122 results about "Traffic planning" patented technology

The invention discloses a pedestrian behavior simulation operation control method based on an unreal engine. Efficient and vivid pedestrian behavior simulation is realized through five core modules: a three-dimensional scene construction module converts a BIM model based on an unreal engine Datasmith plug-in and constructs an interactive dynamic scene; the pedestrian model construction module defines multi-dimensional pedestrian attributes and supports data-driven initial distribution configuration; the hierarchical behavior control module realizes refined regulation and control of pedestrian behaviors through macroscopic path planning, microcosmic behavior decision and emotion driving; the dynamic resource optimization module adopts level-of-detail control and multi-thread task allocation to improve the operation efficiency of the system; and the real-time interaction and data analysis module provides scene regulation and control, data visualization and simulation data recording and playback functions. According to the method, the authenticity, the dynamic response capability and the controllability of pedestrian simulation are remarkably improved, and reliable technical support can be provided for traffic planning, emergency drilling and building design evaluation.

The invention belongs to the technical field of urban traffic planning and intelligent traffic systems, particularly relates to an intersection phase structure optimization method based on a large language model, and aims to improve the intelligent level and operation efficiency of traffic signal control. According to the method, semantic mapping cues of traffic flow and a phase structure are constructed, and a large language model is guided to generate a phase structure scheme adapted to an actual traffic state. Compared with a traditional scheme depending on artificial experience and a fixed structure, the method can automatically generate diversified and data-driven phase structure combinations, and has higher adaptability and generalization ability. In the aspect of technical implementation, the method fuses prompt engineering and guides a large language model to generate an initial phase scheme, and performs evaluation and feedback by using a value network, so that optimization of a phase structure is realized, and the overall operation efficiency of a traffic system is improved.

The invention discloses a traffic planning method and device, a storage medium and a program product, and relates to the technical field of automatic driving. The method comprises the following steps: acquiring vehicle driving data and a real-time traffic condition; according to the vehicle driving data and the real-time traffic condition, a plurality of particles are initialized, and each particle represents an acceleration sequence of the vehicle in a future preset time period; iteratively updating the particles until convergence, and obtaining a preliminarily optimized acceleration sequence; and a quadratic programming algorithm is applied to smooth the preliminarily optimized acceleration sequence, a target acceleration sequence is obtained, and the target acceleration sequence is used for controlling the vehicle to run. The technical problem that a rule-based speed planning method in the prior art lacks flexibility and is difficult to deal with a complex traffic environment is solved.

The invention relates to the field of electric digital data processing, and discloses a signal global induction real-time control method and system. The method comprises the following steps: collecting state data in real time through a thunder detector, and generating a state value through fuzzy comprehensive evaluation; calculating an intersection credit value based on a multi-stage enhanced game model in combination with the state value and the historical compromise rate; dynamically adjusting the cooperation range by adopting a cooperation suppression distance field mechanism; and distributing signal duration according to a three-level arbitration strategy, updating a credit value, and optimizing the system through a credit entropy stabilization mechanism. According to the method, the problem that signal control lacks global collaboration due to the fact that traffic association of intersections of the whole network is not fully considered and data processing is limited to local is solved, a universal global collaborative planning control method is realized, and the traffic planning efficiency and the system stability are improved.

The invention discloses a smart city traffic planning method and system based on deep learning, and relates to the technical field of city traffic management, and the method comprises the steps: recognizing an activity region of a traffic disturbance activity, constructing a disturbance region graph Ga, collecting vehicle driving related data and lamp control cycle data, and constructing a standardized data set H; coupling modeling is carried out on path length change and direction deviation of the traffic driving path before and after the traffic disturbance activity so as to quantify the traffic state of the activity area, a path disturbance deviation coefficient Py is acquired, the traffic state of the activity area is evaluated in combination with a path disturbance threshold Pyyz, and when the traffic state is in an abnormal state, the traffic disturbance deviation coefficient Py is calculated. According to the method, signal lamp cycle rhythm analysis is carried out, a phase dislocation propagation index Xw is obtained, and coupling modeling is carried out to obtain a comprehensive rhythm adaptation index Zh, so that the risk level of a traffic signal control system is divided, a system adjustment instruction is generated, intelligent adjustment is carried out, and the intelligent, precise and real-time level of smart city traffic planning is improved.

