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CN118405128A - Lane keeping method and system based on intelligent network-connected automobile - Google Patents

Lane keeping method and system based on intelligent network-connected automobile Download PDF

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Publication number
CN118405128A
CN118405128A CN202410881039.2A CN202410881039A CN118405128A CN 118405128 A CN118405128 A CN 118405128A CN 202410881039 A CN202410881039 A CN 202410881039A CN 118405128 A CN118405128 A CN 118405128A
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CN
China
Prior art keywords
identifying
generating
lane
feedback parameter
image
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.)
Pending
Application number
CN202410881039.2A
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Chinese (zh)
Inventor
许一凡
王智灵
余结
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Anhui Zhongke Xingchi Automatic Driving Technology Co ltd
Original Assignee
Anhui Zhongke Xingchi Automatic Driving Technology Co ltd
Priority date (The priority date 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 date listed.)
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Publication date
Application filed by Anhui Zhongke Xingchi Automatic Driving Technology Co ltd filed Critical Anhui Zhongke Xingchi Automatic Driving Technology Co ltd
Priority to CN202410881039.2A priority Critical patent/CN118405128A/en
Publication of CN118405128A publication Critical patent/CN118405128A/en
Pending legal-status Critical Current

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Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/10Path keeping
    • B60W30/12Lane keeping
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/14Adaptive cruise control
    • B60W30/16Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
    • B60W30/162Speed limiting therefor
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W30/00Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
    • B60W30/14Adaptive cruise control
    • B60W30/16Control of distance between vehicles, e.g. keeping a distance to preceding vehicle
    • B60W30/165Automatically following the path of a preceding lead vehicle, e.g. "electronic tow-bar"
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06Road conditions
    • B60W40/072Curvature of the road
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2552/00Input parameters relating to infrastructure
    • B60W2552/30Road curve radius
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2554/00Input parameters relating to objects
    • B60W2554/80Spatial relation or speed relative to objects

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention is suitable for the intelligent driving field, and provides a lane keeping method and a lane keeping system based on an intelligent network-connected automobile, wherein the method comprises the following steps: collecting a target image of a driving area in real time; identifying route curved information based on the driving area target image; acquiring a target following distance and a path navigation instruction; collecting and identifying first reference information, and generating a first feedback parameter; collecting and identifying second reference information, and generating second feedback parameters; the method and the device have the beneficial effects that the first feedback parameter and the second feedback parameter are searched, and the deceleration control instruction is calculated and generated: the method and the system can preset the following distance according to the traffic flow of the road surface or the driving habit of the driver, synchronously acquire various reference information and generate various feedback parameters, so that the reliability of lane keeping is improved, the following of the vehicle can be stabilized at a low speed, and the application range of the lane keeping is further improved.

Description

Lane keeping method and system based on intelligent network-connected automobile
Technical Field
The invention belongs to the field of intelligent driving, and particularly relates to a lane keeping method and system based on an intelligent network-connected automobile.
Background
The intelligent network-connected automobile is a new-generation automobile which is provided with advanced devices such as an on-vehicle sensor, a controller and an actuator, integrates modern communication and network technologies, realizes intelligent information exchange and sharing such as automobile and automobile, road, person and cloud, has the functions of complex environment sensing, intelligent decision, cooperative control and the like, can realize safe, efficient, comfortable and energy-saving running, and can finally replace people to operate.
When the intelligent network-connected automobile drives, the driving assistance system can be used for assisting the driving, so that the driver can be assisted to complete a plurality of complicated driving tasks, the lane keeping is a function of the intelligent driving assistance system, most of the existing vehicles can only be used when the speed of the vehicles is high during lane keeping, the application range is limited, and aiming at the problems, the development of a more mature lane keeping method and system based on the intelligent network-connected automobile is needed.
Disclosure of Invention
The embodiment of the invention aims to provide a lane keeping method and a lane keeping system based on an intelligent network-connected automobile, which aim to solve the problems in the background technology.
