CN113990033A - Vehicle traffic accident remote take-over rescue method and system based on 5G internet of vehicles - Google Patents
Vehicle traffic accident remote take-over rescue method and system based on 5G internet of vehicles Download PDFInfo
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- CN113990033A CN113990033A CN202111060113.7A CN202111060113A CN113990033A CN 113990033 A CN113990033 A CN 113990033A CN 202111060113 A CN202111060113 A CN 202111060113A CN 113990033 A CN113990033 A CN 113990033A
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/01—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium
- G08B25/08—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems characterised by the transmission medium using communication transmission lines
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
- G08G1/202—Dispatching vehicles on the basis of a location, e.g. taxi dispatching
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L17/00—Speaker identification or verification
- G10L17/22—Interactive procedures; Man-machine interfaces
- G10L17/24—Interactive procedures; Man-machine interfaces the user being prompted to utter a password or a predefined phrase
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L21/00—Processing of the speech or voice signal to produce another audible or non-audible signal, e.g. visual or tactile, in order to modify its quality or its intelligibility
- G10L21/02—Speech enhancement, e.g. noise reduction or echo cancellation
- G10L21/0208—Noise filtering
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS OR SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique
- G10L25/30—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique using neural networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
Abstract
The invention discloses a vehicle traffic accident remote takeover rescue method and system based on a 5G internet of vehicles, wherein the method comprises the following steps: the 5G vehicle-mounted terminal in the vehicle automatically detects the running state of the vehicle; if the vehicle running state is abnormal, the 5G vehicle-mounted terminal detects the state of the driver once at preset time intervals; if the driver is in a coma state, the 5G vehicle-mounted terminal informs the rescue vehicle of providing vehicle rescue service; if the driver is in a waking state, the 5G vehicle-mounted terminal inquires whether the driver requires vehicle rescue service; and predicting a vehicle traffic accident frequent region by collecting the position information of the vehicle traffic accidents in the past year, and arranging a rescue vehicle in the vehicle traffic accident frequent region. Has the advantages that: the invention can accurately and flexibly know the specific injury of the driver in the vehicle, and the 5G vehicle-mounted terminal is intelligently communicated with the driver, thereby realizing the optimal solution of resource utilization.
Description
Technical Field
The invention relates to the field of traffic safety rescue, in particular to a vehicle traffic accident remote takeover rescue method and system based on a 5G internet of vehicles.
Background
The Internet of Vehicles (IoV) belongs to the Internet of Things (IoT) and is a huge interactive network formed by information such as vehicle position, speed and route. As the evolution of LTE, 5G has a delay of up to 1ms, has a higher bandwidth, supports a larger number of connections, and also supports a higher mobility speed.
The combination of 5G and Internet of vehicles technology will enhance the external communication capability of the vehicle. When a traffic accident happens to the vehicle, a driver is quite possibly unconscious, and the ability of seeking help to a third party and a traffic police when the traffic accident happens to the vehicle can be enhanced through the 5G vehicle networking technology.
A remote rescue method for vehicle traffic accidents in the prior art, such as Chinese patent No. CN103413411B, discloses an active rescue system for major traffic accidents based on the Internet of vehicles, which comprises a vehicle-mounted terminal, a monitoring center upper computer system, an emergency alarm terminal and a mobile internet, wherein the vehicle-mounted terminal activates an alarm program when the vehicle speed is greater than or equal to a certain set threshold value, continuously detects two variables of vehicle acceleration and speed zero-approaching time, triggers an alarm when the two variables both accord with the design threshold value, and sends out voice and buzzing sound alarm to draw attention of pedestrians and nearby residents so as to obtain short-distance rapid rescue. However, the system cannot accurately and flexibly know the specific injury of the driver in the vehicle, and further cannot achieve the optimal solution of resource utilization.
An effective solution to the problems in the related art has not been proposed yet.
Disclosure of Invention
Aiming at the problems in the related art, the invention provides a vehicle traffic accident remote takeover rescue method and system based on a 5G vehicle networking, so as to overcome the technical problems in the prior related art.
Therefore, the invention adopts the following specific technical scheme:
according to one aspect of the invention, a vehicle traffic accident remote takeover rescue method based on 5G internet of vehicles is provided, and the method comprises the following steps:
s1, automatically detecting the vehicle running state by the in-vehicle 5G vehicle-mounted terminal;
s2, if the vehicle running state is abnormal, the 5G vehicle-mounted terminal detects the state of the driver once at preset time intervals;
s3, if the driver is in a coma state, the 5G vehicle-mounted terminal informs the rescue vehicle to provide vehicle rescue service, and provides vehicle position information and personnel information to medical departments and traffic departments near the vehicle;
s4, if the driver is in a waking state, the 5G vehicle-mounted terminal inquires whether the driver requires the vehicle rescue service;
s5, forecasting the frequent area of the vehicle traffic accidents by collecting the position information of the vehicle traffic accidents in the past year, and arranging rescue vehicles in the frequent area of the vehicle traffic accidents.
Further, the step of automatically detecting the vehicle driving state by the in-vehicle 5G vehicle-mounted terminal in S1 further includes the following steps:
s11, connecting a triggering device in the 5G vehicle-mounted terminal with a vehicle airbag sensor, and arranging an acceleration sensor in the 5G vehicle-mounted terminal;
and S12, if the vehicle safety air bag sensor is started or the acceleration value measured by the acceleration sensor reaches or exceeds the design threshold value and the vehicle running speed is less than 5km/h, judging that the vehicle running state is abnormal.
Further, in S2, the 5G in-vehicle terminal detects the state of the driver through the high definition camera.
Further, the number of times the 5G in-vehicle terminal detects the state of the driver is set to at least five times in S2.
Further, the step of detecting the state of the driver by the 5G vehicle-mounted terminal in S2 further includes:
s21, acquiring a collecting picture of the vehicle driving seat through a high-definition camera, setting the first sampling as a first frame, and sampling at a time interval of T seconds as a current frame;
s22, dividing the collected picture into M regions, selecting the central lines of the M regions divided in the X direction or the central lines of the N regions divided in the Y direction as pixel points;
s23, comparing the pixel point of any central line of the current frame with the pixel point of the corresponding central line of the first frame to obtain the difference of the pixel points, if the difference is greater than a first threshold value, judging that the pixel point is different, and if the difference is greater than a second threshold value, judging that the current frame is different from the first frame;
s24, if the times of judging that the pixel points are different are larger than a third threshold value, judging that the current frame is different from the first frame;
and S25, if the current frame is different from the first frame, the driver is in a coma state, otherwise, the driver is in a wakeful state.
Further, in S4, if the driver is awake, the 5G in-vehicle terminal inquiring whether the driver requests the provision of the vehicle rescue service further includes:
s41, if the driver confirms to receive the vehicle rescue service, the 5G vehicle-mounted terminal informs the rescue vehicle of providing the vehicle rescue service;
and S42, if the driver does not accept the vehicle rescue service, the voice print password needs to be input into the 5G vehicle-mounted terminal.
Further, if the driver does not receive the vehicle rescue service in S42, the step of inputting the voiceprint password signal to the 5G vehicle-mounted terminal further includes:
s421, acquiring voice information of a driver, and removing background sound in the voice information to obtain voice of a person;
s422, acquiring a voiceprint password signal in the human voice, and converting the voiceprint password signal into a digital signal through an A/D converter;
s423, eliminating vocal cords and lip effects of the digital signals, passing the digital signals through a high-pass filter, and simultaneously performing discrete FFT (fast Fourier transform) on each frame of digital signals;
s424, inputting the digital signal into the RBF neural network recognition model, and distinguishing whether the digital signal is a voiceprint of the driver, if so, determining that the driver does not accept vehicle rescue service;
and the RBF neural network recognition model is trained and constructed by inputting voiceprints processed by voice of a passing driver into the RBF neural network model.
Further, the step of removing the background sound in the voice information to obtain the human voice in S421 further includes the following steps:
performing framing, windowing and time-frequency conversion on voice information of a driver to obtain an original mixed signal amplitude spectrum and an original mixed signal phase spectrum;
inputting the original mixed signal amplitude spectrum into a convolutional neural network to obtain a low-resolution characteristic diagram;
inputting the low-resolution feature map and the original mixed signal amplitude spectrum into a recurrent neural network to obtain a human voice predicted value and a background voice predicted value;
combining the human voice predicted value and the background voice predicted value with the phase spectrum of the original mixed signal, performing inverse Fourier transform to obtain a human voice signal and a background voice signal, and simultaneously removing the background voice signal.
