JP4481055B2 - Navigation device - Google Patents

Description

  The present invention learns the operation of the navigation device executed by the voice input of the driver and the running situation of the vehicle when the voice is inputted, and executes the action executed by the voice input judging from the current running situation of the vehicle. The present invention relates to a navigation device.

2. Description of the Related Art Conventionally, a navigation device that inputs a command by voice instead of manually inputting a command (Japanese Patent Laid-Open No. 2001-216129) is known.
JP 2001-216129 A

  In the invention described in Japanese Patent Application Laid-Open No. 2001-216129, a command can be input by voice, so that the command can be easily input. However, although it is simple, every time a command is entered, a word must be spoken every time, and there is a problem that it feels troublesome.

The invention of claim 1 is applied to a navigation device, and execution means for executing the operation of the navigation system, an audio input means capable of performing the operations of the navigation device by speech input, detects for detecting a running condition of the vehicle means and a storage means for storing the running state of the vehicle detected by the detecting means when the operation and the voice input of the navigation device in which is executed by the voice input means, voice input from the traveling condition stored by the storage means using a reference calculation means for calculating a reference number of times corresponding to the reference numerical calculates the reference value of the order to execute the operation of the navigation apparatus to execute a function the running status of detected by the detecting means the vehicle by means a digitizing means for digitizing, execution unit, during traveling of the vehicle, it is digitized by digitizing means When the number of times that meet the criteria numerical value calculated traveling condition of the vehicle by the reference calculating means is the reference number of times or more, and executes the operation of the navigation device is executed by the voice input means.
According to a second aspect of the present invention, in the navigation device according to the first aspect, the reference calculating means and the digitizing means calculate the reference numerical values and the numerical values of the vehicle running conditions using a method based on fuzzy theory. Each one is to do .
According to a third aspect of the present invention, in the navigation device according to the first or second aspect, the words input by the voice input means are words indicating road conditions, words indicating vehicle driving conditions, or driver's It is intended to include at least one of the words indicating the physical condition .
According to a fourth aspect of the present invention, in the navigation device according to any one of the first to third aspects, the reference calculating means is used when the running state of the vehicle detected by the detecting means when a voice is input exceeds a predetermined range. And the digitizing means includes an updating means for updating functions used for calculating the reference numerical value and for digitizing the traveling state of the vehicle .
According to a fifth aspect of the present invention, in the navigation device according to any one of the first to fourth aspects, the operations executed by the executing means are a search for a detour route for a traffic jam and a search for a stopover point in a rest area.
According to a sixth aspect of the present invention, in the navigation device according to the third aspect, when the speech input word is a word representing traffic jam, the operation executed by the execution means is a bypass route search.

  If the navigation device of the present invention is used, a voice input word and vehicle situation are learned, and a route search is appropriately performed according to the vehicle situation without displaying voice input, and the result is displayed.

  A configuration of a navigation apparatus according to an embodiment of the present invention is shown in FIG. The navigation device 1 shown in FIG. 1 has a function of recognizing words input from a microphone and operating the navigation device in addition to a normal navigation function such as a map display, and a driver's operation of the navigation device and driving of the vehicle. It has a function of storing the situation in the data storage unit. The navigation device 1 includes a control circuit 11, a ROM 12, a RAM 13, a current location detection unit 14, an image memory 15, an output unit 16, an input unit 17, a VICS (road traffic information system) information reception unit 18, a disk drive 19 and a data storage unit 21. have. The disk drive 19 is loaded with a DVD-ROM 20 on which map data is recorded.

  The control circuit 11 includes a microprocessor and its peripheral circuits, and performs various controls by executing a control program stored in the ROM 12 using the RAM 13 as a work area. When the control circuit 11 performs a predetermined route search process based on the map data stored in the DVD-ROM 20, the processing result is displayed on the display monitor of the output unit 16 as a recommended route.

  The current position detection unit 14 is a device that detects the current position of the vehicle. For example, the current position detection unit 14a detects a traveling direction of the vehicle, a vehicle speed sensor 14b that detects a vehicle speed, and a GPS signal from a GPS (Global Positioning System) satellite. It consists of a GPS sensor 14c and the like. The navigation device 1 determines a display range of the map, a route search start point, and the like based on the current location of the vehicle detected by the current location detection unit 14, and displays the current location on the map.

