JP6717132B2 - Vehicle traveling control method and vehicle traveling control device - Google Patents

Description

The present disclosure relates to a vehicle travel control method and a vehicle travel control device that control a vehicle so as to follow a target trajectory.

As a technique for moving the controlled object so as to follow the target trajectory, for example, the technique described in Patent Document 1 is known. The technique described in Patent Document 1 is configured to generate a target trajectory based on a teaching value stored in a memory and control a control target so as to follow the target trajectory. Then, the deviation between the target trajectory and the actual trajectory is calculated, and the teaching value is corrected based on the deviation at the next driving. As a result, the actual traveling track is made to converge to the target track.

JP-A-64-88711

In the technique described in Patent Document 1, the deviation between the target trajectory and the actual trajectory is recorded in the memory while being associated with each position on the trajectory. Therefore, in order to achieve the technique described in Patent Document 1, it is necessary to accurately measure the position corresponding to the deviation.

In the field of vehicle control, it is well known to measure the traveling position of a vehicle using GPS. However, in the case of position measurement using GPS, it is not easy to obtain a desired accuracy in a city with many obstacles. Therefore, the technique described in Patent Document 1 may not be able to accurately correct the traveling trajectory for the next traveling with respect to the target trajectory.

Therefore, an object of the present disclosure is to realize vehicle traveling control that can accurately correct the traveling path of the next traveling even in a place where the traveling position of the vehicle cannot be accurately measured.

In order to achieve the above object, the present disclosure executes the following processing in a vehicle traveling control method that controls a vehicle so as to follow a target trajectory. That is, the vehicle body azimuth of the vehicle is detected, the lateral deviation amount of the actual traveling track with respect to the target trajectory is measured, and the detected vehicle body azimuth and the lateral deviation amount are stored in association with each other. The learning correction for correcting the target trajectory is executed based on

As a result, it is possible to accurately correct the traveling path for the next traveling without using the traveling position of the vehicle.

FIG. 1 is a block diagram generally showing an outline of a vehicle travel control system to which a vehicle travel control method and a vehicle travel control device according to an embodiment of the present disclosure are applied. It is explanatory drawing for demonstrating the amount of lateral deviation with respect to a target track|path with an actual traveling track. FIG. 8 is an explanatory diagram for explaining a process executed by a learning correction arithmetic unit according to the embodiment. FIG. 8 is an explanatory diagram for explaining a process executed by a learning correction arithmetic unit according to the embodiment. FIG. 8 is an explanatory diagram for explaining a lateral deviation amount and learning data used for learning correction according to the embodiment. It is explanatory drawing which shows the effect of the vehicle running control which concerns on an Example.

Hereinafter, modes for implementing the vehicle travel control method and the vehicle travel control device of the present disclosure will be described based on embodiments illustrated in the drawings.

FIG. 1 is a block diagram generally showing an outline of a vehicle travel control system 1 to which a vehicle travel control method and a vehicle travel control device according to an embodiment are applied. The overall system configuration will be described below with reference to FIG.

As shown in FIG. 1, the vehicle travel control system 1 includes an object detection sensor 21, a wheel speed sensor 22, a yaw rate sensor 23, a geomagnetic sensor 24, a GPS receiver 25, an object recognition calculator 30, an actual travel calculator 40, and A learning correction computing unit 50, a vehicle control computing unit 60, and an actuator 70 are provided. The vehicle traveling control system 1 is a system mounted on the vehicle 10.

The object detection sensor 21 detects the presence or absence of a preceding vehicle or an obstacle existing around the vehicle 10. The object detection sensor 21 is, for example, a scanning laser radar, a millimeter wave radar, or the like.

The wheel speed sensor 22 is provided on the left and right driven wheels of the vehicle 10 and detects the rotational speed of the driven wheels. The rotation speed detected by the wheel speed sensor 22 is used to calculate the vehicle speed and the traveling direction of the vehicle 10. The yaw rate sensor 23 detects the rotational angular velocity of the vehicle 10. The rotational angular velocity detected by the yaw rate sensor 23 is used to calculate the azimuth of the vehicle 10.

