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WO2018163750A1 - Dispositif d'estimation de distance, procédé d'estimation de distance, et programme - Google Patents

Dispositif d'estimation de distance, procédé d'estimation de distance, et programme Download PDF

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Publication number
WO2018163750A1
WO2018163750A1 PCT/JP2018/005325 JP2018005325W WO2018163750A1 WO 2018163750 A1 WO2018163750 A1 WO 2018163750A1 JP 2018005325 W JP2018005325 W JP 2018005325W WO 2018163750 A1 WO2018163750 A1 WO 2018163750A1
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WIPO (PCT)
Prior art keywords
distance
time
feature
moving
vehicle
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PCT/JP2018/005325
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English (en)
Japanese (ja)
Inventor
諒子 新原
加藤　正浩
大数 ▲浜▼田
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パイオニア株式会社
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Publication of WO2018163750A1 publication Critical patent/WO2018163750A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B21/00—Measuring arrangements or details thereof, where the measuring technique is not covered by the other groups of this subclass, unspecified or not relevant
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C22/00—Measuring distance traversed on the ground by vehicles, persons, animals or other moving solid bodies, e.g. using odometers, using pedometers

Definitions

  • the present invention relates to a technique for estimating a moving distance of a moving object.
  • 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.
  • 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. The distance D is obtained. 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.
  • An object of the present invention is to estimate a moving distance of a moving object using any one feature.
  • the invention according to claim 1 is a distance estimation device, and is mounted on the moving body at each of a first time during movement of the moving body and a second time after a predetermined time has elapsed from the first time.
  • a first acquisition unit that acquires the respective distances from the two measurement devices to the predetermined feature, measured by the two measurement devices, the distance acquired by the first acquisition unit, and the distance between the two measurement devices
  • a calculating unit that calculates a moving distance of the moving body from the first time to the second time based on the distance.
  • the invention according to claim 9 is a distance estimation method executed by the distance estimation device, wherein the movement is performed at each of a first time during movement of the moving body and a second time after a predetermined time has elapsed from the first time.
  • the invention according to claim 10 is a program executed by a distance estimation device including a computer, and at each of a first time during movement of the moving body and a second time after a predetermined time has elapsed from the first time,
  • the first acquisition unit that acquires the distances from the two measurement devices to the predetermined feature measured by the two measurement devices mounted on the moving body, and the distance acquired by the first acquisition unit
  • the calculation unit that calculates the moving distance of the moving body from the first time to the second time based on the distance between the two measuring devices.
  • the calculation method of the moving distance of a vehicle is shown. It is a figure explaining average pulse width. It is a flowchart of the process which calculates
  • 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 the horizontal plane of the vehicle is shown.
  • the distance estimation device is mounted on the moving body at each of a first time during movement of the moving body and a second time after a predetermined time has elapsed from the first time.
  • a first acquisition unit that acquires the distances from the two measurement devices to the predetermined feature measured by the two measurement devices, and the distance acquired by the first acquisition unit and the distance between the two measurement devices.
  • a calculating unit that calculates a moving distance of the moving body from the first time to the second time.
  • the distance estimation device described above is measured by the two measurement devices mounted on the moving body at each of the first time during the movement of the moving body and the second time after the predetermined time has elapsed. Each distance from the measuring device to a predetermined feature is acquired. And based on the distance measured by the measuring device and the distance between the two measuring devices, the moving distance of the moving body from the first time to the second time is calculated. According to this distance estimation apparatus, the moving distance of the moving object can be calculated using one feature that can be measured from the moving object.
  • the calculation unit is configured to calculate the per-pulse speed 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. Is calculated. As a result, the vehicle speed pulse signal can be calibrated based on the calculated moving distance.
  • 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.
  • a storage unit that stores information including a distance between the two measurement devices, and a second acquisition unit that acquires a distance between the two measurement devices from the storage unit, are further provided.
  • the distance between the two measuring devices is stored in the storage unit and can be used immediately.
  • the calculation unit changes a time interval from the first time to the second time according to a traveling speed of the moving body.
  • the calculation accuracy of the movement distance can be improved.
  • the calculation unit shortens the time interval as the traveling speed of the moving body increases.
  • the position of the feature to be measured by the two measuring devices is determined based on the current position of the moving object from a map database in which position information of a plurality of features is stored.
  • a third acquisition unit that acquires information is provided, and the measurement device measures a feature existing at a position corresponding to the position information acquired by the third acquisition unit as the predetermined feature.
  • the third acquisition unit acquires position information of a feature to be measured by the two measuring devices based on a current position, a traveling direction, and a moving speed of the moving body.
  • the distance estimation method executed by the distance estimation apparatus moves at each of a first time during movement of the moving body and a second time after a predetermined time has elapsed from the first time.
  • the moving distance of the moving body can be calculated using one feature that can be measured from the moving body.
  • the program executed by the distance estimation apparatus including a computer is a first time during the movement of the moving body and a second time after a predetermined time has elapsed from the first time.
  • the first acquisition unit that acquires the distances from the two measurement devices to the predetermined feature measured by the two measurement devices mounted on the moving body, and the distance acquired by the first acquisition unit
  • the calculation unit that calculates the moving distance of the moving body from the first time to the second time based on the distance between the two measuring devices.
  • 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 ⁇ d is the moving distance per pulse of the vehicle speed pulse signal.
  • the travel distance per pulse varies depending on the vehicle model. 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.
  • the GPS information itself which is a reference, may include a large error.
  • the conditions should be strict, but the more strict the conditions, the less the number of times reference information is obtained, and the conflicting problem that the progress of calibration becomes slower. Comes out.
  • the distance coefficient 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.
  • an external sensor a camera, LiDAR (Light Detection And Ranging), a millimeter wave radar, or the like can be used.
  • FIG. 1 is a flowchart showing a basic process for updating the distance coefficient.
  • the update device at time T 1, to measure one feature using two external sensors mounted on the vehicle.
  • step P2 updating device, at time T 2, which has passed ⁇ T seconds from the time T 1, using the same two external sensor to measure the same feature as that measured at time T 1.
  • step P3 the update device acquires the distance between the two external sensors.
  • step P4 the update device was acquired at time T 1 and time T 2, the distance from the external sensor to feature at each time, in the direction viewed feature from the position of the external sensor at each time
  • the travel distance ⁇ D of the vehicle from time T 1 to time T 2 is calculated using the angle formed.
  • step P5 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 ⁇ T from the time T 1 to time T 2, determined in step P4
  • the moving distance d p per pulse is calculated using the moving distance ⁇ D of the vehicle from time T 1 to time T 2 .
  • step P6 the updating device updates the distance coefficient ⁇ d using the movement distance d p per pulse obtained in step P5.
  • FIG. 2 shows an example of the positional relationship between one feature and a moving vehicle.
  • Two external sensors 12A and 12B are attached to the vehicle. It is assumed that the mounting positions and postures of the external sensors 12A and 12B in the vehicle are known. Therefore, the distance C between the mounting positions of the external sensors 12A and 12B (hereinafter also referred to as “inter-sensor distance C”) is known. Further, the angle ⁇ formed by the direction connecting the external sensors 12A and 12B (hereinafter also referred to as “sensor arrangement direction”) and the traveling direction of the vehicle is also known.
  • the update device detects the feature at ambient sensors 12A and 12B at time T 1, the distance L A from external sensors 12A to feature, and obtains the distance L B from external sensor 12B to feature (Process P1).
  • the update device detects the feature at ambient sensors 12A and 12B at time T 2, the distance L A from external sensors 12A to feature ', and the distance from the external sensor 12B to feature L B' Is acquired (process P2).
  • the update device acquires an inter-sensor distance C that is the distance between the external sensors 12A and 12B from the internal storage unit (step P3).
  • the update device uses these values to calculate the moving distance ⁇ D of the vehicle at time T 2, the time T 1 (step P4). Specifically, the direction of the feature as seen from the position of the external sensor 12A at time T 1, the angle between the alignment direction of the sensor and " ⁇ ". Further, the direction of the feature as seen from the position of the external sensor 12A at time T 2, the angle between the alignment direction of the sensor and "theta ''. In this case, according to the cosine theorem, the angles ⁇ and ⁇ ′ can be calculated by the following equations.
  • the angle ⁇ can be calculated by the following equation.
  • the moving distance ⁇ D of the vehicle can be calculated by the following formula using the cosine theorem.
  • the moving distance of the moving object can be calculated at arbitrary time intervals. Further, only one feature may be used for the calculation, and a plurality of features are not required.
  • 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, you leave buffers can be calculated by taking the average as the following equation (7).
  • the average pulse width can be obtained by sequential calculation using the following equation (8).
  • 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.
  • 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).
  • the update unit determines whether the present time T reaches time T 2 (step S53).
  • the update device by the equation (8), 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.
  • step S53 if the current time T reaches time T 2 (step S53: YES), the process ends.
  • the update device updates the distance coefficient ⁇ d using the movement distance d p obtained in step P5. Specifically, the moving distance d p obtained as a new distance coefficient alpha d.
  • the updated distance coefficient ⁇ d obtained in this way is used for calculation of the vehicle speed v by the equation (1).
  • 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
  • the Z axis indicates the height direction of the vehicle.
  • the length L xy of the line segment OP ′ and the angle ⁇ xy formed by the line segment OP ′ and the X axis are as follows: Can be calculated as follows.
  • the horizontal distance L xy may be obtained using the equation (9) and used. Specifically, in the process P1, the horizontal distances L Axy and L Bxy are obtained. Similarly, in the process P2, the horizontal distances L A ′ xy and L B ′ xy are obtained. And based on these, movement distance (DELTA) D is calculated
  • the length L xy of the line segment OP ′ can be calculated as follows.
  • the horizontal distance L xy obtained by the equation (10) may be used as in (i).
  • FIG. 7 is a block diagram showing the configuration of the update device 1.
  • the update device 1 obtains the travel distance ⁇ D of the vehicle by calculation based on the measurement result of one feature by the external sensor.
  • the update device 1 includes a gyro sensor 10, a vehicle speed sensor 11, external sensors 12A and 12B, a traveling direction acquisition unit 13, a vehicle speed pulse measurement unit 14, a feature measurement unit 15, and a storage unit. 16, a distance coefficient calibration unit 17, a movement distance calculation unit 18, a current position estimation unit 19, a reference feature setting unit 20, and a map database 21.
