Vehicle control device

Abstract

To provide a vehicle control device that takes an account of a progress degree of changing lane, sets a target track while taking an account of an obstacle present in a change destination lane, and can improve safety and comfort of an occupant.SOLUTION: A vehicle control device sets an entry prohibition area on the basis of at least one of movement prediction of an obstacle and road information; calculating a target track under such a restriction as not entering the entry prohibition area; and, when calculating a target track for changing lane from a change source lane to a change destination lane, changing the entry prohibition area on the basis of a position in a transverse direction of own vehicle relative to the change source lane or change destination lane.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present application relates to a vehicle control device. [Background technology]

[0002] In recent years, various technologies for controlling vehicle driving have been proposed. One of these is a device that controls lane changes, which move a vehicle from the lane it is currently traveling in to the adjacent lane.

[0003] For example, the vehicle control device in Patent Document 1 sets a no-entry area around two obstacles in the destination lane, sets a target space between them, determines a target route based on a predicted movement of the target space, and performs a lane change. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-126990 Summary of the Invention [Problem to be solved by the invention]

[0005] If a no-entry zone is set around an obstacle as in Patent Document 1, for example, if the obstacle ahead slows down when the vehicle has moved to the destination lane to a certain extent, even though it would be more natural for the vehicle to slow down as well to avoid a collision, the vehicle may unnaturally go around to the side of the obstacle ahead, that is, return to the original lane to avoid the collision, thereby reducing safety and comfort.

[0006] Therefore, the present application aims to provide a vehicle control device that can improve the safety and comfort of occupants by taking into account the progress of the lane change and setting a target trajectory that takes into account obstacles present in the destination lane. [Means for solving the problem]

[0007] The vehicle control device according to the present application comprises: Obstacle movement prediction and road information To both a no-entry area setting unit that sets a no-entry area for the host vehicle based on the information; a target trajectory generation unit that calculates a target trajectory for the host vehicle over the future under the constraint of not entering the no-entry area; a vehicle control unit that controls the traveling of the host vehicle based on the target trajectory; Equipped with The no-entry area setting unit changes the no-entry area based on the lateral position of the vehicle relative to the source lane or the destination lane when the target trajectory generation unit calculates the target trajectory for changing lanes from the source lane to the destination lane. [Effects of the Invention]

[0008] According to the vehicle control device of the present application, when calculating a target trajectory for a lane change, the no-entry area is changed based on the lateral position of the host vehicle relative to the source lane or the destination lane. Therefore, the no-entry area set based on the predicted movement of an obstacle in the destination lane can be changed depending on the progress of the lane change. Therefore, for example, when the lane change is well underway, a target trajectory that returns to the source lane can be calculated to avoid an obstacle in the destination lane. Alternatively, when the lane change is not yet underway, a target trajectory that returns to the source lane can be calculated to avoid an obstacle in the destination lane. This prevents unnatural lane changes and improves the safety and comfort of occupants. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram showing an example of a vehicle control device according to a first embodiment. [Figure 2] 1 is a diagram showing an example of a host vehicle according to the first embodiment. FIG. [Figure 3] FIG. 2 is a diagram showing an example of a coordinate system according to the first embodiment. [Figure 4] FIG. 2 is a diagram showing an example of a route coordinate system according to the first embodiment. [Figure 5] 4 is a flowchart showing an example of an automatic driving procedure of the host vehicle according to the first embodiment. [Figure 6] 10 is a flowchart showing an example of a procedure for setting a no-entry area according to the first embodiment. [Figure 7] 3 is a schematic diagram showing an example of a surrounding no-entry area according to the first embodiment. FIG. [Figure 8] 2 is a schematic diagram showing an example of an inter-vehicle no-entry area according to the first embodiment. FIG. [Figure 9] 2 is a schematic diagram showing an example of an inter-vehicle no-entry area according to the first embodiment. FIG. [Figure 10] FIG. 4 is another schematic diagram showing an example of an inter-vehicle no-entry area according to the first embodiment. [Figure 11] 3 is a schematic diagram showing an example of a no-entry area during a lane change according to the first embodiment. FIG. [Figure 12] 10 is a flowchart showing an example of a procedure for setting a no-entry area according to the second embodiment. [Figure 13] FIG. 10 is a schematic diagram showing an example of a surrounding no-entry area according to the second embodiment. [Figure 14] FIG. 10 is a schematic diagram showing an example of overlapping of a lane no-entry area and a surrounding no-entry area according to the second embodiment. [Figure 15] FIG. 10 is another schematic diagram showing an example of overlapping of a lane no-entry area and a surrounding no-entry area according to the second embodiment. [Figure 16] 11 is a flowchart showing an example of a procedure for setting a no-entry area according to the third embodiment. [Figure 17] 1 is a schematic hardware configuration diagram of a vehicle control unit and a vehicle control device according to a first embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Embodiment 1 <Block diagram> 1 is a block diagram showing an example of a vehicle control device 201 according to a first embodiment of the present invention. The vehicle control device 201 according to the first embodiment is included in a vehicle control unit 200 of a vehicle. In the following description, the vehicle in which the vehicle control device 201 is installed may also be referred to as the "host vehicle."

[0011] 1 includes a no-entry area setting unit 240, a target trajectory generating unit 250, and a vehicle control unit 260. The vehicle control unit is a unit that controls the vehicle, and is mounted in, for example, an advanced driver assistance system electronic control unit (ADAS-ECU).

[0012] The no-entry area setting unit 240 sets a no-entry area for the host vehicle based on at least one of the obstacle movement prediction and road information. When an obstacle is present around the host vehicle and obstacle movement prediction information, which is obstacle movement prediction information including the obstacle's position, is obtained from the obstacle movement prediction unit 220, the no-entry area setting unit 240 sets a no-entry area around the predicted obstacle. Furthermore, the no-entry area setting unit 240 sets a no-entry area for the host vehicle based on road information. As an example, a no-entry area is set outside a demarcation line based on a demarcation line. Note that when either the obstacle movement prediction or the road information cannot be obtained, the no-entry area setting unit 240 sets a no-entry area for the host vehicle based on the obtained obstacle movement prediction or road information.

[0013] The target trajectory generation unit 250 generates a target trajectory along which the vehicle should travel, based on road information from the road information acquisition unit 120, which is information including the boundaries between the road on which the vehicle is traveling and the adjacent roads, decision-making information from the decision-making unit 230, which is information including the target action to be taken by the vehicle and the target lane along which the vehicle should travel, and the no-entry area from the no-entry area setting unit 240.

[0014] The vehicle control unit 260 calculates target values ​​for steering control and vehicle speed control so that the vehicle follows the target trajectory. The target values ​​include a target steering angle and a target acceleration.

[0015] The vehicle control unit 200 is connected to an obstacle information acquisition unit 110, a road information acquisition unit 120, and a vehicle information acquisition unit 130 as external input devices.

[0016] The obstacle information acquisition unit 110 is an acquisition unit that acquires obstacle information, which is information including the position of an obstacle, and may be, for example, a forward camera, LiDAR (Light Detection and Ranging), radar, sonar, a vehicle-to-vehicle communication device, or a road-to-vehicle communication device.

[0017] The road information acquisition unit 120 is an acquisition unit that acquires road information including the boundary of the road on which the vehicle is traveling, and may be, for example, a front camera, a combination of LiDAR and a map data processing device, or a combination of a Global Navigation Satellite System (GNSS) and a map data processing device. The boundary may be, for example, a dividing line, a curb, a gutter, or a guardrail.

[0018] The vehicle information acquisition unit 130 is an acquisition unit that acquires vehicle information of the host vehicle. The vehicle information acquisition unit 130 may be, for example, a steering angle sensor, a steering torque sensor, a yaw rate sensor, a speed sensor, and an acceleration sensor. The vehicle information refers to the current vehicle state quantity of the host vehicle, and is acquired using, for example, at least one of these sensors.

[0019] The vehicle control unit 200 includes, as internal components, a vehicle state quantity estimating section 210 connected to the vehicle control device 201, an obstacle movement predicting section 220, and a decision making section 230.

[0020] The vehicle state quantity estimation unit 210 estimates, based on the vehicle information, the current vehicle state quantity of the host vehicle that is not acquired by the vehicle information acquisition unit 130. Note that the vehicle state quantity estimation unit 210 may estimate a part of the vehicle information acquired by the vehicle information acquisition unit 130.

[0021] The obstacle movement prediction unit 220 predicts the movement of an obstacle based on obstacle information, which is information including the position of the obstacle from the obstacle information acquisition unit 110, and road information, which is information including the boundary between the road on which the vehicle is traveling and the adjacent roads from the road information acquisition unit 120.

[0022] The decision-making unit 230 determines a target action to be taken by the host vehicle and a target lane in which the host vehicle should travel, based on obstacle information, road information, and vehicle information. The target action is, for example, keeping in a lane or changing lanes. The target lane is, for example, the host vehicle's lane, the left lane, or the right lane.

[0023] The vehicle control unit 200 is connected to an actuator control unit 310 as an external output device. The actuator control unit 310 is a control unit that controls the actuator based on a target value from the vehicle control device 201, and may be, for example, an EPS-ECU (Electric Power Steering - Electric Control Unit), a power train ECU, a brake ECU, or an electric vehicle ECU. In this embodiment, the vehicle control unit performs steering control and vehicle speed control, and the actuator control unit 310 is composed of an EPS-ECU, a power train ECU, and a brake ECU, but is not limited to this.

[0024] <System configuration diagram> 2 is a system configuration diagram showing a schematic configuration of the vehicle control device of Embodiment 1. The host vehicle 1 includes a steering wheel 2, a steering shaft 3, a steering unit 4, an EPS motor 5, a powertrain unit 6, a brake unit 7, a forward camera 111, a radar sensor 112, a GNSS 121, a navigation device 122, a steering angle sensor 131, a steering torque sensor 132, a yaw rate sensor 133, a speed sensor 134, an acceleration sensor 135, a vehicle control unit 200, an EPS controller 311, a powertrain controller 312, and a brake controller 313. The EPS controller 311, the powertrain controller 312, and the brake controller 313 correspond to the actuator control unit 310 described above.

[0025] The steering wheel 2, which is installed so that the driver can operate the vehicle 1, is connected to a steering shaft 3. A steering unit 4 is connected to the steering shaft 3. The steering unit 4 rotatably supports the front wheels as steered wheels, and is supported on the vehicle frame so that the wheels can be steered. Therefore, the torque generated by the driver's operation of the steering wheel 2 rotates the steering shaft 3, and the steering unit 4 steers the front wheels left and right. This allows the driver to control the amount of lateral movement of the vehicle when it moves forward and backward. The steering shaft 3 can also be rotated by an EPS motor 5, and by controlling the current flowing through the EPS motor 5 with an EPS controller 311, the front wheels can be steered freely independent of the driver's operation of the steering wheel 2.

[0026] For example, as shown in FIG. 17, a vehicle control unit 200 includes a processor 90 such as a CPU (Central Processing Unit), a storage device 91, an input / output device 92 for inputting and outputting external signals to the processor 90, and the like.

[0027] The arithmetic processing device 90 may be an ASIC (Application Specific Integrated Circuit), an IC (Integrated Circuit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), a GPU (Graphics Processing Unit), an AI (Artificial Intelligence) chip, various logic circuits, various signal processing circuits, etc. Furthermore, the arithmetic processing device 90 may be a plurality of the same or different types, and each process may be shared and executed. The storage device 91 may be any of various storage devices, such as a RAM (Random Access Memory), a ROM (Read Only Memory), a flash memory, an EEPROM (Electrically Erasable Programmable Read Only Memory), a hard disk, a DVD (Digital Versatile Disc) device, etc.

[0028] The input / output device 92 is equipped with a communication device, an A / D converter, an input / output port, a drive circuit, etc. The input / output device 92 is connected to a forward camera 111, a radar sensor 112, a GNSS 121, a navigation device 122, a steering angle sensor 131 that detects a steering angle, a steering torque sensor 132 that detects a steering torque, a yaw rate sensor 133 that detects a yaw rate, a speed sensor 134 that detects the speed of the host vehicle, an acceleration sensor 135 that detects the acceleration of the host vehicle, an EPS controller 311, a powertrain controller 312, and a brake controller 313.

[0029] The vehicle control unit 200 processes information input from the connected sensors according to a program stored in ROM, and transmits a target steering angle to the EPS controller 311 and a target acceleration to the powertrain controller 312 and the brake controller 313.

[0030] The front camera 111 is installed in a position where it can detect the lane markings ahead of the vehicle as an image, and detects the environment ahead of the vehicle, such as lane information and the location of obstacles, based on the image information. Note that, although the present embodiment has exemplified only a camera that detects the environment ahead, cameras that detect the environment behind or to the sides may also be installed.

[0031] The radar sensor 112 emits radar and detects the reflected waves, thereby outputting the relative distance and relative speed between the host vehicle 1 and an obstacle. This radar sensor can be a well-known type such as a millimeter wave radar, LiDAR, laser range finder, or ultrasonic radar.

[0032] The GNSS sensor 121 receives radio waves from positioning satellites with an antenna, performs positioning calculations, and outputs the absolute position and absolute direction of the vehicle.

[0033] The navigation device 122 has the function of calculating the optimal driving route for the destination set by the driver and records road information on the driving route. The road information is map node data that represents the road alignment, and each map node data incorporates the absolute position (latitude, longitude, altitude) of each node, lane width, cant angle, inclination angle information, etc.

[0034] The EPS controller 311 controls the EPS motor 5 based on the target steering angle transmitted from the vehicle control unit 200 .

[0035] Powertrain controller 312 controls powertrain unit 6 so as to achieve the target acceleration transmitted from vehicle control unit 200. Note that, although the present embodiment has been described with reference to a vehicle using only an engine as a driving force source, the present invention may also be applied to a vehicle using only an electric motor as a driving force source, or a vehicle using both an engine and an electric motor as driving force sources.

[0036] The brake controller 313 controls the brake unit 7 so as to achieve the target acceleration transmitted from the vehicle control unit 200 .

[0037] <Coordinate system> Fig. 3 is a diagram schematically showing a coordinate system used in the first embodiment. In Fig. 3, X and Y represent an inertial coordinate system, and Xg, Yg, and θ represent the position of the center of gravity of the host vehicle and the vehicle body direction in the inertial coordinate system. x and y represent the host vehicle coordinate system, with the center of gravity of the host vehicle as the origin, the x axis pointing forward of the host vehicle, and the y axis pointing leftward.

[0038] In this embodiment, the vehicle's center of gravity positions Xg, Yg and vehicle body orientation θ are initialized to 0 for each execution cycle. That is, the inertial coordinate system and the host vehicle coordinate system are made to coincide for each execution cycle.

[0039] In addition, in this embodiment, a route coordinate system is also used, which is expressed for a certain route χ by the tangent direction s and normal direction w of the route χ. Fig. 4 is a diagram schematically showing the route coordinate system used in embodiment 1. The sequence of points in Fig. 4 is a sequence of points indicating the route χ, which in this case is the center of the lane. However, the route is not limited to the center of the lane as long as it is a sequence of positional points. In Fig. 4, s and w are in the route coordinate system, and sg, wg, and φ are the center of gravity position and vehicle orientation of the host vehicle in the route coordinate system.

[0040] <Optimization problem settings> In this embodiment, the target trajectory generating unit 250 predicts a vehicle state quantity x from the current time 0 for a prediction period Th in the future at a prediction interval Ts using a vehicle model f that mathematically represents the vehicle motion, and solves an optimization problem to find series data of a control input u that minimizes an evaluation function J that expresses a desired behavior of the host vehicle under constraint g. Then, based on the optimized control input u and the vehicle model f found from the optimization problem, the unit predicts series data of the optimized vehicle state quantity x from the current time 0 for a prediction period Th in the future at a prediction interval Ts. Then, based on the series data of the optimized control input u and the series data of the vehicle state quantity x, the unit generates a trajectory ξ, which is series data including the position of the host vehicle. In the following description, the period from the current time to the prediction period Th may be abbreviated as a horizon.

[0041] <Formulation of optimization problem> As described above, in this embodiment, a constrained optimization problem is solved at regular intervals. The optimization problem is formulated as follows:

number

[0042] where J is the evaluation function, x is the vehicle state quantity, u is the control input, f is a vector-valued function related to the dynamic vehicle model, and x0 is the initial value, i.e., the current vehicle state quantity. g is a vector-valued function related to the constraint, and optimization is performed under the constraint g(x, u)≦0. Note that in this embodiment, the above optimization problem is treated as a minimization problem, but it can also be treated as a maximization problem by inverting the sign of the evaluation function.

[0043] In this embodiment, the following equation is used for the evaluation function J.

number

[0044] Here, x(k) is the vehicle state quantity at prediction point k (k=0, , N), and u(k) is the control input at prediction point k (k=0, , N-1). h is a vector-valued function related to the evaluation items, hN is a vector-valued function related to the evaluation items at the end (prediction point N), and r(k) is the reference value at prediction point k (k=0, , N). W and WN are weighting matrices, which are diagonal matrices with weights for each evaluation item in the diagonal elements and can be changed as parameters as needed.

[0045] <Vehicle model> In this embodiment, the vehicle state quantity x and the control input u used in the control quantity calculation unit are set as follows:

number

[0046] Here, β is the sideslip angle, γ is the yaw rate, ax is the longitudinal acceleration, δ is the steering angle, axt is the target longitudinal acceleration, and δt is the target steering angle. jt is the target longitudinal jerk, and ωt is the target steering angular velocity. Note that as long as the vehicle state quantity x includes a variable related to position, the vehicle state quantity x and the control input u may be set in any way. Furthermore, the position variable is not limited to the Cartesian coordinate system, and may be defined, for example, in a path coordinate system.

[0047] The vehicle model f uses the two-wheel model shown below.

number

[0048] Here, M is the vehicle mass, I is the vehicle's yaw moment of inertia. lf and lr are the distances from the front and rear wheel axles to the vehicle's center of gravity. Tax and Tδ are time constants when the tracking ability of the longitudinal acceleration and steering angle to the target values ​​is expressed as a first-order lag system. Yf and Yr are the cornering forces of the front and rear wheels, and are expressed by the following two equations using the cornering stiffnesses Cf and Cr of the front and rear wheels.

number

[0049] It should be noted that the vehicle model f may be a vehicle model other than a two-wheel model.

[0050] <Vehicle control device procedure> FIG. 5 is a flowchart showing an example of a procedure for autonomous driving of the host vehicle according to the first embodiment.

[0051] 5, obstacle information is acquired by the obstacle information acquisition unit 110. The obstacle information is information including the position of the obstacle. In this embodiment, if an obstacle is located to the left front of the host vehicle, the positions of the right front end PFR, right rear end PRR, and left rear end PRL of the obstacle in the host vehicle coordinate system are acquired. If an obstacle is located to the right front of the host vehicle, the positions of the left front end PFL, left rear end PRL, and right rear end PRR of the obstacle in the host vehicle coordinate system are acquired. Furthermore, the obstacle information acquisition unit estimates the position of the left front end PFL or right front end PFR of the obstacle, the positions Xo, Yo of the center PC, the vehicle body orientation θo, the speed Vo, the length lo, and the width wo based on the position information.

[0052] Next, in S120 of Fig. 5, road information is acquired by road information acquisition unit 120. The road information is information including the boundaries of the road on which the vehicle is traveling and the adjacent roads (hereinafter referred to as the current lane, left lane, and right lane), and in this embodiment, the coefficients obtained when the left and right lane markings of the current lane, left lane, and right lane are expressed as a third-order polynomial are acquired. That is, for the left lane marking (which is also the right lane marking) of the current lane, the values ​​of cel0 to cel3 in the following equation are acquired.

number

[0053] For the right dividing line of the own lane (which is also the left dividing line of the right lane), the values ​​of cer0 to cer3 in the following equations are obtained.

number

[0054] For the left lane marking on the left, the values ​​of cll0 to cll3 in the following equations are obtained.

number

[0055] For the right lane marking on the right side, the following values ​​of crr0 to crr3 are obtained.

number

[0056] In this case, the center of the own lane, the center of the left lane, and the center of the right lane are expressed by equations (205), (206), and (207), respectively.

number

[0057] Here, the coefficients are expressed by equations (208), (209), and (210).

number

[0058] Note that the information on the lane markings is not limited to a cubic polynomial, and may be expressed by any function. In this embodiment, the road on which the vehicle is traveling is defined as the road on which the center of gravity of the vehicle is located. However, the definition of the road on which the vehicle is traveling is not limited to this definition.

[0059] 5, vehicle information is acquired by the vehicle information acquisition unit 130. The vehicle information is information such as the steering angle, yaw rate, speed, and acceleration of the host vehicle, and in this embodiment, the steering angle δ, yaw rate γ, speed V, and longitudinal acceleration ax are acquired.

[0060] 5, the vehicle state quantity x is estimated by the vehicle state quantity estimating unit 210. The vehicle state quantity is estimated using known techniques such as a low-pass filter, an observer, a Kalman filter, or a particle filter.

[0061] Next, in S220 of FIG. 5, the obstacle movement prediction unit 220 predicts the movement of the obstacle. In the movement prediction, the center position Xo(k), Yo(k), vehicle body orientation θo(k), and speed Vo(k) of the obstacle at each prediction point k (k=0, , N) are predicted. In this embodiment, it is predicted that the obstacle will move at a constant speed along the lane. If there are multiple obstacles, the above prediction is made for each obstacle. Any other prediction may be made, for example, a driver model may be used.

[0062] Next, in S230 of FIG. 5, decision-making is performed by the decision-making unit 230. The decision-making determines the target action to be taken by the host vehicle and the target lane in which the host vehicle should travel based on obstacle information, road information, and vehicle information. In this embodiment, options for the target action include lane keeping and lane change. In addition, options such as stopping and emergency stopping may also be included.

[0063] For decision-making, known techniques such as finite state machines, ontology, decision trees, reinforcement learning, and Markov decision processes are used. In this embodiment, a finite state machine is used for decision-making, and when autonomous driving starts, the target behavior is to stay in lane, and the need for a lane change is determined based on the destination and the current lane the vehicle is traveling in, and the target behavior is to change the lane. Alternatively, the need for overtaking of the vehicle may be determined based on movement prediction information, and the target behavior may be to change the lane if overtaking is necessary. Note that when the target behavior is to change lanes, it is also determined whether to change lanes to the right or left. This determination is made, for example, based on the position of the overtaking lane, etc.

[0064] For example, if the target action is to maintain the lane, the target lane is the own lane. If the target action is to change lanes to the right, the target lane is the right lane. However, the moment the own vehicle crosses a dividing line to move into the right lane during a lane change, the target lane becomes the right lane as seen from the original lane, i.e., the own lane after crossing the dividing line. The same applies to a lane change to the left.

[0065] 5, the no-entry area setting unit 240 sets the no-entry area S. In this embodiment, when the target trajectory generation unit 250 calculates a target trajectory for changing lanes from the source lane to the destination lane, the no-entry area setting unit 240 changes the no-entry area based on the lateral position of the host vehicle relative to the source lane or the destination lane.

[0066] This configuration allows the no-entry area, which is set based on the predicted movement of an obstacle in the destination lane, to be changed according to the progress of the lane change. Therefore, for example, when the lane change is well underway, a target trajectory that returns to the original lane can be prevented from being calculated in order to avoid an obstacle in the destination lane. Alternatively, when the lane change is not yet underway, a target trajectory that returns to the original lane can be calculated in order to avoid an obstacle in the destination lane. This prevents unnatural lane changes and improves the safety and comfort of occupants.

[0067] For example, before the host vehicle moves to the destination lane, a no-entry area (hereinafter referred to as a surrounding no-entry area) is set around the obstacle so that the host vehicle can travel to the side of the obstacle and does not approach the obstacle by more than a set distance. After the host vehicle has moved to the destination lane, a no-entry area (hereinafter referred to as an inter-vehicle no-entry area) is set so that the host vehicle maintains a distance of more than a set distance between the obstacle in the destination lane and the host vehicle. This allows the host vehicle to avoid the obstacle in the destination lane after moving to the destination lane by a certain distance without returning to the original lane. Therefore, even if the obstacle in the destination lane accelerates or decelerates, the host vehicle will not unnaturally return to the original lane, improving safety and comfort. Note that the reason for setting a no-entry area that allows the host vehicle to travel to the side of the obstacle before moving to the destination lane is to accommodate cases where the obstacle is almost directly beside the host vehicle when starting to change lanes, or cases where the host vehicle changes lanes while overtaking or being overtaken by the obstacle.

[0068] 5, the target trajectory generating unit 250 generates a target trajectory ξ by solving the optimization problem of equation (101). The target trajectory ξ is series data including the target position of the host vehicle, and in this embodiment, it is series data of the vehicle state quantity x of equation (104).

[0069] Next, in S260 of Fig. 5, vehicle control unit 260 calculates target values ​​for steering control and vehicle speed control so that the host vehicle follows target trajectory ξ. In this embodiment, target steering angle δt, which is a target value related to steering, and target longitudinal acceleration axt, which is a target value related to vehicle speed, are calculated. In this embodiment, since target trajectory ξ includes the optimal value of target steering angle δt(k) and the optimal value of target longitudinal acceleration axt(k) at each prediction point k (k = 0,...,N), the target steering angle δt and target longitudinal acceleration axt are calculated by interpolating the optimal value of target steering angle δt(k) and the optimal value of target longitudinal acceleration axt(k) in the time direction according to the control cycle of each actuator.

[0070] 5, the actuator control unit 310 controls the actuators based on the control amount. In this embodiment, the EPS motor 5 is controlled so that the steering angle δ follows the target steering angle δt, and the powertrain unit 6 and the brake unit 7 are controlled so that the longitudinal acceleration ax follows the target longitudinal acceleration axt.

[0071] <Procedure for setting no-entry areas> 6 is a flowchart showing the procedure for setting a no-entry area, which is performed in S240 of FIG.

[0072] In this embodiment, a case where a no-entry area is set for a forward obstacle will be described as an example, but the same applies to a rearward obstacle.

[0073] First, in S241 of Fig. 6, it is determined whether the target action is a lane change. If it is determined that the target action is a lane change, the process proceeds to S242. If it is determined that the target action is not a lane change, the process proceeds to S245.

[0074] If it is determined in S241 of Fig. 6 that the target action is a lane change, it is determined in S242 of Fig. 6 whether or not a forward obstacle exists in front of the vehicle in the destination lane. If it is determined that a forward obstacle exists in the destination lane, the process of S243 is performed and the forward obstacle in the destination lane is selected as the target obstacle. If it is determined that no forward obstacle exists in the destination lane, the process of S247 is performed.

[0075] If it is determined in S242 of FIG. 6 that an obstacle is present ahead in the destination lane, a determination is made in S243 of FIG. 6 based on the lateral position of the host vehicle. In this embodiment, it is determined whether the lateral position of the host vehicle has yet to cross a reference position set within the lateral range of the source lane and the destination lane toward the destination lane. Furthermore, a dividing line indicating the boundary between the source lane and the destination lane is used as the reference position. If it is determined that the host vehicle has yet to cross the reference position, processing in S244 is performed. If it is determined that the host vehicle has yet to cross the reference position, processing in S246 is performed. Note that, although the reference position is set to a dividing line in this embodiment, the reference position may be set at any position within the lateral range of the source lane and the destination lane. For example, the reference position may be set so that it is determined that the entire host vehicle has entered the destination lane, or so that it is determined whether the distance to the lane center is equal to or less than a predetermined value.

[0076] If it is determined in S243 of Fig. 6 that the own lane is not the destination lane, in S244 of Fig. 6, a surrounding no-entry area Ssurr is set so as to leave space for the own vehicle to travel in the source lane on the side of the obstacle selected as the target obstacle in S242 of Fig. 6, and to ensure a set distance or more between the obstacle and the own vehicle. The surrounding no-entry area Ssurr is set around the obstacle. The vertical length of the surrounding no-entry area Ssurr relative to the obstacle is set according to the set distance, and the horizontal length relative to the obstacle is set according to the lane width.

[0077] In this embodiment, an elliptical surrounding no-entry area Ssurr is set. In this case, the surrounding no-entry area Ssurr is expressed inside the elliptical equation ζellps(X,Y)=0. Here, ζellps(X,Y) is expressed by the following equation.

number

[0078] da(k) and db(k) are the lengths of the major and minor axes of the ellipse set for the obstacle at prediction point k. The magnitudes of da(k) and db(k) may be adjusted according to the speed of the host vehicle and the speed of the obstacle. For example, the greater the speed difference between the host vehicle and the obstacle, the larger da(k) and db(k) may be set. Furthermore, the center of the ellipse does not need to coincide with the center position Xo(k) and Yo(k) of the obstacle. Furthermore, the no-entry area set for the obstacle does not need to be elliptical; any shape of no-entry area may be set as long as it allows the vehicle to travel beside the obstacle and does not approach the obstacle more than a set distance. Furthermore, the no-entry area may be set in a path coordinate system instead of an inertial coordinate system.

[0079] Figure 7 is a schematic diagram showing the elliptical surrounding no-entry area Ssurr. The area inside the ellipse ζellps(X,Y)=0 with the central position Xo(k), Yo(k) of the obstacle as its center is the surrounding no-entry area Ssurr.

[0080] If it is determined in S241 of Fig. 6 that the target action is not a lane change, it is determined in S245 of Fig. 6 whether or not there is an obstacle ahead in the own lane. If it is determined that there is an obstacle ahead in the own lane, the process of S246 is performed, and the obstacle ahead in the own lane is selected as the target obstacle. If it is determined that there is no obstacle ahead in the own lane, the process of S247 is performed. Note that in this embodiment, only lane keeping and lane changing are considered as target actions, so S245 is processing for lane keeping.

[0081] If it is determined in S245 of Fig. 6 that an obstacle is present ahead in the own vehicle's lane, or if it is determined in S243 of Fig. 6 that the vehicle has passed the reference position, a vehicle-to-vehicle no-entry area SIVD is set for the obstacle selected as the target obstacle in S246 of Fig. 6 so that a set distance or more can be maintained between the obstacle and the own vehicle. In this embodiment, a boundary line that crosses the original lane and the destination lane in the horizontal direction is set at a distance or more closer to the own vehicle than the obstacle, and the obstacle side of the boundary line is set as the vehicle-to-vehicle no-entry area SIVD. In this example, the boundary line is set to be linear.

[0082] For example, the no-entry zone SIVD is expressed in the route coordinate system as an area on the obstacle side with a boundary of a straight line equation ζstrght(s) = 0. Here, for the obstacle ahead, ζstrght(s) is expressed by the following equation:

number

[0083] so(k) and dc(k) are the tangential position of the obstacle at the predicted point k and the distance between the centers of gravity that you want to maintain. For a rear obstacle, it is expressed by the following equation.

number

[0084] The magnitude of dc(k) may be adjusted according to the speed of the host vehicle and the speed of the obstacle. For example, the greater the speed difference between the host vehicle and the obstacle, the larger dc(k) may be set. Furthermore, the no-entry area set for the obstacle does not have to be linear; any shape of no-entry area may be set as long as it ensures that the inter-vehicle distance between the obstacle and the host vehicle is equal to or greater than the set distance. Furthermore, the no-entry area may be set in an inertial coordinate system instead of a route coordinate system.

[0085] Fig. 8 is a schematic diagram showing a linear no-entry area SIVD. The point cloud represented by χr is a reference route, which will be described later. In Fig. 8, a line ζstrght(s)=0 exists at a distance dc(k) in the tangential direction from the center position so(k),wo(k) of the obstacle in the route coordinate system, and the area on the obstacle side with ζstrght(s)=0 as the boundary is the no-entry area SIVD.

[0086] The magnitudes of da(k) and dc(k) may be set to match the desired inter-vehicle distance dd. This allows a consistent inter-vehicle distance to be maintained before and after passing the reference position. However, depending on the positional relationship between the host vehicle and the surrounding no-entry area when passing the reference position, simply setting dc(k) = da(k) = dd may result in the host vehicle entering the inter-vehicle no-entry area at the current time (k = 0). In this embodiment, the trajectory is calculated as an optimization problem, so it is easier to solve if the host vehicle has not entered the inter-vehicle no-entry area at k = 0, that is, if the initial value does not violate the constraints. To prevent the host vehicle from entering the inter-vehicle no-entry area at k = 0, the magnitude of dc(k) may be set according to the current inter-vehicle distance.

[0087] FIG. 9 is a schematic diagram showing a method for setting the magnitude of dc(k) based on the current inter-vehicle distance. In FIG. 9, the host vehicle is changing lanes and has just crossed a lane line. Since the host vehicle is located ahead of the rear end of ζellps(X,Y)=0 in the direction of travel, setting dc(0)=da(0)=dd sets a boundary such that ζ'strght(s)=0, and the host vehicle is in the inter-vehicle no-entry zone at k=0. Since it is desirable for the host vehicle not to be in the inter-vehicle no-entry zone at k=0, in a scene like FIG. 9, dc(k) is set based on the inter-vehicle distance at the time the vehicle crossed the lane line. For example, setting dc(0)=so(0)-s0 sets a boundary such that the host vehicle is not included in the inter-vehicle no-entry zone, such as ζstrght(s)=0 in FIG. 9. This prevents the initial value from violating constraints, making it easier to solve. However, if the final inter-vehicle distance dd that you want to maintain is dd ≠ so(k) - s(k), then if dc(k) = so(k) - s(k) at all prediction points k (k = 0, , N), the inter-vehicle distance cannot converge to dd. Therefore, to ensure that the final inter-vehicle distance converges to dd, you can set dc(k) = w · dd + (1 - w) · (so(k) - s(k)), which is a weighted average of dd and so(k) - s(k). Here, the weight w is a function of k, and is a monotonically increasing function such that w = 0 when k = 0 and w = 1 when k = N. This ensures that the initial value does not violate the constraints, and allows the inter-vehicle distance to converge to the desired inter-vehicle distance dd.

[0088] Next, in S247 of Fig. 6, if there are obstacles other than the target obstacle selected in S242 or S245 of Fig. 6, a surrounding no-entry area Ssurr is set for each obstacle. The surrounding no-entry area Ssurr set for each obstacle may have any shape as long as it allows the vehicle to travel beside the obstacle and does not approach the obstacle more than a set distance. Note that when the processing described in S242 to S246 is performed for a rear obstacle, a surrounding no-entry area or an inter-vehicle no-entry area is set for the rear obstacle depending on the condition branch.

[0089] As described above, during a lane change, the no-entry area is changed based on the lateral position of the vehicle, so once the vehicle has moved to the destination lane to a certain extent, it will avoid obstacles in the destination lane without returning to the original lane. Therefore, even if an obstacle in the destination lane accelerates or decelerates, the vehicle will not unnaturally return to the original lane, improving the safety and comfort of passengers.

[0090] <Procedure for generating target trajectory> 10 is a flowchart showing the procedure for generating a target trajectory, which is performed in S250 of FIG.

[0091] First, in S251 of Fig. 10, a reference point group is calculated. Here, the reference point group is series data of reference positions Xr, Yr, reference route direction ψr, and reference vehicle speed Vr from the current time 0 to a prediction period Th in the future at time interval Ts. Note that hereinafter, the series data of reference positions Xr(k), Yr(k) (k = 0, , N) will be referred to as reference route χr.

[0092] The reference positions Xr(k), Yr(k), reference route direction ψr(k), and reference vehicle speed Vr(k) (k = 0, , N) at each time are determined as follows: First, the reference vehicle speed Vr(k) is determined based on the speed limit Vl of the lane and the vehicle speed Vp of the preceding vehicle, and is set as Vr(k) = Vl, for example. Note that Vr(k) does not need to be a constant value within the horizon.

[0093] Next, if the target behavior is lane keeping, the reference positions Xr(k), Yr(k) and reference route direction ψr(k) are determined based on the X and Y positions of the lane center and the route direction so that the host vehicle can travel in the center of the target lane. At the same time, conditions are set for the relationship between the reference positions Xr(k), Yr(k) and the reference vehicle speed Vr(k) so that the reference positions Xr(k), Yr(k) and the reference vehicle speed Vr(k) are consistent. In other words, the reference positions Xr(k), Yr(k) are determined so that the following two equations are satisfied:

number

[0094] Equation (401) is the condition for the reference positions Xr(k), Yr(k) to exist on the function Y=l e(X) (equation (205)) that represents the center of the own lane, and equation (402) is the condition for the distance between adjacent reference positions Xr(k-1), Yr(k-1) and Xr(k), Yr(k) to be equal to the amount of movement of the own vehicle over the time interval Ts. By calculating the direction of the own lane center Y=l e(X) at the reference positions Xr(k), Yr(k) determined using these equations, the reference route direction ψr(k) can also be determined. Hereinafter, the reference route for lane keeping will be referred to as the reference lane keeping route χrLK.

[0095] When the target behavior is a lane change, for example, a function Y=lLC(X) is generated to represent a reference path for lane change (reference lane change path χrLC) by connecting the center of the current lane to the center of the target lane so that it is continuous and smooth. For the connection, known methods such as a spline curve or a quintic function are used. Then, the reference positions Xr(k) and Yr(k) are determined using the following equations instead of equation (401).

number

[0096] The reference path direction ψr(k) can also be determined by calculating the direction of the reference lane-change path Y = lLC(X) at the reference positions Xr(k) and Yr(k) determined using these. When connecting, the connections are made so that a reference lane-change path χrLC is generated that will complete the lane change within the target required time tLC, for example, so that the host vehicle completes its lateral movement to the target lane by a distance d that it moves longitudinally during the target required time tLC. The distance d may be calculated by integrating the reference vehicle speed Vr over time, or by multiplying the current vehicle speed V0 by the target required time tLC. Furthermore, if the traveling lane is curved, the connections may be made in the path coordinate system. Furthermore, if there is no need to specify the target required time for a lane change and the prediction period Th is sufficiently long, the reference lane-change path χrLC may not be generated, and the reference positions Xr(k) and Yr(k) may simply be determined using the following equation instead of equation (401):

number

[0097] Here, Y=lt(X) is a function that expresses the center of the target lane, and from equations (205), (206), and (207), lt=le, ll, and lr when the target lane is the own lane, left lane, or right lane, respectively.

[0098] The reference positions Xr(k), Yr(k), reference route direction ψr(k), and reference vehicle speed Vr(k) (k=0, . . . , N) calculated as above are used as a reference point group.

[0099] Next, in S252 of Fig. 10, a constraint g(x, u) ≦ 0 is set. In this embodiment, the function g is set as follows so that the center-of-gravity positions Xg(k) and Yg(k) of the host vehicle at each prediction point k (k = 0, , N) do not enter the surrounding no-entry area Ssurr and the inter-vehicle no-entry area SIVD set in S240, and the control input u(k) falls within a certain range.

[0100]

number

[0101] Here, jHxt, jLxt, ωHt, and ωLt are the upper and lower limit values ​​of each control input. The upper and lower limit values ​​of each control input may be changed for each prediction point k. If there is no obstacle with a surrounding no-entry area Ssurr or an inter-vehicle no-entry area SIVD defined, the corresponding elements are deleted from equations (405) and (406). In this embodiment, a constraint is set only on the control input u, but constraints may also be set on the yaw rate, lateral acceleration, etc. to improve ride comfort. Furthermore, the constraints may be changed according to the target behavior.

[0102] Next, in S253 of Fig. 10, an evaluation function J (equation (103)) is set. In this embodiment, a target trajectory ξ for the host vehicle to follow the reference point group (reference position Xr(k), Yr(k), reference route orientation ψr(k), reference vehicle speed Vr(k) (k = 0,...,N)) calculated in S251 can be generated, and vector value functions h and hN related to the evaluation items are set as follows so that the control input at that time is small.

number

[0103] ew(k) is the lateral deviation from the reference positions Xr(k), Yr(k) at prediction point k (k=0, ,N), and is expressed as follows using the reference positions Xr(k), Yr(k) at prediction point k (k=0, ,N) and the reference route direction ψr(k):

number

[0104] The reference values ​​r(k) and r(N) are set as follows:

number

[0105] Here, Vr(k) is the reference vehicle speed. This allows the target trajectory generation unit 250 to generate a target trajectory that allows the host vehicle to follow the reference point group with a small control input. Note that, in order to improve the followability to the reference point group and the ride comfort, route direction, yaw rate, longitudinal acceleration, lateral acceleration, etc. may be added to the evaluation items. Furthermore, the evaluation function may be changed depending on the target behavior.

[0106] Next, in S254 of FIG. 10, the optimal control input u* is calculated by solving a constrained optimization problem (Equation (101)) using the evaluation function (Equation (103)) and the constraint (Equation (102)). To calculate the optimal control input u*, known methods are used, such as ACADO (Automatic Control And Dynamic Optimization) developed by KULeuven University, or AutoGen, an automatic code generation tool that solves optimization problems based on the C / GMRES method. When ACADO or AutoGen is used, a time series (optimal control input) u* of the optimized control input at each prediction point k (k=0, , N-1) is output. That is, the output of S254 is expressed by the following equation.

number

[0107] Here, jxt*(k) and ωt*(k) (k=0, ,N-1) are the optimal values ​​of the target pitch jerk and target rudder angular velocity. Note that the solution may be a value that makes the evaluation function fall below a predetermined threshold, or if the evaluation function does not fall below the threshold within a predetermined number of iterations, the solution may be a value that minimizes the evaluation function within the predetermined number of iterations.

[0108] Next, in S255 of Fig. 10, the optimal state quantity x* is calculated. In the calculation of the optimal state quantity x*, the optimal control input u* and the vehicle model f are used to calculate the time series (optimal state quantity) x* of the optimized vehicle state quantity at each prediction point k (k = 0, , N). Therefore, the output of S255 is expressed by the following equation.

number

[0109] where Xg*(k), Yg*(k), θ*(k), β*(k), γ*(k), V*(k), ax*(k), axt*(k), δ*(k), δt*(k) (k=0, ,N) are the optimal values ​​of the center of gravity position, vehicle orientation, sideslip angle, yaw rate, vehicle speed, longitudinal acceleration, target longitudinal acceleration, steering angle, and target steering angle, respectively.

[0110] Next, in S256 of Fig. 10, a target trajectory ξ is generated. The target trajectory ξ is generated based on the optimal state quantity x* and the optimal control input u*. In this embodiment, the optimal state quantity x* is set as the target trajectory ξ. Therefore, the output of S256 is expressed by the following equation.

number

[0111] Note that the target trajectory ξ when the target behavior is lane keeping is called the target lane keeping trajectory ξLK, and when the target behavior is lane changing, the target trajectory ξ is called the target lane change trajectory ξLC. As explained in S251, when the target behavior is different, at least the reference path χr is different. However, in addition to this, it is also possible to change the items and values ​​of the constraints in S252, or the items and values ​​of the evaluation function in S253.

[0112] <Comparison of target lane change trajectories when a forward obstacle decelerates during a lane change> The difference in the behavior of the host vehicle between the comparative example and this embodiment when an obstacle ahead decelerates during a lane change will be described.

[0113] 11 is a schematic diagram showing the difference in the behavior of the host vehicle between the comparative example and this embodiment when an obstacle ahead decelerates during a lane change. The host vehicle is changing lanes to the left lane, and an obstacle ahead is present in the left lane. Each diagram shows the center positions Xo(k) and Yo(k) of the obstacle at each prediction point k (k=0, , N) at a certain time, and the optimal center-of-gravity positions Xg*(k) and Yg*(k) of the host vehicle included in the target lane-change trajectory ξLC.

[0114] 11(A) is a diagram showing the state immediately before the host vehicle crosses the lane marking, and is common to both the comparative example and this embodiment. In FIG. 11(A), the host vehicle has not yet crossed the lane marking, so a surrounding no-entry area Ssurr is set for the obstacle ahead. In FIG. 11(A), it is predicted that the host vehicle will complete its movement to the center of the destination lane at the predicted final point.

[0115] Here, consider a case where the obstacle ahead begins to decelerate immediately after FIG. 11(A). FIG. 11(B) is a diagram of the comparative example, showing the state immediately after the host vehicle crosses the lane marking after time has passed since FIG. 11(A). Because the obstacle ahead has decelerated, it is necessary to avoid the obstacle ahead. In the comparative example, the host vehicle is not prohibited from returning to the original lane, so depending on the weight of the evaluation function, a trajectory is generated in which the host vehicle returns to the original lane and goes around the side of the obstacle ahead, as shown in FIG. 11(B), to avoid a collision with the obstacle ahead. However, unless a significant deceleration (e.g., 3.0 m / s or more) is required, it is unnatural for the host vehicle to move to the destination lane and then return to the original lane, which reduces safety and comfort. Furthermore, the target behavior of lane change cannot be achieved.

[0116] FIG. 11(C) is a diagram illustrating the state immediately after the host vehicle crosses the lane marking after time has elapsed since FIG. 11(A) in this embodiment. Because the host vehicle has crossed the lane marking, a vehicle-to-vehicle no-entry area SIVD is set. Because the obstacle ahead has decelerated, it is necessary to avoid the obstacle ahead. However, because the vehicle-to-vehicle no-entry area SIVD has been set, it is no longer possible to avoid a collision with the obstacle ahead by returning to the original lane and going around to the side of the obstacle ahead. Since a collision with the obstacle ahead can only be avoided by deceleration, a trajectory is generated as shown in FIG. 11(C) that avoids a collision with the obstacle ahead while decelerating without returning to the original lane. This is a more natural behavior than FIG. 11(B) and improves safety and comfort. Furthermore, as in FIG. 11(A), the vehicle is predicted to complete movement to the center of the destination lane at the prediction final point, so the target lane change can also be achieved.

[0117] <Summary of the First Embodiment> With this configuration, the no-entry area is changed based on the lateral position of the vehicle during lane change, so once the vehicle has moved to the destination lane to a certain extent, it will avoid obstacles in the destination lane without returning to the original lane. Therefore, even if an obstacle in the destination lane accelerates or decelerates, the vehicle will not unnaturally return to the original lane, improving the safety and comfort of passengers.

[0118] Embodiment 2 In the first embodiment, after the host vehicle moves to the destination lane, an inter-vehicle no-entry area is set so that the host vehicle can avoid a collision with an obstacle without returning to the original lane, but instead, a no-entry area (hereinafter referred to as a lane no-entry area) that prevents the host vehicle from leaving the destination lane and a surrounding no-entry area may be set. As a result, as in the first embodiment, once the host vehicle has moved to the destination lane to a certain extent, the host vehicle can avoid an obstacle in the destination lane without returning to the original lane, so that even if the obstacle in the destination lane accelerates or decelerates, the host vehicle will not unnaturally return to the original lane, improving the safety and comfort of passengers.

[0119] The second embodiment will be described below. Explanations that overlap with the first embodiment will be omitted here. The only difference between the second embodiment and the first embodiment is S246 in FIG.

[0120] <Procedure for setting no-entry areas> S246 in FIG. 12 in the second embodiment will be described. As in the first embodiment, if it is determined in S245 in FIG. 12 that an obstacle is present ahead in the own lane, or if it is determined in S243 in FIG. 12 that the vehicle has passed a predetermined reference position, a lane no-entry area Slane and a surrounding no-entry area Ssurr are superimposed on the obstacle selected as the target obstacle in S246 in FIG. 12 so that the vehicle does not leave the destination lane and maintains a set distance or more between the obstacle and the own vehicle. In this embodiment, the lane no-entry area Slane is an area outside the dividing line of the destination lane. However, if a line other than a dividing line is selected as the reference position in S243 in FIG. 12, the boundary of the lane no-entry area Slane is adjusted laterally to be consistent with the line. In this embodiment, a super-elliptical surrounding no-entry area Ssurr is set. In this case, the surrounding no-entry area Ssurr is expressed within the super-ellipse equation ζsup(X,Y)=0. Here, ζsup(X,Y) is expressed by the following equation.

number

[0121] da(k) and db(k) are the lengths of the major and minor axes of the super ellipse set for the obstacle at prediction point k. n is the order of the ellipse and may be an even number equal to or greater than 4. In this embodiment, n=8. The magnitudes of da(k) and db(k) may be adjusted according to the speed of the host vehicle and the speed of the obstacle. For example, the greater the speed difference between the host vehicle and the obstacle, the larger da(k) and db(k) may be. Furthermore, the center of the super ellipse does not need to coincide with the center positions Xo(k) and Yo(k) of the obstacle. Furthermore, the no-entry area set for the obstacle does not need to be a super ellipse. Any shape of no-entry area may be set as long as it allows the vehicle to travel beside the obstacle and does not approach the obstacle more than a set distance in the vertical direction. Furthermore, the no-entry area may be set in a path coordinate system instead of an inertial coordinate system.

[0122] Fig. 13 is a schematic diagram showing the super-elliptical surrounding no-entry area Ssurr. The inside of the super-ellipse ζsup(X,Y)=0 with the central position Xo(k), Yo(k) of the obstacle as its center is the surrounding no-entry area Ssurr.

[0123] Figure 14 is a schematic diagram showing the result of superimposing the lane no-entry area Slane and the super-elliptical surrounding no-entry area Ssurr. The result of the superimposition is a U-shaped no-entry area. This allows the vehicle to avoid a collision with the obstacle ahead by decelerating without returning to the original lane. The reason for making the surrounding no-entry area Ssurr super-elliptical is to make the boundary of the area nearly flat in the direction of travel. If the surrounding no-entry area Ssurr has a convex shape like an ellipse, the host vehicle may be unable to exit the depression, as shown in Figure 15, and may be unable to reach the center of the destination lane. If the surrounding no-entry area Ssurr is super-elliptical, this possibility disappears, and the host vehicle can reach the center of the destination lane.

[0124] <Summary of Embodiment 2> According to this configuration, after the vehicle has moved to the destination lane to a certain extent, a lane no-entry area and a surrounding no-entry area are set, so that the vehicle can avoid obstacles in the destination lane without returning to the original lane. Therefore, even if an obstacle in the destination lane accelerates or decelerates, the vehicle will not unnaturally return to the original lane, improving the safety and comfort of the occupants.

[0125] Embodiment 3 In the first embodiment, after the host vehicle passes the reference position during a lane change, a no-entry zone is set so that the host vehicle can avoid a collision with an obstacle in the destination lane without returning to the original lane. However, there may be exceptional cases where it is better to return to the original lane to avoid a collision with an obstacle in the destination lane. In such cases, a no-entry zone may be set so that the host vehicle can avoid a collision with an obstacle in the destination lane by returning to the original lane even after passing the reference position. An example of a case where it is better to return to the original lane to avoid a collision with an obstacle in the destination lane is when the absolute value of the acceleration or deceleration required to avoid a collision with the obstacle is equal to or greater than a reference value. This allows the host vehicle to avoid a collision by returning to the original lane in such exceptional cases, thereby improving safety and comfort.

[0126] The following describes the third embodiment. Explanations that overlap with the first embodiment will be omitted here. The only difference between the third embodiment and the first embodiment is S248 in FIG.

[0127] <Procedure for setting no-entry areas> S248 in FIG. 16 according to the third embodiment will be described. If it is determined in S243 of FIG. 16 that the predetermined reference position has been exceeded, it is determined in S248 of FIG. 16 whether or not an exception exists. If it is determined that an exception exists, the process of S244 of FIG. 16 is performed. If it is determined that an exception does not exist, the process of S246 of FIG. 16 is performed. The exception here refers to a case where it would be better to return to the original lane to avoid a collision with an obstacle in the destination lane. For example, a case where an obstacle ahead in the destination lane suddenly decelerates, and the absolute value of the deceleration of the host vehicle necessary to maintain a distance between the vehicles is equal to or greater than a judgment value (e.g., 3.0 m / s), or a case where an obstacle behind the destination lane suddenly accelerates, and the absolute value of the acceleration of the host vehicle necessary to maintain a distance between the vehicles is equal to or greater than a judgment value (e.g., 3.0 m / s). In such cases, if an attempt is made to avoid a collision without returning to the original lane, sudden deceleration or sudden acceleration would be necessary, which would be dangerous. Therefore, it is better to return to the original lane to avoid a collision. By the processing of S248 in FIG. 16, in the event of an exception, a surrounding no-entry area is set in S244 in FIG. 16, so that it becomes possible to avoid a collision by returning to the original lane.

[0128] Note that the exceptions are not limited to the above, and may also include any other case in which it is better to return to the original lane to avoid a collision, such as when it becomes impossible to secure a space of at least the judgment value in the destination lane. The case in which it becomes impossible to secure a space of at least the judgment value in this case applies, for example, to a case in which another obstacle exists in the longitudinal direction of the destination lane, the relative position from the host vehicle is within a predetermined judgment range (for example, the distance traveled by the host vehicle in 0.8 seconds), the case in which the inter-vehicle distance between the obstacle ahead and the obstacle behind the destination lane becomes narrow, or the case in which another obstacle enters the destination lane from a lane further back than the destination lane.

[0129] <Summary of the Third Embodiment> With this configuration, in exceptional cases where it is better to return to the original lane to avoid a collision with an obstacle in the destination lane, the vehicle can return to the original lane to avoid a collision, thereby improving safety and comfort.

[0130] <Summary of various aspects of the present application> Various aspects of the present application will be summarized below as appendices. (Appendix 1) a no-entry area setting unit that sets a no-entry area for the host vehicle based on at least one of predicted obstacle movement and road information; a target trajectory generation unit that calculates a target trajectory for the host vehicle over the future under the constraint of not entering the no-entry area; a vehicle control unit that controls the traveling of the host vehicle based on the target trajectory; Equipped with The no-entry area setting unit is a vehicle control device that changes the no-entry area based on the lateral position of the vehicle relative to the source lane or the destination lane when the target trajectory generation unit calculates the target trajectory for changing lanes from the source lane to the destination lane.

[0131] (Appendix 2) The vehicle control device described in Appendix 1, wherein the no-entry area setting unit sets the no-entry area so that the vehicle avoids a collision with the obstacle present in the destination lane without returning to the source lane after the lateral position of the vehicle exceeds a reference position set within the lateral range of the source lane and the destination lane toward the destination lane.

[0132] (Appendix 3) The vehicle control device described in Appendix 2, wherein the no-entry area setting unit sets the no-entry area so that a distance between the obstacle present in the destination lane is maintained at a set distance or more so that the vehicle can avoid a collision with the obstacle without the vehicle returning to the source lane after the lateral position has exceeded the reference position.

[0133] (Appendix 4) The vehicle control device described in Appendix 2, wherein the no-entry area setting unit sets the no-entry area so that, after the lateral position exceeds the reference position, the host vehicle does not leave the destination lane, so as to avoid a collision with a forward obstacle that is the obstacle present in front of the host vehicle in the destination lane, without the host vehicle returning to the source lane, and sets the no-entry area so that a distance between the obstacle and the host vehicle is equal to or greater than a set distance.

[0134] (Appendix 5) 5. The vehicle control device according to claim 2, wherein the reference position is a dividing line indicating a boundary between the source lane and the destination lane.

[0135] (Appendix 6) The vehicle control device according to any one of appendices 2 to 5, wherein the no-entry area setting unit determines whether or not an exception exists for the host vehicle, and if it determines that the exception exists, sets the no-entry area such that the host vehicle returns to the original lane to avoid a collision with the obstacle present in the destination lane even after the lateral position has exceeded the reference position.

[0136] (Appendix 7) The vehicle control device described in Appendix 6, wherein the exception is when the absolute value of the acceleration or deceleration required for the vehicle to avoid a collision with the obstacle without returning to the original lane is greater than or equal to a judgment value.

[0137] (Appendix 8) The vehicle control device according to claim 6 or 7, wherein the exception is a case where a space of a determination value or more for the host vehicle to change lanes cannot be secured in the destination lane.

[0138] (Appendix 9) 4. The vehicle control device according to claim 3, wherein after the lateral position exceeds the reference position, the no-entry area setting unit sets a boundary line that crosses the source lane and the destination lane laterally at a position closer to the host vehicle than the set distance from the obstacle in the destination lane, and sets the no-entry area on the obstacle side of the boundary line.

[0139] (Appendix 10) 10. The vehicle control device according to claim 3, wherein the no-entry area setting unit sets the set distance to a distance equal to or less than the inter-vehicle distance between the host vehicle and the obstacle at the time when the lateral position has exceeded the reference position.

[0140] (Appendix 11) 11. The vehicle control device according to claim 2, wherein the no-entry area setting unit sets the no-entry area so as to leave space on the source lane side of the obstacle for the host vehicle to travel in the source lane before the lateral position exceeds the reference position, and to ensure a distance between the obstacle and the host vehicle that is equal to or greater than a set distance.

[0141] Although various exemplary embodiments and examples are described in this application, the various features, aspects, and functions described in one or more embodiments are not limited to the application of a particular embodiment, but may be applied to the embodiments alone or in various combinations. Therefore, countless variations not illustrated are contemplated within the scope of the technology disclosed in this specification. For example, this includes cases where at least one component is modified, added, or omitted, or where at least one component is extracted and combined with components of another embodiment. [Explanation of symbols]

[0142] 1 vehicle, 2 steering wheel, 3 steering shaft, 4 steering unit, 5 EPS motor, 6 powertrain unit, 7 brake unit, 111 forward camera, 112 radar sensor, 121 GNSS, 122 navigation device, 131 steering angle sensor, 132 steering torque sensor, 133 yaw rate sensor, 134 speed sensor, 135 acceleration sensor, 200 vehicle control unit, 311 EPS controller, 312 powertrain controller, 313 brake controller

Claims

1. a no-entry area setting unit that sets a no-entry area for the host vehicle based on both the predicted movement of the obstacle and road information; a target trajectory generation unit that calculates a target trajectory for the host vehicle over the future under the constraint of not entering the no-entry area; a vehicle control unit that controls the traveling of the host vehicle based on the target trajectory; Equipped with The no-entry area setting unit is a vehicle control device that changes the no-entry area based on the lateral position of the vehicle relative to the source lane or the destination lane when the target trajectory generation unit calculates the target trajectory for changing lanes from the source lane to the destination lane.

2. 2. The vehicle control device according to claim 1, wherein the no-entry area setting unit sets the no-entry area so that, after the lateral position of the vehicle exceeds a reference position set within a lateral range of the source lane and the destination lane toward the destination lane, the vehicle can avoid a collision with the obstacle present in the destination lane without returning to the source lane.

3. 3. The vehicle control device according to claim 2, wherein the no-entry area setting unit sets the no-entry area so as to maintain a distance of at least a set distance between the vehicle and the obstacle present in the destination lane after the lateral position has exceeded the reference position, so as to avoid a collision with the obstacle without the vehicle returning to the source lane.

4. 3. The vehicle control device according to claim 2, wherein the no-entry area setting unit sets the no-entry area so that the vehicle does not leave the destination lane after the lateral position exceeds the reference position, so as to avoid a collision with a forward obstacle that is the obstacle present in front of the vehicle in the destination lane without the vehicle returning to the source lane, and sets the no-entry area so that a distance between the obstacle and the vehicle is equal to or greater than a set distance.

5. The vehicle control device according to claim 2 , wherein the reference position is a dividing line indicating a boundary between the source lane and the destination lane.

6. 6. A vehicle control device as described in any one of claims 2 to 5, wherein the no-entry area setting unit determines whether or not an exception exists for the vehicle, and if it determines that the exception exists, sets the no-entry area so that the vehicle can return to the original lane to avoid a collision with the obstacle present in the destination lane even after the lateral position has exceeded the reference position.

7. The vehicle control device according to claim 6, wherein the exception is a case where the absolute value of the acceleration or deceleration required for the host vehicle to avoid a collision with the obstacle without returning to the original lane is equal to or greater than a judgment value.

8. The vehicle control device according to claim 6 , wherein the exception occurs when a space equal to or larger than a determination value for the host vehicle to change lanes cannot be secured in the destination lane.

9. 4. The vehicle control device according to claim 3, wherein after the lateral position exceeds the reference position, the no-entry area setting unit sets a boundary line that crosses the source lane and the destination lane laterally at a position closer to the vehicle than the set distance from the obstacle in the destination lane, and sets the no-entry area on the obstacle side of the boundary line.

10. 10. The vehicle control device according to claim 3, wherein the no-entry area setting unit sets the set distance to a distance equal to or less than the inter-vehicle distance between the host vehicle and the obstacle at the time when the lateral position of the host vehicle exceeds the reference position.

11. 3. The vehicle control device according to claim 2, wherein the no-entry area setting unit sets the no-entry area so as to leave space on the source lane side of the obstacle for the host vehicle to travel in the source lane before the lateral position exceeds the reference position, and to ensure a distance between the obstacle and the host vehicle that is equal to or greater than a set distance.

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