JP4696013B2 - Navigation device and route search method - Google Patents

Description

  The present invention relates to a navigation device, and more particularly to a route search technique for an in-vehicle navigation device.

  Some conventional navigation devices search for a recommended route to a destination by using external traffic information in addition to link data constituting a road on the map when searching for a route to the destination. (For example, patent document 1). The navigation device of Patent Document 1 reflects the received traffic information and searches for a recommended route that avoids traffic jams.

JP 10-132591 A

  However, Patent Document 1 has the following problems. Specifically, the traffic situation on the road changes with time. Therefore, as in Patent Document 1, even if the route search is performed using the traffic information received in the previous stage of the route search, and the traffic congestion state changes after that, the searched recommended route is the optimum route. Sometimes not. Therefore, for example, an unnecessary detour may be presented to the user as a recommended route. In addition, there are roads in which traffic congestion changes greatly in a short time, and even when a route search is performed using the received traffic information as it is, an optimal recommended route may not be searched.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to search for an optimum recommended route in a navigation device.

  In order to solve the above problems, one embodiment of the present invention is applied to a navigation device that searches for a recommended route from a departure point to a destination by using link information included in map data.

  The navigation device stores, for each link constituting the road on the map data, statistical traffic information obtained by statistically processing data collected in the past, and the cost of each road from the outside. A route search for searching for a recommended route to a destination by using means for acquiring current traffic information indicating a traffic jam situation, link information included in the map data, the current traffic information, and the statistical traffic information And the statistical traffic information is associated with, for each link, the cost of the link obtained by the statistical processing and prediction information indicating whether or not the traffic congestion status of the link tends to change. The route search means refers to the prediction information corresponding to the extracted link when extracting the link that is a candidate for the recommended route, and refers to the prediction When the report is data indicating that the traffic congestion status of the link tends to change, the cost of the statistical traffic information is used to calculate the cost of the extracted link, and the traffic congestion status of the link does not tend to change In the case of data indicating, the cost of the current traffic information is used for calculating the cost of the extracted link.

  As described above, according to the present invention, when searching for a route, the cost is calculated using the current traffic information for a road where the traffic congestion status does not tend to change, and the statistical traffic is calculated for the road where the traffic congestion status tends to change. The cost is calculated using the information.

  Therefore, according to the present invention, it is possible to increase the possibility that the navigation apparatus searches for a route that reflects the actual traffic congestion situation.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<< First Embodiment >>
First, a first embodiment of the present invention will be described.

  First, a schematic configuration of an in-vehicle navigation device to which the first embodiment is applied will be described with reference to FIG.

  FIG. 1 is a schematic configuration diagram of an in-vehicle navigation device (hereinafter simply referred to as “navigation device”) according to a first embodiment of the present invention.

  As shown in the figure, the navigation device includes an arithmetic processing unit 1, a display 2, a storage device 3 in which map data and the like are stored, a voice input / output device 4, an input device 5, a wheel speed sensor 6, and a geomagnetism. FM multiplex broadcast for acquiring sensor 7, gyro 8, GPS (Global Positioning System) receiving device 9, and traffic information indicating traffic congestion on the road (hereinafter, sometimes referred to as "real-time traffic information") And a receiving device 10.

  In the present embodiment, the FM multiplex broadcast receiving apparatus 10 is used as a means for acquiring traffic information, but this is merely an example. Any device capable of acquiring traffic information from outside may be used. For example, the navigation device may be provided with a beacon receiving device that receives traffic information transmitted by a beacon installed on the road, and the beacon receiving device may acquire the traffic information. The navigation device may be provided with a receiving terminal that receives traffic information distributed by satellite broadcasting, and the receiving terminal may acquire the traffic information.

  The arithmetic processing unit 1 is a central unit for processing various types of information provided to the user by the navigation device. For example, the current position is detected based on information output from the various sensors 6 to 8 and the GPS receiver 9. The arithmetic processing unit 1 reads out map data around the detected current position from the storage device 3, develops the read map data in graphics, and displays a mark indicating the current position on the display 2 in a superimposed manner. In addition, the arithmetic processing unit 1 searches for a recommended route connecting the current position and the destination instructed by the user, and guides the user using the voice input / output device 4 and the display 2.

  The display 2 is a unit that displays the image data generated by the arithmetic processing unit 1 and includes a CRT, a liquid crystal display, or the like. The signal S1 between the arithmetic processing unit 1 and the display 2 is generally connected by an RGB signal or an NTSC (National TV Standards Committee) signal.

  The storage device 3 is a unit that stores map data 310 (see FIG. 2) and statistical traffic information. As the storage device 3, for example, a DVD device or a hard disk device can be used.

  Here, the structure of the map data will be described.

  FIG. 2 is a diagram schematically illustrating the data structure of the map data stored in the storage device 3.

  As shown in the drawing, the map data 310 is classified for each mesh region obtained by dividing the map into a plurality of parts. The map data 310 includes a mesh ID 311 for identifying a mesh area, and link data 312 of each link constituting a road included in the mesh area.

  The link data 312 includes a link ID 3121 for identifying a link, coordinate information 3122 of two nodes (start node and end node) constituting the link, and whether the road to which the link belongs is a “toll road” or “general road”. Road type 3123 indicating whether there is a link, link length information 3124 indicating the length of the link, link travel time (or travel time) information 3125, and link IDs of links connected to two nodes (start node and end node), respectively (Connection link ID) 3126 and the like. The link data 312 is provided with forward data and reverse data for one link.

  The storage device 3 stores a table (referred to as a “mesh conversion table”) for specifying a mesh ID of a mesh including a point specified by the coordinate information from statistical traffic information and coordinate information described later. Yes.

  Returning to FIG. 1, the description will be continued. The voice input / output device 4 converts the message to the user generated by the arithmetic processing unit 1 into a voice signal and outputs it, recognizes the voice uttered by the user, and transfers the recognized content to the arithmetic processing unit 1. To do.

  The input device 5 is a unit that receives instructions from the user for selecting various functions of the navigation device, setting a destination, and the like. Hard switches such as a scroll key and a scale change key, Joystick, a touch panel pasted on the display 2, and the like Consists of.

  The sensors 6 to 8 and the GPS receiver 9 are used by the navigation device to detect the current position. The wheel speed sensor 6 measures the distance from the circumference of the wheel and the measured rotational speed of the wheel, and further measures the angle at which the moving body is bent from the rotational speed of the paired wheel. The geomagnetic sensor 7 detects the magnetism held by the earth and detects the direction in which the moving body is heading. The gyro 8 is composed of an optical fiber gyro and a vibration gyro, and detects an angle at which the vehicle (moving body) is rotated. The GPS receiver 9 receives a signal from a GPS satellite and measures the distance between the mobile body and the GSP satellite and the rate of change of the distance with respect to three or more satellites to thereby determine the current position, travel direction, and travel of the mobile body. Measure orientation.

  The FM multiplex broadcast apparatus 10 receives traffic information (real-time traffic information) transmitted from an FM multiplex broadcast station (not shown). The real-time traffic information includes road congestion information, regulation information, parking lot information, service area information, parking area information, and the like. The traffic jam information includes speed information (information indicating the passing speed of the vehicle) for each road (such as National Highway No. 1).

  Next, characteristic functions of the arithmetic processing unit 1 of the navigation device described above will be described with reference to FIG.

  FIG. 3 is a functional block diagram of the arithmetic processing unit 1 of the present embodiment.

