CN110154757A - The multi-faceted safe driving support method of bus - Google Patents
The multi-faceted safe driving support method of bus Download PDFInfo
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- CN110154757A CN110154757A CN201910463353.8A CN201910463353A CN110154757A CN 110154757 A CN110154757 A CN 110154757A CN 201910463353 A CN201910463353 A CN 201910463353A CN 110154757 A CN110154757 A CN 110154757A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60K—ARRANGEMENT OR MOUNTING OF PROPULSION UNITS OR OF TRANSMISSIONS IN VEHICLES; ARRANGEMENT OR MOUNTING OF PLURAL DIVERSE PRIME-MOVERS IN VEHICLES; AUXILIARY DRIVES FOR VEHICLES; INSTRUMENTATION OR DASHBOARDS FOR VEHICLES; ARRANGEMENTS IN CONNECTION WITH COOLING, AIR INTAKE, GAS EXHAUST OR FUEL SUPPLY OF PROPULSION UNITS IN VEHICLES
- B60K28/00—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions
- B60K28/02—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the driver
- B60K28/06—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the driver responsive to incapacity of driver
- B60K28/066—Safety devices for propulsion-unit control, specially adapted for, or arranged in, vehicles, e.g. preventing fuel supply or ignition in the event of potentially dangerous conditions responsive to conditions relating to the driver responsive to incapacity of driver actuating a signalling device
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q9/00—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
- B60W40/09—Driving style or behaviour
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
- G06V40/169—Holistic features and representations, i.e. based on the facial image taken as a whole
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
- G06V40/171—Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/174—Facial expression recognition
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/18—Eye characteristics, e.g. of the iris
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/20—Movements or behaviour, e.g. gesture recognition
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
- B60W2040/0818—Inactivity or incapacity of driver
- B60W2040/0827—Inactivity or incapacity of driver due to sleepiness
Abstract
The invention discloses a kind of multi-faceted safe driving support methods of bus, comprising the following steps: S1, starting farsighted person, big data audit platform and information open server；S2, farsighted person detect driver's driving status, judge whether driver is in fatigue driving, indignation drives or conflict disagreement state；S3, it will test data transmission to big data audit platform and the progress data processing of information open server；S4, detect whether otherwise receive the remote operation signal that big data audit platform is sent does not operate if being then automatically brought into operation according to remote operation signal to bus.The present invention for the first time combines safely mood detection collision detection with bus, while utilizing recognition of face, and the technologies such as Emotion identification, the situation of accurate quantization driver, convenient for science, objectively carries out early warning, reduce public transport safety accident comprehensively.
Description
Technical field
The invention belongs to public transport security fields, in particular to a kind of multi-faceted safe driving support method of bus.
Background technique
With the rapid development of national economy and the support energetically of Green Policies, China's bus ownership persistently rises.
While bus ownership is promoted rapidly, the traffic accident number as caused by bus is also risen rapidly.According to national statistics inning
According to, between 2009 to 2013,1.4 Wan Yuqi of bus road traffic accident occurs altogether for the whole nation, and cause more than 3500 people dead altogether,
More than 1.6 ten thousand people are injured.The events such as the fatigue driving of bus driver, indignation drive, conflict is disagreed, are that driver is caused to judge
Fault, finally leads to the common factors of tragedy, and cause huge property loss and casualties.And how to prevent bus
The situations such as the fatigue driving of driver, indignation drive, conflict is disagreed have become to reduce the generation of bus accident
Instantly social very urgent problem.
The current product for thering are following a few classes to be directed to above situation in the market:
Fatigue driving early-warning apparatus is that a kind of be mounted on automobile rearview or instrument board can be in time to the fatigue of driver
The equipment of driving behavior progress early warning.The shortcomings that product is the record of no history alarm, it is not possible to export data and audit.
Driving assistance system is a kind of vehicle location of absorbed logistics company, vehicle safety, the vehicle connection in way air control management
Net system.The product function is complete, but the safety of the storage and transmission of data does not ensure.
Such product currently on the market is irregular, and low-end product presence has a single function, no data exports, audit function
Can, real-time Data Transmission the disadvantages of, and high-end product is although feature-rich but price is excessively high, can not provide one effectively
Management platform, and its safety is without guarantee.
