CN111361557B - Early warning method for collision accident during turning of heavy truck - Google Patents
Early warning method for collision accident during turning of heavy truck Download PDFInfo
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- 230000010365 information processing Effects 0.000 abstract description 3
- 208000016285 Movement disease Diseases 0.000 description 14
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- 208000012661 Dyskinesia Diseases 0.000 description 1
- 208000032140 Sleepiness Diseases 0.000 description 1
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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
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q9/00—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
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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
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0953—Predicting travel path or likelihood of collision the prediction being responsive to vehicle dynamic parameters
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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
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
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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
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
- B60W2050/143—Alarm means
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Abstract
The invention discloses a method for early warning the occurrence of a collision accident when a heavy truck turns, wherein the vehicle is provided with a speed sensor, a steering wheel angle sensor, an information processing module, a radar and a vehicle-mounted camera, and the method for early warning the collision of the vehicle comprises the following steps: when the vehicle is ready to turn to run, turning track information of each wheel of the vehicle is obtained through a steering wheel turning angle sensor and a model algorithm, and related information of obstacles around the vehicle is obtained through a radar and a camera; analyzing whether the vehicle has collision danger at a certain future moment or not according to the running information and the related information; if danger happens at a certain moment in the future, the driver is reminded to avoid collision accidents in a sound-light alarm mode. The invention can realize more comprehensive vehicle collision early warning when the vehicle turns and runs, and further improves the accuracy of vehicle collision early warning and the safety of vehicle running.
Description
Technical Field
The invention relates to the field of driving safety, in particular to a method for early warning collision accidents when a heavy truck turns.
Background
At present, the safety driving accidents of vehicle driving are endless, and the most important accident is the collision accident. The reasons for this are not only driver distraction and road emergency, but also a very important reason that the driver cannot be warned in advance and further cannot be dealt with in advance to avoid accidents.
At present, the method only exists for judging the front obstacle by emitting radar waves, but the application range of the early warning method is limited, for example, the early warning method is only effective for front vehicles on a straight lane, but cannot accurately judge for non-straight lanes, such as transverse incoming vehicles at a crossroad, and meanwhile, the precision of detecting other roadside obstacles (such as pedestrians and bicycles) is not high when a heavy truck turns, so that the collision early warning is not comprehensive and accurate enough.
Disclosure of Invention
The invention mainly aims to provide an early warning method for collision accidents when a heavy truck turns, and solves the problems of limited application range and low early warning precision in the conventional collision early warning technology.
In order to realize the purpose, the technical scheme provided by the invention is as follows: a method for early warning of collision accidents when a heavy truck turns comprises the following steps:
when the vehicle is ready to turn to run, obtaining turning track information of each wheel of the vehicle, including position coordinate information and running speed information, through a speed sensor and a steering wheel corner sensor and by establishing a turning model of the heavy truck; obtaining related information of the types of obstacles around the vehicle through a millimeter wave radar and a vehicle-mounted high-definition camera; analyzing whether collision danger exists at a future moment of the vehicle or not according to the turning track information and the related information; if danger can happen at a certain moment in the future, the driver is reminded to avoid collision accidents through the early warning module.
Further, when the position and speed information of the obstacle are acquired, the relevant information uniformly judges whether the movement mode of the obstacle is a static or uniform linear movement mode.
Furthermore, the method for judging the type of the obstacle is that the image collected by the video sensor during the running of the vehicle is taken as the processing content, and the video dynamic image information is subjected to target extraction to provide potential obstacle information for the unmanned vehicle, so that the aims of early warning and automatic adjustment of the speed and direction are fulfilled.
Further, the obstacle type identification process is as follows: in the vehicle identification process, firstly, a vehicle identification interesting area in an image coordinate system is determined according to radar information; then, symmetry analysis is carried out on the region of interest to obtain a vehicle symmetry center, and the shadow feature of the bottom of the vehicle is analyzed to complete vehicle edge detection; and finally, obtaining the vehicle identification width according to the inverse perspective transformation, and verifying the identification result according to the identification width.
And further, in the process of acquiring the turning track information, the turning tracks of the front axle, the hinge point and the geometric center of the trailer of the tractor are obtained by establishing a turning model of the heavy truck, and the motion track of the right wheel of the tractor and the motion track of the right rear wheel of the trailer are obtained through the geometric relation of the truck.
Further, the specific process of analyzing whether the vehicle has collision danger at a future moment through the turning track information and the related information is as follows: according to the obtained motion trail of the right wheel of the tractor and the motion trail of the right rear wheel of the trailer, the track of the point P of the right wheel of the front axle of the tractor and the track of the point K of the right rear wheel of the trailer can be obtained through parameters of the tractor; a rectangular area formed by the movement of the point P and the point K is a collision area, and whether collision occurs can be judged by only giving a time t and judging whether a target object falls into the collision area after the time t; wherein:
the P point trajectory equation is:
the K-point trajectory equation is:
p point coordinate after t time:
k point coordinates after time t:
q (x) point coordinate after time t 2 ,y 2 +v Q t)
When the set of inequalities:
if t is solved, the point C falls into the early warning area, and collision is shown; wherein x p 、y p Is the coordinate of the circle center of the right wheel of the front steering axle of the tractor, x k 、y k Is the center coordinate, x, of the right rear wheel of the trailer 0 、y 0 Is the front steering axle right of the tractorInitial position coordinates of the wheel, x 1 、y 1 Is the initial position coordinate, x, of the trailer's right rear wheel 2 、y 2 Is the initial position coordinate of the moving obstacle, R P 、R K Respectively the turning radius, V, of the front steering axle right wheel of the tractor and the rear wheel of the trailer P 、V K 、V Q The driving speeds of the front steering axle right wheel of the tractor, the rear right wheel of the trailer and the moving obstacle are respectively.
Furthermore, the early warning module is in a sound-light early warning mode, and is used for broadcasting through a voice chip to remind a driver, or is used for reminding the driver through installing a red-green indicating lamp, or is used for reminding the driver through two combination modes.
When the vehicle is ready to turn to run, the turning track information of each wheel of the vehicle is obtained through a steering wheel angle sensor and a model algorithm, and the related information of obstacles around the vehicle is obtained through a radar and a camera; analyzing whether the vehicle has collision danger at a certain future moment or not according to the running information and the related information; if danger happens at a certain moment in the future, the driver is reminded to avoid collision accidents in an audible and visual alarm mode. The invention can realize more comprehensive vehicle collision early warning when the vehicle turns and runs, and further improves the accuracy of vehicle collision early warning and the safety of vehicle running.
Drawings
FIG. 1 is a schematic flow chart of an embodiment of a collision warning method for turning of a heavy truck according to the present invention;
FIG. 2 is a functional block diagram of an embodiment of the collision warning device for heavy truck during turning;
FIG. 3 is a diagram of a train trajectory analysis of a semitrailer in accordance with an embodiment of the warning system for heavy truck cornering collision according to the present invention;
FIG. 4 is a simplified diagram of an analysis model of an embodiment of the collision warning system for turning of a heavy truck according to the present invention;
the objects, features, and advantages of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating an embodiment of a vehicle turning collision warning method according to the present invention. In this embodiment, the vehicle collision warning includes:
step S10, when the vehicle is in an initial state of turning running, obtaining running information of the vehicle, and obtaining related information of obstacles around the vehicle through a millimeter wave radar and a camera;
in this embodiment, the obtaining manner of the running information of the vehicle is not limited, for example, the running information is obtained by a vehicle-mounted sensor, such as a speed sensor, a positioning sensor, a steering wheel angle sensor, a camera, and the content of the running information in this embodiment is not limited, and may include, for example, the running speed, the steering wheel angle, and the driver state (such as drowsiness, drunk driving, and the like) of the vehicle.
