JP6793787B1 - Vehicle control device, parking support device, vehicle control method and parking support method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a vehicle control device and a parking support device which eliminate the possibility of collision with an obstacle in a blind spot which cannot be detected by a sensor. An unspecified area is a region in which the presence or absence of an object around the vehicle is recognized and the presence or absence of the object cannot be recognized based on the peripheral condition obtained by a detection sensor that detects the surrounding condition of the vehicle. The object recognition unit that recognizes as, and outputs these as the recognition result, the travel route calculation unit that calculates the travel route based on the vehicle position and the recognition result detected by the vehicle position detection unit, and the travel route calculation unit. A control unit that controls steering according to the calculated travel path is provided, and the travel path calculation unit calculates the travel path assuming that the object exists in an unspecified region. [Selection diagram] Fig. 1

Description

The present invention relates to a vehicle control device and a parking support device, and more particularly to a vehicle control device and a parking support device that realize vehicle control and parking support at the time of leaving the parking lot.

In the conventional vehicle control device, when the vehicle is discharged from the parking lot, for example, as disclosed in Patent Document 1, the locus based on the steering angle and the rotational state of each wheel when the vehicle is parked in the parking lot is obtained. The vehicle is delivered by controlling the actuator and the wheel drive device so as to memorize and trace the memorized trajectory in the reverse direction.

JP-A-2007-62625

In the conventional vehicle control device, for example, when leaving the parking space, when the own vehicle automatically generates a travel route for leaving the garage, the own vehicle moves at the time of warehousing (the period from the start of warehousing to the end of warehousing). The travel locus is memorized as a travel locus, and the memorized travel locus is used as a travel route for leaving the vehicle. Therefore, for example, if an obstacle that did not exist at the time of warehousing exists in the traveling route for traveling out of the garage, the own vehicle may collide with the obstacle. In particular, when an obstacle that did not exist at the time of warehousing exists in a place that becomes a blind spot of the obstacle detection sensor, it is not possible to generate a traveling route for avoiding the obstacle by using the obstacle detection sensor.

The present invention has been made to solve the above problems, and an object of the present invention is to provide a vehicle control device and a parking support device that eliminate the possibility of collision with an obstacle in a blind spot that cannot be detected by a sensor. And.

The vehicle control device according to the present invention recognizes the presence / absence of an object around the own vehicle and determines the presence / absence of the object based on the peripheral condition obtained by the detection sensor that detects the surrounding condition of the own vehicle. An object recognition unit that recognizes an unrecognizable area as an unspecified area and outputs these as a recognition result, a vehicle position detected by the vehicle position detection unit, and a travel route calculation that calculates a travel route based on the recognition result. The travel path calculation unit includes a unit and a control unit that controls steering according to the travel path calculated by the travel route calculation unit, and the travel route calculation unit assumes that the object exists in the unspecified region of the travel path. calculates have rows, the object recognition unit is configured to create a segmented virtual space in a lattice shape on the vehicle periphery including the vehicle, the first occupied in the initial state to be assigned to the unspecified area in all grid A second occupancy degree, the object, indicating that the lattice of the virtual space is occupied by the object based on the virtual space storage unit that allocates and stores the degree and the position of the own vehicle and the surrounding situation. In the occupancy calculation unit for calculating the third occupancy, which indicates that the object is not occupied, and the first occupancy, which indicates that it is unknown whether or not the object is occupied, and the virtual space storage unit. The virtual space is assigned to the lattice of the stored virtual space by assigning any of the first occupancy, the second occupancy, and the third occupancy calculated by the occupancy calculation unit. It has a virtual space update unit that is updated, stored in the virtual space storage unit, and output to the travel route calculation unit, and the travel route calculation unit is based on the updated virtual space. gratings with 2 of occupancy, and said lattice having a first occupancy intends line calculation of the travel path as the object is present.

It is possible to eliminate the possibility of collision with an obstacle in the blind spot that cannot be detected by the sensor.

It is a block diagram which shows the structure of the vehicle control device of Embodiment 1 which concerns on this invention. It is a flowchart which shows the whole operation of the vehicle control device of Embodiment 1 which concerns on this invention. It is a block diagram which shows the structure of the object recognition part of Embodiment 1 which concerns on this invention. It is a figure explaining the setting method of a sensor model. It is a figure explaining the determination method of the occupancy calculation grid. It is a figure explaining the determination method of the occupancy calculation grid. It is a figure explaining the determination method of the occupancy calculation grid. It is a figure explaining the determination which region of the sensor model the lattice coordinates belong to. It is a flowchart which shows the object recognition process of the object recognition part of Embodiment 1 which concerns on this invention. It is a block diagram which shows the structure of the traveling path calculation part of Embodiment 1 which concerns on this invention. It is the figure which showed the locus that the right front wheel passes at the time of turning. It is the figure which showed the locus through which the left rear wheel passes at the time of turning. It is a flowchart which shows the traveling route calculation processing of the traveling route calculation unit of Embodiment 1 which concerns on this invention. It is a block diagram which shows the structure of the parking support device of Embodiment 2 which concerns on this invention. It is a figure which shows the surrounding situation at the start of parking support. It is a flowchart which shows the whole operation of the parking support device of Embodiment 2 which concerns on this invention. It is a figure which shows typically the result of performing the object recognition processing at the time of retreat delivery. It is a figure which shows an example of the traveling route at the time of performing the front approach storage. It is a figure which shows an example of the map of the movement path and the target curvature at the time of warehousing. It is a figure which shows an example of the map of the movement path and the target curvature in the 1st delivery travel path. It is a figure which shows typically the result of performing the object existence extraction processing at the time of retreat delivery. It is a figure which shows the situation that there is an obstacle which was not present at the time of warehousing at the time of retreat delivery. It is a figure explaining the case where the 1st warehousing travel route is used in the situation where there is an obstacle which was not present at the time of warehousing at the time of retreating warehousing. It is a figure explaining the case where the 2nd warehousing travel route is used in the situation where there is an obstacle which was not present at the time of warehousing at the time of retreating warehousing. It is a figure explaining the case where the 2nd warehousing travel route is used in the situation where there is an obstacle which was not present at the time of warehousing at the time of retreating warehousing. It is a figure explaining the case where the 2nd warehousing travel route is used in the situation where there is an obstacle which was not present at the time of warehousing at the time of retreating warehousing. It is a figure which shows an example of the map of the movement path and the target curvature in the 1st delivery travel path and the 2nd delivery travel path. It is a flowchart which shows the traveling route comparison processing of the traveling route comparison part of Embodiment 2 which concerns on this invention. It is a figure which shows the route division schematically. It is a figure which shows the route division schematically. It is a block diagram which shows the structure of the parking support device of Embodiment 3 which concerns on this invention. It is a flowchart which shows the whole operation of the parking support device of Embodiment 3 which concerns on this invention. It is a flowchart which shows the traveling route comparison processing of the traveling route comparison part of Embodiment 3 which concerns on this invention. It is a flowchart which shows the traveling route recalculation processing of the traveling route comparison part of Embodiment 3 which concerns on this invention. It is a flowchart which shows the traveling route recalculation processing of the traveling route comparison part of Embodiment 2 which concerns on this invention. It is a figure which shows the hardware configuration which realizes the vehicle control device of Embodiment 1 which concerns on this invention. It is a figure which shows the hardware configuration which realizes the vehicle control device of Embodiment 1 which concerns on this invention.

Hereinafter, embodiments of the vehicle control device according to the present invention will be described. In the description of the drawings, the same parts or corresponding parts are designated by the same reference numerals, and duplicate description will be omitted.

<Embodiment 1>
<Device configuration>
FIG. 1 is a functional block diagram showing the configuration of the vehicle control device 100 according to the first embodiment of the present invention. As shown in FIG. 1, the vehicle control device 100 receives the outputs of the surrounding situation detection sensor 1 and the vehicle position detection unit 2, respectively, and the outputs of the vehicle position detection unit 2 and the object recognition unit 3. The vehicle control unit 5 that receives the output of the travel route calculation unit 4 and the travel route calculation unit 4 to control the vehicle is provided.

Next, the operation of each configuration of FIG. 1 will be described. The surrounding situation detection sensor 1 is composed of at least one or more distance sensors attached to the vehicle, and outputs distance data to the detected object to the object recognition unit 3. Specifically, the distance sensor irradiates an object to be detected with ultrasonic waves, receives the ultrasonic waves reflected from the object, performs signal processing based on the time difference from the irradiated ultrasonic waves, and reaches the object. Detect the distance as distance data. In this case, only the distance to the object is obtained by the distance sensor, and the direction of the object may not be detected. In addition, the distance sensor detects distance data at a preset cycle. It is possible to mount multiple distance sensors on the vehicle, and it is possible to arbitrarily set the mounting position, but the distance sensors are mounted on the left front, right front, left rear and right rear of the vehicle, respectively. It is desirable to do.

Here, it is assumed that the mounting position of the distance sensor on the own vehicle, the sensor orientation information of the distance sensor, and the maximum detection distance of the distance sensor are known. The sensor orientation information includes the mounting orientation of the distance sensor and the sensor viewing angle. Further, the sensor viewing angle of the distance sensor corresponds to the directional width that can be detected by the sensor. The mounting position of the distance sensor on the vehicle, the sensor orientation information of the distance sensor, and the maximum detection distance of the distance sensor are collectively referred to as known sensor information.

As the distance sensor, a sensor of a type that detects the distance to an object as distance data by using a detection wave such as an electromagnetic wave instead of ultrasonic waves may be used. Specifically, as the distance sensor, an ultrasonic sensor, a millimeter wave radar, a laser radar, an infrared sensor and the like can be used.

The own vehicle position detection unit 2 detects the state related to the speed and the traveling direction of the own vehicle as the own vehicle data, and detects the position and the attitude angle of the own vehicle from the detected own vehicle data. Then, the detected position and posture angle of the own vehicle are output to the object recognition unit 3 and the travel path calculation unit 4. Specifically, the own vehicle position detection unit 2 detects a state related to the speed and the traveling direction of the own vehicle, such as the speed of the own vehicle, the wheel speed, the steering angle, and the yaw rate, as the own vehicle data. The own vehicle position detection unit 2 detects the own vehicle data at a preset cycle.

The vehicle position detection unit 2 may be configured so as to detect the latitude, longitude, and traveling direction of the vehicle as the vehicle data by using GPS (Global Positioning System).

Various methods can be considered for calculating the position and attitude angle of the own vehicle. As an example, a method using the yaw rate and the wheel speed will be described.

With the vehicle position and the vehicle attitude angle at the start of distance data acquisition from the surrounding situation detection sensor 1 as reference axes, the relative vehicle position coordinates and the vehicle are used for each detection of the vehicle data by the vehicle position detection unit 2. Calculate the attitude angle of the car.

