Control method for vehicle, and vehicle and storage medium

Abstract

A control method for a vehicle (301), and a vehicle (301) and a storage medium. The control method for a vehicle (301) comprises: on the basis of a target driving requirement, determining a target driving trajectory from among at least one driving trajectory, wherein the at least one driving trajectory is a driving trajectory of the vehicle (301) on a road that is obtained by performing prediction by means of a vehicle motion prediction model and on the basis of road parameters, and the vehicle motion prediction model is configured to predict a driving trajectory of the vehicle (301) in a motion state; and controlling the vehicle (301) to drive along the target driving trajectory.

Description

Control method of vehicle, vehicle and storage medium

[0001] This application claims priority to Chinese Patent Application No. 202411048585.4, filed on July 31, 2024, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD

[0002] The present disclosure relates to the technical field of vehicles, and in particular to a control method of a vehicle, a vehicle and a storage medium. BACKGROUND

[0003] With the rapid and continuous updating of science and technology in China, automatic driving technology has become a research hotspot in the current automobile industry. The key to vehicle automatic driving lies in the planning of the automatic driving trajectory at the future time. Therefore, the trajectory planning technology in the automatic driving field is crucial for realizing safe, efficient and natural driving behavior. SUMMARY

[0004] The present disclosure provides a control method of a vehicle, a vehicle and a storage medium, which solves the problem that the trajectory planning scheme in the related art cannot plan a vehicle trajectory according to specific requirements and has poor applicability, and can improve the applicability of the vehicle driving trajectory scheme and enable the vehicle to drive based on target driving requirements.

[0005] In a first aspect, a control method of a vehicle is provided, which includes: determining a target driving trajectory in at least one driving trajectory based on a target driving requirement; the at least one driving trajectory is a driving trajectory of the vehicle in a road predicted based on a road parameter through a vehicle motion prediction model; the vehicle motion prediction model is configured to predict a driving trajectory of the vehicle in a motion state; and controlling the vehicle to drive according to the target driving trajectory.

[0006] In some embodiments, the target driving requirement is one or more of preset driving requirements; and the preset driving requirements include at least one of the following: maximum driving speed, shortest driving time, shortest driving distance, minimum curvature of the driving trajectory, most stable driving state of the vehicle during driving, or highest similarity to an original driving trajectory.

[0007] In some embodiments, determining the target driving trajectory in the at least one driving trajectory based on the preset driving requirement includes: determining, for each driving trajectory in the at least one driving trajectory, a matching degree of the each driving trajectory to the preset driving requirement; and determining the driving trajectory with the maximum matching degree as the target driving trajectory.

[0008] In some embodiments, the method further includes: constructing the vehicle motion prediction model based on a driving state parameter and a motion control parameter of the vehicle.

[0009] In some embodiments, the vehicle motion prediction model is constructed based on the driving state parameters and the motion control parameters, including: constructing a vehicle dynamics model of the vehicle based on the driving state parameters; constructing the vehicle motion prediction model based on the vehicle dynamics model and the motion control parameters.

[0010] In some embodiments, the step of determining at least one driving trajectory includes: determining a drivable range of the vehicle in the road based on the road parameters; constraining the vehicle motion prediction model based on the drivable range and the trajectory constraint conditions to determine at least one driving trajectory.

[0011] In some embodiments, the control of the vehicle to travel according to the target driving trajectory includes: determining target control amounts of the respective actuators in the vehicle based on the target driving trajectory; the target control amount is a control amount performed by one of the respective actuators when the vehicle travels according to the target driving trajectory; sending the target control amounts to the respective actuators in the vehicle through the chassis drive-by-wire execution system of the vehicle, so that the respective actuators perform the target control amounts to control the vehicle to travel according to the target driving trajectory.

[0012] In some embodiments, the determination of the target control amounts of the respective actuators in the vehicle based on the target driving trajectory includes: obtaining a real-time motion state of the vehicle; correcting the target driving trajectory based on the real-time motion state through the vehicle motion prediction model to obtain a corrected target driving trajectory; determining the target control amounts of the respective actuators in the vehicle based on the corrected target driving trajectory.

[0013] In some embodiments, the motion control parameters of the vehicle include at least one of: a motor torque of the vehicle or a wheel angle of the vehicle.

[0014] In some embodiments, when the vehicle is configured with a first motor, a second motor, a third motor, a first steering device and a second steering device, the motion control parameters include at least one of: a first motor torque of the vehicle, a second motor torque of the vehicle, a third motor torque of the vehicle, a front wheel equivalent angle, a left rear wheel angle and a right rear wheel angle; the first motor is configured to drive the left front wheel and the right front wheel of the vehicle, the second motor is configured to drive the left rear wheel of the vehicle, and the third motor is configured to drive the right rear wheel of the vehicle; the first steering device is configured to control the steering of the left rear wheel of the vehicle, and the second steering device is configured to control the steering of the right rear wheel of the vehicle.

[0015] In some embodiments, the driving state parameter of the vehicle comprises at least one of the following: position information of the vehicle, longitudinal speed, lateral speed, body heading angle, yaw rate, mass, longitudinal force each wheel receives in a ground coordinate system, lateral force each wheel receives in the ground coordinate system, whole vehicle rotational inertia, distance from the vehicle center of mass to the front axle, distance from the vehicle center of mass to the rear axle, front wheel track, rear wheel track, wheel angle, longitudinal force each wheel receives in a wheel coordinate system, or lateral force each wheel receives in the wheel coordinate system.

[0016] In some embodiments, the road parameter comprises at least one of the following: road center point position, road width at the center point, and position information of obstacles in the road.

[0017] In some embodiments, the trajectory constraint comprises at least one of the following: vehicle motion state constraint, and motion control parameter increment constraint.

[0018] In a second aspect, a control device of a vehicle is provided, comprising: a processing unit; the processing unit is configured to determine a target driving trajectory from at least one driving trajectory based on a target driving demand; the at least one driving trajectory is a driving trajectory of the vehicle in a road predicted by a vehicle motion prediction model based on a road parameter; the vehicle motion prediction model is configured to predict a driving trajectory of the vehicle in a motion state; and the processing unit is further configured to control the vehicle to drive according to the target driving trajectory.

[0019] In some embodiments, the target driving demand is one or more of preset driving demands; and the preset driving demand comprises at least one of the following: maximum driving speed of the vehicle at a preset position, shortest driving time, shortest driving distance, minimum curvature of the driving trajectory, most stable driving state of the vehicle during driving, and highest similarity to an original driving trajectory.

[0020] In some embodiments, the processing unit is further configured to: determine, for each driving trajectory, a matching degree of the driving trajectory to the preset driving demand; and determine the driving trajectory with the largest matching degree as the target driving trajectory. In an implementation form of the above-mentioned second aspect, the processing unit is further configured to: construct the vehicle motion prediction model based on a driving state parameter of the vehicle and a motion control parameter.

[0021] In some embodiments, the processing unit is further configured to: construct a vehicle dynamics model of the vehicle based on the driving state parameter; and construct the vehicle motion prediction model based on the vehicle dynamics model and the motion control parameter.

[0022] In some embodiments, the processing unit is further configured to determine, based on the road parameter, a drivable range of the vehicle in the road, and constrain the vehicle motion prediction model based on the drivable range and the trajectory constraint condition to determine the at least one driving trajectory.

[0023] In some embodiments, the apparatus further comprises a communication unit, and the processing unit is further configured to determine, based on the target driving trajectory, target control amounts of respective actuators in the vehicle, the target control amount being a control amount performed by one of the respective actuators when the vehicle drives according to the target driving trajectory, and the communication unit is configured to send the target control amounts to the respective actuators in the vehicle through a chassis-by-wire execution system of the vehicle, so that the respective actuators perform the target control amounts to control the vehicle to drive according to the target driving trajectory.

