JP4576861B2 - Navigation system - Google Patents

Description

  The present invention relates to a navigation system.

  Conventionally, in a navigation apparatus mounted on a vehicle such as an automobile, when an operator such as a driver operates a predetermined input unit to set a destination, the destination and the current position detection processing unit detect the destination. Based on the current position of the vehicle, a route from the current position to the destination is searched, and the searched route is guided. In this case, the route is searched so that the distance from the current position to the destination is the shortest, or the route is searched so that the required time is the shortest.

In addition, a system for transmitting road traffic information to a navigation device is also provided so that an optimum route avoiding a traffic jam section can be searched by receiving road traffic jam information (see, for example, Patent Document 1). ). For example, in a road traffic information communication system called VICS (Vehicle Information & Communication System) (R), information on traffic control systems such as the police and the Japan Highway Public Corporation is collected and information on traffic jams and traffic Road traffic information such as regulation information is created and transmitted to the navigation device by communication means. And the navigation apparatus which received the said road traffic information searches a path | route so that required time becomes the shortest based on the said road traffic information.
JP-A-8-338736

  However, in the conventional system, the road traffic information that can be received is the current status information within a predetermined range set in advance. For example, the road traffic information transmitted by the VICS (R) is generally information on the current state in a range about several tens [km] from the current position. Therefore, even if the route search is performed using the traffic information, the information on the place far from the current position is not always searched for the route whose traffic time changes and the required time is the shortest when it actually passes. I couldn't.

  The present invention provides a navigation system capable of solving a problem of the conventional system and searching for a route capable of avoiding a traffic jam in an in-vehicle device by distributing information effective for route search by a server. For the purpose.

Therefore, in the navigation system of the present invention, a traffic information database that stores traffic information, a link group database that stores a link group table indicating links registered for each area, and a route to a destination are searched, When the route passes through the area, a time for passing through the area is calculated as a reference time, and a search for setting the time of a link registered in the area through the same time as the calculated reference time A processing unit and a prediction processing unit that creates predicted traffic information at the set time based on the traffic information for the link.

In another navigation system of the present invention, a traffic information database for storing traffic information, a link group database for storing a link group table indicating links registered for each group obtained by dividing a city expressway, When a route is searched and the route passes through the group, the time passing through the group is calculated as the reference time, and the time of the link registered in the group passing through is the same as the calculated reference time . A search processing unit that sets time, and a prediction processing unit that creates predicted traffic information at the set time for the link based on the traffic information.

  In still another navigation system of the present invention, the prediction processing unit creates a predicted link travel time pattern based on the link travel time pattern stored in the traffic information database, and the predicted link travel time pattern Based on this, the predicted traffic information is created.

  In still another navigation system of the present invention, the link group database further stores a related group table that defines a relationship of a group for which predicted traffic information needs to be created, and the prediction processing unit is configured so that the route is When passing through a plurality of groups, predicted traffic information is created for all groups defined in the related group table.

  In still another navigation system of the present invention, the related group table further defines a group that creates the predicted traffic information and a group that uses the same reference time.

In yet another navigation system of the present invention, a traffic information database for storing traffic information, a link group database for storing a link group table indicating links registered for each group obtained by dividing an urban highway, and a route to a destination When the route passes through the group, the time passing through the group is calculated as the reference time, and the time of the link registered in the group passing through is the same as the calculated reference time. A search processing unit that is set to the server, and a server that generates a predicted traffic information at the set time based on the traffic information and distributes the generated predicted traffic information to the link And a vehicle-mounted device for searching for a route to the destination using the predicted traffic information distributed. That.

  According to the present invention, the server distributes information effective for route search. Therefore, it is possible to search for a route that can avoid traffic jam in the in-vehicle device.

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

  FIG. 2 is a diagram showing the configuration of the navigation system in the embodiment of the present invention.

  In the figure, reference numeral 11 denotes an information providing server as a server, which is configured in a computer provided with arithmetic means such as a CPU and MPU, storage means such as a semiconductor memory, a magnetic disk, and an optical disk, and a communication interface. The computer is not a single computer but may be a so-called distributed server in which a plurality of computers are organically coupled. Further, another system may be constructed in the computer. Further, the information providing server 11 may be one of systems constructed in another computer.

  Reference numeral 31 denotes an in-vehicle device operated by an operator as a user, which is mounted on a vehicle such as a passenger car, a truck, a bus, and a motorcycle. Although there are actually a large number of in-vehicle devices, in the present embodiment, the on-vehicle device 31 is representative for convenience of explanation. The operator is, for example, a driver or a passenger of the vehicle, but may be any person.

  The in-vehicle device 31 includes a calculation device such as a CPU and MPU, a storage device such as a semiconductor memory, a magnetic disk, and an optical disk, a liquid crystal display, an LED (Light Emitting Diode) display, a display device such as a CRT, a keyboard, a joystick, and a cross. An input device such as a key, a push button, a remote controller, and a touch panel, a display control device that controls the display device, and a transmission / reception unit such as a communication interface. The in-vehicle device 31 is, for example, a navigation device, but a stationary phone, a mobile phone, a PHS (Personal Handy-Phon System) phone, a personal digital assistant, a PDA (Personal Digital Assistant), a personal computer, a game machine, a digital TV, and the like. It can be anything.

