CN111516706A - Vehicle automatic detection danger avoidance auxiliary method, device and system - Google Patents

Vehicle automatic detection danger avoidance auxiliary method, device and system Download PDF

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Publication number
CN111516706A
CN111516706A CN202010420481.7A CN202010420481A CN111516706A CN 111516706 A CN111516706 A CN 111516706A CN 202010420481 A CN202010420481 A CN 202010420481A CN 111516706 A CN111516706 A CN 111516706A
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China
Prior art keywords
vehicle
reading
information
vehicle information
automatic detection
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CN202010420481.7A
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Chinese (zh)
Inventor
张国宁
金建
陈强
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Hefei Jiedai Electromechanical Technology Co ltd
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Hefei Jiedai Electromechanical Technology Co ltd
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Priority to CN202010420481.7A priority Critical patent/CN111516706A/en
Publication of CN111516706A publication Critical patent/CN111516706A/en
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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
    • 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
    • B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
    • 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
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/35—Road bumpiness, e.g. potholes
    • 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
    • B60W2552/00—Input parameters relating to infrastructure
    • B60W2552/53—Road markings, e.g. lane marker or crosswalk
    • 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
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/20—Static objects
    • 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
    • B60W2554/00—Input parameters relating to objects
    • B60W2554/40—Dynamic objects, e.g. animals, windblown objects

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Human Computer Interaction (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention relates to the technical field of vehicle assistance, and discloses an auxiliary method, device and system for vehicle automatic detection danger avoidance, wherein the method comprises the following steps: acquiring images of objects around the vehicle, generating imaging data, and acquiring the fluctuation state of the surrounding road surface; writing vehicle information into the electronic tag, reading the vehicle information in real time, comparing the vehicle information, giving attention to the grade, judging the numerical range, sending out a warning, and transmitting the specific driving road state and barrier species to a driver; the method can quickly determine the information of surrounding vehicles, accurately and efficiently detect the abnormal conditions, and provide warning information for drivers in time for reference, and has higher practical value and wide application prospect.

Description

Vehicle automatic detection danger avoidance auxiliary method, device and system
Technical Field
The invention relates to the technical field of vehicle assistance, in particular to an auxiliary method, device and system for vehicle automatic detection danger avoidance.
Background
With the increasing automobile keeping quantity in the world, the automobile traffic accidents have been increased in successive years, and the traffic safety problem becomes a public nuisance in modern society. Statistically, among all traffic accidents, car crash accidents (including car collisions and car-to-fixture collisions) are the predominant form. The collision accident of the automobile is mostly caused by the factors of too fast driving speed, too small driving distance, untimely braking and the like.
In order to further improve road traffic safety and help drivers to reduce erroneous operations, attention has been paid to and intelligent automobile safety technologies represented by Advanced Driver Assistance Systems (ADAS) in recent years. The automobile emergency collision avoidance system assists a driver to adjust the motion track of an automobile through active intervention of an actuator, so that collision avoidance is realized. The novel bicycle can save lives of drivers at critical moment, and has good market prospect.
On the one hand, it is generally important for the pre-avoidance and warning of accidents of vehicles in motion and further for the realization of automated driving to recognize the surroundings in which obstacles such as other vehicles are present and to predict the behavior of the obstacles;
on the other hand, for the grasping of the information of the surrounding vehicles, most distance data formed by radar or laser ranging cannot accurately and quickly acquire the real-time motion information, the internal power, the steering and other important parameter information of the surrounding vehicles, and effective reminding cannot be made.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an auxiliary method for vehicle automatic detection danger avoidance, which is used for solving the problems in the background technology.
The technical scheme adopted by the invention for solving the technical problems is as follows:
the invention provides an auxiliary method for vehicle automatic detection danger avoidance, which comprises the following steps:
acquiring images of objects around the vehicle to generate imaging data;
acquiring the undulation state of the surrounding road surface;
determining a specific driving road state and a barrier type according to a preset regional characteristic template, wherein the regional characteristic template comprises lane line slope, lane line pixels, lane line length, length ratio of lane solid lines to lane dotted lines, pedestrians, vehicles, buildings and traffic equipment;
writing static vehicle information and dynamic vehicle information into an electronic tag in real time to wait for reading, wherein the static vehicle information comprises a license plate number, a vehicle model and a vehicle overall dimension, and the dynamic vehicle information comprises vehicle running direction, real-time speed, engine rotating speed, acceleration, steering angle, load weight and position information;
reading vehicle information stored in all vehicle electronic tags in a preset range in real time, comparing the vehicle information with the vehicle information, granting different attention degrees of the compared vehicles to be sent to a memory for storage or updating the attention degree grade corresponding to the vehicle in the memory;
for the vehicle with the highest attention degree, if the data in the dynamic vehicle information exceeds a preset normal value range, a warning signal is sent to the driver of the vehicle;
according to the vehicle preset route, the vehicle is broadcasted to the driver in real time by referring to the specific driving road state and the obstacle species.
