JP2009257966A - On-vehicle navigation apparatus - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To achieve ecological driving by presenting the highest fuel economy travel speed recommended for each gradient to a user at a suitable timing. <P>SOLUTION: This on-vehicle navigation apparatus includes an arithmetic processing means 11 for setting the segment on a route output by route search and calculating the average gradient for each set segment, a learning processing means 13 for searching for a model where the highest fuel economy travel speed for each gradient and extracting the corresponding highest fuel economy travel speed based on the average gradient calculated whenever the segment is changed during vehicle travel, accumulating and learning a predetermined number of pieces of vehicle information including the gradient and instantaneous fuel economy of one's own vehicle obtained from the outside, and updating the highest fuel economy travel speed in the model extracted by the learning result, and a display processing means 14 for screen-displaying the updated highest fuel economy travel speed in a predetermined form. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to an in-vehicle navigation device.

In recent years, due to soaring fuel costs and demands for emission reduction of exhaust gas, the appearance of vehicles with higher fuel consumption than ever before has been desired.
Factors that determine the fuel consumption of a vehicle depend on the performance of the vehicle, but are also greatly related to the user's driving operation characteristics. Conventionally, instantaneous fuel consumption information is displayed on the screen in real time in order to suppress fuel consumption due to the driving operation characteristics. While driving, the user can know whether the current driving speed is good or bad based on the instantaneous fuel consumption information displayed in real time, and to obtain high fuel consumption according to the driving environment such as road conditions and road gradients. By approaching the driving speed, eco-driving that saves fuel consumption is possible.

A number of patents have been filed for technologies for realizing eco-driving that saves fuel consumption as described above. For example, each driving lane pattern is taken for at least one driving lane pattern that can be taken in the searched route. A vehicle navigation device that predicts the energy consumption rate at the time and performs lane guidance based on the prediction (see, for example, Patent Document 1),
When the fuel consumption reaches a certain amount, the location of the facility that can supply the nearest fuel is automatically searched, the route from the current location to the facility is searched by route search, automatically set, and displayed on the monitor. Navigation system to display (for example, refer to Patent Document 2), fuel efficiency information corresponding to road gradient and travel speed is stored, and a route with less fuel consumption using travel speed and fuel efficiency information estimated from current traffic information There is a route search device (for example, see Patent Document 3).

JP 2005-98749 A JP 2000-46573 A JP 2006-98174 A

  By the way, since the instantaneous fuel consumption described above considers only the current fuel consumption state, it is considered difficult to find the speed at which the vehicle can travel with the highest fuel consumption for each road condition. In addition, the instantaneous fuel consumption is presented to the user in real time, but the presentation information also changes frequently in places where the road conditions such as the slope change suddenly, which causes unnecessary fuel injection due to sudden acceleration or sudden deceleration. This may adversely affect fuel consumption and may also interfere with safe driving.

  On the other hand, according to the technology disclosed in Patent Document 1, since the road gradient is not reflected in the prediction of fuel consumption, it is not possible to accurately predict the speed at which the vehicle can travel with high fuel consumption. Further, according to the technique disclosed in Patent Document 3, the road gradient on the route is reflected in the prediction of fuel consumption, but the estimated traveling speed and fuel consumption are not presented to the user in real time. The travel speed required for high fuel efficiency driving cannot be known at an appropriate timing for each travel point.

  The present invention has been made in order to solve the above-described problems, and presents the highest fuel efficiency traveling speed recommended for each road gradient to the user at an appropriate timing to enable eco-driving and to make the gradient minute. An object of the present invention is to provide an in-vehicle navigation device capable of maintaining the stability of driving operation by avoiding information presentation with a change as much as possible.

  In order to solve the above-described problems, an in-vehicle navigation device according to the present invention sets a section on a route output by a route search, calculates an average gradient for each of the set sections, and vehicle travel Each time the section is switched, based on the calculated average gradient, a model in which the maximum fuel consumption traveling speed for each gradient is defined is searched, and the corresponding maximum fuel consumption traveling speed is extracted. Learning processing means for performing learning by accumulating a predetermined number of vehicle information including vehicle gradient and instantaneous fuel consumption, and updating the maximum fuel consumption traveling speed in the extracted model based on the learning result; and the updated maximum fuel consumption Display processing means for displaying a traveling speed on a screen in a predetermined format.