The geomagnetic sensor 24 detects a vehicle body direction indicating a traveling direction of the vehicle 10 based on the geomagnetism. The GPS receiver 25 receives radio waves from GPS satellites and calculates the position of the vehicle 10.

The object recognition computing unit 30 includes an object trajectory calculation unit 301 and a preceding vehicle determination unit 302. The object trajectory calculation unit 301 calculates the trajectory of the object detected by the object detection sensor 21.
The preceding vehicle determination unit 302 determines whether the detected object is a preceding vehicle based on the size of the object detected by the object detection sensor 21, the relative speed with the vehicle 10, and the trajectory of the object calculated by the object trajectory calculation unit 301. Determine whether or not. When the preceding vehicle following control is executed, the target trajectory of the vehicle 10 is generated based on the trajectory of the object determined by the preceding vehicle determination unit 302 as the preceding vehicle among the trajectory calculated by the object trajectory calculation unit 301. It That is, in such a case, the object trajectory calculation unit 301 also functions as the target trajectory generation unit. The object recognition computing unit 30 also calculates the detected vehicle speed of the preceding vehicle, the inter-vehicle distance between the preceding vehicle and the vehicle 10 and the like in order to realize follow-up control of the preceding vehicle.

The actual traveling calculator 40 includes a traveling trajectory calculation unit 401 and a heading detection unit 402. The running trajectory calculation unit 401 calculates the moving amount and moving direction of the vehicle 10 by, for example, dead reckoning from the outputs of the wheel speed sensor 22 and the yaw rate sensor 23, and based on the calculated moving amount and moving direction of the vehicle 10. The actual running track on which 10 actually traveled is calculated. Alternatively, the actual travel path may be calculated by calculating the movement amount and the movement direction of the vehicle 10 by odometry from the output of the wheel speed sensor 22.

The azimuth detecting unit 402 determines which azimuth the vehicle 10 faces on the relative coordinates with the vehicle 10 as the origin, based on the rotational angular velocity detected by the yaw rate sensor 23 and the azimuth (absolute azimuth) detected by the geomagnetic sensor. The relative direction shown is detected. In this specification, the “learning area” means a certain range in which learning correction to be described later is to be executed, and its coordinate (position) information (latitude, longitude, etc.) is stored in the memory 503 of the learning correction calculator 50. Remembered.

The learning correction calculator 50 includes a difference measurement unit 501, a correction amount calculation unit 502, a memory 503, and an area determination unit 504. The preceding vehicle traveling trajectory (target trajectory) and the actual traveling trajectory of the vehicle 10 calculated by the object trajectory calculating unit 301 and the traveling trajectory calculating unit 401, respectively, are input to the difference measuring unit 501. The difference measurement unit 501 measures the deviation (lateral deviation amount) of the actual traveling track from the received target track.

The lateral shift amount measured by the difference measurement unit 501 is input to the correction amount calculation unit 502. The correction amount calculation unit 502 calculates the correction amount by multiplying the lateral deviation amount measured by the difference measurement unit 501 by a correction coefficient set appropriately. The calculated correction amount is used to correct the control amounts of various actuators when performing follow-up control along the target trajectory, as will be described later.

The measurement of the lateral deviation amount and the calculation process of the correction amount are continuously executed while the vehicle 10 passes through the learning area. Then, in the technique described in Patent Document 1, the calculated correction amount and the like are stored in the memory in association with the position where the vehicle was present when the process was executed. On the other hand, in the embodiment of the present disclosure, the measured lateral deviation amount and the calculated correction amount are stored in the memory 503 in association with the vehicle body direction when the process is executed.

The area determination unit 504 determines whether the vehicle 10 is within the learning area stored in the memory 503 based on the position of the vehicle 10 calculated by the GPS receiver 25 and the traveling direction of the vehicle 10, and When it is determined that the vehicle 10 is in the learning area, it is determined in which learning area among the plurality of learning areas that may exist. That is, in the embodiment of the present disclosure, the GPS receiver 25 is mainly used only for the processing in the area determination unit 504.

