JP2013205227A - Disliked road attribute detecting device, disliked road attribute detecting method and program - Google Patents

Abstract

PROBLEM TO BE SOLVED: To detect a road attribute disliked by a driver.SOLUTION: A disliked road attribute detecting device 1 comprises a dislike candidate DB 20 storing therein candidates of a disliked road attribute disliked by a driver, a travel history DB 22, a two-point detecting section 28 which detects a first point and a second point where a first route most frequently used for moving from the first point to the second point and a second route most frequently used for moving from the second point to the first point are different based on travel history data of a road link read out of the travel history DB 22, and a dislike detecting section 30 which reads the candidates of the disliked road attribute out of the dislike candidate DB 28 searches the first (second) route from the second (first) point to the first (second) point for a road attribute meeting a candidate of the disliked road attribute which is absent in the second (first) route, and when the road attribute meeting the candidate of the disliked road attribute is found, detects that road attribute as a road attribute disliked by the driver.

Description

  The present invention relates to a technique for finding a road attribute that a driver is not good at.

  Conventionally, navigation systems that search for an optimum route from a departure point to a destination are widely used. For example, the invention described in Patent Document 1 is a navigation system proposed by the present applicant. As seen in FIG. 3 of the same document, in the present invention, nodes such as road width, speed limit, number of traffic lights, etc. are involved in the cost tables A to C for searching for a route. By using such a model, a route search can be performed using one of the cost tables A to C according to the preference of the driver and the situation at that time.

JP 2007-10571 A

  In the above navigation system, since the driver's preference is reflected, it can be said that the route search including information such as the road on which the driver can easily travel is realized. However, if the road attributes that the driver is not good at can be identified, the information on the identified road attributes can be directly used for route search and route guidance, and a safe driving environment for the driver can be provided. it can.

  In view of the above background, an object of the present invention is to provide a poor road attribute detection device that detects a poor road attribute of a driver.

  The poor road attribute detection device of the present invention includes a poor candidate storage unit that stores poor road attribute candidates that the driver is not good at, a travel history storage unit that stores a travel history that has passed through each road link, and the travel history storage unit. Based on the travel history data of the road link read out from the first route most frequently used for the movement from the first point to the second point, and the movement from the second point to the first point A two-point detection unit that detects a first point and a second point that are different from the most frequently used second route, and a candidate for poor road attributes is read from the poor candidate storage unit, and the first route is There is a road attribute that matches a candidate for a poor road attribute that is not found in the second route on a road that traces back from the second point to the first point, or the second route is the first route On the road that goes back from the point 1 to the second point If there is a road attribute that matches a poor road attribute candidate that is not in the first route, and a road attribute that matches the poor road attribute candidate is found, that road attribute is used as the poor road attribute of the driver. A weak detection unit for detecting.

  In the present invention, using the travel history data, the first route most frequently used for the movement from the first point to the second point and the most frequently used for the movement from the second point to the first point. The first point and the second point, which are different in the second route used, that is, the first point and the second point where the traveling route is different between the going and the returning are detected. Focusing on the fact that, in the case of a frequently used road, when the driver changes the route between going and returning, there is a possibility that there is a poor road attribute on the road on the going or returning route. If there is a road attribute that matches a candidate for a poor road attribute that is not on the return (going) path but is on a road that is followed by a (return) path, the road attribute is a poor road attribute of the driver. And the poor road attribute is detected. Thereby, the road attribute which a driver is not good at can be found appropriately. Here, the “road attribute” is a feature of a road or a person who passes through a road such as a sharp turn right, a one-lane road, or a road with many school roads or trucks. The first point and the second point may be a place where the vehicle has stopped and the engine has been turned off, such as a departure point or a destination, or a node through which the vehicle has passed while traveling.

  In the poor road attribute detection device of the present invention, the two-point detection unit does not detect the first point and the second point when there is a stop on the first route or the second route. It is good also as a structure.

  When there is a stop on the first route or the second route in this way, the difference between the first route and the second route is not due to poor road attributes, but stops at the stop. Therefore, by excluding the route including the stop-off area from the detection target of the poor road attribute, the detection accuracy of the poor road attribute can be kept high.

  In the poor road attribute detection device of the present invention, the travel history storage unit stores data of a departure place and a destination in association with the travel history, and the two-point detection unit includes the first point and the second point. The search for the point may be started from the starting point and the destination.

  If there is a destination that has been visited many times, the round trip is repeated between the destination and the departure point. 2 points can be obtained efficiently.

  In the poor road attribute detection device according to the present invention, the two-point detection unit detects a road link having a difference in the number of passages by a predetermined threshold or more depending on the direction of passage based on data read from the travel history storage unit. Then, the first point and the second point may be detected around the road link.

  When the number of times of passage differs greatly depending on the direction of passage in this way, it is considered that the difference in the number of times of passage is corrected using another road link for the direction with a small number of passages. Therefore, the first point and the second point can be appropriately found by detecting the first point and the second point around the road link where the number of passages is more than a predetermined threshold. .

  In the poor road detection device according to the present invention, the two-point detection unit is (1) a road that has passed within a predetermined period as travel history data used for detecting the first point and the second point. A link, (2) a road link that has passed a predetermined number of times within a predetermined period, (3) a road link that has passed in the same situation as the present, and (4) a passage that has passed a predetermined number of times in the same situation as the present. (5) Road links that have passed within a predetermined period in the same situation as the present, (6) Road links that have passed a predetermined number of times within the predetermined period in the same situation as now Any of the travel history data may be used.

  By setting the criteria for determining whether or not the road is used regularly by the driver as described in (1) to (6), it is possible to appropriately determine whether or not the road link is used regularly. .

  The poor road detection device of the present invention may include a poor road attribute storage unit that stores poor road attributes detected by the poor detection unit and the number of times of detection.

  Thus, by storing the number of times of detection along with the data of poor road attributes, it is possible to grasp how bad the respective road attributes are.

  The navigation device of the present invention performs a route search from a departure point to a destination using the poor road attribute stored in the poor road attribute storage unit and data of the number of detections thereof in the poor road attribute detection device. It has a configuration. Further, the navigation device of the present invention compares the poor road attribute stored in the poor road attribute storage unit with the poor road attribute detection device described above and the road attribute in front of traveling, and the two match. In such a case, a message alerting the driver may be output. Thus, appropriate route search or route guidance can be performed by making use of the road attribute information that the driver is not good at.

  The poor road attribute detection method of the present invention is a method in which a poor road attribute detection device detects a poor road attribute by a driver based on the travel history data that has passed through each road link stored in the travel history data storage unit. The poor road attribute detection device reads out the travel history data from the travel history storage unit, and the poor road attribute detection device moves from the first point to the second point based on the travel history data. The first point and the second point that are the most frequently used for moving the first route and the second route that is most frequently used for the movement from the second point to the first point are detected. And the poor road attribute detection device reads poor road attribute candidates from a poor candidate storage unit that stores poor road attribute candidates that the driver is not good at, and reads the first route from the second point. There is a road attribute that matches a poor road attribute candidate that is not found in the second route on a road that is traced back to the first point, or the second route from the first point to the second point When there is a road attribute that matches a candidate for a poor road attribute that is not in the first route on a road that is traced back to the point, and when a road attribute that matches the candidate for the poor road attribute is found Detecting the road attribute as a poor road attribute of the driver.

  A program of the present invention is a program for detecting road attributes that a driver is not good on the basis of travel history data that has passed through each road link stored in a travel history data storage unit, and the computer stores the travel history in the computer. The step of reading the travel history data from the storage unit, the first route most frequently used for the movement from the first point to the second point based on the travel history data, and the first from the second point Detecting a first point and a second point which are different in the second route most frequently used for moving to the point, and a weak candidate from the poor candidate storage unit that stores poor road attribute candidates that the driver is not good at Road attributes that read candidate road attributes, and that match candidates for poor road attributes that are not in the second route on roads that follow the first route backward from the second point to the first point Is Alternatively, a search is made as to whether there is a road attribute that matches a poor road attribute candidate not found in the first route on a road that traces the second route backward from the first point to the second point. When a road attribute that matches the poor road attribute candidate is found, the step of detecting the road attribute as a poor road attribute of the driver is executed.

  According to the present invention, it is possible to appropriately find out the road attribute that the driver is not good at from the information of the road that is usually used.

It is a figure which shows the structure of the navigation apparatus of 1st Embodiment. It is a figure which shows the example of the data memorize | stored in weak candidate DB. It is a figure which shows the example of the data memorize | stored in driving | running history DB. It is a figure which shows another example of the data memorize | stored in driving | running history DB. It is a figure which shows the example of the data memorize | stored in the weak road attribute memory | storage part. It is a figure which shows the outline | summary of operation | movement of the poor road attribute detection apparatus of 1st Embodiment. It is a figure which shows the operation | movement of two-point detection by the poor road attribute detection apparatus of 1st Embodiment. (A) It is a figure which shows the example which makes the node branched to a different part in an outward path | route and a return path | route as a 1st point and a 2nd point. (B) It is a figure which shows the example which makes a destination a 2nd point when a path | route differs from the destination. It is a figure which shows the specific operation | movement of a poor road attribute by the poor road attribute detection apparatus of 1st Embodiment. (A) It is a figure which shows the example which may become a weak road attribute depending on a running direction. (B) It is a figure which shows another example which may become a weak road attribute depending on a running direction. (A) It is a figure which shows the example of the data memorize | stored in traveling history DB of the poor road attribute detection apparatus of 2nd Embodiment. (B) It is a figure which shows the example of link ID provided to the road link. It is a figure which shows the operation | movement of two-point detection by the weak road attribute detection apparatus of 2nd Embodiment. It is a figure which shows the data of the passage history for demonstrating the operation | movement of two-point detection by the weak road attribute detection apparatus of 2nd Embodiment. It is a figure which shows the example of the data memorize | stored in driving | running history DB of the poor road attribute detection apparatus of 3rd Embodiment. It is a figure which shows the operation | movement of two-point detection by the poor road attribute detection apparatus of 3rd Embodiment. It is a figure which shows the data of the passage history for demonstrating the operation | movement of two-point detection by the weak road attribute detection apparatus of 3rd Embodiment.

Hereinafter, a poor road attribute detection device and a navigation device having the same according to an embodiment of the present invention will be described with reference to the drawings. In the following description, the road attribute will be mainly described as the road attribute.
(First embodiment)
FIG. 1 is a diagram showing a configuration of a navigation device 10 including a poor road attribute detection device 1 according to the first embodiment of the present invention. The navigation device 10 includes a current position detection unit 12 that detects a current position of a vehicle on which the navigation device 10 is mounted, a map database (hereinafter referred to as “map DB”) 14 having data on road links nationwide, The route search unit 16 searches for the optimum route from the destination to the destination, and the route guide unit 18 guides the route using a screen and voice. As described later, these configurations of the navigation device 10 are basically conventional navigation devices except that control is performed using information on the poor road attribute of the driver obtained by the poor road attribute detection device 1. 10 is the same. Although the navigation device 10 includes other components such as an operation unit for performing an operation and a monitor or a touch monitor for displaying an image, the illustration is omitted.

[Configuration of poor road attribute detection device 1]
The poor road attribute detection device 1 is a calculation control that performs calculation control for obtaining a poor road candidate database (hereinafter, referred to as “weak candidate DB”) 20, a travel history database (hereinafter referred to as “travel history DB”) 22, and poor road attributes. Unit 26 and poor road attribute storage unit 24.

  FIG. 2 is a diagram illustrating an example of data stored in the weak candidate DB 20. The poor candidate DB 20 generally stores road attributes that may be difficult for the driver as “bad road attribute candidates”. In the example illustrated in FIG. 2, “right turn”, “steep right turn”, “one-lane road”, and “road without a sidewalk” are illustrated.

  FIG. 3 is a diagram illustrating an example of data stored in the travel history DB 22. The travel history DB 22 stores the history of each road link through which the vehicle has passed in time series. In addition, at the place where the vehicle stops and the engine is turned off, the data is also stored in association. In the example shown in FIG. 3, it is assumed that the user leaves his home at 9:00 on March 12, 2012, passes the road links L1001, L1002, L1205, L1206, L1102, and L1103, and arrives at the company at 9:08. I understand. Note that the way of holding the data in the travel history DB 22 is not limited to the method of storing the history of the road links that have passed as shown in FIG. Good. This will be described in the second embodiment.

  The arithmetic control unit 26 detects a two-point detecting unit 28 that detects two points (first point and second point) having different routes for going and returning, and a difference between the detected route for the two points and the returning route. And a weakness detection unit 30 for detecting poor road attributes. The arithmetic control unit 26 causes the computer to execute the program, thereby executing the functions of the two-point detection unit 28 and the weak detection unit 30. Such a program is also included in the scope of the present invention.

  The two-point detection unit 28 detects the frequently visited destination (for example, a company, a customer, a bank, a gas station, a supermarket, etc.) and a departure point (for example, a home) when heading there for the first point and the second point. It is determined whether the destination and the departure point can be the first point or the second point by determining whether or not the route is different between going and returning. Of course, even in the case of the same starting point and destination, the route of going and returning is not always the same, but according to the analysis of the inventors, the same starting point and the same destination are If it is, it is known that the road used by the driver will be fixed gradually, so the regular route that is most frequently used for going and returning is treated as the going and returning route.

  If the outbound route and the inbound route are completely different and there is no overlap, the two-point detection unit 28 sets the starting point and the destination as the first point and the second point. In addition, when the forward path and the return path are not completely different, but there are some different parts, the two-point detection unit 28 determines the branch point to the different parts as the first point and the second point. And decide.

  In addition, the two-point detection part 28 is excluded from the detection data of a 1st point and a 2nd point, when there is a stop in either an outward path or a return path. For example, in the example shown in FIG. 4, there is a “supermarket” that is a stopover on the route from the company to the home. In such a case, you go straight from your home to the company, but you think that you are using a different route to stop at the supermarket on your way back. The point is not detected as the second point. This is because when there is a stopover, there is a possibility that the route is not changed on the way to and from the way in order to avoid poor road attributes.

  Next, the weak detection unit 30 will be described. In the following description, the route from the first point to the second point is referred to as “first route”, and the route from the second point to the first point is referred to as “second route”.

  The weakness detection unit 30 searches for a road attribute that matches a poor road attribute candidate not on the second route on a road that traces the first route from the second point to the first point. At the same time, a search is made as to whether or not there is a road attribute that matches a poor road attribute candidate not found in the first route on the road that traces the second route from the first point to the second point. If such a road attribute is found, it is detected as a road attribute that the driver is not good at. The weakness detection unit 30 stores the detected poor road attribute data in the poor road attribute storage unit 24. In the present embodiment, the first route is traced in reverse from the second point to the first point, and the second route is traced in reverse from the first point to the second point. The poor road attribute is searched from both on the road, but it is also possible to search only one of them.

  FIG. 5 is a diagram illustrating an example of data stored in the poor road attribute storage unit 24. As shown in FIG. 5, data on poor road attributes and the number of times of detection are stored. As a result, it is possible to understand what kind of road attribute the driver is not good at, and to grasp the degree to which the road attribute is not good.

[Operation of poor road attribute detection device 1]
FIG. 6 is a flowchart showing an outline of an operation for detecting poor road attributes by the poor road attribute detection device 1. The poor road attribute detection device 1 first reads travel history data from the travel history DB 22 (S10), and based on the travel history data that has been read, detects a first point and a second point that have different routes for going and returning. (S12). This detailed processing will be described later with reference to FIG. In addition, in this process, when a 1st point and a 2nd point are not detected, the operation | movement which detects a weak road attribute is complete | finished.