Preferably, the image is acquired by a binocular vision camera set arranged on the vehicle;
the road surface undulation state is obtained by detecting a laser radar arranged on a vehicle;
the obstacle kind is scanned in each direction by performing electron beam scanning using a millimeter wave radar, and a region that receives a return beam corresponding to the emitted scanning beam is detected as an obstacle region;
matching obstacle types including pedestrian, motor vehicle, non-motor vehicle, building obstacle, plant and traffic equipment according to the difference of relative speed and detection position of the obstacle and the size of the obstacle
The dynamic vehicle information is obtained by the following method:
acquiring parameters including vehicle speed per hour, engine speed, steering angle and acceleration through a CAN bus of the vehicle;
determining vehicle position information and a driving direction through the GPS/INS in cooperation with a gyroscope;
the weight of the load of the vehicle is collected through the arranged pressure sensor.
Preferably, the vehicle information stored in the vehicle electronic tag within the preset range is compared with the vehicle information by the following method:
reading real-time position information of the vehicle and the comparison vehicle, calculating to obtain a linear distance between the two vehicles, and performing orthogonal decomposition on the linear distance along the driving direction of the vehicle to obtain a vertical distance along the driving direction of the vehicle and a transverse distance perpendicular to the driving direction of the vehicle;
reading the running direction data of the vehicle and the comparison vehicle, and calculating to obtain the running direction included angle of the two vehicles;
and reading and comparing the output torque and the engine speed of the vehicle engine, and calculating to obtain the output torque and the speed variation.
Preferably, when the straight-line distance between the vehicle and the comparison vehicle is lower than a preset threshold, the high-precision distance measuring service is triggered, and the method comprises the following steps:
establishing a space coordinate system, wherein the space coordinate system takes the center of the vehicle body of the vehicle as the origin of coordinates, the direction parallel to the ground to the front of the vehicle head is taken as the positive direction of a Y axis, the direction perpendicular to the ground to the lower part of the ground is taken as the positive direction of a Z axis, and the direction parallel to the ground to the right side of a driver is taken as the positive direction of an X axis;
reading the vehicle outline size data to obtain the farthest endpoint coordinates of each surface of the vehicle outline solid;
reading and comparing vehicle outline size data, and combining distance data measured by a laser arranged at the periphery of the vehicle to obtain the coordinates of the farthest end points of all surfaces of the compared vehicle outline stereo;
and calculating the point distance of the coordinate of the farthest end point of each surface of the outline stereo of the vehicle and the coordinate of the farthest end point of each surface of the outline stereo of the comparison vehicle, and feeding back the corresponding position of the point with the minimum distance to the driver of the vehicle and the driver of the comparison vehicle in real time.
Preferably, the high precision distance measurement service further comprises a modeling step of:
and reading the coordinate data of the vehicle in the space coordinate system and the coordinate data of the vehicle with the highest attention degree, and dynamically displaying the outline models of the two vehicles in proportion on a vehicle internal display device.
Preferably, the granting of the attention level comprises the steps of:
reading and comparing the vertical distance S of the vehicle relative to the vehicleVerticalTransverse distance SHorizontal barAngle theta with the direction of travelClip；
Reading and comparing real-time speed V of vehicleTime of flightAnd an acceleration a;
reading the variation delta R of the rotating speed;
substituting formula P ═ λ1SVertical+λ2SHorizontal bar+λ3θClip+λ4VTime of flight+λ5a+λ5Δ R obtains a rating of interest parameter for the aligned vehicle, where λ1、λ2、λ3、λ4、λ5、λ5Reading a weight coefficient value corresponding to a prestored mode according to a driving environment mode selected by a user as a weight coefficient;
ranking the grade parameters after finishing the comparison of all vehicles in the preset range, and awarding attention grades according to the grade from high to low.
