1096 results about "Traffic network" patented technology

An apparatus and system to manage monitored traffic density in relationship to spatial locational flow rates. The system includes a variety of mobile and / or stationary transmitting and receiving comm-devices utilizing certified comm-devices equipped Avics iChipset arranged in a polarity of vehicles, in communication with stationary and / or mobile hub comm-devices and / or other certified comm-devices, strategically arranged within and / or along one or more roadways and in communication with a server channel networked to a central server. Configured to receive and / or transmit encrypted traffic data from the diversity of stationary and / or mobile transmitting and receiving comm-devices over the network, update traffic data in the non shared database, continuously calculate optimal traffic density flow for one or more of vehicles traveling along the one or more roadways based on the updated vehicular transit data, transmitting variations in speed adjustments in a network infrastructure to one or more vehicles; adjusting traffic light intersections based on traffic density traversing such roadways based on the optimal traffic flow suggestions combined with Predicated Traffic Artifacts transmitted via system generated encrypted digital comm-advice directives; and in turn share extracted and / or transmitted data with each state an federal DOT departments and other stack holders, including insurance companies and vehicle manufacturers and dealers with information to assist with making the traffic network safer. The present invention presents an Intuitive ITS engaged in Channeled Vehicular Telematics conveying statistical data, from an plurality of network devices, providing informational services forecasting safety-critical features and more, in return gathering and disseminating connected channelled intelligence between vehicles from within and surrounding infrastructures and other shareholders. Such data includes vehicle Phase-Change Spatial analytics from traffic congestion artifacts, along with Consumption Variable Analysis that provides real-time Energy Summation Data from combined vehicle exhausted energy by adjusting traffic flow based on traffic density in relationship with the human factor, vehicle capacity to navigate and topography and climatic variations in relationship with any area being traversed, and most importantly the use of the unique string identification. USIN acknowledged as ‘tMarker Audit Trail’ or simply tMarker Trail as to data inception creation point. Managed within a secure private network infrastructure, each comm-device is synchronized with localized cloud servers in communication will a central server. This invention embarks on a new era in vehicle management, further enhancing time sensitive movements, leaving no doubt as to Vehicle Symmetry Orientation, especially once you move your vehicle and additional particulars currently not beyond the scope of this art presented herein. ITTS will throughly reduce the worlds fossil fuel supply consumption rate and on many other fronts availed by extracted data, transmitted from each vehicles onboard vehicle processor equipped with Avics iChipSet on certified comm-devices, reducing navigational concerns to elementary variables creating a safe traffic network.

Exemplary methods, apparatuses, and systems determine that a first physical network interface controller of a first host computer has lost a client traffic network connection. At least one data compute node running on the first host computer has client traffic transmitted via the client traffic network connection. In response to the loss of the client traffic network connection, one or more host computers each having a physical network interface controller with a functioning network connection for the client traffic are identified. Further in response to the loss of the client traffic network connection, the data compute node is moved to one of the identified host computers. The first host computer utilizes a second physical network interface controller to move data compute node.

A method for detecting information on occupied parking space in a traffic network, in particular a town, uses a parking space detection control center. Parking space information relating to a stationary phase of a vehicle and the vehicle location is transmitted to the control center from a navigation system at the vehicle. Information relating to empty parking space is generated by the control center and information relating to empty parking space is transmitted from the control center to a navigation system at the vehicle end.

Real-time high-fidelity spatiotemporal data on transportation networks can be used to learn about traffic behavior at different times and locations, potentially resulting in major savings in time and fuel. Real-world data collected from transportation networks can be used to incorporate the data's intrinsic behavior into a time-series mining technique to enhance its accuracy for traffic prediction. For example, the spatiotemporal behaviors of rush hours and events can be used to perform a more accurate prediction of both short-term and long-term average speed on road-segments, even in the presence of infrequent events (e.g., accidents). Taking historical rush-hour behavior into account can improve the accuracy of traditional predictors by up to 67% and 78% in short-term and long-term predictions, respectively. Moreover, the impact of an accident can be incorporated to improve the prediction accuracy by up to 91%.

A method and apparatus for predicting traffic on a transportation network where real time data points are missing. In one embodiment, the missing data is estimated using a calibration model comprised of historical data that can be periodically updated, from select links constituting a relationship vector. The missing data can be estimated off-line whereafter it can be used to predict traffic for at least a part of the network, the traffic prediction being calculated by using a deviation from a historical traffic on the network. The invention further discloses a method for in-vehicle navigation; and a method for traffic prediction for a single lane.