  According to the vehicle-mounted navigation device of the present invention, the maximum fuel efficiency traveling speed recommended for each gradient is presented to the user at an appropriate timing to enable eco-driving, and information presentation with a minute gradient change is made as much as possible. By avoiding this, the stability of the driving operation can be maintained.

Embodiment 1 FIG.
1 is a block diagram showing an internal configuration of an in-vehicle navigation device according to Embodiment 1 of the present invention.
As shown in FIG. 1, the in-vehicle navigation device according to the first embodiment of the present invention has a main storage device 2, a touch panel 3, and a sensor with a control device 1 composed of a CPU (Central Processing Unit) as a core. A device 4, a communication device 5, and an external storage device 6 are configured.

  The main storage device 2 is constituted by, for example, a semiconductor memory, and in addition to route search, current location display, destination guidance, section display or vehicle travel speed for high fuel efficiency driving is obtained and displayed on the touch panel 3 on the screen. A program for navigation is resident. In addition, a fuel consumption model defined by the vehicle maker for each vehicle type, in which the maximum fuel consumption traveling speed for each gradient is defined, is stored. The control device 1 executes various navigation processes described below by executing a program selected from the main storage device 2 based on a user instruction acquired via the touch panel 3.

  The touch panel 3 is configured such that, for example, when a user touches information displayed on an LCD (Liquid Crystal Display Device) panel with a transparent tablet laid on the surface with a finger, the coordinate position and contents are read and the control device 1 reads the information. In addition to transferring, the input / output device displays navigation information generated by the control device 1. As an alternative to the touch panel 3, a remote controller and a display monitor may be independently connected.

  The sensor device 4 is, for example, a GPS (Global Positioning System) sensor, a vehicle speed sensor, an angular velocity sensor, a gyroscope, or the like, which is mounted in each part of the vehicle, and is detected and output by these sensors. By supplying a signal indicating information, rotation angle information, road gradient, or the like to the control device 1, a desired navigation process by the control device 1 described above is realized.

The communication device 5 receives traffic information and the like from an external traffic information center such as VICS (Vehicle Information and Communications) and supplies it to the control device 1 so that the control device 1 can perform navigation while avoiding traffic jams. Become.
The external storage device 6 is composed of, for example, a hard disk, a DVD (Digital Versatile Disc) or the like, and stores a map DB (Data Base) or the like. The control device 1 reads out the corresponding map information from the map DB referred to by the execution of the program described above, and displays it on the touch panel 3 together with the current location of the vehicle.

FIG. 2 is a functional block diagram showing the structure of the program executed by the control device 1 shown in FIG.
As shown in FIG. 2, the control device 1 includes an arithmetic processing unit 11, a vehicle information acquisition unit 12, a learning processing unit 13, and a display processing unit 14.

The arithmetic processing means 11 has a function of setting a section on the route output by the route search and calculating an average gradient for each of the set sections, and internally includes a route information determination unit 111, a road The section setting unit 112 is configured.
The route information determination unit 111 supplies the road section setting unit 112 with information on a route generated according to the destination set by the user operating the touch panel 3. The road section setting unit 112 sets, for each route, a section where a predetermined gradient continues within a predefined error range of the gradient angle change, calculates an average gradient for the set section, and learns processing means 13 ( The data is output to the construction rule management unit 134) and the display processing means 14 (display information determination unit 141).

The vehicle information acquisition unit 12 acquires vehicle information generated based on information acquired via the sensor device 3, for example, including the gradient of the host vehicle and the instantaneous fuel consumption, and learn processing unit 13 (acquired information storage unit 132).
The learning processing unit 13 searches for a model (a model DB 131 described later) in which the maximum fuel consumption traveling speed for each gradient is defined based on the average gradient calculated by the calculation processing unit 11 every time a section is switched during vehicle traveling. A corresponding maximum fuel consumption travel speed is extracted, and a predetermined number of vehicle information including the gradient of the host vehicle, the travel speed, and the instantaneous fuel consumption acquired from the vehicle information acquisition means 12 are accumulated to perform data mining (here, for each data item). And a function of updating the maximum fuel consumption traveling speed in the extracted model based on the learning result, and internally, the model DB 131, the acquired information storage unit 132, The acquisition information learning unit 133 and the construction rule management unit 134 are configured.

As shown in part of the data structure in FIG. 3, the model DB 131 defines and stores the maximum fuel consumption traveling speed for each gradient, and the fuel consumption [km / km] for each gradient (inclination angle [%]). l] is configured by a table that outputs the traveling speed [km / h] of the own vehicle. The model shown here is, for example, information provided by the manufacturer for each vehicle type (fuel consumption [km / l], own vehicle travel speed [km / h] and gradient [ %] Is constructed based on a three-dimensional graph).
The acquired information storage unit 132 stores information on the gradient and traveling speed of the host vehicle during actual traveling and the instantaneous fuel consumption acquired by the vehicle information acquiring unit 12 in time series.

  Note that the model DB 131 and the acquired information storage unit 132 are described here as being internally included in the learning processing unit 13 for the sake of convenience, but in actuality (on the hardware), the model DB 131 and the acquired information storage unit 132 are predetermined in the main storage device 2 illustrated in FIG. It is allocated and stored in the area.

The acquisition information learning unit 133 extracts an appropriate rule by performing a learning process by data mining on a learning table generated when the vehicle information read from the acquisition information storage unit 132 is stored for a predetermined number of records. . As the rules extracted here, for example, when the gradient is -1 [%], the gradient is -1 [%], the recommended speed is 50 [km / h], and the maximum fuel consumption is 21 [km / l]. .
The construction rule management unit 134 is activated by the acquisition information learning unit 133 as a result of the learning process, in addition to starting the learning process by the acquisition information learning unit 133 in response to an intention display of learning start from the user by operating the touch panel 3. According to the rule, the model DB 131 has a function of updating and managing the maximum fuel consumption traveling speed for each gradient.

The display processing unit 14 has a function of displaying the maximum fuel consumption traveling speed updated by the learning processing unit 13 (construction rule management unit 134) in a predetermined format, and internally includes a display information determination unit 141, And an information output unit 142.
The display information discriminating unit 141, except for a section where the section set by the arithmetic processing unit 11 (the road section setting unit 112) is less than a predetermined length or where traffic congestion has occurred due to traffic information acquired from outside, When approaching the next section by a predetermined distance, display information for displaying the maximum fuel consumption traveling speed and the current traveling speed of the own vehicle on the touch panel 3 on the touch panel 3 is generated and the information output unit 142 is displayed. Supply. The information output unit 142 converts the display information generated by the display information determination unit 141 into a predetermined format according to display specifications described later, and outputs the converted information to the touch panel 3.

FIG. 5 is a flowchart showing the basic operation of the in-vehicle navigation device according to Embodiment 1 of the present invention.
The basic operation of the in-vehicle navigation device according to Embodiment 1 of the present invention will be described below with reference to the flowchart of FIG.

First, the arithmetic processing unit 11 extracts the presence / absence of a route generated by the route information determination unit 111 by the route search function (step ST51), and the road segment setting unit 112 sets the road segment according to the presence / absence of the route, Then, the average gradient for each section is calculated and supplied to the learning processing means 13 and the display processing means 14.
As will be described later, the section setting is performed by the road section setting unit 112 using the current vehicle position as a starting point, extracting the end point of the section, and calculating an average gradient. When the route information determination unit 111 determines that a route exists (step ST52 “YES”), the road section setting unit 112 continues the above extraction work until the end point of the route and calculates an average gradient for each section ( When it is determined that there is no route (step ST53) (step ST52 “NO”), the current section is set and the average gradient is calculated (step ST54).