  The image memory 15 stores image data to be displayed on the display monitor of the output unit 16. This image data includes road map drawing data and various graphic data, which are appropriately generated based on map data stored in the DVD-ROM 20 read by the disk drive 19. The navigation device 1 can perform map display and the like by using the image data generated in this way.

  The output unit 16 includes a display monitor and a speaker. The display monitor provides the driver with various information such as a map near the vehicle position as a screen display based on various information such as map data. The speaker provides various information such as a map in the vicinity of the vehicle position to the operator by voice based on various information such as map data by voice. The input unit 17 has a voice input unit for detecting the driver's words and an input switch for the driver to set the destination of the vehicle. This is realized by a microphone, an operation panel, a remote control, or the like. The driver selects the destination and sets the destination by operating the input unit 17 manually or by voice according to an instruction or voice on the screen displayed on the output unit 16.

  When the destination is set by the driver, the navigation apparatus 1 performs a route calculation from the current location detected by the GPS sensor 14c to the destination based on a predetermined algorithm. The route obtained in this way (hereinafter referred to as a search route) is displayed on the screen separately from other roads by changing the display form, for example, the display color. Thereby, the driver can recognize the search route on the map on the screen. In addition, the navigation device 1 guides the vehicle by instructing the driver of the traveling direction by using a screen or voice so that the vehicle can travel according to the searched route.

  The VICS information receiving unit 18 receives VICS information such as traffic jam information supplied from a VICS information center (not shown) and outputs it to the control circuit 11. This VICS information is transmitted mainly by radio beacons installed on highways, optical beacons installed mainly on general roads, or FM multiplex broadcasting. Radio wave beacons and optical beacons transmit VICS information to vehicles passing near the installation site, and FM multiplex broadcasting covers a wider communication area. The navigation device 1 receives the VICS information transmitted by them by the VICS information receiving unit 18.

  The disk drive 19 reads the map data for displaying the map on the display monitor 16 from the loaded DVD-ROM 20. Note that the map data may be read from a recording medium other than the DVD-ROM, such as a CD-ROM or a hard disk. The data storage unit 21 is configured by a rewritable non-volatile recording medium such as a memory or a hard disk, and stores various information such as running conditions and operation history of the navigation device in a database. Information stored in the data storage unit 21 is appropriately read and used by the control circuit 11.

  The navigation device of the present invention learns the operation and vehicle situation executed by voice input, performs route search according to the vehicle situation without displaying voice input from the result, and displays the result on the display screen. Taking a traffic jam as an example, how to make a route search based on a vehicle status and display the result on the display screen will be described. The learning of the navigation device for searching for a detour route in a traffic jam and displaying the detour route will be described with reference to FIG. Fuzzy reasoning is used to learn the navigation device.

  Since the traffic has become congested, in order to search for a detour route and display it on the display screen of the navigation device, the driver utters the word “congestion” on the microphone of the input unit 17 of the navigation device and detours to detour the traffic jam. The route is searched and a detour route for traffic jam is searched for and displayed on the display screen (step S11). At this time, an average speed per unit time, a travel distance per unit time, and a passing time per unit travel distance when the driver searches for and displays a bypass route of the traffic jam are detected by the vehicle speed sensor 14b or the like (step S12). It is stored in the data storage unit 21 together with the operation of the navigation device by voice input.

  Next, based on the average speed membership function when searching for and displaying the detour route of the traffic jam from this measurement result, the degree of fitness that the driver feels that is slow or slow with respect to the average speed per unit time is calculated (step S13). ). The average velocity membership function is shown in FIG. The membership function of average speed is a function used in fuzzy theory, and is a function that expresses the degree of feeling that it is slow or not slow with respect to the average speed per unit time. The goodness of fit is expressed as a value between 0 and 1, and the closer to 1, the greater the degree of feeling that it feels slower or not, and the closer to 0, the slower or slower it feels The degree to which it falls becomes small. In one embodiment of the present invention, when the average speed per unit time is 10 km / h or more, the fitness level that is felt as slow is 0, and the fitness level that is not slow is defined as 1, and the average speed per unit time is 0 km / h. In this case, the fitness level that is felt as late is 1 and the fitness level that is not late is 0. The membership function of the average speed is stored in the data storage unit 21.

