CN114604239A - Vehicle backing anti-collision system based on Internet of things - Google Patents
Vehicle backing anti-collision system based on Internet of things Download PDFInfo
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- 238000013473 artificial intelligence Methods 0.000 claims description 6
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- 238000012360 testing method Methods 0.000 claims description 5
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 claims description 3
- 230000003993 interaction Effects 0.000 claims description 3
- SAZUGELZHZOXHB-UHFFFAOYSA-N acecarbromal Chemical compound CCC(Br)(CC)C(=O)NC(=O)NC(C)=O SAZUGELZHZOXHB-UHFFFAOYSA-N 0.000 claims 1
- 230000006855 networking Effects 0.000 claims 1
- 238000002604 ultrasonography Methods 0.000 description 6
- 230000005856 abnormality Effects 0.000 description 3
- 230000004888 barrier function Effects 0.000 description 3
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/09—Taking automatic action to avoid collision, e.g. braking and steering
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0953—Predicting travel path or likelihood of collision the prediction being responsive to vehicle dynamic parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/08—Active safety systems predicting or avoiding probable or impending collision or attempting to minimise its consequences
- B60W30/095—Predicting travel path or likelihood of collision
- B60W30/0956—Predicting travel path or likelihood of collision the prediction being responsive to traffic or environmental parameters
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2552/00—Input parameters relating to infrastructure
- B60W2552/50—Barriers
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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
- B60W2554/00—Input parameters relating to objects
- B60W2554/80—Spatial relation or speed relative to objects
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Abstract
The invention discloses a vehicle reversing anti-collision system based on the Internet of things, relates to the technical field of vehicle control, and solves the technical problem that in the prior art, in the vehicle reversing process, the safety of a vehicle and a driver cannot be guaranteed in all directions due to the single identification range of obstacles; according to the invention, a data acquisition module acquires original data from data acquisition equipment based on a control instruction, a data analysis module performs data compensation on ultrasonic data in the original data, determines the position of an obstacle through the ultrasonic data and/or image data, and performs omnibearing early warning on a vehicle by combining the size of the vehicle, so that the safety of the vehicle and a driver in the process of backing the vehicle is comprehensively ensured; when the position of the obstacle is determined, the ultrasonic data or the image data is selected according to the application condition, and the ultrasonic data and the image data can be comprehensively analyzed to determine the position of the obstacle, so that the early warning accuracy is improved, and the collision accident is avoided.
Description
Technical Field
The invention belongs to the field of automobile control, relates to a vehicle reversing anti-collision technology, and particularly relates to a vehicle reversing anti-collision system based on the Internet of things.
Background
As the number of vehicles on the road increases, the operation difficulty of a driver is increased, and particularly when the vehicle backs, due to the limited visual field of the driver, the driver cannot find a rear obstacle in time, so that a collision accident is easy to happen.
The prior art (the invention patent with the publication number of CN 104802781A) discloses an automobile reverse collision avoidance system, which automatically monitors the distance between a reverse automobile and an obstacle through an ultrasonic sensor at the tail of the automobile, then reminds a driver in real time and controls the automatic braking of the automobile. In the prior art, in the process of backing a vehicle, most obstacles behind the vehicle can only be identified, and the safety of the vehicle and drivers cannot be guaranteed in an all-around manner; therefore, a vehicle backing collision avoidance system based on the internet of things is needed.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art; therefore, the invention provides a vehicle reversing anti-collision system based on the Internet of things, which is used for solving the technical problem that in the prior art, in the vehicle reversing process, the safety of a vehicle and a driver cannot be guaranteed in all directions due to the single identification range of obstacles.
According to the invention, the data acquisition module acquires original data from the data acquisition equipment based on a control instruction, the data analysis module performs data compensation on ultrasonic data in the original data, the position of an obstacle is determined through the ultrasonic data and/or image data, and the vehicle is subjected to all-round early warning by combining the size of the vehicle, so that the safety of the vehicle and a driver in the process of backing the vehicle is comprehensively ensured.
In order to achieve the above object, a first aspect of the present invention provides an internet of things-based vehicle reversing collision avoidance system, which includes a data analysis module and a data acquisition module, where the data analysis module and the data acquisition module are both disposed in a vehicle and perform data interaction with a vehicle-mounted machine system of the vehicle;
a data acquisition module: identifying a control instruction, acquiring original data through data acquisition equipment connected with the control instruction, preprocessing the data, and sending the original data to a data analysis module; wherein the raw data comprises ultrasonic data, temperature data and image data;
a data analysis module: acquiring a control instruction through the vehicle-mounted machine system, and sending the control instruction to a data acquisition module; and
after data compensation is carried out on the ultrasonic data, the position of an obstacle is determined through the ultrasonic data and/or the image data, early warning is carried out by combining the size of a vehicle, and automatic control of the vehicle is carried out; the automatic control of the vehicle comprises deceleration and braking.