To further acquire the relevant information other than the own vehicle, therefore, the relevant information of the obstacles around the own vehicle, such as the positions, displacement changes, and the like of other vehicles, bicycles, pedestrians relative to the own vehicle, is further acquired by the millimeter wave radar and the camera in the present embodiment. It should be noted that, in the present embodiment, the number of the radar and the camera and the installation position on the host vehicle are not limited, for example, the radar and the camera are installed at the head position, so that the relevant information including the dyskinesia in the direction range of the front, the left, and the right of the vehicle can be monitored. The type of the movement disorder in this embodiment is not limited, and may be, for example, a vehicle in a motion state, such as a motorcycle, a bicycle, and a tricycle, and may also be a pedestrian, an animal, and the like.
Step S20, analyzing whether the vehicle has collision danger at present according to the running information and the related information;
and step S30, if the vehicle is at present in collision danger, sending collision early warning.
In this embodiment, the driving information of the vehicle, the driving information of the surrounding vehicles, and the related information of the surrounding movement disorders are specifically integrated to analyze whether the vehicle is at present in a collision danger, and if so, a collision warning is given out, so that a traffic accident is avoided, and the driving safety is improved. In this embodiment, the manner of analyzing whether the own vehicle currently has a collision risk is not limited.
In addition, it should be further described that, in this embodiment, the manner of identifying the relevant obstacle is not limited, for example, by taking an image collected by a video sensor during the vehicle running as a processing content and performing target extraction on video dynamic image information, potential obstacle information is provided for an unmanned vehicle, and the purposes of early warning and automatic adjustment of the vehicle speed and direction are achieved.
Further, specifically, in the obstacle identification process, firstly, a vehicle identification region of interest in an image coordinate system is determined according to radar information; then, carrying out symmetry analysis on the region of interest to obtain a vehicle symmetry center, and carrying out analysis processing on the shadow features of the bottom of the vehicle to complete vehicle edge detection; and finally, obtaining the vehicle identification width according to the inverse perspective transformation, and verifying the identification result according to the identification width. The result shows that the algorithm has stronger environmental adaptability and accuracy rate, and makes up the defects of a single sensor in vehicle identification.
Further optionally, in another embodiment of the vehicle collision warning method of the present invention, in order to facilitate analysis of whether the vehicle has a collision risk, in this embodiment, the driving information of the vehicle preferably acquired at least includes position and speed information of the vehicle; preferably, the information about the movement disorder surrounding the vehicle at least includes the position and speed information of the movement disorder relative to the vehicle, wherein the type of the movement disorder at least includes other vehicles, bicycles and pedestrians.
Further, based on the above embodiment, in another embodiment of the vehicle collision warning method according to the present invention, the step S20 specifically includes:
analyzing whether the current vehicle and the surrounding vehicles have collision risks or not according to the position and speed information of the vehicle and the position and speed information of the surrounding obstacles;
the analysis at least comprises the information of the motion trail of the vehicle and the position and the speed of peripheral obstacles.
In the embodiment, the turning model of the heavy truck is built in the system, the turning tracks of the front axle of the tractor, the hinge point and the geometric center of the trailer are obtained, and the motion track of the right wheel of the tractor and the motion track of the right wheel of the trailer are obtained through the geometric relation of the truck (assuming that the truck is driven to turn right), because the turning track of the heavy truck cannot be simply regarded as the turning motion of a point in the prediction, a rectangular area formed by the two points can be used as a dangerous area of collision, and therefore the accuracy of early warning is improved.
Further, when the position and speed information of the obstacle is acquired, the movement mode of the obstacle is uniformly judged to be a static or uniform linear movement mode.
In this embodiment, the driving speed of the vehicle, the movement speed of the peripheral obstacle, the movement track of the vehicle, and the movement track of the peripheral obstacle can be further obtained by analyzing the driving information of the vehicle and the related information of the peripheral obstacle. Specifically, the discrimination can be made by the following formula:
when the following inequality with respect to the movement time t has a solution, the risk of collision is considered to occur at that moment.
