CN116030630A - Traffic light learning system based on networking function - Google Patents
Traffic light learning system based on networking function Download PDFInfo
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Abstract
The invention relates to a traffic light learning system, in particular to a traffic light learning system based on a networking function, which comprises comprehensive service base station hardware, traffic light learning machine software and a digital twin platform which are connected with each other, wherein a power supply circuit, a core processing unit, a singlechip, a 5G antenna, a C-V2X antenna, a GNSS antenna, a WIFI antenna, an RS485 interface, an RS232 interface and a network port RJ45 interface are arranged on a comprehensive service base station hardware body; the traffic light learning system software is provided with an RS485 communication module, an RS232 communication module, a 5G & C-V2 communication module, a singlechip module and an Ethernet module; the digital twin platform is divided into: the information acquisition layer, the information interaction layer, the cooperative processing layer, the functional service layer and the business butt joint layer can be installed on occasions with limited space, the wiring mode is simple, the construction efficiency of constructors can be improved, and one machine is multipurpose and compatible with multiple complex application scenes.
Description
Technical Field
The invention relates to the technical field of traffic light learning systems, in particular to a traffic light learning system based on a networking function.
Background
The number of the internet of vehicles lead areas is continuously increasing, intelligent traffic is greatly developed, and the demand for a traffic light learning system is also higher. At present, most traffic lights are in a fixed switching period mode, part of the traffic lights support a networking function, but are only connected to the Internet, cannot be communicated with an intelligent network vehicle in real time, and cannot be integrated with a new generation of collaborative intelligent traffic system, in the intelligent network system, a traffic light learning system can only realize a single function and needs to be used together with other equipment, and the whole equipment has large occupied space, more construction links and complicated field debugging links in the installation process.
Disclosure of Invention
Aiming at the technical defects, the invention provides a traffic light learning system based on a networking function, which solves the problems of single function, large occupied space in the installation process of the whole equipment, more construction links, complicated field debugging links and the like of the existing traffic light learning system.
In order to achieve the above purpose, the present invention provides the following technical solutions:
the traffic light learning system based on the networking function comprises comprehensive service base station hardware, traffic light learning machine software and digital twin platform interconnection, wherein a power supply circuit, a core processing unit, a singlechip, a 5G antenna, a C-V2X antenna, a GNSS antenna, a WIFI antenna, an RS485 interface, an RS232 interface and a network port RJ45 interface are arranged on a comprehensive service base station hardware body; the traffic light learning system software is provided with an RS485 communication module, an RS232 communication module, a 5G & C-V2 communication module, a singlechip module and an Ethernet module; the digital twin platform is divided into: the system comprises an information acquisition layer, an information interaction layer, a cooperative processing layer, a functional service layer and a business butt joint layer.
The technical scheme of the invention is further improved as follows: and a power supply circuit: an external DC12V power supply, which provides 5V/3.8V/3.3V/1.8V/1.5V voltage for other hardware through power management;
and the singlechip is used for: collecting and forwarding traffic light signal time and state;
the core processing unit: optimizing time and state data forwarded by the singlechip, managing communication modes among all communication interfaces, recording and transmitting time and state of a traffic light to a core processing unit through the singlechip, optimizing data by the core processing unit, and finally transmitting the data to an intelligent network bus and a cloud platform in a wired or wireless communication mode;
5G antenna: the equipment is in wireless communication with the 5G base station, and the 5G antenna realizes a long-distance large-range wireless communication network;
D-V2X antenna: the wireless communication mode of the Internet of vehicles adopts a C-V2X technology, which is the combination of direct communication and cellular network communication, and a C-V2X antenna is used for realizing a short-distance wireless communication network;
E-GNSS antenna: the positioning device is arranged at a position, and the GNSS functions are time service and positioning, so that the time synchronization of all devices can be realized while high-precision positioning is provided, and the time delay precision of data transmission is ensured;
WIFI antenna: the wireless communication between the short-distance equipment and the equipment is carried out, the WIFI communication supports the short-distance wireless communication, and the WIFI communication is connected with a plurality of equipment or mobile phones for data bidirectional transmission;
RS485 interface: the RS485 interface is communicated with a device or a sensor of a support 485 interface, and the RS485 interface is in wired long-distance reliable communication with an external support 485 transmission protocol sensor;
RS232 interface: the standard 232 serial port protocol is communicated with equipment or a sensor supporting 232 serial ports, so that wired short-distance communication between the equipment and the equipment or between the equipment and the sensor is realized;
network port RJ45 interface: the gigabit wired network interface RJ45 is connected with other devices or optical cats by a network cable mode for wired communication, and comprises: and the WAN port and the four LAN ports are connected with an external network for wide area network communication and an internal network for local area network communication.
