25 results about "Road traffic management" patented technology

The invention relates to the technical field of road traffic management and maintenance, in particular to a method for configuring ice and snow removing and traffic keeping mechanical equipment in a regional road network, which comprises the following steps of: formulating a standard road section length standard for configuring ice and snow removing mechanical equipment; dividing the roads into different grades based on the requirements of unobstructed and unobstructed road maintenance of different road sections in the regional road network; corresponding ice and snow removing operation time limit requirements are provided according to different grades of roads and different snow conditions; according to the regional characteristics, selecting proper conventional ice and snow removing mechanical equipment types; determining the configuration number of ice and snow removing equipment based on the equipment operation parameters and the actual condition of the road; and in combination with different snow conditions and different grades of roads, an applicable ice and snow removal operation combination mode is calculated, and the number of operation combination tables is determined. According to the method, the configuration number of the equipment is determined by combining the operation parameters of the equipment with the actual condition of the road, so that the allocation of the equipment is more scientific and reasonable, the problem of resource waste is reduced, and the unobstructed and smooth capability of the road in winter is improved.

The invention discloses a BIM-based highway construction period traffic guide and change optimization system, and relates to the technical field of road traffic management. According to the BIM-based highway construction period traffic guide and change optimization system, traffic management in the construction period is dynamically adjusted in real time through space-time modeling, data fusion and optimization decision. The system generates a road network space-time model, matches vehicle trajectory data with lane space data, counts the number and speed of vehicles, and optimizes traffic flow. According to the optimization result, the system outputs the tailgating length, the number of lanes and the speed limit value and generates a corresponding control instruction and a speed limit issuing instruction, traffic management of the highway construction period is accurately optimized through space-time modeling and real-time data fusion based on BIM, the system can obtain vehicle track data in real time, the lanes and the speed limit strategy can be dynamically adjusted, and the speed limit efficiency is improved. Traffic delay in the construction period is minimized, and traffic safety and smoothness of a construction section are effectively guaranteed by generating an accurate lane control and speed limiting instruction.

The invention relates to the technical field of road traffic management, and particularly discloses a signal lamp fault monitoring and early warning method based on Internet data, which comprises the following steps: establishing a historical database, acquiring historical traffic characteristic data of an intersection, establishing a historical traffic characteristic database, and setting an early warning threshold value for each traffic characteristic data; performing data judgment and early warning, comparing the real-time traffic characteristic data of the intersection in the same time section with historical traffic characteristic data, and when any one of the real-time traffic characteristic data reaches an early warning threshold value, sending early warning information to a traffic management department; and fault processing: after the traffic management department receives the early warning information, the traffic management department sends a checker to check the fault, and if the fault check is true, the traffic management department arranges a maintainer to carry out fault maintenance processing. According to the signal lamp fault monitoring and early warning method based on the signal lamp data, the problems that signal lamp fault operation and maintenance are not timely and incomplete, cost is high and the like are effectively solved, and potential traffic safety hazards caused by signal lamp faults are reduced.

The invention relates to the technical field of road traffic management, in particular to a road site security monitoring system and method based on big data and artificial intelligence, and the method comprises the steps: collecting the data of a vehicle entering a target monitoring area according to a preset collection frequency, and monitoring the operation characteristics of the vehicle and the state characteristics of a driver through the vehicle data; based on the vehicle operation characteristics and the driver state characteristics, predicting the vehicle intrusion probability through a pre-trained danger early warning model, and generating corresponding alarm information; judging a vehicle intrusion mode, filtering alarm information, and extracting effective alarm information; after effective alarm information is obtained, a multi-mode grading alarm strategy is constructed, image data of a target monitoring area are fed back in real time, and an optimal risk avoiding path is generated.

The invention belongs to the technical field of road traffic management, and discloses a highway network vehicle running track operation method and system and a computer storage medium, and the method comprises the steps: collecting the running track data of a target vehicle based on satellite positioning; generating space vector information based on the moving trajectory data; on the basis of traffic characteristics of a road, encoding the moving trajectory data by using the spatial vector information to obtain a trajectory point vector code with a direction and a trajectory basic line segment code; according to the track point vector code and the track basic line segment code, executing preset road space vector operation to obtain an operation result; and constructing a road topological space according to the operation result so as to judge a road space relationship by utilizing the road topological space. According to the method, road space point locations, space relation judgment between road sections, road alignment study and judgment and the like can be realized based on operation, and the geographic position and the space relation of the road can be reflected more accurately.