The embodiment of the invention is realized in such a way that, on one hand, the lane keeping method based on the intelligent network-connected automobile comprises the following steps:
Collecting a target image of a driving area in real time;
identifying route curved information based on the driving area target image;
Acquiring a target following distance and a path navigation instruction;
Collecting and identifying first reference information, and generating a first feedback parameter;
collecting and identifying second reference information, and generating second feedback parameters;
the first feedback parameter and the second feedback parameter are retrieved, and a deceleration control instruction is calculated and generated.
As a further aspect of the present invention, the identifying route curved information based on the driving area target image specifically includes:
identifying a driving area target image;
extracting a lane marking image in the driving area targeting image;
recognizing and calculating the curvature of the lane mark in the lane mark image;
if the curvature of the lane marking is greater than or equal to the curvature threshold value;
generating curved lane confirmation information;
If the curvature of the lane marking is smaller than the curvature threshold value;
Then straight lane confirmation information is generated.
As still further aspect of the present invention, the obtaining the target following distance and the path navigation instruction specifically includes:
Importing a target following distance;
generating a vehicle distance control instruction based on the target following distance;
Identifying a path navigation instruction;
and generating a following route based on the path navigation instruction.
As still further aspects of the present invention, the collecting and identifying the first reference information, and generating the first feedback parameter specifically includes:
timely collecting mirror real-time images;
identifying the position of a reflection area in the mirror real-time image;
judging whether the position of the reflecting area is within a preset area position range or not;
If the reflection area position is within the preset area position range;
A first feedback parameter is generated.
As a further aspect of the present invention, the collecting and identifying the second reference information, and generating the second feedback parameter specifically includes:
Acquiring target sensor data at fixed time;
Extracting front vehicle distance data in the target sensor data;
Judging whether the distance data of the front vehicle is larger than or equal to a vehicle following standard threshold value or not;
If the distance data of the front vehicle is larger than or equal to the following standard threshold value;
a second feedback parameter is generated.
As a further scheme of the invention, on the other hand, a lane keeping system based on an intelligent network-connected automobile, a first acquisition module is used for acquiring a driving area targeting image;
The first identification module is used for identifying the route curved information based on the driving area targeting image;
the first acquisition module is used for acquiring the target following distance;
The second acquisition module is used for acquiring the path navigation instruction;
the second acquisition module is used for acquiring the first reference information;
The second identification module is used for identifying the first reference information;
the first generation module is used for generating a first feedback parameter;
The third acquisition module is used for acquiring second reference information;
The third identification module is used for identifying the second reference information;
The second generation module is used for generating a second feedback parameter;
the searching module is used for searching whether the first feedback parameter and the second feedback parameter exist or not;
And the calculation generation module is used for calculating and generating a deceleration control instruction.
As a further aspect of the present invention, the first identification module specifically includes:
the first identification unit is used for identifying the driving area target image;
a first extraction unit for extracting a lane marking image in the travel area targeting image;
the recognition and calculation unit is used for recognizing and calculating the curvature of the lane marking in the lane marking image;
the first judging unit is used for generating curved lane confirmation information if the curvature of the lane marking is greater than or equal to a curvature threshold value;
and the second judging unit is used for generating straight lane confirmation information if the curvature of the lane marking is smaller than the curvature threshold value.
As a further aspect of the present invention, the first generating module specifically includes:
The first timing acquisition unit is used for acquiring mirror real-time images at fixed time;
The second identification unit is used for identifying the position of the reflecting area in the mirror real-time image;
a third judging unit for judging whether the reflection area position is within a preset area position range;
The first generation unit is used for generating a first feedback parameter if the reflection area position is within a preset area position range.
As a further aspect of the present invention, the second generating module specifically includes:
the second timing acquisition unit is used for acquiring the target sensor data at fixed time;
a second extraction unit configured to extract preceding vehicle distance data from the target sensor data;
The fourth judging unit is used for judging whether the distance data of the front vehicle is larger than or equal to a vehicle following standard threshold value or not;
and the second generation unit is used for generating a second feedback parameter if the preceding vehicle distance data is greater than or equal to the following standard threshold value.
