CN110502012A - His a kind of wheel paths prediction technique, device and storage medium - Google Patents
His a kind of wheel paths prediction technique, device and storage medium Download PDFInfo
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- CN110502012A CN110502012A CN201910770522.2A CN201910770522A CN110502012A CN 110502012 A CN110502012 A CN 110502012A CN 201910770522 A CN201910770522 A CN 201910770522A CN 110502012 A CN110502012 A CN 110502012A
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- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000001514 detection method Methods 0.000 claims abstract description 9
- 238000004590 computer program Methods 0.000 claims description 12
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- 238000010586 diagram Methods 0.000 description 4
- 230000008859 change Effects 0.000 description 2
- 230000004888 barrier function Effects 0.000 description 1
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Classifications
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- 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
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3415—Dynamic re-routing, e.g. recalculating the route when the user deviates from calculated route or after detecting real-time traffic data or accidents
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0214—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory in accordance with safety or protection criteria, e.g. avoiding hazardous areas
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- General Physics & Mathematics (AREA)
- Aviation & Aerospace Engineering (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Electromagnetism (AREA)
- Traffic Control Systems (AREA)
Abstract
The present invention provides his a kind of wheel paths prediction technique, device and storage medium, is suitable for automatic Pilot field.This method comprises: the position of the first Vehicle target vehicle and course angle in detection preset range；The target vehicle is positioned to high-precision lane, the first lane topology of course angle and place lane based on the target vehicle, the selection first lane topology direct-connected with lane where target vehicle to the first crossing；Second lane topology according to the target vehicle at the first crossing, obtains the target vehicle and travels to the path planning at the second crossing；The path planning of all target vehicles is obtained, and the path planning of all target vehicles of the first vehicle periphery is sent to control loop decision-making module.Solve the problems, such as that safety is lower in traditional driving scheme with this solution, his vehicle driving trace is effectively predicted in realization, the driving safety of further support vehicles.
Description
Technical field
The present invention relates to automatic Pilot field, more particularly to his a kind of wheel paths prediction technique, device and storage medium.
Background technique
In automatic Pilot, need to consider vehicle body ambient enviroment to the Driving control of vehicle, it is especially desirable to know on lane
The situation of other vehicles could not only ensure driving safety in this way, but also facilitate the travel route of planning vehicle, this will pass through calculating
Machine carries out trajectory predictions to his vehicle.
Generally in vehicle control, when track of other vehicles, is preset, in vehicle travel process, can pass through in real time
Collision calculation, support vehicles safety select to change traveling rail by searching algorithm when colliding or detecting barrier
Mark evades danger, but in practical driving procedure, is easy to appear paroxysmal situation, existing vehicle risk bypassing method is difficult to
Further ensure that the safety of driving, safety is lower.
Summary of the invention
In view of this, the embodiment of the invention provides his a kind of wheel paths prediction technique, device and storage mediums, to solve
Safety issue caused by sudden situation facilitates dynamic adjustment traffic route, avoids risk.
In the embodiment of the present invention in a first aspect, providing his a kind of wheel paths prediction technique, comprising:
Detect the position of the first Vehicle target vehicle and course angle in preset range；
The target vehicle is positioned to high-precision lane, course angle and place lane based on the target vehicle
First lane topology, the selection first lane topology direct-connected with lane where target vehicle to the first crossing；
Second lane topology according to the target vehicle at the first crossing, obtains the target vehicle and travels to the second tunnel
The path planning of mouth；
The path planning of all target vehicles is obtained, and the path planning of all target vehicles of the first vehicle periphery is transmitted
To control loop decision-making module.
In the second aspect of the embodiment of the present invention, his a kind of wheel paths prediction meanss are provided, comprising:
Detection module, for detecting the position of the first Vehicle target vehicle and course angle in preset range；
First prediction module, for positioning the target vehicle to high-precision lane, based on the target vehicle
The first lane in course angle and place lane topology, the selection first lane topology direct-connected with lane where target vehicle to first
Crossing；
Second prediction module obtains the mesh for the second lane topology according to the target vehicle at the first crossing
Mark the path planning of vehicle driving to the second crossing；
Delivery module, for obtaining the path planning of all target vehicles, and by all target vehicles of the first vehicle periphery
Path planning be sent to control loop decision-making module.
In the third aspect of the embodiment of the present invention, a kind of device is provided, including memory, processor and be stored in institute
The computer program that can be run in memory and in the processor is stated, the processor is realized when executing the computer program
Such as the step of first aspect the method for the embodiment of the present invention.
