Unmanned sweeper obstacle avoidance control method and system in high-speed state

Abstract

The invention provides an obstacle avoidance control method and system for an unmanned sweeper in a high-speed state, and relates to the technical field of vehicle control. According to the method, the trajectory of the unmanned sweeper in a future set time period is calculated through a vehicle dynamics model; the track is expanded towards the two sides to form a strip-shaped passing area; dividing the passing area into a deceleration area and an obstacle avoidance area along the axis direction; sensing surrounding pedestrians, obstacles and vehicles, and performing trajectory prediction on the surrounding pedestrians and vehicles; when the predicted tracks of the obstacles or the surrounding pedestrians and vehicles exist in the deceleration area, the motor sweeper is decelerated to the target speed and then runs at a constant speed; if the obstacle exists in the obstacle avoidance area, performing an avoidance action on the obstacle or stopping moving until the obstacle does not exist in the obstacle avoidance area; and if the predicted tracks of the surrounding pedestrians and vehicles exist in the obstacle avoidance area, the vehicles are decelerated to the target speed and then run at a constant speed. According to the invention, stable obstacle avoidance control of the unmanned sweeper in a high-speed state is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic driving control of a road sweeper, and in particular to an obstacle avoidance control method and system for an unmanned road sweeper in a high-speed state. Background Art

[0002] When designing active safety technology to prevent street sweepers from colliding, image data is usually used to detect obstacles in a fixed area in front of the street sweeper. If there are common obstacles such as pedestrians or vehicles in the fixed area, the alarm system will sound an alarm, and the driver on the vehicle will take braking measures after hearing the alarm. The active safety system on the street sweeper generally does not actively brake. Even if it does, it will only adopt a simple braking logic, that is, emergency braking will be performed directly when pedestrians or vehicles are detected in a fixed area of ​​the image to ensure the safe driving of the vehicle. This method is only suitable for low-speed scenarios. In scenarios where the speed of the street sweeper is low, the active safety system of the street sweeper can stop safely in time before colliding with obstacles. As the speed of the street sweeper increases, the safety of this method will decrease rapidly. And this method cannot handle unconventional obstacles. If it encounters unconventional obstacles, the active safety system of the vehicle will fail. In addition, this method will only stop the vehicle, and cannot perform avoidance actions, nor can it calculate the movement trajectory of surrounding pedestrians and vehicles for a period of time in the future to avoid them in advance. Summary of the invention

[0003] In order to solve the above technical problems or at least partially solve the above technical problems, the present invention provides an obstacle avoidance control method and system for an unmanned road sweeper at high speed, which is an active safety control technology specifically used to prevent the road sweeper from colliding in high-speed scenarios.

[0004] In a first aspect, the present invention provides an obstacle avoidance control method for an unmanned road sweeper in a high-speed state, which is applied when the vehicle speed of the unmanned road sweeper is greater than a set vehicle speed, comprising: The trajectory of the driverless road sweeper in a set future time period is calculated through the vehicle dynamics model; The track is extended to both sides by a set distance to form a strip-shaped passage area; the passage area is divided into two parts along the axis direction, the part farther from the unmanned sweeper is the deceleration area, and the area closer to the unmanned sweeper is the obstacle avoidance area; While constructing the traffic area, dividing the obstacle avoidance area and the deceleration area, it senses the surrounding pedestrians, obstacles and vehicles, and predicts the trajectories of the surrounding pedestrians and vehicles; When there are obstacles or predicted trajectories of surrounding pedestrians and vehicles in the deceleration area, the sweeper will be decelerated to the target speed and then run at a constant speed; if there are obstacles in the obstacle avoidance area, the obstacle will be avoided or stopped until there are no obstacles in the obstacle avoidance area; if there are predicted trajectories of surrounding pedestrians and vehicles in the obstacle avoidance area, the vehicle will be decelerated to the target speed and then run at a constant speed.

