CN113221638B - Vehicle target perception method and system - Google Patents
Vehicle target perception method and system Download PDFInfo
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- CN113221638B CN113221638B CN202110349952.4A CN202110349952A CN113221638B CN 113221638 B CN113221638 B CN 113221638B CN 202110349952 A CN202110349952 A CN 202110349952A CN 113221638 B CN113221638 B CN 113221638B
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/86—Combinations of sonar systems with lidar systems; Combinations of sonar systems with systems not using wave reflection
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/88—Sonar systems specially adapted for specific applications
- G01S15/93—Sonar systems specially adapted for specific applications for anti-collision purposes
- G01S15/931—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Abstract
The invention provides a vehicle target sensing method and system, which are based on the detection capability of a monocular camera, detect lane lines in the running process of a vehicle, determine the running track of the vehicle, add extra ultrasonic waves to compensate blind areas of the camera, detect the transverse and longitudinal distances of left and right vehicles of the vehicle, and confirm whether the left and right vehicles invade the vehicle lane through lane line data to be dangerous targets, so that the vehicle can early warn in advance, traffic accidents are reduced, and the safety of vehicle personnel is ensured.
Description
Technical Field
The invention belongs to the field of intelligent driving of automobiles, and particularly relates to a perception technology for a target vehicle IN a CUT-IN scene.
Background
Chinese patent document CN201920607552.7 discloses an ultrasonic ranging obstacle avoidance car safety precaution system, and it includes singlechip, ultrasonic wave receiving detection circuit, ultrasonic wave transmitting circuit and alarm circuit, installs ultrasonic ranging system in car system, through the effective quick measurement to car front and back, left and right sides distance, realizes that the car is automatic to avoid the obstacle, avoids the driver to observe through the people's eyes and keeps away the mistake that the obstacle brought. The problem with this technique is that only the distance of the obstacle from the host vehicle is considered, and whether the obstacle intrudes into the host lane in a normal driving scene is not considered, which may cause a rear-end collision.
In addition, chinese patent document CN201920351678.2 proposes a vehicle radar warning device and a vehicle, which includes at least one millimeter wave radar installed on a side of the vehicle, at least one ultrasonic radar installed around the vehicle, and a warning host for acquiring monitoring signals of the millimeter wave radar and the ultrasonic radar in real time and generating warning information, so as to monitor and warn obstacles for the vehicle in a high-speed and low-speed driving state respectively. The technology makes up the disadvantage of ultrasonic waves in a high-speed scene through the millimeter wave radar, so that the transverse and longitudinal distances of the target can still be detected in the high-speed scene, but whether the target invades the lane is not checked, so that early warning cannot be made in advance, and potential safety hazards exist
Disclosure of Invention
The invention provides a vehicle target sensing method and a system, which solve the problem of fine sensing when left and right vehicles invade a lane IN a low-speed CUT-IN scene, namely accurately sense the transverse and longitudinal positions and course angles of the vehicle targets, and the ultrasonic radar can accurately detect the transverse and longitudinal distances of the targets at the left side and the right side of the vehicle IN the low-speed road condition through the detection capability of a monocular camera on lane lines, so that the sensing and tracking of the targets at the two sides IN the CUT-IN scene are realized, and the early warning capability of the vehicle and the personal safety of personnel on the vehicle are ensured.
The technical scheme of the invention is as follows:
a vehicle target awareness method, comprising the steps of:
step 1, receiving lane line data acquired by a monocular camera and data acquired by an ultrasonic radar for vehicle targets on two adjacent lanes; the data acquired by the ultrasonic radar comprises target data in adjacent lanes on the left side and the right side, the transverse and longitudinal distances of the targets and the sectors for detecting the targets. Here, the sector of the detection target is a sector of a region divided when the ultrasonic sensor mounted on the vehicle detects. The data acquired by the monocular camera comprises left-left lane line data, left-right lane line data, right-left lane line data and right-right lane line data.
And 2, judging the rationality of target data acquired by the ultrasonic radar and tracking the target.
And 3, judging whether the target has a trend of invading the own lane to become a dangerous target.
Further, the step 2 includes:
step 2.1, detecting whether the horizontal and vertical distance of the target represents that the target exists in a side lane or not, and detecting whether the jump of the horizontal and vertical distance is reasonable or not;
step 2.2, tracking a reasonable side lane target, adding a tracking ID to the target, and if the ID changes, changing the target instead of the previous target.
Further, the step 3 includes: and fitting the course of the target by tracking the transverse and longitudinal distances of the target through the left lane line and the right lane line data of the lane lines, and then calculating whether the transverse distance of the target has a trend of invading the own lane. The distance between the head position of the target vehicle and the own lane can be calculated according to the target lateral distance and the course angle, and if the distance value steadily decreases continuously or the distance value is negative, the tendency of invading the own lane is indicated.
The calculating whether the lateral distance of the target has a trend of invading the lane specifically comprises:
if the target continues n frames (for example, 10 frames (500 ms) and the transverse distance is reduced, the vehicle target is considered to have a approaching trend, otherwise the vehicle is considered to be running normally, whether the target invades the own lane is further judged according to lane line data, if the target wheels are already pressed, the target is considered to have a trend of invading the own lane, otherwise, the vehicle is considered to have no trend of invading the own lane.
Further, the method further comprises a step 4 of transmitting all target data to a vehicle target output module, converting the target data into a CAN data format and then transmitting the CAN data to a CAN bus.
Further, in step 1, the method also comprises the step of preprocessing lane line data, wherein the preprocessing comprises lane line complement and prediction.
The invention also provides a vehicle target sensing system for realizing the method, which comprises a monocular camera, an ultrasonic radar and a sensor controller.
The monocular camera acquires lane line data, and the ultrasonic radar acquires data of vehicle targets of adjacent lanes on two sides, wherein the data comprise target data in adjacent lanes on the left side and the right side, the transverse and longitudinal distances of the targets and sectors for detecting the targets; the monocular camera and the ultrasonic radar are connected with the sensor controller through the CAN line, the sensor controller receives and processes data, the rationality of target data acquired by the ultrasonic radar is judged, a vehicle target is tracked, and whether the vehicle target invades the lane to become a dangerous target is judged.
Further, the system also comprises a vehicle target output module, which receives the target data processed by the sensor controller, converts the target data into a CAN data format and then sends the CAN data to the CAN bus.
The invention realizes the perception and tracking of targets on two sides of a CUT-IN scene vehicle based on a sensor system controller, a monocular camera and an ultrasonic radar, and provides a method for solving the problem that target data cannot be predicted IN the scene, and the method has the following specific advantages:
1. the method and the device are based on the detection capability of the monocular camera, detect the lane line in the running process of the vehicle, determine the running track of the vehicle, add the compensation of ultrasonic waves to the blind area of the camera, detect the transverse and longitudinal distance between the left and right vehicles of the vehicle, and confirm whether the left and right vehicles invade the vehicle lane to be a dangerous target through the lane line data, so that the vehicle can early warn in advance.
2. The invention uses the advantage of high detection precision of the transverse and longitudinal distances of the short-distance targets in the low-speed scene by using the ultrasonic waves, carries out transverse and longitudinal distance tracking on the targets on the left side and the right side, senses whether the targets invade the lane to become dangerous targets or not, makes timely response, reduces traffic accidents and ensures the safety of vehicle personnel.
Drawings
FIG. 1 is a schematic diagram of a vehicle target perception system based on ultrasound and monocular cameras;
FIG. 2 is a flow chart of a vehicle object perception method of the present invention;
FIG. 3 is a left-hand vehicle CUT-IN scene diagram.
Detailed Description
The technique of the present invention is further described below with reference to the accompanying drawings.
As shown in fig. 1, in the vehicle target sensing system architecture based on ultrasonic waves and a monocular camera, the monocular camera and an ultrasonic radar are connected with a sensor controller through a CAN line, the controller receives and processes data, and target sensing information on the left side and the right side of the vehicle is sent to a CAN bus for subsequent control.
The monocular camera is used for acquiring lane line data, the ultrasonic radar is used for acquiring data of vehicle targets of adjacent lanes at two sides, and the data comprise target data in the adjacent lanes at the left side and the right side, the transverse and longitudinal distances of the targets and sectors for detecting the targets. The monocular camera and the ultrasonic radar are connected with the sensor controller through the CAN line, the sensor controller receives and processes data, the rationality of target data acquired by the ultrasonic radar is judged, a vehicle target is tracked, and whether the vehicle target invades the lane to become a dangerous target is judged. The vehicle target output module receives target data processed by the sensor controller, converts the target data into a CAN data format and then sends the CAN data to the CAN bus.
The vehicle target perception is realized by adopting the system, which mainly comprises three steps:
and step 1, receiving lane line data of a monocular camera and data of ultrasonic waves for adjacent lane targets at two sides.
And 2, judging the rationality of the ultrasonic target data and tracking the target.
And 3, judging whether the target has a trend of invading the own lane to become a dangerous target.
The following will describe the above three steps in detail with reference to the accompanying drawings:
as shown in fig. 2, a flow chart of a vehicle object sensing method is provided.
Firstly, data are respectively acquired through a monocular camera and an ultrasonic radar, wherein the monocular camera acquires data of left, right and right lane lines, and the ultrasonic radar acquires target data in lanes at the left side and the right side, including the transverse and longitudinal distances of a target and the sector of a detected target.
And then preprocessing lane line data, wherein the preprocessing comprises lane line complement and prediction. The prediction can be based on a certain number of data frames, for example, 20 frames of data before the lane line is lost, and then the lane line fitting is performed by using a least square method, so that the lane line prediction is realized.
And then, carrying out target data rationality detection, including detecting whether the target horizontal and vertical distance represents that the target exists in a side lane, detecting whether the jump of the horizontal and vertical distance is reasonable, and the like. For example, according to the speed and distance of the received data, the horizontal and vertical distance of the next frame of target can be calculated respectively, and uniform motion is performed through the speed value; or calculating the distance of the next frame according to the change value of the distance, and judging whether the jump of the distance is reasonable or not.
Then, a reasonable side lane target is tracked, a tracking ID is added to the target, and if the ID changes, the target changes and is not the previous target.
And then fitting the course of the target by the left lane line and right lane line data of the lane lines and by tracking the transverse and longitudinal distances of the target, and then calculating whether the transverse distance of the target has a trend of invading the own lane.
And finally, transmitting all the target data to a vehicle target output module, converting the target data into a CAN data format and then transmitting the CAN data to a CAN bus.
Here, the left vehicle CUT-IN scene is described as an example, and as shown IN fig. 3, red is left and right lane lines and left lane lines detected by the monocular camera, green area is an ultrasonic detection range, and black module is a mounting position of the ultrasonic radar on the vehicle. The left vehicle invades the lane from the left side lane CUT-IN, the left front corner radar and the side corner radar have the capability of detecting the target vehicle during the period, the transverse and longitudinal distances of the target vehicle are stably output, and the movement trend and the course of the target vehicle can be known by tracking the change of the ultrasonic distances of the two sectors; as shown IN the figure, the left vehicle CUT-IN is a dangerous target, and is converted into a CAN data format by the output module and sent to the CAN bus, so as to contribute to subsequent control.
In a further embodiment, the logic for determining whether the vehicle is a dangerous object is specifically: after lane line data and target vehicle data on the left side and the right side are obtained, tracking the transverse distance of the target, and if the transverse distance of the target is reduced continuously for 10 frames (namely 500 ms), considering that the vehicle target has a approaching trend, otherwise, the vehicle target normally runs; and further judging whether the target invades the lane according to the lane line data, if the target wheel is already pressed, considering the target as a dangerous target, otherwise, considering the vehicle to run obliquely only in the side lane.
Claims (6)
1. A method of vehicle target perception, comprising the steps of:
step 1, receiving lane line data acquired by a monocular camera and data acquired by an ultrasonic radar for vehicle targets on two adjacent lanes; the data acquired by the ultrasonic radar comprises target data in adjacent lanes on the left side and the right side, the transverse and longitudinal distances of the targets and the sectors for detecting the targets;
step 2, judging the rationality of target data acquired by the ultrasonic radar and tracking the target; comprising the following steps:
step 2.1, detecting whether the horizontal and vertical distance of the target represents that the target exists in a side lane or not, and detecting whether the jump of the horizontal and vertical distance is reasonable or not;
step 2.2, tracking a reasonable side lane target, adding a tracking ID to the target, and if the ID changes, changing the target instead of the previous target;
step 3, judging whether the target has a trend of invading the own lane to become a dangerous target, comprising the following steps: fitting the course of the target through left lane line and right lane line data of the lane lines and tracking the transverse and longitudinal distances of the target, and then calculating whether the transverse distance of the target has a trend of invading the own lane or not, wherein the method specifically comprises the following steps of: if the target continues to decrease in n frames of transverse distance, the vehicle target is considered to have a approaching trend, otherwise, the vehicle target is normally driven; whether the target invades the own lane is further judged according to the lane line data, if the target wheels are already pressed, the target is considered to have a trend of invading the own lane, otherwise, the vehicle is considered to have no trend of invading the own lane.
2. The vehicle object sensing method according to claim 1, wherein the data acquired by the monocular camera in step 1 includes four lane line data of left, right and right.
3. The vehicle object sensing method according to claim 1 or 2, further comprising step 4 of transmitting all object data to a vehicle object output module, converting to a CAN data format and transmitting to a CAN bus.
4. The vehicle object sensing method according to claim 1 or 2, further comprising performing lane line data preprocessing in step 1, the preprocessing including lane line complement and prediction.
5. A vehicle object sensing system implementing the method of any of claims 1-4, comprising a monocular camera, an ultrasonic radar, and a sensor controller;
the monocular camera acquires lane line data, and the ultrasonic radar acquires data of vehicle targets of adjacent lanes on two sides, wherein the data comprise target data in adjacent lanes on the left side and the right side, the transverse and longitudinal distances of the targets and sectors for detecting the targets; the monocular camera and the ultrasonic radar are connected with the sensor controller through the CAN line, the sensor controller receives and processes data, the rationality of target data acquired by the ultrasonic radar is judged, a vehicle target is tracked, and whether the vehicle target invades the lane to become a dangerous target is judged.
6. The vehicle target perception system according to claim 5, further comprising a vehicle target output module that receives target data processed by the sensor controller, converts the target data to a CAN data format and transmits the CAN data to the CAN bus.
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| WO2023184051A1 (en) * | 2022-03-26 | 2023-10-05 | 华为技术有限公司 | Intrusion detection method and apparatus, and vehicle |
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