  Next, based on the membership function of the travel distance, the degree of adaptability that the driver feels that is slow or not slow relative to the travel distance per unit time when the detour route of the traffic jam is displayed is calculated (step S14). The membership function of the moving distance is shown in FIG. The movement distance membership function is a function used in fuzzy theory, and is a function that expresses the degree of fitness with respect to the movement distance per unit time as a degree of fitness. The goodness of fit is expressed as a value between 0 and 1, and the closer to 1, the greater the degree of feeling that it feels slower or not, and the closer to 0, the slower or slower it feels The degree to which it falls becomes small. In one embodiment of the present invention, when the moving distance per unit time is 1 km or more, the fitness level that feels slow is 0, the fitness level that feels not slow is 1, and the slowness when the movement distance per unit time is 0 km. The degree of fit that feels like is 1 and the degree of fit that feels not late is 0. The membership function of the moving distance is stored in the data storage unit 21.

  Next, based on the membership function of travel time, the degree of adaptability that the driver feels early and early with respect to the transit time per unit travel distance when searching for and displaying a detour route of traffic jam is calculated (step S15). The membership function of travel time is shown in FIG. The membership function of travel time is a function used in fuzzy theory, and is a function that expresses the degree to which it feels early or not fast with respect to the passing time per unit travel distance as a fitness. The goodness of fit is expressed as a value between 0 and 1, and the closer to 1, the higher the degree of feeling that it is faster or faster, the closer it is to 0, the faster or faster it feels The degree to which it falls becomes small. In one embodiment of the present invention, when the passing time per unit moving distance is 10 minutes or more, the degree of fitness that feels fast is 0, and the degree of fitness that feels not fast is 1, and the time per unit moving distance is 0 minutes. In this case, the fitness level that is felt early is 1 and the fitness level that is not early is 0. The membership function of travel time is stored in the data storage unit 21.

  Next, the minimum value of the fitness is calculated from the suitability of the three items of the average speed per unit time, the travel distance per unit time, and the transit time per unit travel distance when the detour route of the traffic jam is searched and displayed. (Step S16). Here, the minimum value of the fitness is calculated because the common part of the fuzzy sets created with the suitability of the three items becomes the fuzzy set created with the minimum values of the fitness of the three items.

  Then, from the minimum value and the membership function of the traffic jam situation, a fuzzy set of the traffic jam situation when the detour route of the traffic jam is searched and displayed is created (step S17). FIG. 6 shows the membership function of the traffic situation. The traffic condition membership function is a function that represents the relationship between the minimum value of the degree of fitness of the above three items and the degree of traffic jam. The vertical axis represents the minimum value of the degree of fitness of the above three items, and the horizontal axis represents the degree of traffic jam fitness indicating the degree of the traffic jam situation. The degree of fitness representing the degree of traffic congestion is expressed between 0 and 1, and the closer the value of fitness is to 1, the higher the degree of traffic congestion and the lower the degree of non-congestion. Further, the closer the value of fitness is to 0, the lower the degree of traffic congestion and the higher the degree of non-congestion. Further, the fuzzy set of traffic conditions refers to an area equal to or less than the minimum value of the fitness of the above three items in the traffic condition membership function in FIG. The membership function of the traffic situation is stored in the data storage unit 21.

  Next, the degree of matching of the traffic jam corresponding to the center of gravity of the fuzzy set of the traffic jam situation when the detour route of the traffic jam is searched and displayed is obtained (step S18). The degree of matching of the traffic corresponding to the center of gravity of the fuzzy set is defined as “degree of traffic jam”. The degree of traffic jam (J) when a traffic jam bypass route is searched and displayed by voice input is a reference value for searching and displaying the traffic jam bypass route. When the degree of traffic jam in a certain vehicle situation becomes a value of J or more, it becomes necessary to search and display a detour route of the traffic jam.

  Next, the number of consecutive times (N) serving as a reference for searching for and displaying a detour route of traffic jam is calculated (step S19). When the number of consecutive times that the degree of traffic jam is J or more is N or more, a bypass route for the traffic jam is searched and a bypass route for the traffic jam is displayed. The number of consecutive times (N) is calculated by (1-J) × 10. As described above, the navigation apparatus learns, and calculates the degree of traffic jam (J) and the standard number of consecutive times (N) that serve as a reference for searching for and displaying a detour route of the traffic jam.