[0024] In some embodiments, the processing unit is further configured to instruct the communication unit to acquire a real-time motion state of the vehicle, and correct the target driving trajectory based on the real-time motion state by the vehicle motion prediction model to obtain a corrected target driving trajectory, and determine target control amounts of respective actuators in the vehicle based on the corrected target driving trajectory.

[0025] In some embodiments, the motion control parameter comprises at least one of a motor torque of the vehicle and a wheel angle of the vehicle.

[0026] In some embodiments, when the vehicle is configured with a first motor, a second motor, a third motor, a first steering device and a second steering device, the motion control parameter comprises at least one of a first motor torque, a second motor torque, a third motor torque, a front wheel equivalent angle, a left rear wheel angle and a right rear wheel angle of the vehicle, the first motor is configured to drive a left front wheel and a right front wheel of the vehicle, the second motor is configured to drive a left rear wheel of the vehicle, and the third motor is configured to drive a right rear wheel of the vehicle, the first steering device is configured to control the left rear wheel to steer, and the second steering device is configured to control the right rear wheel to steer.

[0027] In some embodiments, the driving state parameter comprises at least one of position information, a longitudinal speed, a lateral speed, a body heading angle, a yaw rate, a mass, a longitudinal force received by each wheel in a ground coordinate system, a lateral force received by each wheel in the ground coordinate system, a total vehicle moment of inertia, a distance from a vehicle center of mass to a front axle, a distance from the vehicle center of mass to a rear axle, a front wheel track, a rear wheel track, a wheel angle, a longitudinal force received by a wheel in a wheel coordinate system and a lateral force received by the wheel in the wheel coordinate system of the vehicle.

[0028] In some embodiments, the road parameter comprises at least one of a road center point position, a road width at the center point and position information of an obstacle in the road.

[0029] In some embodiments, the trajectory constraint condition comprises at least one of the following: a vehicle motion state constraint condition and a motion control parameter increment constraint condition.

[0030] In some embodiments, the preset driving demand further comprises at least one of the following: shortest driving time, shortest driving distance, smallest curvature of the driving trajectory, most stable driving state of the vehicle during driving, and highest similarity to the original driving trajectory.

[0031] In a third aspect, a vehicle is provided, the apparatus comprising: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is configured to run computer programs or instructions to implement the control method of the vehicle as described above.

[0032] In some embodiments, the vehicle further comprises: a first motor, a second motor, and a third motor; the first motor is configured to drive the left front wheel and the right front wheel of the vehicle, the second motor is configured to drive the left rear wheel of the vehicle, and the third motor is configured to drive the right rear wheel of the vehicle.

[0033] In some embodiments, the vehicle further comprises a first steering device and a second steering device; the first steering device is configured to control the steering of the left rear wheel, and the second steering device is configured to control the steering of the right rear wheel.

[0034] In a fourth aspect, a computer readable storage medium is provided, the computer readable storage medium stores instructions, when the instructions are run on a terminal, the terminal executes the control method of the vehicle as described above.

[0035] In a fifth aspect, a computer program product containing instructions is provided, when the computer program product is run on a computer, the computer executes the control method of the vehicle as described above.

[0036] In a sixth aspect, a chip is provided, the chip comprising a processor and a communication interface, the communication interface and the processor are coupled, and the processor is configured to run computer programs or instructions to implement the control method of the vehicle as described above.

[0037] The chip of some embodiments of the present disclosure further comprises a memory configured to store computer programs or instructions.

[0038] It should be noted that the above computer instructions can be stored on the computer readable storage medium in whole or in part. The computer readable storage medium is packaged together with the processor of the apparatus, or packaged separately from the processor of the apparatus.

[0039] In a seventh aspect, a control system of a vehicle is provided, comprising: a vehicle and a data server, the data server is configured to execute the control method of the vehicle as described above.

[0040] Some embodiments of the present disclosure provide a vehicle control method. A target driving trajectory is determined based on a target driving demand from at least one driving trajectory. The at least one driving trajectory is a driving trajectory of a vehicle on a road predicted by a vehicle motion prediction model based on road parameters, and the vehicle motion prediction model is used to predict a driving trajectory of the vehicle in a motion state. The vehicle is controlled to drive according to the target driving trajectory. The above technical solution can determine a suitable driving trajectory according to different target driving demands, solve the problem that the trajectory planning scheme in the related art can only plan a driving trajectory of a vehicle based on curvature, path distance or some constraints, and cannot plan a vehicle trajectory according to specific requirements, and improve the applicability of the vehicle driving trajectory scheme and enable the vehicle to drive according to the target driving demand. BRIEF DESCRIPTION OF DRAWINGS DETAILED DESCRIPTION BRIEF DESCRIPTION OF DRAWINGS

[0041] FIG. 1 is a flowchart of a racing vehicle driving trajectory optimization method in the related art;

[0042] FIG. 2 is a flowchart of a trajectory tracking control method in the related art;

[0043] FIG. 3 is a schematic diagram of an architecture of a vehicle control system according to some embodiments;

[0044] FIG. 4 is a schematic diagram of a vehicle motor according to some embodiments;

[0045] FIG. 5 is a schematic diagram of a vehicle steering device according to some embodiments;

[0046] FIG. 6 is a schematic diagram of a vehicle control method according to some embodiments;

[0047] FIG. 7 is a schematic diagram of a hardware structure of a vehicle according to some embodiments;

[0048] FIG. 8 is a flowchart of a vehicle control method according to some embodiments;

[0049] FIG. 9 is a flowchart of another vehicle control method according to some embodiments;

[0050] FIG. 10 is a flowchart of yet another vehicle control method according to some embodiments;

[0051] FIG. 11 is a flowchart of yet another vehicle control method according to some embodiments;

[0052] FIG. 12 is a schematic diagram of yet another vehicle control method according to some embodiments;

[0053] FIG. 13 is a schematic diagram of a vehicle control device according to some embodiments. DETAILED DESCRIPTION

[0054] The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present disclosure.

[0055] The term "and / or" in the present disclosure is only used to describe the association relationship of the associated objects, which means that there can be three relationships, for example, A and / or B can represent three cases of A alone, A and B together, and B alone.

[0056] The terms "first" and "second" and the like in the description of the present disclosure and the drawings are used to distinguish different objects or different treatments of the same object, rather than to describe a specific order of the objects.

[0057] In addition, the terms "include" and "have" and any variations thereof mentioned in the description of the present disclosure are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units is not limited to the listed steps or units, but also includes other steps or units not listed or other steps or units inherent to the process, method, product or device.

[0058] It should be noted that in some embodiments of the present disclosure, the words "exemplary" or "for example" are used to mean serving as an example, instance, or illustration. Any embodiment or design described as "exemplary" or "for example" in some embodiments of the present disclosure should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of "exemplary" or "for example" is intended to present concepts in a concrete manner.

[0059] In the description of the present disclosure, "a plurality of" means two or more, unless otherwise specified.

[0060] With the rapid and continuous updating and iteration of science and technology in China, automatic driving technology has become a research hotspot in the current automobile industry. The key to vehicle automatic driving is the planning of the automatic driving trajectory at the future time. Therefore, the trajectory planning technology in the automatic driving field is crucial for realizing safe, efficient and natural driving behavior.

[0061] In the related art, the trajectory planning technology used in the automatic driving field is mostly based on curvature, path distance or some constraint conditions to plan the trajectory of the vehicle, for example, to plan the minimum curvature path or the shortest distance trajectory.

[0062] For example, as shown in FIG. 1, in a racing vehicle trajectory optimization method, a time-consuming shortest speed curve is determined according to an initial racing vehicle path and a tire adhesion limit constraint; and a curvature minimum path is determined according to the time-consuming shortest speed curve, the tire adhesion limit constraint, and a vehicle motion state.