The present invention comprises a method for forecasting future economic conditions, land utilization and transportation network utilization and performance of a metropolitan area having a plurality of economic zones, the method includes the steps of: a) receiving a set of calibration values from a first input device; b) calculating a set of calibration constants with a first arithmetic logic unit; c) receiving a set of initial values for a set of desired outputs from a second input device, wherein the set of desired outputs includes regional economic, land use and transportation outputs; d) calculating the regional economic and land use outputs with a second arithmetic logic unit, wherein the regional economic and land use outputs include a first group of variable travel demands; e) calculating an origin to destination matrix with a third arithmetic logic unit, wherein the origin to destination matrix includes two-way daily person trips between an origin economic zone and a destination economic zone; f) calculating the transportation outputs with a fourth arithmetic logic unit, wherein the transportation outputs include a second group of variable travel demands; h) repeating steps d) through f) until the first group of variable travel demands is substantially the same as the second group of variable travel demands; and, g) providing the set of desired outputs to an output device.

The invention discloses an all-weather clean energy comprehensive electricity generating and energy saving method and a facility manufacturing method. In ten inventions, having at least one identical or corresponding specific technical characteristic and related to the total inventive concept, of solar gallery buildings, through graphene series facilities under solar gallery buildings, in a land field, a zero-carbon environment-friendly safe type raft-shaped basic-framed-tube-structured huge building group of a universal wind energy tower shape is established and new energy automobiles and trains are manufactured, wherein cheap wind power solids are established, photoelectric benzene expansion optical fibers are manufactured, lightning is utilized firstly for supplying power externally, various spaces are shared through building three-dimensional afforesting, and three-dimensional energy collection is achieved; in a water field, deep water self-floating buildings of a super steel concrete frame-tube structure (preferably, complete steel plates are adopted) are built, the deep water self-floating buildings are connected in series to form a global ocean water and electricity and agriculture and forestry extraction traffic network and a large lake and reservoir water and electricity and agriculture and forestry dredging dam water level traffic network, wherein the deep water automatic floating buildings are free of influences of earthquakes, tsunamis and wars, the Red Cross can rescue people in all-weather conditions; in a space field, multiple receiving and transmitting solar towers are first established on the equator of the earth and the equator of the moon, the receiving and transmitting solar towers are connected in series to operate in a timed mode in the specific direction and transmit power to the whole world through graphene cables which are all packaged with colored insulating films.

The invention discloses a large-scale traffic network jam prediction method and device based on a convolutional neural network. The time sequence and spatiality of road network vehicle speed information can be considered at the same time, so that the traffic jam state of the whole road network can be predicted more accurately. The method comprises the steps of S1, collecting GPS data of vehicles, extracting vehicle operating data at each moment on each road section, and generating a matrix M according to the acquired vehicle operating data; S2, generating a space-time thermodynamic diagram of at least one day according to the matrix M, wherein the abscissa of the space-time thermodynamic diagram represents time, and the ordinate of the space-time thermodynamic diagram represents road section ID sequence ranked according to spatial relationship; S3, generating a data set (X,Y) through window sliding on the space-time thermodynamic diagram; S4, establishing a convolutional neural network model, and training the convolutional neural network model by means of the data set (X,Y); S5, inputting a data set to be tested into the trained convolutional neural network model to obtain a prediction result.

The invention discloses a station-based urban public traffic network optimized configuration method, which comprises the following steps of: optimized layout of bus stops under the constraint condition; calculation of trip generation of the bus stops; generation of candidate routes based on bus stop generation and route constraint condition; and genetic algorithm-based bus route optimization and index evaluation thereof. The station-based urban public traffic network optimized configuration method can search new routes based on the conventional routes, particularly realizes conventional public traffic network optimized layout in the presence of rapid transit. The station-based urban public traffic network optimized configuration method can directly evaluate the generation of the bus stops based on urban land utilization and population distribution, and also can directly utilize the generation and origin and destination data acquired by field transit survey. The system can be used for spatial distribution optimization of conventional metropolitan public traffic networks, and the efficiency for public traffic network regulation and layout is improved.

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.