  Next, a specific example will be given to explain how the navigation device learns by voice input using the word “congestion”. First, the driver enters the word “congestion” in the navigation device input unit (microphone) in a vehicle situation where the average speed is 7 km / h per unit time, the travel distance is 3 km per unit time, and the transit time is 5 minutes per unit travel distance. ) To search for and display a detour route for traffic jams. The average speed per unit time, the travel distance per unit time, and the passing time per unit travel distance are detected by various sensors of the vehicle.

  Next, as shown in FIG. 7, using a membership function of average speed, a fitness level 0.7 that feels not slow and a fitness level 0.3 that feels slow are calculated from the average speed 7 km / h per unit time. To do. As shown in FIG. 8, using a membership function of the moving distance, a fitness level 0.3 that feels not slow and a fitness level 0.7 that feels slow are calculated from the value of the moving distance 3 km per unit time. Further, as shown in FIG. 9, using a membership function of travel time, a fitness level 0.5 that is felt not to be early and a fitness level 0.5 that is felt to be early are calculated from a value of 5 minutes per unit travel distance. .

  Next, as shown in FIG. 10, it is divided into an element that feels a traffic jam (slow, not early) and an element that doesn't feel a traffic jam (not late, early), and the minimum value of the fitness of each element is calculated. In this embodiment, the minimum value of the fitness level of an element that feels as traffic jam (slow, not early) is 0.3, and the minimum value of the fitness level of an element that does not feel traffic jam (not late, early) is 0.3. Then, using the minimum value of the fitness of each element, the fuzzy set (FIG. 11) of the elements that do not feel traffic jam (not slow, fast) and the elements that feel traffic jam (slow, not fast) from the membership function of the traffic situation A fuzzy set (FIG. 12) is created.

  Next, as shown in FIG. 13, the fuzzy set of two elements is overlapped to create a fuzzy set of a traffic jam situation. This is a fuzzy set when searching and displaying a detour route in a traffic jam. Then, the degree of traffic jam is calculated from the center of gravity (G) of this fuzzy set (FIG. 13). Here, the degree of traffic jam is 0.5. This value is J, which is the standard degree of traffic jam for displaying the detour route of traffic jam. Next, the number of consecutive times (N) serving as a reference for displaying the detour route is calculated. Since the degree of traffic jam (J) when searching and displaying a detour route of traffic jam by voice input is 0.5, N = (1−J) × 10, so the number of consecutive times (N) is 5.

  As described above, if a vehicle situation in which the degree of traffic jam calculated from the value of the center of gravity of the fuzzy set is 0.5 or more is detected continuously, the detour route of the traffic jam is searched and displayed. The degree of traffic jam (J) and the number of consecutive times (N) are stored in the data storage unit 21.

  Next, FIG. 14 shows a process of searching for a detour route of traffic jam based on the vehicle status and displaying it on the display screen. The vehicle speed sensor 14b and the like detect the average speed per unit time, the travel distance per unit time, and the passage time per unit travel distance (step S21).

  Next, the degree of fitness that is slow or not slow relative to the average speed per unit time is calculated from the average speed membership function shown in FIG. 3 (step S22), and the unit time is calculated from the moving distance membership function shown in FIG. The degree of fitness that feels slow and not slow with respect to the per-movement distance is calculated (step S23), and the degree of fitness that feels fast and not early with respect to the passing time per unit movement distance is calculated from the movement time membership function shown in FIG. (Step S24).

  Next, the minimum value of the fitness of an element that feels a traffic jam (slow, not early) and an element that does not feel a traffic jam (not late, early) are calculated from the fitness of the three items (step S25). Then, from the minimum value and the membership function of the traffic situation shown in FIG. 6, the fuzzy set of the traffic situation that feels the traffic jam (slow, not early) and the fuzzy situation of the traffic situation that does not feel the traffic jam (not late, early) A set is created (step S26). Next, two fuzzy sets are superposed, and the degree of traffic jam (P) corresponding to the center of gravity of the superposed fuzzy set is obtained (step S27).

  Next, it is determined whether or not the degree of traffic jam (P) in the vehicle status is greater than or equal to the level of traffic jam (J) that serves as a reference for searching and displaying a detour route of traffic jam (step S28). If yes, then go to step S29, if no, return to the beginning. In step S29, it is determined whether the number of consecutive times P ≧ J is N or more. If N or more, the process advances to step S30 to search for a detour route for traffic jam and display a detour route for traffic jam. If it is not greater than N, return to the beginning. As described above, the navigation device determines a traffic jam condition without inputting a voice command to the navigation device, searches for a bypass route of the traffic jam, and displays the bypass route.