  As shown in the figure, the arithmetic processing unit 1 includes a UI (User Interface) control unit 100, a current position calculation unit 110, a traffic information setting unit 120, a statistical traffic information setting unit 130, a route search unit 140, and a map display processing unit 150. Have

  The UI control unit 100 receives a request from a user input to the input device 5 or the voice input / output device 4, and controls the arithmetic processing unit 1 so that processing corresponding to the requested content is executed. In addition, the UI control unit 100 generates image data for guiding various operations and displays the image data on the display 2. In addition, the UI control unit 100 displays map image data generated by a map display processing unit 150 described later on a display.

  The current position calculation unit 110 uses the distance data and the angle data obtained as a result of integrating the distance pulse data S5 measured by the wheel speed sensor 6 and the angular velocity data S7 measured by the gyro sensor 8, respectively. By integrating with the shaft, the current position (X ′, Y ′), which is the position after the vehicle travels, is periodically calculated from the initial value (X, Y). Then, the current position calculation unit 110 outputs the calculated current position to the map display processing unit 16.

  Here, the current position calculation unit 110 integrates the azimuth data S6 obtained from the geomagnetic sensor 7 and the angular velocity data S7 obtained from the gyro 8 in order to match the relationship between the rotation angle of the host vehicle and the traveling direction. With reference to the angle data, the absolute direction of the direction in which the vehicle is traveling is estimated. As the current position calculation unit 110 integrates the data S5 of the wheel speed sensor 6 and the data S7 of the gyro 8 respectively, an error accumulates. Therefore, the current position calculation unit 110 also stores the position data S8 obtained from the GPS receiver 9 at a certain time. A process for canceling the accumulated error is performed to obtain data on the current position.

  The traffic information setting unit 120 controls the FM multiplex broadcast receiving apparatus 10 and periodically acquires real-time traffic information. The traffic information setting unit 120 generates “current traffic information” in which the cost is associated with each link using the acquired real-time traffic information, and stores it in a predetermined area of the RAM 22 (see FIG. 4). Whenever the traffic information is acquired, the traffic information setting unit 120 generates “current traffic information” and updates the “current traffic information” stored in the RAM 22 to the newly generated information. In addition, the process which the traffic information setting part 120 performs is demonstrated in detail in FIG. 5 mentioned later.

  The statistical traffic information setting unit 130 obtains statistical traffic information including statistical values of each link obtained by statistically processing data collected in the past from the storage device 3 for each link constituting the road on the map data. Reading and statistical data (see FIG. 8) are created. Statistical traffic information stored in advance in the storage device 3 is associated with statistical values (average travel time and average speed) for each predetermined time of each link belonging to the mesh for each mesh.

  Note that the process of creating statistical data (see FIG. 8) performed by the statistical traffic information setting unit 130 may be performed once at the initial setting of the navigation device. The processing performed by the statistical traffic information setting unit 130 will be described in detail with reference to FIGS.

  The route search unit 140 uses a Dijkstra method or the like to search for a recommended route to reach the destination at an optimal cost connecting the two specified points (current position (or the starting point specified by the user) and destination). To do. The route search unit 140 of the present embodiment uses the map data 310 (FIG. 2), the statistical data obtained from the “statistical traffic information” (FIG. 8), and the current traffic information generated by the traffic information setting unit 120. Search for a recommended route to the ground. The process performed by the route search unit 140 will be described in detail later.

The map display processing unit 150 reads from the storage device 3 the map data 310 in the area requested to be displayed on the display 2. In addition, the map display processing unit 150 receives the recommended route searched from the route search unit 140,
Information on the current position is received from the current position calculation unit 110. Then, the map display processing unit 150 generates image data for displaying a mark such as a road, other map components, a current position, a destination, and an arrow for route guidance on the screen of the display 2, and a UI control unit Output to 100. The UI control unit 100 displays the image data generated by the map display processing unit 150 on the display 2.

  Next, the hardware configuration of the arithmetic processing unit 1 according to the present embodiment will be described.

  FIG. 4 is a hardware configuration diagram of the arithmetic processing unit 1.

  As illustrated, the arithmetic processing unit 1 includes a CPU (central processing unit) 21, a RAM (Random Access Memory) 22 that temporarily stores programs executed by the CPU 21 and various data, and the above-described units (UI control unit). 100, ROM in which programs for executing the functions of the current position calculation unit 110, traffic information setting unit 120, statistical traffic information setting unit 130, route search unit 140, and map display processing unit 150) are stored in advance. Read Only Memory) 23, DMA (Direct Memory Access) 24 that transfers data between memories and between the memory and each device, a drawing controller 25 that executes graphic drawing and performs display control, and graphics image data Video random access memory (VRAM) 26 and a color palette for converting image data into RGB signals 27, an A / D converter 28 for converting an analog signal into a digital signal, an SCI (Serial Communication Interface) 29 for converting a serial signal into a parallel signal synchronized with the bus, and a parallel signal on the bus by synchronizing with the bus PIO (Parallel Input / Output) 30 and a counter 31 for integrating the pulse signal. The functions of the above-described units (UI control unit 100, current position calculation unit 110, traffic information setting unit 120, statistical traffic information setting unit 130, route search unit 140, and map display processing unit 150) are stored in the ROM 23 by the CPU 21. This is realized by executing a program for executing the stored functions of the respective units.

  Then, the process which the arithmetic processing part 1 performs is demonstrated concretely.

  First, processing performed by the traffic information setting unit 120 of the arithmetic processing unit 1 will be described with reference to FIG.

  FIG. 5 is a flowchart of traffic information setting processing performed by the navigation device of this embodiment. The following processing is periodically executed at predetermined time intervals. The following processing is also executed when the traffic information setting unit 120 receives a request from a user (request for acquiring real-time traffic information) via the UI control unit 100.

  Here, the traffic information setting unit 120 holds a link conversion table (not shown) in which a link (link ID 3121) on the map data 310 is associated with each road included in the traffic jam information of the real-time traffic information. And

  First, the traffic information setting unit 120 causes the FM multiplex broadcast receiving apparatus 10 to receive real-time traffic information transmitted from an FM multiplex broadcast station (not shown) (S20). Then, the traffic information setting unit 120 acquires the received real-time traffic information from the FM multiplex broadcast receiver 10. As described above, the congestion information included in the real-time traffic information includes speed information (information indicating the passing speed of the vehicle) for each road.

  Next, the traffic information setting unit 120 obtains data in which travel time (cost) is associated with each link ID 3121 from the real-time traffic information received in S20, and stores the data in a predetermined area of the RAM 22 (FIG. 4) (S30). ).

  Specifically, the traffic information setting unit 120 uses the “link conversion table” to convert the traffic jam information in the real-time traffic information into speed information for each link ID. Further, the traffic information setting unit 120 uses the link length information 3124 (see FIG. 2) of the map data 310 and the converted traffic jam information to associate “travel time (cost) for each link ID” with “current traffic information”. Is generated. The traffic information setting unit 120 stores the generated “current traffic information” in a predetermined area of the RAM 22 (FIG. 4). When the “current traffic information” is already stored in the RAM 22, the traffic information setting unit 120 updates the stored “current traffic information” to the newly generated “current traffic information”.

  Next, processing performed by the statistical traffic information setting unit 130 of the arithmetic processing unit 1 will be described with reference to FIGS.

  6 and 7 are diagrams for explaining processing for obtaining change prediction information for each time zone of each link, which is performed by the statistical traffic information setting unit 130 of the present embodiment. FIG. 8 is a diagram schematically illustrating the data structure of statistical data according to the present embodiment.

