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92 results about "Congestion prediction" patented technology

Traffic information prediction system

In a congestion prediction using measurement data which is acquired by an on-road sensor or a probe car, and which includes none of explicit information about bottleneck points, with respect to time-sequence data on congestion ranges accumulated in the past, data on congestion front-end positions are summarized into plural clusters by the clustering. Representative value in each cluster is assumed as position of each bottleneck. A regression analysis, in which day factors are defined as independent variables, is performed with congestion length from each bottleneck point selected as the target. Here, the day factors refer to factors such as day of the week, national holiday / etc. It then becomes possible to precisely predict a future congestion length.
Owner:HITACHI LTD

Method and apparatus for automatic selection of alternative routing through congested areas using congestion prediction metrics

A scheduling system and method for moving plural objects through a multipath system described as a freight railway scheduling system. The scheduling system utilizes a cost reactive resource scheduler to minimize resource exception while at the same time minimizing the global costs associated with the solution. The achievable movement plan can be used to assist in the control of, or to automatically control, the movement of trains through the system. Alternative routes through congested areas are automatically selected using congestion prediction metrics.
Owner:GENERAL ELECTRIC CO

Method for controlling congestion control method by fusing three kinds of information in wired/wireless hybrid network

The invention discloses a method for controlling congestion by fusing three kinds of information in a wired / wireless hybrid network. The three kinds of information include packet loss information, RTT (Radiation Tracking Transducer) information and explicit congestion notification information. The method comprises the following steps of: marking a CE (Conformite Europeenne) bit in IP (International Protocol) packet according to the RTS (Ready-To-Send) repeat times of an MAC (Media Access Control) layer by a wireless node; marking the CE bit in the IP packet by a wired router through an array length; processing a received data packet, confirming the carrying capability through an ACK (Acknowledgement) packet and informing a sending end of the network congestion state by a receiving end; and then, comprehensively considering the packet loss information, the RTT information and the explicit congestion notification information for congestion prediction and adjusting a congestion control mechanism according to a prediction result by the sending end. The method provided by the invention judges the congestion by fusing the three kinds of information, effectively distinguishes wireless packet loss and congestion packet loss, improves the utilization and the throughput of the wired and wireless hybrid network with a wireless link as a bottleneck and improves the whole performance of the network.
Owner:中科博华信息科技有限公司

Highway congestion prediction and active prevention and control method based on big data

The invention relates to a highway congestion prediction and active prevention and control method based on big data. According to the method, firstly, an actual road network is abstracted, a topological graph representing the road network is constructed, and an optimal path between any two points in the graph is calculated; then vehicle historical traffic data are processed to generate a vehicle driving path selection probability table and a road segment vehicle source time-sharing ratio table; according to the vehicle driving path selection probability table, road segments to be reached by network access vehicles at the predicted time are calculated, then the spatial saturation of the road segments is calculated, for the road segment with the saturation greater than a certain threshold, the road segment is judged to be congested at the predicted time, and then the vehicle source ratio on the road segment at the predicted time is found out according to the road segment vehicle source time-sharing ratio table, so that relevant entry points are subjected to vehicle flow entry speed control. According to the method, road congestion can be predicted in advance, a scientific means of avoiding the road congestion is provided, and roads are kept clear.
Owner:JSTI GRP CO LTD

Road congestion detection method and device, computer device and storage medium

The invention discloses a road congestion detection method and device, a computer device and a storage medium. The method comprises the steps of planning a reachable route according to the destinationinformation and the position information sent by a vehicle-mounted terminal, obtaining a current road congestion area of a city, and determining the overlapped area of the reachable route and the road congestion area as a to-be-evaluated congestion area; calculating the prediction time when the vehicle where the vehicle-mounted terminal is located arrives at the to-be-evaluated congestion area, and obtaining a prediction congestion index of the to-be-evaluated congestion area at the prediction time according to the historical congestion data of the to-be-evaluated congestion area; predictinga congestion prediction result when the vehicle arrives at the to-be-evaluated congestion area according to the predicted congestion index; and pushing the congestion prediction result and the reachable route to the vehicle-mounted terminal. According to the technical scheme, the accuracy of the road congestion detection and analysis result and the intelligent level of road congestion detection and analysis are improved.
Owner:ONE CONNECT SMART TECH CO LTD SHENZHEN

Probabilistic congestion prediction with partial blockages

A method of estimating routing congestion between pins in a net of an integrated circuit design, by establishing one or more potential routes between the pins which pass through buckets in the net, assigning a probabilistic usage to each bucket based on any partial blockage of the wiring tracks in each bucket, and computing routing congestion for each bucket using its probabilistic usage. When the net is a two-pin net that is a part of a larger multi-pin net, and a tree is constructed to bridge the two-pin net to another pin of the multi-pin net. The routing congestion for each bucket is computed as a ratio of the bucket usage to bucket capacity. For L-shaped routes (having at least one bend in a bucket), the probabilistic usage is proportional to a scale factor a which is a ratio of a minimum number of available wiring tracks for a given route to a sum of minimum numbers of available wiring tracks for all possible routes. For Z-shaped routes (having at least two bends in two respective buckets), the probabilistic usage is equal to a ratio of a minimum capacity of a given route to a sum of minimum capacities of all routes having an associated orientation with the given route. Assignment of the usage values may entail the creation of a temporary usage map of the net buckets with an initial value of zero usage in every temporary usage map bucket, thereafter storing usage values in corresponding buckets of the temporary usage map, and deriving a final usage map from the temporary usage map.
Owner:GLOBALFOUNDRIES INC

Congestion prediction algorithm based on historical and peripheral intersection data

A congestion prediction algorithm based on historical and peripheral intersection data comprises a first step of performing real-time updating and preprocessing on traffic data; a second step of inputting a predicted target intersection and a time interval; a third step of matching the traffic flow data with historical data of the current area to find out a similar time interval and then carryingout prediction. According to the method, the problem of " traffic flow prediction " is solved by utilizing an algorithm idea of non-parameter regression, the traffic flow is predicted according to historical data and peripheral intersection data, and the traffic data flow is effectively predicted. The congestion situation of the target intersection at the demand time is predicted according to therequirement of a user on the traffic jam prediction situation, and the traffic flow can be efficiently and accurately predicted.
Owner:ZHEJIANG UNIV OF TECH

GPS data-based traffic congestion propagation path calculating method

The invention relates to a GPS data-based traffic congestion propagation path calculating method. By processing and analyzing a large quantity of data collected by a GPS floating vehicle, an urban road network traffic congestion propagation path can be calculated. First, according to the large quantity of GPS data collected by the floating vehicle, average speed of each road segment in a road network is calculated; according to the average speed of each road segment, a congestion time period of each road segment is calculated; according to the congestion time period of each road segment in the road network, a congestion propagation path and key road segments are calculated. According to the GPS data-based traffic congestion propagation path calculating method, based on a sequence of the congestion time period of each road segment in a regional road network, road congestion propagation condition in the road network can be estimated. The calculated key road segments in the propagation path can be applied to police strength deployment, congestion prediction and road planning.
Owner:HANGZHOU YUANTIAO TECH CO LTD

Method and apparatus for automatic selection of alternative routing through congested areas using congestion prediction metrics

A scheduling system and method for moving plural objects through a multipath system described as a freight railway scheduling system. The scheduling system utilizes a cost reactive resource scheduler to minimize resource exception while at the same time minimizing the global costs associated with the solution. The achievable movement plan can be used to assist in the control of, or to automatically control, the movement of trains through the system. Alternative routes through congested areas are automatically selected using congestion prediction metrics.
Owner:GE GLOBAL SOURCING LLC

Urban traffic congestion prediction and prevention system

The invention discloses an urban traffic congestion prediction and prevention system comprising a vehicle-mounted navigation device, a wireless network and a traffic information center. The traffic information center is connected with a meteorological station and traffic police information center via the internet to obtain road condition information and also sends road condition data to a vehicle.The vehicle-mounted navigation device plans a driving path based on the received road condition information and sends the driving path and own vehicle information to the traffic information center. The traffic information center calculates road sections that may have congestion during follow-up periods based on the received vehicle information and the driving path, sends congestion prediction information to the vehicle, and sends out instructions of planning paths again to some vehicles that will pass the congested road sections. The vehicle-mounted navigation device makes a new path plan fordriving based on the new path and sends the new path to the traffic information center; and the traffic information center calculates all paths again and sends congestion prediction information and apath re-planning instruction to the vehicle. On the basis of the repeated adjustment, the prediction congestion rates of all road sections can be reduced.
Owner:邵文远

Traffic data restoration method based on generative adversarial network

A traffic data restoration method based on a generative adversarial network is a data restoration method of machine learning. A missing traffic flow matrix often affects the performance of the intelligent traffic system, such as wrong congestion prediction and route guidance. According to the method, the adversarial training idea is introduced into traffic flow data restoration, and the whole model is divided into two parts, namely a generation network and an identification network. A network part repair missing traffic flow matrix is generated, whether the repaired traffic flow matrix conforms to real distribution or not is judged by the identification network, and the time sequence coherence of the traffic flow matrix is ensured by utilizing consistency constraint. According to the method, the accuracy of traffic data restoration is improved, and accurate estimation of the traffic flow incomplete part is realized.
Owner:BEIJING UNIV OF TECH

Expressway congestion management and control system based on multi-source data

PendingCN113538898AImprove emergency command capabilitiesDynamic real-time traffic information serviceDetection of traffic movementDesign optimisation/simulationControl systemSimulation
The invention discloses an expressway congestion management and control system based on multi-source data, and the system comprises an intelligent perception subsystem, a data management subsystem, a congestion prediction and early warning subsystem, an online simulation subsystem, and a visual application subsystem. The intelligent perception subsystem is connected with the data management subsystem, the data management subsystem is connected with the congestion prediction and early warning subsystem, the congestion prediction and early warning subsystem is connected with the online simulation subsystem and the visual application subsystem;the online simulation subsystem and the visual application subsystem are connected with each other; the intelligent perception subsystem provides basic traffic data support, the data management subsystem processes and stores basic traffic data, the congestion prediction and early warning subsystem performs traffic state evaluation, and the online simulation subsystem performs simulation testing to find an optimal management and control scheme suitable for a current traffic flow state; and the visual application subsystem is used for effect presentation and information release.
Owner:南京领航交通科技有限公司

Network optimization method and device

ActiveCN104768171AEfficient and reliable information technology meansSimple methodWireless communicationPerformance indexCongestion prediction
The invention discloses a network optimization method and device. The method comprises that a polling period is determined according to the communication load; rolling sampling is carried out on all preset communication support cells according to the polling period to obtain the instantaneity index of each the communication support cell; and congestion of each communication support cell is predicted according to the obtained instantaneity index as well as historical performance index under the same communication support scene; and optimization adjustment is carried out according to the congestion prediction result of each communication support cell.
Owner:中国移动通信集团海南有限公司 +1

Traffic intersection congestion prediction method based on machine learning

The invention discloses a traffic intersection congestion prediction method based on machine learning, and belongs to the technical field of machine learning. According to the method, the congestion degree of a corresponding traffic intersection is predicted through multiple structural features, the requirement for equipment is low, and the speed is high; meanwhile, the degree of intersection congestion within a long time can be predicted, and an unstable model is adopted as a base learner for training; and finally, the deviation and variance of the model are reduced through integrated learning and model fusion, so that the generalization ability of a prediction result of the model in an actual scene is ensured.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA

Short-time road traffic congestion prediction method based on CS-SVR algorithm

The invention discloses a short-time road traffic congestion prediction method based on a CS-SVR algorithm, and the algorithm belongs to the technical field of road congestion prediction. The method comprises the following steps that (1) original data is acquired and processed; (2) all parameters are initialized by adopting a Cuckoo Search (CS) algorithm; (3) a target function is built, and initial fitness calculation is carried out; (4) random walk is carried out, and a new bird nest position is calculated; (5) the optimal objective function value is updated; (6) whether a host bird changes or reserves the bird nest position or not when an external bird egg is found is judged, the global optimum position is selected, moreover, whether the number of iterations is reached or not is judged,and if the maximum iteration parameter is not reached, the operation is returned to the step S03, and iteration algebra is plus 1; and (7) if the maximum iteration algebra is reached or the precisionrequirement is met, SVR is used for carrying out traffic congestion prediction on a test sample.
Owner:NANJING UNIV OF SCI & TECH

Intelligent traffic signal light transformation method

The invention relates to an intelligent traffic signal light transformation method, which is applied to the field of traffic signal light control at intersections and solves a problem that the green light is still on when the front phase is congested and a problem of how to control a signal light algorithm according to video vehicle data. The intelligent traffic signal light transformation methodcomprises a congestion prediction algorithm, a signal light combination selection algorithm, a preferential green light algorithm and a delayed green light algorithm. The congestion prediction algorithm is adopted, the naive Bayesian, decision-making tree, logistic regression, K-nearest neighbor, random forest, AdaBoost and gradient lifting methods in a statistical machine learning method are applied, historical data collected from video serves as a training data set, four characteristic attributes such as the intersection leaving distance, the average speed, the speed variation and the average density and the congestion condition are enabled to serve as training data, the average speed, the speed variation and the average vehicle density corresponding to the intersection leaving distancerange in the current real-time video of the road are enabled to serve as characteristic attributes, the congestion probability at a certain position after a certain time is predicted by applying the statistical machine learning method, the transformation of the signal lights is controlled according to the congestion probability, and judging the best phase combination, the preferential green lightphase and the green light delay time according to the number of vehicles inspected and calculated by the real-time video of the road.
Owner:张鹏

Method and system for predicting people crowdedness

The invention discloses a method for predicting people crowdedness and the method comprises: first, obtaining the image frame sequence of a to-be-measured area; inputting the image frame sequence into a pedestrian detection module; through the pedestrian detection module, obtaining the characteristic vectors of the human face images; through the characteristic vectors of the human face images of two adjacent frames, obtaining and outputting the number of the traveling people; based on the number of the traveling people, calculating the people density; and inputting the people density into a people crowdedness predicting module to calculate and output the people crowdedness predicting vector signal. According to the method and the system of the invention, a support vector machine is utilized to train the predicting model, which increases the computation efficiency of the system and the precision of the predicting result so that the method and the system become more adaptable to the data and the environment. In addition, as the method and the system are equipped with a people crowdedness training module and a historical database, the system is empowered with the ability for self-adaptive learning, and therefore, the manual involvement is reduced, the human resource and use difficulty can be saved, making the method and system adaptable to complex and diverse environments. Along with the increase in the learning time and the enlargement of the historical data, the people crowdedness predicting model can achieve more precise predicting results, and the cost in doing so is also reduced.
Owner:CHONGQING UNIV OF ARTS & SCI

Traffic information distributing apparatus and traffic information distributing method

InactiveCN101523460AIncreased communication costsReduce the amount of communication informationInstruments for road network navigationData processing applicationsComputer scienceMarine navigation
In a case where a CPU 11 provided in an information distribution center 3 has received a request command for requesting predicted traffic information transmitted from a navigation apparatus 2 as well as vehicle information such as a navigator identifying ID, coordinate data of a vehicle position, or coordinate data of a destination, the CPU 11 searches a basic route based on update-purpose map information 14A, and sets a distribution range serving as a transmission target of traffic information 16A, 16B, and 16C. Then, the CPU 11 generates the predicted traffic information 16C such as congestion prediction information corresponding to the distribution range, extracts the predicted traffic information 16C of each link having a difference in the generated predicted traffic information 16C and the current traffic information 16A, and distributes the extracted predicted traffic information 16C to the navigation apparatus 2 together with a link ID of a corresponding link.
Owner:AISIN AW CO LTD +1

Traffic jam prediction method and system based on jam portrait

The invention discloses a traffic jam prediction method and system based on a jam portrait. The method comprises the steps of obtaining traffic data, and obtaining the jam portrait data of a traffic bottleneck point in the traffic data according to the traffic data, wherein the jam portrait data reflects the road condition state of the traffic bottleneck point; determining congestion portrait feature parameters of the traffic bottleneck point according to the congestion portrait data of the traffic bottleneck point; and performing congestion prediction on the traffic data according to the congestion portrait feature parameters to obtain a prediction result which is used for traffic management. According to the invention, the traffic data can be predicted based on the congestion portrait, the obtained prediction result can be used for active traffic guidance management, the police basis of the traffic police can be determined according to the prediction result, a basis can be provided for optimization timing of signals and the like, and a basis can also be provided for travel route planning.
Owner:北京奥泽尔科技发展有限公司

Traffic jam prediction method and device and electronic equipment

The invention discloses a traffic jam prediction method and device and electronic equipment. The method comprises the steps: performing road condition similarity processing between every two lanes on obtained road feature data of traffic road conditions to acquire lane similarity data, wherein the road feature data comprises TMC data of multiple periods before a to-be-predicted period; processing the lane similarity data by adopting a first preset network model, extracting lane space topological structure features from the lane similarity data, and outputting to obtain a first processing result; processing the first processing result by adopting a second preset network model, and outputting to obtain a second processing result; and determining a congestion prediction result of at least one lane in the road in the to-be-predicted period according to the second processing result. According to the technical scheme, the accuracy of traffic jam prediction can be improved.
Owner:ZHIDAO NETWORK TECH (BEIJING) CO LTD

Traffic jam prediction method and system

The invention relates to a traffic jam prediction method and system. The method comprises the following steps: acquiring historical trajectory data of all vehicles in a road network to be predicted, wherein the to-be-predicted road network is composed of a plurality of road sections; for any road section, obtaining the average speed of the road section in a set time period according to the historical trajectory data of all the vehicles in the set time period of the road section; determining the average speed of each road section in all time periods as a congestion feature matrix of the road network to be predicted; obtaining an adjacent matrix of the to-be-predicted road network according to the position relation of all the road sections in the to-be-predicted road network; and inputting the congestion feature matrix of the road network to be predicted and the adjacent matrix of the road network to be predicted into a congestion prediction model to obtain a congestion prediction result. According to the invention, the prediction condition of traffic jam can be improved.
Owner:CHANGCHUN UNIV OF SCI & TECH

Congestion prediction method and device

The present invention discloses a congestion prediction method and device. The method comprises the steps of: receiving first data information sent by a first control sensor, and obtaining a first characteristic parameter value in the first data information; determining an associated second monitoring area according to a first monitoring area and preset associated sets; receiving second data information sent by a second control sensor, and obtaining a second characteristic parameter value in the second data information; and determining congestion information of the first monitoring area at a first time length being subjected to preset delayed at a current time period according to the first characteristic parameter value, the second characteristic parameter value and a monitoring model completing training in advance. In the embodiment of the invention, one associated set is stored in each monitoring area, so that the congestion information of the first monitoring area is determined according to the first monitoring area, characteristic parameter values of associated second monitoring area and the monitoring model when congestion prediction is performed. Therefore, the accuracy of congestion prediction is improved.
Owner:ZHEJIANG DAHUA TECH CO LTD

Traffic congestion propagation prediction method based on space-time diagram convolutional neural network

ActiveCN112419718ASolve the accuracy problemSolve problems such as time-consuming algorithm operationsDetection of traffic movementForecastingData setFeature extraction
The invention provides a traffic congestion propagation prediction method based on a space-time diagram convolutional neural network, and relates to the technical field of traffic big data mining andanalysis. Traffic data source data are acquired, a traffic speed data set and sensor network adjacent matrix data are made, a data driving mode is adopted, a space-time diagram convolutional neural network is introduced, and the traffic speed prediction precision of a target road section is improved. A speed prediction module is introduced into a congestion propagation model framework, so that thetraffic congestion prediction precision is improved, the traffic congestion propagation process is accurately represented, and the problems of low prediction precision, time-consuming algorithm operation and the like caused by poor spatial feature extraction of an existing traffic congestion propagation prediction scheme are solved; and the propagation condition of the congestion occurrence roadsection to the adjacent traffic road in the future time period is predicted.
Owner:东北大学秦皇岛分校

Method for predicting traffic congestion probability based on user feedback mechanism

The invention discloses a method for predicting a traffic congestion probability based on a user feedback mechanism. The method comprises steps of determining a traffic flow influencing factor coefficient, determining prediction and correction of a traffic flow, predicting traffic congestion by using probability, and correcting a congestion index. According to the method disclosed by the invention, with the corrected historical flow data as a predicted reference flow, the prediction accuracy of the traffic flow is improved and the good foundation is laid for precise prediction. With consideration of feedback of traffic congestion index issuing by a driver, a prediction result is adjusted, so that the prediction accuracy, adaptability, and practicability are high. Moreover, the probabilityof congest state occurrence is calculated; the prediction result modes are enriched; the result becomes direct; the congestion prediction mode become novel; the prediction credibility is improved; andthe effective and useful reference can be provided for travelling of the driver.
Owner:SOUTHEAST UNIV

Server device, congestion prediction information display system, congestion prediction information distribution method, congestion prediction information display method, and program

According to the present invention, an information terminal (2) transmits information representing the current location and the acceleration to a server device (3). The server device (3) receives the information representing the current position and the acceleration from the information terminal (2), generates a congestion prediction degree using the information representing the acceleration, associates the congestion prediction degree and map data so that the congestion prediction degree can be displayed on a road map, and transmits association information representing the association. The information terminal (2) uses the association information transmitted from the server device (3) to display the congestion prediction degree on a road map on a display device (16).
Owner:HONDA MOTOR CO LTD

Sensor-network-based novel intelligent transportation model design method

The invention discloses a sensor-network-based novel intelligent transportation model design method. The method comprises: according to an indicator function, road traffic volume collection, intersection delay time, and vehicle congestion prediction value are calculated to realize intelligent transportation guidance scheduling. According to the invention, the method has the following advantages: the system model is guided and scheduled by using a transportation performance indicator function; with introduction of the indicator function, credibility and guidance of system implementation are improved; and thus the method has the certain study value in realizing sensor-network-based intelligent transportation.
Owner:NANJING UNIV OF SCI & TECH

ETC portal frame-based highway congestion 5G network prediction system

The invention discloses an ETC portal frame-based highway congestion 5G network prediction system which comprises an ETC portal frame and a detection frame. Data acquisition modules are arranged on the ETC portal frame and the detection frame; the input ends of the data acquisition modules are connected with a positioning module, a monitoring module, a vehicle speed detection module, a counting module, a photographing module, a vehicle distance detection module and a vehicle identification module, the output ends of the data acquisition modules are connected with a cloud uploading module, the output end of the cloud uploading module is connected with a cloud data processing module, the cloud data processing module is in bidirectional connection with a cloud storage module, the output end of the cloud data processing module is connected with an integrated control module, the output end of the integrated control module is connected with a driving module, and the output end of the driving module is connected with a warning module. The data acquisition modules carry out fixed-distance detection on vehicles on a highway, and a main display module and an auxiliary display module in the warning module carry out vehicle speed and vehicle distance reminding on vehicles coming behind, so that an ETC portal frame, a 5G network and congestion prediction are well combined.
Owner:荆朝辉

Predicting short-term traffic flow congestion on urban motorway networks

A system and method for the prediction of vehicle traffic congestion on a given roadway within a region. In particular, the computer implemented method of the present disclosure utilize real time traffic images from traffic cameras for the input of data and utilizes computer processing and machine learning to model a predictive level of congestion within a category of low congestion, medium congestion, or high congestion. By implementing machine learning in the comparison of exemplary images and administrator review, the computer processing system and method steps can predict a more efficient real time congestion prediction over time.
Owner:ADETILOYE TAIWO O
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