The technical scheme of the invention is further improved as follows: the network interface, the RS485 interface, the RS232 interface, the 5G and the WIFI can be communicated in pairs or can be independently used.
The technical scheme of the invention is further improved as follows: the working process of the traffic light learning system software comprises the following steps:
step 1, self-learning of a singlechip module, namely judging the state of a traffic light according to the change condition of a control signal of the traffic light, and judging the countdown time of the traffic light by periodically learning the change frequency so as to realize the self-learning of the state of the traffic light and the countdown information;
step 2, receiving RS485 and RS232 data by the singlechip: the baud rate is 115200bps, and the communication is carried out with an external sensor or equipment, and the data content is obtained;
step 3, the singlechip performs verification on the data and then sends the data in a group package: and verifying all the acquired data, and finally packaging and packaging the data according to a communication protocol between the singlechip and the core processing unit.
Step 4, the core processing unit analyzes and verifies the data: the core processing unit receives all data and performs byte performance verification on the head and the tail of the data according to a protocol;
step 5, SPAT message group package: according to SPAT requirements in the T/TS0117-2020 protocol, performing JSON format packet grouping on SPAT data;
step 6.Info message group package: according to the requirement on INFO in the T/TS0117-2020 protocol, the INFO data is packaged in a JSON format, wherein LAT, LON, DEV _ID necessary filling information is configured and read through a file IO;
step 7, establishing a core processing unit information reporting link: according to the T/TS0117-2020 protocol, a communication link is established with the cloud platform by adopting an MQTT communication mode, wherein communication IP, port, username, password data is configured and read through a file IO;
step 8, the core processing unit periodically reports the data to the Internet of vehicles application service platform or the intelligent network vehicle: according to the T/TS0117-2020 protocol, SPAT data and INFO data are reported to the cloud platform through 5G at a specified frequency, can be reported to the cloud platform through TCP/IP transmission protocol, and can be communicated with surrounding intelligent network vehicles in a two-way through V2X;
step 9, the cloud platform transmits data downwards: data is sent to a traffic light learning machine through a cloud platform, wherein the data comprises equipment with an RS485 or RS232 communication protocol and a sensor, and the communication mode is TCP/IP transmission protocol or 5G; the cloud platform is used for sending a positioning instruction, the core processing unit is used for reading positioning information of the GPNSS module through the AT instruction and feeding back the positioning information to the cloud platform in a wired or wireless mode, after the WIFI function is started, other equipment is connected with the learning machine through a standard WIFI protocol to carry out two-way communication, and therefore wireless communication within a certain distance is achieved.
The technical scheme of the invention is further improved as follows: the traffic light learning machine software also comprises the following functions:
the system log module of the signal machine network system is written, the log module records the signal machine state, the learning machine state and the equipment operation condition, and provides a downloading function, and the operation state of the network system is checked by a remote system to perform simple equipment operation and maintenance;
writing a remote control interface of a network system equipment end, remotely starting equipment, closing the equipment, reading the equipment state, starting or closing WIFI, and remotely upgrading the network operation state and the equipment to restore factory settings;
the network system equipment management module is written, codes on-site installed equipment and comprises equipment ID, equipment model, sim card number, operators, installation positions, namely longitude and latitude, remark information, codes according to a unified data format, and inputs equipment detailed information into the terminal management cloud platform of the Internet of things after on-site installation;
and carrying out network configuration on the signal machine network system, establishing a VPN channel, using the FRP technology to allocate addresses, so that the system and the terminal management cloud platform of the Internet of things are linked, or carrying out data transmission by using a TCP/IP transmission protocol.