  Subsequently, the poor road attribute detection device 1 reads poor road attribute candidates from the poor candidate DB 20 (S14). The poor road attribute detection device 1 refers to the poor road attribute candidate data, and based on the first route and the second route that are regularly used between the first point and the second point, The road attribute that is not good at is identified (S16). This detailed processing will be described later with reference to FIG. Then, the poor road attribute detection device 1 stores the identified poor road attribute data in the poor road attribute storage unit 24 (S18).

  FIG. 7 is a flowchart showing the operation of detecting the first point and the second point, and details the operation of step S12 in FIG. The poor road attribute detection device 1 detects a combination of a departure place and a destination that have made a round trip more than a predetermined number of times based on the read travel history data (S20). It is considered that the route to the place where you go frequently is optimized and fixed during long-term driving, but it is necessary to make a round trip more than a predetermined number of times. This is because if there is a situation where the round trip route is different, there may be some reason for this. On the other hand, for example, in the case of a destination that has been performed only once, the optimal route is not well understood, and the route is often changed experimentally on the way back and forth. Since it is difficult to think of changing the route to avoid road attributes, such data is not helpful for the purpose of searching for poor road attributes.

  Next, the poor road attribute detection device 1 identifies the most frequently used outbound route and return route between the departure point and the destination based on the travel history data (S22). The poor road attribute detection device 1 determines whether or not there is a difference between the most frequently used outbound route and the returning route (S24). If there is no different portion between the forward path and the return path (NO in S24), the operation of detecting the first point and the second point ends.

  If there is a difference between the outbound path and the inbound path, the poor road attribute detection device 1 determines whether or not there is a stop on a path that passes only on the outbound path or the inbound path (S26). If there is a stopover (YES in S26), the operation of detecting the first point and the second point ends. When there is no stopover (NO in S26), as shown in FIG. 8 (a), the poor road attribute detection device 1 sets the node branching to different parts in the forward path and the return path as the first point, (S28). If the route is different from the starting point and destination, not the middle of the route, the starting point and destination are set as the first point and the second point (S28). FIG. 8B is a diagram illustrating an example in which the outbound route and the route differ from the destination. In this case, the destination is the second point. Of course, in the case of completely different routes in which the outbound route and the inbound route do not overlap at all, the starting point is the first point and the destination is the second point.

  FIG. 9 is a flowchart showing an operation for identifying poor road attributes, and details the operation in step S16 in FIG. As a premise of the description here, the first route used when going from the first point to the second point and the first route used when going from the second point to the first point by the above-described processing. A first point and a second point that are different from the second route are required.

  The poor road attribute detection device 1 detects whether there is a bad road attribute of the driver on the road that follows the first (second) route in reverse. The fact that the road that follows the first (second) route in reverse is not used is because there is a possibility that there is a road attribute that is not good on the road that follows the first (second) route in reverse. Here, first, a description will be given of a case where road attributes that are not good when traced backward on the same road may be obtained.

  FIG. 10 is a diagram showing an example in which the road attributes are not good when traveling in a certain direction but are not good road attributes when traveling in the opposite direction. In the example shown in FIG. 10A, there is a sidewalk on one side of the road, but no sidewalk is provided on the opposite side. When traveling in the direction A, there is a sidewalk, so it is not scary, but when traveling in the direction B, there is no sidewalk, so it may be weak. In the example shown in FIG. 10B, there is a road that turns to the left rear side. When traveling in the direction A, it is okay because it is a left turn, but when traveling in the direction B, it is necessary to make a sharp right turn. As in these examples, even if the road shape is the same, it may fall under the road attribute attributed to the direction of travel, and the driver may have changed the route to avoid the road attribute attributed to it. The road attribute detection device 1 detects poor road attributes by paying attention to a difference in route.

  This will be described with reference to FIG. The poor road attribute detecting device 1 collates data of poor road attribute candidates, so that roads that follow the first route in reverse and roads that match poor road attribute candidates from the roads of the second route. An attribute is detected (S30). Subsequently, the poor road attribute detection device 1 determines whether there is a poor road attribute candidate that is present on the road following the first route and is not present on the road of the second route (S32). As a result, if there is a poor road attribute candidate that exists only on the road that follows the first route in the reverse direction (YES in S32), the poor road attribute candidate is specified as the poor road attribute of the driver (S34).

  Next, the poor road attribute detection device 1 performs the same processing as described above for the road that traces the second route in the reverse direction. That is, the poor road attribute detection device 1 matches the poor road attribute candidates from the roads that follow the second route and the roads of the first route by collating with the weak road attribute candidate data. The road attribute to be detected is detected (S36). Subsequently, the poor road attribute detection device 1 determines whether there is a poor road attribute candidate that is present on the road that follows the second route and is not present on the road of the first route (S38). As a result, when there is a poor road attribute candidate that exists only on the road that follows the second route in the reverse direction (YES in S38), the poor road attribute candidate is specified as the poor road attribute of the driver (S40).

[Operation of Navigation Device 10]
Next, the operation of the navigation device 10 using data detected by the poor road attribute detection device 1 and stored in the poor road attribute storage unit 24 will be described. The navigation device 10 performs a route search using the poor road attribute stored in the poor road attribute storage unit 24 and data of the number of times of detection. Specifically, the navigation device 10 performs a route search using the poor road attribute as one of the costs of the road link. At this time, by setting a higher cost for the poor road attribute with a higher number of detections, it becomes possible to search for a route reflecting the degree of weakness, and it becomes difficult to search for a route with a high degree of weakness.

