CN110473402A - A kind of accident detection early warning system based on target abnormal behaviour trajectory analysis - Google Patents
A kind of accident detection early warning system based on target abnormal behaviour trajectory analysis Download PDFInfo
- Publication number
- CN110473402A CN110473402A CN201910770534.5A CN201910770534A CN110473402A CN 110473402 A CN110473402 A CN 110473402A CN 201910770534 A CN201910770534 A CN 201910770534A CN 110473402 A CN110473402 A CN 110473402A
- Authority
- CN
- China
- Prior art keywords
- server
- vehicle
- data
- early warning
- road
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000004458 analytical method Methods 0.000 title claims abstract description 49
- 238000001514 detection method Methods 0.000 title claims abstract description 46
- 206010000117 Abnormal behaviour Diseases 0.000 title claims abstract description 19
- 230000002159 abnormal effect Effects 0.000 claims abstract description 14
- 230000009471 action Effects 0.000 claims abstract description 4
- 230000002547 anomalous effect Effects 0.000 claims description 31
- 230000008859 change Effects 0.000 claims description 20
- 238000012544 monitoring process Methods 0.000 claims description 13
- 230000005540 biological transmission Effects 0.000 claims description 11
- 230000001133 acceleration Effects 0.000 claims description 10
- 238000012545 processing Methods 0.000 claims description 8
- 230000033001 locomotion Effects 0.000 claims description 4
- 238000010223 real-time analysis Methods 0.000 claims description 3
- 238000012549 training Methods 0.000 claims description 3
- 230000005856 abnormality Effects 0.000 claims description 2
- 230000011218 segmentation Effects 0.000 claims description 2
- 230000006399 behavior Effects 0.000 description 18
- 238000005516 engineering process Methods 0.000 description 7
- 238000013499 data model Methods 0.000 description 5
- 238000010586 diagram Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 206010039203 Road traffic accident Diseases 0.000 description 2
- 230000004888 barrier function Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000000034 method Methods 0.000 description 2
- 230000003542 behavioural effect Effects 0.000 description 1
- 239000004020 conductor Substances 0.000 description 1
- 239000000428 dust Substances 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000010191 image analysis Methods 0.000 description 1
- 238000012797 qualification Methods 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- 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
- G08B25/006—Alarm destination chosen according to type of event, e.g. in case of fire phone the fire service, in case of medical emergency phone the ambulance
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0133—Traffic data processing for classifying traffic situation
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/164—Centralised systems, e.g. external to vehicles
-
- 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
- G08G1/205—Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental
Landscapes
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Tourism & Hospitality (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Marketing (AREA)
- Educational Administration (AREA)
- Emergency Management (AREA)
- Economics (AREA)
- Public Health (AREA)
- Human Resources & Organizations (AREA)
- Development Economics (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Traffic Control Systems (AREA)
Abstract
The embodiment of the invention discloses a kind of accident detection early warning systems based on target abnormal behaviour trajectory analysis, it include: goal behavior track acquisition device, PTZ camera and server, real time data is sent to server after the action trail of goal behavior track acquisition device acquisition target, server is compared real time data by trained abnormal event alarming model, detect that goal behavior or track then issue warning information in the presence of abnormal, the image of the PTZ camera acquisition abnormity event generation area confirms warning information, the road real-time pictures of PTZ camera acquisition are stored in server, warning information after verifying is sent to monitoring center by the server, the warning information that monitoring center sends over server, which is confirmed and is shown, issues early warning to the public or third party system.The present invention solves the problems, such as that existing accident detection system detection precision is low, partial event type can not detect, can not give warning in advance.
Description
Technical field
The present embodiments relate to Traffic monitoring fields, and in particular to a kind of based on the different of target abnormal behaviour trajectory analysis
Normal event detection early warning system.
Background technique
There are detection accuracy for existing road accident detection equipment or system not enough, partial event type can not detect report
Alert shortcomings, such as occur collapsing on road, landslide, have barrier or undetectable hazard event on road.Mesh
Preceding field of traffic there are many kinds of event detection technology, for detect in road, bridge, the vehicle in tunnel or region have it is without exception
The appearance of event or dangerous situation.Such as based on video and graphic analysis or the Video Events detection system of video structural, base
Radar event detection system in millimetre-wave radar target following technology, the laser radar event based on laser radar scanning technology
Detection system, the vehicle active alarm system (vehicle SOS) positioned based on vehicle GPS/Beidou etc..
Existing traffic incident detecting system and equipment mostly use the mode of video and graphic analysis to be detected, and pass through
The image that the video camera of road installation provides analyzes the abnormal vehicle in the presence or absence of road or abnormal road with image processing techniques
The appearance of condition simultaneously provides corresponding warning message.Since image analysis processing and video structural side are used in Video Events detection
Formula has accident event without exception to analyze in picture, since this technology is stronger to video image dependence and defeated to front
The camera installation locations of image, height and ambient enviroment are more demanding out, and image comparison technology is for special circumstances, than
Such as shedding object, falling article, the object detection effect of motion profile is not poor after especially falling, can not be accurate right
This kind of event is detected and issues alarm.It is (smog, sand and dust) and meteorological especially in the environment of illumination is weaker or evening
In the case where inclement condition (greasy weather, snowy day, rainy day, haze), Video Events detection detection accuracy is greatly reduced, or even can not be right
Event is detected and is alarmed.Considerably increase the risk that subsequent traffic accident occurs.
Millimetre-wave radar event detection system, this system be based on radar by transmitting radio wave by echo come
The multidate information for obtaining target, since existing radar equipment majority is all using Doppler technology, which can be to the height of movement
Fast target is interested, and the object of object at a slow speed and stopping lower than 5Km/h will can not be tracked and be detected, such as: stop
Vehicle only, sheds the events such as object, road surface collapsing, landslide at pedestrian.
Based on vehicle GPS/BEI-DOU position system accident detection, the system mainly positioning by being installed on vehicle
System and call for service system are completed jointly, and when vehicle occurs abnormal or driver and conductor issues when calling for help, vehicle monitoring center
The warning message of event accident vehicle could be obtained, but other event accidents of traffic information and non-vehicle can not be obtained
Early warning and alarming information.