The vehicle body direction of the vehicle 10 detected by the direction detection unit 402 and the determination result of the area determination unit 504 are also stored in the memory 503. That is, the lateral deviation amount measured by the difference measuring unit 501, the correction amount for the control amount in the follow-up control calculated by the correction amount calculating unit 502, the vehicle body direction detected by the direction detecting unit 402, and the determination of the area determining unit 504. The result is stored in the memory 503. As a result, the lateral shift amount, the correction amount, and the vehicle body direction are stored in the memory 503 in association with each other for each learning area.

Unlike the configuration in which the detection accuracy greatly changes depending on the measurement environment around the vehicle 10 like the GPS receiver 25, in the case of the yaw rate sensor 23 and the geomagnetic sensor 24, the detection accuracy rarely changes significantly depending on the measurement environment. Therefore, by having the configuration in which the calculated correction amount is stored in the memory 503 in association with the vehicle body direction, the correction amount can be accurately reflected in the correction of the control amount for the target trajectory. Further, the measurement result obtained by the GPS receiver 25 is used only for the determination of the learning area, and thus high measurement accuracy is not required.

The vehicle control computing unit 60 includes a target trajectory correction unit 601 and a travel control unit 602. When the vehicle 10 travels in a learning area in which the correction amount and the like are stored in the memory 503, the target trajectory correction unit 601 reads the correction amount (that is, the learning result) associated with the current vehicle body direction from the memory 503. Based on this, the target trajectory (preceding vehicle traveling trajectory calculated by the object trajectory calculator 301) is learned and corrected.

The control amount when the follow-up control is performed along the target trajectory corrected by the target trajectory correction unit 601 is transmitted to the traveling control unit 602. The traveling control unit 602 calculates each control command value for steering, an accelerator, a brake, etc. (none of which is shown) so that the vehicle 10 can travel in accordance with the received corrected control amount. Further, the actuator 70 is driven based on the calculated control command value. Although not shown, the actuator 70 includes a steering actuator, a drive actuator, a braking actuator, and the like.

Next, the processing executed by the learning correction computing unit 50 will be described with reference to FIGS. 2 and 3. FIG. 2 is a diagram showing how the vehicle 10 travels in the learning area 100. Further, FIG. 3 is a diagram showing the measurement result of the lateral shift amount and the like in the situation of FIG.

As shown in FIG. 2, when the target trajectory in the follow-up control is greatly curved, it is difficult to cause the vehicle 10 to accurately follow the target trajectory. Therefore, in such a case, it is necessary to correct the deviation (lateral deviation amount g) of the actual traveling track from the target track. Naturally, the lateral deviation amount g changes every moment while the vehicle 10 is traveling in the learning area, so it is necessary to store the calculated lateral deviation amount g in association with some information.

Therefore, in the present embodiment, as described above, the lateral shift amount g is stored in the memory 503 in association with the vehicle body direction φ. The position information (latitude/longitude information) is used only for determining the learning area 100.

The lateral shift amount g in the present embodiment is represented as a difference between the lateral position y on the actual traveling track and the lateral position y ^{* at} the corresponding point on the target track.

Next, a detailed configuration of the learning correction calculator 50 will be described with reference to FIGS. 4 and 5. FIG. 4 is an explanatory diagram for explaining the processing for the learning area, which is executed by the learning correction calculator 50.

In FIG. 4, a flag F1 indicates whether or not the driver of the vehicle 10 has performed an operation. That is, the bit of the flag F1 is set to 1 when the intervention by the driver is detected during the execution of the preceding vehicle following control, and the bit of the flag F1 is maintained at 0 unless the driver intervenes. The flag F2 indicates whether or not there is an obstacle avoidance operation. That is, when the object detection unit 21 detects an obstacle in front of the vehicle 10 (on the traveling road) and the avoidance operation for it is intervened, the bit of the flag F2 is set to 1; otherwise, the bit of the flag F2 is set. Is maintained at 0.

In addition to the bit values of the flags F1 and F2 described above, map information is input to the area determination unit 504. The map information is updated at any time such as when the vehicle 10 is maintained.