The technical scheme of the invention is further improved as follows: the digital twin platform has map information of intersections in a project planning range, state information of annunciators and digitalized three-dimensional presenting capability of calibration position information, the platform has the capability of providing accurate time synchronization service for various devices, the platform has the capability of uniformly accessing, managing and distributing the devices, carries out link management, data analysis and management on a traffic light learning machine with a networking function, carries out device state acquisition and management on the annunciators and the traffic light learning machine with the networking function, uploads the period and phase providing API interfaces of the annunciators to an upper service platform to support the Internet of vehicles application, and the whole framework is divided into five layers, wherein each layer of framework corresponds to supporting hardware and service functions respectively, and finally supports the upper platform to realize traffic light information broadcasting, green wave speed guiding and red light running early warning Internet of vehicles application;
the signal acquisition layer is used for simulating and acquiring the phase, countdown information, equipment state, basic information and traffic light fault information of the lamp group of the annunciator in a non-contact manner, realizing intelligent learning in the signal control period and rapidly outputting changed results; firstly, the interface development is carried out through the SDK or the interface protocol of the signal machine, and the current configuration scheme, signal period and real-time signal phase state of the signal machine are received. Analyzing the received data information; secondly, updating the state of the annunciator equipment by analyzing the annunciator data, including whether the online and the phase accord with the scheme or not, and updating the state information of the annunciator equipment; then recording fault information of the equipment, reporting the fault to a platform in time, and configuring a mailbox and a short message sending mode to inform a system administrator; finally, all data content packets are sent and reported to the platform;
the signal interaction layer uploads the acquired signal state to a platform through various network channels, and the platform performs data verification on the received data and reads equipment state information;
the collaborative processing layer belongs to a middle platform capacity part of the digital twin platform, and is respectively digital space-time bottom capacity and data middle platform capacity, and the digital space-time base is based on a high-precision map and accurate time synchronization, so that the whole system is ensured to be in a uniform space reference, and all business scenes are supported; the data center station is connected with a signaler and traffic light learning machine equipment with a networking function, and provides accurate and efficient data distribution for a service platform through unified access authentication and protocol adaptation; the digital space-time base is formed by using a high-precision map to establish a space reference system of the intersection as a space reference, realizing the calibration of an intersection time line as a time reference through the time service of GNSS, and forming the intersection digital space-time base consistent with the real intersection space and time reference system based on a space-time synchronization technology; the digital base provides high-precision map service, high-precision time synchronization service and three-dimensional scene construction service based on a high-precision map, and then the edge data base provides unified data standard for data convergence, distribution and circulation and provides data support for digital management and control as well as digital twinning of static and dynamic elements. Through the construction of an edge data base, carrying out virtualization processing on various information data of a road, realizing mapping from a real physical world to a digital twin virtual world through various data interactions based on a space-time reference of a space-time base, and realizing digital support of a networking application scene on the basis;
the functional service layer belongs to a platform layer, the platform layer adopts a digital twin technology to reconstruct road and infrastructure equipment and present real-time traffic state information, and meanwhile, the platform performs tabulated detailed management on the equipment to provide viewing, configuration and modification capabilities for the equipment accessed to the platform;
the service butt-joint layer reserves the possibility of platform service to an upper service platform, the traffic state information reaches the upper service platform, and the traffic light information broadcasting, the green wave speed guiding and the red light running early warning vehicle networking application are supported.
The technical scheme of the invention is further improved as follows: the whole system adopts GNSS time service as a time source, and establishes time references of all hardware devices and servers.
Compared with the prior art, the traffic light learning system based on the internet connection function has the following beneficial effects:
1. the invention provides a traffic light learning system based on a networking function, which is installed in a traffic light signal control cabinet and is in wired connection with a control signal of a traffic light, and a singlechip is used for learning and recording time and state and reporting data. And sending the traffic light signals to an intelligent network car through a C-V2X network, and simultaneously sending the traffic light signals to a cloud platform through an access gateway in a wired network connection mode. The traffic light learning machine with the networking function is combined with the digital twin platform to form a digital traffic light system supporting a new generation of cooperative traffic system. The method is used for realizing the application of the Internet of vehicles such as traffic light information broadcasting, green wave speed guiding, red light running early warning and the like in the Internet of vehicles leading region.
2. The invention provides a traffic light learning system based on a networking function, which not only can record traffic light time and state, but also can process and optimize data results, and can be compatible with various wired and wireless communication modes. The cable is particularly suitable for being installed on occasions with limited space, the wiring mode is simple, the construction efficiency of constructors can be improved, and one cable is multipurpose and compatible with various complex application scenes. The digital traffic light system is matched with a platform system of the intelligent traffic light system to form an intelligent and high-reliability digital traffic light system of a cooperative traffic system.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic hardware structure diagram of a traffic light learning system based on a networking function;
FIG. 2 is a schematic diagram of a software system of the traffic light learning system based on the networking function;
FIG. 3 is a flow chart of a digital twin platform of the traffic light learning system based on the networking function;
fig. 4 is a flowchart of a high-precision time service of the traffic light learning system based on the internet connection function.