Summary of the invention
Mood is detected into collision detection and bus it is an object of the invention to overcome the deficiencies of the prior art and provide a kind of
Safety combines, while utilizing recognition of face, the technologies such as Emotion identification, and the situation of accurate quantization driver, is convenient for section comprehensively
It learns, objectively carry out early warning, reduce the multi-faceted safe driving support method of bus of public transport safety accident.
The purpose of the present invention is achieved through the following technical solutions: the multi-faceted safe driving support method of bus,
The following steps are included:
S1, starting farsighted person, big data audit platform and information open server；
S2, farsighted person detect driver's driving status, judge whether driver is in fatigue driving, indignation drives or conflict is disagreed
State；
S3, it will test data transmission to big data audit platform and the progress data processing of information open server；
S4, it detects whether to receive the remote operation signal that big data audit platform is sent, if then according to remote operation
Signal is automatically brought into operation bus, does not otherwise operate.
Further, the farsighted person carries out state inspection for acquiring driver's picture or video information, and to driver
It surveys, preset voice can be issued automatically if detection discovery driver is in fatigue driving state or angry driving condition and mentioned
It wakes up；If detection discovery driver clashes with passenger, upper lock signal is sent to by bus smart lock by bluetooth, is gone forward side by side
Row voice reminder.
Further, the big data audit platform major function includes long-range control, real time monitoring and data management:
Long-range control refers to that locking is forced in administrator's selection on big data audit platform, and will by wireless transmissions network
Lock signal is transferred to bus smart lock in the pressure, so that bus smart lock is automatic locking；Or it is flat in big data audit
Text information is inputted on platform, text information is transmitted to by farsighted person by wireless transmissions network, is carried out at farsighted person's equipment
Casting；
Real time monitoring refer to big data audit platform can the collected current interior situation of real-time exhibition farsighted person video counts
According to, and the fatigue, indignation, colliding data of quantization are visualized；
Data management refers to that big data audit platform on the one hand can be to platform administrator information (login account, modification logging
Deng), the information (face information, driver license number etc.) of driver make and add, check and modify operation, on the one hand drive a vehicle and produce to driver
Raw data keep a record and check operation；
Further, the information open server is suggested for distributing traveling records and driving；Net can be used in driver
Network terminal device is checked the driving conditions of a period of time and intelligently provided driving suggestion after logging in.
Further, the step S2 includes following sub-step:
S21, driver's facial image is acquired by video camera, and position people using non-maximum restraining NMS algorithm and the library dlib
Eye；
S22, acquisition eye aperture average value EAR, carry out anti-reducing to EAR and obtain fatigue data；
S23, when frames all in one second determine fatigue data be all larger than 0.6, then determine there is fatigue driving situation, otherwise sentence
It is set to normally travel state；
S24, face part is obtained by face recognition algorithms, face is zoomed to the size of network inputs, and to face
Picture carries out dimension expansion；
S25, network is separated using depth face picture is predicted, obtain the array of 7 float numbers composition,
Respectively indicate the probability of seven kinds of moods；
S26, index of the mood of maximum probability in array is obtained, mood is obtained using mapping to dictionary according to index,
If continuous angry mood occurred greater than 2 seconds, determines angry driving condition occur, be otherwise determined as normally travel state；
S27, the thermodynamic chart in relation to driver is constructed using infrared thermal imaging sensor, utilizes edge extracting in computer vision
Technology sketches the contours of the profile of driver；
S28, the edge for having significant change in a digital pictures or discontinuous region a are extracted, if it exists region a,
Then determine conflict situations occur, is otherwise determined as normally travel state.
Further, the step S3 includes following sub-step:
The image data and/or video flowing that S31, farsighted person will test carry out the encryption of Arnold and RC4；
S32, encrypted image data and/or video stream data are transmitted to big data audit platform；
S33, big data audit platform is logged in, receives the data of farsighted person；
S34, the data received are depicted as to line chart and cake chart and real-time exhibition；
S35, video is played in real time；
S36, driving daily paper and driving suggestion are generated；
S37, log-on message open server；
S38, option date and the driving recording for inquiring this day.