The learning processing unit 12 is configured so that the construction rule management unit 134 is switched before the own vehicle enters the next section in the section individually set by the arithmetic processing unit 11 (the road section setting unit 112). Every time (step ST55 “YES”), the legal speed in the planned entry section is acquired from the map DB of the external storage device 6 (step ST56), and is stored in the main storage device 2 based on the average gradient of the section. Appropriate rules within the legal speed of the corresponding section are extracted from the model DB 131 in which the maximum fuel efficiency traveling speed for each gradient is defined (step ST57).
On the other hand, the vehicle information acquisition means 12 always acquires vehicle information indicating vehicle speed, gradient, or instantaneous fuel consumption from the sensor device 4 installed in various parts of the vehicle, and the learning processing means 13 (acquired information storage unit 132) (step ST58).

In the learning processing means 13, the acquisition information learning unit 133 performs learning by data mining on a predetermined number of vehicle information accumulated in the acquisition information storage unit 132. Depending on the learning result, the construction rule management unit 134 first determines the model. The rule (maximum fuel consumption traveling speed) extracted from the DB is updated and delivered to the display processing means 14 (display information determination unit 141) (step ST59).
In response to this, the display processing means 14 determines the content to be displayed in order to display the updated maximum fuel consumption traveling speed on the screen in a predetermined format, and outputs and displays it on the touch panel 3 (step ST60). At this time, the display information discriminating unit 141 is a section except for a section where the section set by the road section setting unit 112 is less than a predetermined length, or a traffic jam occurs due to traffic information acquired from outside. Information for displaying the maximum fuel efficiency traveling speed for each screen is generated and supplied to the information output unit 142. And the information output part 142 provides the information for display to the touch panel 3 according to a display format based on the supplied information (step ST61).

FIG. 6 is a flowchart showing a detailed flow of the section setting and average gradient calculation processing in step ST53 of the basic operation in FIG.
The details of the section setting and the average gradient calculation processing in step ST53 of the basic operation by the arithmetic processing means 11 will be described below with reference to the flowchart of FIG.

  In the flowchart of FIG. 6, the arithmetic processing means 11 (the road section setting unit 112) sets the starting point of the route or the vehicle position as the starting point of the section (step ST531), and from the map DB stored in the external storage device 6 Gradient information A on the vehicle position is acquired (step ST532). Then, the traveling direction B is acquired based on the sensor information output by the vehicle information acquisition means 12 (step ST533), and the acquired gradient is within the ± error range of the gradient A (step ST534), or the ± error of the traveling direction B Within the range (step ST535) is set as a determination condition, and the gradient of A up to outside the ± error range is added (step ST536). Then, when a predetermined distance has been reached on the route, the process returns to step ST532 (step ST537), and the above process is repeated until it is determined that it is outside the ± error range (steps ST534 “NO”, ST535 “NO”).

  Subsequently, the road section setting unit 112 sets a point that is outside the ± error range (step ST534 “NO”, step ST535 “NO”) as an end point, assigns a section name (step ST538), and calculates the sum of the combined gradients. The average gradient of the section is calculated by dividing by the total number of times (step ST539). Then, after the assignment of the section is completed, when the route continues after the section (step ST540 “NO”), the same processing as the series of processes described above is repeated.

FIG. 7 is a flowchart showing a detailed flow of the learning process by data mining in step ST59 of the basic operation in FIG.
The details of the learning process by data mining in step ST59 of the basic operation by the learning processing means 13 will be described below with reference to the flowchart of FIG.

  By the way, the maximum fuel efficiency traveling speed for each gradient is defined, and the format of the rules in the model DB stored in the main storage device 2 is, as described with reference to FIG. 3, the vehicle speed [hm / h] on the horizontal axis, It is shown in a table with a gradient (tilt angle [%]) on the axis. Therefore, the learning processing unit 13 (construction rule management unit 134) searches the model DB 131 for a corresponding gradient based on the average gradient calculated in each section by the arithmetic processing unit 11 (road section setting unit 112). The maximum fuel consumption traveling speed at the gradient is extracted. For example, according to the data structure shown in FIG. 3, when the average gradient is -1 [%], the extracted rules are gradient: -1 [%], travel speed: 50 [km / h], and maximum fuel consumption: 21 [km / l].

