CN112330980B - Intelligent anti-collision system of learner-driven vehicle - Google Patents
Intelligent anti-collision system of learner-driven vehicle Download PDFInfo
- Publication number
- CN112330980B CN112330980B CN202011040710.9A CN202011040710A CN112330980B CN 112330980 B CN112330980 B CN 112330980B CN 202011040710 A CN202011040710 A CN 202011040710A CN 112330980 B CN112330980 B CN 112330980B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- distance
- learner
- intelligent
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/161—Decentralised systems, e.g. inter-vehicle communication
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/165—Anti-collision systems for passive traffic, e.g. including static obstacles, trees
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/166—Anti-collision systems for active traffic, e.g. moving vehicles, pedestrians, bikes
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses an intelligent anti-collision system of a learner-driven vehicle, which is used for assisting the learner-driven vehicle to run in a training field, and comprises the following components: the intelligent road side terminal is installed on the training field, and the intelligent vehicle-mounted terminal, the electric control brake module and the differential GPS mobile station are installed on the instruction car. According to the intelligent anti-collision system, a vehicle-road cooperation technology is utilized, a set of intelligent anti-collision system is deployed in a driving training field, detection results are synchronously sent to the unmanned training vehicle in real time to realize emergency braking, the number of sensors mounted on the unmanned training vehicle is greatly saved, the mounting complexity and the configuration cost are reduced, the intelligent investment cost for the operation of the unmanned driving training system is reduced, the problems of redundancy and complexity of mounting and configuration of the sensors of the unmanned driving training vehicle, high power consumption and the like are solved, meanwhile, the feasibility of realizing safe anti-collision is guaranteed, and the safety of unmanned driving training is improved.
Description
Technical Field
The application belongs to the technical field of driving training, and particularly relates to an intelligent anti-collision system of a learner-driven vehicle.
Background
The driving training is short for motor vehicle driver training, and along with the increasing convenience brought by the vehicle in daily life, the demand of the driving training on the market is higher and higher. In the field of driving training, a learner-driven vehicle is indispensable, and the learner-driven vehicle is a vehicle specially used for teaching in driving schools and is mainly used for driving training of driving trainees. Different from the common special-purpose automobile, the instructional car has special requirements. The technical condition of the instructional car is to meet the requirement of GB 7258 and the technical conditions of a secondary car specified by JT/T198, and the instructional car is provided with an auxiliary rearview mirror, an auxiliary brake pedal, a fire extinguisher and other safety protection devices.
With the development maturity of technologies such as sensor, car networking, intelligent control, deep study, the continuous increase of coach recruitment cost, the intellectuality of driving school training trade, it has become a must development trend to go to coach, but the problem of student's safety learning car is inevitably brought to the reduction of the quantity of driving school owner's coach by a wide margin, simultaneously because new student's misoperation, the vehicle bumps public facilities, flower bed railing or the vehicle bumps little accident that damages the vehicle and can often take place, these bring facility loss of property not a little for the field of driving training. Therefore, how to accurately realize obstacle avoidance and braking of the vehicle in an unmanned driving training teaching scene becomes a problem to be solved.
At present, the comparatively common anticollision system of vehicle emergency braking is realized by installing anticollision millimeter wave radar, ultrasonic radar, camera, electric brake actuating mechanism on every vehicle, and this implementation method is not only expensive, and the installation is complicated, needs to increase the communication between the vehicle in addition and carries out the anticollision between the vehicle and detect, and this can increase the delay of keeping away the barrier brake undoubtedly to there is the monitoring blind area in the radar of installing on the vehicle, receives defects such as interference reinforce, influences the precision that the learner-driven vehicle kept away the barrier brake.
Disclosure of Invention
An object of the application is to provide an intelligence anticollision system of learner-driven vehicle, can effectively reduce unmanned driving training input cost to improve unmanned driving training's security.