Detailed Description
The technical scheme of the present invention will be clearly and completely described in the following detailed description. It will be apparent that the described embodiments are only some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment provides a traffic light learning system based on a networking function, which comprises integrated service base station hardware, traffic light learning machine software and digital twin platform interconnection, wherein a power supply circuit, a core processing unit, a singlechip, a 5G antenna, a C-V2X antenna, a GNSS antenna, a WIFI antenna, an RS485 interface, an RS232 interface and a network port RJ45 interface are arranged on an integrated service base station hardware body; the traffic light learning system software is provided with an RS485 communication module, an RS232 communication module, a 5G & C-V2 communication module, a singlechip module and an Ethernet module; the digital twin platform is divided into: the system comprises an information acquisition layer, an information interaction layer, a cooperative processing layer, a functional service layer and a business butt joint layer.
As shown in fig. 1, a power supply circuit, a core processing unit, a single chip microcomputer, a 5G antenna, a C-V2X antenna, a GNSS antenna, a WIFI antenna, an RS485 interface, an RS232 interface, and a network RJ45 interface are arranged on a hardware body of the integrated service base station, and functions and roles of each part of the hardware of the integrated service base station are as follows:
and a power supply circuit: an external DC12V power supply is used for providing 5V/3.8V/3.3V/1.8V/1.5V voltage for other functional modules through power management.
And the singlechip is used for: and collecting and forwarding the time and state of traffic light signals.
The core processing unit: optimizing time and state data forwarded by the singlechip, managing communication modes among all communication interfaces, recording and transmitting time and state of a traffic light to the core processing unit through the singlechip, optimizing data by the core processing unit, and finally transmitting data to the intelligent network bus and the cloud platform in a wired or wireless communication mode.
5G antenna: the device and the 5G base station are in wireless communication, and the 5G communication is a communication mode of 'fifth generation' cellular communication for wireless long-distance reliable transmission. The 5G antenna realizes a long-distance and large-range wireless communication network and is in bidirectional communication with the C-V2X cloud platform through communication networks of three operators.
C-V2X antenna: the wireless communication mode of the Internet of vehicles adopts a C-V2X technology, is the combination of direct communication and cellular network communication, realizes a short-distance wireless communication network by a C-V2X antenna, carries out C-V2X two-way communication with surrounding vehicles through a C-V2X data channel, and acquires longitude and latitude coordinates of the vehicles through the C-V2X data channel.
D-GNSS antenna: and positioning the installation position of the equipment, and determining the installation position of the current equipment in a GNSS mode. The GNSS functions are time service and positioning, and can synchronize time of all devices while providing high-precision positioning, so that time delay precision of data transmission is ensured.
WIFI antenna: the wireless communication between the short-distance equipment and the equipment can be supported by the WIFI communication, a plurality of equipment or mobile phones can be connected to carry out data bidirectional transmission, and the equipment can be set to be a WIFI terminal or a WIFI hot spot mode to communicate with surrounding equipment.
RS485 interface: the RS485 interface can be communicated with an external 485 transmission protocol sensor in a wired long-distance reliable mode, such as a weather environment sensor and the like, and can monitor local weather in real time. And wired remote bidirectional communication is carried out with an external sensor or equipment in a wired mode.
RS232 interface: and wired short-distance bidirectional communication is carried out with an external sensor or equipment in a serial port mode. The RS232 interface is a standard 232 serial port protocol and can realize wired short-distance reliable communication between the equipment and the equipment or between the equipment and the sensor, such as a humidity sensor and the like, and can monitor the humidity in the case in real time and effectively detect the water leakage or water drop.
Network port RJ45 interface: the gigabit wired network interface RJ45 comprises a WAN port and four LAN ports, can be connected with an external network for wide area network communication and can also be connected with an internal network for local area network communication.
As shown in fig. 2, the traffic light learning system software is provided with an RS485 communication module, an RS232 communication module, a 5g & c-V2 communication module, a singlechip module and an ethernet module, and the working process comprises the following steps:
step 1: the self-learning of the singlechip module is to judge the state of the traffic light according to the change condition of the control signal of the traffic light, and judge the countdown time of the traffic light by periodically learning the change frequency so as to realize the self-learning of the state of the traffic light and the countdown information;
step 2: the singlechip receives RS485 and RS232 data: the baud rate is 115200bps, and the communication is carried out with an external sensor or equipment, and the data content is obtained;
step 3: and the singlechip performs packet transmission after checking the data: checking all acquired data, and finally packaging and packaging the data according to a communication protocol between the singlechip and the core processing unit;
step 4: the core processing unit performs data analysis and verification on the data: the core processing unit receives all data, performs byte verification on the head, the tail and the like of the data according to a protocol, and aims to remove invalid data and ensure the accuracy of the data;
step 5: SPAT message group package: according to SPAT requirements in the T/TS0117-2020 protocol, performing JSON format packet grouping on SPAT data;
step 6: INFO message group package: according to the requirement on INFO in the T/TS0117-2020 protocol, the INFO data is packaged in a JSON format, wherein LAT, LON, DEV _ID and other necessary filling information is configured and read through a file IO;
step 7: and establishing a core processing unit information reporting link: according to the T/TS0117-2020 protocol, a communication link is established with the cloud platform by adopting an MQTT communication mode, wherein data such as communication IP, port, username, password are configured and read through a file IO;
step 8: the core processing unit periodically reports the data to the Internet of vehicles application service platform or the intelligent network vehicle: according to the T/TS0117-2020 protocol, SPAT data and INFO data are reported to the cloud platform through 5G at a specified frequency, can be reported to the cloud platform through TCP/IP transmission protocol, and can be communicated with surrounding intelligent network vehicles in a two-way through V2X;
step 9: the cloud platform sends data downwards: the cloud platform can send data to the traffic light learning machine, the traffic light learning machine comprises equipment with an RS485 or RS232 communication protocol and a sensor, the communication mode is TCP/IP transmission protocol or 5G, the cloud platform can also send a positioning instruction, the core processing unit can read the positioning information of the GPNSS module through the AT instruction and feed back the positioning information to the cloud platform in a wired or wireless mode, after the WIFI function is started, other equipment can be connected with the learning machine to carry out two-way communication through a standard WIFI protocol, and therefore wireless communication within a certain distance is achieved.
Further, the traffic light learning system software also comprises the following functions:
the system log module of the signal machine network system is written, the log module records the signal machine state, the learning machine state and the equipment operation condition, and provides a downloading function, the running state of the network system can be checked by depending on a remote system, and the simple equipment operation and maintenance can be performed.
The remote control interface of the network system equipment end is written, equipment is remotely opened, equipment is closed, equipment states are read, WIFI is opened or closed, network operation states, equipment is remotely updated, factory settings are restored and the like.
The network system equipment management module is written to encode the on-site installed equipment, and comprises equipment ID, equipment model number, sim card number, operators, installation positions, namely longitude and latitude, remark information and the like, and encodes the on-site installed equipment according to a unified data format. After the equipment is installed on site, the equipment detailed information is input into the terminal management cloud platform of the Internet of things.
And carrying out network configuration on the signaler network system, establishing a VPN channel, and using the FRP technology to allocate addresses so that the system and the terminal management cloud platform of the Internet of things establish a link. Or data transmission is performed in a TCP/IP transmission protocol.
As shown in fig. 3, the digital twin platform is divided into: the system comprises an information acquisition layer, an information interaction layer, a cooperative processing layer, a functional service layer and a business butt joint layer. The digital twin platform has the capability of digital three-dimensional stereoscopic presentation of map information, annunciator state information, calibration position information and the like of intersections in a project planning range. The platform has the capability of providing accurate time synchronization services for various devices. The platform has unified access, management and distribution capability of equipment, can carry out link management, data analysis and management on the traffic light learning machine with the networking function, can carry out equipment state acquisition and management on the traffic light learning machine with the signaling machine and the networking function, and can upload the period and phase providing API interface of the signaling machine to an upper service platform to support the application of the Internet of vehicles. The whole framework is divided into five layers, namely an information acquisition layer, an information interaction layer, a cooperative processing layer, a functional service layer and a business butt joint layer, each layer of framework corresponds to supporting hardware and business functions respectively, and finally an upper layer platform is supported to realize vehicle networking applications such as traffic light information broadcasting, green wave speed guiding, red light running early warning and the like.
The signal acquisition layer is used for simulating and acquiring the phase, countdown information, equipment state, basic information and traffic light fault information of a lamp group of the signal machine through a traffic light learning machine with a networking function. And can change in the signal control cycle and can realize intelligent learning and rapidly output changed results. Firstly, the interface development is carried out through the SDK or the interface protocol of the signal machine, and the current configuration scheme, signal period and real-time signal phase state of the signal machine are received. Analyzing the received data information; secondly, updating the state of the annunciator equipment by analyzing the annunciator data, including whether the online and the phase accord with the scheme or not, and updating the state information of the annunciator equipment; then recording fault information of the equipment, reporting the fault to the platform in time, and configuring modes such as mailbox sending, short message sending and the like to inform a system administrator; and finally, all the data content group packages are sent and reported to the platform.
The signal interaction layer also uploads the acquired signal states to the platform through various network channels of the traffic light learning machine with the networking function, and the platform also needs to perform data verification on the received data and read the equipment state information, so that the data reliability is further improved.
The cooperative processing layer belongs to a middle platform capability part of the digital twin platform, and is respectively digital space-time bottom capability and data middle platform capability. The digital space-time base is based on a high-precision map and accurate time synchronization, so that the whole system is ensured to be in a unified space reference, and each business scene is supported. The data center station is connected with the devices such as the signaler, the traffic light learning machine with the internet connection function and the like, and through unified access authentication and protocol adaptation, the simultaneous access capability and the high concurrent data processing capability of the devices are greatly improved, and accurate and efficient data distribution can be provided for a service platform. The digital space-time base is formed by using a high-precision map to establish a space reference system of the intersection as a space reference, realizing the calibration of an intersection time line as a time reference through the time service of GNSS, and forming the intersection digital space-time base consistent with the real intersection space and time reference system based on a space-time synchronization technology. The digital base provides high-precision map service, high-precision time synchronization service, three-dimensional scene construction based on a high-precision map and the like. And then the edge data base provides a unified data standard for data aggregation, distribution and circulation, and provides data support for digital management and control and digital twinning of static and dynamic elements. Through the construction of the edge data base, various information data of the road are subjected to virtualization processing, mapping from the real physical world to the digital twin virtual world is realized through various data interactions based on the space-time reference of the space-time base, and digital support of the networking application scene is realized on the basis.
The functional service layer belongs to a platform layer, the platform layer adopts a digital twin technology to reconstruct road and infrastructure equipment, the convenience in equipment management is greatly improved, three-dimensional full scene presentation and accurate single-point presentation can be realized, real-time traffic state information is presented, and a richer window is provided for vehicle-road cooperative application expansion. Meanwhile, the platform performs tabulated detailed management on the equipment, and provides viewing, configuration, modification and other capabilities for the equipment accessed to the platform.
The service docking layer reserves the possibility of platform services to an upper service platform and meets the integration requirements of owners. Therefore, the traffic state information reaches an upper service platform, and the vehicle networking application such as traffic light information broadcasting, green wave speed guiding, red light running early warning and the like is supported.
As shown in fig. 4, the whole system uses GNSS time service as a time source, and establishes a time reference for all hardware devices and servers. Through the establishment of the time reference, fusion matching of the multi-source perception data is realized, and the range and the reliability of the perception detection system are prompted. And the time synchronization of the data acquisition device is carried out through time service, so that the unified time of information acquisition of each system is ensured.
The above embodiments are merely illustrative of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention, and various modifications and improvements made by those skilled in the art to the technical solutions of the present invention should fall within the protection scope defined by the claims of the present invention without departing from the design spirit of the present invention.
Claims (7)
1. Traffic light learning system based on networking function, its characterized in that: the intelligent service system comprises comprehensive service base station hardware, traffic light learning machine software and a digital twin platform which are connected in an interactive way, wherein a power supply circuit, a core processing unit, a singlechip, a 5G antenna, a C-V2X antenna, a GNSS antenna, a WIFI antenna, an RS485 interface, an RS232 interface and a network port RJ45 interface are arranged on a comprehensive service base station hardware body; the traffic light learning machine software is provided with an RS485 communication module, an RS232 communication module, a 5G & C-V2 communication module, a singlechip module and an Ethernet module; the digital twin platform is divided into: the system comprises an information acquisition layer, an information interaction layer, a cooperative processing layer, a functional service layer and a business butt joint layer.
2. The traffic light learning system based on networking function of claim 1, wherein:
and a power supply circuit: an external DC12V power supply, which provides 5V/3.8V/3.3V/1.8V/1.5V voltage for other hardware through power management;
and the singlechip is used for: collecting and forwarding traffic light signal time and state;
the core processing unit: optimizing time and state data forwarded by the singlechip, managing communication modes among all communication interfaces, recording and transmitting time and state of a traffic light to a core processing unit through the singlechip, optimizing data by the core processing unit, and finally transmitting the data to an intelligent network bus and a cloud platform in a wired or wireless communication mode;
5G antenna: the equipment is in wireless communication with the 5G base station, and the 5G antenna realizes a long-distance large-range wireless communication network;
V2X antenna: the wireless communication mode of the Internet of vehicles adopts a C-V2X technology, which is the combination of direct communication and cellular network communication, and a C-V2X antenna is used for realizing a short-distance wireless communication network;
C-GNSS antenna: positioning equipment is arranged at a position, GNSS functions are time service and positioning, high-precision positioning is provided, all equipment is synchronized in time, and time delay precision of data transmission is guaranteed;
WIFI antenna: the wireless communication between the short-distance equipment and the equipment is carried out, the WIFI communication supports the short-distance wireless communication, and the WIFI communication is connected with a plurality of equipment or mobile phones for data bidirectional transmission;
RS485 interface: the RS485 interface is communicated with a device or a sensor of a support 485 interface, and the RS485 interface is in wired long-distance reliable communication with an external support 485 transmission protocol sensor;
RS232 interface: the standard 232 serial port protocol is communicated with equipment or a sensor supporting 232 serial ports, so that wired short-distance communication between the equipment and the equipment or between the equipment and the sensor is realized;
network port RJ45 interface: the gigabit wired network interface RJ45 is connected with other devices or optical cats by a network cable mode for wired communication, and comprises: and the WAN port and the four LAN ports are connected with an external network for wide area network communication and an internal network for local area network communication.
3. The traffic light learning system based on the internet connection function according to claim 2, wherein: the network interface, the RS485 interface, the RS232 interface, the 5G and the WIFI can be communicated in pairs or can be independently used.
4. The traffic light learning system based on the internet connection function as claimed in claim 1, wherein the traffic light learning machine software working process comprises the following steps:
step 1, self-learning of a singlechip module: judging the state of the traffic light according to the change condition of the control signal of the traffic light, and simultaneously judging the countdown time of the traffic light by periodically learning the change frequency so as to realize the self-learning of the state of the traffic light and the countdown information;
step 2, receiving RS485 and RS232 data by the singlechip: the baud rate is 115200bps, and the communication is carried out with an external sensor or equipment, and the data content is obtained;
step 3, the singlechip performs verification on the data and then sends the data in a group package: and verifying all the acquired data, and finally packaging and packaging the data according to a communication protocol between the singlechip and the core processing unit.
Step 4, the core processing unit analyzes and verifies the data: the core processing unit receives all data and performs byte performance verification on the head and the tail of the data according to a protocol;
step 5, SPAT message group package: according to SPAT requirements in the T/TS0117-2020 protocol, performing JSON format packet grouping on SPAT data;
step 6.Info message group package: according to the requirement on INFO in the T/TS0117-2020 protocol, the INFO data is packaged in a JSON format, wherein LAT, LON, DEV _ID necessary filling information is configured and read through a file IO;
step 7, establishing a core processing unit information reporting link: according to the T/TS0117-2020 protocol, a communication link is established with the cloud platform by adopting an MQTT communication mode, wherein communication IP, port, username, password data is configured and read through a file IO;
step 8, the core processing unit periodically reports the data to the Internet of vehicles application service platform or the intelligent network vehicle: according to the T/TS0117-2020 protocol, SPAT data and INFO data are reported to the cloud platform through 5G at a specified frequency, can be reported to the cloud platform through TCP/IP transmission protocol, and can be communicated with surrounding intelligent network vehicles in a two-way through V2X;
step 9, the cloud platform transmits data downwards: data is sent to a traffic light learning machine through a cloud platform, wherein the data comprises equipment with an RS485 or RS232 communication protocol and a sensor, and the communication mode is TCP/IP transmission protocol or 5G; the cloud platform is used for sending a positioning instruction, the core processing unit is used for reading positioning information of the GPNSS module through the AT instruction and feeding back the positioning information to the cloud platform in a wired or wireless mode, after the WIFI function is started, other equipment is connected with the learning machine through a standard WIFI protocol to carry out two-way communication, and therefore wireless communication within a certain distance is achieved.
5. The traffic light learning system based on the internet connection function according to claim 4, wherein: the traffic light learning machine software also comprises the following functions:
the system log module of the signal machine network system is written, the log module records the signal machine state, the learning machine state and the equipment operation condition, and provides a downloading function, and the operation state of the network system is checked by a remote system to perform simple equipment operation and maintenance;
writing a remote control interface of a network system equipment end, remotely starting equipment, closing the equipment, reading the equipment state, starting or closing WIFI, and remotely upgrading the network operation state and the equipment to restore factory settings;
the network system equipment management module is written, codes on-site installed equipment and comprises equipment ID, equipment model, sim card number, operators, installation positions, namely longitude and latitude, remark information, codes according to a unified data format, and inputs equipment detailed information into the terminal management cloud platform of the Internet of things after on-site installation;
and carrying out network configuration on the signal machine network system, establishing a VPN channel, using the FRP technology to allocate addresses, so that the system and the terminal management cloud platform of the Internet of things are linked, or carrying out data transmission by using a TCP/IP transmission protocol.
6. The traffic light learning system based on the internet connection function according to claim 1, wherein: the digital twin platform has map information of intersections in a project planning range, state information of annunciators and digitalized three-dimensional presenting capability of calibration position information, the platform has the capability of providing accurate time synchronization service for various devices, the platform has the capability of uniformly accessing, managing and distributing the devices, carries out link management, data analysis and management on a traffic light learning machine with a networking function, carries out device state acquisition and management on the annunciators and the traffic light learning machine with the networking function, uploads the period and phase providing API interfaces of the annunciators to an upper service platform to support the Internet of vehicles application, and the whole framework is divided into five layers, wherein each layer of framework corresponds to supporting hardware and service functions respectively, and finally supports the upper platform to realize traffic light information broadcasting, green wave speed guiding and red light running early warning Internet of vehicles application;
the signal acquisition layer is used for simulating and acquiring the phase, countdown information, equipment state, basic information and traffic light fault information of the lamp group of the annunciator in a non-contact manner, realizing intelligent learning in the signal control period and rapidly outputting changed results; firstly, performing docking development through an SDK or interface protocol of a signal machine, and receiving a current configuration scheme, a signal period and a real-time signal phase state of the signal machine; analyzing the received data information; secondly, updating the state of the annunciator equipment by analyzing the annunciator data, including whether the online and the phase accord with the scheme or not, and updating the state information of the annunciator equipment; then recording fault information of the equipment, reporting the fault to a platform in time, and configuring a mailbox and a short message sending mode to inform a system administrator; finally, all data content packets are sent and reported to the platform;
the signal interaction layer uploads the acquired signal state to a platform through various network channels, and the platform performs data verification on the received data and reads equipment state information;
the collaborative processing layer belongs to a middle platform capacity part of the digital twin platform, and is respectively digital space-time bottom capacity and data middle platform capacity, and the digital space-time base is based on a high-precision map and accurate time synchronization, so that the whole system is ensured to be in a uniform space reference, and all business scenes are supported; the data center station is connected with a signaler and traffic light learning machine equipment with a networking function, and provides accurate and efficient data distribution for a service platform through unified access authentication and protocol adaptation; the digital space-time base is formed by using a high-precision map to establish a space reference system of the intersection as a space reference, realizing the calibration of an intersection time line as a time reference through the time service of GNSS, and forming the intersection digital space-time base consistent with the real intersection space and time reference system based on a space-time synchronization technology; the digital base provides high-precision map service, high-precision time synchronization service and three-dimensional scene construction service based on a high-precision map, then the edge data base provides unified data standard for data convergence, distribution and circulation, digital support is provided for digital twinning of digital control and static and dynamic elements, various information data of a road are virtualized through construction of the edge data base, mapping from a real physical world to a digital twinning virtual world is realized through various data interaction based on space-time reference of the space-time base, and digital support of a networking application scene is realized on the basis;
the functional service layer belongs to a platform layer, the platform layer adopts a digital twin technology to reconstruct road and infrastructure equipment and present real-time traffic state information, and meanwhile, the platform performs tabulated detailed management on the equipment to provide viewing, configuration and modification capabilities for the equipment accessed to the platform;
the service butt-joint layer reserves the possibility of platform service to an upper service platform, the traffic state information reaches the upper service platform, and the traffic light information broadcasting, the green wave speed guiding and the red light running early warning vehicle networking application are supported.
7. The traffic light learning system based on networking function of claim 1, wherein: the whole system adopts GNSS time service as a time source, and establishes time references of all hardware devices and servers.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116824895A (en) * | 2023-08-29 | 2023-09-29 | 成都通广网联科技有限公司 | Network connection system and method for controlling automatic driving vehicle to enter intersection waiting area |
| CN117079467A (en) * | 2023-10-12 | 2023-11-17 | 成都通广网联科技有限公司 | Method and system for relieving road congestion based on perception fusion technology |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116824895A (en) * | 2023-08-29 | 2023-09-29 | 成都通广网联科技有限公司 | Network connection system and method for controlling automatic driving vehicle to enter intersection waiting area |
| CN117079467A (en) * | 2023-10-12 | 2023-11-17 | 成都通广网联科技有限公司 | Method and system for relieving road congestion based on perception fusion technology |
| CN117079467B (en) * | 2023-10-12 | 2024-01-02 | 成都通广网联科技有限公司 | Method and system for relieving road congestion based on perception fusion technology |
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