CN109435940B - Method, device and system for identifying highway lane - Google Patents
Method, device and system for identifying highway lane Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT 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
- B60W30/00—Purposes 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
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT 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
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT 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
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Abstract
The invention discloses a method, a device and a system for identifying a highway lane, wherein the method comprises the following steps: acquiring the total number of lanes corresponding to the current position of the vehicle; determining lane line information of left and right adjacent lanes of the vehicle based on image data in front of the vehicle; and determining the current lane of the vehicle based on the lane line information and the total number of the lanes. According to the invention, a high-precision positioning system is not needed, and the influence of weather and the surrounding environment of the vehicle on satellite signals is not limited, so that the current lane of the vehicle is determined by identifying the lane lines in the image data, and the accuracy of judging the current lane of the vehicle is improved.
Description
Technical Field
The invention relates to the technical field of intelligent driving, in particular to a method, a device and a system for identifying a highway lane.
Background
At present, in order to determine that a vehicle is located in a lane several on a highway, a high-precision differential RTK (Real-time kinematic) GPS (Global Positioning System) or a GPS + IMU (Inertial measurement unit) combined navigation Positioning System is generally required to be configured for the vehicle.
However, the positioning signals are easily lost due to weather and surrounding environment of the vehicle, such as rainy days, buildings, tunnels, overpasses, etc., where the satellite signals are shielded, and even if the high-precision positioning system still cannot accurately determine the current lane where the vehicle is located.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus and a system for identifying a highway lane, so as to solve the technical problem in the prior art that the accuracy of determining a current lane where a vehicle is located is poor.
The invention provides a method for identifying a highway lane, which comprises the following steps:
acquiring the total number of lanes corresponding to the current position of the vehicle;
determining lane line information of left and right adjacent lanes of the vehicle based on image data in front of the vehicle;
and determining the current lane of the vehicle based on the lane line information and the total number of the lanes.
Preferably, the determining the current lane of the vehicle based on the lane line information and the total number of lanes includes:
judging whether lane lines of left and right adjacent lanes of the current position of the vehicle are solid lines or dotted lines based on the lane line information;
if the left lane line of the current position of the vehicle is a solid line and the left lane line on the left side is none, determining that the current lane of the vehicle is a first lane on the left side;
if the left lane line of the current position of the vehicle is a dotted line and the left lane line of the left side is a solid line, determining that the current lane of the vehicle is a second lane of the left side;
if the right lane line of the current position of the vehicle is a solid line and the right lane line of the right side is none, determining that the current lane of the vehicle is the Nth lane of the left side, wherein N is the total number of the lanes;
and if the right lane line of the current position of the vehicle is a dotted line and the right lane line of the right side is a solid line, determining that the current lane of the vehicle is the left N-1 th lane.
Preferably, in the above method, if the left lane line, the left lane line, the right lane line, and the right lane line of the current position of the vehicle are all broken lines or all solid lines, the method further includes:
obtaining a change state of a first distance between a target point on the vehicle and a left lane line of the vehicle and obtaining a change state of a second distance between the target point and a right lane line of the vehicle based on image data in front of the vehicle before the current time;
determining whether the vehicle changes lanes based on the changing states of the first distance and the second distance;
if the vehicle changes lanes, determining the current lane of the vehicle based on the lane before the vehicle changes lanes.
Preferably, in the above method, if the left lane line, the left lane line, the right lane line, and the right lane line of the current position of the vehicle are all broken lines or all solid lines, the method further includes:
obtaining a change state of a first distance between a target point on the vehicle and a left lane line of the vehicle and obtaining a change state of a second distance between the target point and a right lane line of the vehicle based on image data in front of the vehicle after the current time;
determining whether the vehicle changes lanes based on the changing states of the first distance and the second distance;
if the vehicle changes lanes, returning to determine lane line information of left and right adjacent lanes of the vehicle based on the image data in front of the vehicle again until determining the lane after the vehicle changes lanes;
and determining the lane before the lane change of the vehicle based on the lane after the lane change.
