JP2020032873A - Automated operation method - Google Patents

Abstract

To provide an automated operation method that enables an automated operation to be continued without any change, even when the accuracy of a position detected by a GPS signal is decreased.SOLUTION: A GPS signal is received during traveling, and a position of a driver's own vehicle is acquired in real time. The vehicle travels by correcting the acquired position of the driver's own vehicle so that it can correspond to a predetermined target locus. In this case, when reliability of positional accuracy of the driver's own vehicle detected by the GPS signal is decreased, the vehicle travels by shifting to traveling using an Inertial Measurement Unit (IMU) comprising a gyro and an acceleration meter.SELECTED DRAWING: Figure 5

Description

  The present invention relates to an automatic operation method using a GPS signal.

  As a method of automatically operating a predetermined route such as a bus, a target trajectory is created in advance, a GPS signal is received, and the position of the own vehicle is acquired in real time to make the vehicle travel along this target trajectory, It is determined whether or not the acquired position of the host vehicle is on the target locus, and the vehicle is traveled with the position corrected so as to follow the target locus.

  Patent Literature 1 discloses that when driving is performed not by automatic driving but by a driver, positional information based on a GPS signal is compared with positional information based on an inertial measurement unit (IMU: Inertial Measurement Unit). It describes that it is determined that the vehicle is traveling in a shielded area (such as a tunnel) in which the reception state of the GPS signal is deteriorated, and that the driver is notified early that the vehicle has entered the shielded area.

  In Patent Document 2, a three-axis angular velocity signal and a three-axis acceleration signal from a MEMS inertial sensor are received by an inertial navigation calculation unit, and each output from the inertial navigation calculation unit is output from a GPS sensor, a tire speed sensor, and a steering angle sensor. It is described that each output is subtracted to estimate and correct an error.

Patent Literature 3 discloses a method in which a road surface image is generated from image data acquired by a vehicle-mounted camera and a pseudo road surface image is generated from road information, and a correlation value between the road surface image and the pseudo road surface image is equal to or more than a certain value ( If it is determined that the deviation has increased), switching from automatic driving based on a GPS signal to manual driving by a driver is described.
Similarly, Patent Document 4 describes switching between automatic driving based on a GPS signal and manual driving by a driver.

  Non-Patent Document 1 and Non-Patent Document 2 describe the contents of a vehicle traveling by RTK (Real Time Kinematics) -GPS.

JP-A-2006-38379 JP-A-2017-017796 JP 2018-077771 A JP-A-2006-124542

"Principles and Applications of RTK-GPS" Hiromune Namie http://www.nda.ac.jp/~nami/research/pdf/CGSIC2001.pdf "Research on Data Exchange of RTK-GPS" Tatsunori Sada et al. Civil Engineering Information Systems Vol.8 1999.p57-64

  At present, the position (absolute position) specified by the GPS signal has an error improved to several cm. However, the position is specified with high accuracy on the precondition that the GPS signal can be received with high sensitivity.

  An error called multipath occurs in the GPS system due to an obstacle (a building, a tree, an electric wire, or the like). When this multipath occurs, the position cannot be specified with high accuracy. When a human is driving, even if an error occurs in the position information of the own vehicle, the driving itself is not particularly hindered. For this reason, in Patent Literatures 1 and 2, the driver is notified only to that effect.

  However, when the vehicle is automatically driven based on the GPS signal, the position error specified by the GPS signal is directly reflected on the driving. Continuing driving without recognizing the error leads to an accident.

  Also in the related art, the reliability of the position information based on the GPS signal can be found by comparing the position information based on the inertial sensor (IMU) with the position information based on the GPS signal. When the reliability decreases, the automatic operation is stopped and the signal strength is restored. It is possible to wait until. However, in this case, the self-driving vehicle frequently stops for reasons other than traffic lights and traffic jams, and the driving with the surrounding vehicles cannot be coordinated, which may lead to traffic jams and accidents.

  Patent Literature 3 describes switching from automatic driving to manual driving, so that traffic confusion due to stopping can be avoided. However, since the driver is always required to ride on the vehicle, completely automatic driving is not achieved.

  Non-Patent Documents 1 and 2 describe a network type (RTK: Real Time Kinematics) GPS, but do not suggest any measures to be taken when the sensitivity of a GPS signal is reduced during automatic driving.

In order to solve the above-mentioned problems, the automatic operation method according to the present invention receives a GPS signal during traveling, acquires the position of the own vehicle in real time, and moves the acquired position of the own vehicle along a predetermined target trajectory. When the vehicle detects that the reliability of the position accuracy of the vehicle detected by the GPS signal has deteriorated, the vehicle travels using an inertial measurement unit (IMU) including a gyro and an accelerometer. In the traveling by the inertial measurement device (IMU), the vehicle travels while matching the coordinates and the azimuth angle of the GPS system with the coordinates and the azimuth angle of the inertial measurement device (IMU).
The vehicle body slip angle required for obtaining the coordinates and the azimuth angle by the inertial measurement device (IMU) is calculated using an equation derived from a vehicle model or a model identification experimental equation.

  When the vehicle is switched to the inertial measurement device (IMU), the position of the vehicle acquired by the inertial measurement device (IMU) and a point on the target trajectory are curve-interpolated with a clothoid curve or the like, and along the interpolated curve. Run and get on the target track.

The traveling speed after switching to the inertial measurement device may be the same as that for GPS traveling. However, since the position accuracy by the inertial measurement device is generally lower than the positional accuracy by GPS, safe traveling can be achieved by switching to the inertial measurement device. It is preferable to run at a reduced speed to a speed that can be confirmed.
The determination as to whether or not the position accuracy detected by the GPS signal is reliable is made based on, for example, the position identification quality of NMEA (National Marine Electronic Association) 0183.

In order to return to the target trajectory from the position of the own vehicle deviating from the target trajectory, the yaw rate, the vehicle body slip angle, and the vehicle speed detected by the inertial measurement device (IMU) are substituted into a calculation formula and acquired.
In other words, the IMU performs a calculation for grasping and estimating a change in the position and the posture of the own vehicle in real time when the target trajectory is traced from the own vehicle position to the target trajectory. That is, the yaw rate, the vehicle body slip angle and the vehicle speed are substituted into a vehicle model formula or a formula using a stability factor. Here, the stability factor is a numerical value that can be obtained from a vehicle model by calculation or experiment and that can obtain a required steering angle with respect to the curvature of the route.

  According to the automatic operation method according to the present invention, even when the detection position accuracy based on the GPS signal is reduced, the automatic operation can be continued as it is, and the completely automatic operation without the driver's riding is possible.

  In addition, the automatic operation method according to the present invention basically does not stop the vehicle even when the detection position accuracy based on the GPS signal is reduced, so that the vehicle can be in harmony with the surrounding vehicles and does not cause a traffic jam or an accident. .

Illustration of target trajectory created from GPS data Illustration of the concept of VRS-GPS Illustration of the structure of GPS data (NMEA0183sentences) Diagram explaining how to obtain the actual steering angle from the curvature of the target trajectory Control flowchart Illustration of switching between GPS driving and inertial measurement device (IMU) driving Illustration of display

  First, in the present invention, a target trajectory is created in advance. As shown in FIG. 1, the target trajectory is created by manually driving a route to be operated and acquiring GPS data. Based on the acquired data, the latitude, longitude, and azimuth of a plurality of points (points N) from the start point to the end point of the route are obtained, an ID number is assigned to each point, and a route locus is created. Drive at speed.

When the vehicle starts traveling along the above-mentioned target locus, the position of the own vehicle is measured in real time by VRS (Virtual Reference Station) -GPS.
Here, as shown in FIG. 2, the VRS-GPS performs observation at a reference point (reference station) installed in advance and sends observation data to the VRS center. The VRS center to which the observation data has been sent creates correction data within $ abc surrounded by the reference station. On the other hand, the vehicle (mobile station) calls the VRS center from the mounted RTK-GPS and informs the VRS center of the current position by single positioning. The VRS center sends the correction data back to the vehicle such that the position determined independently becomes the reference station. With this, the position measured independently becomes a known station (virtual reference position), and the vehicle runs on RTK-GPS based on this position.

  In the case of this embodiment, the GPS data acquired by the vehicle is acquired in the NMEA0183 sentences format. NMEA0183 was originally standardized as an interface for connecting electronic devices such as an acoustic detector, a sonar, an anemometer, and a gyrocompass, and includes not only positional information but also information on errors.

  As shown in FIG. 3, the GPS data (NMEA0183 sentences) is composed of 25 types of sentences (left side in FIG. 3). Each sentence starts with “＄” and ends with “*”. The hexadecimal number after “*” confirms the presence or absence of an error.

“CGA” of the 25 sentences contains time, position, and position determination related data. The time in Coordinated Universal Time, longitude, north latitude, longitude, east longitude, and so on are followed by “numbers. These numbers are 0, 1, 2, 3, and 4 in the order of the poorest location quality.
Further, there is position error statistical data in “GST”, and the error of the major axis, minor axis, latitude, longitude and altitude of the error ellipse is displayed in one sigma (meter unit). That is, the magnitude of the error can be known from “GGA” or “GST”.
In the present embodiment, the position data of “GGA” is used for generating the target trajectory, and when the error number of “GGA” becomes smaller than the threshold value (less than 3), the driving is switched from the GPS driving to the IMU driving, and at the same time, the IMU driving is performed. Reduce the speed to a speed that will not interfere with running. “GST” may be used instead of the error value of “GGA”.

  In order to join the target locus from the deviated position and travel along the target locus, an actual steering angle is obtained from the curvature of the target locus. As shown in the left part of FIG. 4 (steady circular turning), revolving motion around the center of the turning circle and rotational motion around the center of gravity of the vehicle are performed. The sum of the revolution speed and the rotation speed becomes the yaw angular speed (yaw rate, γ). A centrifugal force is generated that is proportional to the square of the vehicle speed and the vehicle mass, and the tire generates a centripetal force that balances the centrifugal force and turns.

  The centripetal force generated by the tire is based on a frictional force (corner force) proportional to the tire slip angle. Although the tire side slip angle (β) is controlled by the front wheel actual steering angle, the rear wheel tire has no steering mechanism, so that the body slips to generate the rear wheel side slip angle. In this state, when the steering wheel is fixed and the vehicle speed is gradually increased, the turning radius increases, and the vehicle body side slip angle changes from the minus side to the plus side. A graph of the relationship is shown in the center of the figure.

The change gradient of the turning radius with respect to the square of the vehicle speed is referred to as a stability factor (K _SF ), and the change in the vehicle body side slip angle is referred to as a side slip coefficient (K _βO ). Changes in the position and speed of the vehicle can be detected by GPS, and the position and the vehicle slip angle (β) of the vehicle can be calculated from the output values of the gyro and the accelerometer of the IMU mounted on the vehicle.

As for the vehicle speed obtained by GPS, the absolute speed (v) shown in the figure is obtained, whereas the speed obtained from the IMU is obtained by integrating the longitudinal speed (v _x ) as the integral value of the longitudinal acceleration and the integral value of the lateral acceleration. Lateral velocity (v _y ). The absolute velocity (v) is obtained by combining the longitudinal velocity (v _y ) and the lateral velocity (v _x ), and the vehicle side slip angle (β) is obtained from the ratio of v _y / v _x .

In the case of the IMU, the accuracy is inferior to GPS because the absolute speed (v) is obtained by calculation, but the GPS has both advantages and disadvantages because the vehicle body slip angle cannot be obtained. By combining the GPS and the IMU, accuracy is improved by compensating for the length. The relationship between the turning radius (R _О ), the slip angle (β _と ) and the actual steering angle δ at an extremely low speed is shown on the right side of the figure.

  FIG. 5 is a flowchart of the automatic operation method according to the present invention. First, control is started in step 1, calibration of the inertial measurement device (IMU) is performed in step 2, an adjustment item for matching between the GPS and the IMU is determined, and the process proceeds to step 3.

  In step 3, the quality of the GPS data (NMEA0183 sentences) is checked, and if the position specifying quality is "3 or more", the flow proceeds to step 4 and the vehicle travels at a predetermined speed by GPS, and travels from step 5 to stop of step 6.

  On the other hand, if the position specifying quality is “less than 3”, the process proceeds to step 7, switches from GPS traveling to IMU traveling, maintains the default target vehicle speed (deceleration), and proceeds to step 8. If the quality has recovered to “3 or more” in step 8, the mode is switched from IMU traveling to GPS traveling in step 9 and the process returns to step 4.

  If the quality has not recovered to "3 or more" in step 8, the process proceeds to step 10 to check whether the distance of the IMU traveling exceeds a predetermined distance. If not, the vehicle speed is lowered. Then, the IMU traveling is continued, and the quality is further confirmed in step 12.

  If the quality has been confirmed and has not recovered to "3 or more", the vehicle stops at step 13 and returns to step 3 to wait for the recovery of the GPS quality.

  FIG. 6 is an explanatory diagram of switching between GPS traveling and traveling by an inertial measurement device (IMU). The upper part of the drawing shows traveling by GPS, and the lower part shows traveling by an inertial measurement device (IMU). At the (1) GPS target trajectory (target trajectory), manual operation is performed in advance to acquire the route GPS data, and the target trajectory (Xo, Yo, φo) is created offline. At the GPS control data of (2), the GPS data is acquired together with the positioning accuracy, and the target locus is traced while confirming the own vehicle position (Xn, Yn, φn) in real time.

(3) shows how to track the target trajectory. The host vehicle is at the point Pn and is about to get on the point Pv on the target locus. See attitude angle φn in Pn point, because it has been found attitude angle φ ₀ in Pv point can curve interpolation between Pn-Pv. The curve interpolation is preferably, but not limited to, a clothoid curve.

