Unmanned vehicle control method, device, electronic device, readable storage medium and chip

Abstract

The present invention provides an unmanned vehicle control method, device, electronic device, readable storage medium and chip. The unmanned vehicle control method includes: obtaining relative path information of the unmanned vehicle; determining a first steering value corresponding to the relative path information according to the driving speed of the unmanned vehicle; determining a second steering value according to the relative path information; obtaining the roll angle of the unmanned vehicle; determining the drop change of the unmanned vehicle according to the roll angle; determining a third steering value according to the drop change; determining a steering curvature value according to the first steering value, the second steering value and the third steering value; and controlling the operation of the unmanned vehicle according to the steering curvature value. By real-time monitoring of the roll angle and calculating the steering curvature value according to the roll angle, the unmanned vehicle can be driven stably on a rugged road surface. For a differential special vehicle, effective lateral control can also be achieved after calculating the curvature value by this method.

Description

Technical Field

[0001] The present invention relates to the field of autonomous driving, and in particular to an unmanned vehicle control method, device, electronic device, readable storage medium and chip. Background Art

[0002] In the current field of autonomous driving, unmanned vehicles generally travel on structured roads. The impact of the road surface on vehicle driving can allow the control algorithm to adjust itself in the form of errors. When the road surface is rough, the algorithm's self-adjustment will result in an error response delay, resulting in an increase in control error. In related technologies, the vehicle's operation is controlled by adjusting the algorithm parameters or increasing the lateral angle parameters to adjust the steering wheel angle. However, for vehicles with differential steering, this method is not applicable if the vehicle's operation is not adjusted through the steering wheel, and the purpose of adjusting the direction cannot be achieved. Summary of the invention

[0003] In order to solve or improve the above-mentioned technical problem of driving stability of a differential steering vehicle on a rough road, an object of the present invention is to provide a method for controlling an unmanned vehicle.

[0004] Another object of the present invention is to provide an unmanned vehicle control device.

[0005] Another object of the present invention is to provide an electronic device.

[0006] Another object of the present invention is to provide a readable storage medium.

[0007] Another object of the present invention is to provide a chip.

[0008] To achieve the above-mentioned objectives, the first aspect of the present invention provides an unmanned vehicle control method, including: obtaining relative path information of the unmanned vehicle; determining a first steering value corresponding to the relative path information according to the driving speed of the unmanned vehicle; determining a second steering value according to the relative path information; obtaining the roll angle of the unmanned vehicle; determining a change in the height of the unmanned vehicle according to the roll angle; determining a third steering value according to the change in the height; determining a steering curvature value according to the first steering value, the second steering value and the third steering value; and controlling the operation of the unmanned vehicle according to the steering curvature value.

[0009] According to the unmanned vehicle control method provided by the present invention, before controlling the unmanned vehicle, it is first necessary to obtain the relative path information of the unmanned vehicle, for example: the unmanned vehicle planning path can be specified according to the planning module in the unmanned vehicle or a submodule with a similar planning path function, and a preset route can be provided to the unmanned vehicle so that the unmanned vehicle can travel along the preset route. Among them, this relative path information includes path coordinate information and path heading information. The path coordinate information can enable the unmanned vehicle to reach the specified coordinate point, and the path heading information can enable the unmanned vehicle to travel in a predetermined direction, which helps the unmanned vehicle to accurately travel to the destination. After obtaining the relative path information of the unmanned vehicle, the real-time positioning coordinate information of the unmanned vehicle is given by the positioning module of the unmanned vehicle, and the positioning coordinate information and the path coordinate information preset by the planning module are used for calculation to obtain the lateral error value of the current vehicle, that is, the distance of the lateral error, and obtain the current driving speed of the unmanned vehicle. The first steering value is calculated by the current vehicle speed, the lateral error value and the gain coefficient set in advance, and used for subsequent calculation of the steering curvature value as data preparation. At the same time, the real-time positioning and heading information of the unmanned vehicle is given by the positioning module of the unmanned vehicle. The positioning and heading information and the path and heading information preset by the planning module are used to calculate the vehicle heading error value of the unmanned vehicle, that is, the angle of the heading error. This error value is used as the second steering value for subsequent calculation of the steering curvature value as data preparation. In addition, before calculating the curvature, it is also necessary to obtain the roll angle and pitch angle of the unmanned vehicle in its current posture. The specific acquisition method can be in various forms. For example, the combined navigation module can output the roll angle and pitch angle of the current unmanned vehicle based on the positioning data, or the roll angle and pitch angle of the current unmanned vehicle can be directly collected through the inclination sensor. After that, the obtained roll angle and pitch angle need to be judged, and the roll angle and pitch angle are compared with the thresholds set in advance to determine whether the roll angle and pitch angle have reached the threshold. It can be understood that this is for the unmanned vehicle. Before continuing to the next step of calculation, the system will judge the acquired data and issue different instructions according to the judgment results. If the roll angle is greater than or equal to the preset roll angle threshold, or the pitch angle is greater than or equal to the preset pitch angle threshold, the unmanned vehicle will actively stop, indicating that the vehicle is too bumpy during driving and the current road conditions are not suitable for the vehicle to continue driving. There are safety hazards, which can better protect the safety of the vehicle. If the roll angle is less than the preset roll angle threshold, or the pitch angle is less than the preset pitch angle threshold, the vehicle will be controlled to continue driving and the roll angle will be brought into the next step of calculation.

[0010] According to the roll angle and the width of the vehicle body, the left and right drop value of the vehicle body is obtained. The method for obtaining the width of the vehicle body can be designed by entering the system in advance according to the vehicle width information, or the vehicle width can be collected in real time by sensors and other equipment to prevent accidents during driving that cause the vehicle width data to change, thereby generating calculation errors. Further, the roll angle corresponding to the previous acquisition cycle is obtained by using a tilt sensor, or the roll angle of the previous cycle is output by the combined navigation system, and the left and right drop value of the vehicle body corresponding to the previous frame is calculated in the same way, and the drop change is obtained by subtracting the left and right drop value of the previous frame. Further, according to the drop change and the appropriate gain coefficient, the third steering value is calculated, and then the first steering value, the second steering value and the third steering value are added and summed to obtain the final steering value. Finally, the final steering value is brought in through the curvature formula, and the steering curvature value is output in combination with the wheelbase value of the unmanned vehicle. The unmanned vehicle is controlled by the steering curvature value so that it can drive stably on a rugged road.

[0011] In general, the present invention compares and calculates the positioning information and the relative path information preset by the planning module to obtain the lateral error value and the heading error value, and then further calculates and determines the first steering value and the second steering value using the lateral error value and the heading error value. According to the combined navigation system and the tilt sensor, the real-time roll angle and pitch angle are obtained, and the unmanned vehicle is controlled to stop by judging the two with the threshold, that is, when the roll angle or the pitch angle is greater than or equal to the threshold, the unmanned vehicle is controlled to stop, and when it is less than the threshold, the roll angle is further calculated to obtain the third steering value, and the first steering value, the second steering value and the third steering value are summed to obtain the final steering value, and the final steering value is substituted into the curvature formula to calculate the steering curvature value, and the purpose of controlling the operation of the unmanned vehicle is achieved through the steering curvature value.

[0012] It should be added that the gain coefficient is not a fixed value. Before the unmanned vehicle drives, a suitable gain coefficient can be selected through debugging or calibration. The gain coefficient configured according to the debugging situation defaults to 1. For example, the initial value of the gain coefficient is set to 1. In the experiment of the unmanned vehicle on rough roads, it was found that when the gain coefficient was set to 1, the adjustment effect of the unmanned vehicle was not ideal. Then the gain coefficient was adjusted by debugging or calibration, and then re-introduced into the system operation until a suitable gain coefficient was selected to achieve the best vehicle control effect.

[0013] In short, the present invention is an improvement on the existing Stanley algorithm. Compared with the Stanley algorithm, the present invention adds roll angle change detection and obtains the final steering curvature value by calculation. When the road surface is rough or the vehicle is pressed on a stone or step on one side, the roll angle change is judged and a certain curvature compensation value is added by formula to ensure that the vehicle completes the tracking error adjustment in time, prevents tracking response delay, and thus causes the tracking error to increase, thereby enhancing the adaptability and stability of the unmanned vehicle on rough roads. Especially for differential steering vehicles, curvature compensation provides a control possibility for differential steering vehicles to drive on rough roads, improves the adaptability to driving on complex roads, and at the same time, through real-time detection and judgment of the roll angle and pitch angle, it is judged whether the current road conditions are suitable for the vehicle to continue driving, thereby avoiding safety hazards during driving and ensuring vehicle safety.

[0014] In addition, the above technical solution provided by the present invention may also have the following additional technical features:

[0015] In some technical solutions, optionally, a first steering value corresponding to the relative path information is determined according to the driving speed of the unmanned vehicle, specifically including: obtaining the positioning coordinate information and the first gain coefficient of the unmanned vehicle; determining the lateral error value according to the coordinate information and the positioning coordinate information of the relative path information; determining the first steering value according to the first gain coefficient, the lateral error value and the driving speed.

[0016] In this technical solution, it is first necessary to obtain the positioning coordinate information and the first gain coefficient of the unmanned vehicle. The positioning coordinate information is used to compare and calculate with the relative path coordinate information preset by the planning module, so as to obtain the lateral error value of the vehicle. The lateral error value can be understood as the distance between the current positioning point and the preset planning point. The deviation distance between the current vehicle position and the preset vehicle position is calculated in real time. Furthermore, the current vehicle speed is detected by using sensors or other electronic devices, and the first steering value is calculated by substituting the current vehicle speed and the gain coefficient constant set in advance into the formula.

[0017] Among them, the gain coefficient can be obtained through debugging or calibration methods, that is, before the unmanned vehicle drives, during the detection process, the appropriate gain coefficient is selected by debugging or calibration to achieve the best control effect of the unmanned vehicle.

[0018] It should be added that the relative path information can be obtained through the planning module under the unmanned vehicle automatic driving system or a sub-module with the same planning function, or it can be directly entered into the unmanned vehicle by the user according to the established route information, and the unmanned vehicle directly executes the call.

[0019] In short, the lateral error value is obtained by calculating the current positioning coordinates of the unmanned vehicle and the preset coordinates, and then the lateral error value is further calculated by obtaining the vehicle speed and gain coefficient to obtain the first steering value, so as to prepare data for the subsequent curvature calculation and thus control the operation of the unmanned vehicle.

[0020] In some technical solutions, optionally, a second steering value is determined based on the relative path information, specifically including: obtaining the positioning heading information of the unmanned vehicle; determining a heading error value based on the heading information of the relative path information and the positioning heading information; and determining the second steering value based on the heading error value.

[0021] In this technical solution, it is first necessary to obtain the positioning and heading information of the unmanned vehicle, that is, the movement heading of the unmanned vehicle in the current state, and then compare and calculate it with the movement heading preset by the unmanned vehicle planning module to obtain the heading error value. The heading error value is the deviation angle between the positioning heading and the preset planned heading, and the heading error value is used as the second steering value to participate in the subsequent curvature calculation.

[0022] It can be understood that the second steering value refers to the offset angle between the current vehicle driving direction and the preset vehicle driving direction, which reflects the degree of heading deviation of the vehicle when driving on a rough road. That is, the larger the heading error value, the greater the offset error between the vehicle driving direction and the preset driving direction.

[0023] In some technical solutions, optionally, before determining the change in the height of the unmanned vehicle based on the roll angle, it also includes: obtaining the pitch angle of the unmanned vehicle; when the roll angle is not less than a first threshold, or the pitch angle is not less than a second threshold, controlling the unmanned vehicle to stop; otherwise, executing the step of determining the change in the height of the unmanned vehicle based on the roll angle.

[0024] In this technical solution, before calculating the change in the height difference of the unmanned vehicle according to the roll angle, the roll angle and the pitch angle must first be obtained. The acquisition method can be directly output by the combined navigation system according to the current positioning data, or directly collected by the tilt sensor and other methods. Then the obtained roll angle and pitch angle are compared with the threshold value set in advance by the unmanned vehicle for determination. It can be understood that when the roll angle obtained in real time is greater than or equal to the first threshold, or the pitch angle obtained in real time is greater than or equal to the second threshold, the unmanned vehicle is controlled to stop, and a parking signal, such as an alarm signal, is transmitted back to the remote control platform, indicating that the current road surface is not suitable for the unmanned vehicle to continue driving, there are safety hazards, and the unmanned vehicle is prevented from rolling over, etc., providing a protection for the unmanned vehicle and improving the safety of unmanned driving. On the contrary, when the roll angle obtained in real time is less than the first threshold, or the pitch angle obtained in real time is less than the second threshold, the vehicle is guaranteed to continue driving, and the roll angle is brought into the subsequent program for calculation, so that the calculation result is output to control the operation of the unmanned vehicle.

[0025] It can be understood that this method provides a protection mechanism for autonomous driving of unmanned vehicles, that is, the vehicle's driving posture is monitored and judged in real time based on road conditions information, and the vehicle automatically stops when the road conditions are not suitable for driving, thus providing protection for the safety of the unmanned vehicle.

[0026] In some technical solutions, optionally, the change in the height of the unmanned vehicle is determined based on the roll angle, specifically including: obtaining the body width of the unmanned vehicle and the parameter collection frequency; determining the left and right height difference values ​​of the unmanned vehicle based on the roll angle and the body width; obtaining the roll angle corresponding to the previous collection cycle through a tilt sensor, or obtaining the roll angle of the previous cycle output by the combined navigation system; determining the previous height difference value based on the parameter collection frequency; determining the change in the height of the unmanned vehicle based on the left and right height difference values ​​and the previous height difference value.