The invention relates to a city traffic network path selecting method which is based on dynamic information. The invention includes the following steps: (1) using the ground sensing coil, GPS and other existing information collecting methods to collect real-time traffic information, and establishing real-time information database; (2) using electronic map information to establish city traffic network topological structure map; (3) using Djkstra labeling method to find the optimal path between the commencement and termination dynamically in time. The invention has the merits of easy achievement, high reliability, high immediacy, a few parameters and so on, which can provide real-time and reliable navigation information for modern city traffic inducement.

The invention provides a cooperative control method for multi-intersection signal lamp based on Q value migration depth reinforcement learning, and belongs to the crossing field of machine learning and intelligent traffic. A multi-intersection traffic network of an area is modeled into a multi-Agent system firstly. Each Agent simultaneously considers the influence of adjacent Agent actions at themost recent moment in the learning strategy process, so that multiple Agents can cooperatively conduct signal lamp control of multi-intersection. Each Agent adaptively controls one intersection through a deep Q network, and a network input is a discrete traffic state code of the original state information of the corresponding intersection. An optimal action Q value of the adjacent Agent at the most recent moment is transferred to the loss function of the network in the process of learning. The cooperative control method for multi-intersection signal lamp based on the Q value migration depth reinforcement learning can improve the traffic flow of the regional road network and the utilization rate of the road and can reduce the queuing length of the vehicle to relieve the traffic jam, and hasno limitation on the structure of each intersection.

Network traffic may be estimated using samples of network activities to identify traffic parameters. A model of the network may be generated using the traffic parameters, and the model can be used to simulate the network using a modified set of parameters. Network traffic may be managed using the results of the simulation. Network traffic can also be managed by intercepting and modifying a control message on a peer-to-peer network.

The invention discloses a road network model based on virtual nodes, and the road network model is the theory for network digitalization. The structure of the model mainly comprises a geometric net and a topology relationship between road sections. The basic elements of the geometric net comprise virtual nodes, road center-lines and shape points. The virtual nodes represent intersections between road sections, the beginnings of road sections or the ends of road sections, and comprises virtual road sections, inner points, envelopes of inner points; the road center-lines express road sections and are connected through inner points and virtual nodes; the shape points express turning points of road sections. The virtual road sections represent the topology relationship between road center-lines and traffic information, such as the distance damp and the time damp when road center-lines passing through junctions, and multi-lanes at junctions and different driving rules; the inner points determines the position information of virtual nodes. The model of the invention not only overcomes the shortages of traditional model, but also reflects the real road network more truly; and the model has better adaptability for functions, such as map match, route planning and real-time analysis for dynamic transportation network.

Network traffic can be prevented from entering a protected network. An alert can be received that can be triggered by network traffic that matches at least one signature that is associated with undesired network behavior. A source of the network traffic that triggered the alert can be determined, and network traffic that originates from the source can be blocked. Blocking the source can include assigning a determination to the alert. It can then be determined whether network traffic from the source should be blocked based on the determination. The source can then be provided to the protected network such that a network device coupled to the protected network can be configured to block network traffic that originates from the source.

The present invention relates to a network management system for management of a traffic network comprising a wired as well as a wireless network backbone. The wireless network backbone comprises relay nodes comprising wireless routers, some acting as gateways to the wired backbone network and some as relay bridge routers for access network access. The management system comprises a logical multilevel hierarchical network overlying the traffic network. It is adapted to use the infrastructure of the traffic network by using the relay nodes as management stations. It comprises grouping means adapted to perform a grouping process by arranging network nodes, comprising the relay nodes, in groups, each with selected a cluster head, on different hierarchical levels. Grouping control means are provided to control the grouping and allocation of cluster heads based on a number of grouping constraints given by one or more criteria to be fulfilled at each hierarchical level. Calculating means are adapted to calculate the criteria based on given metrics and modeling and verification means are provided for modeling the constraints and verifying fulfillment of said constraints at each hierarchical level.

The invention relates to a method for analyzing a traffic network, comprising the steps of: importing, organizing and managing geographic data, mobile phone base station positioning data, road network data and public transportation net data to obtain base data; comprehensively processing the base data and establishing a population travel time-space characteristic model to obtain the comprehensive data; and analyzing the traffic management according to the comprehensive data. In combination with the mobile phone base station positioning data, the public transportation network data, the road network data, and the like, the traffic network analysis method ensures that the population travel information dynamic change is obtained, the traffic information based on the population travel characteristic is found, and the service quality reliability is analyzed through a traffic topology network, traffic accessibility and relative analysis. The invention provides convincement and effective decision support for traffic management, traffic plan, land utilization planning, urban planning, and the like, can effectively improve the use ratio of public traffic and a road network, relieves the pressure of the urban traffic, and provides a method for solving the problems in traffic management and traffic planning.