  Further, the in-vehicle device 31 has a current position detection device (not shown). In the case where the in-vehicle device 31 is a navigation device, for example, the current position detection device is generally based on GPS (Global Positioning System), geomagnetic sensor, distance sensor, steering sensor, beacon sensor, gyro sensor, etc. Detect position. In addition, for example, in the case of a mobile phone, a portable information terminal, etc., generally, based on communication with the base station where the mobile phone, the portable information terminal, etc. are located, the position of the base station is set as the current position. To detect.

  In the present embodiment, the case where the in-vehicle device 31 is a navigation device will be described. In this case, the in-vehicle device 31 has a search function for searching for a facility or a point and a search function for searching for a route, like a normal navigation device. With the search function, the in-vehicle device 31 can perform DRG (Dynamic Route Guidance) as a route search for avoiding traffic restriction and traffic jam using traffic information.

  Here, the information providing server 11 and the in-vehicle device 31 are connected to be communicable with each other via a network (not shown). The network may be any communication such as a wired or wireless public communication network, a dedicated communication network, a mobile phone network, the Internet, an intranet, a LAN (Local Area Network), a WAN (Wide Area Network), a satellite communication network, etc. It may be a line network or a combination of these as appropriate. Moreover, it may communicate using CS broadcasting or BS broadcasting by a broadcasting satellite, may communicate using terrestrial digital television broadcasting, may communicate using FM multiplex broadcasting, Communication may be performed using an optical beacon or a radio beacon installed on the side of the road.

  And the navigation system in this Embodiment is comprised by the said information provision server 11 and the vehicle-mounted apparatus 31. FIG. In this case, it is desirable that the operator is a person who is registered in advance in the navigation system and has a registration ID. Moreover, it is desirable that the in-vehicle device 31 is also registered.

  Here, from the viewpoint of function, the information providing server 11 needs to access the data unit 12 for storing data necessary for creating traffic jam prediction information as predicted traffic information, and to access the data unit 12. It has the process part 21 which performs the process for acquiring data and creating traffic congestion prediction information. The data unit 12 includes a traffic information database 13 and a link group database 14.

  The traffic information database 13 is information relating to road traffic congestion and the like created by collecting information on traffic control systems such as the police and the Japan Highway Public Corporation in a road traffic information communication system called VICS (R), for example. And road traffic information such as traffic regulation information. In this case, information on traffic jams on roads created in the past is also accumulated as statistical traffic jam information. Furthermore, the traffic information database 13 is used to specify event schedule information such as the scheduled location and scheduled date and time of events such as festivals, parades, fireworks displays, etc., for example, roads around stations and large commercial facilities every day except weekends. Statistical traffic jam information and traffic jam prediction information such as traffic jams occurring at the time of day and traffic jams occurring during summer holidays are also stored on roads around the beach. In this case, it is desirable that the statistical traffic jam information and the traffic jam prediction information are associated with a VICS (R) link described later. Furthermore, the traffic information database 13 may store information provided from a number of operators registered in advance. In this case, the information is, for example, detailed information on road traffic information such as road traffic information related to road traffic congestion, traffic control information related to traffic control by the police, traffic regulation information due to road construction, building construction, and the like. In the case of road traffic information, the detailed information is the actual length of the traffic jam, the cause of the traffic jam, the time when the traffic jam is expected to be resolved, etc. , Location, day of the week, time zone, etc., in the case of traffic regulation information, the duration of road construction, building construction, etc., the type of traffic regulation such as traffic closure, one-sided alternate traffic, lane regulation, time zone of traffic regulation, etc. . Further, the traffic information database 13 also stores link travel time patterns accumulated in the past.

  The link group database 14 stores information related to links necessary for providing traffic information. Here, the link is a unit constituting a road, and is usually divided with an intersection of three or more roads as a boundary. The intersection includes not only an intersection where a traffic signal lamp is installed but also an intersection where no traffic signal lamp is installed. Therefore, the number of links on a single road is not constant. In addition, the point where the administrative road attribute of a road changes is also handled as a link boundary. And in a normal navigation apparatus, each link which comprises a road, ie, road link ID as an identification number which identifies a road link, is provided.

  The VICS (R) information, which is traffic information based on the VICS (R), includes a VICS (R) link ID together with information such as type information, position, distance of a traffic jam section, traffic jam degree, and the like. The VICS (R) link ID is an identification number assigned to a VICS (R) link as a travel guidance link that is standardized by dividing a road at predetermined intersections. The VICS (R) information also includes information such as the coordinates of the start point and end point of each VICS (R) link, the distance from the start point to the end point, and the like.

  Here, the road link and the VICS (R) link are not the same (generally, the road link is subdivided more than the VICS (R) link). Therefore, a navigation device having a normal VICS (R) function has a conversion table (contrast table) between a road link ID and the VICS (R) link ID, and is based on the VICS (R) link ID. Thus, the corresponding road link ID can be specified. Therefore, when the in-vehicle device 31 has the conversion table like a navigation device, when the VICS (R) link ID is received from the information providing server 11, it is based on the VICS (R) link ID. It is possible to specify a road section on which VICS (R) information is to be displayed.