  When the positioning accuracy of the GPS decreases, the coordinates (Xn, Yn) of the Pn point are not known, and the azimuth angle at the Pn point, that is, the velocity vector direction is not known. Therefore, the coordinates (Xs, Xs, Ys) and travel using the attitude angle φs.

Switching of coordinates (Xn, Yn) at (10) in FIG. 6 and (Xs, Ys), performs the switching of the attitude angle phi ₀ and .phi.s, the switching is not possible inadvertently to the. Actual GPS positioning precision at the stage of commissioning line entering the operation is to know where on the service route can be received correctly, the coordinates at that location (Xn, Yn) and (Xs, Ys) and an attitude angle phi ₀ and φs Is grasped in association with the path ID, and the difference is used as an adjustment term to switch using the adjustment value added to the IMU data value.

  The positioning accuracy of the GPS is taken in (4) of FIG. 6, and the vehicle speed by GPS is taken in (5). This vehicle speed enters the vehicle speed adjustment map together with the positioning accuracy of (4) and is adjusted according to the positioning accuracy.

When the positioning accuracy is less than “3” as described in FIG. 5, the vehicle switches from GPS to IMU and continues traveling for a predetermined distance. If the positioning accuracy does not recover during that time, the vehicle decelerates.
Further, the inertial measurement device (IMU) of (6) calculates the own vehicle position (X _S , Y _S , φ _S ) by the accelerometer, the wheel speed, and the yaw rate by the gyro as described above.

Under conditions where the positioning accuracy is reduced, the vehicle speed v is not obtained absolute by GPS, the absolute vehicle speed v is divided by the cosine cosβ of the vehicle body slip angle β in the longitudinal velocity v _x obtained from the wheel speed. The β is obtained by dividing the lateral acceleration by (8) by the longitudinal acceleration. Alternatively, β by the approximate expression of (9) is also obtained and prepared. Whether to use β according to (8) or β (Equation 1) according to (9) is determined by repeatedly determining the trial operation.

(11) is provided with a changeover switch for β, and in (7) β (formula 2) obtained by substituting the absolute vehicle speed v by GPS into the model formula, and β obtained from the accelerometer or the approximate formula (formula 1). Is switched based on the GPS positioning accuracy.

The yaw rate 検 出 detected by the gyro in (12) is integrated to determine the yaw angle 、, and when the sum is added to β in (11) in (13), the sum becomes the azimuth angle φ _s . The cosine of φ _s is multiplied by the vehicle speed, and the current position X _S by the inertial measurement device (IMU) of (14) is multiplied by the vehicle speed by the sine of φ _S to obtain the current position Y _S by the inertial measurement device (IMU) of (15). obtain. Ideally, X _n , Y _n , φ _n by GPS and X _S , Y _S , φ _{S by} an inertial measurement unit (IMU) are matched, but in reality, the above-mentioned adjustment terms are required. The above item (10) is provided as an adjustment item. In _{(3) X S, Y S} , control by phi _S is _{X n, Y} n, is performed to phi _n.

FIG. 7 is an explanatory diagram of the concept of the display. Displays GPS and IMU status. Green when the condition is good, yellow when the function is low, and red when the function is low.

Claims (4)

  An automatic driving method for driving a vehicle along a predetermined target trajectory, wherein a GPS signal is received during driving to obtain the position of the own vehicle in real time, and the obtained position of the own vehicle is placed on the target trajectory. When the vehicle travels with such correction, when it is detected that the reliability of the position accuracy of the vehicle detected by the GPS signal has decreased, the vehicle is switched to traveling by an inertial measurement device (IMU). An automatic operation method in which traveling by an IMU is performed by matching the coordinates and the azimuth of the GPS system with the coordinates and the azimuth of the inertial measurement device (IMU).   2. The automatic operation method according to claim 1, wherein a vehicle body slip angle required for obtaining coordinates and an azimuth angle by the inertial measurement device (IMU) is calculated using an equation derived from a vehicle model or a model identification experimental equation. Automatic operation method characterized by performing.   2. In the automatic operation method according to claim 1, in a travel switched to the inertial measurement device (IMU), the position of the own vehicle acquired by the inertial measurement device (IMU) and a point on a target locus are represented by a clothoid curve or the like. An automatic operation method characterized by running with curve interpolation. 2. The automatic operation method according to claim 1, wherein the reliability of the position accuracy of the vehicle detected by the GPS signal is determined based on a position specifying quality indicated by NMEA (National Marine Electronic Association) 0183. Automatic operation method characterized by the following.

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