  The storage device 3 stores in advance statistical traffic information including statistical values of each link obtained by statistically processing data collected in the past for each link constituting a road on the map data 310. Yes. Statistical traffic information includes, for example, cost (travel time and average speed) for each link by day information (information on weekdays, holidays, etc.), by weather information (information such as sunny, rain, snow, etc.) and by time. It is attached.

  In the following, in order to simplify the explanation, an example is given in which the statistical traffic information is the cost for each link (average travel time and average speed). And the statistical traffic information setting part 130 produces change prediction information for every predetermined time slot | zone of each link.

  The change prediction information is data obtained by using statistical traffic information to estimate whether the traffic congestion state is changing or stable for each predetermined time zone of each link. The statistical traffic information setting unit 130 creates statistical data in which statistical values included in the statistical traffic information and change prediction information are associated with each link in the statistical traffic information and stores the statistical data in the storage device 3.

  For example, it is assumed that links 1 to 3 are included in a certain mesh region 1000 as shown in FIG. In this case, the statistical traffic information setting unit 130 uses the statistical value included in the statistical traffic information to determine whether or not the congestion status of the link has changed for each predetermined time zone of each link. In the following, an example will be described in which it is determined whether or not the traffic congestion status has changed in the time zone “8: 0 to 8:30” of links 1 to 3.

  First, the statistical traffic information setting unit 130 sets the average speed of “8:00” and “8:30” for each of the links 1 to 3 in the forward direction and the reverse direction from the stored statistical traffic information. ”And the average speed.

  Next, the statistical traffic information setting unit 130 calculates the difference between the average speed of “8:00” and the average speed of “8:30” for each of the links 1 to 3 (forward direction, reverse direction). Ask. If the difference is larger than the predetermined value, the statistical traffic information setting unit 130 estimates that the traffic congestion state of the link changes in the time zone (here, “8: 0 to 8:30”). On the other hand, if the difference is not greater than the predetermined value, the statistical traffic information setting unit 130 estimates that the traffic congestion state of the link is stable during the time period (here, “8: 0 to 8:30”).

  Then, for example, an estimation result 500 as shown in FIG. 7 is obtained. In the illustrated example, the predetermined value is “15 km / h”.

  As shown in the figure, in the forward direction of the link 1, the difference (“20 km / h”) between the average speed of “8:00” and the average speed of “8:30” is a predetermined value (“15 km / h”). Greater than. For this reason, the statistical traffic information setting unit 130 estimates that the forward direction of the link 1 tends to change the traffic jam situation from “8: 00 to 8:30” (see data surrounded by a broken line 510 shown in the figure). On the other hand, in the reverse direction of the link 3, the difference (“0 km / h”) between the average speed of “8:00” and the average speed of “8:30” is smaller than the predetermined value (“15 km / h”). Therefore, the statistical traffic information setting unit 130 estimates that the reverse direction of the link 3 has a tendency that the traffic congestion state does not change (is stable) at “8: 00 to 8:30” (in the illustrated broken line 520). (See enclosing data).

  In the present embodiment, it is estimated whether or not the traffic congestion state of the link changes based on the difference in average speed, but this is merely an example. For example, the determination may be made not by the difference between the two average speeds but by the rate of change of the two average speeds. For example, if it changes more than a predetermined value (n%), it is estimated that the traffic jam situation has changed, and if the change is less than a predetermined value (n%), it is estimated that the traffic jam situation is stable.

  In the above description, the difference between the average speeds at the start time and the end time in the predetermined time zone is obtained, but this is merely an example. You may make it obtain | require the difference of the average speed of the link of arbitrary two time points in a time slot | zone. Or you may make it determine whether the traffic congestion condition has changed with the difference of the maximum value and minimum value of the average speed in a predetermined time slot | zone. Further, it may be determined whether or not the traffic congestion status tends to change based on values calculated by other statistical processing (for example, variations in average speed at a plurality of points in time).

  In the present embodiment, “1 bit” data is used for “change prediction information” indicating an estimation result. Specifically, “1 (change)” indicates “change prediction information” estimated that the traffic congestion state changes. In addition, “0 (stable)” indicates “change prediction information” estimated that the traffic congestion state does not change.

  Then, the statistical traffic information setting unit 130 obtains “change prediction information” of all links in the stored statistical traffic information, and creates statistical data 801 shown in FIG. The statistical data 801 is obtained by adding “change prediction information” to statistical traffic information stored in advance.

  The illustrated statistical data 801 is classified for each mesh region. The statistical data 801 is management data 815 for managing a mesh ID 802 of a mesh area and traffic information statistical values (statistics of traffic information collected in the past) of each link constituting a road included in the mesh area. Have The mesh ID 802 is the same as the mesh ID 311 of the map data 310. The management data 815 includes a plurality of tables 810 and 830 having a hierarchical structure.

  The table 810 includes a link ID of each link constituting a road included in the mesh area registered by the mesh ID 802 (one link is provided with a link ID for each direction (forward direction and reverse direction). ). The same link ID as the link ID 3121 of the map data 310 is used.

  The table 830 is provided for each link ID registered in the table 810, and the statistical value of the traffic information for each time zone and the above-described “change prediction information” are registered. Specifically, the table 830 includes an entry 831 for registering a time zone, an entry 832 for registering a statistical value of traffic information in the time zone registered in the entry 831, and a time registered in the entry 831. An entry 832 for registering “change prediction information” of the link in the band.

  The statistical value of the traffic information for each time zone includes the link travel time specified by the plurality of traffic information serving as the basis, and the average speed (average moving speed). “Change prediction information” is data created by the statistical traffic information setting unit 130. Then, the navigation device of the present embodiment refers to this “change prediction information” when performing a route search, uses the statistical value of the traffic information registered in the entry 831, or creates it from real-time traffic information It is determined whether to use the current traffic information.

  Specifically, in the present embodiment, the link whose “change prediction information” is “1 (change)” is estimated to be a road where the traffic congestion state changes, and the cost of the link obtained from the real-time traffic information is used. Do not use the cost included in the statistical traffic information. On the other hand, in the present embodiment, a link whose “change prediction information” is “0 (stable)” is estimated as a road where the traffic congestion state does not change, and the cost of the link obtained from the real-time traffic information is used. That is, the link cost obtained from the real-time traffic information is used without using the cost included in the statistical traffic information.

  Next, route search processing performed by the route search unit 140 of the arithmetic processing unit 1 will be described with reference to FIG. In the following, a case where the Dijkstra method is used for searching for a recommended route is taken as an example.

  FIG. 9 is a flowchart of route search processing performed by the navigation device of this embodiment. The following process is started when the route search unit 140 receives a route search request specifying a departure place and a destination from the user via the UI control unit 100. In the following, a case where the current position of the vehicle is set as the departure point is taken as an example, but the present invention is not particularly limited thereto. The route search unit 140 may accept an input of a departure place from the user via the UI control unit 100. Further, it is assumed that current traffic information created using real-time traffic information is stored in a predetermined area of the memory (RAM 22) of the arithmetic processing unit 1 of the navigation device.

  First, when the route search unit 140 receives a route search request from the user via the UI control unit 100, the route search unit 140 acquires the current position from the current position calculation unit 110. In addition, the route search unit 140 receives the setting of the departure time from the user via the UI control unit 100. When the departure time is the current time, the current time acquired from a timer (not shown) in the navigation device may be used as the departure time (S100).

  Next, the route search unit 140 reads a map 310 (see FIG. 2) necessary for searching for a recommended route from the storage device 3 (S101), and proceeds to the processing of S102. Specifically, the route search unit 140 reads a “mesh conversion table (not shown)” from the storage device 3, and from the coordinate information indicating the current position and the destination, a mesh region including a point specified by the coordinate information Specify the mesh ID. Next, the route search unit 140 acquires map data 310 having the identified mesh ID from the storage device 3.

  In S102, using the link data 312 included in the map data 310 read in S101, a link whose start node is the end node of the link (referred to as an extracted link) extracted from the heap table in S110 described later is used as a recommended route. Selected as a candidate link to be configured (referred to as a candidate link). When the processing in S110 is not performed, that is, in the initial stage where no link is registered in the heap table, at least one link whose start node is close to the current position (departure point) is selected as a candidate link. To do. In addition, when there are a plurality of links whose start nodes are the end nodes of the extracted links, a plurality of candidate links are selected.

  Here, the heap table is a table for registering the link data of the link that is a candidate constituting the recommended route together with the total cost (travel time, etc.) from the departure point to the end node of the candidate link, It is stored in a predetermined area of the RAM 22.

  Subsequently, the route search unit 140 determines whether or not the candidate link selected in S102 is located within a predetermined distance from the departure place using the map data 310 (S103). As a result of the determination, if the candidate link selected in S102 is not located within a predetermined distance from the departure place, the process proceeds to S107. On the other hand, as a result of the determination, if the candidate link selected in S102 is located within a predetermined distance from the departure place, the process proceeds to S104.

  In S104, the route search unit 140 reads the statistical data (FIG. 8) from the storage device 3, and extracts change prediction information associated with the same link ID as the candidate link. That is, change prediction information that is the same link as the candidate link and is associated with the same traveling direction is extracted. Next, the route search unit 140 calculates a predicted arrival time at the candidate link. Specifically, the route search unit 140 accesses the heap table and reads the total cost of the extraction links (links that are connection sources of candidate links) registered in the heap table. The route search unit 140 adds the total cost read to the current time acquired in S100, and sets the added value as the predicted arrival time. Then, the route search unit 110 refers to the time zone change prediction information to which the calculated predicted arrival time belongs.

  In the initial stage, no extraction link is registered in the heap table. In this case, the route search unit 140 refers to the time zone change prediction information to which the current time acquired in S100 belongs.

  Here, the process of S104 will be described using FIG. 8 as an example. For example, it is assumed that the candidate link is in the reverse direction of link 1 and the predicted arrival time is “8:35” up to the calculated candidate link. In this case, the route search unit 140 refers to change prediction information associated with the time zone “8:30 to 9:00” (in the example shown, “0 (stable)”.

  Returning to FIG. 9, the description will be continued. Next, the route search unit 140 determines whether the referenced change prediction information is information indicating “stable (0)” (S105). The route search unit 140 proceeds to the process of S106 when the change prediction information is information indicating “stable (0)”, and proceeds to the process of S107 when the information is not information indicating “stable (0)”. That is, in the present embodiment, when the change prediction information referred to is information indicating “stable (0)”, it is estimated that the traffic congestion state of the candidate link in that time zone tends to be stable, and in S106 Proceed to processing. On the other hand, if the referenced change prediction information is information indicating “1 (change)”, it is estimated that the traffic congestion state of the candidate link in the time zone tends to change, and the process proceeds to S107.

  In S <b> 106, the route search unit 140 performs cost calculation using “current traffic information” stored in a predetermined area of the RAM 22. This step is a process performed when it is estimated that the traffic congestion state of the candidate link in the time zone is stable. Therefore, it is estimated that the traffic jam situation received by the real-time traffic information has not changed, and the “current traffic information” created from the real-time traffic information is used.

  Specifically, in S106, the route search unit 140 accesses “current traffic information” stored in the memory (RAM 22), and associates it with the same link ID as the candidate link from the “current traffic information”. Read the cost (travel time). The route search unit 140 adds the cost (travel time) of the read candidate link to the total cost of the extracted link (link of the connection source of the candidate link) read from the heap table in S104. The route search unit 140 uses the value obtained by the addition as the total cost from the departure point to the end node of the candidate link.

  In the initial stage where the extracted link is not registered in the heap table, the route search unit 140 sets the cost of the candidate link (the cost read from the current traffic information) as the total cost to the candidate link.

  Next, description will be made on S107 which is proceeded when it is determined in S103 that the candidate link is not located within the predetermined distance from the departure place, and when it is determined in S105 that the change prediction information is not information indicating “stable”. To do.

  In S107, the route search unit 140 performs cost calculation using “statistical traffic information”. This step is performed when it is determined that the candidate link is not located within a predetermined distance from the departure place, and when it is estimated that the traffic congestion state of the candidate link in the time zone is not stable. It is.

  When it is determined that the candidate link is not located within a predetermined distance from the departure place, it is considered that a certain amount of time has passed since the real-time traffic information was received. That is, the received real-time traffic information is considered to have a high possibility of not reflecting the traffic jam situation when the vehicle actually passes through the candidate link. Therefore, in this step, the statistical value of the statistical traffic information is used without using the “current traffic information” created from the real-time traffic information.

  In addition, even if the candidate link is located within a predetermined distance from the departure place, if it is estimated that the traffic congestion of the road in the time zone of the candidate link is not stable, the road condition indicated by the real-time traffic information (Congestion situation) is likely to change. Therefore, in this step, the statistical value of the statistical traffic information is used without using the “current traffic information” created from the real-time traffic information.

  Specifically, in S107, the route search unit 140 extracts a statistical value associated with the same link ID as the candidate link from the “statistical data (FIG. 8)” read in S104. That is, data (table 830 in FIG. 8) that is the same link as the candidate link and is associated with the same traveling direction is extracted. The route search unit 140 identifies the statistical value of the time zone to which the predicted arrival time calculated in S104 belongs from the extracted data. Further, the route search unit 140 adds the cost (travel time) in the above-described statistical value to the total cost of the extracted link read from the heap table in S104.

  Note that in S107 as well as in S106, at the initial stage where the extraction link is not registered in the heap table, the cost of the candidate link (the cost (travel time) in the specified statistical value) is calculated up to the candidate link. Total cost.

  Next, the route search unit 140 adds the link data of the candidate links and the total cost of the candidate links to the heap table (S108). When there are a plurality of candidate links in S102, the processes of S103 to S108 are performed for each candidate link.

  Next, the route search unit 140 determines whether there is a link where the destination exists or is close to the destination (called a destination link) among the links newly added to the heap table in S108 performed immediately before. Whether or not is checked (S109). If the route search unit 140 determines that there is no destination link, the process proceeds to step S110. If it is determined that there is a destination link, the path search unit 140 proceeds to step S111.

  In S110, the route search unit 140 sorts the information of unextracted links registered in the heap table in ascending order of the total cost, and extracts the first link, for example, to minimize the total cost from the heap table. Extract unextracted links. Then, the process returns to S102.

  Next, the process of S111 that is performed when it is determined in S109 that there is a destination link will be described. In S111, the route search unit 140 performs a recommended route determination process. Specifically, the heap table is searched for a link that has generated the destination link (a link having the start node of the destination link as the end node), and the detected link is determined as a constituent link that constitutes the recommended route. Next, it is checked whether or not the constituent link is a starting point link that exists or is close to the starting point. If it is not a starting point link, the link that generated this constituent link is searched and the detected link is detected. Is determined as a constituent link, and it is further examined whether or not it is a departure link. By repeating this process until it is determined that the configuration link is the departure link, each configuration link that constitutes the recommended route is determined.

  As described above, in the present embodiment, the cost is calculated using the statistical traffic information for the link that is considered to be highly likely to change the traffic jam condition (road condition) of the real-time traffic information, and is indicated by the real-time traffic information. Costs are calculated using current traffic information obtained from real-time traffic information for links that are considered unlikely to change traffic conditions (road conditions).

  Therefore, according to the present embodiment, it is possible to increase the possibility of searching for a recommended route that reflects the actual traffic congestion situation.

  In the first embodiment, the statistical traffic information setting unit 130 uses the statistical traffic information stored in advance to obtain the statistical data shown in FIG. 8, but the present invention is not limited to this. . For example, the data shown in FIG. 8 may be created and stored in the storage device 3 on the manufacturer side of the navigation device. In this case, it is not necessary to provide the function of the statistical traffic information setting unit 130 in the arithmetic processing unit 1.

<< Second Embodiment >>
Next, a second embodiment of the present invention will be described. The second embodiment of the present invention is the same as that of the first embodiment except that part of the processing performed by the statistical traffic information setting unit 130 and part of the processing performed by the route search unit 140 are different. . In the description of the second embodiment, the same reference numerals as those in the first embodiment are used.

  In the navigation device of the second embodiment, when searching for a route, the cost obtained from the real-time traffic information and the cost of the statistical traffic information are used separately for each mesh, not for each link. That is, 2nd Embodiment estimates whether the traffic congestion condition of the road is stable for every mesh. A link belonging to the mesh estimated to have a stable traffic jam on the road performs a route search using the cost obtained from the real-time traffic information. In addition, links belonging to meshes that are estimated to have unstable traffic congestion on the road are route-searched using the cost of statistical traffic information. By doing in this way, the processing time of route search can be shortened compared with 1st Embodiment. Hereinafter, a description will be given centering on differences from the first embodiment.

  The schematic configuration of the second embodiment is the same as that shown in FIG. 1, and the map data illustrated in FIG. 2 is stored in the storage device 3 as in the first embodiment. The storage device 3 stores statistical traffic information including statistical values of each link obtained by statistically processing data collected in the past for each link constituting a road on map data. Yes. In the second embodiment, it is assumed that the statistical traffic information stored in the storage device 3 includes data 850 shown in FIG. Note that the data 850 illustrated in FIG. 14 is obtained by removing “change prediction information” from the statistical data illustrated in FIG. 8, and thus description thereof is omitted here.

  The functional configuration of the arithmetic processing unit 1 is the same as that shown in FIG. 3 except that some of the functions of the statistical traffic information setting unit 130 and the route search unit 140 are different. The hardware configuration of the arithmetic processing unit 1 is the same as that shown in FIG. Hereinafter, the statistical traffic information setting unit 130 and the route search unit 140, which are different from the first embodiment, will be described.

  First, the statistical traffic information setting unit 130 of the second embodiment will be described with reference to FIGS.

  FIG. 10 is a flowchart of statistical traffic information setting processing according to the second embodiment of this invention. FIG. 11 is a diagram for explaining a process of grouping each link in a predetermined direction in the second embodiment. FIG. 12 is a diagram for explaining processing for obtaining change prediction information for each mesh.

  And the statistical traffic information setting part 130 calculates | requires the change prediction information for every time slot | zone of each mesh using the map data and statistical traffic information which are memorize | stored by the process demonstrated below. The statistical traffic information setting unit 130 creates a determination table (see FIG. 13) in which the obtained change prediction information is associated for each time zone of each mesh, and stores the determination table in the storage device 3.

  First, the statistical traffic information setting unit 130 selects a mesh to be subjected to change prediction (S200). Specifically, the statistical traffic information setting unit 130 selects one mesh for which change prediction information is not obtained. Here, it is assumed that the mesh 1000 shown in FIG. 6 is selected.

  Next, the statistical traffic information setting unit 130 reads the selected mesh map data 310 and statistical traffic information from the storage device 3 (S201), and proceeds to the processing of S202.

  In S202, the statistical traffic information setting unit 130 groups the links belonging to the selected mesh in a predetermined direction using the read map data 310. Below, the case where it groups into the direction (direction 1-8) illustrated in FIG. 11 is made into an example. That is, “link 1 (forward direction)”, “link 1 (reverse direction)”, “link 2 (forward direction)”, “link 2 (reverse direction)”, “link 3 (forward direction)” in the mesh 1000 "And" Link 3 (reverse direction) "are classified into any of directions 1 to 8, respectively. Here, “link 1 (forward direction)” and “link 2 (forward direction)” are classified into “direction 1”, “link 3 (forward direction)” is classified into “direction 3”, and “direction 4 “Link 1 (reverse direction)” and “link 2 (reverse direction)” are classified into “direction 6”, and “link 2 (reverse direction)” is classified into “direction 6” (see FIG. 12).

  Next, the statistical traffic information setting unit 130 selects a time zone for which change prediction information is not obtained from preset time zones (S203). Note that the plurality of preset time zones refers to one day divided every predetermined time (for example, “30 minutes”). Here, it is assumed that the statistical traffic information setting unit 130 selects the time zone of “8: 0 to 8:30”.

  Next, the statistical traffic information setting unit 130 calculates the average value of the average speed of the link at the start time and end time of the time zone selected in S203 for each direction in which the links are classified (S204), and proceeds to S205. . Note that the start time and end time are merely examples. You may make it calculate the average value of the average speed of the link of the arbitrary two time points in a time slot | zone.

  Specifically, the statistical traffic information setting unit 130 uses the statistical traffic information read in S201 to calculate the average value of the average speeds of the start time and end time of the time zone for each direction in which the links are classified in S202. calculate. Here, for each of “Direction 1”, “Direction 3”, “Direction 4” and “Direction 6”, the average value of the average speed of “8:00” and the average value of the average speed of “8:30” And are calculated.

  Here, “direction 1” shown in FIG. 12 will be described as an example. In “direction 1”, “link 1 (forward direction)” and “link 2 (forward direction)” are classified. In this case, the statistical traffic information setting unit 130 sets the average speed of “8:00” of “link 1 (forward direction)” and “link 2 (forward direction)” from the statistical traffic information read in S201. From the average speed of “8:00”, the average value of the average speed at “8:00” in “direction 1” is obtained. Similarly, the statistical traffic information setting unit 130 selects “8:30” average speed of “link 1 (forward direction)” and “link 2 (forward direction)” from the statistical traffic information read in S201. From the average speed of “8:30”, the average value of the average speed at “8:30” of “direction 1” is obtained.

  In S205, the statistical traffic information setting unit 130 obtains a difference between the average value of the average speed at the start time calculated in S204 and the average value of the average speed at the end time for each direction in which the links are classified. Then, if the calculated difference is greater than a predetermined value (for example, 15 km / h), the statistical traffic information setting unit 130 estimates that the link in that direction of the mesh tends to change the traffic jam situation, Correlate data indicating “change” in the direction. Note that the data indicating the change is “1” as in the first embodiment. On the other hand, if the calculated difference is not greater than the predetermined value, the statistical traffic information setting unit 130 estimates that the link in the direction of the mesh has a tendency (stable tendency) that the traffic jam does not change, and the direction Is associated with data indicating “stable”. Note that data indicating stability is “0” as in the first embodiment.

  For example, when the predetermined value is set to “15 km”, “direction 1 (refer to the data surrounded by broken line 1200 in FIG. 12)” shown in FIG. 12 changes as change prediction information because the difference is “20 km”. (Change (1)) indicating In addition, since “difference” is “0 km” in “direction 3 (refer to data surrounded by a broken line 1201 in FIG. 12)”, data indicating stability (stable (0)) is associated as change prediction information.

  In the second embodiment, as in the first embodiment, it is estimated whether or not the traffic congestion state of the link changes based on the difference in average speed, but this is merely an example. For example, the determination may be made not by the difference between the two average speeds but by the rate of change of the two average speeds.

  Next, the statistical traffic information setting unit 130 obtains change prediction information of the time zone selected in S203 of the mesh using the change prediction information associated with each direction in S205 (S206). For example, the statistical traffic information setting unit 130 weights the number of links classified in the direction of the change prediction information (information indicating either “change” or “stable”) for each direction obtained in S205. The larger one of “change” and “stable” is used as mesh change prediction information.

  In the example of FIG. 12, the change prediction information of “direction 1” and “direction 4” is “change (1)”, and each of the two links is classified. That is, four links are classified in the direction of change prediction information “change (1)”. Therefore, “change” in the change prediction information is counted as “4”. On the other hand, the change prediction information of “direction 3” and “direction 6” is “stable (0)”, and each one link is classified. That is, two links are classified in the direction in which the change prediction information is “stable (0)”. Therefore, “stable” of the change prediction information is counted as “2”. As a result, since the counted value is “change”, the statistical traffic information setting unit 130 determines the change prediction information of the entire mesh as “change (1)”.

  Returning to FIG. 10, the description will be continued. Next, the statistical traffic information setting unit 130 determines whether or not change prediction information has been obtained for all time zones (S207). When the change prediction information of all time zones is obtained, the process proceeds to S208.

  In S208, the statistical traffic information setting unit 130 determines whether or not change prediction information has been obtained for all meshes. When the change prediction information of all meshes is obtained, the process proceeds to S209. If there is a mesh that has not been obtained yet, the process returns to S200, and the processes of S200 to S208 are performed.

  In S209, a determination table in which change prediction information is associated for each time period of each mesh obtained by the processes of S200 to S208 is created, the determination table is stored in the storage device 3, and the process ends.

  Here, the determination table created by the statistical traffic information setting unit 130 is shown in FIG.

  FIG. 13 is a diagram schematically illustrating the data configuration of the determination table according to the second embodiment.

  As illustrated, the determination table includes a table 1300 in which mesh IDs are registered, and a table 1310 in which change prediction information for each time zone is associated with each mesh ID registered in the table 1300.

  Note that the processing of FIG. 10 performed by the statistical traffic information setting unit 130 described above may be performed once when the navigation device is initially set (or when the navigation device is set in the vehicle at a store or the like). Further, without performing the processing of FIG. 10 by navigation, the manufacturer may create a determination table when the navigation device is manufactured and store it in the storage device 3. In this case, the configuration of the statistical traffic information setting unit 130 can be omitted.

  Next, the route search unit 140 according to the second embodiment will be described with reference to FIG.

  FIG. 15 is a flowchart of route search processing performed by the navigation device of the second embodiment. The following process is a process disclosed when a route search request specifying a departure place and a destination from a user is received. Further, it is assumed that current traffic information created from real-time traffic information is stored in a predetermined area of the memory (RAM 22) of the arithmetic processing unit 1 of the navigation device.

  First, the route search unit 140 specifies a mesh including a departure place and accepts a setting of a departure time. If the departure time is the current time, the current time acquired from a timer (not shown) in the navigation device may be used as the departure time. When the departure point is the current position of the vehicle, the current position calculated by the current position calculation unit 110 is set as the departure place. The route search unit 140 reads a “mesh conversion table (not shown)” from the storage device 3 and specifies the mesh ID of the mesh region including the point specified by the coordinate information from the coordinate information indicating the current position and the destination. . Next, the route search unit 140 acquires map data 310 having the specified mesh ID from the storage device 3 (S300). In this step, the determination table (FIG. 13) is read from the storage device 3.

  Next, the route search unit 140 determines whether or not the identified mesh is within a predetermined distance from the departure point (S301). If it is determined that the distance is not within the predetermined distance, the process proceeds to S305, and if within the predetermined distance, the process proceeds to S302.

  In S302, the route search unit 140 refers to the change prediction information in the determination table (FIG. 13) read out in S300. Specifically, the route search unit 140 obtains an estimated arrival time at the identified mesh. Then, the route search unit 140 reads the table 1310 associated with the identified mesh in the determination table. The route search unit 140 refers to the time zone change prediction information corresponding to the obtained arrival prediction time in the read table 1310.

  Here, when the identified mesh is a mesh including the departure place, the predicted arrival time is the departure time. If the identified mesh is not a mesh that includes the departure point, the estimated arrival time is the total cost of the route from the departure point to the link of the link of the identified mesh link (the link of the mesh adjacent to the identified mesh) ( This is calculated by adding the departure time to (travel time).

  Next, the route search unit 140 determines whether or not the change prediction information referred to in S302 is “stable” (S303). Then, the route search unit 140 proceeds to S304 if it is “stable” and proceeds to S305 if it is not “stable”.

  In S304, the route search unit 140 performs route search using the cost (travel time) of the current traffic information stored in the specified mesh according to the procedure of the Dijkstra method of the existing technology. Then, when the route search in the identified mesh is completed, the process proceeds to S306.

  Thus, the current traffic information is used in S304 for the following reason. That is, this step is a process performed when it is estimated that the traffic congestion state of the identified mesh in the time zone is stable. For this reason, it is estimated that the road conditions received by the real-time traffic information have not changed, and the “current traffic information” created from the real-time traffic information is used.

  On the other hand, if it is determined in S301 that the identified mesh is not located within the predetermined distance from the departure place, and if it is determined that the mesh change prediction information identified in S303 is not “stable”. S305 will be described.

  In S305, the route search unit 140 performs a route search using the cost (travel time) of the data 850 (see FIG. 14) included in the statistical traffic information in accordance with the procedure of the Dijkstra method in the identified mesh. Specifically, the route search unit 140 reads the statistical traffic information of the identified mesh from the storage device 3. Then, the route search unit 140 searches for the route in the identified mesh using the cost of the read statistical traffic information. In this step, when calculating the cost, the estimated arrival time for each link in the mesh is obtained, and the cost is calculated using the statistical value of the time zone to which the estimated arrival time belongs.

  As described above, the statistical traffic information is used in S305 for the following reason. When it is determined that the identified mesh is not located within a predetermined distance from the departure place, it is considered that a certain amount of time has passed since the real-time traffic information was received. That is, the received real-time traffic information is considered to have a high possibility of not reflecting the traffic jam situation when the vehicle passes the specified mesh. Therefore, in this step, the statistical value of the statistical traffic information is used without using the “current traffic information” created from the real-time traffic information.

  In addition, even if the mesh is located within a predetermined distance from the departure place, if it is estimated that the traffic congestion status of the mesh in that time zone is not stable, the traffic congestion status indicated in the real-time traffic information will be There is a high probability of change. Therefore, in this step, the statistical value of the statistical traffic information is used without using the “current traffic information” created from the real-time traffic information.

  In S306, the route search unit 140 determines whether the route searched in S305 or S306 has arrived at the destination. If the destination has not been reached, the process proceeds to S307, and if the destination has been reached, the process proceeds to S308.

  In S307, the route search unit 140 identifies the next mesh. Specifically, the route search unit 140 uses the map data 310 to identify the mesh to which the link connected to the route searched in S305 or S306 belongs, and returns to the processing of S301.

  In S308, the recommended route from the destination to the departure point is determined by the same procedure as in S111 of FIG. 9 described above, and the process ends.

  In addition, although the case where the Dijkstra method is used has been described in S305 and S306, this is merely an example.

  Thus, also in 2nd Embodiment, the effect similar to 1st Embodiment can be acquired. Furthermore, in the second embodiment, since it is not necessary to determine which current traffic information or statistical traffic information is used for each link, the processing can be shortened compared to the first embodiment.

  In the second embodiment, the arrival time to the identified mesh is obtained, and after determining the arrival time, it is determined whether to use the current traffic information or the statistical traffic information. It may be.

  Specifically, the route search unit 140 selects a mesh in a range necessary for route search from the destination to the departure point. Next, a mesh within a predetermined distance from the starting point is extracted from all the selected meshes. Then, for each extracted mesh, using the determination table (FIG. 13), the change prediction information of the time zone corresponding to the departure time is referred to, and the data in which the change prediction information is associated with each mesh (reference result) Create The route search unit 140 calculates the cost by selecting either the current traffic information or the statistical traffic information according to the created reference result for the mesh within a predetermined distance from the departure place. Note that statistical traffic information is used for route search for meshes that are not within a predetermined distance from the departure place.

  If comprised in this way, since the process which calculates | requires the arrival time to the specified mesh can be abbreviate | omitted, a route search process can be shortened further rather than 2nd Embodiment.

<< Third Embodiment >>
Next, a third embodiment of the present invention will be described.

  In the third embodiment, a part of the function of the traffic information setting unit 120 and a part of the function of the route search unit 140 of the first and second embodiments are changed. Specifically, in the third embodiment, when the traffic information setting unit 120 receives real-time traffic information, it is determined whether there is an area where the real-time traffic information is not distributed. Then, the mesh ID of the area that is not distributed is specified, and the mesh ID is notified to the route search unit 140. The traffic information setting unit 120 creates current traffic information from real-time traffic information and stores it in a memory (a predetermined area of the RAM 22), as in the first and second embodiments. Then, when searching for a recommended route, the route search unit 140 does not access the current traffic information in the memory for the notified mesh link, and the cost of the map data 310 (or the cost of the statistical traffic information). ) To search for a route.

  Hereinafter, processing of the traffic information setting unit 120 and the route search unit 140 according to the third embodiment will be described. Note that the third embodiment will also be described using the same reference numerals as those in the first embodiment.

  Initially, the process of the traffic information setting part 120 is demonstrated using FIG.

  FIG. 16 is a flowchart of traffic information setting processing according to the third embodiment of this invention. Note that the following processing is periodically executed at predetermined time intervals as in the first embodiment. The following processing is also executed when the traffic information setting unit 120 receives a request from a user (request for acquiring real-time traffic information) via the UI control unit 100.

  Moreover, the traffic information setting part 120 shall hold | maintain the link conversion table which matched the link on the map data 310 for every road contained in the traffic congestion information of traffic information similarly to 1st Embodiment.

  First, the traffic information setting unit 120 acquires the received real-time traffic information from the FM multiplex broadcast receiving apparatus 10 according to the procedure similar to S20 of FIG. 5 described above (S400). It is assumed that the real-time traffic information is classified for each predetermined area (for example, administrative divisions such as states and cities), and the data of which area can be identified.

  Next, the traffic information setting unit 120 determines whether or not there is an area (for example, an administrative division such as a state or a city) that has no data in the acquired real-time traffic information (S401). As a result of the determination, the traffic information setting unit 120 proceeds to S403 when there is an area without data, and proceeds to S404 when there is no area without data.

  In S403, the traffic information setting unit 120 identifies meshes in areas without data, creates a list of identified meshes, and transmits the created list to the route search unit 140 (S403). The route search unit 140 holds the list from the traffic information setting unit 120.

  In S404, the traffic information setting unit 120 performs the same processing as S30 in FIG. 5, creates current traffic information in which costs are associated with each link from the acquired real-time traffic information, and stores a predetermined area in the memory (RAM 22). To store.

  Subsequently, processing of the route search unit 140 of the third embodiment will be described. The route search unit 140 of the third embodiment is the same except that the process for accessing the current traffic information stored in the memory is different from the first embodiment and the second embodiment. Hereinafter, the process when accessing the current traffic information will be described.

  FIG. 17 is a flowchart of processing when accessing the current traffic information, which is performed by the navigation device according to the third embodiment of the present invention. The following processing is started when the current traffic information created from the real-time traffic information is used in the cost calculation in the route search. It is assumed that route search unit 140 holds a mesh list (hereinafter referred to as “mesh list”) of areas without real-time traffic information. That is, it is assumed that S403 in FIG. 16 is performed before the following processing is executed. In addition, it is assumed that the current traffic information created by the traffic information setting unit 120 is stored in a predetermined area of the memory (RAM 22).

  First, the route search unit 140 determines whether or not the mesh to which the cost calculation link belongs is an area without real-time traffic information (S500). Specifically, the route search unit 140 refers to the retained mesh list to determine whether or not the mesh to which the cost calculation link belongs is an area without real-time traffic information. That is, if the mesh to which the target link belongs is in the mesh list, the route search unit 140 determines that the mesh to which the target link belongs is an area without real-time traffic information. Further, if the mesh to which the target link belongs is not in the mesh list, the route search unit 140 determines that the mesh to which the target link belongs is an area having real-time traffic information.

  When the route search unit 140 determines that the mesh to which the target link belongs is an area without real-time traffic information, the route search unit 140 proceeds to S503. On the other hand, if the route search unit 140 determines that the mesh to which the target link belongs is an area with real-time traffic information, the route search unit 140 proceeds to S502 (S501).

  In S502, the route search unit 140 accesses the current traffic information in the memory, reads the corresponding data, and calculates the cost.

  In S503, the route search unit 140 calculates the cost using the cost in the map data without accessing the current traffic information in the memory (or the cost calculation using the cost in the statistical traffic information). I do).

  As described above, in the third embodiment, when there is only data in a certain area in the real-time traffic information, access to the data in that area is not performed. Therefore, in the third embodiment, unnecessary memory access processing can be omitted, and processing time for route search processing can be shortened.

  The present invention is not limited to the embodiment described above, and various modifications can be made within the scope of the gist of the present invention.

  For example, the route search unit 140 refers to the change prediction information for each link within a predetermined distance from the departure place, and extracts the link whose change prediction information is “change” from the above-described first embodiment. After performing the same processing and extracting the link whose change prediction information is “change”, a route search may be performed using the cost of the statistical traffic information. That is, the route search unit 140 determines whether to use the cost obtained from the real-time traffic information or the cost of the statistical traffic information until the change prediction information extracts the “change” link, and determines the cost according to the determination result. Perform the calculation. Then, after extracting the link whose change prediction information is “change”, the route search unit 140 performs a route search using the cost of the statistical traffic information.

  Further, the route search unit 140 refers to the change prediction information for each mesh within a predetermined distance from the departure place, and extracts the mesh whose change prediction information is “change” from the second embodiment described above. After performing the same processing and extracting a mesh whose change prediction information is “change”, a route search may be performed using the cost of the statistical traffic information.

  In the above embodiment, it is determined whether to use statistical traffic information or real-time traffic information for a link (or mesh) within a predetermined distance from the departure place. May be. That is, it is determined whether to use statistical traffic information or real-time traffic information until a predetermined time elapses from the departure time, and the cost of the link (or mesh) that passes after the predetermined time elapses is statistical traffic. Information may be used.

  Moreover, although the said embodiment demonstrated the cost calculation at the time of searching a recommended route, the calculation of other elements, such as weighting of a charge, is calculated in the same process by calculating the required time of a recommended route. May also be used).

1 is a schematic configuration diagram of an in-vehicle navigation device to which an embodiment of the present invention is applied. It is a figure which shows the data structure of the map data memorize | stored in the memory | storage device 3 of embodiment of this invention in simulation. It is a functional block diagram of the arithmetic processing part 1 of embodiment of this invention. It is a hardware block diagram of the arithmetic processing part 1 of embodiment of this invention. It is a flowchart of the traffic information setting process which the navigation apparatus of 1st Embodiment of this invention performs. It is a figure for demonstrating the process which calculates | requires the change prediction information for every time slot | zone of each link which the statistical traffic information setting part 130 of 1st Embodiment of this invention performs. It is a figure for demonstrating the process which calculates | requires the change prediction information for every time slot | zone of each link which the statistical traffic information setting part 130 of 1st Embodiment of this invention performs. It is a figure which shows the data structure of the statistical data of 1st Embodiment of this invention in simulation. It is a flowchart of the route search process which the navigation apparatus of 1st Embodiment of this invention performs. It is a flowchart of the statistical traffic information setting process of 2nd Embodiment of this invention. It is a figure for demonstrating the process which groups each link of 2nd Embodiment of this invention in a predetermined direction. It is a figure for demonstrating the process which calculates | requires the change prediction information for every mesh of 2nd Embodiment of this invention. It is the figure which showed the data structure of the determination table of 2nd Embodiment of this invention in simulation. It is the figure which showed the data structure of the statistical traffic information of 2nd Embodiment of this invention in simulation. It is a flowchart of the route search process which the navigation apparatus of 2nd Embodiment of this invention performs. It is a flowchart of the traffic information setting process of 3rd Embodiment of this invention. It is a flowchart of the process at the time of accessing the present traffic information which the navigation apparatus of 3rd Embodiment of this invention performs.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 ... Arithmetic processing part, 2 ... Display, 3 ... Memory | storage device, 4 ... Voice input / output device, 5 ... Input device, 6 ... Wheel speed sensor, 7 ... Geomagnetic sensor, 8 ... Gyro, 9 ... GPS receiver, 10 ... FM multiplex broadcast receiver, 15 ... route guidance unit, 16 ... map display processing unit, 17 ... graphics processing unit, 21 ... CPU, 22 ... RAM, 23 ... ROM, 24 ... DMA, 25 ... drawing controller, 26 ... VRAM 27 ... Color palette, 28 ... A / D converter, 29 ... SCI, 30 ... PIO, 31 ... Counter, 100 ... UI control unit, 110 ... Current position calculation unit, 120 ... Traffic information setting unit, 130 ... Statistical traffic Information setting unit, 140 ... route search unit, 150 ... map display processing unit

Claims (6)

A navigation device that searches for a recommended route from a departure point to a destination using link information included in map data,
Means for storing statistical traffic information obtained by statistically processing data collected in the past for each link constituting a road on the map data;
A means of obtaining current traffic information indicating the traffic conditions of each road from the outside ,
A route search means for searching for a recommended route to a destination using the link information, the current traffic information, and the statistical traffic information included in the map data,
In the statistical traffic information, for each link, the cost of the link obtained by the statistical processing is associated with change prediction information obtained based on a change in vehicle speed ,
The route search means includes
Data indicating that, when a link that is a candidate for the recommended route is extracted, the change prediction information corresponding to the extracted link is referred to, and the referred change prediction information tends to change the traffic congestion status of the link. In the case of data indicating that the cost of the statistical traffic information is used to calculate the cost of the extracted link and that the traffic congestion status of the link does not tend to change, the current traffic is used to calculate the cost of the extracted link. A navigation apparatus characterized by utilizing the cost of information. The navigation device according to claim 1,
Each link of the statistical traffic information is associated with the cost and the change prediction information for each predetermined time zone,
Means for accepting the setting of the departure time,
When the candidate link is extracted, the cost from the departure place to the extracted link is calculated, the estimated arrival time obtained by adding the cost to the accepted departure time is obtained, and the estimated arrival time belongs to Navigation with reference to time zone change prediction information and determining whether to use the cost of the statistical traffic information or the cost of the current traffic information for calculating the cost of the link apparatus. A navigation device according to any one of claims 1-2,
The route search means includes
Before referring to the change prediction information , the map data is used to determine whether or not the link is located within a predetermined distance from the departure place, and is not located within a predetermined distance from the departure place. The statistical traffic information is used to calculate the cost of the extracted link, the change prediction information is referred to when the link is located within the predetermined distance, and the cost of the statistical traffic information is calculated to calculate the cost of the link. A navigation device characterized by determining whether to use or to use the cost of the current traffic information. The navigation device according to claim 2,
The statistical traffic information is
Change prediction information indicating that there is a tendency to change is associated with the time zone in which the cost of the link obtained by the statistical processing changes by a predetermined value or more, and the cost of the link obtained by the statistical processing is predetermined. A navigation device, characterized in that change prediction information indicating that there is no tendency to change is associated with the time zone in which the value does not change more than a value. A navigation device that searches for a recommended route from a departure point to a destination using link information included in map data,
Means for storing statistical traffic information obtained by statistically processing data collected in the past for each link constituting a road on the map data;
Means to obtain current traffic information indicating the traffic situation including the cost of each road from the outside,
A route search means for searching for a recommended route to a destination using the link information, the current traffic information, and the statistical traffic information included in the map data,
The link included in the statistical traffic information is associated with the cost of the link obtained by the statistical processing, and the change prediction information obtained based on the change in vehicle speed corresponds to each mesh to which the link belongs. Attached,
The route search means includes
The map data is used to identify a mesh from the starting point to the destination, refer to the change prediction information corresponding to the statistical traffic information for each identified mesh, and the tendency of the congestion state to change For the mesh associated with the change prediction information indicating that the traffic is in the state, the cost of the statistical traffic information is used to calculate the cost of the link in the mesh, and the traffic congestion status does not tend to change A navigation device characterized in that, for a mesh associated with change prediction information , a cost of the current traffic information is used for calculating a cost of a link in the mesh. A route search method performed by a navigation device that searches for a recommended route from a departure place to a destination using link information included in map data,
Means for storing statistical traffic information obtained by statistically processing data collected in the past for each link constituting a road on the map data,
In the statistical traffic information, for each link, the cost of the link obtained by the statistical processing is associated with change prediction information obtained based on a change in vehicle speed ,
The navigation device
Obtaining current traffic information indicating traffic conditions including the cost of each road from the outside;
Searching for a recommended route to the destination using the link information, the current traffic information, and the statistical traffic information included in the map data,
The step of searching for the route includes:
Data indicating that, when a link that is a candidate for the recommended route is extracted, the change prediction information corresponding to the extracted link is referred to, and the referred change prediction information tends to change the traffic congestion status of the link. In the case of data indicating that the cost of the statistical traffic information is used to calculate the cost of the extracted link and the traffic condition of the link does not tend to change, the current traffic is used to calculate the cost of the extracted link. A route search method using the cost of information.

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