61 results about "Traffic diversion" patented technology

The invention provides a real-time warning condition data processing method and system based on edge calculation, and relates to the technical field of traffic management, which comprises the steps of collecting traffic warning condition original data, transmitting the data to a nearby edge server in real time, constructing a lightweight deep learning model on an edge side, generating a traffic situation prediction result, and simultaneously, combining police force information to obtain a real-time warning condition prediction result. And constructing a police deployment optimization matrix, uploading the matrix to the cloud platform, generating a traffic optimization strategy, and issuing the traffic optimization strategy to the edge computing node of the accident area. The method can improve the integrity and timeliness of accident information perception, optimizes the police resource distribution and traffic dispersion decision, and remarkably enhances the intelligence and cooperation capability of traffic accident emergency management.

The invention discloses an expressway reconstruction and extension traffic diversion method, system and device and a medium, and the method comprises the steps: obtaining multi-source dynamic traffic data, and constructing a road network origin-destination matrix through data fusion and demand deduction; a traffic flow distribution result is obtained by constructing a system optimal traffic distribution model; identifying the first congestion time period, and calculating the traffic flow exceeding the residual traffic capacity in the congestion time period to obtain the traffic flow to be shunted; solving an optimal shunting path under the target of minimizing the total travel time of the system through a hybrid intelligent algorithm to obtain an optimal shunting path scheme; and verifying the optimal shunting path scheme by using microscopic traffic simulation software, updating traffic data based on a simulation result, and carrying out iterative optimization to obtain a differentiated traffic organization scheme. According to the invention, the traffic flow passing efficiency during the highway reconstruction and extension period is effectively improved.

The invention relates to an expressway traffic flow prediction and accident identification method and system, and relates to the technical field of intelligent detection, and the method comprises the steps: firstly, carrying out the real-time monitoring of an expressway through a mobile robot, obtaining the traffic flow feature data, and obtaining the traffic flow prediction data of a specified time period through feature extraction analysis and fusion; and then, according to the traffic flow prediction data and traffic flow data acquired in real time, accident identification and accident grading are carried out, when an accident on the highway is identified, dynamic path planning is carried out by using an algorithm and combining the data identified in real time, and based on the planned path, the mobile robot is controlled to execute a dredging task on the lane of the highway. Through robot automatic monitoring and an intelligent algorithm, whole-process unmanned operation of traffic flow prediction and accident identification and disposal is realized, manual intervention is reduced, the monitoring efficiency and the safety of workers are improved, and the operation cost is reduced.

The invention discloses a construction scene traffic diversion prediction system and method based on a digital twinborn technology, and belongs to the technical field of intelligent traffic. A data acquisition module acquires historical traffic flow data, road network data around a construction area and data of a plurality of use sensors deployed in the construction area; the feature extraction module performs time dimension extraction on historical flow data to obtain a time dimension sequence and a trip chain sequence, the flow prediction module trains a traffic flow prediction model, predicts future traffic flow by using the trained model, updates a pre-constructed digital twinborn model according to prediction data, and obtains a traffic flow prediction result; and a traffic diversion strategy is formulated. Prediction is carried out based on real-time flow data and vehicle data, the time dimension and the space dimension of the real-time flow data are combined, real-time dynamic accurate prediction is achieved, meanwhile, the digital twin model is adopted to carry out visual display on field data, and the digital twin model is dynamically updated in real time based on environment data and the flow data.

The invention belongs to the field of intelligent traffic, and particularly relates to a construction area traffic flow guiding and speed cooperative control system which realizes accurate traffic flow control through cooperative operation of an area sensing module, a distributed guiding module, a communication module and an emergency response module. The area sensing module is based on three-dimensional modeling and digital twinning technologies, fuses real-time traffic flow, vehicle states and environment data, and constructs a three-dimensional simulation space of a target area; the distributed guide module establishes a drainage control model by using a distributed reinforcement learning algorithm, dynamically optimizes a sub-region congestion control strategy in combination with a vehicle-road-cloud three-level communication node, and adjusts the acceleration and speed of a vehicle in real time; and the emergency response module rapidly generates an emergency instruction through an anomaly analysis algorithm and a strategy library and feeds back the emergency instruction to the guide model to solve an emergency abnormal event, and the application integrates multi-source data real-time sensing, distributed decision optimization and a multi-stage communication architecture, and realizes dynamic traffic flow distribution and intelligent traffic control in a construction area.

