JP2005315695A - Device and method for estimating curve curvature - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To precisely extract the same curve section, even in the road configuration in which the deviation in point series data of map information is large, and to permit estimation of the curvature thereof. <P>SOLUTION: A curve section extraction means 12 sets a prescribed section in front of the travel route of the vehicle of one's own, among from the point series data around the vehicle of one's own previewed by a road information preview means 11, as the curve extraction objective section, and extracts, within the curve extraction objective section, the section in which the mean value of the link length, the maximum value or the minimum value of the link length, and the mean value of the link angle satisfy a prescribed condition. A curvature arithmetic means 13 obtains the curvature of the curve section, using the point series data within the curve section extracted by the curve section extraction means 12. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a curve curvature estimation device and a curve curvature estimation method for estimating the curvature of a curve existing in a vehicle travel route using point sequence data of map information handled by an in-vehicle navigation device or the like.

  An in-vehicle navigation device that is mounted on a vehicle and displays a map, sets a travel route, provides route guidance, and the like has been accepted by many users and has been widely spread. In the field of such in-vehicle navigation devices, various research and developments are being actively conducted to realize more convenient additional functions. One example is vehicle travel using point sequence data included in map information. Attempts have been made to calculate the curvature of a curve existing in a route and display it on a navigation screen to assist a driver's driving operation or to use it for automatic control of vehicle behavior (for example, Patent Document 1). reference.).

Patent Document 1 calculates the curvature of a curve indicated by these three points based on the distance between the point sequences using three points existing in front of the vehicle among the point sequence data representing the vehicle travel route. A technique of correcting the calculated curve curvature under a predetermined condition is disclosed.
Japanese Patent Laid-Open No. 11-2528

  However, the point sequence data included in the map information is not arranged in a regular manner according to a certain rule, and the link length that is the interval between the point sequences within the same curve section or adjacent There is a large variation in the link angle, which is the angle formed by the two links. For this reason, in the method of calculating the curvature of the curve using the three points existing in front of the vehicle as in the technique disclosed in Patent Document 1, it is difficult to specify the curve section with high accuracy and the same. In some cases, the curve section is regarded as a plurality of curves, and the curvature of the curve is calculated or displayed on the screen, which not only complicates the processing but also gives the driver an uncomfortable feeling.

  The present invention was devised to solve the above-described problems of the prior art, and the same curve section can be accurately extracted even if the road shape has a large variation in point sequence data. It is an object of the present invention to provide a curve curvature estimation device and a curve curvature estimation method that can estimate the curvature of the curve.

  A curve curvature estimation device according to the present invention estimates the curvature of a curve existing in a vehicle travel route using point sequence data representing a road shape of map information, and a curve segment in the vehicle travel route by a curve segment extraction means. And the curvature calculation means obtains the curvature of the curve section using the point sequence data in the curve section extracted by the curve section extraction means. In particular, in the curve section extraction means, a predetermined section in the vehicle travel route is set as a processing target section, and within this processing target section, an average value of link lengths, which is an interval between two consecutive points, and the link length A section where a maximum value or a minimum value and an average value of link angles, which are angles formed by two adjacent links, satisfy a predetermined condition is extracted as a curve section.

  The curve curvature estimation method according to the present invention estimates the curvature of a curve existing in a vehicle travel route using point sequence data representing the road shape of the map information. In the first step, the vehicle travel route is estimated. The curve section is extracted, and the curvature of the curve section is obtained in the second step using the point sequence data in the curve section extracted in the first step. In particular, in the first step, a predetermined section in the vehicle travel route is set as a processing target section, and within this processing target section, an average link length that is an interval between two consecutive points, and the link length A section where a maximum value or a minimum value and an average value of link angles, which are angles formed by two adjacent links, satisfy a predetermined condition is extracted as a curve section.

  According to the present invention, the curve section is extracted depending on whether the average value of the link length, the maximum or minimum value of the link length, and the average value of the link angle in the processing target section satisfy a predetermined condition. Therefore, the same curve section can be accurately extracted even if the road shape has a large variation in point sequence data. Then, by calculating the curvature of the curve section using the point sequence data in the curve section extracted in this way, the curvature of the curve existing in the vehicle travel route can be estimated with high accuracy without causing complicated processing. Therefore, it is possible to present appropriate information and control the behavior of the vehicle without causing the driver to feel uncomfortable.

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

(First embodiment)
The present invention is realized as one function of an in-vehicle navigation device as shown in FIG. This in-vehicle navigation device is mounted on a vehicle and displays various information useful for driving the vehicle in addition to displaying a map, setting a travel route, route guidance, and the like. The position detection means 2, the map matching means 3, the infrastructure receiver 4, and the road information acquisition means 5 are comprised.

  The map information storage means 1 has a recording medium such as a DVD-ROM (Digital Versatile Disc-Read Only Memory) in which map information is recorded, and necessary map information can be extracted from this recording medium. . Here, the map information is composed of point sequence data representing the road shape and other additional data, and the point sequence data is data of nodes indicating points on the map and data of links connecting between the nodes. It becomes more.