This disclosure provides a method and system for generating one or more available paths from a rider origin location to a rider destination location using a trip planning platform. The generated available paths include, at least in part, a rider-sharing route. According to an exemplary system, the transportation network includes one or more fixed routes of transportation associated with one or more of buses, trains, bikes, walking paths and trams.

The invention relates to a public traffic information system for comprehensive management and broadcast and an operation control method thereof. The public traffic information system comprises the components of a vehicle scheduling system, a passenger identification electronic label generating system, a platform passenger flow statistics system, a user information issuing system, a passenger reservation system, a platform electronic board selecting and information upgrading system, an in-vehicle passenger information statistics system and a road condition real-time monitoring system; wherein the vehicle scheduling system, the passenger identification electronic label generating system, the platform passenger flow statics system, the user information issuing system, the passenger reservation system, the platform electronic board selecting and information upgrading system, the in-vehicle passenger information statistics system and the road condition real-time monitoring system are connected with a network node. According to the public traffic information platform and the operation control method thereof, information of the platform, the passenger and the buses can be obtained in real time through the public traffic information platform; furthermore the passenger transport capability of a vehicle is calculated through the vehicle scheduling system according to the invention; and whether vehicle arrangement is required at the platform is determined through the passenger transport capability of the vehicle, thereby reducing a passenger transport pressure. At aspects of actual users and bus scheduling, an integrated information broadcast platform and a bus scheduling method are presented, thereby facilitating public traffic network informatization construction.

The invention discloses a real-time traffic condition acquisition method based on a mobile intelligent terminal. The mobile intelligent terminal identifies the traffic condition according to sensor information, traces a running route in combination with a road database in real time and calculates the running time according to a traced result of the running route and uploads the real-time road condition information to a server; and the server analyses massive received real-time traffic condition information, removes repeated data, saves the result into a traffic condition database and estimates the real-time traffic condition for a minority of road sections in short of uploaded data according to the traffic condition data in the traffic condition database by the compressive sensing technology, to collect the real-time traffic condition of the whole urban traffic network. According to the invention, the mobile intelligent terminal can be used for collecting the real-time traffic condition information so as to obtain massive traffic condition data. The method has the characteristics of low cost, high accuracy, high data volume, good real-time property, high network coverage, good expansibility and the like, and has a quite wide application prospect.

The invention provides a path planning method and system, wherein the method comprises the following steps: mapping roads into nodes in a traffic network topological graph and mapping endpoints of the roads into arc sections in the traffic network topological graph; searching bi-directionally from an original node and a destination node, thus obtaining a plurality of current nodes; calculating the cost from a plurality of current nodes to the original node and the destination node sequentially and obtaining a current node of the minimum cost from the original node to the destination node; and according to the current node of the minimum cost, the original node and the destination node, obtaining a path plan from the original node to the destination node. The method and the system overcome the defect in the prior art that a Dijkstra method of adjacent matrices is adopted to store traffic network topological data, although whether (i; j) is a network edge can be queried within the time O (1), the complexities for querying relevant nodes which are the most significant for the shortest path plan are all O (n), which causes higher query complexity.

The invention relates to a map matching method of floating car data. An optimal matching path is guaranteed and an alternative path set of each global positioning system (GPS) point is minimized at the same time by means of multistandard dynamic planning technology, and therefore the matching efficiency is improved. In addition, aiming at the characteristics of map matching, a traditional shortest path analytical method is improved, and the matching speed is further improved by reducing a mark initialization process and a searching method from multiple points to a single point. Compared with other current methods, the map matching method of the floating car data is better in matching accuracy and matching performance, can achieve real-time map matching processing of low sample frequency floating car data in a city traffic network, and has business popularization and application prospects.

A process for analyzing a traffic network uses a source file including edges and nodes representing the traffic network. The process generates partial routes from the source file, wherein each partial route comprises at least one edge and at least one of the partial routes comprises a plurality of adjoining ones of said edges. Route data can be transmitted between a vehicle and a traffic center by designating the partial route instead of each individual edge, thereby optimizing transmission of data via a transmission channel.