Summary of the invention
For this purpose, the embodiment of the present invention provides a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis
System, to solve on existing road, common accident detection system detection precision is low, partial event type can not detect, can not
The problem of giving warning in advance.
To achieve the goals above, the embodiment of the present invention provides the following technical solutions:
The embodiment of the invention discloses a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis,
The early warning system includes: goal behavior track acquisition device, PTZ camera and server, the goal behavior track acquisition
Real time data is sent to server after the action trail of device acquisition target, the server sends out goal behavior acquisition device
The data sent carry out real-time analysis processing, and server compares real time data by trained abnormal event alarming model
It is right, detect that goal behavior or track then issue warning information in the presence of abnormal, the PTZ camera acquisition abnormity event occurs
The image in region confirms that the road real-time pictures of PTZ camera acquisition are stored in server, described to warning information
Warning information after verifying is sent to monitoring center by server, and the warning information that monitoring center sends over server carries out
Confirm and be shown and early warning is issued to the public or third party system.
Further, goal behavior track acquisition device includes radar sensor, and the radar sensor setting exists
Road side, radar sensor obtain the multidate information of each target point in overlay area in real time by way of high frequency sweep,
It include: instantaneous velocity, driving direction, place lane, latitude and longitude information, target type, the coordinate bit relative to radar sensor
It sets, region, distributing position, the data information of acquisition is sent to server by radar sensor.
Further, the PTZ camera is disposed in an evenly spaced relation in road side, the shooting model of adjacent PTZ camera
It encloses boundary mutually to cover, guarantees that, without shooting blind area, the PTZ camera is connect with server, server control holder is taken the photograph
360 ° of rotary takings of camera, content of shooting includes video, photo, and content of shooting is sent to server.
Further, it is slow that analyses and comparison module, control module, data transmission module, data are provided in the server
Storing module and vehicle running state large database concept, the vehicle running state large database concept include: limit of the present road to vehicle
Fast threshold value distinguishes the speed limit of station wagon, motorbus and lorry；Acceleration when station wagon, motorbus and lorry accelerate
Acceleration when degree and deceleration；The lane quantity of present road, distinguishes fast traffic lane, slow lane, Emergency Vehicle Lane, and each vehicle corresponds to row
The lane sailed；The corresponding relationship of speed and vehicle fleet size on road, it is close to be less than vehicle for average speed in the case that traffic density is big
Spend it is small in the case where average speed；
The data transmission module receives the data of radar sensor monitoring, is cached in data cache module, institute
It states data of the analyses and comparison module based on normal vehicle operation state in vehicle running state large database concept and radar sensor is supervised
The data of survey are analysed and compared, and analyses and comparison result is sent to background server, the control mould by data transmission module
Block controls PTZ camera and shoots road picture.
Further, the analyses and comparison result and correspondence of the vehicle running state large database concept typing analyses and comparison module
Radar sensor detection data, database is carried out it is perfect, analyses and comparison module carry out constantly training study, promoted analysis sentences
Disconnected accuracy.
Further, the server includes multiple storage units, server to analyses and comparison result and road image into
Row stores and is sent to monitoring center.
Further, the monitoring center includes display module and alarm module, and monitoring center receives what server was sent
Analyses and comparison result and road image, according to analysing and comparing as a result, alarm module sounds an alarm, display module pop-up shows road
Image reminds staff to carry out checking processing in time.
Further, the early warning detection system the following steps are included:
Lane segmentation in coverage area is multiple regions, the traveling of monitoring vehicle in each region by radar sensor
State；
Radar sensor acquires the real time kinematics track of all vehicles in each section, the vehicle of the every amount vehicle of acquisition, movement
Speed, acceleration, longitude and latitude and direction angle information；
The data of monitoring are sent to server by radar sensor, detect that vehicle abnormality slows down in a certain region, brake,
Lane change or closeness increase, and server is by the number of normal vehicle operation in the data of monitoring and vehicle running state large database concept
According to analysing and comparing, anomalous event type is judged；
The driving status for analyzing all vehicles in above-mentioned zone adjacent area judges the anomalous event occurred in above-mentioned zone
It whether is incident；
The nearest PTZ camera shooting anomalous event generation area in server command range anomalous event generation area
The road image of video and picture, shooting is sent to server；
The longitude and latitude of position is occurred server for event time, event type, event and road image stores；
The information of storage is sent to monitoring center by server, and monitoring center is alarmed, and pops up road image pop-up,
Remind staff to check and handle, in front of the anomalous event generation area on advices plate prompt front region have anomalous event or
Accident occurs, and pays attention to evacuation of slowing down, gives warning in advance, reduce the generation of accident.
The embodiment of the present invention has the advantages that
The embodiment of the invention discloses a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis,
By the way that radar sensor is arranged in road side, the operating condition of vehicle is monitored, monitoring accuracy is promoted, monitoring data is sent to
Server is compared with normal vehicle running data, judges whether to be abnormal event, and judge event type, realizes abnormal
The preliminary judgement of event, the road picture shot by PTZ camera, confirms the generation of anomalous event, server sentences comparison
Disconnected result and road image are stored, and are sounded an alarm by monitoring center, and pop-up shows road image, staff according to
Actual conditions give warning in advance in incident region fore, reduce accident rate.
Detailed description of the invention
It, below will be to embodiment party in order to illustrate more clearly of embodiments of the present invention or technical solution in the prior art
Formula or attached drawing needed to be used in the description of the prior art are briefly described.It should be evident that the accompanying drawings in the following description is only
It is merely exemplary, it for those of ordinary skill in the art, without creative efforts, can also basis
The attached drawing of offer, which is extended, obtains other implementation attached drawings.
Structure depicted in this specification, ratio, size etc., only to cooperate the revealed content of specification, for
Those skilled in the art understands and reads, and is not intended to limit the invention enforceable qualifications, therefore does not have technical
Essential meaning, the modification of any structure, the change of proportionate relationship or the adjustment of size are not influencing the function of the invention that can be generated
Under effect and the purpose that can reach, should all still it fall in the range of disclosed technology contents obtain and can cover.