[0005] Furthermore, the trajectory of the unmanned road sweeper in the future set time period is calculated by the vehicle dynamics model, including: Obtaining vehicle posture information, which includes vehicle position information and yaw angle; Acquiring vehicle status information, wherein the vehicle status information includes vehicle mass, vehicle speed, acceleration, vehicle yaw angular velocity, vehicle moment of inertia about the z-axis, and vehicle front wheel angle; Update the vehicle's yaw angle and vehicle center of mass velocity in the world coordinate system according to the vehicle dynamics model x Components on the axis, vehicle center of mass velocity in the world coordinate system y After obtaining the components on the axis and the vehicle's yaw rate, the trajectory is obtained by recursively calculating the vehicle's horizontal coordinate in the world coordinate system and the vehicle's vertical coordinate in the world coordinate system using the updated parameters each time. The formula is as follows: ; ; In the formula, for k The horizontal coordinate of the vehicle in the world coordinate system at this moment; for k The vertical coordinate of the vehicle in the world coordinate system at this moment; is the velocity of the vehicle's center of mass in the world coordinate system x Components on the axis; is the velocity of the vehicle's center of mass in the world coordinate system y Components on the axis; for k The yaw angle of the vehicle at the moment, that is, the longitudinal axis of the vehicle and the world coordinate system x The angle of the axes; is the time interval between two adjacent trajectory points; for k The vehicle's yaw angular velocity at time.

[0006] Furthermore, the vehicle dynamics model updates the vehicle's yaw angle and vehicle center of mass velocity in the world coordinate system. x Components on the axis, vehicle center of mass velocity in the world coordinate system y The components on the axes and the vehicle's yaw rate are expressed as follows: ; ; ; ; In the formula, is the vehicle acceleration; is the vehicle mass; is the longitudinal force on the front wheels of the vehicle; is the lateral force on the front wheels of the vehicle; is the lateral force on the rear wheels of the vehicle; is the distance from the center of mass to the front axle; is the distance from the center of mass to the rear axle; is the moment of inertia of the vehicle around the z-axis.

[0007] Furthermore, the lateral force on the front and rear wheels of the vehicle is calculated based on the front wheel steering angle of the vehicle and the vehicle structural performance parameters. The calculation method is as follows: ; ; In the formula, is the lateral force of the front wheel of the vehicle; is the lateral force of the rear wheel of the vehicle; is the cornering stiffness of the front tire; is the cornering stiffness of the rear tire; is the vehicle's front wheel turning angle.

[0008] Furthermore, the width of the passage area is the width of the vehicle body, and the length of the passage area is as follows , where is the total length of the passage area; is the vehicle speed coefficient; is the current vehicle speed; is the minimum length of the pass area.

[0009] Furthermore, the length of the deceleration area is determined according to the acceleration of the vehicle deceleration process and the minimum speed of the vehicle deceleration state, and the formula is as follows: , where is the length of the deceleration area; The minimum speed of the vehicle in deceleration state; is the acceleration of the vehicle deceleration process. is the current vehicle speed; The calculation formula for the obstacle avoidance area length is: , where is the length of the obstacle avoidance area, is the total length of the passage area.

[0010] Furthermore, the acceleration of the vehicle deceleration process changes smoothly according to the tanh function at the beginning and end of deceleration, and the intermediate acceleration is the acceleration of the vehicle deceleration process , the adjustment time is determined by the acceleration change curve and the initial and final velocities, and the obstacle avoidance area length is calculated based on the acceleration change curve, the initial velocity and the integral of the adjustment time.

[0011] In a second aspect, the present invention provides an obstacle avoidance control system for an unmanned road sweeper in a high-speed state, comprising: A trajectory generation module, wherein the trajectory generation module calculates the trajectory of the unmanned road sweeper within a future set time period through a vehicle dynamics model; A passage area construction module, wherein the passage area construction module extends the trajectory output by the trajectory generation module to both sides by a set distance to form a strip-shaped passage area; and divides the passage area into two parts along the axis direction, the part farther from the unmanned sweeper is a deceleration area, and the area closer to the unmanned sweeper is an obstacle avoidance area; A perception module, which senses surrounding pedestrians, obstacles and vehicles; A trajectory prediction module, which predicts the trajectories of surrounding pedestrians and vehicles sensed by the perception module; A decision-making module makes decisions based on the positional relationship between obstacles and the passage area, and the positional relationship between the trajectories of pedestrians and vehicles and the passage area, including: when there are obstacles or predicted trajectories of surrounding pedestrians and vehicles in the deceleration area, the sweeper is decelerated to a target speed and then runs at a constant speed; if there are obstacles in the obstacle avoidance area, the obstacle is avoided or stopped until there are no obstacles in the obstacle avoidance area; if there are predicted trajectories of surrounding pedestrians and vehicles in the obstacle avoidance area, the vehicle is decelerated to a target speed and then runs at a constant speed.

