WO2017109976A1

WO2017109976A1 - Distance estimation device, distance estimation method, and program

Info

Publication number: WO2017109976A1
Application number: PCT/JP2015/086339
Authority: WO
Inventors: 諒子新原; 加藤　正浩; 一嗣金子
Original assignee: パイオニア株式会社
Priority date: 2015-12-25
Filing date: 2015-12-25
Publication date: 2017-06-29

Abstract

This distance estimation device acquires the distance to a physical object from a moving object at a first time and a second time, and also acquires the angle between the direction of travel of the moving object and the direction of the physical object. On the basis of the acquisition results, the device calculates the distance which the moving object moves from the first time until the second time.

Description

Distance estimation device, distance estimation method and program

The present invention relates to a technique for estimating a moving distance of a moving object.

For example, Patent Document 1 discloses a method of correcting a vehicle speed sensor mounted on a moving body by estimating a moving distance of the moving body in a predetermined period. In Patent Document 1, the correction device detects the number of output pulses of the vehicle speed sensor from the recognition of the feature A by the image recognition means to the recognition of the feature B, and the feature A and the feature B from the map information. To obtain the distance D. Then, the correction device corrects an arithmetic expression for obtaining the travel distance or travel speed of the vehicle from the output pulse number based on the relationship between the output pulse number and the distance D.

JP 2008-8783 A

However, in the method of Patent Document 1, only one feature can be recognized at a time by the image recognition means, and only the feature on the road on which the vehicle is traveling, such as a sign drawn on the road, can be used. Can not.

The above are examples of problems to be solved by the present invention. An object of this invention is to estimate the moving distance of a moving body using arbitrary features.

Invention of Claim 1 is a distance estimation apparatus, Comprising: The distance from the mobile body to the feature in each of 1st time and 2nd time, and the angle of the advancing direction of the said mobile body, and the direction of the said feature Each of the acquisition units includes an acquisition unit, and a calculation unit that calculates a moving distance of the moving body from the first time to the second time based on an acquisition result of the acquisition unit.

The invention according to claim 7 is a distance estimation method executed by the distance estimation device, wherein the distance from the moving object to the feature at each of the first time and the second time, the traveling direction of the moving object, and the ground An acquisition step of acquiring an angle with the direction of the object, respectively, and a calculation step of calculating a moving distance of the moving body from the first time to the second time based on an acquisition result of the acquisition step. It is characterized by.

The invention according to claim 8 is a program executed by a distance estimation device including a computer, wherein the distance from the moving object to the feature at each of the first time and the second time, the traveling direction of the moving object, and the The computer as an acquisition unit that acquires an angle with a direction of a feature, and a calculation unit that calculates a moving distance of the moving body from the first time to the second time based on an acquisition result of the acquisition unit. It is made to function.

It is a flowchart which shows the distance coefficient update process which concerns on an Example. An example of the positional relationship between one feature and a moving vehicle is shown. It is a figure explaining average pulse width. It is a flowchart of the process which calculates | requires an average pulse width by sequential calculation. A method for projecting a three-dimensional position of a feature onto a horizontal plane of a vehicle will be described. Another method for projecting a three-dimensional position of a feature onto a horizontal plane of a vehicle is shown. A method for calculating the movement distance based on the three-dimensional position of the feature will be described. Another method for calculating the movement distance based on the three-dimensional position of the feature will be described. It is a block diagram which shows the structure of the distance coefficient update apparatus which concerns on an Example. It is a flowchart of the distance coefficient update process by an Example. The relationship between travel speed and the number of pulses per unit time, and the relationship between travel speed and pulse width are shown.

In a preferred embodiment of the present invention, the distance estimation device acquires the distance from the moving object to the feature and the angle between the traveling direction of the moving object and the direction of the feature at the first time and the second time, respectively. And an calculating unit that calculates a moving distance of the moving body from the first time to the second time based on the acquisition result of the acquiring unit.

The distance estimation apparatus acquires the distance from the moving object to the feature at each of the first time and the second time, and the angle between the traveling direction of the moving object and the direction of the feature. And based on the acquisition result, the moving distance of the moving body from the first time to the second time is calculated. Thereby, the movement distance of a moving body is computable using the arbitrary features which can be measured from a moving body.