[0027] In this technical solution, before determining the change in drop, the body width and parameter acquisition frequency of the unmanned vehicle must be obtained first, wherein the body width can be directly entered according to pre-set data, or can be obtained in real time through the device. In addition, the parameter acquisition frequency is used to determine the collection period of the roll angle. It can be understood that since the unmanned vehicle changes in real time when driving on a rugged road, the acquired roll angle also changes in real time. First, according to the current roll angle and body width, the left and right drop values ​​of the body in the current situation are calculated using the formula, and then the roll angle corresponding to the previous collection period is collected through the tilt sensor, or the roll angle of the previous cycle output by the combined navigation system is obtained, and the vehicle width data is brought into the calculation to obtain the left and right drop values ​​of the body corresponding to the previous frame. Further, the drop change is determined by subtracting the current left and right drop values ​​from the left and right drop values ​​of the previous frame.

[0028] Among them, the parameter collection frequency can be set independently according to user needs. When the roll angle collected in the previous frame is the same as the roll angle collected currently, the corresponding left and right height difference values ​​are the same, and the height change of the unmanned vehicle is zero.

[0029] Using the above steps, the posture of the unmanned vehicle when driving on a rough road can be calculated. The obtained drop change is used for the subsequent calculation of the third steering value to prepare data for the subsequent calculation of the steering curvature, which helps to control the unmanned vehicle when driving on a rough road and make it drive more stably.

[0030] In some technical solutions, optionally, a third steering value is determined according to the change in height, specifically including: obtaining a second gain coefficient; and determining the third steering value according to the change in height, the second gain coefficient and the body width of the unmanned vehicle.

[0031] In this technical solution, the second gain coefficient is first obtained. The gain coefficient is not a fixed value. Before the unmanned vehicle drives, a suitable gain coefficient can be selected by debugging or calibration. The gain coefficient configured according to the debugging situation defaults to 1. For example, the initial value of the gain coefficient is set to 1. In the experiment of the unmanned vehicle on the rugged road, it is found that when the gain coefficient is set to 1, the adjustment effect of the unmanned vehicle is not ideal. Then the gain coefficient is adjusted by debugging or calibration, and then re-entered into the system operation until a suitable gain coefficient is selected to achieve the best vehicle control effect. Subsequently, the third steering value can be obtained by entering the formula for calculation by substituting the drop change, the second gain coefficient and the body width of the unmanned vehicle. Different from the first steering value and the second steering value, the third steering value is calculated based on the roll angle of the unmanned vehicle, that is, the left and right drop degree of the unmanned vehicle, which is equivalent to adding a roll angle offset to the coordinate offset and the direction offset. Through such a design, the curvature calculation can be more accurate, so that the unmanned vehicle can better drive on the rugged road and improve the driving stability of the unmanned vehicle.

[0032] In some technical solutions, optionally, a steering curvature value is determined based on the first steering value, the second steering value and the third steering value, specifically including: determining the sum of the first steering value, the second steering value and the third steering value as the fourth steering value; obtaining the wheelbase of the unmanned vehicle; and determining the steering curvature value based on the wheelbase and the fourth steering value.

[0033] In this technical solution, the final steering value, i.e., the fourth steering value, can be obtained by summing the first steering value, the second steering value, and the third steering value. Then, the wheelbase of the unmanned vehicle, i.e., the distance between the steering wheels of the unmanned vehicle, can be obtained and can be set in advance so that it can be used as a constant for subsequent calculations. Furthermore, the steering curvature value is calculated based on the wheelbase and the fourth steering value to control the unmanned vehicle on a rough road.

[0034] Simply put, the determination of the steering curvature value is closely related to the first steering value, the second steering value and the third steering value. It can be understood that the final curvature value can only be obtained under the joint action of the above three steering values. It is the cumulative effect of the three steering values. If any data is missing, the result obtained will not be accurate enough, and it will be impossible to accurately adjust the steering of the unmanned vehicle.

[0035] It should be added that, in addition to adding the first steering value, the second steering value and the third steering value, the fourth steering value can also be obtained by using an average weighted algorithm to obtain the same result and calculate the curvature.

[0036] The present invention controls the adjustment of the operation of the unmanned vehicle by calculating the steering curvature value. It is applicable to any unmanned vehicle that can adjust the movement direction by curvature. For vehicles with differential steering, unmanned vehicles that are not controlled by a steering wheel but by adjusting the speed of the steering wheel are more useful. By detecting the change of the roll angle and bringing it into the formula to calculate the steering curvature value, a certain curvature compensation is added to the vehicle control according to the change, and the vehicle control has good adaptability to rugged road conditions.

[0037] The second aspect of the present invention provides an unmanned vehicle control device, including: a path acquisition module: used to acquire the relative path information of the unmanned vehicle; a first calculation module: used to determine the first steering value corresponding to the relative path information according to the driving speed of the unmanned vehicle; a second calculation module: used to determine the second steering value according to the relative path information; an angle acquisition module: used to acquire the roll angle of the unmanned vehicle; a drop calculation module: used to determine the drop change of the unmanned vehicle according to the roll angle; a third calculation module: used to determine the third steering value according to the drop change; a curvature calculation module: used to determine the steering curvature value according to the first steering value, the second steering value and the third steering value; a control module: used to control the operation of the unmanned vehicle according to the steering curvature value. The device implements the steps of the unmanned vehicle control method as in any one of the above technical solutions.

[0038] According to the unmanned vehicle control device of the present invention, it mainly includes: a path acquisition module, a first calculation module, a second calculation module, an angle acquisition module, a drop calculation module, a third calculation module, a curvature calculation module and a control module. First, the coordinate information and heading information in the relative path information of the unmanned vehicle are acquired through the path acquisition module, and then the coordinate information in the relative path information is calculated with the positioning coordinate information output by the unmanned vehicle positioning module through the first calculation module to obtain the lateral error value, and further the first steering value is calculated through the lateral error value, the driving speed and the first gain coefficient. Through the second calculation module, the heading information in the relative path information is calculated with the positioning heading information output by the unmanned vehicle positioning module to obtain the heading error value, which is used as the second steering value. Through the angle acquisition module, the roll angle of the unmanned vehicle in real time is acquired. Through the drop calculation module, the left and right drop values ​​of the unmanned vehicle are calculated according to the roll angle and the vehicle width, and the drop change is determined by calculating the current left and right drop values ​​and the left and right drop values ​​of the previous frame. Through the third calculation module, the third steering value is calculated according to the drop change, the vehicle width and the second gain coefficient. The curvature calculation module calculates the first steering value, the second steering value and the third steering value to obtain the fourth steering value, and then uses the wheelbase and the fourth steering value to calculate and determine the steering curvature value. Finally, the control module uses the generated steering curvature value to control the operation of the unmanned vehicle.

[0039] The third aspect of the present invention provides an electronic device, including a processor, a memory, and a program or instruction stored in the memory and executable on the processor, which, when executed by the processor, implements the steps of the unmanned vehicle control method in any of the above-mentioned technical solutions.

[0040] A fourth aspect of the present invention provides a readable storage medium, which stores a computer program. When the computer program is executed by a processor, the steps of the unmanned vehicle control method in any of the above technical solutions are implemented.

[0041] A fifth aspect of the present invention provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the unmanned vehicle control method in any of the above technical solutions.