  The own vehicle position detection means 2 detects the current position of the vehicle (own vehicle) on which the in-vehicle navigation device is mounted, and has a GPS antenna 6 that receives a signal sent from a GPS (Global Positioning System) satellite. doing. The own vehicle position detecting means 2 obtains the absolute value and direction of the own vehicle from the GPS signal received by the GPS antenna 6, and based on the output from various sensors such as a geomagnetic sensor, a gyroscope, and a distance sensor. The correct current position of the vehicle is detected by correcting the information obtained by the autonomous navigation.

  The map matching means 3 matches the current position of the own vehicle detected by the own vehicle position detecting means 2 on the corresponding road of the map read from the map information storage means 1.

  The infrastructure receiver 4 receives information from a narrow range of information providing infrastructure such as a beacon installed on the road and a wide range of information providing infrastructure such as FM multiplex broadcasting. Have.

  The road information acquisition means 5 is the map information read from the map information storage means 1 and matched with the vehicle position by the map matching means 3, the information from the information providing infrastructure received by the infrastructure receiver 4, etc. The present invention is realized as one function of the road information acquisition means 5. That is, the road information acquisition means 5 has a function as a curve curvature estimation device that estimates the curvature of a curve existing on the travel route of the host vehicle using point sequence data representing the road shape of the map information. .

  FIG. 2 is a functional block diagram showing an outline of the curve curvature estimation device realized in the road information acquisition means 5 of the in-vehicle navigation device. As shown in FIG. 2, the curve curvature estimation apparatus of the present embodiment includes road information preview means 11, curve section extraction means 12, and curvature calculation means 13.

  The road information preview unit 11 acquires the point sequence data included in the map information around the vehicle position from the map information storage unit 1 and develops the point sequence data.

  The curve section extraction unit 12 extracts a curve section in the travel route of the host vehicle using the point sequence data around the host vehicle position developed by the road information preview unit 11.

  The curvature calculation means 13 obtains the curvature of the curve section using the point sequence data in the curve section in the travel route of the host vehicle extracted by the curve section extraction means 12.

  In the curve curvature estimation apparatus according to the present embodiment, the curvature of a curve existing on the travel route of the host vehicle is estimated by the processing by each of the above means. The information on the curve curvature estimated by the curve curvature estimation device is handled by the road information acquisition means 5 of the in-vehicle navigation device as information useful for driving the vehicle. For example, the information is displayed on the navigation screen and displayed on the navigation screen. It is used for the purpose of assisting the vehicle and for the automatic control of the vehicle behavior.

  Here, the outline of the processing of the characteristic curve section extraction means 12 in the curve curvature estimation apparatus of the present embodiment as described above will be briefly described.

  Since the map information handled by the current in-vehicle navigation device is basically created as data for map display, it has a structure in which point sequences representing road shapes are regularly plotted according to a certain rule. Absent. However, the link length, which is the distance between two consecutive nodes (the length of the link connecting the two nodes), and the angle formed by two adjacent links (the angle formed by the extension of the previous link and the following link) ), The link length tends to be shorter and the link angle is larger as the curve has a smaller curvature. Therefore, in the curve curvature estimation apparatus of the present embodiment, the curve section extraction unit 12 sets a predetermined section on the travel route of the vehicle as a curve extraction target section (processing target section), and the link length of the curve extraction target section is within this curve extraction target section. By extracting a section where the average value, the maximum or minimum value of the link length, and the average value of the link angle satisfy a predetermined condition as a curve section, the curve section can be extracted with high accuracy. Yes.

  Specifically, for example, the extraction of a curve section starting from P1 in FIG. 3 is performed by using sections (P1 to Pn) constituted by point sequences within a predetermined distance L from the start point P1 as curve extraction target sections. First, the average value of the link length (L1 in FIG. 3) in the longest section (P1 to Pn) of this curve extraction target section, the maximum or minimum value of the link length, the link angle (in FIG. 3) It is determined whether the average value of θ1. Then, the end points of the sections are sequentially moved to the point sequence on the vehicle position side one by one until a predetermined condition is satisfied, and a section that satisfies the predetermined condition is extracted as a curve section. If the number of nodes in the section is 2 or less without satisfying the predetermined condition, it is determined that the curve extraction target section has no curve. In the example illustrated in FIG. 3, the sections P1 to Pn−1 are extracted as curve sections.

  It should be noted that the extraction of the curve section as described above is desirably performed for each curvature level (curve size) of the curve to be extracted. For example, the curvature level of the curve to be extracted is divided into three stages of small R (100R or less), medium R (100R to 300R), and large R (300R to 500R). If the curve segment extraction determination is performed in the order of large R, the curve segment can be extracted more accurately. In this case, assuming that the point sequence data of the travel route of the host vehicle is previewed as shown in FIG. 4, for example, the section P1 to P4 is extracted as a large R curve section, and the section P5 to P9 is a small R section. It will be extracted as a curve section.

  Next, an example of control in the curve curvature estimation apparatus of the present embodiment will be described with reference to the flowcharts of FIGS. In addition, this control is called from the main program of the vehicle-mounted navigation device at regular time intervals (for example, 100 ms) and is repeatedly executed.