The own vehicle position coordinates are based on the hourly movement distance obtained from the wheel speed output from the own vehicle position detection unit 2 and the hourly yaw angle obtained from the yaw rate output from the own vehicle position detection unit 2. , Calculate the moving position for each time, and add the moving position to the own vehicle position on the reference axis. Further, the posture angle of the own vehicle is obtained by adding the yaw angles for each time obtained from the yaw rate output from the own vehicle position detection unit 2 from the time of the reference axis. In the first embodiment, the origin of the reference axis is set at the position centered on the rear wheel axle in the vehicle width direction. However, no matter what position the reference axis is set, the present embodiment Does not affect 1. Further, the own vehicle position detected by the own vehicle position detection unit 2 is stored in a storage unit (not shown) in association with the time when the own vehicle data is detected.

The object recognition unit 3 recognizes the presence or absence of an object around the own vehicle based on the distance data detected by the surrounding situation detection sensor 1 and the own vehicle position and attitude angle detected by the own vehicle position detection unit 2. If the presence or absence of an object cannot be clearly recognized, it is recognized as an unspecified area, and the recognition result is output to the traveling route calculation unit 4.

The traveling route calculation unit 4 calculates the traveling route of the own vehicle based on the recognition result of the existence of the object output from the object recognition unit 3 and the own vehicle position and the attitude angle output from the own vehicle position detection unit 2. , Output to the vehicle control unit 5. At that time, in the recognition result of the existence of the object output from the object recognition unit 3, the traveling path is calculated assuming that the object exists for the unspecified region.

The vehicle control unit 5 performs steering control and drive control of the own vehicle so that it can follow the travel path output from the travel path calculation unit 4.

<Overall operation>
Next, the overall operation of the vehicle control device 100 according to the first embodiment will be described with reference to the flowchart shown in FIG. The processing of the flowchart of FIG. 2 is repeatedly executed while the vehicle is running. The relationship between each step in FIG. 2 and each functional block in FIG. 1 is as follows. Step S1 is an operation performed by the own vehicle position detection unit 2, step S2 is an operation performed by the peripheral situation detection sensor 1, step S3 is an operation performed by the object recognition unit 3, and step S4 is a travel route calculation. The operation is performed by the unit 4, and step S5 is an operation performed by the vehicle control unit 5.

Next, the operation of each step in FIG. 2 will be described. In step S1, the state related to the speed and the traveling direction of the own vehicle is detected as the own vehicle data, and the own vehicle position and the attitude angle are detected from the detected own vehicle data.

In step S2, the detection wave is irradiated to the object to be detected, and the reflected wave is acquired to detect the distance data between the own vehicle and the object.

In step S3, the presence / absence of an object around the own vehicle is recognized based on the position, attitude angle, and distance data of the own vehicle, and if the presence / absence of an object cannot be clearly recognized, it is recognized as an unspecified area.

In step S4, the traveling route of the own vehicle is calculated based on the recognition result of the position and attitude angle of the own vehicle and the existence of the object. At that time, in the recognition result of the existence of the object, the traveling path is calculated assuming that the object exists for the unspecified area.

In step S5, steering control and drive control of the own vehicle are performed so as to follow the calculated travel path.

<Object recognition processing>
Next, the object recognition process in the object recognition unit 3 will be described. FIG. 3 is a functional block diagram showing the configuration of the object recognition unit 3. As shown in FIG. 3, the object recognition unit 3 includes a virtual space storage unit 10, an occupancy calculation unit 11, and a virtual space update unit 12.

In the present embodiment, the object recognition unit 3 virtualizes the area around the vehicle position detected by the vehicle position detection unit 2 in a grid pattern at the start of acquiring the distance data output from the peripheral situation detection sensor 1. Create a space. Hereinafter, the virtual space divided in a grid pattern is referred to as a grid map. At least one grid exists in the grid map, and each grid of the grid map in the initial state is given an occupancy degree (first occupancy degree) indicating an unspecified area. Occupancy is a value that represents a measure of whether or not the grid is occupied by an object. In the above description, the virtual space is divided into grids to generate a map, but the division of virtual spaces is not limited to grids, and polygonal compartments such as triangles, pentagons, and hexagons. Any shape may be used as long as the virtual space can be efficiently divided.

Next, the operation of each functional block of FIG. 3 will be described. The virtual space storage unit 10 uses the vehicle position detected by the vehicle position detection unit 2 and the vehicle position based on the grid map updated by the virtual space update unit 12 from the current time t to the past time t−Δt. A grid map is generated around the position of the own vehicle detected by the detection unit 2. Specifically, it is confirmed whether the grid map updated at the time t−Δt is stored in the virtual space storage unit 10, and if the map is not stored, the current time detected by the own vehicle position detection unit 2 A grid map having a predetermined size is created based on the position of the own vehicle at t, stored in the virtual space storage unit 10, and the created grid map is output. On the other hand, when the grid map updated at the time t−Δt is stored, the stored grid map is read out and output.

The occupancy calculation unit 11 determines that each lattice in the lattice map is occupied by an object based on the lattice map output from the virtual space storage unit 10 and the distance data detected by the surrounding situation detection sensor 1. The occupancy shown (second occupancy), the occupancy indicating that the object is not occupied (third occupancy), and the occupancy indicating whether or not the object is occupied (first occupancy). Occupancy) is calculated and changed, and the change result is output.

By providing the object recognition unit 3 having such a configuration, it is possible to recognize a region where it is unknown whether or not it is occupied by an object as an unspecified region, and it is possible to supplement the blind spot of the sensor.

An example of how to change the occupancy degree will be described below. First, a sensor model is calculated based on the distance data detected by the surrounding situation detection sensor 1, known sensor information, and the vehicle position detected by the vehicle position detection unit 2, and is output from the virtual space storage unit 10. Based on the grid map and the detection range of the peripheral situation detection sensor 1 output from the sensor model, a grid (occupancy calculation grid) for calculating the occupancy of the grid map is determined. Then, whether or not those grids are occupied is set as a random variable, and the occupation probability density function p ( _mi | z _{1: t} ) of the occupation degree calculation grid is based on the distance data detected by the peripheral situation detection sensor 1. By calculating, the calculation result is the occupancy of the grid. However, _mi is the occupancy calculation grid of the i-th index, and z _{1: t} is the distance data obtained by the peripheral situation detection sensor 1 up to the time t.

An example of the sensor model is shown in FIG. In FIG. 4, a diamond-shaped sensor model SM is shown, the position where the detection wave is generated is set as the origin OP, the maximum detection distance is expressed as maxDist, the distance that becomes the maximum irradiation width is expressed as the maximum irradiation range distance maxAngDist, and the distance r. The irradiation range in is shown as θ (r). As for the detection range θ of the peripheral situation detection sensor 1, as shown in FIG. 4, the detection range is set to take the half width θmaxHalfBeamWith of the maximum irradiation range θmax in the maximum irradiation range distance maxAngDist, and the maximum irradiation range distance maxAngDist or more. In terms of distance, the irradiation range may be narrowed as shown in the following mathematical formula (1).

The above mathematical formula (1) defines the detection range θ of the distance sensor of the peripheral situation detection sensor 1. Here, considering the symmetry with respect to the sensor orientation of the sensor model, the mathematical formula (1) is based on the irradiation range upper limit θmax (1). Only r) is shown.

In the above formula (1), min (1.0, 1.0- (r-maxAngDist) / (maxDist-maxAngDist)) is 1.0 and 1.0- (r-maxAngDist) / (maxDist-maxAngDist). ) Means the smaller one, and the irradiation range at a distance greater than or equal to the maximum irradiation range distance maxAngDist is restricted by multiplying the smaller one by HalfBeamWith.

As a method of determining the occupancy calculation grid, as shown in FIG. 5, the common area between the sensor model SM of the peripheral situation detection sensor 1 and the grid map LM is extracted, and the grid in the grid map included in the common area is extracted. Occupancy calculation grid OCL.

Note that FIG. 5 shows the positional relationship between the own vehicle OV and the parked vehicle PV at the current time t, while FIG. 6 shows the positional relationship between the own vehicle OV and the parked vehicle PV at the time t-2Δt. The occupancy calculation grid OCL in the case is shown. Further, FIG. 7 shows the positional relationship between the own vehicle OV and the parked vehicle PV at time t−Δt, and shows the occupancy calculation grid OCL in that case. 6 and 7 show a state in which the own vehicle OV moves backward to the left side of the parked vehicle PV in parallel with respect to the parked vehicle PV.

In the occupancy calculation grid OCL at time t-2Δt shown in FIG. 6, the distance between the own vehicle OV and the parked vehicle PV is large, and the distance sensors on the right rear and right rear sides of the own vehicle OV detect the parked vehicle PV. However, the common part between the sensor model SM of the distance sensor on the right rear side surface and the initial map LM is only a part, and the number of occupancy calculation grids OCL is small, but at the time t−Δt shown in FIG. The common part between the sensor model SM of the distance sensor on the right rear side surface and the initial map LM is almost the entire sensor model SM, and the number of occupancy calculation grids OCL is larger than that at time t-2Δt. At time t shown in 5, the distance sensor on the right front side surface of the own vehicle OV detects the parked vehicle PV, and the number of occupancy calculation grids OCL is further increased.

Next, a method of calculating the occupancy of the occupancy calculation grid will be described. First, the occupancy probability density function p ( _mi | z _{1: t} ) uses the logarithmic odds l _{t and i} at time t, which are the values obtained by taking the natural logarithm of the odds ratio _, by using the following mathematical formula (2). And it can be expressed as (3).

Here, the occupancy probability density function p ( _mi | z _{1: t} ) can be expressed by logarithmic odds l _{t, i} , so that the probability expressed by 0 to 1 can be expressed by −∞ to ∞. , It is possible to prevent digit loss after the decimal point. Further, the occupancy probability density function p ( _mi | z _{1: t} ) expressed by the logarithmic odds l _{t and i} is a recurrence of the mathematical formula (5) by using the Bayes' theorem shown by the following mathematical formula (4). It can be expressed by a recurrence formula.

Here, P (X) is the probability that event X will occur, P (Y) is the probability that event Y will occur, and P (X | Y) is the probability that event X will occur under the condition that event Y has occurred. P (Y | X) is the probability that event Y will occur under the condition that event X has occurred.

The occupancy probability density function p ( _mi ) included in the second term of the equation (5) is called a pre-occupancy probability density function, and l _{t-1 and i} in the third term are at time t-1. The logarithmic odds of. Further, Equation occupancy probability density function p (m _i │z _t) included in the first term of (5) is called the inverse measurement model, the grid is occupied on the basis of the distance data detected by the distance sensor Express the probability of being there. That is, by calculating the occupancy probability density function p (m _i │z _t), it is possible to calculate the occupancy of the occupancy calculation grid. The inverse measurement model is explained in "Probabilistic Robotics (Premium Books Version)" by Mynavi Publishing Co., Ltd., author Sebastian Thrun, Wolfram Burgard, and translator Ryuichi Ueda, pp. 264 to 268.

For occupancy calculation grid mi, describing the calculation method of the occupancy probability density function p _{(m i} │z _t) below. occupancy calculation lattice m _i of i-th index, for inclusion in the sensor model, it is possible to display the coordinates of the occupancy calculation grid m _i in polar coordinates (r, theta). However, the origin (0,0) is the sensor position of the distance sensor of the peripheral situation detection sensor 1.

Based on the distance sensor at time t to the detection distance z _t and sensor model, region (region I) is likely with each grid coordinate obstacle, no likely region obstacle (region II), Which region of the region (region III) that cannot be determined from the sensor data belongs is determined by using the sensor model SM as shown in FIG.

That is, FIG. 8 is a diagram in which the sensor model SM shown in FIG. 4 is superimposed on the initial map LM, the position where the detection wave is generated is set as the origin OP of the coordinates (0,0), and the maximum detection distance is represented as maxDist. , the detection distance _{z t} to _z t-epsilon from _{z t} + epsilon range region I next, range area II next _z t-epsilon from the origin OP, the range of the maximum detection distance maxDist from _{z t} + epsilon and the region III It has become. Incidentally, the constant epsilon, when a distance measurement the distance to the object by the distance sensor near status detection sensor 1, represents the error distance possible, once the detection distance z _t to the object, a predetermined The region I is determined within the range defined by the error ε, the origin OP side of the region I is the region II, and the point side where the maximum detection distance maxDist is the region I is the region III. In FIG. 8, occupancy calculation grid m _i from the coordinates are determined to belong to the region I.

Then, according to the determined region is calculated by the following equation occupancy probability density function p (m _i │z _t) of the grid (6) to (8).

Equation (6) is a conditional expression when the occupancy calculation grid mi is included in the region II, and means that the probability that the occupancy calculation grid mi is occupied by an object is low. Therefore, the occupancy calculation grid mi to approximate the probability of being occupied by 0, set occupancy probability density function p to _{(m i} │z _t) to be in the range of constant _{p min,} the range to _{0 <p} min <0.5 ..

The mathematical formula (7) is a conditional expression when the occupancy calculation lattice mi is included in the area I, and the peripheral condition detection sensor 1 does not know the angle information from the peripheral condition detection sensor 1 of the object, so that the object is accurate. although unable to detect the position, the area I is the regions preceding and following the detection distance z _t, as likely to object exists somewhere in the region I, the probability of being occupied occupancy calculation grid mi to approximate 1, set occupancy probability density function p to _{(m i} │z _t) to be in the range of constant _{p max,} the range is a 0.5 _{<p max} <1.

Equation (8) is a conditional expression if occupancy calculation grid mi is included in the area III, because they are farther range than the detection distance z _t, whether occupancy calculation grid mi is occupied by the object since it is unknown, and p a _{(m i)} and 0.5 as a constant in the occupancy giving advance the occupancy probability density function p _{(m i} │z _t). A probability is given in advance to each grid that divides the initial map LM (prior probability), and the value is set to 0.5.

Further, the constant ε may be arbitrarily set in order to allow an error with respect to the detection distance of the distance sensor of the peripheral situation detection sensor 1. If the constant ε is not set, the occupancy is calculated so that the distance r from the peripheral situation detection sensor 1 to the occupancy calculation grid mi is p _max for the distance r = detection distance. .. Further, as a range in which the constant ε is arbitrarily set, the constant ε is set so as to include a possible distance error according to the ability of the distance sensor 1 of the peripheral situation detection sensor 1 to be used.

Equation of (6) ~ (8) p occupancy probability density function of each grid is calculated using a _{(m i} │z _t), by substituting the equation representing log odds _{l t,} with recurrence formula _i (5) By substituting the obtained logarithmic odds l _{t and i} into the mathematical formula (3), the occupancy probability density function p ( _mi | z _{1: t} ) can be obtained, and the obtained calculation result is the lattice occupancy. It becomes.

That is, with respect to the lattice occupancy p ( _mi ) calculated in the above process, the occupancy degree indicating that each lattice is occupied by an object is a neighborhood value of 1, and the occupancy degree indicating that the lattice is not occupied by an object. Is a value near 0. Then, the occupancy degree indicating that it is unknown whether or not it is occupied is a neighborhood value of 0.5.

The virtual space update unit 12 updates the occupancy of all the grids in the grid map based on the grid occupancy output from the occupancy calculation unit 11 and the grid map LM output from the virtual space storage unit 10. , Output as a grid map. Specifically, for all the grids in the grid map, the grids included in the occupancy calculation grid are updated to the occupancy calculated by the occupancy calculation unit 11, and the other grids retain the occupancy of the grid map LM. By doing so, the grid map LM is updated. The updated grid map LM is stored in place of the grid map LM already stored in the virtual space storage unit 10.

Next, the flow of the operation performed by the object recognition unit 3 will be described with reference to the flowchart shown in FIG. The relationship between each step in FIG. 9 and each functional block in FIG. 3 is as follows. Steps S11, S12, S13, and S14 are operations performed by the virtual space storage unit 10, step S15 is an operation performed by the occupancy calculation unit 11, and step S16 is an operation performed by the virtual space update unit 12.

Next, the operation of each step in FIG. 9 will be described. In step S11, it is determined whether or not the virtual space divided in a grid pattern is stored in the virtual space storage unit 10, and if it is not stored (No), the process proceeds to step S12 and if it is stored (Yes). Goes to step S13.

When the process proceeds to step S12, the vehicle is divided into grids having a predetermined size around the vehicle based on the vehicle position and the posture angle at the current time t detected by the vehicle position detection unit 2. Create a virtual space (grid map). In step S14, the generated grid map is assigned an occupancy degree indicating an unspecified area to each grid in the grid map, and is stored in the virtual space storage unit 10. Further, the stored grid map is output to the occupancy calculation unit 11.

When the process proceeds to step S13, the grid map stored in the virtual space storage unit 10 in the past (t−Δt) is read out and output to the occupancy calculation unit.

In step S15, the object is occupied based on the grid map output from the virtual space storage unit 10, the vehicle position and attitude angle output from the vehicle position detection unit 2, and the distance data detected by the surrounding situation detection sensor 1. The occupancy is changed to the occupancy indicating that the object is occupied, the occupancy indicating that the object is not occupied (non-occupied), and the occupancy indicating that it is unknown whether the object is occupied or not, and the occupancy is output. ..

In step S16, the occupancy of all the grids on the grid map stored in the virtual space storage unit 10 (previous value) and the occupancy of the grid changed by the occupancy calculation unit (current value) are superimposed. Then, the occupancy of the grid is updated and stored in the virtual space storage unit 10.

The superposition with the previous value performed in step S16 is the previous value at time t-1 by using the logarithmic odds l _{t and i} shown in the formula (2) with respect to the gradual formula shown in the formula (5). of occupancy _{p (m i | z 1:} t-1) was calculated as l _{t-1, i,} occupancy probability density function p of the calculated current value _{(m i} │z _t) and in step S15, the above-mentioned by using l _{t-1, i,} was calculated log odds _{l t,} a _i, formula occupancy probability density function _p shown in _{(3) (m i | z} 1: t) by the grating at time t _{m i} Occupancy probability density function p ( _mi | z _{1: t} ) is calculated. Then, this is the occupancy of the lattice m _i.

That, occupancy probability of the lattice _{m i} at time t-1 density function _{p (m i | z 1:} t) and log odds of occupancy probability density function p lattice _{m i} at time t of the _{(m i} │z _t) by adding the log odds, occupancy _p lattice _{m i} at time _{t (m i | z 1:} t) is calculated.

A specific calculation method will be described below. The initial map generated at time t _start, the occupancy p lattice _{m i} when _{(m i} │z _tstart) is 0.5, the time t _start + occupancy in Delta] t probability density function p _{(m i} │z _{tstart + Δt} If) is 0.7, occupancy p lattice _{m i (m i │z tstart:} tstart + Δt) is represented by the following equation using equations (3) (9).

L _{tstart + Δt and i} in the mathematical formula (9) are represented by the following mathematical formula (10) using the mathematical formula (5).

Here, a _{p (m i │z tstart + Δt} ) is _{0.7, p (m i │z tstart} ) is 0.5, if p _{(m i)} is 0.5, _{l tstart, i} When = 0, the mathematical formula (10) is calculated as the following mathematical formula (11).

Substituting the calculation result 0.8473 of the formula (11) into the formula (9), the calculation is performed as in the following formula (12).

As a result, time t _start + occupancy in Delta] t probability density function p when _{(m i} │z _{tstart + Δt)} is 0.7, occupancy p lattice _{m i} at time _{t start + Δt (m i │z} tstart: tstart + Δt) is becomes 0.7, if it becomes 0.7 at time t _start + 2 × occupancy in Delta] t probability density function _{p (m i │z tstart + 2} × Δt), l tstart + Δt, when a i = 0.8473, _{l tstart + 2 × Δt and i} are calculated by the following mathematical formula (13).

Substituting the calculation result 1.6946 of the mathematical formula (13) into the modified formula of the mathematical formula (9), the calculation is performed as the following mathematical formula (14).

As a result, when the time t _start + 2 × occupancy in Delta] t probability density function _{p (m i │z tstart + 2} × Δt) is 0.7, the time t _start + 2 × occupancy grid _{m i} in Δt p _{(m i} │ z _{tstart: tstart + 2 × Δt} ) is 0.8448.

On the other hand, a grid map is generated at time t _start , and the occupancy degree p (m _j │ _z t _start ) of the grid m _{j at} that time is 0.5, and the occupancy probability density function p (m _j │ │) at time t _start + Δt. When z _{tstart + Δt} ) is 0.2 and l _{tstart, i} = 0, l _{tstart + Δt, i} are calculated by the following mathematical formula (15).

Substituting the calculation result of the formula (15) -1.3863 into the modified formula of the formula (9), the calculation is performed as the following formula (16).

As a result, time t _start + occupancy in Delta] t probability density function p when _{(m j} │z _{tstart + Δt)} is 0.2, occupancy p lattice _{m j} at time _{t start + Δt (m j │z} tstart: tstart + Δt) is becomes 0.2, if it becomes 0.2 at time t _start + 2 × occupancy in Delta] t probability density function _{p (m j │z tstart + 2} × Δt), l tstart + Δt, when a i = -1.3863, l _{tstart + 2 × Δt, i} is calculated by the following mathematical formula (17).

Substituting the calculation result of the formula (17) -2.7726 into the modified formula of the formula (9), it is calculated as the following formula (18).

As a result, time t _start + 2 × when occupied in Delta] t probability density function _{p (m j │z tstart + 2} × Δt) is 0.2, the time t _start + 2 × occupancy probability density function of the lattice _{m j} in Delta] t p (m _j │ z _{tstart + 2 × Δt} ) is 0.0588.

<Traveling route calculation processing>
Next, the travel route calculation process in the travel route calculation unit 4 will be described. FIG. 10 is a functional block diagram showing the configuration of the travel path calculation unit 4 of the vehicle control device according to the first embodiment. As shown in FIG. 10, the traveling route calculation unit 4 includes an object existence extraction unit 21 and an object avoidance route calculation unit 22.

The object existence extraction unit 21 is an object for each grid in the grid map based on the grid map output by the object recognition unit 3 and the own vehicle position and the own vehicle attitude angle detected by the own vehicle position detection unit 2. The occupied grid is the existing area of the object. Further, regarding the grid of the unspecified area, if it exists on the side of the own vehicle, it is determined that the object exists, and it is set as the existence area of the object. Then, when a grid of an unspecified region exists in the traveling direction of the own vehicle position or other than the side, it is determined that no object exists at the grid position. After that, the existing areas of these objects are extracted.

Considering the exit of the own vehicle from the parking space, the side of the vehicle is a blind spot of the surrounding condition detection sensor 1, and there is a high possibility that a grid of an unspecified area will be generated on the side of the vehicle. Since there is a possibility that an object that did not exist at the time of warehousing of the own vehicle exists there, it is treated as if an object exists in an unspecified area on the side of the vehicle. This makes it possible to calculate the traveling route by compensating for the blind spot of the peripheral situation detection sensor 1 and avoiding a collision with an obstacle.

Even if there is a grid in an unspecified area in the traveling direction of the vehicle, the distance sensors that detect the left front, right front, left rear, and right rear of the vehicle are installed, so that the vehicle travels in the direction of travel. Even if an object exists, the unspecified area disappears as the vehicle advances, so it is treated as if the object does not exist at the lattice position.

The object avoidance route calculation unit 22 is based on the existence area of the object output by the object existence extraction unit 21, the own vehicle position detected by the own vehicle position detection unit 2, and the own vehicle attitude angle, that is, the lattice. Calculate the travel route that avoids collision with.

Here, a method of avoiding a collision with an obstacle when the vehicle is moving at an extremely low speed will be described with reference to FIGS. 11 and 12.

In FIG. 11, when the own vehicle OV turns at the maximum positive actual steering angle δ _pmax (δ _pmax > 0) when reversing, and an obstacle OB exists on the left side (Y-axis negative region) of the own vehicle OV in the traveling direction. , There is a possibility that the obstacle OB may be involved due to the difference in the outer ring. However, regarding the coordinate system, as shown in FIG. 11, the front side of the own vehicle OV is in the positive direction of the X axis, and the XY axes are in the right hand system. That is, regarding the positive and negative of the actual steering angle, the direction of rotation counterclockwise when moving forward is the positive direction, and the direction of rotation clockwise when moving backward is the positive direction. In FIG. 11, the arc through which the right front wheel passes when turning at the maximum actual steering angle is CA, and the coordinates of the turning center are (x, y) = (0,1 / ρ_max). ρ_max is the curvature of the arc CA. The coordinates of the obstacle OB are (x, y) = (x _nR , y _nR ).

In addition, there is a theoretical formula that defines these relationships between the turning radius of the vehicle and the actual steering angle. This is shown in the mathematical formula (19). The derivation of the above formula (19) is described in "Sankaido Publishing Co., Ltd. Masato Abe, Vehicle Motion and Control, 2nd Edition, Chapter 3, Basics of Vehicle Motion, Section 3.3, Steady Circular Turning of Vehicles".

In formula (19), R is the turning radius, V is the traveling speed of the own vehicle, A is the stability factor, WB is the wheelbase of the vehicle, and δ is the actual steering angle of the front wheels. Since AV ² ≈ 0 at extremely low speeds, the actual steering angle and the minimum turning radius can be expressed by the following mathematical formula (20) using the wheelbase WB.

Further, the turning radius R and the curvature ρ have the relationship of the following mathematical formula (21).

In FIG. 11, since the obstacle OB includes the arc CA and exists inside the arc CA, if the own vehicle OV retreats while turning with a curvature ρ_max, there is a possibility of collision due to an outer ring difference.

Therefore, under this condition, if the coordinates (x, y) = (x _nR , y _nR ) of the obstacle OB are outside the arc CA created by the turning radius drawn by the right front wheel of the own vehicle OV, the collision is avoided. can do. This turning radius is expressed by the following mathematical formula (22).

In the mathematical formula (22), FL is the length of the vehicle in the vehicle length direction, is defined by the length from the center of the rear wheel axle to the front end of the vehicle, and HW represents half the width of the vehicle.

Further, as shown in FIG. 12, when the own vehicle OV moves forward while turning with a curvature ρ_max, the obstacle OB exists on the left side (Y-axis positive region) of the own vehicle OV in the traveling direction, and the obstacle OB is present. If the arc CA is included and exists outside the arc CA, there is a possibility of collision with the obstacle OB due to the inner ring difference.

Therefore, under this condition, the coordinates (x, y) = (x _nL , y _nL ) of the obstacle OB are outside the arc CA created by the turning radius 1 / ρ_max-HW drawn by the left rear wheel of the own vehicle OV. If so, collisions can be avoided.

By formulating the method of avoiding the collision with the obstacles shown in FIGS. 11 and 12, it is possible to calculate the traveling route avoiding the collision with the grid. That is, when the own vehicle OV turns, the range of curvature that can be turned without colliding with the obstacle OB can be obtained.

Here, regarding each of the possibility of collision due to the difference in the outer ring of FIG. 11 and the possibility of collision due to the difference in the inner ring of FIG. 12, the curvature of the own vehicle OV when an obstacle OB exists on the turning radius of the own vehicle OV is calculated. Ask. If the curvature is less than that, the collision between the own vehicle OV and the obstacle OB can be avoided.

That is, for all the grids existing in the existence region of the object extracted by the object existence extraction unit 20, the maximum curvature with respect to the grid is calculated as the limit curvature when an obstacle is involved by the difference between the inner ring and the outer ring of the vehicle. Here, the maximum curvature when turning at a positive actual steering angle is defined as the positive maximum curvature ρpmax, the maximum curvature when turning at a negative actual steering angle is defined as the negative maximum curvature ρnmax, and the maximum positive for each lattice. Find the curvature or the maximum negative curvature, respectively.

Hereinafter, a method for obtaining the maximum curvature with respect to the lattice will be described. First, the maximum curvature under the conditions shown in FIG. 11 will be described.

As shown in FIG. 11, the vehicle OV turns at the maximum positive actual steering angle δ _pmax (δ _pmax > 0) when reversing, and an obstacle OB exists on the left side (Y-axis negative region) of the vehicle OV in the traveling direction. If this is the case, there is a possibility that the obstacle OB may be involved due to the difference in the outer ring.

Therefore, in order to avoid the obstacle OB from being caught by the outer ring difference, the range of curvature that can be turned without being caught by the outer ring difference is obtained. As a method of obtaining it, it may be less than the limit curvature involved in the outer ring difference.

The curvature ρ _RP (x _nR , y _nR ) involved in the outer ring difference can be obtained by the following mathematical formulas (23) and (24).

If the curvature is in the range of the following formula (25) from the formulas (23) and (24), the obstacle OB on the left side in the traveling direction of the own vehicle OV will not be involved due to the difference in the outer ring.

Further, as shown in FIG. 12, the own vehicle OV turns at the maximum positive actual steering angle δ _pmax (δ _pmax > 0) when moving forward, and the obstacle OB is on the left side (Y-axis positive region) of the own vehicle OV in the traveling direction. If there is, there is a possibility that the obstacle OB may be involved due to the difference in the inner ring.

Therefore, in order to avoid the obstacle OB from being caught by the inner ring difference, the range of curvature that can be turned without being caught by the inner ring difference is obtained. As a method of obtaining it, it may be less than the limit curvature involved in the inner ring difference.

The limit curvature ρ _FP (x _nL , y _nL ) involved in the inner ring difference can be obtained by the following mathematical formulas (26) and (27).

If the curvature is within the range of the following mathematical formula (28) from the mathematical formulas (26) and (27), the obstacle OB on the left side in the traveling direction of the own vehicle OV will not be involved due to the inner ring difference.

So far, we have explained the avoidance curvature with obstacles that may collide with the inner ring difference and the outer ring difference when turning at a positive actual steering angle for both forward and backward movements, but next, with a negative actual steering angle The avoidance curvature with an obstacle when turning will be described.

Also in this case, the curvature of the own vehicle OV when the obstacle OB exists on the turning radius of the own vehicle OV is obtained, and if it is less than the curvature, the collision between the own vehicle OV and the obstacle OB can be avoided. ..

First, in order to avoid the involvement of the obstacle OB existing on the right side (Y-axis negative region) of the own vehicle OV due to the inner ring difference when moving forward, the range of curvature that can be turned without being involved due to the inner ring difference is obtained. As a method of obtaining it, it may be less than the limit curvature involved in the inner ring difference.

The limit curvature ρ _FN (x _nR , y _nR ) involved in the inner ring difference can be obtained by the following mathematical formulas (29) and (30).

If the curvature is within the range of the following mathematical formula (31) from the mathematical formulas (29) and (30), the obstacle OB on the left side in the traveling direction of the own vehicle OV will not be involved due to the inner ring difference.

Further, in order to avoid the involvement of the obstacle OB existing on the right side (Y-axis positive region) of the own vehicle OV due to the difference in the outer ring when reversing, the range of curvature that can be turned without being involved due to the difference in the outer ring is obtained. As a method of obtaining it, it may be less than the limit curvature involved in the outer ring difference.

The limit curvature ρ _RN (x _nL , y _nL ) involved in the outer ring difference can be obtained by the following mathematical formulas (32) and (33).

If the curvature is within the range of the following mathematical formula (34) from the mathematical formulas (32) and (33), the obstacle OB on the left side in the traveling direction of the own vehicle OV will not be involved due to the difference in the outer ring.

Although the obstacle has a predetermined size, it can be considered that it is composed of a plurality of lattices, so the maximum positive curvature or the maximum negative curvature with respect to each of the lattices constituting the obstacle is obtained. Then, in each of the maximum curvatures of positive and negative, the minimum value NINρpmax of the maximum positive curvature and the minimum value MINρnmax of the maximum negative curvature are acquired to obtain the travel path of the travel path calculation unit 4.

In other words, the curvature ρ output from the travel path calculation unit 4 is defined within the range of the following mathematical formula (35).

Then, by controlling the vehicle using the curvature ρ in those ranges, it is possible to prevent a collision due to the involvement of the own vehicle and an obstacle.

Next, the flow of the operation performed by the traveling route calculation unit 4 will be described with reference to the flowchart shown in FIG. The relationship between each step in FIG. 13 and each functional block in FIG. 10 is as follows. Steps S41, S42, S43, S44, S45, and S46 are operations performed by the object existence extraction unit 21, and step S47 is an operation performed by the object avoidance path calculation unit 22.

Next, the operation of each step in FIG. 13 will be described. In step S41, it is determined whether or not the occupancy of each lattice in the lattice map output from the object recognition unit 3 is unoccupied. Then, when the occupancy degree indicates non-occupancy (Yes), the process proceeds to step S42, and when the occupancy degree indicates occupancy or unspecified area (No), the process proceeds to step S43.

When the process proceeds to step S42, it is determined that no object exists at the grid position. On the other hand, when the process proceeds to step S43, it is determined whether the occupancy of the lattice indicates an unspecified region. Then, when the occupancy degree indicates an unspecified area (Yes), the process proceeds to step S44, and when the occupancy degree indicates occupancy (No), the process proceeds to step S45.

When the process proceeds to step S44, it is determined whether or not the grid position is on the side of the own vehicle. Then, when the grid position is on or outside the traveling direction of the own vehicle (No), the process proceeds to step S42, and when the lattice position is on the side of the own vehicle (Yes), the process proceeds to step S45.

When the process proceeds to step S45, it is estimated that an object exists at the grid position, and the process proceeds to step S46.

After performing the processes of steps S41 to S45 for each grid in the grid map output from the object recognition unit 3, in step S46, the existing area of the object is extracted from the grid map (virtual space), and in step S47. Transition.

In step S47, a route for avoiding an existing object is generated based on the existence area of the object extracted from the object existence extraction unit 20 and the position of the own vehicle.

The effect of the vehicle control device 100 according to the first embodiment of the present embodiment will be described below. In the conventional vehicle control device, for example, when the own vehicle is automatically parked, in order to generate the travel route of the own vehicle, the surrounding situation information of the own vehicle acquired at the time of warehousing, for example, the traveling at the time of warehousing of the own vehicle A storage device for holding the locus, a so-called memory, is required. However, the vehicle control device 100 of 1 of the present embodiment detects or estimates an object existing in the vicinity of the own vehicle based on the surrounding situation information of the own vehicle, and generates a route for avoiding a collision with the object. Therefore, it does not require a traveling track when the vehicle is warehousing. Therefore, as compared with the conventional vehicle control device, it is sufficient to have a small memory, the vehicle control device 100 can be miniaturized, and the price of the vehicle control device 100 can be reduced.

Further, since the traveling route is created by presuming that an obstacle exists in the unspecified area, the possibility of collision between the own vehicle and the obstacle can be further reduced.

<Embodiment 2>
Hereinafter, the parking support device 200 according to the second embodiment of the present invention will be described. The description of the same configuration as the vehicle control device 100 of the first embodiment will be omitted.

<Device configuration>
FIG. 14 is a functional block diagram showing the configuration of the parking support device 200 according to the second embodiment of the present invention. As shown in FIG. 2, the parking support device 200 has the output and travel path of the first warehousing travel route generation unit 6 and the first warehousing travel route generation unit 6 in the configuration of the vehicle control device 100 shown in FIG. It is further provided with a traveling route comparison unit 7 that receives the output of the calculation unit 4.

The first warehousing travel route generation unit 6 stores the warehousing travel locus until the vehicle enters the parking space, and outputs it as the first warehousing travel route of the own vehicle that traces the reverse of the stored locus. A technique for using the warehousing run locus as the warehousing run path is disclosed in, for example, Japanese Patent Application Laid-Open No. 2007-62625, and a known technique can be used.

Similar to the first embodiment, the traveling route calculation unit 4 uses the own vehicle based on the recognition result of the existence of the object output from the object recognition unit 3 and the own vehicle position and attitude angle output from the own vehicle position detection unit 2. The travel route of is calculated, and the calculated travel route is output as the second delivery travel route.

When the travel route comparison unit 7 compares the first warehousing travel route generated by the first warehousing travel route generation unit 6 with the second warehousing travel route calculated by the travel route calculation unit 4 and matches. Outputs the first travel route, and if they do not match (mismatch), outputs the second travel route.

<Overall operation>
Next, as shown in FIG. 15, the own vehicle OV is stored in the parking space between the parked vehicle PV1 and the parked vehicle PV2 parked in parallel in advance from the warehousing start position SP, and the warehousing start position is facing backward. The overall operation of the parking support device 200 according to the second embodiment will be described by taking as an example a parking support scene in which the parking lot is delivered to the SP.

FIG. 16 is a flowchart showing the overall operation of the parking support device 200 according to the second embodiment. The processing of the flowchart of FIG. 16 is repeatedly executed while the vehicle is running.

The relationship between each step in FIG. 16 and each functional block in FIG. 14 is as follows. Step S101 is an operation performed by the own vehicle position detection unit 2, step S102 is an operation performed by the peripheral situation detection sensor 1, step S103 is an operation performed by the object recognition unit 3, and step S104 is the first delivery operation. The route generation unit 6 performs the operation, step S105 is the operation performed by the travel route calculation unit 4, step S106 is the operation performed by the travel route comparison unit 7, and step S107 is the operation performed by the vehicle control unit 5. ..

When the parking support process is started, first, in step S101, the state related to the speed and the traveling direction of the own vehicle is detected as the own vehicle data, and the own vehicle position and the posture angle are detected from the detected own vehicle data.

In step S102, the situation around the own vehicle is detected by using the distance sensor mounted on the own vehicle. It is assumed that the distance sensors are mounted on the left front side, the right front side, the left rear side, the right rear side, the left front, the right front, the left rear, and the right rear of the own vehicle. After that, the process proceeds to step S103 and step S104.

In step S103, a virtual space (grid map LM) divided in a grid pattern is generated around the own vehicle, and based on the result detected by the surrounding situation detection sensor 1, an object exists in each grid of the grid map LM. Reflect the presence / absence and the occupancy that represents the unspecified area. The details are the same as the processing of the object recognition unit 3 in the first embodiment. After that, the process proceeds to step S104.

Here, the grid map LM generated around the own vehicle through the process of step S103 at the start of the parking support process can be expressed as shown in FIG. In FIG. 17, the grid OEL recognized as having an object is heavily hatched, and the grid UKL recognized as an unspecified region is hatched with diagonal lines.

As shown in FIG. 17, since the distance sensors are provided on the left front side, the right front side, the left rear side, and the right rear side of the own vehicle, the parked vehicle PV1 and the parked vehicle PV1 within the detection range of the distance sensor The side surface of PV2 is recognized as having an object, but the blind spot of the distance sensor is recognized as an unspecified area.

Here, the description returns to FIG. The parking support device 200 has a memory (not shown) for storing the warehousing travel locus DL until the own vehicle OV enters the parking space, and the first warehousing travel route generation unit 6 has the memorized locus. A first delivery route that follows the reverse of is generated and output (step S104). That is, the warehousing travel locus as shown in FIG. 18 is output as the first warehousing travel route. After that, the process proceeds to step S106.

Here, FIG. 19 shows a graph of the relationship between the moving distance and the target curvature when the warehousing travel locus as shown in FIG. 18 is taken. As shown in FIG. 19, at the time of warehousing, the target curvature is 0 because it moves linearly from the warehousing start position SP for a while, and then the target curvature increases until the target curvature reaches ρ1, and the target curvature reaches ρ1. After that, the target curvature ρ1 is maintained, and then the target curvature decreases until the end of the path is reached, and finally becomes 0.

On the other hand, FIG. 20 shows a graph of the relationship between the moving distance and the target curvature when the first warehousing running route that follows the reverse of the warehousing running locus as shown in FIG. 18 is adopted. As shown in FIG. 20, at the time of delivery, the target curvature increases until the target curvature reaches ρ1, the target curvature ρ1 is maintained after the target curvature reaches ρ1, the target curvature decreases thereafter, and the target curvature becomes 0. After becoming, it moves linearly until it reaches the end of the route.

Here, the description returns to FIG. In parallel with the generation of the first delivery travel path by the first delivery travel route generation unit 6, in step S105, the first of the own vehicle is based on the recognition result of the own vehicle position, the own vehicle posture angle, and the existence of the object. Calculate the delivery route of 2. At that time, in the recognition result of the existence of the object, the traveling path is calculated assuming that the object exists for the unspecified region, and the process proceeds to step S106.

Specifically, with respect to the grid map LM shown in FIG. 17, the object existence extraction unit 21 recognizes the grid OEL recognized as the existence of the object and the unspecified region UKL existing on the side of the own vehicle. The grid is extracted as the area where the object exists. Therefore, in FIG. 21, the lattice OEL extracted as the existence of the object and the unspecified region UKL are treated as the lattice OEL by applying the same dark hatching.

Then, the maximum curvature is calculated for each of the lattice OELs extracted assuming that the object exists, as described in the object avoidance path calculation unit 22 of the first embodiment. Then, the smallest of the maximum curvatures of each grid is output as the target curvature of the second delivery travel path.

In step S106, the first warehousing travel route and the second warehousing travel route are compared, and if they match, the first warehousing travel route is selected, and if they do not match, the second warehousing travel route is selected and output. , Step S107.

Here, in step S106, the effect of comparing the first delivery travel route and the second delivery travel route will be described.

22 and 23 are diagrams for explaining the problem of the first delivery travel route. FIG. 22 shows a situation in which an obstacle OB is present at a position that becomes a blind spot of the sensor after warehousing by taking the warehousing traveling locus shown in FIG. In this situation, if the first delivery travel path is used, as shown in FIG. 23, there is a possibility that the own vehicle OV collides with the obstacle OB at the position that becomes the blind spot of the sensor.

Therefore, in step S103, the object recognition unit 3 recognizes the presence / absence of the object and the unspecified area, and in step S105, the second delivery travel route for avoiding the obstacle OB is calculated by extracting the existence area of the object. And output. By using the second warehousing travel route, it is possible to warehousing at the warehousing start position SP without colliding with the obstacle OB.

The delivery using the second delivery travel route will be described with reference to FIGS. 24 to 26. FIG. 24 shows a grid map LM when there is an obstacle OB at a position that becomes a blind spot of the sensor, and the grid OEL recognized as having an object is deeply hatched and recognized as an unspecified area. The grid UKL is hatched with diagonal lines. The obstacle OB exists in the region of the grid UKL. In FIG. 25, the lattice OEL extracted assuming that an object exists and the unspecified region UKL are subjected to the same dark hatching and treated as a lattice OEL. The maximum curvature is calculated for each of the lattice OELs extracted assuming that an object of such a grid map LM exists, and the smallest of the maximum curvatures of each grid is set as the target curvature of the second delivery travel path. By doing so, as shown in FIG. 26, it is possible to avoid the collision with the obstacle OB and leave the warehouse.

Here, FIG. 27 shows the relationship between the movement distance and the target curvature in the first delivery travel path and the second delivery travel route. The first shipping route shown by the broken line in FIG. 27 is the same as the first shipping route shown in FIG. 20, and the target curvature increases immediately from the stop position, but the second shipping route shown by the solid line. After moving linearly from the stop position for a while, the target curvature begins to increase so that the target curvature reaches ρ2. As a result, it is possible to avoid a collision with the obstacle OB and leave the warehouse.

Here, the description returns to FIG. In step S107, steering control and drive control of the own vehicle are performed so as to follow the traveling path selected in step S106.

As described above, in the parking support device 200 of the second embodiment, even if an obstacle OB exists at a position that becomes a blind spot of the sensor, it is possible to leave the parking lot while avoiding a collision.

<Traveling route comparison process>
Next, the travel route comparison process in the travel route comparison unit 7 will be described with reference to the flowchart shown in FIG. 28. When the travel route comparison process is started, first, in step S1061, the first delivery travel route and the second delivery travel route are each divided up to the end of the route for each predetermined route length.

For example, the first outgoing travel path S _A and the second outgoing travel path S _B the result of dividing each same path length, if each were divided into five, the first outgoing travel path S _{A =} {S _{A1, S A2, S A3, S A4} , S A5}, the second outgoing travel path _{S B = {S B1, S} B2, S B3, S B4, can be expressed as _{S B5},} path sequentially index numbers are small The route is divided from the start position. That is, the starting position of the path _{S A} is _{S A1,} the end position is the _{S A5.}

FIG 29 and FIG 30, the path split shows schematically the division of the first outgoing travel path S _A in FIG. 29, in FIG. 30 the division of the second outgoing travel path S _B Illustrate.

Here, the description returns to FIG. 28. After the route division in step S1601, in step S1062, the division route at the same division position is acquired for each of the first delivery travel route and the second delivery travel route. That is, in the above example, the division routes having the same index number are acquired from the first and second delivery travel routes, respectively.

In this way, since the first delivery travel route and the second delivery travel route are divided and compared up to the end of the route for each predetermined route length, accurate route comparison can be performed.

Then, in step S1063, the division route of the first delivery travel route acquired in step S1062 and the division route of the second delivery travel route are compared, and if they do not match (No), the process proceeds to step S1064. If they match (Yes), the process proceeds to step S1065. Here, the path comparison is performed by comparing the curvature of each of the divided paths.

In step S1064, the second delivery travel route is output as the travel route output by the travel route comparison unit 7.

In step S1065, regarding the comparison between the first warehousing travel route and the second warehousing travel route, it is confirmed whether the comparison has been made with the second warehousing travel route from the start position to the end position of the first warehousing travel route, and all comparisons are made. If yes, the process proceeds to step S1066, and if not all are compared (No), the process of step S1062 and subsequent steps is repeated.

In step S1066, the first delivery travel route is output as the travel route output by the travel route comparison unit 7.

In this way, the travel route comparison unit 7 selects and outputs one of the first exit travel route and the second exit travel route to avoid collision between the obstacle and the own vehicle. It will be possible.

<Embodiment 3>
<Device configuration>
FIG. 31 is a functional block diagram showing the configuration of the parking support device 300 according to the third embodiment of the present invention. In FIG. 31, the same components as those of the parking support device 200 described with reference to FIG. 14 are designated by the same reference numerals, and duplicate description will be omitted.

As shown in FIG. 31, the parking support device 300 further includes a configuration in which an input is given from the travel route comparison unit 7 to the travel route calculation unit 4 in the configuration of the parking support device 200 described with reference to FIG. ..

Similar to the parking support device 200 described with reference to FIG. 14, the travel route calculation unit 4 has the recognition result of the existence of the object output from the object recognition unit 3 and the vehicle position output from the vehicle position detection unit 2. And, based on the attitude angle, the travel route of the own vehicle is calculated as the second departure travel route. Further, when a travel route recalculation request is input from the travel route comparison unit 7, the recognition result of the existence of an object output from the object recognition unit 3 and the vehicle position and attitude angle output from the vehicle position detection unit 2. Is used again to calculate the third delivery travel route and output it as the travel route of the own vehicle.

The travel route comparison unit 7 compares the travel route calculated by the travel route calculation unit 4 with the first issue travel route output by the first issue travel route generation unit 6, and if they match, the first issue is issued. If the travel routes do not match, the travel route calculated by the travel route calculation unit 4 is output. Regarding the travel route calculated by the travel route calculation unit 4, the second issue travel route is calculated until the third issue travel route is calculated, and then the third issue travel route is calculated.

Further, when the travel route comparison unit 7 can calculate only a part of the second delivery travel route by the travel route calculation unit 4, that is, all up to the end of the first delivery travel route (receipt start position). If the route cannot be calculated, a travel route recalculation request is output to the travel route calculation unit 4 so as to calculate the travel route again while following the second delivery travel route for which the calculation has been completed.

Here, when only a part of the second warehousing travel route can be calculated, the end position of the first warehousing travel route, that is, the warehousing start position is outside the detection range of the sensor from the warehousing start position, and the unspecified area. Therefore, there are cases where the route termination cannot be specified.

By calculating the travel route again while following the second delivery travel route after the calculation is completed, the detection range of the sensor can be changed and the end of the route can be specified.

<Overall operation>
FIG. 32 is a flowchart showing the overall operation of the parking support device 300 according to the third embodiment. The processing of the flowchart of FIG. 32 is repeatedly executed while the vehicle is running.

The relationship between each step in FIG. 32 and each functional block in FIG. 31 is as follows. Step S201 is an operation performed by the own vehicle position detection unit 2, step S202 is an operation performed by the peripheral situation detection sensor 1, step S203 is an operation performed by the object recognition unit 3, and step S204 is the first delivery. Steps S205, S206 and S207 are operations performed by the travel route calculation unit 4, steps S208, S210 and S211 are operations performed by the travel route comparison unit 7, and steps S209 are performed by the travel route generation unit 6. Is an operation performed by the vehicle control unit 5.

Since the operations of steps S201 to S204 and S209 shown in FIG. 32 are the same as those of steps S101 to S104 and S107 of the flowchart of the second embodiment shown in FIG. 16, the description thereof will be omitted.

In step S203, a grid map is generated around the own vehicle, and based on the result detected by the surrounding situation detection sensor 1, each grid of the grid map reflects the presence / absence of an object and the occupancy that represents an unspecified area. After that, the process proceeds to step S205.

In step S205, it is confirmed whether the travel route recalculation request is requested from the travel route comparison unit 7, and if it is not requested (No), the process proceeds to step S206, and if it is requested (Yes), step S207 Move to.

In step S206, it is basically the same as step S105 of the flowchart of the second embodiment, and the traveling route calculated based on the recognition result of the existence of the object and the position of the own vehicle is output as the second delivery traveling route.

Step S207 is basically the same as step S105 of the flowchart of the second embodiment, and again calculates the traveling path A based on the recognition result of the existence of the object and the position of the own vehicle. In addition, the travel route comparison unit 7 acquires the position and posture angle of the vehicle at the end of the travel route, that is, the warehousing start position in the first exit travel route. Then, a traveling path B capable of guiding the vehicle to the position and attitude angle of the vehicle at the warehousing start position is generated from the current position and attitude angle of the own vehicle. A known technique can be used as a method for generating the traveling path B, and for example, a traveling path (curvature) can be generated by using the technique disclosed in JP-A-2017-88112.

By limiting the curvature range on the travel path A as shown by the mathematical formula (35), the generated curvature on the travel path B is output as the third delivery travel route. That is, when the generated curvature on the traveling path B is 0.1 and the curvature range ρA on the traveling path A is −0.05 ≦ ρA ≦ 0.05, the curvature output as the third shipping route is 0. It becomes 05.

In step S208, the travel routes are compared based on the first warehousing travel route and the second warehousing travel route or the third warehousing travel route output from the travel route calculation unit 4. If the third shipping route does not exist, the first shipping route and the second shipping route are compared, and if they match, the first shipping route is compared, and if they do not match, the second shipping route is used. Output the travel route. If there is a third shipping route, the first shipping route and the third shipping route are compared, and if they match, the first shipping route is compared. If they do not match, the first shipping route is used. Output the delivery travel route of 3.

In step S209, steering control and drive control of the own vehicle are performed so as to follow the traveling path selected in step S208, and the process proceeds to step S210.

In step S210, it is confirmed whether the position of the own vehicle has moved to the end of the first leaving travel route based on the first leaving travel route, and if it has moved (Yes), the operation of the parking support device ends. On the other hand, if it has not moved (No), the process proceeds to step S211.

In step S211, the route length of the second warehousing travel route is less than the route length of the first warehousing travel route based on the second warehousing travel route and the own vehicle position, and the own vehicle position is the first. When the vehicle travels a predetermined distance on the delivery travel route of 2, the recalculation request of the travel route is output and the process of step S201 or less is repeated.

As described above, in the parking support device 300 of the third embodiment, even if an obstacle OB exists at a position that becomes a blind spot of the sensor, it is possible to leave the parking lot while avoiding a collision. Further, even if the travel route calculation unit 4 can calculate only a part of the second delivery travel route, the sensor is detected by calculating the travel route again while following the second delivery travel route for which the calculation has been completed. The range changes, and a third shipping route to the end of the route can be obtained.

<Traveling route comparison process>
Next, the travel route comparison process in the travel route comparison unit 7 will be described with reference to the flowchart shown in FIG.

When the travel route comparison process is started, first, in step S2080, it is determined whether comparison with the third delivery travel route is necessary, and if comparison is necessary (Yes), the process proceeds to step S2090, and comparison is not necessary. (No) shifts to step S2081. Whether or not comparison with the third delivery travel route is necessary can be determined by whether or not the travel route comparison unit 7 issues a travel route recalculation request to the travel route calculation unit 4.

In step S2081, each of the delivery travel routes to be compared is divided up to the end of the route for each predetermined route length. This is the same as the route division process of step S1061 described with reference to FIG. 28 in the second embodiment. After that, the process proceeds to step S2082.

In step S2082, the route length of the connected travel route divided in step S2081 is compared with the route length of the first delivery travel route, and the travel route calculated by the travel route calculation unit is the first delivery travel route. If it is shorter than (Yes), the process proceeds to step S2083, and if it is equal to or longer than the first delivery route (No), the process proceeds to step S2084.

In step S2083, a division route at the same division position is acquired for each of the first delivery travel route and the travel route calculated by the travel route calculation unit (second delivery travel route or third delivery travel route). .. That is, the divided routes having the same index number are acquired from the two delivery travel routes to be compared to the end.