  In the embodiment of the present invention, as shown by the membership functions in FIGS. 3 to 5, when the traveling state of the vehicle is in the range of 0 to 10 km / h average speed per unit time, the moving distance per unit time is 0. In the range of ˜1 km, when the passing time per unit movement distance is 0 to 10 minutes, the driver feels that it is slow or not fast. However, some drivers may feel slow or not fast beyond this range. In such a case, by updating the membership function that is the basis for calculating the degree of traffic jam (J), which is a criterion for judging the traffic jam condition, and the degree of traffic jam (P) representing the driving situation of the vehicle, Appropriate traffic jam levels J and P corresponding to the property are calculated. The update of the membership function will be described by taking as an example a case where the driver feels that the average speed per unit time is slow at 15 km / h and recognizes that it is a traffic jam.

  It is assumed that the driver utters the word “congestion” when the average vehicle speed is 15 km / h, and searches and displays a detour route for the traffic jam. In this case, the driver feels slow even at an average speed of 15 km / h. Therefore, when the average speed membership function shown in FIG. 3 is equal to or higher than the average speed of 15 km / h per unit time, the fitness level that feels slow is updated to 0, and the fitness level that feels not slow is updated to 1 (FIG. 15). Then, based on the updated membership function, a value (J) of the degree of traffic jam serving as a reference for displaying a detour route of the traffic jam and the number of times (N) serving as a reference are calculated.

  Then, the degree of traffic jam (P) representing the vehicle running status is calculated by the updated membership function, and the traffic jam status of the vehicle is calculated based on the updated traffic jam level (J) and the new standard number (N). Judgment is made, search for a detour route of traffic jam and display of the searched route. Such an updated membership function is stored in the data storage unit 21 for each driver. Then, it is possible to search and display the detour route of the traffic congestion accurately according to each driver.

  The degree of traffic jam (J) and the standard number of times (N) for displaying the detour route of the traffic jam may be updated every time learning is performed by voice input, or is calculated by learning by voice input. Only when the standard traffic jam (J) is smaller than the standard traffic jam (J) calculated so far, the standard traffic jam (J) and standard frequency (N) May be updated. Further, every time a fuzzy set learned and calculated by voice input is learned by voice input, it is accumulated in the data storage unit 21, and all the accumulated fuzzy sets are overlapped, and congestion corresponding to the center of gravity of the superimposed fuzzy sets. The degree of traffic jam may be used as the standard degree of traffic jam (J).

  In the embodiment of the present invention, the search and display of the detour route of the traffic jam has been shown. Similarly, the speech input words and the vehicle situation are learned and the voice input is also performed for the search for the waypoint of the resting place and the displayed resting place. Even if not, it is possible to search for a stopover point according to the vehicle situation and display the result. Since the driver gets tired when driving for a long time, if a membership function indicating the driving time and the fatigue level of the driver is created, the resting place can be searched and displayed in the same manner. In addition, since the resting place changes between when driving in the daytime and when driving at nighttime, the operation time is also one of the determination items for searching and displaying the resting place.

  In addition, words that are voice-recognized to search and display detour routes of traffic jams and to search and display rest areas, so that even beginners of navigation devices and those unfamiliar with operations can use it easily, words that are not directly related to operations Is preferably used. A beginner or a person unfamiliar with the operation is not familiar with words related to operation of the navigation device such as “search”, “search”, and “route”. Therefore, for example, do not use words that support direct functions such as “search for a resting place route” as a word for performing a route search for a resting place and displaying the resting place, but “tired”, “want to sleep” It is preferable to use familiar words that are not directly related to the operation, such as “I want to go to the toilet”. Familiar words here are words used in everyday conversation, such as words that indicate road conditions (congestion), words that indicate driving conditions (fast or slow), and words that indicate the condition of the driver's body. (Tired, sleepy, hungry). If such familiar words are used, the contents to be executed by the navigation device from the context can be easily recalled, so that even a beginner of the navigation device can easily learn. In addition, by using such familiar words, the navigation device can execute the function desired by the driver without reading the manual of the navigation device. Also, if functions that cannot be understood without carefully reading the manual of the navigation device can be executed by recognizing such familiar words by voice recognition, the driver can use the unexpected functions of the navigation device based on the words that were used unexpectedly. There is also an advantage that it can be discovered.

The correspondence relationship between the claims and the embodiments will be described.
The “voice input means” in the first aspect of the invention corresponds to the input unit 17. The “detection means” corresponds to the current location detection unit 14. The “storage unit” corresponds to the data storage unit 21. The “reference calculation means” corresponds to the control circuit 11. “Numericalizing means” corresponds to the control circuit 11. The update means in the invention of claim 4 corresponds to the control circuit 11 and the data storage unit 21.

It is a block diagram which shows the structure of the navigation apparatus by embodiment of this invention. It is a flowchart which calculates | requires the reference | standard which searches the detour route of traffic congestion, and displays a detour route. It is a figure which shows the membership function of the average speed of one Embodiment of this invention. It is a figure which shows the membership function of the movement distance of one Embodiment of this invention. It is a figure which shows the membership function of the movement time of one Embodiment of this invention. It is a figure which shows the adaptability of the element (slow, not early) and the element (not late, early) which do not feel traffic jam of one Embodiment of this invention. It is a figure which shows calculation of the adaptability of average speed from the membership function of average speed. It is a figure which shows calculation of the fitness of a movement distance from the membership function of a movement distance. It is a figure which shows calculation of the suitability of travel time from the membership function of travel time. It is a figure which shows the adaptability of the element (slow, not early) and the element (not late, early) which do not feel traffic jam of one Embodiment of this invention. It is a figure which shows the fuzzy set of the element (it is not late, early) which does not feel as traffic congestion of one Embodiment of this invention. It is a figure which shows the fuzzy set of the element (slow, not early) which feels as traffic congestion of one Embodiment of this invention. It is a figure which shows the fuzzy set of the traffic congestion condition of one Embodiment of this invention. It is a flowchart which shows the process of displaying the detour route of traffic congestion on a display screen based on a vehicle condition. It is a figure which shows the update of the membership function of the average speed of one Embodiment of this invention.

Explanation of symbols

1 Navigation device 11 Control circuit 12 ROM
13 RAM
14 current position detection unit 15 image memory 16 output unit 17 input unit 18 VICS reception unit 19 disk drive
20 DVD-ROM
21 Data storage

Claims (6)

A navigation device,
Execution means for executing an operation of the navigation device,
Voice input means capable of executing the operation of the navigation device by voice input;
Detecting means for detecting a running state of the vehicle;
Storage means for storing the running state of the vehicle detected by the detecting means when an operation to the audio input of the navigation was performed apparatus by the voice input means,
A reference calculation means for calculating a reference number of times corresponding to the reference numerical calculates the reference value of the order to perform the operations of was performed by the voice input means from said stored running condition by the storage means and the navigation device ,
A digitizing means for digitizing using a function of the running conditions of the vehicle detected by said detecting means,
Said execution means during traveling of the vehicle, when the number of times the running condition of the vehicle which is digitized by the digitizing means has met the criteria numerical value calculated by the reference calculating means is the reference number of times or more, the A navigation device that performs the operation of the navigation device executed by voice input means. The navigation device according to claim 1, wherein
The navigation apparatus according to claim 1, wherein the reference calculating means and the digitizing means respectively calculate the reference numerical value and digitize the traveling state of the vehicle using a method based on fuzzy theory . The navigation device according to claim 1 or 2,
The words input by the voice input means include at least one of a word indicating a road condition, a word indicating a driving condition of the vehicle, and a word indicating a driver's body condition. Navigation device. The navigation device according to any one of claims 1 to 3,
When the vehicle running state detected by the detecting unit when the voice is input exceeds a predetermined range, the reference calculating unit and the digitizing unit calculate the reference numerical value and digitize the vehicle running state. A navigation device comprising updating means for updating the functions used respectively . The navigation device according to any one of claims 1 to 4,
The navigation device is characterized in that the operations executed by the execution means are a search for a detour route of a traffic jam and a search for a stopover route. The navigation device according to claim 3, wherein
The navigation device according to claim 1, wherein when the voice input word is a word indicating traffic jam, the operation executed by the execution means is a bypass route search.

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