[0063] However, the limitation of such a trajectory planning scheme lies in that the trajectory planning process thereof is to first determine a time-consuming shortest speed curve, and then determine a curvature minimum path based on the time-consuming shortest speed curve, which cannot plan a vehicle trajectory according to specific requirements, and the applicability is poor. For example, for a moose test working condition, such a trajectory planning scheme cannot plan a vehicle driving trajectory with the fastest driving speed; or for an emergency lane changing working condition, such a trajectory planning scheme also cannot plan a vehicle driving trajectory with other targets.

[0064] Moreover, the trajectory planning and tracking technology in the related art only considers a single power driving system and a single front wheel steering system, and the upper limit of the vehicle state change speed limits the optimization of the trajectory planning, so that the trajectory obtained thereby is difficult to meet the actual requirements; and for a trajectory with a fast system state change, the tracking effect is poor, and a large deviation is prone to occur.

[0065] For example, as shown in FIG. 2, in a trajectory tracking control method, a steering angle increment weight of a vehicle at a current time is determined according to a current lateral speed and a current longitudinal speed of the vehicle at the current time, and a desired lateral speed and a desired longitudinal speed of the vehicle at a next time; a trajectory tracking error of the vehicle is determined according to a desired lateral displacement of the vehicle, a desired heading angle of the vehicle, a running state parameter of the vehicle at the current time, and the steering angle increment weight, with the steering angle increment as a parameter; a steering angle increment is calculated with the minimum trajectory tracking error as a target; and a target wheel steering angle of the vehicle at the next time is obtained by adding the current vehicle steering angle and the steering angle increment, so that the vehicle drives according to the target wheel steering angle.

[0066] In the above scheme, the control quantity is only the front wheel steering angle, and the rear wheel steering angle control problem is not considered, which is not applicable to a vehicle with a rear wheel independent control system.

[0067] In view of this, some embodiments of the present disclosure provide a vehicle control method, which determines a target driving trajectory in at least one driving trajectory based on a target driving requirement. The at least one driving trajectory is a driving trajectory of a vehicle on a road predicted by a vehicle motion prediction model based on road parameters, and the vehicle motion prediction model is used to predict a driving trajectory of the vehicle in a motion state. Moreover, the vehicle is controlled to drive according to the target driving trajectory.

[0068] The technical solution can determine a suitable driving track according to different target driving requirements, solve the problem that the track planning scheme in the related art can only plan a driving track of a vehicle based on curvature, path distance or some constraint conditions, and cannot plan a vehicle track according to specific requirements, and improve the applicability of the vehicle driving track scheme and enable the vehicle to drive according to the target driving requirements.

[0069] The embodiments of some embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0070] FIG. 3 is a schematic diagram of an architecture of a control system of a vehicle according to some embodiments. As shown in FIG. 3, the control system of the vehicle includes a vehicle 301 and a data server 302.

[0071] The vehicle 301 and the data server 302 are connected through a communication link. The communication link can be a wired communication link or a wireless communication link, which is not limited in the present disclosure.

[0072] Next, the vehicle 301 will be introduced.

[0073] In an implementation manner, the vehicle 301 is configured to send position information collected by a plurality of vehicle-mounted sensors in the vehicle 301 to the data server 302, so that the data server 302 can determine the relative position of the vehicle 301 in the road based on the position information collected by the plurality of vehicle-mounted sensors.

[0074] In some embodiments, the vehicle 301 is configured with vehicle-mounted sensors such as a camera, a laser radar, a millimeter wave radar, an ultrasonic radar, and an inertial measurement unit (IMU). Through fusion of information collected by the plurality of vehicle-mounted sensors, the relative position of the vehicle 301 in the road can be obtained.

[0075] Of course, the above is only an example of obtaining the relative position of the vehicle 301 in the road, and some embodiments of the present disclosure can also obtain the relative position of the vehicle 301 in the road in other ways, for example, through data collected by any one or more of an attitude and heading reference system (AHRS), a vertical reference unit (VRU), a global navigation satellite system (GNSS), a global positioning system (GPS), a Beidou satellite navigation system (BDS), or an inertial navigation system (INS), etc. to determine the relative position of the vehicle 301 in the road, which is not limited by the present disclosure.

[0076] In some embodiments, as shown in FIGS. 3 and 4, the vehicle 301 is configured with a first motor, a second motor, and a third motor. The first motor is configured to drive the left front wheel and the right front wheel of the vehicle 301, the second motor is configured to drive the left rear wheel of the vehicle, and the third motor is configured to drive the right rear wheel of the vehicle.

[0077] In some embodiments, as shown in FIGS. 3 and 5, the vehicle 301 is further configured with a first steering device and a second steering device. The first steering device is configured to control the left rear wheel to steer, and the second steering device is configured to control the right rear wheel to steer.

[0078] In addition, the vehicle 301 is further configured with a third steering device. The third steering device is configured to control the left front wheel and the right front wheel of the vehicle 301 to steer.

[0079] It should be noted that the rear wheel independent steering system in some embodiments of the present disclosure can increase the speed change of the vehicle 301, increase the optimization potential of trajectory planning, and make the obtained trajectory more in line with actual needs. In addition, different lateral forces and yaw moments are applied to the vehicle 301 through the rear wheel steering device to improve the control effect of the vehicle. Furthermore, based on the three-motor independent driving system, the torque of the left rear wheel and the right rear wheel is driven by independent motors, which can generate additional yaw moments for the vehicle, further improving the control effect.

[0080] In some embodiments, the vehicle 301 in some embodiments of the present disclosure is not limited to the three drive mode, but can also be a four drive mode or a two drive mode. Of course, the above is only an exemplary description of the vehicle drive mode, and as the number of vehicle wheels increases, the vehicle 301 can also be a five drive mode, a six drive mode, etc. The drive mode of the vehicle can be proportional to the number of vehicle wheels, and the present disclosure does not limit this.

[0081] Next, the vehicle 301 in the four drive mode is introduced.

[0082] In an implementation manner, the vehicle 301 in some embodiments of the present disclosure can also be a four drive mode. The vehicle 301 can be configured with four motors, for example, a fourth motor, a fifth motor, a second motor, and a third motor.

[0083] The fourth motor is configured to drive the front left wheel of the vehicle 301; the fifth motor is configured to drive the front right wheel of the vehicle 301; the second motor is configured to drive the rear left wheel of the vehicle; and the third motor is configured to drive the rear right wheel of the vehicle.

[0084] Next, the vehicle 301 in the two drive mode is introduced.

[0085] In addition, the vehicle 301 in some embodiments of the present disclosure can also be a two drive mode. The vehicle 301 can also be configured with two motors, for example, a first motor and a sixth motor.

[0086] The first motor is configured to drive the front left wheel and the front right wheel of the vehicle 301, and the sixth motor is configured to drive the rear left wheel and the rear right wheel of the vehicle 301.

[0087] In some embodiments, the vehicle 301 in the following embodiments of the present disclosure is not limited to the three steering mode, but can also be a four steering mode or a two steering mode. Of course, the above is only an exemplary description of the vehicle steering mode, and as the number of vehicle wheels increases, the vehicle 301 can also be a five steering mode, a six steering mode, etc. The steering mode of the vehicle can be proportional to the number of vehicle wheels, and the present disclosure does not limit this.

[0088] Next, the vehicle 301 in the four steering mode is introduced.

[0089] In an implementation manner, the vehicle 301 in some embodiments of the present disclosure can also be configured with a fourth steering device, a fifth steering device, a first steering device, and a second steering device.

[0090] The fourth steering device is configured to control steering of the left front wheel of the vehicle 301, the fifth steering device is configured to control steering of the right front wheel of the vehicle 301, the first steering device is configured to control steering of the left rear wheel of the vehicle 301, and the second steering device is configured to control steering of the right rear wheel of the vehicle 301.

[0091] Hereinafter, the vehicle 301 in the double steering mode is introduced.

[0092] In an implementation manner, the vehicle 301 in some embodiments of the present disclosure can further comprise a third steering device and a sixth steering device.

[0093] The third steering device is configured to control steering of the left front wheel and the right front wheel of the vehicle 301, and the sixth steering device is configured to control steering of the left rear wheel and the right rear wheel of the vehicle 301.

[0094] Hereinafter, the data server 302 is introduced.

[0095] In an implementation manner, as shown in FIG. 6, the data server 302 is configured to receive position information collected by a plurality of vehicle-mounted sensors in the vehicle 301, and determine a relative position of the vehicle 301 in a road based on the position information collected by the plurality of vehicle-mounted sensors through positioning perception technology, and determine a centroid drivable region of the vehicle in response to input operations of a test personnel for vehicle size information and road parameters (for example, test road boundaries).

[0096] In some embodiments, the data server 302 is further configured to construct a vehicle dynamics model based on a driving state parameter of the vehicle, and construct a vehicle motion prediction model based on a motion control parameter (for example, a first motor torque, a second motor torque, a third motor torque, a front wheel equivalent steering angle, a left rear wheel steering angle, and a right rear wheel steering angle of the vehicle, etc.).

[0097] In some embodiments, the vehicle motion prediction model is constrained based on the centroid drivable region of the vehicle, the trajectory constraint condition, and a preset driving requirement, to determine a target driving trajectory. Then, the target control amount of each actuator in the vehicle 301 is determined based on the target driving trajectory.

[0098] In some embodiments, the road parameters (for example, boundary information of the road, position of the road center point, road width at the center point, and position information of obstacles in the road, etc.) can also be preconfigured information in the data server 302.

[0099] When implemented by hardware, each module in the data server 302 can be integrated on a hardware structure of the vehicle as shown in FIG. 7 to be implemented. As shown in FIG. 7, the basic hardware structure of the vehicle is introduced.

[0100] FIG. 7 is a hardware schematic diagram of a vehicle according to some embodiments. As shown in FIG. 7, the vehicle includes at least one processor 701, a communication line 702, and at least one communication interface 704, and can further include a memory 703. The processor 701, the memory 703, and the communication interface 704 can be connected through the communication line 702.

[0101] The processor 701 can be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to perform one or more of the steps of the embodiments of the present disclosure, such as one or more digital signal processors (DSPs), or one or more field programmable gate arrays (FPGAs).

[0102] The communication line 702 can include a path for transmitting information between the above-mentioned components.

[0103] The communication interface 704, configured to communicate with other devices or communication networks, can use any transceiver-like mechanism, such as an Ethernet, a radio access network (RAN), a wireless local area networks (WLAN), etc.

[0104] The memory 703 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disk storage, a magnetic disk storage or other magnetic storage devices, or any other medium capable of storing desired program code in the form of instructions or data structures and that can be accessed by a computer, but not limited to.

[0105] In one design, the memory 703 can be independent of the processor 701, i.e., the memory 703 can be an external memory of the processor 701, in which case the memory 703 can be connected to the processor 701 via the communication line 702 and configured to store execution instructions or application codes and controlled by the processor 701 to perform the control method of the vehicle provided by the embodiments of the present disclosure.

[0106] In yet another design, the memory 703 can also be integrated with the processor 701, i.e., the memory 703 can be an internal memory of the processor 701, for example, the memory 703 can be a cache configured to temporarily store some data and instruction information, etc.

[0107] In one implementation, the processor 701 can include one or more CPUs, such as the CPU0 and the CPU1 in FIG. 7. In another implementation, the vehicle can include multiple processors, such as the two processors 701 in FIG. 7. In yet another implementation, the vehicle can also include the output device 705 and the input device 706.

[0108] It should be noted that the embodiments of the present disclosure can be mutually referenced or referred to each other, for example, the same or similar steps, method embodiments, system embodiments, and device embodiments can be mutually referenced, without limitation.

[0109] FIG. 8 is a flowchart of a control method of a vehicle according to some embodiments, which can be applied to the vehicle as shown in FIG. 7. As shown in FIG. 8, the method includes the following S801-S802.

[0110] S801, determining a target driving trajectory in at least one driving trajectory based on a target driving demand.

[0111] In some embodiments, the preset driving demand can include at least one of the following: maximum driving speed of the vehicle at a preset position, shortest driving time, shortest driving distance, minimum curvature of the driving trajectory, and maximum average speed. Of course, the above is only an exemplary description of the preset driving demand, and the preset driving demand can also include other demands, such as the most stable driving state of the vehicle during driving and the highest similarity to the original driving trajectory, which are not limited by the present disclosure.

[0112] It should be noted that the target driving demand is one or more of the preset driving demands, which are not limited by the present disclosure. For example, the target driving demand can be the maximum driving speed of the vehicle at the preset position, the target driving demand can also be the shortest driving time and the shortest driving distance, and the target driving demand can also be the maximum driving speed of the vehicle at the preset position, the shortest driving time, the shortest driving distance, and the minimum curvature of the driving trajectory.

[0113] In an implementation manner, for each driving trajectory, a matching degree of the driving trajectory to the target driving demand is determined; and a driving trajectory with the maximum matching degree is determined as the target driving trajectory.

[0114] Hereinafter, the process of determining the target driving trajectory in different cases is introduced through Example 1-Example 3 respectively. Example 1, in the case that the target driving demand is the maximum driving speed of the vehicle at the preset position, the target driving trajectory is determined; Example 2, in the case that the target driving demand is the maximum average speed, the target driving trajectory is determined; Example 3, in the case that the target driving demand is the maximum driving speed of the vehicle at the preset position and the most stable driving state of the vehicle in the driving process, the target driving trajectory is determined.

[0115] Example 1, in the case that the target driving demand is the maximum driving speed of the vehicle at the preset position, the matching degree of the driving trajectory to the preset driving demand is the driving speed of the vehicle at the preset position; the implementation manner of S801 is: for each driving trajectory, the driving speed of the vehicle at the preset position is determined; and the driving trajectory with the maximum driving speed is determined as the target driving trajectory.

[0116] For example, in the unmanned elk speed test scene, for each driving trajectory, the maximum speed at the preset position (x=x0) is determined, that is, maxv(x=x0). All driving trajectories are traversed offline, and the driving trajectory with the maximum driving speed is determined as the target driving trajectory, denoted as ξ r (k).

[0117] Exemplarily, taking the driving trajectories including driving trajectory A, driving trajectory B and driving trajectory C as an example. The speed a of the vehicle at the preset position in the driving trajectory A, the speed b of the vehicle at the preset position in the driving trajectory B and the speed c of the vehicle at the preset position in the driving trajectory C are determined respectively. If the speed a> the speed b, and the speed a> the speed c, the driving trajectory A corresponding to the speed a is determined as the target driving trajectory.

[0118] Example 2, in the case that the target driving demand is the maximum average speed, the matching degree of the driving trajectory to the preset driving demand is the average driving speed of the vehicle in the driving process; the implementation manner of S801 is: for each driving trajectory, the average driving speed of the vehicle in each driving trajectory is determined. The driving trajectory with the maximum average driving speed is determined as the target driving trajectory.

[0119] In Example 3, in a case where the target driving demand is that the driving speed of the vehicle at the preset position is maximum and the driving state of the vehicle during driving is most stable, the matching degree of the driving trajectory to the preset driving demand is the driving speed of the vehicle at the preset position and the driving state of the vehicle during driving; and the implementation of S801 is: determining, for each driving trajectory, the driving speed of the vehicle at the preset position and the driving state of the vehicle during driving; and determining the driving trajectory with the maximum driving speed at the preset position and the most stable driving state as the target driving trajectory.

[0120] In some embodiments, before S801, at least one driving trajectory of the vehicle in the road is predicted based on the road parameters by using a vehicle motion prediction model.

[0121] The road parameters include at least one of the following: the position of the road center point, the road width at the center point, and the position information of the obstacles in the road. The vehicle motion prediction model is configured to predict the driving trajectory of the vehicle in the motion state.

[0122] In an implementation, the process of determining the at least one driving trajectory can be: determining the drivable range of the vehicle in the road based on the road parameters; and determining the at least one driving trajectory by constraining the vehicle motion prediction model based on the drivable range and the trajectory constraint condition.

[0123] The trajectory constraint condition includes at least one of the following: a vehicle motion state constraint condition or a motion control parameter increment constraint condition.

[0124] The process of determining the at least one driving trajectory is described with reference to the embodiments of S1003-S1004 shown in FIG. 10, which will not be repeated here.

[0125] S802, controlling the vehicle to drive according to the target driving trajectory.

[0126] In an implementation, based on the target driving trajectory, the target control amount of each actuator in the vehicle is determined, and the target control amount is sent to each actuator in the vehicle through the chassis-by-wire execution system of the vehicle, so that each actuator executes the target control amount to control the vehicle to drive according to the target driving trajectory.

[0127] The process of controlling the vehicle to drive according to the target driving trajectory is described with reference to the embodiments of S1101-S1102 shown in FIG. 11, which will not be repeated here.

[0128] Based on the technical solution, the control method of the vehicle according to some embodiments of the present disclosure determines a target driving trajectory in at least one driving trajectory based on a target driving demand. The at least one driving trajectory is a driving trajectory of the vehicle in the road predicted by a vehicle motion prediction model based on road parameters, and the vehicle motion prediction model is used to predict the driving trajectory of the vehicle in the motion state. In addition, the vehicle is controlled to drive according to the target driving trajectory. The above technical solution can determine a suitable driving trajectory according to different target driving demands, solve the problem that the trajectory planning scheme in the related art can only plan the driving trajectory of the vehicle based on the curvature, the path distance or some constraint conditions, and cannot plan the vehicle trajectory according to the specific demand, and has poor applicability, improve the applicability of the vehicle driving trajectory scheme, and enable the vehicle to drive according to the target driving demand.

[0129] As an embodiment of the present disclosure, as shown in FIG. 9, before S801, the implementation manner of constructing the vehicle motion prediction model can be implemented through the following S901.

[0130] S901, constructing a vehicle motion prediction model based on driving state parameters and motion control parameters of the vehicle.

[0131] The vehicle motion prediction model is configured to predict the driving trajectory of the vehicle in the motion state.

[0132] In some embodiments, the driving state parameters include at least one of the following: position information of the vehicle, longitudinal speed, lateral speed, body heading angle, yaw rate, mass, longitudinal force received by each wheel in a ground coordinate system, lateral force received by each wheel in the ground coordinate system, vehicle moment of inertia, distance from the vehicle center of mass to the front axle, distance from the vehicle center of mass to the rear axle, front wheel track, rear wheel track, wheel angle, longitudinal force received by the wheel in the wheel coordinate system, or lateral force received by the wheel in the wheel coordinate system.

[0133] In some embodiments, the motion control parameters include at least one of the following: motor torque of the vehicle or wheel angle of the vehicle.

[0134] In some embodiments, when the vehicle is provided with a first motor, a second motor, a third motor, a first steering device, and a second steering device, the motion control parameters specifically include at least one of the following: first motor torque of the vehicle, second motor torque, third motor torque, front wheel equivalent angle, left rear wheel angle, or right rear wheel angle.

[0135] The first motor is configured to drive the left front wheel and the right front wheel of the vehicle, the second motor is configured to drive the left rear wheel of the vehicle, and the third motor is configured to drive the right rear wheel of the vehicle; the first steering device is configured to control the left rear wheel steering, and the second steering device is configured to control the right rear wheel steering.

[0136] In an implementation manner, the implementation of S901 can be: based on the driving state parameter, constructing a vehicle dynamics model of the vehicle. Based on the vehicle dynamics model and the motion control parameter, a vehicle motion prediction model is constructed.

[0137] For example, the implementation process of S901 is described with reference to the embodiment of S1001-S1002 shown in FIG. 10, which will not be repeated here.

[0138] It should be noted that the rear wheel independent steering system in some embodiments of the present disclosure can increase the speed change of the vehicle, increase the optimization potential of the trajectory planning, and make the obtained trajectory more in line with the actual demand. In addition, different lateral forces and yaw moments are applied to the vehicle through the rear wheel steering device to improve the control effect of the vehicle. In addition, based on the three-motor independent driving system, the torque of the left rear wheel and the right rear wheel is driven by the independent motor, which can generate additional yaw moment of the vehicle, further improving the control effect.

[0139] Therefore, based on the steering system and the independent driving system of the vehicle in some embodiments of the present disclosure, the optimization potential of the obtained vehicle motion prediction model is higher when planning the driving trajectory, and the obtained trajectory is more in line with the actual demand.

[0140] As an embodiment of the present disclosure, in combination with FIG. 9, as shown in FIG. 10, the implementation of constructing a vehicle motion prediction model in S901 can be realized through S1001-S1002.

[0141] S1001, based on the driving state parameter, constructing a vehicle dynamics model of the vehicle.

[0142] In an implementation manner, in the case that the driving form of the vehicle is front single rear double (i.e., the vehicle is driven by the first motor, the second motor and the third motor), and the steering system includes the front wheel steering device, the first steering device and the second steering device, a vehicle dynamics model is established based on the driving of the vehicle and the steering system of the vehicle.

[0143] In some embodiments, the vehicle dynamics model satisfies the following formula:

[0144] Wherein, X is the horizontal coordinate of the vehicle in the ground coordinate system, Y is the longitudinal coordinate of the vehicle in the ground coordinate system, v y is the longitudinal speed of the vehicle, vx is the lateral velocity of the vehicle, φ is the body yaw angle, ω is the yaw rate, m is the mass of the vehicle, X ij is the longitudinal force of the left front wheel in the ground coordinate system, X fl is the longitudinal force of the left front wheel in the ground coordinate system, X fr is the longitudinal force of the right front wheel in the ground coordinate system, X rl is the longitudinal force of the left rear wheel in the ground coordinate system, X rr is the longitudinal force of the right rear wheel in the ground coordinate system, y ij is the lateral force of the wheel in the ground coordinate system, Y fl is the lateral force of the left front wheel in the ground coordinate system, Y fr is the lateral force of the right front wheel in the ground coordinate system, Y rl is the lateral force of the left rear wheel in the ground coordinate system, Y rr is the lateral force of the right rear wheel in the ground coordinate system, I z is the moment of inertia of the whole vehicle, a is the distance from the mass center of the vehicle to the front axle, b is the distance from the mass center of the vehicle to the rear axle, t f is the front wheel track, t r is the rear wheel track, δ ij is the wheel angle, F xij is the longitudinal force of the wheel in the wheel coordinate system, F yij is the lateral force of the wheel in the wheel coordinate system.

[0145] S1002, based on the vehicle dynamics model and the motion control parameter, a vehicle motion prediction model is constructed.

[0146] In an example, the motion control parameter is determined based on the drive system of the vehicle and the steering system of the vehicle.

[0147] The motion control parameter includes a first motor torque of the vehicle, a second motor torque, a third motor torque, a front wheel equivalent angle, a left rear wheel angle and a right rear wheel angle.

[0148] In some embodiments, the motion control parameter u can be expressed as: u = [T f , T rl , T rr , δ f , δ rl , δ rr ] T .

[0149] wherein T f is the first motor torque of the vehicle, T rl is the second motor torque, T rr is the third motor torque, δf The equivalent steering angle of the front wheel, δ rl Left rear wheel steering angle, δ rr This is the steering angle of the right rear wheel.