This invention relates to the field of road traffic management technology, specifically disclosing an energy-recovery road lifting robot and its usage method. The robot includes a top plate, a bottom plate, a first inclined plate, and a second inclined plate. The top plate is positioned directly above the bottom plate, and the first and second inclined plates are located on either side of the top plate. A lifting mechanism is installed on the top of the bottom plate. A buffer support mechanism and a sliding mechanism are provided between the first and second inclined plates and the bottom plate. Power generation components are installed at the bottom of both the first and second inclined plates. Multiple ranging components are installed on the top of the bottom plate. Side holes are formed inside both the first and second inclined plates, and cleaning mechanisms are installed inside these side holes. In this invention, the ranging components, in conjunction with the lifting mechanism, can push the top plate upwards to a specified height, adapting to the height of different vehicle chassis. Simultaneously, as a vehicle runs over the robot, the power generation components generate electricity, achieving efficient recovery of the pressure potential energy from passing vehicles and reducing reliance on external power supply.

The utility model relates to the technical field of safety protection equipment, and discloses road traffic management information transceiving and safety protection equipment in a public network environment, which comprises a mainframe box, the mainframe box is provided with a hard disk installation area, a safety chip installation area and an edge computing card installation area, and the hard disk installation area is used for installing a solid state disk; the security chip installation area is used for installing a security chip, and the security chip carries out bidirectional identity authentication on a communication node of a traffic management department and other communication nodes through a cryptographic algorithm; the edge computing card installation area is used for installing an edge computing card, the edge computing card is used for carrying out safety monitoring on information receiving and sending periods of communication nodes and other communication nodes of a traffic control department, the security chip based on the national cryptographic algorithm is added, hard encryption of identity information of equipment is achieved, and the security of bidirectional identity authentication of the equipment is improved; and the edge computing card is added, so that the safety monitoring of information receiving and transmitting periods of communication nodes and other communication nodes of a traffic management department is realized, and the active prevention capability is improved.

The application provides a road traffic state detection method and device based on panoramic monitoring video analysis, at least two detection areas are configured on each road in a video picture; a real-time video stream is acquired, and the real-time video stream is decoded to obtain a video frame image; a detection tracking model is used for vehicle detection tracking on each detection area in the video frame image, to obtain vehicle detection tracking information in each detection area; the number of vehicles and the speed of vehicles in each detection area are calculated according to the vehicle detection tracking information in each detection area; the traffic state of each road is judged according to a preset judgment rule and the number of vehicles and the speed of vehicles in each detection area; wherein, the traffic state of each road reflects the current congestion situation of each road. The application scheme realizes the discovery of traffic congestion from a wider field of view, thereby assisting the road traffic management department to timely deal with traffic congestion events.

The invention belongs to the technical field of road traffic management, and provides a comprehensive traffic management system and method.The system comprises a dispatching platform, a plurality of unmanned aerial vehicles, intelligent street lamps, relay transmission equipment, a controller and traffic signal lamps; the unmanned aerial vehicle is connected with the scheduling platform to execute the instruction; the intelligent street lamps are arranged along the road, connected with the relay equipment, and used for collecting and analyzing road data and interacting; the relay equipment is connected with the scheduling platform and the controller to realize data transmission; the controller is connected with the traffic lights and controls operation of the lights according to platform instructions. The traffic lights are arranged at intersections to adjust traffic order. According to the invention, through cooperation of the scheduling platform and the relay transmission device, the intelligent street lamp, the unmanned aerial vehicle and the traffic signal lamp are connected to realize multi-device data closed-loop circulation; the intelligent street lamp has a data preprocessing capability, and does not need to upload all original data to a centralized platform, so that the processing pressure that data interaction depends on the centralized platform in the background technology is relieved.

The invention belongs to the technical field of road traffic management, and particularly relates to a moving vehicle height real-time detection method based on a two-dimensional laser radar, and the method comprises the following steps: S1, data collection: obtaining point cloud data through the scanning of the two-dimensional laser radar, two-dimensional laser radar equipment is installed at a preset height position, the scanning plane of the two-dimensional laser radar equipment is made to be perpendicular to the ground, a data receiving module is arranged to receive point cloud data sent by a laser radar through a UDP protocol and analyze the point cloud data, and each data packet comprises polar coordinate information of a plurality of distance measuring points; s2, data preprocessing: converting the point cloud data from a polar coordinate system to a rectangular coordinate system through a point cloud processing module; according to the method, high-precision vehicle height detection can be realized only by adopting the single-line two-dimensional laser radar, the equipment cost is remarkably reduced, the height measurement precision of the method is equivalent to that of expensive equipment in an actual detection scene, and the actual application requirement is met.