Preferably, the control command is automatically generated by recognizing the driving state of the vehicle through the vehicle-mounted machine system, or generated by manual control of a driver.
Preferably, before the data preprocessing is performed on the raw data, the data acquisition module analyzes the working state of the data acquisition device, and the method includes:
automatically analyzing the original data, identifying the working state of the data acquisition equipment according to the automatic analysis result and early warning; or alternatively
The data acquisition module periodically sends a test signal to the data acquisition equipment, and identifies the working state and gives an early warning according to a feedback signal of the data acquisition equipment.
Preferably, the data compensation of the ultrasonic data by the temperature data includes:
inputting the temperature data acquired in real time into a compensation mapping curve or a compensation model to acquire compensation data; the compensation mapping curve is obtained through a polynomial fitting method, and a compensation model is established based on an artificial intelligence model;
and performing data compensation on the ultrasonic data through the compensation data.
Preferably, the obstacle position is determined by analyzing the data-compensated ultrasound data or by analyzing the image data by means of image recognition techniques.
Preferably, combining the ultrasound data and the image data to determine the location of the obstacle comprises:
preliminarily determining an obstacle according to the ultrasonic data, calculating the shortest straight-line distance between the edge of the obstacle and the edge of the vehicle, and marking the distance as a distance I;
preliminarily determining an obstacle according to the image data, calculating the shortest straight-line distance between the edge of the obstacle and the edge of the vehicle, and marking the shortest straight-line distance as a distance II;
and comparing the first distance with the second distance, and determining the position of the obstacle according to the comparison result.
Preferably, when the absolute value of the difference between the first distance and the second distance is smaller than a distance threshold, the position of an obstacle is obtained according to the obstacle corresponding to any one of the first distance and the second distance; wherein, the distance threshold is set according to actual experience;
and when the absolute value of the difference value between the first distance and the second distance is greater than or equal to a distance threshold, selecting the smaller one of the first distance and the second distance as a target distance, and acquiring the position of the obstacle according to the obstacle corresponding to the target distance.
Preferably, the data analysis module performs early warning in combination with the size of the vehicle, and includes:
acquiring the position of the obstacle;
the position of the obstacle is combined with the size of the vehicle to carry out omnibearing early warning on the vehicle; wherein, the all-round early warning includes the safety to all around, top and the bottom of vehicle and carries out the early warning.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the invention, the data acquisition module acquires original data from the data acquisition equipment based on a control instruction, the data analysis module performs data compensation on ultrasonic data in the original data, the position of an obstacle is determined through the ultrasonic data and/or image data, and the vehicle is subjected to all-round early warning by combining the size of the vehicle, so that the safety of the vehicle and a driver in the process of backing the vehicle is comprehensively ensured.
2. When the position of the obstacle is determined, the ultrasonic data or the image data is selected according to the application condition, and the ultrasonic data and the image data can be comprehensively analyzed to determine the position of the obstacle, so that early warning is performed according to the distance between the position of the obstacle and a vehicle, the accuracy of the early warning is improved, and collision accidents are avoided.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of the working steps of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood 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.
The prior art (the invention patent with the publication number of CN 104802781A) discloses an automobile reverse collision avoidance system, which automatically monitors the distance between a reverse automobile and an obstacle through an ultrasonic sensor at the tail of the automobile, then reminds a driver in real time and controls the automatic braking of the automobile. In the prior art, most obstacles behind the vehicle can only be identified in the process of backing the vehicle, at the moment, the attention of a driver is mainly focused on the rear of the vehicle, and the obstacles in other directions of the vehicle are not easy to be perceived, such as the roof, the bottom and the like, so that the safety of the vehicle and the driver cannot be guaranteed in all directions.
According to the invention, the data acquisition module acquires original data from the data acquisition equipment based on a control instruction, the data analysis module performs data compensation on ultrasonic data in the original data, the position of an obstacle is determined through the ultrasonic data and/or image data, and the vehicle is subjected to all-round early warning by combining the size of the vehicle, so that the safety of the vehicle and a driver in the process of backing the vehicle is comprehensively ensured.
Referring to fig. 1, an embodiment of the first aspect of the present application provides a vehicle reversing collision avoidance system based on the internet of things, which includes a data analysis module and a data acquisition module, where the data analysis module and the data acquisition module are both disposed inside a vehicle and perform data interaction with a vehicle-mounted machine system of the vehicle;
a data acquisition module: identifying a control instruction, acquiring original data through data acquisition equipment connected with the control instruction, preprocessing the data, and sending the original data to a data analysis module;
a data analysis module: acquiring a control instruction through a vehicle machine system, and sending the control instruction to a data acquisition module; and
after the ultrasonic data are subjected to data compensation, the position of an obstacle is determined through the ultrasonic data and/or the image data, and early warning is performed by combining the size of a vehicle and automatic control of the vehicle is performed.
Interconnect between the car machine system of data analysis module and vehicle in this application, data acquisition module and data acquisition equipment communication and/or electrical connection, data acquisition equipment include ultrasonic sensor, temperature sensor and camera, correspond and acquire ultrasonic data, temperature data and image data, and data acquisition equipment's mounted position should guarantee to gather enough and comprehensive data, guarantees the stable execution of this application technical scheme.
The automatic control of the vehicle comprises deceleration and braking, and when the barrier is close to the vehicle, the deceleration control of the vehicle is performed by combining with the actual situation in order to avoid the inattention of a driver; when the distance between the barrier and the vehicle is very close, the vehicle is subjected to brake control by combining with actual conditions in order to avoid collision accidents.
The control instruction in the application comprises active generation and manual generation; the active generation control instruction is automatically generated according to the driving state when the vehicle system identifies the driving state, if the vehicle is in a reversing state; the manual generation of the control instruction is that a driver sends a signal, the vehicle-mounted machine system analyzes the signal and then generates the control instruction, and if the driver does not know the limit height of the garage, the signal can be sent to identify the limit height device, so that collision is avoided.
In which state the control instruction can be set in advance by actively generating the control instruction, and the manually generated control instruction can be started at any time under the condition of not influencing the running of the vehicle.
In an optional embodiment, the analyzing, by the data acquisition module, the working state of the data acquisition device before the data preprocessing is performed on the raw data includes:
and automatically analyzing the original data, and identifying the working state of the data acquisition equipment and giving an early warning according to the automatic analysis result.
In the embodiment, whether the data acquisition equipment has a fault or not is judged by analyzing the acquired original data, and if the temperature data is 100 ℃, the abnormality of the temperature sensor on the vehicle can be preliminarily judged; if the image data is null, the corresponding camera abnormality on the vehicle can be preliminarily judged; when the data acquisition equipment is abnormal, early warning is sent to a driver.
In another optional embodiment, the data acquisition module periodically sends a test signal to the data acquisition device, and identifies the working state and warns according to a feedback signal of the data acquisition device.
In the embodiment, a test signal is sent to the data acquisition equipment, and then a feedback signal of the data acquisition equipment is analyzed to judge whether the data acquisition equipment has a fault, if the test signal is sent to the ultrasonic sensor, but the feedback signal is not received within a specified time, the abnormality of the ultrasonic sensor can be preliminarily judged; when the data acquisition equipment is abnormal, early warning is sent to a driver.
The two methods for identifying the working state of the data acquisition equipment can be combined for use so as to ensure the stable operation of the data acquisition equipment.
In a preferred embodiment, the data compensation of the ultrasound data by the temperature data comprises:
inputting the temperature data acquired in real time into a compensation mapping curve or a compensation model to acquire compensation data;
and performing data compensation on the ultrasonic data through the compensation data.
In the embodiment, the influence of temperature on the ultrasonic data is considered, before the ultrasonic data is analyzed, data compensation needs to be performed on the ultrasonic data, the external environment temperature (which may influence the work of the ultrasonic sensor) is obtained, and the compensation data can be obtained by combining a compensation mapping curve or a compensation model.
The obtaining of the compensation mapping curve in this embodiment includes:
acquiring standard experimental data; wherein standard experimental data is obtained by a laboratory, including temperature and corresponding ultrasonic error (typically distance);
and (3) acquiring a compensation mapping curve by taking the temperature as an independent variable and the ultrasonic error as a dependent variable and combining a polynomial fitting method, and storing the compensation mapping curve in a data analysis module.
The obtaining of the compensation model in the present application includes:
acquiring standard experimental data;
establishing an artificial intelligence model; the artificial intelligence model comprises a deep convolution neural network model or an RBF neural network model;
and training the artificial intelligence model by taking the temperature as input and the ultrasonic error as output, marking the trained artificial intelligence model as a compensation model, and storing the compensation model in the data analysis module.
In a preferred embodiment, the determination of the position of the obstacle is carried out by analyzing the data-compensated ultrasound data or by analyzing the image data by means of image recognition techniques.
Under the condition of temperature change distance, image data can be analyzed through an image recognition technology to obtain the position of the obstacle; the position of the obstacle can be determined by evaluating the data-compensated ultrasound data in the case of insufficient light.
In an alternative embodiment, combining the ultrasound data and the image data to determine the location of the obstacle comprises:
preliminarily determining an obstacle according to the ultrasonic data, calculating the shortest straight-line distance between the edge of the obstacle and the edge of the vehicle, and marking the distance as a distance I;
preliminarily determining an obstacle according to the image data, calculating the shortest straight-line distance between the edge of the obstacle and the edge of the vehicle, and marking the shortest straight-line distance as a distance II;
and comparing the first distance with the second distance, and determining the position of the obstacle according to the comparison result.
This application both can be through alone through ultrasonic data definite obstacle position, can acquire the obstacle position through image data alone again, considers that ultrasonic data and image data all have different influence data respectively, therefore this embodiment combines together ultrasonic data and image data, and then acquires the obstacle position.
In a specific embodiment, when the absolute value of the distance difference between the first distance and the second distance is smaller than a distance threshold, acquiring the position of an obstacle according to the obstacle corresponding to any one of the first distance and the second distance;
and when the absolute value of the distance difference between the first distance and the second distance is larger than or equal to the distance threshold, selecting the smaller one of the first distance and the second distance as a target distance, and acquiring the position of the obstacle according to the obstacle corresponding to the target distance.
In this embodiment, the first distance obtained by the ultrasonic data is compared with the second distance obtained by the image data, and when the difference between the first distance and the second distance is small enough, both the first distance and the second distance can be used to determine the distance between the vehicle and the obstacle, for example:
the distance I is 1m, the distance II is 1.01m, and the distance threshold value is 0.02 m;
if the absolute value of the distance difference between the first distance and the second distance is smaller than the distance threshold, any one of the first distance and the second distance can be used for judging the state between the vehicle and the obstacle; the distance threshold is set based on practical experience, and in the present illustrative example, an error of 0.02m in the analysis of the distance between the vehicle and the obstacle is not considered.
When the distance difference between the first distance and the second distance is larger, which distance is smaller, the judgment is performed according to which distance, for example:
the distance I is 1m, the distance II is 1.02m, and the distance threshold value is 0.01 m;
if the absolute value of the difference between the first distance and the second distance is greater than the distance threshold, the first distance (small distance) is selected to judge the state between the vehicle and the obstacle, so that the driving feeling is rather influenced, and the occurrence of a collision accident is also avoided.
In a preferred embodiment, the data analysis module performs early warning in conjunction with vehicle size, comprising:
acquiring the position of an obstacle;
the position of the obstacle is combined with the size of the vehicle to carry out all-round early warning on the vehicle; wherein, the all-round early warning includes the safety to all around, top and the bottom of vehicle and carries out the early warning.
This embodiment combines vehicle size and barrier position to carry out all-round early warning, and the key point lies in all judging the vehicle all around, vehicle bottom and roof, realizes the all-round early warning to the vehicle.
It is noted that, under the condition of ensuring that the data acquisition equipment can meet the requirements of precision and range, the data acquisition equipment does not need to be installed at all positions of the vehicle, namely the data acquisition equipment is configured under the double standards of cost and data quality.
The working principle of the invention is as follows:
and acquiring a control instruction through the vehicle-mounted machine system, identifying the control instruction and acquiring original data through data acquisition equipment.
And after data compensation is carried out on ultrasonic data in the original data, the position of the obstacle is determined through the ultrasonic data and/or the image data, and early warning is carried out by combining the size of the vehicle and automatic control of the vehicle is carried out.
Although the present invention has been described in detail with reference to the preferred embodiments, it will be understood by those skilled in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the spirit and scope of the present invention.
Claims (8)
1. The utility model provides a vehicle anticollision system that backs a car based on thing networking, includes data analysis module and data acquisition module, and data analysis module and data acquisition module all set up inside the vehicle, and carry out data interaction, its characterized in that with the car machine system of vehicle:
a data acquisition module: identifying a control instruction, acquiring original data through data acquisition equipment connected with the control instruction, preprocessing the data, and sending the original data to a data analysis module; wherein the raw data comprises ultrasonic data, temperature data and image data;
a data analysis module: acquiring a control instruction through the vehicle-mounted machine system, and sending the control instruction to a data acquisition module; after the ultrasonic data are subjected to data compensation, the position of an obstacle is determined through the ultrasonic data and/or the image data, and early warning is carried out by combining the size of the vehicle and the automatic control of the vehicle is carried out; the automatic control of the vehicle comprises deceleration and braking.
2. The Internet of things-based vehicle reversing anti-collision system according to claim 1, wherein the control command is generated automatically by recognizing the driving state of the vehicle through the vehicle machine system or manually by a driver.
3. The internet of things-based vehicle reversing anti-collision system according to claim 1, wherein the data acquisition module analyzes the working state of the data acquisition device before performing data preprocessing on the raw data, and comprises:
automatically analyzing the original data, identifying the working state of the data acquisition equipment according to the automatic analysis result and early warning; or
The data acquisition module periodically sends a test signal to the data acquisition equipment, and identifies the working state and gives an early warning according to a feedback signal of the data acquisition equipment.
4. The internet of things-based vehicle reversing anti-collision system according to claim 1, wherein the data compensation of the ultrasonic data through the temperature data comprises:
inputting the temperature data acquired in real time into a compensation mapping curve or a compensation model to acquire compensation data; the compensation mapping curve is obtained through a polynomial fitting method, and a compensation model is established based on an artificial intelligence model;
and performing data compensation on the ultrasonic data through the compensation data.
5. The internet of things-based vehicle reversing collision avoidance system according to claim 1, wherein the obstacle position is determined by analyzing the data-compensated ultrasonic data or analyzing the image data by image recognition technology.
6. The internet of things-based vehicle reverse collision avoidance system of claim 1 or 5, wherein combining the ultrasonic data and the image data to determine an obstacle location comprises:
preliminarily determining an obstacle according to the ultrasonic data, calculating the shortest straight-line distance between the edge of the obstacle and the edge of the vehicle, and marking the distance as a distance I;
preliminarily determining an obstacle according to the image data, calculating the shortest straight-line distance between the edge of the obstacle and the edge of the vehicle, and marking the shortest straight-line distance as a distance II;
and comparing the first distance with the second distance, and determining the position of the obstacle according to the comparison result.
7. The Internet of things-based vehicle reversing anti-collision system according to claim 6, wherein when the absolute value of the difference between the first distance and the second distance is smaller than a distance threshold, the position of an obstacle is obtained according to the obstacle corresponding to any one of the first distance and the second distance; wherein, the distance threshold is set according to actual experience;
and when the absolute value of the difference value between the first distance and the second distance is greater than or equal to a distance threshold, selecting the smaller one of the first distance and the second distance as a target distance, and acquiring the position of the obstacle according to the obstacle corresponding to the target distance.
8. The internet of things-based vehicle reversing anti-collision system according to claim 1, wherein the data analysis module performs early warning in combination with vehicle size, and comprises:
acquiring the position of the obstacle;
the position of the obstacle is combined with the size of the vehicle to carry out omnibearing early warning on the vehicle; wherein, the all-round early warning includes the safety to all around, top and the bottom of vehicle and carries out the early warning.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210255242.XA CN114604239A (en) | 2022-03-15 | 2022-03-15 | Vehicle backing anti-collision system based on Internet of things |
| ZA2022/12428A ZA202212428B (en) | 2022-03-15 | 2022-11-15 | Reversing collision-avoidance system based on internet of things for vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210255242.XA CN114604239A (en) | 2022-03-15 | 2022-03-15 | Vehicle backing anti-collision system based on Internet of things |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114604239A true CN114604239A (en) | 2022-06-10 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210255242.XA Pending CN114604239A (en) | 2022-03-15 | 2022-03-15 | Vehicle backing anti-collision system based on Internet of things |
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| CN (1) | CN114604239A (en) |
| ZA (1) | ZA202212428B (en) |
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- 2022-03-15 CN CN202210255242.XA patent/CN114604239A/en active Pending
- 2022-11-15 ZA ZA2022/12428A patent/ZA202212428B/en unknown
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| ZA202212428B (en) | 2023-03-29 |
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