[0012] Furthermore, the trajectory generation module is connected to the positioning module and the vehicle control module; the decision module is connected to the vehicle control module; The positioning module outputs vehicle posture information to the trajectory generation module, and the vehicle posture information includes vehicle position information and yaw angle; the vehicle control module outputs vehicle state information to the trajectory generation module, and the vehicle state information includes vehicle mass, vehicle speed, acceleration, vehicle yaw angular velocity, vehicle moment of inertia around the z-axis, and vehicle front wheel angle; The decision module transmits the decision to the vehicle control module for execution.

[0013] In the third aspect, the present invention provides an obstacle avoidance control device for an unmanned driving sweeper under high-speed state, comprising: at least one processing unit, a processing unit and a storage unit connected through a bus unit, the storage unit being a computer-readable storage medium that can be used to store software programs, computer executable programs and modules, the processing unit implements the obstacle avoidance control method for an unmanned driving sweeper under high-speed state by running the software programs, computer executable programs and modules stored in the storage unit.

[0014] The above technical solution provided by the embodiment of the present invention has the following advantages compared with the prior art: The present application calculates the trajectory of the unmanned sweeper in the future set time period through the vehicle dynamics model; expands the trajectory to both sides to form a strip-shaped passage area; divides the passage area into a deceleration area and an obstacle avoidance area along the axis direction; senses the surrounding pedestrians, obstacles and vehicles, and predicts the trajectories of the surrounding pedestrians and vehicles; when there are obstacles or predicted trajectories of the surrounding pedestrians and vehicles in the deceleration area, the sweeper is decelerated to the target speed and then runs at a constant speed; if there are obstacles in the obstacle avoidance area, the obstacle is avoided or stopped until there are no obstacles in the obstacle avoidance area; if there are predicted trajectories of the surrounding pedestrians and vehicles in the obstacle avoidance area, the vehicle is decelerated to the target speed and then runs at a constant speed. At high speed, the present invention senses surrounding objects on the one hand, and generates a vehicle passage area on the other hand, and the two cooperate to determine the obstacles, pedestrians and vehicles that may collide on the forward path. And combined with the positional relationship between obstacles, pedestrians and vehicles and the deceleration area and obstacle avoidance area in the passage area, a smooth deceleration and avoidance is performed in advance, the stability of obstacle avoidance in high-speed scenes is improved, and the safety of vehicles in high-speed scenes is ensured. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0016] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0017] Figure 1 A flowchart of an obstacle avoidance control method for an unmanned road sweeper in a high-speed state provided by an embodiment of the present invention; Figure 2 A flow chart of calculating the trajectory of an unmanned road sweeper within a set time period in the future by using a vehicle dynamics model provided in an embodiment of the present invention; Figure 3 A schematic diagram of a traffic area provided by an embodiment of the present invention; Figure 4 A schematic diagram of an obstacle avoidance control system for an unmanned road sweeper at high speed provided by an embodiment of the present invention; Figure 5 A schematic diagram of an obstacle avoidance control device for an unmanned road sweeper in a high-speed state provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0020] Example 1 like Figure 1 As shown, the technology of the present invention realizes an obstacle avoidance control method for an unmanned sweeper in a high-speed state, which is applied when the speed of the sweeper is greater than the set speed. The present invention includes the following steps: When the speed of the unmanned road sweeper is greater than the set speed, the following process is performed: The trajectory of the unmanned road sweeper in the future set time period is calculated through the vehicle dynamics model; Figure 2 As shown, the process includes: The vehicle posture information is obtained, and the vehicle posture information includes the vehicle position information and yaw angle.

[0021] The vehicle status information is obtained, wherein the vehicle status information includes vehicle mass, vehicle speed, acceleration, vehicle yaw angular velocity, vehicle moment of inertia about the z-axis, and vehicle front wheel angle.

[0022] Use the vehicle dynamics model to update the vehicle's yaw angle and vehicle center of mass velocity in the world coordinate system x Components on the axis, vehicle center of mass velocity in the world coordinate systemy The components on the axis and the vehicle yaw rate are calculated as follows: ; ; ; ; In the formula, is the vehicle acceleration; is the vehicle mass; is the longitudinal force on the front wheels of the vehicle; is the lateral force on the front wheels of the vehicle; is the lateral force on the rear wheels of the vehicle; is the distance from the center of mass to the front axle; is the distance from the center of mass to the rear axle; is the moment of inertia of the vehicle around the z-axis. In this application, the lateral force on the front and rear wheels of the vehicle is calculated based on the steering angle of the front wheels of the vehicle and the structural performance parameters of the vehicle. The calculation method is as follows: ; ; In the formula, is the lateral force of the front wheel of the vehicle; is the lateral force of the rear wheel of the vehicle; is the cornering stiffness of the front tire; is the cornering stiffness of the rear tire; is the vehicle's front wheel turning angle.

[0023] Update the vehicle's yaw angle and vehicle center of mass velocity in the world coordinate system according to the vehicle dynamics model x Components on the axis, vehicle center of mass velocity in the world coordinate system y After obtaining the components on the axis and the vehicle's yaw rate, the vehicle dynamics model uses each updated parameter to recursively calculate the vehicle's horizontal coordinate in the world coordinate system and the vehicle's vertical coordinate in the world coordinate system to obtain the trajectory. The formula is as follows: ; ; In the formula, for k The horizontal coordinate of the vehicle in the world coordinate system at this moment; for k The vertical coordinate of the vehicle in the world coordinate system at this moment; is the velocity of the vehicle's center of mass in the world coordinate system x Components on the axis; is the velocity of the vehicle's center of mass in the world coordinate system y Components on the axis; fork The yaw angle of the vehicle at the moment, that is, the longitudinal axis of the vehicle and the world coordinate system x The angle of the axes; is the time interval between two adjacent trajectory points; for k The vehicle's yaw angular velocity at time.

[0024] like Figure 3 As shown, the track is extended to both sides by a set distance to form a strip-shaped passage area.

[0025] In the specific implementation process, the width of the passage area is the width of the vehicle body, and the length of the passage area is as follows: , where is the total length of the passage area; is the vehicle speed coefficient; is the current vehicle speed; is the minimum length of the pass area.

[0026] The traffic area is divided into two parts along the axis direction. The part farther away from the unmanned sweeper is the deceleration area, and the area closer to the unmanned sweeper is the obstacle avoidance area.

[0027] In the specific implementation process, the length of the deceleration area is determined according to the acceleration of the vehicle deceleration process and the minimum speed of the vehicle deceleration state, and the formula is as follows: , where is the length of the deceleration area; The minimum speed of the vehicle in deceleration state; is the acceleration of the vehicle deceleration process. is the current vehicle speed; the calculation formula for the obstacle avoidance area length is: , where is the length of the obstacle avoidance area.

[0028] In the specific implementation process, the acceleration of the vehicle deceleration process changes smoothly according to the tanh function at the beginning and end of deceleration, and the intermediate acceleration is the acceleration of the vehicle deceleration process. , determine the adjustment time through the acceleration change curve and the initial and final velocities, and calculate the obstacle avoidance area length based on the acceleration change curve, initial velocity and adjustment time integral. Ensure stable deceleration.

[0029] While constructing the traffic area, dividing the obstacle avoidance area and the deceleration area, the surrounding pedestrians, obstacles and vehicles are sensed, and the trajectories of the surrounding pedestrians and vehicles are predicted. In the specific implementation process, the obstacle and vehicle information around the vehicle output by the perception module of the unmanned sweeper is obtained; the predicted trajectory information of the surrounding pedestrians and vehicles output by the trajectory prediction module is used.

