JPH05172576A - Navigation equipment - Google Patents

Abstract

PURPOSE:To efficiently obtain and indicate the shortest route from a start point to a destination point in a map and make the setting of a running route easy. CONSTITUTION:To a CPU1 via an interface 21, a memory 3 storing Japanese road map data and an image display 5 are connected. The CPU1 also operates as a reference part to refer the shortest route and refer it with a program in a ROM12. Among crossing lattice points where more than 3 roads cross in vector processed data, the reference program selects the crossing lattice points to be the object of spread from the destination point to the start point along a certain route, performs the spread of branches and comparison of vector quantity, obtains the shortest route and indicates it on an image display 5.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a navigation device used for running a vehicle.

[0002]

2. Description of the Related Art Generally, when driving a vehicle, a planned traveling route from a certain point (start point) to another point (destination point) is displayed on a map, or the time required for traveling on the route is calculated. Displaying is an effective means for the driver to change the setting of the traveling route and predict the arrival time.

For this reason, various navigation devices have been proposed in the past, for example, Japanese Patent Laid-Open No. 59-195.
In Japanese Patent Publication No. 790 (Gazette 1), a traveling path from a starting point to a destination is approximated to a straight line of X and Y axis components by sliding a bar code around a road map with a displacement sensor. A method of displaying is described, and Japanese Patent Application Laid-Open No. 64-6861.
Japanese Unexamined Patent Publication No. 5 (Gazette 2) describes a technique of displaying a grid where an intersection is located at the current position of a vehicle by superimposing it on a map based on information from an azimuth sensor and a distance sensor.

Further, in Japanese Laid-Open Patent Publication No. 1-141313 (publication 3), a road on a map is divided into branch points, travel times based on attribute information are allocated between the branch points, and these are added to schedule. A technique for calculating the time required for the traveling route is described.

According to these publications, the planned travel route is displayed in a straight line approximation or overlapped with a grid, so that the way from the starting point to the destination point can be visually inspected. Since the time required for the planned travel route can be grasped, all of them give effective information to the driver.

[0006]

However, in these navigation devices, it is possible to intuitively grasp the distance and compare the distances between the routes since the linear approximation data and the lattice display are superimposed. However, if there are many routes from the starting point to the destination point, especially if there is a large area including the starting point and the destination point and you have to scroll the screen to follow the route, which route It is not easy for the driver to select the shortest distance or time, and it is possible to judge whether the route is an efficient route when the route currently planned and the required time are known. It is difficult to do or to choose a future route. The present invention has been made under such circumstances, and its purpose is to achieve the shortest rule.
It is an object of the present invention to provide a navigation device that can quickly display a travel route and can easily set a travel route.

[0007]

According to the present invention, there is provided a memory for storing data approximate to a vector connecting points arranged on a plane with a fixed pattern for a road map, and this memory. A search section for searching the shortest route among possible routes from the starting point to the destination point based on the data in
And a display unit for displaying the shortest route searched by the search unit, wherein the search unit defines an intersection at which three or more vectors intersect and the length of the vector from the starting point to the intersection. If the sum of the heights is taken as the vector quantity at that point, branching from the intersection to be compared from the preset starting point, the new route from the starting point is expanded, and the expanded new route is calculated.
The vector amount a of the intersection located at the tip of the intersection is compared with the vector amount of the intersection already obtained, and the expansion of the route relating to the larger vector amount is stopped, and the vector amount a is known. When it is larger than the vector quantity of the point, it has a function of stopping the expansion of the route relating to the vector quantity a.

[0008]

By requesting the display of the shortest route from the starting point to the destination point, for example, road map data is approximated to a vector connecting points arranged on a plane with a certain pattern, for example, grid points. Create data and store in memory. However, it is also possible to use a memory in which such data is stored in advance. When a starting point and a destination point are set to the data by, for example, a driver or a passenger, when each intersection is sequentially branched and expanded from the starting point side as described above by search, and the expansions collide with each other. Is
The expansion related to the large absolute vector amount at each intersection is stopped, and the shortest route is searched efficiently and promptly. The shortest route thus obtained is displayed by, for example, a CRT screen or voice guidance.

[0009]

DESCRIPTION OF THE PREFERRED EMBODIMENTS FIG. 1 is an explanatory diagram showing the overall configuration of a navigation device according to an embodiment of the present invention. 1 in FIG. 1 is a CPU
(Central processing unit), 11, 12 are RAM, ROM,
Reference numerals 21 to 23 are input / output interfaces, which are incorporated in, for example, a microcomputer mounted on a vehicle. The CPU 1 performs control such as passing of data and commands between devices connected to the CPU 1 and, in this embodiment, the road of road map data stored in a memory 3 described later. On the other hand, a vectorization processing unit that approximates a vector connecting grid points of XY coordinates, and the shortest rule from the starting point to the destination point based on the data vectorized by this processing unit. It also serves as a search unit that searches

A road map data memory 3, a graphic controller 4, and an amplifier 61 are connected to the CPU 1 via an interface 21, and the graphic controller 4 and the amplifier 61 respectively have an image display section 5. And the voice display unit 6 is connected. Further, the memory 3 stores, for example, all road map data of Japan.

The image display unit 5 is composed of, for example, a CRT and has a role of displaying a road map cut out from the memory 3 and a shortest route searched by the search unit (CPU 1 in this example). In addition, the voice display unit 6 has the shortest rule.
After the vehicle is searched for, the vehicle is provided to display the traveling direction of the next intersection and the like by voice so as to drive the shortest route, if necessary.

Further, the CPU 1 is provided for setting the cut-out area of the road map data in the memory 3, scrolling the image on the image display unit 5 or setting the starting point and the destination point from the driver's seat. The touch panel T is connected via the interface 22, and the distance sensor S1 and the direction sensor S2 for detecting the traveling distance and the direction of the vehicle, respectively, are connected via the interface 23.

An example of vectorization processing of road map data executed by the CPU 1 will be described below.
First, the CPU 1 uses the road map data in the memory 3 to extract the data cut out by operating the touch panel T from the RAM 1
1, the vectorized program in the ROM 12 is read out, and the following processing is performed. That is, as shown in FIG. 2, grids (thin lines) arranged at the same vertical and horizontal intervals are overlapped on a predetermined road map data (thick line), and one grid is set as shown in FIG. When the intersection of the road map data and the grid is on the line segment a, it is at the grid point A, when it is on the line segment b, it is at the grid point B, and when it is on the line segment c, it is at the grid point. When the point C is on the line segment d, the intersections are approximated to the grid points D, and the approximated grid points are connected as a vector to obtain vectorized data. However, the midpoint of A and B is A, the midpoint of B and C, or C and D
The middle point is close to C, and the middle points of D and A are close to D. If the approximated grid point is 1, no vector is assigned (invalid). The long two points are valid. It should be noted that for a one-way road, a vector is assigned only in that direction, and a vector is assigned in both directions other than that direction.

FIG. 4 shows an example of conversion for approximating the intersections of the road map data and the grid into grid points, and FIG. 5 shows vector data obtained by vectorizing the road map data shown in FIG. .. However, in FIG. 5, the vector is shown by a simple straight line for convenience.

Regarding the starting point and the destination point, among the grid points (effective grid points) to which the road data are approximated, the effective grid point closest to the starting point (target point) is set as the starting point (target point). )
Is approximated as. In this approximation processing, for example, square areas each having one side k, 2k, ... nk are sequentially generated until the effective grid point exists around the starting point, the search range is expanded, and all the existing effective grid points are detected. This can be performed by calculating the straight line distance from the starting point and approximating the starting point to the minimum effective grid point among them.

In the above example, the start point and the end point of the vector are in contact with the grid points of the grids orthogonal to each other. The start point and the end point of the vector may be in contact with a set of points arranged in a fixed pattern on a plane such as an array. However, when the grid points are used as in the above-mentioned example, since a certain point is equidistant from the other four points vertically or horizontally adjacent to each other, a line segment of length 1 is assigned and adjacent to each other in the diagonal direction. Since a line segment having a length of 2 ^1/2 and an angle of 45 degrees can be assigned to the other four points, there is an advantage that the calculation is simplified. Regarding the relationship between the distance between grid points along the grid and the actual length, for example, 500m in the city and 1 in the suburbs
The length of km is set as the lattice spacing. The vectorized data as described above may be stored in advance in the vectorized data memory 31 composed of, for example, a ROM shown by a chain line in FIG. 1 corresponding to the Japanese all-road map. In this case, vectorization processing in the CPU 1 is unnecessary.

Next, based on the vectorized data, the CP
The search for the shortest route executed by U1 will be described with reference to FIGS. In this search, the effective lattice points (lattice points in contact with the vector) are expanded by lattice points having three or more vectors (this is called "intersecting lattice point"). Therefore, the following (a),
Preprocessing of (b) and (c) is performed. The numbers given in FIGS. 5 and 6 are the numbers of intersection grid points, ▲ is the starting point, and ■ is the destination point.

(A) For the vector from the intersection grid point,
A relative vector quantity indicating the next crossing grid point position and the total vector quantity up to that point is added. This processing is also performed for all points, treating the starting point and the destination point as intersection grid points.

Taking the crossing grid point (11) in FIG. 6 (numbers in parentheses indicate crossing grid points hereafter) as an example, the next crossing grid point position of the vector a1 is (8). , The relative vector amount up to that point is (a1 + a2). Further, in the vector b1, (10) is the target intersection grid point.

(B) In the search, the crossover grid points are expanded from the starting point to a plurality of routes. At a certain search route at that time, the total vector amount from the starting point to each crossing grid point is calculated. The absolute vector amount shown is added to all intersection grid points, and the initial value is + ∞ (maximum value). However, the initial value of the starting point is 0. For example, in FIG. 5, a search rule
If the starting point is expanded to (20) → (21) ..., the absolute vector amount of (20) is the total vector amount from the starting point to (20), and the absolute vector amount of (21) is the starting point. It is the total vector amount from the point to (21) via (20).

The reason for adding this absolute vector amount is to avoid the expansion if it has already been expanded with a smaller absolute vector amount at the time of expansion to the next intersection lattice point. For example, when a certain search route expands from the starting point → (20) → (21) → (18) → (17), it does not make sense to expand it to (20) next time. Starting point in a search route → (20) →
When the absolute vector amount of (20) when expanded to (21) ... is Z, the starting point is expanded to (22) in another route and the absolute vector amount of (22) + ( It is meaningless to expand to (20) if the relative vector amount to 20) is Z or more.

(C) When expanding from one crossing grid point to the next crossing grid point, calculate [the relative vector amount to the next crossing grid point + the straight line distance from the next crossing grid point to the destination point]. , The one with the smallest value is given priority. However,
The direction of deployment is invalid and does not go back. For example, in FIG. 5, if it is expanded in the order of → (18) → (11), the priority of the next intersecting grid point is the same first rank in (10) and (8), and the next rank is ( 13).

To summarize the above items (a) to (c), the above-described preprocessing is performed by calculating the total amount of the vectors arranged along the route from the starting point to the absolute vector for each intersection grid point. In addition to adding as a quantity, the total amount of vectors arranged along the path from one crossing grid point to the next crossing grid point is added as a relative vector quantity, and the crossing grid point is expanded along the path without reversing. If the absolute vector amount already added to the crossing grid point at the tip is smaller than the absolute vector amount currently obtained when branching, the already developed route is used. Conversely, if it is large, the current route is used. It is intended to reduce the waste of deployment by making the best use of, and to prioritize the deployment further from the one having a smaller straight line distance to the destination point.

A program for executing such preprocessing is stored in the ROM 12 in advance, and the processing shown in FIGS. 7, 8A and 8B is performed by the search program in the ROM 12. The flowcharts shown in FIGS. 7, 8A, and 8B will be described in correspondence with the vectorized data shown in FIG.

First, the outline thereof will be described. The starting point is stored as the first intersection to be developed. Next, the next crossing grid point is determined from the first crossing grid point (starting point) according to the priority of (c) above, and the current absolute vector amount (starting point is 0) + the relative vector to the next crossing grid point. If the quantity is smaller than the absolute vector quantity of the next crossing grid point (initial value is + ∞) and smaller than the absolute vector quantity of the destination point (initial value is + ∞), the crossing grid point is regarded as the second crossing grid point. The absolute vector amount is updated at the same time as the memory is stored. On the contrary, if it is larger, the expansion to the intersection grid point is stopped, the intersection grid point having the next highest priority is determined, and the same processing is performed. or,
When one intersecting grid point is expanded and the intersecting grid point is the destination point, the current expansion route is stored as the shortest route.

When the next expansion at a certain intersection grid point is completed, if the intersection grid point is the first intersection grid point (starting point) to be expanded, the search is terminated, and if not, the expansion is completed. Returning to the previous intersection grid point, the same processing as above is performed again. Therefore, the shortest route is obtained when the development is started from the starting point and finally returned to the starting point.

If such expansion is followed, a large number of branches will occur, and the amount of processing will increase as it is. Therefore, when the expansions of the branches collide with each other, the expansion with the larger absolute vector amount of the intersection grid point is changed. By incorporating a comparison process for canceling thereafter, the processing amount is significantly reduced, and the processing amount can be further reduced by performing a plurality of search routes as shown in FIG.