According to the lane keeping method and system based on the intelligent network-connected automobile, which are provided by the embodiment of the invention, the following distance can be preset according to the traffic flow of the road surface or the driving habit of a driver, and various reference information is synchronously acquired to generate various feedback parameters, so that the reliability of lane keeping is improved, the following of the automobile can be stabilized at a low speed, and the application range of lane keeping is further improved.
Drawings
Fig. 1 is a main flow chart of a lane keeping method based on an intelligent network-connected automobile.
Fig. 2 is a flowchart for identifying route curve information based on a driving area targeting image in a lane keeping method based on an intelligent network-connected vehicle.
Fig. 3 is a flowchart of a specific method for obtaining a target following distance and a path navigation instruction in a lane keeping method based on an intelligent network-connected vehicle.
Fig. 4 is a flowchart for generating a first feedback parameter based on the first reference information collected and identified in the lane keeping method of the intelligent network-connected vehicle.
Fig. 5 is a flowchart for generating a second feedback parameter based on the second reference information collected and identified in the lane keeping method of the intelligent network-connected vehicle.
Fig. 6 is a main structural diagram of a lane keeping system based on an intelligent network-connected car.
Fig. 7 is a block diagram of a first recognition module in a lane keeping system based on an intelligent network-connected car.
Fig. 8 is a block diagram of a first generation module in a lane keeping system based on an intelligent network-connected car.
Fig. 9 is a block diagram of a second generation module in a lane keeping system based on an intelligent network-connected car.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Specific implementations of the invention are described in detail below in connection with specific embodiments.
The lane keeping method and system based on the intelligent network-connected automobile provided by the invention solve the technical problems in the background technology.
As shown in fig. 1, a main flow chart of a lane keeping method based on an intelligent network-connected vehicle according to an embodiment of the present invention includes:
step S100: collecting a target image of a driving area in real time;
step S200: identifying route curved information based on the driving area target image;
Step S300: acquiring a target following distance and a path navigation instruction;
Step S400: collecting and identifying first reference information, and generating a first feedback parameter;
Step S500: collecting and identifying second reference information, and generating second feedback parameters;
Step S600: the first feedback parameter and the second feedback parameter are retrieved, and a deceleration control instruction is calculated and generated.
In the application, the strip-shaped mirror body is vertically embedded and arranged at the outer side of the intelligent network-connected automobile front bumper with the lane keeping method and the intelligent network-connected automobile front bumper system, the special camera for shooting the real-time picture of the strip-shaped mirror body is also arranged, when a vehicle is in a traffic jam and is in a following state, the strip-shaped mirror body can reflect a front vehicle image, can be matched with the special camera according to the image position, can judge the distance from the front vehicle, the vehicle is provided with one or more cameras and sensors, the cameras are usually arranged at the front part or the top of the vehicle, the vehicle cameras and the sensors can acquire a target image of a driving area, the target image of the driving area is acquired, namely, the real-time image of the front end area of the driving area in the driving direction of the vehicle, the camera for acquiring the target image of the driving area is a wide-angle camera, the image acquisition area can be enlarged, and then collect the front vehicle and road condition information, when the driver starts the lane keeping system, the vehicle will enter a driving induction state for a certain time, in the driving induction state, the vehicle still needs the driver to take over driving comprehensively, and in the driving induction state, the vehicle firstly collects the driving area target image in real time, then, based on the driving area target image, identifies the road direction curve information, identifies the curve state of the road, identifies the road as a straight road or curve, after the identification is completed, according to the traffic flow of the road surface or the driving habit of the driver, the driver can select the target following distance with the front vehicle, for example, when the traffic flow of the road surface is larger, the driver can select smaller following distance, further, the continuous changing of the lane of other lane vehicles is prevented from entering, further, the driving efficiency and driving safety are improved, then, the path navigation instruction is led in, the vehicle can install the path navigation instruction to carry out directional driving, and then acquiring and identifying first reference information, wherein the first reference information is parameter information obtained through a distance sensor, generating a first feedback parameter, acquiring and identifying second reference information, the second reference information is image information acquired through a special camera, generating a second feedback parameter, finally searching whether the first feedback parameter and the second feedback parameter exist or not, and generating and calculating and generating a deceleration control instruction if at least one of the first feedback parameter and the second feedback parameter exists, so as to control and regulate the speed of the vehicle.
As shown in fig. 2, as a preferred embodiment of the present invention, the identifying the road direction curved information based on the driving area targeting image specifically includes:
Step S101: identifying a driving area target image;
step S102: extracting a lane marking image in the driving area targeting image;
step S103: recognizing and calculating the curvature of the lane mark in the lane mark image;
Step S104: if the curvature of the lane marking is greater than or equal to the curvature threshold value;
Step S105: generating curved lane confirmation information;
step S106: if the curvature of the lane marking is smaller than the curvature threshold value;
Step S107: then straight lane confirmation information is generated.
When the method is applied, the lane marking image in the driving area targeting image is firstly identified, the lane marking curvature in the lane marking image is identified, the curvature is a measure for describing the curve bending degree, whether a road is a curve can be accurately judged by calculating the curvature of the lane marking, the system can utilize pixel point coordinates in the image to calculate the curvature value of the lane marking through a preset algorithm method, if the curvature of the lane marking is greater than or equal to a curvature threshold value, curve lane confirmation information is generated, the driving area is proved to be the curve, and if the curvature of the lane marking is smaller than the curvature threshold value, straight lane confirmation information is generated, the driving area is proved to be a straight line.
As shown in fig. 3, as a preferred embodiment of the present invention, the acquiring the target following distance and the path navigation instruction specifically includes:
step S301: importing a target following distance;
step S302: generating a vehicle distance control instruction based on the target following distance;
step S303: identifying a path navigation instruction;
step S304: and generating a following route based on the path navigation instruction.
When the method is applied, a navigation system of a vehicle is required to be opened in advance by a driver when the vehicle is kept in use, a route navigation instruction is generated after a destination is set, the navigation system can plan an optimal route, a target following distance can be input into a vehicle system, after the target following distance is imported, a vehicle distance control instruction is generated based on the target following distance, and meanwhile, the route navigation instruction is identified to generate a following route.
As shown in fig. 4, as a preferred embodiment of the present invention, the collecting and identifying the first reference information, and generating the first feedback parameter specifically includes:
step S401: timely collecting mirror real-time images;
Step S402: identifying the position of a reflection area in the mirror real-time image;
step S403: judging whether the position of the reflecting area is within a preset area position range or not;
Step S404: if the reflection area position is within the preset area position range;
Step S405: a first feedback parameter is generated.
It should be understood that the front vehicle image can be reflected by the strip-type mirror body, the distance between the front vehicle and the front vehicle can be judged according to the image position and the special camera, the mirror surface real-time image can be acquired at fixed time, the position of a reflection area in the mirror surface real-time image is identified, if the position of the reflection area is within the range of the preset area position, the front vehicle is proved to be too close to the front end of the front vehicle, and the first feedback parameter is generated.
As shown in fig. 5, as a preferred embodiment of the present invention, the collecting and identifying the second reference information, and generating the second feedback parameter specifically includes:
Step S501: acquiring target sensor data at fixed time;
Step S502: extracting front vehicle distance data in the target sensor data;
step S503: judging whether the distance data of the front vehicle is larger than or equal to a vehicle following standard threshold value or not;
step S504: if the distance data of the front vehicle is larger than or equal to the following standard threshold value;
Step S505: a second feedback parameter is generated.
When the method is applied, the laser radar sensor is arranged at the front end of the vehicle, the laser radar sensor collects target sensor data at fixed time, then the system extracts front vehicle distance data in the target sensor data, judges whether the front vehicle distance data is larger than or equal to the following standard threshold value, and generates a second feedback parameter if the front vehicle distance data is larger than or equal to the following standard threshold value and proves that the following distance between the front vehicle and the front vehicle is too close.
As another preferred embodiment of the present invention, as shown in fig. 6, in another aspect, a lane keeping system based on an intelligent network-connected car, the system comprising:
a first acquisition module 100 for acquiring a traveling region target image;
A first identifying module 200, configured to identify the road direction curved information based on the driving area target image;
a first obtaining module 300, configured to obtain a target following distance;
A second obtaining module 400, configured to obtain a path navigation instruction;
The second acquisition module 500 is configured to acquire first reference information;
a second identifying module 600 for identifying the first reference information;
A first generation module 700, configured to generate a first feedback parameter;
a third acquisition module 800, configured to acquire second reference information;
a third identifying module 900 for identifying the second reference information;
A second generating module 1000, configured to generate a second feedback parameter;
a retrieving module 1100, configured to retrieve whether the first feedback parameter and the second feedback parameter exist;
the calculation generation module 1200 is configured to calculate and generate a deceleration control instruction.
In this embodiment, when the present invention is applied, the first acquisition module 100 acquires the target image of the driving area, the first identification module 200 identifies the road direction curve information based on the target image of the driving area, the first acquisition module 300 acquires the target following distance, the second acquisition module 400 acquires the path navigation instruction, the second acquisition module 500 acquires the first reference information, the second identification module 600 identifies the first reference information, the first generation module 700 generates the first feedback parameter, the third acquisition module 800 acquires the second reference information, the third identification module 900 identifies the second reference information, the second generation module 1000 generates the second feedback parameter, the search module 1100 is used for searching whether the first feedback parameter and the second feedback parameter exist or not, and the calculation generation module 1200 calculates and generates the deceleration control instruction.
As shown in fig. 7, as another preferred embodiment of the present invention, the first identification module 200 specifically includes:
a first recognition unit 201 for recognizing a traveling area target image;
a first extraction unit 202 for extracting a lane marking image in the travel area targeting image;
An identification calculation unit 203 for identifying and calculating a curvature of the lane marking in the lane marking image;
A first judging unit 204, configured to generate curved lane confirmation information if the curvature of the lane marking is greater than or equal to the curvature threshold;
the second judging unit 205 is configured to generate straight lane confirmation information if the curvature of the lane marking is smaller than the curvature threshold.
In this embodiment, when applied, the first recognition unit 201 recognizes the driving area target image, the first extraction unit 202 extracts the lane marking image in the driving area target image, the recognition calculation unit 203 recognizes and calculates the curvature of the lane marking in the lane marking image, the first judgment unit 204 generates curved lane confirmation information if the curvature of the lane marking is greater than or equal to the curvature threshold, and the second judgment unit 205 generates straight lane confirmation information if the curvature of the lane marking is less than the curvature threshold.
As shown in fig. 8, as another preferred embodiment of the present invention, the first generating module 700 specifically includes:
A first timing acquisition unit 701, configured to acquire a mirror real-time image at a timing;
a second identifying unit 702, configured to identify a position of a reflection area in the mirror real-time image;
A third judging unit 703, configured to judge whether the reflection area position is within a preset area position range;
The first generating unit 704 is configured to generate a first feedback parameter if the reflection area position is within a preset area position range.
In this embodiment, when the present invention is applied, the first timing acquisition unit 701 acquires the mirror real-time image at a timing, the second identification unit 702 identifies the position of the reflective area in the mirror real-time image, the third determination unit 703 determines whether the position of the reflective area is within the range of the preset area position, and if the position of the reflective area is within the range of the preset area position, the first generation unit 704 generates the first feedback parameter.
As shown in fig. 9, as another preferred embodiment of the present invention, the second generating module 1000 specifically includes:
A second timing acquisition unit 1001 for timing acquisition of target sensor data;
A second extraction unit 1002 for extracting preceding vehicle distance data in the target sensor data;
a fourth judging unit 1003 for judging whether the preceding vehicle distance data is greater than or equal to a following standard threshold;
The second generating unit 1004 is configured to generate a second feedback parameter if the preceding vehicle distance data is greater than or equal to the following standard threshold.
In this embodiment, when the present embodiment is applied, the second timing acquisition unit 1001 acquires the target sensor data at regular time, the second extraction unit 1002 extracts the front vehicle distance data in the target sensor data, the fourth judgment unit 1003 judges whether the front vehicle distance data is greater than or equal to the following standard threshold, and if the front vehicle distance data is greater than or equal to the following standard threshold, the second generation unit 1004 generates the second feedback parameter.
The embodiment of the invention provides a lane keeping method based on an intelligent network-connected automobile, and provides a lane keeping system based on the intelligent network-connected automobile, wherein a strip-shaped mirror body is vertically embedded and arranged at a set position outside a front bumper of the intelligent network-connected automobile with the lane keeping method and the intelligent network-connected automobile, a special camera for photographing a real-time picture of the strip-shaped mirror body is also arranged, when a vehicle is in a traffic jam, the strip-shaped mirror body can reflect a front vehicle image, can be matched with the special camera according to the image position, can judge the distance from the front vehicle, the vehicle is provided with one or more cameras and sensors, the cameras are usually arranged at the front part or the top of the vehicle, the vehicle cameras and the sensors can acquire a target image of a running area, the target image of the running area is acquired, namely, the real-time image of the front end area of the running direction of the vehicle, the camera for collecting the target image of the driving area is a wide-angle camera, the image collecting area can be enlarged, the front vehicle and road condition information can be collected, when a driver starts a lane keeping system, the vehicle can enter a driving sensing state for a certain time, the vehicle still needs to be comprehensively taken over by the driver in the driving sensing state, and in the driving sensing state, the vehicle firstly collects the target image of the driving area in real time, then, based on the target image of the driving area, the road direction curve information is identified, the curve state of the road is identified, the road is identified as a straight road or a curve, after the identification is completed, the driver can select a target following distance with the front vehicle according to the traffic flow of the road or the driving habit of the driver, if the traffic flow of the road is larger, the driver can select a smaller following distance, so as to prevent the continuous changing of the vehicles of other lanes from entering, and further, the driving efficiency and the driving safety are improved, then guiding in a path navigation instruction, enabling the vehicle to install the path navigation instruction for directional running, collecting and identifying first reference information, wherein the first reference information is parameter information obtained through a distance sensor, generating a first feedback parameter, collecting and identifying second reference information, the second reference information is image information collected through a special camera, generating a second feedback parameter, finally searching whether the first feedback parameter and the second feedback parameter exist or not, and generating calculation and generating a deceleration control instruction if at least one of the first feedback parameter and the second feedback parameter exists, so as to control and regulate the speed of the vehicle; the method and the system can preset the following distance according to the traffic flow of the road surface or the driving habit of the driver, synchronously acquire various reference information and generate various feedback parameters, so that the reliability of lane keeping is improved, the following of the vehicle can be stabilized at a low speed, and the application range of the lane keeping is further improved.
In order to be able to load the method and system described above to function properly, the system may include more or less components than those described above, or may combine some components, or different components, in addition to the various modules described above, for example, may include input and output devices, network access devices, buses, processors, memories, and the like.
The processor may be a central processing unit, or may be other general purpose processors, digital signal processors, application specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, which is a control center of the above system, and various interfaces and lines are used to connect the various parts.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
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.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, and alternatives falling within the spirit and principles of the invention.

Claims (9)

1. A lane keeping method based on intelligent network-connected vehicles, the method comprising:
Collecting a target image of a driving area in real time;
identifying route curved information based on the driving area target image;
Acquiring a target following distance and a path navigation instruction;
Collecting and identifying first reference information, and generating a first feedback parameter;
collecting and identifying second reference information, and generating second feedback parameters;
the first feedback parameter and the second feedback parameter are retrieved, and a deceleration control instruction is calculated and generated.
2. The lane keeping method based on intelligent network-connected vehicles according to claim 1, wherein the identifying the road direction curved information based on the driving area targeting image specifically comprises:
identifying a driving area target image;
extracting a lane marking image in the driving area targeting image;
recognizing and calculating the curvature of the lane mark in the lane mark image;
if the curvature of the lane marking is greater than or equal to the curvature threshold value;
generating curved lane confirmation information;
If the curvature of the lane marking is smaller than the curvature threshold value;
Then straight lane confirmation information is generated.
3. The lane keeping method based on intelligent network-connected vehicles according to claim 1, wherein the obtaining the target following distance and the path navigation instruction specifically comprises:
Importing a target following distance;
generating a vehicle distance control instruction based on the target following distance;
Identifying a path navigation instruction;
and generating a following route based on the path navigation instruction.
4. The lane keeping method based on intelligent network-connected vehicles according to claim 1, wherein the collecting and identifying the first reference information, and generating the first feedback parameter specifically comprises:
timely collecting mirror real-time images;
identifying the position of a reflection area in the mirror real-time image;
judging whether the position of the reflecting area is within a preset area position range or not;
If the reflection area position is within the preset area position range;
A first feedback parameter is generated.
5. The lane keeping method based on intelligent network-connected vehicles according to claim 1, wherein the collecting and identifying the second reference information, and generating the second feedback parameter specifically comprises:
Acquiring target sensor data at fixed time;
Extracting front vehicle distance data in the target sensor data;
Judging whether the distance data of the front vehicle is larger than or equal to a vehicle following standard threshold value or not;
If the distance data of the front vehicle is larger than or equal to the following standard threshold value;
a second feedback parameter is generated.
6. A lane keeping system based on intelligent networked automobiles, the system comprising:
the first acquisition module is used for acquiring a target image of the driving area;
The first identification module is used for identifying the route curved information based on the driving area targeting image;
the first acquisition module is used for acquiring the target following distance;
The second acquisition module is used for acquiring the path navigation instruction;
the second acquisition module is used for acquiring the first reference information;
The second identification module is used for identifying the first reference information;
the first generation module is used for generating a first feedback parameter;
The third acquisition module is used for acquiring second reference information;
The third identification module is used for identifying the second reference information;
The second generation module is used for generating a second feedback parameter;
the searching module is used for searching whether the first feedback parameter and the second feedback parameter exist or not;
And the calculation generation module is used for calculating and generating a deceleration control instruction.
7. The lane keeping system based on intelligent network-connected vehicles according to claim 6, wherein the first recognition module specifically comprises:
the first identification unit is used for identifying the driving area target image;
a first extraction unit for extracting a lane marking image in the travel area targeting image;
the recognition and calculation unit is used for recognizing and calculating the curvature of the lane marking in the lane marking image;
the first judging unit is used for generating curved lane confirmation information if the curvature of the lane marking is greater than or equal to a curvature threshold value;
and the second judging unit is used for generating straight lane confirmation information if the curvature of the lane marking is smaller than the curvature threshold value.
8. The lane keeping system based on intelligent network-connected vehicles according to claim 6, wherein the first generation module specifically comprises:
The first timing acquisition unit is used for acquiring mirror real-time images at fixed time;
The second identification unit is used for identifying the position of the reflecting area in the mirror real-time image;
a third judging unit for judging whether the reflection area position is within a preset area position range;
The first generation unit is used for generating a first feedback parameter if the reflection area position is within a preset area position range.
9. The lane keeping system based on intelligent network-connected vehicles according to claim 6, wherein the second generating module specifically comprises:
the second timing acquisition unit is used for acquiring the target sensor data at fixed time;
a second extraction unit configured to extract preceding vehicle distance data from the target sensor data;
The fourth judging unit is used for judging whether the distance data of the front vehicle is larger than or equal to a vehicle following standard threshold value or not;
and the second generation unit is used for generating a second feedback parameter if the preceding vehicle distance data is greater than or equal to the following standard threshold value.
CN202410881039.2A 2024-07-03 2024-07-03 Lane keeping method and system based on intelligent network-connected automobile Pending CN118405128A (en)

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