WO2024247160A1 - Trajectory generation method and trajectory generation device - Google Patents

Abstract

In a trajectory generation method and a trajectory generation device (20) according to the present invention, when a vehicle (V) is to enter an intersection (B1), a candidate lane (L1, L2, L3), which is a candidate for a lane for the vehicle (V) to travel when exiting the intersection (B1), is detected using detection results of a detection device for detecting lanes, and when there are a plurality of candidate lanes (L1, L2, L3), the accuracy with which the vehicle (V) can travel each of the candidate lanes (L1, L2, L3) using autonomous travel control is calculated, and an exit lane for the vehicle (V) to travel when exiting the intersection (B1) is selected from among the candidate lanes (L1, L2, L3) on the basis of the accuracies.

Description

Trajectory generation method and trajectory generation device

The present invention relates to a trajectory generation method and a trajectory generation device.

When a vehicle passes through an intersection and there are more lanes ahead of the intersection in the direction of travel of the vehicle than before the intersection, a vehicle control device is known that selects the approach lane beyond the intersection depending on the position of the lane the vehicle is traveling in (Patent Document 1).

JP 2016-224802 A

The above-mentioned conventional technology has the problem that if the number of lanes beyond an intersection cannot be accurately recognized, the vehicle cannot properly enter the lanes beyond the intersection, and cannot continue autonomously driving along the lanes.

The problem that this invention aims to solve is to provide a trajectory generation method and device that can continue autonomous driving along a traffic lane after exiting an intersection.

The present invention solves the above problem by calculating the probability that the vehicle can travel in the candidate lanes through autonomous driving control when multiple candidate lanes are detected as candidates for the lane along which the vehicle will travel when exiting the intersection when a vehicle enters an intersection, and then selecting an exit lane along which the vehicle will travel when exiting the intersection from among the candidate lanes based on the calculated probability.

According to the present invention, the vehicle can continue autonomously driving along the lane after exiting an intersection.

1 is a block diagram showing an example of an embodiment of a driving assistance device including a trajectory generation device according to the present invention. 2 is a plan view showing an example of a driving scene in which driving assistance is performed by the driving assistance device of FIG. 1 . 10 is a flowchart showing an example of a processing procedure of accuracy calculation by an accuracy calculation unit in FIG. 1 . FIG. 2 is a plan view showing an example of a travel locus generated by the locus generating device of FIG. 1 . 1. FIG. 4 is a plan view showing another example of a travel locus generated by the locus generating device of FIG. 2 is a flowchart showing an example of a processing procedure in the driving assistance device of FIG. 1 . 10 is a flowchart showing another example of the processing procedure in the driving assistance device of FIG. 1 (part 1). 10 is a flowchart showing another example of the processing procedure in the driving assistance device of FIG. 1 (part 2).

Below, an embodiment of the present invention will be explained with reference to the drawings. Note that the following explanation is based on the assumption that vehicles are driven on the left side of the road in countries that have laws stipulating left-hand traffic. In countries that have laws stipulating right-hand traffic, the left and right in the following explanation should be interpreted as symmetrical.

[Configuration of driving assistance device]
FIG. 1 is a block diagram showing a driving assistance device 10 according to the present invention. The driving assistance device 10 is a group of devices that execute driving assistance for a vehicle, and for example, drives the vehicle by autonomous driving control. As an example, the driving assistance device 10 generates a driving route to a destination set by a vehicle occupant or the like, and controls an actuator of the vehicle to drive the vehicle along the driving route. Alternatively or in addition to this, the driving assistance device 10 may present information to the driver of the vehicle and assist the driver in driving operations. The driving assistance device 10 may be an in-vehicle system, or a part of it may be provided outside the vehicle.

Autonomous driving control refers to autonomously controlling the driving operations of a vehicle using a vehicle control device, and this driving operation includes all driving operations such as acceleration, deceleration, starting, stopping, and steering. Autonomously controlling driving operations means that the control device controls the driving operations using the vehicle's devices. The control device controls these driving operations within a predetermined range, and driving operations that are not controlled by the control device are manually operated by the driver. When the vehicle is driven manually by the driver without autonomous driving control, the control device does not autonomously control the driving operations, and the vehicle's driving operations are controlled by the driver's operation.

As shown in FIG. 1, the driving assistance device 10 comprises a map database 11, a navigation device 12, an imaging device 13, a distance measuring device 14, a display device 15, and a control device 16. The control device 16 in this embodiment also includes a trajectory generating device 20 as part of it. The devices that make up the driving assistance device 10 are connected via a Controller Area Network (CAN) or other in-vehicle LAN, and can exchange information with each other. Information is exchanged with devices installed outside the vehicle via networks such as the Internet or a LAN (local area network).

The map database 11 is a storage medium that stores map information, and is provided inside or outside the vehicle. The control device 16 acquires map information from the map database 11 as necessary. The map information is used for generating driving routes, and includes information on nodes corresponding to specific points on roads where the vehicle's traveling direction changes (intersections, branching points, etc.), and information on links corresponding to road sections connecting the nodes. Node information includes location information (e.g., latitude and longitude), information on entering and exiting intersections and branching points, and link information includes road width, road curvature radius, road shoulder structures, road traffic regulations (e.g., traffic direction), junctions, branching points, and the like. Link information may include information on link lines along the road that indicate the shape of the road. The map information may also be high-precision map information (HD map) that can grasp the movement trajectory for each lane.

The navigation device 12 is a device that references map information to generate a driving route from the vehicle's current position, detected by a positioning system (not shown), to a set destination. The navigation device 12 uses node and link information in the map information to search for a driving route for the vehicle to reach the destination. The driving route includes at least information on the roads the vehicle will travel on and the vehicle's traveling direction, and is displayed, for example, by nodes and link lines. The control device 16 may display the generated driving route on the display device 15.

The imaging device 13 is a device that captures images of objects around the vehicle, and examples of such devices include a camera equipped with an imaging element such as a CCD, an ultrasonic camera, and an infrared camera. In order to reduce blind spots when recognizing objects, multiple imaging devices 13 are installed in the front grille of the vehicle, under the left and right door mirrors, near the rear bumper, etc.

The distance measuring device 14 is a device that acquires the relative distance and relative speed between the distance measuring device 14 and an object, and examples of such devices include laser radar, millimeter wave radar, and LiDAR (Light Detection and Ranging) units. In order to reduce blind spots when recognizing an object, multiple distance measuring devices 14 are installed at the front, right side, left side, and rear of the vehicle.

The object is an object that exists on the road or its surroundings, and includes lane boundaries, center lines, road markings, medians, guard rails, curbs, road signs, traffic lights, and crosswalks. The object also includes obstacles that may affect the travel of the vehicle, such as automobiles other than the vehicle itself, motorcycles, bicycles, and pedestrians. The control device 16 obtains the detection results of the imaging device 13 and the distance measuring device 14 at a predetermined time interval (for example, every 0.1 to 1 millisecond). The detection results of the imaging device 13 and the distance measuring device 14 may also be integrated or synthesized (sensor fusion) by the control device 16. This makes it possible to supplement missing information about the object.

The ranging device 14 may generate point cloud data in which information on ranging points of objects around the vehicle is arranged two-dimensionally in the left-right and up-down directions of the vehicle. The ranging points of the object are points on the object whose distance to the ranging device 14 is measured. The ranging point information includes the reflectance of electromagnetic waves at the ranging point in addition to the position information of the ranging point. The position information of the ranging point includes information on the coordinates of the ranging point, information on the distance from the ranging device 14 to the ranging point, etc.

The distance measuring device 14 generates point cloud data by scanning electromagnetic waves in the left-right direction of the vehicle. For example, the distance measuring device 14 irradiates electromagnetic waves along the vehicle width direction, detects the reflected electromagnetic waves (reflected waves), and calculates the distance to the ranging point and the direction of the ranging point. The irradiation range of the electromagnetic waves is not particularly limited. Examples of electromagnetic waves include millimeter waves, infrared rays, and lasers.

The display device 15 is a device for providing necessary information to the vehicle occupants, and is a liquid crystal display provided on the instrument panel, a projector such as a head-up display (HUD), etc. The display device 15 may also be equipped with an input device (e.g., a touch panel) that allows the occupant to input instructions to the control device 16. The display device 15 may also be equipped with a speaker as an output device.

The control device 16 is a device for executing driving assistance by controlling and cooperating with the devices that make up the driving assistance device 10. The control device 16 is, for example, a computer, and includes a CPU (Central Processing Unit) which is a processor, a ROM (Read Only Memory) in which programs are stored, and a RAM (Random Access Memory) which functions as an accessible storage device. The CPU is an operating circuit for executing the programs stored in the ROM and realizing the functions of the control device 16.

The control device 16 has a driving assistance function that executes driving assistance for the vehicle. The control device 16 also includes a trajectory generation device 20 as part of the driving assistance function, which has a trajectory generation function that generates a driving trajectory of the vehicle as part of the driving assistance function. The ROM stores a program for implementing the driving assistance function, and the driving assistance function including the trajectory generation function is implemented by the CPU executing the program stored in the ROM.

In FIG. 1, the driving control unit 17, lane detection unit 21, accuracy calculation unit 22, lane selection unit 23, and trajectory generation unit 24 are conveniently extracted and shown as functional blocks that realize the driving assistance function. Of these functional blocks, the lane detection unit 21, accuracy calculation unit 22, lane selection unit 23, and trajectory generation unit 24 are functional blocks that realize the trajectory generation function, and are included in the trajectory generation device 20. The functions of each functional block will be explained below with reference to FIG. 2.