The utility model belongs to the technical field of traffic equipment, and discloses a traffic flow guiding device which comprises stand columns and a cross rod, the stand columns are fixedly installed on the two sides of the cross rod respectively, a plurality of cylinders are rotatably installed on the cross rod through damping bearings, box bodies are arranged outside the cylinders respectively, through grooves are formed in the two sides of the box bodies respectively, and the through grooves are communicated with the through grooves. A box body is fixedly installed at the bottom of the cylinder through a support, second through grooves are formed in the two sides of the box body respectively, a motor is fixedly installed in the box body, gear columns arranged in the second through grooves are arranged on the two sides of the motor respectively, and the gear columns are rotationally installed on the box body respectively; according to the device, the height limiting height of each lane can be flexibly adjusted according to actual requirements, traffic accidents caused by collision between a vehicle and equipment can be reduced, and the device is safer to use.

This application discloses a highway traffic diversion alarm broadcasting system and method based on AI recognition, relating to the field of highway diversion technology. This application analyzes the load of each vehicle and the driving experience, historical highway violations, and historical highway accidents of each driver to divert vehicles, diverting high-risk vehicles to safer highways, thereby ensuring vehicle safety. Different safe following distances and speeds are set for different highways to avoid traffic accidents caused by excessively close following distances or excessive speeds. Furthermore, the system monitors all vehicles traveling on each highway, broadcasting warnings when accidents or violations are detected, which enhances deterrence against drivers and prevents repeated violations from leading to traffic accidents.

The invention specifically relates to a 4g highway intelligent traffic road condition monitoring system, and relates to the technical field of intelligent traffic. A data processing and analyzing module; a central management and scheduling module; and an information issuing module. According to the invention, a plurality of devices such as a microwave radar, a camera, a meteorological sensor and the like are arranged in the data acquisition module, so that multi-dimensional data such as traffic flow, vehicle states, environmental meteorology and the like can be acquired in an omnibearing manner; the data is deeply mined through the data processing and analyzing module, and congestion prediction, accident early warning and flow pre-estimation are realized by using algorithms such as LSTM (Long Short Term Memory) and Transform; in the peak period of festivals and holidays, a traffic dispersion scheme can be planned in advance based on historical data and flow prediction of real-time road conditions.

The utility model provides an expressway traffic diversion device which comprises a fixed base, supporting columns fixedly connected to the two sides of the top of the fixed base, and a warning board fixedly connected to the tops of the supporting columns, and is characterized in that an LED lamp screen is fixedly connected to the top of the warning board, a mounting plate is fixedly connected to the surface of the bottom of the fixed base, and the LED lamp screen is fixedly connected to the mounting plate. An anti-impact assembly is fixedly connected to the surface of the mounting plate, an anti-collision assembly is fixedly connected to one end of the anti-impact assembly, the anti-impact assembly can be in linkage with the anti-collision assembly, the anti-collision assembly prevents the whole device from being influenced by slight collision through the structure of the anti-collision assembly, and meanwhile when a vehicle running at a high speed collides, the anti-collision assembly is prevented from being collided. In addition, the anti-impact assembly can prevent fragments from being generated through collapse of the internal structure of the anti-impact assembly, the device is protected while most impact is absorbed, secondary damage caused by fragment splashing is prevented, and therefore the functionality and safety of the device are further improved.

The invention discloses a high-performance network flow refined shunting method and system. The system comprises a flow collection module, a flow analysis and classification module, a strategy matching module and a flow shunting module. The traffic acquisition module directly captures original traffic through a user mode network driver, and distributes the original traffic to a plurality of CPU processing units based on RSS (Received Signal Strength); the flow analysis and classification module performs first-level protocol classification on collected original flow, identifies basic protocol types, extracts key fields of message headers, extracts the extracted key fields of the headers according to the extracted key fields of the headers to further identify application layer protocol types, extracts load parts of the messages to perform feature library matching, and further identifies specific application classification. If the specific application classification cannot be determined, enabling the current message to enter a secondary classification process; the strategy matching module is used for matching a preset shunting strategy in the system according to the protocol classification result, and determining a flow forwarding processing path according to an output port specified by the current strategy; and the flow shunting module forwards the flow hitting the preset shunting strategy to an output port. According to the invention, high-precision, high-efficiency and extensible protocol shunting can be realized.

1. Name of the product in this design: Tidal Robot. 2. Purpose of this design: This design is used for dynamic traffic management, allocating lanes in roads to achieve traffic diversion. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: 3D view 1. 5. The bottom surface of this product is a part that is not easily seen or cannot be seen during use, so the bottom view is omitted.

The application discloses a kind of wisdom car flow trajectory optimization method and system based on AI vision analysis, it is related to intelligent traffic control technical field, the present application is by fusing city-level AI vision perception network and emergency vehicle real-time state data, constructs the dynamic decision dataset of whole element, high precision, provides reliable basis for traffic scheme formulation;The present application is by asymmetric phase compensation, safety redundancy constraint and fast phase recovery mechanism, the influence of signal adjustment is accurately controlled in necessary space-time range.Combining the hierarchical induction strategy from far to near, effectively guide the peripheral traffic diversion, avoid the secondary congestion caused by emergency traffic in a large range, long time, maintain the overall operation efficiency of road network.The present application constructs complete perception-decision-execution-feedback closed-loop control system, ensure the continuous and reliable of emergency corridor under changing environment, guarantee the uninterrupted execution of emergency task.

This application relates to the field of deep foundation pit construction technology, and particularly to a method for constructing deep foundation pits in a subway transfer node area. The transfer node area includes an enlarged section, a pipeline relocation section, and a main connecting section. A temporary partition is set on the side of the main connecting section to separate the transfer node area from the main section of the first subway line. The enlarged section adopts a concrete support system, while the pipeline relocation section and the main connecting section adopt a hybrid support system of concrete and steel supports. The deep foundation pit construction method includes: Step S1: Traffic diversion and pipeline relocation; Step S5: Foundation pit excavation and support: The foundation pit excavation and support adopts a combination of vertical layering and longitudinal segmentation. The longitudinal segmentation sequence is the enlarged section, the main connecting section, and the pipeline relocation section. When excavating and supporting the foundation pit of the pipeline relocation section, the temporary partition at the corresponding depth is removed simultaneously to avoid idle work and greatly shorten the overall construction time.

The present invention provides a method, system, device, computer-readable storage medium, and electronic device for secure access control of DNS resolution. The method comprises: configuring a traffic diversion strategy and a secure resolution strategy for domain name resolution requests for a target user via a cloud security management platform, sending the traffic diversion strategy to a secure access service edge node and a target terminal corresponding to the target user, respectively, and sending the secure resolution strategy to the secure access service edge node; the target terminal sending the domain name resolution request to the corresponding secure access service edge node according to the traffic diversion strategy; and the secure access service edge node performing resolution control on the target domain name to be resolved in the domain name resolution request from the target terminal according to the secure resolution strategy provided by the cloud security management platform. Through the present invention, a new and efficient secure management mode for domain name access is realized.

The invention discloses a cross-border traffic drainage method and device, a medium and equipment, and the method comprises the steps: obtaining a domain name in a DNS request message sent by an intranet gateway of a client through an SDWAN CPE gateway; judging whether a domain name corresponding to the cross-border service matched with the domain name in the DNS request message exists in an overseas domain name white list or not; under the condition of matching, forwarding the DNS request message to an overseas DNS server, and receiving a domain name in a returned DNS response message; judging whether a domain name corresponding to the cross-border service matched with the domain name in the DNS response message exists in an overseas domain name white list or not; and under the condition of matching, generating a host route according to the destination IP address of the DNS response message, and distributing the host route to a plurality of intranet gateways, so that when the client accesses the destination IP address again, overseas service traffic is forwarded to the SDWAN CPE gateway through the intranet gateways.

This invention relates to the fields of intelligent transportation and road construction management technology, and particularly to a multi-scale traffic operation state prediction method and system. The invention achieves high-precision traffic state prediction by constructing a three-layer spatial topology architecture, designing and building a dual-flow independent LSTM architecture, and establishing a recursive rolling and interactive input mechanism. Under complex conditions such as lane closures, temporary traffic diversions, and perception blind spots, this invention, based on a hierarchical spatial perception system and a dual-flow deep temporal model, can perform high-precision short-term predictions of micro, meso, and macro traffic states, providing decision support for lane-level refined management and control in construction areas.

The invention discloses a flow distribution method, a storage medium and electronic equipment. The method comprises the following steps: acquiring a first request message; performing conversion processing on the first request message to generate an accompanying data packet; in the process of transmitting the accompanying data packet by the service calling link, generating a target routing rule based on the accompanying data packet by using a service grid agent corresponding to each application service in the service calling link; and routing the first request message to a target workload of the target application service according to the target routing rule. According to the method and the device, the technical problems that the routing accuracy is poor and the request routing cannot be accurately controlled through the dynamic routing coverage metadata when the flow distribution is carried out in the service grid in the related technology are solved.

The invention relates to the technical field of traffic control, in particular to an intersection traffic control method and system based on vulnerable group passage optimization. When the traffic light is in a green light state, vehicles pass, pedestrians wait at the two sides of the pedestrian path, the identification module obtains human body characteristics and modes of the pedestrians at the two sides of the path at the moment to identify whether vulnerable pedestrians exist or not, and if the vulnerable pedestrians exist, the identification module marks the vulnerable pedestrians as first vulnerable pedestrians and determines vulnerability labels and levels of the vulnerable pedestrians; and the control module determines a delay coefficient according to the delay coefficient, and prolongs the duration of the traffic light in the red light state next time according to the delay coefficient, so that the first vulnerable pedestrian has more passing duration. Besides, in order to avoid corresponding traffic flow congestion caused by red light delay, cloud and dynamic adjustment can be carried out on flow dredging of the original traffic flow based on flow dredging compensation delay increment of the downstream intersection, a more humanized traffic environment can be constructed in an aging structure, and the method has remarkable social benefits.

The application provides a slice division method and system based on a passive optical network architecture, the method comprising: performing global slice division on a network undirected graph based on a traffic matrix of the network undirected graph to obtain a plurality of subgraphs, wherein the network undirected graph comprises nodes and edges connecting the nodes, the nodes represent optical network units, the edges and weights of the edges represent communication relationships and traffic between the optical network units respectively, the subgraphs and the number of optical line terminals are the same, and the traffic matrix comprises traffic between the optical network units; performing local search optimization on each subgraph based on weights of edges connecting each node in the subgraph to obtain a target subgraph with minimized cut value, so as to output a plurality of target slices, wherein the cut value is obtained based on the weights of the edges connecting each node in the corresponding subgraph, and the target slice comprises the optical line terminal and a plurality of optical network units in the corresponding subgraph connected by the target subgraph. The application can improve the traffic diversion efficiency of the access network.

This invention relates to the field of road construction technology and discloses a reverse-construction cut-and-cover method for converting a highway into a bridge. The method includes the following steps: construction preparation and half-width closure, integrated pile-column construction, cap beam and superstructure construction, traffic diversion, reverse-construction cut-and-cover of the soil under the bridge, pier appearance treatment, and repeated construction. This invention directly constructs an integrated pile-column structure on the existing road surface, completely eliminating the need for deep foundation pit excavation (over 9 meters). It transforms high-risk deep foundation pit projects into low-risk shallow foundation pit projects, effectively avoiding safety accidents such as foundation pit collapse and roadbed slippage. Simultaneously, it eliminates the interference of deep foundation pit construction on adjacent highways, ensuring the safety of both construction personnel and passing vehicles.

The invention relates to the technical field of traffic dispersion, and particularly discloses an intelligent traffic dispersion system in urban reconstruction construction, which comprises four core modules: a road image acquisition module which is used for associating a road camera video with a corresponding road section position; the construction condition judgment module is used for identifying a construction area through video frame comparison and obtaining construction type, position and construction period information in combination with a project publicity network; the travel route adjusting module is used for dynamically generating a time-phased detouring strategy according to the construction position, the duration (including the buffer period) and the road occupation proportion; and the electronic map feedback module is used for pushing the bypassing instruction to the navigation map in real time. According to the method, the construction information is automatically identified, the traffic influence is pre-judged, and the bypassing scheme is generated in advance and synchronized to the electronic map, so that a driver can know the road condition in time before going out or during driving, vehicles are effectively shunted, sudden congestion is reduced, and the road traffic efficiency is improved.

The invention discloses a shunting gateway device and a diversion method, belongs to the technical field of network communication, and aims to solve the technical problems of how to reduce time delay and jitter caused by a shunting device during network change, improve the performance of the shunting device and finer-grained control, and effectively improve the shunting effect under a 5G network. According to the technical scheme, shunting gateway equipment is located between a base station and a 5G core network and is close to the base station side, and service data of all 5G terminals are forwarded to the 5G core network or a private cloud through the shunting gateway equipment; dividing the service data into uplink flow service data and downlink flow service data according to the flow direction of the service data; wherein the uplink traffic is service data sent to a destination address by the 5G terminal through a 5G base station and a shunt gateway device; the downlink flow is service data which is sent to the 5G terminal after the service response end requests to initiate from the service end and passes through the shunting gateway equipment and the base station.

The present invention relates to the field of adaptive network traffic diversion technology, and discloses an adaptive network traffic diversion method and system based on deep reinforcement learning, comprising: obtaining traffic data of heterogeneous networks, establishing a protocol fingerprint library, and converting data of different protocols into a unified network state feature vector; constructing a multi-agent reinforcement learning framework, including defining a state space, an action space, and a reward function, and optimizing the strategy of each agent based on differential games; using a meta-learning model to adjust the weight of each agent's reward function, and using deep reinforcement learning to train the multi-agent reinforcement learning framework to learn the optimal diversion strategy under different heterogeneous network conditions; deploying the trained strategy to a heterogeneous network environment, and dynamically selecting the optimal network path based on the current network state. This significantly improves the heterogeneous data processing capability.

This application relates to the technical field of subway construction and provides a construction method for the combined construction of a subway transfer passage and a subway section, including: pre-constructing open-cut stations at both ends, reserving conditions for a concealed excavation transfer between the open-cut stations; constructing reinforced concrete walls on the exterior of the main structure to form the main framework of the subway transfer passage and the subway section; after the exterior structure of the passage is completed, constructing the interior reinforced concrete walls; after the strength of the interior reinforced concrete walls and platform slabs reaches the design strength requirements, track laying operations are carried out within the subway section, and pipeline installation and decoration are carried out within the transfer passage. This optimizes passenger flow organization at the transfer station, effectively reduces early issues such as traffic diversion and pipeline relocation above the transfer passage, reduces the amount of civil engineering work and construction work area, enhances project feasibility, saves construction costs, and solves the problem of transfer passages not meeting open-cut construction conditions and unable to achieve platform-to-platform transfers.

The application provides a tidal flow network optical path planning method, manager, controller and system based on meta-learning, the method comprises the following steps: according to the traffic distribution data of the tidal flow network at the current time step, the retraining of the reinforcement learning intelligent agent is carried out for the initial optical path configuration strategy corresponding to the current time step, so as to obtain the optimal optical path configuration strategy corresponding to the current time step; and in the current time step, the initial optical path configuration strategy corresponding to the current time step is updated based on the meta-learning algorithm to obtain the initial optical path configuration strategy corresponding to the next time step; the optical path of the optical network layer corresponding to the tidal flow network is reconstructed based on the optimal optical path configuration strategy to update the topology structure of the IP layer corresponding to the tidal flow network. The application can reduce the time and energy consumption of the retraining of the intelligent agent, thereby improving the optical network management and control level, providing an effective solution for the traffic diversion of the tidal service, and improving the network service quality.

The application relates to a traffic diversion method based on a network element detection mechanism and related components, belongs to the network security technical field, and comprises the following steps: receiving and verifying configuration information; when the configuration information is successfully verified and a network element detection request is detected, a detection packet is encapsulated based on the configuration information, and the detection packet is sent to a target network element; the forwarding state of the target network element is determined according to the detection packet returned by the target network element; when the forwarding state of the target network element is detected to be a normal state, the diversion configuration of the target network element is issued, and traffic is introduced into the target network element; and when the forwarding state of the target network element is detected to be an abnormal state, the diversion configuration of the target network element is deleted. The application can monitor the network element state, adjust the traffic diversion strategy in time while diverting the traffic, realize traffic escape, and guarantee the stability of services.

The utility model relates to the technical field of diversion equipment, and discloses an equipment moving trolley for intelligent traffic diversion, which comprises a trolley body, the top of the trolley body is fixedly connected with a storage mechanism, and the left side of the storage mechanism is fixedly connected with an operating mechanism; the operating mechanism comprises a T-shaped frame, the T-shaped frame is arranged at the left end of the top of the vehicle body, racks are fixedly connected to the front end and the rear end of the T-shaped frame respectively, limiting groove bases are slidably connected to the right sides of the racks, gears are connected to the surfaces of the racks in an engaged mode, and a positioning base is arranged on the right side of the T-shaped frame. According to the equipment moving trolley for intelligent traffic diversion, when a gear is driven to rotate and a long rod is correspondingly driven to rotate, an L-shaped cover plate is driven to rotate, and the top of the L-shaped cover plate is opened towards the two sides, so that diversion equipment can be opened and correspondingly used, and the equipment moving trolley is convenient and rapid to operate and high in practicability. And the flow guide equipment can be conveniently protected.

The present invention discloses a construction method for an ultra-shallow buried, large-span, underground excavation subway station. The method comprises first excavating an open excavation pit to the underground excavation working surface and installing a pipe curtain. Then, according to design requirements, two side guide tunnels are excavated and side piles and crown beams are installed. Then, two middle guide tunnels are excavated and a secondary lining arch cover is installed. Then, the rock and soil under the arch cover is excavated and concrete and steel supports are erected to the bottom surface of the station tunnel. Finally, a cushion layer is poured, waterproof panels are laid, and the main structure is rebuilt to close the gap. This construction method effectively solves the impact of pipeline relocation, traffic diversion, etc. on the road surface. Compared with the traditional side tunnel method and PBA construction method, the construction process is simpler, the support system is simpler, the amount of abandoned work is reduced, and the long-span structure and waterproofing quality are more easily guaranteed, thereby achieving the advantages of large construction space, high efficiency, short construction period, and low risk. Compared with the traditional arch cover method, the structure is buried at a shallower depth, the structural system is more stable, and the stratum applicability is wider.

The present application discloses a road traffic control method, device, equipment and storage medium, which relates to the field of traffic control technology. The method includes: obtaining road traffic information in the road traffic environment of the road to be controlled, the road traffic information including: road information, vehicle driving information and road condition index information; constructing a road traffic digital twin model based on the actual physical environment and road information of the road to be controlled; inputting the vehicle driving information and road condition index information into the road traffic digital twin model for simulation to determine the traffic flow information of the road to be controlled; generating a road traffic control strategy for the road to be controlled based on the traffic flow information, and performing road traffic control according to the road traffic control strategy. The application of the above technical solution solves the technical problem in the prior art that it is difficult and inefficient to conduct on-site traffic diversion by staff after road traffic congestion occurs.

The invention relates to the technical field of detection, and discloses a multi-detection-line cooperative control and resource dynamic optimization configuration system, which is characterized by comprising a real-time data acquisition module used for acquiring the equipment state, real-time load, to-be-detected vehicle information and historical detection data of each detection line; wherein the real-time data acquisition module comprises an equipment state sensor which is used for acquiring and detecting equipment operation parameters and fault early warning signals in real time; the license plate recognition and RFID dual-mode collector is used for acquiring the information and queuing track of a to-be-detected vehicle; and the edge computing node is used for preprocessing the acquired data, and the throughput is greater than or equal to 500fps. Through real-time data acquisition, edge preprocessing, cross-line shunting according to topology and load algorithms, emergency vehicles are preferentially scheduled; multi-objective optimization dynamic allocation resources, 10-minute one-change scheme and simulation are carried out; the three-dimensional billboard is used for monitoring and early warning, and the block chain storage evidence protection data is safe and traceable; edge-cloud collaborative voltage reduction is achieved, over 80% of loads are automatically shunted, the resource efficiency is improved by 30% +, the equal time is shortened by 40%, and the equipment utilization rate uniformity is improved by 25%.