84 results about "Traffic bottleneck" patented technology

Network configuration hierarchy information is maintained using flexible mechanisms and methods for establishing routes and transferring information between nodes in ad-hoc data communication networks using on-demand multicast and unicast techniques. Communication nodes use network topology information to build and maintain a dynamically mobile, wireless, ad-hoc network capable of efficiently routing both unicast and multicast traffic. Network nodes that facilitate the collection and distribution of network topology and routing data are dynamically selected, configured, and maintained. Network traffic overhead necessary for maintaining and distributing network routing table information is held to a minimum and efficiently distributed across the network, thereby reducing the potential for network traffic bottlenecks due to network overhead processes.

The invention provides an intelligent networked transportation system for an overall road network. The intelligent networked transportation system comprises a sensing, communication and control modulefor managing the entire transportation system connected by road segments and nodes. When intelligent networked vehicles travel in a transportation network, they will route different types of road facilities such as basic road sections, highways, main roads, traffic bottleneck sections, interlaced and confluence sections, intersections, the start or last one kilometer if the road, parking areas, bridges, tunnels, multi-modal hubs, etc. These different sections and nodes in a transportation network have significant differences in geometric design and facility characteristics. The invention provides a specific intelligent networked system subsystem design to adapt to different types of road characteristics and achieve complete door-to-door travel.

An apparatus and method implemented in hardware and embedded software that improves performance, scalability, reliability, and affordability of Storage Area Network (SAN) systems or subsystems. The apparatus contains host computers (application servers, file servers, computer cluster systems, or desktop workstations), SAN controllers connected via a bus or network interconnect, disk drive enclosures with controllers connected via network interconnect, and physical drive pool or cluster of other data storage devices that share I / O traffic, providing distributed high performance centrally managed storage solution. This approach eliminates I / O bottlenecks and improves scalability and performance over the existing SAN architectures. Although this architecture is network interconnect (transport) neutral, additional improvements and cost savings could be made by utilizing existing, of the shelf, low latency and high speed hardware such as Advanced Switching (AS) or Myrinet networks as a transport for data, Small Computer System Interface (SCSI) and other commands and messages. Using AS or Myrinet network as a replacement for Fiber Channel (FC) would significantly reduce the cost of such SAN systems and at the same time boost performance (higher data transfer rates and lower latencies). This invention is about defining hardware and software architectural solution that is specifically designed to eliminate I / O traffic bottlenecks, improve scalability, and reduce the overall cost of today's SAN systems or subsystems. This innovative solution, in addition to it's performance superiority compared to the existing solutions, should also provide 100% compatibility with the all existing Operating Systems (OS), File Systems (FS), and existing applications.

Traffic congestion detection, classification and identification includes analysis of link-speed data representative of vehicular speed and capacity on one or more roadway segments to determine non-linear, multi-segment traffic bottlenecks in a transportation network graph. Link-speed data is processed to detect bottleneck conditions, classify bottlenecks and bottleneck-like traffic features according to their complexity, and identify sustained or recurring bottlenecks. Such a system and method of traffic congestion detection, classification and identification provides a framework for using this link-speed data to detect the head and queue of bottlenecks on a directed graph representing the transportation network, classify the resulting bottlenecks and bottleneck-like traffic features according to the shape of their queue, and identify and measure sustained or recurrent bottlenecks even when the location, or head, of the bottleneck varies slightly across multiple time periods or across multiple days.

The invention provides a method for identifying urban expressway traffic bottlenecks. The method comprises a step of collecting the mobile navigation data of a road vehicle and road fixed detector data, a step of carrying out pretreatment on the collected data, matching the data of different sources, and determining the flow-speed distribution of each detector section, a step of determining a supersaturation critical speed and a supersaturation probability according to the flow-speed distribution, a step of determining supersaturation probability and detector position distribution, and identifying traffic bottlenecks; and classifying the identified urban expressway traffic bottlenecks, and giving corresponding control measures for different types of traffic bottlenecks.