[0042] Additional aspects and advantages of the technical solutions of the present invention will become apparent in the following description or will be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flow chart of an unmanned vehicle control method according to an embodiment of the present invention is shown;

[0044] Figure 2 A flow chart of an unmanned vehicle control method according to an embodiment of the present invention is shown;

[0045] Figure 3 A flow chart of an unmanned vehicle control method according to an embodiment of the present invention is shown;

[0046] Figure 4 A flow chart of an unmanned vehicle control method according to an embodiment of the present invention is shown;

[0047] Figure 5 A flow chart of an unmanned vehicle control method according to an embodiment of the present invention is shown;

[0048] Figure 6 A flow chart of an unmanned vehicle control method according to an embodiment of the present application is shown;

[0049] Figure 7 A flow chart of an unmanned vehicle control method according to an embodiment of the present invention is shown;

[0050] Figure 8 A schematic diagram of the structure of an unmanned vehicle control device according to an embodiment of the present invention is shown;

[0051] Fig. 9 A schematic diagram of the structure of an electronic device according to an embodiment of the present invention is shown;

[0052] Fig.10A schematic flow chart of an unmanned vehicle control method according to an embodiment of the present invention is shown.

[0053] in, Figure 8 and Fig. 9 The corresponding relationship between the reference numerals and the component names is as follows:

[0054] 200: unmanned vehicle control device; 201: path acquisition module; 202: first calculation module; 203: second calculation module; 204: angle acquisition module; 205: drop calculation module; 206: third calculation module; 207: curvature calculation module; 208: control module.

[0055] 300: electronic device; 302: processor; 304: memory. DETAILED DESCRIPTION

[0056] In order to more clearly understand the above-mentioned purposes, features and advantages of the embodiments of the present invention, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and specific implementation methods. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0057] In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the embodiments of the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present application is not limited to the specific embodiments disclosed below.

[0058] Refer to the following Figures 1 to 10 The present invention describes an unmanned vehicle control method, device, electronic device, readable storage medium and chip provided according to some embodiments of the present invention.

[0059] This embodiment provides a method for controlling an unmanned vehicle. Figure 1 As shown, including:

[0060] Step S102: Obtaining relative path information of the unmanned vehicle;

[0061] Step S104: determining a first turning value corresponding to the relative path information according to the driving speed of the unmanned vehicle;

[0062] Step S106: determining a second turning value according to the relative path information;

[0063] Step S108: Obtaining the roll angle of the unmanned vehicle;

[0064] Step S110: determining the height change of the unmanned vehicle according to the roll angle;

[0065] Step S112: determining a third turning value according to the change in the height difference;

[0066] Step S114: determining a turning curvature value according to the first turning value, the second turning value and the third turning value;

[0067] Step S116: Control the operation of the unmanned vehicle according to the steering curvature value.

[0068] The unmanned vehicle control method provided in this embodiment first needs to obtain the relative path information of the unmanned vehicle before controlling the unmanned vehicle. For example, the unmanned vehicle planning path can be specified according to the planning module in the unmanned vehicle or a submodule with a similar planning path function, and a preset route can be provided to the unmanned vehicle so that the unmanned vehicle can travel along the preset route. Among them, this relative path information includes path coordinate information and path heading information. The path coordinate information can enable the unmanned vehicle to reach the specified coordinate point, and the path heading information can enable the unmanned vehicle to travel in a predetermined direction, which helps the unmanned vehicle to accurately travel to the destination. After obtaining the relative path information of the unmanned vehicle, the real-time positioning coordinate information of the unmanned vehicle is given by the positioning module of the unmanned vehicle, and the positioning coordinate information and the path coordinate information preset by the planning module are used for calculation to obtain the lateral error value of the current vehicle, that is, the distance of the lateral error, and obtain the current driving speed of the unmanned vehicle. The first steering value is calculated by the current vehicle speed, the lateral error value and the gain coefficient set in advance, which is used for subsequent calculation of the steering curvature value as data preparation. At the same time, the real-time positioning and heading information of the unmanned vehicle is given by the positioning module of the unmanned vehicle. The positioning and heading information and the path and heading information preset by the planning module are used to calculate the vehicle heading error value of the unmanned vehicle, that is, the angle of the heading error. This error value is used as the second steering value for subsequent calculation of the steering curvature value as data preparation. In addition, before calculating the curvature, it is also necessary to obtain the roll angle and pitch angle of the unmanned vehicle in its current posture. The specific acquisition method can be in various forms. For example, the combined navigation module can output the roll angle and pitch angle of the current unmanned vehicle based on the positioning data, or the roll angle and pitch angle of the current unmanned vehicle can be directly collected through the inclination sensor. After that, the obtained roll angle and pitch angle need to be judged, and the roll angle and pitch angle are compared with the thresholds set in advance to determine whether the roll angle and pitch angle have reached the threshold. It can be understood that this is for the unmanned vehicle. Before continuing to the next step of calculation, the system will judge the acquired data and issue different instructions according to the judgment results. If the roll angle is greater than or equal to the preset roll angle threshold, or the pitch angle is greater than or equal to the preset pitch angle threshold, the unmanned vehicle will actively stop, indicating that the vehicle is too bumpy during driving and the current road conditions are not suitable for the vehicle to continue driving. There are safety hazards, which can better protect the safety of the vehicle. If the roll angle is less than the preset roll angle threshold, or the pitch angle is less than the preset pitch angle threshold, the vehicle will be controlled to continue driving and the roll angle will be brought into the next step of calculation.

[0069] According to the roll angle and the width of the vehicle body, the left and right drop value of the vehicle body is obtained. The method for obtaining the width of the vehicle body can be designed by entering the system in advance according to the vehicle width information, or the vehicle width can be collected in real time by sensors and other equipment to prevent accidents during driving that cause the vehicle width data to change, thereby generating calculation errors. Further, the roll angle corresponding to the previous acquisition cycle is obtained by using a tilt sensor, or the roll angle of the previous cycle is output by the combined navigation system, and the left and right drop value of the vehicle body corresponding to the previous frame is calculated in the same way, and the drop change is obtained by subtracting the left and right drop value of the previous frame. Further, according to the drop change and the appropriate gain coefficient, the third steering value is calculated, and then the first steering value, the second steering value and the third steering value are added and summed to obtain the final steering value. Finally, the final steering value is brought in through the curvature formula, and the steering curvature value is output in combination with the wheelbase value of the unmanned vehicle. The unmanned vehicle is controlled by the steering curvature value so that it can drive stably on a rugged road.

[0070] In general, the present invention compares and calculates the positioning information and the relative path information preset by the planning module to obtain the lateral error value and the heading error value, and then further calculates and determines the first steering value and the second steering value using the lateral error value and the heading error value. According to the combined navigation system and the tilt sensor, the real-time roll angle and pitch angle are obtained, and the unmanned vehicle is controlled to stop by judging the two with the threshold, that is, when the roll angle or the pitch angle is greater than or equal to the threshold, the unmanned vehicle is controlled to stop, and when it is less than the threshold, the roll angle is further calculated to obtain the third steering value, and the first steering value, the second steering value and the third steering value are summed to obtain the final steering value, and the final steering value is substituted into the curvature formula to calculate the steering curvature value, and the purpose of controlling the operation of the unmanned vehicle is achieved through the steering curvature value.