  However, when the in-vehicle device 31 does not have the conversion table, the road section cannot be specified based on the VICS (R) link ID. Therefore, the link table database 14 also stores the conversion table. Thereby, the VICS (R) link ID can be converted into the road link ID used in the in-vehicle device 31, and the VICS (R) information can be transmitted. Further, when the in-vehicle device 31 does not have a map database or the like to be described later and cannot create a map, the information providing server 11 uses the map displayed on the screen as image information. The image information is generated and transmitted to the in-vehicle device 31, and an image based on the image information is displayed on the display device of the in-vehicle device 31. In this case, the conversion table stored in the link group database 14 is used to identify the road section corresponding to the VICS® link ID.

  The data unit 12 preferably stores data relating to all roads including narrow streets, for example, all roads in Japan. Here, intersection data, node data, road data, traffic regulation data, and route display data are also stored in the data relating to the road. In the intersection data, in addition to the number of intersections in which data is stored, data relating to each intersection is assigned with a number for identification as intersection data. Further, each intersection data is stored with a number for identifying each connection road in addition to the number of roads connected to the corresponding intersection, that is, the number of connection roads. The intersection data may include the type of the intersection, that is, whether the intersection is a traffic signal lamp or an intersection where no traffic signal lamp is installed. Further, the node data constitutes at least the position and shape of the road in the map data recorded in the map data file, and includes actual branch points (including intersections, T-junctions, etc.), nodes, And data indicating a link connecting the nodes. Further, the node indicates at least the position of the inflection point of the road.

  In addition to the number of roads in which data is stored, the data unit 12 stores data relating to each road as road data with a number for identification. Each road data stores a road type, a distance as a length of each road, a travel time as a time required for traveling on each road, and the like. Further, the road type includes administrative road attributes such as a national road, a prefectural road, a main local road, a general road, and an expressway.

  In the road data, the width, gradient, cant, altitude, bank, road surface condition, whether or not there is a median strip, the number of road lanes, and the number of lanes are reduced. It is desirable to include data such as points and points where the width becomes narrower. In the case of an expressway or a main road, each of the lanes in the opposite direction is stored as separate road data and processed as a double road. For example, in the case of a trunk road with two or more lanes on one side, it is processed as a two-way road, and the lane in the upward direction and the lane in the downward direction are each stored in the road data as independent roads. Further, for corners, it is desirable to include data such as radii of curvature, intersections, T-junctions, and corner entrances. Road attributes such as railroad crossings, expressway entrance / exit rampways, expressway toll gates, downhill roads, and uphill roads may also be included.

  The data unit 12 preferably includes a map database (not shown) for storing map information, a POI (Point of Interest) database (not shown), a road database (not shown), and the like. Here, the map database stores map information such as nodes, links, coordinates, and facility names for drawing a map. In addition, the POI database stores facility data, town page data, event data, and the like for searching points such as a departure point, a destination, and a passing point. The POI database may include detailed information on facilities and regions. For example, when the facility is a restaurant such as a restaurant or canteen, the detailed information includes business days of the week, business hours, telephone numbers, menus, prices, taste, quality of service, atmosphere in the store, presence / absence of parking, etc. When the facility is a commercial facility such as a convenience store, department store, home center, supermarket, etc., the detailed information includes the day of the week, business hours, telephone number, assortment, price, bargain sale ( Special sale), bargain sale products, service quality, in-store atmosphere, presence of parking lots, types and periods of entertainment and events, etc. The facilities include theme parks, game centers, movie theaters, theaters, etc. In the case of an amusement facility, the detailed information includes the business day of the week, business hours, telephone number, contents of the facility, price, quality of service, atmosphere, presence of parking, It is the products and events of the type and duration, and the like.

  The storage means of the information providing server 11 in which the traffic information database 13 and the link group database 14 are stored may be an internal storage medium of the information providing server 11 or an external storage medium. In this case, the internal storage medium and the external storage medium are magnetic tape, magnetic disk, magnetic drum, CD-ROM, CD-R / RW, MD, DVD-ROM, DVD-RAM, DVD-R / RW, optical disk, Any type of MO, IC card, optical card, memory card, stick memory, etc. may be used.

  The processing unit 21 includes an input processing unit 22, a search processing unit 23, a search processing unit 24, a display processing unit 25, and a prediction processing unit 26. Here, the input processing unit 22 performs an input process of inputting a DRG data distribution request received from the in-vehicle device 31, a facility or point data distribution request, and the like. The search processing unit 23 performs a POI search process for searching for a facility or a point based on a search condition or the like included in a search request received from the in-vehicle device 31. Further, the search processing unit 24 searches for a plurality of routes to the destination, and calculates the passage start time of each link in each route. Further, the display processing unit 25 performs display processing for displaying the created traffic jam prediction information. Further, when the route passes through the city highway, the prediction processing unit 26 creates traffic jam prediction information for each group into which the city highway is divided.