In the fourth aspect of the embodiment of the present invention, a kind of computer readable storage medium is provided, it is described computer-readable
Storage medium is stored with computer program, and first aspect of the embodiment of the present invention is realized when the computer program is executed by processor
The step of the method for offer.
5th aspect of the embodiment of the present invention, provides a kind of computer program product, the computer program product packet
Computer program is included, realizes that first aspect of the embodiment of the present invention mentions when the computer program is executed by one or more processors
The step of the method for confession.
In the embodiment of the present invention, current vehicle surrounding objects vehicle is detected, according to first vehicle in lane where target vehicle
Road topology, selects direct-connected lane to the first crossing, and then the second lane topology according to target vehicle at crossing, selects direct-connected vehicle
Road to the second crossing obtains target vehicle and travels to the path planning at the second crossing, is sent to system decision-making module.So that driving
System can be according to the path planning of other vehicles around current vehicle, and dynamic adjustment solves tradition side from vehicle driving trace
Occurring emergency situations in case has that security risk, further guarantee driving safety evade road risk, has relatively strong real
The property used.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, drawings discussed below is only some implementations of the invention
Example, for those of ordinary skill in the art, without creative efforts, can also obtain according to these attached drawings
Other accompanying drawings.
Fig. 1 is the flow diagram for his the wheel paths prediction technique that the embodiment of the present invention one provides；
Fig. 2 is that second embodiment of the present invention provides the structural schematic diagrams of his wheel paths prediction meanss.
Specific embodiment
In order to make the invention's purpose, features and advantages of the invention more obvious and easy to understand, below in conjunction with the present invention
Attached drawing in embodiment, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that disclosed below
Embodiment be only a part of the embodiment of the present invention, and not all embodiment.Based on the embodiments of the present invention, this field
Those of ordinary skill's all other embodiment obtained without making creative work, belongs to protection of the present invention
Range.
Specification or claims of the invention and the term " includes " in above-mentioned attached drawing and other similar import tables
It states, it is intended that covering non-exclusive includes that such as process, method comprising a series of steps or units or system, equipment do not limit
In listed step or unit.In addition, " first " " second " is not intended to description particular order for distinguishing different objects
Embodiment one:
Automatic driving vehicle can receive cloud or the control instruction execution pair from vehicle control during road driving
The operation answered, such as accelerate, slow down, adjustment direction.The driving trace of vehicle often plans travel route in advance, when encountering spy
Determine condition of road surface, will do it track adjustment.It is reasonably adjusted for support vehicles Trajectory Safety, in the same of real-time monitoring condition of road surface
When, it is necessary to his wheel paths prediction is obtained, such as in vehicle lane change, needs to know the vehicle driving dynamic in each lane.
Referring to Fig. 1, the flow diagram of his wheel paths prediction technique of one kind provided in an embodiment of the present invention, comprising:
The position of first Vehicle target vehicle and course angle in S101, detection preset range；
Other vehicle-states around current vehicle are detected by detection device such as video camera, radar detector, described the
One vehicle is current Driving control vehicle, and from vehicle, the target vehicle is from other vehicles around vehicle, the preset range
It can may be variable value for fixed value.
When detecting other a certain range of vehicles around by video camera or radar detector, such as to be currently from vehicle
Center detects all vehicles in 50 meters of surrounding, each target vehicle is navigated in high-precision, can be clear based on high-precision map
Clear each vehicle driving condition of reflection, convenient for obtaining trajectory planning.The target vehicle state includes target vehicle position and course angle.
Optionally, where choosing first vehicle on road, target carriage identical with first vehicle heading
.The target vehicle in each lane around first vehicle periphery can collect, the vehicle different for driving direction, by
It will not have much impact to current vehicle in it, can be without trajectory predictions, and then reduce operand.
S102, the target vehicle is positioned to high-precision lane, course angle and place based on the target vehicle
The first lane topology in lane, the selection first lane topology direct-connected with lane where target vehicle to the first crossing；
The high-precision lane is the lane that can clearly show in high-precision map and lane line, by the target vehicle
It navigates to specific lane, and regard the position in lane where it as starting point, according to opening up for target vehicle place lane and lane
Structure is flutterred, selects direct-connected lane to the first crossing, the first lane topology includes all topological structures of current lane, described
First crossing is first crossing that target vehicle reaches in current driving direction, and first crossing may include four crossway
The crossing of the shapes such as mouth, T junction or Y shape crossing.
S103, according to the target vehicle the first crossing second lane topology, obtain the target vehicle travel to
The path planning at the second crossing；
The second lane topology includes crossing topology of the target vehicle at the first crossing, and such as straight trip turns left or turns right, also
Including being travelled behind the first crossing to the lane topology at the second crossing.Second crossing be target vehicle in the process of moving
Second crossing passed through, second crossing equally may include the road of the shapes such as crossroad, T junction or Y shape crossing
Mouthful.
Include that target vehicle is travelled by the first crossing to the path at the second crossing in the path planning, further includes target carriage
It is travelled by current location to the path planning at the first crossing.
Preferably, the second lane topology includes:
The target vehicle is in the presence straight trip at the first crossing, left-hand rotation and the lane topology turned right.
Further, when the target vehicle has the lane topology of straight trip at the first crossing, then selection enters with straight trip
The direct-connected lane topology in lane is to the second crossing；
When there is the lane topology turned left at the first crossing in the target vehicle, then choose after the target vehicle turns left with
The direct-connected lane topology of left turn lane is to the second crossing；
When there is the lane topology turned right at the first crossing in the target vehicle, then choose after the target vehicle is turned right with
The direct-connected lane topology of right-turn lane is to the second crossing.
Optionally, the lane center form point for extracting the target vehicle path planning connects the lane center form point
As prediction locus line so that system decision-making module uses.
S104, the path planning for obtaining all target vehicles, and the path of all target vehicles of the first vehicle periphery is advised
It draws and is sent to control loop decision-making module.
The path planning for obtaining all target vehicles can have selection to obtain predeterminated target vehicle multiple target vehicles
Path planning be transferred to the decision-making module of automated driving system.The control loop decision-making module generally operates in vehicle-mounted
Virtual program module in terminal or cloud service, the control loop decision-making module can generate control with logic-based operation and refer to
It enables.
It should be noted that first crossing and the second crossing are for distinguishing target vehicle in current driving direction downlink
The crossing successively passed through during sailing, the first lane topology is from second lane topology for distinguishing different lane topology knots
Fruit.
Method provided in this embodiment calculates support vehicles safety relative to vehicle collision is directly based upon, can be to his vehicle
Track is predicted, obtains his vehicle dynamic, further guarantee driving safety in real time in vehicle travel process.
It should be understood that the serial number size of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, and the implementation process of the embodiments of the invention shall not be constituted with any limitation.
Embodiment two:
Fig. 2 is a kind of structural schematic diagram of his wheel paths prediction meanss provided by Embodiment 2 of the present invention, which includes:
Detection module 210, for detecting the position of the first Vehicle target vehicle and course angle in preset range；
Optionally, the detection module 210 further include:
Module is chosen, it is identical with first vehicle heading for road where choosing first vehicle
Target vehicle.
First prediction module 220 is based on the target vehicle for positioning the target vehicle to high-precision lane
Course angle and place lane first lane topology, the direct-connected first lane topology in selection lane where with target vehicle to the
One crossing；
Second prediction module 230, it is topological for the second lane according to the target vehicle at the first crossing, described in acquisition
Target vehicle is travelled to the path planning at the second crossing；
Preferably, the second lane topology includes:
The target vehicle is in the presence straight trip at the first crossing, left-hand rotation and the lane topology turned right.
Further, when the target vehicle has the lane topology of straight trip at the first crossing, then selection enters with straight trip
The direct-connected lane topology in lane is to the second crossing；
When there is the lane topology turned left at the first crossing in the target vehicle, then choose after the target vehicle turns left with
The direct-connected lane topology of left turn lane is to the second crossing；
When there is the lane topology turned right at the first crossing in the target vehicle, then choose after the target vehicle is turned right with
The direct-connected lane topology of right-turn lane is to the second crossing.
Optionally, the second lane topology according to the target vehicle at the first crossing, obtains the target vehicle
Travelling path planning to the second crossing includes:
The lane center form point for extracting the target vehicle path planning connects the lane center form point as prediction
Trajectory line.
Delivery module 240, for obtaining the path planning of all target vehicles, and by all target carriages of the first vehicle periphery
Path planning be sent to control loop decision-making module.
Device through this embodiment in real time can predict his wheel paths at vehicle end or cloud and be transmitted to system
Decision-making module, support vehicles driving safety.
In the above-described embodiments, it all emphasizes particularly on different fields to the description of each embodiment, is not described in detail or remembers in some embodiment
The part of load may refer to the associated description of other embodiments.
Those of ordinary skill in the art will appreciate that implement the method for the above embodiments be can be with
Relevant hardware is instructed to complete by program, the program can be stored in a computer readable storage medium,
When being executed, including step S101 to S104, the storage medium includes such as to the program: ROM/RAM, magnetic disk, CD.
The above, the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although referring to before
Stating embodiment, invention is explained in detail, those skilled in the art should understand that: it still can be to preceding
Technical solution documented by each embodiment is stated to modify or equivalent replacement of some of the technical features；And these
It modifies or replaces, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution.
Claims (10)
1. his a kind of wheel paths prediction technique characterized by comprising
Detect the position of the first Vehicle target vehicle and course angle in preset range；
The target vehicle is positioned to high-precision lane, first of course angle and place lane based on the target vehicle
Lane topology, the selection first lane topology direct-connected with lane where target vehicle to the first crossing；
Second lane topology according to the target vehicle at the first crossing, obtains the target vehicle and travels to the second crossing
Path planning；
The path planning of all target vehicles is obtained, and the path planning of all target vehicles of the first vehicle periphery is sent to and is driven
Sail system decision-making module.
2. the method according to claim 1, wherein the first Vehicle target vehicle in the detection preset range
Position and course angle include:.
Where choosing first vehicle on road, target vehicle identical with first vehicle heading.
3. the method according to claim 1, wherein the second lane topology includes:
The target vehicle is in the presence straight trip at the first crossing, left-hand rotation and the lane topology turned right.
4. according to the method described in claim 3, it is characterized in that, the second lane is topological further include:
When the target vehicle has the lane topology of straight trip at the first crossing, then selection enters the direct-connected lane in lane with straight trip
Topology is to the second crossing；
When there is the lane topology turned left at the first crossing in the target vehicle, then choose after the target vehicle turns left with left-hand rotation
The direct-connected lane topology in lane is to the second crossing；
When there is the lane topology turned right at the first crossing in the target vehicle, then choose after the target vehicle is turned right with right-hand rotation
The direct-connected lane topology in lane is to the second crossing.
5. the method according to claim 1, wherein it is described according to the target vehicle the second of the first crossing
Lane topology, obtaining the path planning that the target vehicle is travelled to the second crossing includes:
The lane center form point for extracting the target vehicle path planning connects the lane center form point as prediction locus
Line.
6. his a kind of wheel paths prediction meanss characterized by comprising
Detection module, for detecting the position of the first Vehicle target vehicle and course angle in preset range；
First prediction module, for positioning the target vehicle to high-precision lane, the course based on the target vehicle
The first lane in angle and place lane topology, the selection first lane topology direct-connected with lane where target vehicle to the first via
Mouthful；
Second prediction module obtains the target carriage for the second lane topology according to the target vehicle at the first crossing
Traveling to the second crossing path planning；
Delivery module, for obtaining the path planning of all target vehicles, and by the road of all target vehicles of the first vehicle periphery
Diameter planning is sent to control loop decision-making module.
7. device according to claim 6, which is characterized in that the detection module further include:
Module is chosen, for road where choosing first vehicle, target identical with first vehicle heading
Vehicle.
8. device according to claim 6, which is characterized in that the second lane topology includes:
The target vehicle is in the presence straight trip at the first crossing, left-hand rotation and the lane topology turned right.
9. a kind of device further includes memory, processor and storage in the memory and can transport on the processor
Capable computer program, which is characterized in that the processor is realized when executing the computer program as in claim 1 to 5
Described in any one the step of his wheel paths prediction technique.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In realizing his the wheel paths prediction technique as described in any one of claim 1 to 5 when the computer program is executed by processor
Step.
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| CN201910770522.2A CN110502012A (en) | 2019-08-20 | 2019-08-20 | His a kind of wheel paths prediction technique, device and storage medium |
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| CN111797780A (en) * | 2020-07-08 | 2020-10-20 | 中国第一汽车股份有限公司 | Vehicle following track planning method, device, server and storage medium |
| CN112710317A (en) * | 2020-12-14 | 2021-04-27 | 北京四维图新科技股份有限公司 | Automatic driving map generation method, automatic driving method and related product |
| CN115346370A (en) * | 2022-08-10 | 2022-11-15 | 重庆大学 | Intersection anti-collision system and method based on intelligent traffic |
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| CN115346370B (en) * | 2022-08-10 | 2023-11-03 | 重庆大学 | Intersection anti-collision system and method based on intelligent traffic |
| CN117576950A (en) * | 2024-01-16 | 2024-02-20 | 长沙行深智能科技有限公司 | Method and device for predicting vehicle to select crossing entrance and crossing exit |
| CN117576950B (en) * | 2024-01-16 | 2024-04-09 | 长沙行深智能科技有限公司 | Method and device for predicting vehicle to select crossing entrance and crossing exit |
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