In the above method, preferably, the first distance is smaller than 0, and the second distance is greater than 0;
wherein determining whether the vehicle changes lanes based on the magnitude change states of the first distance and the second distance includes:
if the first distance and the second distance are both large, determining that the vehicle changes lane to the left;
and if the first distance and the second distance are both smaller, determining that the vehicle changes lane to the right.
In the above method, preferably, the first distance is greater than 0, and the second distance is greater than 0;
wherein determining whether the vehicle changes lanes based on the magnitude change states of the first distance and the second distance includes:
if the first distance becomes smaller and the second distance becomes larger, determining that the vehicle changes lane to the left;
and if the first distance becomes larger and the second distance becomes smaller, determining that the vehicle changes lane to the right.
The method preferably determines the lane before the lane change of the vehicle based on the lane after the lane change, and includes:
if the vehicle changes lane to the left, adding one lane after the lane change as a lane before the lane change of the vehicle;
and if the vehicle changes lane to the right, subtracting one from the lane after the lane change as the lane before the lane change of the vehicle.
Preferably, the method for acquiring the total number of lanes corresponding to the current position of the vehicle includes:
obtaining the current position of a vehicle and map data corresponding to the current position;
and determining the total number of lanes corresponding to the current position based on the map data.
The present invention also provides a recognition apparatus for a road lane, comprising:
the total number obtaining unit is used for obtaining the total number of lanes corresponding to the current position of the vehicle;
a lane line determination unit configured to determine lane line information of left and right adjacent lanes of the vehicle based on image data in front of the vehicle;
and the lane determining unit is used for determining the current lane of the vehicle based on the lane line information and the total number of the lanes.
The present invention also provides a recognition system for a road lane, comprising:
the positioning instrument is used for acquiring the current position of the vehicle and the total number of lanes corresponding to the current position;
the image acquisition device is used for acquiring image data in front of the vehicle;
and the processor is used for determining lane line information of left and right adjacent lanes of the vehicle based on the image data in front of the vehicle, and determining the current lane of the vehicle based on the lane line information and the total number of the lanes.
According to the technical scheme, the method, the device and the system for recognizing the highway lane disclosed by the invention have the advantages that the total number of lanes corresponding to the current position of the vehicle is obtained, and meanwhile, the lane line information of the left lane and the right lane of the vehicle adjacent to each other is determined by utilizing the image data in front of the vehicle, so that the current lane of the vehicle can be determined by recognizing the lane line information and further based on the total number of the lanes. Therefore, the method and the device do not need a high-precision positioning system and are not limited by the influence of weather and the surrounding environment of the vehicle on satellite signals, so that the current lane of the vehicle is determined by identifying the lane lines in the image data, and the accuracy of judging the current lane of the vehicle is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a method for identifying a lane of a road according to an embodiment of the present invention;
FIGS. 2 and 3 are diagrams illustrating examples of applications of embodiments of the present invention;
FIG. 4 is another flow chart of the first embodiment of the present invention;
FIGS. 5-8 are diagrams of another exemplary application of the embodiment of the present invention;
FIG. 9 is a flowchart of a first embodiment of the present invention;
FIGS. 10-14 are diagrams illustrating another exemplary application of an embodiment of the present invention;
FIG. 15 is another flow chart of the first embodiment of the present invention;
fig. 16 is a schematic structural diagram of a road lane recognition device according to a second embodiment of the present invention;
fig. 17 is a schematic structural diagram of a road lane recognition system according to a third embodiment of the present invention;
FIG. 18 is a diagram of another exemplary application of the embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a flowchart of an implementation of a method for identifying a lane of a highway according to an embodiment of the present invention is provided, where the method in this embodiment is applied to a vehicle on a highway to obtain a current lane of the vehicle on the highway, as shown in fig. 2.
Specifically, the method in this embodiment may include the following steps:
step 101: and acquiring the total number of lanes corresponding to the current position of the vehicle.
For example, in the present embodiment, the current total number of lanes may be determined by the location of the vehicle and the road information in the high-precision map, which is denoted as N, where N is a positive integer greater than or equal to 1.
Specifically, in this embodiment, the total number of lanes corresponding to the current position may be determined by obtaining the current position of the vehicle and the map data corresponding to the current position, and then based on the map data. For example, in this embodiment, the current position of the vehicle can be obtained by roughly positioning the vehicle according to the single-point GPS, and after obtaining the high-precision map from the server or the cloud, the road information near the current position of the vehicle is queried based on the positioning, which is mainly the total information of the current lane, that is, the total number N of lanes.
Step 102: lane line information of adjacent lanes to the left and right of the vehicle is determined based on image data in front of the vehicle.
The lane line information is information in which the lane line is a broken line or a solid line. In this embodiment, lane line information of a left lane line, a right lane line, and a right lane line of a current lane of the vehicle may be analyzed through image data in front of the vehicle, as shown in fig. 3, the determined lane line information includes information whether each of the left lane line, the right lane line, and the right lane line of the current lane of the vehicle is a dotted line or a solid line.
Step 103: and determining the current lane of the vehicle based on the lane line information and the total number of the lanes.
In this embodiment, the lane line information may be analyzed and determined, and the current lane of the vehicle may be determined by combining the total number of lanes.
As can be seen from the foregoing technical solutions, in the method for identifying a highway lane provided in the embodiments of the present invention, the total number of lanes corresponding to the current position of the vehicle is obtained, and the lane line information of the left and right adjacent lanes of the vehicle is determined by using the image data in front of the vehicle, so that the current lane of the vehicle can be determined based on the total number of lanes by identifying the lane line information. Therefore, in the embodiment, a high-precision positioning system is not needed, and the influence of weather and the surrounding environment of the vehicle on the satellite signal is not limited, so that the current lane of the vehicle is determined by identifying the lane line in the image data, and the accuracy of determining the current lane of the vehicle is improved.
In one implementation, step 103 may be implemented by the following steps, as shown in fig. 4:
step 401: based on the lane line information, it is judged whether the lane lines of the left and right adjacent lanes of the current position of the vehicle are solid lines or dotted lines, and accordingly, the current lane of the vehicle is determined based on the judgment result.
Specifically, if the left lane line of the current position of the vehicle is a solid line and the left lane line of the left side is none, step 402 is executed to determine that the current lane of the vehicle is the first lane on the left side. As shown in fig. 5, if the left lane line of the current position of the vehicle is a solid line and the left lane line of the left side is none, it indicates that the left side of the current position of the vehicle is not a lane, and it can be characterized that the current lane of the vehicle is the first lane on the left side.
If the left lane line of the current position of the vehicle is a dashed line and the left lane line of the left side is a solid line, step 403 is performed to determine that the current lane of the vehicle is the second lane on the left side. As shown in fig. 6, the left lane line of the current lane position is a dashed line and the left lane line of the left side is a solid line, indicating that the left lane of the vehicle is the first lane on the left side, and then the current lane of the vehicle is the second lane on the left side.
If the right lane line of the current position of the vehicle is a solid line and the right lane line of the right side is none, go to step 404, determine that the current lane of the vehicle is the nth lane on the left side, i.e. the rightmost lane. As shown in fig. 7, the right lane line of the current position of the vehicle is a solid line and the right lane line of the right side is none, indicating that the right side of the current position of the vehicle is not a lane, then it can be characterized that the current lane of the vehicle is the rightmost lane, i.e. the nth lane on the left side.
If the right lane line of the current position of the vehicle is a dotted line and the right lane line of the right side is a solid line, step 405 is executed to determine that the current lane of the vehicle is the left N-1 th lane, i.e., the right second lane. As shown in fig. 8, if the right lane line of the current position of the vehicle is a dashed line and the right lane line of the right side is a solid line, which indicates that the right lane of the current position of the vehicle is the right first lane, it can be characterized that the current lane of the vehicle is the right second lane, i.e. the left N-1 th lane.
In addition, if the left lane line, the left lane line, the right lane line and the right lane line of the current position of the vehicle are all dotted lines, the vehicle cannot judge the current lane in lanes in the middle of the highway and with changeable lanes; or, if the left lane line, the left lane line, the right lane line and the right lane line of the current position of the vehicle are all dotted lines, the vehicle cannot determine the current lane in the middle of the highway and the lane is not changeable, and at this time, the present embodiment may further include the following steps, as shown in fig. 9:
step 406: based on image data ahead of the vehicle before the current time, a state of change of a first distance between a target point on the vehicle and a left lane line of the vehicle is obtained, and a state of change of a second distance between the target point and a right lane line of the vehicle is obtained.
The image data in front of the vehicle before the current time may be understood as image data at a time point when the lane status changes in the image data in front of the vehicle before the current time. The target point may be a position point on the vehicle where image data is collected, such as a position point of an image collecting device such as a camera, which is used to collect image data in front of the vehicle. In this embodiment, through performing image depth analysis on the image data, a change state of a first distance between the position point of the collected image data and the lane line on the left side of the vehicle and a change state of a second distance between the position point of the collected image data and the lane line on the right side of the vehicle are monitored, as shown in fig. 10, a size change of the first distance represents whether the vehicle moves to the left, and a size change of the second distance represents whether the vehicle moves to the right.
Step 407: it is determined whether the vehicle changes lanes based on the change states of the first distance and the second distance, and if the vehicle changes lanes, step 408 is performed.
In this embodiment, the current position of the vehicle may be taken as the origin of the X-axis coordinate, where the first distance is smaller than 0, the second distance is greater than 0, an absolute value of the first distance indicates a distance between the left lane line and the target point, and an absolute value of the second distance indicates a distance between the right lane line and the target point;
accordingly, if both the first distance and the second distance are detected to be greater in step 407, it may be determined that the vehicle is changing lanes to the left, and if both the first distance and the second distance are detected to be less, it may be determined that the vehicle is changing lanes to the right, as shown in fig. 11 changing lanes to the left and fig. 12 changing lanes to the right.
Or, in this embodiment, the current position of the vehicle is taken as the origin, the first distance is greater than 0, the second distance is also greater than 0, the first distance indicates the distance between the left lane line and the target point, and the second distance indicates the distance between the right lane line and the target point;
accordingly, in step 407, if it is detected that the first distance becomes smaller and the second distance becomes larger, it may be determined that the vehicle is changing lanes to the left, and if it is detected that the first distance becomes larger and the second distance becomes smaller, it may be determined that the vehicle is changing lanes to the right, as shown in the left lane changing of fig. 13 and the right lane changing of fig. 14.
Step 408: and determining the current lane of the vehicle based on the lane before the vehicle changes the lane.
In this embodiment, the lane before lane change of the vehicle may be obtained through the scheme shown in fig. 1 and related contents in the foregoing description, specifically, lane line information of left and right adjacent lanes of the vehicle may be determined based on image data of the vehicle in front of the vehicle before lane change, and then the lane of the vehicle before lane change may be determined based on the lane line information and the total number of lanes. Then, the current lane of the vehicle is determined based on the lane of the vehicle before lane change, specifically, in this embodiment, if the vehicle changes lane to the left, the current lane after lane change of the vehicle may be determined as the lane minus one of the lane before lane change of the vehicle, and if the vehicle changes lane to the right, the current lane after lane change of the vehicle may be determined as the lane plus one of the lane before lane change of the vehicle.
In another implementation, when the current lane of the vehicle cannot be determined, the present embodiment may further include the following steps, as shown in fig. 15:
step 409: based on image data in front of the vehicle after the current time, a change state of a first distance between a target point on the vehicle and a left lane line of the vehicle is obtained, and a change state of a second distance between the target point and a right lane line of the vehicle is obtained.
The image data in front of the vehicle after the current time may be understood as image data at a time when the state of the lane changes in the image data in front of the vehicle after the current time. The target point may be a position point on the vehicle where image data is collected, such as a position point of an image collecting device such as a camera, which is used to collect image data in front of the vehicle. In this embodiment, through performing image depth analysis on the image data, a change state of a first distance between the position point of the collected image data and the lane line on the left side of the vehicle and a change state of a second distance between the position point of the collected image data and the lane line on the right side of the vehicle are monitored, referring to fig. 10, a change in the size of the first distance indicates whether the vehicle moves to the left, and a change in the size of the second distance indicates whether the vehicle moves to the right.
Step 410: it is determined whether the vehicle changes lanes based on the change states of the first distance and the second distance, and if the vehicle changes lanes, step 411 is performed.
In this embodiment, the current position of the vehicle may be taken as the origin of the X-axis coordinate, where the first distance is smaller than 0, the second distance is greater than 0, an absolute value of the first distance indicates a distance between the left lane line and the target point, and an absolute value of the second distance indicates a distance between the right lane line and the target point;
accordingly, if both the first distance and the second distance are detected to be greater, it may be determined that the vehicle is changing lanes to the left in step 410, and if both the first distance and the second distance are detected to be less, it may be determined that the vehicle is changing lanes to the right, as shown in fig. 11 and 12.
Or, in this embodiment, the current position of the vehicle is taken as the origin, the first distance is greater than 0, the second distance is also greater than 0, the first distance indicates the distance between the left lane line and the target point, and the second distance indicates the distance between the right lane line and the target point;
accordingly, if it is detected that the first distance becomes smaller and the second distance becomes larger in step 410, it may be determined that the vehicle changes lane to the left, and if it is detected that the first distance becomes larger and the second distance becomes smaller, it may be determined that the vehicle changes lane to the right, as shown in fig. 13 and 14.
Step 411: and determining the lane after the lane change of the vehicle, and determining the lane before the lane change of the vehicle based on the lane after the lane change.
It should be noted that, when determining the lane after the lane change of the vehicle in the present embodiment, the scheme described in the above embodiment may be adopted. Specifically, lane line information of the left and right adjacent lanes of the vehicle may be determined based on image data of the front of the vehicle after lane change, and the lane of the vehicle after lane change may be determined based on the lane line information and the total number of lanes. Then, based on the lane of the vehicle after lane change, the lane of the vehicle before lane change is determined. Specifically, if the vehicle changes lane to the left, the lane after the lane change is added by one to be used as the lane before the vehicle changes lane, and if the vehicle changes lane to the right, the lane after the lane change is subtracted by one to be used as the lane before the vehicle changes lane.
Referring to fig. 16, a schematic structural diagram of a road lane recognition apparatus according to a second embodiment of the present invention, which may be disposed in a vehicle to recognize a lane in which the vehicle is located, specifically, the apparatus may include the following structure:
the total number acquiring unit 1601 is configured to acquire a total number of lanes corresponding to a current position of the vehicle.
A lane line determining unit 1602, configured to determine lane line information of left and right adjacent lanes of the vehicle based on image data in front of the vehicle.
A lane determining unit 1603, configured to determine a current lane of the vehicle based on the lane line information and the total number of lanes.
As can be seen from the foregoing technical solutions, in the identification apparatus for a highway lane according to the second embodiment of the present invention, the total number of lanes corresponding to the current position of the vehicle is obtained, and the lane line information of the left and right adjacent lanes of the vehicle is determined by using the image data in front of the vehicle, so that the current lane of the vehicle can be determined based on the total number of lanes by identifying the lane line information. Therefore, in the embodiment, a high-precision positioning system is not needed, and the influence of weather and the surrounding environment of the vehicle on the satellite signal is not limited, so that the current lane of the vehicle is determined by identifying the lane line in the image data, and the accuracy of determining the current lane of the vehicle is improved.
It should be noted that, the specific implementation of each unit of the apparatus in the present embodiment can be described with reference to the corresponding drawings and contents in the foregoing, and is not stated herein.
Referring to fig. 17, a schematic structural diagram of a recognition system for a road lane according to a third embodiment of the present invention is provided, where the system may include the following structures:
the locator 1701 is configured to obtain a current position of the vehicle and a total number of lanes corresponding to the current position.
An image capturing device 1702 for capturing image data in front of the vehicle.
The image capturing device 1702 may be implemented as a camera, and may be disposed in the vehicle or on the vehicle head, for example, the camera may be disposed at a position between the central rearview mirror and the windshield, so as to avoid blocking the view of the vehicle.
A processor 1703, configured to determine lane line information of left and right adjacent lanes of the vehicle based on image data in front of the vehicle, and determine a current lane of the vehicle based on the lane line information and the total number of lanes.
As can be seen from the foregoing technical solutions, in the recognition system for a highway lane provided in the third embodiment of the present invention, the total number of lanes corresponding to the current position of the vehicle is obtained, and meanwhile, the lane line information of the left and right adjacent lanes of the vehicle is determined by using the image data in front of the vehicle, so that the current lane of the vehicle can be determined based on the total number of lanes by recognizing the lane line information. Therefore, in the embodiment, a high-precision positioning system is not needed, and the influence of weather and the surrounding environment of the vehicle on the satellite signal is not limited, so that the current lane of the vehicle is determined by identifying the lane line in the image data, and the accuracy of determining the current lane of the vehicle is improved.
It should be noted that, the specific implementation of each structure of the system in the present embodiment can be described with reference to the corresponding drawings and contents in the foregoing, and is not stated herein.
The following takes the determination of the vehicle lane on the expressway as an example to illustrate the scheme in the embodiment:
as shown in fig. 18, the implementation system provided in the vehicle may implement the lane determination by:
step S1, obtaining the total number of lanes on the current road according to the positioning and high-precision map, the concrete implementation method is as follows:
and roughly positioning the vehicle according to the single-point GPS. And inquiring road information near the position of the vehicle according to the rough positioning and the high-precision map, wherein the road information is mainly the total number information of the current lane. And determining the current total number of lanes according to the positioning of the vehicle and the road information in the high-precision map, and recording the total number as N.
And step S2, installing a camera on the vehicle head to detect the types of the current lane and the left and right adjacent lane lines, and judging the current lane according to the actual and actual types of the detected lane lines and the current total lane number. The specific implementation method comprises the following steps:
if the camera detects that the left lane line is a solid line and the left lane line on the left is absent, the vehicle is considered to be located in a left 1 lane, if the camera detects that the left lane line is a dotted line and the left lane line on the left is a solid line, the vehicle is considered to be located in a left 2 lane, if the camera detects that the right lane line is a solid line and the right lane line on the right is absent, the vehicle is considered to be located in an N lane, and if the camera detects that the right lane line is a dotted line and the right lane line on the right is a solid line, the vehicle is considered to be located in an N-1 lane. In addition to the above conditions, it is considered that the specific lane is not judged by the broken solid line, and thus the following step S3 is executed.
And step S3, judging whether the vehicle has left lane changing and right lane changing according to the lane line information output by the camera. The specific implementation method comprises the following steps:
the installed camera needs to output the distance between the line of the detected lane and the camera, and the distance between the camera and the Left lane is recorded as Left _ d: (<0) Right _ d is the distance from the Right lane>0). When the vehicle changes lanes to the Left, Left _ d and Right _ d are gradually increased, and when the vehicle changes lanes to the Right, Left _ d and Right _ d are gradually decreased. And judging whether the vehicle changes lanes or not according to the characteristics. According to lane change result and lane mark at last time, calculating nk-1K is a positive integer which is more than 1 and less than N, and if the vehicle has a left lane change, the current lane N isk＝nk-1-1, if the vehicle makes a right lane change, then the current lane nk＝nk-1+1, otherwise nk＝nk-1。
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. A method of identifying a highway lane, comprising:
acquiring the total number of lanes corresponding to the current position of the vehicle;
determining lane line information of left and right adjacent lanes of the vehicle based on image data in front of the vehicle;
determining a current lane of the vehicle based on the lane line information and the total number of lanes;
determining a current lane of the vehicle based on the lane line information and the total number of lanes, including:
judging whether lane lines of left and right adjacent lanes of the current position of the vehicle are solid lines or dotted lines based on the lane line information;
if the left lane line of the current position of the vehicle is a solid line and the left lane line on the left side is none, determining that the current lane of the vehicle is a first lane on the left side;
if the left lane line of the current position of the vehicle is a dotted line and the left lane line of the left side is a solid line, determining that the current lane of the vehicle is a second lane of the left side;
if the right lane line of the current position of the vehicle is a solid line and the right lane line of the right side is none, determining that the current lane of the vehicle is the Nth lane of the left side, wherein N is the total number of the lanes;
if the right lane line of the current position of the vehicle is a dotted line and the right lane line of the right side is a solid line, determining that the current lane of the vehicle is the left N-1 th lane;
if the left lane line, the right lane line and the right lane line of the current position of the vehicle are all dotted lines or all solid lines, the method further comprises:
obtaining a change state of a first distance between a target point on the vehicle and a left lane line of the vehicle and obtaining a change state of a second distance between the target point and a right lane line of the vehicle based on image data in front of the vehicle before the current time;
determining whether the vehicle changes lanes based on the changing states of the first distance and the second distance;
if the vehicle changes lanes, determining the current lane of the vehicle based on the lane before the vehicle changes lanes.
2. The method of claim 1, wherein if the left lane line, the left lane line, the right lane line, and the right lane line of the current location of the vehicle are all dashed lines or all solid lines, the method further comprises:
obtaining a change state of a first distance between a target point on the vehicle and a left lane line of the vehicle and obtaining a change state of a second distance between the target point and a right lane line of the vehicle based on image data in front of the vehicle after the current time;
determining whether the vehicle changes lanes based on the changing states of the first distance and the second distance;
if the vehicle changes lanes, returning to determine lane line information of left and right adjacent lanes of the vehicle based on the image data in front of the vehicle again until determining the lane after the vehicle changes lanes;
and determining the lane before the lane change of the vehicle based on the lane after the lane change.
3. The method of claim 1 or 2, wherein the first distance is less than 0 and the second distance is greater than 0;
wherein determining whether the vehicle changes lanes based on the magnitude change states of the first distance and the second distance includes:
if the first distance and the second distance are both large, determining that the vehicle changes lane to the left;
and if the first distance and the second distance are both smaller, determining that the vehicle changes lane to the right.
4. The method of claim 1 or 2, wherein the first distance is greater than 0 and the second distance is greater than 0;
wherein determining whether the vehicle changes lanes based on the magnitude change states of the first distance and the second distance includes:
if the first distance becomes smaller and the second distance becomes larger, determining that the vehicle changes lane to the left;
and if the first distance becomes larger and the second distance becomes smaller, determining that the vehicle changes lane to the right.
5. The method of claim 2, wherein determining the lane of the vehicle before the lane change based on the lane after the lane change comprises:
if the vehicle changes lane to the left, adding one lane after the lane change as a lane before the lane change of the vehicle;
and if the vehicle changes lane to the right, subtracting one from the lane after the lane change as the lane before the lane change of the vehicle.
6. The method of claim 1, wherein obtaining a total number of lanes corresponding to a current location of the vehicle comprises:
obtaining the current position of a vehicle and map data corresponding to the current position;
and determining the total number of lanes corresponding to the current position based on the map data.
7. A road lane recognition device, comprising:
the total number obtaining unit is used for obtaining the total number of lanes corresponding to the current position of the vehicle;
a lane line determination unit configured to determine lane line information of left and right adjacent lanes of the vehicle based on image data in front of the vehicle;
a lane determining unit configured to determine a current lane of the vehicle based on the lane line information and the total number of lanes;
wherein determining the current lane of the vehicle based on the lane line information and the total number of lanes comprises:
judging whether lane lines of left and right adjacent lanes of the current position of the vehicle are solid lines or dotted lines based on the lane line information;
if the left lane line of the current position of the vehicle is a solid line and the left lane line on the left side is none, determining that the current lane of the vehicle is a first lane on the left side;
if the left lane line of the current position of the vehicle is a dotted line and the left lane line of the left side is a solid line, determining that the current lane of the vehicle is a second lane of the left side;
if the right lane line of the current position of the vehicle is a solid line and the right lane line of the right side is none, determining that the current lane of the vehicle is the Nth lane of the left side, wherein N is the total number of the lanes;
if the right lane line of the current position of the vehicle is a dotted line and the right lane line of the right side is a solid line, determining that the current lane of the vehicle is the left N-1 th lane;
if the left lane line, the right lane line and the right lane line of the current position of the vehicle are all dotted lines or all solid lines, then: obtaining a change state of a first distance between a target point on the vehicle and a left lane line of the vehicle and obtaining a change state of a second distance between the target point and a right lane line of the vehicle based on image data in front of the vehicle before the current time; determining whether the vehicle changes lanes based on the changing states of the first distance and the second distance;
if the vehicle changes lanes, determining the current lane of the vehicle based on the lane before the vehicle changes lanes.
8. A highway lane identification system, comprising:
the positioning instrument is used for acquiring the current position of the vehicle and the total number of lanes corresponding to the current position;
the image acquisition device is used for acquiring image data in front of the vehicle;
the processor is used for determining lane line information of left and right adjacent lanes of the vehicle based on image data in front of the vehicle, and determining the current lane of the vehicle based on the lane line information and the total number of the lanes;
wherein determining the current lane of the vehicle based on the lane line information and the total number of lanes comprises:
judging whether lane lines of left and right adjacent lanes of the current position of the vehicle are solid lines or dotted lines based on the lane line information;
if the left lane line of the current position of the vehicle is a solid line and the left lane line on the left side is none, determining that the current lane of the vehicle is a first lane on the left side;
if the left lane line of the current position of the vehicle is a dotted line and the left lane line of the left side is a solid line, determining that the current lane of the vehicle is a second lane of the left side;
if the right lane line of the current position of the vehicle is a solid line and the right lane line of the right side is none, determining that the current lane of the vehicle is the Nth lane of the left side, wherein N is the total number of the lanes;
if the right lane line of the current position of the vehicle is a dotted line and the right lane line of the right side is a solid line, determining that the current lane of the vehicle is the left N-1 th lane;
if the left lane line, the right lane line and the right lane line of the current position of the vehicle are all dotted lines or all solid lines, then: obtaining a change state of a first distance between a target point on the vehicle and a left lane line of the vehicle and obtaining a change state of a second distance between the target point and a right lane line of the vehicle based on image data in front of the vehicle before the current time; determining whether the vehicle changes lanes based on the changing states of the first distance and the second distance;
if the vehicle changes lanes, determining the current lane of the vehicle based on the lane before the vehicle changes lanes.
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| CN112406884B (en) * | 2019-08-20 | 2022-03-15 | 北京地平线机器人技术研发有限公司 | Vehicle driving state recognition method and device, storage medium and electronic equipment |
| CN111089598B (en) * | 2019-11-25 | 2021-08-06 | 首都师范大学 | Vehicle-mounted lane-level real-time map matching method based on ICCIU |
| CN111439258A (en) * | 2020-02-27 | 2020-07-24 | 广汽蔚来新能源汽车科技有限公司 | Control method and device for tire burst vehicle, computer equipment and storage medium |
| CN111959515B (en) * | 2020-08-19 | 2023-11-03 | 无锡威孚高科技集团股份有限公司 | Forward target selection method, device and system based on visual detection |
| CN112070839A (en) * | 2020-09-11 | 2020-12-11 | 武汉理工大学 | Method and equipment for positioning and ranging rear vehicle transversely and longitudinally |
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