The utility model discloses a warning sign for road traffic management relates to traffic management technical field, including base, the top rotation of base is connected with support frame, and the top fixed connection of support frame has traffic warning sign body, and traffic warning sign body includes first sign body, second sign body, third sign body, and the inside of first sign body is established with first male slide groove, and the inside slide coupling of first male slide groove has first male sliding block, and first male sliding block is fixedly connected with second sign body, and the inside of second sign body is established with second male slide groove. The utility model has the beneficial effect that: the warning sign for road traffic management, through annular warning sign, is convenient for warning to multiple directions simultaneously, does not need to increase the number of warning sign extra, thereby saves the cost, and multiple sign body is the sliding type structure, and is fixed through magnetic metal strip and magnet layer, makes the warning sign collapsible or unfolding, is favorable for reducing the occupation to space when not using.

The invention relates to the field of road traffic management, in particular to a road weighing platform vehicle license plate shielding behavior dynamic tracking and evidence obtaining method. According to the method, multi-modal sensors such as a millimeter wave radar, a high-definition camera, a thermal imaging device and a laser radar are deployed, a hierarchical data processing system is constructed, vehicle driving data are collected in real time, and multi-dimensional verification analysis is carried out. When the system detects that a vehicle enters a weighing area, lightweight video preliminary screening is triggered, dual verification is carried out in combination with laser radar point cloud density analysis and thermal imaging temperature difference detection, and finally the shielding behavior is judged through a fusion judgment mechanism. The problems that a single sensor is high in misjudgment rate, low in recognition rate in a severe environment, incapable of forming a complete evidence chain and the like are solved, all-weather high-precision detection is achieved, and the law enforcement efficiency and the intelligent level are greatly improved.

This invention discloses an adaptive merging control method for intelligent connected vehicles, comprising the following steps: acquiring the initial speed of the merging vehicle, the initial speed of the vehicles in the convoy, and the position information of the merging vehicle and the vehicles in the convoy; acquiring road traffic management information; calculating the distance between the current position of the merging vehicle and all candidate merging positions; calculating the merging time required for each merging position based on the merging distance and speed and acceleration constraints; and evaluating each merging position considering both the merging time and merging distance, thereby enabling the vehicle to adaptively select the optimal merging position. This invention considers the speed and position relationship between the vehicle convoy and the merging vehicle, road speed limits, and vehicle comfort requirements, solves for the merging time of the vehicle merging into all candidate merging positions, and evaluates the candidate merging positions by comprehensively considering the merging distance and merging time, thereby enabling the merging vehicle to adaptively select the optimal merging position and improving vehicle merging efficiency.

The present application provides a traffic collision accident detection method, device and readable medium. The present application first obtains multiple road perception data of the road section to be detected; then determines the current collision accident type based on the intensity of the sound; finally, based on the current collision accident type, combined with the multiple road perception data, determines the accident information of the traffic collision accident. By coordinating the road perception data of multiple sensors, first determining the collision type based on the sound, and then combining all the road perception data to comprehensively judge whether it is a collision accident, the application solves the drawbacks of traffic flow comparison-based and video-based detection, and provides road traffic management departments with richer accident information to facilitate timely processing.

The present application relates to the field of vehicle monitoring, in particular to a vehicle driving data analysis system and method based on big data, comprising: a radar acquisition module, a signal identification module, a vehicle positioning module, a motion speed measurement module and a trajectory snapshot module, the radar acquisition module is used for building a radar acquisition platform and storing double-channel spectrum, the signal identification module is used for determining a vehicle target area, the vehicle positioning module is used for constructing a vehicle contour model, the motion speed measurement module is used for measuring the speed of a target vehicle, and the trajectory snapshot module is used for outputting a safe speed limit and snapshotting an overspeed target, the present application can improve the accuracy of vehicle detection and snapshotting, improve the accuracy and reliability of target identification, filter out radar noise, improve the signal-to-noise ratio, realize long-distance vehicle sensing, road trajectory modeling and road detection, avoid vehicle overspeed, assist in optimizing the driving path of the vehicle and improve the road traffic management capability.

The invention discloses a road vehicle overrun dynamic monitoring management method and system, and relates to the technical field of vehicle monitoring. The method comprises the following steps: firstly, on the basis of collected road vehicle data, synthesizing vehicle passing frequency of each specified road section area to obtain a whole road network flow thermodynamic diagram, and performing road traffic management; then, in the road traffic management process, according to the vehicle weighing data corresponding to the dispatching dynamic weighing section, in combination with the vehicle image identification data in the preset monitoring time period, carrying out overrun state monitoring, and finally, based on the overrun state monitoring result, in combination with the vehicle image monitored by the road network, carrying out road traffic management. Track monitoring is performed on the driving track of the specified vehicle, load and risk road sections are determined through traffic management, dynamic resource scheduling is realized, and meanwhile, the accuracy and reliability of overrun state monitoring are improved by combining cross validation of dynamic weighing data and vehicle identification data. The problem that the accuracy of vehicle feature recognition monitoring management is low is effectively solved.

The invention relates to the technical field of road traffic management, and discloses an expressway abnormal behavior detection system and method based on big data, and the system comprises a first obtaining module which obtains the motion video information of a target vehicle driving on an expressway in real time through a visual sensor, and extracts a plurality of key frames from the motion video information; the first analysis module is used for setting the target positioning object as a positioning reference point for analyzing the transverse displacement of the target vehicle in each key frame, setting the target vehicle as a relative change point, and calculating the distance between the relative change point and the positioning reference point; in different key frames, if the distance changes, the change size of the distance is the transverse displacement of the target vehicle; and the vehicle deviation judgment module is used for representing that the target vehicle deviates if the transverse displacement is not smaller than the first deviation threshold value and is smaller than the first drift threshold value, and counting the deviation times of the target vehicle. According to the invention, whether the vehicle driving behavior is abnormal can be accurately identified.

This invention discloses an AI-powered BeiDou vehicle-road-cloud system and method for source control of vehicle violations, relating to the fields of traffic safety and vehicle-road-cloud integration technology. Currently, most traffic violations are handled post-incidentally, resulting in shortcomings such as insufficient source control (e.g., drunk driving, unlicensed driving, fatigued driving, inadequate screening of hazardous and prohibited items), data gaps across departments, and delayed early warnings. The nation's vigorous promotion of the strategies of a safe China, a strong transportation nation, national security governance, and vehicle-road-cloud integration urgently requires proactive and preemptive safety control technologies. This invention relies on AI large-scale models and BeiDou high-precision positioning, with hardware integrated and deployed in key areas of the vehicle. It enables driver facial recognition verification, identity verification, intelligent alcohol control, fatigue driving intervention, in-vehicle status perception, detection of drugs, dangerous goods, and explosives, multilingual sensitive word monitoring, biometric comparison of rear-seat occupants, and multi-dimensional risk assessment. Combined with vehicle-road-cloud collaborative interaction and black box full-process evidence storage, it connects with the public security system, enabling silent and unobtrusive reporting of abnormal risks and tiered, humane handling. It blocks traffic violations and public safety hazards at the source, deeply aligning with national security governance strategic needs, balancing road traffic management and national security prevention and control requirements, and is suitable for large-scale deployment and application of various commercial and social vehicles.

The present invention relates to a method and device for identifying critical paths for urban road congestion, belonging to the technical field of road traffic management. The method comprises: obtaining a target model and a graph neural network interpretation algorithm; the target model is a fitting model for urban road congestion constructed based on a graph neural network; obtaining an urban road congestion example graph through prediction using the target model; identifying important subgraphs of the urban road congestion example graph using the graph neural network interpretation algorithm to obtain a target subgraph; the target subgraph includes nodes, connecting edges between nodes, and weights of the connecting edges; and determining the critical congestion paths in the urban road congestion example graph based on the weights of the connecting edges in the target subgraph. The present invention can reasonably identify the critical paths that cause urban road congestion, providing a basis for preventing and alleviating urban road congestion.

The invention discloses a vision-based road information detection and front vehicle identification method, which relates to the field of road vehicles, and comprises the following steps: setting a traffic supervision management platform, and constructing a traffic ecological image according to road element data, vehicle edge data and traffic flow element data; obtaining traffic flow frame data according to the historical vehicle driving data and the traffic flow element data, obtaining road phase solution data and traffic flow chain data according to the road element data and the traffic flow frame data, and constructing a traffic co-cultivation image according to the road phase solution data, the traffic flow chain data and the traffic ecological image; obtaining a vehicle expression coefficient according to the vehicle edge data, and obtaining a lane dominant coefficient and a vehicle recessive coefficient according to the standard road condition, the standard traffic flow condition, the vehicle expression coefficient and the traffic flow chain data; generating a vehicle guiding scheme according to the traffic cooperation image, the vehicle road dominant data and the vehicle recessive data; according to the invention, the road traffic management efficiency and safety are improved.

The present invention relates to the technical field of road traffic management, and in particular to a road on-site security monitoring system and method based on big data and artificial intelligence. The method comprises: collecting vehicle data entering a target monitoring area according to a preset collection frequency, and using the vehicle data to monitor vehicle operation characteristics and driver status characteristics; predicting the vehicle intrusion probability through a pre-trained danger warning model based on the vehicle operation characteristics and driver status characteristics, and generating corresponding alarm information; determining the vehicle intrusion mode, filtering the alarm information, and extracting effective alarm information; and after obtaining the effective alarm information, constructing a multimodal hierarchical alarm strategy, providing real-time feedback of target monitoring area image data, and generating an optimal risk avoidance path.

The invention relates to the technical field of construction road traffic management, and discloses a construction road intelligent traffic management system, which solves the problem that the height of a construction road intelligent traffic management device cannot be adjusted according to the actual condition of a construction road in the use process, and comprises a supporting base, a round opening is formed in the middle of the top end of the supporting base in a penetrating mode, a control switch is fixedly installed in the middle of the front side of the supporting base, strip-shaped fixing plates are symmetrically and fixedly installed at the bottom of the supporting base, fixing installation holes are formed in the two ends of each strip-shaped fixing plate in a penetrating mode, and an adjusting supporting assembly is installed at the top of the supporting base. A traffic management assembly is fixedly installed on the outer side of the adjusting supporting assembly. According to the intelligent traffic management device for the construction road, in the using process, the height can be adjusted according to the actual situation of the construction road, the warning performance of the device is improved, and therefore a better traffic management effect can be achieved.

The invention belongs to the technical field of road traffic measurement, and particularly discloses a vehicle contour detection method and device, and the method comprises the steps: obtaining an estimated height and a driving speed after a target vehicle is driven into a detection range; moving the infrared device to a corresponding height according to the estimated height; controlling the infrared device to project infrared rays of a predetermined model to a target vehicle; receiving infrared rays reflected from the target vehicle through the infrared device to obtain measurement data; and analyzing and calculating three-dimensional data of the target vehicle according to the estimated height and the driving speed measurement data to complete detection. The position of the infrared device is dynamically adjusted after the estimated height of the vehicle is obtained, the detection requirements of different types of vehicles can be met, the detection flexibility and accuracy are improved, the three-dimensional data of the truck can be rapidly and accurately obtained in a high-speed moving environment, the problem that a static measurement method is difficult to deal with a dynamic object is solved, and the detection efficiency is improved. The efficiency and accuracy of road traffic management are improved.

The present invention relates to the technical field of intelligent transportation management, and specifically provides a road traffic management system based on smart street lights. The system includes a data perception module, a traffic flow assessment module, a signal adjustment module, a sudden event recognition module, and a response optimization module. In the present invention, through the fusion of geomagnetic and camera data, high-frequency and accurate perception of vehicle dynamic behaviors is achieved, improving the timeliness and integrity of data. By jointly analyzing traffic density and time periods, the saturation determination becomes more detailed. By comparing the queue length with the number of passing vehicles, traffic overload can be identified in advance. By jointly judging the signal skewness through the signal cycle ratio, the regional signal timing coordination is enhanced. By jointly recognizing dense vehicle shadows and sudden speed changes, the accuracy of anomaly detection is improved. By comparing the response delay and dynamically adjusting the priority, the signal precise regulation of key areas is strengthened. Overall, a leap from static control to active closed-loop regulation is achieved, improving traffic operation efficiency and adaptability.

The present application relates to the technical field of traffic dynamic management and control, in particular to a road traffic multidirectional dynamic management and control method based on vehicle flow monitoring, which can dynamically adjust road traffic management and control measures according to the road traffic operation state, thereby improving the traffic efficiency and reducing the traffic energy consumption. In view of the shortcomings and deficiencies in the prior art, the present application proposes a method for multidirectional dynamic management and control of large vehicle flow based on vehicle flow monitoring, which can monitor and predict traffic flow data in real time, then convert the traffic flow data into a matrix and a coordinate data model in multiple dimensions, and analyze and process the data by an artificial intelligence algorithm, thereby efficiently and accurately outputting a red-green light control strategy, so as to effectively improve the traffic control capability. Compared with the prior art, the storage capacity and cost of traffic data are greatly reduced, and the data processing efficiency is improved by dimensionality reduction reconstruction of real-time traffic data such as video, picture and radar signal.