[0071] It should be added that the gain coefficient is not a fixed value. Before the unmanned vehicle drives, a suitable gain coefficient can be selected through debugging or calibration. The gain coefficient configured according to the debugging situation defaults to 1. For example, the initial value of the gain coefficient is set to 1. In the experiment of the unmanned vehicle on rough roads, it was found that when the gain coefficient was set to 1, the adjustment effect of the unmanned vehicle was not ideal. Then the gain coefficient was adjusted by debugging or calibration, and then re-introduced into the system operation until a suitable gain coefficient was selected to achieve the best vehicle control effect.

[0072] In short, the present invention is an improvement on the existing Stanley algorithm. Compared with the Stanley algorithm, the present invention adds roll angle change detection and obtains the final steering curvature value by calculation. When the road surface is rough or the vehicle is pressed on a stone or step on one side, the roll angle change is judged and a certain curvature compensation value is added by formula to ensure that the vehicle completes the tracking error adjustment in time, prevents tracking response delay, and thus causes the tracking error to increase, thereby enhancing the adaptability and stability of the unmanned vehicle on rough roads. Especially for differential steering vehicles, curvature compensation provides a control possibility for differential steering vehicles to drive on rough roads, improves the adaptability to driving on complex roads, and at the same time, through real-time detection and judgment of the roll angle and pitch angle, it is judged whether the current road conditions are suitable for the vehicle to continue driving, thereby avoiding safety hazards during driving and ensuring vehicle safety.

[0073] Alternatively, if Figure 2 As shown, step S104: determining a first turning value corresponding to the relative path information according to the driving speed of the unmanned vehicle, specifically includes:

[0074] Step S1042: Obtaining the positioning coordinate information and the first gain coefficient of the unmanned vehicle;

[0075] Step S1044: determining a lateral error value according to the coordinate information of the relative path information and the positioning coordinate information;

[0076] Step S1046: Determine a first steering value according to the first gain coefficient, the lateral error value and the driving speed.

[0077] In this embodiment, it is first necessary to obtain the positioning coordinate information and the first gain coefficient of the unmanned vehicle. The positioning coordinate information is used to compare and calculate with the relative path coordinate information preset by the planning module, so as to obtain the lateral error value of the vehicle. The lateral error value can be understood as the distance between the current positioning point and the preset planning point. The deviation distance between the current vehicle position and the preset vehicle position is calculated in real time. Furthermore, the current vehicle speed is detected by using sensors or other electronic devices, and the first steering value is calculated by substituting the current vehicle speed and the gain coefficient constant set in advance into the formula.

[0078] Among them, the gain coefficient can be obtained through debugging or calibration methods, that is, before the unmanned vehicle drives, during the detection process, the appropriate gain coefficient is selected by debugging or calibration to achieve the best control effect of the unmanned vehicle.

[0079] It should be added that the relative path information can be obtained through the planning module under the unmanned vehicle automatic driving system or a sub-module with the same planning function, or it can be directly entered into the unmanned vehicle by the user according to the established route information, and the unmanned vehicle directly executes the call.

[0080] In a specific embodiment, the lateral error is e, the gain coefficient is k1, that is, the first gain coefficient is k1, the current vehicle speed is v, and the first steering value θ1 is according to the following formula:

[0081] Θ1=arctan(k1×e / v)

[0082] In short, the lateral error value is obtained by calculating the current positioning coordinates of the unmanned vehicle and the preset coordinates, and then the lateral error value is further calculated by obtaining the vehicle speed and gain coefficient to obtain the first steering value, so as to prepare data for the subsequent curvature calculation and thus control the operation of the unmanned vehicle.

[0083] Alternatively, if Figure 3 As shown, step S106: determining a second turning value according to the relative path information, specifically includes:

[0084] Step S1062: Obtaining the positioning and heading information of the unmanned vehicle;

[0085] Step S1064: determining a heading error value according to the heading information of the relative path information and the positioning heading information;

[0086] Step S1066: Determine a second steering value according to the heading error value.

[0087] In this embodiment, it is first necessary to obtain the positioning and heading information of the unmanned vehicle, that is, the movement heading of the unmanned vehicle in the current state, and then compare and calculate it with the movement heading preset by the unmanned vehicle planning module to obtain the heading error value. The heading error value is the deviation angle between the positioning heading and the preset planned heading, and the heading error value is used as the second steering value to participate in the subsequent curvature calculation.

[0088] It can be understood that the second steering value refers to the offset angle between the current vehicle driving direction and the preset vehicle driving direction, which reflects the degree of heading deviation of the vehicle when driving on a rough road. That is, the larger the heading error value, the greater the offset error between the vehicle driving direction and the preset driving direction.

[0089] In a specific embodiment, the heading error value of the vehicle is δ, and the second steering value θ2 = δ.

[0090] Alternatively, if Figure 4 As shown, before step S110: determining the height change of the unmanned vehicle according to the roll angle, the following steps are also included:

[0091] Step S1092: Obtain the pitch angle of the unmanned vehicle;

[0092] Step S1094: When the roll angle is not less than the first threshold, or the pitch angle is not less than the second threshold, the unmanned vehicle is controlled to stop;

[0093] Step S1096: Otherwise, execute the step of determining the change in height of the unmanned vehicle based on the roll angle.

[0094] In this embodiment, before calculating the change in the height difference of the unmanned vehicle according to the roll angle, the roll angle and the pitch angle must first be obtained. The acquisition method can be directly output by the combined navigation system according to the current positioning data, or directly collected by the tilt sensor, etc., and then the obtained roll angle and pitch angle are compared with the threshold value set in advance by the unmanned vehicle for determination. It can be understood that when the roll angle obtained in real time is greater than or equal to the first threshold, or the pitch angle obtained in real time is greater than or equal to the second threshold, the unmanned vehicle is controlled to stop, indicating that the current road surface is not suitable for the unmanned vehicle to continue driving, there are safety hazards, and the unmanned vehicle is prevented from rolling over, etc., providing a protection for the unmanned vehicle and improving the safety of unmanned driving. On the contrary, when the roll angle obtained in real time is less than the first threshold, or the pitch angle obtained in real time is less than the second threshold, the vehicle is guaranteed to continue driving, and the roll angle is brought into the subsequent program for calculation, so that the calculation result is output to control the operation of the unmanned vehicle.

[0095] It can be understood that this method provides a protection mechanism for autonomous driving of unmanned vehicles, that is, the vehicle's driving posture is monitored and judged in real time based on road conditions information, and the vehicle automatically stops when the road conditions are not suitable for driving, thus providing protection for the safety of the unmanned vehicle.

