CN113324554A - Automatic driving route planning method and device, readable storage medium and electronic equipment - Google Patents
Automatic driving route planning method and device, readable storage medium and electronic equipment Download PDFInfo
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- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3446—Details of route searching algorithms, e.g. Dijkstra, A*, arc-flags, using precalculated routes
Abstract
An automatic driving route planning method, an automatic driving route planning device, a readable storage medium and an electronic device are provided, wherein the method comprises the following steps: determining the current position of the vehicle according to the positioning information of the vehicle; determining a target preview point which is closest to the current position in a track preview point set, wherein the track preview point set comprises a plurality of preview points and driving parameter information which is correspondingly set by each preview point; planning a driving route of a current planning period according to the driving parameter information of the target pre-aiming point and the driving parameter information of a preset pre-aiming point behind the target pre-aiming point; detecting whether the driving route of the current planning period is finished or not; if yes, returning to the step of acquiring the current position of the vehicle. The automatic driving route planning method can realize automatic driving control without other modules such as perception, map, prediction and the like, and can efficiently and conveniently obtain a smooth and safe driving route by using a low-cost scheme.
Description
Technical Field
The present invention relates to the field of automatic driving technologies, and in particular, to a method and an apparatus for planning an automatic driving route, a readable storage medium, and an electronic device.
Background
With the rapid development of the related technologies of intelligent automobiles, the degree of intelligence of the automobiles is gradually improved, and drivers are gradually liberated from heavy driving tasks. How to safely and effectively plan a driving route is one of the biggest problems to be solved by automatically driving an automobile. In fact, path planning technology is a very active research field at present. Route planning is so complex because it covers all the technical areas of autonomous driving, from the most basic brakes, to sensors sensing the surroundings, to positioning and prediction models, etc. Accurate path planning requires the car to understand where we are and what actions the surrounding objects (other vehicles, pedestrians, animals, etc.) will take in the next few seconds.
The existing decision making technology of the automatic driving system is based on deep learning, and the system also makes reasonable and optimal judgment of a planned path mainly by processing data provided by a high-precision map and a prediction module. In a complex road scene, continuous, safe and reliable automatic driving can be fully realized only by the dynamic planning capability of at least 10 times per second, and in order to meet the aim, a controller with an Intel CPU + NVIDIA GPU architecture is required to perform deep learning processing on laser point cloud information and camera video information, deeply fuse the laser radar point cloud and visual information, and classify and extract the obstacle. This places considerable demands on the autopilot operating system and the planning module, resulting in complex and costly existing autopilot control systems.
Disclosure of Invention
In view of the above, it is necessary to provide an automatic driving route planning method, an automatic driving route planning device, a readable storage medium, and an electronic device for solving the problems of the prior art that an automatic driving control system is complex and high in cost.
An automated driving route planning method, comprising:
determining the current position of the vehicle according to the positioning information of the vehicle;
determining a target preview point which is closest to the current position in a track preview point set, wherein the track preview point set comprises a plurality of preview points and driving parameter information which is correspondingly set by each preview point;
planning a driving route of a current planning period according to the driving parameter information of the target pre-aiming point and the driving parameter information of a preset pre-aiming point behind the target pre-aiming point;
detecting whether the driving route of the current planning period is finished or not;
if yes, returning to the step of acquiring the current position of the vehicle.
Further, the automatic driving route planning method may further include the step of determining a target preview point closest to the current position in the preview point set, including:
inquiring whether a historical driving route exists;
when a historical driving route is inquired, searching a pre-aiming point which is closest to the relative time of the current planning cycle in the latest historical driving route;
calculating the distance between the pre-aiming point and the current position;
when the distance is smaller than a threshold value, taking the preview point closest to the relative time as the target preview point;
and when the distance is larger than a threshold value or no historical driving route is found, calling a vehicle _ state _ point function to calculate a target aiming point closest to the current position in the track aiming point set.
Further, in the automatic driving route planning method, the formula for calculating the target preview point closest to the current position in the set of track preview points by calling the vehicle _ state _ point function is as follows:
calling an ehicle _ state _ point function, and inputting the positioning information of the current position and the position information of each preview point in the track aiming point set;
and executing the ehicle _ state _ point function to respectively calculate the distance between the current position and each preview point in the track aiming point set, and determining a preview point with the shortest distance relative to the current position according to the calculation result to be used as the target preview point.