The learning correction computing unit 50 searches the map information input to the area determination unit 504 for an area (place) where the radius of curvature of the traveling path is equal to or greater than a predetermined value, and sets the corresponding area as a learning area. Here, the area in which the radius of curvature of the traveling road is equal to or greater than a predetermined value is assumed to be, for example, an intersection, a sharp curve road, a branch/join road, or a rampway. The position information (latitude, longitude, etc.) of the set learning area is stored in the memory 503.

In an area where the radius of curvature of the traveling path is equal to or larger than a predetermined value, it is expected that even if the follow-up control is executed, the target trajectory cannot be sufficiently followed by the control similar to the normal time. Therefore, such an area is set as a learning area in advance, and its position information is stored in the memory 503.

In addition, when the lateral deviation amount g of the actual traveling trajectory with respect to the target trajectory becomes equal to or larger than a predetermined amount as a result of traveling in a certain area, the learning correction computing unit 50 newly sets the area as a learning area and the position information thereof. Are stored in the memory 503. With such a configuration, it is possible to execute the learning correction and correct the control amount for the target trajectory even in an area where lateral deviation is not expected from the map information. As a result, it is possible to improve the followability to the target trajectory during the second and subsequent travels.

On the other hand, even when the area is preset as the learning area, the lateral deviation amount g is less than the predetermined amount as a result of actually traveling, or the lateral deviation amount g is the predetermined amount as a result of the learning correction described above. If it is less than this, it can be determined that further learning correction is unnecessary. Therefore, in such a case, the learning correction computing unit 50 may erase the learning area from the control target. Note that the predetermined amount may be the same value as the above-described predetermined amount serving as a threshold value when a learning area is newly set, or may be a different value.

Further, even at the same point, the traveling locus (turning radius) drawn when the vehicle 10 turns on the outward path and the return path are different at, for example, an intersection. Therefore, in the embodiment of the present disclosure, the outward route and the return route are set as separate learning areas even at the same point, and the position information thereof is stored in the memory 503.

In addition, regarding a learning area that has not been traveled for a predetermined period (for example, one year), the travel frequency may be considered to be sufficiently low, and the related information may be deleted from the memory 503.

Further, the learning correction computing unit 50 does not perform the learning correction when the value of one of the bits of the flag F1 and the flag F2 input to the area determination unit 504 is 1. More precisely, when the value of any one of the flags F1 and F2 is 1, the lateral deviation amount g measured by the difference measuring unit 501 and the correction amount calculated by the correction amount calculating unit 502 are stored in the memory 503. I can't remember.

That is, it means that the vehicle 10 did not properly execute the follow-up traveling control for traveling along the target trajectory when the driver intervenes. Therefore, in order to prevent the learning correction from being performed using the correction amount measured under such a situation, the lateral shift amount g and the correction amount concerned are not stored in the memory 503 in such a case. Further, even when there is an obstacle avoidance operation intervention, it means that the follow-up traveling control is not properly executed, and therefore the lateral deviation amount g and the correction amount are not stored in the memory 503 in such a case.

Further, as well shown in FIG. 5, the learning correction computing unit 50 enlarges or reduces the learning area according to the lateral deviation amount g2 after learning correction. Specifically, the range of the learning area is changed so that the range in which the lateral deviation occurs is included in the learning area. Note that only the range in which the lateral deviation has occurred may be used as the learning area, or the range in which a predetermined range is added to the range in which the lateral deviation has occurred may be used as the learning area.

By appropriately enlarging or reducing the learning area as described above, the range of the learning area can be made necessary and sufficient. As a result, it is possible to improve the followability to the target trajectory without increasing the data capacity excessively.

In the embodiment of the present disclosure, when the learning data before the learning correction is s1, the lateral deviation amount at the next running after the learning correction based on the learning data s1 is g2, and the learning coefficient is k The learning data s2 obtained during the next running is represented by the following formula.
s2=s1+k*g2 (k=0.0 to 1.5)
However, the above formula and learning coefficient are merely examples, and the present invention is not limited to these. When the vehicle travels again in the learning area, the current learning data s2 is substituted into s1 of the above equation, and new learning data s2 is obtained based on the same idea.

FIG. 6 is an explanatory diagram showing the effect of the vehicle traveling control according to the embodiment. It can be clearly seen from FIG. 6 that the trackability with respect to the target trajectory is gradually improved by executing the vehicle traveling control described above.

