Vehicle motion control device and vehicle motion control method

Abstract

The purpose of this invention is to provide a vehicle motion control device for generating a travel track that achieves a comfortable ride and high safety by minimizing vehicle behavior-related physical quantities such as longitudinal acceleration, lateral acceleration, and vertical acceleration when traversing or avoiding predetermined areas such as uneven surfaces on the vehicle's path. To this end, the vehicle motion control device of this invention comprises: a vehicle behavior prediction unit that predicts vehicle behavior-related physical quantities generated when the vehicle maintains a reference path toward a predetermined area on its path and when the vehicle moves to an avoidance path to avoid the predetermined area; and a track generation unit that generates a travel track defined by the reference path or the avoidance path, wherein the physical quantities are less than predetermined values.

Description

Technical Field

[0001] This invention relates to a vehicle motion control device and a vehicle motion control method that generates a travel track that serves as the target of the vehicle and controls the movement of the vehicle based on the generated travel track. Background Technology

[0002] Autonomous driving technology is known for generating a driving trajectory consisting of information such as the driving path and speed, based on road conditions and vehicle status obtained using maps, communications, and sensors, and controlling the powertrain, braking, and steering by having the vehicle follow the generated driving trajectory.

[0003] Patent Document 1 describes a method for generating a travel track in cases where there are uneven surfaces on the road ahead of a vehicle. The method involves increasing or decreasing the vehicle speed in a way that avoids vibrations generated when passing over uneven surfaces and resonance with the vehicle's springs, thereby reducing the vertical acceleration generated by the vehicle's springs and improving ride quality.

[0004] Existing technical documents

[0005] Patent documents

[0006] Patent Document 1: Japanese Patent Application Publication No. 2009-248909 Summary of the Invention

[0007] The problem the invention aims to solve

[0008] However, the method described in Patent Document 1 does not take into account the front-to-rear acceleration caused by changes in vehicle speed. Therefore, the front-to-rear acceleration may become extremely large due to changes in vehicle speed or differences in the size of bumps, resulting in a worse ride quality compared to a situation without speed control. Furthermore, it does not consider the possibility of suspension damage caused by the generation of a driving track to avoid bumps or vibrations generated under the vehicle's springs when traversing bumps. Consequently, it may not achieve the necessary level of ride quality and safety relative to the road conditions and vehicle status.

[0009] Therefore, the purpose of this invention is to provide a vehicle motion control device and a vehicle motion control method for generating a driving track. The driving track can achieve a comfortable ride and high safety by minimizing the physical quantities related to vehicle behavior, such as front-to-back acceleration, lateral acceleration, and vertical acceleration, generated when passing through or avoiding specified areas such as bumps and depressions on the vehicle's path.

[0010] Technical means to solve the problem

[0011] To solve the above problems, the vehicle motion control device of the present invention includes: a vehicle behavior prediction unit that predicts vehicle behavior-related physical quantities generated when the vehicle maintains a reference path toward a predetermined area on the road ahead and vehicle behavior-related physical quantities generated when the vehicle moves to an avoidance path to avoid the predetermined area; and a track generation unit that generates a travel track defined by the reference path or the avoidance path where the physical quantities are less than a predetermined value.

[0012] Furthermore, the vehicle motion control method of the present invention includes the following steps:

[0013] Physical quantities related to vehicle behavior that are predicted when a vehicle maintains a baseline path toward a designated area on its path of progress.

[0014] Predicting the physical quantities related to vehicle behavior generated when the vehicle moves to an avoidance path to avoid the designated area; and

[0015] Generate a travel trajectory defined by the reference path or the avoidance path where the physical quantity is less than a specified value.