[Functions of the trajectory generation device]
Fig. 2 is a plan view showing an example of a driving scene in which the control device 16 executes autonomous driving control by the driving assistance function. In the driving scene shown in Fig. 2, two lanes roads A1 and A2 extend in the vertical direction of the drawing, and a three lanes road A3 extends in the horizontal direction of the drawing, with an intersection B1 between the roads A1 and A3, and an intersection B2 between the roads A2 and A3. In addition, a crosswalk C is provided on the side of the intersection B1 between the intersections B1 and B2, crossing the road A3.

In the driving scene shown in FIG. 2, the vehicle V is traveling at position P1 on lane La of road A1, and travels to destination D ahead on lane Lb of road A2. In addition, the vehicle V traveling on lane L1 of road A3 can turn left or go straight at intersection B2, the vehicle V traveling on lane L2 can go straight at intersection B2, and the vehicle V traveling on lane L3 can turn right or go straight at intersection B2. In this case, the control device 16, using the function of the driving control unit 17, generates a driving route that enters intersection B1 from position P1, turns right at intersection B1 and enters one of lanes L1 to L3 of road A3, enters intersection B2 from lane L1 and turns left, and heads toward destination D at the end of lane Lb of road A2. Then, the control device 16 autonomously controls the driving operation of the vehicle V so that the vehicle V travels along the driving route.

If the map information stored in the map database 11 is high-precision map information, the lanes can be recognized from the lane information of roads A1 to A3, but if the map information does not include lane information for roads A1 to A3, the lanes of roads A1 to A3 are detected from images acquired from the imaging device 13, and a driving trajectory is generated. This lane detection that does not rely on map information may not be able to detect the lanes accurately, and there is a risk that autonomous driving control may not be able to continue. Therefore, the control device 16 of this embodiment selects the lane in which the vehicle V will travel based on the probability that the detected lane can be traveled by autonomous driving control.

The driving control unit 17 has a function of generating a driving route for the vehicle V and activating the actuator of the vehicle V so that the vehicle V drives along the driving route. The control device 16 uses the function of the driving control unit 17 to determine whether the vehicle V driving along the driving route will enter an intersection, and if it determines that the vehicle V will enter an intersection, outputs an execution instruction to the trajectory generation device 20 to generate a driving trajectory in which the vehicle V enters the exit lane of the intersection.

When vehicle V enters an intersection, lane detection unit 21 has the function of detecting candidate lanes that are candidates for the lanes along which vehicle V will travel when exiting the intersection. Using the function of lane detection unit 21, trajectory generation device 20 obtains the traveling direction of vehicle V when exiting the intersection from the travel path and the current position of vehicle V obtained from a positioning system (not shown), and detects the lane along which vehicle V will travel after exiting the intersection as a candidate lane.

Specifically, if vehicle V goes straight through the intersection, the traveling direction of vehicle V after leaving the intersection is forward, and trajectory generating device 20 detects the lane ahead in the traveling direction (beyond the intersection) as a candidate lane. If vehicle V turns right at the intersection, the traveling direction of vehicle V after leaving the intersection is right, and trajectory generating device 20 detects the lane on the right side of the traveling direction as a candidate lane. If vehicle V turns left at the intersection, the traveling direction of vehicle V after leaving the intersection is left, and trajectory generating device 20 detects the lane on the left side of the traveling direction as a candidate lane. Note that the reason lane candidates are used is because the lane in which vehicle V will travel when leaving the intersection has not been determined at the time of lane detection.

The trajectory generating device 20 detects candidate lanes from the detection results of a detection device that detects lanes. The detection device that detects lanes is, for example, at least one of an imaging device 13 mounted on the vehicle V that captures images of the surroundings of the vehicle V, and a distance measuring device 14 mounted on the vehicle V that generates point cloud data. The trajectory generating device 20 detects candidate lanes from images acquired from the imaging device 13, and may alternatively or in addition detect candidate lanes from point cloud data acquired from the distance measuring device 14.

Specifically, the trajectory generating device 20 performs processes such as edge extraction, semantic segmentation, and pattern matching on the image acquired from the imaging device 13, and extracts from the image portions corresponding to lanes separated by lane boundaries or the like. The trajectory generating device 20 may also acquire position information of ranging points from the point cloud data acquired from the ranging device 14, generate an image on which the ranging points are plotted, and perform processes such as pattern matching on the image to extract portions corresponding to the lanes.

For example, the trajectory generating device 20 detects structures that define lanes, such as curbs, medians, and guardrails, from an image on which the measurement points are plotted, and recognizes lanes. The trajectory generating device 20 may also detect lane boundaries from information on the reflectance of electromagnetic waves, utilizing the difference in reflectance between the road surface and the lane boundary (white line) portions. Note that lane boundaries refer to boundaries marked on the road surface, and are different from structures that define lanes, such as medians.