Preferably, the warning signal is sent to the driver of the vehicle, and the warning signal is sent to the vehicle with the highest attention degree.
The invention also provides an auxiliary device for vehicle automatic detection danger avoidance, which comprises:
the video acquisition module is used for acquiring images of objects around the vehicle and generating imaging data;
the radar test module is used for acquiring the undulation state of the surrounding road surface;
the system comprises a preprocessing module, a data processing module and a data processing module, wherein the preprocessing module is used for determining a specific driving road state and an obstacle type according to a preset regional characteristic template, and the regional characteristic template comprises a lane line slope, lane line pixels, a lane line length, a length ratio of a lane solid line and a lane dotted line, and pedestrians, vehicles, buildings and traffic equipment;
the electronic tag module is used for storing static vehicle information and dynamic vehicle information, wherein the static vehicle information comprises a license plate number, a vehicle model and a vehicle overall dimension, and the dynamic vehicle information comprises a vehicle running direction, a real-time speed, an engine rotating speed, an acceleration, a steering angle, a load weight and position information;
the data reading and writing module is used for writing the static vehicle information and the dynamic vehicle information into the electronic tag in real time to wait for reading;
the data processing module is used for reading vehicle information stored in all vehicle electronic tags in a preset range in real time, comparing the vehicle information with the vehicle information, granting different attention degrees of the compared vehicles to be sent to the memory for storage or updating the attention degree grade corresponding to the vehicle in the memory;
and the reminding display module is used for sending a warning signal to the driver of the vehicle when the data in the dynamic vehicle information corresponding to the vehicle with the highest attention degree exceeds a preset normal value range.
The invention also provides an auxiliary system for vehicle automatic detection danger avoidance, which comprises:
one or more processors;
storage means for storing one or more programs;
the vehicle automatic detection danger-avoiding auxiliary device;
when the one or more programs are executed by the one or more processors, the vehicle automatic detection risk avoidance assistance is enabled to cooperate with the one or more processors to implement any one of the vehicle automatic detection risk avoidance assistance methods described above.
The invention also provides a vehicle control system which is characterized by comprising the vehicle automatic detection danger avoiding auxiliary system.
Compared with the prior art, the invention has the following beneficial effects:
on one hand, the method is characterized in that road condition information and obstacles are preliminarily obtained according to preset regional characteristics by collecting images around the vehicle and matching radar wave detection, and then the types of the obstacles are obtained according to a matched obstacle model; on the other hand, by collecting important static information and real-time dynamic information in the running process of the vehicle and utilizing a control system and a data collector of the vehicle, the information is quickly and accurately collected and is waited to be read, so that data delay and data errors caused by the need of external measurement for data collection in the prior art are avoided, and on the other hand, vehicle information data of the vehicle, which cannot be measured externally but is expected to be important and effectively known for surrounding vehicle drivers, is provided in real time, so that accurate and effective driving auxiliary information is further processed to be obtained for the drivers to refer to;
according to the invention, the surrounding vehicle information in the preset range is compared with the vehicle information, different attention levels are granted according to the comparison result, the important vehicle information is mainly monitored for the highest level, and once an abnormal condition occurs, the important vehicle information is timely reported, so that the surrounding vehicles are dynamically monitored and prompted according to the actual driving environment.
Further salient features and significant advances with respect to the present invention over the prior art are described in further detail in the examples section.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a schematic flow chart of an auxiliary method for vehicle automatic detection risk avoidance according to the present invention;
FIG. 2 is a schematic structural diagram of an automatic vehicle detection risk avoidance aid according to the present invention;
FIG. 3 is a schematic diagram of a driving assistance system according to the present invention;
fig. 4 is a schematic structural diagram of a vehicle control system according to 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.
It should be noted that certain names are used throughout the specification and claims to refer to particular components. It will be understood that one of ordinary skill in the art may refer to the same component by different names. The present specification and claims do not intend to distinguish between components that differ in name but not function. As used in the specification and claims of this application, the terms "comprises" and "comprising" are intended to be open-ended terms that should be interpreted as "including, but not limited to," or "including, but not limited to. The embodiments described in the detailed description are preferred embodiments of the present invention and are not intended to limit the scope of the present invention.
Moreover, those skilled in the art will appreciate that aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, various aspects of the present invention may be embodied in a combination of hardware and software, which may be referred to herein generally as a "circuit," module "or" system. Furthermore, in some embodiments, various aspects of the invention may also be embodied in the form of a computer program product in one or more microcontroller-readable media having microcontroller-readable program code embodied therein.
As shown in fig. 1 to 4, the vehicle automatic detection risk avoiding auxiliary method of the present embodiment includes the following steps:
acquiring images of objects around the vehicle to generate imaging data;
acquiring the undulation state of the surrounding road surface;
determining a specific driving road state and a barrier type according to a preset regional characteristic template, wherein the regional characteristic template comprises lane line slope, lane line pixels, lane line length, length ratio of lane solid lines to lane dotted lines, pedestrians, vehicles, buildings and traffic equipment;
writing static vehicle information and dynamic vehicle information into an electronic tag in real time to wait for reading, wherein the static vehicle information comprises a license plate number, a vehicle model and a vehicle overall dimension, and the dynamic vehicle information comprises vehicle running direction, real-time speed, engine rotating speed, acceleration, steering angle, load weight and position information;
reading vehicle information stored in all vehicle electronic tags in a preset range in real time, comparing the vehicle information with the vehicle information, granting different attention degrees of the compared vehicles to be sent to a memory for storage or updating the attention degree grade corresponding to the vehicle in the memory;
for the vehicle with the highest attention degree, if the data in the dynamic vehicle information exceeds a preset normal value range, a warning signal is sent to the driver of the vehicle;
according to the vehicle preset route, the vehicle is broadcasted to the driver in real time by referring to the specific driving road state and the obstacle species.
The images in the embodiment are acquired through a binocular vision camera group arranged on the vehicle;
the road surface undulation state is obtained by detecting a laser radar arranged on a vehicle;
the obstacle kind is scanned in each direction by performing electron beam scanning using a millimeter wave radar, and a region that receives a return beam corresponding to the emitted scanning beam is detected as an obstacle region;
matching obstacle types according to the difference of the relative speeds of the obstacles, the detection positions and the sizes of the obstacles, wherein the obstacle types comprise pedestrians, motor vehicles, non-motor vehicles, building obstacles, plants and traffic equipment;
the dynamic vehicle information is acquired by the following method:
acquiring parameters including vehicle speed per hour, engine speed, steering angle and acceleration through a CAN bus of the vehicle;
determining vehicle position information and a driving direction through the GPS/INS in cooperation with a gyroscope;
the weight of the load of the vehicle is collected through the arranged pressure sensor.
The real-time parameter information of the vehicle is directly obtained on the basis of the existing CAN bus of the vehicle and the GPS/INS matched with the gyroscope and the pressure sensor, and no new equipment is required to be added, so that the application of the invention has practicability and economy.
In the embodiment, vehicle information stored in a vehicle electronic tag within a preset range is compared with vehicle information of a vehicle by the following method:
reading real-time position information of the vehicle and the comparison vehicle, calculating to obtain a linear distance between the two vehicles, and performing orthogonal decomposition on the linear distance along the driving direction of the vehicle to obtain a vertical distance along the driving direction of the vehicle and a transverse distance perpendicular to the driving direction of the vehicle;
reading the running direction data of the vehicle and the comparison vehicle, and calculating to obtain the running direction included angle of the two vehicles;
and reading and comparing the output torque and the engine speed of the vehicle engine, and calculating to obtain the output torque and the speed variation. And comparing the vehicle of the vehicle with the comparison vehicle to provide detailed reference data for subsequent attention levels.
The granting of the attention level in this embodiment includes the steps of:
reading and comparing the vertical distance S of the vehicle relative to the vehicleVerticalTransverse distance SHorizontal barAngle theta with the direction of travelClip；
Reading and comparing real-time speed V of vehicleTime of flightAnd an acceleration a;
reading the variation delta R of the rotating speed;
substituting formula P ═ λ1SVertical+λ2SHorizontal bar+λ3θClip+λ4VTime of flight+λ5a+λ5Δ R obtains a rating of interest parameter for the aligned vehicle, where λ1、λ2、λ3、λ4、λ5、λ5And reading a weight coefficient value corresponding to a prestored mode according to the driving environment mode selected by the user as the weight coefficient.
Ranking the grade parameters after finishing the comparison of all vehicles in the preset range, and awarding attention grades according to the grade from high to low. Weights are given to comparison results through selection of different driving environments, attention levels of comparison vehicles are obtained, and accordingly layered monitoring is conducted on the road vehicles in a distinguished mode.
In the present embodiment, a warning signal is issued to the driver of the vehicle and a warning signal is issued to the vehicle having the highest attention level.
In this embodiment, when this car is less than the predetermined threshold with the comparison vehicle linear distance, trigger high accuracy distance measurement service, include:
establishing a space coordinate system, wherein the space coordinate system takes the center of the vehicle body of the vehicle as the origin of coordinates, the direction parallel to the ground to the front of the vehicle head is taken as the positive direction of a Y axis, the direction perpendicular to the ground to the lower part of the ground is taken as the positive direction of a Z axis, and the direction parallel to the ground to the right side of a driver is taken as the positive direction of an X axis;
reading the vehicle outline size data to obtain the farthest endpoint coordinates of each surface of the vehicle outline solid;
reading and comparing vehicle outline size data, and combining distance data measured by a laser arranged at the periphery of the vehicle to obtain the coordinates of the farthest end points of all surfaces of the compared vehicle outline stereo;
and calculating the point distance of the coordinate of the farthest end point of each surface of the outline stereo of the vehicle and the coordinate of the farthest end point of each surface of the outline stereo of the comparison vehicle, and feeding back the corresponding position of the point with the minimum distance to the driver of the vehicle and the driver of the comparison vehicle in real time.
The actual contour of the vehicle is compared in a space modeling mode when the distance between the vehicles is small in the embodiment, the most accurate and effective comparison model can be obtained, and therefore reasonable, effective and accurate reference data can be provided for drivers from the practical use angle.
The high-precision distance measurement service in this embodiment further includes a modeling step:
and reading the coordinate data of the vehicle in the space coordinate system and the coordinate data of the vehicle with the highest attention degree, and dynamically displaying the outline models of the two vehicles in proportion on a vehicle internal display device. In the embodiment, the outline model of the vehicle can be displayed for a driver in a three-dimensional manner, so that the road condition can be visually displayed, and particularly, a warning effect is provided for certain blind areas.
This embodiment still provides a dangerous auxiliary device is kept away in automatic detection of vehicle, includes:
the video acquisition module is used for acquiring images of objects around the vehicle and generating imaging data;
the radar test module is used for acquiring the undulation state of the surrounding road surface;
the preprocessing module is used for determining the specific driving road state and the barrier type according to a preset regional characteristic template,
the region characteristic template comprises lane line slope, lane line pixels, lane line length, lane solid line and lane virtual line
The length ratio of the lines and pedestrian, vehicle, building and traffic equipment;
the electronic tag module is used for storing static vehicle information and dynamic vehicle information, wherein the static vehicle information comprises a license plate number, a vehicle model and a vehicle overall dimension, and the dynamic vehicle information comprises a vehicle running direction, a real-time speed, an engine rotating speed, an acceleration, a steering angle, a load weight and position information;
the data reading and writing module is used for writing the static vehicle information and the dynamic vehicle information into the electronic tag in real time to wait for reading;
the data processing module is used for reading vehicle information stored in all vehicle electronic tags in a preset range in real time, comparing the vehicle information with the vehicle information, granting different attention degrees of the compared vehicles to be sent to the memory for storage or updating the attention degree grade corresponding to the vehicle in the memory;
and the reminding display module is used for sending a warning signal to the driver of the vehicle when the data in the dynamic vehicle information corresponding to the vehicle with the highest attention degree exceeds a preset normal value range.
This embodiment still provides a dangerous auxiliary system is kept away in automatic detection of vehicle, includes:
one or more processors;
storage means for storing one or more programs;
the vehicle automatic detection danger-avoiding auxiliary device;
the one or more programs, when executed by the one or more processors, cause the vehicle automated detection hedge assist to implement, in cooperation with the one or more processors, the vehicle automated detection hedge assist method as described above.
The embodiment also provides a vehicle control system, which comprises the vehicle automatic detection danger avoiding auxiliary system.
The vehicle automatic detection danger avoiding auxiliary method can quickly determine the information of surrounding vehicles, accurately and efficiently detect abnormal conditions, provide warning information for drivers in time for reference, and has high practical value and wide application prospect.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.