  As a result, the information providing server 11 can search for all routes that may pass, create highly accurate traffic jam prediction information about each route, and distribute the information to the in-vehicle device 31.

  The information providing server 11 has a communication unit 17 for communicating with the in-vehicle device 31. Upon receiving a route search request, a traffic congestion prediction information distribution request, etc., the communication unit 17 identifies the in-vehicle device 31 that has transmitted the distribution request, and identifies the distribution data created by the processing unit 21 Transmit to the in-vehicle device 31.

  Next, the operation of the navigation system having the above configuration will be described. First, an operation in which the information providing server 11 creates a predicted link travel time pattern will be described.

  FIG. 3 is a first diagram showing an operation for creating a short-term predicted link travel time pattern in the embodiment of the present invention, and FIG. 4 shows an operation for creating a short-term predicted link travel time pattern in the embodiment of the present invention. FIG. 5 and FIG. 5 are diagrams showing an operation of creating a long-term predicted link travel time pattern in the embodiment of the present invention.

  In the present embodiment, the prediction processing unit 26 can create short-term and long-term predicted link travel time patterns. First, when creating a short-term predicted link travel time pattern, the prediction processing unit 26 creates a predicted link travel time pattern by performing feedback on the current status. That is, a predicted link travel time pattern is created by a method such as pattern matching or waveform correction based on the current traveling state of the vehicle received from the in-vehicle device 31. Here, the prediction period in the case of creating a short-term predicted link travel time pattern is, for example, a period from the current time to about two hours later, but can be arbitrarily set.

  First, a case where a predicted link travel time pattern is created by a pattern matching method will be described. In this case, the prediction processing unit 26 is based on the data received from the in-vehicle device 31 and indicating the status of the vehicle on which the in-vehicle device 31 is mounted, as shown in FIG. A link travel time pattern of the vehicle in a past predetermined period is created. The past predetermined period is, for example, a period from midnight on the current day to the current time, but can be arbitrarily set. In the link travel time pattern shown in FIG. 3A, the horizontal axis indicates time, and the vertical axis indicates total travel time.

  Subsequently, the prediction processing unit 26 accesses the traffic information database 13 and is stored in advance in the created link travel time pattern and the traffic information database 13 as shown in FIG. Pattern matching is performed by comparing with the past link travel time patterns. Note that the link travel time pattern shown in FIG. 3B shows a change in the total travel time in one day, similarly to the link travel time pattern shown in FIG. As a result of pattern matching, the prediction processing unit 26 calculates the link travel in the range from the origin to the current time in the range of the horizontal axis from the past link travel time patterns stored in the traffic information database 13 in advance. The one that is most approximate to the link travel time pattern in which the time pattern is created is extracted.

  Subsequently, the prediction processing unit 26 cuts out the link travel time pattern in the prediction period after the current time from the extracted link travel time pattern in the past to obtain a link travel time pattern. Thereby, as shown in FIG. 3C, a predicted link travel time pattern including the link travel time pattern shown in FIG. 3A can be obtained.

  Next, a case where a predicted link travel time pattern is created by a waveform correction method will be described. In this case, the prediction processing unit 26 uses an average link travel time pattern in the past stored in advance in the traffic information database 13. The point A in FIG. 4A is a point indicating the situation at the current time of the vehicle on which the in-vehicle device 31 is received, which is received from the in-vehicle device 31, and the line B in FIG. A typical link travel time pattern. In the link travel time pattern shown in FIG. 4A, the horizontal axis indicates the time, and the vertical axis indicates the total travel time.

  Subsequently, the prediction processing unit 26 corrects the line B so as to match the point A, and creates a link travel time pattern. In this case, as shown in FIG. 4B, the average link travel time pattern in the past can be changed in an equivalent ratio to create a predicted link travel time pattern as shown by the line C. . That is, the value of the total travel time indicated by the line B at the time corresponding to the point A is changed to the value of the total travel time indicated by the point A. Then, according to the ratio of the value after the change to the value before the change at the time corresponding to the point A, the value of the total travel time indicated by the line B is changed in all time ranges. As a result, the value of the total travel time indicated by the line B in all time ranges is changed at a ratio equal to the ratio of the value after the change to the value before the change at the time corresponding to the point A. In FIG. A predicted link travel time pattern as shown by line C can be created.

  Further, as shown in FIG. 4C, a predicted link travel time pattern as shown by the line C can be created by translating the average link travel time pattern in the past in the vertical direction. That is, the value of the total travel time indicated by the line B at the time corresponding to the point A is changed to the value of the total travel time indicated by the point A. Then, according to the difference between the value before the change at the time corresponding to the point A and the value after the change, the value of the total travel time indicated by the line B is changed in all time ranges. As a result, the value of the total travel time indicated by the line B in all the time ranges is changed by a value equal to the difference between the value before the change and the value before the change at the time corresponding to the point A. In FIG. A predicted link travel time pattern as shown by line C can be created.

  Further, as shown in FIG. 4D, an average link travel time pattern in the past can be inclined according to the history, and a predicted link travel time pattern as shown by line C can be created. In this case, the entire line B is inclined so as to pass through the point A and the point AA indicating the situation before the current time of the vehicle. Thereby, the prediction link travel time pattern as shown by the line C in FIG.4 (d) can be created.