Further, the step S4 includes following sub-step:
S41, big data audit platform input of text messages are simultaneously encrypted text message；
S42, by encrypted text message transmission to farsighted person；
S43, farsighted person receive text message, are decrypted to the text message received, then carry out voice broadcast；
Locking program is forced in S44, big data audit platform starting, and lock signal is to farsighted person in transmission；
S45, farsighted person receive lock signal and send to smart lock；
S46, smart lock receive upper lock signal, lock to the isolating door of driver driving room.
The beneficial effects of the present invention are:
(1) mood detection collision detection is combined safely for the first time with bus, while utilizes recognition of face, Emotion identification
Etc. technologies, the situation of accurate quantization driver, convenient for science, objectively carries out early warning, reduces public transport safety accident comprehensively.
(2) system for using active service is carried out on embedded device in the case where poor network connectivity based on energy
It moves and provides fatigue, indignation and conflict early warning for driver, take emergency measures automatically.System is also the administrator of big data platform
Real-time video audit and human-computer interaction function are provided, when driver the case where other improper driving occurs by backstage manager
After it was found that, backstage manager directly can remotely lock, can prevent to occur other than three kinds of states such as fatigue driving its
His situation.The interface of real-time query oneself travelling data, driving suggestion is provided simultaneously for driver.Whole system will be active
The theory of service is dissolved into running.
(3) using the video stream cipher algorithm based on grouping Arnold and RC4 of highly effective and safe, guaranteeing Video stream information
Under the premise of safety, the encryption efficiency to video is improved, enhances serious forgiveness, the pictorial information of loss is restored automatically.
Detailed description of the invention
Fig. 1 is the flow chart of the multi-faceted safe driving support method of bus of the invention.
Fig. 2 is the integrated stand composition that depth separates convolutional network.
Specific embodiment
Technical solution of the present invention is further illustrated with reference to the accompanying drawing.
As shown in Figure 1, the multi-faceted safe driving support method of bus, comprising the following steps:
S1, starting farsighted person, big data audit platform and information open server；
S2, farsighted person detect driver's driving status, judge whether driver is in fatigue driving, indignation drives or conflict is disagreed
State；
The present invention proposes the convolutional neural networks model that face mood is accurately identified under a mini Mod.It can be divided using depth
From convolutional network, traditional convolution module is revised as Depthwise process and Pointwise process, fortune can be greatly reduced
The parameter amount of calculation, allow our algorithm it is low calculate power embedded device on real time execution.
FER human face expression data set is the data set that trained network relies on.This data set is public in Kaggle big data platform
Cloth to be developed, is made of 35886 human face expression pictures, every picture is made of the gray level image that size is fixed as 48 × 48,
Show 7 kinds of basic emotions of someone, be (anger) anger respectively, (disgust) detests, and (fear) is frightened, (happy) happily,
(sad) sad, (surprised) is surprised and (normal) is neutral.
The overall architecture of network such as Fig. 2, Conv2D are common convolution, and SepConv2D is that depth separates convolution,
BatchNorm is that batch normalizes, and MaxPool is maximum pond, and Global Avg Pool is global maximum pond.
Depth separates convolution and convolution module is divided into two parts, is Depthwise process and Pointwise mistake respectively
Journey, that is, spatial convoluted is executed respectively to each channel of input, it is then by point-by-point convolution (1 × 1 convolution) that output is logical
Road mixing.Specific detection includes following sub-step:
S21, driver's facial image is acquired by video camera, and position people using non-maximum restraining NMS algorithm and the library dlib
Eye；
S22, acquisition eye aperture average value EAR, carry out anti-reducing to EAR and obtain fatigue data；
S23, when frames all in one second determine fatigue data be all larger than 0.6, then determine there is fatigue driving situation, otherwise sentence
It is set to normally travel state；
S24, face part is obtained by face recognition algorithms, face is zoomed to the size of network inputs, and to face
Picture carries out dimension expansion；
S25, network is separated using depth face picture is predicted, obtain the array of 7 float numbers composition,
Respectively indicate the probability of seven kinds of moods；
S26, index of the mood of maximum probability in array is obtained, mood is obtained using mapping to dictionary according to index,
If continuous angry mood occurred greater than 2 seconds, determines angry driving condition occur, be otherwise determined as normally travel state；
S27, the thermodynamic chart in relation to driver is constructed using infrared thermal imaging sensor, utilizes edge extracting in computer vision
Technology sketches the contours of the profile of driver；
S28, the edge for having significant change in a digital pictures or discontinuous region a are extracted, if it exists region a,
Then determine conflict situations occur, is otherwise determined as normally travel state.
S3, it will test data transmission to big data audit platform and the progress data processing of information open server；Including with
Lower sub-step:
The image data and/or video flowing that S31, farsighted person will test carry out the encryption of Arnold and RC4；
S32, encrypted image data and/or video stream data are transmitted to big data audit platform；
S33, big data audit platform is logged in, receives the data of farsighted person；
S34, the data received are depicted as to line chart and cake chart and real-time exhibition；
S35, video is played in real time；
S36, driving daily paper and driving suggestion are generated；
S37, log-on message open server；
S38, option date and the driving recording for inquiring this day.
S4, it detects whether to receive the remote operation signal that big data audit platform is sent, if then according to remote operation
Signal is automatically brought into operation bus, does not otherwise operate；Including following sub-step:
S41, big data audit platform input of text messages are simultaneously encrypted text message；
S42, by encrypted text message transmission to farsighted person；
S43, farsighted person receive text message, are decrypted to the text message received, then carry out voice broadcast；
Locking program is forced in S44, big data audit platform starting, and lock signal is to farsighted person in transmission；
S45, farsighted person receive lock signal and send to smart lock；
S46, smart lock receive upper lock signal, lock to the isolating door of driver driving room.
Further, the farsighted person carries out state inspection for acquiring driver's picture or video information, and to driver
It surveys, preset voice can be issued automatically if detection discovery driver is in fatigue driving state or angry driving condition and mentioned
It wakes up；If detection discovery driver clashes with passenger, upper lock signal is sent to by bus smart lock by bluetooth, is gone forward side by side
Row voice reminder.
Further, the big data audit platform major function includes long-range control, real time monitoring and data management:
Long-range control refers to that locking is forced in administrator's selection on big data audit platform, and will by wireless transmissions network
Lock signal is transferred to bus smart lock in the pressure, so that bus smart lock is automatic locking；Or it is flat in big data audit
Text information is inputted on platform, text information is transmitted to by farsighted person by wireless transmissions network, is carried out at farsighted person's equipment
Casting；
Real time monitoring refer to big data audit platform can the collected current interior situation of real-time exhibition farsighted person video counts
According to, and the fatigue, indignation, colliding data of quantization are visualized；
Data management refers to that big data audit platform on the one hand can be to platform administrator information (login account, modification logging
Deng), the information (face information, driver license number etc.) of driver make and add, check and modify operation, on the one hand drive a vehicle and produce to driver
Raw data keep a record and check operation；
Further, the information open server is suggested for distributing traveling records and driving；Net can be used in driver
Network terminal device is checked the driving conditions of a period of time and intelligently provided driving suggestion after logging in.
Those of ordinary skill in the art will understand that the embodiments described herein, which is to help reader, understands this hair
Bright principle, it should be understood that protection scope of the present invention is not limited to such specific embodiments and embodiments.This field
Those of ordinary skill disclosed the technical disclosures can make according to the present invention and various not depart from the other each of essence of the invention
The specific variations and combinations of kind, these variations and combinations are still within the scope of the present invention.
Claims (7)
1. the multi-faceted safe driving support method of bus, which comprises the following steps:
S1, starting farsighted person, big data audit platform and information open server；
S2, farsighted person detect driver's driving status, judge whether driver is in fatigue driving, indignation drives or conflict disagreement shape
State；
S3, it will test data transmission to big data audit platform and the progress data processing of information open server；
S4, it detects whether to receive the remote operation signal that big data audit platform is sent, if then according to remote operation signal
Bus is automatically brought into operation, is not otherwise operated.
2. the multi-faceted safe driving support method of bus according to claim 1, which is characterized in that a thousand li is ophthalmically acceptable
State-detection is carried out in acquisition driver's picture or video information, and to driver, if detection discovery driver is in fatigue
Driving condition or angry driving condition can then issue preset voice reminder automatically；If detection discovery driver rushes with passenger
It is prominent, then upper lock signal is sent to by bus smart lock by bluetooth, and carry out voice reminder.
3. the multi-faceted safe driving support method of bus according to claim 1, which is characterized in that the big data is examined
Counting platform major function includes long-range control, real time monitoring and data management:
Long-range control refers to that locking is forced in administrator's selection on big data audit platform, and by wireless transmissions network that this is strong
Lock signal is transferred to bus smart lock in system, so that bus smart lock is automatic locking；Or on big data audit platform
Text information is inputted, text information is transmitted to by farsighted person by wireless transmissions network, is broadcasted at farsighted person's equipment；
Real time monitoring refer to big data audit platform can the collected current interior situation of real-time exhibition farsighted person video data, and
The fatigue, indignation, colliding data of quantization are visualized；
Data management refers on the one hand big data audit platform can add platform administrator information, the information of driver, look into
Operation is seen and modifies, the data on the one hand generated to driver's driving keep a record and check operation.
4. the multi-faceted safe driving support method of bus according to claim 1, which is characterized in that the information discloses
Server is suggested for distributing traveling records and driving.
5. the multi-faceted safe driving support method of bus according to claim 1, which is characterized in that the step S2 packet
Include following sub-step:
S21, driver's facial image is acquired by video camera, and position human eye using non-maximum restraining NMS algorithm and the library dlib；
S22, acquisition eye aperture average value EAR, carry out anti-reducing to EAR and obtain fatigue data；
S23, when frames all in one second determine fatigue data be all larger than 0.6, then determine there is fatigue driving situation, be otherwise determined as
Normally travel state；
S24, face part is obtained by face recognition algorithms, face is zoomed to the size of network inputs, and to face picture
Carry out dimension expansion；
S25, network is separated using depth face picture is predicted, obtain the array of 7 float numbers composition, respectively
Indicate the probability of seven kinds of moods；
S26, index of the mood of maximum probability in array is obtained, mood is obtained using mapping to dictionary according to index, if even
It is continuous angry mood occur greater than 2 seconds, then determine angry driving condition occur, is otherwise determined as normally travel state；
S27, the thermodynamic chart in relation to driver is constructed using infrared thermal imaging sensor, utilizes edge extracting skill in computer vision
Art sketches the contours of the profile of driver；
S28, the edge for having significant change in a digital pictures or discontinuous region a are extracted, region a, then sentence if it exists
Existing conflict situations are made, are otherwise determined as normally travel state.
6. the multi-faceted safe driving support method of bus according to claim 1, which is characterized in that the step S3 packet
Include following sub-step:
The image data and/or video flowing that S31, farsighted person will test carry out the encryption of Arnold and RC4；
S32, encrypted image data and/or video stream data are transmitted to big data audit platform；
S33, big data audit platform is logged in, receives the data of farsighted person；
S34, the data received are depicted as to line chart and cake chart and real-time exhibition；
S35, video is played in real time；
S36, driving daily paper and driving suggestion are generated；
S37, log-on message open server；
S38, option date and the driving recording for inquiring this day.
7. the multi-faceted safe driving support method of bus according to claim 1, which is characterized in that the step S4 packet
Include following sub-step:
S41, big data audit platform input of text messages are simultaneously encrypted text message；
S42, by encrypted text message transmission to farsighted person；
S43, farsighted person receive text message, are decrypted to the text message received, then carry out voice broadcast；
Locking program is forced in S44, big data audit platform starting, and lock signal is to farsighted person in transmission；
S45, farsighted person receive lock signal and send to smart lock；
S46, smart lock receive upper lock signal, lock to the isolating door of driver driving room.
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110765945A (en) * | 2019-10-23 | 2020-02-07 | 上海能塔智能科技有限公司 | Test driving management method, vehicle-mounted intelligent device and computer readable storage medium |
| CN110796059A (en) * | 2019-10-23 | 2020-02-14 | 上海能塔智能科技有限公司 | Test driving control method and system, cloud platform and computer readable storage medium |
| CN111008586A (en) * | 2019-11-29 | 2020-04-14 | 上海能塔智能科技有限公司 | Data processing method, device, equipment and storage medium for passenger car conflict detection |
| CN111445669A (en) * | 2020-03-12 | 2020-07-24 | 杭州律橙电子科技有限公司 | Safety monitoring system of bus |
| CN112036329A (en) * | 2020-09-02 | 2020-12-04 | 上海本安仪表系统有限公司 | Vehicle-mounted human-computer interface with face and emotion recognition function |
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