Highway operation and service intelligent system

Abstract

The invention provides a highway operation and service intelligent system, which comprises a road section platform, an area platform and a road network platform, and is characterized in that the road section platform is used for collecting and summarizing various sensing data of a corresponding highway section based on an ETC system to obtain system business data; road network situation historical statistics, road network situation real-time monitoring and road network situation future prediction are carried out according to the ETC data of the corresponding expressway section and the adjacent expressway road network; and long and short time traffic flow prediction, congestion prediction, holiday and festival traffic flow prediction and traffic flow prediction in a severe weather scene aiming at the corresponding expressway section are realized from multiple angles. According to the invention, the emergency disposal response speed and the intelligent degree of expressway operation and service can be improved, the timeliness rate, the accuracy rate and the correct rate of detection of various traffic and meteorological events can be improved, and the requirements of cooperative monitoring and linkage emergency disposal of low-time-delay traffic safety events are met.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of expressways, and in particular to an expressway operation and service intelligent system. BACKGROUND

[0002] With the rapid development of economy, the number of motor vehicles is increasing year by year, the traffic volume of expressways is continuously increasing, and traffic congestion is very common, which leads to a high incidence of traffic accidents. The increasingly complex highway operation conditions put more and more stringent requirements on the safe operation and management of expressways. At the same time, the road closure caused by bad weather not only affects the traffic efficiency of the expressway and causes toll loss, but also has slow emergency response and few safety warning channels for vehicles in the network.

[0003] At present, although new technologies are beginning to emerge in the field of expressways, the combination of new technologies and traditional operation and service business is not enough, resulting in a large number of technology stacking phenomena. Compared with technology investment, the value of technology empowerment to business is insufficient. The existing various systems have high dependence on manual judgment, lack of intelligent traction based on knowledge decision-making, and have not achieved comprehensive intelligent upgrading. As a result, there is a lack of linkage mechanism between provinces, the disposition and information warning capabilities are insufficient, it is difficult to meet the requirements of the service level of expressways, and it is difficult to meet the demand for low-latency traffic safety event collaborative monitoring and linkage emergency disposal. SUMMARY

[0004] In view of this, the embodiments of the present application provide an expressway operation and service intelligent system to eliminate or improve one or more defects in the prior art.

[0005] One aspect of the present application provides an expressway operation and service intelligent system, comprising: a road section platform, configured to collect and aggregate various types of sensing data of an expressway road section corresponding to the road section platform based on an ETC system to obtain system business data, and perform safety event identification, road section hazard early warning, road section operation analysis, and extraction of traffic information and event information based on an edge computing manner on the system business data, and upload the traffic information and event information to a regional platform to which the road section platform belongs, and publish travel information, safety warning information, traffic guidance information, and vehicle-road cooperation information in the expressway road section; wherein the road section platform is further configured to perform road network situation history statistics, road network situation real-time monitoring, and road network situation future prediction based on ETC data of the expressway road section corresponding to the road section platform and adjacent expressway road networks, to realize long and short traffic flow prediction, congestion prediction, holiday traffic flow prediction, and traffic flow prediction under bad weather scenarios for the expressway road section corresponding to the road section platform from multiple angles; The regional platform is configured to aggregate traffic information and event information of each road section platform corresponding to the regional platform based on a pre-constructed provincial data resource pool, to obtain corresponding regional aggregated data, and to upload the regional aggregated data to a road network platform to which the regional platform belongs, and to perform provincial road network operation state prediction, road network hidden danger early warning, cross-road section information publishing, and cross-provincial information sharing based on the road network platform according to the traffic information and the event information. The road network platform is configured to aggregate regional aggregated data uploaded by each regional platform in the expressway network based on a pre-constructed network data resource pool, to store the data based on a block chain for data sharing between the regional platforms, and to evaluate operation service quality of each regional platform and each road section platform according to a pre-constructed intelligent level index system.

[0006] In some embodiments of the present application, the road section platform includes a road section platform business system, a model center, a data center, a cloud control center, a fusion communication layer, and an infrastructure layer. The regional platform includes a regional platform business system, a model center, a data center, a cloud control center, and a fusion communication layer. The infrastructure layer includes an edge computing module and a roadside device module. The edge computing module is configured to aggregate various types of sensing data of the expressway road section collected by the infrastructure layer to obtain system business data, and to perform security event identification, road section hidden danger early warning, road section operation analysis, and traffic information and event information extraction on the system business data based on an edge computing method. The roadside device module is configured to collect vehicle operation data of the expressway road section based on an ETC system, a video collection device, and a radar, to collect weather environment data of the expressway road section based on a grating sensor, and to publish travel information, safety warning information, traffic guidance information, and vehicle-road cooperation information in the expressway road section based on an on-board unit (OBU). The data center is configured to store structured data and monitoring video data collected by the infrastructure layer based on a data resource pool. The model center is configured to store an algorithm library and a business model library, and the algorithm library stores mathematical models of data mining, algorithms, visual AI algorithms, machine learning algorithms, event identification algorithms, operation trend analysis algorithms, meteorological analysis algorithms, and digital twin algorithms. The cloud control center in the road section platform is configured to connect the road section platform business system, the model center, and the data center, and to connect the road section platform and the regional platform, and the cloud control center in the regional platform is configured to connect the regional platform business system, the model center, and the data center, and to connect the regional platform and the road network platform. The fusion communication layer is configured to receive data of the infrastructure layer and transmit data of the fusion communication layer to the cloud control center.

[0007] In some embodiments of the present application, the roadside device module comprises a video monitoring unit, an ETC vehicle feature recognition unit, a traffic parameter perception unit, a traffic event perception unit, a traffic environment perception unit, an infrastructure health monitoring unit, and a key area monitoring unit, which are connected to the cloud control center based on the fusion communication layer respectively. The video monitoring unit is configured to collect vehicle operation data in the highway section based on a video monitoring system of the highway section, a UAV video monitoring device, and a vehicle-mounted mobile video monitoring device. The ETC vehicle feature recognition unit is configured to identify vehicle features of vehicles in the highway section based on a license plate recognition device of an ETC gantry. The traffic parameter perception unit is configured to collect traffic parameters of the highway section based on a traffic control station. The traffic event perception unit is configured to monitor traffic events of the highway section based on a video monitoring system and a millimeter wave radar of the highway section. The traffic environment perception unit is configured to collect weather environment data of the highway section. The infrastructure health monitoring unit is configured to monitor the health of bridges, tunnels, and high slopes in the highway section. The key area monitoring unit is configured to monitor traffic events of preset key areas of the highway section based on an ETC gantry system.

[0008] In some embodiments of the present application, the key areas include tunnels with a length exceeding a preset length threshold, sections with traffic flow exceeding a preset flow threshold, predetermined accident-prone sections, predetermined severe weather-prone sections, service area dangerous goods monitoring and early warning areas, and toll stations.

[0009] In some embodiments of the present application, the section platform business system comprises an all-weather passing system, a digital management and control system, and a public travel service system. The all-weather passing system comprises a meteorological automatic monitoring and early warning module. Correspondingly, the traffic environment perception unit comprises a grating sensor, a meteorological detector, a visibility detector, and a road surface state detector corresponding to the meteorological automatic monitoring and early warning module respectively. The model is used for road traffic meteorological early warning detection on weather environment data collected by the grating sensor, the meteorological detector, the visibility detector and the road surface state detector based on at least one of preset visual AI algorithm, machine learning algorithm, event recognition algorithm and meteorological analysis algorithm; The cloud control center is used for generating meteorological early warning prediction information for the expressway section according to a corresponding detection result of the road traffic meteorological early warning detection, and sending the meteorological early warning prediction information to an on-board unit OBU in a vehicle in the expressway section based on the fusion communication layer, so as to publish the meteorological early warning prediction information in the expressway section based on the on-board unit OBU.

[0010] In some embodiments of the present application, the quasi-all-weather passing system further comprises a driving safety guiding module; Correspondingly, the road-side equipment module further comprises a driving safety guiding device corresponding to the driving safety guiding module; The driving safety guiding device comprises a node control host and an intelligent guiding lamp connected to the node control host; The node control host is used for controlling the intelligent guiding lamp to display light in different colors and / or flashing modes according to the received different mode functions, wherein the mode functions include standby state, road contour strengthening mode function, driving active guiding mode function and anti-collision warning mode function.

[0011] In some embodiments of the present application, the quasi-all-weather passing system further comprises an intelligent ice-melting and snow-removing module; Correspondingly, the road-side equipment module further comprises a road surface information acquisition subsystem, a spraying subsystem and a sub-control system corresponding to the intelligent ice-melting and snow-removing module, wherein the sub-control system and the cloud control center jointly constitute a processing control subsystem corresponding to the intelligent ice-melting and snow-removing module; The road surface information acquisition subsystem is used for acquiring road surface state information and temperature information of the expressway section; The spraying subsystem is used for performing proportioning and spraying of a spraying agent on the expressway section according to an instruction of the processing control subsystem.

[0012] In some embodiments of the present application, the digital management and control system comprises a lane-level active management and control system, a split-flow zone safety early warning system and a key operating vehicle management and control system; The lane-level active management and control system is used for automatically adjusting lane management and control measures based on a preset traffic control strategy and controlling change of image display of a variable information sign according to collected expressway traffic flow, traffic event and meteorological environment information; The split-flow area safety early warning system is used to generate safety early warning information for the cases of unstable vehicle speed, non-ideal sight, ramp congestion, continuous lane changing of vehicles, vehicle parking in the flow guide area, vehicle forcibly changing lane when passing through the lane changing area, vehicle reversing when passing through the split-flow port, vehicle emergency braking, and temporary parking for passenger drop-off at the split-flow area and the merging area of the expressway section, and the safety early warning information is issued based on the integrated safety reminding device of the split-flow area and the merging area. The key operating vehicle management and control system is used to dynamically monitor the pre-determined key operating vehicles in real time to obtain the vehicle information, running track, and historical driving route range, time period, and number of the key operating vehicles running on the expressway section, and to determine whether the key operating vehicle travels according to the specified route. If not, the corresponding abnormal state alarm information is generated to issue the abnormal state alarm information based on the on-board unit (OBU) in the key operating vehicle.

[0013] In some embodiments of the present application, the public travel service system includes a roadside device information issuing system, an ETC-based vehicle-road cooperation service system, an internet information issuing system, and a smart scene service system. The roadside device information issuing system is used to issue the information issued by the cloud control center. The ETC-based vehicle-road cooperation service system is used to issue the information issued by the cloud control center based on the ETC gate and the on-board unit (OBU). The internet information issuing system is used to send the information issued by the cloud control center to the internet device that passes the authentication and authorization based on the unified external interface. The smart scene service system is used to control the information issuing device of the service area to issue the information issued by the cloud control center.

[0014] In some embodiments of the present application, the smart scene service system includes a service area video monitoring system, a passenger flow analysis system, a parking guidance system, a service area information issuing and querying system, a broadcast system, a WIFI system, and a smart toilet.

[0015] The expressway operation and service intelligent system provided by the application comprises a road section platform, which is used for collecting and summarizing various types of sensing data of the expressway road section corresponding to the road section platform based on an ETC system to obtain system business data, performing safety event identification, road section hidden danger early warning, road section operation analysis, and traffic information and event information extraction on the system business data based on an edge computing mode, uploading the traffic information and event information to a regional platform to which the road section platform belongs, and publishing travel information, safety warning information, traffic guidance information, and vehicle-road cooperation information in the expressway road section; wherein the road section platform is further used for performing road network situation history statistics, road network situation real-time monitoring, and road network situation future prediction based on ETC data of the expressway road section corresponding to the road section platform and adjacent expressway road networks, so as to realize long and short traffic flow prediction, congestion prediction, holiday traffic flow prediction, and traffic flow prediction in a severe weather scenario for the expressway road section corresponding to the road section platform from multiple angles; a regional platform is used for summarizing traffic information and event information of each road section platform corresponding to the regional platform based on a pre-constructed provincial data resource pool to obtain corresponding regional summary data, uploading the regional summary data to a road network platform to which the regional platform belongs, and performing provincial road network operation state prediction, road network hidden danger early warning, cross-road section information publishing, and cross-provincial information sharing based on the road network platform for a region corresponding to the regional platform; and a road network platform is used for summarizing regional summary data uploaded by each regional platform in an expressway road network based on a pre-constructed whole-network data resource pool, performing data storage based on a block chain to realize data sharing between the regional platforms, and performing operation service quality evaluation for each regional platform and each road section platform based on a pre-constructed intelligent level price index system. The expressway operation and service intelligent system can improve the emergency disposal response speed and the intelligent degree of expressway operation and service, can improve the timeliness, accuracy, and correctness of various traffic and weather event detection, and can meet the low-latency traffic safety event cooperative monitoring and joint emergency disposal demand. On the basis of guaranteeing user convenience and safety travel, the intelligent operation and management capability is continuously improved, the cost is reduced and the income is increased for the expressway management and operation unit, and the healthy and sustainable development of the intelligent expressway system is promoted.

[0016] Additional advantages, objects, and features of the application will be set forth in part by the description that follows, and will become apparent to those skilled in the art upon examination of the following figures and detailed description thereof or can be learned by practice of the application. The objects and other advantages of the application can be realized and attained by the structure particularly pointed out in the specification and drawings.

[0017] It will be understood by those skilled in the art that the objects and advantages of the present application can not be limited to the above specifically described, and the above and other objects that can be achieved by the present application will be more clearly understood according to the following detailed description. Attached Figure Description

[0018] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, do not constitute a limitation thereof. The components in the drawings are not drawn to scale but are merely for illustrating the principles of this application. For ease of illustration and description of certain parts of this application, corresponding portions in the drawings may be enlarged, i.e., may appear larger relative to other components in an exemplary system actually manufactured according to this application. In the drawings: Figure 1 This is a schematic diagram of the structure of an intelligent highway operation and service system according to one embodiment of this application.

[0019] Figure 2 This is a schematic diagram illustrating the specific objectives and functional architecture of an intelligent highway operation and service system according to one embodiment of this application.

[0020] Figure 3 This is an example diagram illustrating the architecture of an intelligent highway operation and service system according to one embodiment of this application.

[0021] Figure 4 This is a schematic diagram of a vehicle-road cooperative service based on ETC in one embodiment of this application. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the embodiments and accompanying drawings. Here, the illustrative embodiments and their descriptions are used to explain this application, but are not intended to limit it.

[0023] It should also be noted that, in order to avoid obscuring this application with unnecessary details, only the structures and / or processing steps closely related to the solution according to this application are shown in the accompanying drawings, while other details that are not closely related to this application are omitted.

[0024] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, element, step, or component, but does not exclude the presence or addition of one or more other features, elements, steps, or components.

[0025] It should also be noted that, unless otherwise specified, the term "connection" in this article can refer not only to a direct connection, but also to an indirect connection involving an intermediary.

[0026] In the following description, embodiments of the present application will be illustrated with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar parts, or the same or similar steps.

[0027] The current methods of highway operation and service management have the following main problems: (1) Emergency response is slow: With the rapid economic development, the number of motor vehicles is increasing year by year, and the traffic volume of expressways is continuously growing. Traffic congestion is very common, leading to a high incidence of traffic accidents. The increasingly complex highway operating conditions have put increasingly strict requirements on the safe operation and management of expressways. At the same time, road closures caused by bad weather not only affect the efficiency of expressway traffic and cause toll losses, but also slow down emergency response and provide few safety warnings for vehicles on the network. Currently, the reporting of blockages and incidents is still the main method, and the safety warning methods for vehicles are relatively simple, mainly relying on variable message signs, information prompts from third-party internet companies, and traffic radio, etc. The timeliness, accuracy, convenience, and effectiveness of expressway incident information user reach need to be improved. It has failed to truly meet the public's requirements for safe, smooth, and efficient travel and services.

[0028] (2) Low degree of intelligence: New technologies such as vehicle-road cooperation, big data, artificial intelligence, the Internet of Things, cloud computing, and connected vehicles have begun to emerge in the field of expressways. However, the combination of new technologies and traditional operations and services is not sufficient, resulting in a large number of technical stacking phenomena. Compared to technology investment, the value of technology empowerment for business is insufficient. The existing various systems rely heavily on human judgment and lack intelligent traction based on knowledge-based decision-making. At the same time, there are many complex information systems, and data is scattered and fragmented. There is a lack of integrated management system, making it difficult to effectively support cross-domain collaborative operation and service. The overall level of the industry has limited improvement, and comprehensive intelligent upgrading has not been achieved.

[0029] (3) Difficulty in connecting road segments: In recent years, various regions have been exploring and trying to build smart expressways. A number of smart expressway pilot sections have been built and completed. However, each of the existing smart expressway pilot sections operates independently and cannot form a network or provide integrated services, limiting the interconnection of the entire network of smart expressways and making it difficult to improve the consistency of user experience for smart expressway services.

[0030] (4) High construction and operation and maintenance costs: After years of concentrated construction, expressways have moderately exceeded economic and social development. Due to the use of a large number of new technologies and advanced equipment, the construction cost of smart expressways has been at a high level. At the same time, the overall operation and service effectiveness of smart expressways depends on the good operation and maintenance of a large number of front-end equipment and systems. The current operation and maintenance cost of smart expressways is generally high, and the operating units spend a lot, which is not conducive to their sustainable development.

[0031] In other words, the existing highway operation and service management methods have relatively independent operations such as operation monitoring, command and dispatch, toll collection services, and travel services, with a lack of information sharing and coordination mechanisms between these operations. Some provinces have formed joint operation mechanisms, which have become an important support for smooth road network operation, but there is a lack of coordination mechanisms between provinces. The ability to conduct pre-disposal analysis and information early warning is insufficient, making it difficult to meet the service level requirements of a "single network" of highways and to cope with the needs of collaborative monitoring and joint emergency response for low-latency traffic safety incidents.

[0032] Based on this, the embodiments of this application integrate and connect the three major electromechanical systems of the existing highways—toll collection, monitoring, and communication—and integrate data resources from related systems such as emergency rescue, maintenance management, and road administration, significantly improving the intelligence and digitalization level of the highway operation service system. It promotes the convergence, sharing, and intelligent application of transportation data resources, drives the industry application of technologies such as big data, artificial intelligence, blockchain, BeiDou, 5G, and vehicle-road cooperation, improves standards and specifications to achieve a standardized information service platform, and constructs a comprehensive network and information security prevention system. It enhances the timeliness, accuracy, and correctness of various traffic and meteorological event detection, enriches information delivery methods, and fully utilizes systems such as ETC gantry systems, on-board units (OBUs), and variable message signs to send event reminders to vehicle users, guiding users to drive safely. It initially realizes vehicle-road cooperation based on ETC, striving to significantly improve the safety and efficiency of highway traffic in the short term and enhance the service guarantee capability for "all-weather" traffic. While ensuring convenient and safe travel for users, it continuously improves intelligent operation and management capabilities, promotes cost reduction and revenue increase for highway operation and management units, and promotes the healthy and sustainable development of the intelligent highway system.

[0033] The specific examples below will illustrate this.

[0034] This application provides an intelligent highway operation and service system that can be implemented by an intelligent highway operation and service system. See [link to relevant documentation]. Figure 1 The intelligent highway operation and service system specifically includes the following components: Road segment platform 1 is used to collect and aggregate various sensor data from its corresponding highway segment based on the ETC system to obtain system business data. It then uses edge computing to perform security event identification, road segment hazard warning, road segment operation analysis, and extraction of traffic and event information from this system business data. The platform uploads the traffic and event information to its own regional platform and publishes travel information, safety warning information, traffic guidance information, and vehicle-road cooperative information within the highway segment. Furthermore, the road segment platform is used to perform historical statistics of the road network situation, real-time monitoring of the road network situation, and analysis of future road network situation based on the ETC data of its corresponding highway segment and adjacent highway networks. The system aims to predict traffic flow, including short- and long-term traffic flow forecasts, congestion forecasts, holiday traffic flow forecasts, and traffic flow forecasts under adverse weather conditions, from multiple perspectives. Specifically, at the cognitive level, the platform is primarily responsible for the aggregation and fusion of sensor data. Through the perception system equipment and information dissemination system equipment of the highway sections within its jurisdiction, it aggregates existing system business data to complete edge perception for safety event identification, road section hazard warnings, road section operation analysis, and traffic information extraction. At the decision-making level, it is primarily responsible for cross-road section collaboration, emergency command and dispatch within road sections, and incident hazard assessment. At the dissemination level, it is primarily responsible for disseminating travel information, safety warnings, traffic guidance, and vehicle-road cooperative information within the road sections.

[0035] Regional Platform 2 is used to aggregate traffic and event information from various road segment platforms based on a pre-built provincial data resource pool to obtain corresponding regional aggregated data. This regional aggregated data is then uploaded to its own road network platform. Based on the traffic and event information, the platform performs provincial road network operation status prediction, road network hazard warning, cross-road segment information dissemination, and cross-provincial information sharing based on the road network platform. At the cognitive level, the regional platform is primarily responsible for data governance, including road network hazard warning and provincial road network operation analysis. At the decision-making level, it provides cross-road segment collaborative organization and emergency command and dispatch functions, and cooperates with the road network platform to achieve cross-provincial collaboration. At the dissemination level, it provides cross-road segment collaborative guidance and cross-road segment information dissemination functions. Based on the provincial data resource pool, the regional platform aggregates traffic and event information from various road segment platforms, improving data processing, data aggregation, data analysis, and command and control capabilities, and strengthening traffic situation integration analysis, traffic control, cross-road segment information distribution, and emergency command and dispatch capabilities and methods.

[0036] The road network platform 3 is used to aggregate regional summary data uploaded by various regional platforms in the entire highway network based on a pre-built network-wide data resource pool, and to store the data using blockchain for data sharing among the various regional platforms. It also evaluates the operational service quality of each regional platform and each road segment platform according to a pre-built intelligent level price index system. Specifically, the road network platform is also used for predicting traffic safety hazards across the entire highway network, coordinating cross-regional operational operations, and emergency command and dispatch of safety incidents. Based on traffic incident information reported by the regional platforms, it generates intelligent highway service strategy information for vehicles in designated areas, and publishes this intelligent highway service strategy information across provinces. It also publishes pre-established information and service standards and specifications for the entire highway network, and provides intelligent algorithm and basic model management services for the entire highway network.

[0037] Specifically, the road network platform is the central system for the intelligent operation and service of highways. It serves as a bridge connecting various regional platforms, supporting the exchange, sharing, and reuse of data resources between regions. It is mainly used to support various business processes, forming an information flow between various regional platforms through information interaction, and ensuring the efficient collaborative operation of different businesses.

[0038] In addition, the road network platform is responsible for the formulation and release of standards and specifications for the entire network's security, business, operation and services. It is also responsible for the management of intelligent algorithms and basic models for the entire network, realizing algorithm management functions such as basic algorithm training, algorithm submission and algorithm review, so as to build a unified algorithm and strategy for the entire network and ensure the consistency of the experience across the entire intelligent highway network.

[0039] See Figure 2 The specific objectives of the intelligent highway operation and service system provided in this application are as follows: (1) Understandable: Intelligent analysis and monitoring system for road network operation By fully leveraging existing equipment and infrastructure achievements and utilizing intelligent technologies to enhance the service efficiency of existing facilities, strengthen the perception capabilities of facilities and equipment, and improve the comprehensive utilization capabilities of facilities and equipment such as ETC gantries and video surveillance networks, a ubiquitous perception system for road networks across multiple levels (scales) can be constructed. This system will enable timely, accurate, and comprehensive all-weather identification of traffic network status. By comprehensively utilizing advanced information technologies such as AI and big data, the system will conduct in-depth mining and intelligent analysis of the collected multi-source perception data, automatically extract traffic scenario information, and dynamically match key indicators from the evaluation indicator library (scenario matching). This will significantly reduce road congestion and traffic accidents, reduce highway closure time, and provide targeted monitoring and evaluation of the road network's operational status and service level.

[0040] (2) Accurate judgment: Realizing traffic safety identification, early warning and collaborative handling Based on proactive identification of traffic safety incidents, a road network operation status evolution chain is established using advanced technologies such as AI and big data to predict road network operation evolution trends. Scientific methods, including adaptive threshold setting, are used to predict and warn of safety hazards, enhancing business and data sharing capabilities, improving cross-departmental and cross-business system capabilities, and strengthening collaborative command, emergency response, rescue services, maintenance management, and road administration. This enables cross-scale determination of the scope of incident impact and dynamic coordination of emergency response and command and dispatch.

[0041] (3) Refined services: Promote proactive safety early warning services Leveraging next-generation information technologies such as big data, cloud computing, artificial intelligence, and BeiDou communication, and employing a cloud-edge collaborative approach, we can improve the timeliness, accuracy, and correctness of road network event detection. Based on infrastructure such as ETC, we provide highway travelers with streamlined, real-time safety warnings based on OBUs, reducing secondary accidents and improving travel efficiency while ensuring safety. By fully utilizing service access methods such as variable message signs, ETC antennas, on-board units (OBUs), and mobile internet, we can quickly achieve vehicle-road collaboration based on ETC, improving the timeliness and accuracy of user information services throughout the entire travel process, thereby enhancing user experience and satisfaction.

[0042] (4) Enhanced security: Ensure the safe operation of the road network and strengthen network and data security protection. To achieve comprehensive traffic situation awareness and intelligent management and emergency response for key road sections, a proactive prediction and early warning road network operation safety assurance system will be created. A traffic perception network will be constructed to support all-weather traffic, full-section perception, and full-process management, reducing the potential traffic impact of construction, accidents, and severe weather, reducing the road network operation load, improving road section traffic capacity, and effectively enhancing road network traffic capacity and driving safety.

[0043] Strengthen network security operation mechanisms, streamline boundary protection strategies, and optimize subnet planning; thoroughly understand the widely distributed, large-scale, and complex asset portfolio, conduct statistics and classification of networked device assets from the perspective of devices, and construct basic protection objects; establish a reliable and compliant internal protection system for networked devices to avoid security risks such as virus propagation, malicious attacks, and Trojan implantation; explore the construction of a blockchain-based data reconciliation mechanism to achieve key business support under trusted data sharing.

[0044] (5) Establishing standards: Establishing a standard and normative system for operation and service. Establish and improve a standard and specification system for traffic safety incidents, perception data, algorithm models, business processes, system / network interfaces, etc., build a business data model swarm intelligence development environment, comprehensively enhance the real-time monitoring capabilities, road network collaborative management capabilities, scientific decision-making capabilities, and personalized traffic information service capabilities of the expressway network, and promote the construction and development of intelligent travel services and standardized and regulated operation supervision of expressways.

[0045] Based on existing equipment and facilities, and with full utilization of new technologies in fields such as information and communication, this system integrates cognition, decision-making, dissemination, security, and standards to build a smart highway operation and service system that includes a road network platform, a regional platform, and a road segment platform.

[0046] As described above, the intelligent highway operation and service system provided in this application can improve the level of intelligent highway management and service, meet the requirements of overall planning, and is constructed in accordance with the principles of systematicness, practicality, safety, advancement, economy, and scalability, guided by the management needs of all parties involved in the operation period and the public's travel needs. Centered on the needs of highway vehicle users, with the goal of promoting high-quality development of highways, and using the integration of new technologies and applications to promote the intelligentization of existing facilities through new infrastructure, it significantly improves the operational efficiency and service level of highways.

[0047] In one example, see Figure 3 The architecture of the intelligent highway operation and service system includes a road network platform at the ministerial level; a regional platform at the regional level including provincial central intelligent platforms and urban agglomeration regional central intelligent platforms; and a road segment platform at the road segment level including road segment sub-centers (regional centers) road segment intelligent platforms and field equipment (including roadside equipment and vehicle-mounted units).

[0048] The road network platform will be upgraded and constructed to be more intelligent, relying on the existing system of the Ministry's Road Network Monitoring and Emergency Response Center.

[0049] The regional platform will be upgraded intelligently based on the existing system of the provincial expressway center. It will be used to build regional-level intelligent platforms for key areas such as urban clusters and the main expressway network, including national and provincial trunk lines.

[0050] The road section platform will upgrade and construct intelligent systems based on the existing systems of the road section sub-center or area center, and improve the construction of field equipment and facilities in accordance with the functional and capability requirements of this plan.

[0051] In an intelligent highway operation and service system provided in this application embodiment, the road segment platform of the intelligent highway operation and service system includes: a road segment platform business system, a model middle platform, a data center, a cloud control center, a converged communication layer, and an infrastructure layer; the regional platform of the intelligent highway operation and service system includes: a regional platform business system, a model middle platform, a data center, a cloud control center, and a converged communication layer.

[0052] The infrastructure layer comprises an edge computing module and a roadside equipment module. The edge computing module aggregates various sensor data collected by the infrastructure layer from highway sections to obtain system business data, and performs security event identification, road hazard warning, road operation analysis, and traffic and event information extraction based on edge computing. The roadside equipment module collects vehicle operation data from the highway section using ETC systems, video acquisition equipment, and radar; collects weather and environmental data from the highway section using grating sensors; and publishes travel information, safety warning information, traffic guidance information, and vehicle-road cooperative information from the highway section using on-board units (OBUs). The infrastructure layer consists of roadside equipment and edge computing. In the roadside equipment layer, these devices serve three main functional modules: operation perception, environmental perception, and information dissemination. The operation perception module includes ETC, video, and radar devices, which are used to perceive and record relevant data during vehicle operation. The environmental perception module includes meteorological, fog, infrastructure, and drone devices, which are used to perceive environmental information around vehicles. The information dissemination module includes ETC gantry-OBU, variable message signs, warning devices, internet access, and vehicle-to-everything (V2X) communication equipment, used to disseminate information to drivers and other vehicles, supporting dissemination capabilities. At the edge computing level, it mainly includes data aggregation, analysis and processing, information interaction, algorithm management and monitoring, and equipment monitoring functions, supporting cognitive capabilities.

[0053] The data center is used to store structured data and surveillance video data collected by the infrastructure layer based on a data resource pool. The data center includes two functional modules: a data resource pool and a data management module. The data resource pool stores various types of data, including structured data (such as ETC data, traffic incident data, and environmental monitoring data) and surveillance video data (such as incident scene video data and monitoring data of important locations). The data management module includes functions such as data fusion, data governance, classification and grading, trusted sharing, data assets, and data security, supporting data service capabilities.

[0054] The model platform stores algorithm libraries and business model libraries. The algorithm libraries contain mathematical models for data mining, algorithms for visual AI, machine learning, event recognition, trend analysis, meteorological analysis, and digital twins. The model platform includes an algorithm resource pool and a model management module. The algorithm resource pool is a collection storing various basic algorithm libraries and business model libraries, such as data mining, visual AI, and machine learning algorithms, as well as business models for event recognition, trend analysis, meteorological analysis, and digital twins. The model management module provides functions such as data and computing resource scheduling, model trial and verification environment, low-code development, model certification and release, and model operation monitoring. This helps users effectively manage model resources, optimize model development processes, and ensure model reliability and stability, thus supporting decision-making capabilities.

[0055] The cloud control center in the road segment platform connects the road segment platform's business system, model middleware, and data center, and also connects the road segment platform and the regional platform. Similarly, the cloud control center in the regional platform connects the regional platform's business system, model middleware, and data center, and also connects the regional platform and the road network platform. Both the road segment platform and the regional platform comprise a cloud base and a data bus. The cloud base includes computing services, storage services, network services, and security services, providing services to the upper-layer data bus and supporting cloud service capabilities. The data bus connects the data center, model center, and business system. During operation, the operation of sensing devices and model algorithms needs to be monitored, as well as the usage of computing and data resources. The converged communication layer receives data from the infrastructure layer and sends data from the converged communication layer to the cloud control center. The converged communication layer supports multiple protocols, including SD-WAN, MPLS, 4G / 5G, and 5.8GDSRC, supporting operation in different network environments. The business systems of the road segment platform and the regional platform include multiple subsystems. Among them, the intelligent perception / operation monitoring system uses smart highway front-end perception equipment to monitor the conditions of vehicles on the road and environmental conditions such as weather, so as to realize overall traffic situation perception and collect infrastructure status for maintenance.

[0056] Based on the above, the road network platform includes six modules: information and service standards and specifications, intelligent level evaluation index system, data and algorithm resources, algorithm certification and registration, unified map service, and BeiDou ground-based augmentation, which support the core capabilities of the system.

[0057] Specifically, the support capabilities provided by the aforementioned road network platform are as follows: (1) Information and service standards and specifications: Information resources are uniformly sorted out, and an information and service standards and specifications system is established based on national and industry standards. This system constrains and regulates data collection and access, data storage format, data content quality, data classification and hierarchical management, and data sharing and exchange in business systems.

[0058] (2) Intelligent level evaluation index system: The road network level platform shall formulate an intelligent level evaluation index system. The evaluation system shall consist of four aspects of evaluation indicators: technical status, operation and service, service level and green development.

[0059] (3) Data and Algorithm Resources: The road network-level platform aggregates and stores various types of data, including raw data, information release data, and cross-provincial information release data, uploaded by regional / segment platforms, generating a data resource pool and providing data services to external parties. The road network-level platform manages and evaluates the collected excellent algorithms in a unified manner and provides service lists and algorithm services to external parties.

[0060] (4) Construct a unified data service bus to realize unified management of data services, provide unified data interface services for various applications, realize unified application gateway, unified application registration, unified application management, unified application authentication, and unified user center for data services, and realize user and service monitoring, rate limiting and degradation, service sharing, etc.

[0061] (5) Algorithm certification and registration: The network-level platform should have basic algorithm training, algorithm submission, algorithm review, algorithm certification and registration and other algorithm management functions. At the same time, the algorithm versions developed by the regional and road segment-level platforms through iteration are uploaded to the network-level platform. The algorithm versions reviewed and tested by the network-level platform are promptly distributed to the regional and road segment-level platforms for reference and use, so as to build a unified algorithm and strategy for the whole network and ensure the consistency of the experience of the entire network of smart highways.

[0062] (6) Unified map service: The road network platform should have the ability to provide a unified spatiotemporal reference service for the entire network of expressways. Based on the construction of high-precision maps for the entire line, and through cooperation with map providers, the map providers should uniformly complete the static data collection of high-precision maps for the entire network and the generation of dynamic high-precision maps for the entire network.

[0063] (7) Beidou ground-based augmentation: The road network-level platform utilizes the Beidou ground-based augmentation equipment installed in the ETC gantry system and the existing basic resources of the Ministry of Transport's expressway network toll collection center to form a Beidou ground-based augmentation network for expressways based on the ETC gantry system. It will build a high-precision positioning service network covering the entire expressway network in China, providing strong support for applications such as high-precision navigation, smart expressways, smart cities, vehicle-road cooperation, autonomous driving, smart construction, and smart logistics.

[0064] The cognitive capabilities of the aforementioned intelligent highway operation and service system are specifically reflected in the following aspects: (1) The system’s cognitive capabilities are mainly composed of two parts: edge infrastructure and model platform. Intelligent algorithms provide comprehensive support for the construction, management, maintenance, operation and service of highways.

[0065] (2) Edge infrastructure includes two categories: ubiquitous sensing devices and information dissemination devices. Ubiquitous sensing devices use digital and intelligent sensing methods to construct a multi-dimensional holographic ubiquitous sensing system by sensing the status of infrastructure, traffic, environment, and key areas, thereby enabling the monitoring of traffic operation status. Information dissemination terminals disseminate the same travel information through variable message signs, vehicle-mounted intelligent terminals, call services, the Internet, broadcasting, and other means to ensure the consistency of information dissemination content.

[0066] (3) The edge computing layer is built on edge computing nodes deployed along the road to realize the collaborative linkage between edge infrastructure and regional / road segment level platforms, realize the data aggregation and preprocessing of sensing information and other effective data, edge computing and analysis processing of algorithms such as meteorological early warning and event detection, and realize the management and monitoring of running algorithms at the edge layer.

[0067] (4) The model platform is an algorithm resource pool consisting of a basic algorithm library and a business model library, supporting the calculation and analysis of road network information in business systems. The basic algorithm library mainly includes data mining algorithms, visual AI algorithms, speech AI algorithms, and spatiotemporal sequence analysis algorithms. The business model library mainly includes models for event recognition, operational trend analysis, and meteorological analysis. Among them, the event recognition model supports the detection of typical road traffic events, the operational trend analysis model provides real-time and predictive analysis of traffic safety status, and the meteorological analysis model integrates meteorological environmental perception data along highways to provide accurate meteorological services. At the same time, the model platform is responsible for the management of related model algorithms, mainly including data and computing resource scheduling, model trial calculation and verification environment, low-code development, model certification and release, and model operation monitoring. Algorithms and models should meet the requirements of continuous optimization and continuous iteration.

[0068] Information dissemination terminals should include various devices, such as ETC gantries and OBUs, variable message signs, warning devices, and the internet. These terminals should be able to disseminate information to drivers and other vehicles and provide services such as reservation-based passage, route planning, and traffic condition inquiries. Users can reserve passages via the internet, i.e., reserving passage within a specific area for a specific time period; the system will then schedule and arrange passage based on the user's reservation information. Route planning can be implemented using variable message signs and the internet. Variable message signs can display road conditions and traffic information, such as congestion, construction, and speed limits, on gantries or beside the road, helping drivers choose the best route. Simultaneously, internet clients can provide real-time traffic information, such as traffic flow, congestion, and traffic accidents, processing this information through intelligent algorithms to provide drivers with optimal route planning options. Traffic condition inquiry functions can be implemented using warning devices and the internet. Warning devices can display current traffic information and safety reminders, such as speed limits and traffic accidents, beside the road. The internet can also provide real-time traffic condition inquiry services, such as traffic congestion and construction information.

[0069] To ensure the quality of access services provided by this system, the system should clearly define the main content of access information dissemination and the quality standards for information services, and formulate corresponding service level agreements based on actual needs. Simultaneously, the system should clearly define the methods of information dissemination and the unified external information service interface, enabling different terminal devices to access and use the system services. Finally, the system should specify detailed requirements for each component, such as the reliability of the service platform, the stability and security of the information dissemination terminals, to ensure the system operates safely and stably and provides high-quality services.

[0070] Furthermore, the cloud service capabilities of the aforementioned intelligent highway operation and service system are specifically reflected in the following aspects: The regional and road segment platforms are built upon a unified cloud infrastructure, encompassing data centers, model platforms, and business systems. This cloud infrastructure provides fundamental support for computing, storage, and networking, and utilizes a cloud operating system to pool resources, enabling automatic and on-demand allocation of computing resources, storage devices, and network equipment. Furthermore, the cloud infrastructure offers elastic resource scaling and intelligent scheduling capabilities, supporting unified access, unified operation and maintenance management, and unified scheduling of virtual resources, while also providing resource security control functions.

[0071] The platform adopts a logical cloud architecture, achieving interconnection with external platforms such as the Internet through a road network-level platform, and interconnection with regional maintenance platforms, road administration platforms, and engineering construction platforms within the region through a regional-level platform. Leveraging the new infrastructure policy and implementing the platform's microservice concept, the platform builds a support platform that enables automatic service registration, unified permission management, unified traffic access, and unified platform operation and maintenance. It decouples platform services from business services, constructing a data middle platform and a business middle platform to enhance the sharing capabilities of business and data, improve cross-departmental and cross-business system capabilities, and enhance collaborative command, emergency response, and rescue services. Furthermore, the platform also achieves edge-sensing device control based on cloud-native edge management capabilities.

[0072] Through the resource pooling, elastic scaling, and intelligent scheduling capabilities of the cloud-based infrastructure, resource allocation becomes more automated and intelligent. Simultaneously, it enhances business and data sharing capabilities in support platforms and data middleware, providing strong collaborative and emergency service capabilities. Furthermore, the edge-aware device management based on cloud-native edge management capabilities improves the platform's edge computing and device management capabilities, ensuring high service reliability and security.

[0073] In an intelligent highway operation and service system provided in this application embodiment, the roadside equipment module of the intelligent highway operation and service system specifically includes the following: The system is connected to the cloud control center via a converged communication layer, comprising a video surveillance unit, an ETC vehicle feature recognition unit, a traffic parameter sensing unit, a traffic event sensing unit, a traffic environment sensing unit, an infrastructure health monitoring unit, and a key area monitoring unit. The video surveillance unit is used to collect vehicle operation data on highway sections using video surveillance systems, drone video surveillance equipment, and vehicle-mounted mobile video surveillance equipment. The road section platform's business system, cloud control center, converged communication layer, and roadside equipment modules, combined with the characteristics of the road section and demand-oriented design, adopt a "1+1+1+3+N" overall framework to construct one multi-dimensional sensing system, one converged communication system, one cloud control center, and three application platforms. This creates three major categories and N subcategories of smart services and applications: near-all-weather traffic, digital management and control, and public travel services. This achieves digital operation monitoring, precise management and dispatching, efficient emergency rescue, intelligent management decision-making, and integrated travel services, promoting the "safe, efficient, convenient, green, and economical" development of transportation.

[0074] The ETC vehicle feature recognition unit is used by the license plate recognition equipment based on the ETC gantry to identify vehicle features in highway sections; Specifically, taking full account of existing facilities, checkpoint equipment or license plate recognition equipment using ETC gantries will be installed between adjacent interchanges on the main road and at key locations. This will enable accurate identification functions such as license plate recognition, vehicle color recognition, vehicle logo recognition, and vehicle type recognition, allowing for real-time monitoring of the specific information of each vehicle traveling within the closed space of the highway in each section. Simultaneously, by comparing this data with toll collection data, relevant evidence chains will be provided for hit-and-run incidents and toll evasion, providing data support for subsequent operations.

[0075] The traffic parameter sensing unit is used to collect traffic parameters of highway sections based on traffic control stations; The traffic incident sensing unit is used to monitor traffic incidents on the highway section based on the video surveillance system and millimeter-wave radar of the highway section. By analyzing video images captured by cameras, target information is selected from changes in the image sequence for calculation and processing. Vehicle movement trajectories are analyzed, and event alarms are generated based on image processing algorithms. Automatic detection of traffic-related events (congestion, abnormal parking, obstruction of emergency lanes, pedestrian intrusion, non-motorized vehicle intrusion, wrong-way driving / reversing, construction) and weather-related events is performed, and monitoring operators are promptly alerted. This provides a superior monitoring tool for improving the real-time performance and visibility of traffic monitoring, which is of great significance for improving emergency response speed, reducing secondary accidents, minimizing accident losses, and enhancing operational management.

[0076] Depending on road conditions, millimeter-wave radar is deployed as needed on key road sections (such as accident-prone sections, sections prone to severe weather, and high-traffic sections), with increased deployment density on special sections. Millimeter-wave radar enables all-weather, all-time traffic incident detection on key road sections. It provides accurate road condition information, traffic status information, incident / accident location information, vehicle distribution information, and early warning information even in adverse weather conditions (rain, snow, fog, dust storms, smoke) and in low-light conditions. It can complement video detection methods to improve the accuracy of traffic incident detection.

[0077] The traffic environment sensing unit is used to collect weather environment data of the expressway section. Adverse weather conditions such as heavy fog, heavy rain, heavy snow, and strong winds pose a great threat to expressway traffic safety. Therefore, as expressway managers, we should promptly understand the weather conditions along the expressway and take corresponding traffic control measures based on the weather conditions. Once an abnormal weather occurs, we should be able to formulate reasonable control measures in a timely manner to ensure the safety of life and property of road users.

[0078] Meteorological detection equipment such as weather detectors, visibility detectors, and road condition detectors are installed along the route to collect meteorological information. At the same time, video images captured by cameras can be analyzed to automatically detect weather phenomena such as fog. Meteorological data is also connected to the cloud control center. Through various means, the traffic environment is perceived, providing data support for the automatic meteorological monitoring and early warning system.

[0079] The infrastructure health monitoring unit is used to monitor the health of bridges, tunnels, and high slopes within the highway section. The bridge health monitoring system primarily monitors the health of important bridges. By installing sensors on these bridges, it can analyze and assess their health status, gaining a detailed understanding of specific structural changes. This provides reliable foundational data for accurate analysis and evaluation of bridge structural health, forecasting, and maintenance, and offers a scientific basis for decision-making departments to formulate appropriate disaster prevention and mitigation strategies. The bridge health monitoring system consists of sensors, BeiDou monitoring stations, and a central infrastructure health monitoring platform. Sensors include inclinometers, wire displacement gauges, crack gauges, and rain gauges, collecting information on pier misalignment, bearing slippage, main beam deformation, and cracks. The infrastructure health monitoring platform can monitor the structural operational status in real time, analyze and assess the bridge's operational status and safety condition, propose structural maintenance decisions, issue safety warnings, and provide a basis for bridge structural maintenance decisions, effectively guiding the maintenance management work of maintenance departments.

[0080] The tunnel health monitoring system is mainly used for health monitoring of long tunnels. By installing sensors in long tunnels, the system can analyze and assess the health status of the tunnel, gain a detailed understanding of the specific changes in its structure, provide reliable basic data for accurate analysis and evaluation of the tunnel's structural health status, forecasting and maintenance, and provide a scientific basis for decision-making departments to formulate corresponding disaster prevention and mitigation strategies.

[0081] The tunnel health monitoring system consists of sensors, BeiDou monitoring stations, and a central infrastructure health monitoring platform. Sensors include laser rangefinders, hydrostatic levels, crack gauges, and strain gauges, which collect data on structural deformation, structural strain, and crack patterns within the tunnel structure to understand its deformation status. Tunnel robots can also be used to monitor the tunnel's condition. The infrastructure health monitoring platform collects, stores, analyzes, manages, and applies monitoring data in real time, providing real-time feedback and early warning information. It issues warnings before disasters occur, allowing for proactive measures to minimize their impact and meet the maintenance and management needs of tunnel monitoring.

[0082] The high slope health monitoring system consists of sensors, Beidou monitoring stations, and a central infrastructure health monitoring platform. Sensors include fixed inclinometers, rain gauges, and anchor cable gauges, which collect raw data on surface deformation, deep displacement, rainfall, and anchor cable stress of the high slope project to assess slope stability. The infrastructure health monitoring platform analyzes and processes the collected data to promptly grasp the safety status of the high slope during construction and operation, transmits the overall traffic load trend of the high slope to management personnel in real time, and presents monitoring data and early warning information in real time via the internet, providing a basis for the formulation of subsequent maintenance plans.

[0083] The key area monitoring unit is used to monitor traffic incidents in preset key areas of the highway section based on the ETC gantry system.

[0084] In an intelligent highway operation and service system provided in this application embodiment, the key areas in the intelligent highway operation and service system include: tunnels with a length exceeding a preset length threshold, road sections with traffic flow exceeding a preset flow threshold, pre-determined accident-prone road sections, pre-determined severe weather-prone road sections, service area hazardous materials monitoring and early warning areas, and toll stations.

[0085] Based on this, the monitoring process for tunnels exceeding a preset length threshold includes: tunnel monitoring, by reproducing the real-time road conditions intuitively, allows monitoring and management personnel at the monitoring center to understand the road and traffic conditions along the route, weather conditions, and the actual situation of traffic anomalies, enabling them to quickly take measures such as traffic control and rescue. The tunnel monitoring system is fully utilized, employing traffic event detection AI algorithms to analyze video images captured by cameras within the tunnel. ETC gantry systems are installed at the entrances and exits of long tunnels, equipped with ETC antennas, license plate recognition cameras, vehicle type recognition cameras, supplementary lighting, and other equipment to detect vehicles entering and exiting the tunnel, accurately determining the real-time number, type, and license plate of vehicles within the tunnel. ETC antennas are deployed at specific intervals within long tunnels as needed to collect cross-sectional traffic parameters and vehicle passage information, enabling vehicle detection within a designated area and information dissemination within the tunnel.

[0086] The monitoring process for road sections where traffic flow exceeds a preset threshold includes: setting up millimeter-wave radar and high-definition cameras in high-traffic sections to monitor the road sections around the clock, accurately sensing information such as traffic flow, vehicle trajectories, and traffic incidents, providing data support for lane-level management of high-traffic sections, reducing rear-end collisions, and ensuring vehicle traffic safety.

[0087] The monitoring process for pre-determined accident-prone road sections includes: setting up millimeter-wave radar and increasing the density of high-definition cameras in these sections to monitor them around the clock, promptly detect traffic incidents, and improve emergency management and response speed.

[0088] The monitoring process for pre-determined road sections prone to severe weather includes: setting up millimeter-wave radar and increasing the density of high-definition cameras on these sections to monitor them around the clock, accurately sensing information such as traffic flow, vehicle trajectories, and traffic incidents, providing data support for near-all-weather traffic and ensuring vehicle traffic safety.

[0089] The monitoring process for hazardous materials monitoring and early warning areas in service areas includes: installing ETC antennas and high-definition checkpoint cameras at service area entrances and exits to statistically analyze the license plates, vehicle types, and numbers of vehicles entering and exiting the service area. This provides functions such as service area traffic monitoring, entrance and exit vehicle information statistics, vehicle type analysis, passenger flow prediction, and hazardous materials vehicle monitoring and early warning, enabling precise management of vehicles entering and exiting the service area and supporting service area resource scheduling. Through network-wide data sharing, vehicles are monitored and warned in real time, supporting functions such as fatigue driving control, and improving the safety, efficiency, and intelligence of service areas.

[0090] The monitoring process for toll stations includes: The traffic capacity of highway toll stations directly affects the traffic capacity of the entire road segment and restricts the traffic operation of the highway. Real-time understanding of the queuing situation at highway toll stations is of great significance for road management personnel to make decisions, which can improve the traffic capacity of highway toll stations and enhance the service level of highways.

[0091] By using video images captured by high-definition cameras in the toll plaza, and through traffic event detection AI algorithms, the traffic conditions of the toll plaza and ramps are analyzed in real time. The system can accurately analyze vehicle queue length, average speed, and queue duration, intelligently determine the congestion situation at the toll plaza and issue early warnings. This allows managers to have timely and comprehensive access to toll plaza traffic information and improve the efficiency of congestion management.

[0092] In an intelligent highway operation and service system provided in this application embodiment, the road segment platform business system in the intelligent highway operation and service system includes: a quasi-all-weather traffic system, a digital management and control system, and a public travel service system; The quasi-all-weather access system includes: an automatic weather monitoring and early warning module; Correspondingly, the traffic environment perception unit includes: a grating sensor, a weather detector, a visibility detector, and a road surface condition detector, each corresponding to the automatic meteorological monitoring and early warning module; the model platform is used to perform road traffic meteorological early warning detection on the weather environment data collected by the grating sensor, weather detector, visibility detector, and road surface condition detector based on at least one of a preset visual AI algorithm, machine learning algorithm, event recognition algorithm, and meteorological analysis algorithm; the cloud control center is used to generate meteorological early warning and forecast information for the highway section based on the detection results corresponding to the road traffic meteorological early warning detection, and send the meteorological early warning and forecast information to the on-board units (OBUs) in the vehicles on the highway section based on the fused communication layer, so as to publish the meteorological early warning and forecast information within the highway section based on the on-board units (OBUs).

[0093] Severe weather conditions such as fog, heavy rain, and icy roads are significant factors contributing to traffic accidents, making accurate meteorological perception and early warning crucial. To meet the needs of road traffic meteorological services, a road traffic meteorological early warning and forecasting system is developed. This system utilizes a traffic incident detection AI algorithm located at the center, along with roadside meteorological detectors, visibility detectors, and road surface condition detectors to collect meteorological data across the entire route. It also incorporates monitoring data from meteorological stations along the road and in surrounding major areas, including visibility, air pressure, temperature, humidity, precipitation, wind direction, and wind speed. This system enables the monitoring and early warning of various meteorological disasters such as rain, fog, ice, and snow, providing meteorological data support for road traffic management by operational management units.

[0094] The road traffic meteorological early warning and detection system consists of meteorological detection equipment, an integrated traffic incident detection machine (optional), and a cloud control center comprehensive management and control platform.

[0095] (1) Meteorological detection equipment: The meteorological detection equipment mainly consists of meteorological detectors, visibility detectors and road condition detectors.

[0096] 1.1 Weather detectors: Weather detectors are installed on road sections prone to severe weather to automatically detect information such as visibility, air temperature, air humidity, rainfall, wind speed, wind direction, road surface temperature and humidity, and road surface condition.

[0097] 1.2 Visibility Detector: Visibility detectors are installed in foggy road sections to automatically detect the visibility information of the area.

[0098] 1.3 Road surface condition detectors: Road surface condition detectors are installed on the shaded sides of bridges, tunnels and other road sections prone to icing to automatically detect information such as road surface temperature, freezing point temperature, road surface condition (dry, damp, wet, ice, snow, frost), friction coefficient, and ice content.

[0099] (2) Traffic incident detection all-in-one machine (optional): The traffic incident detection all-in-one machine analyzes the video images collected by the camera and automatically detects meteorological information such as fog.

[0100] (3) Integrated Management and Control Platform: The cloud control center's integrated management and control platform has meteorological early warning and forecasting functions. In the absence of a traffic incident detection all-in-one machine, the management and control platform allocates certain resources to deploy AI algorithms for automatic meteorological detection.

[0101] By collecting data through roadside meteorological monitoring equipment, a refined meteorological early warning and forecasting model is established. The meteorological data is analyzed to accurately grasp the characteristics and patterns of weather changes, and to achieve comprehensive perception and early warning and forecasting of information such as icing, fog, crosswinds, precipitation, and road surface high temperatures at the minute and kilometer levels.

[0102] The specific functions of the road traffic meteorological early warning and detection system include: (1) Traffic meteorological data collection: Different collection methods are adopted according to different sources of meteorological data to achieve compatibility and aggregation of multi-source meteorological data.

[0103] (2) Traffic meteorological data processing and analysis: Data processing is responsible for analyzing, processing, implementing algorithms, and integrating the collected data, and generating final applicable product data to achieve kilometer-level and minute-level early warning and forecast meteorological data.

[0104] (3) Traffic meteorological road network data service: Based on the functions of traffic meteorological data collection, traffic meteorological data processing and analysis, and traffic meteorological data storage, the corresponding hardware devices are configured to provide data services for the early warning, forecasting and handling analysis of traffic meteorological disasters such as rain, fog, ice and snow that are of key concern to highways through reserved data access interfaces.

[0105] (4) Traffic Meteorological Decision Analysis: Based on traffic meteorological data collection, processing and analysis, storage and service, this system provides an integrated display of traffic meteorological data elements, offering decision-making support for operation and management units. Key components include the visualization of real-time monitoring information from traffic meteorological stations and road networks, statistical analysis of traffic meteorological data, and real-time push notifications of traffic meteorological early warnings and forecasts.

[0106] In a highway operation and service intelligent system provided in this application embodiment, the quasi-all-weather traffic system in the highway operation and service intelligent system further includes: a driving safety guidance module; Correspondingly, the roadside equipment module also includes: a driving safety guidance device corresponding to the driving safety guidance module; the driving safety guidance device includes a node control host and an intelligent guide light connected to the node control host; the node control host is used to control the intelligent guide light to display light in different colors and / or flashing modes according to different received mode functions, wherein the mode functions include: standby state, road contour enhancement mode function, driving active guidance mode function, and rear-end collision prevention warning mode function.

[0107] A driving safety guidance system is installed on foggy road sections. The system integrates weather detection, intelligent guide lights and other equipment to prevent traffic incidents through reminders and guidance.

[0108] By installing intelligent guide lights on both sides of the road, the red and yellow light signals emitted by the guide lights help drivers judge the road conditions and the conditions of vehicles ahead, realizing intelligent guidance functions such as safety outline, warning and rear-end collision prevention warning. This enhances the road perception and control capabilities of drivers and passengers, as well as the warning and early warning capabilities of dangerous road sections. It provides highly reliable intelligent guidance visual navigation services for safe driving on highways, significantly reducing the primary accident rate, avoiding secondary accidents such as rear-end collisions, and effectively improving vehicle traffic efficiency and traffic safety.

[0109] The driving safety guidance system consists of meteorological detection equipment, intelligent guide lights, node control host and cloud control center platform.

[0110] The driving safety guidance system primarily provides functions such as road contour enhancement, active driving guidance, and rear-end collision warning. Based on the visibility conditions and pre-set thresholds, the system automatically switches operating modes to guide vehicles safely in varying visibility and weather conditions. The driving guidance system's response is divided into four levels: Level 1: Standby. When visibility is greater than 500m, the guide lights are off, and the device is in low-power mode. Level 2: Road contour enhancement mode. When visibility is greater than 400m but less than 500m, the system enters road contour enhancement mode. The guide lights on both sides of the road are active, illuminating the yellow guide lights and turning off the red guide lights, thus providing high-contrast road alignment guidance in low-visibility environments. This guidance system provides long-distance, high-precision, and high-definition alignment guidance both day and night, ensuring a relatively safe operating environment for vehicles in foggy weather. Level 3: Active driving guidance mode. When visibility is greater than 300m but less than 400m, the system enters active driving guidance mode. The yellow guide lights can flash synchronously at a pre-set frequency, while the red warning lights remain off. This dynamic flashing light alerts the driver to road conditions and to drive cautiously. Level 4: Rear-end Collision Prevention Warning Mode. When visibility is less than 200 meters, the system enters rear-end collision prevention warning mode. When a vehicle passes the guide device, it triggers the red warning lights of a certain group of upstream guide devices to illuminate, creating a red trail to indicate that a vehicle is ahead and to maintain a safe distance. At this time, the yellow guide lights of other guide devices can flash synchronously. As the vehicle moves forward and passes the next group of guide devices, the red trail will move forward in dynamic synchronization with the vehicle.

[0111] In an intelligent highway operation and service system provided in this application embodiment, the quasi-all-weather traffic system within the intelligent highway operation and service system further includes an intelligent snow and ice melting module. Correspondingly, the roadside equipment module further includes a road surface information acquisition subsystem, a spraying subsystem, and a sub-control system corresponding to the intelligent snow and ice melting module. The sub-control system and the cloud control center together constitute the processing and control subsystem corresponding to the intelligent snow and ice melting module. The road surface information acquisition subsystem is used to collect road surface status information and temperature information of the highway section. The spraying subsystem is used to perform spraying and mixing of spraying agents on the highway section according to the instructions of the processing and control subsystem.

[0112] For road sections with relatively ample construction funds, intelligent de-icing and snow removal systems are installed at tunnel entrances on the shaded side, bridges, and other sections prone to icing. This improves driving safety under snow accumulation and icing conditions, reducing traffic accident rates. Road surface condition detectors monitor road surface conditions and temperature in real time, transmitting this data using IoT technologies such as digital communication and automatic control. The cloud control center platform analyzes the collected traffic and meteorological data and road surface condition information in real time, predicting road icing time and ice thickness, and automatically issuing icing and black ice warnings. Before road icing occurs, the system uses pumps and electric valves to promptly spray de-icing agents onto the road surface, ensuring safe vehicle operation and preventing major traffic accidents.

[0113] The intelligent ice melting and snow removal module consists of a road information collection subsystem, a spraying subsystem, and a processing and control subsystem.

[0114] (1) Road surface information acquisition subsystem: Road surface condition detectors are set up in sections of road prone to icing to collect road surface condition information and temperature information, providing monitoring information for the pump station control system.

[0115] (2) Processing and Control Subsystem: This system consists of the central control system of the cloud control center and the sub-control systems on site. The central control system of the cloud control center supports remote control of the sub-control systems. The sub-control systems are managed and controlled by the pump room based on the signals from the road surface acquisition subsystems according to the pre-set snow removal plan. They start the pressure pumps and the field spray controllers to manage and control each spraying subsystem. This system is the core of the processing.

[0116] (3) Spraying subsystem: It consists of nozzles, controllers, snow melting agents, etc. It executes the mixing ratio and spraying of the spraying agent according to the instructions of the processing control subsystem.

[0117] In an intelligent highway operation and service system provided in this application embodiment, the digital management and control system includes: a lane-level active management and control system, a merging and diverging zone safety early warning system, and a key operating vehicle management and control system. The lane-level active management and control system is used to automatically adjust lane control measures based on a preset traffic control strategy according to the collected highway traffic flow, traffic incident, and meteorological environment information, and to control the changes in the image display of variable information signs. The lane-level active management and control system automatically adjusts lane control measures based on the collected highway traffic flow, traffic incident, and meteorological environment information, and realizes lane control and speed limits for different sections, different lanes, and different levels through variable information signs, thereby achieving active intervention in highway traffic flow, stabilizing traffic flow, reducing speed differences, improving traffic efficiency, and reducing traffic accident rates.

[0118] System Composition: The lane-level active control system consists of field sensing equipment, information dissemination equipment, and a cloud control center integrated management and control platform.

[0119] (1) Field sensing equipment: Based on the field sensing equipment, information such as road traffic flow, traffic events, traffic environment, and vehicle trajectory is collected to provide front-end data support for lane-level active control.

[0120] (2) Integrated management and control platform: The cloud control center's integrated management and control platform has intelligent management and control functions.

[0121] The system establishes lane-level real-time traffic control strategies and algorithms, including those for preventing rear-end collisions on highways, dynamic speed limits for each lane, dynamic control of emergency lane opening and closing, and near-all-weather passage under adverse weather conditions. By combining multi-source heterogeneous data, it calculates the probability and risk value of traffic incidents on highways in real time. Once the risk value exceeds the threshold, corresponding control measures are immediately activated. Lane-level control, speed limits, and information dissemination are carried out through variable message signs, third-party navigation software, and other means to regulate traffic volume and flow on road sections.

[0122] It can achieve lane-level active control under conditions of high traffic volume, traffic incidents, severe weather, and maintenance work.

[0123] (3) Variable message signs / third-party navigation software: Variable message signs are installed before interchange exits to enable lane-level speed limits, traffic control, and traffic information dissemination. For high-traffic, accident-prone sections, these signs can be densified at 2-kilometer intervals to gradually reduce or increase speed and smooth traffic flow. Simultaneously, relevant control and information dissemination are conducted through third-party navigation software.

[0124] The system functions are as follows: (1) When traffic conditions are normal, the variable information sign displays the normal speed limit.

[0125] (2) Dynamic speed limits in case of emergencies: Highways are divided into several control units. When an emergency occurs in a certain area, speed control of upstream vehicles is required. By dynamically adjusting the speed limits of upstream sections, vehicles gradually approaching the incident site are controlled. By gradually decreasing the speed limits, the speed of traffic along the route is slowed down. As traffic volume continues to increase, vehicle queues will gradually spread upstream. To reduce the speed difference between adjacent sections, the speed limits of upstream sections need to be adjusted in a gradient to achieve smooth traffic flow. At the same time, variable message signs indicate "Accident Warning Ahead".

[0126] (3) Dynamic speed limits during heavy traffic congestion: When traffic congestion occurs along the route, vehicle speeds decrease, and speed differences become large, easily leading to rear-end collisions. Dynamic speed limit control can fundamentally reduce the speed difference between adjacent vehicles, thereby alleviating congestion while improving driving safety. When traffic congestion occurs along the route, effective dynamic speed control reduces the proportion of high-speed vehicles in a certain section, keeping vehicle speeds within the section stable and uniform. Furthermore, by coordinating the speed limits of adjacent sections, the speed difference can be reduced, decreasing the occurrence of rear-end collisions and ensuring vehicle traffic safety during periods of heavy traffic. Simultaneously, variable message signs display "Congestion Warning Ahead."

[0127] (4) Dynamic speed limits under severe weather conditions: When severe weather conditions such as heavy fog, heavy precipitation, freezing rain, and blizzard occur, dynamic speed limits can effectively reduce vehicle speeds on relevant road sections, achieving near all-weather accessibility on highways. In conjunction with the overspeed capture system, the maximum speed limit values ​​for different sections of the highway can be changed in a timely manner to achieve dynamic control of vehicle speeds within the road sections. At the same time, variable message signs will display "severe weather warning" information.

[0128] The merging and diverging zone safety early warning system is used to generate safety early warning information for situations such as unstable vehicle speed, poor visibility, ramp congestion, continuous lane changes, vehicles stopping in the merging zone, vehicles forcibly changing lanes after passing the lane change area, vehicles reversing after passing the diverging point, vehicles braking suddenly, and temporary stops to drop off passengers at the merging and diverging points on highway sections. The system also publishes the safety early warning information based on the pre-set integrated safety reminder equipment at the merging and diverging points. Diverging and merging points are areas where highway traffic flows intersect, and are prone to abnormal situations such as unstable vehicle speeds, poor visibility, ramp congestion, continuous lane changes, vehicles stopping in the merging area, vehicles forcibly changing lanes after passing the lane change area, vehicles reversing after passing the merging point, emergency braking, and temporary stops to drop off passengers. These are high-risk areas for highway accidents, especially in severe weather conditions such as fog when visibility is poor, making traffic accidents extremely likely.

[0129] System Composition: An integrated safety reminder device is installed at the diversion point. This device integrates high-definition cameras, millimeter-wave radar, displays, and audible and visual alarms. It can detect abnormal events such as parking, congestion, slow driving, and lane changes on the deceleration lane and ramps. It generates comprehensive reminder information through audible and visual alarms and text messages to remind mainline vehicles that are about to transition from high speed to low speed and enter the deceleration lane, reminding drivers to concentrate on driving safety and reducing accidents in the diversion area.

[0130] The integrated safety warning equipment installed at the merging point detects whether there are vehicles approaching in the outermost lane of the main line, especially large freight vehicles. It forms a comprehensive guidance and warning information through sound and light alarms and text, so as to remind vehicles that are about to enter the main line from the ramp and are in the acceleration phase to reduce traffic accidents at the merging point.

[0131] The key operating vehicle management system is used to perform real-time dynamic monitoring of pre-determined key operating vehicles, to obtain vehicle information, operating trajectory, and historical travel route range, time period, and frequency of key operating vehicles traveling on the highway section, and to determine whether the key operating vehicle is traveling on the prescribed route. If not, a corresponding abnormal status alarm message is generated and issued based on the on-board unit (OBU) in the key operating vehicle.

[0132] The key operating vehicle management system should enable real-time dynamic monitoring of key operating vehicles, allowing for on-the-go querying of information and operational trajectories of key vehicles, as well as historical route ranges, adherence to prescribed routes, time periods, and frequency, providing decision support for prediction. It should also provide immediate alerts for abnormal conditions such as speeding, fatigued driving, and abnormal parking of relevant key operating vehicles, assisting in rapid emergency response and eliminating blind spots in monitoring "moving hazards." The construction of this key operating vehicle management system can effectively ensure the safety of key vehicles on the road, reduce traffic delays and congestion, improve road operational safety and efficiency, and enhance the overall traffic capacity of the road segment. Its system structure is as follows: The key operational vehicle management system integrates roadside sensing data, ETC data, and on-board terminal data to monitor key vehicles on the road in real time. It can use control measures set up on road sections to provide alerts or warnings to drivers. Once a key operational vehicle is found to be illegally parked or otherwise abnormal, the system will automatically respond, displaying the location of the vehicle, the road section, and the type of alarm. Emergency rescue teams can be quickly dispatched to the scene, and warning information will be issued to notify other vehicles passing through the area to be cautious, enabling the fastest possible handling of traffic accidents and preventing further serious incidents or disasters.

[0133] In an embodiment of this application, a smart highway operation and service system is provided, in which the public travel service system includes: a roadside equipment information release system, an ETC-based vehicle-road cooperative service system, an Internet information release system, and a smart scenario service system.

[0134] Public travel services should meet the needs of travelers, fully reflect the characteristics of public services, and provide the public with travel-related information services. The roadside equipment information publishing system is used to publish information issued by the cloud control center. Based on information collected along the route, including road conditions, emergencies, construction, roadside information, weather, and environmental data, as well as internet traffic information data, and combined with vehicle location and terminal type, the cloud control center uniformly plans the information content and publishes traffic information through variable message signs and broadcasts along the road, realizing vehicle guidance and travel assistance information push, providing drivers with safer, more convenient, and more reliable comprehensive road network information services.

[0135] Variable message signs and broadcasts are installed before interchange exits, tollbooth entrances, and key road sections to provide information services to road users. The ETC-based vehicle-road cooperative service system is used to publish information issued by the cloud control center based on ETC gantries and on-board units (OBUs). The internet information publishing system is used to send the information published by the cloud control center to authenticated and authorized internet devices via a unified external interface. The cloud control center provides a unified external interface to push travel information to internet platforms such as Gaode Maps, Baidu Maps, mobile apps, and WeChat official accounts through authentication and authorization. Internet companies obtain user locations and send different service information based on different user locations.

[0136] Based on a unified, network-wide hierarchical and categorized management method for event information, the road segment platform comprehensively assesses the impact range of events of different levels and types, taking into account the current traffic conditions and future traffic trends. Based on this impact range, it matches appropriate dissemination channels and facilities, including ETC gantries, variable message signs, and the internet. Dissemination strategies can be specifically optimized and adjusted according to road segment traffic characteristics, the deployment of dissemination equipment and facilities, and other relevant factors. Road segments can add, modify, and delete dissemination strategies according to their own business needs.

[0137] The intelligent scene service system is used to control the information publishing devices in the service area to publish the information issued by the cloud control center.

[0138] System Composition: Based on the integration of the existing ETC toll collection and monitoring systems on highways, an ETC-based vehicle-road cooperative system is built by upgrading the ETC gantry hardware and software. The ETC-based vehicle-road cooperative service system consists of three main parts: "vehicle-side - roadside - central terminal," as shown below. Figure 4 As shown.

[0139] For existing ETC users, an event reception, processing, decision-making, and distribution platform will be gradually established based on a unified architecture. This platform can send reminders to ETC vehicle users via the ETC gantry system, using a buzzer to alert them of events affecting driving safety. For pre-installed OBUs and next-generation on-board power supply OBUs, the ETC gantry can provide richer roadside information to passing vehicles, enhancing user service reach by providing event announcements through voice broadcasts and text reminders in addition to buzzer alerts.

[0140] ETC-based vehicle-road cooperative service roadside facilities are mainly divided into two categories: utilizing existing ETC gantry facilities and adding new roadside infrastructure at specific locations. Each category provides different application scenarios for various OBU users. For existing ETC gantry facilities, the bidirectional communication between the ETC antenna and the OBU serves as the vehicle-road cooperative information transmission channel, adding broadcasts of service information beyond ETC transaction information. For newly added roadside infrastructure at specific locations, such as appropriately deploying ETC roadside facilities in key road sections like tunnels, long bridges / tunnels, service areas, and accident-prone sections, a widely covered ETC information service network is formed, enabling more refined information broadcasts.

[0141] In addition, an ETC information release platform will be built in the center of the road section to expand the information interaction between the ETC toll collection system and the road monitoring system, realize data interaction and sharing, and form effective information that can serve users.

[0142] The service scenarios are as follows: The ETC-based vehicle-road cooperative service provides users with a safe and efficient highway travel experience. The system supports typical application scenarios oriented towards safety, efficiency, and service, including but not limited to the typical application scenarios specified in Table 1.

[0143] Table 1 Typical Application Scenarios of Vehicle-Road Cooperative Systems on Highways (1) Dangerous Road Section Warning: For dangerous road sections such as sharp bends, steep slopes, long downhill slopes, long uphill slopes, and sections prone to collapses and landslides, the RSU issues risk relative location warning information to vehicles. By sensing the environment of relevant dangerous road sections, identifying risk factors, and generating information such as hazard type, road section signage, road section location, and up / down signage, the ETC information release platform distributes this information to designated RSUs near the dangerous road sections according to the release strategy. The RSU then releases the dangerous road section warning information to the OBUs that are about to enter the area, providing a warning to the driver.

[0144] (2) Traffic Control Reminders and Guidance: Upstream of a road segment where a traffic control event (such as construction and maintenance, road closure, lane closure, or traffic control) occurs, the RSU sends relative location warnings and lane-level control information to vehicles. The system generates information such as the event type, event location, and lane of the relevant traffic control segment through event identification, which is then distributed by the ETC information publishing platform to designated RSUs upstream of the controlled road segment according to the publishing strategy. The RSU then publishes the relative location warnings and lane-level control information to the OBUs about to enter the area, providing a warning to the driver.

[0145] (3) Traffic Incident Perception and Early Warning: Upstream of a road segment where a traffic incident (such as an accident, vehicle stoppage, slow-moving vehicle, vehicle going the wrong way, or congestion) occurs, a relative position warning is sent to vehicles via the RSU to ensure the safe and smooth passage of vehicles. The traffic incident perception and recognition system detects a traffic incident occurring on the current road segment, generates traffic incident warning information including the incident type, incident location, and lane occupancy, and uploads it. The traffic incident warning information is then disseminated to the OBU (On-Board Unit) about to enter the area via a designated RSU upstream of the road segment, alerting the driver to the potential collision risk with the vehicle ahead.

[0146] (4) Road Hazard Warning: Upstream of road sections where road hazards occur (such as pedestrians crossing, littering, water accumulation on the road, slippery road surface, etc.), the RSU sends a relative position warning to vehicles to ensure the safe and smooth passage of vehicles. The system analyzes the sensing data, detects road hazards in the current road section, and generates road hazard warning information including hazard type, hazard location, and the lane where the hazard is located. The ETC information release platform then releases this warning information to the OBU about to enter the area through the designated RSU upstream of the road section according to the release strategy, thus warning the driver and reminding them of the road hazard ahead.

[0147] (5) Severe Traffic Weather Warning: Upstream of road sections where severe traffic weather events (such as heavy rain, hail, dense fog, etc.) occur, relative location warning information is sent to vehicles via RSUs to ensure the safe and smooth passage of vehicles. The meteorological detection system detects severe traffic weather events occurring on the current road section, generates severe traffic weather warning information including the type of severe weather event and the location of the event, and distributes the warning information to the designated RSUs upstream of the road section according to the release strategy by the ETC information release platform. The RSUs release the severe traffic weather warning information to the OBUs that are about to enter the area, warning the drivers and reminding them that there is severe traffic weather ahead. The roadside meteorological detection subsystem should support the detection of typical severe traffic weather events, including but not limited to: heavy rain, hail, strong winds, dense fog, blizzards, patchy fog, and crosswinds.

[0148] (6) Restricted Road Section Warning: Upstream of a specific restricted road section, the RSU sends warnings about traffic restrictions (such as exceeding height, width, load, time restrictions, and special vehicle restrictions) to specific vehicles to ensure the safe and smooth passage of vehicles. The restricted road section warning supports the configuration of restricted road section location, restriction type, and other restriction information, which is then distributed by the ETC information publishing platform to the designated RSU upstream of the restricted road section according to the publishing strategy. The RSU then publishes the restriction information to the OBU that is about to enter the area, providing a warning to the driver.

[0149] (7) Priority passage for emergency rescue vehicles: On road sections where emergency rescue vehicles (such as ambulances, police cars, fire trucks, etc.) travel, the RSU broadcasts reminders to nearby ordinary vehicles to ensure priority passage for emergency rescue vehicles. The roadside sensing system and RSU detect the location, direction of travel, lane, and other information of emergency rescue vehicles, generate priority passage information for emergency rescue vehicles, and distribute this information to designated RSUs near the road section by the ETC information publishing platform. The RSU publishes the priority passage information for emergency rescue vehicles to nearby OBUs, reminding surrounding vehicles to give way.

[0150] (8) Traffic Information Broadcasting and Guidance: On normal driving sections, the RSU broadcasts real-time traffic conditions and traffic diversion information to vehicles. By detecting traffic parameters such as traffic flow and average speed, real-time traffic conditions are generated ahead, traffic diversion decisions are made, and the ETC information publishing platform distributes the information to designated RSUs according to the publishing strategy. The RSU then publishes the information to the OBU for broadcasting and guidance to drivers.

[0151] (9) In-vehicle signage: On specific road sections, traffic sign information (such as speed limit signs, sharp bends ahead, and other static information) is broadcast through the RSU to provide drivers with corresponding traffic sign reminders and ensure safe driving. The in-vehicle signage information supports configuration of sign type, sign location, etc., and is distributed to the RSUs on specific road sections through the ETC information release platform. The RSU releases the traffic sign information to the OBU to warn drivers and remind them to drive safely according to the current road section's driving requirements.

[0152] (10) Travel Information Services: On specific road sections, such as near service areas and toll stations, relevant service information will be released to passing vehicles, including but not limited to the service types of service areas, passenger flow, and queue length at toll stations. At the same time, guidance suggestions will be released to passing vehicles, including but not limited to lane guidance at toll stations and guidance at service areas.

[0153] In an embodiment of this application, an intelligent system for highway operation and service is provided. The intelligent scene service system in the intelligent system for highway operation and service includes: a service area video surveillance system, a passenger flow analysis system, a parking guidance system, a service area information release and query system, a broadcasting system, a WIFI system, and a smart toilet.

[0154] The service area video surveillance system establishes an integrated monitoring system through the construction and optimization of video resources, enabling global three-dimensional monitoring of the entire area in a single view, detailed monitoring display in separate views, automatic video patrol monitoring, and intelligent analysis. Panoramic cameras and high-definition remote-controlled cameras are installed in the service area, while dome cameras are installed indoors and in underground passages to monitor the entire service area. The passenger flow analysis system collects passenger flow information within the service area's main building using passenger flow detection cameras deployed in the main building and throughout the service area, supplemented by WiFi probes (AP nodes). The required field equipment for the passenger flow analysis system includes passenger flow detection cameras and wireless APs. This information is used to collect passenger flow information within the service area's main building, including passenger composition, density, path, and distribution, and provides visual displays. This assists in functions such as analyzing consumer habits, determining congestion levels, managing merchant passenger flow, predicting large-scale events, tracking personnel, and managing service area employees, and provides a data foundation for the intelligent energy dispatch system.

[0155] The parking guidance system utilizes high-definition cameras and information display screens installed in the service area to monitor parking spaces, identify vehicle entry, and provide parking guidance. Intelligent analysis of video images from service area plaza cameras collects parking information, including vehicle occupancy, entry time, departure time, and dwell time. Parking space signs at the service area entrance and parking guidance screens within the service area provide predictive information on available parking spaces for vehicles on the main route and guidance on parking zones and availability for vehicles already in the service area. This alleviates uneven parking flow, reduces vehicle dwell time, and improves parking turnover rate within the service area.

[0156] The service area information dissemination and inquiry system consists of information display screens and touch screen kiosks, providing travelers with information on highway traffic conditions and service information for various areas within the service area through a simple and clear interactive interface. Information display screens are installed in front of the main buildings on both sides of the service area, disseminating information on road traffic policies, road conditions, weather, tourist resources, and traffic control to those resting there. Touch screen kiosks on both sides of the service area offer services such as highway route inquiries, road condition inquiries (including accident locations and congestion levels), weather inquiries, and information on nearby tourist attractions and restaurants, all displayed in graphic and textual format. The service area broadcasting system uses digital voice broadcasting technology to play emergency broadcasts, business broadcasts, and paging broadcasts, promptly announcing important and urgent information, and providing background music broadcasts for public areas and functional rooms within the service area.

[0157] The broadcasting system consists of a broadcast control console and speakers. Full Wi-Fi coverage is provided throughout the service area, offering wireless internet access and location services to staff and drivers entering the area. Indoor access points (APs) are deployed in office buildings to provide wireless network access; outdoor APs (APs) are deployed in outdoor public areas. Smart restrooms utilize various sensors to collect real-time equipment usage information and environmental parameters, effectively monitoring and adjusting the environment and equipment in the service area restrooms. Information dissemination, odor detection, and sterilization / deodorization technologies enhance the user experience in the restrooms. A smart restroom (also known as a smart toilet) refers to a restroom system that includes air purifiers, information boards, odor sensors, smoke sensors, toilet stall occupancy indicators, and door magnetic sensors. It can achieve functions such as odor detection, sterilization / deodorization, toilet stall information dissemination, consumable monitoring, service management, and information transmission.

[0158] In one embodiment of an intelligent highway operation and service system proposed in this application, the smart toll station consists of a toll station-level system, a toll lane system, and a ramp pre-transaction system. The toll station-level system adopts a star-shaped open network structure and is equipped with computing and storage devices, network devices, network security devices, etc., with computing and storage implemented using cloud computing technology.

[0159] The intelligent toll station system centrally controls all ETC lane equipment and ramp pre-transaction system equipment through standardized toll station lane equipment interface specifications, eliminating the need for lane industrial control machines in ETC lanes and ramp pre-transaction systems.

[0160] The toll station-level system includes a station-level transaction system and a station-level management system.

[0161] (1) Station-level trading system: The station-level trading system is divided into a basic support subsystem and a trading service subsystem.

[0162] The basic support subsystem mainly includes functions such as parameter management, lane logic control, lane peripheral control, remote monitoring, list service, log generation, data transmission, and billing service; the transaction service subsystem mainly includes lane entry / exit transaction functions and centralized transaction processing functions of the ramp pre-transaction system.

[0163] (2) Station-level management system: The station-level management system has functions such as query service, ticket management, operation monitoring, shift handover management, data verification, data analysis, statistical reports and access control for toll stations.

[0164] The toll lane system refers to the construction of a reduced-staff, narrow-island toll lane system at toll stations with low traffic volume, reducing the need for toll collectors and lowering operating costs. At toll stations with high traffic volume, the number of toll lanes is increased by narrowing the toll lanes, and these narrow-island lanes can be configured for unmanned operation, improving traffic efficiency while reducing operating costs. The toll lane system utilizes highly integrated, intelligent, and IP-based equipment.

[0165] In one embodiment of an intelligent highway operation and service system proposed in this application, the cloud control center's architecture is divided into four layers and two systems: the four layers are the infrastructure layer, the infrastructure service layer, the digital platform layer, and the application system layer. The infrastructure layer and infrastructure service layer correspond to the Infrastructure as a Service (IaaS); the digital platform layer corresponds to the Platform as a Service (PaaS); and the application system layer corresponds to the Application Software as a Service (SaaS). The two systems, namely the security management system and the operation and maintenance management system, permeate all four layers, providing crucial guarantees for system security and operational management at each layer.

[0166] In one embodiment of an intelligent highway operation and service system of this application, the integrated management and control platform includes functional modules such as real-time monitoring and early warning, traffic operation status assessment, traffic situation analysis and forecasting, automatic weather monitoring and early warning, intelligent proactive management and control, and comprehensive information travel services. This provides managers with scientific and accurate data for analyzing, judging, and making decisions about traffic conditions, ensuring traffic safety and improving traffic efficiency. Specific details are as follows: (1) Real-time monitoring and early warning: The real-time monitoring and early warning subsystem realizes comprehensive monitoring and early warning of road traffic from four perspectives: road, objects, events, and vehicles. Through cameras, vehicle detectors, meteorological detection equipment, ETC antennas, infrastructure health monitoring equipment, etc. deployed on the roadside, data such as traffic volume, vehicle speed, traffic events, road construction, blockage information, and meteorological information along the highway are collected. Through processing and analysis by the cloud control center, supplemented by monitoring video information, real-time online monitoring of various traffic equipment and infrastructure and monitoring and early warning of highway traffic flow, traffic events, and traffic environment are realized.

[0167] (2) Traffic Operation Status Assessment: The traffic operation status assessment subsystem mainly constructs a highway operation status assessment index system and comprehensive assessment method. Based on the intelligent sensing data such as traffic flow detection equipment, video cameras, road surface condition detection equipment, and visibility detection equipment accessed by the cloud control center, and fully combines the ETC data of this road section and adjacent road networks, it completes the analysis and calculation of indicators such as traffic operation interruption rate, congestion, saturation, traffic characteristic index, and traffic weather index through in-depth data analysis and mining. It realizes the comprehensive assessment of the traffic operation status of the highway at different times and provides managers with an intuitive display of the traffic status at all times.

[0168] (3) Traffic Situation Analysis and Forecasting: Through ETC data of this road section and adjacent road networks, functions such as historical statistics of road network situation, real-time monitoring of road network situation, and future forecasting of road network situation are realized. From micro, meso and macro perspectives, long-term and short-term traffic flow forecasting, congestion forecasting, traffic flow forecasting under holidays and severe weather scenarios are realized in multiple modes, providing managers with comprehensive, accurate and efficient data resources for implementation of control; based on traffic situation inference algorithms, the spatiotemporal impact range of traffic flow is determined, providing support for highway operation management departments to make scientific decisions; on this basis, through reasonable threshold settings, timely warnings are given for possible or impending emergencies, and effective measures are taken through reasonable analysis for different warning levels to realize daily operation management and coordinated scheduling.

[0169] (4) Automatic meteorological monitoring and early warning: The automatic meteorological monitoring and early warning function module (including early warning and forecast model), meteorological detection equipment, and traffic incident detection integrated machine (optional) constitute the automatic meteorological monitoring and early warning system.

[0170] (5) Intelligent active control: The intelligent active control function module (including traffic control strategy algorithm), field sensing equipment, and information release equipment constitute the lane-level active control system.

[0171] (6) Integrated Information Travel Service: The integrated information travel service enables unified monitoring, dissemination, and management of all information dissemination devices. Based on information collected along the route, including road conditions, emergencies, construction, roadside conditions, weather, and environment, as well as internet traffic information data, and combined with vehicle location and terminal type, the cloud control platform uniformly plans the information content and disseminates traffic information through variable message signs, broadcasts, and mobile terminals along the road, realizing vehicle guidance and travel assistance information push. The pushed information should include information on highway infrastructure, service facility status, travel planning, traffic operation status, traffic emergencies, highway construction and maintenance, highway meteorological environment, emergency rescue, safe driving assistance, tunnel passage, and service area toll station operation, etc. The integrated information travel service provides drivers with safer, more convenient, and more reliable integrated road network travel information services in a timely manner.

[0172] The road segment platform in the intelligent highway operation and service system provided in this application can realize functions such as historical statistics of road network status, real-time monitoring of road network status, and future prediction of road network status through ETC data of the current road segment and adjacent road networks. It achieves multi-mode prediction from micro, meso, and macro perspectives, including short- and long-term traffic flow prediction, congestion prediction, and traffic flow prediction under holiday and severe weather scenarios, providing comprehensive, accurate, and efficient data resources for management personnel to implement control measures. Based on traffic situation extrapolation algorithms, it determines the spatiotemporal impact range of traffic flow, supporting highway operation management departments in making scientific decisions.

[0173] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to the embodiments of this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A highway operation and service intelligent system, characterized in that, The application relates to a highway ETC system, which comprises a road section platform, a regional platform and a road network platform. The road section platform is used for collecting and summarizing various types of sensing data of a corresponding highway road section based on an ETC system to obtain system service data, performing safety event identification, road section hidden danger early warning, road section operation analysis and traffic information and event information extraction on the system service data based on an edge computing mode, uploading the traffic information and event information to a regional platform to which the road section platform belongs, and publishing travel information, safety early warning information, traffic guidance information and vehicle-road cooperation information in the highway road section. The regional platform is used for summarizing traffic information and event information of each road section platform based on a pre-constructed provincial data resource pool to obtain corresponding regional summary data, uploading the regional summary data to a road network platform to which the regional platform belongs, performing provincial road network operation state prediction, road network hidden danger early warning, cross-road section information publishing and cross-provincial information sharing based on the road network platform on a corresponding region of the regional platform. The road network platform is used for summarizing regional summary data uploaded by each regional platform in a highway road network based on a pre-constructed whole-network data resource pool, storing the data based on a block chain to realize data sharing between the regional platforms, and performing operation service quality evaluation on each regional platform and each road section platform based on a pre-constructed intelligent level index system.

2. The intelligent highway operation and service system of claim 1, wherein, The road section platform comprises a road section platform business system, a model center, a data center, a cloud control center, a fusion communication layer and an infrastructure layer. The regional platform comprises a regional platform business system, a model center, a data center, a cloud control center and a fusion communication layer. The infrastructure layer comprises an edge computing module and a roadside device module. The edge computing module is used for summarizing various types of sensing data of a highway road section collected by the infrastructure layer to obtain system service data, and performing safety event identification, road section hidden danger early warning, road section operation analysis and traffic information and event information extraction on the system service data based on an edge computing mode. The roadside device module is used for collecting vehicle operation data of the highway road section based on an ETC system, a video collection device and a radar, collecting weather environment data of the highway road section based on a grating sensor, and publishing travel information, safety early warning information, traffic guidance information and vehicle-road cooperation information in the highway road section based on an on-board unit (OBU). The data center is used for storing structured data and monitoring video data collected by the infrastructure layer based on a data resource pool. The model platform is configured to store an algorithm library and a business model library, and the algorithm library is configured to store mathematical models of data mining, algorithms, visual AI algorithms, machine learning algorithms, event recognition algorithms, running trend analysis algorithms, meteorological analysis algorithms, and digital twin algorithms; The cloud control center in the road segment platform is configured to connect the road segment platform business system, the model platform, and the data center, and connect the road segment platform and the regional platform; and the cloud control center in the regional platform is configured to connect the regional platform business system, the model platform, and the data center, and connect the regional platform and the road network platform; The fusion communication layer is configured to receive data from the infrastructure layer and send data from the fusion communication layer to the cloud control center.

3. The intelligent highway operation and service system of claim 2, wherein The road side device module includes a video monitoring unit, an ETC vehicle feature recognition unit, a traffic parameter perception unit, a traffic event perception unit, a traffic environment perception unit, an infrastructure health monitoring unit, and a key area monitoring unit, which are connected to the cloud control center based on the fusion communication layer; The video monitoring unit is configured to collect vehicle operation data in the highway road segment based on a video monitoring system of the highway road segment, a drone video monitoring device, and a vehicle-mounted mobile video monitoring device; The ETC vehicle feature recognition unit is configured to identify vehicle features of vehicles in the highway road segment based on a license plate recognition device of an ETC gantry; The traffic parameter perception unit is configured to collect traffic parameters of the highway road segment based on a traffic control station; The traffic event perception unit is configured to monitor traffic events of the highway road segment based on a video monitoring system of the highway road segment and a millimeter wave radar; The traffic environment perception unit is configured to collect weather environment data of the highway road segment; The infrastructure health monitoring unit is configured to monitor the health of bridges, tunnels, and high slopes in the highway road segment; The key area monitoring unit is configured to monitor traffic events in preset key areas of the highway road segment based on an ETC gantry system.

4. The highway operation and service intelligent system according to claim 3, wherein, The key areas include tunnels with a length exceeding a preset length threshold, road segments with traffic flow exceeding a preset flow threshold, predetermined accident-prone road segments, predetermined severe weather-prone road segments, service area hazardous goods monitoring and early warning areas, and toll stations.

5. The intelligent highway operation and service system of claim 3, wherein, The road segment platform business system includes an all-weather passing system, a digital management and control system, and a public travel service system; The all-weather passing system includes a meteorological automatic monitoring and early warning module; Correspondingly, the traffic environment perception unit includes a grating sensor, a meteorological detector, a visibility detector, and a road surface state detector corresponding to the meteorological automatic monitoring and early warning module; The model platform is configured to perform road traffic meteorological early warning detection on weather environment data collected by the grating sensor, the meteorological detector, the visibility detector, and the road surface state detector based on at least one of the preset visual AI algorithm, the machine learning algorithm, the event recognition algorithm, and the meteorological analysis algorithm. The cloud control center is configured to generate meteorological warning and forecasting information for the expressway section according to the corresponding detection result of the road traffic meteorological warning detection, and send the meteorological warning and forecasting information to an on-board unit (OBU) in a vehicle in the expressway section based on the fusion communication layer, so as to publish the meteorological warning and forecasting information in the expressway section based on the OBU.

6. The intelligent highway operation and service system of claim 5, wherein, The quasi-all-weather traffic system further comprises a driving safety guiding module. Correspondingly, the roadside equipment module further comprises a driving safety guiding device corresponding to the driving safety guiding module. The driving safety guiding device comprises a node control host and an intelligent guiding lamp connected to the node control host. The node control host is configured to control the intelligent guiding lamp to display light in different colors and / or flashing modes according to the received different mode functions, wherein the mode functions include a standby state, a road contour strengthening mode function, a driving active guiding mode function, and a rear-end collision prevention warning mode function.

7. The highway operation and service intelligent system of claim 6, wherein, The quasi-all-weather traffic system further comprises an intelligent ice-melting and snow-removing module. Correspondingly, the roadside equipment module further comprises a road surface information acquisition subsystem, a spraying subsystem, and a sub-control system corresponding to the intelligent ice-melting and snow-removing module, wherein the sub-control system and the cloud control center jointly constitute a processing control subsystem corresponding to the intelligent ice-melting and snow-removing module. The road surface information acquisition subsystem is configured to acquire road surface state information and temperature information of the expressway section. The spraying subsystem is configured to perform proportioning and spraying of a spraying agent on the expressway section according to an instruction of the processing control subsystem.

8. The intelligent highway operation and service system of claim 5, wherein, The digital management and control system comprises a lane-level active management and control system, a split-merge zone safety warning system, and a key operating vehicle management and control system. The lane-level active management and control system is configured to automatically adjust lane management and control measures based on a preset traffic control strategy and control a variable information sign to change image display according to acquired expressway traffic flow, traffic events, and meteorological environment information. The split-merge zone safety warning system is configured to generate safety warning information for unstable vehicle speed, poor visibility, ramp congestion, continuous lane changing of vehicles, vehicle parking in a flow guide zone, vehicle lane changing when passing through a lane-changing area, vehicle reversing when passing through a split-merge port, vehicle emergency braking, and temporary parking for passengers at a split-merge zone of the expressway section, and publish the safety warning information based on a preset integrated safety warning device of the split-merge zone. The key operating vehicle management and control system is configured to perform real-time dynamic supervision on a predetermined key operating vehicle to acquire vehicle information, a running track, and a historical driving route range, time period, and frequency of the key operating vehicle running on the expressway section, and determine whether the key operating vehicle travels according to a prescribed route, and if not, generate corresponding abnormal state warning information to publish the abnormal state warning information based on an OBU in the key operating vehicle.

9. The intelligent highway operation and service system of claim 5, wherein, The public travel service system comprises a roadside device information publishing system, an ETC-based vehicle-road cooperation service system, an Internet information publishing system and a smart scene service system. The roadside device information publishing system is configured to publish information issued by the cloud control center. The ETC-based vehicle-road cooperation service system is configured to publish information issued by the cloud control center based on an ETC gantry and an on-board unit (OBU). The Internet information publishing system is configured to send information published by the cloud control center to Internet devices that pass authentication and authorization based on a unified external interface. The smart scene service system is configured to control information publishing devices in a service area to publish information issued by the cloud control center.

10. The intelligent highway operation and service system of claim 9, wherein, The smart scene service system comprises a service area video monitoring system, a passenger flow analysis system, a parking guidance system, a service area information publishing and query system, a broadcasting system, a WIFI system and a smart toilet.

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