  Next, when creating a long-term predicted link travel time pattern, the prediction processing unit 26 creates a predicted link travel time pattern without performing feedback on the current situation. That is, a past link travel time pattern stored in the traffic information database 13 is statistically analyzed to create a predicted link travel time pattern. Here, the prediction period when creating a long-term predicted link travel time pattern is, for example, a period after about two hours from the current time, but can be arbitrarily set.

  First, the prediction processing unit 26 accesses the traffic information database 13 and acquires a past link travel time pattern stored in advance in the traffic information database 13 as shown in FIG. The link travel time pattern shown in FIG. 5 (a) indicates a change in the total travel time in one day, and all the link travel time patterns stored in the traffic information database 13, that is, Shows the fluctuations of the whole day. In the link travel time pattern shown in FIG. 5A, the horizontal axis indicates time, and the vertical axis indicates total travel time.

  Subsequently, the prediction processing unit 26 classifies the link travel time pattern shown in FIG. 5A according to the calendar. Here, as shown in FIG. 5B, the case is divided into a link travel time pattern on weekdays and a link travel time pattern on holidays. That is, it is divided into a weekday change and a holiday change. Holidays are Saturdays, Sundays and public holidays, and weekdays are other days. In addition, for example, it is possible to extract only the link travel time pattern on a specific day or period such as Golden Week, summer vacation, year-end and New Year holidays. Furthermore, by removing abnormal values from the link travel time pattern, data variation can be reduced.

  Subsequently, the prediction processing unit 26 classifies the link travel time patterns classified according to the calendar according to events such as weather, events, and regulations. Here, as shown in FIGS. 5C and 5D, in the case classification according to the weather, the link travel time pattern in the fine weather, the link travel time pattern in the rain, and the link travel in the snow as fluctuations according to the weather. Divide into time patterns. Thereby, the prediction link travel time pattern according to the condition of the vehicle in which the vehicle equipment 31 is mounted can be obtained.

  The link travel time is the time required to pass through each link, and the length of each link is stored in the link group database 14, so the travel speed in each link is calculated from the link travel time in each link. Can be calculated. Therefore, a predicted speed pattern can be obtained based on the predicted link travel time pattern. In addition, the degree of congestion as traffic jam information in the VICS (R) information is defined as “traffic jam”, “congestion”, and “no traffic jam” according to the road type and travel speed. Can obtain traffic information on each link. Therefore, traffic jam prediction information can be obtained based on the predicted link travel time pattern.

  Next, a basic operation for creating and distributing DRG distribution data will be described.

  FIG. 6 is a diagram for explaining the basic concept of DRG data distributed in the embodiment of the present invention.

  In the present embodiment, the information providing server 11 uses the current location as a departure location based on the current location, destination, search conditions, etc. included in the DRG data distribution request received from the in-vehicle device 31. A search process for searching for a route to is performed. Then, the information providing server 11 searches for a plurality of routes, calculates a predicted passing time when the vehicle passes through each link in each route based on the predicted link travel time pattern, and predicts traffic at the predicted passing time. Information is created, and DRG distribution data is distributed to the in-vehicle device 31. That is, a recommended route that is the most recommended route in normal route search and an alternative route that can be a substitute for the recommended route are searched, and congestion of each link on the recommended route and the alternative route is predicted. Then, data such as traffic jam prediction information is transmitted to the in-vehicle device 31. As a result, the in-vehicle device 31 can perform DRG using the received data and search for a route that avoids traffic congestion.

  Here, as shown in FIG. 6, when a route is searched under the search condition that the highway is given priority from the starting point 41 to the destination 42, two routes 43 and 44 are searched. To do. For example, it is assumed that the route 43 is a recommended route and the route 44 is an alternative route. Then, based on the predicted link travel time pattern created as described above, the occurrence of traffic congestion on the route 43 and the route 44 is predicted, and traffic congestion prediction information is created for the region where the occurrence of traffic congestion is predicted. . The reference time of the traffic jam prediction information is the time when the vehicle will pass through the area where the occurrence of the traffic jam is predicted, that is, the predicted passing time of the vehicle. The reference time is set while being shifted, that is, slid, in accordance with the predicted vehicle passage time on the links on the route 43 and the route 44.

  In the example shown in FIG. 6, occurrence of traffic congestion is predicted on the route 43 in the region 45a and the region 45b. Then, for the area 45a, traffic jam prediction information at 10:00, which is a predicted passage time of a vehicle, is created, and for the area 45b, traffic jam prediction information at 11:00, which is a predicted traffic time of a vehicle, is created. . On the route 44, occurrence of traffic jam is predicted in the area 46a and the area 46b. For the region 46a, traffic jam prediction information at 10:30, which is a predicted vehicle passage time, is created, and for the region 46b, traffic jam prediction information at 11:30, which is a predicted vehicle passage time, is created. .