In order to achieve the purpose, the technical scheme adopted by the application is as follows:
an intelligent anti-collision system of a learner-driven vehicle for assisting the learner-driven vehicle to travel in a training field, the intelligent anti-collision system of the learner-driven vehicle comprising: install radar video perception module, intelligent roadside terminal, difference GPS reference station on the training place, and install intelligent vehicle mounted terminal, automatically controlled brake module, difference GPS mobile station on the learner-driven vehicle, wherein:
the differential GPS mobile station is used for acquiring GPS information of a learner-driven vehicle in a training field based on the differential GPS reference station and sending the GPS information to an intelligent vehicle-mounted terminal corresponding to the learner-driven vehicle;
the radar video sensing module is used for acquiring distance information between moving objects in a training field and sending the distance information to the intelligent road side terminal, wherein the moving objects comprise a learner-driven vehicle and a dynamic barrier in the training field;
the intelligent road side terminal is used for sending the pre-loaded static obstacle information in the training field and the distance information to the intelligent vehicle-mounted terminal;
the intelligent vehicle-mounted terminal is used for calculating the distance between the instructional car and the static barrier and the distance between the instructional car and other moving objects except the vehicle according to the received GPS information, the distance information and the static barrier information, and issuing a braking instruction to the electric control braking module when the distance is smaller than a preset threshold value;
the electronic control brake module is used for receiving a brake instruction issued by the intelligent vehicle-mounted terminal to control the brake of the instructional car;
the intelligent vehicle-mounted terminal is also used for sending the GPS information of the vehicle to the intelligent road-side terminal;
the intelligent road side terminals are also used for collecting and sending the GPS information of all the learner-driven vehicles to each intelligent vehicle-mounted terminal after receiving the GPS information sent by the intelligent vehicle-mounted terminals on all the learner-driven vehicles;
the intelligent vehicle-mounted terminal calculates the distance between the learner-driven vehicle and other moving objects except the learner-driven vehicle, and when the distance is smaller than a preset threshold value, a braking instruction is issued to the electronic control braking module to execute the following operations:
screening distance information related to the vehicle based on the distance information, taking the distance information between the vehicle and the rest of the learner-driven vehicles in the distance information related to the vehicle as a fourth distance, and taking the distance information between the vehicle and the dynamic obstacle as a fifth distance;
when the fifth distance is smaller than a third threshold value, a braking instruction is issued to the electronic control braking module, otherwise, a sixth distance between the instructional cars is calculated according to the GPS information of all instructional cars sent by the intelligent vehicle-mounted terminal;
calculating a difference value between the fourth distance and the sixth distance, if the difference value is smaller than a fluctuation threshold value, taking the smaller value of the fourth distance and the sixth distance, and when the smaller value is smaller than a third threshold value, issuing a braking instruction to the electronic control braking module; and if the difference value is larger than the fluctuation threshold value, ending the distance judgment operation.
Several alternatives are provided below, but not as an additional limitation to the above general solution, but merely as a further addition or preference, each alternative being combinable individually for the above general solution or among several alternatives without technical or logical contradictions.
Preferably, the static obstacle information includes an equation model of an electronic fence corresponding to the static obstacle, and the method for constructing the equation model includes:
acquiring a GIS vector map corresponding to a training field;
obtaining barrier points corresponding to all static barriers in the training field based on the GIS vector map;
generating an electronic fence according to the coordinates of the obstacle points;
and constructing an equation model of each electronic fence according to the position information of each electronic fence on the GIS vector map.
Preferably, the intelligent vehicle-mounted terminal calculates a distance between the learner-driven vehicle and the static obstacle, and when the distance is smaller than a preset threshold, issues a braking instruction to the electronic control braking module to execute the following operations:
calculating a first distance between the vehicle and each static obstacle according to the received GPS information and the coordinates of the obstacle points, and screening the static obstacles with the first distance smaller than a first threshold value;
if the screened static obstacle exists, a vehicle position model is established according to the GPS information and the vehicle size information, an equation model of the electronic fence and the vehicle position model corresponding to the screened static obstacle are taken to carry out combined solution, if the combined solution has a solution, the distance between the vehicle and the static obstacle is smaller than a second threshold value, and a braking instruction is issued to the electronic control braking module; if the joint solution is not solved, generating an alarm prompt;
and if the screened static barrier does not exist, ending the distance judgment operation.
Preferably, the intelligent vehicle-mounted terminal calculates the distance between the learner-driven vehicle and the other moving objects except the learner-driven vehicle, and when the distance is smaller than a preset threshold, issues a braking instruction to the electronic control braking module to execute the following operations:
screening distance information related to the vehicle based on the distance information, and taking the distance information related to the vehicle as a third distance between the vehicle and other moving objects except the vehicle;
and when the third distance is smaller than a third threshold value, issuing a braking instruction to the electronic control braking module.
The application provides an intelligence anticollision system of learner-driven vehicle, utilize the car road collaborative technique, one set of intelligence anticollision system is arranged in driving the training field, give unmanned learner-driven vehicle to the detection result real-time synchronization and realize emergency braking, the quantity of installation sensor on the unmanned learner-driven vehicle has been saved greatly, reduce installation complexity and configuration cost, reduce the intelligent input cost of unmanned training system operation, solve redundancy and the complexity of unmanned training vehicle sensor installation configuration, the great scheduling problem of consumption, guarantee the feasibility that safe anticollision realized simultaneously, the security that unmanned training was driven is improved.