Further, the predicting the area where the vehicle traffic accident is frequently generated by collecting the past year vehicle traffic accident location information in S5 further includes the following steps:
s51, collecting the traffic accident position information of the vehicles in the past year;
s52, training a GM grey prediction model through the position information of the traffic accident of the vehicle in the past year;
s53, predicting the vehicle traffic accident frequent region on any day through the GM grey prediction model, and arranging a rescue vehicle in the vehicle traffic accident frequent region on the same day.
According to another aspect of the present invention, there is provided a vehicle traffic accident remote takeover rescue system based on 5G internet of vehicles, the system comprising: the device comprises a vehicle running state detection module, a driver state detection module and a prediction module;
the vehicle running state detection module is used for automatically detecting the vehicle running state through a 5G vehicle-mounted terminal;
the driver state detection module is used for detecting the state of the driver once by the 5G vehicle-mounted terminal at preset time intervals if the driving state of the vehicle is abnormal, informing the rescue vehicle to provide vehicle rescue service if the driver is in a coma state, and providing vehicle position information and personnel information to medical departments and traffic departments nearby the vehicle, and inquiring whether the driver requires the vehicle rescue service by the 5G vehicle-mounted terminal if the driver is in a waking state;
the prediction module is used for collecting the position information of the traffic accidents of vehicles in the past year, predicting the frequent traffic accident areas of the vehicles and setting rescue vehicles in the frequent traffic accident areas of the vehicles.
The invention has the beneficial effects that: compared with the prior art, the vehicle traffic accident remote takeover rescue method and system based on the 5G internet of vehicles can automatically judge the state of the vehicle and the state of a driver, so that the intellectualization and automation level of remote takeover rescue is improved, and the labor cost can be reduced. And the state of the driver is detected, so that the specific injury of the driver in the vehicle can be accurately and flexibly known, and the 5G vehicle-mounted terminal is intelligently communicated with the driver, so that the optimal solution of resource utilization can be realized. Background sound in the voice information of the driver is removed, so that a voiceprint password signal of the driver can be accurately transmitted to the 5G vehicle-mounted terminal. By predicting the frequent area of the vehicle traffic accidents every day, the rescue efficiency of the vehicle traffic accidents can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a flowchart of a vehicle traffic accident remote takeover rescue method based on a 5G internet of vehicles according to an embodiment of the invention.
Detailed Description
For further explanation of the various embodiments, the drawings which form a part of the disclosure and which are incorporated in and constitute a part of this specification, illustrate embodiments and, together with the description, serve to explain the principles of operation of the embodiments, and to enable others of ordinary skill in the art to understand the various embodiments and advantages of the invention, and, by reference to these figures, reference is made to the accompanying drawings, which are not to scale and wherein like reference numerals generally refer to like elements.
According to the embodiment of the invention, a vehicle traffic accident remote takeover rescue method and system based on the 5G internet of vehicles are provided.
Referring now to the drawings and the detailed description, the invention is further illustrated, as shown in fig. 1, according to one aspect of the invention, there is provided a vehicle traffic accident remote takeover rescue method based on 5G car networking, the method comprising the following steps:
s1, automatically detecting the vehicle running state by the in-vehicle 5G vehicle-mounted terminal;
wherein, the step of automatically detecting the vehicle driving state by the in-vehicle 5G vehicle-mounted terminal in the vehicle in S1 further comprises the following steps:
s11, connecting a triggering device in the 5G vehicle-mounted terminal with a vehicle airbag sensor, and arranging an acceleration sensor in the 5G vehicle-mounted terminal;
and S12, if the vehicle airbag sensor is started or the acceleration value measured by the acceleration sensor reaches or exceeds a design threshold value and the vehicle running speed is less than 5km/h, judging that the vehicle running state is abnormal (when the vehicle running state is abnormal, starting an alarm in a 5G vehicle-mounted terminal for warning nearby passers-by and prompting the personnel to carry out personnel rescue in the future).
S2, if the vehicle running state is abnormal, the 5G vehicle-mounted terminal detects the state of the driver once at preset time intervals;
and in the step S2, the 5G vehicle-mounted terminal detects the state of the driver through the high-definition camera. The number of times that the 5G in-vehicle terminal detects the state of the driver is set to at least five times.
The 5G vehicle-mounted terminal in the S2 further comprises the following steps of:
s21, acquiring a collecting picture of the vehicle driving seat through a high-definition camera, setting the first sampling as a first frame, and sampling at a time interval of T seconds as a current frame;
s22, dividing the collected picture into M regions, selecting the central lines of the M regions divided in the X direction or the central lines of the N regions divided in the Y direction as pixel points;
s23, comparing the pixel point of any central line of the current frame with the pixel point of the corresponding central line of the first frame to obtain the difference of the pixel points, if the difference is greater than a first threshold value, judging that the pixel point is different, and if the difference is greater than a second threshold value, judging that the current frame is different from the first frame;
s24, if the times of judging that the pixel points are different are larger than a third threshold value, judging that the current frame is different from the first frame;
and S25, if the current frame is different from the first frame, the driver is in a coma state, otherwise, the driver is in a wakeful state.
S3, if the driver is in a coma state, the 5G vehicle-mounted terminal informs the rescue vehicle to provide vehicle rescue service, and provides vehicle position information and personnel information to medical departments and traffic departments near the vehicle;
s4, if the driver is in a waking state, the 5G vehicle-mounted terminal inquires whether the driver requires the vehicle rescue service;
wherein, if the driver is in the waking state in S4, the step of inquiring whether the driver requests the vehicle rescue service by the 5G in-vehicle terminal further comprises:
s41, if the driver confirms to receive the vehicle rescue service, the 5G vehicle-mounted terminal informs the rescue vehicle of providing the vehicle rescue service;
and S42, if the driver does not accept the vehicle rescue service, the voice print password needs to be input into the 5G vehicle-mounted terminal.
Wherein, if the driver does not accept the vehicle rescue service in S42, the step of inputting the voiceprint password signal to the 5G vehicle-mounted terminal further includes:
s421, acquiring voice information of a driver, and removing background sound in the voice information to obtain voice of a person;
s422, acquiring a voiceprint password signal in the human voice, and converting the voiceprint password signal into a digital signal through an A/D converter;
s423, eliminating vocal cords and lip effects of the digital signals, passing the digital signals through a high-pass filter, and simultaneously performing discrete FFT (fast Fourier transform) on each frame of digital signals;
s424, inputting the digital signal into the RBF neural network recognition model, and distinguishing whether the digital signal is a voiceprint of the driver, if so, determining that the driver does not accept vehicle rescue service;
and the RBF neural network recognition model is trained and constructed by inputting voiceprints processed by voice of a passing driver into the RBF neural network model.
In S421, the step of removing the background sound in the speech information to obtain the human speech further includes the following steps:
performing framing, windowing and time-frequency conversion on voice information of a driver to obtain an original mixed signal amplitude spectrum and an original mixed signal phase spectrum;
inputting the original mixed signal amplitude spectrum into a convolutional neural network to obtain a low-resolution characteristic diagram;
inputting the low-resolution feature map and the original mixed signal amplitude spectrum into a recurrent neural network to obtain a human voice predicted value and a background voice predicted value;
combining the human voice predicted value and the background voice predicted value with the phase spectrum of the original mixed signal, performing inverse Fourier transform to obtain a human voice signal and a background voice signal, and simultaneously removing the background voice signal.
S5, forecasting the frequent area of the vehicle traffic accidents by collecting the position information of the vehicle traffic accidents in the past year, and arranging rescue vehicles in the frequent area of the vehicle traffic accidents.
Wherein, the predicting the area where the vehicle traffic accident frequently occurs by collecting the past year vehicle traffic accident location information in S5 further comprises the steps of:
s51, collecting the traffic accident position information of the vehicles in the past year;
s52, training a GM grey prediction model through the position information of the traffic accident of the vehicle in the past year;
s53, predicting the vehicle traffic accident frequent region on any day through the GM grey prediction model, and arranging a rescue vehicle in the vehicle traffic accident frequent region on the same day.
According to another aspect of the present invention, there is provided a vehicle traffic accident remote takeover rescue system based on 5G internet of vehicles, the system comprising: the device comprises a vehicle running state detection module, a driver state detection module and a prediction module; the vehicle running state detection module is used for automatically detecting the vehicle running state through the 5G vehicle-mounted terminal; the driver state detection module is used for detecting the state of the driver once by the 5G vehicle-mounted terminal at preset time intervals if the driving state of the vehicle is abnormal, informing the rescue vehicle to provide vehicle rescue service if the driver is in a coma state, and providing vehicle position information and personnel information to medical departments and traffic departments nearby the vehicle, and inquiring whether the driver requires the vehicle rescue service by the 5G vehicle-mounted terminal if the driver is in a waking state; the prediction module is used for collecting the position information of the traffic accidents of vehicles in the past year, predicting the frequent traffic accident areas of the vehicles and setting rescue vehicles in the frequent traffic accident areas of the vehicles.
In conclusion, compared with the prior art, the vehicle traffic accident remote takeover rescue method and system based on the 5G internet of vehicles can automatically judge the state of the vehicle and the state of the driver, so that the intellectualization and automation level of remote takeover rescue is improved, and the labor cost can be reduced. And the state of the driver is detected, so that the specific injury of the driver in the vehicle can be accurately and flexibly known, and the 5G vehicle-mounted terminal is intelligently communicated with the driver, so that the optimal solution of resource utilization can be realized. Background sound in the voice information of the driver is removed, so that a voiceprint password signal of the driver can be accurately transmitted to the 5G vehicle-mounted terminal. By predicting the frequent area of the vehicle traffic accidents every day, the rescue efficiency of the vehicle traffic accidents can be improved.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.
Claims (10)
1. Vehicle traffic accident remote taking-over rescue method based on 5G Internet of vehicles is characterized by comprising the following steps:
s1, automatically detecting the vehicle running state by the in-vehicle 5G vehicle-mounted terminal;
s2, if the vehicle running state is abnormal, the 5G vehicle-mounted terminal detects the state of the driver once at preset time intervals;
s3, if the driver is in a coma state, the 5G vehicle-mounted terminal informs the rescue vehicle to provide vehicle rescue service, and provides vehicle position information and personnel information to medical departments and traffic departments near the vehicle;
s4, if the driver is in a waking state, the 5G vehicle-mounted terminal inquires whether the driver requires the vehicle rescue service;
s5, forecasting the frequent area of the vehicle traffic accidents by collecting the position information of the vehicle traffic accidents in the past year, and arranging rescue vehicles in the frequent area of the vehicle traffic accidents.
2. The vehicle traffic accident remote takeover rescue method based on 5G internet of vehicles according to claim 1, wherein the step of automatically detecting the vehicle driving state by the in-vehicle 5G vehicle-mounted terminal in S1 further comprises the following steps:
s11, connecting a triggering device in the 5G vehicle-mounted terminal with a vehicle airbag sensor, and arranging an acceleration sensor in the 5G vehicle-mounted terminal;
and S12, if the vehicle safety air bag sensor is started or the acceleration value measured by the acceleration sensor reaches or exceeds the design threshold value and the vehicle running speed is less than 5km/h, judging that the vehicle running state is abnormal.
3. The vehicle traffic accident remote takeover rescue method based on the 5G internet of vehicles according to claim 1, wherein the 5G vehicle-mounted terminal in the S2 detects the state of the driver through a high-definition camera.
4. The vehicle traffic accident remote takeover rescue method based on the 5G internet of vehicles according to claim 3, characterized in that the number of times that the 5G vehicle-mounted terminal detects the state of the driver in S2 is set to be at least five times.
5. The vehicle traffic accident remote takeover rescue method based on the 5G internet of vehicles according to claim 5, wherein the detection of the state of the driver by the 5G vehicle-mounted terminal in S2 further comprises the following steps:
s21, acquiring a collecting picture of the vehicle driving seat through a high-definition camera, setting the first sampling as a first frame, and sampling at a time interval of T seconds as a current frame;
s22, dividing the collected picture into M regions, selecting the central lines of the M regions divided in the X direction or the central lines of the N regions divided in the Y direction as pixel points;
s23, comparing the pixel point of any central line of the current frame with the pixel point of the corresponding central line of the first frame to obtain the difference of the pixel points, if the difference is greater than a first threshold value, judging that the pixel point is different, and if the difference is greater than a second threshold value, judging that the current frame is different from the first frame;
s24, if the times of judging that the pixel points are different are larger than a third threshold value, judging that the current frame is different from the first frame;
and S25, if the current frame is different from the first frame, the driver is in a coma state, otherwise, the driver is in a wakeful state.
6. The vehicle traffic accident remote takeover rescue method based on 5G internet of vehicles according to claim 1, wherein if the driver is awake in S4, the 5G vehicle-mounted terminal inquiring whether the driver requires vehicle rescue services further comprises the following steps:
s41, if the driver confirms to receive the vehicle rescue service, the 5G vehicle-mounted terminal informs the rescue vehicle of providing the vehicle rescue service;
and S42, if the driver does not accept the vehicle rescue service, the voice print password needs to be input into the 5G vehicle-mounted terminal.
7. The vehicle traffic accident remote takeover rescue method based on 5G Internet of vehicles according to claim 6, wherein if the driver does not accept the vehicle rescue service in S42, the step of inputting the voiceprint password signal to the 5G vehicle-mounted terminal further comprises the following steps:
s421, acquiring voice information of a driver, and removing background sound in the voice information to obtain voice of a person;
s422, acquiring a voiceprint password signal in the human voice, and converting the voiceprint password signal into a digital signal through an A/D converter;
s423, eliminating vocal cords and lip effects of the digital signals, passing the digital signals through a high-pass filter, and simultaneously performing discrete FFT (fast Fourier transform) on each frame of digital signals;
s424, inputting the digital signal into the RBF neural network recognition model, and distinguishing whether the digital signal is a voiceprint of the driver, if so, determining that the driver does not accept vehicle rescue service;
and the RBF neural network recognition model is trained and constructed by inputting voiceprints processed by voice of a passing driver into the RBF neural network model.
8. The vehicle traffic accident remote takeover rescue method based on 5G internet of vehicles according to claim 7, wherein the step of eliminating the background sound in the voice information to obtain the human voice in S421 further comprises the steps of:
performing framing, windowing and time-frequency conversion on voice information of a driver to obtain an original mixed signal amplitude spectrum and an original mixed signal phase spectrum;
inputting the original mixed signal amplitude spectrum into a convolutional neural network to obtain a low-resolution characteristic diagram;
inputting the low-resolution feature map and the original mixed signal amplitude spectrum into a recurrent neural network to obtain a human voice predicted value and a background voice predicted value;
combining the human voice predicted value and the background voice predicted value with the phase spectrum of the original mixed signal, performing inverse Fourier transform to obtain a human voice signal and a background voice signal, and simultaneously removing the background voice signal.
9. The vehicle traffic accident remote takeover rescue method based on 5G internet of vehicles according to claim 1, wherein the step of predicting the frequent vehicle traffic accident area by collecting the past vehicle traffic accident location information in S5 further comprises the steps of:
s51, collecting the traffic accident position information of the vehicles in the past year;
s52, training a GM grey prediction model through the position information of the traffic accident of the vehicle in the past year;
s53, predicting the vehicle traffic accident frequent region on any day through the GM grey prediction model, and arranging a rescue vehicle in the vehicle traffic accident frequent region on the same day.
10. The vehicle traffic accident remote takeover rescue system based on the 5G Internet of vehicles is used for realizing the vehicle traffic accident remote takeover rescue method based on the 5G Internet of vehicles, which is characterized by comprising the following steps: the device comprises a vehicle running state detection module, a driver state detection module and a prediction module;
the vehicle running state detection module is used for automatically detecting the vehicle running state through a 5G vehicle-mounted terminal;
the driver state detection module is used for detecting the state of the driver once by the 5G vehicle-mounted terminal at preset time intervals if the driving state of the vehicle is abnormal, informing the rescue vehicle to provide vehicle rescue service if the driver is in a coma state, and providing vehicle position information and personnel information to medical departments and traffic departments nearby the vehicle, and inquiring whether the driver requires the vehicle rescue service by the 5G vehicle-mounted terminal if the driver is in a waking state;
the prediction module is used for collecting the position information of the traffic accidents of vehicles in the past year, predicting the frequent traffic accident areas of the vehicles and setting rescue vehicles in the frequent traffic accident areas of the vehicles.
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