  Then, the searched data of the route 43 and the route 44 and the data including the traffic congestion prediction information about the region 45a, the region 45b, the region 46a, and the region 46b are transmitted as data for DRG from the information providing server 11 to the in-vehicle device 31. be delivered. Accordingly, the in-vehicle device 31 can perform DRG using the received DRG data, and can search for a route that avoids traffic jams. In addition, the estimated arrival time at the destination 42 can be accurately calculated.

  Next, the operation of the navigation system in the present embodiment will be described in detail. Here, for convenience of explanation, the operation when the route to the destination is an urban highway will be described.

  FIG. 1 is a diagram showing an example of dividing an urban highway into a plurality of groups in the embodiment of the present invention, FIG. 7 is a diagram showing an example of a link group table in the embodiment of the present invention, and FIG. FIG. 9 is a diagram showing an example of a reference time set for each group in the embodiment, FIG. 9 is a diagram showing an example of a route passing through a plurality of groups in the embodiment of the present invention, and FIG. 10 is an embodiment of the present invention. FIG. 11 is a flowchart illustrating an operation of the information providing server according to the embodiment of the present invention.

  First, the operator operates the input device of the in-vehicle device 31 to set a destination. For example, a search condition for searching for a route such as highway priority can be set as necessary. Subsequently, the operator operates an input device of the in-vehicle device 31 to operate means for transmitting a DRG data distribution request to the information providing server 11. Then, the in-vehicle device 31 transmits a current position, a destination, a search condition, and the like to the information providing server 11 as a DRG data distribution request.

  Subsequently, when the information providing server 11 receives a current position, a destination, a search condition, etc. as a DRG data distribution request from the in-vehicle device 31, based on the current position, a destination, a search condition, etc. Search for a recommended route from your current location to your destination. In this case, it is assumed that a route passing through the city highway is searched as a recommended route. The city expressway is in service in areas such as the capital, Hanshin, Nagoya, Fukuoka and Kitakyushu, but here it will be described as being a metropolitan expressway.

  Subsequently, the information providing server 11 searches for an alternative route for the recommended route. When n alternative routes exist, the alternative route is searched n times repeatedly. Note that n is a natural number. Further, an upper limit value of n can be set as necessary. That is, it is possible to limit the number of times of searching for alternative routes.

  Here, the city expressway is divided into a plurality of groups in advance. The method and number of division of the group can be arbitrarily set. In the present embodiment, as shown in FIG. 1, six groups included in the range shown in (1) to (6) are used. That is, the description will be made assuming that it is divided into groups 1 to 6. Then, a link group table indicating which group includes the links constituting the roads included in the groups 1 to 6 is created in advance and stored in the link group database 14 as shown in FIG. . The link group table is a table indicating links registered in each group. In FIG. 7, links 10, 11 and 12 are road link IDs for identifying the respective links.

  Subsequently, the information providing server 11 determines whether the searched recommended route or alternative route passes through the group, that is, whether the route registered in each group as shown in the link group table passes. Judge whether or not. And when passing a link, the said information provision server 11 divides reference | standard time for every group to pass, and produces the traffic congestion prediction information as prediction traffic information. Here, the reference time of the traffic jam prediction information is determined for each group, and the traffic jam prediction information is created at the same reference time for all the links registered in the same group. In this case, the reference time is a time at which the group first enters the group on the recommended route, that is, a link passage start time starting from a node corresponding to the entrance of the group on the recommended route.

  As shown in FIG. 8, an example in which the searched recommended route is 51 and the recommended route 51 passes through the group 1 will be described. The departure point is on the left side of FIG. 8, the destination is on the right side of FIG. 8, and the vehicle travels along the recommended route 51 from left to right in FIG. Reference numerals 52-1 to 52-4 denote links constituting the recommended route 51. Reference numerals 53-1 to 53-4 are nodes on the recommended route 51. In addition, 52-5 to 52-7 are links constituting a road branched from the recommended route 51 in the node 53-2, and 53-5 and 53-6 are nodes on the road branched from the recommended route 51. It is. The traveling direction of the vehicle at each link is the direction indicated by the arrow. The links 52-3 to 52-7 are links registered in the group 1, and the links 52-1 and 52-2 are links existing outside the group 1.

  In the example shown in FIG. 8, the node 53-2 corresponds to the entrance of the group 1 on the recommended route 51. Therefore, the arrival time at the node 53-2, that is, the passage start time of the link 52-3 starting from the node 53-2 becomes the group 1 reference time. For example, assuming that the arrival time at the node 53-2 is 10:00, the traffic jam prediction information on the link 52-3 and the link 52-4 registered in the group 1 and constituting the recommended route 51 Is created with 10:00 as the reference time. Further, the traffic jam prediction information in all other links registered in the group 1, that is, the links 52-5 to 52-7 is also created with 10:00 as the reference time. Congestion prediction information is created for all links registered in group 1 at the same reference time.

  Subsequently, the information providing server 11 creates the congestion prediction information of the group in which the association with the group through which the searched route passes is defined in advance.