Drawings
Fig. 1 is a schematic structural diagram of an intelligent collision avoidance system of a learner-driven vehicle according to the present application;
FIG. 2 is a schematic diagram of a vehicle position model constructed according to the present application.
In the drawings: 1. a training field; 2. a differential GPS reference station; 3. a radar video sensing module; 4. an intelligent roadside terminal; 5. a coach car.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, 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 application.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the present application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.
In one embodiment, an intelligent anti-collision system of a learner-driven vehicle is provided, which is used for assisting the learner-driven vehicle to drive in a training field and promoting the realization of unmanned driving training.
As shown in fig. 1, the intelligent anti-collision system of the learner-driven vehicle of the present embodiment includes: install radar video perception module 3, intelligent roadside terminal (Road Side Unit, RSU)4, difference GPS reference station 2 On training place 1 and install intelligent On-vehicle terminal (On board Unit, OBU), automatically controlled brake module, difference GPS mobile station On learner-driven vehicle 5.
Considering the security problem, usually drive the training and practice the place position spaciously, shelter from thing few and the road surface is flat, consequently set up a set of radar video perception module, intelligent roadside terminal, difference GPS reference station and can satisfy and drive the training and practice the demand on the training place. Certainly, this is not restricted to setting up only one set, when too big or because the information in the training place can't be acquireed comprehensively to the shelter in the area of training place, can carry out the subregion with the training place, sets up one set of in each region to with the cooperation of the learner-driven vehicle that is located this region realize anticollision and detect.
Specifically, the differential GPS mobile station is used for acquiring GPS information of a learner-driven vehicle in a training field based on the differential GPS reference station 2 and sending the GPS information to an intelligent vehicle-mounted terminal corresponding to the learner-driven vehicle.
The radar video sensing module 3 is used for acquiring distance information between moving objects in a training field and sending the distance information to the intelligent road side terminal 4, wherein the moving objects comprise a learner-driven vehicle 5 and a dynamic barrier in the training field;
the intelligent road side terminal 4 is used for sending the pre-loaded static obstacle information and the distance information in the training field to the intelligent vehicle-mounted terminal;
the intelligent vehicle-mounted terminal is used for calculating the distance between the instructional car and the static barrier and the distance between the instructional car and other moving objects except the vehicle according to the received GPS information, the distance information and the static barrier information, and issuing a braking instruction to the electric control braking module when the distance is smaller than a preset threshold value;
and the electric control brake module is used for receiving a brake instruction issued by the intelligent vehicle-mounted terminal to control the brake of the instructional car. The electronic control brake module is an existing control module, and may include a brake system and an electronic control module, or may only include an electronic control module connected to the brake system of the learner-driven vehicle, which is not limited herein.
The intelligent vehicle-mounted terminal is connected with the electric control brake module through the can bus or the serial port and issues an instruction to realize the brake braking of the learner-driven vehicle, and the auxiliary brake system of the learner-driven vehicle is controlled to perform the brake braking based on the vehicle structure of the learner-driven vehicle.
This embodiment installs a set of radar video perception module on training field, intelligence roadside terminal, difference GPS reference station can realize detecting the anticollision of all learner-driven vehicles in the training field, saved and installed all kinds of sensors on each learner-driven vehicle, the degree of difficulty of reforming transform the learner-driven vehicle has been reduced promptly, the cost of reforming transform has also been saved simultaneously, and this application can obtain including the interval between all moving objects on the training field within the learner-driven vehicle, only focus on the learner-driven vehicle in the current anticollision system has been overcome, and the people that probably appears on the training field has been ignored, the defect of animal or other mobile device's detection, make this application have more comprehensively, reliable anticollision detects.
In the embodiment, the GPS information of the learner-driven vehicle is acquired based on the differential GPS positioning device, and the positioning precision can reach 2 cm. The differential GPS positioning device comprises a differential GPS reference station and differential GPS mobile stations, wherein the differential GPS reference station is installed on a training field, the differential GPS mobile stations are installed on each instructional car, a positioning receiving antenna and a directional receiving antenna are installed at the top of each instructional car, differential resolving data sent by the differential GPS reference station are received in real time, and high-precision positioning of the cars is achieved.
In order to directly use the distance information obtained by the radar video perception module through measurement, the method preferably installs a mark for identifying each instructional car on the surface or the car body of each instructional car, so that the distance information output by the radar video perception module comprises the car mark.
Distance information obtained based on the vehicle mark radar video perception module comprises the distance between two vehicle marks and the distance between the vehicle marks and dynamic obstacles, the dynamic obstacles can be collectively called as dynamic obstacles, and can also be subdivided into people, animals, mobile equipment and the like, namely, people, animals or mobile equipment on a detection site can be only appointed, and all dynamic obstacles can also be detected.
It should be noted that, the radar video sensing module can be realized by adopting the existing radar video vehicle inspection device, and also can be realized by adopting the existing radar + video comprehensive sensing technology based on the processor, and the realization of the radar + video comprehensive sensing technology is not repeated in this application.
The static obstacle information in this embodiment includes an equation model of the electronic fence corresponding to the static obstacle, and the equation model may be directly obtained from a constructed equation model or may be constructed by itself according to a GIS vector map corresponding to a training field. The method for constructing the equation model according to the GIS vector map corresponding to the training field comprises the following steps:
acquiring a GIS vector map corresponding to a training field; obtaining barrier points corresponding to all static barriers in the training field based on the GIS vector map; generating an electronic fence according to the coordinates of the obstacle points; and constructing an equation model of each electronic fence according to the position information of each electronic fence on the GIS vector map.
The obstacle point may be one point in a static obstacle specified by human input, or one point in the static obstacle may be randomly acquired as the obstacle point, and the generation of the electronic fence may be to generate a circular electronic fence according to the obstacle point and a preset radius, or to generate a rectangular electronic fence according to the obstacle point and a preset length and width. The direction model of the corresponding electronic fence can be a circular equation of a circular electronic fence or a four-edge equation corresponding to a rectangular electronic fence.
It should be noted that the static obstacle information may be directly introduced into the intelligent roadside terminal, or may be constructed by the intelligent roadside terminal, which is not limited herein. In consideration of the reasonableness of the electronic fence generation, the embodiment preferably uses a mode of importing the static obstacle information generated by mapping and constructing by professional mappers into the intelligent roadside terminal in advance. And under the condition that static barriers in the training field are not changed, the intelligent road side terminal only needs to send static barrier information to the interactive intelligent vehicle-mounted terminal once.
Because in the anticollision detection between static barrier and the learner-driven vehicle, only the learner-driven vehicle is the dynamic object, consequently mainly acquire the real-time position information of learner-driven vehicle and can realize position judgement between them, at intelligent vehicle mounted terminal, calculate the interval between place learner-driven vehicle and the static barrier, when the interval is less than and predetermines the threshold value, to automatically controlled brake module issue the brake instruction, carry out following operation:
calculating a first distance between the vehicle and each static obstacle according to the received GPS information and the coordinates of the obstacle points, and screening the static obstacles with the first distance smaller than a first threshold value; if the static obstacles meeting the conditions are not screened out at this time, the fact that the distance between the vehicle and the static obstacles is large is indicated, braking is not needed, and the collision-prevention calculation is finished.
If the screened static obstacles exist, a vehicle position model is constructed according to the GPS information and the vehicle size information; taking an equation model of the electronic fence corresponding to the screened static obstacle and a vehicle position model for joint solution, if the joint solution has a solution, indicating that the distance between the vehicle and the static obstacle is smaller than a second threshold value, and issuing a braking instruction to the electronic control braking module; and if the joint solution is not solved, generating an alarm prompt.
If the screened static barriers do not exist, the fact that the distance between the current learner-driven vehicle and the static barriers on the field is large is shown, no collision risk exists, and the distance judgment operation can be finished.
In this embodiment, the static obstacles with the distance smaller than the first distance are further determined, so that the reliability of the anti-collision detection can be improved, a part of static obstacles which do not need to be solved by the joint equation can be removed for subsequent solution and screening of the joint equation, the operation pressure is reduced, and the anti-collision detection efficiency is improved.
As shown in fig. 2, when constructing the vehicle position model, if the known vehicle size information includes: the four vertex angles of the minimum circumscribed rectangle vertically projected by the learner-driven vehicle are C, D, E, F respectively, the lengths of the side DE and the side CF are l, the lengths of the side EF and the side CD are w, the distance between the vertical projection point A of the positioning receiving antenna mounted on the learner-driven vehicle and the side CF of the minimum circumscribed rectangle is b, and the distance between the vertical projection point A and the side CD of the minimum circumscribed rectangle is a. And the acquired GPS information includes: including the coordinates (x) of the vertical projection point Ao，y0) And the orientation angle gamma is an included angle between the connection of the differential GPS orientation positioning receiving antenna and the true north direction.