The invention discloses an urban microscopic traffic flow simulation system based on a cellular machine, which comprises a simulated inner core, an initialization model, a human-computer interaction model, a database management system and an induction and control coordination system. The initialization model consists of a road network generating model, a vehicle generating model and a control and induction device generating model; the simulated inner core consists of a vehicle running model and a control and induction device running model; and the human-computer interaction model is in charge of the setting of a user on various parameters in the simulation system and the screen display work of a whole traffic network. The invention researches the overall design of the urban microscopic traffic flow simulation system, various running rules of vehicles at different road network positions and other necessary component parts for constructing the simulation system, mainly starts with the realization of the whole microscopic traffic flow simulation system to provide an overall framework of program running, and carries out corresponding simplification for certain complex independent parts so that the realization of the system is more feasible.

The invention relates to a motor vehicle travel route determination method based on historical data, which assumes that the travel time of a road section is mutually independent, and is in normal distribution, and the congestion probability is mutually independent, and particularly comprises the following steps that: step 1, setting the origin point and the destination point, resolving traffic network balance problem considering section capacity restrain to obtain a candidate route set and section congestion waiting time, for candidate routes, evaluating the steering delay at crossings, calibrating the difference of the expected value of the travel time of the road section and the standard, and taking the road section lower than 10km / h as a congestion road section to calculate the congestion probability of the road sections; step 2, respectively resolving the waiting time of the candidate routes, determining the travel time distribution of the candidate routes to obtain the alpha-position travel time of the candidate routes, and calculating the congestion probability of the candidate routes; and step 3, displaying the alpha-position travel time, the congestion probability and the waiting time of the candidate routes according to the small to large order of the alpha-position travel time of the candidate routes, and selecting the travel route by a user from the candidate routes.

Provided is a vehicle-mounted GPS space-time trajectory big data optimization method and system. The vehicle-mounted GPS space-time trajectory big data optimization method comprises the steps that map matching processing is performed according to original GPS trajectory data and a road-grade traffic network, and a road section corresponding to each trajectory point is determined; the initial optimization rate is determined according to a GPS trajectory error distribution law; preliminary optimization is performed based on density and includes the preliminary optimization performed according to a density evaluation model and the initial optimization rate, so that the trajectory points gathered on the road surfaces are selected, and the points away from the road surfaces are regarded as drifting points to be abandoned; secondary optimization is performed based on angle similarity and includes similarity value calculation conducted on preliminary optimization results by utilizing an angle similarity evaluation model, clustering processing is performed, then the results having highest similarity values in clustering categories are selected as final optimization results, and selected high-quality data are obtained. By means of the vehicle-mounted GPS space-time trajectory big data optimization method and system, overall positioning accuracy based on low-accuracy vehicle-mounted GPS trajectory big data is improved. The optimization method is simple and easy to achieve.

Provided are a real-time traffic flow control and dynamic route guidance system, a parking guidance system using the same, and a method thereof capable of guiding a vehicle distribution. and a transportation flow by collecting positional information, destination information, a vehicle moving speed, and the like from each vehicle in real time at one or a plurality of central centers by using an in-vehicle navigator with bidirectional communication and a GPS to dynamically calculate and provide an optimal route of an individual vehicle so as to make a flow of the entire transportation network smooth and perform a control for a transportation network structure through various kinds of traffic control devices installed on roads.

The invention provides a method for planning a path in an urban road traffic network. The method comprises the steps of dividing a region to be searched, which is determined according to a start point and a final point, into multiple sub regions according to a given road network density; then mapping the multiple sub regions into one-dimensional discrete points, and forming a Voronoi graph based on the discrete points; determining an adjacency relation between every two of all the sub regions according to the Voronoi graph, and judging the connectivity between every two adjacent sub regions; constructing a new road network according to a set of the selected adjacent sub regions which are communicated, and searching an optimal path between the start point and the final point in the new constructed road network. According to the method, the construction time of a road network topological structure is shortened; furthermore, the search range of the path is narrowed, the search time is shortened and the search efficiency is improved.

A method and system are disclosed for estimating origin and destination locations of users of a transportation system. The origins and destinations of known users are determined during a segment of an analysis period from validation information for all users of the transportation system. The origins and destinations are then mapped to probable locations associated with the transportation network. A destination probability is then computed for each destination location of an individual origin location. A unknown users are then apportioned to each destination, which may be based on the number of unknown users on a vehicle traveling from the origin to the destination, the computed probability, and the validation information, so as to estimate the number of users traveling from an origin location to any corresponding destination location on the transportation system.