CN112330964A - Road condition information monitoring method and device - Google Patents
Road condition information monitoring method and device Download PDFInfo
- Publication number
- CN112330964A CN112330964A CN202011364748.1A CN202011364748A CN112330964A CN 112330964 A CN112330964 A CN 112330964A CN 202011364748 A CN202011364748 A CN 202011364748A CN 112330964 A CN112330964 A CN 112330964A
- Authority
- CN
- China
- Prior art keywords
- population
- information
- vehicle
- data
- 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
- 238000012544 monitoring process Methods 0.000 title claims abstract description 127
- 238000000034 method Methods 0.000 title claims abstract description 44
- 238000010586 diagram Methods 0.000 claims abstract description 100
- 238000012806 monitoring device Methods 0.000 claims abstract description 6
- 238000012549 training Methods 0.000 claims description 24
- 230000011218 segmentation Effects 0.000 claims description 12
- 238000000605 extraction Methods 0.000 claims description 5
- 238000013135 deep learning Methods 0.000 claims description 4
- 238000010276 construction Methods 0.000 claims description 3
- 238000001514 detection method Methods 0.000 abstract 1
- 230000001133 acceleration Effects 0.000 description 6
- 238000011161 development Methods 0.000 description 4
- 230000018109 developmental process Effects 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 206010039203 Road traffic accident Diseases 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000007547 defect Effects 0.000 description 1
- DMBHHRLKUKUOEG-UHFFFAOYSA-N diphenylamine Chemical group C=1C=CC=CC=1NC1=CC=CC=C1 DMBHHRLKUKUOEG-UHFFFAOYSA-N 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- 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
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B7/00—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00
- G08B7/06—Signalling systems according to more than one of groups G08B3/00 - G08B6/00; Personal calling systems according to more than one of groups G08B3/00 - G08B6/00 using electric transmission, e.g. involving audible and visible signalling through the use of sound and light sources
-
- 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
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Traffic Control Systems (AREA)
Abstract
The embodiment of the invention provides a road condition information monitoring method and a road condition information monitoring device, wherein the method comprises the following steps: constructing a population thermodynamic diagram and a vehicle real-time movement data diagram of a target monitoring area; acquiring road network data of the target monitoring area; respectively extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram; and monitoring whether the users in the target monitoring area are in a dangerous environment or not according to the population information and the vehicle movement information. According to the embodiment of the invention, population thermodynamic diagrams and vehicle real-time movement data diagrams are used for extracting population information and vehicle movement information, so that whether the environment where a user is located is safe or not is judged, and the accuracy of the detection result is ensured.
Description
Technical Field
The embodiment of the invention relates to the technical field of traffic safety, in particular to a road condition information monitoring method and a road condition information monitoring device.
Background
In recent years, the progress of science and technology has led to rapid development of the traffic field, and people go out by walking and simple transportation means such as a bicycle, and come to various transportation means such as the existing electric vehicle, automobile and unmanned automobile. However, the development of the traffic field brings convenience to people, and meanwhile, a plurality of potential safety hazards are increased, and traffic safety accidents happen occasionally. If the traffic accident cannot be timely alarmed and handled, larger loss is easily caused.
In the related art, a safety monitoring method is provided, that is, whether a user driving or riding a vehicle is in a dangerous state is determined according to state information of the vehicle, such as vehicle running speed, acceleration and the like, and when the acceleration is greater than a preset threshold, the user is determined to be in the dangerous state.
However, the result is not accurate only through the vehicle state information, for example, when a user drives a vehicle and encounters an emergency, the vehicle may suddenly brake, the acceleration of the vehicle may also change greatly, but an accident may occur, and a false alarm may be generated.
Disclosure of Invention
The embodiment of the invention provides a road condition information monitoring method and a road condition information monitoring device, which aim to solve the technical problems that in the prior art, the road condition information is not accurately monitored, whether a user is in a dangerous state or not can not be accurately judged, and therefore false alarm is caused.
In a first aspect, an embodiment of the present invention provides a method for monitoring road condition information, including:
constructing a population thermodynamic diagram and a vehicle real-time movement data diagram of a target monitoring area;
acquiring road network data of the target monitoring area;
respectively extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram;
and monitoring whether the users in the target monitoring area are in a dangerous environment or not according to the population information and the vehicle movement information.
Optionally, the constructing a population thermodynamic diagram and a vehicle real-time movement data diagram of the target monitoring area includes:
acquiring user real-time position information and vehicle real-time position information in the target monitoring area;
and constructing the population thermodynamic diagram according to the user real-time position information, determining the vehicle moving speed according to the vehicle real-time position information, and generating the vehicle real-time moving data diagram according to the vehicle moving speed.
Optionally, the obtaining road network data of the target monitoring area includes:
obtaining a remote sensing image corresponding to the target monitoring area;
and extracting the road network data from the remote sensing image.
Optionally, the road network data includes trunk road data and branch road data, the extracting the road network data from the remote sensing image includes:
and inputting the remote sensing image into a semantic segmentation network model obtained by pre-training to obtain trunk road data and branch road data in the remote sensing image.
Optionally, the method further includes:
acquiring training samples, wherein the training samples are a plurality of remote sensing images marked with road network data labels;
and inputting the training samples into a deep learning network for training to obtain the semantic segmentation network model.
Optionally, the extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram respectively includes:
and respectively extracting population information and vehicle movement information in a trunk road area and a branch road area in the population thermodynamic diagram and the vehicle real-time movement data diagram according to the trunk road data and the branch road data.
Optionally, the population information includes population number and population movement speed, the vehicle movement information includes vehicle movement speed, and monitoring whether a user in the target monitoring area is in a dangerous environment according to the population information and the vehicle movement information includes:
if the population number is larger than a first number threshold value, and the population moving speed and the vehicle moving speed are both smaller than a first speed threshold value, determining that the user in the target monitoring area is in a safe environment;
and if the population number is smaller than a second number threshold, determining that the users in the target monitoring area, the moving speeds of which are smaller than a second speed threshold in a preset time length, are in a dangerous environment.
In a second aspect, an embodiment of the present invention provides an information monitoring apparatus, including:
the construction module is used for constructing a population thermodynamic diagram and a vehicle real-time movement data diagram of the target monitoring area;
the acquisition module is used for acquiring road network data of the target monitoring area;
the extraction module is used for respectively extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram;
and the monitoring module is used for monitoring whether the user in the target monitoring area is in a dangerous environment or not according to the population information and the vehicle movement information.
In a third aspect, an embodiment of the present invention provides an electronic device, including: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the traffic information monitoring method according to the first aspect and various possible designs of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, where a computer executing instruction is stored in the computer-readable storage medium, and when a processor executes the computer executing instruction, the traffic information monitoring method according to the first aspect and various possible designs of the first aspect is implemented.
According to the road condition information monitoring method and device provided by the embodiment of the invention, a population thermodynamic diagram and a vehicle real-time moving data diagram of a target monitoring area are constructed; acquiring road network data of the target monitoring area; then respectively extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram; and monitoring whether the users in the target monitoring area are in a dangerous environment or not according to the population information and the vehicle movement information. According to the embodiment, the population thermodynamic diagram and the real-time vehicle movement data diagram are constructed, and then whether the user in the target monitoring area is in a dangerous environment or not is monitored according to the population information in the area corresponding to the road network data in the population thermodynamic diagram and the vehicle movement information in the vehicle real-time movement data diagram, so that the accuracy of road condition information monitoring is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is an application scene diagram of a road condition information monitoring method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a road condition information monitoring method according to an embodiment of the present invention;
fig. 3 is a schematic flow chart of a road condition information monitoring method according to another embodiment of the present invention;
FIG. 4 is a population thermodynamic diagram provided by an embodiment of the present invention;
fig. 5a is a schematic diagram of a remote sensing image according to an embodiment of the present invention;
fig. 5b is a schematic diagram of a road network extracted from a remote sensing image according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of a traffic information monitoring device according to an embodiment of the present invention;
fig. 7 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In recent years, the progress of science and technology has led to rapid development of the traffic field, and people go out by walking and simple transportation means such as a bicycle, and come to various transportation means such as the existing electric vehicle, automobile and unmanned automobile. However, the development of the traffic field brings convenience to people, and meanwhile, a plurality of potential safety hazards are increased, and traffic safety accidents happen occasionally. If the traffic accident cannot be timely alarmed and handled, larger loss is easily caused.
In the related art, a safety monitoring method is provided, that is, whether a user driving or riding a vehicle is in a dangerous state is determined according to state information of the vehicle, such as vehicle running speed, acceleration and the like, and when the acceleration is greater than a preset threshold, the user is determined to be in the dangerous state. However, the result is not accurate only through the vehicle state information, for example, when a user drives a vehicle and encounters an emergency, the vehicle may suddenly brake, the acceleration of the vehicle may also change greatly, but an accident may occur, and a false alarm may be generated.
Aiming at the defect, the technical concept provided by the application is as follows: constructing a population thermodynamic diagram and a vehicle real-time movement data diagram of a target monitoring area; acquiring road network data of the target monitoring area; then respectively extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram; and monitoring whether the users in the target monitoring area are in a dangerous environment or not according to the population information and the vehicle movement information. According to the embodiment, the population thermodynamic diagram and the vehicle real-time mobile data diagram are constructed, and then whether the user in the target monitoring area is in a dangerous environment or not is monitored according to the population information in the area corresponding to the road network data in the population thermodynamic diagram and the vehicle mobile information in the vehicle real-time mobile data diagram, so that the accuracy of road condition information monitoring is improved.
Fig. 1 is an application scenario diagram of a road condition information monitoring method according to an embodiment of the present invention.
As shown in fig. 1, in the application scenario provided in this embodiment, a Beidou Positioning System or a Global Positioning System (GPS) 101 acquires real-time location information of a user and a vehicle in a monitoring area, and then sends the real-time location information to a server 102, and the server processes the real-time location information to obtain road condition information in the monitoring area, thereby determining whether a traffic environment in the monitoring area is safe and whether the user is in a safe state, and sending a final monitoring result to a display terminal 103 for display.
The real-time position information is obtained by detecting a positioning device mounted on an electronic device such as a mobile phone carried by a user and a positioning device carried by a vehicle.
Fig. 2 is a schematic flow chart of a traffic information monitoring method according to an embodiment of the present invention, and an execution main body of the method according to this embodiment may be a server in the embodiment shown in fig. 1.
As shown in fig. 2, the method provided by the present embodiment may include the following steps.
S201, constructing a population thermodynamic diagram and a vehicle real-time movement data diagram of a target monitoring area.
Specifically, the position information of the user is collected in real time through positioning devices installed in electronic equipment such as mobile phones carried by all users in a monitoring area, and the position information of the vehicle is collected in real time through the positioning devices installed on the vehicle. And calculating the movement information of all users in the monitoring area according to the real-time position information of the users, wherein the movement information comprises the number of the users in the target monitoring area, the movement speed of each user and the like, and then constructing a population thermodynamic diagram according to the movement information of all the users in the monitoring area, such as the population thermodynamic diagram shown in fig. 4. Similarly, the vehicle speed is calculated according to the real-time position information of the vehicles in the target monitoring area, and then a vehicle real-time movement data graph is generated according to the movement speed of each vehicle.
Wherein, positioner can be big dipper positioner or GPS positioner.
And S202, acquiring road network data of the target monitoring area.
The road network data is main road data and branch road data in a target monitoring area, for example, position area information of the main road and the branch road.
In one possible embodiment, remote sensing images of the target monitoring area, such as satellite photos and space photos, can be obtained through networking, and then road network data in the target monitoring area is extracted from the remote sensing images.
For example, assuming that the obtained remote sensing image of the target monitoring area is shown in fig. 5a, the data of the trunk road and the branch road in the remote sensing image may be extracted through an image processing algorithm, and the extracted image is shown in fig. 5 b. The specific extraction method will be described in the following examples.
And S203, respectively extracting population information and vehicle movement information in the region corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram.
Specifically, the population thermodynamic diagram and the vehicle real-time movement data diagram obtained in the above steps respectively reflect population movement information and vehicle movement information of the entire target monitoring area, and in order to more accurately monitor road condition information on a road, it is necessary to extract the population information and the vehicle movement information in the area corresponding to the road network data obtained in step S202. For example, according to the population thermodynamic diagram, the population number and population moving speed on trunk roads and branch roads in the target monitoring area are extracted, and according to the vehicle real-time moving data diagram, vehicle moving information on the trunk roads and the branch roads in the target monitoring area is extracted.
And S204, monitoring whether the user in the target monitoring area is in a dangerous environment or not according to the population information and the vehicle movement information.
Specifically, whether a trunk road and a branch road of a target monitoring area are congested or not can be judged according to population information and vehicle movement information, and if the trunk road and the branch road are in a congested road section and the overall movement speed is slow, it is judged that people moving slowly in the area are in a safe environment; if the surrounding population is small and the vehicle is moving slowly, it is determined that the user is likely to be in a dangerous environment.
In the embodiment, a population thermodynamic diagram and a vehicle real-time movement data diagram of a target monitoring area are constructed; acquiring road network data of the target monitoring area; then respectively extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram; and monitoring whether the users in the target monitoring area are in a dangerous environment or not according to the population information and the vehicle movement information. According to the embodiment, the population thermodynamic diagram and the vehicle real-time mobile data diagram are constructed, and then whether the user in the target monitoring area is in a dangerous environment or not is monitored according to the population information in the area corresponding to the road network data in the population thermodynamic diagram and the vehicle mobile information in the real-time vehicle mobile data diagram, so that the accuracy of road condition information monitoring is improved.
Fig. 3 is a schematic flow chart of a road condition information monitoring method according to another embodiment of the present invention, and the present embodiment further describes the road condition information monitoring method in detail based on the embodiment shown in fig. 2.
As shown in fig. 3, the method provided by the present embodiment may include the following steps.
S301, a population thermodynamic diagram and a vehicle real-time movement data diagram of the target monitoring area are constructed in real time.
Specifically, the position information of the user is collected in real time through positioning devices installed in electronic equipment such as mobile phones carried by all users in a monitoring area, and the position information of the vehicle is collected in real time through the positioning devices installed on the vehicle. And then, a population thermodynamic diagram is constructed according to the mobile information of all the users in the monitoring area, and the thermodynamic area in the population thermodynamic diagram changes according to the movement of the population. Similarly, the vehicle speed is calculated according to the real-time position information of the vehicles in the target monitoring area, and then a vehicle real-time movement data graph is generated according to the movement speed of each vehicle.
And S302, obtaining a remote sensing image corresponding to the target monitoring area.
Specifically, the remote sensing image is an aerial photograph obtained by continuously photographing from the air to the ground through a photo obtained by a remote sensor installed on a satellite and an aerial photograph obtained by an aerial camera, and the satellite or the aerial camera transmits the obtained remote sensing image to a server on the ground.
And S303, extracting road network data from the remote sensing image based on a semantic segmentation network model obtained by pre-training, wherein the road network data comprises trunk road data and branch road data.
In some embodiments, before extracting the road network data, a semantic segmentation network model needs to be obtained through training, specifically, a remote sensing image road network database is established, a large number of training samples are stored in the database, that is, after a large number of remote sensing images are obtained, technicians label main roads and branch roads in each remote sensing image (that is, road network data labels), and input the remote sensing image with the labels into a deep learning network model for training, so as to obtain the semantic segmentation network model.
It should be noted that, in the training process, parameters in the network model need to be adjusted according to the training result to obtain an optimal training result.
Further, after the semantic segmentation network model is obtained through training, after a remote sensing image (refer to fig. 5a) of the target monitoring area is obtained, the remote sensing image is input into the semantic segmentation network model as an input quantity, the semantic segmentation network model automatically extracts road network data in the remote sensing image, and a result is extracted and referred to fig. 5 b.
And S304, respectively extracting population information and vehicle movement information in a trunk road area and a branch road area in the population thermodynamic diagram and the vehicle real-time movement data diagram according to the trunk road data and the branch road data.
The population information comprises population number and population moving speed, and the vehicle moving information comprises vehicle moving speed.
In this step, in order to more accurately monitor road condition information on a road, population information and vehicle movement information in an area corresponding to the acquired road network data need to be extracted.
Specifically, according to the population thermodynamic diagram, the population number and the population moving speed on a trunk road and a branch road in the population thermodynamic diagram are extracted, and the vehicle moving speed on the trunk road and the branch road in the target monitoring area is obtained according to the vehicle real-time moving data diagram.
In a possible embodiment, the population thermodynamic diagram and the vehicle movement data diagram are respectively, and the server respectively generates the population thermodynamic diagram and the vehicle movement data diagram after acquiring the number and the movement speed of all users and the number and the movement speed of vehicles in the target monitoring area, and simultaneously stores real-time information such as the number of all users, user position information, user movement speed, vehicle number, vehicle position information, vehicle movement speed and the like in the target monitoring area into the database, and after extracting road network data (main road position information and branch road position information) in the remote sensing image, the server acquires the corresponding number of users, the movement speed of each user, the number of vehicles and the movement speed of each vehicle on the main road and the branch road in the database according to the road network data.
S305, monitoring whether the user in the target monitoring area is in a dangerous environment or not according to the population information and the vehicle movement information.
In some embodiments, if the population number is greater than a first number threshold and the population movement speed and the vehicle movement speed are both less than a first speed threshold, determining that the users within the target monitoring area are in a safe environment; and if the population number is smaller than a second number threshold, determining that the users in the target monitoring area, the moving speeds of which are smaller than a second speed threshold in a preset time length, are in a dangerous environment. The first number threshold, the first speed threshold, the second number threshold and the second speed threshold can be determined according to actual conditions.
Specifically, if the population number is greater than a first number threshold value, and the population moving speed and the vehicle moving speed are both less than a first speed threshold value, it is indicated that the road section is relatively congested, and the overall moving speed is slow, and belongs to a normal road condition, so that it is determined that the user in the target monitoring area is in a safe environment. If the population number is smaller than the second number threshold, the road section is indicated to have fewer people, normally, the moving speed of the vehicle is not too slow in the road section with fewer people, and if the moving speed of the vehicle is monitored to be too slow and the moving speed of the vehicle is too slow in a preset time period, the user is indicated to be possibly in a dangerous environment.
It can be understood that, since the vehicle may temporarily stop in a special situation during the driving process, in this case, even if the road section where the vehicle is located is not congested, the driving speed of the vehicle may still be smaller than the second speed threshold, therefore, a preset time period is set, and if the moving speed of the vehicle is consistently smaller than the second speed threshold within the preset time period, it is determined that the user may be in a dangerous environment, and the accuracy of the determination is increased to a certain extent.
In a possible embodiment, after monitoring whether a user in the target monitoring area is in a dangerous environment, alarm information is generated according to a monitoring result, and the alarm information is displayed on a display screen in a text mode, or the alarm information is played in a voice mode, or related personnel are prompted in a sound-light alarm mode, so that the related personnel can conveniently and timely handle the alarm information.
Fig. 6 is a schematic structural diagram of a traffic information monitoring device according to an embodiment of the present invention.
As shown in fig. 6, the apparatus provided in this embodiment includes: a construction module 601, an acquisition module 602, an extraction module 603 and a monitoring module 604; the building module 601 is used for building a population thermodynamic diagram and a vehicle real-time movement data diagram of a target monitoring area; an obtaining module 602, configured to obtain road network data of the target monitoring area; an extracting module 603, configured to extract population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram, respectively; and the monitoring module 604 is configured to monitor whether the user in the target monitoring area is in a dangerous environment according to the population information and the vehicle movement information.
In some embodiments, the building module is specifically configured to: acquiring user real-time position information and vehicle real-time position information in the target monitoring area; and constructing the population thermodynamic diagram according to the user real-time position information, determining the vehicle moving speed according to the vehicle real-time position information, and generating the vehicle real-time moving data diagram according to the vehicle moving speed.
In some embodiments, the obtaining module is specifically configured to: obtaining a remote sensing image corresponding to the target monitoring area; and extracting the road network data from the remote sensing image.
In some embodiments, the obtaining module is specifically configured to: and inputting the remote sensing image into a semantic segmentation network model obtained by pre-training to obtain trunk road data and branch road data in the remote sensing image.
In some embodiments, the apparatus provided in this embodiment further includes: the training module is used for acquiring training samples, and the training samples are a plurality of remote sensing images marked with road network data labels; and inputting the training samples into a deep learning network for training to obtain the semantic segmentation network model.
In some embodiments, the extraction module is specifically configured to: and respectively extracting population information and vehicle movement information in a trunk road area and a branch road area in the population thermodynamic diagram and the vehicle real-time movement data diagram according to the trunk road data and the branch road data.
In some embodiments, the monitoring module is specifically configured to: if the population number is larger than a first number threshold value, and the population moving speed and the vehicle moving speed are both smaller than a first speed threshold value, determining that the user in the target monitoring area is in a safe environment; and if the population number is smaller than a second number threshold, determining that the users in the target monitoring area, the moving speeds of which are smaller than a second speed threshold in a preset time length, are in a dangerous environment.
The apparatus provided in this embodiment may be used to implement the technical solutions of the above method embodiments, and the implementation principles and technical effects are similar, which are not described herein again.
Fig. 7 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present invention. As shown in fig. 7, the electronic apparatus 70 of the present embodiment includes: a processor 701 and a memory 702; wherein
A memory 702 for storing computer-executable instructions;
the processor 701 is configured to execute the computer-executable instructions stored in the memory to implement the steps performed by the network coverage problem identification method in the above embodiments. Reference may be made in particular to the description relating to the method embodiments described above.
Alternatively, the memory 702 may be separate or integrated with the processor 701.
When the memory 702 is provided separately, the electronic device further includes a bus 703 for connecting the memory 702 and the processor 701.
An embodiment of the present invention further provides a computer-readable storage medium, where a computer execution instruction is stored in the computer-readable storage medium, and when a processor executes the computer execution instruction, the method for monitoring road condition information as described above is implemented.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules is only one logical division, and other divisions may be realized in practice, for example, a plurality of modules may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to implement the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each module may exist alone physically, or two or more modules are integrated into one unit. The unit formed by the modules can be realized in a hardware form, and can also be realized in a form of hardware and a software functional unit.
The integrated module implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a processor to execute some steps of the methods described in the embodiments of the present application.
It should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor, or in a combination of the hardware and software modules within the processor.
The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile storage NVM, such as at least one disk memory, and may also be a usb disk, a removable hard disk, a read-only memory, a magnetic or optical disk, etc.
The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present application are not limited to only one bus or one type of bus.
The storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the storage medium may reside as discrete components in an electronic device or host device.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A road condition information monitoring method is characterized by comprising the following steps:
constructing a population thermodynamic diagram and a vehicle real-time movement data diagram of a target monitoring area;
acquiring road network data of the target monitoring area;
respectively extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram;
and monitoring whether the users in the target monitoring area are in a dangerous environment or not according to the population information and the vehicle movement information.
2. The method of claim 1, wherein the constructing a population thermodynamic map and vehicle real-time movement data map of the target monitoring area comprises:
acquiring user real-time position information and vehicle real-time position information in the target monitoring area;
and constructing the population thermodynamic diagram according to the user real-time position information, determining the vehicle moving speed according to the vehicle real-time position information, and generating the vehicle real-time moving data diagram according to the vehicle moving speed.
3. The method of claim 1, wherein said obtaining road network data for said target monitoring area comprises:
obtaining a remote sensing image corresponding to the target monitoring area;
and extracting the road network data from the remote sensing image.
4. The method of claim 3, wherein said road network data comprises trunk road data and branch road data, and said extracting said road network data from said remote sensing image comprises:
and inputting the remote sensing image into a semantic segmentation network model obtained by pre-training to obtain trunk road data and branch road data in the remote sensing image.
5. The method of claim 4, further comprising:
acquiring training samples, wherein the training samples are a plurality of remote sensing images marked with road network data labels;
and inputting the training samples into a deep learning network for training to obtain the semantic segmentation network model.
6. The method of claim 4, wherein said extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram, respectively, comprises:
and respectively extracting population information and vehicle movement information in a trunk road area and a branch road area in the population thermodynamic diagram and the vehicle real-time movement data diagram according to the trunk road data and the branch road data.
7. The method of any one of claims 1-6, wherein the population information includes population number and population movement speed, wherein the vehicle movement information includes vehicle movement speed, and wherein the monitoring whether the users in the target monitoring area are in a dangerous environment according to the population information and the vehicle movement information comprises:
if the population number is larger than a first number threshold value, and the population moving speed and the vehicle moving speed are both smaller than a first speed threshold value, determining that the user in the target monitoring area is in a safe environment;
and if the population number is smaller than a second number threshold, determining that the users in the target monitoring area, the moving speeds of which are smaller than a second speed threshold in a preset time length, are in a dangerous environment.
8. A road condition information monitoring device is characterized by comprising:
the construction module is used for constructing a population thermodynamic diagram and a vehicle real-time movement data diagram of the target monitoring area;
the acquisition module is used for acquiring road network data of the target monitoring area;
the extraction module is used for respectively extracting population information and vehicle movement information in an area corresponding to the road network data in the population thermodynamic diagram and the vehicle real-time movement data diagram;
and the monitoring module is used for monitoring whether the user in the target monitoring area is in a dangerous environment or not according to the population information and the vehicle movement information.
9. An electronic device, comprising: at least one processor and memory;
the memory stores computer-executable instructions;
the at least one processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the traffic information monitoring method according to any one of claims 1 to 7.
10. A computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when a processor executes the computer-executable instructions, the method for monitoring road condition information according to any one of claims 1 to 7 is implemented.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011364748.1A CN112330964B (en) | 2020-11-27 | 2020-11-27 | Road condition information monitoring method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011364748.1A CN112330964B (en) | 2020-11-27 | 2020-11-27 | Road condition information monitoring method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112330964A true CN112330964A (en) | 2021-02-05 |
| CN112330964B CN112330964B (en) | 2021-11-30 |
Family
ID=74309334
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011364748.1A Active CN112330964B (en) | 2020-11-27 | 2020-11-27 | Road condition information monitoring method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112330964B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114337777A (en) * | 2021-12-23 | 2022-04-12 | 广州爱浦路网络技术有限公司 | Thermodynamic diagram-based satellite energy-saving method, system, device and medium |
| CN114973732A (en) * | 2022-04-20 | 2022-08-30 | 安徽皖通科技股份有限公司 | Voice guidance system and method based on intelligent road network monitoring |
| CN116136415A (en) * | 2023-02-07 | 2023-05-19 | 深圳市冠标科技发展有限公司 | Navigation guidance method, device, electronic equipment and storage medium |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102129776A (en) * | 2011-04-28 | 2011-07-20 | 北京市劳动保护科学研究所 | Automatic detection method and system of abnormal pedestrian traffic state |
| CN105632202A (en) * | 2014-10-30 | 2016-06-01 | 唐国桥 | Real-time speed adjustment guiding method and navigation software |
| CN106297279A (en) * | 2015-05-20 | 2017-01-04 | 中兴通讯股份有限公司 | A kind of real-time road monitoring method and system |
| CN106571064A (en) * | 2016-11-10 | 2017-04-19 | 深圳市元征软件开发有限公司 | Pedestrian monitoring method based on roadside unit and pedestrian monitoring device thereof |
| CN107161100A (en) * | 2017-05-04 | 2017-09-15 | 广东轻工职业技术学院 | A kind of pedestrains safety guard method and system |
| US20180012504A1 (en) * | 2016-07-11 | 2018-01-11 | Izak Jan van Cruyningen | UAV Routing in Utility Rights of Way |
| CN108492625A (en) * | 2018-03-25 | 2018-09-04 | 张小莲 | A kind of pedestrian's intelligent collision traffic management control system based on NB-IoT |
| CN109889991A (en) * | 2019-04-28 | 2019-06-14 | 广东小天才科技有限公司 | Safety reminding method and device and mobile device |
| US20190251843A1 (en) * | 2018-02-09 | 2019-08-15 | Blackberry Limited | Method and apparatus for vulnerable road user alert |
| CN110738871A (en) * | 2019-09-29 | 2020-01-31 | 北京浪潮数据技术有限公司 | prompting method and system |
| CN111383362A (en) * | 2018-12-29 | 2020-07-07 | 北京骑胜科技有限公司 | Safety monitoring method and device |
-
2020
- 2020-11-27 CN CN202011364748.1A patent/CN112330964B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102129776A (en) * | 2011-04-28 | 2011-07-20 | 北京市劳动保护科学研究所 | Automatic detection method and system of abnormal pedestrian traffic state |
| CN105632202A (en) * | 2014-10-30 | 2016-06-01 | 唐国桥 | Real-time speed adjustment guiding method and navigation software |
| CN106297279A (en) * | 2015-05-20 | 2017-01-04 | 中兴通讯股份有限公司 | A kind of real-time road monitoring method and system |
| US20180012504A1 (en) * | 2016-07-11 | 2018-01-11 | Izak Jan van Cruyningen | UAV Routing in Utility Rights of Way |
| CN106571064A (en) * | 2016-11-10 | 2017-04-19 | 深圳市元征软件开发有限公司 | Pedestrian monitoring method based on roadside unit and pedestrian monitoring device thereof |
| CN107161100A (en) * | 2017-05-04 | 2017-09-15 | 广东轻工职业技术学院 | A kind of pedestrains safety guard method and system |
| US20190251843A1 (en) * | 2018-02-09 | 2019-08-15 | Blackberry Limited | Method and apparatus for vulnerable road user alert |
| CN108492625A (en) * | 2018-03-25 | 2018-09-04 | 张小莲 | A kind of pedestrian's intelligent collision traffic management control system based on NB-IoT |
| CN111383362A (en) * | 2018-12-29 | 2020-07-07 | 北京骑胜科技有限公司 | Safety monitoring method and device |
| CN109889991A (en) * | 2019-04-28 | 2019-06-14 | 广东小天才科技有限公司 | Safety reminding method and device and mobile device |
| CN110738871A (en) * | 2019-09-29 | 2020-01-31 | 北京浪潮数据技术有限公司 | prompting method and system |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114337777A (en) * | 2021-12-23 | 2022-04-12 | 广州爱浦路网络技术有限公司 | Thermodynamic diagram-based satellite energy-saving method, system, device and medium |
| CN114337777B (en) * | 2021-12-23 | 2022-12-02 | 广州爱浦路网络技术有限公司 | Thermodynamic diagram-based satellite energy-saving method and computer-readable storage medium |
| CN114973732A (en) * | 2022-04-20 | 2022-08-30 | 安徽皖通科技股份有限公司 | Voice guidance system and method based on intelligent road network monitoring |
| CN114973732B (en) * | 2022-04-20 | 2023-09-08 | 安徽皖通科技股份有限公司 | Speech guiding system and method based on intelligent road network monitoring |
| CN116136415A (en) * | 2023-02-07 | 2023-05-19 | 深圳市冠标科技发展有限公司 | Navigation guidance method, device, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112330964B (en) | 2021-11-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112330964B (en) | Road condition information monitoring method and device | |
| CN109145680B (en) | Method, device and equipment for acquiring obstacle information and computer storage medium | |
| CN111506980B (en) | Method and device for generating traffic scene for virtual driving environment | |
| CN109345829B (en) | Unmanned vehicle monitoring method, device, equipment and storage medium | |
| CN108256404B (en) | Pedestrian detection method and device | |
| CN109655075B (en) | Unmanned vehicle positioning method and device | |
| CN109377694B (en) | Monitoring method and system for community vehicles | |
| CN104239386A (en) | Method and system for prioritizion of facial recognition matches | |
| CN111914656A (en) | Personnel behavior detection method and device, electronic equipment and storage medium | |
| CN111428644A (en) | Zebra crossing region monitoring method, system and medium based on deep neural network | |
| CN109564724A (en) | Information processing method, information processing unit and message handling program | |
| CN110147731A (en) | Vehicle type recognition method and Related product | |
| CN112907867A (en) | Early warning method and device based on image recognition and server | |
| CN114194180A (en) | Method, device, equipment and medium for determining auxiliary parking information | |
| CN113657299A (en) | Traffic accident determination method and electronic equipment | |
| CN115965913A (en) | Security monitoring method, device and system and computer readable storage medium | |
| CN112562406A (en) | Method and device for identifying off-line driving | |
| CN111582239A (en) | Violation monitoring method and device | |
| CN115019242A (en) | Abnormal event detection method and device for traffic scene and processing equipment | |
| CN115165398A (en) | Vehicle driving function test method and device, computing equipment and medium | |
| JP6606779B6 (en) | Information providing apparatus, information providing method, and program | |
| CN115981344B (en) | Automatic driving method and device | |
| CN111626419A (en) | Convolutional neural network structure, target detection method and device | |
| CN110852253A (en) | Ladder control scene detection method and device and electronic equipment | |
| CN116311157A (en) | Obstacle recognition method and obstacle recognition model training method |
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 |