Wherein x is 0 、y 0 Is the initial position coordinate, x, of the right wheel of the front steering axle of the tractor 1 、y 1 Is the initial position coordinate, x, of the trailer's right rear wheel 2 、y 2 Is the initial position coordinate of the moving obstacle, R P 、R K Respectively the turning radius V of the front steering axle right wheel and the trailer right wheel of the tractor P 、V K 、V Q The driving speeds of the front steering axle right wheel of the tractor, the rear right wheel of the trailer and the moving obstacle are respectively.
Further, in another embodiment of the vehicle collision warning method according to the present invention, the step S30 further includes:
if the current vehicle and the surrounding obstacles have collision danger, a collision early warning is sent to the vehicle;
in this embodiment, the collision warning manner is not limited, such as sound warning, light flicker warning, risk avoidance action processing, and the like.
For example, when the vehicle has collision danger with the front vehicle, the driver of the vehicle can be informed of the collision danger with the front vehicle through voice, and meanwhile, the brake pedal is automatically controlled to brake; when the vehicle and the movement disorder have collision danger, the safety of the vehicle is ensured, and meanwhile, the damage to the movement disorder (such as pedestrians) is further avoided, so that when the vehicle gives an early warning to the driver of the vehicle, the vehicle also gives an early warning to the movement disorder, such as a sudden horn sound.
In the embodiment, different collision early warning treatments are adopted according to different collision objects, so that the driving safety is improved to the maximum extent, and traffic accidents are avoided.
Referring to fig. 2, fig. 2 is a functional module schematic diagram of an embodiment of the vehicle collision warning apparatus of the present invention. In this embodiment, the vehicle is provided with a speed sensor, a steering wheel angle sensor, an information processing module, a millimeter wave radar and a vehicle-mounted high-definition camera, wherein the speed sensor and the steering wheel sensor can acquire driving information of the vehicle, and the radar and the camera can acquire information related to the peripheral movement disorder of the vehicle.
For the accuracy of vehicle collision early warning and the security that the vehicle travel that have improved, in this embodiment, vehicle collision early warning device includes:
an acquisition module 10 (radar and camera) for acquiring the driving information (position, speed, etc.) of the vehicle when the vehicle is in a driving state, and acquiring the related information of surrounding obstacles by the radar and the camera;
in this embodiment, the obtaining manner of the running information of the vehicle is not limited, for example, obtaining the running information by an on-vehicle sensor, such as a speed sensor, a positioning sensor, a camera, and the like, and meanwhile, the content of the running information of the vehicle is not limited in this embodiment, and may include, for example, the running speed of the vehicle, the vehicle load, and the driver state (such as sleepiness, drunk driving, and the like).
In order to further acquire information of other movement obstacles except for the vehicle, therefore, the present embodiment further acquires information related to the movement obstacles around the vehicle, such as the position, displacement change, and the like of the bicycle and the pedestrian relative to the vehicle, through the radar and the camera. In this embodiment, the obtaining manner of the running information of the vehicle is not limited, for example, the running information is obtained by a vehicle-mounted sensor, such as a speed sensor, a positioning sensor, a steering wheel angle sensor, a camera, and the content of the running information in this embodiment is not limited, and may include, for example, the running speed, the steering wheel angle, and the driver state (such as sleepy, drunk driving, etc.) of the vehicle
An information processing module 20 (using a vehicle-level chip, such as IMX 6Q) for determining whether there is a collision risk accident at a future time by using a correlation algorithm based on the position and speed information obtained by the information module;
and the early warning module 30 is used for sending collision early warning to remind a driver in an audible and visual alarm mode when the analysis module predicts that a collision accident occurs.
In this embodiment, when the vehicle is in a turning driving state, the driving information of the vehicle itself is acquired, meanwhile, the related information of the peripheral movement disorder of the vehicle is further acquired through the radar and the camera, so that more comprehensive data information is acquired, whether the vehicle is at present in a collision danger is analyzed according to the acquired data information, and if the vehicle is at risk, a collision early warning is sent out, so that a driver or other related personnel can conveniently perform processing such as deceleration and braking according to the early warning.
Further, in another embodiment of the vehicle collision warning apparatus of the present invention, the warning module 30 is specifically configured to:
when the current vehicle has collision danger with surrounding obstacles, sending collision early warning to the current vehicle;
in this embodiment, the collision warning manner is not limited, such as sound warning, light flicker warning, risk avoidance action processing, and the like.
For example, when the vehicle has collision danger with the front vehicle, the driver of the vehicle can be informed of the collision danger with the front vehicle through voice, and meanwhile, the brake pedal is automatically controlled to brake; when the vehicle and the movement disorder have collision danger, the safety of the vehicle is ensured, and meanwhile, the damage to the movement disorder (such as pedestrians) is further avoided, so that when the vehicle gives an early warning to the driver of the vehicle, the vehicle also gives an early warning to the movement disorder, such as a sudden horn sound.
In the embodiment, different collision early warning treatments are adopted according to different collision objects, so that the driving safety is improved to the maximum extent, and traffic accidents are avoided.
Referring to fig. 3, fig. 3 is a train track analysis diagram of a semi-trailer according to an embodiment of the collision warning system for turning of a heavy truck of the present invention. In this example, the model is based on the PRT method, and defines OX as the polar axis and the counterclockwise included angle between each polar diameter and the positive axis of OX as positive, and can derive the relationship that the lengths of the polar diameters r0, r2, r3 at points a, M, G on the vehicle change with the change of the polar angle n of the polar diameter r1 at point B.
Firstly, relevant parameters of the point B are determined, and the formula is as follows:
r 1 ＝OB'＝OBsin(m 1 )/sin(π-n 1 -m 1 )
x 1 ＝r 1 cosn
y 1 ＝r 1 sinn
wherein r is 1 Is the B point polar diameter of the tractor, m 1 Is the polar diameter r of the points AB and B of the axis of the tractor 1 Angle between n and 1 is the increment of the positive included angle between the B point polar diameter of the tractor and the X axis, n is the positive included angle between the B point polar diameter of the tractor and the X axis, and X is the positive included angle between the B point polar diameter of the tractor and the X axis 1 、y 1 And (4) positioning the B point coordinate of the tractor.
And then determining relevant parameters of the point A, specifically, selecting three motion states of the point A, namely circular motion, 90-degree turning and 180-degree turning:
when the tractor A point moves along the circle, the following steps are provided:
r 0 ＝r
x＝r 0 cos(n 6 +n)
y＝r 0 sin(n 6 +n)
wherein r is 0 Is the polar diameter of the A point of the tractor, r is the radius of the center line of the curved road, n 6 Is the midpoint pole diameter r of the front axle of the tractor 0 And the middle point polar diameter r of the rear axle 1 Angle between l 1 The distance between the A point and the B point of the tractor, and x and y are the coordinates of the A point of the tractor
When the tractor gradually goes out of a 90-degree curve along the negative X-axis direction from the point A (0, r), the following steps are carried out:
y＝r
when the tractor gradually runs out of a 180-degree curve along the negative direction of the Y axis from (-r, 0), the following steps are provided:
x＝-r
after determining the pole diameter r0, there are:
n 2 ＝arcsin[esin(m 1 )/r 2 ]
the above formula can be rewritten as:
when the temperature is higher than the set temperature
The above formula is a formula of the non-steering state of the semi-trailer wheel:
wherein r is 2 Is M point radius of the tractor r 3 Is the polar diameter of the G point of the semitrailer, e is the offset distance MB between the M point and the B point of the tractor, and s is the polar angle increment n 1 The corresponding path increment GG' of the G point of the semitrailer is used for calculating an intermediate length variable l 2 The distance between M point and G point of the semitrailer, M 2 Is the semitrailer axis MG and G point polar diameter r 1 Angle between initial positions OG, n 2 Is M point polar diameter r of tractor 2 And B point radius of pole r 1 Angle between, n 3 Is a positive included angle n between the G point polar diameter of the semitrailer and the X axis 4 Is the angle increment of the positive included angle between the G multipoint polar diameter of the semitrailer and the X axis, n 5 For calculating intermediate angle variables, n 10 Is the direction angle (theta angle) of the semitrailer G point, n 11 To calculate the intermediate angle variables, the lower right hand corner (°) of the formula represents the initial value of the variable, and the upper right hand corner (,) represents the first derivative of each variable with respect to the argument n.
Through the formula, the motion tracks of the geometrical central point A of the front axle of the tractor, the geometrical central point B of the rear axle of the tractor, the hinge point M of the tractor and the geometrical central point G of the trailer in the model can be obtained.
Referring to fig. 4, fig. 4 is a simplified diagram of an analysis model of an embodiment of the heavy truck turning collision warning system of the present invention; in this embodiment, according to the previously obtained geometric center trajectory of the tractor, the trajectory of the point P on the right wheel of the front axle of the tractor and the trajectory of the point K on the right wheel of the rear wheel of the trailer can be obtained through the parameters of the tractor. The rectangular area formed by the movement of the point P and the point K is the collision area, and whether collision occurs can be judged by only giving a time t and judging whether a target object falls into the collision area after the time t.
Specifically, FIG. 4 is a motion simplification model, where:
p point trajectory equation of:
The K-point trajectory equation is:
p point coordinate after t time:
k point coordinates after t time:
q (x) coordinate of point Q after time t 2 ,y 2 +v Q t)
When the set of inequalities:
and if t is solved, namely the point C falls into the early warning area, the collision can be caused. Wherein x is p 、y p Is the center coordinate, x, of the right wheel of the front steering axle of the tractor k 、y k Is the center coordinate of the right rear wheel of the trailer, x 0 、y 0 Is the initial position coordinate, x, of the right wheel of the front steering axle of the tractor 1 、y 1 Is the initial position coordinate, x, of the trailer's right rear wheel 2 、y 2 Is the initial position coordinate of the moving obstacle, R P 、R K Respectively the turning radius, V, of the front steering axle right wheel of the tractor and the rear wheel of the trailer P 、V K 、V Q The driving speeds of the front steering axle right wheel of the tractor, the rear right wheel of the trailer and the moving obstacle are respectively.
In this embodiment, when the vehicle is in a driving state, the driving information of the vehicle itself is acquired, meanwhile, the related information of the peripheral movement disorder of the vehicle is further acquired through the radar and the camera, more comprehensive data information is further acquired, whether the vehicle is at present in a collision danger is analyzed according to the acquired data information, and if the vehicle is at risk, a collision early warning is sent out, so that a driver or other related personnel can conveniently perform processing such as deceleration and braking according to the early warning.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (5)
1. A method for early warning of collision accidents when a heavy truck turns is characterized by comprising the following steps:
when the vehicle is ready to turn to run, obtaining turning track information of each wheel of the vehicle, including position coordinate information and running speed information, through a speed sensor and a steering wheel corner sensor and by establishing a turning model of the heavy truck; obtaining related information of the types of obstacles around the vehicle through a millimeter wave radar and a vehicle-mounted high-definition camera; analyzing whether the vehicle has collision danger at a certain future moment or not according to the turning track information and the related information; if danger occurs at a certain moment in the future, the driver is reminded to avoid collision accidents through the early warning module;
in the process of obtaining the turning track information, the turning tracks of a front axle, a hinge point and a geometric center of a trailer of the tractor are obtained by establishing a turning model of the heavy truck, and the motion track of a right wheel of the tractor and the motion track of a right rear wheel of the trailer are obtained through the geometric relation of the truck;
the specific process of analyzing whether the vehicle has collision danger at a certain future moment through the turning track information and the related information is as follows: according to the obtained motion trail of the right wheel of the tractor and the motion trail of the right rear wheel of the trailer, the track of the point P of the right wheel of the front axle of the tractor and the track of the point K of the right rear wheel of the trailer can be obtained through parameters of the tractor; a rectangular area formed by the movement of the point P and the point K is a collision area, and whether collision occurs can be judged by only giving a time t and judging whether a target object falls into the collision area after the time t; wherein:
the P point trajectory equation is:
the K-point trajectory equation is:
p point coordinate after t time:
k point coordinates after time t:
q (x) point coordinate after time t 2 ,y 2 +v Q t)
When the set of inequalities:
if t is solved, the point C falls into the early warning area, and collision is shown; wherein x p 、y p Is the coordinate of the circle center of the right wheel of the front steering axle of the tractor, x k 、y k Is the center coordinate, x, of the right rear wheel of the trailer 0 、y 0 Is the initial position coordinate, x, of the right wheel of the front steering axle of the tractor 1 、y 1 Is the initial position coordinate, x, of the trailer's right rear wheel 2 、y 2 Is the initial position coordinate of the moving obstacle, R P 、R K Respectively the turning radius V of the front steering axle right wheel and the trailer right wheel of the tractor P 、V K 、V Q The driving speeds of a front steering axle right wheel of the tractor, a rear right wheel of the trailer and a moving obstacle are respectively.
2. The method as claimed in claim 1, wherein the related information is used to uniformly determine whether the obstacle moves in a stationary or uniform linear motion manner when the position and speed information of the obstacle are obtained.
3. The method as claimed in claim 1, wherein the method for determining the type of the obstacle comprises using the image collected by the video sensor during the vehicle running as the processing content, and performing target extraction on the video dynamic image information to provide potential obstacle information for the unmanned vehicle, so as to achieve the purposes of early warning and automatic adjustment of the vehicle speed and direction.
4. The method for warning the occurrence of a collision accident when a heavy truck turns a corner according to claim 1, wherein the obstacle type identification process is: in the vehicle identification process, firstly, a vehicle identification interesting area in an image coordinate system is determined according to radar information; then, carrying out symmetry analysis on the region of interest to obtain a vehicle symmetry center, and carrying out analysis processing on the shadow features of the bottom of the vehicle to complete vehicle edge detection; and finally, obtaining the vehicle identification width according to inverse perspective transformation, and verifying the identification result according to the identification width.
5. The method as claimed in claim 1, wherein the pre-warning module is a sound and light pre-warning module, and the voice chip is used to broadcast the pre-warning message to remind the driver, or the red and green indicator is installed to remind the driver, or a combination of the two methods.
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| CN112776714A (en) * | 2021-01-27 | 2021-05-11 | 吉林云帆智能工程有限公司 | Turning monitoring and early warning method for railway vehicle |
| CN113276769B (en) * | 2021-04-29 | 2023-05-26 | 深圳技术大学 | Vehicle blind area anti-collision early warning system and method |
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| CN113511198B (en) * | 2021-09-15 | 2021-12-31 | 天津所托瑞安汽车科技有限公司 | Method, apparatus and storage medium for predicting blind zone collision when self-vehicle turns |
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| TWI797997B (en) * | 2022-02-21 | 2023-04-01 | 輝創電子股份有限公司 | Warning method and system for vehicle turning |
| CN115861972A (en) * | 2022-12-22 | 2023-03-28 | 北京斯年智驾科技有限公司 | Collision detection method and device, electronic equipment and storage medium |
| CN115951692B (en) * | 2023-03-15 | 2023-05-12 | 珠海骏驰智联科技有限公司 | Unmanned trajectory control system based on model predictive control |
| CN116176576B (en) * | 2023-04-25 | 2023-07-14 | 巨野金牛车业有限公司 | Trailer collision intelligent early warning system and method based on artificial intelligence |
| CN117710909B (en) * | 2024-02-02 | 2024-04-12 | 多彩贵州数字科技股份有限公司 | Rural road intelligent monitoring system based on target detection and instance segmentation |
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