[0150] In one example, the vehicle dynamics model in S901 is represented as

[0151] Where x=[X,Y,φ,v] x ,v y ,ω] T , representing the driving state variable; Characterize the derivative with respect to x.

[0152] Furthermore, the vehicle dynamics model is linearized and discretized, and the motion control parameter u is converted into the form of wheel control increments to obtain the vehicle motion prediction model.

[0153] For example, the vehicle motion prediction model satisfies the following formula:

[0154] Where ξ is the vehicle state variable; The coefficient matrix, is a constant matrix; Δu is the wheel control increment; k is the time step.

[0155] In some embodiments, the longitudinal force of the front wheel is determined based on the vehicle's first motor torque and the equivalent radius of the front wheel. The front wheel steering angle can be converted to the equivalent front wheel steering angle based on the vehicle design. The tire lateral force can be converted to the slip angle using an equivalent tire model. Examples 1-3 below illustrate how the longitudinal force of the wheel can be converted to the motor torque using an equivalent tire model.

[0156] Example 1 mainly introduces the process of determining the longitudinal force of the front wheel; Example 2 mainly introduces the process of determining the longitudinal force of the left rear wheel; Example 3 mainly introduces the process of determining the longitudinal force of the right rear wheel.

[0157] Example 1: Determine the longitudinal force of the front wheel based on the vehicle's first motor torque and the equivalent radius of the front wheel.

[0158] It should be noted that since the left and right front wheels are controlled by the same first motor, and their equivalent radii are the same, the longitudinal force on the left front wheel is the same as the longitudinal force on the right front wheel, and both can be determined by the equivalent radius of the front wheel and the torque of the first motor.

[0159] For example, front wheel F xf The longitudinal force satisfies the following formula:

[0160] wherein T f is the first motor torque of the vehicle, R f is the equivalent radius of the front wheel.

[0161] Example 2, determine the longitudinal force of the left rear wheel based on the second motor torque of the vehicle and the equivalent radius of the left rear wheel.

[0162] For example, the longitudinal force F xrl satisfies the following formula:

[0163] wherein T rl is the second motor torque, R r is the equivalent radius of the rear wheel.

[0164] Example 3, determine the longitudinal force of the right rear wheel based on the third motor torque of the vehicle and the equivalent radius of the right rear wheel.

[0165] For example, the longitudinal force F xrr satisfies the following formula:

[0166] wherein T rr is the third motor torque, R r is the equivalent radius of the rear wheel.

[0167] Based on the above technical solution, a vehicle dynamics model of the vehicle is constructed based on the driving state parameters. A vehicle motion prediction model is constructed based on the vehicle dynamics model and the motion control parameters. Based on the above technical solution, the vehicle motion prediction model can be established for the driving system of the vehicle and the steering system of the vehicle, which is convenient for subsequent planning of the driving trajectory based on the vehicle motion prediction model.

[0168] As an embodiment of the present disclosure, as shown in FIG. 10, the implementation manner of the above-mentioned determining at least one driving trajectory can be implemented through the following S1003-S1004.

[0169] S1003, determine the drivable range of the vehicle in the road based on the road parameters.

[0170] In an implementation manner, in the case that the road is a road in which the obstacle has been removed, the implementation manner of S1003 can be: obtaining the position of the vehicle center of mass. A plane rectangular coordinate system is established with the position of the vehicle center of mass as the origin, and the road parameters are subjected to corresponding coordinate transformation to determine the road parameters in the plane rectangular coordinate system. Based on the road parameters in the plane rectangular coordinate system and the maximum distance of the vehicle boundary relative to the center of mass in the Y direction when the vehicle heading angle is φ, the drivable range of the vehicle center of mass in the road is determined.

[0171] wherein the road parameters can be Tt = [X t , Y t , W t ].

[0172] wherein X t , Y t represent the positions of the road center points. X t is the horizontal coordinate position of the road center points, X t = {x t1 , x t2 ,..., x tn}; Y t is the vertical coordinate position of the road center points, Y t = {y t1 , y t2 ,..., y tn}; and W t represents the road width at the road center points, W t = {w t1 , w t2 ,..., w tn}.

[0173] In an example, the drivable range P t of the vehicle in the road satisfies the following formula:

[0174] It should be noted that the meaning of D ((x, y), (x ti , y ti ), (x ti+1 , y ti+1 )) is the perpendicular distance from the point (x, y) to the line segment (x ti , y ti ), (x ti+1 , y ti+1 ); and B is the maximum distance of the vehicle boundary relative to the center of mass in the Y direction when the vehicle heading angle is φ.

[0175] In another implementation, the implementation of S1003 can also be: obtaining the position of the center of mass of the vehicle. A plane rectangular coordinate system is established with the position of the center of mass of the vehicle as the origin, and the road parameters are subjected to corresponding coordinate transformation to determine the position coordinates of each center point in the road and the position coordinates of the obstacles in the road in the plane rectangular coordinate system. Based on the position coordinates of each center point in the road and the position coordinates of the obstacles in the road in the plane rectangular coordinate system, and the maximum distance of the vehicle boundary relative to the center of mass in the Y direction when the vehicle heading angle is φ, the drivable range of the center of mass of the vehicle in the road is determined.

[0176] S1004, based on the drivable range and the trajectory constraint condition, the vehicle motion prediction model is constrained, and at least one driving trajectory is determined.

[0177] For example, the drivable range is: {x, y, φ} ∈ P t .

[0178] Wherein, x is the lateral coordinate of the vehicle in the ground coordinate system, y is the longitudinal coordinate of the vehicle in the ground coordinate system, and φ is the body heading angle.

[0179] For example, the trajectory constraint condition includes at least one of the following: a vehicle motion state constraint condition and a motion control parameter increment constraint condition.

[0180] Hereinafter, the vehicle motion state constraint condition is introduced by condition 1; the motion control parameter increment constraint condition is introduced by condition 2.

[0181] Condition 1, the vehicle motion state constraint condition can be determined by stability constraint and control limit constraint. The vehicle motion state constraint condition can be represented by the following formula: ξ min ≤ξ(k)≤ξ max

[0182] Wherein, ξ min is the minimum value of each parameter in the preset vehicle state quantity, and ξ max is the maximum value of each parameter in the preset vehicle state quantity.

[0183] It should be noted that when each parameter in the vehicle state quantity reaches the minimum value of each parameter in the preset vehicle state quantity, the vehicle satisfies the stability constraint and is in a stable driving state. When each parameter in the vehicle state quantity reaches the maximum value of each parameter in the preset vehicle state quantity, the vehicle satisfies the control limit constraint and is in a driving limit state; if the maximum value of each parameter is exceeded, the vehicle has a risk of losing control.

[0184] Condition 2, the motion control parameter increment constraint condition is mainly determined by the increment limit constraint. For example: ΔU min ≤ΔU(k)≤ΔU max

[0185] Wherein, ΔU min is the minimum value of the motion control parameter increment, and ΔU max is the maximum value of the motion control parameter increment.

[0186] Based on the above technical solution, based on the road parameters, the drivable range of the vehicle in the road is determined. Based on the drivable range and the trajectory constraint condition, the vehicle motion prediction model is constrained to determine at least one driving trajectory. The above technical solution can determine at least one driving trajectory through road constraints and trajectory constraints.

[0187] As an embodiment of the present disclosure, as shown in FIG. 11, the process of controlling the vehicle to travel according to the target driving trajectory in S802 can be implemented through S1101-S1102.

[0188] S1101, determining the target control amount of each actuator in the vehicle based on the target driving trajectory.

[0189] The target control amount is the control amount of the actuator when the vehicle travels according to the target driving trajectory.

[0190] In an implementation manner, the implementation process of S1101 can be implemented through the following steps 1-3.

[0191] Step 1, obtaining the real-time motion state of the vehicle.