[0096] like Figure 5 As shown, step S110: determining the change in height of the unmanned vehicle according to the roll angle, specifically includes:

[0097] Step S1101: Obtain the body width and parameter collection frequency of the unmanned vehicle;

[0098] Step S1102: determining the left-right height difference of the unmanned vehicle according to the roll angle and the vehicle width;

[0099] Step S1103: obtaining the roll angle corresponding to the previous acquisition cycle through the tilt sensor, or obtaining the roll angle of the previous cycle output by the integrated navigation system;

[0100] Step S1104: determining the previous drop value according to the parameter acquisition frequency;

[0101] Step S1105: Determine the change in height of the unmanned vehicle based on the left and right height differences and the previous height difference.

[0102] In this embodiment, before determining the change in height, the body width and parameter acquisition frequency of the unmanned vehicle must be obtained first, wherein the body width can be directly entered according to pre-set data, or can be obtained in real time through the device. In addition, the parameter acquisition frequency is used to determine the collection period of the roll angle. It can be understood that since the unmanned vehicle changes in real time when driving on a rugged road, the acquired roll angle also changes in real time. First, according to the current roll angle and body width, the left and right drop values ​​of the body in the current situation are calculated using a formula, and then the roll angle corresponding to the previous collection period is collected through the tilt sensor, or the roll angle of the previous cycle output by the combined navigation system is obtained, and the vehicle width data is brought into the calculation to obtain the left and right drop values ​​of the body corresponding to the previous frame. Further, the drop change is determined by subtracting the current left and right drop values ​​from the left and right drop values ​​of the previous frame.

[0103] Among them, the parameter collection frequency can be set independently according to user needs. When the roll angle collected in the previous frame is the same as the roll angle collected currently, the corresponding left and right height difference values ​​are the same, and the height change of the unmanned vehicle is zero.

[0104] In a specific embodiment, the roll angle is r, the vehicle width is L, and the current left-right drop value of the vehicle body is d, according to the following formula:

[0105] d = L × sin (r)

[0106] Take the left and right drop value of the vehicle body in the previous frame as d0, and the drop change The calculation formula is as follows:

[0107]

[0108] Using the above steps, the posture of the unmanned vehicle when driving on a rough road can be calculated. The obtained drop change is used for the subsequent calculation of the third steering value to prepare data for the subsequent calculation of the steering curvature, which helps to control the unmanned vehicle when driving on a rough road and make it drive more stably.

[0109] like Figure 6 As shown, step S112: determining a third turning value according to the change in the height difference, specifically includes:

[0110] Step S1122: obtaining a second gain coefficient;

[0111] Step S1124: Determine the third steering value according to the height change, the second gain coefficient and the body width of the unmanned vehicle.

[0112] In this embodiment, the second gain coefficient is first obtained. The gain coefficient is not a fixed value. Before the unmanned vehicle drives, a suitable gain coefficient can be selected by debugging or calibration. The gain coefficient configured according to the debugging situation defaults to 1. For example, the initial value of the gain coefficient is set to 1. In the experiment of the unmanned vehicle on the rough road, it is found that when the gain coefficient is set to 1, the adjustment effect of the unmanned vehicle is not ideal. Then the gain coefficient is adjusted by debugging or calibration, and then re-entered into the system operation until a suitable gain coefficient is selected to achieve the best vehicle control effect. Subsequently, the third steering value can be obtained by entering the formula for calculation by the drop change, the second gain coefficient and the body width of the unmanned vehicle. Different from the first steering value and the second steering value, the third steering value is calculated based on the roll angle of the unmanned vehicle, that is, the left and right drop degree of the unmanned vehicle, which is equivalent to adding a roll angle offset to the coordinate offset and the direction offset. Through such a design, the curvature calculation can be more accurate, so that the unmanned vehicle can better drive on the rough road and improve the driving stability of the unmanned vehicle.

[0113] In a specific embodiment, the gain coefficient is k2, that is, the second gain coefficient is k2, the vehicle width is L, and the height change is The third steering value θ3 satisfies the following formula:

[0114]

[0115] like Figure 7 As shown, step S114: determining the turning curvature value according to the first turning value, the second turning value and the third turning value, specifically includes:

[0116] Step S1142: determining that the sum of the first steering value, the second steering value and the third steering value is a fourth steering value;

[0117] Step S1144: obtaining the wheelbase of the unmanned vehicle;

[0118] Step S1146: Determine the turning curvature value according to the wheelbase and the fourth turning value.

[0119] In this embodiment, the final steering value, i.e., the fourth steering value, can be obtained by summing the first steering value, the second steering value, and the third steering value. Then, the wheelbase of the unmanned vehicle, i.e., the distance between the steering wheels of the unmanned vehicle, can be obtained and can be set in advance so that it can be brought into the subsequent calculation as a constant. Furthermore, the steering curvature value is calculated based on the wheelbase and the fourth steering value to control the unmanned vehicle driving on a rough road.

[0120] Simply put, the determination of the steering curvature value is closely related to the first steering value, the second steering value and the third steering value. It can be understood that the final curvature value can only be obtained under the joint action of the above three steering values. It is the cumulative effect of the three steering values. If any data is missing, the result obtained will not be accurate enough, and it will be impossible to accurately adjust the steering of the unmanned vehicle.

[0121] It should be added that, in addition to adding the first steering value, the second steering value and the third steering value, the fourth steering value can also be obtained by using an average weighted algorithm to obtain the same result and calculate the curvature.

[0122] In a specific embodiment, the first turning value is Θ1, the second turning value is Θ2, the third turning value is Θ3, and the fourth turning value Θ is calculated as follows:

[0123] Θ=Θ1+Θ2+Θ3

[0124] Taking the wheelbase as l, the curvature (kappa) calculation formula is as follows:

[0125] kappa=sin(Θ) / l

[0126] The present invention controls the adjustment of the operation of the unmanned vehicle by calculating the steering curvature value. It is applicable to any unmanned vehicle that can adjust the movement direction by curvature. For vehicles with differential steering, unmanned vehicles that are not controlled by a steering wheel but by adjusting the speed of the steering wheel are more useful. By detecting the change of the roll angle and bringing it into the formula to calculate the steering curvature value, a certain curvature compensation is added to the vehicle control according to the change, and the vehicle control has good adaptability to rugged road conditions.

[0127] like Figure 8 As shown, the embodiment of the present application provides an unmanned vehicle control device 200. The unmanned vehicle control device 200 includes: a path acquisition module 201, a first calculation module 202, a second calculation module 203, an angle acquisition module 204, a drop calculation module 205, a third calculation module 206, a curvature calculation module 207, and a control module 208.

[0128] Among them, firstly, the coordinate information and heading information in the relative path information of the unmanned vehicle are obtained through the path acquisition module 201, and then the coordinate information in the relative path information is calculated with the positioning coordinate information output by the unmanned vehicle positioning module through the first calculation module 202 to obtain the lateral error value, and further the first steering value is calculated through the lateral error value, the driving speed and the first gain coefficient. Through the second calculation module 203, the heading information in the relative path information is calculated with the positioning heading information output by the unmanned vehicle positioning module to obtain the heading error value, which is used as the second steering value. Through the angle acquisition module 204, the roll angle of the unmanned vehicle in real time is obtained. Through the drop calculation module 205, the left and right drop values ​​of the unmanned vehicle are calculated according to the roll angle and the vehicle width, and the drop change is determined by calculating the current left and right drop values ​​and the left and right drop values ​​of the previous frame. Through the third calculation module 206, the third steering value is calculated according to the drop change, the vehicle width and the second gain coefficient. The curvature calculation module 207 calculates the first steering value, the second steering value and the third steering value to obtain a fourth steering value, and then uses the wheelbase and the fourth steering value to calculate and determine the steering curvature value. Finally, the control module 208 controls the operation of the unmanned vehicle using the generated steering curvature value.

[0129] In some embodiments, optionally, the device is also used to: obtain positioning coordinate information and a first gain coefficient of the unmanned vehicle; determine a lateral error value based on the coordinate information of the relative path information and the positioning coordinate information; determine a first steering value based on the first gain coefficient, the lateral error value and the driving speed.

[0130] In some embodiments, optionally, the device is also used to: obtain positioning heading information of the unmanned vehicle; determine a heading error value based on the heading information of the relative path information and the positioning heading information; and determine a second steering value based on the heading error value.

[0131] In some embodiments, optionally, the device is also used to: obtain the pitch angle of the unmanned vehicle; control the unmanned vehicle to stop when the roll angle is not less than a first threshold, or the pitch angle is not less than a second threshold; otherwise, execute the step of determining the change in the height of the unmanned vehicle based on the roll angle.

[0132] In some embodiments, optionally, the device is also used to: obtain the body width and parameter collection frequency of the unmanned vehicle; determine the left and right drop values ​​of the unmanned vehicle based on the roll angle and the body width; obtain the roll angle corresponding to the previous collection cycle through the tilt sensor, or obtain the roll angle of the previous cycle output by the combined navigation system; determine the previous drop value based on the parameter collection frequency; determine the drop change of the unmanned vehicle based on the left and right drop values ​​and the previous drop value.

[0133] In some embodiments, optionally, the device is also used to: obtain a second gain coefficient; and determine a third steering value based on the height change, the second gain coefficient and the body width of the unmanned vehicle.

[0134] In some embodiments, optionally, the device is also used to: determine the sum of the first steering value, the second steering value and the third steering value as a fourth steering value; obtain the wheelbase of the unmanned vehicle; and determine the steering curvature value based on the wheelbase and the fourth steering value.

[0135] like Fig. 9 As shown, the third aspect of the present invention provides an electronic device 300, including a processor 302, a memory 304, and a program or instruction stored in the memory 304 and executable on the processor 302. When the program or instruction is executed by the processor 302, the steps of the unmanned vehicle control method of the first aspect of the present invention are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0136] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned electronic devices and non-electronic devices.

[0137] The fourth aspect of the present invention provides a readable storage medium, which stores programs or instructions. When the program or instructions are executed by a processor, the steps of the unmanned vehicle control method of the first aspect of the present invention are implemented, and the same technical effects can be achieved. To avoid repetition, they will not be repeated here.

[0138] The methods may be implemented in a variety of different ways depending on the specific features and / or example applications. For example, the methods may be implemented by a combination of hardware, firmware, and / or software. For example, in a hardware implementation, the processor may be implemented in one or more application-specific integrated circuits, digital signal processors, digital signal processing devices, programmable logic devices, field programmable gate arrays, controllers, microcontrollers, microprocessors, electronic devices, other device units for performing the above functions, and / or combinations thereof.

[0139] A computer readable storage medium may be a tangible device that can retain and store instructions for use by an instruction execution device. A computer readable storage medium may be an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above devices, but is not limited thereto. A non-exhaustive list of more specific examples of computer readable storage media includes: a portable computer floppy disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, a static random access memory, a portable optical disk read-only memory, a digital universal disk, a memory card, a floppy disk, an encoding mechanical device (such as a punched card or a groove with a raised structure having instructions recorded thereon), and any suitable combination of the above devices. The computer readable storage medium used herein should not be understood as a transmission signal itself, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium, or an electrical signal transmitted through a wire, etc.

[0140] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0141] The fifth aspect of the present invention provides a chip, which includes a processor and a communication interface. The communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the unmanned vehicle control method of the first aspect of the present invention, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0142] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0143] The present invention provides an unmanned vehicle control method, device, electronic device, readable storage medium and chip, which are improvements on the existing Stanley algorithm. Compared with the Stanley algorithm, the present invention adds roll angle change detection, and obtains the final steering curvature value by calculation. When the road surface is rough or the vehicle is pressed on a stone or step on one side, the roll angle change is judged, and a certain curvature compensation value is added by using a formula to ensure that the vehicle completes the tracking error adjustment in time, and prevents the tracking response delay, which leads to an increase in tracking error, thereby enhancing the adaptability and stability of the unmanned vehicle when driving on rough roads. In particular, for differential steering vehicles, a curvature compensation method is used to provide a control possibility for differential steering vehicles to drive on rough roads, thereby improving the adaptability to driving on complex roads. At the same time, through real-time detection and judgment of the roll angle and pitch angle, it is judged whether the current road condition is suitable for the vehicle to continue driving, thereby avoiding safety hazards caused during driving and ensuring vehicle safety.

[0144] In a specific embodiment, the present invention provides a method for lateral control of an unmanned vehicle on a rough road, namely, an unmanned vehicle control method.

[0145] In the current field of autonomous driving, driving is generally based on structured roads, so the impact of the road surface on the motion control algorithm is not considered separately. The impact of the road surface allows the control algorithm to adjust itself in the form of errors. However, when an unmanned vehicle is driving on a rough road, the control method based on the algorithm's self-adjustment will have an error response delay, resulting in an increase in control error.

[0146] Taking into account that the vehicle will tilt to a certain extent when traveling on a rugged road, the present invention obtains the changes in the vehicle's roll angle and pitch angle through combined navigation, detects that the vehicle is in an unstable state, calculates the change in the height difference of the unmanned vehicle according to the tilt angle, and applies an additional corrective steering value to the unmanned vehicle based on this.

[0147] In the Stanley control algorithm that is widely used at present, the wheel turning angle required to drive to the target path is calculated based on the vehicle's heading angle and lateral deviation by utilizing the vehicle's steering geometry. When driving on structured roads, the algorithm has a relatively small tracking error. When the road surface is rough, there will be a delay in responding to the tracking error, which will cause the tracking error to become larger.

[0148] Compared with the Stanley control algorithm, this method adds roll angle change detection. When the road surface is rough or the vehicle presses on stones or steps on one side, the roll angle change is judged and the steering wheel compensation steering value is calculated through the formula to ensure that the vehicle can complete the tracking error adjustment in real time.

[0149] The advantages of the present invention are as follows:

[0150] Based on the Stanley control algorithm, this method takes into account the impact of rugged roads on vehicle control. By detecting the change in roll angle, a certain curvature compensation is added to the vehicle control according to the change. This method has good adaptability to vehicle control on rugged roads.

[0151] Judge the road conditions in real time and automatically stop the vehicle when the road conditions are not suitable for driving to ensure safety.

[0152] The specific implementation plan is as follows:

[0153] Step 1: Calculate the vehicle lateral error e according to the relative path coordinates specified by the planning module, select the appropriate gain coefficient k1 through debugging or calibration methods, obtain the current vehicle speed v, and calculate the first front wheel steering value Θ1 = arctan (k1×e / v).

[0154] Step 2: According to the relative path heading specified by the planning module, calculate the vehicle heading error δ as the second front wheel steering value θ2=δ.

[0155] Step 3: According to the positioning data output by the integrated navigation, obtain the current roll angle r and pitch angle p.

[0156] Step 4: Determine whether the roll angle r and pitch angle p have reached the threshold. If they reach the threshold, the vehicle will stop automatically to ensure vehicle safety.

[0157] Step 5: According to the roll angle r and the vehicle width L, obtain the left-right height difference of the vehicle body d=L×sin(r).

[0158] Step 6: Calculate the difference from the previous frame Where d0 represents the left-right height difference of the vehicle body in the previous frame.

[0159] Step 7: According to the change in height, select the appropriate gain coefficient k2 through debugging or calibration method, and calculate the third front wheel steering value

[0160] Step 8: Combining the first, second and seventh steps, we get the final front wheel steering value Θ=Θ1+Θ2+Θ3.

[0161] Step 9: Output Θ as the lateral control result.

[0162] Step 10: For differential steering vehicles, the vehicle is controlled by obtaining the steering curvature through curvature kappa = sin(Θ) / l, where l is the wheelbase.

[0163] In a specific embodiment, Fig.10 As shown, the unmanned vehicle control method of the present invention is as follows:

[0164] Step S201 starts; Step S202 calculates the vehicle lateral error e according to the relative path coordinates specified by the planning module; Step S203 calculates the front wheel steering Θ1=arctan(k1×e / v) according to the Stanley algorithm; Step S204 calculates the vehicle heading error δ according to the relative path heading specified by the planning module; Step S205 calculates the front wheel steering Θ2=δ according to the Stanley algorithm; Step S206 obtains the current roll angle r and pitch angle according to the positioning data of the integrated navigation module p; Step S207: if the roll angle r exceeds the threshold or the pitch angle p exceeds the threshold, the vehicle stops and an alarm is sounded; Step S208: according to the front roll angle r and the vehicle width L, the current left-right drop d=L×sin(r) is calculated; Step S209: the drop change φ=d–d0 compared with the previous frame is calculated; Step S210: according to the drop change φ, the front wheel steering Θ3=arcsin(k2×φ / L) is calculated; Step S211: the curvature kappa=sin(Θ) / L is used to obtain the steering curvature; Step S212: end. k1, k2 are gain coefficients configured according to the debugging situation, and the default value is 1.

[0165] It should be noted that, in this article, the terms "comprise", "include" or any other variant thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise one..." do not exclude the presence of other identical elements in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0166] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A method for controlling an unmanned vehicle, characterized in that: include: Get the relative path information of the unmanned vehicle; Determining a first steering value corresponding to the relative path information according to the driving speed of the unmanned vehicle; Determining a second turning value according to the relative path information; Obtaining a roll angle of the unmanned vehicle; Determining a change in height of the unmanned vehicle according to the roll angle; Determining a third turning value according to the change in the height difference; determining a steering curvature value according to the first steering value, the second steering value, and the third steering value; The operation of the unmanned vehicle is controlled according to the steering curvature value.

2. The unmanned vehicle control method according to claim 1, characterized in that: The determining, according to the driving speed of the unmanned vehicle, a first turning value corresponding to the relative path information specifically includes: Obtaining positioning coordinate information and a first gain coefficient of the unmanned vehicle; Determining a lateral error value according to the coordinate information of the relative path information and the positioning coordinate information; A first steering value is determined according to the first gain coefficient, the lateral error value and the driving speed.

3. The unmanned vehicle control method according to claim 1, characterized in that: The determining the second turning value according to the relative path information specifically includes: Obtaining positioning and heading information of the unmanned vehicle; Determining a heading error value according to the heading information of the relative path information and the positioning heading information; A second steering value is determined according to the heading error value.

4. The unmanned vehicle control method according to claim 1, characterized in that: Before determining the height change of the unmanned vehicle according to the roll angle, the method further includes: Obtaining the pitch angle of the unmanned vehicle; When the roll angle is not less than a first threshold value, or the pitch angle is not less than a second threshold value, controlling the unmanned vehicle to stop; Otherwise, execute the step of determining the change in height of the unmanned vehicle based on the roll angle.

5. The unmanned vehicle control method according to claim 1, characterized in that: Determining the change in height of the unmanned vehicle according to the roll angle specifically includes: Obtaining the body width and parameter collection frequency of the unmanned vehicle; Determining a left-right drop value of the unmanned vehicle according to the roll angle and the vehicle body width; Obtain the roll angle corresponding to the previous acquisition cycle through the tilt sensor, or obtain the roll angle of the previous cycle output by the integrated navigation system; Determine the previous drop value according to the parameter acquisition frequency; The change in height of the unmanned vehicle is determined according to the left-right height difference value and the previous height difference value.

6. The unmanned vehicle control method according to claim 1, characterized in that: Determining the third turning value according to the drop change specifically includes: Obtaining a second gain coefficient; A third steering value is determined according to the height difference change, the second gain coefficient and the body width of the unmanned vehicle.

7. The unmanned vehicle control method according to claim 1, characterized in that: The determining the turning curvature value according to the first turning value, the second turning value and the third turning value specifically includes: Determine a sum of the first steering value, the second steering value and the third steering value as a fourth steering value; Obtaining the wheelbase of the unmanned vehicle; A turning curvature value is determined according to the wheelbase and the fourth turning value.

8. An unmanned vehicle control device, characterized in that: include: Path acquisition module: used to obtain the relative path information of the unmanned vehicle; A first calculation module: used for determining a first turning value corresponding to the relative path information according to the driving speed of the unmanned vehicle; A second calculation module: used for determining a second turning value according to the relative path information; Angle acquisition module: used to obtain the roll angle of the unmanned vehicle; A drop calculation module is used to determine the drop change of the unmanned vehicle according to the roll angle; A third calculation module is used to determine a third turning value according to the change in the height difference; A curvature calculation module: used to determine a turning curvature value according to the first turning value, the second turning value and the third turning value; Control module: used for controlling the operation of the unmanned vehicle according to the steering curvature value; The unmanned vehicle control device is used to implement the steps of the unmanned vehicle control method according to any one of claims 1 to 7.

9. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the unmanned vehicle control method as described in any one of claims 1 to 7.

10. A readable storage medium, characterized in that: The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of the unmanned vehicle control method as described in any one of claims 1 to 7 are implemented.

11. A chip, characterized in that: The chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run programs or instructions to implement the steps of the unmanned vehicle control method as described in any one of claims 1 to 7.

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