  First, the flow of control of the entire curve curvature estimation apparatus of this embodiment will be described with reference to FIG.

  In step S111, the road information preview unit 11 acquires point sequence data around the vehicle position from the map information storage unit 1 of the in-vehicle navigation device, and previews the acquired point sequence data.

Next, in step S112, the curve section extraction means 12 sets the _start point P _start of the first curve extraction target section on the travel route of the own vehicle to the own vehicle position from the point sequence data previewed by the road information preview means 11. It is determined at a close point (P1 in the example shown in FIG. 3). In step S113, an _end point P _end of the curve extraction target section is determined, and a section between the _start point P _start and the end point P _end is set as the curve extraction target section. Details of the process for determining the _end point P _end of the curve extraction target section in step S113 will be described later with reference to FIG.

  Next, in step S114, small R curve sections having a radius of curvature of about 100R or less are extracted within the set curve extraction target section. If a small R curve section is extracted here, the process proceeds to step S117. On the other hand, if the small R curve section is not extracted, in the next step S115, the middle R curve section is extracted with a radius of curvature of approximately 100R to 300R, and if the middle R curve section is extracted, the process proceeds to step S117. On the other hand, if the middle R curve section is not extracted, a large R curve section having a radius of curvature of approximately 300R to 500R is extracted in the next step S116. If a large R curve section is extracted, the process proceeds to step S117. If a large R curve section is not extracted, the process proceeds to step S118.

  As described above, in the curve curvature estimation apparatus of the present embodiment, the curve section extraction unit 12 extracts the curve section for each curvature level (curve size) of the curve to be extracted. The curve sections are extracted in the order of the medium R curve section and the large R curve section from the small R curve section having a small curvature radius, which is highly necessary for display and vehicle behavior control. Details of the process of extracting the curve section in steps S114 to S116 will be described later with reference to FIGS.

  In step S117, the curvature calculation means 13 calculates the curve curvature using the point sequence data in the curve section extracted in any of steps S114 to S116. Specifically, for example, the curve curvature R is calculated by the following equation (1) using the link length and link angle of each link in the extracted curve section. Note that LS in the following equation (1) is the sum of the link lengths in the extracted curve section (L1 +... + Ln−2 in the example shown in FIG. 3), and θS is the link angle in the extracted curve section. The sum is (θ1 +... Θn−1 in the example shown in FIG. 3).

R = LS / θS (1)
In step S118, the curve section extraction unit 12 moves the _start point P _start of the curve extraction target section to the next point. As a method of moving the _start point P _start , as in the example shown in FIG. 4, when the end of the curve section (P1 to P4, P5 to P9) is divided by a straight line, in this example, P1 is followed by P4, You may make it move to the terminal of the end of a curve area like P6 next to P5. Similarly, when the turning direction changes in the S-curve or when the curve section is divided by other factors such as an intersection, the _start point P _start of the next curve extraction target section is moved to the end of the curve section. It may be.

On the other hand, as shown in FIG. 10, when the curve section is extracted for a long curve, the end point of the curve extraction target section starting from P1 exceeds the distance upper limit L in Pn. It is also assumed that the curve sections to be set and extracted are P1 to Pn-1 as the curve extraction target sections as they are. Thus, when the end of the curve section is limited by the distance upper limit value of the curve extraction target section, the start point P _start of the next curve extraction target section is the next point (P2 in the example shown in FIG. 10). Determined.

Once the _start point P _start of the next curve extraction target section is determined in step S118, next, in step S119, the _start point P _start determined in step S118 is the final point sequence data previewed by the road information preview unit 11 in step S111. It is determined whether or not the end point (the point farthest from the vehicle position on the travel route of the vehicle, Pn in the example shown in FIG. 4), and the _start point P _start determined in step S118 is previewed. If it is not the final end, the process returns to step S113 and the subsequent processing is repeated. Then, when the starting point P _start determined in step S118 becomes the final end of the previewed point sequence data, a series of control flow ends.

Next, details of the process of determining the _end point P _end of the curve extraction target section in step S113 in the flowchart of FIG. 5 will be described with reference to FIG.

When setting the _end point P _end , first, in step S211, the end point candidate P _end ′ of the curve extraction target section is set to the next point of the _start point P _start defined in step S112 or step S118 of FIG. In step S212, the total link length in the section from the _start point P _start to the end point candidate P _end ′ is obtained, and it is determined whether or not this exceeds a predetermined distance upper limit value L. As a result, if the total link length in the section from the _start point P _start to the end point candidate P _end ′ exceeds the distance upper limit value L, the process proceeds to step S216, and if not, the process proceeds to the next step S213.

  Note that the distance upper limit value L used for the determination here is preferably set according to the curvature level (curve size) of the curve to be extracted. Specifically, for example, the distance upper limit L is set to 100 m in the extraction of the small R curve section, and the distance upper limit L is set to 200 m in the extraction of the middle R curve section and the large R curve section.

