JP7687377B1 - Automatic driving device and automatic driving method - Google Patents

Abstract

A moving object is caused to travel along a route suited to the location of an obstacle.
[Solution] The autonomous driving device 30 has a first determination unit 321 that determines a first potential, which quantifies the degree to which it is recommended for the moving body to travel, for each position around the obstacle based on the position of the obstacle extracted from point cloud data. The first determination unit 321 determines the output value output by the potential function as the first potential by inputting the positions around the obstacle into a potential function that includes a first coefficient for determining the ratio between a first amount of change in the first potential in the traveling direction of the moving body and in the direction opposite to the traveling direction, and a second amount of change in the first potential in the right direction and the left direction with respect to the traveling direction, a second coefficient for determining the ratio between the first amount of change in the traveling direction from the obstacle and the first amount of change in the direction opposite to the traveling direction from the obstacle, and a third coefficient for determining the magnitude of the first potential.
[Selected Figure] Figure 4

Description

The present invention relates to an automatic driving device and an automatic driving method.

The driving assistance device described in Patent Document 1 sets potential values, which are numerical values representing the degree to which it is advisable for the vehicle to travel, at each position around the vehicle, based on the positions of objects around the vehicle (which is a moving body) and the shape of the road, and sets the vehicle's travel route based on the potential values.

JP 2018-192954 A

Conventional driving assistance devices set the largest potential value (where it is least recommended for the moving body to travel) at the position of an obstacle present around the moving body, and set smaller potential values for positions that are farther away from the obstacle position. In other words, in conventional driving assistance devices, the same potential value spreads out in concentric circles around the obstacle position, and the greater the distance between the obstacle position and the position, the smaller the potential value becomes.

Therefore, the travel route set so that the moving body does not come into contact with an obstacle ahead in the traveling direction is a semicircle centered on the obstacle, so the distance between the moving body and the obstacle in the width direction and traveling direction of the travel path indicated by the travel route becomes larger as one increases, and the other also increases. As a result, even if the moving body travels in a way that does not come into contact with the obstacle, there are problems such as the time it takes to return from obstacle avoidance travel to normal travel being unnecessarily long, and the risk of contact with other moving bodies traveling in the opposite direction to the moving body's direction of travel.

Therefore, the present invention was made in consideration of these points, and aims to make a mobile object travel along a route that is appropriate for the location of an obstacle.

The autonomous driving device according to the first aspect of the present invention has an acquisition unit that acquires point cloud data generated by measuring an area around a moving body, and a first determination unit that determines a first potential that quantifies the degree to which it is recommended for the moving body to travel for each position around the obstacle based on the position of the obstacle extracted from the point cloud data. The first determination unit inputs the positions around the obstacle into a potential function including a first coefficient for determining a ratio between a first change in the first potential in the traveling direction of the moving body and in the direction opposite to the traveling direction, and a second change in the first potential in the right direction and the left direction with respect to the traveling direction, a second coefficient for determining a ratio between the first change in the traveling direction from the obstacle and the first change in the direction opposite to the traveling direction from the obstacle, and a third coefficient for determining the magnitude of the first potential, thereby determining an output value output by the potential function as the first potential.

The vehicle may further include a second determination unit that determines a second potential that quantifies the degree to which it is recommended that the moving body travel for each position around the obstacle by referring to map information including the position of the travel path, a synthesis unit that generates a synthetic potential by synthesizing the first potential and the second potential for each position around the obstacle, and a setting unit that sets a route for the moving body to travel based on the synthetic potential.

The first determination unit may determine, as the first potential, an output value of the potential function that further includes a fourth coefficient and a fifth coefficient for determining the first change amount, the second change amount, and the magnitude of the second potential relative to the first potential.

The first determination unit may input to the potential function, as positions around the obstacle, a coordinate corresponding to one of a plurality of second coordinates within a predetermined distance from a first coordinate, the coordinate being set as an origin, and an angle formed between a line passing through the origin and the coordinate corresponding to the one of the second coordinates and a line indicating the traveling direction of the moving body.

The first determination unit may calculate, for each of the first coordinates, the output value for each of the second coordinates corresponding to the first coordinates, and if the first potential of the second coordinates corresponding to the output value has not been determined before the output value is calculated, determine the output value to be the first potential, and if the first potential of the second coordinates corresponding to the output value has been determined before the output value is calculated, add the output value to the first potential.

The acquisition unit may acquire point cloud data that excludes point clouds generated by reflection at a position different from the position of the obstacle from among a plurality of point clouds included in the point cloud data generated by measuring the area around the moving body.

The autonomous driving method according to the second aspect of the present invention includes an acquisition step of acquiring point cloud data generated by measuring an area around a moving body, and a determination step of determining a first potential that quantifies the degree to which it is recommended for the moving body to travel for each position around the obstacle based on the position of the obstacle extracted from the point cloud data. In the determination step, the positions around the obstacle are input to a potential function including a first coefficient for determining a ratio between a first change amount of the first potential in the traveling direction of the moving body and in the direction opposite to the traveling direction, and a second change amount of the first potential in the right direction and the left direction with respect to the traveling direction, a second coefficient for determining a ratio between the first change amount in the traveling direction from the obstacle and the first change amount in the direction opposite to the traveling direction from the obstacle, and a third coefficient for determining the magnitude of the first potential, thereby determining an output value output by the potential function as the first potential.

The present invention has the effect of making a mobile object travel along a route that is appropriate for the location of an obstacle.

FIG. 1 is a diagram for explaining an overview of an automatic driving system S. 1A and 1B are diagrams illustrating the operation of a vehicle when an obstacle is present ahead in the traveling direction. 4 shows an example of an obstacle risk potential set for the host vehicle S1. FIG. 1 is a diagram showing the configuration of an automatic driving system S. FIG. 11 is a diagram for explaining information indicating positions around an obstacle. An example of a potential field when each coefficient is set is shown below. An example of the potential field when the value of the coefficient a is increased is shown. An example of the potential field when the value of the coefficient σ is increased is shown. An example of the potential field when the value of the coefficient β is increased is shown. An example of the potential field when the coefficient _S0 is increased is shown. FIG. 2 is a diagram showing an example of a processing sequence in the automatic driving device 30.

<Overview of the Autonomous Driving System S>
FIG. 1 is a diagram for explaining an overview of an automatic driving system S. The automatic driving system S is a system for determining a travel route of a moving body based on information indicating obstacles and a travel route around the moving body, and for causing the moving body to travel along the travel route, and is, for example, a system provided in the moving body. The moving body is, for example, a vehicle or a robot. In this embodiment, a case where the moving body is a vehicle will be described. An obstacle is an object that is stationary on the travel route, for example, another vehicle that is stopped, a fallen object, or a safety fence. The travel route is a road on which the vehicle can travel. The travel route includes a plurality of travel positions where the vehicle is made to travel and the vehicle orientation corresponding to each travel position.

First, the operation of the automatic driving system S for determining a driving route will be described.
The autonomous driving system S generates a first potential field in which a first potential value is set at a position around the vehicle based on point cloud data generated by a LiDAR (Light Detection And Ranging) equipped in the vehicle measuring obstacles around the vehicle (shown in FIG. 1 (1)). The overhead view 1a and the heat map 1b are examples of the first potential field, in which the x-axis indicates the traveling direction of the vehicle, the y-axis indicates the vehicle width direction, and the z-axis indicates the first potential value. In the first potential field, the largest first potential value is set at a position corresponding to an obstacle, and the larger the distance between the position and the position corresponding to the obstacle, the smaller the first potential value is set. In the following description, the first potential may be referred to as an "obstacle risk potential".

The autonomous driving system S generates a second potential field in which second potential values are set at positions around the vehicle based on the position of the vehicle based on the point cloud data and map information including the position of the road (shown in FIG. 1 (2)). The overhead view 2a and heat map 2b are an example of the second potential field, and the x-axis, y-axis, and z-axis are the same as the x-axis, y-axis, and z-axis shown in the overhead view 1a and heat map 1b. In the second potential field, the smallest second potential value is set at the center of the road in the width direction of the road, and the largest second potential value is set at a position different from the road. In the following description, the second potential may be referred to as an "attractive potential."

The autonomous driving system S generates a composite potential field in which a composite potential value is set by combining (adding) an obstacle risk potential value with an attractive potential value at each position around the vehicle (as shown in FIG. 1 (3)). Heat map 3 is an example of a composite potential field, and the x-axis and y-axis are the same as the x-axis and y-axis shown in heat map 1b. The autonomous driving system S determines route K, which minimizes the sum of the composite potential values in the composite potential field, as the driving route, and drives the vehicle along route K.

Next, the operation of the autonomous driving system S to set an obstacle risk potential will be described. FIG. 2 is a diagram showing the operation of the vehicle when there is an obstacle ahead in the traveling direction. FIG. 2 shows the host vehicle S1 equipped with the autonomous driving system S, another vehicle S2 (obstacle) stopped ahead in the traveling direction D1 of the host vehicle S1, and another vehicle S3 (oncoming vehicle) traveling in a lane R2 adjacent to the lane R1 in which the host vehicle S1 is traveling. The traveling direction D2 of the lane R2 is opposite to the traveling direction D1 of the lane R1. As shown in FIG. 2, the host vehicle S1 starts an operation to travel a route to avoid contact with the other vehicle S2 (hereinafter referred to as "contact avoidance traveling") at position PB, and ends the contact avoidance traveling at position PE.

Figure 3 shows an example of an obstacle risk potential set for the host vehicle S1. In Figure 3, positions where the obstacle risk potential has the same value are indicated by dashed lines. Figure 3(a) shows an obstacle risk potential as a comparative example, and Figure 3(b) shows the obstacle risk potential according to this embodiment.

In FIG. 3(a), the same obstacle risk potential value spreads out in concentric circles centered on the position of the other vehicle S2 (obstacle), and the greater the distance from the position of the other vehicle S2, the smaller the obstacle risk potential value. In this case, the longer the distance LV between the position PB where the contact avoidance driving starts and the position PE where it ends, and the distance LH between the host vehicle S1 and the other vehicle S2 in the width direction of the host vehicle S1, the longer the other becomes. As a result, the host vehicle S1 may come into contact with the other vehicle S3 shown in FIG. 2 during contact avoidance driving against the other vehicle S2 because the distance LH increases with the distance LV, or the distance and time for contact avoidance driving may become unnecessarily long because the distance LV increases with the distance LH.

Therefore, the autonomous driving system S adjusts the amount of change in the obstacle risk potential, which changes depending on the distance to the obstacle position, in the traveling direction D1, the direction opposite to the traveling direction D1, and the vehicle width direction of the traveling direction D1. For example, in FIG. 3(b), the amount of change in the obstacle risk potential in the traveling direction D1 is made larger than the amount of change in the obstacle risk potential in the direction opposite to the traveling direction D1. Furthermore, the amount of change in the obstacle risk potential in the vehicle width direction of the traveling direction D1 is made smaller than the amount of change in the obstacle risk potential shown in FIG. 3(a).

By operating the autonomous driving system S in this manner, the host vehicle S1 can travel along a route K that is appropriate for the location of the obstacle. As a result, the autonomous driving system S can drive the host vehicle S1 during contact avoidance driving so that the host vehicle S1 does not come into contact with another vehicle S2 that is stopped ahead of the host vehicle S1 in the traveling direction D1 of the host vehicle S1. Furthermore, the autonomous driving system S can prevent the host vehicle S1 from coming into contact with another vehicle S3 traveling in the opposite direction (traveling direction D2) to the traveling direction D1 of the host vehicle S1 during contact avoidance driving, or prevent the distance the host vehicle S1 travels during contact avoidance driving from becoming unnecessarily long.

<Configuration of the automatic driving system S>
4 is a diagram showing a configuration of the automatic driving system S. The automatic driving system S includes a measurement device 10, a driving control device 20, and an automatic driving device 30.

The measuring device 10 is a three-dimensional laser measuring device for measuring the distance between the host vehicle S1 and objects around the host vehicle S1, and includes, for example, LiDAR. The measuring device 10 outputs point cloud data generated by measuring the distance between the host vehicle S1 and objects included in the area around the host vehicle S1 to the automatic driving device 30 at a constant control period. The control period is, for example, 0.1 seconds. The area around the host vehicle S1 is, for example, an area included in the traveling direction D1, 100 meters ahead of the host vehicle S1, 50 meters behind the host vehicle S1, 50 meters to the left of the host vehicle S1, and 50 meters to the right of the host vehicle S1.

The driving control device 20 controls the speed and direction of the host vehicle S1. The driving control device 20 controls the direction of the host vehicle S1 according to the steering angle at the time of the next control cycle, which is output by the automatic driving device 30 at a fixed control cycle.

The automatic driving device 30 determines a composite potential value at a constant control period by combining an obstacle risk potential value based on the point cloud data input from the measurement device 10 with an attractive potential value based on map information including the position of the driving path. The automatic driving device 30 determines a driving route for the host vehicle S1 based on the composite potential value, and calculates a steering angle for the host vehicle S1 based on the position of the host vehicle S1 on the driving route. The automatic driving device 30 inputs the calculated steering angle to the driving control device 20, thereby causing the host vehicle S1 to travel along the driving route. The automatic driving device 30 may have a housing including electronic components, or may be a printed circuit board on which electronic components are mounted.
The configuration and operation of the automatic driving device 30 will be described in detail below.

<Configuration of automatic driving device 30>
4 , the autonomous driving device 30 has a storage unit 31 and a control unit 32. The control unit 32 has an acquisition unit 320, a first determination unit 321, a second determination unit 322, a synthesis unit 323, a setting unit 324, and a driving control unit 325.

The memory unit 31 has a storage medium such as a read only memory (ROM), a random access memory (RAM), a hard disk drive (HDD), or a solid state drive (SSD). The memory unit 31 stores a program executed by the control unit 32. The memory unit 31 stores various information for determining the driving route of the host vehicle S1.

The control unit 32 is, for example, a processor such as a CPU (Central Processing Unit) or an ECU (Electronic Control Unit). The control unit 32 executes a program stored in the storage unit 31 to function as an acquisition unit 320, a first determination unit 321, a second determination unit 322, a synthesis unit 323, a setting unit 324, and a driving control unit 325. The control unit 32 may be configured with one processor, or may be configured with multiple processors or a combination of one or more processors and an electronic circuit.
The configuration of each unit realized by the control unit 32 will be described below.

The acquisition unit 320 acquires point cloud data generated by measuring the area around the vehicle S1 from the measurement device 10 at a constant control period. The acquisition unit 320 may acquire point cloud data excluding point clouds generated by reflection at a position different from the position of an obstacle from among multiple point clouds included in the point cloud data generated by measuring the area around the vehicle S1.

As an example, the acquisition unit 320 determines whether or not the value corresponding to the measurement distance indicated by each point cloud included in the point cloud data acquired from the measuring device 10 is equal to or less than a threshold value, and acquires data obtained by excluding point clouds indicating values equal to or less than the threshold value from the point cloud data as point cloud data. The threshold value is, for example, the maximum value that can be estimated as the distance reflected on the ground. As another example, the acquisition unit 320 acquires data obtained by extracting point clouds indicating values different from the value that can be estimated as the ground from a plurality of point clouds included in the point cloud data acquired from the measuring device 10 as point cloud data. By operating the acquisition unit 320 in this manner, the first determination unit 321 can easily extract the position of an obstacle from the point cloud data. Note that the acquisition unit 320 may acquire point cloud data excluding point clouds generated by reflection at a position different from the position of the obstacle from the measuring device 10 at a constant control period.

The first determination unit 321 determines an obstacle risk potential, which is a numerical representation of the degree to which it is recommended that the host vehicle S1 should continue traveling, for each position around the obstacle, based on the position of the obstacle extracted from the point cloud data. For example, at a constant control period, the first determination unit 321 extracts the position of the obstacle's outline from the point cloud data acquired by the acquisition unit 320, and determines the obstacle risk potential for each position around the obstacle. The positions around the obstacle are positions included in a circle of a predetermined radius centered on the point cloud corresponding to the obstacle's outline. The predetermined radius is, for example, a fixed value between 5 meters and 10 meters. In the following description, the position extracted from the point cloud data (i.e., the position where the light irradiated by the measurement device 10 is reflected by the obstacle) among the multiple positions corresponding to the obstacle's outline may be referred to as an "observation point".

The first determination unit 321 inputs the positions around the obstacle into a potential function including a plurality of coefficients, and determines an output value of the potential function as the obstacle risk potential value. The potential function can be given as in Equation (1), Equation (2), and Equation (3).
The angle θ, the position x, and the position y are information input to the potential function as positions around the obstacle. The coefficients a, σ, β, and _S0 are coefficients determined by experiments or simulations before the host vehicle S1 travels.
The information indicating the positions around an obstacle and the above coefficients will be described in detail below.

First, the information indicating the position around the obstacle will be described. FIG. 5 is a diagram for explaining the information indicating the position around the obstacle. FIG. 5 shows a coordinate A1 (0,0) corresponding to one of the first coordinates among a plurality of first coordinates indicating the position of the obstacle, and a coordinate A2 (x1,y1) corresponding to one of the second coordinates among a plurality of second coordinates within a predetermined distance from the first coordinate. The first coordinate is a coordinate indicating the position of the observation point, and the second coordinate is a coordinate indicating the position around the obstacle at the observation point. The predetermined distance is, for example, a fixed value of 5 meters or more and 10 meters or less. For example, the first determination unit 321 inputs the coordinate (coordinate A2) corresponding to the second coordinate when the first coordinate is set as the origin (coordinate A1), and the angle θ between the straight line passing through the coordinates A1 and A2 and the straight line indicating the traveling direction D1 of the host vehicle S1 into the potential function as the position around the obstacle.

For example, the first determination unit 321 calculates an output value for each second coordinate corresponding to each first coordinate. That is, in a plurality of point cloud data forming the outline of an obstacle, the first determination unit 321 identifies, for each first coordinate corresponding to the point cloud data, a second coordinate corresponding to each position within a predetermined distance from the position of the point cloud data. For each first coordinate, the first determination unit 321 inputs the coordinate A2 and angle θ corresponding to the second coordinate into a potential function for each second coordinate, and calculates an obstacle risk potential for each second coordinate.

For example, if the obstacle risk potential of the second coordinate corresponding to the output value has not been determined before the output value is calculated, the first determination unit 321 determines the output value as the obstacle risk potential. Also, for example, if the obstacle risk potential of the second coordinate corresponding to the output value has been determined before the output value is calculated, the first determination unit 321 adds the output value to the obstacle risk potential. That is, for each first coordinate having a position around the obstacle as a second coordinate, the first determination unit 321 outputs an output value obtained by inputting the position into a potential function, and determines the sum of the output values for each first coordinate as the obstacle risk potential for the position.

Next, the coefficients included in the potential function will be described. As shown in equations (1), (2) and (3), the potential function includes a coefficient a, a coefficient σ, a coefficient β and a coefficient _S0 . The coefficient a is a first coefficient for determining the ratio between a first change amount of the obstacle risk potential in the traveling direction D1 of the host vehicle S1 and in the direction opposite to the traveling direction D1, and a second change amount of the obstacle risk potential in the right direction and the left direction with respect to the traveling direction D1. The coefficient a is, for example, a value of 1 or more, and the larger the coefficient a, the larger the ratio of the second change amount to the first change amount. Here, the coefficient a will be described with reference to the potential fields shown in Figs. 6 and 7.

Fig. 6 shows an example of a potential field when each coefficient is set. Fig. 6(a) is an overhead view of the potential field, and Fig. 6(b) is a heat map of the potential field. The x-axis, y-axis, and z-axis shown in Fig. 6 are the same as the x-axis, y-axis, and z-axis shown in Fig. 1. Fig. 6 shows a potential field of obstacle risk potential values calculated by setting coefficients a = 2.0, σ = 0.0, β = 0.0, and S ₀ = 3.0 in the potential function. The origin (0,0) shown in Fig. 6 is a coordinate indicating a position corresponding to the observation point (i.e., coordinate A1 shown in Fig. 5).

In FIG. 6(b), coefficient a is a coefficient for determining the ratio between the first amount of change in the ±x direction and the second amount of change in the ±y direction. That is, coefficient a is a coefficient for determining the ratio between width RX6 corresponding to the first amount of change (width corresponding to distance LV shown in FIG. 3) and width RY6 corresponding to the second amount of change (width corresponding to distance LH shown in FIG. 3). In FIG. 6(b), the larger the first amount of change, the smaller the width RX6, and the larger the second amount of change, the smaller the width RY6. That is, the larger coefficient a is, the smaller the width RY6 relative to width RX6.

Figure 7 shows an example of a potential field when the value of coefficient a is increased. The potential field shown in Figure 7 differs from the potential field shown in Figure 6 (b) in that coefficient a is set to 4.0, but is otherwise the same. As shown in Figure 7, the ratio of width RY7 to width RX7 is smaller than the ratio of width RY6 to width RX6 shown in Figure 6. In this way, the first determination unit 321 uses a potential function including coefficient a, so that the setting unit 324 can set a driving route for the host vehicle S1 in which the ratio between the distance LV corresponding to the first change amount and the distance LH corresponding to the second change amount shown in Figure 3 is adjusted.

The coefficients σ and β are second coefficients for determining the ratio between the first forward change amount in the travel direction D1 (+x direction) from the obstacle and the first backward change amount in the opposite direction (-x direction) of the travel direction D1 from the obstacle. The coefficient σ is, for example, a value between -1 and 1. When the coefficient σ>0, the first forward change amount is greater than the first backward change amount, when the coefficient σ<0, the first backward change amount is greater than the first forward change amount, and when the coefficient σ=0, the first forward change amount and the first backward change amount are the same. For example, in FIG. 6(a), since the coefficient σ=0, the width PZ6 corresponding to the first forward change amount (the width corresponding to the distance LV1 shown in FIG. 3) and the width MZ6 corresponding to the first backward change amount (the width corresponding to the distance LV2 shown in FIG. 3) are the same width.

Figure 8 shows an example of the potential field when the value of the coefficient σ is increased. The potential field shown in Figure 8 differs from the potential field shown in Figure 6 (a) in that the coefficient σ is set to 0.6, but is otherwise the same. As shown in Figure 8, when the coefficient σ = 0.6, the first forward change amount is greater than the first backward change amount, so that the width MZ8 corresponding to the first backward change amount is greater than the width PZ8 corresponding to the first forward change amount. In this way, the first determination unit 321 uses a potential function including the coefficient σ, so that the setting unit 324 can set a driving route for the host vehicle S1 in which the ratio between the distance LV1 corresponding to the first forward change amount and the distance LV2 corresponding to the first backward change amount shown in Figure 3 is adjusted.

The coefficient β is, for example, a value equal to or greater than 0, and the greater the value of the coefficient β, the greater the difference between the first forward change amount and the first backward change amount. In other words, when the coefficient σ>0, the greater the value of the coefficient β, the greater the first forward change amount becomes relative to the first backward change amount, and when the coefficient σ<0, the greater the value of the coefficient β, the greater the first backward change amount becomes relative to the first forward change amount.

9 shows an example of the potential field when the value of the coefficient β is increased. The potential field shown in FIG. 9 differs from the potential field shown in FIG. 8 in that β=1.0 is set, but is otherwise the same. The width PZ9 shown in FIG. 9 is the distance corresponding to the first forward change amount, and the width MZ9 is the distance corresponding to the first backward change amount. As shown in FIG. 9, the width MZ9 relative to the width PZ9 when the coefficient β=1.0 and the coefficient σ=0.6 is larger than the width MZ8 relative to the width PZ8 when the coefficient β=0.0 and the coefficient σ=0.6 shown in FIG. 8. In this way, the first determination unit 321 uses a potential function including the coefficient β, so that the setting unit 324 can set a driving route for the host vehicle S1 in which the ratio between the distance LV1 corresponding to the first forward change amount and the distance LV2 corresponding to the first backward change amount shown in FIG. 3 is adjusted to be even larger.

The coefficient _S0 is a third coefficient for determining the magnitude of the obstacle risk potential. In the potential functions given by equations (1), (2), and (3), the larger the coefficient _S0 , the larger the obstacle risk potential value at each position. FIG. 10 shows an example of a potential field when the coefficient _S0 is increased. The potential field shown in FIG. 10 differs from the potential field shown in FIG. 6(b) in that the coefficient _S0 is set to 6.0, but is otherwise the same. A width RX10 shown in FIG. 10 is a distance corresponding to the first amount of change and is a distance corresponding to the distance LV shown in FIG. 3. A width RY10 shown in FIG. 10 is a distance corresponding to the second amount of change and is a distance corresponding to the distance LH shown in FIG. 3.

As shown in Fig. 10, by increasing the coefficient _S0 , the absolute value of the width RX10 is larger than the absolute value of the width RX6 shown in Fig. 6, and the absolute value of the width RY10 is larger than the absolute value of the width RY6 shown in Fig. 6. In this way, the first determination unit 321 can increase the potential value around the obstacle by using a potential function including the coefficient _S0 , so that the setting unit 324 can set a driving route in which the distance between the position where the host vehicle S1 is traveling and the obstacle is adjusted.

As described above, the first determination unit 321 determines the obstacle risk potential using a potential function in which the coefficients a, σ, β, and S ₀ are set, and thereby it is possible to adjust the obstacle risk potential value around the obstacle. As a result, it is possible to adjust the positions PB and PE shown in Fig. 3 and the distances LV1, LV2, and LH, and therefore the autonomous driving device 30 can adjust the route for the host vehicle S1 to travel in a manner to avoid contact with the obstacle.
The information indicating the positions around an obstacle and the above coefficients have been described in detail above.

The first determination unit 321 may determine, as the obstacle risk potential, an output value of a potential function further including a fourth coefficient p and a fifth coefficient q for determining the first change amount, the second change amount, and the magnitude of the attractive potential with respect to the obstacle risk potential. The potential function using the fourth coefficient p and the fifth coefficient q can be given by replacing equation (1) with equation (4).
The fourth coefficient p and the fifth coefficient q are set so that the fourth coefficient p is greater than the fifth coefficient q. In this way, by the first determination unit 321 using a potential function using the fourth coefficient p and the fifth coefficient q, the first determination unit 321 can further fine-tune the first change amount and the second change amount, or adjust the ratio of the obstacle risk potential to the composite potential.

Returning to FIG. 4, the second determination unit 322 determines an attractive potential for each position around the obstacle by referencing map information including the position of the travel path, the attractive potential being a numerical value representing the degree to which travel of the vehicle S1 is recommended. The second determination unit 322 determines the attractive potential at a constant control period, for example. The second determination unit 322 estimates the position of the vehicle S1, for example, based on the point cloud data acquired by the acquisition unit 320. The second determination unit 322 identifies the position of the travel path around the estimated position of the vehicle S1 by referencing the map information stored in the memory unit 31. The second determination unit 322 determines the attractive potential for each position around the obstacle based on the identified position of the travel path. The attractive potential value is smallest at the center of the travel path and largest at a position different from the travel path.

The synthesis unit 323 generates a synthetic potential by synthesizing the obstacle risk potential and the gravitational potential for each position around the obstacle. For example, at a constant control period, the synthesis unit 323 calculates an added value by adding the obstacle risk potential value determined by the first determination unit 321 to the gravitational potential value determined by the second determination unit 322 for each position around the obstacle, and determines the added value as the synthetic potential value.

The setting unit 324 sets the route K along which the host vehicle S1 travels based on the composite potential. For example, the setting unit 324 sets, as the travel route, the route K along which the sum of the composite potential values is minimized in a composite potential field in which the composite potential values determined by the synthesis unit 323 are set for each position around an obstacle at a constant control period.

The driving control unit 325 calculates the steering angle of the steering wheel or tires of the vehicle S1 at a constant control period based on the position of the vehicle S1 estimated by the second determination unit 322 and the driving route set by the setting unit 324, and outputs the steering angle to the driving control device 20. The driving control unit 325, for example, identifies the position of the vehicle S1 estimated by the second determination unit 322 on the driving route set by the setting unit 324. The driving control unit 325 calculates a steering angle for driving the vehicle S1 along the driving route from the identified position, and outputs the steering angle to the driving control device 20.

<Processing sequence in the automatic driving device 30>
Fig. 11 is a diagram showing an example of a processing sequence in the automated driving device 30. The processing sequence in Fig. 11 is a processing sequence showing the operation of the automated driving device 30 to determine an obstacle risk potential value. The automated driving device 30 executes the processing sequence shown in Fig. 11 at a fixed control period.

The acquisition unit 320 acquires point cloud data from the measurement device 10 (S11). The first determination unit 321 identifies a plurality of first coordinates indicating the position of the obstacle by extracting the position of the obstacle from the point cloud data (S12). The first determination unit 321 selects one of the plurality of first coordinates (S13). The first determination unit 321 identifies a plurality of second coordinates corresponding to the selected first coordinate (S14). The plurality of second coordinates are coordinates within a predetermined range from the selected first coordinate, for example, coordinates within a position of 5 meters from the first coordinate.

The first determination unit 321 selects one second coordinate from the multiple identified second coordinates (S15), and inputs position information corresponding to the selected second coordinate to the potential function, thereby causing the potential function to output an output value (S16). The position information is the coordinate value (x1, y1) of the second coordinate selected in step S15, with the first coordinate selected in step S13 as the origin, and the angle θ between a line passing through the origin and the coordinate value and a line indicating the traveling direction of the host vehicle S1.

If the obstacle risk potential corresponding to the second coordinate selected in step S15 has been determined (YES in S17), the first determination unit 321 adds the output value output from the potential function to the obstacle risk potential value (S18). If the obstacle risk potential corresponding to the second coordinate selected in step S15 has not been determined (NO in S17), the first determination unit 321 determines the output value output from the potential function as the obstacle risk potential value (S19).

If the first determination unit 321 has not finished selecting all of the multiple second coordinates identified in step S14 (NO in S20), it repeats the process from step S15 to step S19. If the first determination unit 321 has finished selecting all of the multiple second coordinates identified in step S14 (YES in S20), it proceeds to the process of step S21. If the first determination unit 321 has not finished selecting all of the multiple first coordinates identified in S12 (NO in S21), it repeats the process from step S13 to step S20. If the first determination unit 321 has finished selecting all of the multiple first coordinates identified in S12 (YES in S21), it ends the process.

<Effects of the automatic driving device 30>
As described above, the autonomous driving device 30 has an acquisition unit 320 that acquires point cloud data generated by measuring the area ahead in the direction of travel of the host vehicle S1, and a first determination unit 321 that determines an obstacle risk potential that quantifies the degree to which it is recommended that the host vehicle S1 continue traveling, for each position around the obstacle, based on the position of the obstacle extracted from the point cloud data.

Then, the first determination unit 321 inputs the positions around the obstacle into a potential function including a first coefficient for determining the ratio between a first change amount of the obstacle risk potential in the traveling direction of the host vehicle S1 and the direction opposite to the traveling direction and a second change amount of the obstacle risk potential in the right direction and the left direction with respect to the traveling direction, a second coefficient for determining the ratio between the first change amount in the traveling direction of the host vehicle S1 from the obstacle and the first change amount in the direction opposite to the traveling direction of the host vehicle S1 from the obstacle, and a third coefficient for determining the magnitude of the obstacle risk potential, and determines the output value output by the potential function as the obstacle risk potential.

By configuring the automatic driving device 30 in this manner, the automatic driving device 30 can adjust the positions at which the vehicle S1 starts and ends traveling to avoid contacting an obstacle ahead in the traveling direction (driving lane), and the distance between the vehicle S1 and the obstacle. As a result, the automatic driving device 30 can prevent the vehicle S1 from coming into contact with another vehicle S3 traveling in the opposite direction to the traveling direction D1 of the vehicle S1, or from traveling an unnecessarily long distance to avoid contacting an obstacle, and can cause the vehicle S1 to travel along the route K appropriate for the location of the obstacle.

Furthermore, the autonomous driving device 30 generates a potential field based on the position (of the obstacle) extracted from the point cloud data, without identifying the size, shape, or type of the obstacle from the point cloud data measured and generated by the measurement device 10. Therefore, it is possible to prevent the autonomous driving device 30 from setting an incorrect route K due to an incorrect identification of an obstacle, and to prevent the host vehicle S1 from traveling along the incorrect route K.

Although the present invention has been described above using embodiments, the technical scope of the present invention is not limited to the scope described in the above embodiments, and various modifications and changes are possible within the scope of the gist of the invention. For example, all or part of the device can be configured by distributing or integrating functionally or physically in any unit. In addition, new embodiments resulting from any combination of multiple embodiments are also included in the embodiments of the present invention. The effect of the new embodiment resulting from the combination also has the effect of the original embodiment.

10 Measurement device 20 Travel control device 30 Automatic driving device 31 Storage unit 32 Control unit 320 Acquisition unit 321 First decision unit 322 Second decision unit 323 Synthesis unit 324 Setting unit 325 Travel control unit

Claims (5)

An acquisition unit that acquires point cloud data generated by measuring an area around a moving object;
a first determination unit that determines a first potential, which is a numerical value representing a degree of recommendation for the traveling of the moving object, for each position around the obstacle, based on a position of the obstacle extracted from the point cloud data;
a second determination unit that determines a second potential, which is a numerical value representing a degree of recommendation for the traveling of the moving object, for each position around the obstacle by referring to map information including a position of a traveling path;
a combining unit that generates a combined potential by combining the first potential and the second potential for each position around the obstacle;
a setting unit that sets a route along which the moving object travels based on the composite potential ,
The first determination unit,
a potential function including a first coefficient for determining a ratio between a first change amount of the first potential in the traveling direction of the moving body and a direction opposite to the traveling direction and a second change amount of the first potential in a right direction and a left direction with respect to the traveling direction, a second coefficient for determining a ratio between the first change amount in the traveling direction from the obstacle and the first change amount in a direction opposite to the traveling direction from the obstacle , a third coefficient for determining a magnitude of the first potential, and fourth and fifth coefficients for determining the first change amount and the second change amount, and the magnitude of the second potential with respect to the first potential ,
By inputting the position around the obstacle, an output value output by the potential function is determined as the first potential.
Autonomous driving device. the first determination unit inputs, into the potential function as positions around the obstacle, a coordinate corresponding to one of a plurality of second coordinates within a predetermined distance from a first coordinate, the coordinate being set as an origin, and an angle formed between a line passing through the origin and the coordinate corresponding to the one second coordinate and a line indicating a traveling direction of the moving body;
The automatic driving device according to claim 1 . The first determination unit,
calculating, for each of the first coordinates, the output value for each of the second coordinates corresponding to the first coordinates;
If the first potential of the second coordinate corresponding to the output value has not been determined before the output value is calculated, the output value is determined to be the first potential;
if the first potential of the second coordinate corresponding to the output value has been determined before the output value is calculated, the output value is added to the first potential.
The automatic driving device according to claim 2 . the acquisition unit acquires point cloud data excluding a point cloud generated by reflection at a position different from the position of the obstacle from a plurality of point clouds included in the point cloud data generated by measuring an area around the moving object;
The automatic driving device according to claim 1 . An acquisition step of acquiring point cloud data generated by measuring an area around the moving object;
a first determination step of determining a first potential, which is a numerical value representing a degree of recommendation for the traveling of the moving object, for each position around the obstacle based on the position of the obstacle extracted from the point cloud data;
a second determination step of determining a second potential, which is a numerical value representing a degree of recommendation for the traveling of the moving object, for each position around the obstacle by referring to map information including a position of a traveling route;
a combining step of generating a combined potential by combining the first potential and the second potential for each position around the obstacle;
A setting step of setting a route along which the moving object travels based on the composite potential ,
In the first determination step, a position around the obstacle is input to a potential function including a first coefficient for determining a ratio between a first change amount of the first potential in the traveling direction of the moving body and a direction opposite to the traveling direction and a second change amount of the first potential in a right direction and a left direction with respect to the traveling direction, a second coefficient for determining a ratio between the first change amount in the traveling direction from the obstacle and the first change amount in the opposite direction to the traveling direction from the obstacle, a third coefficient for determining a magnitude of the first potential, and fourth and fifth coefficients for determining the first change amount, the second change amount, and a magnitude of the second potential relative to the first potential, thereby determining an output value output by the potential function as the first potential.
Autonomous driving method.

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