T _c = (1−α) Nt _c , and the total determination time is Ta _{+ b} + T _c = N (t _a + t _b ) + (1−α) Nt _c .

On the other hand, the judgment time in the conventional method is N (t _a + t _c ). Taking these differences, the difference ΔT becomes ΔT = N (αt _c −t _b ) ≒ Nαt _c (t _b is assumed to be sufficiently shorter than t _c ).

Therefore, the processing time as a whole can be reduced by the amount of the link reduction rate α due to the narrowing down. In the embodiments described above, a link having a start node in the range E + U is searched. However, the present invention is not limited to this, and may search for a link having a terminal node in the range E + U. In this case, it is necessary to store the coordinates of the terminal node and store the pointer to the start node as the storage structure of the road map data. FIG. 6 illustrates some links whose end nodes fall within the range E + U, and FIG. 7 illustrates links whose end nodes do not fall within the range E + U.

In the present invention, a link having a start node or end node in the range E + U is searched. According to this search, as shown in FIG.
Although + does not enter into the U, and the link L _a termination node falls within the limits error range E, although the end node does not fall within the scope E + U, the link start node falls within the limits error range E L _b Is thought to be eliminated. However, since the length of the longest link is set to L _max and circumscribed to the limit error range E, a band U of width L _max is formed.
The case shown in FIG. 8 cannot occur, and there is no problem.

In this way, a link existing in the marginal error range E is finally obtained. The matching evaluation unit 6 performs a map matching process on these links. Since this map matching method is publicly implemented, it will be briefly described below with reference to FIG.

FIG. 9 is a diagram showing a part of a road map. Among many links, link L ₀ , link L ₁ starting at node n ₁ , link L ₂ starting at node n ₂ , and node L ₂ the n ₃ with only the link L ₃ to start is shown, the vehicle is as shown by a broken line S, a state that running from the link L ₀ through L ₁ is shown. The dashed-dotted line T indicates the trajectory of the estimated position, a, b, c, and d are branches,
Alternatively, a curve is shown, and E indicates a marginal error range.

First, the matching evaluation unit 6 determines the distance (correction) between the estimated position P of the vehicle and each of the nodes n ₁ , n ₂ , n ₃ at the time when the estimated azimuth of the vehicle has turned largely (turned at the intersection). Value). Then, as the vehicle travels, the distances from the estimated position of the vehicle to the links L ₁ , L ₂ , L ₃ starting from the nodes are added to the distances. This value is called “correction value γ”.

At the same time, the matching evaluation section 6 obtains a heading difference between the estimated heading of the vehicle and the link heading. This azimuth difference is called “correlation degree α”. The matching evaluation unit 6 evaluates the magnitude relationship between the correlation degrees α corresponding to the respective links, specifies the link corresponding to the smallest correlation degree α ₀ ,
One or a plurality of links having a correlation degree α whose difference | α−α ₀ | from the correlation degree α ₀ is smaller than the threshold value are determined.

Then, for the determined link, a change amount Δγ of the correction value γ is obtained, and the change amount Δγ
Determines the smallest link and identifies the current position of the vehicle on this link. Since the amount of change Δγ changes every moment, an average of the latest period may be taken, and this average value may be used as a determination target. At this time, the correction values γ for other links are also kept stored in principle. Therefore, one link and several candidate links are stored as the vehicle travels.

The link is deleted when the degree of correlation α becomes larger than the threshold value or when the amount of change Δγ of the correction value becomes larger than the threshold value. That is, the correlation α
Is performed at predetermined timings, and the registration of the link corresponding to the correlation α that is larger than the predetermined threshold value or the link whose change amount Δγ of the correction value is larger than the threshold value is deleted. The correction value γ corresponding to the link whose registration has not been deleted will be sequentially updated to a new correction value γ in the target link extracting unit 5 thereafter, and the above evaluation will be performed again. Then, by continuing the above-described series of evaluation operations, only one link is finally left under the influence of a road branch or the like, and the position on the remaining link is continuously displayed as the current position.

The embodiment of the present invention is not limited to the above-described embodiment. For example, instead of the traveling distance detecting unit and the traveling direction detecting unit, a GPS (G
(lobal Positioning System) It is also possible to use a receiver. In addition, various design changes can be made within the scope of the present invention.

[0034]

【Example】

(1) The processing of the above embodiment was performed on a road map having 1703 nodes and 4080 links. The limit error range E is 100m x 100m, the longest link length L
_max was set to 500 m. The retrieval time of the start coordinates per node is 83 μsec, and the range E per node
Judgment time of whether it is in + U is 31μsec
Therefore, the time required for processing of all nodes was 1703 × (83 + 31) = 194 msec. By the above selection process, the number of links was reduced to 255.

Next, the termination coordinates of 255 links were determined, and it was determined whether or not the links were within the marginal error range E. The time for extracting the end coordinates per link is 373 μsec, and the time for determining whether or not the link is within the marginal error range E per link is 50 μsec.
Therefore, the time required to process the 255 links was 255 × (373 + 50) = 108 msec. Therefore, a total of 302 msec was required.

(2) Next, the conventional processing was performed. Node 1
The time required to extract the start coordinates of each node was 83 μsec, so the time required to extract the start coordinates of all nodes is 1703 × 83 = 141 msec. Judged if he was in E. The time required was 4080 × (373 + 50) = 1726 msec. Therefore, a total of 1867 msec was required.

[0037]

As described above, according to the position detecting device of the present invention, the number of links which are candidates for map matching target links can be reduced before selecting the target links for map matching. In the shortest time, it is possible to select target links for map matching and execute map matching on these links.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating an embodiment of a position detection device according to the present invention.

FIG. 2 is a structural diagram of road map data.

FIG. 3 shows a marginal error range E including an estimated position P of a vehicle and four adjacent meshes M ₁ , M ₂ , M ₃ ,
Is a road map depicting the M _4.

FIG. 4 is a diagram exemplifying a link whose starting node falls within a range E + U;

FIG. 5 is a diagram illustrating a link whose starting node does not fall within a range E + U;

FIG. 6 is a diagram illustrating a link whose end node falls within a range E + U;

FIG. 7 is a diagram illustrating a link whose end node does not fall within a range E + U;

FIG. 8 shows _a link La in which the start node does not fall within the range E + U and the end node falls within the marginal error range E, and the end node does not fall within the range E + U, but the start node falls within the marginal error range. shows virtually the link L _b fall within the E.

FIG. 9 is a diagram showing a part of a road map for explaining a map matching method.

FIG. 10 is a diagram for explaining a method of selecting a map matching target link.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Running distance detection part 2 Traveling direction detection part 3 Road map memory 4 Estimated position calculation part 5 Target link extraction part 6 Matching evaluation part

Claims (2)

[Claims] An estimated position of a vehicle is determined.
By performing map matching with road map data
The position of the vehicle on the road
In addition, as the road map data,
A vehicle that uses coordinates that have been stored and that is caused by a vehicle position error, road map error, etc.
The road map is located on the outer periphery of the range E of the marginal error between the two estimated positions.
Length L of the longest link in the data _maxWith
The start coordinate of the link exists in the added range E + U
Link selecting means for obtaining a link to be linked, and linking the link obtained by the link selecting means to a map map.
Featured as links for linking
Position detecting device. 2. An estimated position of the vehicle is determined, and the estimated position is
By performing map matching with road map data
The position of the vehicle on the road
In addition, as the road map data,
A vehicle that uses coordinates that have been stored and that is caused by a vehicle position error, road map error, etc.
The road map is located on the outer periphery of the range E of the marginal error between the two estimated positions.
Length L of the longest link in the data _maxWith
Link end coordinates exist in the added range E + U
Link selecting means for obtaining a link to be linked, and linking the link obtained by the link selecting means to a map map.
Status of link for linking or link for map matching
A position detection device, which is employed as a complement.