JP2002303531A - Method and program for route search - Google Patents

Abstract

PROBLEM TO BE SOLVED: To search a route to be used for easily preparing a recognition map and suitable for a situation and a request for guidance in such a way that excellent efficiency and result can be achieved. SOLUTION: As for nodes such as crossing points on map data, the process for determining nodes from a starting node to a relay node is repeated and the optimum route from the starting node to the destination node is searched (Steps 24-38). A group of candidates for the relay node is prepared around the starting node (Step 26), then the relay node is determined based on the evaluation of the candidates for the relay node in the group (Steps 28 and 30). The evaluation is made based on the density of the number of nodes around each candidate for the relay node and the candidate with a smaller density is evaluated higher.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a pedestrian guidance device and a vehicle-mounted guidance device (car navigation device) that take into account the formation of a cognitive map envisioned when a route is guided and the situation in which the route is guided. The present invention relates to a route search method and a route search program (including a device itself using the method or the program and a computer-readable recording medium storing the program).

[0002]

2. Description of the Related Art Hitherto, since route search technology is often developed mainly for car navigation devices, the Dijkstra method for searching for the shortest route between intersections is widely valued for short distances. Used. That is, when searching for a route from the initial intersection to the target intersection by tracing the intersection on the map data, first, the distance between the initial intersection and the adjacent intersection connected to the target intersection is obtained, and the adjacent intersection having the minimum value is marked. And then add the distance from the marked intersection to the unmarked adjacent intersection to the distance so far, and mark the intersection with the smallest value among the distances obtained so far. The process is repeated until all intersections are marked.
Then, the route finally connected to the target intersection is determined as the optimum route, and this optimum route is the shortest distance among all the routes.

In addition, based on the Dijkstra method,
There is also known a method of avoiding an intersection where a traffic obstacle such as traffic jam or traffic regulation has occurred. That is, when traffic obstacle information is obtained,
The distance is virtually increased according to the degree of the obstacle, and the next best shortest path (the optimal path in the presence of the obstacle) is searched.

[0004]

In the conventional route search,
Since the route is searched only based on the Dijkstra method with a value only for the distance to the adjacent intersection, an optimal route that is difficult to form a cognitive map is often determined. For example, as shown in FIG. 3, a route that has a small number of turns and does not enter the back alley is easier to assume a map even if it travels a little, but in the Dijkstra method, a route having the shortest distance as shown in FIG. The route that enters the alley) is the optimal route. Similarly, a route that passes through an easy-to-understand intersection, such as a nearby mark or a large scale, or a route that includes an intersection whose position is easy to understand with respect to a target intersection may be excluded.

[0005] In some cases, such as when explaining a route to a pedestrian, a route where a sidewalk, an electric light, a signal or the like exists may be desired, but a virtual distance is provided between intersections having no sidewalk or the like. Then, the amount of data and the amount of calculation would be very large, and the resulting route would be extremely unrealistic, such as including a sidewalk, etc., unless the virtual distance was adjusted for each route. It will be something.

Therefore, the first invention according to claim 1 is:
It is an object of the present invention to provide a route search method for easily forming a cognitive map and searching for a route suitable for a situation or a request to be guided with a good efficiency or a result.

According to a second aspect of the present invention, there is provided a route search program which easily forms a cognitive map and outputs a route suitable for a situation or a request to be guided in a state in which good efficiency or a result is obtained. The purpose is to provide.

[0008]

According to a first aspect of the present invention, there is provided a method for searching for a route to a target node by tracing a node in map data. Determining a set of relay node candidates from the map data based on the start node, and determining a candidate state evaluation by calculating, for each candidate, a density of a predetermined state quantity in a predetermined range including the candidate. And selecting the candidate with the highest evaluation as a relay node, and sets the relay node as a new start node and repeats the above processing until the relay node matches the target node. Is what you do.

[0009] In addition to the above-mentioned objects, the invention according to claim 2 aims to further increase the ease of recognition by imitating an actual search when performing a route search for a pedestrian or the like. In order to achieve the above condition, a set of candidates or a predetermined range is determined based on a circle having a radius of view distance or a polygon near the circle.