  The navigation device 10 always checks whether the road attribute ahead of the road on which the vehicle is currently traveling matches the poor road attribute, and if it matches the poor road attribute, Output a message to call attention. For example, a message such as “There is a sudden right turn at 100m ahead. Please be careful.” Is output.

  The configuration and operation of the navigation device 10 including the poor road attribute detection device 1 according to the first embodiment have been described above. The poor road attribute detection device 1 according to the present embodiment can detect two points having different routes for going and returning, and appropriately detect the road attribute that the driver is not good at based on the difference between the going and returning routes. .

  In the present embodiment, based on a combination of a frequently visited destination and a departure place to the destination, it is possible to appropriately detect two points having different routes for going and returning.

  The navigation device 10 of the present embodiment can perform appropriate route search and route guidance by using poor road attribute data, and can provide a safe driving environment for the driver.

(Second Embodiment)
Next, a poor road attribute detection apparatus according to the second embodiment of the present invention will be described. The basic configuration of the poor road attribute detection device of the second embodiment is the same as that of the first embodiment (see FIG. 1), but the method of obtaining two points with different routes is different between going and returning. . Hereinafter, the configuration and operation of the poor road attribute detection device according to the second embodiment will be described focusing on differences from the first embodiment.

  FIG. 11A is a diagram illustrating an example of data stored in the travel history DB 22 included in the poor road attribute detection device according to the second embodiment, and FIG. 11B is an example of an ID assigned to a road link. FIG. As shown in FIG. 11B, a link ID is assigned to each road link. A node ID is also attached to a node connecting road links. In this specification, the direction in which the link ID is increased is referred to as an uplink direction, and the opposite is referred to as a downlink direction. The link ID data is stored in the map DB 14. Therefore, it is possible to know the connection between road links by referring to the map DB 14.

  In the travel history DB 22, data on the number of times each road link ID is passed is stored for each passing direction. For example, for the road link with the link ID “L1001”, data indicating that it has passed 50 times in the upward direction and 20 times in the downward direction is stored. The travel history DB 22 also stores the number of times a node connecting road links is passed. In the example shown in FIG. 11A, for the node with the node ID “N101”, the number of times of passing from the road link L1002 to the road link L1003 is 10 times, and the number of times of passing through the road link L2001 from the road link L1002 is 10 times. Data indicating that the number of passes from the road link L1002 to the road link L2002 is 30 is stored. In addition, since the data of the number of times of passing through the node can be calculated from the data of the number of times of passing through the link, the data need not necessarily be stored in the travel history DB 22. However, by storing the number of times the node has passed, the process of restoring the number of times the node has passed can be omitted, and the burden of calculation processing can be reduced.

  Next, the operation of the two-point detection unit 28 will be described. The two-point detection method described below is an example of an algorithm for detecting two points from the travel history data as shown in FIG. 11 (a), and there are various other algorithms for detecting two points. Things can be considered. Therefore, the present invention does not limit the algorithm for obtaining the two points to the content described below.

  The two-point detection unit 28 reads travel history data of road links whose number of passages is equal to or greater than a predetermined threshold from the travel history DB 22 shown in FIG. This is because a road link whose number of passes is less than a predetermined threshold is not a regular road, and does not indicate a road optimized by a driver during a long-term driving, and thus is omitted.

  FIG. 12 is a diagram illustrating the operation of the two-point detection unit 28, and FIG. 13 is a diagram illustrating the number of times the link passes for explaining the operation of the two-point detection unit 28. In FIG. 13, for road links L20111, L2113, and L2202, the number of passages is less than a predetermined threshold value (for example, 10 times), and thus travel history data is not read.

  The two-point detection unit 28 refers to the read travel history data and detects a road link in which the difference in the number of passages in the passage direction is equal to or greater than a predetermined threshold (for example, the difference is 30 times or the ratio is 10 times, etc.) (S50). ). Here, for example, it is assumed that the road link L2012 is detected from the travel history data shown in FIG. The two-point detection unit 28 moves to the road link adjacent in the up direction of the road link that detected the target road link (S52). In this example, the road link L2013 and the road link L2202 are adjacent to each other in the upstream direction of the road link L2012. However, the road link L2202 has a small number of passages and need not be considered. Therefore, focus on the road link L2013.

  The two-point detection unit 28 determines whether or not the difference in the number of passages in the passage direction of the road link of interest is equal to or greater than a predetermined threshold (S54). Here, when the difference in the number of passages in the passing direction is equal to or greater than a predetermined threshold (YES in S54), the link of interest is moved again to the road link adjacent in the upward direction (S52). When the difference in the number of passages due to the passage direction is not equal to or greater than the predetermined threshold (NO in S54), the node that connects the noticed road link and the noticed road link is identified as the node Na. In other words, the fact that the difference in the number of passages is less than the predetermined threshold means that the number of passages was unbalanced between the up and down passages has been corrected in the road link of interest. It can be seen that the connection point with the road link is the branching point of the usual route.

  In the example illustrated in FIG. 13, in the road link L2013, the difference in the number of passages due to the passage direction is equal to or greater than a predetermined threshold value, so attention is paid to the adjacent road link in the upward direction. Here, attention is focused on road links L2014 and L2201. Looking at the number of passages of each road link, for the road link L2014, the difference in the number of passages depending on the passage direction is less than a predetermined threshold, so the node Na that connects the road link L2014 and the road link L2013 is specified (S56).

  The two-point detection unit 28 performs the same processing for the downward direction of the road link L2012 focused first. That is, the two-point detection unit 28 moves the target road link to a road link adjacent in the downward direction of the detected road link (S58). The two-point detection unit 28 determines whether or not the difference in the number of passages in the passage direction of the road link of interest is greater than or equal to a predetermined threshold (S60). Here, when the difference in the number of passages due to the passage direction is greater than or equal to a predetermined threshold (YES in S60), the link of interest is moved again to the road link adjacent in the downward direction (S58). If the difference in the number of passages due to the passage direction is not equal to or greater than the predetermined threshold (NO in S60), the node that connects the noticed road link and the noticed road link is identified as the node Nb (S62).

  In the example shown in FIG. 13, paying attention to the road link L2112 in the downward direction of the road link L2012, and looking at the number of passages of the road link L2112, the difference in the number of passages by the passage direction is greater than or equal to a predetermined threshold value. Further, the target road link is moved to road links L2111 and L3002 in the downward direction. Here, looking at the number of times of passage, since the difference in the number of passages of the road link L2111 is not greater than or equal to a predetermined threshold value, the node connecting the road link L2111 and the road link L2112 is specified as the node Nb.

  Subsequently, the two-point detection unit 28 searches for a regular route passing through the identified nodes Na and Nb (S64). Here, the regular route is a route that can be connected by road links whose number of passages is a predetermined threshold (for example, 30 times) or more. Basically, a route that connects road links focused on to detect the nodes Na and Nb is one of the usual routes. When two regular routes passing through the nodes Na and Nb are found, the two-point detection unit 28 detects the nodes Na and Nb as the first point and the second point.

  In addition, when there is a stop-off place on one of the two regular routes, the nodes Na and Nb are not adopted as the first point and the second point as in the case of the first embodiment. It is. In order to determine whether or not there is a stopover place, it is assumed that the poor road attribute detection device stores data of a destination and a stopover place. Heretofore, the processing for obtaining two points with different going and returning routes by the poor road attribute detecting device of the second embodiment has been described. The poor road attribute detection device according to the second embodiment uses the two points of data to detect poor road attributes as in the first embodiment.

  Similarly to the first embodiment, the poor road attribute detection apparatus according to the second embodiment detects two points with different routes on the way and the way back, and the driver is not good at the difference between the way back and on the way back. Road attributes can be detected appropriately.

  In this embodiment, since the data of the number of times each road link passes is analyzed to obtain two different points on the going and return routes, two points are appropriately detected even when there are no frequent destinations. be able to.

(Third embodiment)
Next, a poor road attribute detection apparatus according to the third embodiment of the present invention will be described. The basic configuration of the poor road attribute detection device of the third embodiment is the same as that of the first embodiment (see FIG. 1), but the method of obtaining two points with different routes is different for going and returning. . Hereinafter, the configuration and operation of the poor road attribute detection device according to the third embodiment will be described focusing on differences from the first embodiment.

  FIG. 14 is a diagram illustrating an example of data stored in the travel history DB 22 included in the poor road attribute detection device according to the third embodiment. In the travel history DB 22, data of the combination of the departure point and the destination when passing through each road link ID and the number of times of passage are stored for each passage direction. For example, for the road link with the link ID “L1001”, in the upward direction, the number of times of passing when going from the home to the office is 50 times, the number of times passing when going from the home to the store is 20 times, and the downward direction Is stored as data that the number of times of going to the home from the company is 50 times and the number of times of going to the home from the store is 20 times.

  Next, the operation of the two-point detection unit 28 will be described. The two-point detection unit 28 reads out the most frequently used combinations of starting points and destinations for each road link from the travel history DB 22 shown in FIG. However, when the maximum number of times of passage is less than a predetermined threshold (for example, 10 times), the road link is not a regular road, so data is not read out.

  FIG. 15 is a diagram illustrating the operation of the two-point detection unit 28, and FIG. 16 is a diagram illustrating combinations of the starting point and the destination in the up and down directions used for explaining the operation of the two-point detection unit 28. In FIG. 16, the road links L20111, L2113, and L2202, and the downlink direction of the road link L2013 and the uplink direction of L2201 and L2203 are less than a predetermined threshold (for example, 10 times). Destination combination data has not been read.

  The two-point detection unit 28 refers to the read travel history data, and detects a road link in which the combination of the starting point and the destination does not match on the up and down sides (S70). Here, for example, it is assumed that the road link L2012 is detected from the travel history data shown in FIG. The two-point detection unit 28 moves to the road link adjacent in the up direction of the road link that detected the target road link (S72). In this example, the road link L2013 and the road link L2202 are adjacent to each other in the upstream direction of the road link L2012. However, the road link L2202 has a small number of passages and need not be considered. Therefore, focus on the road link L2013.

  The two-point detection unit 28 determines whether or not the combination of the departure point and the destination is the same for the up and down road links of interest (S74). Here, if the combination of the departure point and the destination does not match (NO in S74), the link of interest is moved again to the road link adjacent in the upward direction (S72). When the combination of the departure point and the destination coincides with each other in the up and down directions (YES in S74), the node that connects the noticed road link and the noticed road link is identified as the node Na. In other words, if the combination of the starting point and the destination is the same on the up and down sides, the regular road that goes back and forth between the starting point and the destination is the same. Therefore, it can be seen that the connection point with the focused road link is the branching point of the commonly used route.

  In the example shown in FIG. 16, in the road link L2013, the combination of the departure point and the destination does not match in the up and down directions, so attention is paid to the adjacent road link in the up direction. Here, attention is focused on road links L2014 and L2201. Looking at each road link, the road link L2014 specifies the node Na that connects the road link L2014 and the road link L2013 because the combination of the starting point and the destination coincides with each other in the upward and downward directions (S76).

  The two-point detection unit 28 performs the same processing for the downward direction of the road link L2012 focused first. That is, the two-point detection unit 28 moves the target road link to a road link adjacent in the downward direction of the detected road link (S78). The two-point detection unit 28 determines whether or not the road link of interest matches the combination of the starting point and the destination in the up and down directions (S80). Here, if the combination of the departure point and the destination does not match (NO in S80), the link of interest is moved again to the road link adjacent in the downward direction (S78). If the combination of the departure point and the destination coincides with each other on the up and down sides (YES in S80), the node that connects the noticed road link and the noticed road link is identified as the node Nb (S82).

  In the example shown in FIG. 16, paying attention to the road link L2112 in the downward direction of the road link L2012, and looking at this road link L2112, the combination of the starting point and the destination does not match up and down. The target road link is moved to road links L2111 and L3002 in the downward direction. Here, the road link L2111 specifies the node connecting the road link L2111 and the road link L2112 as the node Nb because the combination of the start point and the destination coincides in the up and down directions.

  Subsequently, the two-point detection unit 28 searches for a regular route passing through the identified nodes Na and Nb (S84). Here, the regular route is a route that can be connected by road links whose number of passages is a predetermined threshold (for example, 30 times) or more. Basically, a route that connects road links focused on to detect the nodes Na and Nb is one of the usual routes. When two regular routes passing through the nodes Na and Nb are found, the two-point detection unit 28 detects the nodes Na and Nb as the first point and the second point.

  In addition, when there is a stop-off place on one of the two regular routes, the nodes Na and Nb are not adopted as the first point and the second point as in the case of the first embodiment. It is. In order to determine whether or not there is a stopover place, it is assumed that the poor road attribute detection device stores data of a destination and a stopover place. In the above, the process which calculates | requires two points | pieces from which the path | route of a return and a return is different was demonstrated with the weak road attribute detection apparatus of 3rd Embodiment. The poor road attribute detection device according to the third embodiment uses the two points of data to detect poor road attributes as in the first embodiment.

  Similarly to the first embodiment, the poor road attribute detection device according to the third embodiment detects two points with different routes on the way and the way back, and the driver is not good at the difference between the way back and on the way back. Road attributes can be detected appropriately.

  In the present embodiment, the example of using the combination of the starting point and the destination having the highest number of times of travel among the combinations of the starting point and the destination has been described, but in addition to the combination of the most starting point and the destination, It is good also as using the combination of the departure place and destination which have the driving | running results more than a predetermined threshold value.

  As mentioned above, although the poor road attribute detection apparatus of this invention and the navigation apparatus provided with this were demonstrated in detail, giving embodiment, this invention is not limited to embodiment mentioned above.

  In 2nd Embodiment mentioned above, although the example which calculates | requires a 1st point and a 2nd point based on the road link where the difference in the frequency | count of a passage by a passage direction is more than a predetermined threshold was demonstrated, Even if the difference is a road link with a predetermined threshold value or more, if the smaller number of passes is greater than or equal to the predetermined number of passes (for example, 10 times or more), it is determined that there is no weak road attribute. The road link may be excluded from detection targets of poor road attributes.

  In the above-described embodiment, the two-point detection unit 28 may exclude the first point and the second point even when there is a one-way road link on either the forward path or the return path.

  In the second embodiment described above, the two-point detection unit 28 reads the travel history data of road links whose number of passages is equal to or greater than a predetermined threshold from the travel history DB 22, but simply based on the total number of passages. Instead of deciding whether or not to read the travel history data, a road link used for detecting poor road attributes may be decided according to the condition of the number of passages for each period or situation. For example, (1) a road link that has passed within a predetermined period, (2) a road link that has passed a predetermined number of times within a predetermined period, and (3) a road link that has passed in the same situation as the present Road links, (4) Road links that have passed more than a predetermined number of times in the same situation as the current situation, (5) Road links that have passed within the prescribed period in the same situation as the current situation, (6) The same situation as now It is possible to use any travel history data of road links that have passed a predetermined number of times within a predetermined period. In order to enable such processing, the travel history DB 22 may store the date and time data passing through each road link and the situation data when passing through each road link in association with each other. In this way, it is possible to appropriately determine whether or not the road is a regular road by the driver by reading the travel history data of the road link whose number of passages is equal to or greater than a predetermined threshold after specifying the period and situation.

  In the above-described embodiment, the road shape is taken up as an example of the road attribute. However, road attributes other than the road shape, such as school roads, roads that are easily congested, and large vehicles such as trucks and buses often pass. It is also possible to detect poor road attributes for features such as roads to be used. In order to detect such a feature as a poor road attribute, the feature of the road is also stored in the map DB. As a result, as in the above-described embodiment, a road attribute that is used when going back (return) is traced in reverse, but a road attribute that is not included in the return (going) path can be found.

  In the above-described embodiment, the example of the navigation device 10 that uses poor road attribute data obtained by the poor road attribute detection device for route search and route guidance has been described. However, poor road attribute data is used for other purposes. It is also possible to do. For example, by collecting weak road attribute data, it can be used for future road planning.

  INDUSTRIAL APPLICABILITY The present invention has an effect that it is possible to appropriately find out road attributes that a driver is not good at from information on roads that are usually used, and is useful for a navigation device or the like.

1 poor road attribute detection device 10 navigation device 12 current position detection unit 14 map DB
16 route search unit 18 route guidance unit 20 weak candidate DB
22 Travel history DB
24 poor road attribute storage unit 26 calculation control unit 28 two-point detection unit 30 poor detection unit

Claims (10)

A poor candidate storage unit that stores poor road attribute candidates that the driver is not good at,
A travel history storage unit that stores a travel history passing through each road link;
Based on the travel history data of the road link read from the travel history storage unit, the first route most frequently used for moving from the first point to the second point and the first point from the second point A two-point detection unit that detects a first point and a second point that are different from each other in the second route most frequently used for moving to the point;
A poor road attribute candidate is read from the poor candidate storage unit, and is not on the second route on a road that reversely traces the first route from the second point to the first point. Or a road attribute that does not exist in the first route on a road that traces the second route backward from the first point to the second point. Search for whether there is a road attribute that matches the candidate, and when a road attribute that matches the poor road attribute candidate is found, the poor detection unit that detects the road attribute as a poor road attribute of the driver;
A poor road attribute detecting device.   2. The poor road attribute detection according to claim 1, wherein the two-point detection unit does not detect the first point and the second point when there is a stop on the first route or the second route. apparatus. The travel history storage unit stores data of a departure place and a destination in association with the travel history,
The poor road attribute detection device according to claim 1 or 2, wherein the two-point detection unit starts a search for a first point and a second point from a starting point and a destination. The two-point detection unit is
Based on the data read from the travel history storage unit, a road link having a difference in the number of passages by a predetermined threshold or more depending on the direction of passage is detected, and the first point and the second point around the road link The poor road attribute detection device according to any one of claims 1 to 3, which detects a road.   The two-point detection unit includes (1) a road link that has passed within a predetermined period, and (2) a predetermined period as travel history data used to detect the first point and the second point. (3) A road link that has passed a predetermined number of times, (3) A road link that has passed in the same situation as the present, (4) A road link that has passed a predetermined number of times in the same situation as the present, (5) Any travel history data of a road link that has passed within a predetermined period in the same situation as the present, and (6) a road link that has passed a predetermined number of times within the predetermined period in the same situation as now The travel direction prediction apparatus according to any one of claims 1 to 4.   The poor road attribute detection device according to any one of claims 1 to 5, further comprising a poor road attribute storage unit that stores poor road attributes detected by the poor detection unit and the number of times of detection.   A navigation apparatus for searching for a route from a departure place to a destination using the poor road attribute stored in the poor road attribute storage unit and data of the number of detections thereof in the poor road attribute detection apparatus according to claim 6.   The poor road attribute detection device according to claim 6 compares the poor road attribute stored in the poor road attribute storage unit with the road attribute in front of traveling, and if both match, the driver A navigation device that outputs a message that calls attention to the device. Based on the travel history data that has passed through each road link stored in the travel history data storage unit, a method for detecting a road attribute that the driver is not good at using a poor road attribute detection device,
The poor road attribute detection device reads the travel history data from the travel history storage unit;
Based on the travel history data, the poor road attribute detection device uses the first route most frequently used for moving from the first point to the second point, and from the second point to the first point. Detecting a first point and a second point that are different in the second route most frequently used to move the vehicle,
The poor road attribute detection device reads poor road attribute candidates from a poor candidate storage unit that stores poor road attribute candidates that the driver is not good at, and the first route from the second point to the first point There is a road attribute that matches a candidate for a weak road attribute that is not found in the second route on the road that is traced back to the second route, or the second route from the first point to the second point. If there is a road attribute that matches the poor road attribute candidate not found in the first route on the road traced in reverse, and if a road attribute that matches the poor road attribute candidate is found, the road attribute is found. Detecting as a poor road attribute of the driver,
A poor road attribute detection method comprising: A program for detecting road attributes that the driver is not good on the basis of the travel history data that has passed through each road link stored in the travel history data storage unit,
Reading travel history data from the travel history storage unit;
Based on the travel history data, the most frequently used first route for moving from the first point to the second point and the most used for moving from the second point to the first point. Detecting a first point and a second point with different second paths;
On the road that reads the poor road attribute candidate from the poor candidate storage unit that stores the poor road attribute candidate that the driver is not good at and follows the first route from the second point to the first point in reverse. There is a road attribute that matches a candidate for a weak road attribute that is not in the second route, or on the road that traces the second route backward from the first point to the second point. A search is made for a road attribute that matches a poor road attribute candidate not found in the first route, and when a road attribute that matches the poor road attribute candidate is found, the road attribute is detected as a poor road attribute of the driver. And steps to
A program that executes

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