  On the other hand, the data mining executed by the acquired information learning unit 133 is performed when the predetermined number of records are stored in the actual driving environment of the host vehicle stored in the acquired information storage unit 132. Here, by extracting an appropriate rule and transferring it to the construction rule management unit 134, it is possible to reflect it in the model DB 131 in which the maximum fuel consumption traveling speed for each gradient is defined. As a result, it becomes possible to improve the accuracy of the rule of the maximum fuel consumption traveling speed suitable for each actual traveling environment.

Specifically, as illustrated in the flowchart of FIG. 7, the learning processing unit 13 (the construction rule management unit 134) is triggered by a user instruction that reflects the learning result, for example, a predetermined pressing by the user of the touch panel 3. (Step ST591 “YES”), while the host vehicle is traveling (Step ST592 “YES”), the vehicle information including the gradient information, travel speed, and instantaneous fuel consumption acquired via the vehicle information acquisition means 12 is learned in the acquisition information storage unit 32. This is stored as a table for use (steps ST593 and ST594). When the learning table exceeds the prescribed number for each data record, the acquisition information learning unit 133 is activated (step ST595 “YES”), and the rule extraction process by the acquisition information learning unit 133 is started (step ST596).
The acquisition information learning unit 133 extracts an appropriate rule by data mining from the vehicle information at the time of actual traveling set in the learning table of the acquisition information storage unit 132 and passes it to the construction rule management unit 134 when starting the rule extraction process. (Step ST597).

The construction rule management unit 134 searches and responds to the model DB 131 stored in the main storage device 2 based on the average gradient calculated by the road section setting unit 112 of the arithmetic processing unit 11 every time the section is switched during traveling. The maximum fuel consumption traveling speed is extracted (step ST598).
The construction rule management unit 134 acquires the correlation between the rule (maximum fuel consumption traveling speed X) learned by the acquisition information learning unit 133 and the rule (maximum fuel consumption traveling speed Y) extracted from the model DB 131 (step ST599). When it is determined that the rule (maximum fuel consumption traveling speed X) learned by the information learning unit 133 is appropriate (“YES” in step ST599), the rule (maximum fuel consumption traveling speed Y) in the model DB 131 is replaced, and display processing means is performed. 14 (display information determination unit 141) (step ST600).

  That is, the construction rule management unit 134 updates the rules defined in the model DB 131 with the rules learned by the acquisition information learning unit 133. In addition, for example, when it is determined that the rule defined in the model DB 131 is appropriate because the rule extracted by learning exceeds the legal speed (step ST599 “NO”), the rule defined in the model DB 131 Is passed to the display processing means 14 (display information determination unit 141).

  The above-described rule extraction processing is repeatedly executed by the acquisition information learning processing unit 133 for a specified number of records included in the learning table of the acquisition information storage unit 132 (step ST601). Finally, the acquired information learning processing unit 133 resets the learning table, thereby ending the learning process by data mining (step ST602).

When the initial model case table shown in FIG. 4 is stored in the model DB 131, learning is performed from the learning table stored in the acquired information storage unit 132 by actual traveling, thereby learning a more appropriate rule than the initial rule. can do. FIG. 8 shows an example in which the rules learned from the learning table stored as needed are reflected in the model DB 131 shown in FIG.
As is clear from comparison between FIG. 4 and FIG. 8, for example, according to the initial rule, a maximum fuel consumption of 25 [l] is realized at a traveling speed of 50 [km / h] at a gradient of −2 [%]. On the other hand, according to the updated rule, it can be seen that a traveling speed of 60 [km / h] is required to achieve the maximum fuel consumption of 25 [l] under the same gradient condition. As described in the basic operation shown in FIG. 5, when the traveling speed exceeds the legal speed, the traveling speed is corrected so as to be within the legal speed.

FIG. 9 is a flowchart showing a detailed flow of the display information determination process in step ST60 of the basic operation in FIG.
Hereinafter, the details of the display information determination processing by the display processing means 14 in step ST60 of the basic operation will be described with reference to the flowchart of FIG.

In the flowchart of FIG. 9, in the display processing unit 11, first, the display information determination unit 141 acquires information on the section length of the section set from the road section setting unit 112 of the arithmetic processing unit 11 (step ST611).
Next, the display information determination unit 141 compares the acquired section length with a threshold (step ST612), and when it is determined that the section length is equal to or less than a predetermined distance (step ST612 "YES"), the updated model DB 131 is displayed. The information output unit 142 is instructed not to perform guidance based on the display of the traveling speed or the like but only to update the display of an icon to be described later (step ST613).

On the other hand, when it is determined that the set section length is longer than the predetermined distance (step ST612 “NO”), the display information determination unit 141 determines the presence or absence of section congestion from the congestion information such as VICS acquired by communication. However, when it is determined that there is a traffic jam (step ST615 “NO”), as in the case where the section length is short as described above, the travel speed or the like based on the updated model DB 131 is displayed. Do not give guidance. When it is determined that there is no traffic jam (step ST615 “YES”), the display information determination unit 141 determines the maximum fuel consumption travel speed (updated model) in the section before the host vehicle enters the next section. Guidance based on the travel speed based on DB) is performed and icon display update described later is performed (step ST616).
The information output unit 142 converts the display information generated by the display information determination unit 141 into a predetermined format according to display specifications described later, and outputs the converted information to the touch panel 3.

As described above, according to the vehicle-mounted navigation device according to Embodiment 1 of the present invention,
By presenting in real time the driving speed that realizes the maximum fuel consumption suitable for actual driving conditions such as road gradients, the user can check the fuel consumption during driving at any time, enabling driving at the optimal driving speed for eco-driving Thus, useless fuel consumption can be saved.
In addition, the instantaneous fuel consumption for each gradient is acquired, stored, and learned at any time to update and present the high fuel consumption traveling speed according to the current driving environment and state (air pressure, engine oil, etc.) of the vehicle. be able to.

  Moreover, according to the vehicle-mounted navigation device according to Embodiment 1 of the present invention, in setting the section, the section in which the constant gradient continues within the error range of the gradient angle change without mixing the gradient of the up and down slopes. By searching and setting, it is possible to guide the user to the travel speed suitable for the current travel situation as necessary. In addition, the curved section is excluded from the guidance, and the frequent change of the gradient angle in the short-distance section prevents frequent information presentation, thereby preventing sudden acceleration or sudden deceleration. The stability of the driving operation can be maintained.

  Next, based on the display specification realized by the display processing means 14, it demonstrates, referring an example of the screen structure shown in FIGS.

For example, as shown in FIG. 10, when the vehicle approaches the next section, the display processing means 14 switches and displays the current traveling speed of the host vehicle and the traveling speed at which high fuel consumption driving is possible in that section. Can guide you. In addition, if the vehicle traveling speed or fuel consumption of a section during actual traveling is different from the maximum fuel consumption traveling speed or fuel consumption of the section, the vehicle traveling speed or fuel consumption is displayed on the screen according to the speed difference or fuel consumption difference. May be highlighted.
That is, as shown in FIG. 11, for example, an icon whose color changes according to the speed difference is displayed so that the user can intuitively know the fuel efficiency at the current traveling speed of the host vehicle, or the character color is changed to the speed color. You may make it change according to a difference. At this time, the information output unit 142 generates display information under the control of the display information determination unit 141, and performs display modification control by color, for example, and outputs the display information to the touch panel 3.

The display processing unit 14 also detects a section touched by the user in a route displayed on the screen of the touch panel 3 as shown in FIG. 12 as an example of the screen configuration, and displays the highest of the detected sections. The fuel consumption traveling speed or the fuel consumption may be displayed. At this time, the information output unit 142 acquires coordinate data from the touch panel 3 under the control of the display information determination unit 141, and displays display information for displaying the maximum fuel consumption traveling speed or fuel consumption in the corresponding section on the screen. Generate and output to the touch panel 3.
It should be noted that the above high fuel consumption traveling speed is not displayed when the section length is short, but as shown in FIG. 13, the icon indicating the fuel consumption is updated and displayed even when the section length is short. To do.

The display processing means 14 also displays each section constituting the route output by the route search on the touch panel 3 screen as shown in FIG. 14 as an example of the screen configuration, and is assigned to an arbitrary area of the touch panel 3 screen. When pressing of the “maximum fuel consumption traveling speed display button” to be displayed is detected, the maximum fuel consumption traveling speed of the entire route section may be displayed. However, information regarding a section for which display guidance is not performed due to the section length or the like is not displayed.
Further, as shown in FIG. 15 as an example of the screen configuration, the display processing unit 14 displays each section constituting the route output by the route search on the screen of the touch panel 3, and arbitrarily displays the screen of the touch panel 3. When the pressing of the “section predicted fuel consumption display button” assigned to the area and detected is detected, the section predicted fuel consumption of the section of the entire route may be displayed. However, information regarding a section for which display guidance is not performed due to the section length or the like is not displayed.

As described above, according to the vehicle-mounted navigation device according to Embodiment 1 of the present invention, the user can check the fuel consumption during traveling at any time by displaying the maximum fuel consumption speed on the touch panel 3 when approaching the next section. Eco-driving can be practiced, and the user can intuitively determine the current driving state by performing highlighting by changing the color according to the speed difference from the actual traveling speed.
In addition, it is possible to display the maximum fuel consumption traveling speed or fuel consumption in the section only by touching a section in the route, and furthermore, the section predicted fuel consumption or section predicted fuel consumption is displayed by pressing a button assigned on the screen. In addition to providing convenience to the user, it is possible to improve the usability.

Note that the functions of the control device 1 shown in FIG. 2 may be realized entirely by software, or at least a part thereof may be realized by hardware.
For example, the section on the route output by the route search is set, the data processing as the arithmetic processing means 11 for calculating the average slope for each set section, the average slope calculated every time the section is switched while the vehicle is running Based on the above, a model in which the maximum fuel consumption traveling speed for each gradient is defined is searched and the corresponding maximum fuel consumption traveling speed is extracted, and vehicle information including the gradient of the own vehicle and the instantaneous fuel consumption obtained from the outside is obtained in a predetermined number. Data processing as learning processing means 13 for accumulating and learning and updating the maximum fuel consumption traveling speed in the model extracted based on the learning result, and display processing for displaying the updated maximum fuel consumption traveling speed on a screen in a predetermined format The data processing as the means 14 may be realized on a computer by one or a plurality of programs, and at least a part thereof is implemented by hardware. It may be.

It is a block diagram which shows the internal structure of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention. It is the block diagram which expanded the function and showed the structure of the program which the control apparatus shown in FIG. 1 performs. It is a figure which shows an example of the data structure of model DB shown in FIG. It is a figure which shows an example of the rule extracted from model DB shown in FIG. It is a flowchart which shows the basic operation | movement of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention. It is a flowchart which shows the road area setting process operation | movement of the vehicle-mounted navigation apparatus concerning Embodiment 1 of this invention. It is a flowchart which shows the learning process operation | movement by the data mining of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention. It is a figure which shows an example of the data structure of rule DB in which the data mining result of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention was reflected. It is a flowchart which shows the display processing operation | movement of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention. It is a figure which shows an example (1) of the screen structure of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention. It is a figure which shows an example (2) of the screen structure of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention. It is a figure which shows an example (3) of the screen structure of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention. It is a figure which shows an example (4) of a screen structure of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention. It is a figure which shows an example (1) of the screen structure of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention. It is a figure which shows an example (5) of a screen structure of the vehicle-mounted navigation apparatus which concerns on Embodiment 1 of this invention.

Explanation of symbols

  1 control device, 2 main storage device, 3 touch panel, 4 sensor device, 5 communication device, 6 external storage device, 11 arithmetic processing means (111 route information discrimination unit, 112 road section setting unit), 12 both information acquisition means, 13 Learning processing means (131 model DB, 132 acquisition information storage section, 133 acquisition information learning section, 134 construction rule management section), 14 display processing means (141 display information determination section, 142 information output section).

Claims (11)

An arithmetic processing means for setting a section on the route output by the route search and calculating an average gradient for each of the set sections;
While driving the vehicle, based on the average gradient calculated by the arithmetic processing means every time the section is switched, a model in which the maximum fuel consumption traveling speed for each gradient is defined is searched and the corresponding maximum fuel consumption traveling speed is extracted. Learning processing means for accumulating a predetermined number of vehicle information including the gradient of the own vehicle acquired from the outside and the instantaneous fuel consumption, learning, and updating the maximum fuel consumption traveling speed in the extracted model according to the learning result;
Display processing means for displaying the highest fuel efficiency traveling speed updated by the learning processing means on a screen in a predetermined format;
An in-vehicle navigation device comprising: The arithmetic processing means includes:
The vehicle-mounted navigation device according to claim 1, wherein a section in which a predetermined gradient continues within an error range of a gradient angle change defined in advance is set, and the average gradient is calculated for the set section. The learning processing means includes
In response to a user instruction that reflects the learning result, vehicle information including the vehicle gradient and instantaneous fuel consumption during vehicle travel is acquired from the outside, stored separately from the model, and when a predetermined number of vehicle information is stored. 2. A rule is extracted, a correlation is obtained based on the extracted rule and a rule extracted from the model, and a maximum fuel consumption traveling speed for each gradient in the model is updated based on the correlation. The in-vehicle navigation device described. The learning processing means includes
Each time the section is switched while the vehicle is running, the legal speed of the section scheduled to enter is acquired from the map information, and the legality of the corresponding section is obtained from the model in which the maximum fuel consumption traveling speed for each slope is defined based on the average slope of the section. 4. The in-vehicle navigation device according to claim 3, wherein a rule in the speed is extracted. The display processing means includes
The maximum fuel consumption traveling speed for each section is displayed on the screen except for a section where the section set by the arithmetic processing means is less than a predetermined length or where traffic congestion has occurred due to traffic information acquired from outside. The in-vehicle navigation device according to claim 1. The display processing means includes
6. The vehicle according to claim 5, wherein when the vehicle approaches the next section for a predetermined distance, the maximum fuel consumption traveling speed in the next section and the current traveling speed of the host vehicle are displayed on a screen. Car navigation system. The display processing means includes
The in-vehicle navigation device according to claim 5 or 6, wherein the state of the fuel consumption at the current traveling speed of the host vehicle is displayed on the screen with an icon that changes in accordance with the level. The display processing means includes
The section touched by the user on the route displayed on the screen is detected, and the maximum fuel consumption traveling speed or the fuel consumption of the detected section is displayed. The vehicle-mounted navigation device according to item. The display processing means includes
If the running speed or fuel consumption of the vehicle in a section that is currently running differs from the maximum fuel consumption traveling speed or fuel consumption of the section, the vehicle traveling speed or fuel consumption is displayed on the screen according to the speed difference or fuel consumption difference. The in-vehicle navigation device according to any one of claims 5 to 8, wherein highlighting is performed. The display processing means includes
Each section constituting the route output by the route search is displayed on the screen, and when pressing of the maximum fuel consumption traveling speed display button displayed and assigned to an arbitrary area of the screen is detected, the entire route is displayed. 6. The in-vehicle navigation device according to claim 5, wherein the maximum fuel consumption traveling speed of the section is displayed. The display processing means includes
A section of the entire route is displayed when each section constituting a route output by the route search is displayed on the screen, and pressing of a section expected fuel consumption display button assigned to an arbitrary area of the screen is detected. The vehicle-mounted navigation device according to claim 5 or 10, wherein the estimated fuel consumption of the section is displayed.

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