In the driving scene shown in FIG. 2, a driving route is set in which vehicle V turns right at intersection B1, so the trajectory generating device 20 detects the lane on the right side of vehicle V's traveling direction relative to intersection B1 as a candidate lane. If curb X1, white lines X2 and X3, and center divider X4 are detected from the detection results of imaging device 13 and distance measuring device 14, then trajectory generating device 20 detects lane L1 defined by curb X1 and white line X2, lane L2 defined by white lines X2 and X3, and lane L3 defined by white line X3 and center divider X4 as candidate lanes.

The accuracy calculation unit 22 has a function of calculating the accuracy that the vehicle V can travel along the candidate lane. The accuracy that the vehicle V can travel along the candidate lane is, in particular, the accuracy that the vehicle V can travel along the candidate lane by autonomous driving control, and more specifically, the accuracy that the vehicle V exiting the intersection can enter the candidate lane by autonomous driving control and travel along the candidate lane. In other words, this accuracy is the accuracy that the vehicle V can pass through the intersection and enter the candidate lane by autonomous driving control, and the accuracy that the vehicle V that entered the intersection by autonomous driving control can exit the intersection and enter the candidate lane while continuing the autonomous driving control.

The accuracy of driving through a candidate lane by autonomous driving control is calculated based on the accuracy of the lane actually existing at the position where the candidate lane was detected, the accuracy of the lane boundary line defining the candidate lane being detectable, the accuracy of the structure actually existing at the position where the structure defining the candidate lane was detected, and the accuracy of the travel direction of the candidate lane being aligned with the traveling direction of the vehicle V. For example, the accuracy of a candidate lane where there is no boundary line between the sidewalk and the roadway is calculated to be lower than the accuracy of a candidate lane where there is a boundary line between the sidewalk and the roadway, and the accuracy of a candidate lane where the lane boundary line is interrupted midway is calculated to be lower than the accuracy of a candidate lane where the lane boundary line is not interrupted.

As an example, the trajectory generating device 20 uses the function of the accuracy calculation unit 22 to calculate the accuracy of a candidate lane in which lane boundaries on both sides are detected to be higher than the accuracy of a candidate lane in which at least one lane boundary is not detected. For example, in the driving scene shown in FIG. 2, the accuracy of lane L2 in the case where white lines X2 and X3 can be accurately detected is calculated to be higher than the accuracy of lane L2 in the case where white line X2 has disappeared due to wear and cannot be detected.

The trajectory generating device 20 may calculate the accuracy of a candidate lane that is bounded on at least one side by a structure to be higher than the accuracy of a candidate lane that is bounded on both sides by lane boundary lines. This is because three-dimensional objects such as structures are less likely to be erroneously detected than lane boundary lines such as white lines. For example, in the driving scene shown in Figure 2, the accuracy of lane L3, the right side of which is bounded by a center divider X4, is calculated to be higher than the accuracy of lane L2, the right side of which is bounded by white lines X2, X3.

In addition, if a pedestrian crossing is present near the exit where vehicle V exits the intersection, the trajectory generating device 20 may calculate the accuracy of a candidate lane closer to the edge of the pedestrian crossing in the road width direction to be higher than the accuracy of a candidate lane farther from the edge of the pedestrian crossing. This is because the closer you are to the center of the pedestrian crossing, the more difficult it is to distinguish between the own lane and the oncoming lane. For example, in the driving scene shown in FIG. 2, a pedestrian crossing C is present near the exit E when vehicle V passes through intersection B1 along the driving route. In this case, the accuracy of lane L1 close to the edge on the left side of the crosswalk C in the traveling direction is calculated to be higher than the accuracy of lanes L2 and L3 farther from the edge on the left side of the crosswalk C in the traveling direction (i.e., closer to the center of the crosswalk C).

Furthermore, when there is a preceding vehicle traveling ahead of vehicle V, the trajectory generating device 20 may calculate the accuracy of a candidate lane in which the preceding vehicle has traveled to be higher than the accuracy of a candidate lane in which the preceding vehicle has not traveled. This is because there is a high probability that vehicle V can travel in the lane since there is a track record of the preceding vehicle having traveled in the lane. For example, in the driving scene shown in FIG. 2, when there is a preceding vehicle Vx traveling at position Px of lane L2, the accuracy of lane L2 is calculated to be higher than the accuracy of lanes L1 and L3.

The trajectory generating device 20 calculates, particularly when there are multiple candidate lanes, the probability that the vehicle V can travel through the candidate lane by autonomous driving control for each candidate lane. In contrast, when there is only one candidate lane, the trajectory generating device 20 may or may not calculate the probability. Note that when there are multiple candidate lanes, the trajectory generating device 20 may calculate the probability for only some of the candidate lanes.

FIG. 3 is an example of a flowchart showing information processing executed in the trajectory generating device 20 when the above-mentioned accuracy is calculated using the function of the accuracy calculation unit 22. The processing described below is executed by the processor (CPU) of the control device 16.

First, in step S1, the accuracy of the candidate lane for which the accuracy is calculated is set to "0", and in the following step S2, it is determined whether or not the boundaries on both sides of the candidate lane are defined. If it is determined that the boundaries on both sides of the candidate lane are defined, "8" is added to the accuracy of the candidate lane, and if it is determined that the boundary on at least one side of the candidate lane is not defined, the process proceeds to step S4.

In step S4, it is determined whether at least one side of the candidate lane is defined by a structure. If it is determined that at least one side of the candidate lane is defined by a structure, the process proceeds to step S5, where "6" is added to the accuracy of the candidate lane. If it is determined that both sides of the candidate lane are not defined by a structure, the process proceeds to step S6.

In step S6, it is determined whether the candidate lane is closer to the edge of the crosswalk in the road width direction. If it is determined that the candidate lane is closer to the edge of the crosswalk in the road width direction, the process proceeds to step S7, where "4" is added to the accuracy of the candidate lane. If it is determined that the candidate lane is farther from the edge of the crosswalk in the road width direction, the process proceeds to step S8.

In step S8, it is determined whether or not there is a preceding vehicle Vx traveling in the candidate lane. If it is determined that there is a preceding vehicle Vx traveling in the candidate lane, the process proceeds to step S9, where "10" is added to the accuracy of the candidate lane, and if it is determined that there is no preceding vehicle Vx traveling in the candidate lane, the process proceeds to step S10.

In step S10, it is determined whether the accuracy has been calculated for all candidate lanes. If it is determined that the accuracy has been calculated for all candidate lanes, the process ends, and if it is determined that the accuracy has not been calculated for some candidate lanes, the process proceeds to step S1.

When the accuracy of lanes L1 to L3 shown in FIG. 2 is calculated according to the flowchart shown in FIG. 3, the accuracy of lane L1 is increased by "8" due to the curb X1 and white line X2 (step S3), "6" due to the curb X1 (step S5), and "4" due to being closer to the edge of the crosswalk C in the road width direction than lanes L2 and L3 (step S7), for a total of "18." The accuracy of lane L2 is increased by "8" due to the white lines X2 and X3 (step S3), and "10" due to the presence of the preceding vehicle Vx (step S9), for a total of "18." The accuracy of lane L3 is increased by "8" due to the white line X3 and center divider X4 (step S3), and "6" due to the center divider X4 (step S5), for a total of "14."

The lane selection unit 23 has a function of selecting, from the candidate lanes, an exit lane along which the vehicle V will actually travel when exiting the intersection, based on the calculated degree of certainty. For example, the trajectory generating device 20 uses the function of the lane selection unit 23 to select, as the exit lane, the candidate lane along which the vehicle V will be able to travel by autonomous driving control.

In the driving scene shown in FIG. 2, the accuracy of lanes L1 and L2 is the same, but the trajectory generating device 20 recognizes that lane L2, where the preceding vehicle Vx is present, has a higher accuracy than lane L1, and selects lane L2 as the exit lane. Note that if there is only one candidate lane, the trajectory generating device 20 sets the only candidate lane as the exit lane along which vehicle V will travel when exiting the intersection.

The trajectory generating device 20 may also select an exit lane based on the distance between a first intersection ahead of the vehicle V and a second intersection that the vehicle V will enter after the first intersection. For example, the trajectory generating device 20 calculates the distance between a first intersection ahead of the vehicle V that the vehicle V will enter, and a second intersection that the vehicle V will enter after the first intersection. Then, if the distance between the first intersection and the second intersection is equal to or greater than a predetermined value, the candidate lane with the highest probability is selected as the exit lane.

In contrast, if the distance between the first intersection and the second intersection is less than a predetermined value, a candidate lane that will result in the least number of lane changes by the vehicle V between the first intersection and the second intersection is selected as the exit lane. Alternatively or in addition, if the distance between the first intersection and the second intersection is less than a predetermined value, a candidate lane that will result in the least number of lane changes by the vehicle V between the first intersection and the second intersection may be selected as the exit lane from among the candidate lanes whose probability of being able to travel through the candidate lane by autonomous driving control is equal to or greater than a predetermined threshold. However, when traveling straight through the second intersection, the candidate lane with the highest probability may be selected as the exit lane even if the distance between the first intersection and the second intersection is less than the predetermined value. The predetermined threshold can be set to an appropriate value within a range in which the vehicle V can continue traveling by autonomous driving control.

The predetermined value can be set appropriately based on the travel distance (e.g., 15 to 30 m) required for vehicle V to change lanes. The first intersection and the second intersection are recognized from the position information of the nodes on the travel route and the current position of vehicle V obtained from a positioning system (not shown). The distance between the first intersection and the second intersection is obtained from the road information of the link between the nodes corresponding to the first intersection and the second intersection.

For example, in the driving scene shown in FIG. 2, if the distance between intersection B1, which is the first intersection, and intersection B2, which is the second intersection, is equal to or greater than a predetermined value, the trajectory generating device 20 selects lane L2, which has the highest probability of being able to travel among the candidate lanes by autonomous driving control, as the exit lane. In contrast, if the distance between intersections B1 and B2 is less than the predetermined value, the trajectory generating device 20 selects lane L1 as the exit lane to avoid changing lanes and turn left at intersection B2.

The trajectory generating unit 24 has a function of generating a driving trajectory of the vehicle V entering the selected exit lane. The trajectory generating device 20 uses the function of the trajectory generating unit 24 to generate a driving trajectory of the vehicle V traveling from the current position to the exit lane based on the detection results of objects around the vehicle V, the minimum turning radius of the vehicle V, and the like. The generated driving trajectory is output to the driving control unit 17. In addition to this, the trajectory generating device 20 may also display the generated driving trajectory on the display device 15.

FIG. 4 is a plan view showing the driving trajectory generated by the trajectory generating device 20 when the distance between intersections B1 and B2 in the driving scene shown in FIG. 2 is equal to or greater than a predetermined value. The trajectory generating device 20 generates driving trajectories T1 and T2 that enter lane L2 from position P1, which is the current position. The control device 16, using the function of the driving control unit 17, causes the vehicle V to travel from position P1 on lane La to position P2 along the driving trajectory T1, and causes the vehicle V to travel from position P2 on lane La to position P3 on lane L2 along the driving trajectory T2.

Then, the control device 16 generates a driving trajectory T3 in which the vehicle V changes lanes from lane L2 to lane L1. The control device 16 drives the vehicle V along the driving trajectory T3 from position P2 on lane L2 to position P4 on lane L1. The control device 16 then generates a driving trajectory T4 in which the vehicle V turns left at intersection B2 and enters lane Lb. The control device 16 drives the vehicle V along the driving trajectory T4 from position P4 on lane L1 to position P5 on lane Lb. After the vehicle V enters lane Lb, the control device 16 controls the driving operation of the vehicle V so that it autonomously drives along lane Lb to destination D.

In contrast, FIG. 5 is a plan view showing the driving trajectory generated by the trajectory generating device 20 when the distance between intersections B1 and B2 in the driving scene shown in FIG. 2 is less than a predetermined value. The trajectory generating device 20 generates driving trajectories T1 and T5 that enter lane L1 from position P1, which is the current position. The control device 16, using the function of the driving control unit 17, causes the vehicle V to travel from position P1 on lane La to position P2 along the driving trajectory T1, and causes the vehicle V to travel from position P2 on lane La to position P6 on lane L1 along the driving trajectory T5.

Then, the control device 16 generates a driving trajectory T6 in which the vehicle V drives along the lane L1. The control device 16 drives the vehicle V from position P6 to position P4 on the lane L1 along the driving trajectory T6. The control device 16 then generates a driving trajectory T4 in which the vehicle V turns left at the intersection B2 and enters the lane Lb. The control device 16 drives the vehicle V from position P4 on the lane L1 to position P5 on the lane Lb along the driving trajectory T4. After the vehicle V enters the lane Lb, the control device 16 controls the driving operation of the vehicle V so that it drives autonomously along the lane Lb to the destination D.

[Processing in driving assistance device]
6 and 7A-7B, the procedure for processing information by the control device 16 will be described. The process described below is executed by a processor (CPU) included in the control device 16 at predetermined time intervals (for example, every 0.1 to 1 millisecond).

FIG. 6 is an example of a flowchart showing information processing executed by the driving assistance device 10 of this embodiment.

First, in step S11, the lane detection unit 21 detects candidate lanes, and in the following step S12, the accuracy calculation unit 22 determines whether there are multiple candidate lanes. If it is determined that there are multiple candidate lanes, the process proceeds to step S13, where the accuracy of traveling through the candidate lanes by autonomous driving control is calculated, and in the following step S14, the lane selection unit 23 selects an exit lane from the candidate lanes based on the accuracy. On the other hand, if it is determined that there is only one candidate lane, the process proceeds to step S15, where the candidate lane is set as the exit lane. Then, in step S16, a driving trajectory for entering the selected exit lane is generated.

Next, Figures 7A and 7B are another example of a flowchart showing information processing executed in the driving assistance device 10 of this embodiment.

First, in step S21 of FIG. 7A, the driving control unit 17 generates a driving route from the current position to destination D and drives the vehicle V along the driving route, and then in step S22, it is determined whether the vehicle V will enter an intersection. If it is determined that the vehicle V will not enter an intersection, the process proceeds to step S21. On the other hand, if it is determined that the vehicle V will enter an intersection, the process proceeds to step S23.

In step S23, the lane detection unit 21 detects candidate lanes, and in the following step S24, the probability calculation unit 22 determines whether there are multiple candidate lanes. If it is determined that there are multiple candidate lanes, the process proceeds to step S25, where the probability that the candidate lane can be traveled through by autonomous driving control is calculated for each candidate lane, and the process proceeds to step S27 in FIG. 7B. On the other hand, if it is determined that there is only one candidate lane, the process proceeds to step S26, where the candidate lane is set as an exit lane, and the process proceeds to step S30 in FIG. 7B.

In step S27 of FIG. 7B, the lane selection unit 23 calculates the distance between the first intersection and the second intersection, and in the following step S28, it is determined whether the distance between the intersections is less than a predetermined value. If it is determined that the distance between the intersections is equal to or greater than the predetermined value, the process proceeds to step S29, where the candidate lane with the highest degree of certainty is selected as the exit lane.

In contrast, if it is determined that the distance between the intersections is less than the predetermined value, the process proceeds to step S30, where it is determined whether or not the vehicle V will go straight through the second intersection. If it is determined that the vehicle V will not go straight through the second intersection, the process proceeds to step S29. In contrast, if it is determined that the vehicle V will go straight through the second intersection, the process proceeds to step S31, where the candidate lane that minimizes the number of lane changes between the first intersection and the second intersection is selected as the exit lane. Then, in step S32, the function of the trajectory generation unit 24 is used to generate a driving trajectory for entering the selected exit lane.

Note that step S15 in FIG. 6 is not essential to the present invention and may be omitted if necessary. Steps S21, S22, and S26 in FIG. 7A and steps S27, S28, S30, and S31 in FIG. 7B are not essential to the present invention and may be omitted if necessary.

[Embodiments of the invention]
According to this embodiment, in a trajectory generation method executed by a trajectory generation device, the trajectory generation device 20 detects candidate lanes that are candidates for lanes along which the vehicle V will travel when exiting the intersection from the detection results of a detection device that detects lanes when the vehicle V enters an intersection, calculates a probability that the vehicle V can travel on the candidate lanes by autonomous driving control when there are multiple candidate lanes, selects an exit lane along which the vehicle V will travel when exiting the intersection from the candidate lanes based on the probability, and generates a travel trajectory of the vehicle V entering the exit lane. This allows the vehicle V to continue autonomous driving along the lanes after exiting the intersection.

In the trajectory generation method of this embodiment, the trajectory generation device 20 may calculate the accuracy of the candidate lane in which lane boundaries on both sides are detected to be higher than the accuracy of the candidate lane in which the lane boundary on at least one side is not detected. This allows the vehicle V to enter a lane in which it is easier to continue autonomous driving.

In the trajectory generation method of this embodiment, the trajectory generation device 20 may calculate the accuracy of the candidate lane that is separated by a structure on at least one side to be higher than the accuracy of the candidate lane that is separated by lane boundary lines on both sides. This allows the vehicle V to enter a lane where it is easier to continue autonomous driving.

In the trajectory generation method of this embodiment, if a pedestrian crossing is present near the exit where the vehicle V exits the intersection, the trajectory generation device 20 may calculate the accuracy of the candidate lane closer to the end of the pedestrian crossing in the road width direction to be higher than the accuracy of the candidate lane farther from the end of the pedestrian crossing. This allows the vehicle V to enter a lane where it is easier to continue autonomous driving.

In the trajectory generation method of this embodiment, when a preceding vehicle Vx is present traveling ahead of the vehicle V, the trajectory generation device 20 may calculate the accuracy of the candidate lane in which the preceding vehicle Vx has traveled to be higher than the accuracy of the candidate lane in which the preceding vehicle Vx has not traveled. This allows the vehicle V to enter a lane in which it is easier to continue autonomous driving.

In the trajectory generation method of this embodiment, the trajectory generation device 20 calculates the distance between a first intersection B1 in front of the vehicle V and a second intersection B2 that the vehicle V will enter after the first intersection B1, and if the distance is equal to or greater than a predetermined value, the candidate lane with the highest degree of certainty may be selected as the exit lane. This allows the vehicle V to enter a lane in which it is easier to continue autonomous driving.

In the trajectory generation method of this embodiment, the trajectory generation device 20 calculates the distance between a first intersection B1 in front of the vehicle V and a second intersection B2 that the vehicle V will enter after the first intersection B1, and if the distance is less than a predetermined value, the candidate lane that will result in the fewest number of lane changes by the vehicle V between the first intersection B1 and the second intersection B2 may be selected as the exit lane. This makes it possible to prevent the occurrence of a situation in which lane changes are not completed between intersections and travel along the travel route becomes impossible.

In the trajectory generation method of this embodiment, the trajectory generation device 20 calculates the distance between a first intersection B1 in front of the vehicle V and a second intersection B2 that the vehicle V will enter after the first intersection B1, and if the distance is less than a predetermined value, the candidate lane that minimizes the number of lane changes of the vehicle V between the first intersection B1 and the second intersection B2 may be selected as the exit lane from among the candidate lanes whose accuracy is equal to or greater than a predetermined threshold. This makes it possible to prevent the occurrence of a situation in which lane changes are not completed between intersections and travel along the travel route becomes impossible.

In addition, according to this embodiment, a trajectory generating device 20 is provided that includes a lane detection unit 21 that detects candidate lanes that are candidates for lanes along which the vehicle V will travel when it exits the intersection from the detection results of a detection device that detects lanes when the vehicle V enters the intersection, a probability calculation unit 22 that calculates the probability that the vehicle V can travel along the candidate lanes by autonomous driving control when there are multiple candidate lanes detected by the lane detection unit 21, a lane selection unit 23 that selects an exit lane along which the vehicle V will travel when it exits the intersection from the candidate lanes based on the probability calculated by the probability calculation unit 22, and a trajectory generation unit 24 that generates a driving trajectory of the vehicle V entering the exit lane selected by the lane selection unit 23. This allows the vehicle V to continue autonomous driving along the lanes after exiting the intersection.

10...driving assistance device 11...map database 12...navigation device 13...imaging device 14...distance measuring device 15...display device 16...control device 17...driving control unit 20...trajectory generation device 21...lane detection unit 22...accuracy calculation unit 23...lane selection unit 24...trajectory generation unit A1, A2, A3...road B1, B2...intersection C...crosswalk D...destination E...exit L1, L2, L3, La, Lb...lanes P1, P2, P3, P4, P5, P6, Px...positions T1, T2, T3, T4, T5, T6...driving trajectory V...vehicle Vx...preceding vehicle X1...curb X2, X3...white line X4...center divider

Claims (9)

A trajectory generation method executed by a trajectory generation device,
The trajectory generating device is
When a vehicle enters an intersection, a candidate lane is detected from a detection result of a detection device that detects lanes, the candidate lane being a candidate for a lane in which the vehicle will travel when exiting the intersection;
When there are a plurality of the candidate lanes, a probability that the vehicle can travel in the candidate lanes by autonomous travel control is calculated;
selecting an exit lane in which the vehicle will travel when exiting the intersection from the candidate lanes based on the probability;
A trajectory generation method for generating a driving trajectory of the vehicle entering the exit lane. The trajectory generation method according to claim 1, wherein the trajectory generation device calculates the accuracy of the candidate lane in which lane boundaries on both sides are detected to be higher than the accuracy of the candidate lane in which the lane boundary on at least one side is not detected. The trajectory generation method according to claim 1 or 2, wherein the trajectory generation device calculates the accuracy of the candidate lane that is separated by a structure on at least one side to be higher than the accuracy of the candidate lane that is separated by lane boundary lines on both sides. The trajectory generation method according to any one of claims 1 to 3, wherein, if a pedestrian crossing is present near the exit where the vehicle exits the intersection, the trajectory generation device calculates the accuracy of the candidate lane close to the end of the pedestrian crossing in the road width direction to be higher than the accuracy of the candidate lane far from the end of the pedestrian crossing. The trajectory generation method according to any one of claims 1 to 4, wherein, when a preceding vehicle is present ahead of the vehicle, the trajectory generation device calculates the accuracy of the candidate lane in which the preceding vehicle is traveling to be higher than the accuracy of the candidate lane in which the preceding vehicle is not traveling. The trajectory generating device is
Calculating a distance between a first intersection ahead of the vehicle and a second intersection into which the vehicle will enter after the first intersection;
The trajectory generating method according to any one of claims 1 to 5, wherein, if the distance is equal to or greater than a predetermined value, the candidate lane having the highest degree of certainty is selected as the exit lane. The trajectory generating device is
Calculating a distance between a first intersection ahead of the vehicle and a second intersection into which the vehicle will enter after the first intersection;
A trajectory generation method according to any one of claims 1 to 6, wherein if the distance is less than a predetermined value, the candidate lane that results in the least number of lane changes by the vehicle between the first intersection and the second intersection is selected as the exit lane. The trajectory generating device is
Calculating a distance between a first intersection ahead of the vehicle and a second intersection into which the vehicle will enter after the first intersection;
A trajectory generation method as described in any one of claims 1 to 7, wherein if the distance is less than a predetermined value, the candidate lane that minimizes the number of lane changes of the vehicle between the first intersection and the second intersection is selected as the exit lane from among the candidate lanes whose accuracy is equal to or greater than a predetermined threshold. a lane detection unit that detects candidate lanes, which are candidates for lanes along which a vehicle will travel when exiting an intersection, based on a detection result of a detection device that detects lanes when the vehicle enters an intersection;
a probability calculation unit that calculates a probability that the vehicle can travel in the candidate lane by autonomous travel control when there are a plurality of the candidate lanes detected by the lane detection unit;
a lane selection unit that selects, from the candidate lanes, an exit lane in which the vehicle will travel when exiting the intersection, based on the certainty calculated by the certainty calculation unit;
a trajectory generation unit that generates a travel trajectory of the vehicle entering the exit lane selected by the lane selection unit.

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