186 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 discloses a county and rural traffic planning decision-making method and system based on a road traffic index. The method comprises the following steps: acquiring navigation API data, social economic data and POI information related to county and rural traffic planning; the method comprises the following steps: acquiring data, processing the data, then calculating a route growth index, a per-hour time index, a holiday influence index, a broken road index and a planning simulation index, carrying out weighted fusion to obtain a road traffic index, when the road traffic index is calculated, distributing an initial weight for each index, and adopting a self-adaptive weight adjustment algorithm to calculate the road traffic index. Dynamically adjusting the weight of each index according to the real-time traffic data and the simulation result; county and rural traffic planning is carried out by taking reduction of the road traffic index as a target, and a road traffic index difference value before and after planning is calculated as a decision basis. According to the invention, the problem of asymmetry of basic traffic management information is effectively solved, and the connection accuracy of the road network is improved.

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 technical field of traffic planning, in particular to a road congestion shunting system suitable for urban design, which comprises a node congestion identification module, a signal time sequence adjustment module, a path interference screening module, a signal priority ordering module and a linkage time period correction module. According to the method, a multi-direction traffic pressure concentration area is formed through path overlapping structure identification, an association boundary of a path group and a node state is opened, a green light starting time sequence is adjusted in combination with a column head static continuous behavior, a vehicle response and period synchronization relation is reconstructed, and structural proximity judgment is introduced in path conflict screening. High-interference paragraphs are identified by utilizing the correlation degree of guidance, speed and lane parameters, a node sorting mechanism dynamically generates priorities through the consistency of a frequent path and a queuing trend, real-time refreshing of a signal response sequence is realized, linkage rhythm correction is bidirectionally verified according to release delay and an adjacent node blocking state, a starting segment is dynamically adjusted, and the linkage rhythm is corrected. Chained dislocation is avoided.

The invention relates to the field of traffic planning, and discloses an urban road network multi-path coordination control method and system considering multi-dimensional dynamic characteristics, and the method comprises the steps: obtaining the traffic flow data, congestion indexes and bidirectional green wave bandwidth difference data of each path in a road network at an intersection; calculating the multi-dimensional dynamic weight of each path at the intersection according to the traffic flow data, the congestion index and the bidirectional green wave bandwidth difference data; constructing a target function by taking the maximum weighted green wave bandwidth sum as a target, and embedding a multi-dimensional dynamic weight into the target function; constructing a collaborative optimization system comprising a high-weight path guarantee constraint, a dynamic adaptability constraint and an auxiliary constraint; and solving an optimal signal timing parameter based on the objective function and the collaborative optimization system, and generating a multi-path coordination control scheme. According to the method, through high-weight path guarantee constraint, dynamic adaptability constraint, flexible breakpoint constraint and the like, the length of a green wave band is increased, and the continuity of green waves and the anti-interference capability of a road network are improved.

The invention provides a multi-destination travel itinerary planning method, system and device and a storage medium. The method comprises the following steps: receiving a travel planning request of a user; based on keywords in the tourism planning request, matching a plurality of related scenic spots and tourism destination cities to which the scenic spots belong; at least according to the traffic information between the tourism destination cities, generating a tourism sequence based on the tourism destination city playing sequence, inter-city traffic planning between the tourism destination cities and tourism sub-planning of each tourism destination city, and obtaining daily tourism tracks, daily accommodation hotels and scenic spot routes; and generating a travel itinerary plan according to the daily travel track, the scenic spot itinerary, the daily accommodation hotel and the inter-city traffic plan, and feeding back the travel itinerary plan to the user. According to the invention, travel, accommodation and travel time arrangement and route planning schemes in the travel itinerary of the user can be finely designed, the travel time cost of the user is reduced, and the experience in the travel itinerary is improved.

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 invention relates to the technical field of urban and rural traffic planning, in particular to a rail transit connection shared bicycle use influence analysis method based on built environment and interpretable machine learning, which comprises the following steps: S1, identifying traffic behaviors of taking shared bicycles as rail transit connection trips, obtaining shared bicycle order data in a target area, and determining the order data of the shared bicycles in the target area; constructing a shared bicycle connection use database; s2, determining a research area of a built environment around each subway station, and delimiting an annular buffer area around the subway station as a research range; s3, fusing multi-source built-up environment data, including objective built-up environment indexes and perceptual built-up environment indexes; s4, on the basis of the data in S1 and S3, establishing an influence factor data set of the environment on the use of the shared bicycle; the method comprises the following steps: identifying a traffic behavior of taking a shared bicycle as a rail traffic connection trip, obtaining shared bicycle order data in a target area, extracting riding OD point, distance and time information, and constructing a shared bicycle connection use database;

The invention discloses an expressway flow prediction method based on multi-modal fusion and sequence decomposition, and relates to the technical field of traffic flow prediction, and the method comprises the steps: obtaining expressway traffic flow historical monitoring data, meteorological condition data and sampling time mark data, and constructing a multi-modal feature input sample; calling a two-channel neural network prediction model to extract trend term and remainder term features according to the sample, and calculating a traffic flow prediction result; combining prediction results of the trend term and the remainder term features, adjusting model parameters by adopting a feedback mechanism based on multi-modal coding parameter optimization, and generating a final traffic flow prediction model; and by using the trained prediction model and combining highway traffic flow monitoring data, realizing accurate prediction of regional traffic flow and inter-regional traffic flow at a specified moment and period in the future. Through multi-modal data fusion, feature extraction and model parameter optimization, the highway traffic flow can be accurately predicted, and powerful support is provided for traffic planning and management.

The invention provides a traffic planning data processing method and device, and relates to the technical field of traffic planning data processing, and the method comprises the steps: extracting the dynamic behavior characteristics of traffic participants in a designated road segment from traffic planning data; determining synchronous car-following indexes corresponding to the various types of traffic participation states, and copying all the synchronous car-following indexes in real time through a data synchronization protocol to form a dynamically updated coordination planning period; planning and deducing the traffic association information to obtain a traffic decision database, and determining an interaction constraint level of the traffic participants in traffic planning through the traffic decision database and the traffic linkage trends of the traffic participants in different time periods in the specified road section; and according to the coordination planning period and the interaction constraint level, traffic planning adjustment is executed by using the traffic planning data sharing platform and is synchronized to a remote database. According to the invention, distributed decision-making of data can be realized under complex traffic planning data update delay, so that the dynamic adaptability of traffic flow is improved.

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.

The present invention discloses a road marking device for traffic planning, which relates to the technical field of road marking. The road marking device for traffic planning includes a nozzle tube, an air pipe and an injection pipe are provided on one side of the nozzle tube, which are used for air injection and injection respectively; a needle valve rod, the needle valve rod is located in the nozzle tube, and a blocking ball is provided at the lower end of the needle valve rod, which is used to block or not block the spray hole, a piston plate is fixed to the upper end of the needle valve rod, and a reset spring is provided between the piston plate and the top end of the nozzle tube. The injection pipe is cut off by a three-way valve, and the valve plate is lifted to open the pressure relief pipe, so that the air pressure inside the nozzle tube drops. The step-by-step drop in air pressure effectively eliminates the inertia of paint injection caused by the sudden drop in pressure. The reset spring and the air pressure difference work together to push the blocking ball to block the spray hole, forming a physical secondary seal, realizing a mechanical-pneumatic dual-drive seal, thereby reducing paint leakage and avoiding the accumulation of paint spots at the starting and ending ends of the marking due to a sudden increase or drop in pressure.

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 a traffic planning system and method, electronic equipment and a storage medium. The traffic planning method comprises the steps of obtaining type characteristics of interaction obstacles around a current vehicle; speculating the motion intention of the interaction obstacle according to the type characteristic of the interaction obstacle; and obtaining a passing decision of the current vehicle according to the motion intention. The motion intention of the dynamic obstacle is speculated according to the type characteristic of the dynamic obstacle, so that decision information is provided for the current vehicle, the problems of low passing efficiency, low safety and poor experience of the automatic driving vehicle at the intersection caused by the problems of frequent snub braking, rapid stopping and the like of the automatic driving vehicle are solved, the flexibility is high, the passing efficiency is high, the safety is high, and the practicability is high. And the experience feeling is improved.

The invention provides a traffic optimization and influence evaluation method based on a space-time traffic network model, and the method comprises the steps: constructing a space-time traffic network model, and obtaining space-time information based on a graph theory through the historical traffic flow data, and predicting the future traffic flow; the bridge collapse influence is evaluated, and traffic flow and stakeholders are involved; a multi-target bus route optimization model is constructed, bus station distribution is optimized, and multi-target optimization is achieved; determining an optimal traffic network project by using an analytic hierarchy process, and analyzing advantages and influences of the optimal traffic network project; according to the method, the space-time traffic network model is constructed, so that the traffic flow can be predicted, and particularly, the influence of emergencies on traffic is considered; through a bus route multi-objective optimization model, bus station distribution is optimized, the coverage rate of a bus network is improved, and the operation cost and the average commuting time are reduced; the traffic network project is comprehensively evaluated, the advantages of each project and the influence on different stakeholders are comprehensively analyzed, and a scientific basis is provided for traffic planning and decision making.

The invention provides road traffic planning and design surveying equipment which comprises a box body, moving wheels, telescopic rods and a lifting frame structure, a tilt angle sensor and the four telescopic rods are arranged below a partition plate at the lower end of the box body, the tilt angle of the box body can be detected in real time through a PID self-adaptive control module, and the telescopic amount of the telescopic rods is automatically adjusted; measuring equipment is ensured to be located on a horizontal reference surface, and distance and angle measurement accuracy is improved; the handle box on the side surface of the box body and the moving wheels realize convenient transfer of the equipment, and collision loss of the instrument in the carrying process is reduced; the shield at the top end of the lifting frame and the measuring instrument bottom frame form a two-degree-of-freedom adjusting mechanism, the shield can transversely rotate by 360 degrees, the measuring instrument bottom frame achieves head raising / lowering angle adjustment through an arc groove and a clamping column structure, the measuring datum plane can be accurately calibrated in cooperation with scale marks and a rotary adjusting bolt, and the measuring requirements of different terrains and directions are met. Through automatic horizontal calibration, multi-angle adjustment and integrated design, the precision and efficiency of road survey are 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, in particular to a shift determination method and device of an unmanned bus and related equipment. The method comprises the following steps: determining target riding information of a target passenger and character information of a target user according to a reservation request about an unmanned bus sent by the target passenger; according to the target riding information, determining at least one alternative shift in the plurality of alternative shifts; determining a target shift which can be reserved by the target passenger in the at least one alternative shift according to the character information of the target user; passive acceptance of passenger demands is converted into active participation, so that shift arrangement can dynamically respond to individual differences; in addition, the passenger preference is quantified through character information, and resource waste or experience decline possibly caused by purely depending on time matching can be avoided.

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.