  • the external sensors 12A and 12B are not distinguished, they are simply referred to as “external sensor 12”.
  • the traveling direction acquisition unit 13, the vehicle speed pulse measurement unit 14, the feature measurement unit 15, the distance coefficient calibration unit 17, the movement distance calculation unit 18, the current position estimation unit 19, and the reference feature setting unit 20 are a computer such as a CPU. Can be realized by executing a program prepared in advance.
  • the position of a feature that is preferable as a reference for calculating the moving distance of the vehicle is stored in association with a point on the map data.
  • a preferable feature as a reference for calculating the moving distance of the vehicle is a feature that does not change in shape or position depending on time, season, weather, etc., and exists around the road, such as a road sign, This includes traffic lights, utility poles, billboards, and buildings.
  • the current position estimation unit 19 estimates the current position of the vehicle based on positioning information received from a positioning satellite belonging to, for example, GNSS (Global Navigation Satellite System / Global Positioning Satellite System). Alternatively, the current position estimation unit 19 estimates the current position of the vehicle by performing map matching with the map data in the map database 21 based on the output of the gyro sensor 10, the output from the vehicle speed sensor 11, the output of the external sensor 12, and the like. You may do.
  • GNSS Global Navigation Satellite System / Global Positioning Satellite System
  • the reference feature setting unit 20 When the reference feature setting unit 20 tries to execute the calibration of the vehicle speed pulse signal, the reference feature setting unit 20 determines the vehicle position based on the current position of the vehicle estimated by the current position estimation unit 19, the traveling direction of the vehicle, and the vehicle speed. A feature preferable as a reference for calculating the moving distance is extracted from the map data and set as a reference feature.
  • the traveling direction acquisition unit 13 acquires the traveling direction of the vehicle based on the output of the gyro sensor 10 and supplies it 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, a LiDAR, a millimeter wave radar, or the like, and the feature measuring unit 15 is a distance to the reference feature set by the reference feature setting unit 20 based on the output of the external sensor 12. Measure. Specifically, feature measuring section 15 at time T 1, 2 one external sensor 12A, a distance L A from 12B to feature measures the L B, and supplies the moving distance calculating unit 18. Further, feature measurement unit 15, at time T 2, 2 two external sensor 12A, a distance L A from 12B to feature ', L B' were measured and supplied to the moving distance calculating unit 18.
  • the storage unit 16 stores a distance between the two external sensors 12A and 12B attached to the vehicle, that is, a distance C between the sensors.
  • the movement distance calculation unit 18 calculates the above formula. From (3) to (5), the moving distance ⁇ D of the vehicle is calculated and supplied to the distance coefficient calibration unit 17.
  • the moving distance d p per pulse (i.e. , A distance coefficient ⁇ d ) is calculated.
  • the vehicle body speed may be calculated from the obtained movement distance per pulse.
  • FIG. 8 is a flowchart of the distance coefficient update process.
  • 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 ⁇ D output by the movement distance calculation unit 18 decreases when the vehicle is not traveling straight ahead.
  • the gyro sensor 10 can detect the angular velocity ⁇ in the yaw direction of the vehicle, it may be determined that the vehicle is traveling straight when
  • the steering angle ⁇ of the vehicle it may be determined that the vehicle is traveling straight when
  • step S11: NO If the vehicle is not traveling straight (step S11: NO), the process ends.
  • the reference feature setting unit 20 is based on the current position of the vehicle estimated by the current position estimation unit 19, the traveling direction of the vehicle, and the vehicle speed. Then, a feature preferable as a reference for calculating the moving distance of the vehicle is extracted from the map data around the current position of the vehicle, and set as a reference feature (step S12). Specifically, the reference feature setting unit 20 determines a predetermined time required for measuring a feature among features existing in the traveling direction along the road on which the vehicle is traveling, based on the current position and traveling direction of the vehicle.
  • the external sensor may be too close to or over the feature.
  • the position information of the features closest to the current position of the vehicle is acquired from the map data and set as the reference feature position. That is, the reference feature setting unit 20 sets a feature that is as close as possible to the current position of the vehicle as a reference feature within a range where measurement is not possible during measurement.
  • the updating device 1 sets the reference feature within a predetermined angle range including the direction in which the reference feature exists, which is set based on the position information in the map data of the reference feature. and, a feature existing within a predetermined distance range including the distance that features of the reference is present, the two external sensors 12A, detected in 12B, at time T 1, T 2 of one of the feature detected Measurement is performed (step S13), and the inter-sensor distance C between the external sensors 12A and 12B is acquired from the storage unit 16 (step S14).
  • step S15 NO
  • the updating device 1 calculates the movement distance ⁇ D as described above (step S18), and calculates the movement distance d p per pulse using the movement distance ⁇ D. (step S19), and updates the distance coefficient alpha d (step S20). Then, the process ends.
  • 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 ⁇ T 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 ⁇ T 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.
  • FIG. 9B shows the relationship between the traveling speed and the pulse width.
  • ⁇ T 300 ms when the traveling speed is less than 20 km / h
  • ⁇ T 200 ms when the speed is 20 km / h or more and less than 30 km / h.
  • the number of pulses that can be measured during the time interval ⁇ T is about 1 pulse or 2 pulses, and the moving distance is high.
  • d p can be calculated.
  • 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 movement of the vehicle is erroneously based on the moving object.
  • the distance is not calculated, and the reliability of the calculated moving distance can be improved.
  • the external sensor 12 can measure the distance to the feature with high accuracy, and the accuracy of the calculated movement distance Can be improved.

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  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
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Abstract

L'invention concerne un dispositif d'estimation de distance qui acquiert les distances à partir de deux dispositifs de mesure montés sur un corps mobile jusqu'à une caractéristique prescrite, les distances ayant été mesurées par les dispositifs de mesure à un premier instant lors du déplacement du corps mobile et à un second instant après l'écoulement d'un temps prescrit à partir du premier instant. Le dispositif d'estimation de distance calcule la distance de déplacement du corps mobile entre le premier instant et le second instant sur la base des distances mesurées par les dispositifs de mesure et de la distance entre les deux dispositifs de mesure.
PCT/JP2018/005325 2017-03-06 2018-02-15 Dispositif d'estimation de distance, procédé d'estimation de distance, et programme WO2018163750A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102023208727A1 (de) * 2023-09-08 2025-03-13 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren und Ermittlungsvorrichtung zum Ermitteln einer von einem Fahrzeug zurückgelegten Strecke

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JP2005006081A (ja) * 2003-06-12 2005-01-06 Denso Corp 画像サーバ、画像収集装置、および画像表示端末
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JP2012073810A (ja) * 2010-09-29 2012-04-12 Hitachi Ltd 路面状況推定装置および路面状況推定方法
JP2012189467A (ja) * 2011-03-11 2012-10-04 Casio Comput Co Ltd 測位装置、歩幅データ補正方法およびプログラム
JP2014232411A (ja) * 2013-05-29 2014-12-11 富士通テン株式会社 携帯端末、及び、危険報知システム

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Publication number Priority date Publication date Assignee Title
JPH1059120A (ja) * 1996-06-11 1998-03-03 Toyota Motor Corp 障害物検知装置及びその装置を用いた乗員保護装置
JP2005006081A (ja) * 2003-06-12 2005-01-06 Denso Corp 画像サーバ、画像収集装置、および画像表示端末
JP2007240193A (ja) * 2006-03-06 2007-09-20 Denso Corp ランドマーク報知装置、車載用ナビゲーション装置および車載用ナビゲーションシステム
JP2008008783A (ja) * 2006-06-29 2008-01-17 Toyota Motor Corp 車輪速パルス補正装置
JP2008020462A (ja) * 2007-08-16 2008-01-31 Olympus Corp 距離測定装置
JP2012073810A (ja) * 2010-09-29 2012-04-12 Hitachi Ltd 路面状況推定装置および路面状況推定方法
JP2012189467A (ja) * 2011-03-11 2012-10-04 Casio Comput Co Ltd 測位装置、歩幅データ補正方法およびプログラム
JP2014232411A (ja) * 2013-05-29 2014-12-11 富士通テン株式会社 携帯端末、及び、危険報知システム

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102023208727A1 (de) * 2023-09-08 2025-03-13 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren und Ermittlungsvorrichtung zum Ermitteln einer von einem Fahrzeug zurückgelegten Strecke

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