[0030] When there are obstacles or predicted trajectories of surrounding pedestrians and vehicles in the deceleration area, the sweeper will be decelerated to the target speed and then run at a constant speed; if there are obstacles in the obstacle avoidance area, the obstacle will be avoided or stopped until there are no obstacles in the obstacle avoidance area; if there are predicted trajectories of surrounding pedestrians and vehicles in the obstacle avoidance area, the vehicle will be decelerated to the target speed and then run at a constant speed.

[0031] By following the above strategies, the stability of the vehicle can be effectively improved when it is driving at high speed and approaching surrounding pedestrians, vehicles and obstacles, and the vehicle can be prevented from colliding with surrounding pedestrians, vehicles and obstacles.

[0032] Example 2 See also Figure 4 As shown, an embodiment of the present invention provides an obstacle avoidance control system for an unmanned sweeper in a high-speed state, comprising: A trajectory generation module, wherein the trajectory generation module calculates the trajectory of the unmanned sweeper within a future set time period through a vehicle dynamics model. The trajectory generation module is connected to the positioning module and the vehicle control module; the positioning module outputs vehicle posture information to the trajectory generation module, and the vehicle posture information includes vehicle position information and yaw angle; the vehicle control module outputs vehicle status information to the trajectory generation module, and the vehicle status information includes vehicle mass, vehicle speed, acceleration, vehicle yaw angular velocity, vehicle moment of inertia around the z-axis, and vehicle front wheel angle.

[0033] The process of the trajectory generation module calculating the trajectory of the unmanned sweeper in the future set time period through the vehicle dynamics model includes: Use the vehicle dynamics model to update the vehicle's yaw angle and vehicle center of mass velocity in the world coordinate system x Components on the axis, vehicle center of mass velocity in the world coordinate system y The components on the axis and the vehicle yaw rate are calculated as follows: ; ; ; ; In the formula, is the vehicle acceleration; is the vehicle mass; is the longitudinal force on the front wheels of the vehicle; is the lateral force on the front wheels of the vehicle; is the lateral force on the rear wheels of the vehicle; is the distance from the center of mass to the front axle; is the distance from the center of mass to the rear axle; is the moment of inertia of the vehicle around the z-axis. In this application, the lateral force on the front and rear wheels of the vehicle is calculated based on the steering angle of the front wheels of the vehicle and the structural performance parameters of the vehicle. The calculation method is as follows: ; ; In the formula, is the lateral force of the front wheel of the vehicle; is the lateral force of the rear wheel of the vehicle; is the cornering stiffness of the front tire; is the cornering stiffness of the rear tire; is the vehicle's front wheel turning angle.

[0034] Update the vehicle's yaw angle and vehicle center of mass velocity in the world coordinate system according to the vehicle dynamics model x Components on the axis, vehicle center of mass velocity in the world coordinate system y After obtaining the components on the axis and the vehicle's yaw rate, the vehicle dynamics model uses each updated parameter to recursively calculate the vehicle's horizontal coordinate in the world coordinate system and the vehicle's vertical coordinate in the world coordinate system to obtain the trajectory. The formula is as follows: ; ; In the formula, for k The horizontal coordinate of the vehicle in the world coordinate system at this moment; for k The vertical coordinate of the vehicle in the world coordinate system at this moment; is the velocity of the vehicle's center of mass in the world coordinate system x Components on the axis; is the velocity of the vehicle's center of mass in the world coordinate system y Components on the axis; for k The yaw angle of the vehicle at the moment, that is, the longitudinal axis of the vehicle and the world coordinate system x The angle of the axes; is the time interval between two adjacent trajectory points; for k The vehicle's yaw angular velocity at time.

[0035] A passage area construction module, wherein the passage area construction module extends the trajectory output by the trajectory generation module to both sides by a set distance to form a strip-shaped passage area; and divides the passage area into two parts along the axis direction, the part farther from the unmanned sweeper is the deceleration area, and the area closer to the unmanned sweeper is the obstacle avoidance area.