According to a third aspect of the present invention, in addition to the above object, in order to achieve an object of searching for an optimum route according to a user's needs, a function of a candidate or a predetermined state quantity is represented by the number of nodes, It is characterized in that it is determined on the basis of the number of representative nodes, the angle of tune, the number of lights, the number of signals, the width of a road, the width of a sidewalk or the presence or absence of a sidewalk, a height difference or a step, or their density.

According to a fourth aspect of the present invention, in addition to the above object, in consideration of a global situation, an object of further assisting formation of a cognitive map is achieved. The distance is a function of a predetermined state quantity, and the evaluation is higher as the distance is shorter, or the evaluation is eliminated from the candidates if there is no predetermined closeness.

The invention described in claim 5 provides an optimum route which is more easily recognized while taking into account local conditions and leaving the possibility of searching or guiding to the back alley in addition to the above objects. In order to achieve the purpose of performing, the higher the evaluation of the straightness from the start node to the candidate for the relay node as the function of the predetermined state quantity, the higher the evaluation of the straightness, or excluding the straightness from the candidate if there is no predetermined straightness. It is assumed that.

[0013] The invention according to claim 6 provides, in addition to the above object, weighting for evaluation in order to achieve the object of providing a customized optimal route that meets individual abilities and demands. It is a feature.

According to a second aspect of the present invention, there is provided a program for searching for a route to a target node by tracing a node in map data. A function of creating a set of relay node candidates from the map data, a function of determining the evaluation of the candidate by calculating the density of a predetermined state quantity in a predetermined range including the candidate, and The function of selecting the highest candidate as a relay node and the function of setting the relay node as a new start node and repeating the above processing until the relay node matches the target node are realized by a computer. Is what you do.

According to an eighth aspect of the present invention, in addition to the above object, in order to achieve the purpose of searching for a relay node in a just suitable range according to a real situation, a set of candidates or a predetermined range is defined by a view distance. Is determined based on a circle having a radius of or a polygon near the circle.

According to the ninth aspect of the present invention, in addition to the above object, in order to achieve the object of reflecting factors which have not been considered so far but are important in the formation of a cognitive map in a route search, The function of the candidate or the predetermined state quantity is represented by the number of nodes, the number of representative nodes, the tune angle, the number of lights, the number of signals, the road width,
It is characterized in that it is determined based on the sidewalk width, the presence or absence of a sidewalk, a height difference or a step, or their density.

According to a tenth aspect of the present invention, in addition to the above object, a global relation with a destination, which is always grasped when recognizing geography, is specifically included in a route search. In order to achieve the above, the distance between the candidate relay node and the target node is made higher as the distance is shorter as a function of the predetermined state quantity, or the candidate is removed from the candidate if there is no predetermined closeness. .

According to the invention described in claim 11, in addition to the above objects, important straightness for facilitating recognition of a route is provided.
To achieve the objectives of the assessment from a local perspective,
The straightness from the start node to the relay node candidate is evaluated as a function of the predetermined state quantity as the straightness is superior, or the straightness is removed from the candidates if the straightness is not provided.

According to the twelfth aspect of the present invention, in addition to the above objects, according to the degree of individual demands and abilities, the evaluation is weighted in order to achieve the purpose of searching for an optimal route based on these. It is characterized by the following.

[0020]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 shows a route search program 10
FIG. 1 is an explanatory diagram of a computer 1 that can operate and a mobile phone 2 wirelessly connected thereto. The mobile phone 2 includes a microphone 3 for inputting audio and a speaker 4 for outputting audio. The sound is encoded by a control unit (not shown), superimposed on a radio wave, and transmitted and received from the antenna 5.

On the other hand, the computer 1 stores a route search program 10 and map data 11 in which nodes and their connections (links) are recorded. Here, the node is an arbitrary set point that is a unit of route search, such as an intersection, a vertex of a curve, a building, or a place in front thereof.

Further, the computer 1 has a data control unit 12 for accessing the route search program 10 and the map data 11, and a voice for interpreting voices (radio waves from the antenna 5 or signals from the relay station) relating to the plurality of mobile phones 2. An input processing unit 13, an audio output processing unit 14 that outputs the synthesized audio to a specific mobile phone 2 via a relay station or radio waves, and a part or all of the route search program 10 and the map data 11 for processing. It has a RAM 15 for storing, and a CPU 16 for controlling these.

The route search program 10 repeats the route search between the start node and the relay node while creating a set of relay node candidates as shown in FIG. Here, the start node is a node at the head (or the periphery thereof) of the determined optimum route portion, and the relay node is a node defined to pass the optimum route (relay the optimum route). The candidate relay node is a node selected as a relay node candidate. Note that the start node and the relay node are not necessarily adjacent (not directly connected by one link). Hereinafter, a route search (for a pedestrian, for a pedestrian, for a pedestrian) for a pedestrian in the map data 11 (north is set to the right) as shown in FIG. 3 will be described.

When a pedestrian calls the route search service on the mobile phone 2, it responds through the voice input processing unit 13 to prompt input of an initial node or the like (step 2).
0). Here, the initial node is a node corresponding to the start point (mostly the current location) of the entire optimal route. That is, a voice saying "Please give the name of the intersection or building where guidance is started" is output to the mobile phone 2 by the voice output processing unit 14, and the input of the initial node by voice is awaited. If a voice input such as "parco" is made here,
The voice input processing unit 13 recognizes this, and the initial node is set to S before parco.

Similarly, a response such as "Nagoya Sports Center" to "Please answer the destination with the name of the intersection or building" is interpreted, and the destination node is Nishi-Osu G (intersection).
Is set to That is, even if the node names do not exactly match, if a keyword such as a registered mark is input, the corresponding node name is derived and set. The input of "300" for "Please give the approximate distance you can see" is interpreted as 300 meters and stored in the RAM 15 as the field radius. In addition, "Medium" for "Please answer the degree of straight road in large, medium and small"
Set to 60 degrees. The destination node is a node corresponding to a goal point (a guidance target or a destination) of the entire optimal route. Among the routes from the initial node to the destination node, the one that has been optimally evaluated is the optimal route. is there.

Following the input of these parameters, the user is prompted to input a weight coefficient (step 22). The weighting factor is the evaluation V for “individual situations”, “local situations”, and “global situations”.
1, V2, and V3 (here, values of 0 to 1; the larger the value, the higher the actual evaluation), represent the ratio of how much importance is placed on each of them, which are W1, W2, and W3 in order.

The "individual situation" represents the situation of the relay node, and here is based on the density of the number of surrounding nodes in the candidate relay node.
The evaluation V1 is represented by (a function of the density of the number of nodes).
However, “cluster” means a circle whose radius is around the candidate node and has a visibility distance, and “cluster area” is represented by the product of the pi and the square of the visibility distance. The “number of nodes” is the number of nodes in the cluster, and the “ideal density” is the density of a large cluster whose radius is a general limit (4 to 5 km, here, 4 km) of the pedestrian's search distance. (Number of nodes in large cluster / large cluster area).
When the density is lower than the ideal density (ideal value), 1 which is the maximum evaluation is given. When the density is higher than the ideal density, the higher the density, the lower the evaluation.

[0028]

[Formula 1]

The "local situation" is a situation between the start node and the relay node candidate. Here, the straightness from the start node to the relay node is good, and Equation 2 (a function of the distance difference) Expresses the evaluation V2. Note that the linear distance is the Euclidean distance between two points, and the route distance is the sum of the distances of the route following the link. The local distance is a linear distance (local linear distance) in this case.

[0030]

[Formula 2]

Further, the "global situation" is a situation between a relay node candidate and a target node. Here, the degree of closeness from the relay node to the target node is expressed.
The evaluation V3 is determined by (function of distance). The ideal value is the shortest linear distance.

[0032]

[Equation 3]

That is, the weighting factors W1, W2, and W3 are used to set weights for determining how much the determination of the evaluations V1, V2, and V3 is affected, and according to the ability and situation of the individual who receives the route search service. Evaluation or route search is realized. Then, the weighting factors W1, W2, and W3 are made equal by voice (W1 = W2 = W3 =
If there is an input such as 1), the process proceeds to step 24, where the initial setting of the start node is performed. That is, the start node is set as the initial node (before Parco S), and the processing of the relay node starts from the main start node.

In the main process, first, a partial candidate set is created from nodes on the map data 10 (step 26). Here, a node that is not farther than the viewing distance from the start node is picked up and put into a set element as a candidate for a relay node. In other words, nodes that fall within a circle whose center is the start node and whose radius is the view distance are used as elements of the set, and candidates are limited. For example, a node within a circle having a radius of 300 m from Parco S to Wakamiya Odori T1 is included as a candidate.

Next, for the nodes in this candidate set,
While grasping and adding the angle of the link and tracing the link from the starting node without returning, if there is a node in the set where the sum of the angles exceeds the bending angle (360 degrees),
The node is excluded from the candidate set (step 26).
In step 26, since the relay node candidates are divided by the view distance or the bending angle, the relay nodes can be narrowed down to a range corresponding to the visual recognition and the peeping when actually searching for a road, and the It helps to create an optimal route that is easy to follow.

Subsequently, an evaluation calculation is performed on the nodes in the candidate set by the equations 1 to 3 (step 28,
Customized path method). Note that, in order to surely prevent rare generation of a route that is an extremely local optimal route, but leaves a target node, only a node (candidate of a relay node) closer to the target node than the start node is evaluated and calculated. In this case, nodes that are substantially farther from the destination node than the start node are dropped from candidates.

In the evaluation calculation, for example, with respect to Odori Wakamiya T1, which is a candidate for a relay node, how many other nodes are within a circle centered on this and whose radius is the visibility distance In order to evaluate the difference in the number by comparing the area, the difference from the ideal value (deviation, probability distribution, Equation 1) is evaluated, so that the nodes around the large cluster are denser than the large cluster. The evaluation of the relay node candidate is relatively low. Therefore, it is possible to individually respond to the situation around the relay node candidate, and by looking at the node density, a route including a comparatively large street can be highly evaluated, and it is possible to pass through a back alley even if it is not the shortest distance. The evaluation can be lowered for a route that is difficult to remember.

In addition, from the start node (before Parco S) to the relay node candidate (such as Odori Wakamiya T1), the deviation (straightness, probability distribution, equation 2) of the total distance of the link connecting these from the straight line distance is calculated. Because the evaluation is performed, a local situation within the candidate set (within the viewable range) can be reflected in the route evaluation. In particular, by taking into account the straightness, it is easy to recognize a route with a good line of sight and proceed straight. The route can be highly evaluated.

Further, by evaluating the distance from the shortest one in the candidate set (probability distribution, Equation 3), the distance from Odori Wakamiya T1 or the like to Nishi-Osu G (the target node) is evaluated. The global situation with the target node can be incorporated into the route search, and the evaluation can be performed with the target node in mind, as in the case of forming a cognitive map. Note that each distance and the like can be calculated from the ordinate value and the abscissa value of the node on the map data 10 (further considering the scale as appropriate).

Then, the weighting coefficient W1 is added to the result of the evaluation calculation.
The candidate node having the highest overall evaluation V is set as a relay node by reflecting the weighting by the above (step 30). Each evaluation can be adjusted by a weighting factor, so it is possible to emphasize individual situations and make it as easy as possible to pass through the main street, or to emphasize local situations and make the route as bend as possible. A suitable route can be guided. Note that the evaluation V is obtained by the following Expression 4.

[0041]

(Equation 4)

When the relay node is determined, the node is traced in the candidate set, and a part of the optimum route is determined (step 32). A part of the optimum route in the candidate set is determined by the Dijkstra method. The evaluation is performed within the area (cluster) divided by the radius of sight, and after the evaluation, the Dijkstra method is used to make it easier to recognize and pass through a relay point that matches the individual's situation, but also to improve the efficiency in terms of distance or processing Can be made favorable.

Then, it is determined whether or not the determined relay node is Nishi-Osu G, which is the target node.
6), the main processing is repeated from step 26. That is,
Performs processing with Odori Wakamiya T1 as a new starting node, performs weighted evaluation calculation of individual situations, local to global situations, selects the next relay node, Akamon-mae T2, and determines the optimal route as the current candidate set. After that, a new starting node is set as a new starting node, and a subsequent relay node is evaluated after creating a candidate set.

When the relay node coincides with the target node in this way, the optimum route from Pareo S, the initial node, to Nishi-Osu G, the target node, is determined as shown in FIG. The information is provided to the mobile phone 2 at the section, and the guidance is provided by being heard from the speaker 4 (by being appropriately recorded). At this time, the mobile phone number of the output destination (and a part of the output contents, for example, initial and target nodes)
Is stored in a recording medium (not shown) in association with the information, and is used as a reference when charging for the service. Also, it takes at most several tens of seconds from the input of the weight coefficient to the output,
During this time, a message such as “Please wait” is played by the audio output processing unit 14.

Here, the contents of the guidance synthesized by the voice output processing unit 14 are "go to the south and Yabacho area", "go to the west of the Yabacho north intersection and go to the Chukyo Bank head office", and "cross the Wakamiya Odori". "Go south on the Wakamiya intersection toward Osu."
"At the Osu intersection, proceed west toward Suizuki-cho.""Please. Nishi-Osu intersection, in front of the Nagoya Sports Center."
And so on.

The optimum route is not determined as shown in FIG. 4 by the Dijkstra method only as the shortest route.
It is determined as shown in FIG. 3 by evaluating the relay nodes. In particular, the vehicle enters a non-street road in the latter half, and can be guided along an easily recognizable route without turning many times.

The present invention is not limited to the above-described embodiment, but can be variously modified as partially shown below.

The initial node is a mobile phone base station or GPS.
(Global Positioning System
According to the position information from m), the information may be automatically input or the input range may be narrowed. For some or all of the various parameters such as the viewing distance and the weighting coefficient, input may not be particularly received, and a predetermined value may be used. In this case, the predetermined value can be changed according to the initial node, the type of map data, and the like. Also, ideal density etc.
A predetermined value (including a value to be changed) can be used without calculating each time.

The setting of the candidate set may be performed based on only the view radius without performing the drop-out process of the candidate based on the music angle.
In addition, the deviation of the music angle and the like are included in the local evaluation, for example,
You may make it consider as evaluation rather than selection of a candidate. Similarly, other parameters can be appropriately reflected in the selection, evaluation, or both of the candidates.

The evaluation is not performed based on the three situations, and a part of the evaluation can be omitted. In addition, the weighting of the evaluation according to the route search requester and the situation around the route search (type of map data) can be omitted. In addition, the evaluation is not represented by a value between 0 and 1 according to the probability distribution, but may be represented in various ranges by a total, a deviation from the average, and the like. Also, the lower the value, the higher the actual evaluation may be.

In the evaluation, in addition to the nodes, the installation points of the lighting are held on the map data, and the number of lightings on a predetermined cluster around the relay node candidate (lighting density) According to the above, it is also possible to adopt a higher value as the number increases. In this case, the best route is calculated taking into account the desire to guide you on a bright road at night,
Can be provided.

Similarly, the presence of a signal or a step is included in the map data, a route with a signal is evaluated as high as possible, a candidate passing through a step is removed, and altitude information is given to a node. A route with a small difference is evaluated higher (an altitude difference of a certain value or more is excluded from candidates), or a flag is set for a widely recognized node, and the distance or density to the flagged node is small. Is included in the evaluation so as to pass through a representative node or its side as much as possible.Include information on the presence or absence of a sidewalk in each node to evaluate the route with the density of the node having the sidewalk, By incorporating it into map data, it is possible to provide route guidance mainly on wide roads.

Further, the range (cluster) for determining the candidate set, the node density, and the like may not be centered on the relay node and may be shifted in the direction of the target node. It can be within the vertical and horizontal coordinates (within the same map data). In addition, map data can be created in stages, such as a wide range, a medium range, and a detailed range, and a specific range can be picked up according to the situation, and evaluation calculations and the like can be performed on this range. it can. In addition, the optimum route after the relay node is determined may use the obtained evaluation to follow a node with a high evaluation.

In addition, the condition for terminating the route search is not limited to the case where the relay node exactly matches the target node, but the case where the relay node is adjacent to the target node or a node within a certain range from the target node. Or when it comes out in the same way as the node. In these cases,
At the end, a route to the destination node can be set. Also, for example, when providing an optimal route to a pedestrian,
If the destination node is too far away, a representative node may be selected, these may be used as the destination nodes, and the route search may be repeated.

The input of various parameters, initial nodes, and the like may be made by a keyboard, a pointing device, or a combination thereof without using voice. or,
As for the output, it is possible to display an optimal route drawn on the map data on a display, or to use the output of the display and voice together. Therefore, the present route search method and program can be applied to a map display service for a mobile terminal device, a car navigation device, and the like. Even a car navigation device can provide an easy-to-understand optimal route suitable for a cognitive map formed by a driver by appropriately adjusting the radius of view or emphasizing a global concept. .

[0056]

According to the present invention, a candidate set of relay nodes is created, and evaluation is performed on the set based on the density of a predetermined state quantity around the candidate. Therefore, there is an effect that it is easy to draw a cognitive map, and it is possible to search for an optimum route that is very easy for the user to understand (even if provided only by voice, the optimum route can be grasped).

Further, by allowing the evaluation to be weighted, in addition to the above-described effects, it is possible to provide an optimum route that matches the user's ability and demand.

[Brief description of the drawings]

FIG. 1 is an explanatory diagram of a route guidance device capable of executing a route search method according to the present invention.

FIG. 2 shows a route search method (route search program,
9 is a flowchart illustrating a customized path method.

FIG. 3 is an explanatory diagram of an optimal route obtained by the route search method of the present invention.

FIG. 4 is an explanatory diagram of an optimal route obtained by a conventional route search method (Dijkstra method).

[Explanation of symbols]

1. Computer, 2. Mobile phone, 3. Microphone,
4. Speaker, 5 Antenna, 10 Route search program, 11 Map data, 12 Data control unit, 13 Voice input processing unit, 14 Voice output processing unit, 15 RAM , 16 ... CPU.

Continuing from the front page (72) Inventor Naohiro Ishii Nagoya Institute of Technology, Nagoya-shi, Showa-ku, Nagoya-shi HC13 HC16 HC21 HC31 HD12 HD16 2F029 AA02 AA07 AB05 AB07 AC02 AC14 AC18 5H180 AA01 AA21 BB05 CC12 EE01 FF05 FF13 FF22 FF27 FF32

Claims (12)

[Claims] 1. A method for searching for a route to a destination node by tracing nodes in map data, comprising: creating a set of relay node candidates from the map data based on a start node; Determining a candidate evaluation by calculating a function of a predetermined state quantity in a predetermined range including the candidate, and selecting a candidate having the highest evaluation as a relay node; A route search method, wherein a relay node is set as a new start node and the above processing is repeated until the destination node matches the destination node. 2. The route search method according to claim 1, wherein a set of candidates or a predetermined range is determined based on a circle having a radius of view or a polygon near the circle. 3. The function of a candidate or a predetermined state quantity is represented by the number of nodes, the number of representative nodes, the angle of music, the number of lights, the number of signals, the road width,
The route search method according to claim 1, wherein the determination is performed based on a sidewalk width, presence / absence of a sidewalk, a height difference or a step, or their density. 4. The method according to claim 1, wherein the closer the distance between the candidate relay node and the target node as a function of a predetermined state quantity, the higher the evaluation is, or the higher the evaluation is, the more the candidate is removed from the candidate if there is no predetermined proximity. The route search method according to claim 3. 5. The method according to claim 1, wherein the linearity from the start node to the relay node candidate is evaluated as a function of a predetermined state quantity as the linearity is excellent, or the linearity is excluded from the candidates if the linearity is not predetermined. The route search method according to claim 1. 6. The route search method according to claim 1, wherein the evaluation is weighted. 7. A program for searching for a route to a destination node by tracing nodes in map data, comprising: a function of creating a set of relay node candidates from map data based on a start node; For a candidate, a function of determining the evaluation of the candidate by calculating a function of a predetermined state quantity in a predetermined range including the candidate, a function of selecting the candidate with the highest evaluation as a relay node, A function of setting a relay node as a new start node and repeating the above-described processing until the value matches the above. 8. The route search program according to claim 7, wherein the set of candidates or the predetermined range is determined based on a circle having a radius of view distance or a polygon near the circle. 9. The function of a candidate or a predetermined state quantity is represented by the number of nodes, the number of representative nodes, the angle of a song, the number of lights, the number of signals, the road width,
The route search program according to any one of claims 7 to 8, wherein the determination is performed based on a sidewalk width, presence / absence of a sidewalk, a height difference or a step, or a density thereof. 10. The method according to claim 7, wherein the closer the distance between the candidate relay node and the target node as a function of the predetermined state quantity is, the higher the evaluation is, or if the distance is not the predetermined distance, the evaluation is removed from the candidates. 10. The route search program according to claim 9. 11. The straightness from the start node to the candidate for the relay node as a function of a predetermined state quantity is evaluated higher as the straightness is better, or the straightness is excluded from the candidates if there is no predetermined straightness. The route search program according to any one of claims 7 to 10. 12. The route search program according to claim 7, wherein the evaluation is weighted.