In step S213, it is determined whether or not the sign of the link angle in the _end point candidate P _end ′ is different from the sign of the link angle at the previous point. As a result, the end point candidate P _{end The 'if} the sign of the link angle in is different from the sign of the link angle at the point just before the end point candidate P _{end The'} is in the turning direction changing point Pc in the S-shaped curve as shown in FIG. 11 The process proceeds to step S217, and if the sign of the link angle in the _end point candidate P _end ′ is equal to the sign of the link angle at the previous point, the process proceeds to the next step S214.

In step S214, it is determined whether or not the number of branches in the _end point candidate P _end ′ is equal to or greater than a predetermined value (eg, 3 or greater). As a result, if the number of branches at the _end point candidate P _end ′ is equal to or greater than a predetermined value, it is determined that the end point candidate P _end ′ is an intersection Px having a complicated shape with five or more roads as shown in FIG. If the number of branches at the _end point candidate P _end ′ is less than the predetermined value, the process proceeds to the next step S215.

In step S215, the end point candidate P _end ′ is moved to the next point, and the process returns to step S212. Then, the _end point candidate P _end ′ is sequentially moved to a position away from the _start point P _start until it is determined Yes in any of steps S212 to S214.

In step S216, if it is determined in step S212 that the total link length in the section from the _start point P _start to the end point candidate P _end ′ exceeds the predetermined distance upper limit L, the end point candidate P _end ′ is determined as the immediately preceding point. The process proceeds to step S217.

In step S217, it is determined whether the number of points (nodes) in the section from the _start point P _start to the end point candidate P _end ′ is 2 or more. As a result, if there are two or more points in the section from the _start point P _start to the end point candidate P _end ′, the end point candidate P _end ′ is set as the _end point P _end of the curve extraction target section in the next step S218. In step S219, a section between the _start point P _start and the end point P _end is set as a curve extraction target section, and the process proceeds to step S114 in the flowchart of FIG.

On the other hand, as a result of the determination in step S217, if the number of points in the section from the _start point P _start to the end point candidate P _end ′ is less than 2, the process proceeds to step S118 in the flowchart of FIG. The _start point P _{start of the} target section is moved to the next point.

  Next, details of the process of extracting the small R curve section in step S114 of the flowchart of FIG. 5 will be described with reference to FIG.

When extracting the small R curve section, first, in step S311, an average link length Lm in the curve extraction target section is obtained, and whether or not the average link length Lm is less than a threshold L _small (for example, 20 m). judge. As a result, if the link length average value Lm is the threshold _{L small} or in a curve extraction target section proceeds to step S315, the process proceeds to the next step S312 if it is less than the threshold value _{L small.}

In step S312, the maximum value L _max of the link length in the curve extraction target section is obtained, and it is determined whether or not this maximum link length value L _max is less than a threshold value L _{small_max} (for example, 30 m). As a result, if the link length maximum value L _max in the curve extraction target section is equal to or _larger than the threshold value L _{small_max} , the process proceeds to step S315, and if it is less than the threshold value L _{small_max} , the process proceeds to the next step S313.

In step S313, an average value θm of link angles in the curve extraction target section is obtained, and it is determined whether or not the absolute value | θm | of the link angle average value exceeds a threshold value θ _small (for example, 10 deg.). As a result, if the absolute value | θm | of the link angle average value in the curve extraction target section is equal to or smaller than the threshold value θ _small , the process proceeds to step S315, and if it exceeds the threshold value θ _small , the process proceeds to the next step S314.

  If all of the above steps S311 to S313 are determined to be Yes and all the conditions of these steps S311 to S313 are satisfied, then in step S314, the section is extracted as a small R curve section. The process proceeds to step S117 in the flowchart of FIG.

On the other hand, if it is determined No in any of steps S311 to S313, the end of the section is moved to a point immediately before the _end point Pend in step S315. In step S316, it is determined whether or not the number of points (nodes) in the section up to the end set in step S315 is two or more. If the number of points in the section is two or more, the process returns to step S311 and step S311 is performed. -The determination in step S313 is repeated. If all the conditions in steps S311 to S313 are not satisfied and the score in the section is less than 2, the process proceeds to step S115 in the flowchart of FIG.

Here, the process of extracting the small R curve section will be specifically described by taking the point sequence data shown in FIG. 3 as an example. First, the curve extraction target section is set to P1 to Pn. The determination of step S311 to step S313 is performed for the section of Pn. As a result, in this example, the link length maximum value L _max (here, Ln−1) exceeds the threshold L _{small_max} (for example, 30 m), so in step S315, the section end is _moved to the point Pn−1 that is one before. Move. Then, the determinations in step S311 to step S313 are performed for the sections P1 to Pn-1. As a result, in this example, the section from P1 to Pn-1 satisfies all the conditions for extracting the small R curve section, so that the section from P1 to Pn-1 is extracted as the small R curve section. Become.

  Next, details of the process of extracting the middle R curve section in step S115 in the flowchart of FIG. 5 will be described with reference to FIG.