In one aspect of the distance estimation apparatus, the calculation unit includes an angle between the traveling direction of the moving body at the first time and the direction of the feature, and the traveling direction of the moving body at the second time. Based on the angle between the direction of the feature and the direction of the feature at the first time and the direction of the feature at the second time, the angle, the first time, and the second time are calculated. The moving distance is calculated based on the distance from the moving body to the feature in each.

In another aspect of the distance estimation apparatus, the calculation unit may calculate 1 of the vehicle speed pulse signal based on a moving distance from the first time to the second time and an average pulse width of the vehicle speed pulse signal. Calculate the travel distance per pulse. As a result, the vehicle speed pulse signal can be calibrated based on the calculated moving distance.

In another aspect of the distance estimation apparatus, the calculation unit calculates the movement distance when an angular velocity or a steering angle in a yaw direction of the moving body is less than a predetermined threshold. Thereby, the calculation accuracy of the movement distance can be improved.

In another aspect of the distance estimation apparatus, the calculation unit changes a time interval from the first time to the second time according to a traveling speed of the moving body. Thereby, the calculation accuracy of the movement distance can be improved. Preferably, the calculation unit shortens the time interval as the traveling speed of the moving body increases.

In another preferred embodiment of the present invention, the distance estimation method executed by the distance estimation device includes the distance from the moving object to the feature at each of the first time and the second time, the traveling direction of the moving object, and the ground. An acquisition step of acquiring an angle with the direction of the object, respectively, and a calculation step of calculating a moving distance of the moving body from the first time to the second time based on an acquisition result of the acquisition step. Thereby, the movement distance of a moving body is computable using the arbitrary features which can be measured from a moving body.

In another preferred embodiment of the present invention, a program executed by a distance estimation device including a computer includes a distance from a moving object to a feature at each of a first time and a second time, a traveling direction of the moving object, and the The computer as an acquisition unit that acquires an angle with a direction of a feature, and a calculation unit that calculates a moving distance of the moving body from the first time to the second time based on an acquisition result of the acquisition unit. Make it work. Thereby, the movement distance of a moving body is computable using the arbitrary features which can be measured from a moving body. The above program can be stored in a storage medium and used.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings. Below, the Example which uses the moving distance of the moving body obtained by the distance estimation method of this invention for the calibration of the vehicle speed pulse of a vehicle is described.

[background]
In the self-position estimation system installed in current car navigation systems, the vehicle speed is detected using a vehicle speed sensor, and the traveling state is detected using an angular velocity sensor or a steering angle sensor, thereby measuring the movement state of the vehicle. Then, the current position is estimated by integrating these with information measured by the GPS or the external sensor. Therefore, in order to improve the self-position estimation accuracy, it is required to detect the vehicle speed with high accuracy.

The vehicle speed sensor outputs a vehicle speed pulse signal at a time interval proportional to the output shaft of the transmission or the rotational speed of the wheels, for example. Then, as shown in the following formula (1), the distance coefficient alpha _d can be calculated vehicle speed v by dividing a pulse width t _p. This distance coefficient α _d is the moving distance per pulse of the vehicle speed pulse signal.

The moving distance per pulse varies depending on the vehicle type. Further, when the outer diameter of the tire changes due to a change in tire air pressure or tire replacement, the moving distance per pulse also changes. Furthermore, the moving distance per pulse varies depending on the traveling speed. Usually, the running resistance causes a difference between the wheel speed obtained from the vehicle speed pulse and the actual vehicle speed. Since the running resistance is higher during high speed running than during low speed running, the speed difference between the wheel speed and the vehicle body speed is also greater during high speed running than during low speed running. Therefore, the moving distance per pulse differs between high speed traveling and low speed traveling. As described above, in order to obtain the vehicle speed with high accuracy, the distance coefficient needs to be appropriately calibrated and updated.

Conventionally, information obtained from GPS has been used as a reference when calibrating a distance coefficient. For example, using a moving distance ΔD the vehicle speed pulse number n of the vehicle obtained by the GPS position obtained from GPS, by the following equation (2) calculates the moving distance d _p per pulse, constantly subjected to averaging processing There is a method in which correction is performed.