In the vehicle travel control method and the vehicle travel control device according to the above-described embodiment, the following effects can be obtained.

(1) In the vehicle travel control method of controlling the vehicle 10 so as to follow the target trajectory, the vehicle body orientation φ of the vehicle 10 is detected (the yaw rate sensor 23, the geomagnetic sensor 24, the orientation detection unit 402), and the actual traveling to the target trajectory is performed. The lateral deviation amount g of the trajectory is measured (object trajectory generation unit 301, preceding vehicle determination unit 302, running trajectory calculation unit 401, difference measurement unit 501), and the detected vehicle body orientation φ and lateral deviation amount g are stored in association (memory 503), the next time the vehicle travels, learning correction is performed to correct the target trajectory based on the stored vehicle body direction φ and lateral deviation amount g (correction amount calculation unit 502, memory 503, target trajectory correction unit 601).

That is, the measured lateral deviation amount g is stored in association with the vehicle body orientation φ when the process is executed. Therefore, unlike the position information that may greatly affect the detection accuracy depending on the place where the learning correction is executed, the lateral deviation amount g can be stored in association with the vehicle body orientation φ that can realize the relatively stable detection accuracy. As a result, the learning result can be accurately reflected in the correction of the control amount for the target trajectory at the time of next running.

(2) Further, the current position information of the vehicle 10 is acquired (GPS receiver 25), it is determined whether the vehicle 10 exists in the learning area based on the position information (area determining unit 504), and the vehicle 10 becomes the learning area. If it is determined that there is a lateral deviation amount g corresponding to the learning area, learning correction is executed (learning correction calculator 50, target trajectory correction unit 601).

That is, if the lateral deviation amount g between the target trajectory and the actual traveling trajectory is associated only with the vehicle body orientation φ, when the same vehicle body orientation φ is repeatedly generated during traveling, for example, when the vehicle travels in a zigzag manner, the vehicle travels in different places. Nevertheless, there is a possibility that the wrong lateral deviation amount g (correction amount) may be read from the stored lateral deviation amount g. However, since the lateral displacement amount g is stored in association with not only the vehicle body direction φ but also the learning area with the above-described configuration, in addition to the effect of (1), the incorrect lateral displacement amount g (correction amount) is obtained. Can be prevented from being read.

(3) Further, when lateral shift amount g measured during actual running of the vehicle is equal to or greater than a predetermined amount, and obtains the positional information of the vehicle, the learning area, Ru is based-out set to the acquired position information (learning correction Computing unit 50, difference measurement unit 501, memory 503, GPS receiver 25, area determination unit 504). Thereby, in addition to the effect of (2), the learning correction can be surely executed in the learning area where it can be determined that the learning is particularly necessary. Therefore, the following accuracy of the vehicle 10 can be improved in the following control execution.

(4) Further, a place where the radius of curvature of the traveling road is equal to or larger than a predetermined value is searched from the map information, and the searched place is set as a learning area (learning correction computing unit 50, memory 503, area determination unit 504). ). As a result, in addition to the effects of (2) and (3), it is possible to predict in advance a place where the lateral deviation amount g is relatively large, and improve the tracking accuracy of the vehicle 10 in the second and subsequent travel tracking controls. be able to.

(5) Further, based on the detected vehicle body direction φ, the forward path and the return path are set as independent learning areas (learning correction computing unit 50, memory 503, area determination unit 504). That is, even at the same intersection or the like, the traveling path (turning radius) drawn when the vehicle 10 turns is different between the outward path and the return path. Therefore, by setting the forward path and the return path as separate learning areas, the accuracy of learning correction can be further improved in addition to the effects of (3) and (4).

(6) Further, among the learning areas, the area that has not been traveled for a predetermined period (for example, one year) is deleted (learning correction computing unit 50, memory 503, area determination unit 504). In other words, it is considered that an occupant does not feel a sense of discomfort in an area where the traveling frequency is low even if the learning correction is not sufficiently performed. Therefore, such an area is excluded from the learning area. As a result, in addition to the effects (2) to (5), the used capacity of the memory 503 can be suppressed.

(7) Further, as a result of performing the learning correction, when the lateral deviation amount g is less than the predetermined amount, the corresponding learning area is erased (learning correction computing unit 50, memory 503, area determination unit 504). When the lateral deviation amount g is less than the predetermined amount as a result of the learning correction, it can be determined that no further learning correction is necessary. Therefore, in such a case, the learning correction computing unit 50 may erase the learning area from the control target. As a result, in addition to the effects (2) to (6), the used capacity of the memory 503 can be suppressed. Note that the predetermined amount may be the same value as the above-described predetermined amount serving as a threshold value when a learning area is newly set, or may be a different value.

(8) Further, the learning area is enlarged or reduced according to the measurement result of the lateral deviation amount g at the time of the next traveling (learning correction computing unit 50). Specifically, the range of the learning area is changed so that the range in which the lateral deviation occurs is included in the learning area. Thereby, in addition to the effects (2) to (7), the range of the learning area can be made necessary and sufficient. Therefore, it is possible to improve the followability with respect to the target trajectory without excessively increasing the data capacity.

(9) Further, when there is a driving intervention by the driver of the vehicle 10, the storage of the lateral shift amount g is stopped (learning correction computing unit 50, memory 503). That is, in the first place, when the driver intervenes, the vehicle 10 does not properly execute the follow-up traveling control for traveling along the target trajectory. Therefore, in order to prevent the learning correction from being performed using the correction amount measured under such a situation, the lateral deviation amount g and the correction amount are not stored in the memory 503 in such a case. Thus, in addition to the effects (1) to (8), it is possible to avoid improper learning correction of the control amounts of various actuators when performing follow-up control along the target trajectory.

(10) When the obstacle is detected and the obstacle avoidance control for avoiding the detected obstacle is executed, the storage of the lateral deviation amount g is stopped (learning correction arithmetic unit 50, memory 503). That is, when the obstacle avoidance control intervenes, the vehicle 10 did not properly execute the follow-up traveling control for traveling along the target trajectory, as in the case where the driver intervention described above occurs. Therefore, in such a case, the corresponding lateral deviation amount g and correction amount are not stored in the memory 503. As a result, in addition to the effects (1) to (9), it is possible to avoid improper learning correction of the control amount for the target trajectory.

(11) Further, a controller (object recognition computing unit 30, learning correction computing unit 50, vehicle control computing unit 60) that controls the vehicle 10 so as to follow the target trajectory and the vehicle body orientation of the vehicle 10 are detected. In the vehicle traveling control device (vehicle traveling control system 1) including the azimuth detector (yaw rate sensor 23, geomagnetic sensor 24), the controller measures the lateral deviation amount g of the actual traveling trajectory with respect to the target trajectory (measurement unit (difference)). The measurement unit 501), the memory 503 that stores the detected vehicle body direction φ and the lateral deviation amount g in association with each other , the positional information of the vehicle 10 is acquired at the time of the next traveling, and the vehicle 10 is set as a learning area based on the acquired positional information. When it is determined that there is a lateral deviation amount g with respect to the learning area, a learning correction unit (learning correction arithmetic unit 50) that corrects the target trajectory based on the stored vehicle body orientation φ and lateral deviation amount g And a drive unit (travel control unit 602) that drives the actuator 70 of the vehicle 10 based on the corrected target trajectory.

That is, the measured lateral deviation amount g is stored in association with the vehicle body orientation φ when the process is executed. Therefore, unlike the position information that may greatly affect the detection accuracy depending on the place where the learning correction is executed, the lateral deviation amount g can be stored in association with the vehicle body orientation φ that can realize the relatively stable detection accuracy. As a result, the learning result can be accurately reflected in the correction of the control amount for the target trajectory at the time of next running.

As described above, the vehicle travel control method and the vehicle travel control device of the present disclosure have been described based on the embodiment, but the specific configuration is not limited to this embodiment, and is related to each claim of the claims. Design changes and additions are allowed without departing from the spirit of the invention.

In addition, in the embodiment, as the object detection sensor 21, a scanning laser radar or a millimeter wave radar is exemplified. However, the object detection sensor 21 is not limited to this. For example, the object may be detected based on the image in front of the vehicle captured by the camera.