When extracting the middle R curve section, first, in step S411, an average value Lm of the link length in the curve extraction target section is obtained, and this link length average value Lm is not less than a threshold value L _small (for example, 20 m) and the threshold value L. It is determined whether it is less than _middle (for example, 30 m). As a result, the link length average value Lm is less than the threshold value _{L small} in curve extraction target section, or if the threshold value _{L middle} or proceeds to step S415, in the next step S412 is less than the threshold value _{L small} and not more than the threshold value _{L middle} move on.

In step S412, the maximum value L _max of the link length in the curve extraction target section is obtained, and it is determined whether or not this maximum link length value L _max is less than a threshold value _{L_middle_max} (for example, 60 m). As a result, if the maximum link length L _max in the curve extraction target section is _greater than or equal to the threshold value _{L_middle_max} , the process proceeds to step S415, and if less than the threshold value _{L_middle_max} , the process proceeds to the next step S413.

Determining whether exceeds the threshold theta _{middle (e.g.,} 5 deg.) | In step S413, the absolute value .theta.m the average value of the link angle in the curve extraction target section, the absolute value of the link angle mean value | .theta.m . As a result, the absolute value of the link angle mean value of the curve extraction target section | .theta.m | proceeds to step S415 if less than the threshold value theta _middle, if exceeding the threshold theta _small proceeds to the next step S414.

  If all of the above steps S411 to S413 are determined as Yes and all the conditions of these steps S411 to S413 are satisfied, then in step S414, the section is extracted as a middle R curve section. The process proceeds to step S117 in the flowchart of FIG.

On the other hand, if it is determined No in any of steps S411 to S413, the end of the section is moved to a point immediately before the _end point Pend in step S415. In step S416, it is determined whether or not the number of points (nodes) in the section up to the terminal end set in step S415 is two or more. If the number of points in the section is two or more, the process returns to step S411, and step S411 is performed. -The determination in step S413 is repeated. If all the conditions in steps S411 to S413 are not satisfied and the score in the section is less than 2, the process proceeds to step S116 in the flowchart of FIG.

  Next, details of the process of extracting the large R curve section in step S116 of the flowchart of FIG. 5 will be described with reference to FIG.

When extracting the large R curve section, first, in step S511, an average value Lm of the link length in the curve extraction target section is obtained, and it is determined whether or not the link length average value Lm is greater than or equal to a threshold _Lmiddle (for example, 30m). judge. As a result, the process proceeds to step S515 if the link length average value Lm in curve extraction target section is smaller than the threshold value _{L middle,} the process proceeds to the next step S512, if the threshold value _{L middle} or higher.

In step S512, the minimum value L _min of the link length in the curve extraction target section is obtained, and it is determined whether or not this minimum link length value L _min exceeds a threshold value L _{large — min} (for example, 20 m). As a result, if the link length minimum value _{L min} of the curve extraction target section is below the threshold value _{L Large_min} proceeds to step S515, if exceeding the threshold value _{L Large_min} proceeds to the next step S513.

In step S513, the average value θm of the link angles in the curve extraction target section is obtained, and it is determined whether or not the absolute value | θm | of the link angle average value is less than a threshold value θ _large (for example, 4.5 degrees). As a result, if the absolute value | θm | of the link angle average value in the curve extraction target section is equal to or _larger than the threshold θ _large , the process proceeds to step S515, and if it is less than the threshold θ _large , the process proceeds to the next step S514.

  If all of the above steps S511 to S513 are determined to be Yes and all of the conditions of these steps S511 to S513 are satisfied, then in step S514, the section is extracted as a large R curve section. The process proceeds to step S117 in the flowchart of FIG.

On the other hand, if it is determined No in any of steps S511 to S513, the end of the section is moved to a point immediately before the _end point Pend in step S515. In step S516, it is determined whether or not the number of points (nodes) in the section up to the end set in step S515 is two or more. If the number of points in the section is two or more, the process returns to step S511, and step S511 is performed. -The determination in step S513 is repeated. If all the conditions in steps S511 to S513 are not satisfied and the score in the section is less than 2, the process proceeds to step S116 in the flowchart of FIG.

As described above, in the curve curvature estimation apparatus according to the present embodiment, the curve section extraction unit 12 extracts a curve section for each curvature level (curve size) of the curve to be extracted. Is extracted depending on whether the link length average value Lm, link length maximum value L _max or link length minimum value L _min , and link angle average value θm within a section satisfy predetermined conditions. The condition for extracting the curve section is set according to the curvature level of the curve to be extracted.

Table 1 below summarizes an example of curve section extraction conditions set for each curvature level of a curve to be extracted.

Among the threshold _values used for the above curve segment extraction, the threshold _values related to the link length (L _small , L _middle , L _{small_max} , L _{middle_max,} L _{large_min} ) are included in the map information stored in the map information storage means 1 It is determined from the trend of how the column data is plotted. In addition, you may make it change the threshold value regarding these link lengths according to the road classification of a curve extraction object area. That is, for example, in the case of an expressway, the interval of the point sequence data tends to be plotted longer, so that the thresholds for the link length average value Lm are set to L _small = 30 m, L _middle = 40 m, and the like. You may make it easy to extract the curve section in an interchange or junction by changing to a larger size. At the same time, threshold values (L _{small_max} , L _{middle_max,} ) for the maximum link length value L _max and threshold values (L _{large_min} ) for the minimum link length value L _min may be changed.

Further, the threshold regarding the link length may be changed according to the number of points constituting the point sequence in the curve extraction target section. For example, when extracting a small R-curve section, since a link length tends to be short in a point sequence constituted by a small number of points as shown in FIG. 13, depending on the number of points constituting the point sequence, The thresholds (L _small , L _{small — max} ) relating to the link length may be changed as follows. In addition to this, the threshold value related to the link angle may be changed.

Number of points constituting the point sequence = 3 → L _small = 20 m, L _{small_max} = 20 m
Number of points constituting the point sequence = 2 → L _small = 15 m, L _{small_max} = 20 m
Of the threshold values used for curve section extraction, the threshold values related to the link angle (θ _small , θ _middle , θ _large ) are determined by the threshold value related to the link length and the curvature level of the curve to be extracted. For example, when extracting a small R curve section, a sector central angle having a threshold L _small (for example, 20 m) with respect to the link length average value Lm as the arc length and a radius of the maximum curvature radius (100 m) of the small R curve section as a radius. As a result, 11.5 deg. Therefore, considering the plot variation of the point sequence data, the threshold θ _{small with} respect to the link angle average value θm is, for example, 10 deg. It is determined. Similarly, the threshold θ _middle for the link angle average value θm in the case of extracting the middle R curve section is, for example, 5 deg. The threshold θ _{large with} respect to the link angle average value θm when extracting a large R curve section is, for example, 4.5 deg. It is determined.

  As described above, in the curve curvature estimation apparatus according to the present embodiment, the curve section extraction unit 12 sets a predetermined section on the travel route of the host vehicle as a curve extraction target section, and within this curve extraction target section, the link length Since the section where the average value, the maximum or minimum value of the link length, and the average value of the link angle satisfy the predetermined condition is extracted as the curve section, the variation of the point sequence data increases. Even in such a road shape, the curve section can be extracted with high accuracy. Since the curvature calculation means 13 obtains the curvature of the curve section using the point sequence data in the curve section extracted in this way, it exists in the vehicle travel route without causing complication of processing. It is possible to estimate the curvature of the curve to be performed with high accuracy, and to perform appropriate information presentation and vehicle behavior control without causing the driver to feel uncomfortable.

(Second Embodiment)
Next, a second embodiment of the present invention will be described. The present embodiment is characterized in that the curve section extracting means 12 sets the _end point P _end of the curve extraction target section. That is, in the first embodiment described above, when there is a point where the sign of the link angle is different from the sign of the link angle at the immediately preceding point between the _start point P _start of the curve extraction target section and the predetermined distance L, that point Is set to the _end point P _end of the curve extraction target section. In this embodiment, three consecutive points (first point, point) from the _start point P _start of the curve extraction target section to the predetermined distance L are set. The sign of the link angle at the first point is different from the sign of the link angle at the second point, and the sign of the link angle at the second point is the third point. The second point is set to the _end point P _end of the curve extraction target section when the link angle has the same sign as the link angle. Note that the basic configuration and control outline of the curve curvature estimation apparatus of the present embodiment are the same as those of the first embodiment described above, and therefore, the same portions as those of the first embodiment are described here. Omitted, only the parts characteristic of this embodiment will be described.

In the present embodiment, for example, as shown in FIG. 14 or FIG. 15, it corresponds to a case where there is a point whose position varies with respect to the center line of the road in the point sequence representing the travel route of the own vehicle. Therefore, it is possible to appropriately set the curve extraction target section. That is, in the point sequence data included in the map information, for example, a point Pn in FIG. 14 or FIG. 15 is plotted with a shift of one point inside the curve in the point sequence of the same curve section. There is. At this time, using the fact that the sign of the link angle θn at the point Pn is different from the signs of the link angles θn−1 and θn + 1 at the preceding and subsequent points Pn−1 and Pn + 1, the turning direction of the S-shaped curve shown in FIG. In this case, the point Pn is not set as the _end point Pend of the curve extraction target section.

  Here, the outline of the processing of the characteristic part of the curve curvature estimation apparatus of the present embodiment will be described with reference to the flowchart of FIG. This process is executed in place of the process in step S213 in the flowchart of FIG.

Assuming that the _end point candidate P _end ′ of the curve extraction target section is a point Pn, first, in step S611, the link angle θn at the point Pn is the link angle θn−1 at the point Pn−1 immediately before the point Pn. It is determined whether or not the sign is different. When the sign of the link angle θn is different from the sign of θn−1, in the next step S612, the sign of the link angle θn at this point Pn is the link at the point Pn + 1 that is one point after the point Pn. It is determined whether or not the sign of the angle θn + 1 is different.

  If it is determined Yes in step S611 and No in step S612, the point Pn can be determined as a turning direction change point of the S-shaped curve as shown in FIG. 11, and thus the process proceeds to step S614. On the other hand, when it is determined Yes in both step S611 and step S612, the point Pn is not the turning direction change point of the S-shaped curve, but is located with respect to the center line of the road in the point sequence of the same curve section. Therefore, the process proceeds to the next step S613.

In step S613, in order to determine whether or not the point Pn is a curve exit point as shown in FIG. 15, is the link length Ln that is the interval between the point Pn and the point Pn + 1 less than a predetermined value? For example, it is determined whether or not the link length Ln is less than the thresholds (L _{small_max} , L _{middle_max,} ) for the link length maximum value L _max used in the curve section extraction. As a result, if the link length Ln is less than the predetermined value, it can be determined that the point Pn is not a turning point change point of the S-shaped curve and is not a curve exit point. without setting a P _{end the,} moves on to the next process (step S214 in the flowchart of FIG. 6). On the other hand, if the link length Ln is equal to or greater than the predetermined value, the point Pn can be determined to be a curve exit point, and the process proceeds to step S614.

In step S614, the point Pn is set as the _end point P _end of the curve extraction target section. Through the above processing, in the present embodiment, a curve extraction target section having the _end point Pend as the turning point of the turning direction of the S-shaped curve or the point at the curve exit is set while eliminating the influence due to the variation in the plot of the point sequence data. It is possible to extract the curve section with higher accuracy.

(Third embodiment)
Next, a third embodiment of the present invention will be described. The present embodiment is characterized in that it includes a curve section correcting means for correcting the curve section extracted by the curve section extracting means 12. Note that the basic configuration and control outline of the curve curvature estimation apparatus of the present embodiment are the same as those of the first and second embodiments described above, so here the same parts as those of the first and second embodiments. The description which overlaps is abbreviate | omitted and only the characteristic part of this embodiment is demonstrated.

  In the present embodiment, as shown in FIG. 17, it is assumed that the straight line portion may be extracted as a part of the curve section when the straight line distance between the curves is short on a zigzag mountain road or the like. In this case, the curve section extracted by the curve section extraction means 12 is corrected by the curve section correction means so that an appropriate curve section not including a straight line portion can be extracted.

Specifically, in the example shown in FIG. 17, for example, the section from the point P1 to the point Pn-1 is one curve section, but the link length Ln-1 between the point Pn-1 and the next point Pn. Is less than the threshold value (L _{small_max} , L _{middle_max,} ) for the maximum link length L _max of the curve section extraction condition, the curve section extraction means 12 extracts the section from the point P1 to the point Pn as the curve section. Will end up. Therefore, in the present embodiment, the curve section correction unit links the start point (P1) to the point (Pn-1) immediately before the end point (Pn) among the curve sections extracted by the curve section extraction unit 12. When the link length (Ln-1) at the end of the curve section is longer than the link length average value by a predetermined length or more with respect to the link length average value, the end point (Pn) of the curve section extracted by the curve section extraction means 12 is obtained. Is corrected to the previous point (Pn-1) with respect to the vehicle position. Thereby, also in the example shown in FIG. 17, the section from the point P1 to the point Pn-1 can be accurately extracted as the curve section.

  Here, an outline of processing by the curve section correcting means characteristic of the curve curvature estimation apparatus of the present embodiment will be described with reference to the flowchart of FIG. This process is executed as a pre-process of the process in step S117 in the flowchart of FIG.

  If the section from the point P1 to the point Pn is extracted as the curve section by the curve section extraction unit 12, the curve section correction unit firstly, in step S711, immediately before the start point P1 to the end point Pn of the extracted curve section. The link length average value Lm (n−1) up to the point Pn−1 is obtained by calculation. In step S712, it is determined whether the link length Ln-1 at the end of the curve section satisfies the condition of the following equation (2) with respect to the link length average value Lm (n-1) obtained in step S711. In the following formula (2), K is a constant, and its value is set to a value of 1 or more, for example, 1.5.

K × Lm (n−1) <Ln−1 (2)
Further, in the determination in step S712, the condition of the following formula (3) may be used instead of the above formula (2). In the following formula (3), C is a constant value, for example, 10 m.

Lm (n-1) + C <Ln-1 (3)
If it is determined in step S712 that the link length Ln-1 at the end of the curve section satisfies the above conditions, the curve extracted by the curve section extraction unit 12 in step S713 is then executed. The end point Pn of the section is corrected to the point Pn-1 one before the own vehicle position. On the other hand, when the link length Ln-1 at the end of the curve section does not satisfy the condition, the process ends without correcting the curve section. With the above processing, in this embodiment, curve sections can be extracted with high accuracy even in road conditions where the straight line distance between curves is short.

It is a block diagram which shows the structure of a vehicle-mounted navigation apparatus. It is a functional block diagram which shows the structure of the curve curvature estimation apparatus implement | achieved as one function of a vehicle-mounted navigation apparatus. It is a figure explaining the outline | summary of the process which extracts a curve area, and is a schematic diagram which shows an example of the previewed point sequence data. It is a figure explaining the outline | summary of the process which extracts a curve area, and is a schematic diagram which shows the other example of the point sequence data previewed. It is a flowchart which shows the flow of the whole control of the curve curvature estimation apparatus to which this invention is applied. It is a flowchart which shows the flow of the process which determines the end point of a curve extraction object area. It is a flowchart which shows the flow of the process which extracts the small R curve area with a small curvature level. It is a flowchart which shows the flow of the process which extracts a medium R curve area with a medium curvature level. It is a flowchart which shows the flow of the process which extracts the large R curve area with a large curvature level. It is a figure explaining the process in the case of extracting a curve section with respect to a long curve, and is a schematic diagram which shows the further another example of the point sequence data previewed. It is a figure explaining the curve area extraction process in the case of S character curve, and is a mimetic diagram showing other examples of the point sequence data previewed. It is a figure explaining the process in the case of extracting a curve section with respect to the road containing an intersection, and is a schematic diagram which shows the other example of the point sequence data previewed. It is a figure explaining the curve section extraction process in case it is comprised by the point with few point sequences of a curve extraction object area, and is a schematic diagram which shows the other example of the previewed point sequence data. It is a figure explaining the curve section extraction process in case the position of the point in the point sequence showing the driving route of the own vehicle varies in position with respect to the center line of the road. It is a schematic diagram which shows another example. It is a figure explaining the curve section extraction processing when the position of the point that becomes the curve exit varies from the center line of the road in the point sequence that represents the travel route of the vehicle, It is a schematic diagram which shows the other example of column data. It is a flowchart which shows the flow of the process which sets the end point of the curve extraction object area characteristic to 2nd Embodiment. It is a figure explaining the process which corrects the curve area extracted when the straight line distance between curves is short, and is a schematic diagram which shows the other example of the point sequence data previewed. It is a flowchart which shows the flow of the curve area correction process characteristic of 3rd Embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 1 Map information storage means 5 Road information acquisition means 11 Road information preview means 12 Curve area extraction means 13 Curvature calculation means

Claims (11)

A curve curvature estimation device that estimates the curvature of a curve existing in a vehicle travel route using point sequence data representing a road shape of map information,
A predetermined section in the vehicle travel route is set as a processing target section, and within this processing target section, an average value of link lengths, which is an interval between two consecutive points, and the maximum value or minimum value of the link length are adjacent to each other. A curve section extracting means for extracting a section in which an average value of link angles, which are angles formed by two links, satisfies a predetermined condition as a curve section;
A curve curvature estimation apparatus comprising: curvature calculation means for obtaining curvature of the curve section using point sequence data in the curve section extracted by the curve section extraction means.   2. The curve curvature estimation apparatus according to claim 1, wherein the curve section extraction unit sets the predetermined condition according to a size of a curve to be extracted.   The curve curvature estimation device according to claim 2, wherein the curve section extraction unit sets the predetermined condition according to a size of a curve to be extracted and a road type of the processing target section. .   3. The curve section extracting unit sets the predetermined condition according to a size of a curve to be extracted and a number of points constituting a point sequence in the processing target section. The curve curvature estimation apparatus described in 1.   The curve section extracting means starts from an arbitrary point in front of the vehicle, sets a point within a predetermined distance along the vehicle travel route from the start point, and sets a section between the start point and the end point as the processing target section. The curve curvature estimation apparatus according to claim 1, wherein the curve curvature estimation apparatus is set as follows.   6. The curve curvature estimation apparatus according to claim 5, wherein the curve section extraction unit sets the predetermined distance according to a size of a curve to be extracted.   If there is a point having a predetermined number of branches or more between the starting point and a point separated by a predetermined distance along the vehicle travel route, the curve section extracting means determines this point as the end point of the processing target section. The curve curvature estimation apparatus according to claim 5, wherein the curve curvature estimation apparatus is set as follows.   If there is a point where the sign of the link angle is different from the sign of the link angle at the immediately preceding point between the start point and a point that is separated by a predetermined distance along the vehicle travel route, 7. The curve curvature estimation apparatus according to claim 5, wherein a point is set as an end point of the processing target section.   The curve section extracting means includes first to third consecutive three points existing between the starting point and a point separated by a predetermined distance along the vehicle travel route, and the sign of the link angle at the first point is Unlike the sign of the link angle at the second point, when the sign of the link angle at the second point and the sign of the link angle at the third point are the same, the second point is set as the end point of the processing target section. The curve curvature estimation apparatus according to claim 8, wherein the curve curvature estimation apparatus is set.   In the curve section extracted by the curve section extraction means, the average link length of the section from the start point of the curve section to the point one point before the end point is compared to the point from the point one point before the end point to the end point. The curve curvature estimation according to any one of claims 1 to 9, further comprising: a curve section correcting unit that corrects the end point of the curve section to a point in between when the link length is longer than a predetermined value. apparatus. A curve curvature estimation method for estimating a curvature of a curve existing in a vehicle travel route using point sequence data representing a road shape of map information,
A predetermined section in the vehicle travel route is set as a processing target section, and within this processing target section, an average value of link lengths, which is an interval between two consecutive points, and the maximum value or minimum value of the link length are adjacent to each other. A first step of extracting, as a curve section, a section in which an average value of link angles that are angles formed by two links satisfies a predetermined condition;
And a second step of obtaining a curvature of the curve section using the point sequence data in the curve section extracted in the first step.

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