[0192] In an example, based on the vehicle information collected by the vehicle configuration of each vehicle-mounted sensor (such as an inertial measurement unit, a vehicle-mounted camera, a millimeter wave radar, an ultrasonic radar, a laser radar, etc.), the real-time motion state of the vehicle is determined through a multi-sensor information fusion manner and a vehicle state estimation module.

[0193] It should be noted that in the actual driving process of the vehicle, the vehicle may deviate from the target signal driving trajectory. Therefore, based on the real-time motion state of the vehicle, it can be monitored whether the vehicle deviates from the target driving trajectory.

[0194] Step 2, correcting the target driving trajectory through a vehicle motion prediction model based on the real-time motion state to obtain a corrected target driving trajectory.

[0195] In an example, the target driving trajectory and the real-time motion state are sent to the vehicle motion prediction model, so that the vehicle motion prediction model can correct the target driving trajectory based on the real-time motion state, and improve the accuracy of the vehicle in the driving process.

[0196] It should be noted that based on the real-time motion state, the target driving trajectory can be corrected in time when the vehicle deviates from the target driving trajectory.

[0197] Step 3, determining the target control amount of each actuator in the vehicle based on the corrected target driving trajectory.

[0198] In an example, based on the target function and the corrected target driving trajectory, the target control amount of each actuator in the vehicle is determined through optimal quadratic programming.

[0199] In some embodiments, the target function is determined by the trajectory tracking accuracy and the control amount cost. For example, the target function J can be:

[0200] wherein N p is a prediction step, Q and R are weight coefficients.

[0201] S1102, sending, by the chassis-by-wire execution system of the vehicle, the target control quantity to each execution device in the vehicle, so that each execution device executes the target control quantity to control the vehicle to travel along the target travel trajectory.

[0202] In an example, the target control quantity is sent to the chassis-by-wire execution system of the vehicle, and the corresponding target control quantity is sent by the chassis-by-wire execution system to each execution device (for example, each motor or each steering device) of the vehicle, so that each execution device can control the vehicle based on the target control quantity.

[0203] Further, S1101-S1102 are repeatedly executed until the vehicle reaches the test endpoint.

[0204] For example, as shown in FIG. 12, based on the target travel trajectory and the real-time motion state of the vehicle fed back by the vehicle state estimation module in real time, the vehicle motion prediction model updates and corrects the target control quantity executed by each execution device, and sends the updated and corrected target control quantity to the chassis-by-wire execution system of the vehicle, so that the chassis-by-wire execution system (the first motor control module, the second motor control module, the third motor control module, the third steering device control module, the first steering device control module, and the second steering device control module) of the vehicle sends the updated and corrected target control quantity to each execution device in the vehicle, so that each execution device can control the vehicle based on the target control quantity.

[0205] The vehicle state estimation module also feeds back the real-time motion state of the vehicle to the chassis-by-wire execution system of the vehicle in real time.

[0206] Based on the above technical solution, the target control quantity of each execution device in the vehicle is determined based on the target travel trajectory. The target control quantity is sent by the chassis-by-wire execution system of the vehicle to each execution device in the vehicle, so that each execution device executes the target control quantity. The above technical solution can make each execution device execute the target control quantity to control the vehicle to travel along the target travel trajectory.

[0207] Some embodiments of the present disclosure can divide the functional modules or functional units of the vehicle according to the above method examples, for example, each functional module or functional unit can be divided according to each function, or two or more functions can be integrated into one processing module. The above integrated module can be realized in the form of hardware or software functional module or functional unit. The division of modules or units in some embodiments of the present disclosure is illustrative, and is only a logical functional division. When actually implemented, there can be another division manner.

[0208] As shown in FIG. 13, there is a block diagram of a control device 130 of a vehicle according to some embodiments, the control device 130 of the vehicle comprising: a communication unit 1301 and a processing unit 1302.

[0209] The processing unit 1302 is configured to predict at least one driving trajectory of the vehicle in the road based on the road parameters through a vehicle motion prediction model; the vehicle motion prediction model is configured to predict the driving trajectory in the motion state of the vehicle.

[0210] The processing unit 1302 is further configured to determine a target driving trajectory in the at least one driving trajectory based on a preset driving requirement.

[0211] In an implementation manner, the preset driving requirement comprises at least one of: a maximum driving speed of the vehicle at a preset position, a shortest driving time, a shortest driving distance, a minimum curvature of the driving trajectory, a most stable driving state of the vehicle during driving, and a highest similarity to an original driving trajectory.

[0212] In an implementation manner, in a case where the preset driving requirement is a maximum driving speed of the vehicle at a preset position, the processing unit 1302 is further configured to: determine, for each driving trajectory, a driving speed of the vehicle at the preset position; and determine a driving trajectory with the maximum driving speed as the target driving trajectory.

[0213] In an implementation manner, the processing unit 1302 is further configured to construct the vehicle motion prediction model based on driving state parameters and motion control parameters of the vehicle.

[0214] In an implementation manner, the processing unit 1302 is further configured to construct a vehicle dynamics model of the vehicle based on the driving state parameters; and construct the vehicle motion prediction model based on the vehicle dynamics model and the motion control parameters.

[0215] In an implementation manner, the processing unit 1302 is further configured to determine a drivable range of the vehicle in the road based on the road parameters; and constrain the vehicle motion prediction model based on the drivable range and a trajectory constraint condition to determine the at least one driving trajectory.

[0216] In an implementation manner, the processing unit 1302 is further configured to determine target control amounts of each actuator in the vehicle based on the target driving trajectory; the target control amount is a control amount performed by the actuator when the vehicle drives according to the target driving trajectory; and the communication unit 1301 is configured to send the target control amounts to each actuator in the vehicle through a chassis drive-by-wire execution system of the vehicle, so that each actuator performs the target control amount.

[0217] In an implementation manner, the processing unit 1302 is further configured to instruct the communication unit to acquire a real-time motion state of the vehicle; correct the target driving trajectory based on the real-time motion state by using a vehicle motion prediction model to obtain a corrected target driving trajectory; and determine target control amounts of various actuators in the vehicle based on the corrected target driving trajectory.

[0218] In an implementation manner, the motion control parameter comprises at least one of a motor torque of the vehicle or a wheel angle of the vehicle.

[0219] In an implementation manner, in a case where the vehicle is configured with a first motor, a second motor, a third motor, a first steering device and a second steering device, the motion control parameter comprises at least one of a first motor torque of the vehicle, a second motor torque of the vehicle, a third motor torque of the vehicle, a front wheel equivalent angle, a left rear wheel angle or a right rear wheel angle; the first motor is configured to drive a left front wheel and a right front wheel of the vehicle, the second motor is configured to drive a left rear wheel of the vehicle, and the third motor is configured to drive a right rear wheel of the vehicle; the first steering device is configured to control the left rear wheel steering, and the second steering device is configured to control the right rear wheel steering.

[0220] In an implementation manner, the driving state parameter comprises at least one of position information of the vehicle, a longitudinal speed, a lateral speed, a body heading angle, a yaw rate, a mass, a longitudinal force received by each wheel in a ground coordinate system, a lateral force received by each wheel in the ground coordinate system, a total vehicle moment of inertia, a distance from a vehicle center of mass to a front axle, a distance from the vehicle center of mass to a rear axle, a front wheel track, a rear wheel track, a wheel angle, a longitudinal force received by the wheel in a wheel coordinate system or a lateral force received by the wheel in the wheel coordinate system.

[0221] In an implementation manner, the road parameter comprises at least one of a road center point position, a road width at the center point or position information of an obstacle in the road.

[0222] In an implementation manner, the trajectory constraint condition comprises at least one of a vehicle motion state constraint condition or a motion control parameter increment constraint condition.

[0223] In an implementation manner, the control device 130 of the vehicle can further comprise a storage unit 1303 (shown in a dashed box in FIG. 13) which stores programs or instructions, when the processing unit 1302 executes the programs or instructions, the control device 130 of the vehicle can execute the vehicle control method described in the above method embodiment.

[0224] Those skilled in the art can clearly understand the vehicle's control method in the method flow of the above-described method embodiments through the description of the above embodiments. For the convenience and brevity of description, only the division of the above functional modules is taken as an example in the actual application. The above functions can be completed by different functional modules according to the needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the above-described system, device and unit can refer to the corresponding process in the foregoing method embodiments, which will not be described here.

[0225] Some embodiments of the present disclosure further provide a computer program product containing instructions, which, when executed on a computer, cause the computer to perform the vehicle control method in the above method embodiments.

[0226] Some embodiments of the present disclosure further provide a computer readable storage medium, which stores instructions. When the instructions are executed on a computer, the computer performs the vehicle control method in the method flow shown in the above method embodiments.

[0227] The computer readable storage medium may, for example, be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium include an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can be a component of the processor. The processor and the storage medium can be located in an application specific integrated circuit (ASIC). In some embodiments of the present disclosure, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device.

[0228] Since the vehicle, the computer readable storage medium, and the computer program product in some embodiments of the present disclosure can be applied to the above method, the technical effects that can be achieved thereby can also be referred to the above method embodiments, which will not be repeated here.

[0229] In several embodiments provided by the present disclosure, it should be understood that the disclosed system, device and method can be implemented in other manners. For example, the described device embodiments are merely schematic. The division of the units is merely a logical function division. There can be another division manner for the actual implementation, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the displayed or discussed mutual couplings or direct couplings or communication connections can be indirect couplings or communication connections through some interfaces, devices or units, and can be in electrical, mechanical or other forms.

[0230] It should be understood that the various forms of flow shown above can be reordered, added, or deleted steps. For example, the steps described in the present disclosure can be executed in parallel, in sequence, or in a different order, as long as the desired results of the technical solutions of the present disclosure can be achieved, and the present disclosure is not limited herein.

[0231] The above detailed description does not constitute a limitation on the protection scope of the present disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

[0232] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they can be located in one place or distributed on multiple network units. Some or all of the units can be selected to achieve the purpose of the present embodiment according to actual needs.

[0233] In addition, each functional unit in each embodiment of the present disclosure can be integrated into one processing unit, or each unit can exist physically, or two or more units can be integrated into one unit.

[0234] The above is merely a specific implementation of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any change or substitution within the technical scope disclosed by the present disclosure shall be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be subject to the protection scope of the claims.

Claims

1. A control method of a vehicle, comprising: determining a target driving trajectory among at least one driving trajectory based on a target driving demand; the at least one driving trajectory is a driving trajectory of the vehicle in a road predicted by a vehicle motion prediction model based on road parameters; the vehicle motion prediction model is configured to predict a driving trajectory of the vehicle in a motion state; and controlling the vehicle to drive according to the target driving trajectory.

2. The method of claim 1, wherein, The target driving demand is one or more of preset driving demands; the preset driving demands include at least one of the following: the driving speed of the vehicle at a preset position is maximum, the driving time is shortest, the driving distance is shortest, the curvature of the driving trajectory is minimum, the driving state of the vehicle during driving is most stable, or the similarity with an original driving trajectory is highest.

3. The method of claim 1 or 2, wherein, The determination of the target driving trajectory among the at least one driving trajectory based on the target driving demand comprises: for each driving trajectory among the at least one driving trajectory, determining a matching degree of the each driving trajectory to the target driving demand; determining the driving trajectory with the maximum matching degree as the target driving trajectory.

4. The method of any one of claims 1 to 3, further comprising: constructing the vehicle motion prediction model based on driving state parameters and motion control parameters of the vehicle.

5. The method of claim 4, wherein, The construction of the vehicle motion prediction model based on the driving state parameters and the motion control parameters of the vehicle comprises: constructing a vehicle dynamics model of the vehicle based on the driving state parameters; constructing the vehicle motion prediction model based on the vehicle dynamics model and the motion control parameters.

6. The method of any one of claims 1 to 5, wherein, The determination of the at least one driving trajectory comprises: determining a drivable range of the vehicle in the road based on the road parameters; constraining the vehicle motion prediction model based on the drivable range and a trajectory constraint condition to determine the at least one driving trajectory.

7. The method of claim 6, wherein, The trajectory constraint condition includes at least one of the following: a vehicle motion state constraint condition or a motion control parameter increment constraint condition.

8. The method of any one of claims 1 to 7, wherein, The control of the vehicle to drive according to the target driving trajectory comprises: determining target control amounts of each actuator in the vehicle based on the target driving trajectory; the target control amount is a control amount performed by one of the actuators in the vehicle when the vehicle drives according to the target driving trajectory; sending the target control amounts to the actuators in the vehicle through a chassis drive-by-wire execution system of the vehicle, so that the actuators perform the target control amounts to control the vehicle to drive according to the target driving trajectory.

9. The method of claim 8, wherein, The determination of the target control amounts of each actuator in the vehicle based on the target driving trajectory comprises: obtaining a real-time motion state of the vehicle; correcting the target driving trajectory based on the real-time motion state through the vehicle motion prediction model to obtain a corrected target driving trajectory; determining the target control amounts of the actuators in the vehicle based on the corrected target driving trajectory.

10. The method of any one of claims 1-9, wherein, The motion control parameters of the vehicle include at least one of the following: a motor torque of the vehicle or a wheel angle of the vehicle.

11. The method of claim 10, wherein, In a case where the vehicle is configured with a first motor, a second motor, a third motor, a first steering device, and a second steering device, the motion control parameter comprises at least one of: a first motor torque, a second motor torque, a third motor torque, a front wheel equivalent angle, a left rear wheel angle, or a right rear wheel angle of the vehicle; wherein the first motor is configured to drive a left front wheel and a right front wheel of the vehicle, the second motor is configured to drive a left rear wheel of the vehicle, and the third motor is configured to drive a right rear wheel of the vehicle; the first steering device is configured to control steering of the left rear wheel, and the second steering device is configured to control steering of the right rear wheel.

12. The method of any one of claims 1-11, wherein, The driving state parameter of the vehicle comprises at least one of: a position information, a longitudinal speed, a lateral speed, a body heading angle, a yaw rate, a mass, a longitudinal force received by each wheel in a ground coordinate system, a lateral force received by each wheel in the ground coordinate system, a vehicle moment of inertia, a distance from a vehicle center of mass to a front axle, a distance from the vehicle center of mass to a rear axle, a front wheel track, a rear wheel track, a wheel angle, a longitudinal force received by a wheel in a wheel coordinate system, or a lateral force received by the wheel in the wheel coordinate system.

13. The method of any one of claims 1-12, wherein, The road parameter comprises at least one of: a road center point position, a road width of the center point position, or position information of an obstacle in the road.

14. A vehicle comprising: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is configured to run a computer program or instructions to implement the control method of the vehicle according to any one of claims 1-13.

15. The vehicle of claim 14, further comprising: a first motor, a second motor, and a third motor; wherein the first motor is configured to drive a left front wheel and a right front wheel of the vehicle, the second motor is configured to drive a left rear wheel of the vehicle, and the third motor is configured to drive a right rear wheel of the vehicle.

16. The vehicle of claim 14 or 15, further comprising a first steering device and a second steering device; wherein the first steering device is configured to control steering of the left rear wheel of the vehicle, and the second steering device is configured to control steering of the right rear wheel of the vehicle.

17. A computer readable storage medium, wherein, The computer readable storage medium stores instructions, when the computer executes the instructions, the computer executes the control method of the vehicle according to any one of claims 1-13.

18. A computer program product, comprising computer instructions, when the computer instructions are run on a computer, causing the computer to execute the control method of the vehicle according to any one of claims 1-13.

Images