However, depending on the conditions, the GPS information itself, which is a reference, may include a large error. When calibration calculation is performed using GPS information including a large error as a reference, there is a problem that the distance coefficient is deviated from the true value. is there. To obtain GPS information as a reference more accurately, the conditions should be strict, but the more strict the conditions, the less the number of times reference information is acquired, and the conflicting problem that the progress of calibration becomes slow. Comes out.

[Distance coefficient update processing]
From the above viewpoint, the distance coefficient updating apparatus according to the present embodiment (hereinafter also simply referred to as “updating apparatus”) does not use GPS information as a reference, but based on the measurement of a feature by an external sensor, the moving distance of the vehicle Is used as a reference for calibration of the vehicle speed pulse signal. As the external sensor, a camera, LiDAR (Light Detection And Ranging), a millimeter wave radar, or the like can be used.

FIG. 1 is a flowchart illustrating distance coefficient update processing according to the embodiment. First, in step P1, the update device, at time T _1, to measure one feature using external sensors. Next, in step P2, updating device, at time T _2, which has passed ΔT seconds from the time T _1, to measure the same feature as that measured at time T _1.

Next, in step P3, the update device was acquired at time T ₁ and time T _2, the distance from the vehicle center position to feature at each time, by using the feature of the angle with respect to the traveling direction of the vehicle, calculates a moving distance ΔD the vehicle from time T ₁ to time T _2.

Next, in step P4, the update device, an average pulse width _{t p} of the vehicle speed pulse signal from the time _{T 1} of the time _{T 2,} the elapsed time ΔT from the time _{T 1} to time _{T 2,} determined in step P3 The moving distance d _p per pulse is calculated using the moving distance ΔD of the vehicle from time T ₁ to time T ₂ . In step P5, the update device updates the distance coefficient α _d using the movement distance d _p per pulse obtained in step P4.

Next, each step of the distance coefficient update process will be described in detail.

(1) Feature measurement (process P1-P2)
FIG. 2 shows an example of the positional relationship between one feature and a moving vehicle. Vehicle during the period from the time T ₁ time T _2, is to have moved as shown in FIG. First, the update device detects the feature at time T _1, to obtain the angle phi ₁ and the distance L ₁ and the traveling direction Hd ₁ and the direction of the feature of the vehicle from the vehicle to the feature (step P1) .

Next, the updating device also detects the feature at time T ₂ in the same manner as at time T _1, and the angle φ ₂ between the distance L ₂ from the vehicle to the feature and the traveling direction Hd _{1 of the} vehicle and the direction of the feature. Is acquired (process P2). (2) Calculation of movement distance ΔD (process P3)
Next, the update device includes a distance _{L 1} and the angle phi ₁ acquired at time _{T 1,} by using the distance _{L 2} and the angle phi ₂ acquired in time _{T 2,,} the vehicle from time _{T 1} to time _{T 2,} Is calculated. Specifically, in FIG. 2, the angle θ defined by the direction of the feature at time T ₁ and the direction of the feature at time T ₂ is given by the following equation.

Accordingly, the movement distance ΔD is obtained as follows by the cosine theorem.

(3) Calculation of moving distance d _p per pulse (process P4)
Next, the update device, by using the moving distance ΔD the vehicle in ΔT seconds from the time T ₁ to time T _2, the average pulse width t _p of the vehicle speed pulse signal, as described below, the movement per pulse The distance d _p is calculated.

Figure 3 is a diagram for explaining the average pulse width t _p. Average pulse width t _p is the pulse width measured between the time T ₁ of the time T _2, leave buffers can be calculated by taking the average as in the following formula (6).

Instead, the average pulse width can also be obtained by sequential calculation using Equation (7). When the average pulse width is obtained by sequential calculation, it is not necessary to buffer the measured pulse width, so that the amount of memory used in the apparatus can be reduced.

FIG. 4 is a flowchart of a process for obtaining the average pulse width by sequential calculation. At time T = _{T 1,} the update unit resets the coefficient k indicating the number of detected pulses to "0" (step S51), and acquires the current time T (step S52). Next, the update unit determines whether the present time T reaches time T ₂ (step S53).

If the current time T is not in time _{T 2} (step S53: NO), the update unit detects the vehicle speed pulse signal, and obtains the pulse width _{t k} (step S54). Next, the update device increments the coefficient k by 1 (step S55), and determines whether or not the coefficient k = 1 (step S56).

If the coefficient k = 1 (step S56: YES), and assigns the pulse width _{t k} to the average pulse width tp (step S58), the flow returns to step S52. On the other hand, if not the coefficient k = 1 (step S56: NO), the update device, by the equation (7), obtained by dividing the difference between the average pulse width t _p and the current pulse width t _k at the time by a factor k value _{_{(t k -t p) / k}} , that is, to update the current pulse width _{t k} average pulse _{t p} the variation of adding the average pulse width _{t p} of the time average pulse width _{t p} by, step S52 Return to. Then, in step S53, if the current time T reaches time _{T 2} (step S53: YES), the process ends.

(4) Updating the distance coefficient α _d (process P5)
Next, the update device updates the distance coefficient α _d using the movement distance d _p obtained in step P4. Specifically, the obtained moving distance d _p is set as a new distance coefficient α _d . The updated distance coefficient α _d obtained in this way is used for calculation of the vehicle speed v by the equation (1).

(5) Method of projecting a three-dimensional position of a feature onto the horizontal plane of the vehicle The above description assumes that the road surface is a plane, the vehicle moves in the plane, and the feature is in the same plane as the vehicle. It can be realized by considering it. However, many features in the real environment, such as road signs and traffic lights, have a height in the space. Thus, by projecting the three-dimensional coordinates of the feature onto the horizontal plane of the vehicle, the moving distance of the vehicle can be calculated by the same method as described above. This method will be described below.

Here, a vehicle coordinate system (XYZ coordinate system) is defined as shown in FIG. The X axis indicates the traveling direction of the vehicle, the Y axis indicates the direction perpendicular to the traveling direction of the vehicle in the horizontal plane of the vehicle, and the Z axis indicates the height direction of the vehicle.

(I) When the three-dimensional position of the feature can be acquired When the three-dimensional coordinates of the feature can be acquired using an external sensor capable of measuring the three-dimensional position of the feature, or the three-dimensional position of the feature in the map data When coordinate data is included, it is assumed that the three-dimensional coordinates P of the feature in the vehicle coordinate system can be acquired as shown in FIG.

At this time, if the orthogonal projection from the point P to the XY plane (the leg of the perpendicular line dropped from the point P to the XY plane) is set as a point P ′, the length L _xy of the line segment OP ′ and the line segment OP ′ The angle φ _xy formed with the X axis can be calculated as follows.

Thus, the processing in step P1 ~ P3 determines the horizontal distance _{L xy} and angle phi _xy using equation (12), it may be used. Specifically, in the process P1, the horizontal distance L _1xy and the angle φ _1xy are obtained. Similarly, in the process P2, the horizontal distance L _2xy and the angle φ _2xy are obtained. And based on these, movement distance (DELTA) D is calculated | required by process P3.

(Ii) When the distance and angle to the feature can be obtained Using an external sensor capable of measuring the distance and angle to the feature, as shown in FIG. 6, the distance L from the vehicle to the feature, the progress of the vehicle It is assumed that the azimuth angle φ _xy of the feature with respect to the direction (X axis of the vehicle coordinate system) and the elevation angle φ _xyz of the feature with respect to the horizontal plane of the vehicle (XY plane of the vehicle coordinate system) can be acquired.

In this case, if the orthogonal projection from the point P to the XY plane (the leg of the perpendicular line dropped from the point P to the XY plane) is set as the point P ′, the length L _xy of the line segment OP ′ can be calculated as follows.

Therefore, in the processes in steps P1 to P3, the horizontal distances L _{1xy and} L _2xy and the angles φ _{1xy and} φ _2xy may be used as in (i).

(6) Method of calculating the movement distance based on the three-dimensional position of the feature (Example 1)
Using an external sensor capable of measuring the distance and angle to the feature, as shown in FIG. 7, the distance L from the vehicle to the feature, the direction of the feature with respect to the traveling direction of the vehicle (the X axis of the vehicle coordinate system) Assume that the angle θ and the elevation angle φ of the feature with respect to the horizontal plane of the vehicle (the XY plane of the vehicle coordinate system) can be acquired. Specifically, at time T _1, the distance L ₁ from the vehicle to the _feature, the azimuth angle theta ₁ of the _feature, can retrieve elevation angle phi ₁ is the feature, at time T _2, the distance from the vehicle to feature L _2. Assume that the azimuth angle θ _{2 of} the feature and the elevation angle φ _{2 of} the feature have been acquired.

At this time, an orthogonal projection from the point P to the XY plane (perpendicular foot dropped from the point P to the XY plane) is set as a point P ′, and a normal foot dropped from the point P ′ to the vehicle travel path is defined as a point H ′. Then, the length of the line segment O ₁ P ′ is obtained by the equation (10-1), the length of the line segment P′H is obtained by the equation (10-2), and the length of the line segment PP ′ is It is obtained by the formula (10-3). Therefore, the length of the line segment PH is obtained by Expression (10-4), and Expression (10-5) is established with respect to an angle α ₁ formed by the vehicle traveling direction and the feature position P at time T ₁ .

Thus, alpha ₁ is represented by the formula (11).

Similarly, an angle α ₂ formed by the traveling direction of the vehicle at time T ₂ and the feature position P is expressed by Expression (12).

Therefore, an angle β formed by a line segment connecting the vehicle position and the feature position at time T ₁ and a line segment connecting the vehicle position and the feature at time T ₂ is expressed by Expression (13).

Therefore, according to the cosine theorem, the movement distance ΔD is

And obtained.

(Example 2)
As in Example 1, using an external sensor capable of measuring the distance and angle to the feature, as shown in FIG. 7, the distance L from the vehicle to the feature, the traveling direction of the vehicle (the X axis of the vehicle coordinate system) ) And the elevation angle φ of the feature with respect to the horizontal plane of the vehicle (the XY plane of the vehicle coordinate system). Specifically, at time T _1, the distance L ₁ from the vehicle to the _feature, the azimuth angle theta ₁ of the _feature, can retrieve elevation angle phi ₁ is the feature, at time T _2, the distance from the vehicle to feature L _2. Assume that the azimuth angle θ _{2 of} the feature and the elevation angle φ _{2 of} the feature have been acquired. Note that indicates the position of the vehicle at time _{T 1} in _{O 1,} indicates the position of the vehicle at time _{T 2,} with _{O 2.} Further, an orthogonal projection from the point P to the XY plane (a leg of a perpendicular line dropped from the point P to the XY plane) is set as a point P ′.

At this time, as shown in FIG. 8A, when the triangle O ₁ PH is considered, the movement distance ΔD is obtained by the equation (15).

Here, PH can be obtained using either the measurement result at time T _{1 or} the measurement result at time T ₂ . When the measurement result at time T ₁ is used, PH is obtained by Expression (16-4).

Further, using the measurement result at time T ₂ , PH is obtained by Expression (17-4).

On the other hand, as shown in FIG. 8 (B), given the triangle _O 1 P'H, moving distance ΔD is obtained by the equation (18). Here, P′H can be obtained using either the measurement result at time T _{1 or} the measurement result at time T ₂ . Using the measurement result at time T ₁ , P′H is obtained by the above equation (16-2). Further, using the measurement result at time T ₂ , P′H is obtained by Expression (17-2).

[Example]
Next, an embodiment of the above update device will be described. FIG. 9 is a block diagram illustrating the configuration of the update device 1 according to the embodiment. In this embodiment, the update device 1 determines the movement distance ΔD based on the measurement result of one feature by the external sensor.

As illustrated, the update device 1 includes a gyro sensor 10, a vehicle speed sensor 11, an external sensor 12, a traveling direction acquisition unit 13, a vehicle speed pulse measurement unit 14, a feature measurement unit 15, and a distance coefficient calibration unit. 17 and a movement distance calculation unit 18. The traveling direction acquisition unit 13, the vehicle speed pulse measurement unit 14, the feature measurement unit 15, the distance coefficient calibration unit 17, and the movement distance calculation unit 18 are executed by executing a program prepared in advance by a computer such as a CPU. Can be realized.

The traveling direction acquisition unit 13 acquires the traveling directions Hd ₁ and Hd ₂ of the vehicle based on the output of the gyro sensor 10 and supplies them to the feature measurement unit 15 and the distance coefficient calibration unit 17. Vehicle speed pulse measuring unit 14, a vehicle speed pulse outputted from the vehicle speed sensor 11 measures and supplies the distance coefficient calibration unit 17 calculates the like mean pulse width t _p of the vehicle speed pulse signal.

