JPH09229699A - Position sensing device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To offer a position sensing method which allows performing a map matching process to be made on the basis of the position and azimuth of a car acquired by the autonomous navigation method, satellite telemetry navigation method, etc., in which the accuracy of the link azimuth is taken in consideration and which can manage with a less quantity of map data. SOLUTION: The road map data used is such that the coordinates for the starting and ending points of each of links constituting a road are stored in memory, and the azimuth of the link is determined from the coordinates for the starting and the ending point accommodated in the road map data, and when the difference between the azimuth of the link and the sensed azimuth of the car concerned is smaller than the threshold decided while the accuracy of the car azimuth sensing and the error Δθ of the link azimuth originating from the map resolution are taken into consideration, this link is adopted as a one to undergo the map matching or a candidate for it. If greater than the threshold, it is excluded.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a position detecting method 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.

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

As a map memory used in a device that executes this map matching process, there is one that stores the road direction of each road as data (Japanese Patent Laid-Open No. 2-300625).
Reference).

[0005]

However, if the road direction is stored as data, the map data becomes redundant and the range of the map stored as data becomes narrow. Therefore, the road segmented (link)
A method is conceivable in which only the coordinates of the start and end points of are stored and the road direction (link direction) is calculated.

However, when the link length is short, the coordinate resolution at the beginning and the end greatly affects the azimuth accuracy, and the quantization error cannot be ignored. For example, if the coordinate resolution of the start end and the end is 1 m, and the link length is 10 m, the resolution of the link azimuth is about 8 °. Therefore, when executing the map matching process, the accuracy of the link direction on the map must be taken into consideration for roads with a link length of a fixed value or less.

According to the present invention, when map matching processing is performed based on the position and direction of a vehicle obtained by autonomous navigation, satellite positioning navigation, etc., the amount of map data is small and the accuracy of link direction is taken into consideration. It is an object of the present invention to realize a position detecting method capable of performing map matching processing.

[0008]

According to the position detecting method of the present invention, as the road map data, the ones storing the coordinates of the start end and the end of the link constituting the road are used and stored in the road map data. The direction of the link is obtained from the coordinates of the start end and the coordinates of the end, and the difference between the direction of this link and the detected direction of the vehicle considers the accuracy of the direction detection of the vehicle and the error of the link direction on the map. It is a method of adopting the link as a map matching target link or a map matching target link candidate when it is smaller than the threshold value (claim 1).

According to this method, when the difference between the link azimuth and the detected vehicle azimuth is smaller than the threshold value in consideration of the vehicle azimuth detection accuracy and the link azimuth error on the map. Since the possibility that the link is a running link cannot be ignored, the link is adopted as a map matching target link or its candidate. Further, the position detection method of the present invention is such that the difference between the direction of the link on the map and the detected direction of the vehicle is more than a threshold value considering the accuracy of the direction detection of the vehicle and the error of the link direction on the map. This is a method of excluding the link from the map matching target link when the value is large (claim 2).

According to this method, when the difference between the link azimuth and the detected vehicle azimuth is larger than the threshold value in consideration of the vehicle azimuth detection accuracy and the link azimuth error on the map. Since the possibility that the link is a traveling link can be ignored, the link is excluded from the map matching target links.

[0011]

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

More specifically, the traveling distance detecting unit 1 has, for example, a magnetic sensor for detecting the rotation of the wheel, and the number of waves of the sine wave signal output from the magnetic sensor is counted by a counter to detect the wheel. A so-called wheel speed sensor configured to obtain the number of revolutions and calculate the traveling distance per unit time by multiplying the count data output from the counter by a predetermined constant indicating the outer circumference of the wheel by a multiplier. It suffices to have, but it is possible to use a conventionally known configuration such as a vehicle speed sensor configured to calculate the traveling speed of the vehicle based on the Doppler shift or the like and integrate it to calculate the traveling distance.

As the traveling direction detecting section 2, for example, a gyro which outputs rotation angle data per unit time can be used. 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 a semiconductor memory, a cassette tape, a CD-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.
It has a square shape with km. A node is generally
It is a coordinate position for identifying a road intersection or a bending point. A node representing the intersection is called an intersection node, and a node representing a road bending point (excluding the intersection) is called an interpolation point node. Here, the structure of the road map data is illustrated in FIG. 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.

A link connecting the start node and the end node is a link, which is a polygonal line with a direction along the shape of the road. The estimated position calculating unit 4 uses the distance data Δd output from the traveling distance detecting unit 1 and the azimuth data θ output from the traveling direction detecting unit 2 to calculate the east-west direction component Δx (= Δd × cos θ) of the distance. ), And north-south direction component Δ
The current estimated position data (Px, Py) is calculated by calculating y (= Δd × sin θ) and adding the components Δx, Δy to the previous estimated position data (Px ′, Py ′).
Is calculated.

Further, the marginal error corresponding to the traveling amount of the vehicle with respect to the range of marginal error (including the distance error, the azimuth error, and the error of the road map) which may be possessed by the previous estimated position data. The range of the marginal error that the current estimated position data may have is calculated by adding the increment of. 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 this limit error range E usually exists 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 the links in the mesh are considered, the number is too large, so it is necessary to limit the links.
Therefore, in this embodiment, the target links are limited as follows. To limit the number, there are a method of limiting to links within the limit error range E in the mesh and a method of specifying a link having an orientation close to the orientation of the vehicle among the links in the mesh. , Of 2
Adopt the logical product of two methods (and; it does not matter which comes first).

First, the procedure for actually executing the method will be described. The target link extraction unit 5 determines the limit error range E
One or a plurality of meshes having a common part with is specified, and among the nodes included in the mesh, the nodes included in the marginal error range E are extracted. As a result, a link in which both the start node and the end node are included in the limit error range E (see L _{a in} FIG. 3) and only the end node has the limit error range E
Link (see L _{b in} FIG. 3) included in the marginal error range E (see L _{c in} FIG. 3).
Is specified.

Even if the start node and the end node are not included in the limit error range E, as shown in L _d of FIG. 3, there is a link whose middle part is included in the limit error range E. This link L _d may be added as it exists. In the determination of the link L _d, the diagonal point coordinates of the marginal error range E are (X ₁ , Y ₁ ), (X ₂ , Y ₂ ), and the start or end node coordinates are (x _i , y _i ), etc. Let (x _j , y _j ) be the node coordinates of the determination formula (X ₁ <x _i <X ₂ ) and [(y _i <Y ₁ ) or (Y
₂ <y _i )] and (Y ₁ <y _j <Y ₂ ) and [(x
_j <X ₁ ) or (X ₂ <x _j )].

[0022] Incidentally, as shown in L _e of FIG. 3, the link is not contained at all in the limit error range E link L _e are excluded. In the case of actually executing the above method, the end node in the case where the target node is the start node is specified, and the link azimuth is expressed by the following equation: tan ⁻¹ (y _j −y _i ) / (x _j −x _i ), and with respect to the link bearing, it is determined whether or not | vehicle bearing−link bearing | <threshold T ₁ holds, and this determination formula is satisfied. Exclude links that do not exist.

Here, the threshold value T ₁ is determined for each link in consideration of the direction detection accuracy of the direction sensor and the error of the link direction on the map. The accuracy of the azimuth detection of the azimuth sensor is unique to the azimuth sensor and is a constant value (for example, 30 °). The error of the link direction on the map is an amount that changes according to the inter-node distance, that is, the link distance.

A detailed description will be given with reference to FIG. If the peculiar resolution of the map is the east-west direction dx and the north-south direction dy, the error of the bearing θ from the east direction of the link is as shown in FIG. 5, the bearing difference Δθ between the _two links L ₁ and L _2. Becomes
According to the equation, Δθ is Δθ≈ (dx ² + dy ² ) / D (D: link length).

Therefore, the threshold value T ₁ is T ₁ = (accuracy of azimuth detection of the azimuth sensor, for example, 30 °)
It may be + Δθ. In this way, when a link that exists in the marginal error range E for one mesh and has a bearing close to the bearing of the vehicle is determined, the same processing is performed for the other meshes. Eventually, a link existing in the marginal error range E and having an azimuth close to the azimuth of the vehicle is found across the mesh.

The matching evaluation unit 6 performs map matching processing on these links. Since this map matching method has been publicly implemented, it will be briefly described below with reference to FIG. Figure 4 is a diagram showing a part of a road map, a number of links, the link L _0, the link L ₁ to the node n ₁ and the starting end, the link L ₂ to the node n ₂ to start, the node n ₃ Only the link L ₃ that is the starting end is shown, and a state in which the vehicle is traveling through the links L ₀ to L ₁ as shown by a broken line S is shown. The dashed-dotted line T indicates the trajectory of the estimated position, and
b, c, and d indicate branches or curves, and E indicates a marginal error range.

First, the matching evaluation unit 6 calculates the distance (correction) between the estimated position P of the vehicle and each of the nodes n ₁ , n ₂ and n ₃ at the time when the estimated direction of the vehicle largely rotates (at the time of turning the intersection). Calculate the initial 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 unit 6 obtains the 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, the change amount Δγ of the correction value γ is found for each of the determined links, and this change amount Δγ is obtained.
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, as the vehicle travels, one link and some candidate links are saved.

The link is deleted when the correlation degree α becomes larger than the threshold value T ₁ or when the correction value change amount Δγ becomes larger than the threshold value. That is, the correlation α is evaluated at every predetermined timing, and the link corresponding to the correlation α larger than the predetermined threshold value T ₁ or
The registration of the link whose correction value change amount Δγ is larger than the threshold is deleted, and the correction value γ corresponding to the link whose registration is not deleted is sequentially corrected by the target link extraction unit 5 thereafter. The value γ is updated and the above evaluation is 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, and for example, instead of the traveling distance detecting portion and the traveling direction detecting portion, 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.

[0032]

As described above, according to the position detecting method of the present invention, when the target link for map matching is selected, the difference between the direction of the link and the detected direction of the vehicle is detected by the direction of the vehicle. It is adopted as the map matching target link only when it is smaller than the threshold value considering the accuracy and the error of the link orientation on the map, so the criteria for discriminating the links suitable for the map matching target and the links not suitable for the map matching are more accurate. , It is possible to improve the success rate of map matching (Claim 1).

Further, according to the position detecting method of the present invention, when the target link for map matching is selected, the difference between the link azimuth and the detected vehicle azimuth is the accuracy of the vehicle azimuth detection and on the map. If it is larger than the threshold considering the error of the link orientation of, it can be excluded from the map matching target links, so the criteria for distinguishing the links that are suitable as the map matching target links and the links that are not suitable are more accurate, and the map matching succeeds. The rate can be improved (claim 2).

[Brief description of drawings]

FIG. 1 is a block diagram showing an embodiment of a position detection device.

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 showing a part of a road map for explaining a map matching method.

FIG. 5 is a diagram showing a link direction error Δθ when the peculiar resolution of the map is east-west direction dx and north-south direction dy.

[Explanation of symbols]

 1 traveling distance detection unit 2 traveling direction detection unit 3 road map memory 4 estimated position calculation unit 5 target link extraction unit 6 matching evaluation unit

Claims (2)

[Claims] 1. A position detecting method for estimating a current position of a vehicle and specifying the current position of the vehicle on a road based on the estimated current position and road map data. Using the one that stores the start and end coordinates of the link to be constructed, the direction of the link is obtained from the start and end coordinates stored in the road map data, and the direction of this link is detected. When the difference from the vehicle heading is smaller than a threshold value that considers the vehicle heading detection accuracy and the link heading error on the map, the link is considered as a map matching target link or a map matching target link candidate. A position detection method characterized by being adopted. 2. A position detecting method for estimating a current position of a vehicle and specifying the current position of the vehicle on the road based on the estimated current position and the road map data. Using the one that stores the start and end coordinates of the link to be constructed, the direction of the link is obtained from the start and end coordinates stored in the road map data, and the direction of this link is detected. When the difference from the direction of the vehicle is larger than a threshold value in consideration of the accuracy of the direction detection of the vehicle and the error of the link direction on the map, the link is excluded from the map matching target links. Position detection method.