  By the way, when the searched route passes through a plurality of groups, if the traffic jam prediction information is created only for the group through which the route passes and is distributed to the vehicle-mounted device 31, the vehicle-mounted device 31 has no traffic jam for other groups. It can be considered that the route passing through another group is selected as a route for avoiding traffic jam. As shown in FIG. 9, it is assumed that the searched route is 55 and that the route 55 leaves the group 6 and arrives at the group 3 via the group 1. And if the said information provision server 11 produces the traffic jam prediction information about the group 1, the group 3 and the group 6 along which the route 55 passes, and does not create the traffic jam prediction information about the other group, The traffic jam prediction information for group 1, group 3 and group 6 is distributed, and the traffic jam prediction information for other groups is not received. Then, it is conceivable that the in-vehicle device 31 determines that there is no traffic jam for the other groups, and selects a route as indicated by 56 in FIG. 9, for example. In general, an urban expressway such as the Metropolitan Expressway has a developed road network and has many branching points and junctions. Therefore, various ways of selecting a route are possible. It is conceivable to select a route that passes through a group through which the searched route 55 does not pass.

  In order to prevent such a problem, in the present embodiment, when the searched route passes through a plurality of groups, there is a relationship between groups that need to generate congestion prediction information and distribute it to the in-vehicle device 31. , Predefined according to the order of passage. Further, since the reference time of the traffic jam prediction information cannot be determined for the group through which the route does not pass, the reference time for the group through which the route passes is used. For example, in the example shown in FIG. 9, for the group 2 through which the route 55 does not pass, the traffic jam prediction information is created using the reference time for the group 3 through which the route 55 passes.

  FIG. 10 shows an example of a related group table that defines the relationship of groups for which traffic jam prediction information needs to be created. In the related group table, a group for creating traffic jam prediction information and a group using the same reference time are defined for each group passing order. The related group table is created in advance and stored in the link group database 14.

  For example, in the first from the top of the related group table, when the searched route leaves the group 1 and arrives at the group 2, the traffic jam prediction information is generated for the group 1, the group 2 and the group 3, and the group 2 and For group 3, it is defined that traffic jam prediction information is created using the same reference time. For group 1, the time of first entering group 1, that is, the departure time is set as the reference time.

  In the second from the top of the related group table, when the searched route leaves the group 1 and arrives at the group 3, the traffic jam prediction information is created for the group 1, the group 2, the group 3 and the group 4, For group 2, group 3, and group 4, it is defined that traffic jam prediction information is created using the same reference time. For group 1, the time of first entering group 1, that is, the departure time is set as the reference time.

  Further, in the third from the top of the related group table, when the searched route leaves group 6 and arrives at group 3, congestion prediction information is displayed for group 1, group 2, group 3, group 4 and group 6. It is defined that the traffic jam prediction information is created using the same reference time for group 1 and group 2, and the traffic jam prediction information is created using the same reference time for group 3 and group 4. It is defined to create. For example, in the example shown in FIG. 9, when the first entry time to the group 1 on the route 55 is 10:00 and the first entry time to the group 3 is 10:30, the group 1 and For group 2, 10:00 is set as the reference time, and for group 3 and group 4, 10:30 is set as the reference time. For group 6, the time of first entering group 6, that is, the departure time is set as the reference time.

  Subsequently, the information providing server 11 distributes the created traffic jam prediction information to the in-vehicle device 31 and ends the process. Further, it is determined whether or not the searched route passes a link registered in each group. When the route does not pass through the link, that is, when none of the groups passes, the information providing server 11 Congestion prediction information is created using the passage start time of the link on the route as a reference time. That is, the traffic jam prediction information is created in the same manner as the example described in FIG. And the produced traffic jam prediction information is delivered to the said vehicle-mounted apparatus 31, and a process is complete | finished.

  In addition, the said vehicle-mounted apparatus 31 will search for the path | route which avoids traffic jam by performing DRG, if the traffic jam prediction information delivered from the said information provision server 11 is received.

  By the way, the navigation system in the present embodiment can perform the same operation even when the route to the destination is not an urban highway. In this case, instead of the group obtained by dividing the city expressway, an area such as an area in administrative districts or an area in map mesh units obtained by dividing map data is used. Therefore, the link group table shows links registered for each predetermined area. Then, when the searched route passes through the area, the search processing unit 24 calculates the time that passes through the area as the reference time. Furthermore, the prediction processing unit 26 creates traffic jam prediction information as predicted traffic information at the reference time based on the traffic information for each area.

Next, a flowchart will be described.
Step S1: A recommended route from the current position to the destination is searched.
Step S2: Search for an alternative route to the recommended route. If there are n alternative routes, the alternative route is searched n times.
Step S3: It is determined whether or not the link registered in each group is passed. If the link registered in each group passes, the process proceeds to step S4. If the link registered in the group does not pass, the process proceeds to step S7.
Step S4 The traffic jam prediction information is created by dividing the reference time for each passing group.
Step S5: Create traffic jam prediction information for a group whose association with the passing group is defined in advance.
Step S6: Congestion prediction information is distributed to the in-vehicle device 31, and the process is terminated.
Step S7: Congestion prediction information is created using the link passage start time on each route as a reference time.

  Thus, in the present embodiment, the information providing server 11 searches for a plurality of routes to the destination, and when the route passes through a group of urban expressways divided into a plurality of routes, the route passes. The traffic jam prediction information is created for each group to be distributed to the in-vehicle device 31. When the searched route passes through a plurality of groups, the traffic jam prediction information is also created for the groups that are defined in advance according to the order of passage and are related to the groups, and distributed to the in-vehicle device 31.