Claims (10)

1. An auxiliary method for vehicle automatic detection risk avoidance is characterized by comprising the following steps:
acquiring images of objects around the vehicle to generate imaging data;
acquiring the undulation state of the surrounding road surface;
determining a specific driving road state and a barrier type according to a preset regional characteristic template, wherein the regional characteristic template comprises lane line slope, lane line pixels, lane line length, length ratio of lane solid lines to lane dotted lines, pedestrians, vehicles, buildings and traffic equipment;
writing static vehicle information and dynamic vehicle information into an electronic tag in real time to wait for reading, wherein the static vehicle information comprises a license plate number, a vehicle model and a vehicle overall dimension, and the dynamic vehicle information comprises vehicle running direction, real-time speed, engine rotating speed, acceleration, steering angle, load weight and position information;
reading vehicle information stored in all vehicle electronic tags in a preset range in real time, comparing the vehicle information with the vehicle information, granting different attention degrees of the compared vehicles to be sent to a memory for storage or updating the attention degree grade corresponding to the vehicle in the memory;
for the vehicle with the highest attention degree, if the data in the dynamic vehicle information exceeds a preset normal value range, a warning signal is sent to the driver of the vehicle;
according to the vehicle preset route, the vehicle is broadcasted to the driver in real time by referring to the specific driving road state and the obstacle species.
2. The vehicle automatic detection danger avoiding auxiliary method according to claim 1, wherein the image is acquired by a binocular vision camera set arranged on a vehicle;
the road surface undulation state is obtained by detecting a laser radar arranged on a vehicle;
the obstacle kind is scanned in each direction by performing electron beam scanning using a millimeter wave radar, and a region that receives a return beam corresponding to the emitted scanning beam is detected as an obstacle region;
matching obstacle types according to the difference of the relative speeds of the obstacles, the detection positions and the sizes of the obstacles, wherein the obstacle types comprise pedestrians, motor vehicles, non-motor vehicles, building obstacles, plants and traffic equipment;
the dynamic vehicle information is obtained by the following method:
acquiring parameters including vehicle speed per hour, engine speed, steering angle and acceleration through a CAN bus of the vehicle;
determining vehicle position information and a driving direction through the GPS/INS in cooperation with a gyroscope;
the weight of the load of the vehicle is collected through the arranged pressure sensor.
3. The vehicle automatic detection risk avoiding auxiliary method according to claim 1, wherein vehicle information stored in a vehicle electronic tag in a preset range is compared with vehicle information of a vehicle by the following method:
reading real-time position information of the vehicle and the comparison vehicle, calculating to obtain a linear distance between the two vehicles, and performing orthogonal decomposition on the linear distance along the driving direction of the vehicle to obtain a vertical distance along the driving direction of the vehicle and a transverse distance perpendicular to the driving direction of the vehicle;
reading the running direction data of the vehicle and the comparison vehicle, and calculating to obtain the running direction included angle of the two vehicles;
and reading and comparing the output torque and the engine speed of the vehicle engine, and calculating to obtain the output torque and the speed variation.
4. The vehicle automatic detection risk avoiding auxiliary method according to claim 3, wherein when the straight-line distance between the vehicle and the comparison vehicle is lower than a preset threshold, the high-precision distance measuring service is triggered, and the method comprises the following steps:
establishing a space coordinate system, wherein the space coordinate system takes the center of the vehicle body of the vehicle as the origin of coordinates, the direction parallel to the ground to the front of the vehicle head is taken as the positive direction of a Y axis, the direction perpendicular to the ground to the lower part of the ground is taken as the positive direction of a Z axis, and the direction parallel to the ground to the right side of a driver is taken as the positive direction of an X axis;
reading the vehicle outline size data to obtain the farthest endpoint coordinates of each surface of the vehicle outline solid;
reading and comparing vehicle outline size data, and combining distance data measured by a laser arranged at the periphery of the vehicle to obtain the coordinates of the farthest end points of all surfaces of the vehicle outline stereo;
and calculating the point distance of the coordinate of the farthest end point of each surface of the outline stereo of the vehicle and the coordinate of the farthest end point of each surface of the outline stereo of the comparison vehicle, and feeding back the corresponding position of the point with the minimum distance to the driver of the vehicle and the driver of the comparison vehicle in real time.