[0036] In the specific implementation process, the width of the passage area constructed by the passage area construction module is the width of the vehicle body, and the length of the passage area is as follows: , where is the total length of the passage area; is the vehicle speed coefficient; is the current vehicle speed; is the minimum length of the pass area. The pass area is divided into two parts along the axis direction. The part farther from the unmanned sweeper is the deceleration area, and the area closer to the unmanned sweeper is the obstacle avoidance area. In the specific implementation process, the length of the deceleration area is determined according to the acceleration of the vehicle deceleration process and the minimum speed of the vehicle deceleration state. The formula is as follows: , where is the length of the deceleration area; The minimum speed of the vehicle in deceleration state; is the acceleration of the vehicle deceleration process. is the current vehicle speed; the calculation formula for the obstacle avoidance area length is: , where is the length of the obstacle avoidance area.

[0037] A perception module, wherein the perception module perceives surrounding pedestrians, obstacles and vehicles.

[0038] The trajectory prediction module predicts the trajectories of surrounding pedestrians and vehicles perceived by the perception module.

[0039] A decision-making module makes decisions based on the positional relationship between obstacles and the passage area, and the positional relationship between the trajectories of pedestrians and vehicles and the passage area, including: when there are obstacles or predicted trajectories of surrounding pedestrians and vehicles in the deceleration area, the sweeper is decelerated to a target speed and then runs at a constant speed; if there are obstacles in the obstacle avoidance area, the obstacle is avoided or stopped until there are no obstacles in the obstacle avoidance area; if there are predicted trajectories of surrounding pedestrians and vehicles in the obstacle avoidance area, the vehicle is decelerated to a target speed and then runs at a constant speed.

[0040] The decision module is connected to the vehicle control module; the decision module transmits the decision to the vehicle control module for execution.

[0041] Example 3 See also Figure 5As shown, an embodiment of the present invention provides an obstacle avoidance control device for an unmanned driving sweeper in a high-speed state, comprising: at least one processing unit, a processing unit, a storage unit connected via a bus unit, the storage unit being a computer-readable storage medium, and being used to store software programs, computer executable programs, and modules, such as the software programs, computer executable programs, and modules corresponding to an obstacle avoidance control method for an unmanned driving sweeper in a high-speed state in an embodiment of the present invention. The processing unit implements the above-mentioned obstacle avoidance control method for an unmanned driving sweeper in a high-speed state by running the software programs, computer executable programs, and modules stored in the storage unit, comprising: The trajectory of the driverless road sweeper in a set future time period is calculated through the vehicle dynamics model; The track is extended to both sides by a set distance to form a strip-shaped passage area; the passage area is divided into two parts along the axis direction, the part farther from the unmanned sweeper is the deceleration area, and the area closer to the unmanned sweeper is the obstacle avoidance area; While constructing the traffic area, dividing the obstacle avoidance area and the deceleration area, it senses the surrounding pedestrians, obstacles and vehicles, and predicts the trajectories of the surrounding pedestrians and vehicles; When there are obstacles or predicted trajectories of surrounding pedestrians and vehicles in the deceleration area, the sweeper will be decelerated to the target speed and then run at a constant speed; if there are obstacles in the obstacle avoidance area, the obstacle will be avoided or stopped until there are no obstacles in the obstacle avoidance area; if there are predicted trajectories of surrounding pedestrians and vehicles in the obstacle avoidance area, the vehicle will be decelerated to the target speed and then run at a constant speed.

[0042] Of course, the computer program stored in the storage unit of the obstacle avoidance control device for an unmanned sweeper at high speed provided in an embodiment of the present invention is not limited to the operation of the method described above, but can also execute related operations in the obstacle avoidance control method for an unmanned sweeper at high speed provided in any embodiment of the present invention.

[0043] Example 4 An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program. When the computer program is executed, the obstacle avoidance control method for an unmanned road sweeper in a high-speed state is implemented, including: The trajectory of the driverless road sweeper in a set future time period is calculated through the vehicle dynamics model; The track is extended to both sides by a set distance to form a strip-shaped passage area; the passage area is divided into two parts along the axis direction, the part farther from the unmanned sweeper is the deceleration area, and the area closer to the unmanned sweeper is the obstacle avoidance area; While constructing the traffic area, dividing the obstacle avoidance area and the deceleration area, it senses the surrounding pedestrians, obstacles and vehicles, and predicts the trajectories of the surrounding pedestrians and vehicles; When there are obstacles or predicted trajectories of surrounding pedestrians and vehicles in the deceleration area, the sweeper will be decelerated to the target speed and then run at a constant speed; if there are obstacles in the obstacle avoidance area, the obstacle will be avoided or stopped until there are no obstacles in the obstacle avoidance area; if there are predicted trajectories of surrounding pedestrians and vehicles in the obstacle avoidance area, the vehicle will be decelerated to the target speed and then run at a constant speed.

[0044] A computer-readable storage medium provided in an embodiment of the present invention stores a computer program which is not limited to the method operations described above, but can also execute related operations in an obstacle avoidance control method for an unmanned sweeper in a high-speed state provided in any embodiment of the present invention.

[0045] In the embodiments provided by the present invention, it should be understood that the disclosed structures and methods can be implemented in other ways. For example, the structural embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, structures or units, which can be electrical, mechanical or other forms.

[0046] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0047] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0048] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. An obstacle avoidance control method for an unmanned road sweeper at high speed, which is applied when the vehicle speed of the unmanned road sweeper is greater than a set speed, and is characterized in that: include: The trajectory of the driverless road sweeper in a set future time period is calculated through the vehicle dynamics model; The track is extended to both sides by a set distance to form a strip-shaped passage area; the passage area is divided into two parts along the axis direction, the part farther from the unmanned sweeper is the deceleration area, and the area closer to the unmanned sweeper is the obstacle avoidance area; While constructing the traffic area, dividing the obstacle avoidance area and the deceleration area, it senses the surrounding pedestrians, obstacles and vehicles, and predicts the trajectories of the surrounding pedestrians and vehicles; When there are obstacles or predicted trajectories of surrounding pedestrians and vehicles in the deceleration area, the sweeper will be decelerated to the target speed and then run at a constant speed; if there are obstacles in the obstacle avoidance area, the obstacle will be avoided or stopped until there are no obstacles in the obstacle avoidance area; if there are predicted trajectories of surrounding pedestrians and vehicles in the obstacle avoidance area, the vehicle will be decelerated to the target speed and then run at a constant speed.

2. The obstacle avoidance control method for an unmanned road sweeper at high speed according to claim 1, characterized in that: The vehicle dynamics model is used to calculate the trajectory of the driverless road sweeper in the future set time period, including: Obtaining vehicle posture information, which includes vehicle position information and yaw angle; Acquiring vehicle status information, wherein the vehicle status information includes vehicle mass, vehicle speed, acceleration, vehicle yaw angular velocity, vehicle moment of inertia about the z-axis, and vehicle front wheel angle; Update the vehicle's yaw angle and vehicle center of mass velocity in the world coordinate system according to the vehicle dynamics model x Components on the axis, vehicle center of mass velocity in the world coordinate system y After obtaining the components on the axis and the vehicle's yaw rate, the trajectory is obtained by recursively calculating the vehicle's horizontal coordinate in the world coordinate system and the vehicle's vertical coordinate in the world coordinate system using the updated parameters each time. The formula is as follows: ； ； In the formula, for k The horizontal coordinate of the vehicle in the world coordinate system at this moment; for k The vertical coordinate of the vehicle in the world coordinate system at this moment; is the velocity of the vehicle's center of mass in the world coordinate system x Components on the axis; is the velocity of the vehicle's center of mass in the world coordinate system y Components on the axis; for k The yaw angle of the vehicle at the moment, that is, the longitudinal axis of the vehicle and the world coordinate system x The angle of the axes; is the time interval between two adjacent trajectory points; for k The vehicle's yaw rate at time.

3. The obstacle avoidance control method for an unmanned road sweeper at high speed according to claim 2, characterized in that: The vehicle dynamics model updates the vehicle's yaw angle and vehicle center of mass velocity in the world coordinate system x Components on the axis, vehicle center of mass velocity in the world coordinate system y The components on the axes and the vehicle's yaw rate are expressed as follows: ； ； ； ； In the formula, is the vehicle acceleration; is the vehicle mass; is the longitudinal force on the front wheels of the vehicle; is the lateral force on the front wheels of the vehicle; is the lateral force on the rear wheels of the vehicle; is the distance from the center of mass to the front axle; is the distance from the center of mass to the rear axle; is the moment of inertia of the vehicle around the z-axis.

4. The obstacle avoidance control method for an unmanned road sweeper at high speed according to claim 3, characterized in that: The lateral force on the front and rear wheels of the vehicle is calculated based on the vehicle's front wheel steering angle and the vehicle's structural performance parameters. The calculation method is as follows: ； ； In the formula, is the lateral force of the front wheel of the vehicle; is the lateral force of the rear wheel of the vehicle; is the cornering stiffness of the front tire; is the cornering stiffness of the rear tire; is the vehicle's front wheel turning angle.

5. The obstacle avoidance control method for an unmanned road sweeper at high speed according to claim 1, characterized in that: The width of the pass area is the width of the vehicle body, and the length of the pass area is as follows , where is the total length of the passage area; is the vehicle speed coefficient; is the current vehicle speed; is the minimum length of the pass area.

6. The obstacle avoidance control method for an unmanned road sweeper at high speed according to claim 1, characterized in that: The length of the deceleration area is determined according to the acceleration of the vehicle deceleration process and the minimum speed of the vehicle deceleration state. The formula is as follows: , where is the length of the deceleration area; The minimum speed of the vehicle in deceleration state; is the acceleration of the vehicle deceleration process. is the current vehicle speed; The calculation formula for the obstacle avoidance area length is: , where is the length of the obstacle avoidance area, is the total length of the passage area.

7. The obstacle avoidance control method for an unmanned road sweeper at high speed according to claim 1, characterized in that: The acceleration of the vehicle deceleration process changes smoothly according to the tanh function at the beginning and end of deceleration, and the intermediate acceleration is the acceleration of the vehicle deceleration process ; The adjustment time is determined by the acceleration change curve and the initial and final velocities, and the obstacle avoidance area length is calculated based on the acceleration change curve, initial velocity and adjustment time integral.

8. An obstacle avoidance control system for an unmanned road sweeper at high speed, characterized in that: include: A trajectory generation module, wherein the trajectory generation module calculates the trajectory of the unmanned road sweeper within a future set time period through a vehicle dynamics model; A passage area construction module, wherein the passage area construction module extends the trajectory output by the trajectory generation module to both sides by a set distance to form a strip-shaped passage area; and divides the passage area into two parts along the axis direction, the part farther from the unmanned sweeper is a deceleration area, and the area closer to the unmanned sweeper is an obstacle avoidance area; A perception module, which senses surrounding pedestrians, obstacles and vehicles; A trajectory prediction module, which predicts the trajectories of surrounding pedestrians and vehicles sensed by the perception module; A decision-making module makes decisions based on the positional relationship between obstacles and the passage area, and the positional relationship between the trajectories of pedestrians and vehicles and the passage area, including: when there are obstacles or predicted trajectories of surrounding pedestrians and vehicles in the deceleration area, the sweeper is decelerated to a target speed and then runs at a constant speed; if there are obstacles in the obstacle avoidance area, the obstacle is avoided or stopped until there are no obstacles in the obstacle avoidance area; if there are predicted trajectories of surrounding pedestrians and vehicles in the obstacle avoidance area, the vehicle is decelerated to a target speed and then runs at a constant speed.

9. The obstacle avoidance control system for an unmanned road sweeper at high speed according to claim 8, characterized in that: The trajectory generation module is connected to the positioning module and the vehicle control module; the decision module is connected to the vehicle control module; The positioning module outputs vehicle posture information to the trajectory generation module, and the vehicle posture information includes vehicle position information and yaw angle; the vehicle control module outputs vehicle state information to the trajectory generation module, and the vehicle state information includes vehicle mass, vehicle speed, acceleration, vehicle yaw angular velocity, vehicle moment of inertia around the z-axis, and vehicle front wheel angle; The decision module transmits the decision to the vehicle control module for execution.

10. An obstacle avoidance control device for an unmanned road sweeper at high speed, characterized in that: include: At least one processing unit connects the processing unit and the storage unit through a bus unit. The storage unit is a computer-readable storage medium that can be used to store software programs, computer executable programs and modules. The processing unit runs the software programs, computer executable programs and modules stored in the storage unit, thereby implementing the obstacle avoidance control method for an unmanned road sweeper under high-speed conditions as described in any one of claims 1 to 7.

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