The invention relates to a traffic control method for passing efficiency improvement facing different traffic bottleneck sections. For a rapid road bottleneck section, division is carried out based on geometrical characteristics; different traffic control methods are employed for different traffic bottleneck types; an optimal control method in a current traffic flow state is determined based on traffic demands of a main road and a ramp; and optimized control on a traffic flow is realized by employing ramp controlling and variable speed-limiting controlling comprehensively. Therefore, defects that various traffic control methods are not targeted and applicability and advantages and disadvantages of different bottleneck types and control principles are not taken into consideration in the prior art can be overcome. Advantages of ramp controlling and variable speed-limiting controlling are realized fully based on a practical measuring traffic flow state. The road passing efficiency is improved by reducing the system passing time in a range of the rapid road section.

A Storage Area Network (SAN) system has host computers, front-end SAN controllers (FE_SAN) connected via a bus or network interconnect to back-end SAN controllers (BE_SAN), and physical disk drives connected via network interconnect to the BE_SANs to provide distributed high performance centrally managed storage. Described are hardware and software architectural solutions designed to eliminate I / O traffic bottlenecks, improve scalability, and reduce the overall cost of SAN systems. In an embodiment, the BE_SAN has firmware to recognize when, in order to support a multidisc volume, such as a RAID volume, it is configured to support, it requires access to a physical disk attached to a second BE_SAN; when such a reference is recognized it passes assess commands to the second BE_SAN. Further, the BE_SAN has firmware to make use of the physical disk attached to the second BE_SAN as a hot-spare for RAID operations.

The present invention provides a technical scheme capable of improving highway traffic and its correspondent installation. The invented scheme and installation can make installation transformation and intelligent management for typical traffic bottle-neck road of existent high-speed highway and main road system, and its key is characterized by that on the proper locations in the road system the queueing and parking installations can be respectively set so as to improve the traffic congestion condition of highway.

An urban traffic bottleneck mining method includes the following steps that firstly, microwave data and floating car data are cleaned, wherein data interpolation is carried out to solve the data missing problem of the microwave data and the floating car data; secondly, road segment traffic states are estimated by taking set time quanta as time granularity; thirdly, the total occurrence probability of traffic congestion of each road segment in the set time quanta within a statistical cycle is calculated; fourthly, the balance degree of traffic congestion occurring at each day within the statistical cycle is calculated; fifthly, the upper bound of the balance degrees of traffic congestion within the statistical cycle is worked out; sixthly, the normalization balance degree of traffic congestion within the statistical cycle is worked out; seventhly, the severity of traffic bottlenecks is figured out. The urban traffic bottleneck mining method has good reliability.

The invention discloses a traffic bottleneck identification method in a complicated traffic environment, mainly solving the problem of serous traffic congestion because the prior art cannot satisfy the current requirement for traffic. The implementation steps of the traffic bottleneck identification method are 1) using an undirected graph with weight to represent a complex network which abstracts a practical traffic network; 2) utilizing a tolerance flow allocation algorithm to perform balanced flow allocation for a user on the abstract network topological graph; 3) distributing a weight for each road segment in the network, wherein the weight is a zero flow impedance on each road segment; 4) according to the network after the weights are distributed, searching for a minimal spanning tree for the zero flow impedance; and 5) performing priority ranking for the degree of importance of the bottlenecks in the minimal spanning tree obtained from the step 5). The traffic bottleneck identification method in an urban traffic network can provide quantitative description for the degree of importance of the bottlenecks for a traffic management department to enable the traffic management department to accurately grasp the distribution characteristics of the traffic bottlenecks, reasonably plan the traffic network topology and match the traffic demand for each road segment of a road network with the traffic capacity, and can be applied to an integrated traffic dispersion system.

The invention provides a traffic capacity estimation method and device of a congestion region and data processing equipment. The method comprises the steps of acquiring historical travelling track data of a plurality of vehicles on a target road; acquiring a road speed distribution matrix according to the historical travelling track data; identifying a bottleneck generation position and bottleneckgeneration time of a traffic bottleneck from the road speed distribution matrix; determining a critical travelling speed and a congestion propagation speed of the congestion region caused by the traffic bottleneck according to the bottleneck generation position and the bottleneck generation time; and performing forecast calculation on a traffic flow basic map according to the critical travellingspeed, the congestion propagation speed, preset congestion vehicle density and a preset smooth travelling speed, and outputting corresponding vehicle flow as traffic capacity of the congestion region.Therefore, the track data which is low in cost and is capable of completely and continuously reflecting a road traffic state is used for estimating the traffic capacity of the congestion region, an estimation result can be more accurate, and reliable reference data is provided for traffic control.

The invention discloses a data transmission method in a wireless access system, which comprises that a base station directly sends control information to a mobile station and / or a relay station; the mobile station and / or the relay station transmits corresponding data to next hop according to the control information until the data is transmitted to a target station. The invention also discloses a base station, a delay station and a wireless access system which use the data transmission method in the wireless access system. The method of the invention can effectively realize peer-to-peer communication between the mobile station and / or the relay station, can flexibly select an optimal transmission path so as to achieve load balancing, and can effectively overcome the problem of traffic bottleneck and transmission delay at the base station in the prior art, and meanwhile, can still guarantee the management control function of data transmission by the base station.

The invention relates to a network equipment version loading method, and a device and a system thereof, belonging to the field of network communications. The method comprises the following steps: receiving an upgrade message sent from a version server; acquiring download images of local equipment and neighboring equipment; and selecting the neighboring equipment from an upgrade equipment list according to the download images, and acquiring the file segments which are not downloaded from the selected neighboring equipment. In the technical scheme provided by the embodiment of the invention, the network equipment can download the file segments from the neighboring equipment, so as to reduce traffic load of the version server, and solve the traffic bottleneck problem of the version server in the case of batch version loading or version upgrade in the prior art.

The invention belongs to the technical field of traffic engineering, and relates to a construction area traffic organization scheme design method considering network load balancing. The method comprises the following steps: (1) setting a road network balance hypothesis; (2) constructing a traffic flow redistribution model based on network equalization; (3) solving a traffic flow redistribution model based on network equalization; (4) identifying road network traffic bottlenecks based on a network balance loading result; (5) designing a traffic bottleneck eliminating method based on a network balance loading result; According to the invention, a traditional qualitative analysis method is improved; A'traffic bottleneck 'concept is introduced, a traffic flow redistribution model based on network equalization is established from the overall level of a road network by taking network equalization as a target for special roads and traffic conditions of a construction influence area, reasonable constraint conditions are set, the traffic capacity of a surrounding road network is fully utilized, and the traffic flow is distributed in an equalized manner.

Traffic congestion detection, classification and identification includes analysis of link-speed data representative of vehicular speed and capacity on one or more roadway segments to determine non-linear, multi-segment traffic bottlenecks in a transportation network graph. Link-speed data is processed to detect bottleneck conditions, classify bottlenecks and bottleneck-like traffic features according to their complexity, and identify sustained or recurring bottlenecks. Such a system and method of traffic congestion detection, classification and identification provides a framework for using this link-speed data to detect the head and queue of bottlenecks on a directed graph representing the transportation network, classify the resulting bottlenecks and bottleneck-like traffic features according to the shape of their queue, and identify and measure sustained or recurrent bottlenecks even when the location, or head, of the bottleneck varies slightly across multiple time periods or across multiple days.

The invention relates to a road bottleneck identification method and system based on congested transmission analysis. The method comprises the following steps: determining a congested road section ofa road and recording congestion time; forming a plurality of groups of congested road section pairs related to traffic congestion and sequencing; deleting the congested road section pairs, which do not meet pre-set frequency, in the sequenced congested road section pairs; constructing a directed graph with a tree-shaped structure; decomposing the directed graph and maximizing the quantity of directed edges of a tree to form a traffic congestion tree; carrying out weight distribution on each vertex of the traffic congestion tree; analyzing the probability of transmitting from one vertex to theother adjacent vertex in the traffic congestion tree according to a Markov model; calculating a comprehensive weight value of each vertex in the traffic congestion tree and determining a traffic congestion bottleneck according to comprehensive weight. According to the road bottleneck identification method and system provided by the invention, a time and space relationship and a causal relationshipof transmission of the traffic congestion in an urban road net are comprehensively considered, and a traffic bottleneck in the urban road net can be identified; the road bottleneck identification method and system are applicable to traffic bottleneck identification requirements under an urban complicated road net topological scene.

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.

The invention relates to a traffic bottleneck prediction method and system based on congestion diffusion and electronic equipment. The method comprises the following steps: step a, acquiring historical road condition data of all roads in a traffic network structure, and evaluating road conditions according to the historical road condition data; step b, based on the road condition evaluation result, constructing a congestion diffusion state transfer matrix by utilizing space-time correlation; and step c, utilizing the sub-modality of the congestion diffusion state transition matrix, and adopting a greedy algorithm to search a node which has the greatest influence on the traffic state in the traffic network structure to obtain a traffic bottleneck prediction result. Traffic jam propagation is predicted in real time based on the jam diffusion model of traffic jam spatial-temporal correlation, and on this basis, traffic bottleneck prediction is performed by using an influence maximizationtheory in a specific traffic network jam state, so that the purpose of discovering dynamically changing traffic bottlenecks in real time in a complex traffic environment is achieved.

The invention discloses a method of identifying urban expressway recurrent traffic bottlenecks, which is applied to a road condition prediction system provided with a plurality of detectors. The method comprises the following steps: data acquisition is carried out; data fusion is carried out; a corresponding synthesis rule is selected for the traffic flow data of each road section; a saturation critical speed and a supersaturation probability are determined according to flow-speed distribution; traffic bottlenecks are identified; and corresponding countermeasures are proposed according to different types of traffic bottlenecks. Based on fusion of mobile navigation data and data monitored by fixed detectors, a new method of identifying urban expressway recurrent major traffic bottlenecks isdisclosed, data fusion utilization and data mining under the current computer processing capability can be effectively realized, the expressway traffic bottlenecks can be recognized from the urban level, and more accurate and scientific advice is provided for traffic congestion management and optimization.

The invention discloses an online traffic bottleneck prediction control method based on an FPGA (Field Programmable Gate Array) and an improved Ross model, which is used for solving the technical problem that the conventional method is unlikely to perform online prediction regulation control on traffic bottleneck in the practical high-speed road or blocked road. The online traffic bottleneck prediction control method comprises the following steps: improving a Ross model; fusing a variable information display board into the Ross model; carrying out predictive analysis on the high-speed road or blocked road through the improved Ross model based on an FPGA platform; finding out the traffic bottleneck according to the defined state variable; giving out control schemes for gate control and the variable information display board, and introducing the control schemes into a prediction model by priority to find a reasonable control scheme; and carrying out online control on the traffic bottleneck, so that the traffic bottleneck in the high-speed road or blocked road can be effectively controlled.

The invention discloses a dynamic speed limit control method and system based on an intelligent network connection vehicle, a terminal and a readable storage medium, and the method comprises the steps: through the close connection between an intelligent vehicle-mounted information terminal and an information network, in a scene that a traffic bottleneck exists at the downstream of a road section, intelligent network connection vehicles are used for leading manual driving vehicles to form a motorcade for dynamic speed limit control, so that the safety of highway speed limit control is improved, the cost of speed limit control is reduced, the road traffic accident rate is reduced, and the highway traffic safety and efficiency are improved. Deceleration parameters of a head vehicle in a motorcade are controlled based on a dynamic speed limit control model, and a neural network model is further constructed by using the dynamic speed limit control model and is applied to a vehicle speed control process. The method can overcome the defects of the existing expressway dynamic speed limit control, effectively improves the traffic safety of the expressway, and is suitable for expressway traffic safety management and control under the condition that future network connection vehicles and non-network connection vehicles are mixed.