5. The vehicle automatic detection risk avoiding auxiliary method according to claim 4, wherein the high precision distance measuring service further comprises a modeling step:
and reading the coordinate data of the vehicle in the space coordinate system and the coordinate data of the vehicle with the highest attention degree, and dynamically displaying the outline models of the two vehicles in proportion on a vehicle internal display device.
6. The vehicle automatic detection risk avoiding auxiliary method according to claim 3, wherein the awarding of the attention level comprises the following steps:
reading and comparing the vertical distance S of the vehicle relative to the vehicleVerticalTransverse distance SHorizontal barAngle theta with the direction of travelClip；
Reading and comparing real-time speed V of vehicleTime of flightAnd an acceleration a;
reading the variation delta R of the rotating speed;
substituting formula P ═ λ1SVertical+λ2SHorizontal bar+λ3θClip+λ4VTime of flight+λ5a+λ5Δ R obtains a rating of interest parameter for the aligned vehicle, where λ1、λ2、λ3、λ4、λ5、λ5Reading a weight coefficient value corresponding to a prestored mode according to a driving environment mode selected by a user as a weight coefficient;
ranking the grade parameters after finishing the comparison of all vehicles in the preset range, and awarding attention grades according to the grade from high to low.
7. The vehicle automatic detection danger avoiding auxiliary method according to claim 1, characterized in that the warning signal is sent to the driver of the vehicle and simultaneously the warning signal is sent to the vehicle with the highest attention degree.
8. The utility model provides a dangerous auxiliary device is kept away in automatic detection of vehicle which characterized in that includes:
the video acquisition module is used for acquiring images of objects around the vehicle and generating imaging data;
the radar test module is used for acquiring the undulation state of the surrounding road surface;
the system comprises a preprocessing module, a data processing module and a data processing module, wherein the preprocessing module is used for determining a specific driving road state and an obstacle type according to a preset regional characteristic template, and the regional characteristic template comprises a lane line slope, lane line pixels, a lane line length, a length ratio of a lane solid line and a lane dotted line, and pedestrians, vehicles, buildings and traffic equipment;
the electronic tag module is used for storing static vehicle information and dynamic vehicle information, wherein the static vehicle information comprises a license plate number, a vehicle model and a vehicle overall dimension, and the dynamic vehicle information comprises a vehicle running direction, a real-time speed, an engine rotating speed, an acceleration, a steering angle, a load weight and position information;
the data reading and writing module is used for writing the static vehicle information and the dynamic vehicle information into the electronic tag in real time to wait for reading;
the data processing module is used for reading vehicle information stored in all vehicle electronic tags in a preset range in real time, comparing the vehicle information with the vehicle information, granting different attention degrees of the compared vehicles to be sent to the memory for storage or updating the attention degree grade corresponding to the vehicle in the memory;
and the reminding display module is used for sending a warning signal to the driver of the vehicle when the data in the dynamic vehicle information corresponding to the vehicle with the highest attention degree exceeds a preset normal value range.
9. The utility model provides a vehicle automatic detection keeps away dangerous auxiliary system which characterized in that includes:
one or more processors;
storage means for storing one or more programs;
the vehicle automatic detection danger-avoiding auxiliary device;
the one or more programs, when executed by the one or more processors, cause a vehicle automated detection hedge assist to implement, in cooperation with the one or more processors, the method of any one of claims 1-7.
10. A vehicle control system characterized by comprising the vehicle automatic detection risk avoiding auxiliary system according to claim 9.
CN202010420481.7A 2020-05-18 2020-05-18 Vehicle automatic detection danger avoidance auxiliary method, device and system Withdrawn CN111516706A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112148004A (en) * 2020-09-08 2020-12-29 中电海康集团有限公司 Emergency obstacle avoidance method and system for unmanned driving training vehicle
CN113065517A (en) * 2021-04-23 2021-07-02 上海寅家电子科技股份有限公司 Safety obstacle avoidance method, vehicle and computer storage medium

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112148004A (en) * 2020-09-08 2020-12-29 中电海康集团有限公司 Emergency obstacle avoidance method and system for unmanned driving training vehicle
CN112148004B (en) * 2020-09-08 2023-04-14 中电海康集团有限公司 Emergency obstacle avoidance method and system for unmanned driving training vehicle
CN113065517A (en) * 2021-04-23 2021-07-02 上海寅家电子科技股份有限公司 Safety obstacle avoidance method, vehicle and computer storage medium

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Application publication date: 20200811