CN115909716A - Traffic intersection scheduling system, method and equipment based on internet cloud control platform - Google Patents
Traffic intersection scheduling system, method and equipment based on internet cloud control platform Download PDFInfo
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Abstract
The application relates to a traffic intersection scheduling system, method and device based on a network connection cloud control platform, comprising the following steps: collecting traffic participant information and traffic event information, and fusing the traffic participant information, the traffic event information and vehicle fusion data to obtain fusion perception data; receiving fusion sensing data, shared data sent by a target resource platform and vehicle fusion data sent by a target networked vehicle, generating traffic full-factor real-time digital mapping data, processing part of the traffic full-factor real-time digital mapping data into non-real-time type cooperative application data, and processing the rest of the traffic full-factor real-time digital mapping data into real-time type cooperative application data; and constructing a data set of traffic big data, generating a traffic equipment control instruction and traffic control data, and generating a dispatching signal of a traffic intersection. The problems that the direction with more vehicles is insufficient in conduction time, the direction with less vehicles is remained in conduction time, the vehicles in one direction are crowded, the traffic flow in the other direction is low and the like are solved.
Description
Technical Field
The application relates to the technical field of intelligent traffic systems, in particular to a traffic intersection scheduling system, method and device based on a network connection cloud control platform.
Background
In recent years, the quantity of automobiles in China is increased sharply, the popularization of private automobiles is becoming a trend increasingly, however, many adverse factors are generated under the condition, such as frequent road blockage and frequent traffic accidents, which often occur at the most dense places of the road, namely traffic intersections, because the traffic conditions at different moments are very complicated, highly nonlinear and random and are often influenced by human factors, the reasons for the conditions are mainly that the scheduling system is not perfect and intelligent enough, so that the due effect is not achieved, the resources of the road cannot be reasonably utilized, for example, timing control is adopted once, traffic cannot be reasonably evacuated, and the waste of effective application time of the road is caused, fewer vehicles in the green light direction are generated, the quantity of vehicles in the red light direction is overstocked, and the use efficiency of the road is greatly influenced. Therefore, a large number of vehicles stay at the crossroad, and continuously and meaninglessly consume gasoline, thereby causing energy waste and environmental pollution. Due to the limitation of land, the solution of all the problems can not be completed only by the extension of roads, and an intelligent traffic intersection maneuvering system is particularly necessary.
The development of intelligent transportation systems began in the 70 s. In the experiment of the dynamic route guidance system, the driver on the vehicle can select the best route to the destination according to the road traffic jam condition and the guidance direction displayed on the display mounted on the vehicle. In 10 years from the middle of the 80 s to the middle of the 90 s, research on road-to-vehicle inter-communication systems, traffic information communication systems, wide-area travel information systems, ultra-intelligent vehicle systems, safety vehicle systems, new traffic management systems, and the like has been successively completed. On the basis of this, the road traffic vehicle Intelligent propulsion association is established to promote the development of ITS (Intelligent Transport System).
At present, although the traffic lights at urban street intersections in China are automatic, careful observation shows that the alternating conversion of the traffic lights is in a timing mode, namely the interval time of the conversion is fixed and invariable. The timing pattern does not meet the practical requirements. This is because if the traffic flow in the east-west and north-south directions is very different, and the turn-on time is equally distributed by the signal lamps, the problem arises that: the unreasonable situation that the vehicles in one direction are crowded and the traffic flow in the other direction is small is caused by insufficient conduction time in the direction with more vehicles and the surplus conduction time in the direction with less vehicles, so that a network cloud control is necessary to be created to optimize a traffic scheduling system.
Disclosure of Invention
The application provides a traffic intersection dispatching system, a traffic intersection dispatching method and traffic intersection dispatching equipment based on a network connection cloud control platform, and solves the problems that the conduction time of a plurality of vehicles in the direction is insufficient, the conduction time of a few vehicles in the direction is remained, the vehicles in one direction are crowded, the traffic flow in the other direction is low, unreasonable and the like, the coordination of traffic facility control and vehicle control is realized, the capacity of intelligent network connection driving service is enhanced, the casualty rate of traffic accidents is reduced, the traffic jam time is reduced, and the traffic efficiency and the intersection dispatching efficiency are improved.
An embodiment of a first aspect of the present application provides a traffic intersection scheduling system based on a network connection cloud control platform, including the following steps: the road side sensing component is used for acquiring traffic participant information and traffic event information of a plurality of target areas, receiving vehicle fusion data sent by target networked vehicles, and fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain fusion sensing data; the data processing component is used for receiving the fusion perception data sent by the roadside perception component, the shared data sent by a target resource platform and the vehicle fusion data sent by the target internet vehicle, generating traffic full-factor real-time digital mapping data according to the fusion perception data, the shared data and the vehicle fusion data, processing part of the traffic full-factor real-time digital mapping data into non-real-time type cooperative application data, and processing the rest of the traffic full-factor real-time digital mapping data into real-time type cooperative application data; and the internet cloud control platform is used for constructing a data set of traffic big data according to the non-real-time type cooperative application data and the real-time type cooperative application data, generating a traffic equipment control instruction of the roadside sensing assembly and traffic control data of the target internet vehicle according to the data set of the traffic big data, and generating a dispatching signal of a traffic intersection according to the traffic equipment control instruction and the traffic control data.
Optionally, the roadside sensing assembly includes: the roadside sensing unit is used for acquiring traffic participant information and traffic event information of the target area; the road side communication unit is used for receiving vehicle fusion data sent by the target networked vehicle; and the fusion unit is used for fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain the fusion perception data based on a preset fusion algorithm.
Optionally, the data processing assembly includes: the multi-level fusion unit is used for receiving and fusing the fusion perception data, the shared data and the vehicle fusion data to generate the traffic full-factor real-time digital mapping data; the data analysis unit is used for constructing a data set based on partial data in the traffic full-factor real-time digital mapping data and analyzing and learning the data set to obtain the data of the non-real-time type collaborative application; and the application planning unit is used for carrying out real-time application calculation by combining the residual data of the traffic full-element real-time digital mapping data under the condition of preset overall planning to obtain the data of the real-time type cooperative application.
An embodiment of a second aspect of the present application provides a traffic intersection scheduling method based on a networking cloud control platform, including: collecting traffic participant information and traffic event information of a plurality of target areas, receiving vehicle fusion data sent by target networked vehicles, and fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain fusion perception data; receiving the fusion perception data sent by the roadside perception component, the shared data sent by a target resource platform and the vehicle fusion data sent by the target networked vehicle, generating traffic full-factor real-time digital mapping data according to the fusion perception data, the shared data and the vehicle fusion data, processing part of the traffic full-factor real-time digital mapping data into non-real-time type cooperative application data, and processing the rest of the traffic full-factor real-time digital mapping data into real-time type cooperative application data; and constructing a data set of traffic big data according to the data of the non-real-time type cooperative application and the data of the real-time type cooperative application, generating a traffic equipment control instruction of the roadside sensing component and traffic control data of the target networked vehicle according to the data set of the traffic big data, and generating a dispatching signal of a traffic intersection according to the traffic equipment control instruction and the traffic control data.
Optionally, the traffic intersection scheduling method based on the internet cloud control platform further includes: collecting traffic participant information and traffic event information of the target area; receiving vehicle fusion data sent by the target networked vehicle; and fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain the fusion perception data based on a preset fusion algorithm.
Optionally, the traffic intersection scheduling method based on the internet cloud control platform further includes: receiving and fusing the fusion perception data, the shared data and the vehicle fusion data to generate the traffic full-factor real-time digital mapping data; constructing a data set based on partial data in the traffic full-factor real-time digital mapping data, and analyzing and learning the data set to obtain data of the non-real-time type collaborative application; and under the condition of a preset overall plan, performing real-time application calculation by combining the residual data of the traffic full-factor real-time digital mapping data to obtain the data of the real-time type cooperative application.
Optionally, the shared data includes at least one of map data of the plurality of target areas, traffic management data of the plurality of target areas, meteorological data of the plurality of target areas, and positioning data of the plurality of target areas.
An embodiment of a third aspect of the present application provides an electronic device, including: the system comprises a memory, a processor and a computer program which is stored on the memory and can run on the processor, wherein the processor executes the program to realize the traffic intersection scheduling method based on the internet cloud control platform.
A fourth aspect of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor, so as to implement the traffic intersection scheduling method based on a networking cloud control platform as described in the foregoing embodiments.
The method includes the steps of acquiring traffic participant information and traffic event information of a target area, receiving vehicle fusion data sent by a target internet vehicle, fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain fusion perception data, receiving the fusion perception data sent by a roadside perception component, shared data sent by a target resource platform and vehicle fusion data sent by the target internet vehicle, generating traffic full-element real-time digital mapping data, processing part of data in the traffic full-element real-time digital mapping data into non-real-time cooperative application data, processing residual data in the traffic full-element real-time digital mapping data into real-time cooperative application data, constructing a data set of traffic big data according to the non-real-time cooperative application data and the real-time cooperative application data, generating a traffic equipment control instruction and traffic control data of the target internet vehicle, and generating a scheduling signal of a traffic intersection according to the traffic equipment control instruction and the traffic control data. Therefore, the problems that the direction with more vehicles is insufficient in conduction time, the direction with less vehicles is remained in conduction time, the vehicles in one direction are crowded, the vehicle flow in the other direction is low are unreasonable and the like are solved, the coordination of traffic facility control and vehicle control is realized, the capability of intelligent internet driving service is enhanced, the casualty rate of traffic accidents is reduced, the traffic jam time is reduced, and the traffic efficiency and the crossing scheduling efficiency are improved.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
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The above and/or additional aspects and advantages of the present application will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
fig. 1 is a schematic block diagram of a traffic intersection scheduling system based on a networked cloud control platform according to an embodiment of the present application;
fig. 2 is a schematic diagram of an overall architecture of a traffic intersection scheduling system based on a networked cloud control platform according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a traffic sensor working big data fusion scheduling process according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a vehicle road cloud standardized communication technology composition architecture according to an embodiment of the present application;
fig. 5 is a schematic diagram of a vehicle-road cloud fusion awareness technology composition architecture according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary and intended to be used for explaining the present application and should not be construed as limiting the present application.
The traffic intersection scheduling system, method and device based on the internet cloud control platform according to the embodiments of the present application are described below with reference to the accompanying drawings. Aiming at the unreasonable problems that the direction conduction time of a plurality of vehicles is insufficient and the direction conduction time of a few vehicles is remained to cause the congestion of one direction vehicle and the low traffic flow of the other direction, the application provides a traffic intersection scheduling system based on a network connection cloud control platform, and the system comprises: the roadside sensing component is used for acquiring traffic participant information and traffic event information of a plurality of target areas, receiving vehicle fusion data sent by target networked vehicles, and fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain fusion sensing data; the data processing assembly is used for receiving the fusion sensing data sent by the road side sensing assembly, the shared data sent by the target resource platform and the vehicle fusion data sent by the target networked vehicle, generating traffic full-factor real-time digital mapping data according to the fusion sensing data, the shared data and the vehicle fusion data, processing part of the traffic full-factor real-time digital mapping data into non-real-time type cooperative application data, and processing the rest of the traffic full-factor real-time digital mapping data into real-time type cooperative application data; the network cloud control platform is used for constructing a data set of traffic big data according to the non-real-time type cooperative application data and the real-time type cooperative application data, generating a traffic equipment control instruction of the road side sensing assembly and traffic control data of a target network connection vehicle according to the data set of the traffic big data, and generating a dispatching signal of a traffic intersection according to the traffic equipment control instruction and the traffic control data. . Therefore, the problems that the direction with more vehicles is insufficient in conduction time, the direction with less vehicles is remained in conduction time, the vehicles in one direction are crowded, the vehicle flow in the other direction is low are unreasonable and the like are solved, the coordination of traffic facility control and vehicle control is realized, the capability of intelligent internet driving service is enhanced, the casualty rate of traffic accidents is reduced, the traffic jam time is reduced, and the traffic efficiency and the crossing scheduling efficiency are improved.
Before introducing the traffic intersection scheduling system based on the internet cloud control platform according to the embodiment of the present application, the cloud control platform, the road test infrastructure, and the communication network that are involved in the traffic intersection scheduling system based on the internet cloud control platform according to the embodiment of the present application are simply introduced.
Specifically, an intelligent networked automobile cloud control system, also called a vehicle-road cloud fusion control system, is an information physical system which utilizes new-generation information and communication technology to integrate physical layers, information layers and application layers of people, vehicles, roads and clouds into a whole, performs fusion sensing, decision making and control, and can comprehensively improve the performances of safety, efficiency and the like of vehicle running and traffic operation.
The cloud control platform, the drive test infrastructure and the communication network are described in detail below.
(1) A cloud control platform;
the cloud control platform consists of a cloud control basic platform and a cloud control application platform, and is a cloud platform for constructing a vehicle road cloud standard communication and real-time computing environment, fusing vehicle road cloud data in real time, further uniformly coordinating and operating intelligent internet driving and intelligent traffic application, and supporting the cloud control system to optimize vehicle running and traffic running performance. The cloud control basic platform provides a communication link, traffic full-factor real-time data and an application real-time operation environment for the cooperative application. And the cloud control platform performs unified regulation and control and management on the cloud control basic platform and the cooperative application according to the optimization requirements of vehicles and traffic.
(2) A drive test infrastructure;
a sensing network formed by the road side sensors provides a stable and reliable real-time sensing source of microscopic traffic elements for the cloud control system and is also used for realizing vehicle-road fusion sensing. The roadside communication equipment establishes a closed loop feedback link at the front end, and the communication coverage and performance of the cloud control system are enhanced.
(3) A communication network;
the cloud control system uses a heterogeneous communication network and integrates various wired and wireless communication technologies. Based on a standardized communication mechanism, the wide interconnection communication of people, vehicles, roads and clouds in the system is realized. And the high performance and high controllability of communication are realized by using advanced communication technologies such as 5G and software defined network.
Specifically, fig. 1 is a schematic block diagram of a traffic intersection scheduling system based on an internet cloud control platform according to an embodiment of the present disclosure.
As shown in fig. 1, the traffic intersection scheduling system based on the internet cloud control platform includes: roadside perception component 100, data processing component 200 and networking cloud control platform 300.
