阅读说明：本技术 零位偏差动态标定方法、装置、电子设备及存储介质 (Zero offset dynamic calibration method and device, electronic equipment and storage medium ) 是由 袁光 于 2021-09-01 设计创作，主要内容包括：本申请实施例提供一种零位偏差动态标定方法、装置、电子设备及存储介质,通过在目标车辆行驶过程中,获取道路图像数据,并根据道路图像数据,确定道路标识,其中,道路标识用于指示车道方向；根据道路标识,确定道路状况信息,道路状况信息用于表征目标车辆的前方车道的弯曲度；若道路状况信息满足预设的道路条件,则执行标定程序,标定程序用于对目标车辆的转向轮进行偏差标定,生成偏差标定数据,偏差标定数据用补偿目标车辆行驶过程中转向轮的零位偏差。通过在车辆行驶过程中,对道路状况信息进行预测,判断前方车道在满足弯曲度条件下,再执行标定程序,实现了在车辆行驶过程中的动态零位偏差标定,提高偏差标定的准确性和实时性。(The embodiment of the application provides a method and a device for dynamically calibrating zero offset, electronic equipment and a storage medium, wherein road image data are acquired in the running process of a target vehicle, and a road mark is determined according to the road image data, wherein the road mark is used for indicating the lane direction; determining road condition information according to the road identification, wherein the road condition information is used for representing the curvature of a front lane of the target vehicle; and if the road condition information meets the preset road condition, executing a calibration program, wherein the calibration program is used for carrying out deviation calibration on the steering wheel of the target vehicle to generate deviation calibration data, and the deviation calibration data is used for compensating the zero deviation of the steering wheel in the running process of the target vehicle. By predicting the road condition information in the vehicle running process, judging that the front lane meets the curvature condition and then executing a calibration program, the dynamic zero offset calibration in the vehicle running process is realized, and the accuracy and the real-time performance of the offset calibration are improved.)

1. A zero offset dynamic calibration method is characterized by comprising the following steps:

acquiring road image data in the running process of a target vehicle, and determining a road mark according to the road image data, wherein the road mark is used for indicating the lane direction;

determining road condition information according to the road mark, wherein the road condition information is used for representing the curvature of a front lane of the target vehicle;

and if the road condition information meets the preset road condition, executing a calibration program, wherein the calibration program is used for carrying out deviation calibration on a steering wheel of the target vehicle to generate deviation calibration data, and the deviation calibration data is used for compensating the zero deviation of the steering wheel in the running process of the target vehicle.

2. The method of claim 1, wherein determining road condition information based on the road identification comprises:

acquiring identification coordinates corresponding to the road identification;

determining curvature information according to the identification coordinates, wherein the curvature information represents the curvature of a lane in front of the target vehicle;

and determining road condition information according to the curvature information.

3. The method of claim 2, wherein determining curvature information from the identified coordinates comprises:

determining at least two road reference points according to the identification coordinates, wherein the road reference points are distributed at equal intervals;

and determining the curvature information according to the position relation between the adjacent road reference points.

4. The method of claim 1, wherein identifying a road sign from the road image data comprises:

acquiring preset target characteristic information, wherein the target characteristic information represents an identification target in an image identification process;

and carrying out image recognition on the road image data according to the target characteristic information to obtain the road identifier.

5. The method of claim 1, further comprising:

acquiring the real-time speed of the target vehicle;

if the road condition information meets the preset road condition, executing a calibration program, including:

and if the road condition information meets the preset road condition and the real-time vehicle speed is less than the preset vehicle speed threshold value, executing a calibration program.

6. The method of claim 5, further comprising:

acquiring a current advancing direction angle of a vehicle, wherein the advancing direction angle represents an included angle between the target vehicle and a front lane;

if the road condition information meets the preset road condition and the real-time vehicle speed is less than the preset vehicle speed threshold value, executing a calibration program, comprising:

and if the road condition information meets the preset road condition, the real-time vehicle speed is less than the preset vehicle speed threshold value, and the advancing direction angle is less than the preset advancing direction angle threshold value, executing a calibration program.

7. The method according to any of claims 1-6, wherein a calibration procedure is performed, comprising:

sending a first control instruction to a steering mechanism of a target vehicle, wherein the first control instruction is used for controlling the target vehicle to run at a first running angle;

acquiring a first deviation distance of the target vehicle after the target vehicle runs for a first time, wherein the first deviation distance is a transverse deviation amount of the target vehicle in the front lane;

and determining deviation calibration data according to the first deviation distance.

8. The method of claim 7, wherein obtaining the first offset distance after the target vehicle has traveled for the first length of time comprises:

acquiring an initial deviation distance, wherein the initial deviation distance is the initial distance between the target vehicle and the center line of the front lane when the target vehicle executes a calibration program;

after the first duration, acquiring a second deviation distance, wherein the second deviation distance represents the distance between the target vehicle and the center line of the front lane after the target vehicle runs for the first duration;

and determining the first deviation distance according to the initial deviation distance and the second deviation distance.

9. The method of claim 8, wherein determining offset calibration data based on the first offset distance comprises:

acquiring an accumulated running distance, wherein the accumulated running distance is a distance moved by the target vehicle after running for a first time;

and determining deviation calibration data according to the first deviation distance and the accumulated running distance.

10. The method of claim 9, wherein determining deviation calibration data based on the first deviation distance and the accumulated distance traveled comprises:

acquiring preset vehicle wheel base information, wherein the vehicle wheel base information is used for representing the wheel base length of the target vehicle;

determining a deviation angle of a steering wheel according to the vehicle wheel base information, the accumulated running distance and the first deviation distance;

and determining deviation calibration data according to the proportional relation between the front wheel corner and the steering wheel corner and the deviation angle of the steering wheel.

11. The method according to any of claims 1-6, wherein after starting to perform the calibration procedure, the method further comprises:

and if the target vehicle meets the preset stop regulation, exiting the calibration program, wherein the preset stop regulation comprises at least one of the following:

the real-time speed of the target vehicle is greater than a preset speed threshold value;

and the accumulated running distance of the target vehicle in the process of executing the calibration program is greater than the preset distance.

12. A zero offset dynamic calibration device is characterized by comprising:

the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring road image data in the running process of a target vehicle and determining a road mark according to the road image data, and the road mark is used for indicating the lane direction;

the determining module is used for determining road condition information according to the road identification, wherein the road condition information is used for representing the curvature of a front lane of the target vehicle;

and the calibration module is used for executing a calibration program if the road condition information meets the preset road condition, wherein the calibration program is used for carrying out deviation calibration on the steering wheel of the target vehicle to generate deviation calibration data, and the deviation calibration data is used for compensating the zero deviation of the steering wheel in the running process of the target vehicle.

13. An electronic device, comprising: a memory, a processor, and a computer program;

wherein the computer program is stored in the memory and configured to be executed by the processor to implement the dynamic calibration method for zero offset as claimed in any one of claims 1 to 11.

14. A computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, which when executed by a processor, are configured to implement the dynamic calibration method for null offset according to any one of claims 1 to 11.

15. A computer program product comprising a computer program which, when executed by a processor, implements the dynamic calibration method for null offset of any one of claims 1 to 11.

Technical Field

The present disclosure relates to the field of automatic driving technologies, and in particular, to a method and an apparatus for dynamically calibrating zero offset, an electronic device, and a storage medium.

Background

At present, with the development of an automatic driving technology, the degree of autonomy of an automatic driving function is higher and higher, wherein in the process of automatically driving and controlling a vehicle by a vehicle controller, route planning is performed based on navigation data and sensor data, and the vehicle is controlled to go straight or turn based on the route planning data, so that the automatic driving of the vehicle is completed.

The vehicle controller controls the vehicle to go straight or steer through a specific control interface and a steering mechanism for driving a steering wheel to rotate, but along with the accumulation of running time of the steering mechanism based on a mechanical mechanism, the steering mechanism cannot be completely reset, so that zero deviation exists in the steering wheel of the vehicle, and the steering precision and accuracy of the vehicle are influenced.

In the prior art, a mechanical steering mechanism is usually calibrated in a periodic off-line vehicle maintenance mode, compensation data is generated and stored in a storage medium in a vehicle, and when the vehicle actually runs, zero offset caused by the mechanical steering mechanism is compensated through the compensation data, so that steering accuracy in an automatic driving process is improved.

However, zero offset calibration is performed in an off-line vehicle maintenance mode, so that the maintenance cost is high, the calibration real-time performance is poor, and at the end of a maintenance period, a large zero offset can cause potential safety hazards and affect the driving safety and comfort of a vehicle.

Disclosure of Invention

The application provides a zero offset dynamic calibration method, a zero offset dynamic calibration device, electronic equipment and a storage medium, which are used for solving the problems of high maintenance cost and poor calibration effect during zero offset calibration.

According to a first aspect of an embodiment of the present application, there is provided a method for dynamic calibration of zero offset, the method including:

acquiring road image data in the running process of a target vehicle, and determining a road mark according to the road image data, wherein the road mark is used for indicating the lane direction; determining road condition information according to the road mark, wherein the road condition information is used for representing the curvature of a front lane of the target vehicle; and if the road condition information meets the preset road condition, executing a calibration program, wherein the calibration program is used for carrying out deviation calibration on a steering wheel of the target vehicle to generate deviation calibration data, and the deviation calibration data is used for compensating the zero deviation of the steering wheel in the running process of the target vehicle.

In one possible implementation, determining road condition information according to the road identifier includes: acquiring identification coordinates corresponding to the road identification; determining curvature information according to the identification coordinates, wherein the curvature information represents the curvature of a lane in front of the target vehicle; and determining road condition information according to the curvature information.

In one possible implementation, determining curvature information according to the identification coordinates includes: determining at least two road reference points according to the identification coordinates, wherein the road reference points are distributed at equal intervals; and determining the curvature information according to the position relation between the adjacent road reference points.

In one possible implementation, identifying a road identifier according to the road image data includes: acquiring preset target characteristic information, wherein the target characteristic information represents an identification target in an image identification process; and carrying out image recognition on the road image data according to the target characteristic information to obtain the road identifier.

In one possible implementation, the method further includes: acquiring the real-time speed of the target vehicle; if the road condition information meets the preset road condition, executing a calibration program, including: and if the road condition information meets the preset road condition and the real-time vehicle speed is less than the preset vehicle speed threshold value, executing a calibration program.

In one possible implementation, the method further includes: acquiring a current advancing direction angle of a vehicle, wherein the advancing direction angle represents an included angle between the target vehicle and a front lane; if the road condition information meets the preset road condition and the real-time vehicle speed is less than the preset vehicle speed threshold value, executing a calibration program, comprising: and if the road condition information meets the preset road condition, the real-time vehicle speed is less than the preset vehicle speed threshold value, and the advancing direction angle is less than the preset advancing direction angle threshold value, executing a calibration program.

In one possible implementation, a calibration procedure is performed, comprising: sending a first control instruction to a steering mechanism of a target vehicle, wherein the first control instruction is used for controlling the target vehicle to run at a first running angle; acquiring a first deviation distance of the target vehicle after the target vehicle runs for a first time, wherein the first deviation distance is a transverse deviation amount of the target vehicle in the front lane; and determining deviation calibration data according to the first deviation distance.

In one possible implementation, obtaining a first deviation distance of the target vehicle after traveling for a first duration includes: acquiring an initial deviation distance, wherein the initial deviation distance is the initial distance between the target vehicle and the center line of the front lane when the target vehicle executes a calibration program; after the first duration, acquiring a second deviation distance, wherein the second deviation distance represents the distance between the target vehicle and the center line of the front lane after the target vehicle runs for the first duration; and determining the first deviation distance according to the initial deviation distance and the second deviation distance.

In one possible implementation, determining offset calibration data according to the first offset distance includes: acquiring an accumulated running distance, wherein the accumulated running distance is a distance moved by the target vehicle after running for a first time; and determining deviation calibration data according to the first deviation distance and the accumulated running distance.

In one possible implementation, determining deviation calibration data according to the first deviation distance and the accumulated travel distance includes: acquiring preset vehicle wheel base information, wherein the vehicle wheel base information is used for representing the wheel base length of the target vehicle; determining a deviation angle of a steering wheel according to the vehicle wheel base information, the accumulated running distance and the first deviation distance; and determining deviation calibration data according to the proportional relation between the front wheel corner and the steering wheel corner and the deviation angle of the steering wheel.

In one possible implementation, after starting to execute the calibration procedure, the method further includes: and if the target vehicle meets the preset stop regulation, exiting the calibration program, wherein the preset stop regulation comprises at least one of the following: the real-time speed of the target vehicle is greater than a preset speed threshold value; and the accumulated running distance of the target vehicle in the process of executing the calibration program is greater than the preset distance.

According to a second aspect of the embodiments of the present application, there is provided a dynamic calibration apparatus for zero offset, including:

the system comprises an acquisition module, a display module and a control module, wherein the acquisition module is used for acquiring road image data in the running process of a target vehicle and determining a road mark according to the road image data, and the road mark is used for indicating the lane direction;

the determining module is used for determining road condition information according to the road identification, wherein the road condition information is used for representing the curvature of a front lane of the target vehicle;

and the calibration module is used for executing a calibration program if the road condition information meets the preset road condition, wherein the calibration program is used for carrying out deviation calibration on the steering wheel of the target vehicle to generate deviation calibration data, and the deviation calibration data is used for compensating the zero deviation of the steering wheel in the running process of the target vehicle.

In a possible implementation manner, the determining module is specifically configured to: acquiring identification coordinates corresponding to the road identification; determining curvature information according to the identification coordinates, wherein the curvature information represents the curvature of a lane in front of the target vehicle; and determining road condition information according to the curvature information.

In a possible implementation manner, when determining the curvature information according to the identification coordinate, the determining module is specifically configured to: determining at least two road reference points according to the identification coordinates, wherein the road reference points are distributed at equal intervals; and determining the curvature information according to the position relation between the adjacent road reference points.

In a possible implementation manner, when the determining module identifies the road identifier according to the road image data, the determining module is specifically configured to: acquiring preset target characteristic information, wherein the target characteristic information represents an identification target in an image identification process; and carrying out image recognition on the road image data according to the target characteristic information to obtain the road identifier.

In a possible implementation manner, the obtaining module is further configured to: acquiring the real-time speed of the target vehicle; the calibration module is specifically configured to, when determining that the road condition information satisfies a preset road condition and executing a calibration program, perform: and if the road condition information meets the preset road condition and the real-time vehicle speed is less than the preset vehicle speed threshold value, executing a calibration program.

In a possible implementation manner, the obtaining module is further configured to: acquiring a current advancing direction angle of a vehicle, wherein the advancing direction angle represents an included angle between the target vehicle and a front lane; the calibration module is specifically configured to, when determining that the road condition information satisfies a preset road condition and the real-time vehicle speed is less than a preset vehicle speed threshold value, execute a calibration procedure: and if the road condition information meets the preset road condition, the real-time vehicle speed is less than the preset vehicle speed threshold value, and the advancing direction angle is less than the preset advancing direction angle threshold value, executing a calibration program.

In a possible implementation manner, when executing the calibration program, the calibration module is specifically configured to: sending a first control instruction to a steering mechanism of a target vehicle, wherein the first control instruction is used for controlling the target vehicle to run at a first running angle; acquiring a first deviation distance of the target vehicle after the target vehicle runs for a first time, wherein the first deviation distance is a transverse deviation amount of the target vehicle in the front lane; and determining deviation calibration data according to the first deviation distance.

In a possible implementation manner, when obtaining the first deviation distance after the target vehicle travels for the first duration, the calibration module is specifically configured to: acquiring an initial deviation distance, wherein the initial deviation distance is the initial distance between the target vehicle and the center line of the front lane when the target vehicle executes a calibration program; after the first duration, acquiring a second deviation distance, wherein the second deviation distance represents the distance between the target vehicle and the center line of the front lane after the target vehicle runs for the first duration; and determining the first deviation distance according to the initial deviation distance and the second deviation distance.

In a possible implementation manner, when determining the offset calibration data according to the first offset distance, the calibration module is specifically configured to: acquiring an accumulated running distance, wherein the accumulated running distance is a distance moved by the target vehicle after running for a first time; and determining deviation calibration data according to the first deviation distance and the accumulated running distance.

In a possible implementation manner, when determining the deviation calibration data according to the first deviation distance and the accumulated travel distance, the calibration module is specifically configured to: acquiring preset vehicle wheel base information, wherein the vehicle wheel base information is used for representing the wheel base length of the target vehicle; determining a deviation angle of a steering wheel according to the vehicle wheel base information, the accumulated running distance and the first deviation distance; and determining deviation calibration data according to the proportional relation between the front wheel corner and the steering wheel corner and the deviation angle of the steering wheel.

In a possible implementation manner, after the calibration procedure is started to be executed, the calibration module is further configured to: and if the target vehicle meets the preset stop regulation, exiting the calibration program, wherein the preset stop regulation comprises at least one of the following: the real-time speed of the target vehicle is greater than a preset speed threshold value; and the accumulated running distance of the target vehicle in the process of executing the calibration program is greater than the preset distance.

According to a third aspect of embodiments of the present application, there is provided an electronic device, comprising: a memory, a processor, and a computer program;

wherein the computer program is stored in the memory and configured to be executed by the processor to perform the dynamic calibration method for zero offset according to any one of the first aspect of the embodiments of the present application.

According to a fourth aspect of embodiments of the present application, there is provided a computer-readable storage medium having stored therein computer-executable instructions, which when executed by a processor, are configured to implement the dynamic calibration method for zero offset according to any one of the first aspect of embodiments of the present application.

According to a fifth aspect of embodiments of the present application, there is provided a computer program product comprising a computer program that, when executed by a processor, implements the first aspect and various possible dynamic calibration methods for null offset as described above.

According to the zero offset dynamic calibration method, the zero offset dynamic calibration device, the electronic equipment and the storage medium, road image data are obtained in the running process of a target vehicle, and a road mark is determined according to the road image data, wherein the road mark is used for indicating the lane direction; determining road condition information according to the road mark, wherein the road condition information is used for representing the curvature of a front lane of the target vehicle; and if the road condition information meets the preset road condition, executing a calibration program, wherein the calibration program is used for carrying out deviation calibration on a steering wheel of the target vehicle to generate deviation calibration data, and the deviation calibration data is used for compensating the zero deviation of the steering wheel in the running process of the target vehicle. By predicting the road condition information in the vehicle running process, judging that the front lane meets the curvature condition and then executing a calibration program, the dynamic zero offset calibration in the vehicle running process is realized, the vehicle offset calibration cost is reduced, and the accuracy and the real-time performance of the offset calibration are improved.

Drawings

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

Fig. 1 is an application scenario diagram of a zero offset dynamic calibration method according to an embodiment of the present application;

FIG. 2 is a flowchart of a dynamic calibration method for zero offset according to an embodiment of the present application;

FIG. 3 is a flow chart of the implementation steps for executing a calibration routine;

FIG. 4 is a schematic diagram of determining offset calibration data according to an embodiment of the present application;

FIG. 5 is a flowchart of a dynamic calibration method for zero offset according to another embodiment of the present application;

FIG. 6 is a schematic view of lane curvature provided by an embodiment of the present application;

FIG. 7 is a flowchart illustrating the implementation steps of step S210 in the embodiment shown in FIG. 5;

fig. 8 is a schematic structural diagram of a zero offset dynamic calibration apparatus according to an embodiment of the present application;

fig. 9 is a schematic diagram of an electronic device according to an embodiment of the present application.

With the above figures, there are shown specific embodiments of the present application, which will be described in more detail below. These drawings and written description are not intended to limit the scope of the inventive concepts in any manner, but rather to illustrate the inventive concepts to those skilled in the art by reference to specific embodiments.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

The following explains an application scenario of the embodiment of the present application:

fig. 1 is an application scenario diagram of the zero offset dynamic calibration method provided in the embodiment of the present application, and the zero offset dynamic calibration method provided in the embodiment of the present application may be applied to an application scenario of zero offset automatic correction in an automatic driving process, specifically, as shown in fig. 1, an execution main body of the method provided in the embodiment of the present application may be a vehicle controller 2 of a target vehicle 1, and in a process of performing automatic driving on the target vehicle 1, a vehicle controller in the target vehicle 1 calibrates a zero offset of a steering wheel 3 by measuring an offset amount generated in a driving process of the vehicle, so as to generate offset calibration data. Then, in the process of carrying out conventional automatic driving on the vehicle, the zero offset of the steering wheel 3 is compensated based on the offset calibration data, so that the actual driving angle of the vehicle is the same as the theoretical driving angle output based on the automatic driving control algorithm, and the accuracy of the driving direction of the vehicle is improved.

In the prior art, an open transverse control interface of a drive-by-wire chassis of an automatic driving vehicle is a steering wheel angle control interface, and a transverse control algorithm calculates a steering wheel angle command and outputs the steering wheel angle command to a steering mechanism for execution. However, the core of most lateral control algorithms is to calculate the front wheel deflection angle of the vehicle, and then convert the front wheel deflection angle into a corresponding steering wheel rotation angle according to the transmission ratio of a steering mechanism or a model of the steering mechanism and output the steering wheel rotation angle to a drive-by-wire chassis for lateral control. This is done by default when the angle fed back by the steering wheel sensor is zero, and the front wheel (steering wheel) angle is also zero, i.e. the vehicle will travel straight ahead. In practice, however, the direction of travel of the vehicle is not straight ahead due to measurement variations of the steering wheel angle sensor and mechanical variations of the steering mechanism.

For the problem of steering wheel zero offset caused by errors of the steering mechanism, the mechanical steering mechanism is usually calibrated in a periodic off-line vehicle maintenance mode, compensation data are generated and stored in a storage medium in the vehicle, and when the vehicle actually runs, the zero offset caused by the mechanical steering mechanism is compensated through the compensation data, so that the steering precision in the automatic driving process is improved. However, the off-line vehicle maintenance scheme requires cooperation of vehicle manufacturers or related professionals, which is costly, and the deviation of the steering mechanism increases with the accumulation of the vehicle running time, so that it needs to be repeatedly calibrated at intervals, and at the end of each maintenance period, a large zero deviation may cause a safety hazard in the automatic driving process, which further increases the vehicle maintenance cost and reduces the safety in the automatic driving control process of the vehicle. However, compared with the off-line calibration scheme, the off-line maintenance scheme is difficult to apply to the on-line dynamic zero offset calibration due to the complex running state of the vehicle in the running process. Therefore, there is a need for a method capable of performing zero offset calibration on a steering wheel of a vehicle during driving of the vehicle to solve the above problems.

The following describes the technical solutions of the present application and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.

Fig. 2 is a flowchart of a zero offset dynamic calibration method according to an embodiment of the present application, where the method provided in this embodiment may be applied to a vehicle controller, as shown in fig. 2, the zero offset dynamic calibration method provided in this embodiment includes the following steps:

step S101, acquiring road image data in the driving process of a target vehicle, and determining a road mark according to the road image data, wherein the road mark is used for indicating the lane direction.

For example, during automatic driving of the vehicle, the vehicle controller acquires a road image through an image sensor arranged on the target vehicle, and obtains road image data. More specifically, the road image data includes a road image of a lane ahead of the current position of the target vehicle, wherein the road image includes road signs indicating the lane direction, such as lane lines on both sides of the lane, or a center line of the vehicle, and the road signs in the road image data can be determined by performing feature extraction and feature recognition on the road image data.

In a possible implementation manner, a specific implementation method for determining a road identifier according to road image data includes: acquiring preset target characteristic information, wherein the target characteristic information represents an identification target in an image identification process; and carrying out image recognition on the road image data according to the target characteristic information to obtain a road identifier. The target feature information may be information configured as required to use different objects in the road image data as identification targets, and further use the identification targets as road identifiers, so as to implement that different markers in the road image corresponding to the road image data are used as road identifiers to adapt to different road conditions.

In another possible implementation manner, intelligent sensing devices such as eye q4 are provided on the target vehicle, and through the above intelligent sensing devices, road image data can be collected and corresponding road identifiers can be output, and the intelligent sensing devices such as eye q4 are prior art, and the implementation principle and manner thereof are not described herein again.

And S102, determining road condition information according to the road identification, wherein the road condition information is used for representing the curvature of a front lane of the target vehicle.

The road sign is illustratively a sign for indicating a lane direction, and taking the road sign as a lane line as an example, the extending direction of the lane line is the same as the lane direction, i.e., if the lane line extends straight forward, the lane direction is also straight forward. Conversely, if the lane line is curved, the lane direction is also curved. Thus, from the road marking, the degree of curvature of the lane ahead of the target vehicle, i.e. the road state information, can be determined.

The road sign may be represented by a sign coordinate, which is a two-dimensional or three-dimensional coordinate system constructed based on the road image data to identify a spatial position of the road sign. More specifically, the road sign may correspond to a coordinate sequence composed of a plurality of sign coordinates, by which the course of the road sign (e.g., lane line) may be identified. And determining the degree of curvature of the corresponding front lane, namely the road condition information, through the difference relation between the coordinate values in the coordinate sequence.

And step S103, if the road condition information meets the preset road condition, executing a calibration program, wherein the calibration program is used for carrying out deviation calibration on the steering wheel of the target vehicle to generate deviation calibration data, and the deviation calibration data is used for compensating the zero deviation of the steering wheel in the running process of the target vehicle.

For example, in a scenario in which the present embodiment is applied, when a steering wheel of the vehicle generates null deviation, which may cause deviation between an actual driving direction of the target vehicle and a theoretical driving direction output according to the automatic driving control algorithm, a calibration procedure needs to be executed in order to calibrate the null deviation of the steering angle. When a vehicle controller outputs a steering angle of 0 degree to a driving mechanism of a steering wheel (namely, the steering wheel is controlled to be turned right), measuring the transverse displacement generated by a target vehicle within a certain time, wherein the larger the transverse displacement is, the larger the zero offset is; conversely, a smaller null offset is indicated. In a scenario aimed at the preventive correction of the null shift, the null shift is relatively small, so that it is necessary to measure an obvious amount of lateral displacement after the target vehicle has moved a relatively long distance, and therefore, in the process of executing the calibration procedure, it is necessary for the vehicle controller to always output a steering angle of 0 degrees to the drive mechanism of the steering wheel. In the process, if the degree of curvature of the lane in front of the target vehicle is too large, the vehicle controller automatically adjusts the steering angle of the driving mechanism output to the steering wheel based on the automatic driving control algorithm, and the steering angle cannot be guaranteed to be 0 degree all the time. Therefore, a deviation of the calibration data is introduced, so that an error occurs in the calibration result.

Therefore, for the above reasons, in the application scenario of the present embodiment, before executing the calibration procedure, it is necessary to determine whether the front road satisfies the condition, that is, the road condition information satisfies the preset road condition. Specifically, for example, the total length of the lane is greater than a preset length threshold, the curvature of the lane is less than a preset curvature threshold, and the like. And then, executing a calibration program to generate deviation calibration data, and realizing accurate calibration of the zero deviation of the steering wheel of the target vehicle.

Fig. 3 is a flowchart of implementation steps for executing the calibration program, and as shown in fig. 3, an implementation manner for executing the calibration program includes three specific implementation steps S1031, S1032 and S1033:

in step S1011, a first control instruction for controlling the target vehicle to travel at a first travel angle is sent to the steering mechanism of the target vehicle.

The vehicle controller sends a first control instruction to a steering mechanism through a specific control interface, and the steering mechanism is a steering wheel steering actuator. The first control instruction includes therein a first travel angle as an input control parameter of the target vehicle for controlling the travel angle of the steered wheels of the target vehicle by controlling the steering wheel to rotate, more specifically, for example, the first travel angle is 0 degrees, that is, the steering wheel is controlled to be straight, and the target vehicle travels forward.

In step S1012, a first deviation distance of the target vehicle after traveling for a first duration is obtained, where the first deviation distance is a lateral deviation amount of the target vehicle in a front lane.

And S1013, determining deviation calibration data according to the first deviation distance.

For example, after the target vehicle travels for a first period of time, a lateral shift amount generated by the target vehicle traveling in the front lane is detected by an image sensor or a radar sensor. Specifically, for example, by acquiring image data, when the target vehicle starts to execute the calibration routine, the distance between the vehicle and the lane line in the image data is determined again after a first period of time, thereby determining the first deviation distance. Of course, the first offset distance may also be determined, for example, by measuring the change in distance of the vehicle from the roadside marker, for example, by a radar sensor. And will not be described in detail herein.

For example, fig. 4 is a schematic diagram of determining deviation calibration data according to an embodiment of the present application, and as shown in fig. 4, after determining a first deviation distance generated by a target vehicle within a first time period and a driving distance corresponding to an actual driving route of the target vehicle within the first time period, a deviation angle of a steering wheel may be determined by scaling a proportional relationship between the first deviation distance and the driving distance, and further, a deviation angle of the steering wheel may be calculated according to a proportional relationship between rotation angles of the steering wheel and the steering wheel, so as to generate the deviation calibration data. And compensating the deviation angle of the steering wheel on the basis of the steering angle of the steering wheel after the steering angle of the steering wheel is calculated based on a transverse control algorithm in an automatic driving control algorithm by using the deviation calibration data in the running process of the target vehicle, so that the zero deviation of the steering wheel is eliminated.

It can be known from the above steps of the embodiment that, in the process of calibrating the zero offset of the steering wheel of the vehicle, a large amount of sensor data needs to be processed to determine the lateral offset of the vehicle on the lane, and further determine the deviation angle of the steering wheel and the deviation calibration data. The processing procedure of the correction program needs to consume large computing resources. According to the embodiment, the road condition information is determined firstly, and the correction program is executed after the road condition information meets the road condition, so that invalid calculation is avoided, and the waste of calculation resources is reduced.

In the embodiment, road image data are acquired in the running process of a target vehicle, and a road mark is determined according to the road image data, wherein the road mark is used for indicating the lane direction; determining road condition information according to the road identification, wherein the road condition information is used for representing the curvature of a front lane of the target vehicle; and if the road condition information meets the preset road condition, executing a calibration program, wherein the calibration program is used for carrying out deviation calibration on the steering wheel of the target vehicle to generate deviation calibration data, and the deviation calibration data is used for compensating the zero deviation of the steering wheel in the running process of the target vehicle. By predicting the road condition information in the vehicle running process, judging that the front lane meets the curvature condition and then executing a calibration program, the dynamic zero offset calibration in the vehicle running process is realized, the vehicle offset calibration cost is reduced, and the accuracy and the real-time performance of the offset calibration are improved.

Fig. 5 is a flowchart of a zero offset dynamic calibration method according to another embodiment of the present application, and as shown in fig. 5, the zero offset dynamic calibration method according to this embodiment further refines steps S102 to S103 on the basis of the zero offset dynamic calibration method according to the embodiment shown in fig. 2, and adds a determination condition before executing a calibration procedure, so that the zero offset dynamic calibration method according to this embodiment includes the following steps:

step S201, in the driving process of the target vehicle, acquiring road image data, and determining a road sign according to the road image data, wherein the road sign is used for indicating the lane direction.

Step S202, obtaining identification coordinates corresponding to the road identification, and determining curvature information according to the identification coordinates, wherein the curvature information represents the curvature of a front lane of the target vehicle.

In step S203, the road condition information is determined based on the curvature information.

Illustratively, the road sign identified by the road image data is a discrete data composed of a plurality of discrete data points, each discrete data point is characterized in the form of a sign coordinate, the sign coordinate is stored in a storage medium locally connected with the vehicle controller, and the vehicle controller determines the curvature of the front lane according to the road sign characterized by the sign coordinate by acquiring the sign coordinate corresponding to each discrete data point. The curvature is a rotation rate of a tangential direction angle to an arc length at a certain point on a curve, and can be defined by differentiation, indicating a degree of deviation of the curve from a straight line, and mathematically indicating a numerical value of a degree of curvature of the curve at a certain point.

Illustratively, the implementation manner of determining the curvature information includes: determining at least two road reference points according to the identification coordinates, wherein the road reference points are distributed at equal intervals; and determining curvature information according to the position relation between the adjacent road reference points.

Fig. 6 is a schematic view of a lane curvature according to an embodiment of the present disclosure, as shown in fig. 6, a road sign corresponds to a lane line on the right side of a lane, the road sign includes a plurality of road reference points, and the road reference points are obtained by sampling discrete data points of the road sign. Of course, in another possible implementation, the road reference point is a discrete data point. And performing curvature calculation according to the position relation between each road reference point and other adjacent road reference points, namely based on the identification coordinates of the corresponding discrete data points, so that curvature information representing the curvature of the front lane of the target vehicle can be determined. The specific process of calculating the curvature according to the coordinates of the plurality of points is the prior art, and is not described herein again.

Step S204, acquiring the real-time speed of the target vehicle and the current advancing direction angle of the vehicle, wherein the advancing direction angle represents the included angle between the target vehicle and a front lane;

step S205, if the road condition information satisfies the preset road condition, the real-time vehicle speed is less than the preset vehicle speed threshold, and the forward direction angle is less than the preset forward direction angle threshold, a calibration procedure is executed.

For example, in addition to the road condition information, the real-time speed of the target vehicle and the current heading angle of the vehicle may also affect the calibration procedure, reducing the accuracy of the calibration result. For example, when the real-time vehicle speed is high, the zero offset of the steering wheel changes, so that the calibration result is influenced; meanwhile, when the angle of the forward direction is too large, secondary adjustment of vehicle steering may be caused based on some safety mechanisms and algorithms in the automatic driving control process, for example, the angle of the forward direction is too large, the vehicle controller adjusts the angle of the forward direction of the vehicle based on a safety avoidance algorithm to avoid collision of the vehicle which is driven out, and meanwhile, the safety avoidance algorithm has higher priority, so that the vehicle controller can automatically adjust the steering angle output to a driving mechanism of a steering wheel, and cannot ensure that the steering angle is always 0 degree, thereby affecting the accuracy of a calibration program.

Therefore, in the step of this embodiment, when the road condition information satisfies the preset road condition, the execution of the calibration program is triggered and limited through two dimensions, namely the real-time vehicle speed and the heading direction angle, so as to further improve the execution accuracy of the calibration program.

Optionally, for similar reasons, after starting to execute the calibration procedure, the method further includes the steps of: and if the target vehicle meets the preset stop regulation, exiting the calibration program, wherein the preset stop regulation comprises at least one of the following steps: the real-time speed of the target vehicle is greater than a preset speed threshold; the accumulated travel distance of the target vehicle in the process of executing the calibration program is greater than the preset distance.

In step S206, a first control instruction is sent to the steering mechanism of the target vehicle, and the first control instruction is used for controlling the target vehicle to travel at a first travel angle.

Step S207, an initial deviation distance is obtained, where the initial deviation distance is an initial distance between the target vehicle and a center line of the front lane when the target vehicle executes the calibration procedure.

For example, after the calibration procedure is started, the vehicle controller sends a first control command to the steering wheel steering mechanism through a preset chassis control interface, where the first control command includes a steering wheel steering angle corresponding to the first driving angle. Then, an initial distance, i.e., an initial deviation distance, of the target vehicle from the center line of the preceding lane is acquired. Specifically, the steering wheel steering angle is 0 degrees even if the steering wheel is in the null state (the plus state). And driving a steering mechanism corresponding to the steering wheel to move through a torque transmission mechanism directly or indirectly connected with the steering mechanism of the steering wheel, so that the steering wheel is steered, and the control target vehicle runs at a first running angle. The method for identifying the center line of the lane and the method for determining the distance between the center line of the lane and the vehicle are described above, and the process is known to those skilled in the art and will not be described herein again.

And step S208, after the first time period, acquiring a second deviation distance, wherein the second deviation distance represents the distance between the target vehicle and the center line of the front lane after the target vehicle runs for the first time period.

In step S209, a first deviation distance is determined according to the initial deviation distance and the second deviation distance.

For example, in an ideal situation, the steering angle of the steering wheel has a fixed proportional relationship with the steering angle of the steering wheel, and when the steering wheel is rotated to the null position according to the first control instruction, the steering wheel should be at the null position so that the target vehicle travels in a straight line (0 degrees, i.e., the first travel angle). However, due to the steering wheel null offset, the steering wheel of the target vehicle is not at the null position when the steering wheel is at the null position, so that the target vehicle travels for a first period of time and then has a lateral distance from the center line of the road, i.e., a second offset distance, which may be determined, for example, by the distance from the center line of the lane ahead of the target vehicle. Further, according to the difference between the initial offset distance and the second offset distance, the lateral offset of the target vehicle caused by the null offset of the steering wheel after the first time period, that is, the first offset distance, can be determined.

And step S210, determining deviation calibration data according to the first deviation distance and the accumulated running distance.

After the first deviation distance is determined, a direction deviation angle of the target vehicle in the driving process can be determined according to a proportional relation between the first deviation distance and the total distance of the target vehicle in the first time length which is too long, and then deviation calibration data can be determined.

Optionally, as shown in fig. 7, step S210 includes three specific implementation steps S2101, S2102, and S2103:

step S2101, preset vehicle wheel base information is obtained, and the vehicle wheel base information is used for representing the wheel base length of the target vehicle.

In step S2102, a steered wheel deviation angle is determined based on the vehicle wheel base information, the accumulated travel distance, and the first deviation distance.

And step S2103, determining deviation calibration data according to the proportional relation between the front wheel corner and the steering wheel corner and the deviation angle of the steering wheel.

In one possible implementation, the offset calibration data is determined by a steered wheel offset angle of the steered wheel determined by the target vehicle during execution of a calibration procedure. Specifically, the steered wheel deviation angle of the target vehicle may be determined based on equation (1) in consideration of the front-rear wheel distance (i.e., wheel base) of the target vehicle:

e＝arctan(2×L×d/(S²)) (1)

where e is a steering wheel deviation angle, L is a wheel base of the target vehicle, S is an accumulated running distance, and d is a first deviation distance. The wheel base L is a preset value corresponding to the target vehicle, and the accumulated running distance S can be determined according to the product of the running speed of the vehicle in the first time length and the first time length. And (3) generating deviation calibration data according to the steering wheel deviation angle which can be determined by the formula (1) to finish the calibration process of the angle deviation. Furthermore, a rotation proportional relation exists between the front wheel steering angle and the steering wheel steering angle, the angle deviation on one side of the steering wheel is correspondingly determined according to the deviation angle of the steering wheel and the rotation proportional relation, and the angle deviation on one side of the steering wheel is used as deviation calibration data. In this embodiment, as described above, the zero offset of the steering wheel may be caused by the measurement offset of the steering wheel angle sensor and/or the mechanical offset of the steering mechanism, and therefore, the offset angle of the steering wheel corresponding to the steering wheel needs to be converted into the angular offset corresponding to one side of the steering wheel, and then the offset calibration data is generated, so as to compensate the measurement offset of the steering wheel angle sensor and the mechanical offset of the steering mechanism from the source. And then in the actual running process of the target vehicle, the zero position deviation of the steering wheel in the running process of the target vehicle is compensated through the deviation calibration data, so that when the steering wheel of the target vehicle is in the zero position, the steering wheel can also be synchronously in the zero position, and the accurate transverse control of the target vehicle is realized.

In this embodiment, the implementation manner of step S201 is the same as the implementation manner of step S101 in the embodiment shown in fig. 2 of this application, and is not described in detail here.

Fig. 8 is a schematic structural diagram of a zero offset dynamic calibration device provided in an embodiment of the present application, and is applied to a vehicle controller, as shown in fig. 8, a zero offset dynamic calibration device 3 provided in this embodiment includes:

the acquiring module 31 is configured to acquire road image data during the driving process of a target vehicle, and determine a road identifier according to the road image data, where the road identifier is used to indicate a lane direction;

the determining module 32 is configured to determine road condition information according to the road identifier, where the road condition information is used to represent a degree of curvature of a lane ahead of the target vehicle;

and the calibration module 33 is configured to execute a calibration program if the road condition information meets a preset road condition, where the calibration program is configured to perform deviation calibration on a steering wheel of the target vehicle to generate deviation calibration data, and the deviation calibration data is used to compensate for zero offset of the steering wheel in the running process of the target vehicle.

In a possible implementation manner, the determining module 32 is specifically configured to: acquiring identification coordinates corresponding to the road identification; determining curvature information according to the identification coordinates, wherein the curvature information represents the curvature of a front lane of the target vehicle; from the curvature information, road condition information is determined.

In a possible implementation manner, when determining the curvature information according to the identification coordinates, the determining module 32 is specifically configured to: determining at least two road reference points according to the identification coordinates, wherein the road reference points are distributed at equal intervals; and determining curvature information according to the position relation between the adjacent road reference points.

In a possible implementation manner, the determining module 32, when recognizing the road identifier according to the road image data, is specifically configured to: acquiring preset target characteristic information, wherein the target characteristic information represents an identification target in an image identification process; and carrying out image recognition on the road image data according to the target characteristic information to obtain a road identifier.

In a possible implementation manner, the obtaining module 31 is further configured to: acquiring the real-time speed of a target vehicle; the calibration module 33 is specifically configured to, when determining that the road condition information satisfies the preset road condition and executing a calibration procedure: and if the road condition information meets the preset road condition and the real-time vehicle speed is less than the preset vehicle speed threshold value, executing a calibration program.

In a possible implementation manner, the obtaining module 31 is further configured to: acquiring a current advancing direction angle of the vehicle, wherein the advancing direction angle represents an included angle between a target vehicle and a front lane; the calibration module 33 is specifically configured to, when determining that the road condition information satisfies the preset road condition and the real-time vehicle speed is less than the preset vehicle speed threshold, execute a calibration procedure: and if the road condition information meets the preset road condition, the real-time vehicle speed is less than the preset vehicle speed threshold value, and the advancing direction angle is less than the preset advancing direction angle threshold value, executing a calibration program.

In a possible implementation manner, the calibration module 33, when executing the calibration procedure, is specifically configured to: sending a first control instruction to a steering mechanism of the target vehicle, wherein the first control instruction is used for controlling the target vehicle to run at a first running angle; acquiring a first deviation distance of the target vehicle after the target vehicle runs for a first time, wherein the first deviation distance is a transverse offset of the target vehicle in a front lane; and determining deviation calibration data according to the first deviation distance.

In one possible implementation, the calibration module 33, when obtaining the first deviation distance after the target vehicle travels for the first duration, is specifically configured to: acquiring an initial deviation distance, wherein the initial deviation distance is the initial distance between a target vehicle and the center line of a front lane when the target vehicle executes a calibration program; after the first time length, acquiring a second deviation distance, wherein the second deviation distance represents the distance between the target vehicle and the center line of the front lane after the target vehicle runs for the first time length; and determining a first deviation distance according to the initial deviation distance and the second deviation distance.

In a possible implementation manner, the calibration module 33, when determining the biased calibration data according to the first biased distance, is specifically configured to: acquiring an accumulated running distance, wherein the accumulated running distance is a distance moved by a target vehicle after running for a first time; and determining deviation calibration data according to the first deviation distance and the accumulated running distance.

In one possible implementation, the calibration module 33, when determining the offset calibration data according to the first offset distance and the accumulated driving distance, is specifically configured to: acquiring preset vehicle wheel base information, wherein the vehicle wheel base information is used for representing the wheel base length of a target vehicle; determining a deviation angle of a steering wheel according to the vehicle wheel base information, the accumulated running distance and the first deviation distance; and determining deviation calibration data according to the proportional relation between the front wheel corner and the steering wheel corner and the deviation angle of the steering wheel.

In one possible implementation, after the calibration procedure is started, the calibration module 33 is further configured to: and if the target vehicle meets the preset stop regulation, exiting the calibration program, wherein the preset stop regulation comprises at least one of the following steps: the real-time speed of the target vehicle is greater than a preset speed threshold; the accumulated travel distance of the target vehicle in the process of executing the calibration program is greater than the preset distance.

The obtaining module 31, the determining module 32 and the calibrating module 33 are connected in sequence. The zero offset dynamic calibration apparatus 3 provided in this embodiment may implement the technical solutions of the method embodiments shown in fig. 2 to fig. 7, and the implementation principles and technical effects thereof are similar, and are not described herein again.

Fig. 9 is a schematic view of an electronic device according to an embodiment of the present application, and as shown in fig. 9, the electronic device according to the embodiment includes: a memory 41, a processor 42 and a computer program.

The computer program is stored in the memory 41 and configured to be executed by the processor 42 to implement the dynamic calibration method for zero offset provided in any embodiment corresponding to fig. 2 to 7 in the present application.

The memory 41 and the processor 42 are connected by a bus 43.

The relevant descriptions and effects corresponding to the steps in the embodiments corresponding to fig. 2 to fig. 7 can be understood, and are not described in detail herein.

One embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the dynamic calibration method for zero offset provided in any one of the embodiments corresponding to fig. 2 to fig. 7 of the present application.

The computer readable storage medium may be, among others, ROM, Random Access Memory (RAM), CD-ROM, magnetic tape, floppy disk, optical data storage device, and the like.

An embodiment of the present application provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the method for dynamic calibration of null offset provided in any embodiment of fig. 2 to fig. 7 of the present application is implemented.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of modules is merely a division of logical functions, and an actual implementation may have another division, for example, a plurality of modules or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.

Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.