CN110154757A - The multi-faceted safe driving support method of bus - Google Patents

The multi-faceted safe driving support method of bus Download PDF

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Publication number
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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China
Prior art keywords
driver
big data
bus
data
driving
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Pending
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CN201910463353.8A
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Chinese (zh)
Inventor
田凯彬
张西源
陈思宇
王瑞锦
洪磊
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University of Electronic Science and Technology of China
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University of Electronic Science and Technology of China
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Priority to CN201910463353.8A priority Critical patent/CN110154757A/en
Publication of CN110154757A publication Critical patent/CN110154757A/en
Pending legal-status Critical Current

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    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60KARRANGEMENT 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
    • B60K28/00Safety 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
    • B60K28/02Safety 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
    • B60K28/06Safety 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
    • B60K28/066Safety 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
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60QARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
    • B60Q9/00Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/08Estimation 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
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/08Estimation 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
    • B60W40/09Driving style or behaviour
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16Human faces, e.g. facial parts, sketches or expressions
    • G06V40/168Feature extraction; Face representation
    • G06V40/169Holistic features and representations, i.e. based on the facial image taken as a whole
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16Human faces, e.g. facial parts, sketches or expressions
    • G06V40/168Feature extraction; Face representation
    • G06V40/171Local features and components; Facial parts ; Occluding parts, e.g. glasses; Geometrical relationships
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16Human faces, e.g. facial parts, sketches or expressions
    • G06V40/174Facial expression recognition
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/18Eye characteristics, e.g. of the iris
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/20Movements or behaviour, e.g. gesture recognition
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B60VEHICLES IN GENERAL
    • B60WCONJOINT 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
    • B60W40/00Estimation 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
    • B60W40/08Estimation 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
    • B60W2040/0818Inactivity or incapacity of driver
    • B60W2040/0827Inactivity 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

The multi-faceted safe driving support method of bus
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.
CN201910463353.8A 2019-05-30 2019-05-30 The multi-faceted safe driving support method of bus Pending CN110154757A (en)

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Cited By (3)

* Cited by examiner, † Cited by third party
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
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

Citations (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102509083A (en) * 2011-11-19 2012-06-20 广州大学 Detection method for body conflict event
CN104200598A (en) * 2014-07-01 2014-12-10 徐州工程学院 Bus fire early warning and armored window glass bursting remote control system
CN104751663A (en) * 2015-02-28 2015-07-01 北京壹卡行科技有限公司 Safe driving auxiliary system and safe driving auxiliary method for driver
CN205428100U (en) * 2015-12-30 2016-08-03 江苏穿越金点信息科技有限公司 Intelligent alarm system of regional invasion monitoring of bus driver's cabin
CN105898239A (en) * 2016-06-03 2016-08-24 北京中电万联科技股份有限公司 Bus driver abnormal behavior monitoring system and monitoring method
CN107341438A (en) * 2017-01-24 2017-11-10 问众智能信息科技(北京)有限公司 The method and apparatus of in-car safety monitoring based on computer vision
CN107633196A (en) * 2017-06-14 2018-01-26 电子科技大学 A kind of eyeball moving projection scheme based on convolutional neural networks
CN108288075A (en) * 2018-02-02 2018-07-17 沈阳工业大学 A kind of lightweight small target detecting method improving SSD
CN108564007A (en) * 2018-03-27 2018-09-21 深圳市智能机器人研究院 A kind of Emotion identification method and apparatus based on Expression Recognition
CN108790816A (en) * 2018-05-24 2018-11-13 安徽中科中涣防务装备技术有限公司 A kind of bus driver's compartment safety comprehensive electronic enclosure system
CN109034099A (en) * 2018-08-14 2018-12-18 华中师范大学 A kind of expression recognition method and device
CN109190468A (en) * 2018-07-26 2019-01-11 深圳市赛亿科技开发有限公司 A kind of fatigue driving monitoring method and system
CN109426765A (en) * 2017-08-23 2019-03-05 厦门雅迅网络股份有限公司 Driving dangerousness mood based reminding method, terminal device and storage medium
CN109523450A (en) * 2018-12-10 2019-03-26 鄂尔多斯市普渡科技有限公司 A kind of bus driving monitoring system
CN109711356A (en) * 2018-12-28 2019-05-03 广州海昇教育科技有限责任公司 A kind of expression recognition method and system
CN109733319A (en) * 2019-03-01 2019-05-10 河西学院 Bus driver's seat safe and intelligent protective device based on deep learning and single-chip microcontroller

Patent Citations (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102509083A (en) * 2011-11-19 2012-06-20 广州大学 Detection method for body conflict event
CN104200598A (en) * 2014-07-01 2014-12-10 徐州工程学院 Bus fire early warning and armored window glass bursting remote control system
CN104751663A (en) * 2015-02-28 2015-07-01 北京壹卡行科技有限公司 Safe driving auxiliary system and safe driving auxiliary method for driver
CN205428100U (en) * 2015-12-30 2016-08-03 江苏穿越金点信息科技有限公司 Intelligent alarm system of regional invasion monitoring of bus driver's cabin
CN105898239A (en) * 2016-06-03 2016-08-24 北京中电万联科技股份有限公司 Bus driver abnormal behavior monitoring system and monitoring method
CN107341438A (en) * 2017-01-24 2017-11-10 问众智能信息科技(北京)有限公司 The method and apparatus of in-car safety monitoring based on computer vision
CN107633196A (en) * 2017-06-14 2018-01-26 电子科技大学 A kind of eyeball moving projection scheme based on convolutional neural networks
CN109426765A (en) * 2017-08-23 2019-03-05 厦门雅迅网络股份有限公司 Driving dangerousness mood based reminding method, terminal device and storage medium
CN108288075A (en) * 2018-02-02 2018-07-17 沈阳工业大学 A kind of lightweight small target detecting method improving SSD
CN108564007A (en) * 2018-03-27 2018-09-21 深圳市智能机器人研究院 A kind of Emotion identification method and apparatus based on Expression Recognition
CN108790816A (en) * 2018-05-24 2018-11-13 安徽中科中涣防务装备技术有限公司 A kind of bus driver's compartment safety comprehensive electronic enclosure system
CN109190468A (en) * 2018-07-26 2019-01-11 深圳市赛亿科技开发有限公司 A kind of fatigue driving monitoring method and system
CN109034099A (en) * 2018-08-14 2018-12-18 华中师范大学 A kind of expression recognition method and device
CN109523450A (en) * 2018-12-10 2019-03-26 鄂尔多斯市普渡科技有限公司 A kind of bus driving monitoring system
CN109711356A (en) * 2018-12-28 2019-05-03 广州海昇教育科技有限责任公司 A kind of expression recognition method and system
CN109733319A (en) * 2019-03-01 2019-05-10 河西学院 Bus driver's seat safe and intelligent protective device based on deep learning and single-chip microcontroller

Cited By (3)

* Cited by examiner, † Cited by third party
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
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

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