The roadside sensing component 100 is configured to collect traffic participant information and traffic event information of a plurality of target areas, receive vehicle fusion data sent by target networked vehicles, fuse the traffic participant information, the traffic event information and the vehicle fusion data, and obtain fusion sensing data. The data processing component 200 is configured to receive the fusion sensing data sent by the roadside sensing component 100, the shared data sent by the target resource platform, and the vehicle fusion data sent by the target internet vehicle, generate traffic full-factor real-time digital mapping data according to the fusion sensing data, the shared data, and the vehicle fusion data, process part of the traffic full-factor real-time digital mapping data into non-real-time-type cooperative application data, and process the remaining data in the traffic full-factor real-time digital mapping data into real-time-type cooperative application data. The internet cloud control platform 300 is configured to construct a data set of traffic big data according to the non-real-time type cooperative application data and the real-time type cooperative application data, generate a traffic device control instruction of the roadside sensing component and traffic control data of the target internet vehicle according to the data set of the traffic big data, and generate a scheduling signal of a traffic intersection according to the traffic device control instruction and the traffic control data.
Optionally, in some embodiments, the roadside sensing assembly 100, includes: the road side sensing unit is used for collecting traffic participant information and traffic event information of a target area; the road side communication unit is used for receiving vehicle fusion data sent by a target networked vehicle; and the fusion unit is used for fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain fusion perception data based on a preset fusion algorithm.
Optionally, in some embodiments, the data processing component 200, comprises: the multi-level fusion unit is used for receiving and fusing the fusion sensing data, the shared data and the vehicle fusion data to generate traffic full-factor real-time digital mapping data; the data analysis unit is used for constructing a data set based on partial data in the traffic full-factor real-time digital mapping data and analyzing and learning the data set to obtain non-real-time data of the cooperative application; and the application planning unit is used for carrying out real-time application calculation by combining the residual data of the traffic full-factor real-time digital mapping data under the condition of preset overall planning to obtain real-time type cooperative application data.
Optionally, in some embodiments, the shared data includes at least one of map data of the plurality of target areas, traffic management data of the plurality of target areas, meteorological data of the plurality of target areas, and positioning data of the plurality of target areas.
Specifically, as shown in fig. 2, fig. 2 is a schematic diagram of a traffic intersection scheduling system architecture based on a networking cloud control platform according to an embodiment of the present application.
The cloud control basic platform integrates information support real-time and non-real-time type cooperative application to form the cloud control platform, and information is issued to the internet-connected intelligent vehicle and the traffic equipment. After obtaining information of vehicle state, road traffic, meteorological traffic management and the like, the cloud control base platform performs fusion perception and digital mapping construction and updating of full-element real-time digital mapping with different granularities to meet different requirements of different cooperative applications on perception data granularity and quality, then data distribution is divided into two large parts, one part is analyzed and learned by using a processed data construction data set to support statistical analysis type non-real-time application, the other part is subjected to real-time application calculation by combining cloud computing resources to support real-time type application under the condition of conforming to application overall planning, and a control data instruction of a real-time calculation result is issued to a perception decision system and traffic equipment in a cellular wireless mode to determine actions, traffic signals, facility guidance and the like of the internet-connected automobile, so that a real-time all-level interactive system is constructed.
In the whole cloud control system, a communication network organically connects all components together in a safe, efficient and reliable manner according to the requirements of standardized information transmission and interaction among all the components, so that a cloud control platform is ensured to become an information physical system which is logically cooperative, physically dispersed and capable of supporting the development of an intelligent networked automobile industry, and the networked intelligent automobile is a data source and a controlled object of the cloud control system. The vehicle end data comprise running data of a vehicle system and driving environment data acquired by a sensor, interaction with cooperative application relates to sensing, decision making, control and other links of auxiliary driving or automatic driving, and under the action of the cooperative application, the cloud control system not only directly improves the running performance of the internet-connected intelligent vehicle, but also improves the running performance of mixed traffic by using the internet-connected intelligent vehicle, and the effect of improving the efficiency of crossing scheduling is achieved.
Cloud control is a novel technical means for realizing high concurrency of a cloud control system and running real-time cloud control application as required. The requirements of real-time cloud control applications such as high-level automatic driving on millisecond-level time delay and ultrahigh reliability of information transmission far exceed the technical capability of the traditional cloud computing architecture, and the actual requirements of a cloud control system need to be met through the cloud control architecture design. The cloud control architecture aims to integrate real-time communication, real-time data exchange and real-time cooperative computing technologies, achieve real-time performance of system response, low time delay of data transmission and high concurrency of access requests, guarantee that vehicle road cloud data exchange meets the actual requirements of automatic driving control on real-time performance and availability and information safety under large concurrency on the application level, and guarantee interoperability and usability. The related technical work comprises the steps of formulating a unified data interaction standard, developing a basic data grading sharing interface, optimizing a data storage model, establishing a high-performance message system, ensuring the real-time performance of cloud control service by adopting a lightweight infrastructure and a virtualization management platform, optimizing the performance of a reporting and issuing communication link and the like.
Cloud takeover is one of the important functions of the cloud control base platform. The dynamic cloud connection pipe is oriented to various task entities and comprises road-end intelligent interconnected vehicles, basic physical construction equipment, regional cloud and cloud control computing equipment and central cloud top layer management. The intelligent networked vehicle facing the road end can help the cloud control basic platform to remotely take over decision of the unmanned aerial vehicle in a complex environment, safety and reliability of unmanned driving are improved, and driving under complex road conditions is achieved. By introducing an optimization decision based on global perception, traffic accidents and casualties are reduced. In mining and driving, optimization decisions based on global perception are introduced to reduce traffic accidents and casualties. Other traffic participants are crowded and injured due to abnormal or uncontrolled vehicles or problems in the mine, and the cloud control basic platform can be helped to carry out more robust operation design when facing terminal equipment and cloud computing equipment. Through comprehensive information aggregation of network connection, a dynamic cloud connection function can be established from three layers of vehicle end, road side and cloud platform coordination. The safe and efficient combination of the terminal and the cloud platform is realized through the real-time transmission of the three-layer architecture of the cloud control, the regional cloud and the central cloud. The vehicle end comprises vehicle types and vehicle-mounted equipment, and the vehicle types comprise different types such as mine trucks, excavators and unmanned minibuses; the vehicle-mounted hardware comprises basic facilities such as a camera, a millimeter wave radar, a laser radar, positioning, a vehicle-mounted controller and the like, and environment sensing and information transmission are achieved. For example, sensing devices such as millimeter wave radars, laser radars, cameras and the like can realize environment perception and information fusion, and obstacle detection is completed. The construction of the three-dimensional network is based on information transmission of cloud control, regional cloud, central cloud, vehicle-to-vehicle and vehicle-to-scheduling center.
The traffic intersection scheduling system based on the internet cloud control platform is mainly characterized by being a group of domain specific standard components, and is used for supporting cloud control application function construction such as blind area and beyond-visual-distance danger early warning and collaborative lane change planning through basic services such as road traffic predictive perception and decision suggestion. The cloud control basic service system provides high-instantaneity and weak-instantaneity cloud control basic service for enhancing driving safety for the internet-connected automobile, and comprises high dynamic data management, multi-sensor fusion perception, traffic participant and traffic event perception, and a coordination decision planning and control standard component. The cloud control system has the advantages that real-time structured data of sensing equipment such as a road end and a vehicle end are accessed by the data management standard component through communication modes such as 4G/5G/C-V2X, and the like, such as V2X, video, millimeter wave radar, laser radar and the like, the traffic participants and traffic event information can be timely and accurately detected and obtained through a multi-sensor fusion sensing technology, cloud control basic scene functions including road danger information, traffic accident information, emergency vehicle information, traffic jam information, expressway weak traffic participant reminding, cooperative (intersection and ramp) communication and the like can be realized, and the basic function of a comprehensive cloud control application scene is supported. Through flexible architecture reorganization and continuous deep optimization of technology, according to different stages and application requirements of communication technology, for example, LTE-V/C-V2X is used in the initial stage, a cloud-controlled low-delay calculation model is combined, finally, high-availability and high-concurrency millisecond-level delay service is achieved when 5G land falls, and intelligent networked automobiles of different levels achieve edge calculation-based cooperative decision and cooperative control functions for improving vehicle running safety, efficiency and other performances, such as blind area and beyond visual range danger early warning, optimal vehicle speed planning, cooperative lane change planning, formation control and the like. In addition, various real-time, quasi-real-time and non-real-time basic data related to vehicles and driving environments thereof are provided for various cloud control application platforms, common services with dimensions of safety, high efficiency, comfort, energy conservation and the like are provided for vehicle enterprises or external systems as required through containerized management and unified interfaces, and specific services mainly comprise related real-time data services such as perception and early warning facing to driving safety and decision and control services facing to driving efficiency and energy conservation. The cloud control performance, such as real-time performance, time delay and high concurrency capability, is realized in stages in the development and landing processes of the cloud control system.
Limited by the design mechanism of the traditional traffic sensor system, the detection coverage, the communication transmission capability and the survival capability of a single sensor system cannot meet the actual requirements of an intelligent traffic big data platform for distributing mass data quickly and efficiently. Therefore, it is necessary to establish a multi-source heterogeneous communication cluster system including a large number of small, low-power-consumption and low-weight traffic sensor units, as a special "big data space sensing network" operating in a big data space environment, where the system employs a self-organization and self-management technology in the big data space to complete a series of big data space exploration tasks through networking cooperation. A large multi-source heterogeneous communications cluster is made up of multiple subsets. The sub-cluster is a sub-cluster which is temporarily organized flexibly aiming at the observation task of a certain traffic area, and the members of the flow sensors in the cluster are divided into three types, namely a director responsible for directing and coordinating the traffic sensors of the cluster members, a worker carrying a large number of special detection devices, and a messenger responsible for coordinating and organizing data communication among the director, an implementer and a gathering station. These heterogeneous micro-traffic sensors, while varying in load, role and responsibility, rely primarily on solar energy for data acquisition, processing and communication. Due to the size limitation of the traffic sensor solar panel, energy efficiency issues must be considered when designing such a multi-source heterogeneous communication cluster system. Therefore, for the multi-source heterogeneous communication cluster, selecting a proper traffic sensor working mode is a problem to be solved urgently. An online big data fusion scheduling algorithm aiming at the working state of the traffic sensor is designed, and the data acceptance of the time averaging system is improved to the maximum extent under the condition of ensuring the stability of the system and energy consumption constraint. The embodiment of the application mainly researches a big data fusion scheduling technology of traffic sensor work under energy constraint, and a schematic diagram of a big data fusion scheduling process of traffic sensor work is shown in fig. 3. And considering the energy consumption and power supply constraint of the micro traffic sensor, selecting the working mode of the traffic sensor, and respectively establishing a multi-source heterogeneous communication cluster system model and a virtual queue model. On the basis, an online big data fusion scheduling algorithm based on the Lyapunov optimization technology can be used for solving the problem of scheduling the working state of the traffic sensor with limited energy.
The vehicle-road cloud standardized communication technology establishes wide interconnection of vehicles, roads and clouds of a cloud control system by a standardized mechanism, and realizes high performance, high safety and high customizability of high concurrent communication. The specific key technologies include heterogeneous converged communication, standard communication protocol and application protocol self-adaptation, high-performance message middleware, communication performance optimization for a cloud control platform and a communication network, self-adaptive information security based on dynamic demand analysis and the like. The vehicle road cloud standardized communication technology composition architecture is shown in fig. 4, heterogeneous converged communication components need to communicate different types of wired and wireless communication networks, wide interconnection among nodes of a vehicle road cloud is achieved, meanwhile, different communication networks are abstracted, and different communication modes are hidden in a message middleware to achieve concrete implementation. To better support communication performance optimization, heterogeneous converged communication also needs to have and abstract controllability of the communication network and the data transmission therein. Heterogeneous converged communication needs to meet the requirements of control of networked vehicles on communication real-time performance, reliability, rate under concurrent communication and the like. The standard communication protocol component is used for modeling the traffic full-factor data in a unified standard mode, determining a data classification system and standardizing attributes such as data names, data precision and errors, updating frequency and the like and description of the attributes. Under the framework of a standard communication protocol, each cooperative application self-defines an application protocol, and the self-adaptation of the application protocols at all places of the vehicle road cloud is realized through the automatic updating and synchronization mechanism of the application protocols.
According to the vehicle road cloud fusion perception technology, vehicle road cloud perception information acquired by a cloud control platform is subjected to microscopic perception fusion on edge clouds and macroscopic perception fusion on regional clouds to form real-time digital mapping of all traffic elements, and a big data set is constructed on a central cloud. Each edge cloud and each regional cloud perform information synchronization and sharing with adjacent same-level clouds to improve response and reliability of digital mapping data, and a vehicle-road cloud fusion perception technology composition architecture is shown in fig. 5.
The real-time digital mapping of all traffic elements is a digital twin required by a cloud control system for realizing vehicle running and traffic operation optimization through fusion perception, decision and control, and mainly comprises a model of relevant elements of vehicle running and traffic operation, real-time updated state data and historical state data. The key of the real-time digital mapping is that the frequency and the time delay of state updating meet the requirements of real-time type cooperative application on input data, so that the real-time perception fusion of digital mapping is mainly constructed by an edge cloud and a regional cloud. The requirements of cooperative application on the granularity and timeliness of the perception data can be classified according to levels, and therefore a layered perception fusion framework is designed. The cooperative application has high requirement on the timeliness of microscopic data (such as the state of a road user), and the microscopic data fusion performed at the road side and the edge cloud has high frequency and low time delay. The timeliness requirement of the cooperative application on the macroscopic traffic and the environmental data (such as the speed of the macroscopic traffic flow of a road network and meteorological conditions) is relatively low, and the macroscopic data fusion in regional clouds can have relatively low frequency and larger time delay. The deployment of the edge cloud and the deployment of the regional cloud are both physically dispersed, and each machine room or data center serves a certain geographical range, so the perception fusion is also performed dispersedly. The geographic range of data required by the collaborative application may span multiple cloud service areas, and therefore a synchronization mechanism of real-time digital mapping is also required between the edge cloud and the area cloud of the same level to ensure the performance of cross-region data distribution. The central cloud mainly utilizes the digital mapping of the edge cloud and the regional cloud to construct a data set of the traffic big data.
According to the traffic intersection scheduling system based on the internet cloud control platform, provided by the embodiment of the application, traffic participant information and traffic event information of a target area are collected, vehicle fusion data sent by a target internet vehicle are received, the traffic participant information, the traffic event information and the vehicle fusion data are fused to obtain fusion perception data, the fusion perception data sent by a road side perception component, shared data sent by a target resource platform and vehicle fusion data sent by the target internet vehicle are received, all-element real-time digital mapping data are generated, part of data in the all-element real-time digital mapping data are processed into non-real-time type cooperative application data, residual data in the all-element real-time digital mapping data are processed into real-time type cooperative application data, a traffic big data set is constructed according to the non-real-time type cooperative application data and the real-time type cooperative application data, a traffic equipment control instruction and traffic control data of the target internet vehicle are generated, and traffic signals of a traffic intersection are generated according to the traffic equipment control instruction and the traffic control data. Therefore, the problems that the direction with more vehicles is insufficient in conduction time, the direction with less vehicles is remained in conduction time, the vehicles in one direction are crowded, the vehicle flow in the other direction is low are unreasonable and the like are solved, the coordination of traffic facility control and vehicle control is realized, the capability of intelligent internet driving service is enhanced, the casualty rate of traffic accidents is reduced, the traffic jam time is reduced, and the traffic efficiency and the crossing scheduling efficiency are improved.
The embodiment of the application provides a traffic intersection scheduling method based on a networking cloud control platform, which comprises the following steps: collecting traffic participant information and traffic event information of a plurality of target areas, receiving vehicle fusion data sent by target networked vehicles, and fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain fusion perception data; receiving fusion perception data sent by a roadside perception component, shared data sent by a target resource platform and vehicle fusion data sent by a target networked vehicle, generating traffic full-element real-time digital mapping data according to the fusion perception data, the shared data and the vehicle fusion data, processing part of data in the traffic full-element real-time digital mapping data into non-real-time type cooperative application data, and processing the rest of data in the traffic full-element real-time digital mapping data into real-time type cooperative application data; and constructing a data set of traffic big data according to the non-real-time type cooperative application data and the real-time type cooperative application data, generating a traffic equipment control instruction of the road side sensing assembly and traffic control data of the target networked vehicle according to the data set of the traffic big data, and generating a dispatching signal of a traffic intersection according to the traffic equipment control instruction and the traffic control data.
Optionally, in some embodiments, the traffic intersection scheduling method based on the internet-connected cloud control platform further includes: collecting traffic participant information and traffic event information of a target area; receiving vehicle fusion data sent by a target networked vehicle; and fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain fusion perception data based on a preset fusion algorithm.
Optionally, in some embodiments, the traffic intersection scheduling method based on the internet cloud control platform further includes: receiving and fusing the fusion sensing data, the shared data and the vehicle fusion data to generate traffic full-factor real-time digital mapping data; constructing a data set based on partial data in the traffic full-factor real-time digital mapping data, and analyzing and learning the data set to obtain non-real-time data of the cooperative application; and under the condition of a preset overall plan, performing real-time application calculation by combining the residual data of the traffic full-factor real-time digital mapping data to obtain real-time type cooperative application data.
Optionally, in some embodiments, the shared data includes at least one of map data of the plurality of target areas, traffic management data of the plurality of target areas, meteorological data of the plurality of target areas, and positioning data of the plurality of target areas.
According to the traffic intersection scheduling method based on the internet cloud control platform, traffic participant information and traffic event information of a target area are collected, vehicle fusion data sent by a target internet vehicle are received, the traffic participant information, the traffic event information and the vehicle fusion data are fused to obtain fusion perception data, the fusion perception data sent by a road side perception component, shared data sent by a target resource platform and the vehicle fusion data sent by the target internet vehicle are received, all-traffic-element real-time digital mapping data are generated, part of the all-traffic-element real-time digital mapping data are processed into non-real-time-type cooperative application data, residual data in the all-traffic-element real-time digital mapping data are processed into real-time-type cooperative application data, a traffic big data set is constructed according to the non-real-time-type cooperative application data and the real-time-type cooperative application data, traffic equipment control instructions and traffic control data of the target internet vehicle are generated, and traffic signals of a traffic intersection are generated according to the traffic equipment control instructions and the traffic control data. Therefore, the problems that the direction with more vehicles is insufficient in conduction time, the direction with less vehicles is remained in conduction time, the vehicles in one direction are crowded, the vehicle flow in the other direction is low are unreasonable and the like are solved, the coordination of traffic facility control and vehicle control is realized, the capability of intelligent internet driving service is enhanced, the casualty rate of traffic accidents is reduced, the traffic jam time is reduced, and the traffic efficiency and the crossing scheduling efficiency are improved.
Fig. 6 is a schematic structural diagram of an electronic device according to an embodiment of the present application. The electronic device may include:
a memory 601, a processor 602, and a computer program stored on the memory 601 and executable on the processor 602.
When the processor 602 executes the program, the traffic intersection scheduling method based on the internet cloud control platform provided in the above embodiments is implemented.
Further, the electronic device further includes:
a communication interface 603 for communication between the memory 601 and the processor 602.
The memory 601 is used for storing computer programs that can be run on the processor 602.
If the memory 601, the processor 602 and the communication interface 603 are implemented independently, the communication interface 603, the memory 601 and the processor 602 may be connected to each other through a bus and perform communication with each other. The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 6, but this is not intended to represent only one bus or type of bus.
Optionally, in a specific implementation, if the memory 601, the processor 602, and the communication interface 603 are integrated into a chip, the memory 601, the processor 602, and the communication interface 603 may complete mutual communication through an internal interface.
The embodiment of the application further provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the traffic intersection scheduling method based on the internet cloud control platform is implemented.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or N embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "N" means at least two, e.g., two, three, etc., unless explicitly defined otherwise.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more N executable instructions for implementing steps of a custom logic function or process, and alternate implementations are included within the scope of the preferred embodiment of the present application in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present application.
The logic and/or steps represented in the flowcharts or otherwise described herein, such as an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or N wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods may be implemented in software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are well known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc. Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. The utility model provides a traffic crossing dispatch system based on networking cloud accuse platform which characterized in that includes:
the road side sensing component is used for acquiring traffic participant information and traffic event information of a plurality of target areas, receiving vehicle fusion data sent by target networked vehicles, and fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain fusion sensing data;
the data processing component is used for receiving the fusion perception data sent by the roadside perception component, the shared data sent by a target resource platform and the vehicle fusion data sent by the target internet vehicle, generating traffic full-factor real-time digital mapping data according to the fusion perception data, the shared data and the vehicle fusion data, processing part of the traffic full-factor real-time digital mapping data into non-real-time type cooperative application data, and processing the rest of the traffic full-factor real-time digital mapping data into real-time type cooperative application data; and
and the internet cloud control platform is used for constructing a data set of traffic big data according to the non-real-time type cooperative application data and the real-time type cooperative application data, generating a traffic equipment control instruction of the roadside sensing assembly and traffic control data of the target internet vehicle according to the data set of the traffic big data, and generating a dispatching signal of a traffic intersection according to the traffic equipment control instruction and the traffic control data.
2. The system of claim 1, wherein the roadside sensing component comprises:
the roadside sensing unit is used for acquiring traffic participant information and traffic event information of the target area;
the road side communication unit is used for receiving vehicle fusion data sent by the target networked vehicle;
and the fusion unit is used for fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain the fusion perception data based on a preset fusion algorithm.
3. The system of claim 1, wherein the data processing component comprises:
the multi-level fusion unit is used for receiving and fusing the fusion perception data, the shared data and the vehicle fusion data to generate the traffic full-factor real-time digital mapping data;
a data analysis unit for constructing a data set based on partial data in the traffic full-factor real-time digital mapping data, and analyzing and learning the data set to obtain the data of the non-real-time type collaborative application
And the application planning unit is used for carrying out real-time application calculation by combining the residual data of the traffic full-element real-time digital mapping data under the condition of preset overall planning to obtain the data of the real-time type cooperative application.
4. The system of claim 3, wherein the shared data comprises at least one of map data of the plurality of target areas, traffic data of the plurality of target areas, meteorological data of the plurality of target areas, and positioning data of the plurality of target areas.
5. A traffic intersection scheduling method based on a networked cloud control platform is characterized in that the traffic intersection scheduling system based on the networked cloud control platform as claimed in any one of claims 1 to 4 is adopted, and the method comprises the following steps:
collecting traffic participant information and traffic event information of a plurality of target areas, receiving vehicle fusion data sent by target networked vehicles, and fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain fusion perception data;
receiving the fusion perception data sent by the roadside perception component, the shared data sent by a target resource platform and the vehicle fusion data sent by the target networked vehicle, generating traffic full-factor real-time digital mapping data according to the fusion perception data, the shared data and the vehicle fusion data, processing part of the traffic full-factor real-time digital mapping data into non-real-time type cooperative application data, and processing the rest of the traffic full-factor real-time digital mapping data into real-time type cooperative application data; and
and constructing a data set of traffic big data according to the data of the non-real-time type cooperative application and the data of the real-time type cooperative application, generating a traffic equipment control instruction of the roadside sensing component and traffic control data of the target networked vehicle according to the data set of the traffic big data, and generating a dispatching signal of a traffic intersection according to the traffic equipment control instruction and the traffic control data.
6. The method of claim 5, further comprising:
collecting traffic participant information and traffic event information of the target area;
receiving vehicle fusion data sent by the target networked vehicle;
and fusing the traffic participant information, the traffic event information and the vehicle fusion data to obtain the fusion perception data based on a preset fusion algorithm.
7. The method of claim 5, further comprising:
receiving and fusing the fusion perception data, the shared data and the vehicle fusion data to generate the traffic full-factor real-time digital mapping data;
constructing a data set based on partial data in the traffic full-factor real-time digital mapping data, and analyzing and learning the data set to obtain the data of the non-real-time type collaborative application
And under the condition of a preset overall plan, performing real-time application calculation by combining the residual data of the traffic full-factor real-time digital mapping data to obtain the data of the real-time type cooperative application.
8. The method of claim 7, wherein the shared data includes at least one of map data of the plurality of target areas, traffic data of the plurality of target areas, meteorological data of the plurality of target areas, and positioning data of the plurality of target areas.
9. An electronic device comprising a memory, a processor;
wherein the processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the internet cloud control platform-based traffic intersection scheduling method according to any one of claims 5 to 8.
10. A computer-readable storage medium storing a computer program, wherein the program, when executed by a processor, implements the internet cloud control platform-based traffic intersection scheduling method according to any one of claims 5 to 8.
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| CN117079451B (en) * | 2023-07-11 | 2024-04-19 | 清华大学 | Control method and device for mixed traffic system in urban continuous intersection scene |
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