CN115691220A - Backward-coming vehicle anti-collision early warning system and method based on Internet of things - Google Patents
Backward-coming vehicle anti-collision early warning system and method based on Internet of things Download PDFInfo
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Abstract
The invention relates to the technical field of backward coming vehicle anti-collision early warning, in particular to a backward coming vehicle anti-collision early warning system and a method based on the Internet of things, wherein the system comprises a device component module, a millimeter wave radar module, a communication and signal processing mainboard module, a wireless signal action module and a parameter track display module; the device component module is used for setting a device shell component for the backward coming vehicle anti-collision early warning system; the millimeter wave radar module is used for measuring and positioning the space distance and the speed; the communication and signal processing mainboard module is used for receiving and transmitting communication signals and analyzing and processing data transmitted by the millimeter radar module; the wireless signal action module is used for carrying out action response on a wireless signal; and the parameter track display module is used for realizing parameter configuration of the device and graphically displaying the data acquired by the communication and signal processing mainboard module.
Description
Technical Field
The invention relates to the technical field of backward coming vehicle anti-collision early warning, in particular to a backward coming vehicle anti-collision early warning system and a backward coming vehicle anti-collision early warning method based on the Internet of things.
Background
With the continuous development of traffic transportation, in the maintenance construction of highway roads, the collision and scratch events of construction vehicles, maintenance personnel, traffic polices for handling accidents and the like occur, and the serious damage to front operation equipment, casualties and serious injury to rear-end vehicles, drivers and passengers can be caused. The accidents are untimely and arouse the severe situation of the current maintenance safety work, higher standards and requirements are provided for the maintenance safety work, and more effective measures are needed to prevent the maintenance construction accidents.
Disclosure of Invention
The invention aims to provide a backward vehicle collision avoidance early warning system and method based on the Internet of things, and aims to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the utility model provides a backward anticollision early warning system of coming car based on thing networking, includes device subassembly module, millimeter wave radar module, communication and signal processing mainboard module, wireless signal effect module and parameter orbit display module:
the device component module is used for setting a device shell component for a backward coming vehicle anti-collision early warning system;
the millimeter wave radar module is used for measuring and positioning the space distance and the speed;
the communication and signal processing mainboard module is used for receiving and transmitting communication signals and analyzing and processing data transmitted by the millimeter radar module;
the wireless signal action module is used for carrying out action response on a wireless signal;
the parameter track display module is used for realizing parameter configuration of the device and graphically displaying data acquired by the communication and signal processing mainboard module.
The millimeter wave radar module and the communication and signal processing mainboard module are connected with the device component module, namely the millimeter wave radar module and the communication and signal processing mainboard module are arranged in a device shell; the millimeter wave radar module is connected with the communication and signal processing mainboard module through a CAN bus; the communication and signal processing mainboard module is connected with the wireless signal action module through a switching value, and the parameter track display module is connected with the communication and signal processing mainboard module through a Bluetooth signal.
The wireless signal action module comprises a wireless bracelet signal transmitting plate unit and a wireless bracelet alarm unit;
the wireless bracelet signal transmitting board unit is used for transmitting a wireless signal to the wireless bracelet alarm unit when the communication and signal processing main board module transmits the signal;
the wireless bracelet alarm unit is used for receiving wireless signals and triggering the wireless bracelet to perform sound, light and vibration multi-dimensional alarm work. The wireless bracelet alarm unit can remind field workers to avoid danger in time.
The wireless bracelet signal transmitting board unit is connected with the communication and signal processing mainboard module; the wireless bracelet signal transmitting plate is arranged in the device shell; the wireless bracelet signal transmitting plate unit is connected with the wireless bracelet alarm unit.
Further, the device component module comprises a millimeter wave radar antenna housing, a device middle fixing piece, a device rear cover and a vehicle-mounted mounting bracket;
the millimeter wave radar antenna housing and the device rear cover are fixed on the device middle fixing piece;
the middle fixing piece of the device is arranged on the top of the vehicle through a vehicle-mounted mounting bracket;
the millimeter wave radar antenna housing and the device middle fixing piece form a millimeter wave radar assembling space;
a vent hole is formed in the top of the millimeter wave radar antenna housing; the vent hole is used for radar heat dissipation;
the device intermediate fixing piece and the device rear cover form an installation space of the communication and signal processing main board module and the wireless bracelet signal transmitting board unit. The design of the installation space reaches the IP66 protection level, and the condition that dust and rain and snow influence the normal work of the device under the vehicle-mounted environment can be effectively avoided.
Further, the communication and signal processing mainboard module comprises a CAN protocol analysis module, an anti-collision early warning judgment algorithm module, a Bluetooth communication module and a switching value output module;
the CAN protocol analysis module is used for realizing millimeter wave radar signal access, processing the signals and acquiring distance and speed information of a backward coming vehicle target;
the anti-collision early warning judgment algorithm module is used for judging the danger level of a backward coming vehicle target through an algorithm;
the Bluetooth communication module is used for communicating with the WeChat small program through the Bluetooth module;
the switching value output module is used for triggering the work of the indicator light, the wireless bracelet signal transmitting plate unit and the external equipment through the switching value.
A backward vehicle collision avoidance early warning method based on the Internet of things comprises the following analysis steps:
step S1: receiving millimeter wave radar data and analyzing to obtain the position and speed information of a vehicle target;
step S2: determining whether the received same incoming vehicle target data is equal to n 1 If the same incoming vehicle target data is equal to n 1 Calculating the farthest coordinates of the target and three preset coming lane tracks; if the same incoming vehicle target data is not equal to n 1 Turning to the step S3;
and step S3: judging whether the received same incoming vehicle target data is larger than n 2 If the same incoming vehicle target data is less than or equal to n 2 If yes, turning to the step S1 to continue receiving the millimeter wave radar data; if the same incoming vehicle target data is larger than n 2 Judging to collide the dangerous level with the vehicle target by using the absolute value of the deviation and carrying out early warning linkage, and n 2 >n 1 。
Further, the step S1 of receiving millimeter wave radar data and analyzing and obtaining the position and speed information of the vehicle target includes the following analysis steps:
step S1.1: receiving radar data by using a CAN communication interface;
step S1.2: analyzing the data packet, acquiring an incoming vehicle target and extracting a target ID, wherein the target ID is an ID which is allocated by the radar to each detected moving target and is used as a target identifier; the number of the target IDs is more than 0 and less than or equal to 255;
step S1.3: acquiring and storing jth distance data (X) of ith target ID ij ,Y ij ) And velocity data (Vx) ij ,Vy ij ) (ii) a Wherein X ij Abscissa, Y, of jth distance data representing ith object ID ij An ordinate of jth distance data indicating an ith object ID; vx ij A velocity component, vy, in the abscissa direction of the jth velocity data representing the ith object ID ij A velocity component of the jth velocity data indicating the ith object ID in the ordinate direction.
Further, the step S2 of calculating the farthest coordinates of the target and three preset incoming lane tracks includes the following analysis steps:
step S2.1: extracting the first m data of the ith target ID entering the radar monitoring range, and using a formula:
calculating the average Y of the longitudinal distances of the ith target ID i0 And the average value X of the lateral distances i0 Constructing the first coordinate (X) i0 ,Y i0 )；
Step S2.2: acquiring the position of a radar, establishing a two-dimensional rectangular coordinate system according to the position of the radar as a coordinate origin (0, 0), wherein the two-dimensional rectangular coordinate system is a coordinate system parallel to a road surface, the direction of the radar is a y axis, and the direction perpendicular to the radar is an x axis;
in a first coordinate (X) i0 ,Y i0 ) The distance to (D, 0) constructs the trajectory Li of the lane; d = { -D,0, D, }, li = { Li1, li2, li3}, and D represents the road width preset by the system; the track Li refers to a track constructed by a first coordinate corresponding to the ith target ID; li1 denotes a first coordinate (X) i0 ,Y i0 ) The distance to (-d, 0) constructs track one of the left lane, li2 represents the first coordinate (X) i0 ,Y i0 ) The distance to (0, 0) constitutes the second trajectory of the middle lane, li3 denotes the first coordinate (X) i0 ,Y i0 ) Constructing a track three of the right lane by the distance from (d, 0);
using the formula:
(x-D)/(X i0 -D)＝y/Y i0
calculating a corresponding relation between y and x to be a track Li of the corresponding coordinate;
step S2.3: obtaining an absolute value Eij of a deviation from the ith target jth distance data to the trajectory Li based on the trajectory Li, eij = { E1 = ij ,E2 ij ,E3 ij }; the absolute value of the deviation refers to the absolute value of the deviation between the value of the distance in the horizontal direction corresponding to the distance data and the value in the same horizontal direction corresponding to the trajectory Li.
Further, the absolute value of the deviation in step S2.3 comprises the following analysis steps:
obtaining the jth distance data (X) of the ith target ID ij ,Y ij ) Obtaining distance data (X) ij ,Y ij ) The coordinates of the corresponding trajectory Li in the horizontal direction are analog coordinates P ij ，P ij ＝(p xij ,p yij )，P ij ＝{P1 ij ,P2 ij ,P3 ij }，p xij ＝{p1 xij ,p2 xij ,p3 xij }，p yij ＝{p1 yij ,p2 yij ,p3 yij In which P1 ij An analog coordinate P2 representing the output of the ith target ID and the jth distance data corresponding to the track Li1 ij An analog coordinate P3 representing the output of the ith target ID and the jth distance data corresponding to the track Li2 ij Representing the analog coordinate output by the jth distance data corresponding to the locus Li3 of the ith target ID;
wherein p is xij Abscissa, p, representing the corresponding analog coordinate of the jth distance data of the ith object ID yij A vertical coordinate representing the corresponding analog coordinate of the jth distance data of the ith target ID; p1 xij Represents the abscissa, p1, of the output of the trajectory Li1 corresponding to the jth distance data of the ith target ID yij A vertical coordinate representing the output of the locus Li1 corresponding to the jth distance data of the ith target ID;
then p is yij ＝Y ij A 1 is to p yij ＝Y ij Substituting the locus Li to obtain the abscissa p corresponding to the analog coordinate xij ，
Analog coordinate
Using the formula:
calculating the absolute value E of the deviation from the jth distance data of the ith target ID to the track Li Lij ，E Lij ＝{E L1ij ,E L2ij ,E L3ij }；E L1ij Denotes the absolute value of the deviation, E, of the ith target ID, the jth distance data from the trajectory Li1 L2ij Denotes the absolute value of the deviation, E, of the jth distance data of the ith object ID from the trajectory Li2 L3ij Indicating the absolute value of the deviation of the ith target ID and the jth distance data from the trajectory Li 3.
Further, the step S3 of judging the collision danger level of the vehicle target and performing early warning linkage comprises the following analysis steps:
step S3.1: obtaining the first m deviation absolute values of the ith target ID of the track Li corresponding to the current position of the radar, and summing the values to obtain SUM Li ；SUM Li ＝{SUM Li1 ,SUM Li2 ,SUM Li3 }；
Step S3.2: comparison SUM Li1 、SUM Li2 、SUM Li3 Extracting the lane track corresponding to the minimum value, namely judging that the coming vehicle is in the lane;
step S3.3: if the lane of the incoming vehicle is L2, judging the speed danger level according to a preset speed limit threshold value and early warning; if the lane where the incoming vehicle is located is L1 or L3, the danger prompting signal is not output. The position of the radar is used as a middle lane, but the lane where the radar is located in practical application is not limited, if the radar is located on the leftmost side or the rightmost side, the left side or the right side of the radar is a virtual lane, and no vehicle exists; namely, the invention is to indicate the danger early warning judgment when the lane is the same as the radar. Whether the lane where the vehicle is located is the L2 lane or not is analyzed because the L2 lane is a straight line track from the detected position of the target to the position where the radar is located, if the target is judged to be the L2 lane, the fact that the driving direction of the vehicle is the origin where the radar is located is indicated, and the fact that the collision risk exists can be preliminarily judged.
Compared with the prior art, the invention has the following beneficial effects:
1) The structural design of the invention not only considers the heat dissipation requirement of the millimeter wave radar during working, but also considers the waterproof and dustproof requirements of the circuit part, and can meet the normal use in vehicle-mounted environments such as insolation, rain and snow;
2) The invention adopts the long-distance millimeter wave radar to monitor the coming vehicles, can monitor the coming vehicles within the range of 250 meters farthest, and can effectively distinguish the lanes where the coming vehicles are located;
3) According to the invention, a self-adaptive incoming vehicle anti-collision early warning judgment algorithm is adopted, so that a dangerous vehicle can be effectively identified under the condition of not calibrating the lane direction, and danger prompt is carried out through an indicator lamp, a wireless bracelet and external equipment;
4) The invention is provided with the mobile client small program, can carry out parameter configuration on the device through the small program and display the track information of the coming vehicle in real time, and can facilitate the on-site safety management personnel to monitor the coming vehicle in real time and check the effectiveness of the device.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic diagram of a system framework of a backward vehicle collision avoidance early warning system based on the internet of things;
FIG. 2 is a schematic structural diagram of a backward vehicle collision avoidance early warning system based on the Internet of things;
FIG. 3 is a flow chart of a judging method of a backward vehicle collision avoidance early warning method based on the Internet of things;
in the figure: 1. a device housing; 2. a millimeter wave radar; 3. a communication and signal processing mainboard; 4. a wireless bracelet signal transmitting plate; 5. a wireless alarm bracelet; 6. a parameter configuration and trajectory display applet; 11. a millimeter wave antenna radome; 12. a device middle fixing piece; 13. a rear cover of the device; 14. a vehicle-mounted mounting bracket; 15. a vent hole; 16. an LED indicator lamp mounting position; 31. a CAN protocol analysis module; 32. an anti-collision early warning judgment algorithm module; 33. a Bluetooth communication module; 34. and a switching value output module.
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.
Referring to fig. 1-3, the present invention provides a technical solution: the utility model provides a backward come car anticollision early warning system based on thing networking, includes device subassembly module, millimeter wave radar module, communication and signal processing mainboard module, wireless signal effect module and parameter orbit display module:
the device component module is used for setting a device shell component for the backward coming vehicle anti-collision early warning system;
the millimeter wave radar module is used for measuring and positioning the space distance and the speed;
the communication and signal processing mainboard module is used for receiving and transmitting communication signals and analyzing and processing data transmitted by the millimeter radar module;
the wireless signal action module is used for carrying out action response of wireless signals;
the parameter track display module is used for realizing parameter configuration of the device and graphically displaying data acquired by the communication and signal processing mainboard module.
The millimeter wave radar module and the communication and signal processing mainboard module are connected with the device component module, namely the millimeter wave radar module and the communication and signal processing mainboard module are arranged in a device shell; the millimeter wave radar module is connected with the communication and signal processing mainboard module through a CAN bus; the communication and signal processing mainboard module is connected with the wireless signal action module through a switching value, and the parameter track display module is connected with the communication and signal processing mainboard module through a Bluetooth signal.
The millimeter wave radar in the millimeter wave radar module adopts a long-distance millimeter wave radar, can monitor the coming vehicle within the range of 250m, and can effectively distinguish the lane where the coming vehicle is located. The communication and signal processing mainboard module is provided with 3 switching value output interfaces, 1 CAN bus communication interface, 1 485 communication interface and 2 LED control interfaces.
The wireless signal action module comprises a wireless bracelet signal transmitting plate unit and a wireless bracelet alarm unit;
the wireless bracelet signal transmitting board unit is used for transmitting a wireless signal to the wireless bracelet alarm unit when the communication and signal processing main board module transmits the signal;
the wireless bracelet alarm unit is used for receiving wireless signals and triggering the wireless bracelet to carry out sound, light and vibration multidimensional alarm work. The wireless bracelet alarm unit can remind field workers to avoid danger in time.
The wireless bracelet signal transmitting board unit is connected with the communication and signal processing mainboard module; the wireless bracelet signal transmitting plate is arranged in the device shell; the wireless bracelet signal transmitting plate unit is connected with the wireless bracelet alarm unit.
Wireless bracelet signal emission board unit passes through 433MHz radio signal and wireless bracelet communication connection.
As shown in example fig. 1: a backward coming vehicle anti-collision early warning system comprises a device shell 1, a millimeter wave radar 2, a communication and signal processing mainboard 3, a wireless bracelet signal transmitting plate 4, a wireless alarm bracelet 5 and a parameter configuration and track display small program 6; the millimeter wave radar 2, the communication and signal processing mainboard 3 and the wireless bracelet signal transmitting board 4 are arranged in the device shell 1; the millimeter wave radar 2 is connected with the communication and signal processing mainboard 3 through a CAN bus; the communication and signal processing mainboard 3 is connected with the wireless bracelet signal transmitting board 4 through a switching value; the wireless bracelet signal transmitting plate 4 is communicated with the wireless bracelet 5 through 433MHz wireless signals; the wireless bracelet 5 has sound, light and vibration functions and can remind field workers to avoid danger in time; the parameter configuration and trajectory display applet 6 communicates with the communication and signal processing motherboard 3 via bluetooth signals.
As shown in fig. 2: the device component module comprises a millimeter wave radar antenna housing 11, a device middle fixing piece 12, a device rear cover 13 and a vehicle-mounted mounting bracket 14;
the millimeter wave radar antenna cover 11 and the device rear cover 13 are fixed on the device middle fixing piece 12;
the device middle fixing piece 12 is arranged on the top of the vehicle through a vehicle-mounted mounting bracket 14;
the millimeter wave radar antenna housing 11 and the device middle fixing piece 12 form a millimeter wave radar assembling space;
a vent hole 15 is formed in the top of the millimeter wave radar antenna housing 11; the vent hole is used for radar heat dissipation;
two LED indicator lamp mounting positions 16 are arranged at the front part of the millimeter wave radar antenna housing 11 and are used for indicating the working state of the device;
the device middle fixing piece 12 and the device rear cover 13 form an installation space of the communication and signal processing mainboard 3 and the wireless bracelet signal transmitting board 4. The design of the installation space reaches the IP66 protection level, and the condition that dust and rain and snow influence the normal work of the device under the vehicle-mounted environment can be effectively avoided.
The communication and signal processing mainboard 3 comprises a CAN protocol analysis module 31, an anti-collision early warning judgment algorithm module 32, a Bluetooth communication module 33 and a switching value output module 34;
the CAN protocol analysis module is used for realizing millimeter wave radar 2 signal access, processing the signals and acquiring the distance and speed information of a backward coming vehicle target;
the anti-collision early warning judgment algorithm module 32 is used for judging the danger level of the backward coming vehicle target through an algorithm;
the Bluetooth communication module 33 is used for communicating with the WeChat applet 6 through the Bluetooth module;
the switching value output module 34 is used for triggering the operation of the indicator light, the wireless bracelet signal transmitting plate 4 unit and the external device through the switching value.
A backward coming vehicle anti-collision early warning method based on the Internet of things comprises the following analysis steps:
step S1: receiving millimeter wave radar data and analyzing to obtain the position and speed information of a vehicle target;
step S2: determining whether the received same incoming vehicle target data is equal to n 1 If the same incoming vehicle target data is equal to n 1 Calculating the farthest coordinates of the target and three preset incoming lane tracks; if the same incoming vehicle target data is not equal to n 1 Turning to the step S3;
and step S3: judging whether the received same incoming vehicle target data is larger than n 2 If the same incoming vehicle target data is less than or equal to n 2 If yes, turning to the step S1 to continue receiving the millimeter wave radar data; if the same incoming vehicle target data is larger than n 2 Judging to collide the dangerous level with the vehicle target by using the absolute value of the deviation and carrying out early warning linkage, and n 2 >n 1 . N can be set in the invention by statistical analysis of data 1 ＝10，n 2 ＝20。
In the step S1, millimeter wave radar data is received and analyzed to obtain the position and speed information of the vehicle target, and the method comprises the following analysis steps:
step S1.1: receiving radar data by using a CAN communication interface;
step S1.2: analyzing the data packet, acquiring an incoming vehicle target and extracting a target ID, wherein the target ID is an ID which is allocated by the radar to each detected moving target and is used as a target identifier; the number of the target IDs is more than 0 and less than or equal to 255;
step S1.3: acquiring and storing jth distance data (X) of ith target ID ij ,Y ij ) And velocity data (Vx) ij ,Vy ij ) (ii) a Wherein X ij Abscissa, Y, of jth distance data representing ith object ID ij A vertical coordinate of jth distance data indicating an ith object ID; vx ij A velocity component, vy, in the abscissa direction of the jth velocity data representing the ith object ID ij A velocity component of the jth velocity data indicating the ith object ID in the ordinate direction. Since the distance and velocity data will be detected by the radar every 50ms over time after the same target enters the surveillance area.
In the step S2, the farthest coordinates of the target and three preset coming lane tracks are calculated, and the method comprises the following analysis steps:
step S2.1: extracting the first m data of the ith target ID entering the radar monitoring range, and using a formula:
calculating the average Y of the longitudinal distances of the ith target ID i0 And the average value X of the lateral distance i0 Constructing the first coordinate (X) i0 ,Y i0 ) (ii) a In practical application, m is 10;
step S2.2: acquiring the position of a radar, establishing a two-dimensional rectangular coordinate system according to the position of the radar as a coordinate origin (0, 0), wherein the two-dimensional rectangular coordinate system is a coordinate system parallel to a road surface, the direction of the radar is a y axis, and the direction perpendicular to the radar is an x axis;
in the first coordinate (X) i0 ,Y i0 ) The distance to (D, 0) constructs the trajectory Li of the lane; d = { -D,0,d, }, li = { Li1, li2,li3, and d represents the road width preset by the system; the track Li refers to a track constructed by a first coordinate corresponding to the ith target ID; li1 denotes a first coordinate (X) i0 ,Y i0 ) The distance to (-d, 0) constructs track one of the left lane, li2 denotes the first coordinate (X) i0 ,Y i0 ) The distance to (0, 0) constitutes the second trajectory of the middle lane, li3 denotes the first coordinate (X) i0 ,Y i0 ) Constructing a track three of the right lane by the distance from (d, 0); d can be set according to the width of each lane in the road in practical application;
using the formula:
(x-D)/(X i0 -D)＝y/Y i0
calculating a corresponding relation between y and x to be a track Li of the corresponding coordinate;
step S2.3: obtaining an absolute value Eij of a deviation from the ith target jth distance data to the trajectory Li based on the trajectory Li, eij = { E1 = ij ,E2 ij ,E3 ij }; the absolute value of the deviation refers to the absolute value of the deviation of the distance value in the horizontal direction corresponding to the distance data and the value in the same horizontal direction corresponding to the trajectory Li.
If L1 is the first coordinate (X) i0 ,Y i0 ) To (-d, 0): y = [ Y) i0 /(X i0 +d)]x+[(Y i0 *d)/(X i0 +d)]；
The absolute value of the deviation in step S2.3 comprises the following analysis steps:
obtaining the jth distance data (X) of the ith target ID ij ,Y ij ) Obtaining distance data (X) ij ,Y ij ) The coordinates corresponding to the trajectory Li in the horizontal direction are analog coordinates P ij ，P ij ＝(p xij ,p yij )，P ij ＝{P1 ij ,P2 ij ,P3 ij }，p xij ＝{p1 xij ,p2 xij ,p3 xij }，p yij ＝{p1 yij ,p2 yij ,p3 yij In which P1 ij Represents the analog coordinate P2 output by the locus Li1 corresponding to the jth distance data of the ith target ID ij An analog coordinate P3 representing the output of the ith target ID and the jth distance data corresponding to the track Li2 ij Representing the analog coordinate output by the jth distance data corresponding to the locus Li3 of the ith target ID;
wherein p is xij Abscissa, p, representing the corresponding analog coordinate of the jth distance data of the ith object ID yij A vertical coordinate representing the corresponding analog coordinate of the jth distance data of the ith target ID; p1 xij Represents the abscissa, p1, of the output of the trajectory Li1 corresponding to the jth distance data of the ith target ID yij The ordinate of the output of the locus Li1 corresponding to the jth distance data of the ith target ID is shown, and other coordinates are the same;
because the ordinate, which exists in the same horizontal direction as the distance data, is the same when the distance data is determined;
then p is yij ＝Y ij A 1 is to p yij ＝Y ij Substituting the trajectory Li to obtain the abscissa p corresponding to the analog coordinate xij ，
Analog coordinate
Using the formula:
calculating the absolute value E of the deviation from the jth distance data of the ith target ID to the track Li Lij ，E Lij ＝{E L1ij ,E L2ij ,E L3ij }；E L1ij Represents the ith target ID, the jth distance data to the trackAbsolute value of deviation of Li1, E L2ij Denotes the absolute value of the deviation, E, of the jth distance data of the ith object ID from the trajectory Li2 L3ij Indicating the absolute value of the deviation of the ith target ID and the jth distance data from the trajectory Li 3.
As shown in the examples:
when the trajectory is L1, the corresponding deviation distance is
The corresponding offset distance is L2 when the trajectory is L2
The corresponding offset distance is L3 when the trajectory is
If it is the first coordinate (X) i0 ,Y i0 ) =0, 10, D =5,
then L1: y =2x +10; l2: x =0; l3: y = -2x +10;
current distance data (X) ij ,Y ij ) (= (-2.5,6)), the analog coordinate on the corresponding trajectory L1 is (-2,6); the analog coordinates on the corresponding trajectory L2 are (0, 6); the analog coordinates on the corresponding trajectory L3 are (2, 6);
the absolute value of the deviation from the trajectory L1 is | -2.5- (-2) | =0.5; the absolute value of the deviation from the trajectory L2 is | -2.5-0| =2.5; the absolute value of the deviation from the trajectory L3 is | -2.5-2| =4.5.
And step S3, judging the collision danger level of the vehicle target and early warning linkage, wherein the method comprises the following analysis steps:
step S3.1: obtaining the first m deviation absolute values of the ith target ID of the track Li corresponding to the current position of the radar, and summing the values to obtain SUM Li ；SUM Li ＝{SUM Li1 ,SUM Li2 ,SUM Li3 }；
Step S3.2: comparing SUMs Li1 、SUM Li2 、SUM Li3 Extracting the lane track corresponding to the minimum value, namely judging that the coming vehicle is in the lane;
step S3.3: if the lane of the incoming vehicle is L2, judging the speed danger level according to a preset speed limit threshold value and early warning; if the lane where the incoming vehicle is located is L1 or L3, the danger prompting signal is not output. The position of the radar is used as a middle lane, but the lane where the radar is located in practical application is not limited, if the radar is located on the leftmost side or the rightmost side, the left side or the right side of the radar is used as a virtual lane, and no vehicle exists; namely, the invention is to indicate the danger early warning judgment when the lane is the same as the radar; if the speed limit is 50km/h, if the coming vehicle is 20km/h, the danger level is determined as no danger, and no alarm is given. Whether the lane where the vehicle is located is the L2 lane or not is analyzed because the L2 lane is a straight line track from the detected position of the target to the position where the radar is located, if the target is judged to be the L2 lane, the fact that the driving direction of the vehicle is the origin where the radar is located is indicated, and the fact that the collision risk exists can be preliminarily judged.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The utility model provides a backward anticollision early warning system of coming car based on thing networking which characterized in that, includes device subassembly module, millimeter wave radar module, communication and signal processing mainboard module, wireless signal effect module and parameter orbit display module:
the device component module is used for setting a device shell component for a backward coming vehicle anti-collision early warning system;
the millimeter wave radar module is used for measuring and positioning spatial distance and speed;
the communication and signal processing mainboard module is used for receiving and transmitting communication signals and analyzing and processing data transmitted by the millimeter radar module;
the wireless signal action module is used for carrying out action response of wireless signals;
the parameter track display module is used for realizing parameter configuration of the device and graphically displaying the data acquired by the communication and signal processing mainboard module.
2. The internet of things-based backward vehicle collision avoidance early warning system according to claim 1, characterized in that: the wireless signal action module comprises a wireless bracelet signal transmitting plate unit and a wireless bracelet alarm unit;
the wireless bracelet signal transmitting board unit is used for transmitting a wireless signal to the wireless bracelet alarm unit when the communication and signal processing main board module transmits the signal;
the wireless bracelet alarm unit is used for receiving the wireless signals and triggering the wireless bracelet to carry out sound, light and vibration multi-dimensional alarm work.
3. The internet of things-based backward vehicle collision avoidance early warning system according to claim 2, characterized in that: the device component module comprises a millimeter wave radar antenna housing, a device middle fixing piece, a device rear cover and a vehicle-mounted mounting bracket;
the millimeter wave radar antenna cover and the device rear cover are fixed on the device middle fixing piece;
the middle fixing piece of the device is arranged on the top of the vehicle through a vehicle-mounted mounting bracket;
the millimeter wave radar antenna housing and the device middle fixing piece form a millimeter wave radar assembling space;
a vent hole is formed in the top of the millimeter wave radar antenna housing; the vent hole is used for radar heat dissipation;
the device middle fixing piece and the device rear cover form an installation space of the communication and signal processing mainboard module and the wireless bracelet signal transmitting board unit.
4. The internet of things-based backward vehicle collision avoidance early warning system according to claim 2, characterized in that: the communication and signal processing mainboard module comprises a CAN protocol analysis module, an anti-collision early warning judgment algorithm module, a Bluetooth communication module and a switching value output module;
the CAN protocol analysis module is used for realizing millimeter wave radar signal access, processing the signals and acquiring the distance and speed information of a backward coming vehicle target;
the anti-collision early warning judgment algorithm module is used for judging the danger level of a backward coming vehicle target through an algorithm;
the Bluetooth communication module is used for communicating with the WeChat small program through the Bluetooth module;
the switching value output module is used for triggering the work of the indicator lamp, the wireless bracelet signal transmitting plate unit and the external equipment through the switching value.
5. The backward coming vehicle anti-collision early warning method based on the internet of things, which is applied to the backward coming vehicle anti-collision early warning system based on the internet of things as claimed in any one of claims 1 to 4, is characterized by comprising the following analysis steps:
step S1: receiving millimeter wave radar data and analyzing to obtain the position and speed information of a vehicle target;
step S2: determining whether the received same incoming vehicle target data is equal to n 1 If the same incoming vehicle target data is equal to n 1 Calculating the farthest coordinates of the target and three preset incoming lane tracks; if the same incoming vehicle target data is not equal to n 1 Turning to the step S3;
and step S3: judging whether the received same incoming vehicle target data is larger than n 2 If the same incoming vehicle target data is less than or equal to n 2 If yes, turning to the step S1 to continue receiving the millimeter wave radar data; if the same incoming vehicle target data is larger than n 2 Judging to collide the dangerous level with the vehicle target by using the absolute value of the deviation and carrying out early warning linkage, and n 2 >n 1 。
6. The internet of things-based backward vehicle collision avoidance early warning method according to claim 5, wherein: in the step S1, the millimeter wave radar data is received and analyzed to obtain the vehicle target position and speed information, and the method includes the following analysis steps:
step S1.1: receiving radar data by using a CAN communication interface;
step S1.2: analyzing the data packet, acquiring an incoming vehicle target and extracting a target ID, wherein the target ID is an ID which is allocated by the radar to each detected moving target and is used as a target identifier; the number of the target IDs is greater than 0 and less than or equal to 255;
step S1.3: acquiring and storing jth distance data (X) of ith object ID ij ,Y ij ) And velocity data (Vx) ij ,Vy ij ) (ii) a Wherein X ij Abscissa, Y, of jth distance data representing ith object ID ij An ordinate of jth distance data indicating an ith object ID; vx ij A velocity component, vy, in the abscissa direction of the jth velocity data representing the ith object ID ij A velocity component of the jth velocity data indicating the ith object ID in the ordinate direction.
7. The internet of things-based backward vehicle collision avoidance early warning method according to claim 6, wherein: the step S2 of calculating the farthest coordinates of the target and three preset incoming lane tracks comprises the following analysis steps:
step S2.1: extracting the first m data of the ith target ID entering the radar monitoring range, and using a formula:
calculating the average Y of the longitudinal distances of the ith target ID i0 And the average value X of the lateral distance i0 Constructing the first coordinate (X) i0 ,Y i0 )；
Step S2.2: acquiring the position of a radar, establishing a two-dimensional rectangular coordinate system according to the position of the radar as a coordinate origin (0, 0), wherein the two-dimensional rectangular coordinate system is a coordinate system parallel to a road surface, the direction of the radar is a y axis, and the direction perpendicular to the radar is an x axis;
in a first coordinate (X) i0 ,Y i0 ) The distance to (D, 0) constructs the trajectory Li of the lane; d = { -D,0, D, }, li = { Li1, li2, li3}, and D represents the road width preset by the system; the track Li refers to a track constructed by a first coordinate corresponding to the ith target ID; the Li1 represents a first coordinate (X) i0 ,Y i0 ) The distance to (-d, 0) constructs track one of the left lane, and Li2 represents the first coordinate (X) i0 ,Y i0 ) The distance to (0, 0) constitutes the second trajectory of the middle lane, li3 representing the first coordinate (X) i0 ,Y i0 ) The distance to (d, 0) constructs a third trajectory for the right lane;
using the formula:
(x-D)/(X i0 -D)＝y/Y i0
calculating a corresponding relation between y and x to obtain a track Li of a corresponding coordinate;
step S2.3: obtaining an absolute value Eij of a deviation from the ith target jth distance data to the trajectory Li based on the trajectory Li, eij = { E1 = ij ,E2 ij ,E3 ij }; the absolute value of the deviation refers to the absolute value of the deviation between the distance value in the horizontal direction corresponding to the distance data and the value in the same horizontal direction corresponding to the track Li.
8. The internet of things-based backward vehicle collision avoidance early warning method according to claim 7, wherein: the absolute value of the deviation in step S2.3 comprises the following analysis steps:
obtaining the jth distance data (X) of the ith target ID ij ,Y ij ) Obtaining distance data (X) ij ,Y ij ) The coordinates of the corresponding trajectory Li in the horizontal direction are analog coordinates P ij ，P ij ＝(p xij ,p yij )，P ij ＝{P1 ij ,P2 ij ,P3 ij }，p xij ＝{p1 xij ,p2 xij ,p3 xij }，p yij ＝{p1 yij ,p2 yij ,p3 yij In which P1 ij An analog coordinate P2 representing the output of the ith target ID and the jth distance data corresponding to the track Li1 ij An analog coordinate P3 representing the output of the ith target ID and the jth distance data corresponding to the track Li2 ij Representing the analog coordinate output by the jth distance data corresponding to the ith target ID and the jth track Li 3;
wherein p is xij Abscissa, p, representing the corresponding analog coordinate of the jth distance data of the ith object ID yij A vertical coordinate representing the corresponding analog coordinate of the jth distance data of the ith target ID; p1 xij Represents the abscissa, p1, of the output of the trajectory Li1 corresponding to the jth distance data of the ith target ID yij A vertical coordinate representing the output of the locus Li1 corresponding to the jth distance data of the ith target ID;
due to p yij ＝Y ij Let p be yij ＝Y ij Substituting the trajectory Li to obtain the abscissa p corresponding to the analog coordinate xij ，
Then the analog coordinate
Using the formula:
calculating the absolute value E of the deviation from the jth distance data of the ith target ID to the track Li Lij ，E Lij ＝{E L1ij ,E L2ij ,E L3ij }；E L1ij Denotes the absolute value of the deviation, E, of the ith target ID, the jth distance data from the trajectory Li1 L2ij Denotes the absolute value of the deviation, E, of the jth distance data of the ith object ID from the trajectory Li2 L3ij Indicating the absolute value of the deviation of the ith target ID and the jth distance data from the trajectory Li 3.
9. The internet of things-based backward vehicle collision avoidance early warning method according to claim 8, wherein: the step S3 of judging the collision danger level of the vehicle target and early warning linkage comprises the following analysis steps:
step S3.1: obtaining the first m deviation absolute values of the ith target ID of the track Li corresponding to the current position of the radar, and summing to obtain SUM Li ；SUM Li ＝{SUM Li1 ,SUM Li2 ,SUM Li3 }；
Step S3.2: comparison SUM Li1 、SUM Li2 、SUM Li3 Extracting the lane track corresponding to the minimum value, namely judging that the coming vehicle is in the lane;
step S3.3: if the lane of the incoming vehicle is L2, judging the speed danger level according to a preset speed limit threshold value and early warning; if the lane where the incoming vehicle is located is L1 or L3, the danger prompting signal is not output.
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