The invention discloses an evaluation index system construction method for a construction time sequence of an urban composite channel, relates to the technical field of traffic engineering and urban planning, and solves the problems of facility layout conflict, traffic operation disturbance, low efficiency of resource allocation and the like caused by the lack of scientific time sequence overall planning of the construction time sequence of an existing urban rail-road composite channel. The construction method comprises the following steps: S11, dividing a city composite channel construction process into a plurality of evaluation stages of construction time sequence influence; s12, determining an evaluation dimension in each evaluation stage; s13, extracting an evaluation criterion based on each evaluation dimension; s14, refining a plurality of secondary evaluation indexes according to each evaluation criterion, and constructing an evaluation index system according to the secondary evaluation indexes; and S15, determining the meaning, the calculation method and the numerical value acquisition mode of each secondary evaluation index. The invention further discloses an evaluation method for the construction time sequence of the urban composite channel. According to the invention, the scientificity of traffic planning decision and the efficiency and benefit of engineering implementation can be improved.

The invention relates to a traffic facility attribute mining method and system based on multi-modal network open source data. The method comprises the following steps: extracting traffic facility information from a webpage to construct a knowledge graph; extracting positions and appearances of traffic facilities from the images, and analyzing streetscape images to obtain attributes such as road traffic; collecting map images, tiles and vector data to construct a road network topology and attribute database; associating webpage texts, pictures, streetscape images and network map multi-source data according to the spatial position of the traffic facility; through comprehensive and deep attribute mining, different modal data are integrated to improve the accuracy and reliability of attribute mining, the real-time and dynamic updating capability, the convenient visualization and interaction operation, the data sharing and integration convenience, and the traffic facility management efficiency and collaboration are improved. According to the method, comprehensive, accurate and real-time traffic facility attribute data support can be provided for urban traffic planning, traffic management and intelligent traffic system construction, so that the efficiency and the intelligent level of traffic facility management are remarkably improved.

The invention relates to the technical field of comprehensive traffic planning and logistics optimization, in particular to a multimodal transportation junction transportation path collaborative optimization system and a method thereof.The multimodal transportation junction transportation path collaborative optimization system comprises a data layer, a model layer, an application layer and a feedback layer, the data layer comprises a data acquisition module and a data processing module, the data acquisition module mainly acquires node basic data, network topology data, freight demand data and cost aging data, and the processing content of the data processing module comprises standardization processing, space-time alignment, abnormal value cleaning and data storage processing; and the model layer is used for multi-objective optimization model and intelligent algorithm processing. According to the method, the multi-objective optimization model is constructed, so that the scientific site selection of the transit hub, the intelligent matching of the transportation mode and the path and the collaborative optimization of the whole link cost and the time efficiency are realized, meanwhile, various resource constraint conditions are met, and the overall operation efficiency of the multimodal transportation network is improved.

The invention provides an urban traffic carbon emission correlation analysis method and system based on a space syntax, and the method comprises the steps: obtaining the road network vector data of a target city, carrying out the preprocessing of the road network vector data through ArcGIS software, and generating a road grid unit which comprises the road network density, constructing a road network topological space model by adopting a line segment model through DepthmapX software, and calculating a road segment-level space syntactic index of each road segment; aggregating the road section level space syntax indexes and the road network density of the road grid units to all the road grid units; based on the economic activity intensity, generating a road grid unitized carbon emission distribution diagram by using the total urban traffic carbon emission amount; and constructing a multiple regression model, determining a quantitative relationship between the road structure and carbon emission based on the multiple regression model, and making a traffic planning scheme. According to the method, the high-carbon emission area and the key road nodes are accurately recognized, and the method is high in universality and can be popularized to traffic carbon emission analysis and optimization practice of different cities.

The application discloses a kind of attention mechanism trajectory generation and simulation methods for sparse data completion, belong to intelligent transportation and trajectory prediction field.The application fills in trajectory missing value using high-precision sensor and map information, combines graph attention network (GAT) and multi-modal fusion technology;Adopt the attention module based on distance (D-GAT) and based on view (V-GAT), capture the interaction between vehicles, improve the understanding of complex traffic scene;Through prediction supervision generator and multi-modal trajectory generator, combine LSTM and Gaussian mixture model (GMM) to generate multiple possible trajectories, and use Kalman filter for online adjustment, ensure the accuracy and real-time of trajectory.The application realizes the intelligent completion of sparse traffic data and the accurate generation of trajectory, provides reliable data support and decision basis for intelligent transportation system, helps the efficient operation and sustainable development of urban traffic planning and management.