Further, the automatic driving route planning method may further include, before the step of determining the current position of the vehicle according to the positioning information of the vehicle:
detecting whether the vehicle has chassis information and positioning information;
if yes, executing the step of obtaining the positioning information of the vehicle;
if not, the automatic driving mode is exited.
Further, in the automatic driving route planning method, the driving parameter information of the preview point includes position information, an angle, a curvature, a relative time, a linear velocity, an acceleration, and a distance from the start point.
The invention also provides an automatic driving route planning device, which comprises:
the first determination module is used for determining the current position of the vehicle according to the positioning information of the vehicle;
the second determination module is used for determining a target preview point which is closest to the current position in a track preview point set, wherein the track preview point set comprises a plurality of preview points and driving parameter information which is correspondingly set by each preview point;
the planning module is used for planning a driving route of the current planning period according to the driving parameter information of the target pre-aiming point and the driving parameter information of a preset pre-aiming point behind the target pre-aiming point;
and the return execution module is used for detecting whether the driving route of the current planning period is finished or not and returning to execute the step of acquiring the current position of the vehicle when the driving is finished.
Further, the automatic driving route planning apparatus is configured to, wherein the second determining module is specifically configured to:
inquiring whether a historical driving route exists;
when a historical driving route is inquired, searching a pre-aiming point which is closest to the relative time of the current planning cycle in the latest historical driving route;
calculating the distance between the pre-aiming point and the current position;
when the distance is smaller than a threshold value, taking the preview point closest to the relative time as the target preview point;
and when the distance is larger than a threshold value or no historical driving route is found, calling a vehicle _ state _ point function to calculate a target aiming point closest to the current position in the track aiming point set.
Further, the automatic driving route planning apparatus further includes:
the judging module is used for detecting whether the vehicle has chassis information and positioning information;
the execution module is used for executing the step of acquiring the positioning information of the vehicle when the vehicle has the chassis information and the positioning information;
and the exit module is used for exiting the automatic driving mode when the vehicle has no chassis information and no positioning information.
The present invention also provides an electronic device, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the method of any one of the above when executing the computer program.
The invention also provides a computer readable storage medium having a program stored thereon, which when executed by a processor implements any of the methods described above.
The automatic driving route planning method can realize automatic driving control without other modules such as perception, map, prediction and the like, uses a low-cost scheme, is efficient and convenient, obtains a smooth and safe driving route, processes the obtained path information into a safe and executable driving track, and delivers the safe and executable driving track to the vehicle control module for execution.
Drawings
FIG. 1 is a flow chart of a method of automated driving route planning in a first embodiment of the present invention;
FIG. 2 is a flow chart of a method of automated driving route planning in a second embodiment of the present invention;
fig. 3 is a block diagram of an automatic driving route planning apparatus according to a third embodiment of the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
These and other aspects of embodiments of the invention will be apparent with reference to the following description and attached drawings. In the description and drawings, particular embodiments of the invention have been disclosed in detail as being indicative of some of the ways in which the principles of the embodiments of the invention may be practiced, but it is understood that the scope of the embodiments of the invention is not limited correspondingly. On the contrary, the embodiments of the invention include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.
The automatic driving route planning method is mainly applied to specific park scenes such as schools, shopping malls, communities and the like. The vehicle path planning system stores a pre-recorded pre-aiming route, and the pre-aiming route comprises a plurality of pre-aiming points and driving parameter information corresponding to each pre-aiming point. The pre-aiming route passes through a plurality of manual driving tests, determines each pre-aiming point in the driving route, and records the driving parameter information of each pre-aiming point. The driving parameter information includes position information, angle (theta), curvature (Kappa), relative time (relative), linear velocity (linear velocity), acceleration (acceleration a), and distance (estimated _ s) from the start point.
The automatic driving system is efficient and convenient by using a low-cost scheme without other modules for sensing, mapping, predicting and the like according to historical track information and by combining the current vehicle position state, obtains a smooth and safe track, processes the obtained path information into a safe and executable path, and sends the safe and executable path to a control module of the vehicle for execution, so that automatic driving is realized.
Referring to fig. 1, the method for planning an automatic driving route according to the first embodiment of the present invention includes steps S11-S14.
And step S11, determining the current position of the vehicle according to the positioning information of the vehicle.
The current location of the vehicle is determined based on positioning information collected by a vehicle's positioning system (e.g., GPS).
And step S12, determining a target preview point closest to the current position in the track preview point set.
The driving parameter information of each preview point in the preview point set comprises position information, an angle, a curvature, relative time, a linear velocity, an acceleration and a distance parameter. And calculating a preview point closest to the current position of the vehicle according to the position information of each preview point and the current position of the vehicle, and acting on the target preview point.
And step S13, planning the driving route of the current planning cycle according to the driving parameter information of the target pre-aiming point and the driving parameter information of a preset pre-aiming point behind the target pre-aiming point.
In this embodiment, the driving route is performed periodically, and each planned driving route includes a certain number of track points, for example, 800 points. And after the target pre-aiming point is determined, taking the target pre-aiming point as a starting point of the driving route planned currently, and taking a preset pre-aiming point behind the starting point in the track pre-aiming point set and the starting point as track points on the driving route planned currently.
And step S14, detecting whether the driving route of the current planning cycle is finished, if so, returning to execute step S11.
In the embodiment, the driving route of paper pile driving is planned periodically, for example, the planning period of panning is 200Ms, and the driving route is planned by using the point pre-aiming point closest to the driving route in 0s-200 Ms. And after the driving route is generated, the ProtoBuf is used for issuing the driving parameter information of each pre-aiming point of the driving route to the control module, and after the control module receives the driving parameter information, the control module automatically drives the vehicle according to the driving route.
The automatic driving route planning method in the embodiment can realize automatic driving control without other modules such as perception, map and prediction, and the like, and can obtain a smooth and safe driving route by using a low-cost scheme, efficiently and conveniently, and process the obtained path information into a safe and executable driving track to be executed by the vehicle control module.
Referring to fig. 2, a method for planning an automatic driving route according to a second embodiment of the present invention includes steps S21-S26.
Step S21, detecting whether the vehicle has chassis information and positioning information, if yes, executing step S21, otherwise, executing step S29.
And step S22, acquiring the positioning information of the vehicle and inquiring whether a historical driving route exists.
When the vehicle starts an automatic driving mode, a planning module is firstly established in an automatic driving main function, then a local aiming point planning node and a track running generating function are established, and the issuing frequency of the track running generating function is 5 Hz. The loop run function run () is then called to call the chassis information and positioning information of the autonomous vehicle. If the chassis information and the positioning information are not called in the system, the system reports the error that the chassis information and the positioning information are not reliable, and the system exits from the automatic driving planning circulation mode! ". And if the reliable chassis information and the positioning information in the vehicle can be received, starting a local planning flow and calling a function algorithm related to aiming point planning in the system.
The chassis information includes a steering wheel angle, a steering wheel angular velocity, a vehicle speed, an acceleration, and the like. The automatic driving planning module determines some speed states of the current vehicle according to the chassis information, so that the whole vehicle can be controlled in real time according to the current speed state of the vehicle and driving parameters of each pre-aiming point of the driving route when the planned driving route is executed.
In the automatic driving process of the vehicle, the automatic driving route is planned periodically in real time, and the successfully planned track is stored as a historical track every time so as to be convenient for generating the automatic driving route planned next time, and the historical driving route can be searched through a search function.
In step S23, when the historical driving route is found, the preview point closest to the relative time of the current planning cycle in the latest historical driving route is searched.
And step S24, calculating the distance between the preview point and the current position.
And step S25, when the distance is smaller than a threshold value, taking the closest preview point as the target preview point.
Step S26, when the distance is larger than the threshold or no historical driving route is found, calling a vehicle _ state _ point function to calculate a target aiming point closest to the current position in a preset track aiming point set.
After the last historical driving route is inquired, an automatic calculation starting point matching function is called, driving parameter information of a pre-aiming point in the last historical driving route is obtained, a binary rule is utilized to find the pre-aiming point which is closest to relative time in the last historical driving route, and then the position of the pre-aiming point is compared with the actual position of the vehicle, and a corresponding deviation value is calculated. Such as: the planning period of the panning is 200Ms, the route is planned by using the point matching closest to the vehicle in the time of 0s-200Ms, for example, aiming at the time of 200Ms, the method of two minutes is used for starting to search the pre-aiming point A ' with the relative time close to 200Ms in the previous historical driving route, and then the position of the vehicle is compared with the matched pre-aiming point A ' to calculate the deviation value of the vehicle and the pre-aiming point A '.
Therefore, after one planning period is finished each time, the comparison is started by using the method of 2 minutes, and if the deviation value is larger than the threshold value, the driving route is planned after the point closest to the driving route is calculated; if the deviation is less than the threshold, then the driving route is planned backwards with the point A'. Specifically, the threshold is, for example, 2m, if the deviation value is less than 2 meters, the nearest pre-aiming point from the current position and the index of the nearest pre-aiming point are calculated, and 800 pre-aiming points are calculated afterwards, and if the planning is successful, last _ traj is assigned to the planning _ traj of the planning for the next path planning. If the deviation value is larger than 2 meters, then vehicle _ state _ point is used to calculate the nearest matching point, then the planning is carried out again, and the function Plan of the planning algorithm of tracking is called (vehicle _ state _ point, planning _ project).
In this embodiment, a function is called to calculate a preview point closest to the current position of the vehicle in the preview point set, that is, a point is found in the history data and then is regarded as a close point of the starting point. Then, the elements of the pre-aiming point interval [ the first pre-aiming point and the last pre-aiming point ] of the current planning cycle are assigned to the track container, and the relative time in the track set is modified. And taking the first point as a 0 starting point, then filling the first point to 800 points, clearing the track sequence of the time after the planning is unsuccessful, returning false, and if the planning is successful, taking the planned track as the planned track of the last time and taking the release time as the execution starting time. And then, the ProtoBuf is used for releasing the information of the track points to a control module, and the control module receives the position information, the theta angle, the Kappa curvature, the relative time, the V linear velocity, the acceleration of the acquisition a and the acquired _ s distance parameter and carries out automatic driving control on the vehicle to drive according to the previous pre-aiming route.
And step S27, planning the driving route of the current planning cycle according to the driving parameter information of the target pre-aiming point and the driving parameter information of a preset pre-aiming point behind the target pre-aiming point.
And step S28, detecting whether the driving route of the current planning cycle is finished, if so, returning to execute step S21.
In step S29, the automatic driving mode is exited.
Referring to fig. 3, an automatic driving route planning apparatus according to a third embodiment of the present invention includes:
the first determination module 10 is used for determining the current position of the vehicle according to the positioning information of the vehicle;
a second determining module 20, configured to determine a target preview point closest to the current position in a track preview point set, where the track preview point set includes a plurality of preview points and driving parameter information corresponding to each preview point;
the planning module 30 is configured to plan a driving route of a current planning period according to the driving parameter information of the target preview point and the driving parameter information of a preset preview point after the target preview point;
and the return execution module 40 is used for detecting whether the driving route of the current planning cycle is finished and returning to the step of acquiring the current position of the vehicle when the driving is finished.
Further, in the automatic driving route planning apparatus, the second determining module 20 is specifically configured to:
inquiring whether a historical driving route exists;
when a historical driving route is inquired, searching a pre-aiming point which is closest to the relative time of the current planning cycle in the latest historical driving route;
calculating the distance between the pre-aiming point and the current position;
when the distance is smaller than a threshold value, taking the preview point closest to the relative time as the target preview point;
and when the distance is larger than a threshold value or no historical driving route is found, calling a vehicle _ state _ point function to calculate a target aiming point closest to the current position in the track aiming point set.
Further, the automatic driving route planning apparatus includes:
the judging module is used for detecting whether the vehicle has chassis information and positioning information;
the execution module is used for executing the step of acquiring the positioning information of the vehicle when the vehicle has the chassis information and the positioning information;
and the exit module is used for exiting the automatic driving mode when the vehicle has no chassis information and no positioning information.
The implementation principle and the generated technical effect of the automatic driving route planning device provided by the embodiment of the invention are the same as those of the method embodiment, and for brief description, the corresponding contents in the method embodiment can be referred to where the embodiment of the device is not mentioned.
The present invention also provides an electronic device, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the method of any of the above embodiments when executing the computer program.
The invention also provides a computer-readable storage medium, on which a program is stored, which, when being executed by a processor, carries out the method of any of the above-mentioned embodiments.
Those of skill in the art will understand that the logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be viewed as implementing logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. An automated driving route planning method, comprising:
determining the current position of the vehicle according to the positioning information of the vehicle;
determining a target preview point which is closest to the current position in a track preview point set, wherein the track preview point set comprises a plurality of preview points and driving parameter information which is correspondingly set by each preview point;
planning a driving route of a current planning period according to the driving parameter information of the target pre-aiming point and the driving parameter information of a preset pre-aiming point behind the target pre-aiming point;
detecting whether the driving route of the current planning period is finished or not;
if yes, returning to the step of acquiring the current position of the vehicle.
2. The automated driving route planning method of claim 1, wherein the step of determining a target home point in the set of home points that is closest to the current location comprises:
inquiring whether a historical driving route exists;
when a historical driving route is inquired, searching a pre-aiming point which is closest to the relative time of the current planning cycle in the latest historical driving route;
calculating the distance between the pre-aiming point and the current position;
when the distance is smaller than a threshold value, taking the preview point closest to the relative time as the target preview point;
and when the distance is larger than a threshold value or no historical driving route is found, calling a vehicle _ state _ point function to calculate a target aiming point closest to the current position in the track aiming point set.
3. The automated driving route planning method according to claim 2, wherein the formula for invoking the vehicle _ state _ point function to calculate the target preview point closest to the current position in the set of track preview points is:
calling an ehicle _ state _ point function, and inputting the positioning information of the current position and the position information of each preview point in the track aiming point set;
and executing the ehicle _ state _ point function to respectively calculate the distance between the current position and each preview point in the track aiming point set, and determining a preview point with the shortest distance relative to the current position according to the calculation result to be used as the target preview point.
4. The autonomous driving route planning method of claim 1, wherein the step of determining the current location of the vehicle based on the positioning information of the vehicle is preceded by the step of:
detecting whether the vehicle has chassis information and positioning information;
if yes, executing the step of obtaining the positioning information of the vehicle;
if not, the automatic driving mode is exited.
5. The automated driving route planning method according to claim 1, wherein the driving parameter information of the preview point includes position information, angle, curvature, relative time, linear velocity, acceleration, and distance from a start point.
6. An autonomous driving route planning apparatus, comprising:
the first determination module is used for determining the current position of the vehicle according to the positioning information of the vehicle;
the second determination module is used for determining a target preview point which is closest to the current position in a track preview point set, wherein the track preview point set comprises a plurality of preview points and driving parameter information which is correspondingly set by each preview point;
the planning module is used for planning a driving route of the current planning period according to the driving parameter information of the target pre-aiming point and the driving parameter information of a preset pre-aiming point behind the target pre-aiming point;
and the return execution module is used for detecting whether the driving route of the current planning period is finished or not and returning to execute the step of acquiring the current position of the vehicle when the driving is finished.
7. The autonomous driving route planning apparatus of claim 6, wherein the second determining module is specifically configured to:
inquiring whether a historical driving route exists;
when a historical driving route is inquired, searching a pre-aiming point which is closest to the relative time of the current planning cycle in the latest historical driving route;
calculating the distance between the pre-aiming point and the current position;
when the distance is smaller than a threshold value, taking the preview point closest to the relative time as the target preview point;
and when the distance is larger than a threshold value or no historical driving route is found, calling a vehicle _ state _ point function to calculate a target aiming point closest to the current position in the track aiming point set.
8. The autonomous driving route planning apparatus of claim 6, further comprising:
the judging module is used for detecting whether the vehicle has chassis information and positioning information;
the execution module is used for executing the step of acquiring the positioning information of the vehicle when the vehicle has the chassis information and the positioning information;
and the exit module is used for exiting the automatic driving mode when the vehicle has no chassis information and no positioning information.
9. An electronic device, comprising: memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the method of any one of claims 1-5 when executing the computer program.
10. A computer-readable storage medium, on which a program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1 to 5.
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| CN113978547A (en) * | 2021-10-21 | 2022-01-28 | 江铃汽车股份有限公司 | Automatic driving steering control method and system |
| CN114355874A (en) * | 2021-11-11 | 2022-04-15 | 北京百度网讯科技有限公司 | Path planning method and device, electronic equipment and automatic driving equipment |
| CN114485710A (en) * | 2022-01-19 | 2022-05-13 | 北京百度网讯科技有限公司 | Map navigation method, system, device, electronic equipment and storage medium |
| CN116381748A (en) * | 2023-04-06 | 2023-07-04 | 黑龙江惠达科技发展有限公司 | Agricultural machinery straight line automatic driving track comparison method and device |
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