The invention discloses a road network traffic bottleneck identification method integrating wavelet transform and image binarization. The method mainly comprises the following steps: inputting speed time sequence data, and searching time and positions of a speed sudden change point and an output speed sudden change point according to a wavelet transform principle; sorting the speed values of the speed sudden change points from small to large, selecting a speed threshold value according to a quartile method, and converting speed time sequence data into a speed space-time thermodynamic diagram;setting a speed threshold as an image binaryzation parameter, and dividing the speed space-time thermodynamic diagram into a congestion area and a non-congestion area through image binaryzation; finally, for irregularly scattered congestion areas in the binarized image, considering that the influence of the irregularly scattered congestion areas on the congestion of the whole traffic network is relatively small, eliminating irregularly and randomly distributed pixel points and small bottleneck points by utilizing median filtering so as to improve the calculation efficiency and the identification accuracy of frequently occurring traffic bottlenecks in the urban road network.

The invention discloses an on-line traffic bottleneck predictive control method based on a field programmable gate array (FPGA) and an improved dispersed macroscopic D model. The method is used for solving the technical problem that by means of existing methods, on-line predictive control of traffic bottlenecks in actual highways or closed roads is difficult to achieve. The method improves a dispersed macroscopic D model and integrates a variable information display board into the dispersed macroscopic D model, the highways or the closed roads are wholly subjected to predictive analyzing through the improved dispersed macroscopic D model on the basis of an FPGA platform, the traffic bottlenecks are found according to defined state variables, control schemes of a turn port and the variable information display board are given, and the control schemes are brought to a prediction model according to priority to find a reasonable control scheme so that on-line control of the traffic bottlenecks is achieved, and the traffic bottlenecks on the highways or the closed roads can be effectively controlled.

The invention discloses an on-line predictive control method of traffic bottlenecks based on an FPGA and an improved Papageorgiou-E model, and aims to solve the technical problem that on-line predictive control is difficult to perform on the traffic bottlenecks on actual highways or blocked roads in the existing method. According to the method, the Papageorgiou-E model is improved, a variable information display board is integrated into the Papageorgiou-E model, predictive analysis is performed on highways or blocked roads based on an FPGA platform and the improved Papageorgiou-E model, the traffic bottlenecks are found according to a defined state variable, and then control schemes of ramp control and the variable information display board are provided and taken to prediction models according to priority to find reasonable control schemes to perform on-line control on the traffic bottlenecks, so that the traffic bottlenecks on the actual highways or blocked roads can be effectively controlled.

The invention relates to the technical field of trajectory planning, in particular to a motorcade optimal trajectory control method and device, electronic equipment and a storage medium, and the method comprises the steps: determining an initial state and a target state of a motorcade; based on the relative motion between the vehicles, dispersing the road space where the motorcade is located into uniform grid spaces according to a preset rule, generating discrete grid spaces, representing the discrete grid spaces with a state matrix, and generating a graph space for a motorcade state space; based on a vehicle team state space graph space, a step-by-step expansion strategy that only one intelligent network connection vehicle is allowed to move within any step number is adopted, a distributed random A * algorithm is used for solving a vehicle team recombination optimization moving track, and optimal track control is carried out on a vehicle team. Therefore, the vehicle team can be efficiently converted from any initial layout state to any target layout, efficient cooperative driving of the intelligent network connection vehicle team is realized, the road traffic capacity can be greatly improved in a traffic bottleneck road section, and meanwhile, the traffic safety of the vehicle team is guaranteed.

The invention discloses a transport hub system for concurrent free flow of sixteen directions at a crossroad, which is composed of a concave lane and an arch bridge form effective height for car running, and four left change lanes are arranged at the bottom of an approach bridge of the arch bridge and at the corner of a pier, thereby really realizing the concurrent free flow of the sixteen directions at the cross road, greatly increasing the car running speed, basically solving the traffic bottleneck problem, effectively reducing the vertical height and the span of 50 percent of bridge climbing and the depth of the concave lane down grading, saving land use without affecting city appearance and scenic visual field, maintaining the coordination and elegance of the surrounding environment, and providing a good development platform for the prosperity of the city; and the adoption of guard rail web strips, pedestrian overpasses or tunnels and nonmotorized vehicle lanes and the implementation of man and car separation basically avoid the occurrence of tragic accidents that a man is hit by a car, the occurrence probability of the traffic accidents is greatly reduced. The system of the invention is widely applicable to the construction of traffic road junctions, in particular to the reformation and reconstruction of the cross roads in old cities and inner cities of a metropolis.

A system and method for packet data transmission is described, particularly in the case of dispersed networks that are at least occasionally in data communication with each other (such as in a wide area network), in which efficient packet transmission is provided while avoiding traffic bottlenecks and the like. In general, a combination of multicast communication and peer-to-peer communication is used to set up data links between nodes (such as servers and the like) on different networks, especially in a wide area network environment. Multicast communication is characteristically used within a respective network whereas peer-to-peer communication is used between nodes in different networks. The disclosed system and method is useful in network environments involving third-party application service providers.

The invention discloses an on-line traffic bottleneck control method based on a field programmable gate array (FPGA) and an improved light water reactor (LWR) model and aims to solve the technical problem that existing methods can not perform on-line predictive regulating and controlling for traffic bottlenecks in actual expressways or blocked roads. According to the on-line traffic bottleneck predictive control method, the LWR model is improved, a variable information display board is integrated into the LWR model, a whole predictive analysis is performed for the expressways or the blocked roads through the improved LWR model based on the FPGA platform, the road bottleneck is found out according to defined state variables, then control schemes of junction control and the variable information display board are provided, the control schemes can be taken into prediction models according to priority levels, a reasonable control scheme can be found out, the on-line control for the traffic bottleneck can be achieved, and thereby the traffic bottleneck in the expressways or the blocked roads can be effectively controlled.

The invention discloses an on-line predictive control method of traffic bottlenecks based on an FPGA and an improved Aw-Rascle model, and aims to solve the technical problem that on-line predictive control is difficult to perform on the traffic bottlenecks on actual highways or blocked roads in the existing method. According to the method, the Aw-Rascle model is improved, a variable information display board is integrated into the Aw-Rascle model, predictive analysis is performed on highways or blocked roads based on an FPGA platform and the improved Aw-Rascle model, the traffic bottlenecks are found according to a defined state variable, and then control schemes of ramp control and the variable information display board are provided and taken to prediction models according to priority to find reasonable control schemes to perform on-line control on the traffic bottlenecks, so that the traffic bottlenecks on the actual highways or blocked roads can be effectively controlled.

The invention discloses an on-line predictive control method of traffic bottlenecks based on an FPGA and an improved Kerner-Konhauser model, and aims to solve the technical problem that on-line predictive control is difficult to perform on the traffic bottlenecks on actual highways or blocked roads in the existing method. According to the method, the Kerner-Konhauser model is improved, a variable information display board is integrated into the Kerner-Konhauser model, predictive analysis is performed on highways or blocked roads based on an FPGA platform and the improved Kerner-Konhauser model, the traffic bottlenecks are found according to a defined state variable, and then control schemes of ramp control and the variable information display board are provided and taken to prediction models according to priority to find reasonable control schemes to perform on-line control on the traffic bottlenecks, so that the traffic bottlenecks on the actual highways or blocked roads can be effectively controlled.