Next, the flowcharts of FIGS. 7, 8A, and 8B will be described in correspondence with the outline of the search based on FIG. 5 described above. 9 and 10 are image diagrams of the first area and the second area, respectively, where r and p of K (r, p) in FIG. 9 are the root number and the starting point at the root, respectively. Shows the number of intersection points counted, thus 2 from the starting point
The th intersection grid point is denoted as K (1,2), and K (1 ,,
If the expansion up to 2) has been completed, the pointer of route 1, that is, P (1) becomes number 2, and this value becomes the number of the pointer related to search route 1 in the second area shown in FIG.

Next, the data of the first memory will be described with reference to FIG. When the number of search routes is set to 2 (n = 2),
First, at 101 of FIG. 7, the position (coordinate position) of the starting point is registered at the first intersection grid points K (1,1) and K (2,1) of the routes 1 and 2, and at 102. Pointer P for roots 1 and 2
(1) and P (2) are set to 1 (the starting point is the first intersection grid point). Then, the search route 1 is selected by 103, the pointer of the route 1 is obtained by 104, and in this case, the first (starting point) is obtained, and the process proceeds to 105, and FIGS.
Execute the search process of. In this search processing, as shown in FIG. 8A, it is confirmed by 201 whether or not the search is completed for all the vectors branched from the starting point. From the grid points, the crossing grid point that is closest to the destination point, that is, (20) is picked up, and 203 is used to select (2
After setting the searched flag for the vector going to 0), at 204 from the starting point along route 1 (20)
The absolute vector amount a up to is obtained. Then, the absolute vector amount already obtained in 205 is compared with a in this (20). However, since + ∞ is assigned at first, the process proceeds to 207 via 206, and (20)
The absolute vector amount is updated as the current absolute vector amount. Then after clearing the searched flag,
Proceeding to 213 via 209, registering the position of the intersecting grid point (20) in K (1, 2), adding 1 to the pointer (P), and proceeding to Exit via 214, the processing is completed.

Then, proceeding to 106 in FIG. 7, the pointer P (1) of the route 1 in the second area is updated to be number 2, and 1
It moves to 108 via 07 and moves to the next search route by 108-110. 202 in search route 2
(22), which has the next highest priority after (20), becomes the target of expansion, and after the same steps, K is entered in 213.
The position of (22) is registered in (2, 2), and the pointer P (2) of the root 2 is updated to be 2 at 106 via 214, and then the process moves to 108 via 107. That is, in this case, since the routes are 1 and 2, the process for route 1 is performed again from 104.

By repeating the above processing,
Start point 1 → (20) → (21) → (18) → (1
1) → (8), Route 2 is the starting point → (22) → (23)
→ (24) → (19) → (10) Assuming that the development has progressed, first, in the route 1, the intersection lattice point (8) of No. 6 is obtained at 104, and the target point is extracted at 202. 203
From 209 to 210 via K (1,1) to K
(1, 6) → Register the route up to the destination point as the shortest route at the present time.

Next, in the route 2, the 104th intersection lattice point (10) is obtained at 104, and the destination point is picked up at 202.
At 205, the absolute vector amount is compared with the next intersecting lattice point (in this case, the target point), but the process returns to 201 because the absolute vector amount a obtained at 204 is larger. And 2
Next, in (02), (9) is picked up, but in the comparison process of 206, the process returns to 201. Then at 202 (11)
Similarly, at 205, the flow returns to 201 at 201, and since all the expansions at the intersection lattice point (10) are completed, the process proceeds to 211 through 212, and the previous intersection lattice point (1
Return to 9). At this time, the pointer P (2) of the root 2 is 5
Becomes

When the above processing is advanced, the object of expansion returns to the starting point, the search is completed, and the route where the absolute vector amount of the destination point becomes the minimum value, that is, the shortest route is obtained. If multiple routes are set as search routes, 1
After completion of one search route, pointer P of each route
(1), P (2), ... P (n) is searched for a minimum value other than 1 and the crossing grid point position of the searched route is transferred to the route for which the search is completed. -This is preferable because it further improves the performance. The flow chart in this case is shown in FIG.

Next, returning to FIG. 1, the overall operation of the embodiment of the present invention will be described. Now, the driver or the passenger operates the touch panel T to cut out the area including the starting point and the destination point from the road map data in the memory 3 and stores it in the graphic controller 4, for example, while scrolling the starting point. And after setting the target point, the search instruction is sent to the CPU.
Give to one. In response to this instruction, the CPU 1 first performs vectorization processing on the cut out road map data as described above, stores the vectorization data in the RAM 11 and then performs search processing as described above. Determine the shortest route. When the memory 31 is used, vectorization processing is unnecessary. After that, the graphic controller 4 displays, for example, the shortest route of the road map data displayed on the image display unit 5 in a color display or blinking display.
Further, a voice display for detecting the position of the vehicle by the azimuth sensor S1 and the distance sensor S2 and guiding the traveling direction of the intersection and the like may be performed together with the screen display, for example.