[0016] The effects of the invention

[0017] According to the vehicle motion control device or vehicle motion control method of the present invention, it is possible to achieve a comfortable ride and high safety with low physical quantities related to vehicle behavior, such as front-to-back acceleration, lateral acceleration, and vertical acceleration, when passing through or avoiding specified areas such as bumps and depressions on the vehicle's path. Attached Figure Description

[0018] Figure 1 This diagram illustrates a configuration example of an onboard system 1 that includes a vehicle motion control device 2 according to one embodiment.

[0019] Figure 2 This diagram illustrates an example of the functional blocks of a travel track generation unit 22 in one embodiment.

[0020] Figure 3 This is a diagram illustrating an example of driving status information input to a driving trajectory generation unit 22 in one embodiment.

[0021] Figure 4 A diagram illustrating the front and rear wheel models of one embodiment.

[0022] Figure 5 A flowchart illustrating the processing outline of the Action Decision Department 22e.

[0023] Figure 6 A flowchart illustrating the processing outline of the Action Decision Department 22e.

[0024] Figure 7A flowchart illustrating the processing outline of the Action Decision Department 22e.

[0025] Figure 8 This figure illustrates an example of the processing result given by the travel track generation unit 22 in one embodiment.

[0026] Figure 9 This figure illustrates an example of the processing results given by a vehicle 60 equipped with an onboard system 1 that includes a vehicle motion control device 2 according to one embodiment.

[0027] Figure 10 A flowchart illustrating the processing outline of the Action Decision Department 22e. Detailed Implementation

[0028] Next, use Figures 1-10 This document provides a detailed description of an in-vehicle system incorporating a vehicle motion control device according to an embodiment of the present invention.

[0029] <In-vehicle System 1>

[0030] Figure 1 This diagram illustrates a configuration example of an in-vehicle system 1 that includes the vehicle motion control device 2 of this embodiment. As shown here, the in-vehicle system 1 includes an external communication device 11, a GNSS 12, a map information storage unit 13, a sensor 14, an HMI unit 15, a vehicle motion control device 2, a powertrain system 3, a braking system 4, and a steering system 5.

[0031] The in-vehicle system 1 is installed in the vehicle to perform vehicle motion control, such as autonomous driving or driver assistance.

[0032] The vehicle-to-vehicle communication device 11 communicates with other vehicles via wireless communication, and communicates with other vehicles via road, thereby transmitting and receiving information about the vehicle and its surrounding environment.

[0033] GNSS 12 receives radio waves transmitted from artificial satellites such as Quasi-Zenith Satellites or GPS satellites to obtain information such as the vehicle's location.

[0034] In addition to storing general road information used in navigation systems, the map information storage unit 13 also stores road information such as road width and curvature, the driving status of other vehicles and road conditions, traffic conditions, and other surrounding environmental information. The surrounding environmental information is updated sequentially using information obtained through vehicle-to-vehicle communication or road-to-road communication via the external communication device 11.

[0035] In addition to external identification sensors such as image sensors, millimeter-wave radar, and lidar that detect information about the surrounding environment, sensor 14 also includes sensors that detect driver operations, vehicle speed, acceleration, angular velocity, steering angle, etc. The surrounding environment information detected by the external identification sensors includes various objects existing around the vehicle, such as obstacles, other vehicles, pedestrians, signs, lane markings, and buildings. For example, sensor 14 identifies lane markings and lane outer lines based on the difference in brightness between the white lines in the image data captured by the image sensor and the road surface.

[0036] In addition to accepting user input operations such as driving mode selection and destination setting, the HMI unit 15 also displays the information required by the user on the display and generates voice guidance or alarms through the speaker based on various information obtained from the external communication device 11 or sensor 14.

[0037] The vehicle motion control device 2 includes an operation management unit 21, a travel trajectory generation unit 22, and a travel control unit 23. The operation management unit 21, travel trajectory generation unit 22, and travel control unit 23 are computers equipped with hardware such as a CPU and other computing devices, a main storage device such as a semiconductor memory, an auxiliary storage device, and a communication device to comprehensively control the vehicle. Various functions are implemented by the computing device executing programs loaded into the main storage device; however, such well-known technologies will be omitted from the following description as appropriate. Furthermore, in this embodiment, for ease of understanding, a configuration where the operation management unit 21, travel trajectory generation unit 22, and travel control unit 23 are separate is illustrated. However, when this invention is used in an actual vehicle, these functions can also be implemented by a higher-level controller.

[0038] The operation management unit 21 generates vehicle location information, information about various objects around the vehicle, and information related to vehicle behavior based on information acquired by the external communication device 11, GNSS 12, map information storage unit 13, and sensors 14. Furthermore, the operation management unit 21 periodically transmits this location information, surrounding environment information, and vehicle behavior-related information via the external communication device 11, and updates the map information storage unit 13 accordingly. In addition to this location information, surrounding environment information, and vehicle behavior-related information, the operation management unit 21 also sets a path from the vehicle's current location to its destination based on information such as the destination acquired by the HMI unit 15. Hereinafter, the information generated or set by the operation management unit 21 will be referred to as driving status information.

[0039] The driving control unit 23 sets the target driving force, target braking force, target steering angle, etc., so that the vehicle follows the driving trajectory output by the driving trajectory generation unit 22, and controls the powertrain system 3, braking system 4, and steering system 5.

[0040] The powertrain system 3 controls the driving force generated by the internal combustion engine or electric motor, etc., based on the driver's operation and the target driving force output from the driving control unit 23.

[0041] The braking system 4 controls the braking force generated by the brake calipers, etc., based on the driver's operation and the target braking force output from the driving control unit 23.

[0042] The steering system 5 controls the wheel steering angle based on the driver's operation and the target steering angle output from the driving control unit 23.

[0043] <Trajectory Generation Unit 22>

[0044] Next, use Figures 2-4 An example of a functional block of the travel track generation unit 22 is summarized below.

[0045] The driving trajectory generation unit 22 generates a driving trajectory for the vehicle, which is defined by information such as driving path and speed, using the driving status information mentioned above as input. It includes an information acquisition unit 22a, a driving area information calculation unit 22b, a vehicle behavior prediction unit 22c, an action extraction unit 22d, an action decision unit 22e, and a driving trajectory generation unit 22f.

[0046] The information acquisition unit 22a acquires driving status information from the operation management unit 21.

[0047] The driving area information calculation unit 22b takes the driving condition information output from the information acquisition unit 22a as input to calculate the area in which the vehicle can travel without contacting obstacles such as other vehicles, pedestrians, and buildings on the road ahead, as well as the lateral movement distance, target speed, and road surface friction coefficient required to avoid bumps and unevenness. Figure 3 Here is an overview of an example of driving area information output from the driving area information processing unit 22b.

[0048] exist Figure 3 In the situation shown, vehicle 60 is traveling on road 70, which consists of two lanes, from... Figure 3 The vehicle 60 travels from left to right, and its path includes uneven or rough roads (hereinafter referred to as "designated area 71"). Here, as an example of travel area information, the distance from the vehicle 60 to the farthest point detectable by sensor 14 is defined as L. Figure 3 Under these conditions, the width of the road surface 70, which is also the width of the drivable area, is set as W, and the distance from the vehicle 60 to the designated area 71 is set as L. a Let the length of the specified region 71 be L. b Let L be the distance from the specified area 71 to the farthest point that the sensor 14 can detect.c The lateral movement distance of vehicle 60 required to avoid designated area 71 is set as W. n Set the width of the specified area 71 to W. b The height of the protrusion in the designated area 71 is set to Hb, the current speed of the vehicle 60 is set to V0, and the predetermined upper and lower speed limits for driving on the road surface 70 are set to V0 and V0 respectively. U V L In the travel trajectory generation unit 22, a baseline path 81 to the designated area 71 or an avoidance path 82 to avoid the designated area 71 is generated based on this travel area information.

[0049] Furthermore, besides traversable rough roads such as uneven surfaces, puddles, and icy roads, the designated area 71 can also be impassable obstacles such as other vehicles traveling slower than vehicle 60; the type of designated area 71 is not limited. Additionally, when the designated area 71 is occupied by other slow-moving vehicles, a target speed is defined such that vehicle 60 will not come into contact with the designated area 71 even while maintaining the baseline path 81, at which point the relative speed with the designated area 71 becomes 0. Furthermore, the driving area information calculation unit 22b can also output a risk potential map calculated considering the movement range of other vehicles and the reach range of pedestrians when they dart out, as a drivable area. Moreover, Figure 3 The avoidance path 82 shown is a path that avoids the designated area 71 by changing lanes to the left lane and then returning to the original right lane. However, it can also be a path that does not return to the original lane or a path that avoids or crosses the designated area 71 within the same lane. The shape of the avoidance path 82 is not limited.

[0050] The vehicle behavior prediction unit 22c uses driving condition information output from the information acquisition unit 22a and driving area information output from the driving area information calculation unit 22b as inputs to predict physical quantities related to vehicle behavior, such as acceleration, when maintaining the baseline path 81 and switching to the avoidance path 82. Figure 4 An example of the physical quantities related to vehicle behavior predicted by the vehicle behavior prediction unit 22c is summarized. Figure 4 The diagram, which is a view of the vehicle 60 with vertical displacement of the road surface from the left, is a diagram showing the front and rear wheel models. The front and rear wheel models are represented by mass points such as the vehicle body and wheels, and the mass points are connected by springs or shock absorbers.

[0051] The coordinate system uses the vehicle's longitudinal direction as the x-axis, the vehicle's lateral direction as the y-axis, and the vehicle's vertical direction as the z-axis. The unsprung mass on the front and rear axle sides is denoted as m. 1f m 1r Let m2 be the mass on the spring, and z be the vertical displacement of the center of gravity 61 on the spring. 2cg Let z be the vertical displacement of the springs on each wheel.2f z 2r Let z be the vertical displacement of the spring. 1f z 1r The vertical displacement of the road surface is denoted as z. 0f z 0r Let θ denote the pitch angle of the center of gravity 61 on the spring, and let k denote the suspension spring constant. sf k sr Let the suspension damping coefficient be denoted as c. sf c sr Let l be the distance between the front and rear axles, i.e., the wheelbase. Let l be the distance between the front and rear axles in the longitudinal direction of the vehicle, up to the sprung center of gravity. f l r Let h be the height of the center of gravity 61 on the spring.

[0052] In the vehicle behavior prediction unit 22c, the model is input with road surface height-related information as part of the driving area information, and the sprung center of gravity, the sprung and unsprung vertical accelerations of each wheel, and the relative vertical displacement of the sprung and unsprung parts, i.e., the suspension travel, are calculated. In addition to the front-to-back acceleration, lateral acceleration, and vertical acceleration generated at the sprung center of gravity, the vehicle behavior-related physical quantities predicted by the vehicle behavior prediction unit 22c can also be the velocity, acceleration, jerk, angle, angular velocity, and angular acceleration of each degree of freedom of the vehicle; the vehicle behavior-related physical quantities predicted by the vehicle behavior prediction unit 22c are not limited. Furthermore, regarding the vehicle behavior-related physical quantities predicted by the vehicle behavior prediction unit 22c, predictions can be made for one velocity and one lateral movement for passing and evasive maneuvers respectively, and predictions can also be made for... Figure 3 The upper limit velocity V shown U With lower limit speed V L The prediction is performed using multiple speed candidates defined between the two sides and multiple lateral movement candidates required for avoidance defined within the width W of the drivable area. The conditions for the prediction objects of the vehicle behavior prediction unit 22c are not limited. Furthermore, in this embodiment, the case of using a front and rear wheel model considering the computational load of the vehicle behavior prediction unit 22c is summarized. However, when the unevenness of the designated area 71 traversed by the left and right wheels of the vehicle 60 is different, from the viewpoint of predicting the vertical movement accuracy, it is ideal to use a model that can consider... Figure 4 The four-wheeled vehicle model shown depicts motion along the y-axis and around the x and z axes. The methods for predicting physical quantities related to vehicle behavior are not limited.

[0053] The action extraction unit 22d takes the driving condition information output from the information acquisition unit 22a and the acceleration and other vehicle behavior-related physical quantities output from the vehicle behavior prediction unit 22c as inputs, and extracts and outputs actions below the vehicle limits from the candidates output from the vehicle behavior prediction unit 22c. Here, specific examples of vehicle limits are explained. First, regarding the vehicle's planar motion, since it is impossible to generate acceleration exceeding the vehicle performance and road friction coefficient of the engine and tires, the acceleration based on these vehicle performance and road friction coefficients becomes the vehicle limit. Furthermore, the acceleration related to the vehicle's planar motion, i.e., the planar composite acceleration, can be calculated using the square root of the front-rear acceleration and the lateral acceleration. Second, regarding the vehicle's vertical motion, the upper limit of the sprung and unsprung vertical accelerations on each wheel of the vehicle's undamaged suspension and the upper limit of the suspension travel becomes the vehicle limit. Furthermore, regarding this upper limit, for example, the sprung vertical acceleration on each wheel is approximately 1G, the unsprung vertical acceleration on each wheel is approximately 20G, and the suspension travel varies depending on the shape of the suspension, approximately 0.1m. Thus, in the action extraction unit 22d, only safe and feasible actions are extracted and output. Furthermore, if there are no actions with physical quantities related to vehicle behavior below the vehicle limit, a passing action that decelerates at the vehicle limit is extracted and output for safety reasons.

[0054] The driving trajectory generation unit 22f takes the driving status information output from the information acquisition unit 22a and the action-related information output from the action decision unit 22e as inputs to set the driving path and speed for the action determined by the action decision unit 22e, and outputs it as a driving trajectory to the driving control unit 23.

[0055] <The handling of Action Decision Department 22e>

[0056] Next, use Figure 5 The outline of the processing of the Action Decision Department 22e is explained.

[0057] First, in step S1, the action decision unit 22e acquires driving status information output from the information acquisition unit 22a, and physical quantities related to vehicle behavior output from the action extraction unit 22d, which are actions below the vehicle limit or deceleration through actions with front and rear acceleration at the vehicle limit.

[0058] Next, in step S11, the action decision unit 22e determines, based on the information obtained in step S1, whether the physical quantity related to the vehicle behavior during the travel of the avoidance path 82 is greater than a predetermined value. If it is greater than the predetermined value (yes in step S11), the process proceeds to step S12; if it is less than the predetermined value (no in step S11), the process proceeds to step S13. Here, the predetermined value can be a predetermined value set in advance considering factors such as ride quality, or a vehicle limit value based on the road friction coefficient obtained by the sensor 14, etc. The definition of the predetermined value is not limited.

[0059] In step S12, the action decision unit 22e selects maintaining the reference path 81 as the action of the vehicle 60. Furthermore, if there is not even one avoidance path 82 extracted by the action extraction unit 22d, the process also proceeds to step S12 and selects maintaining the reference path 81.

[0060] On the other hand, in step S13, the action decision unit 22e determines whether the physical quantity related to vehicle behavior at the reference path is greater than a predetermined value based on the information obtained in step S1 (step S13). If it is greater than the predetermined value (yes in step S13), it proceeds to step S14. If it is less than the predetermined value (no in step S13), it proceeds to step S15.

[0061] In step S14, the action decision unit 22e selects the transfer to the avoidance path 82 as the action of the vehicle 60. Furthermore, if there is not even one reference path 81 extracted by the action extraction unit 22d, the process also proceeds to step S14 and selects the transfer to the avoidance path 82.

[0062] On the other hand, in step S15, the action decision unit 22e determines whether the physical quantity related to vehicle behavior during the reference path is lower than the physical quantity related to vehicle behavior during the avoidance path based on the information obtained in step S1. If the former is lower than the latter (yes in step S15), the process proceeds to step S12. If the former is greater than the latter (no in step S15), the process proceeds to step S14.

[0063] Through the above processing, the action decision unit 22e selects either maintaining the baseline path 81 or transferring to the evasion path 82 as the action of the vehicle 60.

[0064] The difference between the Action Decision Department 22e and Figure 5 Processing>

[0065] Next, use Figure 6 The following is a summary of the processing procedures of the Action Decision Department 22e. Here, the discussion focuses on... Figure 5 Explain the differences, and Figure 5 Similar explanations are omitted. Furthermore, Figure 6 and Figure 5 The main difference is that the method of action selection processing has been changed from processing based on the relationship between the magnitude of physical quantities related to vehicle behavior, such as acceleration, and the specified value, to processing based on the sum of physical quantities related to vehicle behavior calculated using acceleration, etc.

[0066] First, the action decision-making unit 22e, in step S1, and Figure 5 Similarly, information output from information acquisition unit 22a and action extraction unit 22d is acquired, and in step S21, the sum of physical quantities related to vehicle behavior in the same dimension, such as acceleration, is calculated based on the acquired information.

[0067] Next, in step S22, the action decision unit 22e determines whether the sum of the physical quantities related to vehicle behavior calculated in step S21 for the reference path is less than or equal to the sum of the physical quantities related to vehicle behavior for the avoidance path (step S22). If the former is less than or equal to the latter (yes in step S22), the process proceeds to step S23 and selects to maintain the reference path 81. If the former is greater than the latter (no in step S22), the process proceeds to step S24 and selects to transfer to the avoidance path 82.

[0068] The difference between the Action Decision Department 22e and Figure 5 and Figure 6 Processing>

[0069] Next, use Figure 7 The following is a summary of the processing procedures of the Action Decision Department 22e. Here, the discussion focuses on... Figure 5 and Figure 6 Explain the differences, and Figure 5 and Figure 6 Similar explanations are omitted. Furthermore, Figure 7 and Figure 5 and Figure 6 The main difference is that the method of action selection processing has changed from the method of processing based on the relationship between the physical quantities related to vehicle behavior, such as acceleration, and the specified values, or the sum of the physical quantities related to vehicle behavior calculated using acceleration, to the method of processing action selection processing based on the evaluation values ​​calculated using acceleration, etc.

[0070] First, the action decision-making unit 22e, in step S1, and Figure 5 and Figure 6 Similarly, information output from information acquisition unit 22a and action extraction unit 22d is acquired, and in step S31, an evaluation value Q is calculated based on the acquired information using an evaluation function shown in Equation 1 or Equation 2, which takes physical quantities related to vehicle behavior such as acceleration as input.

[0071] [Formula 1]

[0072]

[0073] [Formula 2]

[0074]

[0075] Here, A, B, C, and D in (Equation 1) or (Equation 2) are weighting coefficients, and G... xm G ym G zm For the maximum acceleration (forward / backward, lateral, up / down), t m G is the time of travel caused by vehicle 60 passing through or avoiding designated area 71. xs G ys G zs For the specified acceleration values ​​(forward / backward, lateral, up / down), t s This refers to the travel time caused by vehicle 60 passing through or avoiding designated area 71 at its current speed V0. Furthermore, G shown in (Equation 1) or (Equation 2) xm The numerator of the evaluation function can be not only acceleration, but also distance, velocity, jerk, angular velocity, and angular acceleration. Furthermore, it can be not only the maximum value but also the integral value. The physical quantities related to vehicle behavior defined in the numerator of the evaluation function are not limited. In addition, G shown in (Equation 1) or (Equation 2) xs The denominator of the evaluation function can be acceleration, distance, velocity, jerk, angular velocity, or angular acceleration. In addition, it can be a predetermined value or a value based on the road surface friction coefficient, ride quality, vehicle status, etc., output from the driving area information calculation unit 22b. The coefficient related to vehicle behavior defined in the denominator of the evaluation function is not limited.

[0076] Next, in step 32, the action decision unit 22e determines whether the evaluation value of the baseline path calculated in step S31 is lower than the evaluation value of the avoidance path (step S32). If the former is lower than the latter (yes in step S32), the process proceeds to step S33 and selects to maintain the baseline path 81. If the former is greater than the latter (no in step S32), the process proceeds to step S34 and selects to transfer to the avoidance path 82.

[0077] <Effects of this embodiment>

[0078] Next, use Figure 8 and Figure 9 An example of the effect achieved by a vehicle 60 equipped with an onboard system 1 including the vehicle motion control device 2 described above will be explained. Figure 8 and Figure 9 To indicate in Figure 3 Using this embodiment under the conditions shown Figure 6The flowchart shown is a diagram illustrating the effect of the given scenario.

[0079] exist Figure 8 In the various charts, the horizontal axis represents the target velocity, and the vertical axis, from the top left, sequentially represents (a) the sum of maximum accelerations, (b) the maximum combined planar acceleration, (c) the travel time, (d) the maximum forward and backward acceleration, (e) the maximum lateral acceleration, (f) the maximum vertical acceleration, (g) the maximum sprung vertical acceleration, (h) the maximum unsprung vertical acceleration, and (i) the maximum suspension travel. Furthermore, the "white circles" and "black circles" in each chart represent data corresponding to the baseline path 81, the "white squares" and "black squares" represent data corresponding to the avoidance path, and the single-dotted line represents the specified value or upper limit value.

[0080] First, under these conditions, (b)(g)(h)(i) refers to vehicle behavior that allows safe travel on both the baseline and the avoidance path, below the upper limit that serves as the vehicle's limit. Figure 8 The two actions are "black circle" and "black square". Therefore, the action extraction unit 22d extracts these two actions.

[0081] Furthermore, regarding the sum of the maximum accelerations of these two vehicle behaviors, such as Figure 8 As shown in (a), the reference path of the "black circle" is shorter than the avoidance path of the "black square". Therefore, the action decision unit 22e decides to drive the reference path 81 at the target speed shown by the "black circle" as the action with the best ride quality.

[0082] Figure 9 To indicate Figure 8 The selected chart of vehicle behavior shows (a) speed, (b) front-to-rear acceleration, (c) vertical displacement of the road surface (front wheel side), and (d) changes in vertical acceleration relative to distance. Figure 9 The single-dot dashed line indicates the upper and lower limits of the specified range. When passing through the specified area 71 shown in (c), the forward and backward acceleration and lateral acceleration generated are within the specified range as shown in (b) and (d), which can generate a travel track that safely achieves the set ride quality.

[0083] The difference between the Action Decision Department 22e and Figures 5-7 An example of a flowchart

[0084] Next, use Figure 10 The following is a summary of the processing procedures of the Action Decision Department 22e. Here, the discussion focuses on... Figures 5-7 Explain the differences, and Figures 5-7 Similar explanations are omitted. Furthermore, Figure 10 and Figures 5-7The main difference is that it adds processing for selecting actions corresponding to the movement time priority mode in the driving mode set in the operation management unit 21.

[0085] First, in step S1, the action decision unit 22e and Figures 5-7 Similarly, information output from the information acquisition unit 22a and the action extraction unit 22d is acquired.

[0086] Next, in step S41, the action decision unit 22e determines whether the driving mode set in the operation management unit 21 is a travel time priority mode. If the driving mode is a travel time priority mode (yes in step S41), it proceeds to step S42 to select the shortest action. If the driving mode is not a travel time priority mode, it proceeds to step S43 to perform action selection processing. In step S43, the following steps are performed: Figure 5 The example routine R1 shown Figure 6 The example shown is R2 or Figure 7 The example shown in routine R3 handles any action selection. Furthermore, for example, in the case of... Figure 8 Under the same circumstances, the action with the shortest time selected in step S42 will be below the vehicle's limit and Figure 8 (c) The evasion path shown by the "black square" with the minimum movement time.

[0087] The above is an example of the method for generating a travel trajectory for a vehicle as a target and the method for controlling vehicle motion in this invention. By using an onboard system 1 that includes a vehicle motion control device 2 with such a configuration, it is possible to achieve a comfortable ride and high safety with low physical quantities related to vehicle behavior, such as front-to-back acceleration, lateral acceleration, and vertical acceleration, when passing through or avoiding a designated area on the vehicle's path of travel.

[0088] Symbol Explanation

[0089] 1…Onboard system, 2…Vehicle motion control device, 21…Operation management unit, 22…Trajectory generation unit, 22a…Information acquisition unit, 22b…Traffic area information processing unit, 22c…Vehicle behavior prediction unit, 22d…Action extraction unit, 22e…Action decision unit, 22f…Trajectory generation unit, 23…Traffic control unit, 3…Powertrain system, 4…Braking system, 5…Steering system, 11…External communication device, 12…GNSS, 13…Map information storage unit, 14…Sensor, 15…HMI unit, 60…Vehicle, 70…Road surface, 71…Designated area, 81…Base path, 82…Avoidance path.

Claims

1. A vehicle motion control device, characterized in that, have: The vehicle behavior prediction unit predicts the vehicle behavior-related physical quantities generated when the vehicle maintains a baseline path toward a specified area on the road ahead and the vehicle behavior-related physical quantities generated when the vehicle moves to an avoidance path to avoid the specified area. as well as The track generation unit generates a travel track defined by the reference path or the avoidance path, where the physical quantity is less than a predetermined value. The track generation unit generates the sum of the physical quantities to form the minimum travel track. When the sum of physical quantities related to vehicle behavior generated while maintaining the reference path is equal to the sum of physical quantities related to vehicle behavior generated while transferring to the avoidance path, the track generation unit generates a travel track that maintains the reference path.

2. The vehicle motion control device according to claim 1, characterized in that, If both the physical quantities related to vehicle behavior generated when maintaining the baseline path and the physical quantities related to vehicle behavior generated when transferring to the avoidance path are greater than a predetermined value, the track generation unit generates a travel track that passes through the baseline path and minimizes the physical quantities.

3. The vehicle motion control device according to claim 1, characterized in that, The physical quantity is any one of time, displacement, velocity, acceleration, jerk, angle, angular velocity, and angular acceleration.

4. The vehicle motion control device according to claim 3, characterized in that, The acceleration can be any one of forward / backward acceleration, lateral acceleration, or vertical acceleration.

5. The vehicle motion control device according to claim 3, characterized in that, The physical quantity is the maximum value or integral value.

6. A vehicle motion control method, characterized in that, The following steps are required: Physical quantities related to vehicle behavior that are predicted when a vehicle maintains a baseline path toward a designated area on its path of progress. The physical quantities related to vehicle behavior that are predicted when the vehicle moves to an avoidance path to avoid the designated area; as well as Generate a travel trajectory defined by the reference path or the avoidance path where the physical quantity is less than a specified value. The vehicle motion control method further includes: The sum of the physical quantities generated becomes the minimum travel trajectory. If the sum of the physical quantities related to vehicle behavior generated when maintaining the baseline path is equal to the sum of the physical quantities related to vehicle behavior generated when transferring to the avoidance path, a driving trajectory that maintains the baseline path is generated.

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