One implementation of constructing the vehicle location model is as follows:
according to the coordinates (x)o，y0) And orientation angle γ, the coordinates of the four corners C, D, E, F of the smallest circumscribed rectangle are calculated as follows:
the coordinate of the vertex angle C is (x)C，yC) And x isC＝xo+b sinγ+a cosγ，yC＝y0+b cosγ-a sinγ；
The coordinate of the vertex angle D is (x)D，yD) And x isD＝xo-(w-b)sinγ+a cosγ，yD＝y0-(w-b)cosγ-a sinγ；
The coordinate of the apex angle E is (x)E，yE) And x isE＝xo-(w-b)sinγ-(l-a)cosγ，yE＝y0-(w-b)cosγ+(l-a)sinγ；
The coordinate of the vertex angle F is (x)F，yF) And x isF＝xo+bsinγ-(l-a)cosγ，yF＝y0+b cosγ+(l-a)sinγ；
A vehicle position model is obtained as follows:
the linear equation for the edge CD is:
and satisfies the restriction condition min (x)C，xD)≤x≤max(xC，xD) And min (y)C，yD)≤y≤max(yC，yD)；
The linear equation for edge DE is: y-yD＝-tanγ(x-xD) And satisfies the restriction condition min (x)D，xE)≤x≤max(xD，xE) And min (y)D，yE)≤y≤max(yD，yE)；
The linear equation for edge EF is:
and satisfies the restriction condition min (x)E，xF)≤x≤max(xE，xF) And min (y)E，yF)≤y≤max(yE，yF)；
The linear equation for the edge CF is: y-yC＝-tanγ(x-xC) And satisfies the restriction condition min (x)C，xF)≤x≤max(xC，xF) And min (y)C，yF)≤y≤max(yC，yF)。
It should be noted that the above is only one preferred way to construct the vehicle location model provided for the present application, and in other embodiments, the vehicle location model may be constructed based on other ways, for example, it is known that the vehicle size information includes the diagonal length of the minimum circumscribed rectangle of the vertical projection of the vehicle, and the vehicle location information may be constructed by directly calculating the circular equation with the positioning coordinates in the GPS information as the center and the diagonal length as the diameter.
When the joint solution of the equation model of the electronic fence corresponding to the screened static barrier and the vehicle position model is not solved, the fact that the distance between the vehicle and the corresponding static barrier is larger than the second threshold and smaller than the first threshold is indicated, active interference on vehicle emergency braking is not needed at the moment, an alarm prompt is generated to remind a student to notice avoidance, meanwhile, judgment of the student on the vehicle distance can be improved in the form of alarm prompt feedback, safe and reliable driving training is achieved, meanwhile, the subjective judgment capability and the driving technology of the student are improved, and the probability of collision in driving training is reduced.
Because the instructional car and the moving object both have moving speeds, the judgment mode of the instructional car and the judgment mode of the static barrier need to be distinguished so as to take corresponding measures in time. In this embodiment, the intelligent vehicle-mounted terminal calculates a distance between the learner-driven vehicle and the other moving objects except the vehicle, and when the distance is smaller than a preset threshold, issues a braking instruction to the electronic control braking module, and executes the following operations:
screening distance information related to the vehicle based on the distance information, and taking the distance information related to the vehicle as a third distance between the vehicle and other moving objects except the vehicle;
and when the third distance is smaller than a third threshold value, issuing a braking instruction to the electronic control braking module.
In order to increase the effectiveness of the collision avoidance implementation in case of movement, the third threshold value is typically set larger than the second threshold value, and may even be set larger than the first threshold value. The braking of the distance information that this embodiment was direct to obtain based on radar video perception module accomplishes between instruction car and the moving object braking between both, has saved the processing procedure to multiple sensor information data, improves braking's promptness to intelligent vehicle mounted terminal's operating pressure has been reduced.
In order to further improve the reliability of collision prevention between the learner-driven vehicle and each moving object, in another embodiment, the intelligent vehicle-mounted terminal is further configured to send the GPS information of the vehicle to the intelligent road-side terminal, because the position relationship between the moving objects is fast in change speed and the relative relationship is complex; and the intelligent road side terminals are also used for summarizing and sending the GPS information of all the learner-driven vehicles to each intelligent vehicle-mounted terminal after receiving the GPS information sent by the intelligent vehicle-mounted terminals on all the learner-driven vehicles.
Based on the GPS information of all the learner-driven vehicles, the intelligent vehicle-mounted terminal calculates the distance between the learner-driven vehicle and other moving objects except the learner-driven vehicle, and when the distance is smaller than a preset threshold value, a braking instruction is issued to the electronic control braking module to execute the following operations:
and screening distance information related to the vehicle based on the distance information, wherein the distance information between the vehicle and the rest of the learner-driven vehicles in the distance information related to the vehicle is used as a fourth distance, and the distance information between the vehicle and the dynamic obstacle is used as a fifth distance.
And when the fifth distance is smaller than a third threshold value, issuing a braking instruction to the electronic control braking module, otherwise, calculating a sixth distance between the instructional cars according to the GPS information of all instructional cars sent by the intelligent vehicle-mounted terminal.
Calculating a difference value between the fourth distance and the sixth distance, if the difference value is smaller than a fluctuation threshold value, taking the smaller value of the fourth distance and the sixth distance, and when the smaller value is smaller than a third threshold value, issuing a braking instruction to the electronic control braking module; and if the difference value is larger than the fluctuation threshold value, ending the distance judgment operation.
Since the dynamic barrier other than the learner-driven vehicle is not usually provided with a GPS positioning device, the learner-driven vehicle and the dynamic barrier are respectively determined in this embodiment. The distance between the vehicle and the dynamic barrier is judged based on the distance information acquired by the radar video sensing module. And the distance between the vehicle and other learner-driven vehicles is judged based on the distance information acquired by the radar video sensing module and based on the GPS information between the two vehicles. The situation that the radar video sensing module is in distance measurement error due to vehicle condition complexity and the like or the GPS positioning device is in brake failure or brake error due to positioning error caused by GPS signal drift is overcome, and the anti-collision real-time effectiveness in the driving training is remarkably improved.
And in the judgment of the learner-driven vehicle and the dynamic barrier, the distance between the learner-driven vehicle and the dynamic barrier is preferentially judged so as to avoid the learner-driven vehicle from damaging human beings, animals and the like without protective measures. And the threshold value between the vehicle and the instruction vehicle and the threshold value between the vehicle and the dynamic barrier can be the same or different, so that the protection of the instruction vehicle on human or animals on the training field is improved.
In this application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any particular order or number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means at least two, e.g., two, three, etc., unless specifically limited otherwise.
In this application, the terms "comprises" and "comprising," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a system, article, or apparatus that comprises a list of elements is not necessarily limited to those elements explicitly listed, but may include other elements not expressly listed or inherent to such system or apparatus.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (4)
1. An intelligent anti-collision system of a learner-driven vehicle, which is used for assisting the learner-driven vehicle to run in a training field, and is characterized by comprising: install radar video perception module, intelligent roadside terminal, difference GPS reference station on the training place, and install intelligent vehicle mounted terminal, automatically controlled brake module, difference GPS mobile station on the learner-driven vehicle, wherein:
the differential GPS mobile station is used for acquiring GPS information of a learner-driven vehicle in a training field based on the differential GPS reference station and sending the GPS information to an intelligent vehicle-mounted terminal corresponding to the learner-driven vehicle;
the radar video sensing module is used for acquiring distance information between moving objects in a training field and sending the distance information to the intelligent road side terminal, wherein the moving objects comprise a learner-driven vehicle and a dynamic barrier in the training field;
the intelligent road side terminal is used for sending the pre-loaded static obstacle information in the training field and the distance information to the intelligent vehicle-mounted terminal;
the intelligent vehicle-mounted terminal is used for calculating the distance between the instructional car and the static barrier and the distance between the instructional car and other moving objects except the vehicle according to the received GPS information, the distance information and the static barrier information, and issuing a braking instruction to the electric control braking module when the distance is smaller than a preset threshold value;
the electronic control brake module is used for receiving a brake instruction issued by the intelligent vehicle-mounted terminal to control the brake of the instructional car;
the intelligent vehicle-mounted terminal is also used for sending the GPS information of the vehicle to the intelligent road-side terminal;
the intelligent road side terminals are also used for collecting and sending the GPS information of all the learner-driven vehicles to each intelligent vehicle-mounted terminal after receiving the GPS information sent by the intelligent vehicle-mounted terminals on all the learner-driven vehicles;
the intelligent vehicle-mounted terminal calculates the distance between the learner-driven vehicle and other moving objects except the learner-driven vehicle, and when the distance is smaller than a preset threshold value, a braking instruction is issued to the electronic control braking module to execute the following operations:
screening distance information related to the vehicle based on the distance information, taking the distance information between the vehicle and the rest of the learner-driven vehicles in the distance information related to the vehicle as a fourth distance, and taking the distance information between the vehicle and the dynamic obstacle as a fifth distance;
when the fifth distance is smaller than a third threshold value, a braking instruction is issued to the electronic control braking module, otherwise, a sixth distance between the instructional cars is calculated according to the GPS information of all instructional cars sent by the intelligent vehicle-mounted terminal;
calculating a difference value between the fourth distance and the sixth distance, if the difference value is smaller than a fluctuation threshold value, taking the smaller value of the fourth distance and the sixth distance, and when the smaller value is smaller than a third threshold value, issuing a braking instruction to the electronic control braking module; and if the difference value is larger than the fluctuation threshold value, ending the distance judgment operation.
2. The intelligent collision avoidance system of a learner-driven vehicle according to claim 1, wherein the static obstacle information includes an equation model of an electronic fence corresponding to the static obstacle, and the equation model is constructed by a method comprising:
acquiring a GIS vector map corresponding to a training field;
obtaining barrier points corresponding to all static barriers in the training field based on the GIS vector map;
generating an electronic fence according to the coordinates of the obstacle points;
and constructing an equation model of each electronic fence according to the position information of each electronic fence on the GIS vector map.
3. The intelligent anti-collision system of the learner-driven vehicle as claimed in claim 2, wherein the intelligent vehicle-mounted terminal calculates a distance between the learner-driven vehicle and a static obstacle, and when the distance is smaller than a preset threshold, issues a braking instruction to the electronic control braking module to perform the following operations:
calculating a first distance between the vehicle and each static obstacle according to the received GPS information and the coordinates of the obstacle points, and screening the static obstacles with the first distance smaller than a first threshold value;
if the screened static obstacle exists, a vehicle position model is established according to the GPS information and the vehicle size information, an equation model of the electronic fence and the vehicle position model corresponding to the screened static obstacle are taken to carry out combined solution, if the combined solution has a solution, the distance between the vehicle and the static obstacle is smaller than a second threshold value, and a braking instruction is issued to the electronic control braking module; if the joint solution is not solved, generating an alarm prompt;
and if the screened static barrier does not exist, ending the distance judgment operation.
4. The intelligent anti-collision system of the learner-driven vehicle as claimed in claim 1, wherein the intelligent vehicle-mounted terminal calculates a distance between the learner-driven vehicle and other moving objects except the learner-driven vehicle, and when the distance is smaller than a preset threshold, issues a braking instruction to the electronically controlled braking module to perform the following operations:
screening distance information related to the vehicle based on the distance information, and taking the distance information related to the vehicle as a third distance between the vehicle and other moving objects except the vehicle;
and when the third distance is smaller than a third threshold value, issuing a braking instruction to the electronic control braking module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011040710.9A CN112330980B (en) | 2020-09-28 | 2020-09-28 | Intelligent anti-collision system of learner-driven vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011040710.9A CN112330980B (en) | 2020-09-28 | 2020-09-28 | Intelligent anti-collision system of learner-driven vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112330980A CN112330980A (en) | 2021-02-05 |
| CN112330980B true CN112330980B (en) | 2022-04-15 |
Family
ID=74303371
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011040710.9A Active CN112330980B (en) | 2020-09-28 | 2020-09-28 | Intelligent anti-collision system of learner-driven vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112330980B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114664154A (en) * | 2022-02-17 | 2022-06-24 | 豪德天沐(深圳)科技有限公司 | Vehicle-mounted control method for learning to ride |
| CN115482679B (en) * | 2022-09-15 | 2024-04-26 | 深圳海星智驾科技有限公司 | Automatic driving blind area early warning method and device and message server |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008059181A (en) * | 2006-08-30 | 2008-03-13 | Toshiba Corp | Road traffic control training device and road traffic control training system |
| CN102156767A (en) * | 2010-12-31 | 2011-08-17 | 长安大学 | Automobile and ground fixed object collision accident analytical calculation and simulation reproduction system |
| CN102390320A (en) * | 2011-08-22 | 2012-03-28 | 武汉理工大学 | Vehicle anti-collision early warning system based on vehicle-mounted sensing network |
| CN106898159A (en) * | 2017-03-23 | 2017-06-27 | 奇瑞汽车股份有限公司 | Learner-driven vehicle spacing early warning system and its method for early warning |
| CN107117099A (en) * | 2017-03-29 | 2017-09-01 | 深圳市元征科技股份有限公司 | A kind of vehicle collision reminding method and vehicle |
| JP2018009868A (en) * | 2016-07-13 | 2018-01-18 | 株式会社Ｓｏｋｅｎ | Position estimation device |
| CN108738021A (en) * | 2017-04-20 | 2018-11-02 | 松下电器（美国）知识产权公司 | The recording medium of communication system, mobile unit and logging program |
| CN208484681U (en) * | 2018-06-11 | 2019-02-12 | 安徽国华智能交通科技有限公司 | One kind driving training learner-driven vehicle active anti-collision device |
| CN111540224A (en) * | 2020-06-12 | 2020-08-14 | 深圳市元征科技股份有限公司 | Road data processing method and related equipment |
-
2020
- 2020-09-28 CN CN202011040710.9A patent/CN112330980B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008059181A (en) * | 2006-08-30 | 2008-03-13 | Toshiba Corp | Road traffic control training device and road traffic control training system |
| CN102156767A (en) * | 2010-12-31 | 2011-08-17 | 长安大学 | Automobile and ground fixed object collision accident analytical calculation and simulation reproduction system |
| CN102390320A (en) * | 2011-08-22 | 2012-03-28 | 武汉理工大学 | Vehicle anti-collision early warning system based on vehicle-mounted sensing network |
| JP2018009868A (en) * | 2016-07-13 | 2018-01-18 | 株式会社Ｓｏｋｅｎ | Position estimation device |
| CN106898159A (en) * | 2017-03-23 | 2017-06-27 | 奇瑞汽车股份有限公司 | Learner-driven vehicle spacing early warning system and its method for early warning |
| CN107117099A (en) * | 2017-03-29 | 2017-09-01 | 深圳市元征科技股份有限公司 | A kind of vehicle collision reminding method and vehicle |
| CN108738021A (en) * | 2017-04-20 | 2018-11-02 | 松下电器（美国）知识产权公司 | The recording medium of communication system, mobile unit and logging program |
| CN208484681U (en) * | 2018-06-11 | 2019-02-12 | 安徽国华智能交通科技有限公司 | One kind driving training learner-driven vehicle active anti-collision device |
| CN111540224A (en) * | 2020-06-12 | 2020-08-14 | 深圳市元征科技股份有限公司 | Road data processing method and related equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112330980A (en) | 2021-02-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113140125B (en) | Vehicle-road cooperative auxiliary driving method and road side equipment | |
| US10332401B2 (en) | Running vehicle alerting system and method | |
| US20210122364A1 (en) | Vehicle collision avoidance apparatus and method | |
| CN110126820B (en) | Automatic parking system, parking method and vehicle | |
| CN109733283B (en) | AR-based shielded barrier recognition early warning system and recognition early warning method | |
| JP6962604B2 (en) | Collaborative blindspot alerting methods and equipment for inter-vehicle communication infrastructure with fault tolerance and fracture robustness in extreme situations | |
| CN108749813B (en) | Automatic parking system and parking method | |
| CN112330980B (en) | Intelligent anti-collision system of learner-driven vehicle | |
| US11496707B1 (en) | Fleet dashcam system for event-based scenario generation | |
| CN105957401A (en) | Intersection pedestrian anti-collision method based on vehicle-road coordination and device thereof | |
| CN107218947A (en) | Inductive loop detecting system and method | |
| CN111104957A (en) | Detecting attacks on a vehicle network | |
| CN109839281A (en) | A kind of real steering vectors acquisition system and method | |
| US11866068B2 (en) | Detecting and responding to malfunctioning traffic signals for autonomous vehicles | |
| CN111445725A (en) | Blind area intelligent warning device and algorithm for meeting scene | |
| UA126222C2 (en) | A system for monitoring and ensuring the safe movement of vehicles | |
| WO2022145286A1 (en) | Information processing device, information processing method, program, moving device, and information processing system | |
| US11932242B1 (en) | Fleet dashcam system for autonomous vehicle operation | |
| EP4140815A1 (en) | Information processing device, information processing method, and program | |
| CN214355775U (en) | Display device of automatic driving vehicle, automobile central control and automatic driving vehicle | |
| CN114822083A (en) | Intelligent vehicle formation auxiliary control system | |
| CN112148004B (en) | Emergency obstacle avoidance method and system for unmanned driving training vehicle | |
| CN114572243A (en) | Target object detection device and vehicle equipped with the same | |
| CN113936457A (en) | Ultra-large bus bending early warning system and method based on vehicle-road cooperation | |
| WO2020241273A1 (en) | Vehicular communication system, onboard device, control method, and computer program |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |