CN111489555A - Traffic running state prediction method, device and system - Google Patents
Traffic running state prediction method, device and system Download PDFInfo
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- CN111489555A CN111489555A CN202010409144.8A CN202010409144A CN111489555A CN 111489555 A CN111489555 A CN 111489555A CN 202010409144 A CN202010409144 A CN 202010409144A CN 111489555 A CN111489555 A CN 111489555A
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- 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
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/067—Enterprise or organisation modelling
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
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- 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
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0116—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from roadside infrastructure, e.g. beacons
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- 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
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/012—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from other sources than vehicle or roadside beacons, e.g. mobile networks
Abstract
The embodiment of the invention provides a method, a device and a system for predicting a traffic running state, wherein the method comprises the following steps: acquiring multi-source traffic data of a target intersection; and establishing a traffic running state model based on the multi-source traffic data so as to obtain the road traffic state and the vehicle passing state of the target intersection. According to the traffic running state prediction method, the device and the system provided by the embodiment of the invention, a multi-mode data fusion technology is adopted, the traffic flow characteristics of three types of traffic data sources are integrated and extracted, and the road traffic state of the current intersection is obtained. And the edge node processes the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information. The traffic state of the intersection is described from two levels of vehicles and roads, and the traffic running state of the intersection can be accurately and comprehensively predicted by the method, so that the safety and the efficiency of road traffic are improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of intelligent traffic, in particular to a traffic running state prediction method and a traffic running state prediction device.
Background
The living standard of people is increasingly improved, cities are rapidly developed, urban traffic systems face more and more severe tests along with the progress of urban modernization, the quantity of vehicles kept increases year by year, the vehicle congestion is more and more severe, traffic accidents are frequent, social resources are wasted, the environmental pollution is aggravated, the traveling efficiency, the living quality and the physical and psychological health of people are seriously influenced, and therefore the urban traffic congestion relieving system has great economic and ecological significance.
The evaluation of the traffic state has an important influence on the safety and efficiency of road traffic. The monitoring and prediction of the traffic running state is always the focus and difficulty of the research in the field of traffic running state evaluation, and the evaluation of the traffic running state of the expressway has become one of the hot spots in the field of dynamic traffic management research since the sixties of the last century, and a great deal of results emerge.
At present, the research on the evaluation of the traffic running state mostly depends on the data of a fixed vehicle detector, however, due to the limitation of cost, the number of the arranged vehicle detectors is very limited, the obtained vehicle detector data is very limited, and the traffic data is the basis for monitoring and predicting the traffic running state.
Disclosure of Invention
The embodiment of the invention provides a traffic running state prediction method and a traffic running state prediction device, which are used for solving the defects of insufficient accuracy and insufficient space coverage of the conventional traffic state prediction method.
In a first aspect, an embodiment of the present invention provides a method for predicting a traffic operation state, including:
acquiring multi-source traffic data of a target intersection; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data;
and establishing a traffic running state model based on the multi-source traffic data so as to obtain the road traffic state and the vehicle passing state of the target intersection.
Further, based on the multi-source traffic data, a traffic running state model is established to obtain a road traffic state and a vehicle passing state of the target intersection, and the method specifically comprises the following steps:
respectively extracting traffic flow characteristics in geomagnetic coil data, radar microwave data and road video monitoring data of the target intersection; the traffic flow characteristics are large-scale vehicle track data comprising time series position information and movement characteristics;
integrating and extracting traffic flow characteristics of three types of traffic data sources by adopting a multi-modal data fusion technology to obtain a road traffic state of a target intersection;
and processing the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information, so as to obtain the vehicle passing state of the target intersection.
Further, radar microwave data at least comprise road sections, timestamps, average speeds, lane numbers and vehicle numbers, geomagnetic coil data at least comprise detector numbers, detector positions and occupation time, road video monitoring data at least comprise directions, lane numbers, average speeds and average occupation rates, and floating vehicle track data at least comprise vehicle numbers, longitude and latitude, vehicle traveling directions and vehicle states.
In a second aspect, an embodiment of the present invention provides a traffic operation state prediction apparatus, including:
the acquisition module is used for acquiring multi-source traffic data of the target intersection; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data;
and the traffic running state prediction module is used for establishing a traffic running state model based on the multi-source traffic data so as to obtain the road traffic state and the vehicle passing state of the target intersection.
Further, the traffic operation state prediction module specifically includes:
the extraction unit is used for respectively extracting traffic flow characteristics in geomagnetic coil data, radar microwave data and road video monitoring data of the target intersection; the traffic flow characteristics are large-scale vehicle track data comprising time series position information and movement characteristics;
the road traffic state prediction unit is used for integrating and extracting traffic flow characteristics of three types of traffic data sources by adopting a multi-mode data fusion technology to obtain the road traffic state of the target intersection;
and the vehicle passing state prediction unit is used for processing the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information so as to obtain the vehicle passing state of the target intersection.
In a third aspect, an embodiment of the present invention provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the traffic operation state prediction method according to the embodiment of the first aspect of the present invention when executing the program.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the traffic behavior prediction method according to an embodiment of the first aspect of the present invention.
In a fifth aspect, an embodiment of the present invention provides a traffic running state prediction system, including an edge node and a multi-source traffic data acquisition device, which are arranged at each intersection in an area;
the multi-source traffic data acquisition equipment is used for acquiring multi-source traffic data of the current intersection and sending the multi-source traffic data to the corresponding edge node; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data;
and the edge nodes are used for establishing a traffic running state model based on the multi-source traffic data to obtain the road traffic state and the vehicle passing state of the current intersection.
According to the traffic running state prediction method, the device and the system provided by the embodiment of the invention, a multi-mode data fusion technology is adopted, the effective analysis of multi-source traffic data is realized, a traffic running state model of a single intersection is further established, and the traffic state of the intersection is described from two levels of vehicles and roads.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings 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 a schematic flow chart of a traffic operation state prediction method according to an embodiment of the present invention;
FIG. 2 is a schematic view of a traffic operating state model according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a traffic operation state prediction apparatus according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a traffic operation state prediction system 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.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
Fig. 1 is a traffic running state prediction method according to an embodiment of the present invention, and with reference to fig. 1, the method includes:
Specifically, the target intersection is a single intersection selected in this embodiment. In the embodiment, geomagnetic coil data, road video monitoring data and radar microwave data of the target intersection are acquired through geomagnetic coil equipment, video monitoring equipment and radar microwave equipment.
The system comprises a plurality of sets of radar microwave data, a plurality of ground coils, a plurality of sensors, a plurality of video monitoring sensors, a plurality of ground coils, a.
And 102, establishing a traffic running state model based on the multi-source traffic data so as to obtain the road traffic state and the vehicle passing state of the target intersection.
Specifically, fig. 2 is a schematic diagram of a traffic operation state model according to an embodiment of the present invention. Referring to fig. 2, the present embodiment builds a traffic operation state model shown in fig. 2 based on multi-source traffic data. Here, the traffic running state includes a road traffic state and a vehicle passing state.
In the embodiment, traffic flow characteristics in geomagnetic coil data, radar microwave data and road video monitoring data of a target intersection are respectively extracted, and by adopting a multi-mode data fusion technology, traffic flow characteristics of three types of traffic data sources are integrated and extracted to obtain multi-mode fusion data characteristics, so that a road traffic state of the target intersection is obtained, and the road traffic state describes traffic running states of the intersection in all directions from a road level. Here, the traffic flow characteristics are large-scale vehicle trajectory data including time-series position information and movement characteristics. The time series position information is a passing road junction position sequence or a bayonet position sequence, and the movement characteristics comprise speed, direction and the like.
The floating car track data is from historical traffic flow data of urban area traffic network statistics, and comprises GPS (global positioning system) position information, timestamp information and the like of small cars and medium cars in the urban road network. Such information is readily available with the aid of GPS or beidou positioning devices carried by modern vehicles.
In addition, the embodiment processes the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information, so that the vehicle passing state of the target intersection is obtained. The vehicle traffic state describes, on the vehicle level, the driving behavior of the motor vehicle and the traffic state in the intersection. Here, the time-series characteristic is a dynamic change of vehicle trajectory information possessed by the vehicle trajectory information in time units of day and week, and the state characteristic is a traffic flow parameter extracted from the vehicle trajectory information, including a trip average speed, a trip time, a traveling direction, and the like.
According to the traffic running state prediction method provided by the embodiment of the invention, a multi-mode data fusion technology is adopted, the effective analysis of multi-source traffic data is realized, a traffic running state model of a single intersection is further established, and the traffic states of the intersection are described from two levels of vehicles and roads.
Fig. 3 is a schematic structural diagram of a traffic operation state prediction apparatus according to an embodiment of the present invention, and referring to fig. 3, the apparatus includes:
the acquisition module 301 is used for acquiring multi-source traffic data of a target intersection; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data;
and the traffic running state prediction module 302 is configured to establish a traffic running state model based on the multi-source traffic data to obtain a road traffic state and a vehicle passing state of the target intersection.
On the basis of the foregoing embodiment, the traffic operation state prediction module 302 specifically includes:
the extraction unit is used for respectively extracting traffic flow characteristics in geomagnetic coil data, radar microwave data and road video monitoring data of the target intersection; the traffic flow characteristics are large-scale vehicle track data comprising time series position information and movement characteristics;
the road traffic state prediction unit is used for integrating and extracting traffic flow characteristics of three types of traffic data sources by adopting a multi-mode data fusion technology to obtain the road traffic state of the target intersection;
and the vehicle passing state prediction unit is used for processing the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information so as to obtain the vehicle passing state of the target intersection.
Specifically, fig. 2 is a schematic diagram of a traffic operation state model according to an embodiment of the present invention. Referring to fig. 2, the present embodiment builds a traffic operation state model shown in fig. 2 based on multi-source traffic data. Traffic flow characteristics in geomagnetic coil data, radar microwave data and road video monitoring data of the target intersection are respectively extracted, and traffic flow characteristics of three types of traffic data sources are integrated and extracted by adopting a multi-mode data fusion technology to obtain the road traffic state of the target intersection. Here, the traffic flow characteristics are large-scale vehicle trajectory data including time-series position information and movement characteristics. The time series position information is a passing road junction position sequence or a bayonet position sequence, and the movement characteristics comprise speed, direction and the like. In addition, the embodiment processes the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information, so that the vehicle passing state of the target intersection is obtained.
The traffic running state prediction device provided by the embodiment of the invention adopts a multi-mode data fusion technology to realize effective analysis of multi-source traffic data, further establishes a traffic running state model of a single intersection and describes the traffic state of the intersection from two levels of vehicles and roads.
An embodiment of the present invention provides an electronic device, as shown in fig. 4, where the electronic device may include: a processor (processor)401, a communication Interface (communication Interface)402, a memory (memory)403 and a communication bus 404, wherein the processor 401, the communication Interface 402 and the memory 403 complete communication with each other through the communication bus 404. The processor 501 may call the logic instructions in the memory 403 to execute the traffic operation state prediction method provided by the above embodiments, for example, including: acquiring multi-source traffic data of a target intersection; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data; and establishing a traffic running state model based on the multi-source traffic data so as to obtain the road traffic state and the vehicle passing state of the target intersection.
An embodiment of the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program is implemented to, when executed by a processor, perform the traffic operation state prediction method provided in the foregoing embodiments, for example, including: acquiring multi-source traffic data of a target intersection; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data; and establishing a traffic running state model based on the multi-source traffic data so as to obtain the road traffic state and the vehicle passing state of the target intersection.
Fig. 5 is a schematic structural diagram of a traffic running state prediction system according to an embodiment of the present invention, and referring to fig. 5, the system includes edge nodes and multi-source traffic data acquisition devices disposed at each intersection in an area; wherein:
the multi-source traffic data acquisition equipment is used for acquiring multi-source traffic data of the current intersection and sending the multi-source traffic data to the corresponding edge node; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data;
and the edge nodes are used for establishing a traffic running state model based on the multi-source traffic data to obtain the road traffic state and the vehicle passing state of the current intersection.
Referring to fig. 5, in this embodiment, the edge nodes are an edge node and a set of multi-source traffic data acquisition equipment corresponding to an intersection of a computing platform with independent data acquisition, analysis processing and communication functions, where the computing platform is located at a traffic intersection, and the multi-source traffic data acquisition equipment includes a geomagnetic coil device, a video monitoring device and a radar microwave device. Specifically, the method comprises the following steps. The road video monitoring equipment respectively monitors and analyzes multi-lane and multi-traffic flow in four directions of an intersection, geomagnetic coil induction equipment is buried below each lane, and radar microwave equipment sets corresponding sectors for lanes at the traffic flow inlet of the intersection to acquire traffic flow information.
And processing the multi-source traffic data of the single intersection at the corresponding edge node. Specifically, the edge nodes extract traffic flow characteristics in geomagnetic coil data, radar microwave data and road video monitoring data of the current intersection, and the traffic flow characteristics of three types of traffic data sources are integrated and extracted by adopting a multi-mode data fusion technology to obtain the road traffic state of the current intersection. In addition, the embodiment processes the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information, so that the vehicle passing state of the target intersection is obtained.
Furthermore, each edge node uniform end is connected with a multi-source traffic data acquisition device to acquire multi-source traffic data, the other end of each edge node uniform end is connected with a cloud center, and a processing result of the multi-source traffic data is sent to the cloud center.
According to the traffic running state prediction system provided by the embodiment of the invention, edge nodes are arranged at each intersection in the area, the edge nodes receive and process multi-source traffic data acquired by multi-source traffic data acquisition equipment, and the multi-mode data fusion technology is adopted to integrate and extract traffic flow characteristics of three types of traffic data sources so as to obtain the road traffic state of the current intersection. And the edge node processes the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information. According to the embodiment, the multi-source traffic data of the corresponding intersection are processed at the edge node, so that the vehicle passing state of each intersection in the area can be obtained, and the safety and efficiency of road traffic in the area are improved.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (8)
1. A traffic operation state prediction method is characterized by comprising the following steps:
acquiring multi-source traffic data of a target intersection; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data;
and establishing a traffic running state model based on the multi-source traffic data so as to obtain the road traffic state and the vehicle passing state of the target intersection.
2. The traffic running state prediction method according to claim 1, wherein a traffic running state model is established based on the multi-source traffic data to obtain a road traffic state and a vehicle passing state of a target intersection, and specifically comprises:
respectively extracting traffic flow characteristics in geomagnetic coil data, radar microwave data and road video monitoring data of the target intersection; the traffic flow characteristics are large-scale vehicle track data comprising time series position information and movement characteristics;
integrating and extracting traffic flow characteristics of three types of traffic data sources by adopting a multi-modal data fusion technology to obtain a road traffic state of a target intersection;
and processing the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information, so as to obtain the vehicle passing state of the target intersection.
3. The traffic behavior prediction method according to claim 1, wherein the radar microwave data includes at least a road section, a time stamp, an average speed, a lane number, and a vehicle number, the geomagnetic coil data includes at least a detector number, a detector position, and an occupancy time, the road video monitoring data includes at least a direction, a lane number, an average speed, and an average occupancy, and the floating car trajectory data includes at least a vehicle number, a longitude and latitude, a vehicle traveling direction, and a vehicle state.
4. A traffic running state prediction device characterized by comprising:
the acquisition module is used for acquiring multi-source traffic data of the target intersection; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data;
and the traffic running state prediction module is used for establishing a traffic running state model based on the multi-source traffic data so as to obtain the road traffic state and the vehicle passing state of the target intersection.
5. The traffic running state prediction device according to claim 4, wherein the traffic running state prediction module specifically includes:
the extraction unit is used for respectively extracting traffic flow characteristics in geomagnetic coil data, radar microwave data and road video monitoring data of the target intersection; the traffic flow characteristics are large-scale vehicle track data comprising time series position information and movement characteristics;
the road traffic state prediction unit is used for integrating and extracting traffic flow characteristics of three types of traffic data sources by adopting a multi-mode data fusion technology to obtain the road traffic state of the target intersection;
and the vehicle passing state prediction unit is used for processing the floating vehicle track data to obtain the time sequence characteristics and the state characteristics of the motor vehicle track information so as to obtain the vehicle passing state of the target intersection.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the traffic behavior prediction method according to any one of claims 1 to 3 when executing the program.
7. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the traffic behavior prediction method according to any one of claims 1 to 3.
8. A traffic running state prediction system is characterized by comprising edge nodes and multi-source traffic data acquisition equipment, wherein the edge nodes are arranged at each intersection in an area;
the multi-source traffic data acquisition equipment is used for acquiring multi-source traffic data of the current intersection and sending the multi-source traffic data to the corresponding edge node; the multi-source traffic data comprises geomagnetic coil data, road video monitoring data, radar microwave data and floating car track data;
and the edge nodes are used for establishing a traffic running state model based on the multi-source traffic data to obtain the road traffic state and the vehicle passing state of the current intersection.
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| US11887376B2 (en) | 2020-12-03 | 2024-01-30 | Beijing Baidu Netcom Science Technology Co., Ltd. | Method and apparatus of estimating road condition, and method and apparatus of establishing road condition estimation model |
| CN112669594A (en) * | 2020-12-11 | 2021-04-16 | 国汽(北京)智能网联汽车研究院有限公司 | Method, device, equipment and storage medium for predicting traffic road conditions |
| CN113011323A (en) * | 2021-03-18 | 2021-06-22 | 北京百度网讯科技有限公司 | Method for acquiring traffic state, related device, road side equipment and cloud control platform |
| US11783588B2 (en) | 2021-03-18 | 2023-10-10 | Apollo Intelligent Connectivity (Beijing) Technology Co., Ltd. | Method for acquiring traffic state, relevant apparatus, roadside device and cloud control platform |
| CN113420805A (en) * | 2021-06-21 | 2021-09-21 | 车路通科技(成都)有限公司 | Dynamic track image fusion method, device, equipment and medium for video and radar |
| CN116403402A (en) * | 2023-04-13 | 2023-07-07 | 交通运输部公路科学研究所 | Traffic state prediction method for urban intersection area in network environment |
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