  Therefore, the in-vehicle device 31 provides highly accurate traffic jam prediction information for all the routes that may pass even when the road network is developed and passes through an urban expressway having many branch points and junctions. Since it can be used, it is possible to search for an appropriate route that avoids traffic congestion. In addition, the estimated arrival time at the destination can be accurately calculated.

  In the conventional system, the information center server creates traffic jam prediction information for each link on the searched recommended route and alternative route, distributes it to the navigation device, and uses the traffic jam prediction information received by the navigation device. And search for routes that avoid traffic jams. Therefore, when passing through an intercity highway, the navigation device can search for a route that avoids traffic congestion. However, when the road network develops and passes through a city expressway with many branching points and junctions, it is possible to select various routes, so the server creates traffic jam prediction information for a plurality of routes. Even if distributed, the navigation apparatus selects a route for which the server has not created the traffic jam prediction information as a route for which traffic jam is not predicted. However, since there is a high possibility that a traffic jam will occur on the route for which the server has not created the traffic jam prediction information, the route selected by the navigation device is likely to be an inappropriate route with a long required time. There was a problem.

  In the present embodiment, the traffic congestion prediction information can be distributed to the in-vehicle device 31 for all the routes that may pass without causing such problems in the conventional system, so that the road network is developed. Even when the vehicle passes through an urban highway with many branch points and junctions, the in-vehicle device 31 can search for an appropriate route for avoiding traffic jams, and can further predict the arrival time at the destination. Can be calculated accurately.

  In addition, this invention is not limited to the said embodiment, It can change variously based on the meaning of this invention, and does not exclude them from the scope of the present invention.

It is a figure which shows the example which divides | segments the city highway in embodiment of this invention into a some group. It is a figure which shows the structure of the navigation system in embodiment of this invention. It is a 1st figure which shows the operation | movement which produces the short-term prediction link travel time pattern in embodiment of this invention. It is a 2nd figure which shows the operation | movement which produces the short-term prediction link travel time pattern in embodiment of this invention. It is a figure which shows the operation | movement which produces the long-term prediction link travel time pattern in embodiment of this invention. It is a figure explaining the basic concept of the data for DRG delivered in embodiment of this invention. It is a figure which shows the example of the link group table in embodiment of this invention. It is a figure which shows the example of the reference time set for every group in embodiment of this invention. It is a figure which shows the example of the path | route which passes through the some group in embodiment of this invention. It is a figure which shows the example of the relationship between the group which the path | route passes in Embodiment of this invention, and reference | standard time. It is a flowchart which shows operation | movement of the information provision server in embodiment of this invention.

Explanation of symbols

DESCRIPTION OF SYMBOLS 11 Information provision server 13 Traffic information database 14 Link group database 24 Search process part 26 Prediction process part 31 In-vehicle apparatus 42 Destination 43, 44, 55, 56 Route 52-1, 52-2, 52-3, 52-4, 52-5, 52-6, 52-7 links

Claims (6)

(A) a traffic information database for storing traffic information;
(B) a link group database storing a link group table indicating links registered for each area;
(C) A route to the destination is searched, and when the route passes through the area, the time passing through the area is calculated as a reference time, and the time of the link registered in the area passing through is calculated. A search processing unit for setting the same time as the set reference time;
(D) A navigation system including a prediction processing unit that generates predicted traffic information at the set time for the link based on the traffic information. (A) a traffic information database for storing traffic information;
(B) a link group database for storing a link group table indicating links registered for each group obtained by dividing a city highway;
(C) When a route to the destination is searched and the route passes through the group, a time passing through the group is calculated as a reference time, and a time of a link registered in the group passing through is calculated. A search processing unit for setting the same time as the set reference time;
(D) A navigation system including a prediction processing unit that generates predicted traffic information at the set time for the link based on the traffic information. The prediction processing unit creates a predicted link travel time pattern based on a link travel time pattern stored in the traffic information database, and creates predicted traffic information based on the predicted link travel time pattern. Navigation system. (A) The link group database stores a related group table that defines the relationship of groups for which predicted traffic information needs to be created;
(B) The navigation system according to claim 2 or 3 , wherein the prediction processing unit creates predicted traffic information for all groups defined in the related group table when the route passes through a plurality of groups. The navigation system according to claim 4 , wherein the related group table defines a group that creates predicted traffic information and a group that uses the same reference time. (A) a traffic information database for storing traffic information;
(B) a link group database for storing a link group table indicating links registered for each group obtained by dividing a city expressway;
(C) When a route to the destination is searched and the route passes through the group, a time passing through the group is calculated as a reference time, and a time of a link registered in the group passing through is calculated. A search processing unit for setting the same time as the reference time, and
(D) a server for generating predicted traffic information at the set time based on the traffic information for the link, and a server for distributing the generated predicted traffic information;
(E) A navigation system comprising: an in-vehicle device that searches for a route to the destination using the distributed predicted traffic information.

Images