CN113324554B - 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
- Publication number
- CN113324554B CN113324554B CN202110592927.9A CN202110592927A CN113324554B CN 113324554 B CN113324554 B CN 113324554B CN 202110592927 A CN202110592927 A CN 202110592927A CN 113324554 B CN113324554 B CN 113324554B
- Authority
- CN
- China
- Prior art keywords
- point
- pretightening
- driving route
- vehicle
- current position
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 39
- 230000006870 function Effects 0.000 claims description 24
- 230000001133 acceleration Effects 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 3
- 230000008447 perception Effects 0.000 abstract description 4
- 238000005516 engineering process Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 3
- 238000003491 array Methods 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 241001465754 Metazoa Species 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 238000013135 deep learning Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000004091 panning Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Automation & Control Theory (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
Abstract
An automatic driving route planning method, an automatic driving route planning device, a readable storage medium and an electronic device, 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 pre-aiming point closest to the current position in a track pre-aiming point set, wherein the track pre-aiming point set comprises a plurality of pre-aiming points and driving parameter information correspondingly set by each pre-aiming 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 the preset pre-aiming points after the target pre-aiming point; detecting whether the driving route of the current planning period is finished; if yes, returning to execute 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 autopilot technologies, and in particular, to an autopilot route planning method and apparatus, a readable storage medium, and an electronic device.
Background
With the rapid development of the related technology of intelligent automobiles, the intelligent degree of 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 an automatic driving automobile. In fact, path planning technology is now a very active area of research. Path planning is so complex as it covers all areas of technology for autopilot, from the most basic brakes, to sensors sensing the surrounding environment, to positioning and predictive models, etc. Accurate path planning requires the car to understand what actions we are taking in the next few seconds where we are and surrounding objects (other vehicles, pedestrians, animals, etc.).
The decision technology of the existing automatic driving system is based on deep learning, and the system also makes reasonable judgment on the optimal planning path mainly by processing the data provided by the high-precision map and the prediction two modules. Under the complex scene of highway, at least need 10 dynamic programming ability can fully realize continuous, safe, reliable autopilot, in order to satisfy this target, need adopt Intel CPU + NVIDIA GPU architecture's controller to carry out degree of depth study processing to laser point cloud information and camera video information, degree of depth fuses laser radar point cloud and visual information, carries out classification and attribute extraction to the barrier. This places considerable demands on the autopilot operating system and planning module, resulting in the complexity and cost of existing autopilot control systems.
Disclosure of Invention
In view of the foregoing, it is necessary to provide an automatic driving route planning method, an automatic driving route planning device, a readable storage medium and an electronic apparatus, which solve the problems of complexity and high cost of the automatic driving control system in the prior art.
An automatic driving route planning method, comprising:
determining the current position of the vehicle according to the positioning information of the vehicle;
determining a target pre-aiming point closest to the current position in a track pre-aiming point set, wherein the track pre-aiming point set comprises a plurality of pre-aiming points and driving parameter information correspondingly set by each pre-aiming 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 the preset pre-aiming points after the target pre-aiming point;
detecting whether the driving route of the current planning period is finished;
if yes, returning to execute the step of acquiring the current position of the vehicle.
Further, in the automatic driving route planning method, the step of determining the target pretightening point closest to the current position in the pretightening point set includes:
inquiring whether a historical driving route exists or not;
when the historical driving route is inquired, searching a pretightening point closest to the relative time of the current planning period 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 pretightening point closest to the relative time as the target pretightening point;
and when the distance is greater than a threshold value or no historical driving route is inquired, a vehicle_state_point function is called to calculate a target pre-aiming point closest to the current position in the track aiming point set.
Further, in the automatic driving route planning method, the formula for calling the vehicle_state_point function to calculate the target pre-aiming point closest to the current position in the track aiming point set is as follows:
calling an ehicle_state_point function, and inputting positioning information of a current position and position information of each pre-aiming 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 pretightening point in the track aiming point set, and determining the pretightening point of the shortest distance relative to the current position according to the calculation result and taking the pretightening point as the target pretightening point.
Further, the automatic driving route planning method further includes, 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 acquiring 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 pre-aiming point includes position information, angle, curvature, relative time, linear velocity, acceleration and distance from a starting point.