This invention relates to the field of mining area traffic planning and discloses a method for planning vehicle speed in mining areas that integrates AI algorithms and multimodal data. The method includes the following steps: S1, determining that the current vehicle is in a following state and collecting the current vehicle's driving parameters, the position of the leading vehicle, and the distance between the two vehicles; S2, based on the positions of the current vehicle and the leading vehicle, determining whether the leading vehicle is traveling on a slope or about to leave the slope; S3, if the leading vehicle is on a slope or about to leave the slope, determining a safe following distance based on the distance between the two vehicles and the leading vehicle's slope travel distance; S4, planning the current vehicle's driving speed. This invention identifies vehicle following patterns and collects multimodal data in real time and comprehensively. It utilizes AI algorithms to perform high-precision perception and forward-looking prediction of the leading vehicle's slope travel status, enabling the solution to fully understand the complex terrain environment currently and in the future, thus allowing for pre-emptive risk assessment.

The invention provides an electric bicycle facility layout collaborative optimization method based on multi-dimensional features, and relates to the technical field of urban traffic planning, and the method comprises the steps: obtaining a comprehensive demand potential index of a candidate position, and decomposing the comprehensive demand potential index into a parking facility demand, a sharing facility demand and a charging facility demand; constructing a collaborative efficiency gain function for each candidate position; constructing a service interference loss function for each candidate position; constructing a facility configuration efficiency index of each candidate position; establishing a multi-target planning model; solving the multi-objective planning model by adopting a multi-objective genetic algorithm to obtain a Pareto optimal solution set; and identifying suitable area characteristics of composite configuration and single configuration from the Pareto optimal solution set according to the facility configuration efficiency index value, and outputting facility type configuration and layout scale of each candidate position. The technical problem that in the prior art, composite site configuration lacks quantitative basis can be solved.

The invention relates to the field of traffic signals, in particular to a novel traffic signal lamp for traffic planning, which comprises a fixed box and a mounting rod arranged on the fixed box, a traffic signal lamp is arranged on the mounting rod, a cavity is formed in the fixed box, and a driving part is arranged in the cavity. The driving piece drives the mounting rod to move up and down and adjusts the overall gravity center of the equipment; the driving part comprises a driving gear and a threaded rod, the upper end of the threaded rod is arranged in the mounting rod and is in meshed connection with the mounting rod, and the threaded rod rotates to drive the mounting rod to move up and down. The telescopic height of the mounting rod is adjusted through meshing transmission of the driving motor, the threaded rod and the mounting rod, so that the overall gravity center is dynamically reduced, meanwhile, the balance blocks in the anti-toppling piece can slide downwards and outwards along the inclined guide rails, the gravity center is dispersed to the four corners of the bottom of the equipment, and a low-gravity-center and multi-point-supporting stable structure is formed; and the anti-overturning performance in a strong wind environment can be conveniently improved.

The invention discloses an urban comprehensive traffic digital platform based on a GIS technology, and the platform comprises a business layer, an application layer, a data layer, a support layer, and an infrastructure layer. The application layer comprises an urban traffic monitoring and evaluation module, an expressway traffic monitoring and evaluation module, a traffic image evaluation module, a comprehensive consultation decision support module and a parking facility management module; according to the invention, the urban comprehensive traffic digital platform is constructed by using urban traffic data resources and industry management data, based on the GIS technology and by using information technologies such as the Internet of Things, cloud computing and big data; the functions of monitoring the urban road traffic state in real time, evaluating the traffic condition, analyzing the traffic jam cause, predicting the traffic travel demand, evaluating the traffic measure implementation effect and the like are achieved, scientific decision support is provided for urban traffic planning, infrastructure construction and traffic management, the wide application prospect is achieved, and application and popularization are facilitated.

The application discloses a road domain space quantization delimitation method, device, equipment and medium, relates to the field of road traffic planning and highway economic development, and the method comprises the following steps: acquiring road network data, constructing a traffic road network topology according to the road network data; taking a highway entrance and exit as a starting point, acquiring a first preset time isochronous circle and a second preset time isochronous circle according to the traffic road network topology; wherein the first preset time is less than the second preset time; acquiring a preliminary road domain space range according to the first preset time isochronous circle and the second preset time isochronous circle; the preliminary road domain space range comprises a facility layer, a management and control layer, a core layer, a radiation layer and an edge layer; and performing difference correction on the preliminary road domain space range to acquire a target road domain space range. The application provides a more scientific and more accurate boundary delimitation method.

The invention relates to the technical field of traffic planning, and discloses an urban traffic optimization and planning method and system based on artificial intelligence data processing, and the method comprises the steps: collecting a time sequence perception data flow of a target intersection, and carrying out the extraction of an occupancy state tensor based on a time window, and obtaining the occupancy state tensor of the target intersection in the time window; using the occupancy mode analysis model to output occupancy mode probability distribution of the target intersection in the time window; and outputting the lane traffic capacity of the target intersection by using a lane traffic capacity calculation function which is corrected by introducing dynamic factors of a temporary parking type occupation reduction factor and a queuing type occupation delay factor, and dynamically adjusting a short-time traffic control strategy of the target intersection. According to the invention, through time sequence perception and occupation mode analysis, the temporary parking and queuing occupation modes are distinguished, and the traffic capacity of the lane is dynamically quantified and corrected, so that the short-time traffic control strategy is adjusted in real time, and refined and adaptive traffic control and optimization under complex disturbance conditions in a city are realized.

The invention discloses a road traffic capacity assessment method and system, a medium and equipment, and relates to the technical field of traffic planning and management, and the method comprises the steps: obtaining a plurality of groups of input parameter combinations of a road in a simulated traffic environment; determining a mixed traffic flow traffic capacity value and a standard traffic flow traffic capacity value according to the multiple groups of input parameter combinations, and determining a traffic capacity adjustment coefficient CAF according to the mixed traffic flow traffic capacity value and the standard traffic flow traffic capacity value; constructing a training database based on the multiple groups of input parameter combinations and the traffic capacity adjustment coefficient CAF; and training the machine learning regression model based on the training database, and determining an agent model for predicting the road traffic capacity.

Embodiments of the present application provide a traffic state data processing method and device, equipment and a storage medium, belonging to the field of intelligent transportation. The method comprises: acquiring a data receiving time of traffic state data; if the data receiving time is less than a preset data processing time, storing the traffic state data in a preset data queue, and calling out the traffic state data from the data queue at the data processing time to obtain a traffic state view through visualization; if the data receiving time is greater than the preset data processing time, compensating the traffic state data based on a time difference between the data receiving time and the data processing time and a preset time interval to update the traffic state view or discard the traffic state data; and displaying the traffic state view. The embodiments of the present application can cope with network problems occurring in the data transmission process, and provide more intuitive traffic state for traffic planning and management.

A method to determine if a traffic situation comprising a plurality of heavy-duty vehicles following a plurality of guided vehicle trajectories in a defined area will lead to a vehicle deadlock is described. For example, one method includes generating a traffic situation representation for the defined area comprising, for each of the plurality of vehicles, an initial vehicle trajectory segment location and a subsequent deadlock status, inputting the traffic situation representation to a traffic situation deadlock classifier which has been trained to output a traffic situation deadlock classification based on an input representation of a traffic situation in the defined area, and, based on the input traffic situation representation, generating a predicted deadlock classification of a subsequent traffic situation for that input traffic situation representation.

The invention relates to the technical field of intelligent medical building and traffic planning, in particular to a method for building a three-dimensional parking building in a hospital based on instant modeling and analogue simulation analysis, and solves the problem that a traditional planning method mainly depends on manual investigation and static capacity estimation. In order to solve the problems of backward data acquisition, single analysis dimension, decision dependence on subjective experience and insufficient prediction and evaluation ability in the prior art, the method comprises the following steps: S1, constructing a binocular depth camera operation environment, configuring ORB-SLAM, YOLOv8 and Byterack algorithms, and carrying out simulation test and field calibration; s2, field space properties are investigated on site, the EMR of a patient, namely electronic case data of the patient, is acquired and analyzed, main traffic flow lines of the patient are visualized, and high-frequency nodes and traffic paths are determined. According to the method, the defects of data lag, high subjectivity and the like of a traditional planning method are overcome, a whole-process quantitative decision from data acquisition, simulation modeling to scheme generation is realized, and the hospital traffic efficiency and the medical treatment quality are remarkably improved.

The present application provides a network topology configuration method, a communication system, and a related device. In the method, before distributed training of an AI model begins, a network controller can analyze a training task and determine traffic demand information for the training task. The traffic demand information comprises a bandwidth demand between different processors in a training process of an AI training task. Network topology information of an optical-electrical hybrid network can be determined on the basis of the traffic demand information. Configuration information of an optical switching device is then generated on the basis of the network topology information, so that the optical switching device can perform link switching on the basis of the configuration information and complete topology reconfiguration of the optical-electrical hybrid network. In this way, the network controller can actively perform traffic planning before AI model training, avoiding the problem of large network delay in the training process caused by a slow link switching speed of the optical switching device.

This invention relates to the field of airport integrated transportation, specifically to a method for assessing the competitive status of airport landside transportation niches. Based on niche theory, this invention uses the breadth, overlap, and competitive dynamics of transportation niches as core dimensions for evaluating airport landside transportation competitiveness. By constructing a quantitative model of transportation niches, it analyzes the competitive and cooperative relationships among different modes of transportation and the mechanism of imbalance in carrying capacity ratios, thereby characterizing the comprehensive competitiveness of airport landside transportation and providing a scientific basis for optimizing airport landside transportation planning and improving transportation efficiency. This invention can be used to reveal the competitive and cooperative mechanisms and evolutionary patterns of airport landside transportation niches, in order to solve the key problems currently facing the development of airport landside transportation.

The invention relates to the technical field of traffic planning, and discloses a traffic planning path optimization method based on Beidou positioning, and the method comprises the steps: constructing a regional traffic node network based on Beidou positioning data, and generating an initial path link; according to real-time traffic flow, dynamically distributing node traffic weights, dividing a path adjustment gradient in a pre-planning stage, matching traffic parameters, and collecting dynamic traffic data; clustering the traffic parameters based on the dynamic data to generate a path adaptation parameter set; in the navigation execution stage, traffic state data are acquired in real time, target parameters are determined, and the adaptive parameter set is called to generate a traffic regulation and control instruction. The method further comprises abnormal event processing, parameter set storage calling, dynamic optimization and a user interactive adjustment mechanism. According to the method, the high-precision characteristic of Beidou positioning is utilized, multi-dimensional traffic data dynamic processing is combined, real-time accurate optimization of path planning is achieved, traffic passing efficiency and user navigation experience are improved, and the method is suitable for the field of urban traffic planning and navigation.

The application relates to a prefabricated pavement system, a prefabricated plate mold and a preparation method, wherein a main structure of the prefabricated pavement system is a prefabricated plate, a plurality of blind holes are arranged on an upper surface of the prefabricated plate, monitoring devices are arranged in the plurality of blind holes, the monitoring devices can monitor pavement conditions and generate relevant monitoring data, an upper computer is in communication connection with the monitoring devices, and the monitoring devices can transmit the monitoring data to the upper computer. Compared with a common prefabricated assembly pavement, the prefabricated pavement system can better monitor pedestrians and vehicles on the road section, can provide reliable credentials for subsequent traffic planning of the road section according to the collected relevant data, and is beneficial to planning and design of traffic, construction and the like of the road section. The prefabricated plate mold can be used to produce the prefabricated plate, and the application further provides a preparation method of the prefabricated pavement system, so that the prefabricated pavement system is more convenient to use.

The invention provides a track planning method for continuous intersection ecological driving of an unmanned bus, and relates to the technical field of traffic planning. The data acquisition module acquires basic data used for unmanned bus track planning. And the running state description module establishes a state space model for describing the running state of the driverless bus, and by taking the lowest energy consumption as an optimization target and applying various constraint conditions, an driverless bus speed track considering continuous intersections is constructed, so that the effects of energy conservation and emission reduction are achieved. Finally, track planning information is transmitted to the unmanned bus through the vehicle-mounted terminal, and accurate vehicle speed reference is provided for ecological operation of the unmanned bus. According to the invention, a green and ecological effect can be provided for the operation of the driverless bus, a remarkable practical effect is achieved for reducing the energy consumption of the bus and saving the operation cost of the bus, and assistance is provided for promoting the green development of an urban public transport system.

The application provides a kind of urban vehicle carrying capacity scale optimization method and system based on mixed prediction, it is related to traffic transport engineering technical field, the method steps include obtaining city, traffic, running track, travel and point of interest data, and pre-processing;Supply capacity and travel demand mixed two-way prediction model is constructed, based on the upper limit of physical capacity of urban road and parking resources, combined with the reasonable sharing rate of taxicab in traffic structure to calculate the supply capacity, by fusing deep learning and traffic planning theory to simulate the space-time network distribution of origin-destination travel, obtain the initial carrying capacity scale based on travel demand;The initial carrying capacity scale is corrected based on the model of multimodal traffic development trend and estimated and adjusted based on horizontal city comparison, to obtain the recommended carrying capacity scale after optimization;Set up multi-dimensional monitoring index system, real-time monitoring and evaluation of the operation state of taxicab market, execute corresponding control response measures.

The application relates to the field of electric digital data processing and discloses a signal global induction real-time control method and system. The method comprises the following steps: collecting state data in real time through a radar detector, generating a state value through fuzzy comprehensive evaluation; combining the state value with a historical compromise rate, calculating a crossing credit value based on a multi-stage reinforcement game model; adopting a cooperative inhibition distance field mechanism to dynamically adjust a cooperative range; distributing signal duration according to a three-level arbitration strategy, updating the credit value and optimizing the system through a credit entropy quantity stabilization mechanism. The application solves the problem of lack of global synergy in signal control caused by insufficient consideration of the correlation of crossing traffic in the whole network and the limitation of data processing to a local part, realizes a general global collaborative planning control method, and improves the traffic planning efficiency and system stability.

The utility model provides a road traffic planning passage early warning device, and belongs to the technical field of early warning devices. Comprising a bottom plate; the connecting plate is rotationally connected into the bottom plate; the warning device body is stably connected to the connecting plate, and the warning device body is located on the side, away from the bottom plate, of the connecting plate; and the number of the electric rotator is at least one, and the electric rotator is stably installed on the top of the warning device body. According to the utility model, through the cooperation of the bottom plate, the connecting plate, the warning device main body, the electric rotator, the adjusting block and other structures, the purpose that the early warning range and angle can be flexibly adjusted according to actual requirements after the early warning device is installed is achieved; the purpose that the connecting bolt is prevented from rotating along with the nut when the connecting plate is installed is achieved.

The invention discloses a comprehensive transportation channel optimization method based on a complex network and a multi-objective decision, and relates to the technical field of traffic planning and optimization, and the method comprises the steps: S1, constructing a comprehensive traffic current situation network based on a complex network theory; s2, analyzing the comprehensive traffic network characteristics; and S3, comprehensively considering traffic demands, accessibility, balance, network toughness, construction condition constraints and fund constraints, planning new construction and existing facility upgrading and reconstruction on the basis of the current comprehensive transportation channel, and carrying out channel multi-objective optimization. According to the method, the comprehensive transportation channel is regarded as a complex network system, comprehensive consideration is carried out from multiple dimensions such as traffic demands, node accessibility, network balance and network toughness, and construction conditions and fund constraints are included, so that the optimization result is more systematic and comprehensive, deviation caused by a single target or local optimization is avoided, and the optimization efficiency is improved. And a more powerful basis is provided for optimization decision making.

The invention relates to the technical field of smart city and traffic planning, and discloses a public transport accessibility level map generation method and system based on localized path planning, and the method comprises the steps: S1, constructing a localized public transport network database; s2, based on a public transport network database, calculating the total travel time of all possible public transport travel paths between the starting point grid and the terminal point grid; s3, taking any grid in the research area as a starting point grid, repeatedly executing the step S2, obtaining the shortest travel time from the starting point grid to all grids except the starting point grid in the research area, and forming a travel time matrix; s4, based on the travel time matrix, counting the number or area of grids which can be reached by each grid as a starting point within a preset time, and taking the number or area of the grids as a reachability level quantized value of the grid; and S5, according to the reachability level quantized values of all grids, generating a public transport reachability level map. According to the invention, the calculation cost is reduced.