CN112037509A - Urban traffic situation perception method and early warning system based on big data - Google Patents
Urban traffic situation perception method and early warning system based on big data Download PDFInfo
- Publication number
- CN112037509A CN112037509A CN202010851525.1A CN202010851525A CN112037509A CN 112037509 A CN112037509 A CN 112037509A CN 202010851525 A CN202010851525 A CN 202010851525A CN 112037509 A CN112037509 A CN 112037509A
- Authority
- CN
- China
- Prior art keywords
- traffic
- road
- detection module
- unit
- urban
- 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.)
- Pending
Links
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
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention discloses a big data-based urban traffic situation perception method and an early warning system. A cloud service platform and a detection unit are arranged to be matched for use, the detection unit collects data of multiple factors of parking spaces, smoke, traffic flow, pedestrian flow, motorcade length, vehicle speed, lane occupation, vehicle distance and driving time which affect urban road traffic through big data, and combines basic conditions of roads to carry out weighted average to obtain the traffic situation of the current urban whole road section, so that the overall situation of urban traffic can be reflected more accurately.
Description
Technical Field
The invention relates to the field of big data, in particular to the field of urban traffic situation perception methods and early warning systems based on big data.
Background
As is well known, the existing urban traffic is crowded, and in order to solve the problem of the existing urban traffic being crowded, many people think of relieving the situation of the urban traffic being crowded by changing the waiting time of traffic lights.
For example, a new intelligent traffic light control system is disclosed in the current chinese patent No. CN100595809C, which is mainly composed of a camera module, an identifier, a server and a traffic light controller which are cascaded in sequence, wherein the identifier includes a vehicle detection module, a flow detection module, a vehicle snapshot module, a vehicle number plate identification module and a vehicle type identification module; the recognizer adopts a video virtual coil technology to count passing vehicles, calculates the traffic flow, recognizes the vehicle type and the number plate according to the snapshot image, and inputs other information formed by the traffic flow, the vehicle type and the number plate to the traffic light time operation module. The invention has high vehicle counting accuracy, greatly increases the amount of acquired information, can calculate the traffic light time with the shortest average waiting time of the vehicles and saves road traffic resources.
Although the situation of road congestion is relieved to a certain extent by utilizing the patents, the method also has some problems that firstly, the method only collects the information of traffic flow, vehicle type and number plate, the collected information is comparatively comprehensive, the factors influencing the congestion of urban traffic are required to be known to be various, and how to consider each influencing factor in place is a problem, secondly, the problem of road congestion can not be solved only by adjusting the time of the traffic lights in real time, and the problem can be solved by combining a plurality of departments such as a driver, a traffic management department, a medical care department, a fire department and the like in emergency, how to quickly enable a driver, a traffic management department, a medical care department and a plurality of fire departments to quickly know the urban road condition in real time and quickly solve the emergency is an urgent problem to be solved, in order to solve the problems, a city traffic situation perception method and an early warning system based on big data are provided.
Disclosure of Invention
The invention mainly aims to provide an urban traffic situation perception method and an early warning system based on big data, which can effectively solve the problems in the background technology: the factor that influences the jam of urban traffic is various, how to consider each influence factor to target in place is a problem, secondly, solve the crowded problem of road and can not only rely on the time of real time adjustment traffic lights to solve, meet emergency and still need driver, traffic control department, medical care department and many departments such as fire department to jointly solve, how to make driver, traffic control department, medical care department and many departments of fire department can both know the condition of urban road fast and in real time and solve emergency fast like this is a problem that awaits for a moment to solve.
In order to achieve the purpose, the invention adopts the technical scheme that:
a city traffic situation perception method based on big data comprises the following steps:
1) the method comprises the steps that a large data platform is utilized to carry out comprehensive system modeling on basic conditions of road routes of a city through modeling software, a city traffic cloud service platform is built, and an access port and an access mode of the cloud service platform are determined through the roles of all departments;
2) the detection unit carries out real-time, comprehensive and systematic detection and perception on the conditions of each road line of the city through a parking space detection module, a smoke detection module, a traffic flow detection module, a pedestrian flow detection module, a fleet length detection module, a vehicle speed detection module, a lane occupation detection module, a vehicle distance detection module and a driving time detection module, effectively displays the conditions in a model established by modeling software, and meanwhile updates the detection result of the detection unit on a cloud platform in real time;
3) carrying out weighted average on data of multiple factors of detected parking spaces, smoke, traffic flow, pedestrian flow, fleet length, vehicle speed, lane occupancy, vehicle distance and driving time by combining basic conditions of roads to obtain the traffic situation of the current urban whole road section, and analyzing the time-space evolution process of urban roads to further send out early warning information;
4) various conditions of urban traffic are shared to drivers, traffic management departments, medical care departments and fire departments in real time through the cloud service platform, and the traffic light control module of the control unit processes various problems generated in the urban traffic by adjusting the time of the traffic light in real time.
The invention has further technical improvements that: an urban traffic situation and early warning system based on big data comprises a detection unit, an alarm unit, a control unit, a cloud service platform, an information transmission unit, a Beidou positioning service unit, a data storage unit and a calculation unit, the detection unit is suitable for detecting and sensing the condition of each road line of a city in real time, comprehensively and systematically through a plurality of detection modules, the alarm unit is suitable for rapidly giving an alarm on the road jam condition to enable a driver to know the road jam condition as early as possible, the control unit is suitable for controlling the operation of the whole system, and the calculation unit is suitable for carrying out weighted average on the data measured by the detection unit to obtain the traffic situation of the whole road section of the current city, the data storage unit is suitable for storing the data detected by the detection mechanism so as to provide scientific basis for later road construction.
The invention has further technical improvements that: the cloud service platform is suitable for displaying information detected by the detection unit and information of the whole system at each terminal by utilizing a big data network so that a user can accurately know the accurate condition of the whole urban road, the Beidou positioning service unit is suitable for providing positioning and navigation services for the user through a Beidou navigation system, the information transmission unit is suitable for conducting mutual information transmission between the user and the cloud service platform through big data and an internet system, the control unit comprises a traffic light control module, and the traffic light control module is suitable for comprehensively solving various problems of different positions, different times and different conditions in the urban traffic road through controlling the conversion time interval of traffic lights in real time.
The invention has further technical improvements that: the detection unit comprises a parking space detection module, a smoke detection module, a traffic flow detection module, a pedestrian flow detection module, a fleet length detection module, a vehicle speed detection module, a lane occupation detection module, a vehicle distance detection module and a driving time detection module, the parking space detection module is suitable for detecting the saturation of the parking space of the city through a big data system, accurate parking space saturation information is provided for drivers on a cloud platform, the smoke detection module is suitable for detecting smoke generated on each traffic road in a city, and judges the occurrence of traffic accidents based on the traffic flow, the traffic flow detection module is suitable for detecting the traffic flow of each traffic road in the city, the pedestrian flow detection module is suitable for detecting pedestrian flow of each traffic road in a city, and the motorcade length detection module is suitable for detecting the length of a motorcade of each intersection in the city so as to analyze the degree of congestion of the intersection.
The invention has further technical improvements that: the speed of a motor vehicle detection module is suitable for the speed of a motor vehicle of surveying the car and going in the city to congestion degree to the road provides the reference foundation, the lane occupies the lane condition of detecting each road in city that detection module is suitable for, the vehicle distance that the vehicle distance detection module was suitable for going on the road measures, the time of driving detection module is suitable for the time of driving of calculating each vehicle on the road in city to remind driver's tired driving, carries out effective comprehensive detection to the data of parking stall, smog, traffic flow, pedestrian flow, motorcade length, speed of a motor vehicle, lane occupation, vehicle distance and the time of driving multifactor's like this, provides effective and reasonable basis for the traffic situation judgement in current city.
The invention has further technical improvements that: cloud service platform is provided with two access ports, is management end interface and service end interface respectively, the management end interface passes through the thing networking and is connected with traffic control department server, traffic control department server is suitable for and carries out integrated management to whole urban traffic condition through cloud service platform to issue important urban traffic situation information, service interface is connected with pedestrian cell-phone software terminal, driver vehicle mounted terminal, medical care department terminal, fire department terminal and roadside display terminal respectively through the thing networking, pedestrian cell-phone software terminal is suitable for the basic condition that reflects urban road to the pedestrian through cell-phone software's form, driver vehicle mounted terminal is suitable for through cloud service platform and provides the basic condition of navigation and urban road information for the driver in real time, and can provide the parking stall condition of destination for the driver, medical care department terminal is suitable for through cloud service platform and provides accurate traffic accident information for medical care department the very first time after the traffic accident takes place The system comprises a cloud service platform, a fire department terminal, a road side display terminal and a road side display terminal, wherein the cloud service platform is used for providing accurate early warning information for medical staff, the fire department terminal is suitable for providing accurate accident information for the fire department at the first time after an accident occurs through the cloud service platform, the accurate early warning information is provided for the fire staff for rescuing, the accident occurrence can be effectively and quickly processed, the rescuing efficiency for the accident is greatly improved, the road can be quickly dredged, the road side display terminal is suitable for providing basic information of the road section for pedestrians and drivers through large screen display equipment arranged on two sides of each road in a city, and the pedestrians and the drivers can quickly know the basic conditions of the road section.
The invention has further technical improvements that: the early warning unit comprises a traffic jam condition warning module, a parking space warning unit and a traffic accident condition warning unit, the traffic jam condition warning unit is suitable for providing a proper traffic jam warning grade for a traffic management department and a driver in real time according to a traffic jam condition early warning system of a road section, the parking space warning unit is suitable for estimating the residual parking space condition of a destination according to the destination of the driver and providing a proper parking space warning grade for the driver according to the residual parking space condition, and the traffic accident condition warning module is suitable for processing accident information detected by the detection unit to obtain a proper traffic accident warning grade and give a warning to the traffic management department and a medical department.
Compared with the prior art, the invention has the following beneficial effects:
through the cloud service platform and the detection unit cooperation use that set up, the detection unit is gathered the data that influence the parking stall of urban road traffic, smog, traffic flow, pedestrian flow, motorcade length, the speed of a motor vehicle, lane occupy, the vehicle distance and the multiple factor of driving time through big data to combine the basic condition of road to carry out the average traffic situation of obtaining the whole highway section in current city on a weighted basis, can comparatively accurate reflection urban traffic's whole situation like this.
The control unit, the cloud service platform and the early warning unit are matched for use, various conditions occurring on urban roads can be shared to drivers, traffic management departments, medical departments and fire departments in real time through the cloud service platform, the traffic light control module can be used for processing the congestion problem generated in urban traffic by adjusting the time of traffic lights in real time, so that traffic accidents can be effectively and quickly processed, the rescue efficiency of the traffic accidents is greatly improved, and the roads can be quickly dredged.
Drawings
Fig. 1 is a schematic overall flow chart of a method for sensing urban traffic situation based on big data according to the present invention.
Fig. 2 is a schematic operation flow diagram of an urban traffic situation early warning system based on big data according to the present invention.
Fig. 3 is a schematic flow chart of a detection unit of the urban traffic situation perception method and the early warning system based on big data according to the present invention.
Fig. 4 is a schematic flow diagram of a cloud service platform of the urban traffic situation awareness method and the early warning system based on big data.
Fig. 5 is a schematic flow chart of an alarm unit of the urban traffic situation perception method and the early warning system based on big data.
Detailed Description
In order to make the technical means, the original characteristics, the achieved objects and the functions of the present invention easy to understand, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. indicate the orientation or the positional relationship based on the orientation or the positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, but not for indicating or implying that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and thus not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. The invention will be further illustrated with reference to specific embodiments.
Example 1
As shown in fig. 1-4, a method for sensing urban traffic situation based on big data includes the following steps:
1) the method comprises the steps that a large data platform is utilized to carry out comprehensive system modeling on basic conditions of road routes of a city through modeling software, a city traffic cloud service platform is built, and an access port and an access mode of the cloud service platform are determined through the roles of all departments;
2) the detection unit carries out real-time, comprehensive and systematic detection and perception on the conditions of each road line of the city through a parking space detection module, a smoke detection module, a traffic flow detection module, a pedestrian flow detection module, a fleet length detection module, a vehicle speed detection module, a lane occupation detection module, a vehicle distance detection module and a driving time detection module, effectively displays the conditions in a model established by modeling software, and meanwhile updates the detection result of the detection unit on a cloud platform in real time;
3) carrying out weighted average on data of multiple factors of detected parking spaces, smoke, traffic flow, pedestrian flow, fleet length, vehicle speed, lane occupancy, vehicle distance and driving time by combining basic conditions of roads to obtain the traffic situation of the current urban whole road section, and analyzing the time-space evolution process of urban roads to further send out early warning information;
4) various conditions of urban traffic are shared to drivers, traffic management departments, medical care departments and fire departments in real time through the cloud service platform, and the traffic light control module of the control unit processes various problems generated in the urban traffic by adjusting the time of the traffic light in real time.
A big data-based urban traffic situation and early warning system comprises a detection unit, an alarm unit, a control unit, a cloud service platform, an information transmission unit, a Beidou positioning service unit, a data storage unit and a calculation unit, wherein the detection unit is suitable for carrying out real-time, comprehensive and systematic detection and perception on the condition of each road line of a city through a plurality of detection modules, the alarm unit is suitable for carrying out rapid alarm on the road blockage condition so that a driver can know the road blockage condition as early as possible, and the control unit is suitable for controlling the operation of the whole system, the calculation unit is suitable for carrying out weighted average on the data measured by the detection unit to obtain the traffic situation of the whole road section of the current city, and the data storage unit is suitable for storing the data detected by the detection mechanism to provide scientific basis for later road construction.
The cloud service platform is suitable for displaying information detected by the detection unit and information of the whole system at each terminal by utilizing a big data network, so that a user can accurately know the accurate condition of the whole urban road, the Beidou positioning service unit is suitable for providing positioning and navigation services for the user through a Beidou navigation system, the information transmission unit is suitable for conducting mutual information transmission between the user and the cloud service platform through big data and an internet system, the control unit comprises a traffic light control module, and the traffic light control module is suitable for comprehensively solving various problems of different positions, different times and different conditions in the urban traffic road through controlling the conversion time interval of the traffic light in real time.
The detection unit comprises a parking space detection module, a smoke detection module, a traffic flow detection module, a pedestrian flow detection module, a fleet length detection module, a vehicle speed detection module, a lane occupation detection module, a vehicle distance detection module and a driving time detection module, wherein the parking space detection module is suitable for detecting the saturation of parking spaces of a city through a big data system and providing accurate parking space saturation information for a driver on a cloud platform, the smoke detection module is suitable for detecting smoke generated on each traffic road in the city and judging the occurrence of traffic accidents according to the smoke, the traffic flow detection module is suitable for detecting the traffic flow of each traffic road in the city, the pedestrian flow detection module is suitable for detecting the pedestrian flow of each traffic road in the city, and the fleet length detection module is suitable for detecting the length of each fleet in the city and analyzing the congestion degree of the road.
The vehicle speed detection module is suitable for detecting the vehicle speed of a vehicle running in a city to provide reference basis for the crowdedness degree of a road, the lane occupation detection module is suitable for detecting the lane occupation condition of each road in the city, the vehicle distance detection module is suitable for measuring the vehicle distance of the vehicle running on the road, and the driving time detection module is suitable for calculating the driving time of each vehicle on the road in the city to remind a driver of fatigue driving, so that the data of multiple factors of parking space, smoke, traffic flow, pedestrian flow, fleet length, vehicle speed, lane occupation, vehicle distance and driving time are effectively and comprehensively detected, and effective and reasonable basis is provided for judging the traffic situation of the current city.
By adopting the technical scheme: through the cloud service platform and the detection unit cooperation use that set up, the detection unit is gathered the data that influence the parking stall of urban road traffic, smog, traffic flow, pedestrian flow, motorcade length, the speed of a motor vehicle, lane occupy, the vehicle distance and the multiple factor of driving time through big data to combine the basic condition of road to carry out the average traffic situation of obtaining the whole highway section in current city on a weighted basis, can comparatively accurate reflection urban traffic's whole situation like this.
As shown in fig. 1-5, a method for sensing urban traffic situation based on big data includes the following steps:
1) the method comprises the steps that a large data platform is utilized to carry out comprehensive system modeling on basic conditions of road routes of a city through modeling software, a city traffic cloud service platform is built, and an access port and an access mode of the cloud service platform are determined through the roles of all departments;
2) the detection unit carries out real-time, comprehensive and systematic detection and perception on the conditions of each road line of the city through a parking space detection module, a smoke detection module, a traffic flow detection module, a pedestrian flow detection module, a fleet length detection module, a vehicle speed detection module, a lane occupation detection module, a vehicle distance detection module and a driving time detection module, effectively displays the conditions in a model established by modeling software, and meanwhile updates the detection result of the detection unit on a cloud platform in real time;
3) carrying out weighted average on data of multiple factors of detected parking spaces, smoke, traffic flow, pedestrian flow, fleet length, vehicle speed, lane occupancy, vehicle distance and driving time by combining basic conditions of roads to obtain the traffic situation of the current urban whole road section, and analyzing the time-space evolution process of urban roads to further send out early warning information;
4) various conditions of urban traffic are shared to drivers, traffic management departments, medical care departments and fire departments in real time through the cloud service platform, and the traffic light control module of the control unit processes various problems generated in the urban traffic by adjusting the time of the traffic light in real time.
A big data-based urban traffic situation and early warning system comprises a detection unit, an alarm unit, a control unit, a cloud service platform, an information transmission unit, a Beidou positioning service unit, a data storage unit and a calculation unit, wherein the detection unit is suitable for carrying out real-time, comprehensive and systematic detection and perception on the condition of each road line of a city through a plurality of detection modules, the alarm unit is suitable for carrying out rapid alarm on the road blockage condition so that a driver can know the road blockage condition as early as possible, and the control unit is suitable for controlling the operation of the whole system, the calculation unit is suitable for carrying out weighted average on the data measured by the detection unit to obtain the traffic situation of the whole road section of the current city, and the data storage unit is suitable for storing the data detected by the detection mechanism to provide scientific basis for later road construction.
The cloud service platform is provided with two access ports which are respectively a management end interface and a server end interface, the management end interface is connected with a traffic management department server through the Internet of things, the traffic management department server is suitable for comprehensively managing the whole urban traffic condition through the cloud service platform and distributing important urban traffic situation information, the service interface is respectively connected with a pedestrian mobile phone software terminal, a driver vehicle-mounted terminal, a medical care department terminal, a fire department terminal and a roadside display terminal through the Internet of things, the pedestrian mobile phone software terminal is suitable for reflecting the basic condition of the urban road to pedestrians in a mobile phone software mode, the driver vehicle-mounted terminal is suitable for providing the basic condition of navigation and urban road information for the driver in real time through the cloud service platform and providing the parking space condition of a destination for the driver, and the medical care department terminal is suitable for providing accurate traffic accident information for the medical care department in the first time after a traffic accident occurs through the cloud service platform, accurate early warning information is provided for medical personnel to rescue, the fire department terminal is suitable for providing accurate accident information for the fire department the very first time after the accident happens through the cloud service platform, provide accurate early warning information for the fire fighter rescues, can effectively and rapidly handle the emergence of the accident like this, the rescue efficiency to the accident has greatly been improved, and can dredge the road fast, the roadside display terminal is suitable for providing the essential information of this highway section for pedestrian and driver through the large-scale screen display equipment that sets up in each road both sides in city, so that pedestrian and driver can know the essential condition of this section of road fast.
The early warning unit comprises a traffic jam condition warning module, a parking space warning unit and a traffic accident condition warning unit, the traffic jam condition warning unit is suitable for providing a proper traffic jam warning grade for a traffic management department and a driver in real time according to a traffic jam condition early warning system of a road section, the parking space warning unit is suitable for estimating the condition of the rest parking spaces of a destination according to the destination of the driver and providing a proper parking space warning grade for the driver according to the condition of the rest parking spaces, and the traffic accident condition warning module is suitable for processing traffic accident information detected by the detection unit to obtain a proper traffic accident warning grade and warning the traffic management department, a fire department and a medical department.
By adopting the technical scheme: the control unit, the cloud service platform and the early warning unit are matched for use, various conditions occurring on urban roads can be shared to drivers, traffic management departments, medical departments and fire departments in real time through the cloud service platform, the traffic light control module can be used for processing the congestion problem generated in urban traffic by adjusting the time of traffic lights in real time, so that traffic accidents can be effectively and quickly processed, the rescue efficiency of the traffic accidents is greatly improved, and the roads can be quickly dredged.
When the urban traffic situation perception method and the early warning system based on the big data are used, firstly, the big data platform is utilized to carry out comprehensive and systematic modeling on the basic conditions of the urban road routes through modeling software, the urban traffic cloud service platform is built, the access ports and the access modes of the cloud service platform are determined through the duties of all departments, secondly, the detection unit carries out real-time, comprehensive and systematic detection and perception on the conditions of all the urban road routes through the parking space detection module, the smoke detection module, the traffic flow detection module, the pedestrian flow detection module, the fleet length detection module, the vehicle speed detection module, the lane occupation detection module, the vehicle distance detection module and the driving time detection module, the detection result is effectively displayed in the model built by the modeling software, and the detection result of the detection unit is updated on the cloud platform in real time, then, the traffic situation of the current urban whole road section is obtained by carrying out weighted average on the data of multiple factors of detected parking places, smoke, traffic flow, pedestrian flow, motorcade length, vehicle speed, lane occupancy, vehicle distance and driving time and combining the basic conditions of roads, the space-time evolution process of the urban roads is analyzed, early warning information is sent out, finally, various conditions of urban traffic are shared to drivers, traffic control departments, medical departments and fire departments in real time through cloud service platforms respectively, and various problems generated in urban traffic are processed by a traffic light control module of a control unit through real-time adjustment of the time length of traffic lights.
The foregoing shows and describes the general principles and broad features of the present invention and advantages thereof. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (7)
1. A city traffic situation perception method based on big data is characterized in that: the method comprises the following steps:
the method comprises the steps that a large data platform is utilized to carry out comprehensive system modeling on basic conditions of road routes of a city through modeling software, a city traffic cloud service platform is built, and an access port and an access mode of the cloud service platform are determined through the roles of all departments;
the detection unit carries out real-time, comprehensive and systematic detection and perception on the conditions of each road line of the city through a parking space detection module, a smoke detection module, a traffic flow detection module, a pedestrian flow detection module, a fleet length detection module, a vehicle speed detection module, a lane occupation detection module, a vehicle distance detection module and a driving time detection module, effectively displays the conditions in a model established by modeling software, and meanwhile updates the detection result of the detection unit on a cloud platform in real time;
carrying out weighted average on data of multiple factors of detected parking spaces, smoke, traffic flow, pedestrian flow, fleet length, vehicle speed, lane occupancy, vehicle distance and driving time by combining basic conditions of roads to obtain the traffic situation of the current urban whole road section, and analyzing the time-space evolution process of urban roads to further send out early warning information;
4) various conditions of urban traffic are shared to drivers, traffic management departments, medical care departments and fire departments in real time through the cloud service platform, and the traffic light control module of the control unit processes various problems generated in the urban traffic by adjusting the time of the traffic light in real time.
2. The big data based urban traffic situation early warning system according to claim 1, wherein: the early warning system comprises a detection unit, an alarm unit, a control unit, a cloud service platform, an information transmission unit, a Beidou positioning service unit, a data storage unit and a calculation unit, wherein the detection unit is suitable for performing real-time, comprehensive and systematic detection and perception on the condition of each road line of a city through a plurality of detection modules and rapidly identifying special vehicles such as medical vehicles and police vehicles on each road section, the alarm unit is suitable for rapidly alarming the road jam condition to enable a driver to know the road jam condition as early as possible, the control unit is suitable for controlling the operation of the whole system and processing various problems generated in traffic by controlling the time length of traffic lights, the calculation unit is suitable for performing weighted average on data measured by the detection unit to obtain the traffic situation of the whole road section of the current city, and the data storage unit is suitable for storing the data detected by a detection mechanism to provide a department for future road construction And (5) learning the basis.
3. The big data based urban traffic situation early warning system according to claim 2, wherein: the cloud service platform is suitable for displaying information detected by the detection unit and information of the whole system at each terminal by utilizing a big data network so that a user can accurately know the accurate condition of the whole urban road, the Beidou positioning service unit is suitable for providing positioning and navigation services for the user through a Beidou navigation system, the information transmission unit is suitable for conducting mutual information transmission between the user and the cloud service platform through big data and an internet system, the control unit comprises a traffic light control module, and the traffic light control module is suitable for comprehensively solving various problems of different positions, different times and different conditions in the urban traffic road through controlling the conversion time interval of traffic lights in real time.
4. The big data based urban traffic situation early warning system according to claim 2, wherein: the detection unit comprises a parking space detection module, a smoke detection module, a traffic flow detection module, a pedestrian flow detection module, a fleet length detection module, a vehicle speed detection module, a lane occupation detection module, a vehicle distance detection module and a driving time detection module, the parking space detection module is suitable for detecting the saturation of the parking space of the city through a big data system, accurate parking space saturation information is provided for drivers on a cloud platform, the smoke detection module is suitable for detecting smoke generated on each traffic road in a city, and judges the occurrence of traffic accidents based on the traffic flow, the traffic flow detection module is suitable for detecting the traffic flow of each traffic road in the city, the pedestrian flow detection module is suitable for detecting pedestrian flow of each traffic road in a city, and the motorcade length detection module is suitable for detecting the length of a motorcade of each intersection in the city so as to analyze the degree of congestion of the intersection.
5. The big data based urban traffic situation early warning system according to claim 4, wherein: the speed of a motor vehicle detection module is suitable for the speed of a motor vehicle of surveying the car and going in the city to congestion degree to the road provides the reference foundation, the lane occupies the lane condition of detecting each road in city that detection module is suitable for, the vehicle distance that the vehicle distance detection module was suitable for going on the road measures, the time of driving detection module is suitable for the time of driving of calculating each vehicle on the road in city to remind driver's tired driving, carries out effective comprehensive detection to the data of parking stall, smog, traffic flow, pedestrian flow, motorcade length, speed of a motor vehicle, lane occupation, vehicle distance and the time of driving multifactor's like this, provides effective and reasonable basis for the traffic situation judgement in current city.
6. The big data based urban traffic situation early warning system according to claim 5, wherein: cloud service platform is provided with two access ports, is management end interface and service end interface respectively, the management end interface passes through the thing networking and is connected with traffic control department server, traffic control department server is suitable for and carries out integrated management to whole urban traffic condition through cloud service platform to issue important urban traffic situation information, service interface is connected with pedestrian cell-phone software terminal, driver vehicle mounted terminal, medical care department terminal, fire department terminal and roadside display terminal respectively through the thing networking, pedestrian cell-phone software terminal is suitable for the basic condition that reflects urban road to the pedestrian through cell-phone software's form, driver vehicle mounted terminal is suitable for through cloud service platform and provides the basic condition of navigation and urban road information for the driver in real time, and can provide the parking stall condition of destination for the driver, medical care department terminal is suitable for through cloud service platform and provides accurate traffic accident information for medical care department the very first time after the traffic accident takes place The system comprises a cloud service platform, a fire department terminal, a road side display terminal and a road side display terminal, wherein the cloud service platform is used for providing accurate early warning information for medical staff, the fire department terminal is suitable for providing accurate accident information for the fire department at the first time after an accident occurs through the cloud service platform, the accurate early warning information is provided for the fire staff for rescuing, the accident occurrence can be effectively and quickly processed, the rescuing efficiency for the accident is greatly improved, the road can be quickly dredged, the road side display terminal is suitable for providing basic information of the road section for pedestrians and drivers through large screen display equipment arranged on two sides of each road in a city, and the pedestrians and the drivers can quickly know the basic conditions of the road section.
7. The big data based urban traffic situation early warning system according to claim 2, wherein: the early warning unit comprises a traffic jam condition warning module, a parking space warning unit and a traffic accident condition warning unit, the traffic jam condition warning unit is suitable for providing a proper traffic jam warning grade for a traffic management department and a driver in real time according to a traffic jam condition early warning system of a road section, the parking space warning unit is suitable for estimating the residual parking space condition of a destination according to the destination of the driver and providing a proper parking space warning grade for the driver according to the residual parking space condition, and the traffic accident condition warning module is suitable for processing accident information detected by the detection unit to obtain a proper traffic accident warning grade and give a warning to the traffic management department and a medical department.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010851525.1A CN112037509A (en) | 2020-08-21 | 2020-08-21 | Urban traffic situation perception method and early warning system based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010851525.1A CN112037509A (en) | 2020-08-21 | 2020-08-21 | Urban traffic situation perception method and early warning system based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112037509A true CN112037509A (en) | 2020-12-04 |
Family
ID=73581822
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010851525.1A Pending CN112037509A (en) | 2020-08-21 | 2020-08-21 | Urban traffic situation perception method and early warning system based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112037509A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112885082A (en) * | 2021-01-11 | 2021-06-01 | 浙江海峡创新科技有限公司 | Cloud server-based remote measurement and control system for urban roads with multiple units |
| CN113269966A (en) * | 2021-07-21 | 2021-08-17 | 广东新中望信息科技有限公司 | Space-time situation perception model based on combination of geomagnetism big data software and hardware |
| CN113643539A (en) * | 2021-08-12 | 2021-11-12 | 合肥永信科翔智能技术有限公司 | Intelligent traffic control system based on big data |
| CN113689701A (en) * | 2021-08-31 | 2021-11-23 | 温州智慧科技有限公司 | Fire-fighting alarm-giving linkage system and method based on big data |
| CN114495494A (en) * | 2022-01-06 | 2022-05-13 | 电子科技大学 | Traffic situation assessment method based on traffic flow parameter prediction |
| CN114613145A (en) * | 2022-05-12 | 2022-06-10 | 中运科技股份有限公司 | Passenger traffic flow perception early warning system and method under big data |
| CN115206090A (en) * | 2022-06-07 | 2022-10-18 | 安徽超清科技股份有限公司 | Traffic situation estimation system based on traffic big data |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103065459A (en) * | 2011-10-18 | 2013-04-24 | 上海宝康电子控制工程有限公司 | Intelligent transportation integration control platform system based on Web geographical information system technology |
| CN204256966U (en) * | 2014-12-11 | 2015-04-08 | 杨绍鹏 | Intelligence commander managing and control system |
| CN104794895A (en) * | 2015-04-09 | 2015-07-22 | 吉林大学 | Multisource traffic information fusion method for expressways |
| CN105374205A (en) * | 2015-11-20 | 2016-03-02 | 南京中科创达软件科技有限公司 | Wi-Fi network-based urban emergency event processing system |
| KR102020340B1 (en) * | 2019-02-12 | 2019-09-11 | 한성정보기술주식회사 | A intersection and walking safety monitoring system using lidar |
| CN110907966A (en) * | 2019-11-22 | 2020-03-24 | 东华理工大学 | Emergency vehicle navigation system and method based on real-time traffic flow in time of Internet of things |
-
2020
- 2020-08-21 CN CN202010851525.1A patent/CN112037509A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103065459A (en) * | 2011-10-18 | 2013-04-24 | 上海宝康电子控制工程有限公司 | Intelligent transportation integration control platform system based on Web geographical information system technology |
| CN204256966U (en) * | 2014-12-11 | 2015-04-08 | 杨绍鹏 | Intelligence commander managing and control system |
| CN104794895A (en) * | 2015-04-09 | 2015-07-22 | 吉林大学 | Multisource traffic information fusion method for expressways |
| CN105374205A (en) * | 2015-11-20 | 2016-03-02 | 南京中科创达软件科技有限公司 | Wi-Fi network-based urban emergency event processing system |
| KR102020340B1 (en) * | 2019-02-12 | 2019-09-11 | 한성정보기술주식회사 | A intersection and walking safety monitoring system using lidar |
| CN110907966A (en) * | 2019-11-22 | 2020-03-24 | 东华理工大学 | Emergency vehicle navigation system and method based on real-time traffic flow in time of Internet of things |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112885082A (en) * | 2021-01-11 | 2021-06-01 | 浙江海峡创新科技有限公司 | Cloud server-based remote measurement and control system for urban roads with multiple units |
| CN113269966A (en) * | 2021-07-21 | 2021-08-17 | 广东新中望信息科技有限公司 | Space-time situation perception model based on combination of geomagnetism big data software and hardware |
| CN113643539A (en) * | 2021-08-12 | 2021-11-12 | 合肥永信科翔智能技术有限公司 | Intelligent traffic control system based on big data |
| CN113689701A (en) * | 2021-08-31 | 2021-11-23 | 温州智慧科技有限公司 | Fire-fighting alarm-giving linkage system and method based on big data |
| CN114495494A (en) * | 2022-01-06 | 2022-05-13 | 电子科技大学 | Traffic situation assessment method based on traffic flow parameter prediction |
| CN114613145A (en) * | 2022-05-12 | 2022-06-10 | 中运科技股份有限公司 | Passenger traffic flow perception early warning system and method under big data |
| CN115206090A (en) * | 2022-06-07 | 2022-10-18 | 安徽超清科技股份有限公司 | Traffic situation estimation system based on traffic big data |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112037509A (en) | Urban traffic situation perception method and early warning system based on big data | |
| TWI691927B (en) | External coordinate real-time three-dimensional road condition auxiliary device for mobile vehicle and the system | |
| US11967230B2 (en) | System and method for using V2X and sensor data | |
| CN108346288B (en) | Road section operation state early warning method and device and electronic equipment | |
| CN109084794B (en) | Path planning method | |
| CN103473939B (en) | A kind of road signal control method and system | |
| WO2023019761A1 (en) | Road network operation state detection system and method for mixed traffic flow | |
| CN112071061A (en) | Vehicle service system based on cloud computing and data analysis | |
| EP2700032A2 (en) | A comprehensive and intelligent system for managing traffic and emergency services | |
| CN111681445A (en) | Indoor parking lot management system, V2X road side equipment and vehicle-mounted equipment | |
| CN106251621A (en) | Wisdom traffic control system and method | |
| CN110992712A (en) | Traffic signal lamp light control system based on cloud computing | |
| CN113689701A (en) | Fire-fighting alarm-giving linkage system and method based on big data | |
| CN112140995A (en) | Intelligent automobile safe driving system based on network cloud | |
| CN112734242A (en) | Method and device for analyzing availability of vehicle running track data, storage medium and terminal | |
| CN113628472A (en) | Community security control system and method based on Internet of things | |
| CN112652178B (en) | Control system for urban traffic | |
| CN114244827A (en) | Wisdom city monitored control system | |
| CN112907960B (en) | Traffic jam monitoring devices based on big data | |
| CN112216106A (en) | Intelligent traffic management system based on BIM technology | |
| US11928962B2 (en) | Location risk determination and ranking based on vehicle events and/or an accident database | |
| CN115472016A (en) | Big data acquisition system and method based on intelligent traffic | |
| CN114596704B (en) | Traffic event processing method, device, equipment and storage medium | |
| CN211319386U (en) | Vehicle-road cooperative system | |
| CN115359671A (en) | Intersection vehicle cooperative control method and related equipment |
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 | ||
| WD01 | Invention patent application deemed withdrawn after publication | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20201204 |