Fig. 1 is a kind of accident detection early warning system flow chart provided in an embodiment of the present invention；
Fig. 2 is a kind of road anomalous event schematic diagram provided in an embodiment of the present invention；
Fig. 3 is another road anomalous event schematic diagram provided in an embodiment of the present invention；
Fig. 4 is another road anomalous event schematic diagram provided in an embodiment of the present invention；
In figure: 1- radar sensor, 2- PTZ camera, 3- server.
Specific embodiment
Embodiments of the present invention are illustrated by particular specific embodiment below, those skilled in the art can be by this explanation
Content disclosed by book is understood other advantages and efficacy of the present invention easily, it is clear that described embodiment is the present invention one
Section Example, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not doing
Every other embodiment obtained under the premise of creative work out, shall fall within the protection scope of the present invention.
Embodiment 1
With reference to Fig. 1, present embodiment discloses a kind of accident detection early warning based on target abnormal behaviour trajectory analysis
System, comprising: goal behavior track acquisition device, PTZ camera 2 and server 3, goal behavior track acquisition device
Real time data is sent to server 3 after the action trail of acquisition target, the server 3 sends goal behavior acquisition device
Data carry out real-time analysis processing, server 3 is compared real time data by trained abnormal event alarming model,
Detect that goal behavior or track then issue warning information, the 2 acquisition abnormity event generating region of PTZ camera in the presence of abnormal
The image in domain confirms that the road real-time pictures that PTZ camera 2 acquires are stored in server, the clothes to warning information
Warning information after verifying is sent to monitoring center by business device 3, and the warning information that monitoring center sends over server carries out
Confirm and be shown and early warning is issued to the public or third party system.
Goal behavior track acquisition device includes radar sensor 1, and the radar sensor 1 is arranged in road side, thunder
Obtain the multidate information of each target point in overlay area in real time by way of high frequency sweep up to sensor 1, comprising: i.e. speed per hour
Degree, driving direction, place lane, latitude and longitude information, target type, the coordinate position relative to radar sensor 1, location
The data information of acquisition is sent to server 3 by domain, distributing position, radar sensor 1.
PTZ camera 2 is disposed in an evenly spaced relation in road side, and the coverage boundary of adjacent PTZ camera 2 is mutual
Covering guarantees that, without shooting blind area, the PTZ camera 2 is connect with server 3, and server 3 controls 360 ° of PTZ camera
Rotary taking, content of shooting include video, photo, and content of shooting is sent to server 3.Analyses and comparison are provided in server 3
Module, control module, data transmission module, data cache module and vehicle running state large database concept, the vehicle driving shape
State large database concept includes: speed limit threshold value of the present road to vehicle, distinguishes the speed limit of station wagon, motorbus and lorry；
Acceleration when acceleration when station wagon, motorbus and lorry accelerate and deceleration；
The lane quantity of present road, distinguishes fast traffic lane, slow lane, Emergency Vehicle Lane, and the lane of the corresponding traveling of each vehicle is small
Car walks fast traffic lane under normal circumstances, and lorry walks slow lane under normal circumstances；
The corresponding relationship of speed and vehicle fleet size on road, average speed is less than traffic density in the case that traffic density is big
Average speed in the case where small；
The data transmission module receives the data that radar sensor 1 monitors, and is cached in data cache module, institute
It states data of the analyses and comparison module based on normal vehicle operation state in vehicle running state large database concept and radar sensor 1 is supervised
The data of survey are analysed and compared, and the control module control PTZ camera 2 shoots road picture.
Server 3 includes multiple storage units, and 3 pairs of analyses and comparison results of server and road image are stored and sent
To monitoring center.Monitoring center includes display module and alarm module, and monitoring center receives the analyses and comparison knot that server is sent
Fruit and road image, according to analysing and comparing as a result, alarm module sounds an alarm, display module pop-up shows road image, reminds
Staff carries out checking processing in time.
The analyses and comparison result and corresponding radar sensor 1 of vehicle running state large database concept typing analyses and comparison module
Detection data, database is carried out it is perfect, analyses and comparison module carry out constantly training study, promote the accuracy of analytical judgment,
Faster judge the anomalous event occurred on road.
Embodiment 2
Present embodiment discloses a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis, references
In Fig. 2, region C occur parking or shed, fall event when.Front vehicle normal pass is influenced, back car can select to become
Road avoids current obstacle, and is possible to only lane change without slowing down.Single car lane change is not as Rule of judgment, if met pre-
The continuous vehicle first set is provided simultaneously with this behavior, for example the two vehicles that are connected all carry out lane change in this region, pass through comparison
The judgement output alert data model set in database compares judgement and analyzes normal vehicle traveling and lane change behavior rail
Mark, this behavior judge comparison condition as one.
The judgement of server 3 has a special event herein, and trigger event is alarmed while to drive PTZ camera 2 to shoot special
The video and picture of event generation area are checked.The road that 3 pairs of analyses and comparison results of server and PTZ camera 2 are shot
Picture data carries out event information storage, and the information of storage is sent to monitoring center by server 3, and monitoring center is alarmed,
And road image pop-up is popped up, it reminds staff to check and handle, is prompted on advices plate in front of the anomalous event generation area
Front region has anomalous event or accident, pays attention to evacuation of slowing down, gives warning in advance, reduce the generation of accident.
With reference to Fig. 2, when occur in the C of region parking or shed, fall event when.Front vehicle normal pass is influenced,
Front vehicle is possible to that deceleration and lane change can be selected during evacuation.When radar sensor 1 finds single target in this area
Slow down in domain and after lane change.Radar sensor 1 is by vehicle lane change data transmission to server 3, and server 3 is by lane change data
It is compared with normal vehicle operation status data in vehicle running state large database concept, judges that current region has anomalous event hair
It is raw.It can be alarmed at this time with trigger event, server 3 drives the video and figure of the shooting of PTZ camera 2 special event generation area
Piece is checked.It will count simultaneously, server 3 carries out event information storage, and the information of storage is sent in monitoring by server 3
The heart, monitoring center are alarmed, and pop up road image pop-up, and staff is reminded to check and handle, and are occurred in anomalous event
It prompts front region to have anomalous event or accident on region fore advices plate, pays attention to evacuation of slowing down, give warning in advance, reduce thing
Therefore generation.
Embodiment 3
Present embodiment discloses a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis, references
Fig. 3, slow lane driving vehicle is lorry and motorbus in vehicle running state large database concept.In front of slow lane in the C of region
When closely without vehicle, while when thering are two or two or more carts to drive into fast traffic lane, and lane change rear close second simultaneously
Cart has brake behavior and follows lane change.Then there may be the barrier to fall among the current region C, the more vehicles in rear is caused to become
Road evacuation.Radar sensor 1 is by vehicle lane change data transmission to server 3, and server 3 is by lane change data and vehicle running state
Normal vehicle operation status data is compared in large database concept, it is possible to determine that in the region slow lane C, there may be anomalous events.
The video and figure that 3 trigger event of server alarms while PTZ camera 2 being driven to shoot special event generation area
Piece is checked.The road picture data that 3 pairs of analyses and comparison results of server and PTZ camera 2 are shot carries out event information and deposits
The information of storage is sent to monitoring center by storage, server 3, and monitoring center is alarmed, and pops up road image pop-up, is reminded
Staff checks and handles, and prompt front region has anomalous event or accident on advices plate in front of the anomalous event generation area
Occur, pays attention to evacuation of slowing down, give warning in advance, reduce the generation of accident.
With reference to Fig. 3, detections of radar into region C traffic density relative to two neighboring region B, D larger, average speed
It is relatively low.Radar sensor 1 is by vehicle lane change data transmission to server 3, and server 3 is by lane change data, speed data and vehicle
Density data is compared with normal vehicle operation status data in vehicle running state large database concept, to determine current region
For improper phenomenon, it is understood that there may be anomalous event.
The video and figure that 3 trigger event of server alarms while PTZ camera 2 being driven to shoot special event generation area
Piece is checked.The road picture data that 3 pairs of analyses and comparison results of server and PTZ camera 2 are shot carries out event information and deposits
The information of storage is sent to monitoring center by storage, server 3, and monitoring center is alarmed, and pops up road image pop-up, is reminded
Staff checks and handles, and prompt front region has anomalous event or accident on advices plate in front of the anomalous event generation area
Occur, pays attention to evacuation of slowing down, give warning in advance, reduce the generation of accident.
Embodiment 4
Present embodiment discloses a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis, references
Fig. 4, when region C is there is a situation where collapsing, all vehicles in rear can all follow same track and be hidden to carry out lane change.It can
To analyze multiple types vehicle by server 3, the same or similar track of a variety of quantity vehicle lane changes judges on road
Whether abnormal conditions are had.
The video and figure that 3 trigger event of server alarms while PTZ camera 2 being driven to shoot special event generation area
Piece is checked.The road picture data that 3 pairs of analyses and comparison results of server and PTZ camera 2 are shot carries out event information and deposits
The information of storage is sent to monitoring center by storage, server 3, and monitoring center is alarmed, and pops up road image pop-up, is reminded
Staff checks and handles, and prompt front region has anomalous event or accident on advices plate in front of the anomalous event generation area
Occur, pays attention to evacuation of slowing down, give warning in advance, reduce the generation of accident.
When front vehicles exist go slowly but not up to go slowly standard when.The more vehicles in rear are hidden, such as slow down
Or lane change.PTZ camera 2 can be driven to check the slow-moving vehicle of current region with the presence or absence of unusual condition at this time.If hair
Raw abnormal conditions can be tracked and early warning, data are sent to server 3 simultaneously and are stored, and monitoring center is reported
It is alert, and real-time video picture is popped up, remind operator on duty to check and handle.
The Parking of region occurrence of large-area before the same area and this region, and rear region do not detect
In this region major accident or event may occur for vehicle at this time.Server 3 drives PTZ camera 2 to check this region
It transmits data to server 3 simultaneously to be stored, monitoring center is alarmed, and pops up real-time video picture, is reminded on duty
Personnel check and handle.
A variety of models are existed simultaneously on highway, the anxious acceleration of cart and trolley and the time suddenly slowed down and form are not
It is logical.It can whether there is trail change by judging the whether normal acceleration and deceleration of vehicle in combination with vehicle, can be used as judgement item
Part judges whether behavior generation area has special event.Driving PTZ camera 2 checks this region at this time, is tracked
And the road picture that early warning, 1 detection data of radar sensor and PTZ camera 2 are shot is sent to the progress of server 3 simultaneously
It stores and alarms, alarm in monitoring center and carry out real-time video broadcasting, operator on duty is reminded to check and handle.
The above several scenes can be included in the storage of vehicle behavior judgement output alert data model in the database, after system
Phase carries out self-perfection to judgement output alert data model by constantly learning.And it can be used as new comparison references object
Come with judgement output alert data model using when occurring later, anomalous event accident pattern or vehicle similar or that appearance is new are non-
Normal behaviour can be judged quickly.Vehicle normal behaviour data and the improper behavioral data of vehicle are constantly improve.Knot
The warning message that feedback arrives work station is closed, so that judgement output alert data model is constantly learnt and is improved, the event of can be improved is sentenced
It disconnected accuracy rate and shortens event and judges the time.
Realization detection type existing for event detection system is lacked, detection content lacks, undetectable target and
Blind area is supplemented.Increase event recall rate is predicted that may be present in advance it is possible thereby to reduce the traffic accident rate on road
Risk promotes traffic safety, makes safety high speed.
Although above having used general explanation and specific embodiment, the present invention is described in detail, at this
On the basis of invention, it can be made some modifications or improvements, this will be apparent to those skilled in the art.Therefore,
These modifications or improvements without departing from theon the basis of the spirit of the present invention are fallen within the scope of the claimed invention.
Claims (8)
1. a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis, which is characterized in that the early warning
System includes: goal behavior track acquisition device, PTZ camera and server, and goal behavior track acquisition device obtains
Real time data is sent to server, the data that the server sends goal behavior acquisition device after the action trail of target
Real-time analysis processing is carried out, server is compared real time data by trained abnormal event alarming model, detects
Warning information, the image of the PTZ camera acquisition abnormity event generation area is then issued and there is exception in goal behavior or track
Warning information is confirmed, the road real-time pictures of PTZ camera acquisition are stored in server, and the server will be tested
Warning information after card is sent to monitoring center, and the warning information that monitoring center sends over server is confirmed and carried out
It shows and early warning is issued to the public or third party system.
2. a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis as described in claim 1,
It being characterized in that, goal behavior track acquisition device includes radar sensor, and the radar sensor is arranged in road side,
Radar sensor obtains the multidate information of each target point in overlay area in real time by way of high frequency sweep, comprising: immediately
Speed, driving direction, place lane, latitude and longitude information, target type, the coordinate position relative to radar sensor, location
The data information of acquisition is sent to server by domain, distributing position, radar sensor.
3. a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis as described in claim 1,
It is characterized in that, the PTZ camera is disposed in an evenly spaced relation in road side, the coverage boundary of adjacent PTZ camera
Mutually covering guarantees that, without shooting blind area, the PTZ camera is connect with server, and server controls 360 ° of PTZ camera
Rotary taking, content of shooting include video, photo, and content of shooting is sent to server.
4. a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis as described in claim 1,
Be characterized in that, be provided in the server analyses and comparison module, control module, data transmission module, data cache module and
Vehicle running state large database concept, the vehicle running state large database concept include: speed limit threshold value of the present road to vehicle, area
Divide the speed limit of station wagon, motorbus and lorry；When acceleration when station wagon, motorbus and lorry accelerate and deceleration
Acceleration；The lane quantity of present road distinguishes fast traffic lane, slow lane, Emergency Vehicle Lane, the lane of the corresponding traveling of each vehicle；
The corresponding relationship of speed and vehicle fleet size on road, average speed is less than the small situation of traffic density in the case that traffic density is big
Under average speed；
The data transmission module receives the data of radar sensor monitoring, is cached in data cache module, described point
Analyse data and radar sensor monitoring of the comparison module based on normal vehicle operation state in vehicle running state large database concept
Data are analysed and compared, and analyses and comparison result is sent to background server, the control module control by data transmission module
PTZ camera processed shoots road picture.
5. a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis as claimed in claim 4,
It is characterized in that, the analyses and comparison result of the vehicle running state large database concept typing analyses and comparison module and corresponding radar pass
Sensor detection data, database is carried out it is perfect, analyses and comparison module carry out constantly training study, promote the accurate of analytical judgment
Degree.
6. a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis as described in claim 1,
It is characterized in that, the server includes multiple storage units, and server stores simultaneously analyses and comparison result and road image
It is sent to monitoring center.
7. a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis as described in claim 1,
It is characterized in that, the monitoring center includes display module and alarm module, and monitoring center receives the analyses and comparison that server is sent
As a result and road image, according to analysing and comparing as a result, alarm module sounds an alarm, display module pop-up shows road image, mentions
Awake staff carries out checking processing in time.
8. a kind of accident detection early warning system based on target abnormal behaviour trajectory analysis as described in claim 1,
Be characterized in that, the early warning detection system the following steps are included:
Lane segmentation in coverage area is multiple regions, the traveling shape of monitoring vehicle in each region by radar sensor
State；
Radar sensor acquire the real time kinematics track of all vehicles in each section, the vehicle of the every amount vehicle of acquisition, movement speed,
Acceleration, longitude and latitude and direction angle information；
The data of monitoring are sent to server by radar sensor, detect that vehicle abnormality slows down in a certain region, brake, lane change
Or closeness increases, server by the data of normal vehicle operation in the data of monitoring and vehicle running state large database concept into
Row is analysed and compared, and judges anomalous event type；
Whether the driving status for analyzing all vehicles in above-mentioned zone adjacent area judges the anomalous event occurred in above-mentioned zone
For incident；
The video of the nearest PTZ camera shooting anomalous event generation area in server command range anomalous event generation area
And picture, the road image of shooting are sent to server；
The longitude and latitude of position is occurred server for event time, event type, event and road image stores；
The information of storage is sent to monitoring center by server, and monitoring center is alarmed, and pops up road image pop-up, is reminded
Staff checks and handles, and prompt front region has anomalous event or accident on advices plate in front of the anomalous event generation area
Occur, pays attention to evacuation of slowing down, give warning in advance, reduce the generation of accident.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910770534.5A CN110473402B (en) | 2019-08-20 | 2019-08-20 | Abnormal event detection and early warning system based on target abnormal behavior trajectory analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910770534.5A CN110473402B (en) | 2019-08-20 | 2019-08-20 | Abnormal event detection and early warning system based on target abnormal behavior trajectory analysis |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110473402A true CN110473402A (en) | 2019-11-19 |
| CN110473402B CN110473402B (en) | 2021-04-27 |
Family
ID=68512930
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910770534.5A Active CN110473402B (en) | 2019-08-20 | 2019-08-20 | Abnormal event detection and early warning system based on target abnormal behavior trajectory analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110473402B (en) |
Cited By (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111325977A (en) * | 2020-02-25 | 2020-06-23 | 创捷运维智能科技有限责任公司 | Tunnel intelligence edge calculation management and control system |
| CN111523797A (en) * | 2020-04-21 | 2020-08-11 | 深圳中科慧据科技有限公司 | Rail transit early warning event scheduling method and device, computer equipment and storage medium |
| CN111578964A (en) * | 2020-04-13 | 2020-08-25 | 河北德冠隆电子科技有限公司 | High-precision map road information rapid generation system and method based on space-time trajectory reconstruction |
| CN111613013A (en) * | 2020-06-03 | 2020-09-01 | 克拉玛依市格恩赛电子科技有限公司 | Security positioning analysis early warning system, storage medium and method |
| CN111696366A (en) * | 2020-06-04 | 2020-09-22 | 中国人民解放军战略支援部队信息工程大学 | Road accident perception and identification method and system |
| CN111932882A (en) * | 2020-08-13 | 2020-11-13 | 广东飞达交通工程有限公司 | Real-time early warning system, method and equipment for road accidents based on image recognition |
| CN112257546A (en) * | 2020-10-19 | 2021-01-22 | 浙江宇视科技有限公司 | Event early warning method and device, electronic equipment and storage medium |
| CN112700638A (en) * | 2020-12-04 | 2021-04-23 | 杭州亥迪交通设备有限公司 | Intelligent road section intelligent detection system based on laser radar and millimeter wave radar |
| CN112804489A (en) * | 2020-12-31 | 2021-05-14 | 重庆文理学院 | Internet + -based intelligent construction site management system and method |
| CN112861706A (en) * | 2021-02-04 | 2021-05-28 | 北京百度网讯科技有限公司 | Road state monitoring method, device, equipment and storage medium |
| CN113468284A (en) * | 2021-06-29 | 2021-10-01 | 北京市商汤科技开发有限公司 | Object detection method and device, electronic equipment and storage medium |
| CN113516343A (en) * | 2021-04-06 | 2021-10-19 | 青岛以萨数据技术有限公司 | Vehicle early warning system, method and storage medium based on map and track data |
| CN113554881A (en) * | 2021-07-20 | 2021-10-26 | 周刚 | Artificial intelligence road event monitoring method, device, system and storage medium |
| CN113627213A (en) * | 2020-05-06 | 2021-11-09 | 浙江宇视科技有限公司 | Vehicle abnormal behavior monitoring method, device and system |
| CN113630543A (en) * | 2020-05-06 | 2021-11-09 | 杭州海康威视数字技术股份有限公司 | Falling object and person smashing event monitoring method and device, electronic equipment and monitoring system |
| CN113793524A (en) * | 2021-08-27 | 2021-12-14 | 深圳市分米互联科技有限公司 | Intelligent traffic science and technology operation platform |
| WO2021254175A1 (en) * | 2020-06-17 | 2021-12-23 | 华为技术有限公司 | Road safety monitoring method and system, and computer device |
| CN113920728A (en) * | 2021-10-11 | 2022-01-11 | 南京微达电子科技有限公司 | Detection and early warning method and system for obstacles thrown on expressway |
| CN114017092A (en) * | 2021-11-04 | 2022-02-08 | 山东东山新驿煤矿有限公司 | Coal mine operation ventilation system |
| CN114093152A (en) * | 2021-12-29 | 2022-02-25 | 安徽达尔智能控制系统股份有限公司 | Expressway tunnel abnormal event alarm method and system based on multiple information channels |
| CN114333366A (en) * | 2021-09-28 | 2022-04-12 | 宁波均联智行科技股份有限公司 | Danger early warning method and device based on V2X |
| CN114333330A (en) * | 2022-01-27 | 2022-04-12 | 浙江嘉兴数字城市实验室有限公司 | Intersection event detection system and method based on roadside edge holographic sensing |
| CN114530049A (en) * | 2020-11-06 | 2022-05-24 | 上海擎感智能科技有限公司 | Vehicle rescue and early warning method, system and computer storage medium |
| CN114596714A (en) * | 2022-05-10 | 2022-06-07 | 四川思百特科技有限责任公司 | Battery car guiding system and method |
| CN115019514A (en) * | 2022-08-09 | 2022-09-06 | 临沂市公路事业发展中心 | Highway inspection system based on car networking |
| CN115100865A (en) * | 2022-06-24 | 2022-09-23 | 上海市政工程设计研究总院（集团）有限公司 | Management and control system for traffic safety of tunnel portal area |
| CN115148018A (en) * | 2021-03-31 | 2022-10-04 | 海信集团控股股份有限公司 | Traffic incident detection apparatus and method |
| CN115359658A (en) * | 2022-08-17 | 2022-11-18 | 阿里云计算有限公司 | Method, device, equipment, storage medium and program product for detecting traffic incident |
| CN115641719A (en) * | 2022-10-25 | 2023-01-24 | 东南大学 | Method and device for detecting pedestrians on expressway |
| CN117494029A (en) * | 2023-12-29 | 2024-02-02 | 苏州映赛智能科技有限公司 | Road casting event identification method and device |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005056441A (en) * | 2004-11-10 | 2005-03-03 | Mitsubishi Electric Corp | Traffic flow measurement device |
| DE102011016217A1 (en) * | 2011-04-06 | 2012-10-11 | Connaught Electronics Ltd. | Method for warning driver of passenger car before rear end collision, involves projecting path of image, and warning driver of vehicle based on image with projected path, where path is determined based on velocity and steering angle |
| US9007197B2 (en) * | 2002-05-20 | 2015-04-14 | Intelligent Technologies International, Inc. | Vehicular anticipatory sensor system |
| CN104952273A (en) * | 2015-07-17 | 2015-09-30 | 东方网力科技股份有限公司 | Warning method, device and system aiming at vehicle behaviors |
| CN105844904A (en) * | 2016-04-22 | 2016-08-10 | 北京航空航天大学 | Vehicle abnormal behavior detection and tracking method based on DSRC |
| CN106952473A (en) * | 2017-04-01 | 2017-07-14 | 深圳市元征科技股份有限公司 | Road service system detection method and device |
| CN107742418A (en) * | 2017-09-29 | 2018-02-27 | 东南大学 | A kind of urban expressway traffic congestion status and stifled point position automatic identifying method |
| CN108922188A (en) * | 2018-07-24 | 2018-11-30 | 河北德冠隆电子科技有限公司 | The four-dimensional outdoor scene traffic of radar tracking positioning perceives early warning monitoring management system |
| CN109212520A (en) * | 2018-09-29 | 2019-01-15 | 河北德冠隆电子科技有限公司 | The road conditions perception accident detection alarm system and method for comprehensive detection radar |
| CN109741600A (en) * | 2018-12-29 | 2019-05-10 | 南京奥杰智能科技有限公司 | Road incidents detection system |
| CN109816982A (en) * | 2019-02-25 | 2019-05-28 | 东南大学 | Virtual networks non-motorized lane attribute modification method based on shared bicycle track |
| CN109949581A (en) * | 2019-04-11 | 2019-06-28 | 浙江无极互联科技有限公司 | A kind of road condition judgment method based on computer vision |
-
2019
- 2019-08-20 CN CN201910770534.5A patent/CN110473402B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9007197B2 (en) * | 2002-05-20 | 2015-04-14 | Intelligent Technologies International, Inc. | Vehicular anticipatory sensor system |
| JP2005056441A (en) * | 2004-11-10 | 2005-03-03 | Mitsubishi Electric Corp | Traffic flow measurement device |
| DE102011016217A1 (en) * | 2011-04-06 | 2012-10-11 | Connaught Electronics Ltd. | Method for warning driver of passenger car before rear end collision, involves projecting path of image, and warning driver of vehicle based on image with projected path, where path is determined based on velocity and steering angle |
| CN104952273A (en) * | 2015-07-17 | 2015-09-30 | 东方网力科技股份有限公司 | Warning method, device and system aiming at vehicle behaviors |
| CN105844904A (en) * | 2016-04-22 | 2016-08-10 | 北京航空航天大学 | Vehicle abnormal behavior detection and tracking method based on DSRC |
| CN106952473A (en) * | 2017-04-01 | 2017-07-14 | 深圳市元征科技股份有限公司 | Road service system detection method and device |
| CN107742418A (en) * | 2017-09-29 | 2018-02-27 | 东南大学 | A kind of urban expressway traffic congestion status and stifled point position automatic identifying method |
| CN108922188A (en) * | 2018-07-24 | 2018-11-30 | 河北德冠隆电子科技有限公司 | The four-dimensional outdoor scene traffic of radar tracking positioning perceives early warning monitoring management system |
| CN109212520A (en) * | 2018-09-29 | 2019-01-15 | 河北德冠隆电子科技有限公司 | The road conditions perception accident detection alarm system and method for comprehensive detection radar |
| CN109741600A (en) * | 2018-12-29 | 2019-05-10 | 南京奥杰智能科技有限公司 | Road incidents detection system |
| CN109816982A (en) * | 2019-02-25 | 2019-05-28 | 东南大学 | Virtual networks non-motorized lane attribute modification method based on shared bicycle track |
| CN109949581A (en) * | 2019-04-11 | 2019-06-28 | 浙江无极互联科技有限公司 | A kind of road condition judgment method based on computer vision |
Cited By (42)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111325977A (en) * | 2020-02-25 | 2020-06-23 | 创捷运维智能科技有限责任公司 | Tunnel intelligence edge calculation management and control system |
| CN111578964A (en) * | 2020-04-13 | 2020-08-25 | 河北德冠隆电子科技有限公司 | High-precision map road information rapid generation system and method based on space-time trajectory reconstruction |
| CN111523797A (en) * | 2020-04-21 | 2020-08-11 | 深圳中科慧据科技有限公司 | Rail transit early warning event scheduling method and device, computer equipment and storage medium |
| CN113627213A (en) * | 2020-05-06 | 2021-11-09 | 浙江宇视科技有限公司 | Vehicle abnormal behavior monitoring method, device and system |
| CN113630543B (en) * | 2020-05-06 | 2022-12-06 | 杭州海康威视数字技术股份有限公司 | Falling object and person smashing event monitoring method and device, electronic equipment and monitoring system |
| CN113627213B (en) * | 2020-05-06 | 2024-04-02 | 浙江宇视科技有限公司 | Method, device and system for monitoring abnormal behavior of vehicle |
| CN113630543A (en) * | 2020-05-06 | 2021-11-09 | 杭州海康威视数字技术股份有限公司 | Falling object and person smashing event monitoring method and device, electronic equipment and monitoring system |
| CN111613013A (en) * | 2020-06-03 | 2020-09-01 | 克拉玛依市格恩赛电子科技有限公司 | Security positioning analysis early warning system, storage medium and method |
| CN111696366A (en) * | 2020-06-04 | 2020-09-22 | 中国人民解放军战略支援部队信息工程大学 | Road accident perception and identification method and system |
| WO2021254175A1 (en) * | 2020-06-17 | 2021-12-23 | 华为技术有限公司 | Road safety monitoring method and system, and computer device |
| CN111932882A (en) * | 2020-08-13 | 2020-11-13 | 广东飞达交通工程有限公司 | Real-time early warning system, method and equipment for road accidents based on image recognition |
| CN111932882B (en) * | 2020-08-13 | 2022-05-06 | 广东飞达交通工程有限公司 | Real-time early warning system, method and equipment for road accidents based on image recognition |
| CN112257546B (en) * | 2020-10-19 | 2024-04-09 | 浙江宇视科技有限公司 | Event early warning method and device, electronic equipment and storage medium |
| CN112257546A (en) * | 2020-10-19 | 2021-01-22 | 浙江宇视科技有限公司 | Event early warning method and device, electronic equipment and storage medium |
| CN114530049A (en) * | 2020-11-06 | 2022-05-24 | 上海擎感智能科技有限公司 | Vehicle rescue and early warning method, system and computer storage medium |
| CN112700638A (en) * | 2020-12-04 | 2021-04-23 | 杭州亥迪交通设备有限公司 | Intelligent road section intelligent detection system based on laser radar and millimeter wave radar |
| CN112804489A (en) * | 2020-12-31 | 2021-05-14 | 重庆文理学院 | Internet + -based intelligent construction site management system and method |
| CN112861706A (en) * | 2021-02-04 | 2021-05-28 | 北京百度网讯科技有限公司 | Road state monitoring method, device, equipment and storage medium |
| CN115148018B (en) * | 2021-03-31 | 2024-05-24 | 海信集团控股股份有限公司 | Traffic event detection device and method |
| CN115148018A (en) * | 2021-03-31 | 2022-10-04 | 海信集团控股股份有限公司 | Traffic incident detection apparatus and method |
| CN113516343A (en) * | 2021-04-06 | 2021-10-19 | 青岛以萨数据技术有限公司 | Vehicle early warning system, method and storage medium based on map and track data |
| CN113516343B (en) * | 2021-04-06 | 2024-01-12 | 青岛以萨数据技术有限公司 | Vehicle early warning system, method and storage medium based on map and track data |
| CN113468284A (en) * | 2021-06-29 | 2021-10-01 | 北京市商汤科技开发有限公司 | Object detection method and device, electronic equipment and storage medium |
| CN113554881A (en) * | 2021-07-20 | 2021-10-26 | 周刚 | Artificial intelligence road event monitoring method, device, system and storage medium |
| CN113793524A (en) * | 2021-08-27 | 2021-12-14 | 深圳市分米互联科技有限公司 | Intelligent traffic science and technology operation platform |
| CN114333366A (en) * | 2021-09-28 | 2022-04-12 | 宁波均联智行科技股份有限公司 | Danger early warning method and device based on V2X |
| CN113920728B (en) * | 2021-10-11 | 2022-08-12 | 南京微达电子科技有限公司 | Detection and early warning method and system for obstacles thrown on highway |
| CN113920728A (en) * | 2021-10-11 | 2022-01-11 | 南京微达电子科技有限公司 | Detection and early warning method and system for obstacles thrown on expressway |
| CN114017092A (en) * | 2021-11-04 | 2022-02-08 | 山东东山新驿煤矿有限公司 | Coal mine operation ventilation system |
| CN114093152A (en) * | 2021-12-29 | 2022-02-25 | 安徽达尔智能控制系统股份有限公司 | Expressway tunnel abnormal event alarm method and system based on multiple information channels |
| CN114333330B (en) * | 2022-01-27 | 2023-04-25 | 浙江嘉兴数字城市实验室有限公司 | Intersection event detection system based on road side edge holographic sensing |
| CN114333330A (en) * | 2022-01-27 | 2022-04-12 | 浙江嘉兴数字城市实验室有限公司 | Intersection event detection system and method based on roadside edge holographic sensing |
| CN114596714A (en) * | 2022-05-10 | 2022-06-07 | 四川思百特科技有限责任公司 | Battery car guiding system and method |
| CN114596714B (en) * | 2022-05-10 | 2022-07-26 | 四川思百特科技有限责任公司 | Battery car guiding system and method |
| CN115100865A (en) * | 2022-06-24 | 2022-09-23 | 上海市政工程设计研究总院（集团）有限公司 | Management and control system for traffic safety of tunnel portal area |
| CN115019514B (en) * | 2022-08-09 | 2022-11-15 | 临沂市公路事业发展中心 | Highway inspection system based on car networking |
| CN115019514A (en) * | 2022-08-09 | 2022-09-06 | 临沂市公路事业发展中心 | Highway inspection system based on car networking |
| CN115359658A (en) * | 2022-08-17 | 2022-11-18 | 阿里云计算有限公司 | Method, device, equipment, storage medium and program product for detecting traffic incident |
| CN115641719A (en) * | 2022-10-25 | 2023-01-24 | 东南大学 | Method and device for detecting pedestrians on expressway |
| CN115641719B (en) * | 2022-10-25 | 2024-03-19 | 东南大学 | Expressway pedestrian detection method and device |
| CN117494029A (en) * | 2023-12-29 | 2024-02-02 | 苏州映赛智能科技有限公司 | Road casting event identification method and device |
| CN117494029B (en) * | 2023-12-29 | 2024-04-19 | 苏州映赛智能科技有限公司 | Road casting event identification method and device |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110473402B (en) | 2021-04-27 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110473402A (en) | A kind of accident detection early warning system based on target abnormal behaviour trajectory analysis | |
| US11074813B2 (en) | Driver behavior monitoring | |
| US20220262239A1 (en) | Determining causation of traffic events and encouraging good driving behavior | |
| CN109212520B (en) | Road condition sensing abnormal event detection alarm system and method for omnibearing detection radar | |
| CN112885144B (en) | Early warning method and system for vehicle crash event in construction operation area | |
| US11314209B2 (en) | Detection of driving actions that mitigate risk | |
| CN108919256B (en) | Four-dimensional real-scene traffic simulation vehicle overspeed whole-course tracking detection alarm system and method | |
| US10332401B2 (en) | Running vehicle alerting system and method | |
| US11380105B2 (en) | Identification and classification of traffic conflicts | |
| CN110718062B (en) | Large-area multi-target traffic incident detection system and method | |
| EP3403219A1 (en) | Driver behavior monitoring | |
| CN104809887B (en) | A kind of retrograde detection method of vehicle on expressway and autoalarm | |
| KR102360568B1 (en) | Method and system for detecting incident in tunnel environment | |
| CN114639231B (en) | Road traffic processing method, device and system | |
| Mampilayil et al. | Deep learning based detection of one way traffic rule violation of three wheeler vehicles | |
| CN113221724B (en) | Vehicle spray detection method and system | |
| CN112422672A (en) | Electronic escorting system and escorting method | |
| CN114360224A (en) | Danger distinguishing and early warning system, method and device for automobile running red light | |
| Wang et al. | Development of requirement specifications for transit frontal collision warning system | |
| Tsai | Development of a Sensing Methodology for Intelligent and Reliable Work-Zone Hazard Awareness | |
| CN115620228A (en) | Subway shield door passenger door-rushing early warning method based on video analysis |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CP02 | Change in the address of a patent holder |
Address after: 050030 2002, block B, white commercial plaza, 105 Huaian East Road, Yuhua District, Shijiazhuang City, Hebei Province Patentee after: HEBEI DEGUROON ELECTRONIC TECHNOLOGY Co.,Ltd. Address before: 050000 705, block C, white commercial plaza, 105 Huaian East Road, Yuhua District, Shijiazhuang City, Hebei Province Patentee before: HEBEI DEGUROON ELECTRONIC TECHNOLOGY Co.,Ltd. |
|
| CP02 | Change in the address of a patent holder |