For example, the first outgoing travel path S _A and the travel path calculation section 4 running path S _C calculated by the respective results of division by the same path length, the first outgoing travel path S _A is divided into five, the travel route calculation If the travel path _{S C} calculated in part 4 is divided into three parts, namely, the path _{S A = {S A1, S} A2, S A3, S A4, S A5}, path _{S C = {S C1, S} C2 , if it can be expressed as _{S C3},} in step S2083, with respect to the path _{S a} and path _{S C,} to obtain the first to 3-th index divided paths, respectively. After that, the process proceeds to step S2085.

On the other hand, in step S2084, for each of the first warehousing travel route and the travel route calculated by the travel route calculation unit 4, the division route at the same division position is acquired up to the end of the first warehousing travel route. That is, each of the travel path S _D calculated in the first issuing the travel route and the travel path calculation unit results were divided by the same path length, the first outgoing travel path S _A is divided into five, the travel path S _D 7 When divided, the route S _A = {S _A1 , S _A2 , S _A3 , S _A4 , S _A5 }, the route S _D = {S _D1 , S _D2 , S _D3 , S _D4 , S _D5 , S _D6 , S If it can be expressed as _D7}, in step S2084, with respect to the path _{S a} and path _{S D,} to obtain the first to fifth index of split-path. After that, the process proceeds to step S2085.

In step S2085, the division route of the first delivery travel route and the division route of the travel route calculated by the travel route calculation unit 4 are compared, and if they do not match (No), the process proceeds to step S2086 and they match. If yes, the process proceeds to step S2087.

In step S2086, as the travel route output by the travel route comparison unit 7, the delivery travel route calculated by the travel route calculation unit 4 is output, and the process proceeds to step S2089.

In step S2087, the first delivery travel route is output as the travel route output by the travel route comparison unit 7, and the process proceeds to step S2089.

In step S2089, the travel route output from the travel route comparison unit 7 is stored in a travel route storage unit (not shown). That is, when the traveling route comparator 7 outputs a first issuing the travel route travel route _S A = stores the _{{S A1, S A2, S} A3, S A4, S A5}, the travel route calculating section 4 when outputting the computed issuing travel route, the travel route _{S C = {S C1, S} C2, S C3} , or, the travel path _{S D = {S D1, S} D2, S D3, S D4, S D5, S _D6 , S _D7 } are stored.

Incidentally, the travel path comparison unit 7, the travel path _{S C = {S C1, S} C2, S C3} If having stored outputs a travel route recalculation request to travel path calculation unit 4.

Here, regarding the processing in the case of shifting to step S2090, a case where the travel route calculation unit 4 outputs the second delivery travel route at time t and outputs the third delivery travel route at time t + Δt will be described.

First, the second outgoing travel path S _B is output at time t, the result in step S2081, each of the first outgoing travel path S _A and the second outgoing travel path S _B, divided by the same path length, the 1 of issuing travel path _{S a} is divided into five, when the second outgoing travel path _{S B} are divided by two, that is, the travel route _{S a = {S A1, S} A2, S A3, S A4, S A5} and If the travel path _{S B = {S B1, S} B23} can be expressed as in step S2083, with respect to the travel path _{S a} and running path _{S B,} to obtain a segmentation path. Then, although divided path in step S2085 is compared for matches respectively, does not match, after outputting a travel route _{S B} In step S2086, in step S2089, the travel path _S B = a _{{S B1, S B23}} Remember. This, so that the travel path S _B to the travel path storage unit (not shown) that is output at time t are stored.

Then, at time t + Delta] t, when the third outgoing travel path _{S C} is output, in step S2080, it is determined that required compared with the third outgoing travel path, the process proceeds to step S2090.

In step S2090, the travel route to the travel path storage unit in the travel path comparison unit 7 confirms whether stored, if it is stored, connecting the third outgoing travel path S _C to the travel route is stored Let it be a traveling route _SD . That _is, the _{S D = {S B1, S} B2, S C}.

The result of the division with the same path length in step S2081, the travel path _{S A} is divided into five, when the traveling route _{S D} is divided into five, i.e., the travel route _{S A = {S A1, S} A2, S A3, If it can be expressed as S _A4 , S _A5 }, S _D = {S _D1 , S _D2 , S _D3 , S _D4 , S _D5 }, the routes of the first to fifth indexes are acquired in step S2084.

Thereafter, in step S2085, after comparing whether each of the divided paths are matched, if they match (Yes), it outputs a travel route _{S A} in step S2088, in step S2089, the travel route _S A = _{{S A1,} S _A2 , S _A3 , S _A4 , S _A5 } are stored.

On the other hand, in step S2085, if it is the respective divided paths do not match (No), and outputs a travel route _{S D} at step S2088, at step S2089, the travel path _{S D = {S D1, S} D2, S _D3 , S _D4 , S _D5 } are stored.

In the above example, the case where the recalculation request is made once is shown, but even when the recalculation request is made twice or more, the traveling path _{SD at the} time t + Δt with respect to the output path stored at the time t. As a result, the recalculated route may be added.

<Traveling route recalculation request processing>
Next, the travel route recalculation request processing in the travel route comparison unit 7 will be described with reference to the flowchart shown in FIG.

When the travel route recalculation request processing is started, first, in step S2091, it is confirmed whether the travel route recalculation request has been made within the predetermined time, and if there is no recalculation request (No), the process proceeds to step S2092 and recalculation. When there is a calculation request (Yes), the process is completed and the recalculation request is not output to the traveling route calculation unit 4.

In step S2092, it is confirmed whether or not the own vehicle has moved a predetermined distance on the second leaving travel route based on the second leaving travel route and the position of the own vehicle. When the movement is performed by a predetermined distance (Yes), the process proceeds to step S2093, and when the movement is not performed by a predetermined distance (No), the process is terminated and the recalculation request is not output to the traveling route calculation unit 4.

In step S2093, the travel route recalculation request is output to the travel route calculation unit 4. Further, the fact that the recalculation request is output is stored in the traveling route comparison unit 7 together with the output time. Further, the route end position of the first warehousing travel path, that is, the warehousing start position and the posture angle are output.

It should be noted that the travel route recalculation request process may be repeated while the third delivery travel route is being moved, and the recalculation request may be repeatedly issued. The traveling route recalculation request processing in this case will be described with reference to the flowchart shown in FIG.

As shown in FIG. 35, when there is a recalculation request (Yes) in step S2091, the process proceeds to step S2094, and it is confirmed whether or not the own vehicle has moved a predetermined distance on the third delivery travel route. When the movement is performed by a predetermined distance (Yes), the process proceeds to step S2093, and when the movement is not performed by a predetermined distance (No), the process is terminated and the recalculation request is not output to the traveling route calculation unit 4. The operation of step S2093 is the same as that of FIG. 34.

The travel route recalculation request process may be repeated until the end of the first delivery travel route, that is, the warehousing start position is reached.

As described above, in the parking support device 300 of 3 of the present embodiment, since it is determined that an obstacle exists in the unspecified area of the obstacle and the traveling route is created, the vehicle and the obstacle The possibility of collision can be eliminated. Further, when an obstacle that did not exist at the time of warehousing exists at the time of warehousing, the two traveling routes are appropriately selected to drive the own vehicle, so that the possibility of collision between the own vehicle and the obstacle can be further reduced. ..

Each part of the vehicle control device 100 of the first embodiment described above can be configured by using a computer, and is realized by the computer executing a program. That is, the vehicle control device 100 shown in FIG. 1 is realized by, for example, the processing circuit 100 shown in FIG. A processor such as a CPU or DSP (Digital Signal Processor) is applied to the processing circuit 100, and the functions of each part are realized by executing a program stored in the storage device.

Dedicated hardware may be applied to the processing circuit 100. When the processing circuit 100 is dedicated hardware, the processing circuit 100 corresponds to, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC, an FPGA, or a combination thereof. To do.

Further, FIG. 37 shows a hardware configuration when the vehicle control device 100 shown in FIG. 1 is configured by using a processor. In this case, the functions of each part of the vehicle control device 100 are realized by a combination of software and the like (software, firmware, or software and firmware). The software or the like is described as a program and stored in the memory 120. The processor 110, which functions as the processing circuit 100, realizes the functions of each part by reading and executing the program stored in the memory 120 (storage device).

Further, the parking support devices 200 and 300 of the second and third embodiments can also be configured by using a computer in the same manner as the vehicle control device 100, and are realized by executing a program by the computer, the configuration of which is shown in FIG. 36. Is the same as. Further, the hardware configuration when the parking support devices 200 and 300 are configured by using the processor is the same as that in FIG. 37.

In the present invention, each embodiment can be freely combined, and each embodiment can be appropriately modified or omitted within the scope of the invention.

1 Peripheral situation detection sensor, 2 Own vehicle position detection unit, 3 Object recognition unit, 4 Travel route calculation unit, 5 Vehicle control unit, 6 First delivery travel route generation unit, 7 Travel route comparison unit, 10 Virtual space storage unit , 11 Occupancy calculation unit, 12 Virtual space update unit, 21 Object existence extraction unit, 22 Object avoidance route calculation unit.

Claims (18)

Based on the surrounding situation obtained by the detection sensor that detects the surrounding situation of the own vehicle, the presence / absence of an object around the own vehicle is recognized and the area where the presence / absence of the object cannot be recognized is recognized as an unspecified area. And the object recognition unit that outputs these as the recognition result,
A travel route calculation unit that calculates a travel route based on the vehicle position detected by the vehicle position detection unit and the recognition result.
A control unit that controls steering according to the travel path calculated by the travel route calculation unit is provided.
The traveling route calculation unit
Wherein the unspecified areas have line calculation of the travel path as the object is present,
The object recognition unit
A virtual space storage unit that creates a virtual space divided in a grid pattern around the vehicle including the vehicle, and allocates and stores a first occupancy assigned to the unspecified area to all the grids in the initial state. ,
Based on the vehicle position and the surrounding situation, a second occupancy indicating that the lattice in the virtual space is occupied by the object, and a third occupancy indicating that the lattice is not occupied by the object. An occupancy calculation unit that calculates the degree and the first occupancy indicating that it is unknown whether or not the object occupies the object.
Any one of the first occupancy, the second occupancy, and the third occupancy calculated by the occupancy calculation unit is displayed on the lattice of the virtual space stored in the virtual space storage unit. It has a virtual space update unit that allocates and updates the virtual space, stores it in the virtual space storage unit, and outputs it to the travel route calculation unit.
The traveling route calculation unit
Based on the updated virtual space, the vehicle control device that calculates the travel path assuming that the object exists in the grid having the second occupancy and the grid having the first occupancy. .. The traveling route calculation unit
An object existence extraction unit that extracts the grid having the second occupancy and the grid having the first occupancy as the existence region of the object based on the vehicle position and the updated virtual space.
A claim having an object avoidance route calculation unit that calculates the traveling path so as to avoid the existence region of the object based on the existence region of the object and the position of the own vehicle extracted by the object existence extraction unit. Item 1. The vehicle control device according to item 1. Based on the surrounding situation obtained by the detection sensor that detects the surrounding situation of the own vehicle, the presence / absence of an object around the own vehicle is recognized and the area where the presence / absence of the object cannot be recognized is recognized as an unspecified area. And the object recognition unit that outputs these as the recognition result,
A first warehousing travel route generator that outputs a warehousing travel locus until the vehicle enters the parking space as a first warehousing travel route for the vehicle to exit the parking space.
Based on the own vehicle position detected by the own vehicle position detection unit and the recognition result, a travel route calculation unit that calculates and outputs a second exit travel route for the own vehicle to leave the parking space, and a travel route calculation unit.
A comparison unit that compares the first warehousing travel route and the second warehousing travel route and outputs one as a travel route.
A control unit that controls steering according to the traveling path output from the comparison unit is provided.
The traveling route calculation unit
The calculation of the second delivery travel path is performed assuming that the object exists in the unspecified area.
The comparison unit
When the first warehousing travel route and the second warehousing travel route match, the first warehousing travel route is output as the travel route.
A parking support device that outputs the second exit travel route as the travel route when the first exit travel route and the second exit travel route do not match. Based on the surrounding situation obtained by the detection sensor that detects the surrounding situation of the own vehicle, the presence / absence of an object around the own vehicle is recognized and the area where the presence / absence of the object cannot be recognized is recognized as an unspecified area. And the object recognition unit that outputs these as the recognition result,
A first warehousing travel route generator that outputs a warehousing travel locus until the vehicle enters the parking space as a first warehousing travel route for the vehicle to exit the parking space.
Based on the own vehicle position detected by the own vehicle position detection unit and the recognition result, at least a travel route calculation unit that calculates and outputs a second delivery travel route for the own vehicle to leave the parking space, and
A comparison unit that compares at least the first warehousing travel route and the second warehousing travel route and outputs one as a travel route.
A control unit that controls steering according to the traveling path output from the comparison unit is provided.
The traveling route calculation unit
At least the calculation of the second delivery travel path is performed assuming that the object exists in the unspecified area.
The comparison unit
When the first warehousing travel route and the second warehousing travel route match, the first warehousing travel route is output as the travel route.
When the first warehousing travel route and the second warehousing travel route do not match, the second warehousing travel route is output as the travel route.
When the travel route calculation unit can calculate only a part of the second delivery travel route,
By the time the own vehicle reaches the terminal position of the second delivery travel path, the travel route calculation unit is requested to calculate the third delivery travel route.
When the first warehousing travel route and the third warehousing travel route match, the first warehousing travel route is output as the travel route.
A parking support device that outputs the third exit travel route as the travel route when the first exit travel route and the third exit travel route do not match. The object recognition unit
A virtual space divided in a grid pattern is created around the own vehicle including the own vehicle stored in the parking space, and in the initial state, all the grids are assigned a first occupancy to be assigned to the unspecified area. Virtual space storage unit to store and
Based on the vehicle position and the surrounding situation, a second occupancy indicating that the lattice in the virtual space is occupied by the object, and a third occupancy indicating that the lattice is not occupied by the object. An occupancy calculation unit that calculates the degree and the first occupancy indicating that it is unknown whether or not the object occupies the object.
Any one of the first occupancy, the second occupancy, and the third occupancy calculated by the occupancy calculation unit is displayed on the lattice of the virtual space stored in the virtual space storage unit. It has a virtual space update unit that allocates and updates the virtual space, stores it in the virtual space storage unit, and outputs it to the travel route calculation unit.
The traveling route calculation unit
Based on the updated virtual space, the calculation of the second warehousing travel route is performed assuming that the object exists in the grid having the second occupancy and the grid having the first occupancy. , The parking support device according to claim 3 or 4 . The traveling route calculation unit
An object existence extraction unit that extracts the grid having the second occupancy and the grid having the first occupancy as the existence region of the object based on the vehicle position and the updated virtual space.
A claim having an object avoidance route calculation unit that calculates the traveling path so as to avoid the existence region of the object based on the existence region of the object and the position of the own vehicle extracted by the object existence extraction unit. Item 5. The parking support device according to item 5 . The comparison unit
The parking support device according to claim 3 or 4, wherein the first warehousing travel route and the second warehousing travel route are compared for each predetermined route length to determine whether or not they match. When the travel route calculation unit can calculate only a part of the second delivery travel route,
The traveling route calculation unit
The third aspect of claim 4 , wherein the third warehousing travel route is calculated so that the end position of the first warehousing travel route is the terminal position while moving the own vehicle along the second warehousing travel route. Parking support device. The traveling route calculation unit
The parking according to claim 5 , wherein when the grid having the first occupancy is on the side of the own vehicle, the calculation of the second leaving travel route is performed assuming that the object exists in the grid. Support device. (A) Steps to detect the position of the own vehicle and
(B) Steps to detect the surrounding situation of the own vehicle and
(C) A step of recognizing the presence / absence of an object around the vehicle and recognizing a region in which the presence / absence of the object cannot be recognized as an unspecified region based on the surrounding situation.
(D) A step of calculating a traveling route based on the own vehicle position detected in the step (a) and the recognition result in the step (c).
(E) A step of steering and controlling according to the traveling path calculated in the step (d) is provided.
The step (d) is
Wherein the unspecified areas have line calculation of the travel path as the object is present,
The step (c) is
(C-1) A virtual space divided in a grid pattern is set around the own vehicle including the own vehicle, and in the initial state, a first occupancy degree assigned to the unspecified area is assigned to all the grids and stored. Steps to do and
(C-2) A second degree of occupancy indicating that the lattice in the virtual space is occupied by the object, based on the position of the own vehicle and the surrounding situation, that the object is not occupied. A step of calculating the third occupancy shown and the first occupancy indicating that it is unknown whether or not the object occupies the object.
(C-3) Any one of the first occupancy, the second occupancy, and the third occupancy is assigned to the grid of the virtual space stored in the step (c-1). The step of updating and storing the virtual space and
The step (d) is
Based on the updated virtual space, a vehicle control method for calculating the travel path assuming that an object exists in the grid having the second occupancy and the grid having the first occupancy. .. The step (d) is
(D-1) A step of extracting the grid having the second occupancy and the grid having the first occupancy as the existing region of the object based on the vehicle position and the updated virtual space. When,
(D-2) A step of calculating the traveling path so as to avoid the existing area of the object based on the existing area of the object and the position of the own vehicle extracted in the step (d-1). The vehicle control method according to claim 10 . (A) Steps to detect the position of the own vehicle and
(B) Steps to detect the surrounding situation of the own vehicle and
(C) A step of recognizing the presence / absence of an object around the vehicle and recognizing a region in which the presence / absence of the object cannot be recognized as an unspecified region based on the surrounding situation.
(D) A step of setting the warehousing travel locus until the vehicle enters the parking space as the first warehousing travel route for the vehicle to exit the parking space.
(E) Based on the position of the own vehicle detected in the step (a) and the recognition result in the step (c), the step of calculating the second delivery travel route for the own vehicle to leave the parking space. ,
(F) A step of comparing the first delivery travel route and the second delivery travel route and using one as the travel route.
(G) A step of steering and controlling according to the traveling path calculated in the step (f) is provided.
The step (e) is
The calculation of the second delivery travel path is performed assuming that the object exists in the unspecified area.
The step (f) is
When the first warehousing travel route and the second warehousing travel route match, the first warehousing travel route is set as the travel route.
A parking support method in which when the first warehousing travel route and the second warehousing travel route do not match, the second warehousing travel route is used as the travel route. (A) Steps to detect the position of the own vehicle and
(B) Steps to detect the surrounding situation of the own vehicle and
(C) A step of recognizing the presence / absence of an object around the vehicle and recognizing a region in which the presence / absence of the object cannot be recognized as an unspecified region based on the surrounding situation.
(D) A step of setting the warehousing travel locus until the vehicle enters the parking space as the first warehousing travel route for the vehicle to exit the parking space.
(E) Based on the position of the own vehicle detected in the step (a) and the recognition result in the step (c), the step of calculating the second delivery travel route for the own vehicle to leave the parking space. ,
(F) A step of comparing at least the first warehousing travel route and the second warehousing travel route and outputting one of them as a travel route.
(G) A step of steering and controlling according to the traveling path calculated in the step (f) is provided.
The step (e) is
At least the calculation of the second delivery travel path is performed assuming that the object exists in the unspecified area.
The step (f) is
When the first warehousing travel route and the second warehousing travel route match, the first warehousing travel route is set as the travel route.
When the first warehousing travel route and the second warehousing travel route do not match, the second warehousing travel route is set as the travel route.
When only a part of the second delivery travel route can be calculated in the step (e),
(F-1) The step (e) includes a step of causing the step (e) to calculate a third exit travel route until the own vehicle reaches the terminal position of the second exit travel route.
When the first warehousing travel route and the third warehousing travel route match, the first warehousing travel route is set as the travel route.
A parking support method in which when the first warehousing travel route and the third warehousing travel route do not match, the third warehousing travel route is used as the travel route. The step (c) is
(C-1) A first method in which a virtual space divided in a grid pattern is created around the own vehicle including the own vehicle stored in the parking space, and all the grids are allocated to the unspecified area in the initial state. Steps to assign and store occupancy,
(C-2) A second degree of occupancy indicating that the lattice in the virtual space is occupied by the object, based on the position of the own vehicle and the surrounding situation, that the object is not occupied. A step of calculating the third occupancy shown and the first occupancy indicating that it is unknown whether or not the object occupies the object.
(C-3) Any one of the first occupancy, the second occupancy, and the third occupancy is assigned to the grid of the virtual space stored in the step (c-1). The step of updating and storing the virtual space and
The step (e) is
Based on the updated virtual space, the calculation of the second warehousing travel route is performed assuming that the object exists in the grid having the second occupancy and the grid having the first occupancy. , The parking support method according to claim 12 or 13 . The step (e) is
(E-1) A step of extracting the grid having the second occupancy and the grid having the first occupancy as the existing region of the object based on the vehicle position and the updated virtual space. When,
(E-2) Based on the existing area of the object and the position of the own vehicle extracted in the step (e-1), the second delivery travel route is calculated so as to avoid the existing area of the object. The parking support method according to claim 14 , further comprising a step. The step (f) is
The parking support method according to claim 12 or 13, wherein the first warehousing travel route and the second warehousing travel route are compared for each predetermined route length to determine whether or not they match. The step (e) is
When only a part of the second delivery travel route can be calculated,
13. The thirteenth aspect of the present invention, wherein the third warehousing travel route is calculated so that the end position of the first warehousing travel route is the terminal position while moving the own vehicle along the second warehousing travel route. Parking support method. The step (e) is
The parking according to claim 14 , wherein when the grid having the first occupancy is on the side of the own vehicle, the calculation of the second leaving travel route is performed assuming that the object exists in the grid. Support method.

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