The external sensor 12 is, for example, a camera, LiDAR, millimeter wave radar, or the like, and the feature measuring unit 15 measures the distance to the feature based on the output of the external sensor 12. Specifically, the feature measurement unit 15 measures the distance L ₁ from the vehicle to one feature at time T ₁ , and the vehicle travel direction Hd ₁ supplied from the travel direction acquisition unit 13 and its An angle φ ₁ formed with the direction of the feature is calculated and supplied to the movement distance calculation unit 18. Further, feature measurement unit 15, at time T _2, with measuring the distance L ₂ to the same feature from the vehicle, the traveling direction Hd ₂ and the direction of the feature of the supplied vehicle from the traveling direction acquisition unit 13 calculating the angle phi ₂ and is supplied to the moving distance calculating unit 18.

Based on the distances L ₁ and L ₂ and the angles φ ₁ and φ ₂ supplied from the feature measuring unit 15, the moving distance calculation unit 18 calculates the moving distance of the vehicle according to the above formulas (3) to (4). ΔD is calculated and supplied to the distance coefficient calibration unit 17.

Distance coefficient calibration unit 17, and the average pulse width t _p supplied from the vehicle speed pulse measuring unit 14, based on a moving distance ΔD supplied from the moving distance calculating unit 18, the moving distance d _p per pulse _(i.e. , A distance coefficient α _d ) is calculated. The vehicle body speed may be calculated from the obtained movement distance per pulse.

Next, distance coefficient update processing according to the embodiment will be described. FIG. 10 is a flowchart of the distance coefficient update process according to the embodiment.

First, the updating device 1 determines whether or not the vehicle is traveling straight ahead based on the traveling direction of the vehicle output by the traveling direction acquisition unit 13 (step S11). This is because the accuracy of the movement distance ΔD output by the movement distance calculation unit 18 decreases when the vehicle is not traveling straight ahead. Specifically, when the gyro sensor 10 can detect the angular velocity ω in the yaw direction of the vehicle, it may be determined that the vehicle is traveling straight when | ω | <Δω (Δω: a predetermined threshold). . When the steering angle δ of the vehicle can be detected, it may be determined that the vehicle is traveling straight when | δ | <Δδ (Δδ: a predetermined threshold).

If the vehicle is not traveling straight (step S11: NO), the process ends. On the other hand, when the vehicle is traveling straight (step S11: YES), the update device 1 measures one feature and acquires the distance L and the angle φ from the vehicle to the feature (step S12).

Next, the update device 1 determines whether or not flag = 0 (step S13). Note that “flag” is reset to “0” at the start of processing. If a flag = 0 (step S13: YES), updating apparatus 1 is set to "1" to the flag (step S14), and starts the calculation of the average pulse width _{t p} (step S15), and returns to step S11 .

On the other hand, when flag = 0 is not satisfied (step S13: NO), the updating device 1 calculates the movement distance ΔD as described above (step S16), and calculates the movement distance d _p per pulse using the movement distance ΔD. (step S17), and updates the distance coefficient alpha _d (step S18). Then, the process ends.

[Feature measurement cycle]
The movement distance d _p per pulse obtained in the above-described distance coefficient update process is an average value of the movement distance per pulse during the time interval ΔT from time T ₁ to time T ₂ . Therefore, the large variation of the pulse width of the time interval [Delta] T, the accuracy of the moving distance d _p which is calculated is deteriorated. Therefore, it is desirable that the number of pulses during the time interval ΔT is as small as possible.

The number of pulses per unit time varies depending on the running speed of the vehicle. For example, consider the number of pulses per second as shown in FIG. In a vehicle type that outputs two pulses per tire rotation, the number of pulses per second is 3 pulses at 10 km / h, 17 pulses at 50 km / h, and 35 pulses at 100 km / h, and there is a large difference depending on the running speed.

Therefore, in view of the measurement cycle of the external sensor and the vehicle type, if the time interval ΔT is changed according to the traveling speed, it is possible to suppress the deterioration of the accuracy of the moving distance d _p due to the fluctuation of the pulse width. FIG. 11B shows the relationship between the traveling speed and the pulse width. For example, in the case of a vehicle type in which the measurement cycle of the external sensor is 50 ms (20 Hz) and two pulses are output per revolution, ΔT = 300 ms when the traveling speed is less than 20 km / h, and ΔT = 200 ms when the speed is 20 km / h or more and less than 30 km / h. When ΔT = 100 ms when the speed is 30 km / h or more and less than 60 km / h, and ΔT = 50 ms when the speed is 60 km / h or more, the number of pulses that can be measured during the time interval ΔT is about 1 pulse or 2 pulses, and the moving distance is high. d _p can be calculated.

[Modification]
(Modification 1)
As shown in step S11 of FIG. 10, in the distance coefficient update process of the embodiment, the distance coefficient is basically updated when the vehicle is traveling straight ahead. However, in reality, even if the vehicle appears to be traveling straight ahead, it is not strictly going straight and there is a slight fluctuation. Therefore, the movement distance ΔD obtained in the process P3 is not an actual movement distance but an approximate value. For this reason, if the time interval ΔT is too large, the difference between the actual moving distance and the moving distance calculated in the process P3 becomes large. From this point of view, it is desirable to make the time interval ΔT from time T ₁ to time T ₂ as small as possible.

(Modification 2)
If the external sensor is attached to a low position of the vehicle, it is considered that the occlusion increases by surrounding vehicles, and the frequency with which a suitable feature for updating the distance coefficient can be detected decreases. Therefore, it is preferable to install the external sensor so that the upper side can be measured above the height of the surrounding vehicle. Thereby, since the detection frequency of the feature increases and the number of updates of the distance coefficient increases, the accuracy of the distance coefficient can be improved.

The present invention can be used for an apparatus mounted on a moving body.

DESCRIPTION OF SYMBOLS 10 Gyro sensor 11 Vehicle speed sensor 12 External sensor 13 Travel direction acquisition part 14 Vehicle speed pulse measurement part 15 Feature measurement part 17 Distance coefficient structure part 18 Travel distance calculation part 19 Map database

Claims

An acquisition unit for acquiring the distance from the moving object to the feature at each of the first time and the second time and the angle between the traveling direction of the moving object and the direction of the feature;
A calculating unit that calculates a moving distance of the moving body from the first time to the second time based on the acquisition result of the acquiring unit;
A distance estimation apparatus comprising:
The calculation unit is based on an angle between the traveling direction of the moving body and the direction of the feature at the first time, and an angle between the traveling direction of the moving body and the direction of the feature at the second time. Calculating the angle between the direction of the feature at the first time and the direction of the feature at the second time, and the distance from the moving object to the feature at each of the first time and the second time. The distance estimation apparatus according to claim 1, wherein the moving distance is calculated based on the following.
The calculation unit calculates a movement distance per pulse of the vehicle speed pulse signal based on a movement distance from the first time to the second time and an average pulse width of the vehicle speed pulse signal. The distance estimation apparatus according to claim 1 or 2.
The distance according to any one of claims 1 to 3, wherein the calculation unit calculates the movement distance when an angular velocity or a steering angle in a yaw direction of the moving body is less than a predetermined threshold. Estimating device.
The distance according to claim 1, wherein the calculation unit changes a time interval from the first time to the second time according to a traveling speed of the moving body. Estimating device.
6. The distance estimating apparatus according to claim 5, wherein the calculating unit shortens the time interval as the traveling speed of the moving body increases.
A distance estimation method executed by a distance estimation device,
An acquisition step of acquiring the distance from the moving object to the feature at each of the first time and the second time and the angle between the traveling direction of the moving object and the direction of the feature;
A calculation step of calculating a moving distance of the moving body from the first time to the second time based on the acquisition result of the acquisition step;
A distance estimation method comprising:
A program executed by a distance estimation device including a computer,
An acquisition unit for acquiring the distance from the moving object to the feature at each of the first time and the second time and the angle between the traveling direction of the moving object and the direction of the feature;
A calculating unit that calculates a moving distance of the moving body from the first time to the second time based on an acquisition result of the acquiring unit;
A program for causing the computer to function as:
A storage medium storing the program according to claim 8.