CN116311592A - AI collision vehicle event data recorder adopting inertial sensing technology - Google Patents
AI collision vehicle event data recorder adopting inertial sensing technology Download PDFInfo
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- CN116311592A CN116311592A CN202310335929.9A CN202310335929A CN116311592A CN 116311592 A CN116311592 A CN 116311592A CN 202310335929 A CN202310335929 A CN 202310335929A CN 116311592 A CN116311592 A CN 116311592A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0816—Indicating performance data, e.g. occurrence of a malfunction
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0841—Registering performance data
- G07C5/085—Registering performance data using electronic data carriers
- G07C5/0866—Registering performance data using electronic data carriers the electronic data carrier being a digital video recorder in combination with video camera
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Abstract
The invention discloses an AI collision vehicle recorder adopting an inertial sensing technology, which comprises a central control module, a power module, a WIFI module, a 4G communication module, a TF storage module and a data acquisition module, wherein the data acquisition module is electrically connected with an inertial sensor; providing evidence when traffic accidents happen through the functions of video recording and wireless transmission of video data; through the safety monitoring function, the driving life is recorded, and the vehicle is prevented from being stolen; through the auxiliary navigation function, the distance recognition can be carried out on the obstacles around the vehicle or the vehicle; through traffic collision accident recognition function and dangerous driving accident recognition function, can realize the emergence of intelligent identification traffic accident, send early warning information to the rescue backstage voluntarily when taking place the accident, improved the intellectuality of record appearance.
Description
Technical Field
The invention relates to the field of automobile data recorders, in particular to an AI collision automobile data recorder adopting an inertial sensing technology.
Background
AI collides vehicle event data recorder, as on-vehicle electronic product, uses in car driving auxiliary field, along with the continuous development of scientific and technological level, is higher and higher to its function requirement, so design an intelligent, comprehensive function's vehicle event data recorder is imperative.
Disclosure of Invention
The invention aims to overcome the defects and provides an AI collision vehicle recorder adopting an inertial sensing technology.
The invention realizes the above purpose through the following technical scheme:
an AI collision vehicle recorder adopting an inertial sensing technology comprises a central control module, a power module, a WIFI module, a 4G communication module, a TF storage module and a data acquisition module, wherein the data acquisition module is electrically connected with an inertial sensor;
the central control module comprises the following functions:
i, recording video, namely recording and circularly updating road surface conditions in front of, in and around the automobile through digital video, wherein information data comprise recording in-automobile recordings, acceleration, steering, braking and the like of the automobile so as to be used for investigating traffic accident responsibility;
II, wirelessly transmitting video data, and providing evidence recording materials by a recorder when traffic accidents such as rear-end collision, injury and pedestrians are caused by vehicle collision and illegal overtaking, and playing back pictures through a WIFI network and a mobile phone carrier;
III, auxiliary navigation, namely judging the distances between the vehicle and various obstacles in front of, behind and around through an AI video/image recognition algorithm;
IV, safety monitoring, namely monitoring the conditions of the vehicle at the moment by a vehicle recorder, and providing clues for recovering the stolen vehicle by shooting the conditions inside and outside the vehicle through instructions when the vehicle is lost by combining with remote network control;
v, identifying traffic collision accidents;
VI, dangerous driving accident identification;
VII, normal driving identification;
the working steps of the function V are as follows:
step one: any single shaft of the inertial sensor is perpendicular to the advancing direction of the vehicle;
step two: distinguishing a vertical axis from the other two axes according to the three-axis readings;
step three: calculating the installation angle of the equipment according to the triaxial reading, establishing a carrier coordinate system and establishing a rotation matrix;
step four: converting the original data into a carrier coordinate system reading by using a rotation matrix, wherein an x-axis is along the movement direction of the carrier, a z-axis is upward, and a y-axis is vertical to the x and z;
step five: stationary reading = uniform linear motion = (x ≡0, y ≡0, z approximately equal to 980), and x 2 +y2+z2≈980 2 980 is the gravitational acceleration;
step six: a carrier coordinate system reading (x, y, z), the change in the reading representing acceleration of the carrier due to the opposite force;
step seven: designing a normal driving threshold, a dangerous driving threshold and a collision threshold;
step eight: judging whether collision occurs or not, judging whether the stress in any direction exceeds a collision threshold or not or judging whether the resultant force exceeds the collision threshold, if so, entering the next step, and if not, entering the step of circularly recording data;
step nine: further judging whether collision occurs or not, carrying out continuous N times of sampling data, judging, entering the next step if the continuous N times of sampling data exceed a collision threshold value, and entering the step of circularly recording data if the continuous N times of sampling data do not exceed the collision threshold value;
step ten: judging whether the vehicle is stationary or not, sampling and judging according to collision threshold values in the step eight and the step nine, if the vehicle needs to be stationary, stopping the vehicle, reporting an accident at the same time, and if the vehicle does not need to be stationary, entering a step of clearing cycle information;
the step of circularly recording data and the step of clearing period information enter an inertial sensor original reading resetting step, and enter a step two for circulation after the inertial sensor original reading resetting step is executed, so that the next collision threshold measurement judgment is accurate.
Preferably, the central control module is further electrically connected with a key module, a display module and a debugging module, the key module is electrically connected with keys of the recorder, a user presses the corresponding keys, and the key module acquires corresponding data and transmits the corresponding data to the central control module; the display module is electrically connected with a display screen of the recorder, and the central control module sends a corresponding display instruction, and the display instruction is decoded by the display module and then sent to the display screen for video indication; the debugging module is used for connecting the MCU in the central control module when software is input or debugged.
Preferably, in the seventh step, the design values of the normal driving threshold, the dangerous driving threshold and the collision threshold are obtained through a collision test and an acceleration test.
Preferably, in the function vi, the collision threshold is changed to a dangerous driving threshold, so that dangerous driving threshold judgment can be performed, and dangerous driving accident recognition is realized.
Preferably, in the function vii, the collision threshold is changed to a normal running threshold, so that the normal running threshold can be judged, and normal driving recognition is realized.
Preferably, the inertial sensor is model SC7a20, and SC7a20 is a 3-axis accelerometer of an LGA package with extremely small volume, ultra low power consumption and digital output. The complete circuit chip comprises a mechanical sensing unit and an integrated circuit interface. An integrated circuit interface for interfacing with the mechanical sensing unit, reading its sensor information, and passing through I 2 The C/SPI interface is provided for an external MCU, so that the workload of the MCU is greatly reduced, and the running stability of the device is improved.
The beneficial effects of the invention are as follows: the AI collision vehicle event data recorder adopting the inertia sensing technology comprises:
1. video recording can be performed, so that porcelain collision is prevented;
2. providing evidence when traffic accidents happen through the functions of video recording and wireless transmission of video data;
3. through the safety monitoring function, the driving life is recorded, and the vehicle is prevented from being stolen;
4. through the auxiliary navigation function, the distance recognition can be carried out on the obstacles around the vehicle or the vehicle;
5. through traffic collision accident recognition function and dangerous driving accident recognition function, can realize the emergence of intelligent identification traffic accident, send early warning information to the rescue backstage voluntarily when taking place the accident, improved the intellectuality of record appearance.
Drawings
The invention will now be described by way of example and with reference to the accompanying drawings in which:
FIG. 1 is a schematic diagram of a system of the present invention;
fig. 2 is a logic schematic diagram of the traffic collision accident recognition function of the present invention.
Detailed Description
The invention will now be described in further detail with reference to the accompanying drawings. The drawings are simplified schematic representations which merely illustrate the basic structure of the invention and therefore show only the structures which are relevant to the invention.
As shown in fig. 1, an AI collision vehicle recorder adopting an inertial sensing technology comprises a central control module 1, a power supply module 2, a WIFI module 6, a 4G communication module 7, a TF storage module 8 and a data acquisition module 9, wherein the data acquisition module 9 is electrically connected with an inertial sensor 10, the central control module 1 is also electrically connected with a key module 3, a display module 4 and a debugging module 5, the key module 3 is electrically connected with keys of the recorder, a user presses corresponding keys, and the key module 3 acquires corresponding data and transmits the corresponding data to the central control module 1; the display module 4 is electrically connected with a display screen of the recorder, and the central control module 1 sends a corresponding display instruction, and the display instruction is decoded by the display module 4 and then sent to the display screen for video indication; the debugging module 5 is used for connecting the MCU in the central control module 1 when software is recorded or debugged.
As shown in fig. 2, the central control module 1 includes the following functions:
i, recording video, namely recording and circularly updating road surface conditions in front of, in and around the automobile through digital video, wherein information data comprise recording in-automobile recordings, acceleration, steering, braking and the like of the automobile so as to be used for investigating traffic accident responsibility;
II, wirelessly transmitting video data, and providing evidence recording materials by a recorder when traffic accidents such as rear-end collision, injury and pedestrians are caused by vehicle collision and illegal overtaking, and playing back pictures through a WIFI network and a mobile phone carrier;
III, auxiliary navigation, namely judging the distances between the vehicle and various obstacles in front of, behind and around through an AI video/image recognition algorithm;
IV, safety monitoring, namely monitoring the conditions of the vehicle at the moment by a vehicle recorder, and providing clues for recovering the stolen vehicle by shooting the conditions inside and outside the vehicle through instructions when the vehicle is lost by combining with remote network control;
v, identifying traffic collision accidents;
VI, dangerous driving accident identification, namely, changing a collision threshold into a dangerous driving threshold, and judging the dangerous driving threshold to realize dangerous driving accident identification;
VII, normal driving identification, namely, changing a collision threshold value into a normal driving threshold value, and judging the normal driving threshold value to realize normal driving identification;
the working steps of the function V are as follows:
step one: any one of the single axes of the inertial sensor 10 is perpendicular to the vehicle advancing direction;
step two: distinguishing a vertical axis from the other two axes according to the three-axis readings;
step three: calculating the installation angle of the equipment according to the triaxial reading, establishing a carrier coordinate system and establishing a rotation matrix;
step four: converting the original data into a carrier coordinate system reading by using a rotation matrix, wherein an x-axis is along the movement direction of the carrier, a z-axis is upward, and a y-axis is vertical to the x and z;
step five: stationary reading = uniform linear motion = (x ≡0, y ≡0, z approximately equal to 980), and x 2 +y2+z2≈980 2 980 is the gravitational acceleration;
step six: a carrier coordinate system reading (x, y, z), the change in the reading representing acceleration of the carrier due to the opposite force;
step seven: designing a normal driving threshold, a dangerous driving threshold and a collision threshold;
step eight: judging whether collision occurs or not, judging whether the stress in any direction exceeds a collision threshold or not or judging whether the resultant force exceeds the collision threshold, if so, entering the next step, and if not, entering the step of circularly recording data;
step nine: further judging whether collision occurs or not, carrying out continuous N times of sampling data, judging, entering the next step if the continuous N times of sampling data exceed a collision threshold value, and entering the step of circularly recording data if the continuous N times of sampling data do not exceed the collision threshold value;
step ten: judging whether the vehicle is stationary or not, sampling and judging according to collision threshold values in the step eight and the step nine, if the vehicle needs to be stationary, stopping the vehicle, reporting an accident at the same time, and if the vehicle does not need to be stationary, entering a step of clearing cycle information;
the step of circularly recording data and the step of clearing period information both enter the step of resetting the original reading of the inertial sensor 10, and enter the step two for circulation after the step of resetting the original reading of the inertial sensor 10 is completed, so as to ensure that the next collision threshold measurement judgment is accurate.
As a specific embodiment, in the seventh step, the design values of the normal driving threshold, the dangerous driving threshold, and the collision threshold are obtained through a collision test and an acceleration test.
As a specific example, the inertial sensor 10 is of the model SC7A20, and the model SC7A20 is a 3-axis accelerometer of an LGA package with extremely small volume, ultra low power consumption and digital output. The complete circuit chip comprises a mechanical sensing unit and an integrated circuit interface. An integrated circuit interface for interfacing with the mechanical sensing unit, reading its sensor information, and passing through I 2 The C/SPI interface is provided for an external MCU, so that the workload of the MCU is greatly reduced, and the running stability of the device is improved.
The present invention has been made in view of the above-described circumstances, and it is an object of the present invention to provide a portable electronic device capable of performing various changes and modifications without departing from the scope of the technical spirit of the present invention. The technical scope of the present invention is not limited to the description, but must be determined according to the scope of claims.
Claims (6)
1. An AI collision vehicle event data recorder of inertial sensing technique, its characterized in that: the intelligent monitoring system comprises a central control module, a power module, a WIFI module, a 4G communication module, a TF storage module and a data acquisition module, wherein the data acquisition module is electrically connected with an inertial sensor;
the central control module comprises the following functions:
i, recording video, namely recording and circularly updating road surface conditions in front of, in and around the automobile through digital video, wherein information data comprise recording in-automobile recordings, acceleration, steering, braking and the like of the automobile so as to be used for investigating traffic accident responsibility;
II, wirelessly transmitting video data, and providing evidence recording materials by a recorder when traffic accidents such as rear-end collision, injury and pedestrians are caused by vehicle collision and illegal overtaking, and playing back pictures through a WIFI network and a mobile phone carrier;
III, auxiliary navigation, namely judging the distances between the vehicle and various obstacles in front of, behind and around through an AI video/image recognition algorithm;
IV, safety monitoring, namely monitoring the conditions of the vehicle at the moment by a vehicle recorder, and providing clues for recovering the stolen vehicle by shooting the conditions inside and outside the vehicle through instructions when the vehicle is lost by combining with remote network control;
v, identifying traffic collision accidents;
VI, dangerous driving accident identification;
VII, normal driving identification;
the working steps of the function V are as follows:
step one: any single shaft of the inertial sensor is perpendicular to the advancing direction of the vehicle;
step two: distinguishing a vertical axis from the other two axes according to the three-axis readings;
step three: calculating the installation angle of the equipment according to the triaxial reading, establishing a carrier coordinate system and establishing a rotation matrix;
step four: converting the original data into a carrier coordinate system reading by using a rotation matrix, wherein an x-axis is along the movement direction of the carrier, a z-axis is upward, and a y-axis is vertical to the x and z;
step five: stationary reading = uniform linear motion = (x ≡0, y ≡0,z is equal to about 980), and x 2 +y2+z2≈980 2 980 is the gravitational acceleration;
step six: a carrier coordinate system reading (x, y, z), the change in the reading representing acceleration of the carrier due to the opposite force;
step seven: designing a normal driving threshold, a dangerous driving threshold and a collision threshold;
step eight: judging whether collision occurs or not, judging whether the stress in any direction exceeds a collision threshold or not or judging whether the resultant force exceeds the collision threshold, if so, entering the next step, and if not, entering the step of circularly recording data;
step nine: further judging whether collision occurs or not, carrying out continuous N times of sampling data, judging, entering the next step if the continuous N times of sampling data exceed a collision threshold value, and entering the step of circularly recording data if the continuous N times of sampling data do not exceed the collision threshold value;
step ten: judging whether the vehicle is stationary or not, sampling and judging according to collision threshold values in the step eight and the step nine, if the vehicle needs to be stationary, stopping the vehicle, reporting an accident at the same time, and if the vehicle does not need to be stationary, entering a step of clearing cycle information;
the step of circularly recording data and the step of clearing period information enter an inertial sensor original reading resetting step, and enter a step two for circulation after the inertial sensor original reading resetting step is executed, so that the next collision threshold measurement judgment is accurate.
2. The AI crash vehicle recorder employing inertial sensing technology of claim 1, wherein: the central control module is also electrically connected with a key module, a display module and a debugging module.
3. The AI crash vehicle recorder employing inertial sensing technology of claim 1, wherein: in the seventh step, the normal driving threshold value, the dangerous driving threshold value and the design value of the collision threshold value are obtained through a collision test and an acceleration test.
4. The AI crash vehicle recorder employing inertial sensing technology of claim 1, wherein: in the function VI, the collision threshold is changed into the dangerous driving threshold, so that the dangerous driving threshold can be judged, and the dangerous driving accident identification is realized.
5. The AI crash vehicle recorder employing inertial sensing technology of claim 1, wherein: in the function VII, the collision threshold is changed into a normal running threshold, so that the normal running threshold can be judged, and the normal driving identification is realized.
6. The AI crash vehicle recorder employing inertial sensing technology of claim 1, wherein: the model of the inertial sensor is SC7A20.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117746526A (en) * | 2023-12-15 | 2024-03-22 | 重庆大学 | Driving event recording system and method based on driving data triggering |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117746526A (en) * | 2023-12-15 | 2024-03-22 | 重庆大学 | Driving event recording system and method based on driving data triggering |
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