JPH10197270A - Navigation system, required time information calculating method and recording medium - Google Patents

Abstract

PROBLEM TO BE SOLVED: To determine the time required for passing through a specified course accurately at the time of course calculation. SOLUTION: A learning table A is formed in an RAM while being sectioned into 'general period' and 'congested period', 'weekday' and 'holiday', and 'rush time', 'day' and 'night' for each type of road. At the time of traveling, a passing speed/hour is acquired for one road link being passed and the average speed/hour for same conditions is updated at any time in the learning table A. When a time required for passing through a specified course accurately at the time of course calculation, average speed/hour of a road link constituting a specified course is read out from the learning table A depending on the conditions at that moment of time and utilized. Road situation related to traffic jam is reflected on the calculation of required time, and the required time can be calculated more accurately.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a navigation device having a route calculation function, a required time information calculation method, and a recording medium.

[0002]

2. Description of the Related Art Conventionally, in a vehicle-mounted navigation device, a route calculation function for automatically calculating a recommended route from a start point to a goal point, displaying the recommended route on a map, and a calculation of the calculated recommended route. A route guidance function is provided to guide the user to the destination while displaying the position of the vehicle on the map as a guidance route. In calculating a recommended route by the calculation function, a basic condition is to calculate a route that has the shortest distance to the destination and the shortest required time. The calculation of the required time is performed based on the distance to the destination, the average traveling speed set in advance, and the traveling speed set by the user.

[0003]

However, the traveling speed used for calculating the required time to the destination described above is
This is only a guide, and even if there is a section with a high probability of congestion on the recommended route, the required time is calculated at an average traveling speed. For this reason, when the vehicle is involved in traffic congestion on the way, a large error occurs between the calculated required time to the destination and the required time. In other words, it is difficult to correctly calculate the recommended route with the shortest required time, and when calculating the expected arrival time to the destination by the route calculation function or when the user travels according to the route set by the user. Had a large difference between the expected arrival time and the actual arrival time. Needless to say, such a trouble is caused by the fact that the navigation device sequentially acquires real-time traffic congestion information such as VICS, which is becoming popular recently,
This can be solved by performing route calculation or the like using this, but in that case, the system becomes expensive. And even in that case, if you want to calculate recommended routes in advance,
For example, there is a problem that it is not possible to cope with a case where a traveling route is determined in advance.

The present invention has been made in view of such conventional problems, and is a navigation apparatus and a required time information calculation method capable of more accurately knowing the required time required for passing through a specified route at a low cost. And a recording medium on which a program for realizing the method is recorded.

[0005]

In order to solve the above-mentioned problems, a navigation device according to the present invention has a self-position obtaining means for obtaining self-position data indicating a current self-position, and map data. Map data storage means; display means for displaying a map near the self-position indicated by the self-position data acquired by the self-position acquisition means based on the map data stored in the map data storage means; Route setting means for setting a route to the ground,
Storage means for storing traveling state data relating to the traveling state acquired during traveling, and control for calculating data relating to the time required for traveling on the route set by the route setting means based on the traveling state data read from the storage means Means.

In such a configuration, data on the time required for traveling on the route set by the route setting means is calculated based on the traveling state data on the traveling state acquired during traveling. Here, if the road on which the vehicle was traveling when the traveling state data was acquired was congested, this is reflected in the traveling state data, so the data on the calculated time is calculated based on the actual road conditions of the road. Is reflected.

In another apparatus, a self-position acquiring means for acquiring self-position data indicating a current self-position, a map data storing means for storing map data, and a self-position acquiring means for acquiring the self-position data. Display means for displaying a map near the self-position indicated by the self-position data based on the map data stored in the map data storage means; storage means for storing running state data relating to the running state acquired during running; Control means for calculating data on the time required for traveling on the candidate route based on the traveling state data read from the storage means; and departure based on the data on the time required for traveling on the candidate route calculated by the control means. Route setting means for setting a route from the ground to the destination.

In this configuration, the control means calculates data on the time required for traveling on the candidate route based on the traveling state data acquired during traveling, and sets the route setting means on the basis of the calculated data. Sets the route from the starting point to the destination. Here, if the road on which the vehicle was traveling when the traveling state data was acquired was congested, this is reflected in the traveling state data and also in the data relating to the time required for traveling on the candidate route. You. Therefore, the actual cost of the road is reflected in the additional cost used for calculating the route from the departure point to the destination and obtained from various conditions such as the traveling distance and the traveling time.

In the method of the present invention, a method for calculating data relating to a time required for traveling on a set route by using map data stored in a map data storage means is provided. The traveling state data is stored, and data on the time required for traveling on the set route is calculated based on the stored traveling state data. According to such a method, it is possible to calculate data on the time at which the actual road conditions of the road are reflected.

A recording medium according to the present invention is a recording medium in which a program read and executed by a computer is recorded, wherein the map data and the stored driving state data relating to the driving state in the past driving are stored. And a program for calculating data relating to the time required for traveling on the set route. By using the program recorded on such a recording medium, it is possible to cause the computer to calculate data on the time at which the actual road conditions of the road are reflected.

[0011]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing a navigation device according to a first embodiment and a second embodiment of the present invention. This navigation device has general functions such as a route calculation function, a route guidance function, and a point registration function, and has a GPS antenna 1 as a reception function.
And a GPS block 2 for demodulating and decoding the L1 band C / A code from the satellite received by the GPS antenna 1 to determine the latitude and longitude of the current location. GPS unit 2
Is connected to the CPU 4 via the bus 3, and the latitude and longitude information determined by the GPS unit 2 is taken into the CPU 4. The CPU 4 has the RAM 5 and R via the bus 3.
An OM 6, a graphic controller 7, a clock unit 8 having a clock function and a calendar function, and a CPU peripheral circuit 9 are connected. The ROM 6 stores various data such as a program for causing the CPU 4 to control the entire navigation device using the RAM 5 as a working area.

The graphic controller 7 has a video R
The AM 10 and the monitor 11 are connected. The CPU peripheral circuit 9 includes a CD unit 13 and a key input unit 1 having a plurality of operation keys (not shown) for operating a navigation device.
3 are connected. The CD unit 12 generates a map CD-R based on the latitude and longitude of the current location determined by the GPS unit 2.
Read stored data from OM14. Map CD-ROM
14 stores various data such as map / road information such as road data and place name data, and traffic regulation data used for automatic route calculation and the like. The road data is divided for each road link, which is the minimum unit, and each road link includes a road type and road information. C
The various data read from the map CD-ROM 14 by the D unit 13 are sent to the CPU 4 via the CPU peripheral circuit 9 and then via the RAM 5 together with the data read from the ROM 6. Furthermore, map CD-ROM
The data read from 14 is sent by the graphic controller 7 to the monitor 11 via the video RAM 10, whereby a map showing the position of the vehicle and the surrounding area is displayed on the monitor 11.

The RAM 5 is backed up by a battery so that its contents can be retained even when the power is turned off, and its memory space includes a working memory area and a storage area for link data and the like.
When the navigation device operates in a driving situation learning mode described later, a memory area for constructing the first learning table A shown in FIG. 2 and the ROM 6 or the map CD-ROM
A memory area for expanding the conversion table B shown in FIG. 6 based on the data recorded in the memory 14 and a second learning table C shown in FIG. And a memory area for it.

The first learning table A in FIG. 2 is composed of the road types and the driving conditions included in the above-mentioned road links.
It is classified into "Expressways" and "Detailed Roads". Also,
The driving conditions are divided into "general period" and "congestion period" that can be determined based on the calendar information obtained from the clock section 8, and both are classified into "weekdays" and "holidays / holidays". In addition, both are further divided into three time zones of “rush hour”, “day”, and “night” that can be distinguished from the time information obtained from the clock unit 8. As the above-mentioned “congestion period”, four periods are set: golden week, summer vacation, year-end and new year. And RAM
The first learning table A of No. 5 stores an average hourly speed corresponding to each road type and traveling condition.

The conversion table B shown in FIG. 6 includes three traffic congestion ranks ("heavy", "medium", and "light"), a multiplication coefficient corresponding to each rank and used at the time of route calculation, It consists of display symbols and average speed per hour. The conversion table B is stored in the ROM 6 or the map CD.
-It may be stored in the ROM 14. FIG.
The second learning table C is formed by sequentially storing identification data indicating a road link that has passed, and a set of data including an average speed and the number of passes.

Next, the operation of the navigation device having the above configuration according to the first embodiment will be described with reference to the flowcharts of FIGS. FIG. 3 is a flowchart showing an operation at the time of traveling when the traveling situation learning mode is set in the navigation device. Hereinafter, an example will be described in which the driving situation learning mode is set when the own vehicle is stopped at a point corresponding to one of the road links, and then the vehicle starts running. That is, after setting the mode, the navigation device first determines, based on the link data of the currently displayed map developed in the RAM 5 and the own position data, whether or not the own vehicle has entered one road link. It is determined whether the vehicle has entered the road link (SA1). At this point, the vehicle is in the middle of one of the road links, and the result of the determination is NO, so that the process is terminated. Eventually, when the vehicle enters a new road link for the first time during traveling (YES in step SA1), it is determined whether or not the clock unit 8 is measuring time (SA2). The determination result is NO. Therefore, the process proceeds to step SA3 to cause the clock unit 8 to start time measurement, temporarily store the type of the road link passing at that time in the working memory area of the RAM 5 (SA4), and terminate the process.

On the other hand, when the vehicle further travels and the own vehicle enters the next new road link, that is, when the vehicle passes one road link that has been traveling immediately before (YE in step SA1).
S), the determination result of step SA2 becomes YES. Then, the time measured by the clock unit 8 at that time, that is, the lap time is stored in the working memory area of the RAM 5, and the time required for passing one road link that has passed is calculated (SA5). The calculation here is
The processing is performed by subtracting the time stored in the working memory area of the RAM 5 from the lap time at the time of performing such processing. In other words, RAM5
Is the transit time as it is. Next, based on the calculated transit time and the travel information (distance) of one road link that has passed, after calculating the average speed per hour when passing through the road link (SA6), the date, day of week, and time that the clock unit 8 has Then, the traveling condition at that time is determined based on the above information (SA7).

Subsequently, the running conditions determined here and the past average speeds stored in the memory area corresponding to the road type of the one road link passed immediately before, which were previously stored in step SA4, are stored in the RAM 5. After reading from the learning table A, the average hourly speed and the average hourly speed calculated in step SA6 are averaged, and then updated and recorded (SA8). At this time, if the data of the average speed is not recorded in the corresponding memory area in the learning table A, the average speed calculated in step SA6 is recorded as it is. Thereafter, the road type stored in the working memory area of the RAM 5 is updated and stored as the road type of the currently passing road link, that is, the road type of the road link determined to have newly entered at step SA1 (SA4). finish.

Thereafter, until the driving situation learning mode is canceled, the aforementioned steps SA1, SA2 and SA2 are performed based on the link data of the currently displayed map developed in the RAM 5 and the own position data. SA5
To SA8 and SA4 are sequentially and repeatedly performed. As a result, the average speed data corresponding to the road type and the driving conditions are stored in the RAM 5, the learning table A is completed, and the stored average speed data is stored. Updated as needed. As a result, the first learning table A stores the data of the average hourly speed on which the road conditions relating to the traffic congestion are reflected, for each type of road, and for each day and time zone.

FIG. 4 is a flow chart showing the operation of the navigation apparatus when the route from the departure point to the destination is calculated after the learning table A is completed in the RAM 5 by the above-described operation. That is,
The navigation device starts operation when the route calculation mode is set, and after a user inputs a departure place and a destination (SB1), starts a route calculation connecting a plurality of points, that is, a plurality of road links. A network composed of a plurality of connected road links, that is, a plurality of candidate routes is constructed (SB2). Next, the learning table A described above is used for all road links constituting a plurality of networks.
(See FIG. 2), the required travel time is predicted (SB
3). In the prediction processing, based on the information such as the date, day of the week, and time of the clock unit 8 and the road type of each road link, the corresponding average hourly speed data is read from the learning table A, and the distance that each road link has Is calculated on the basis of the information (distance information).

That is, as shown in FIG. 5, when the driving condition A obtained from the information of the clock unit 8 is a weekday afternoon (A) in late December and the current time B is 12:00 (B). The average speed obtained from the learning table A in FIG. 2 is 15 km / h on a general road, 30 km / h on a highway, and 8 km / h on a detailed road. In the case of 300m, the required transit time is 1 minute and 12 seconds. Similarly, in the case of a highway and a 2.5km road, the required transit time is 5 minutes. Similarly, in the case of a detailed road and a 20m road, the required transit time is Means that the time required for passage is 9 seconds (D).

Subsequently, in step SB4, the required travel times of the road links constituting each candidate route are added, and the required required time of each network (candidate route) is calculated (SB4). For example, under the same driving conditions as the example illustrated in FIG. 5, for a certain network, the entire distance of the route is 12 km (E), and the configuration of the route is 3 km for a general road and 3 km for an expressway. If the distance is 5 km and the detailed road is 4 km (F), the time required to pass each road is 12 minutes, 10 minutes,
Since it is 30 minutes, the addition required time is 52 minutes (F). Thereafter, the calculated addition time of each network is compared, and the network with the shortest addition time is displayed as a recommended route on the map displayed on the monitor 12 (SB5), and the process is terminated. When the recommended route is displayed on the map, the time at which the required time has elapsed from the current time at that time is simultaneously displayed as the estimated arrival time.

Here, in the above-described route calculation, the time required for passing through all the road links in step SB3 is
Since the prediction is made based on the average speed stored in the first learning table A, that is, the average speed on which the driving speed of the driver for each road type is reflected, a more accurate passage time can be obtained. Therefore, choose a more accurate recommended route that meets the shortest travel time,
It can be presented to the user. That is, more accurate route calculation can be performed. At the same time, a more accurate estimated arrival time can be notified. In addition, the above-mentioned effect can be obtained at a lower cost than in the case of using real-time traffic congestion information such as VICS, and it is possible to cope with a case where a recommended route is calculated in advance, for example.

In addition, in the present embodiment, the data of the average speed per hour used in the route calculation is stored for each road type, so that the roads which have not actually traveled are the starting point and the destination. Even when included in between,
In step SB4, the required time required for passing through each network can be more accurately known, so that the estimated arrival time to the destination and the recommended route can be performed more accurately. In addition, since the data of the average hourly speed is stored for each road type, the memory capacity can be saved. Further, since the average hourly speed data used in the route calculation is stored and used separately for each character and time zone on the calendar, the actual travel time required for all road links predicted in step SB3 is used as the actual time required. Since the road situation can be reflected, the expected arrival time and the recommended route can be calculated more accurately.

In the present embodiment, in the above-described route calculation, the addition required time based on the average hourly speed corresponding to the time zone or the like at the time of performing the route calculation is used.
Although the case of calculating the estimated time of arrival at the destination when the recommended route is used has been described, the estimated time of arrival may be calculated as follows, for example. In other words, based on the distance of each road link constituting the recommended route and its average speed,
The passage time zone and the like of each road link when traveling on the recommended route are predicted, and the calculation of the required addition time is performed based on the average speed corresponding to the predicted passage time zone and the like. By doing so, for example, when the recommended route is long, the departure point departs during a rush hour, and the destination arrives at night, such as when the transit time zone of each road link is different, the accuracy is further improved. Required addition time, that is, estimated arrival time can be calculated. Further, the calculation method in consideration of the predicted passage time zone of each road link may be applied to the calculation of the recommended route.

Next, the operation of the navigation apparatus according to the second embodiment shown in FIG. 1 will be described with reference to the flowcharts of FIGS. FIG. 8 is a flowchart showing an operation at the time of traveling when the traffic congestion rank learning mode is set in the navigation device. Less than,
An example will be described in which the traffic jam rank learning mode is set when the vehicle stops at a point corresponding to one of the road links, and then the vehicle starts running. That is, after setting the mode, the navigation device first determines, based on the link data of the currently displayed map developed in the RAM 5 and the own position data, whether or not the own vehicle has entered one road link. It is determined whether the vehicle has entered a road link (SC1). At this point, the vehicle is in the middle of one of the road links, and the result of the determination is NO, so that the process is terminated. Eventually, when a new road link is entered for the first time along with the traveling (Y in step SC1)
ES), it is determined whether or not the clock unit 8 is measuring time (S
C2) At this point, since the measurement has not been performed yet, the determination result is NO. Therefore, the process proceeds to step SC3 to cause the clock unit 8 to start time measurement, temporarily store the identification data indicating the road link passing at that time in the working memory area of the RAM 5 (SC4), and terminate the process.

On the other hand, when the vehicle further travels and the own vehicle enters the next new road link, that is, when the own vehicle passes one road link which has been traveling immediately before (YE in step SC1).
S), this time the determination result of step SC2 is YES. Then, the time measured by the clock unit 8 at that time, that is, the lap time, is stored in the working memory area of the RAM 5, and the time required for passing one road link is calculated (SC5). The calculation here is
The processing is performed by subtracting the time stored in the work memory area of the RAM 5 from the lap time at the time of performing such processing. That is, at this beginning, the time stored in the working memory area of the RAM 5 becomes the passing time as it is. Next, based on the calculated transit time and the travel information (distance) of one road link that has passed, an average hourly speed when passing through the road link is calculated (SC6), and whether the average hourly speed is 15 km / h or less is determined. Is determined (SC7).

At this time, if the average speed exceeds 15 km / h (NO in SC7), it is determined that no congestion rank data is recorded (SC8), and the identification data indicating the road link passing at that time is stored in the RAM 5. Is stored once in the working memory area (SC4), and the processing is terminated. Also, when the average speed is 15 km / h or less and the result of the determination of SC7 is YE
If S, whether or not there is a past record of the road link that has just passed,
It is determined whether or not the road link data corresponding to the identification data stored in the working memory area No. 5 exists in the second learning table C of FIG. 7 (SC9). If it does not exist (NO in SC9), the identification data indicating the road link, the average hourly speed calculated in step SC6, and the number of passes (one time) of the road link are stored in the second learning table C. Is newly stored (SC10), and after the processing of step SC4 described above is performed, the processing is terminated.

Conversely, if the result of the determination in step SC9 is NO and there is a past record in the second learning table C for the road link that has just passed, the average hourly speed that has already been stored is used. The new average speed calculated by accumulating the average speed calculated in step SC6 and the number of times of passage added by one are updated and stored. For example, when the already stored average hourly speed is 11 km / h and the number of passes is four, if the average hourly speed calculated in step SC6 is 6 km / h, it is stored in the second learning table C. The data show that the average speed is 10 km / h and the number of passes is five. Thereafter, after performing the above-described process of step SC4, the process ends.

After that, until the traffic jam rank learning mode is canceled, the map C based on the own vehicle position is used.
Each time the road data is read from the D-ROM 14, the above-described steps SC1, SC2, SC5 to SC11, S
The processing of C4 is sequentially and repeatedly performed, whereby the average speed per hour and the number of passes of the road link once passed are stored,
Further, the information is updated as needed, and the above-described second learning table C is formed in the RAM 5. That is, the second learning table C
In, data on the average hourly speed reflecting road conditions related to traffic congestion is stored for each road link that has traveled.

FIG. 9 shows the operation of the navigation device when the route from the departure point to the destination is calculated using the second learning table C after the second learning table C is constructed in the above-described traffic jam rank learning mode. It is a flowchart which shows. That is, the navigation apparatus starts operation when the route calculation mode is set, and after the user inputs a departure place and a destination (SD1), performs a route calculation connecting a plurality of points, that is, a plurality of road links. Starting, a network including a plurality of connected road links, that is, a plurality of candidate routes is constructed (SD2). Next, the road link having the congestion rank, that is, the second
It is determined whether or not the road link stored in the learning table C is on the network (SD3). If there is no such road link, the process proceeds to step SD5, where a plurality of networks as candidate routes are calculated, and recommended in consideration of other conditions such as a mileage in each network (candidate route) and the number of right / left turns. Calculate the additional cost as a selection criterion when selecting a route (SD
5). Thereafter, the addition costs of the respective networks are compared, and the candidate route having the lowest addition cost is displayed as a recommended route on the map displayed on the monitor 12 (SD
6), end the process.

On the other hand, if the decision result in the above-mentioned step SD3 is YES and there is a road link having a congestion rank on the network, the process proceeds to step SD4.
Then, the distance of the road link (the distance obtained from the distance information) is converted into a distance multiplied by the multiplication coefficient corresponding to the road link in the conversion table B (see FIG. 6). For example, when the distance of a certain road link having a congestion rank is 200 m and the corresponding multiplication coefficient is 5, the distance is set to 1 km. Then, in step SD5, for the road link having the congestion rank, the added cost of each network is calculated using the converted distance, and the network with the smallest added cost is displayed on the map displayed on the monitor 12 as the recommended route. (SD
6), end the process.

In the above-described route calculation, the distance of each road link used when calculating the added cost of each network in step SD5 is determined by the average speed stored in the second learning table C, that is, the road related to traffic congestion. Since the calculation is performed using the multiplication coefficient in the conversion table B determined by the average speed reflecting the circumstances, more accurate addition cost can be obtained. Therefore, step SD6
In, a more accurate recommended route that meets the condition that the required time is the shortest can be selected and presented to the user. At the same time, a more accurate estimated arrival time can be notified. Further, as described in the first embodiment, the effect can be obtained at a lower cost as compared with the case where real-time traffic information such as VICS is used. In addition, for example, a recommended route is calculated in advance. It is possible to cope with such cases.

In addition, in the present embodiment, the average speed data stored in the second learning table C is stored in the storage means for each road link, and the distance is stored in the conversion table B for each road link. Is obtained by using the multiplication coefficient of, when a part or all of each network includes a road that has actually traveled, the addition cost can be calculated extremely accurately. it can. In addition, since the average speed data stored in the second learning table C is limited to a predetermined traveling speed of 15 km / h or less, the number of data stored in the RAM 5 and the number of data used for the route calculation at the same time are reduced. Few. For this reason, the average speed data stored in the second learning table C is set to an average speed that does not significantly affect the error correction of the travel time calculated during the route calculation, that is, a value close to 1 is set as the multiplication coefficient. The required memory capacity of the RAM 5 can be reduced as compared with the case where data of an average speed to be stored is stored. In addition, it is possible to reduce the load of the CUP 4 when calculating the route.

In this embodiment, the RAM 5
When the above-mentioned second learning table is formed,
When the display mode of the congestion rank is set, the map screen shown in FIG. 10 is displayed at the time of traveling by performing the congestion rank display operation. The traffic congestion rank display operation is, for example,
After the setting of the mode, the map / road information is read out from the map CD-ROM 14 based on the own vehicle position acquired by the GPS unit 2 and is expanded in the VRAM 10. If there is a road link whose average speed is stored in the second learning table C (FIG. 7) in the road data included in the converted road data, the conversion table B based on the average speed for all the road links is used. The display symbol is obtained from (FIG. 6),
This is performed by displaying the acquired display symbol on the corresponding road. Therefore, the user can roughly know whether or not there is an easily congested section on a road that has traveled in the past, and about the degree of congestion in a section where traffic is easily congested. For example, in the example shown in FIG. 10, there are two sections A on the road near the vehicle that are congested (the congestion rank is “light”), but not so much, and are slightly congested (the congestion rank is “medium”). B, it can be known that there is one section C that is very likely to be congested (the congestion rank is "heavy").

In this case, even when the display mode of the congestion rank is not set, the user presses the congestion rank display key assigned to any one of the operation keys of the key input unit 13. In such a case, the information may be displayed on the already displayed map. For example, it may be displayed only for a few seconds after the traffic jam rank display key is pressed, or may be displayed only while the key is pressed. In this case, it is possible to prevent the map from being difficult to read in a normal state by notifying the section where the traffic is likely to be congested and the degree of the congestion on the road that has been driven in the past only when necessary. Further, in the present embodiment, description has been made of a case where the degree of congestion is represented by a difference in the shape of a display symbol. However, the display color may be changed with the same symbol shape. Furthermore, it is also possible to set the congestion rank more finely than in the present embodiment, and to display the degree of congestion more finely by combining the symbol shape and the display color.

In the present embodiment, the second learning table C stores data obtained by averaging the passing average speed during traveling by the number of passes, but the passing time during traveling is averaged by the number of passes. Even if the converted data is stored and the data is used, the same effect as in the present embodiment can be obtained. The second learning table C stores the road link that has passed once and the number of passes. However, the data may be stored by distinguishing the traveling direction such as going up and down the road link, or by using FIG. First learning table A explained
As described above, data may be stored separately for the type of the day based on calendar information or the time zone based on time information.
In that case, when calculating the route, if the required time according to the traveling direction, the type of day, and the time zone is acquired,
A more accurate travel time can be obtained. Further, the second learning table C indicates that the average passing speed during traveling is 15 km / h.
Only the data related to the following road links were stored, but the data related to the road links whose average speed exceeded 15 km / h were also stored, and only the data whose average speed was 15 km / h or less during route calculation etc. May be used.

On the other hand, in the first and second embodiments described above, the case where the program for controlling the navigation device is stored in the ROM 6 has been described. However, the program is stored in a recording medium such as the map CD-ROM 14. The recorded program may be read into the RAM 5 or the ROM 6 if the ROM 6 is rewritable. Further, the data stored in the RAM 5 described above may be used directly or via a recording medium such as a floppy disk or an IC card in another device such as a personal computer equipped with a computer. If the program is recorded on the map CD-ROM 14, if the program is used together with the floppy disk or the like to cause a device such as a personal computer to perform the same operation as the navigation device shown in the present embodiment, Particularly convenient.

[0039]

As described above, in the present invention,
On the basis of the traveling state data on the traveling state acquired at the time of traveling, data on the time required for traveling on the set route is calculated, and the data on the calculated time reflects the actual road conditions of the road. Therefore, the required time required for passing through the set route can be more accurately known. As a result, it is possible to more accurately calculate the expected arrival time at the destination when traveling along the set route. Moreover, this can be realized at a lower cost than when real-time traffic information is used.

In addition, in the navigation device of the present invention, the driving state data is stored in the storage means for each type of road, and the control means reads out the driving state data corresponding to the type of road from the storage means, and reads the driving state data. If data relating to the time required for traveling on the route set by the route setting means is calculated based on the state data, a road that has never traveled is included in a part or the front of the route. In such a case, it is possible to more accurately know the time required for passing through the route.

The running state data is stored in the storage means for each road link constituting the road, and the control means reads out the running state data corresponding to the road link forming the route from the storage means and stores the running state data in the storage state data. If the data relating to the time required for traveling on the specified route is calculated based on the specified route, if the part or the front of the route includes a road that has actually traveled, the required time is calculated as Can be known very accurately.

If the traveling state data is data relating to traveling speeds equal to or lower than the determined traveling speed, the number of traveling state data used for calculating the required time required to pass the specified route is small. Become. Therefore, the memory capacity required for the device can be reduced. In addition, the load on the apparatus when calculating the required time can be reduced, and the processing speed can be improved.

Further, if the vehicle is provided with running state display means for displaying information on the running state on a map based on the running state data stored in the storage means, it is possible to display the information independently without using another system. It is possible to make the user predict the actual road situation from the information on the traveled state.

The running state data is stored in the storage means in correspondence with calendar information relating to the calendar from which the traveling state data was obtained or time information relating to the time, and the control means records the calendar information or time information at the time of performing the calculation. If the data on the time required for traveling on the set route is calculated based on the traveling state data based on the traveling state data, the actual road conditions are further reflected in the required time. Can be done. Therefore, it is possible to calculate more accurately than the expected arrival time.

[0045] Further, if a notifying means for notifying the time required for traveling on the set route is provided based on the data on the time calculated by the control means, the usability is improved.

In another apparatus of the present invention, the actual cost of the road is calculated by adding costs obtained from various conditions, such as the traveling distance and the traveling time, used in calculating the route from the departure point to the destination. It was reflected. Therefore, when calculating the route, it is possible to more accurately calculate the recommended route with the shortest traveling distance and the required time.

[0047]

[Brief description of the drawings]

FIG. 1 is a block diagram of a navigation device showing one embodiment of the present invention.

FIG. 2 is a configuration diagram illustrating a first learning table.

FIG. 3 is a flowchart illustrating an operation of the navigation device in a driving situation learning mode.

FIG. 4 is a flowchart illustrating an operation of the navigation device when calculating a route.

FIG. 5 is an explanatory diagram showing a specific calculation example at the time of the same route calculation.

FIG. 6 is a configuration diagram showing a conversion table.

FIG. 7 is a configuration diagram illustrating a second learning table.

FIG. 8 is a flowchart showing the operation of the navigation device in the traffic jam rank learning mode.

FIG. 9 is a flowchart showing an operation of the navigation device when calculating another route.

FIG. 10 is a diagram showing an example of a map displayed in accordance with a traffic jam rank display operation.

[Explanation of symbols]

 2 GPS unit 4 CPU 5 RAM 6 ROM 8 Clock unit 11 Monitor 12 CD unit

Claims (10)

[Claims] 1. self-position acquisition means for acquiring self-position data indicating a current self-position; map data storage means in which map data is stored; and self-location data indicated by the self-position data acquired by the self-position acquisition means. Display means for displaying a map near the position based on the map data stored in the map data storage means; route setting means for setting a route from the departure point to the destination; and travel related to the travel state acquired during travel. Storage means for storing state data; and control means for calculating data relating to the time required for traveling on the route set by the route setting means based on the traveling state data read from the storage means. Navigation device. 2. The driving state data is stored in the storage unit for each type of road, and the control unit reads driving state data corresponding to the type of road from the storage unit, and stores the driving state data in the storage state data. 2. The navigation device according to claim 1, wherein data related to a time required for traveling on a set route is calculated based on the data. 3. The traveling state data is stored in the storage unit for each road link constituting a road, and the control unit reads out traveling state data corresponding to the road link constituting the route from the storage unit. 2. The navigation device according to claim 1, wherein data relating to a time required for traveling on the set route is calculated based on the traveling state data. 4. The navigation device according to claim 3, wherein the traveling state data is data relating to a traveling speed equal to or lower than a determined traveling speed. 5. The navigation device according to claim 4, further comprising a traveling state display unit that displays information on a traveling state on the map based on the traveling state data stored in the storage unit. 6. The running state data is stored in the storage unit corresponding to calendar information and / or time information related to a time when the traveling state data is acquired, and the control unit performs the calculation when the calculation is performed. 4. The method according to claim 1, wherein calendar information and / or traveling state data corresponding to the time is read out from the storage unit, and data relating to a time required for traveling on the set route is calculated based on the traveling state data. 5. The navigation device according to any one of 5. 7. The navigation according to claim 1, further comprising a notifying unit that notifies a time required for traveling on the set route based on data on the time calculated by the control unit. apparatus. 8. Self-position acquisition means for acquiring self-position data indicating a current self-position, map data storage means in which map data is stored, and self-position data indicated by the self-position data acquired by the self-position acquisition means. Display means for displaying a map in the vicinity of the position based on the map data stored in the map data storage means; storage means for storing travel state data relating to the travel state acquired during travel; and travel read from the storage means Control means for calculating data relating to the time required for traveling on the candidate route based on the state data; and A navigation device comprising: a route setting means for setting a route. 9. A method for calculating data relating to a time required for traveling on a set route using map data stored in a map data storage means, wherein driving state data relating to a traveling state during traveling is stored and stored. A method for calculating required time information, comprising calculating data on a time required for traveling on a set route based on traveling state data. 10. A recording medium on which a program read and executed by a computer is recorded, wherein the traveling of a set route is performed based on map data and traveling state data relating to traveling states stored in the past traveling. A recording medium characterized by including a program for calculating data relating to the time required for recording.