Further, in the embodiment, the example has been described in which the learning correction computing unit 50 automatically searches for and sets the learning area to be subjected to the learning correction from the map information. However, the user may be allowed to set the learning area by directly inputting the position information.

Further, in the embodiment, the lateral deviation amount g and the correction amount are stored in association with only the vehicle body direction φ, but if the position measurement accuracy by the GPS receiver 25 can be sufficiently secured, the vehicle body direction φ is added. The position information obtained by the GPS receiver 25 may be combined and stored.

10 vehicle, 21 object detection sensor, 23 yaw rate sensor, 24 geomagnetic sensor, 25 GPS receiver, 30 object recognition arithmetic unit, 301 object trajectory calculation unit, 302 preceding vehicle determination unit, 40 traveling arithmetic unit, 401 traveling trajectory calculation unit , 402 azimuth detecting unit, 50 learning correction computing unit, 501 difference measuring unit, 502 correction amount calculating unit, 503 memory, 504 area determination unit, 60 vehicle control computing unit, 601 target trajectory correction unit, 602 running control unit, 70 Actuator

Claims (10)

In a vehicle traveling control method for controlling a vehicle to follow a target trajectory,
Detecting the body direction of the vehicle,
Measuring the amount of lateral deviation of the actual running track with respect to the target track,
The detected vehicle body direction and the lateral deviation amount are stored in association with each other,
When the vehicle travels next time, the positional information of the vehicle is acquired, and it is determined that the vehicle is present in the learning area based on the acquired positional information, and if the lateral deviation amount corresponding to the learning area is present, A vehicle traveling control method comprising: performing a learning correction for correcting the target trajectory based on the stored vehicle body direction and lateral deviation amount. The vehicle travel control method according to claim 1 ,
When the lateral displacement amount measured during actual traveling of the vehicle is equal to or greater than a predetermined amount, the positional information of the vehicle is acquired,
The learning area, the vehicle travel control method characterized by that will be based-out set to the acquired position information. In the vehicle travel control method according to claim 1 or 2 ,
Search the place where the radius of curvature of the route is more than a predetermined value from the map information,
The vehicle travel control method, wherein the searched location is set as the learning area. The vehicle travel control method according to claim 2 or 3 ,
A vehicle traveling control method, characterized in that the forward path and the return path are set as independent learning areas based on the detected vehicle body direction. The vehicle running control method as claimed in any one of claims 1 to 4,
Among the learning areas, a vehicle travel control method is characterized in that an area that has not been traveled for a predetermined period or more is deleted. The vehicle running control method as claimed in any one of claims 1 to 5,
As a result of performing the learning correction, if the lateral deviation amount is less than a predetermined amount, the corresponding learning area is deleted. The vehicle travel control method according to any one of claims 1 to 6 ,
The vehicle traveling control method, wherein the learning area is enlarged or reduced according to a result of measuring the lateral deviation amount during the next traveling. In the vehicle travel control method according to any one of claims 1 to 7 ,
A vehicle traveling control method, wherein storage of the lateral deviation amount is stopped when there is a driving intervention by a driver of the vehicle. In the vehicle travel control method according to any one of claims 1 to 8 ,
A vehicle travel control method, which detects an obstacle and stops the storage of the lateral deviation amount when the obstacle avoidance control for avoiding the detected obstacle is executed. In the vehicle travel control device,
A controller that controls the vehicle to follow the target trajectory,
An azimuth detector for detecting the vehicle body azimuth of the vehicle,
And the controller is
A measuring unit for measuring the amount of lateral deviation of the actual traveling track with respect to the target track,
A memory that stores the detected vehicle body direction and the lateral displacement amount in association with each other;
When the vehicle travels next time, the positional information of the vehicle is acquired, and it is determined that the vehicle is present in the learning area based on the acquired positional information, and if the lateral deviation amount corresponding to the learning area is present, A learning correction unit that corrects the target trajectory based on the stored vehicle body direction and lateral deviation amount;
A drive unit that drives the actuator of the vehicle based on the corrected target trajectory;
A vehicle travel control device comprising: