JP2006030116A - U-turn detecting device and its u-turn detecting method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a U-turn detecting device and its U-turn detecting method capable of determining a U-turn accurately in a short travel distance after start of the U-turn. <P>SOLUTION: A navigation system for detecting the U-turn of a vehicle calculates a turning angle from the turning start position of the vehicle to the present vehicle position, calculates an average curvature in the turning part, and determines that the U-turn has been performed when the turning angle is within a set angle range and the average curvature is smaller than a set curvature. The navigation system stops the U-turn determination when the vehicle exists on a pass. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a U-turn detection device and a U-turn detection method thereof, and more particularly to a U-turn detection device of a navigation system that detects a U-turn of a vehicle and a U-turn detection method thereof.

The navigation device reads map data corresponding to the current position of the vehicle from a map data storage unit such as a DVD or HDD, draws it on the display screen, and moves the vehicle mark on the map according to traveling, or The mark is fixedly displayed at a fixed position on the display screen (for example, the center position of the display screen), and the map is scrolled.
Map data includes (1) a road layer consisting of node data, road link data, intersection data, etc., (2) a background layer for displaying objects on the map, and (3) a name of the city, town, and village. A map image composed of the character layer and the like and displayed on the display screen is generated based on the background layer and the character layer, and map matching processing and guidance route search processing are performed based on the road layer.
In such a navigation device, it is essential to measure the current position of the vehicle. For this reason, conventionally, a measurement method (self-contained navigation) that measures the vehicle position using a distance sensor and an orientation sensor (gyro) mounted on the vehicle, and a measurement method (satellite navigation) using GPS (Global Positioning System) using a satellite A method using both of them has been put into practical use.

  Recent in-vehicle navigation systems use both self-contained navigation and satellite navigation. Normally, the vehicle position and orientation are estimated by self-contained navigation, and the estimated vehicle position is determined by map matching processing (combining pattern matching and projection). Is corrected to obtain the actual vehicle position on the road. If map matching by the pattern matching method becomes impossible for some reason, the map matching process is initialized and the vehicle position is set to the position measured by the GPS or the self-contained navigation position. The map matching process is started, and the estimated vehicle position is corrected to the actual vehicle position on the traveling road.

In the self-contained navigation, the vehicle position is detected by integration based on the outputs of the distance sensor and the relative azimuth sensor as follows. FIG. 9 is an explanatory diagram of a vehicle position detection method based on self-contained navigation. The distance sensor outputs a pulse every time the vehicle travels a certain unit distance L0 (for example, 10 m), and sets a reference direction (θ = 0). The positive direction of the X axis and the counterclockwise direction from the reference azimuth are defined as the + direction. Assuming that the previous vehicle position is point P0 (X0, Y0), the absolute azimuth in the vehicle traveling direction at point P0 is θ0, and the output of the relative azimuth sensor at the time of traveling the unit distance L0 is Δθ1, the change in the vehicle position Minutes
ΔX = L0 · cos (θ0 + Δθ1)
ΔY = L0 · sin (θ0 + Δθ1)
The estimated direction θ1 of the vehicle traveling direction and the estimated vehicle position (X1, Y1) at the current point P1 are
θ1 = θ0 + Δθ1 (1)
X1 = X0 + ΔX = X0 + L0 · cosθ1 (2)
Y1 = Y0 + ΔY = Y0 + L0 · sinθ1 (3)
Can be calculated by vector synthesis. Therefore, if the absolute azimuth and position coordinates of the vehicle at the start point are given by GPS, the vehicle position is detected in real time by repeating the calculations of equations (1) to (3) each time the vehicle travels a unit distance thereafter. (Estimated).

However, in self-contained navigation, errors accumulate as the vehicle travels, and the estimated vehicle position deviates from the road. Therefore, the estimated vehicle position is collated with the road data by map matching processing to correct the actual vehicle position on the road.
FIG. 10 is an explanatory diagram of map matching by the projection method. It is assumed that the current vehicle position is at a point Pi-1 (Xi-1, Yi-1) and the vehicle direction is θi-1 (in the figure, the point Pi-1 does not coincide with the road RDa). If the relative azimuth when traveling a certain distance L0 (for example, 10 m) from the point Pi-1 is Δθi, the estimated vehicle position Pi ′ (Xi ′, Yi ′) by self-contained navigation and the estimated vehicle azimuth θi at Pi ′ are And the following equation θi = θi−1 + Δθi
Xi ′ = Xi−1 + L0 · cos θi
Yi ′ = Yi−1 + L0 · sinθi
Is required.

At this time, (a) a link (element constituting a road) that is included in a 200 m square with the estimated vehicle position Pi ′ as the center and that can be lowered, and the estimated vehicle direction at the estimated vehicle position Pi ′ A search is made for the angle formed by θi and the link within a certain value (for example, within 450), and the length of the perpendicular dropped from the estimated vehicle position Pi ′ to the link within a certain distance (for example, 100 m). Here, the link LKa1 (straight line connecting the nodes Na0 and Na1) on the road RDa and the link LKb1 (straight line connecting the nodes Nb0 and Nb1) on the road RDb. Next, (b) the lengths of the perpendicular lines RLia and RLib dropped from the estimated vehicle position Pi ′ to the links LKa1 and LKb1 are obtained. (c) After that, Z = dL ・ 20 ＋ dθ ・ 20 (dθ ≦ 250) (4)
Z = dL ・ 20 ＋ dθ ・ 40 (dθ> 250) (4) ′
The coefficient Z is calculated by DL is the length of the perpendicular line from the estimated vehicle position Pi ′ to the link (distance from the estimated vehicle position to the link), dθ is the angle formed by the estimated vehicle direction θi and the link, and the larger the angle dθ, the more the weight coefficient Has increased.

(d) Once the coefficient value Z is obtained, the following conditions 1), 2), 3)
1) Distance dL ≦ 75m (maximum attraction distance 75m)
2) Angular difference dθ ≦ 300 (maximum attraction angle 300)
3) Coefficient value Z ≦ 1500
A link satisfying the above is obtained, and a link having the smallest coefficient value is set as a matching candidate (optimum road). Here, the link LKa1 is obtained. (e) Then, the traveling locus SHi connecting the point Pi-1 and the point Pi ′ is translated in the direction of the perpendicular line RLia until the point Pi-1 is on the link LKa1 (or on the extension line of the link LKa1). −1 and Pi ′ are obtained as moving points PTi-1 and PTi ′. (F) Finally, the point PTi-1 is rotated around the point PTi-1 until it is on the link LKa1 (or on the extension line of the link LKa1). Thus, the moving point is obtained and set as the actual vehicle position Pi (Xi, Yi). Note that the vehicle orientation at the actual vehicle position Pi remains θi. Further, as shown in FIG. 11, when the point Pi-1 that is the previous vehicle position is on the road RDa, the moving point PTi-1 coincides with the point Pi-1.

12 to 14 are explanatory diagrams of map matching by pattern matching. The pattern matching method saves the travel locus (position and orientation by self-contained navigation for each predetermined travel distance), obtains a road on the same map as the travel locus, and maps the vehicle mark to the points on the road It is a method to make it. When matching the travel locus pattern and the candidate road pattern, as shown in FIG. 12A, the pattern of the travel locus LP is approximated by a polygonal line, and candidate roads existing in a predetermined area around the vehicle are displayed. Ask. Then, the pattern of each candidate road RP is similarly approximated by a broken line by an equal-length line segment as shown in FIG. Next, as shown in FIG. 13, the traveling locus LP ′ is translated so that the leading position of the traveling locus LP ′ approximated to the broken line comes to the leading position of the candidate road RP ′ approximated to the broken line. It rotates by a predetermined angle θ (initially 0 ⁰ ). In this state, the sum of the distances between corresponding points (pi, qi) and (lI, mi) between the road RP 'and the travel locus LP' is calculated (i = 1, 2,... N). Thereafter, similarly, the total sum of distances is obtained by changing the rotational angle θ, and the rotational angle θm with the smallest total distance Lm is obtained (see FIG. 14). For other candidate roads, the above calculation is performed to determine the sum of distances and the rotation angle. Thereafter, the candidate road having the smallest sum of the distances, that is, the candidate road having the largest correlation is obtained, and after the parallel movement is made so that the traveling locus start point overlaps the head position of the candidate road, the vehicle position is rotated by the rotation angle θm. The map is matched with the candidate road and the process is terminated. From the above, pattern matching is based on obtaining correlation.

  Since the map matching process by the pattern matching method has a large calculation amount, for example, the map matching process is performed every 150 m or every several seconds, and the map matching by the projection method is performed every 10 m or every 0.8 seconds. Since the map matching process by the projection method is performed only locally, once the matching is wrong, the vehicle position is continuously corrected on the wrong road. For this reason, the pattern matching is used together to prevent the map matching from continuing on the wrong road.

FIG. 15 is an explanatory diagram of an initial operation of map matching. Initially, a position measured by GPS is set as a vehicle position P, a rectangular area SQAR of a predetermined size centered on the vehicle position P is set, and a road having a perpendicular foot in the rectangular area is set as a candidate road RDA, Obtained as RDb and let the foot of the perpendicular line be the leading positions Qa and Qb of the candidate road. After that, the position and direction of the vehicle are estimated by self-contained navigation and converted into an isometric vector, and after running a predetermined distance, pattern matching processing is performed to obtain the candidate road RDb having the highest correlation, and the estimated vehicle position P _M on the driving road RDb The actual vehicle position Q _M is corrected. Thereafter, a map matching process using pattern matching and a projection method is performed to correct the vehicle position on the traveling road RDb. If pattern matching becomes impossible, the initial operation is performed. In the initial operation after the pattern matching becomes impossible, the autonomous navigation position is used as the vehicle position P.

  By the way, in the map matching method using both the pattern matching method and the projection method, when the vehicle makes a U-turn, the vehicle position mark is mismatched from the actual traveling road to the wrong road, or the distance until the actual traveling road is matched. There is a problem that it becomes longer and the position accuracy of the own vehicle becomes worse. This is because in pattern matching, only the process of moving the vehicle estimated position forward is performed, so that the correlation value of the pattern matching is deteriorated at the time of the U-turn, and the pattern matching cannot be continued and is finally initialized. FIG. 16 shows an example in which when a U-turn is made before the intersection A while traveling on the road RDa, a mismatch is made with the parallel road RDb 30 to 40 m away from the road RDa. In the figure, the black circle is the locus of the vehicle mark. FIG. 17 shows a case where a U-turn is made at point B while traveling on a straight road RD. The dotted line is the actual self-contained navigation position trajectory, the black circle is the vehicle mark trajectory, and after traveling a long distance to point C after U-turn Matching is initialized and the vehicle mark is finally corrected on the road. From the above, it is necessary to eliminate the mismatching by detecting and initializing the U-turn at an early stage, and to shorten the distance until matching with the actual traveling road.

Several methods have been proposed as conventional techniques for detecting a U-turn. The first prior art determines a U-turn when the vehicle turns more than a predetermined angle (see, for example, Patent Document 1). The second prior art, the vehicle obtains the orientation change amount θ of the road at the current position within a predetermined range before and after, and 3 times the U-turn certification number Ns in the case of the θ, for example, 180 ⁰ or less, 180 ⁰ or more In this case, it is assumed that the vehicle is on a road or interchange, and Ns = 10 times. A U-turn determination is made every 100 m, and it is not heading for the destination within a predetermined time (toward the departure point). It is determined that a U-turn has been made when the number N of times determined is greater than Ns (see, for example, Patent Document 2).
JP-A-8-334357 JP-A-8-145707

Since the first prior art only sees a change in angle, there is a problem that it is easy to make a wrong U-turn determination by turning in a parking lot, turning corner, Internet change, roadway, etc.
In addition, the second prior art has a problem that the travel distance from the U-turn to the completion of the U-turn determination is long.
From the above, an object of the present invention is to enable a U-turn determination accurately with a short travel distance after the start of a U-turn.

  According to the present invention, in the U-turn detection method of the navigation system for detecting the U-turn of the vehicle, the turning angle from the turning start position of the vehicle to the current vehicle position is calculated, and the average curvature at the turning portion is calculated. This is achieved by a U-turn detection method comprising a step of determining that a U-turn has been made when the turning angle is within a set angle range and the average curvature is smaller than the set curvature. The U-turn detection method further includes the step of storing the vehicle direction for each predetermined travel distance, and refers to the stored data to determine the end point of the straight portion of the predetermined length closest to the vehicle current position as the turning start position of the vehicle. It has a step. The U-turn detection method further includes a step of determining that the vehicle exists on the road, and stops the U-turn determination if the vehicle exists on the road.

  According to the present invention, in the U-turn detection device for a navigation system that detects a U-turn of a vehicle, the vehicle position and direction are detected and stored as a travel locus, and the vehicle turning start position is determined from the travel locus. When the turning angle from the turning start position of the vehicle to the current vehicle position is calculated, the average curvature at the turning portion is calculated, the turning angle is within the set angle range, and the average curvature is smaller than the set curvature This is achieved by providing a U-turn determination means for determining that a U-turn has been made. The U-turn determining means refers to the travel locus and sets the end point of the straight portion having a predetermined length closest to the current vehicle position as the turning start position of the vehicle. Further, the U-turn determination means stops the U-turn determination process when the vehicle exists on the road.

According to the present invention, the turning angle from the turning start position of the vehicle to the current vehicle position is calculated, the average curvature at the turning portion is calculated, the turning angle is within the set angle range, and the average curvature is the set curvature. When it is smaller, it is determined that the U-turn has been made, so that the U-turn can be determined accurately with a short distance after the U-turn. In particular, since the curvature is set as a condition for determining the U-turn, it is possible to eliminate an error that erroneously determines a turn in an area other than a road, for example, a turn in a parking lot or a turn to a highway as a U-turn.
According to the present invention, since it is determined that the vehicle exists on the saddle road and the U-turn determination is stopped when the vehicle exists on the saddle road, a mistake that erroneously determines a sharp curve on the saddle road as a U-turn. Can be eliminated.

  FIG. 1 is an explanatory diagram of an embodiment of the present invention. In a self-contained navigation position calculation / storage unit 29, a position / orientation calculation unit 29a determines the vehicle position (estimated vehicle position) and vehicle direction based on the output of the self-contained navigation sensor 8. The relative distance and direction in the X and Y directions are calculated and stored in the travel locus storage unit 29b as a travel locus (equal length vector locus) for each predetermined travel distance (for example, 10 m). In the U-turn detection unit 36, the turning start position calculation unit 36a refers to the travel locus, calculates the end point of the straight portion of the predetermined length closest to the current vehicle position as the turning start position, and turns angle / average curvature calculation unit. 36b calculates a turning angle from the turning start position of the vehicle to the current vehicle position, and calculates an average curvature in the turning portion, and the U-turn determination unit 36c has the turning angle within the set angle range and the average curvature. Is smaller than the set curvature, it is determined that a U-turn has been made. In this case, the U-turn determination unit 36c determines whether the vehicle exists on the road, stops the U-turn determination if the vehicle exists on the road, and prevents erroneous U-turn detection on the road.

(A) Navigation System FIG. 2 is a configuration diagram of a navigation system provided with a U-turn detection unit of the present invention.
It has a navigation control device 1, a remote control 2, a display device (color monitor) 3, a hard disk (HDD) 4, an HDD control device 5, a multi-beam antenna 6, a GPS receiver 7, a self-contained navigation sensor 8, and an audio unit 9. Yes. The hard disk (HDD) 4 stores map data. The self-contained navigation sensor 8 includes a relative azimuth sensor (angle sensor) 8a such as a vibration gyro that detects a vehicle rotation angle, and a distance sensor 8b that generates one pulse for each predetermined travel distance.

In the navigation control device 1, the map readout control unit 21 reads out predetermined map information from the HDD 4 by controlling the HDD control device 5 based on the vehicle position or the focus position (when scrolling). The map buffer 22 stores the map information read from the HDD, and stores multiple pieces (multiple units) of map information around the vehicle position or the focus position, for example, 3 × 3 units of map information so that the map can be scrolled. To do.
The map drawing unit 23 generates a map image using the map information stored in the map buffer 22, the VRAM 24 stores the map image, and the read control unit 25 is based on the screen center position (own vehicle position, focus position). The position of one screen cut out from the VRAM 24 is changed, and the map is scroll-displayed according to the movement of the own vehicle position or the focus movement.

The intersection guide unit 26 displays an enlarged view of the intersection at the approaching intersection and guides the traveling direction at the intersection using a display image and sound. That is, when the vehicle approaches within a predetermined distance from the approaching intersection, the intersection guide map (intersection enlarged view, travel direction arrow) is displayed on the display screen and the travel direction is guided by voice. To do. The remote controller control unit 27 receives a signal in response to an operation of the remote controller and instructs each unit. The GPS position calculation unit 28 calculates the current position (GPS position) of the vehicle and the vehicle position based on the GPS data input from the GPS receiver. The self-contained navigation position calculation / storage unit 29 calculates the vehicle position and direction by self-contained navigation with the GPS position as the initial position. That is, the self-contained navigation position calculation / storage unit 29 calculates the own vehicle position (estimated vehicle position) and vehicle direction based on the output of the self-contained navigation sensor, and the relative distance in the X and Y directions for each predetermined travel distance (for example, 10 m). And the azimuth are stored as a running locus (equal length vector locus).
The map matching control unit 30 performs map matching processing using the map information read to the map buffer 22, the estimated vehicle position, the vehicle orientation, and the travel locus to correct the position of the own vehicle on the travel road. The map matching processing is performed by using both pattern matching and the projection method, the pattern matching is performed every 150 m, and the map matching by the projection method is performed every 0.8 seconds. Further, when the U-turn is detected, the map matching control unit 30 initializes the map matching and starts over from the beginning (see FIG. 15).

The guide route control unit 31 performs a calculation process of a guide route (search route) from the input departure point to the destination, the guide route memory 32 stores the guide route, and the guide route drawing unit 33 guides the vehicle during driving. The guide route information (node sequence) is read from the route memory 32 and the guide route is drawn. The operation screen generator 34 generates various menu screens (operation screens), and the image composition unit 35 synthesizes and outputs various images.
The U-turn detection unit 36 performs U-turn detection according to a processing flow described later. The lane determination unit 37 determines whether the vehicle is passing the lane. The saddle road judgment is (1) with reference to the running trajectory, if there are more than the set number of inflection points whose direction changes more than the set angle, it is judged as a saddle road, or (2) the map Include road start / end information in the information and use this information to determine the road, or (3) analyze the road information ahead of the vehicle and the number of inflection points where the direction changes more than the set angle If it is equal to or more than the set number within a predetermined distance, it is determined as a tunnel.

(B) U-turn determination process FIG. 3 is an explanatory diagram of the U-turn determination process of the present invention, and FIG. 4 is a determination process flow of the U-turn detection unit 36. In navigation control, map matching is performed using both pattern matching and a projection method.
The map matching process is normally performed and the vehicle mark is corrected on the traveling road. Further, every time the vehicle travels 10 m by self-contained navigation, a trajectory isometric vector composed of the relative movement distance in the X and Y directions from the previous position to the current position and the direction of the vehicle is created and stored as travel trajectory data. In such a traveling state, the U-turn detection unit 36 performs the following process to detect the U-turn.
That is, the U-turn detection unit 36 calculates the gyro direction (trajectory isometric vector azimuth) θ ₁ of the point P ₁ 40 m before the latest trajectory equal length vector end (referred to as the current point) P ₀ every 10 m and the travel trajectory data. Ask more.

Then, U-turn detecting unit 36, a gyro azimuth theta ₀ and gyro azimuth theta ₁ of the angular difference of the point P ₁ of the current point _{P 0 (= | θ 0 -θ} 1 |) is calculated, and the angle difference threshold whether the value theta _TH1 (180 ± 30 ⁰⁾ within, i.e., determines whether present within the range of 150 ⁰ to 210 ⁰ (step 102). This process is a simple filter process for U-turn determination, and is a step for reducing the U-turn determination process and is not necessarily required.
If the angle difference (= | θ ₀ −θ ₁ |) is outside the range of the threshold value θ _TH1 , it is regarded as not a U-turn and the process is terminated and the process returns to the beginning. On the other hand, if the angle difference (= | θ ₀ −θ ₁ |) is within the range of the threshold value θ _TH1 , a straight line portion having a set length (50 m) or more is within the set distance (100 m) from the current point P _0. It is determined whether it exists by referring to the travel locus data (step 103). If it does not exist, it is assumed that it is not a U-turn and the process ends and the process returns to the beginning. This process is a process for estimating the U-turn start point P _US . As shown in FIG. 5, when the road RD is gently undulating, when the straight line distance between two points Q1 and Q2 on the road is L ₁ and the actual road length is L ₀ , L ₁ · cos 10 ^{When 0} <L ₀ ≦ L ₁ , the area between Q1 and Q2 is regarded as a straight line portion.

If there is a straight line portion, the straight line end portion closest to the current point P ₀ is estimated as the U-turn start point P _US of the vehicle, and the direction θbase of the straight line portion is calculated. That is, the direction θbase at the U-turn start point P _US is obtained (step 104). Next, the U-turn detection unit 36 calculates a distance L and a change angle θ from the straight line end portion P _US to the current point P ₀ , and the following equation r = L / θ
To calculate the average curvature r of the turning portion (step 105).
If the average curvature is calculated, the U-turn detector 36 determines that the angle difference (= | θ ₀ −θbase |) between the azimuth θ ₀ and the azimuth θbase at the current point is within the range of the threshold θ _TH2 (180 ± 20 ⁰ ). It is determined whether the average curvature r is within the threshold value (10R) (steps 106 to 107), and the angle difference is outside the range of the threshold value _θTH2 , or the average curvature r is equal to or greater than the threshold value (10R). In the case of, it is considered that it is not a U-turn, and the process ends and returns to the beginning. The process of step 107 is because the smaller the curvature, the higher the possibility of a U-turn, and the turn in a non-road area such as a turn in a parking lot or a ramp RMP that joins the highway HWY as shown in FIG. This is to prevent erroneous determination of the U-turn. Although the curvature threshold is 10R, the threshold can be set to width W if the width W of the road is known.

The angle difference (= | θ ₀ −θbase |) between the azimuth θ ₀ and the azimuth θbase at the current point is within the range of the threshold θ _TH2 (180 ± 20 ⁰ ), and the average curvature r is within the threshold (10R). In this case, the U-turn detection unit 36 checks whether the vehicle exists on the road (step 108), and stops the U-turn determination process if it exists on the road. This is to prevent misturning a turn on a saddle road as a U-turn, but is not necessarily a necessary step.
If it is not a saddle road, it is determined that the vehicle has made a U-turn (step 109). In the case where the saddle road judgment process 108 is omitted, when the angle difference is within the range of the threshold value θ _TH2 (180 ± 20 ⁰ ) and the average curvature r is within the threshold value (10R), the vehicle It is determined that a U-turn has been made.
After detecting the U-turn, in order not to repeatedly detect the same U-turn, the U-turn determination process is stopped until the vehicle travels 60 m after the U-turn is detected (step 110), and then the process returns to the beginning to restart the U-turn determination process.
When the U-turn is detected, the map matching control unit 30 (FIG. 30) initializes the map matching and starts the map matching from the beginning.

As described above, according to the present invention, the U-turn determination can be performed accurately with a short mileage after the U-turn. As a result, map matching is initialized early to eliminate mismatching, and The time required for matching on the actual road can be shortened. FIG. 7 is a vehicle mark trajectory when making a U-turn before the intersection A while traveling on the road RDa, and there is no mismatching with the parallel road RDb 30 to 40 m away as in the past (see FIG. 16) Matching is corrected on the road in a short time. A black circle is a locus of a vehicle mark. FIG. 8 shows a case where a U-turn is made at a point B while traveling on a straight road RD. A dotted line is a locus of an actual autonomous navigation position, a black circle is a locus of a vehicle mark, and a vehicle mark is a traveling road in a short time after the U-turn. It has been corrected above.
In addition, according to the present invention, since the curvature is set as a condition for determining the U-turn, it is possible to eliminate an error that erroneously determines a turn at a non-road area, for example, a turn in a parking lot or a turn to a highway as a U-turn. . In addition, it is possible to eliminate the mistake of misidentifying a sharp curve in a saddle road as a U-turn.

It is embodiment explanatory drawing of this invention. It is a block diagram of the navigation system provided with the U-turn detection part of this invention. It is U-turn determination process explanatory drawing. It is the determination processing flow of a U-turn detection part. It is determination explanatory drawing of a linear part. It is turning explanatory drawing in the ramp which joins a highway. It is explanatory drawing of the vehicle mark locus | trajectory of the navigation apparatus provided with the U-turn detection apparatus of this invention. It is explanatory drawing of the vehicle mark locus | trajectory of another navigation apparatus provided with the U-turn detection apparatus of this invention. It is explanatory drawing of the vehicle position detection method by a self-supporting navigation. It is explanatory drawing of the map matching by a projection method. It is another explanatory drawing of the map matching by a projection method. It is the 1st explanatory view of map matching by pattern matching. It is the 2nd explanatory view of map matching by pattern matching. It is the 3rd explanatory view of map matching by pattern matching. It is an initial operation explanatory view of map matching. It is mismatch explanatory drawing by the conventional map matching. It is vehicle mark position explanatory drawing by the conventional map matching.

Explanation of symbols

8 self-contained navigation sensor 29 self-contained navigation position calculation / storage unit 29a position / orientation calculation unit 29b travel locus storage unit 36 U-turn detection unit 36a turn start position calculation unit 36b turn angle / average curvature calculation unit 36c determination unit

Claims (6)

In a U-turn detection method of a navigation system for detecting a U-turn of a vehicle,
Calculate the turning angle from the turning start position of the vehicle to the current vehicle position, and calculate the average curvature at the turning portion,
When the turning angle is within the set angle range and the average curvature is smaller than the set curvature, it is determined that the U-turn has been made.
The U-turn detection method characterized by the above-mentioned. Save the azimuth of the vehicle for each predetermined mileage,
With reference to the stored data, the end point of the straight portion of the predetermined length closest to the current vehicle position is set as the turning start position of the vehicle.
The U-turn detection method according to claim 1. Determine that the vehicle is on the road,
Stop U-turn judgment if it exists in the tunnel,
The U-turn detection method according to claim 1. In a U-turn detection device of a navigation system for detecting a U-turn of a vehicle,
Means for detecting the position and direction of the vehicle and storing it as a travel locus;
A turning start position of the vehicle is obtained from the travel locus, a turning angle from the turning start position of the vehicle to the current vehicle position is calculated, an average curvature in the turning portion is calculated, the turning angle is within a set angle range, and U-turn determination means for determining that a U-turn has been made when the average curvature is smaller than the set curvature;
A U-turn detection device comprising: The U-turn determination means refers to the travel locus, and sets the end point of the straight portion of the predetermined length closest to the vehicle current position as the turning start position of the vehicle.
The U-turn detection device according to claim 4. The U-turn detection device further includes a saddle road judging means for judging that the vehicle exists on the saddle road,
The U-turn determination means stops the U-turn determination process when the vehicle is on a saddle road.
The U-turn detection device according to claim 4.

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