In the above embodiment, only one-way vector is assigned to the one-way road, but it is also possible to assign vectors in both directions without incorporating one-way elements.

Further, each vector is multiplied by a coefficient in consideration of attribute information to define an actual vector amount, and this actual vector amount is replaced with the vector amount in the retrieval processing of the above-mentioned embodiment to perform the search for the shortest route. Good. As the attribute information, for example, traffic volume, speed limit, weather, time zone, etc. are used,
As the coefficient, for example, a ratio of times of passing the same distance can be used.

An example of the coefficient in consideration of such attribute information will be described. For example, when an intersection between three or more roads is defined as a road section L1, L2, ..., Each road section and time as shown in FIG. A traffic volume table that links a traffic volume that represents the degree of traffic volume (the degree of congestion of vehicles) for each zone, and a traffic volume coefficient that associates the traffic volume and the traffic volume coefficient as shown in FIG. Tables are provided, and attribute information is given to each vector by these tables. 12
In FIG. 13, T1 to Tm are time zones, numbers are traffic volume frequencies, and K1 to Kn in FIG. 13 are traffic volume coefficients.
For example, for the time (average speed) to pass the same distance,
It is the ratio to the reference time (reference average speed). Therefore, the larger the traffic frequency is, the greater the traffic coefficient is and the smaller the average speed of the road section is. In the example of the figure, the road with the traffic frequency of 1 is about half the time compared with the road with the traffic frequency of 3. It means that you can pass by. In this case, the average speed is often different between the expressway and the general road even if the congestion levels are the same, so the assigned traffic frequency differs.

When the real vector quantity is defined in this way, it is difficult to intuitively judge even when the starting point and the destination point are close to each other and they fit on one screen. Therefore, the shortest route display is It is very effective.

[0039]

As described above, according to the present invention, it is possible to retrieve and display the route having the smallest vector from the starting point to the destination point in the vectorized data for the road map. Therefore, the shortest route can be easily grasped. In addition, when searching for the shortest route, the route comparison process is performed while branching from the intersection to be expanded and expanding the route. It can be carried out.

[Brief description of drawings]

FIG. 1 is an explanatory diagram showing an overall configuration of an embodiment of the present invention.

FIG. 2 is an explanatory diagram in which road map data is superimposed on a grid.

FIG. 3 is an explanatory diagram illustrating conditions for displaying a road in contact with a grid point.

FIG. 4 is an explanatory diagram exemplifying vectorization of roads.

FIG. 5 is an explanatory diagram showing vectorized data.

6 is an explanatory diagram showing a part of the vectorized data of FIG.

FIG. 7 is a flowchart showing an example of processing by a search unit.

FIG. 8A is a flowchart showing an example of processing by a search unit.
It is

FIG. 8B is a flowchart showing an example of processing by the search unit.
It is

FIG. 9 is an image diagram of data in the first memory.

FIG. 10 is an image diagram of data in the second memory.

FIG. 11 is a flowchart showing another example of part of the processing of the search unit.

FIG. 12 is an explanatory diagram showing an example of a traffic volume table.

FIG. 13 is an explanatory diagram showing an example of a traffic volume coefficient table.

[Explanation of symbols]

 1 CPU 21-23 Interface 3 Road map data memory 31 Vectorized data memory 5 Image display section 6 Voice display section

Claims (1)

[Claims] 1. A memory for storing data approximating a vector connecting points arranged on a plane with a certain pattern to a road map, and a memory for storing the data based on the data in the memory. A search unit for searching the shortest route among possible routes from the starting point to the destination, and a display unit for displaying the shortest route searched by the search unit. If the intersection of three or more vectors is the intersection, and the total vector length from the starting point to the intersection is the vector quantity at that point, then the comparison is made from the preset starting point. A new route is branched from the intersection and the vector amount a of the intersection located at the tip of the expanded new route is compared with the vector amount of the intersection already obtained, and the larger vector is obtained. While stopping the development of the route related to the amount, Vector amount a is at greater than vector quantity known object point, Le according to the vector quantity a - navigate, characterized in that those having a function to stop the deployment of bets - Deployment apparatus.