The invention also provides an automatic driving route planning device, which comprises:
the first determining module is used for determining the current position of the vehicle according to the positioning information of the vehicle;
the second determining module is used for determining a target pre-aiming point closest to the current position in a track pre-aiming point set, wherein the track pre-aiming point set comprises a plurality of pre-aiming points and driving parameter information correspondingly set by each pre-aiming point;
the planning module is used for 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 the preset pre-aiming points after 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 in running or not, and returning to execute the step of acquiring the current position of the vehicle when the running is finished.
Further, in the automatic driving route planning device, the second determining module is specifically configured to:
inquiring whether a historical driving route exists or not;
when the historical driving route is inquired, searching a pretightening point closest to the relative time of the current planning period 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 pretightening point closest to the relative time as the target pretightening point;
and when the distance is greater than a threshold value or no historical driving route is inquired, a vehicle_state_point function is called to calculate a target pre-aiming point closest to the current position in the track aiming point set.
Further, the automatic driving route planning device 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 chassis information and 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 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 the computer program is executed.
The present invention also provides a computer-readable storage medium having stored thereon a program 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, is efficient and convenient by using a low-cost scheme, obtains a smooth and safe driving route, and processes the obtained path information into a safe and executable driving track to be delivered to a vehicle control module for execution.
Drawings
FIG. 1 is a flow chart of an automatic driving route planning method according to a first embodiment of the present invention;
FIG. 2 is a flow chart of an automatic driving route planning method according to 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
Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are illustrative only and are not to be construed as limiting the invention.
These and other aspects of embodiments of the invention will be apparent from and elucidated with reference to the description and drawings described hereinafter. In the description and drawings, particular implementations of embodiments of the invention are disclosed in detail as being indicative of some of the ways in which the principles of embodiments of the invention may be employed, 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 alternatives, modifications and equivalents as may be included within the spirit and scope of the appended claims.
The automatic driving route planning method is mainly applied to specific park scenes, such as schools, markets, communities and the like. The vehicle path planning system stores a prerecorded pretightening route, and the pretightening route comprises a plurality of pretightening points and driving parameter information corresponding to each pretightening point. The pre-aiming route is used for determining each pre-aiming point in the driving route and recording driving parameter information of each pre-aiming point through multiple manual driving experiments. The driving parameter information includes position information, angle (theta), curvature (Kappa), relative time (relative), linear velocity, acceleration (acceleration a), and distance (accumulated_s) from the start point.
The method has the advantages that the preset route is driven manually, the preset route is recorded, detailed planning pre-aiming point information of route points is stored, and according to historical track information and the current vehicle position state, an automatic driving system is enabled to use a low-cost scheme without other modules such as perception, map and prediction, a smooth and safe track is obtained efficiently and conveniently, the obtained path information is processed into a safe executable path, and the safe executable path is transmitted to a control module of a vehicle to be executed, so that automatic driving is achieved.
Referring to fig. 1, a method for planning an automatic driving route according to a first embodiment of the present invention includes steps S11 to S14.
Step S11, determining the current position of the vehicle according to the positioning information of the vehicle.
The current position of the vehicle is determined based on positioning information collected by a positioning system (e.g., GPS) of the vehicle.
And step S12, determining a target pre-aiming point closest to the current position in the track pre-aiming point set.
The driving parameter information of each pretightening point in the pretightening point set comprises position information, angle, curvature, relative time, linear velocity, acceleration and distance parameters. And calculating one pretightening point closest to the current position of the vehicle according to the position information of each pretightening point and the current position of the vehicle, and acting as a target pretightening point.
Step S13, 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 the preset pre-aiming points after the target pre-aiming point.
In this embodiment, the driving route is periodically performed, and each planned driving route includes a certain number of track points, for example, 800 points. When the target pre-aiming point is determined, taking the target pre-aiming point as a starting point of a driving route planned currently, and taking preset pre-aiming points after the starting point in the track pre-aiming point set and the starting point as track points on the driving route of the current planning period.
And step S14, detecting whether the driving route of the current planning period is finished, and if so, returning to the step S11.
In this embodiment, the driving route of the pile driving is planned periodically, for example, the planning period of the routing is 200Ms, and the driving route is planned by pre-aiming the closest point to the pile driving point in 0s-200 Ms. After the driving route is generated, the ProtoBuf is used for issuing driving parameter information of each pre-aiming point of the driving route to the control module, and after the driving parameter information is received by the control module, 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, is efficient and convenient by using a low-cost scheme, obtains a smooth and safe driving route, and processes the obtained path information into a safe and executable driving track to be transmitted to a vehicle control module for execution.
Referring to fig. 2, a method for planning an automatic driving route according to a second embodiment of the present invention includes steps S21 to S26.
Step S21, detecting whether the vehicle has chassis information and positioning information, if yes, executing step S21, otherwise executing step S29.
Step S22, positioning information of the vehicle is acquired, and whether a historical driving route exists is inquired.
When the vehicle starts an automatic driving mode, a planning module is firstly built in an automatic driving main function, then a local aiming point planning node and a track running generating function are built, and the release frequency of the track running generating function is 5Hz. And then calling a circulation running function run (), so as to call chassis information and positioning information of the automatic driving vehicle. If the chassis information and the positioning information are not called in the system, the system reports error that the chassis and the positioning information are not reliable, and exits the automatic driving planning circulation mode-! ". If reliable chassis information and positioning information in the vehicle can be received, a local planning flow is started, and a function algorithm related to aiming point planning in the system is called.
The chassis information includes steering wheel angle, steering wheel angular velocity, vehicle speed, acceleration, etc. The automatic driving planning module determines a plurality of 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 track successfully planned each time is stored as a historical track so as to facilitate the generation of the automatic driving route planned next time, and the historical driving route can be searched through a searching function.
Step S23, when the historical driving route is inquired, searching a pretightening point closest to the relative time of the current planning period in the latest historical driving route.
And step S24, calculating the distance between the pre-aiming point and the current position.
And S25, when the distance is smaller than a threshold value, taking the closest pretightening point as the target pretightening point.
And S26, when the distance is greater than a threshold value or no historical driving route is inquired, a vehicle_state_point function is called to calculate a target pre-aiming point closest to the current position in a preset track aiming point set.
When the last historical driving route is inquired, an automatic calculation starting point matching function is called, driving parameter information of a pretightening point in the last historical driving route is obtained, a pretightening point with the closest relative time in the last historical driving route is found by utilizing a bipartite rule, and then the position of the pretightening point is compared with the actual position of the vehicle, and a corresponding deviation value is calculated. Such as: the planning period of panning is 200Ms, the route is planned by matching the nearest point from 0s to 200Ms, for example, for 200Ms, the search of the pretightening point A ' which is close to 200Ms in the last historical driving route is started by a bipartite method, and then the deviation value of the pretightening point A ' is calculated by comparing the position of the vehicle with the matched pretightening point A '.
So that after one planning period is finished, the comparison is started by a 2-way method, and if the deviation value is larger than the threshold value, the point closest to the user is calculated to plan the driving route after going and going; if the deviation is less than the threshold, the driving route is planned later with the point A'. Specifically, if the threshold value is 2m, and if the deviation value is smaller than 2m, calculating the nearest pretightening point at the position and index of the nearest pretightening point, and 800 pretightening points at the back, if the planning is successful, assigning the planning_traj of the current planning with last_traj for the next path planning. If the deviation value is greater than 2 meters, the nearest matching point is calculated with the vehicle_state_point, then the vehicle is re-planned, and the function Plan (vehicle_state_point) of the planning algorithm of tracking is called.
In this embodiment, the pretightening point closest to the current position of the vehicle in the pretightening point set is calculated by calling a function, that is, a point is found in the history data, and then is regarded as a similar point of the starting point. Then, the elements of the pretightening point interval [ the first pretightening point and the last pretightening point ] of the current planning period are assigned to the track container, and the relative time in the track set is modified. Taking the first point as a starting point of 0, filling the starting point to 800 points, after unsuccessful planning, clearing the track sequence at this time, returning to false, and taking the planned track as the last planned track and the release time as the execution starting time if the planning is successful. And then the ProtoBuf is used for issuing information of the track points to a control module, and the control module receives position information, theta angle, kappa curvature, relative time, V linear speed, accelerationa acceleration and accumulated_s distance parameters to automatically drive and control the vehicle to run according to the previous pre-aiming route.
Step S27, 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 the preset pre-aiming points after the target pre-aiming point.
And step S28, detecting whether the driving route of the current planning period is finished, and if so, returning to the step S21.
Step S29, the automatic driving mode is exited.
Referring to fig. 3, an automatic driving route planning device according to a third embodiment of the present invention includes:
a first determining module 10, configured to determine a current position of a vehicle according to positioning information of the vehicle;
a second determining module 20, configured to determine a target pre-aiming point closest to the current position in a track pre-aiming point set, where the track pre-aiming point set includes a plurality of pre-aiming points and driving parameter information set corresponding to each pre-aiming point;
the planning module 30 is configured to plan a driving route in 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 after the target pre-aiming point;
the return execution module 40 is configured to detect whether the driving route of the current planning period is completed, and return to execute the step of acquiring the current position of the vehicle when the driving is completed.
Further, in the above automatic driving route planning apparatus, the second determining module 20 is specifically configured to:
inquiring whether a historical driving route exists or not;
when the historical driving route is inquired, searching a pretightening point closest to the relative time of the current planning period 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 pretightening point closest to the relative time as the target pretightening point;
and when the distance is greater than a threshold value or no historical driving route is inquired, a vehicle_state_point function is called to calculate a target pre-aiming point closest to the current position in the track aiming point set.
Further, the automatic driving route planning device 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 chassis information and 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 automatic driving route planning device provided by the embodiment of the invention has the same implementation principle and technical effects as those of the embodiment of the method, and for the sake of brevity, reference is made to the corresponding content in the embodiment of the method.
The invention also provides an electronic device, comprising: the computer program comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor realizes the method of any embodiment when running the computer program.
The present invention also provides a computer-readable storage medium having stored thereon a program which, when executed by a processor, implements a method as described in any of the above embodiments.
Those of skill in the art will appreciate that the logic and/or steps represented in the flow diagrams or otherwise described herein, e.g., a ordered listing of executable instructions for 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). In addition, the computer readable medium may even be paper or other suitable medium on which the program is printed, as the program may 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 is to be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above-described embodiments, the various steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, may be implemented using any one or combination of the following techniques, as is well known in the art: discrete logic circuits having logic gates for implementing logic functions on data signals, application specific integrated circuits having suitable combinational logic gates, programmable Gate Arrays (PGAs), field Programmable Gate Arrays (FPGAs), and the like.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means 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 present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiments or examples. 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 foregoing examples illustrate only a few embodiments of the invention and are described in detail herein without thereby limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (8)
1. An automatic driving route planning method, comprising:
determining the current position of the vehicle according to the positioning information of the vehicle;
determining a target pretightening point closest to the current position in a track pretightening point set, wherein the track pretightening point set comprises a plurality of pretightening points and driving parameter information correspondingly set by each pretightening 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 the preset pre-aiming points after the target pre-aiming point;
detecting whether the driving route of the current planning period is finished;
if yes, returning to execute the step of acquiring the current position of the vehicle;
the step of determining the target pretightening point closest to the current position in the track pretightening point set comprises the following steps:
inquiring whether a historical driving route exists or not;
when a historical driving route is inquired, searching a pretightening point closest to the relative time of the current planning period in the latest historical driving route by adopting a binary rule;
calculating the distance between the pre-aiming point and the current position;
when the distance is smaller than a threshold value, taking the pretightening point closest to the relative time as the target pretightening point;
and when the distance is greater than a threshold value or no historical driving route is inquired, a vehicle_state_point function is called to calculate a target pre-aiming point closest to the current position in the track aiming point set.
2. The automatic driving route planning method according to claim 1, wherein the formula for calculating the target pre-aiming point closest to the current position in the track aiming point set by calling a vecycle_state_point function is:
calling an ehicle_state_point function, and inputting positioning information of a current position and position information of each pre-aiming 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 pretightening point in the track aiming point set, and determining the pretightening point of the shortest distance relative to the current position according to the calculation result and taking the pretightening point as the target pretightening point.
3. The automatic driving route planning method according to claim 1, wherein the step of determining the current position of the vehicle based on the positioning information of the vehicle further comprises:
detecting whether the vehicle has chassis information and positioning information;
if yes, executing the step of acquiring the positioning information of the vehicle;
if not, the automatic driving mode is exited.
4. An automatic driving route planning method according to claim 1 wherein the driving parameter information of the pre-aiming point comprises position information, angle, curvature, relative time, line speed, acceleration and distance from the starting point.
5. An automatic driving route planning device, comprising:
the first determining module is used for determining the current position of the vehicle according to the positioning information of the vehicle;
the second determining module is used for determining a target pretightening point closest to the current position in a track pretightening point set, wherein the track pretightening point set comprises a plurality of pretightening points and driving parameter information correspondingly set by each pretightening point;
the planning module is used for 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 the preset pre-aiming points after the target pre-aiming point;
the return execution module is used for detecting whether the driving route of the current planning period is finished in running or not, and returning to execute the step of acquiring the current position of the vehicle when the running is finished;
the second determining module is specifically configured to:
inquiring whether a historical driving route exists or not;
when a historical driving route is inquired, searching a pretightening point closest to the relative time of the current planning period in the latest historical driving route by adopting a binary rule;
calculating the distance between the pre-aiming point and the current position;
when the distance is smaller than a threshold value, taking the pretightening point closest to the relative time as the target pretightening point;
and when the distance is greater than a threshold value or no historical driving route is inquired, a vehicle_state_point function is called to calculate a target pre-aiming point closest to the current position in the track aiming point set.
6. The automatic driving route planning apparatus of claim 5, 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 chassis information and 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.
7. 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 claims 1-4 when the computer program is executed.
8. A computer readable storage medium having stored thereon a program, which when executed by a processor implements the method according to any of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110592927.9A CN113324554B (en) | 2021-05-28 | 2021-05-28 | Automatic driving route planning method and device, readable storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110592927.9A CN113324554B (en) | 2021-05-28 | 2021-05-28 | Automatic driving route planning method and device, readable storage medium and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113324554A CN113324554A (en) | 2021-08-31 |
| CN113324554B true CN113324554B (en) | 2023-12-29 |
Family
ID=77422319
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110592927.9A Active CN113324554B (en) | 2021-05-28 | 2021-05-28 | Automatic driving route planning method and device, readable storage medium and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113324554B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113978547B (en) * | 2021-10-21 | 2022-08-02 | 江铃汽车股份有限公司 | Automatic driving steering control method and system |
| CN114355874B (en) * | 2021-11-11 | 2024-03-22 | 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 |
| CN115092184A (en) * | 2022-07-20 | 2022-09-23 | 江苏徐工工程机械研究院有限公司 | Vehicle control method and device and vehicle |
| CN116381748B (en) * | 2023-04-06 | 2023-11-21 | 黑龙江惠达科技股份有限公司 | Agricultural machinery straight line automatic driving track comparison method and device |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108088456A (en) * | 2017-12-21 | 2018-05-29 | 北京工业大学 | A kind of automatic driving vehicle local paths planning method with time consistency |
| CN109059944A (en) * | 2018-06-06 | 2018-12-21 | 上海国际汽车城（集团）有限公司 | Motion planning method based on driving habit study |
| CN109976321A (en) * | 2017-12-27 | 2019-07-05 | 湖南中车时代电动汽车股份有限公司 | A kind of method for planning track and intelligent driving system for intelligent driving system |
| CN110262506A (en) * | 2019-07-02 | 2019-09-20 | 华人运通(上海)自动驾驶科技有限公司 | Confirmation method, vehicle travel control method, device and equipment a little is taken aim in advance |
| CN110316193A (en) * | 2019-07-02 | 2019-10-11 | 华人运通(上海)自动驾驶科技有限公司 | Setting method, device, equipment and the computer readable storage medium of preview distance |
| CN110667563A (en) * | 2019-09-20 | 2020-01-10 | 北京汽车集团有限公司 | Transverse control method and device for automatic driving vehicle and vehicle |
| CN111289008A (en) * | 2020-04-28 | 2020-06-16 | 南京维思科汽车科技有限公司 | Local path planning algorithm for unmanned vehicle |
| WO2020187257A1 (en) * | 2019-03-18 | 2020-09-24 | 长城汽车股份有限公司 | Vehicle abnormal lane change control method, device and system |
| CN111806437A (en) * | 2020-09-10 | 2020-10-23 | 中汽研（天津）汽车工程研究院有限公司 | Method, device, equipment and storage medium for determining aiming point of automatic driving automobile |
| CN112433531A (en) * | 2021-01-27 | 2021-03-02 | 国汽智控(北京)科技有限公司 | Trajectory tracking method and device for automatic driving vehicle and computer equipment |
| CN112764415A (en) * | 2019-11-05 | 2021-05-07 | 北京新能源汽车股份有限公司 | Method and device for generating automatic driving planning track and automobile |
-
2021
- 2021-05-28 CN CN202110592927.9A patent/CN113324554B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108088456A (en) * | 2017-12-21 | 2018-05-29 | 北京工业大学 | A kind of automatic driving vehicle local paths planning method with time consistency |
| CN109976321A (en) * | 2017-12-27 | 2019-07-05 | 湖南中车时代电动汽车股份有限公司 | A kind of method for planning track and intelligent driving system for intelligent driving system |
| CN109059944A (en) * | 2018-06-06 | 2018-12-21 | 上海国际汽车城（集团）有限公司 | Motion planning method based on driving habit study |
| WO2020187257A1 (en) * | 2019-03-18 | 2020-09-24 | 长城汽车股份有限公司 | Vehicle abnormal lane change control method, device and system |
| CN110262506A (en) * | 2019-07-02 | 2019-09-20 | 华人运通(上海)自动驾驶科技有限公司 | Confirmation method, vehicle travel control method, device and equipment a little is taken aim in advance |
| CN110316193A (en) * | 2019-07-02 | 2019-10-11 | 华人运通(上海)自动驾驶科技有限公司 | Setting method, device, equipment and the computer readable storage medium of preview distance |
| CN110667563A (en) * | 2019-09-20 | 2020-01-10 | 北京汽车集团有限公司 | Transverse control method and device for automatic driving vehicle and vehicle |
| CN112764415A (en) * | 2019-11-05 | 2021-05-07 | 北京新能源汽车股份有限公司 | Method and device for generating automatic driving planning track and automobile |
| CN111289008A (en) * | 2020-04-28 | 2020-06-16 | 南京维思科汽车科技有限公司 | Local path planning algorithm for unmanned vehicle |
| CN111806437A (en) * | 2020-09-10 | 2020-10-23 | 中汽研（天津）汽车工程研究院有限公司 | Method, device, equipment and storage medium for determining aiming point of automatic driving automobile |
| CN112433531A (en) * | 2021-01-27 | 2021-03-02 | 国汽智控(北京)科技有限公司 | Trajectory tracking method and device for automatic driving vehicle and computer equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113324554A (en) | 2021-08-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113324554B (en) | Automatic driving route planning method and device, readable storage medium and electronic equipment | |
| CN110692094B (en) | Vehicle control apparatus and method for control of autonomous vehicle | |
| CN111559388B (en) | Target vehicle screening method, device, equipment and storage medium | |
| CN110834630A (en) | Vehicle driving control method and device, vehicle and storage medium | |
| CN105774806A (en) | Vehicle travelling control device | |
| CN109421712B (en) | Vehicle control device, vehicle control method, and storage medium | |
| JP6792704B2 (en) | Vehicle control devices and methods for controlling self-driving cars | |
| KR102488526B1 (en) | Scenario based control of autonomous driving vehicle | |
| JP2019039831A (en) | Automatic driving device | |
| US11467584B2 (en) | Multi-layer grid based open space planner | |
| US11556127B2 (en) | Static obstacle map based perception system | |
| EP3914492B1 (en) | A parking-trajectory generation method combined with offline and online solutions | |
| JP2022522625A (en) | Autonomous vehicle turn signaling | |
| US11407419B2 (en) | Central line shifting based pre-change lane path planning | |
| CN112829770A (en) | Detour decision based on lane boundary and vehicle speed | |
| JP6867257B2 (en) | Vehicle control devices, vehicles, vehicle control methods and programs | |
| US20210370941A1 (en) | Precautionary slowdown speed planning | |
| US11325529B2 (en) | Early brake light warning system for autonomous driving vehicle | |
| CN114415688A (en) | Automatic driving remote control system for automobile | |
| CN113753038A (en) | Trajectory prediction method and apparatus, electronic device and storage medium | |
| CN113366400A (en) | Method for implementing dynamic cost function of automatic driving vehicle | |
| CN115892076B (en) | Lane obstacle screening method and device and domain controller | |
| CN117601867B (en) | Vehicle lane changing method, vehicle lane changing device, storage medium and vehicle control system | |
| US20230202516A1 (en) | Planning under prediction with confidence region for an autonomous driving vehicle | |
| CN113075924B (en) | Automatic driving vehicle parking scene design |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |