47 results about "Transit network" patented technology

The invention discloses a method and equipment for constructing a bus carbon emission factor library of unit passengers, and a medium. The method comprises the steps: obtaining a bus network, and estimating bus attribute parameters including the bus passenger capacity, the bus speed and the bus size; calculating an energy consumption factor, a fuel consumption factor, a fuel combustion carbon emission factor, a cold start carbon emission factor and / or a lubricant carbon emission factor of the bus so as to estimate direct carbon emission of the bus; calculating the total carbon emission of the corresponding oil well to oil tank stage of the bus, the carbon emission factor of the corresponding oil well to oil tank stage of the electric bus, the carbon emission factor of the whole life cycle of the bus and / or the infrastructure carbon emission factor of the bus so as to estimate the indirect carbon emission of the bus; and deriving individual-level, grid-level, region-level, link-level and line-level bus carbon emission factors according to the estimated direct and indirect carbon emission of the bus.

The invention discloses a public transportation network reconstruction method under urban rail networking operation, and the method comprises the steps: obtaining multivariate travel data, carrying out the data-driven calculation of passenger flow OD, and providing scientific data support for network planning; meanwhile, when the whole line network is established, a backbone network and a connection network are adopted to simplify levels, technical indexes and service standards of all the levels are defined, actual passenger flow distribution is accurately measured and calculated, and the reasonability of line planning is ensured; and meanwhile, by establishing a three-dimensional matching index system, quantifying the difference between the current situation and the ideal network, and by differentiating schemes and implementing priority ranking, lines with large difference are optimized according to priorities, so that gradual optimization of the whole network is realized, large-scale oscillation is avoided, and finally reconstruction of the public transport network is realized. A complementary situation with urban rail transit is formed, redundant waste of public traffic design is avoided, and meanwhile, residents can go out more conveniently by optimizing lines.

The invention relates to the technical field of intelligent bus prediction, in particular to an intelligent bus kiosk real-time bus prediction method and system. The method comprises the following steps: acquiring a bus route vector data set, and determining a bus operation chain topology table according to the bus route vector data set based on a bus network spatio-temporal topology coupling strategy; acquiring a real-time severe weather influence data set, and constructing a bus station pressure propagation network based on a traffic node load distribution strategy according to the real-time severe weather influence data set and the bus operation chain topology table; on the basis, predicting dynamic pressure influence on each bus station and each bus route caused by negative influence caused by real-time severe weather and a networked conduction path of the dynamic pressure influence, and determining a dynamic coupling disturbance conduction network; and according to the dynamic coupling disturbance conduction network, carrying out real-time prediction on the bus condition in the bus operation chain topology table, and outputting and pushing prediction information. According to the invention, the operation state of the bus in the dynamic scene is accurately predicted.

The invention discloses an unmanned aerial vehicle and bus cooperative distribution method considering a forward rate, and the method comprises the steps: additionally installing an unmanned aerial vehicle parking and charging device at the top of each bus, generating a supply point and a demand point according to a transportation demand, enabling a user to carry out the route planning after completing the cargo loading at the supply point, enabling the user to carry a bus to move to a destination when the electric quantity does not meet the condition, and enabling the user to carry out the transportation. And the vehicle roof device is used for charging. During the period, the unmanned aerial vehicle can flexibly avoid congestion and route deviation through transfer. And when the electric quantity is enough to directly fly to the destination, the unmanned aerial vehicle flies to a supply point from the top of the bus to unload the goods, and then returns to the top of the nearest bus to be charged to prepare for the next task. The mode combines the advantages of'fixed route 'and'high frequency' of an urban public transportation network, expands the service range of the unmanned aerial vehicle, and improves the distribution capability; meanwhile, the unmanned aerial vehicle replaces a traditional delivery car, and traffic energy consumption is reduced. According to the method, the advance rate is used as a decision basis, and the unmanned aerial vehicle can dynamically evaluate the comprehensive income of each route, so that the optimal route is selected.

The invention discloses a real-time subway passenger destination prediction method based on a subway-bus network, and the method comprises the steps: making a subway passenger travel data set which comprises the context information of a subway passenger starting station, the arrival frequency of a subway passenger, the instant travel information of the subway passenger, and the subway-bus fusion travel information; constructing a graph convolution attention network model GCAISN, and training the GCAISN model by using the subway passenger travel data set to obtain a trained GCAISN model; and integrating a plurality of trained GCAISN models by using an AdaBoost algorithm to construct a strong learning device, and predicting metro passenger destinations with different travel characteristics through integrated learning. According to the method, the subway travel records of the subway passengers are analyzed, the travel preferences of the subway passengers can be effectively analyzed and mined, the time cost of a large number of training samples can be effectively reduced, and the accuracy of predicting the subway destinations of the passengers in real time is improved.

A method for configuring a first autonomous system in a transit network is described. The method includes obtaining information according to which the traffic received by an ingress router of the first autonomous system is saturated, and determining a prefix of a destination subnet of a third autonomous system downstream of the first autonomous system. The method also includes extending the path associated with the prefix on at least one target router of the first autonomous system, the prefix and the at least one target router being determined by optimizing an objective function so that the path associated with the prefix must be extended for all the ingress routers of the first autonomous system which are geographically closer to the saturated router than the target router.

The application discloses a bus passenger trip planning method based on a multiple graph, and steps of the method comprise the following steps: 1. obtaining an original bus network; 2. generating a direct link multiple graph based on the original bus network; 3. constructing a passenger super-path sub-network based on the multiple graph and passenger trip information; 4. recommending an optimal trip path to the passenger according to an optimal strategy distribution principle; and 5. tracking the passenger position in real time and dynamically adjusting the recommended trip path. The application can recommend more abundant trip path schemes from the passenger's perspective, give the passenger more free selection space, dynamically adjust the trip path scheme to a certain extent, adapt to the change of a traffic environment, thereby meeting the path selection under various environments, greatly simplifying the process of searching for a trip path, and improving the path search efficiency.

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

This invention discloses a method and apparatus for assessing the importance of stations, belonging to the field of transportation networks and propagation dynamics technology. It addresses the problem that existing methods for assessing station importance fail to fully reflect operating routes and rely on global network topology information based on shortest paths, leading to relatively time-consuming calculations of the impact of distant stations on station importance. The method includes: constructing a bus-metro dual-layer network, a node network, a route network, and a bipartite graph network based on the bus and metro networks; determining the community structure and community center nodes of the node network using a community mining algorithm to form an enhanced node network; determining the preliminary importance of each second node based on the enhanced node network, and determining the preliminary importance of each third node based on the route network; and determining the final importance of the second nodes included in the node network based on the bipartite graph network, the preliminary importance of each second node, and the preliminary importance of each third node.

The invention relates to a bus timetable synchronization and cross-line scheduling method for a fuel-electric hybrid fleet, and the method comprises the steps: constructing a data set according to bus network information, including lines, transfer stations, passenger arrival rates, driving time and power consumption; constructing a multi-target integer programming model which minimizes the operation cost of a bus company and the waiting time of passengers and maximizes the number of convenient transfer times; an NSGAII-SA-PSO nested heuristic algorithm is designed, and the most suitable algorithm is allocated to decision variables with different characteristics, so that the quality of the solution is improved. According to the invention, through timetable synchronization and vehicle cross-line coordination, the operation efficiency of buses is significantly improved, and the travel experience of passengers is effectively improved.

The invention discloses a construction method of an urban rail-public transportation network transfer station line topology network, and belongs to the technical field of urban multi-mode traffic network topology analysis, and the method specifically comprises the steps: constructing a rail network topology structure and a public transportation network topology structure, and storing the structural data of stations and links; constructing a track-bus space relation topological structure and a rectangular area covering all stations, and generating an irregular area completely contained in the rectangular area; and designing a mode transfer station extractor, traversing irregular areas and extracting transfer stations by dynamically adjusting the moving step length of a movable area, and generating a transfer station line topology network. The method has the beneficial effects that the topology complexity of a traditional super network is remarkably reduced, the problem that the path search efficiency is reduced due to the introduction of a virtual link is avoided, the dependence of the model on high-precision real-time data is reduced, the method can adapt to the data isomerism of different cities, and the accuracy of transfer station identification is effectively improved.

The invention discloses a public transit network optimization method and system. The method comprises the steps of 1, acquiring urban traffic network data, bus station data, station data, passenger flow OD and lines needing to be adjusted; step 2, mapping bus stops to an urban traffic road network; 3, updating the urban traffic network data; 4, adjacent bus stations are connected to form a bus traffic network; step 5, finding out a target OD which needs to be covered by the planned route; step 6, generating a candidate line pool; and 7, calculating a coverage relationship between the lines in the candidate line pool and the target OD, and then finding out a line set which can cover all the target OD and has the shortest mileage to realize public transit network optimization. According to the method, the problem of network optimization adjustment of a common asymmetric traffic network can be solved, and the applicability of the network optimization method is greatly improved. Particularly, under the condition that the current bus operation cost is high, the service level is not reduced while the operation cost is reduced.

A photovoltaic bus stop board with a shared charging function provided by the present invention comprises a bus stop board body, the top of the bus stop board body is provided with a photovoltaic panel, the left end of the inner side of the bus stop board body is fixedly connected with a mounting plate, and the mounting plate is provided with a shared power bank power supply box. A driving box is correspondingly arranged above the shared power bank power supply box, and the driving box is also fixedly installed at the left end of the inner side of the bus stop board body. Full-color photoelectricity, photovoltaic energy storage and shared economy are fused, shared charging is reconstructed by relying on a bus network, photovoltaic panel power generation is subjected to voltage stabilization and energy storage through an energy storage module, and the energy storage module is connected with the shared power bank power supply box. Multi-specification voltages are converted for power banks, illumination and the like, and power grid dependence is avoided; a motor, a gear and a screw in the driving box drive the protective cover to ascend and descend, a control switch can be pressed to start to take the charge pal and close protection, 'upper taking and lower taking 'can be achieved at multiple stations, and the problems that a traditional station board is single in function, and shared charge pals are difficult to return are solved.

The invention discloses a public transportation network key road section identification method, an electronic device and a storage medium, and the method comprises the steps: extracting the moving trajectory of each public transportation line based on the GPS data of public transportation vehicles in a research range; acquiring an urban road network in a research range, and constructing a map matching algorithm based on a hidden Markov model; the constructed map matching algorithm is used for matching the bus running track of each line with the actual road network, and the route bus route information of each road section in the road network is obtained; and according to the extracted route bus route information, lane information, surrounding population and POI information of each road section and the departure frequency of each bus route, calculating a key index of each road section in the road network, and identifying a key road section in the bus network. According to the method, time-space fusion of the public transportation network and the urban road network is considered, the key road sections in the public transportation network are accurately identified from the road network level, and decision support is provided for network planning, station layout and transport capacity configuration of the public transportation.

The invention discloses an urban bus station layout multi-objective optimization method based on a genetic algorithm, and relates to the technical field of public transportation, in particular to the urban bus station layout multi-objective optimization method based on the genetic algorithm. The bus station optimization method comprises the steps of establishing a multi-objective optimization model, selecting bus evaluation indexes, solving by adopting a genetic algorithm, evaluating an optimization result and determining an optimization scheme. According to the urban bus station layout multi-objective optimization method based on the genetic algorithm, a random bus network is established from a theoretical angle to verify the reliability of the model, then application analysis is performed by taking an actual case as an example, and a result shows that the proposed model has a relatively good optimization effect; the constructed station layout optimization model not only can be applied to various public transportation networks, has high practicability, but also can assist public transportation enterprises in station adjustment and optimization.

The application provides a kind of urban multi-mode traffic network post-disaster repair strategy efficiency evaluation method and system, belongs to the technical field of urban traffic operation management, constructs multi-mode traffic network structure model using road network and bus network open source data;Using traffic travel demand data to simulate urban traffic distribution, construct multi-mode traffic network function model;Based on multi-mode traffic network function model, according to the spatial distribution characteristics of disaster and post-disaster network repair strategy, construct multi-mode traffic network structure recovery model, evaluate the efficiency of structure recovery;Based on multi-mode traffic network structure recovery model, reload travel demand, construct multi-mode traffic network function recovery model, evaluate the efficiency of function recovery.The application can comprehensively consider various traffic modes and the complex dynamic game between travelers, provide more accurate and more comprehensive repair strategy evaluation, can enhance the resilience of urban integrated transport system, so that it can better cope with various disasters and emergencies.

The invention discloses an over-path traffic solving method for a completely-crowded large-scale public transportation network, and the method comprises the steps: obtaining a getting-on arc and a corresponding effective departure frequency through a first algorithm; the second algorithm calculates the use probability of passing through all the upper turning arcs under the super path, so that the complete upper turning arc flow distribution of the super path, the use probability vector of the upper turning arcs and the use probability vector upper turning arcs of the nodes are obtained; then, adopting column generation to construct an OD pair sub-problem, and determining the optimal transfer amount from a non-reference super path to a reference super path in the OD pair sub-problem through binary search; and the fourth algorithm obtains an over-path traffic equilibrium solution under the public transportation network equilibrium condition. Therefore, by setting the first algorithm, the second algorithm and the like, a complete algorithm capable of processing large-scale public transportation network distribution is constructed, so that the super path is constructed based on the effective departure frequency, and the method is suitable for practical application of the city-level large-scale public transportation network.

The application belongs to the field of network security and communication privacy protection. A hidden network construction method combining anonymous network and protocol camouflage includes constructing an initial hidden network overall framework, wherein the initial hidden network overall framework includes an initial source protocol camouflage and an initial transit network path jump; according to the protocol camouflage of the tunnel, the initial source protocol camouflage is adjusted by selecting a tunnel to obtain a target source protocol camouflage; the initial transit network path jump is configured by using a transit node to obtain a target transit network path jump; and the target source protocol camouflage and the target transit network path jump are verified to obtain a target hidden network overall framework. Through the above method, the subject information of network behavior can be disturbed, and problems such as privacy leakage and attack positioning caused by user feature portrait in the big data era can be effectively avoided.

The invention relates to a bus route contract scheme optimization method and device. According to the method, a three-layer planning model is constructed based on three-party interaction logic of a system planning end, an operator end and a passenger end in a public transit network; solving the three-layer planning model by using a nested generalized Benders decomposition algorithm to obtain a line contract scheme and a corresponding service frequency scheme which minimize the total cost of the system; based on tested bus network data, a numerical experiment is carried out on a line contract scheme and a service frequency scheme to obtain an experiment result, and the method has the advantages that strategy interaction of a system planning end, an operator end and a passenger end can be accurately described, efficient solving is carried out through a nested decomposition algorithm, and the system performance is improved. And finally, outputting an optimal line contract and frequency setting scheme with the total social cost being minimized.

The application relates to a bus schedule synchronization and cross-line scheduling method for a hybrid electric vehicle fleet, comprising the following steps: constructing a data set according to bus network information, including lines, transfer stations, passenger arrival rates, travel times and power consumption; constructing a multi-objective integer programming model for minimizing the operating cost of a bus company and passenger waiting time and maximizing the number of convenient transfers; designing an NSGAII-SA-PSO nested heuristic algorithm to assign the most suitable algorithm to different characteristic decision variables, thereby improving the quality of the solution. Through schedule synchronization and vehicle cross-line coordination, the application can significantly improve the operating efficiency of the bus and effectively improve the travel experience of passengers.

The application discloses a city traffic network evaluation and optimization method and system based on different interests, and relates to the technical field of traffic network analysis. Firstly, based on road network information, traffic flow and passenger flow data, three directed and weighted complex networks representing different interests are constructed: high-speed traffic and convenience network, urban motor vehicle road traffic and convenience network, and public transportation network. Then, the weighted edge community detection algorithm is used to divide each network into communities, and the traffic flow, passenger flow, vehicle speed and average travel time of each community area are evaluated. Through network connectivity analysis, the traffic accessibility of each area is evaluated. Combined with population density, enterprise distribution and other data, the weighted vertex importance algorithm is used to identify important nodes and evaluate their rationality and role. Finally, according to the evaluation results, optimization schemes such as road repair, widening, new road construction and additional public transportation lines are proposed.

The present invention discloses a method, device, and medium for constructing a bus carbon emission factor library for individual passengers, including: obtaining a bus network, and estimating bus attribute parameters such as bus passenger capacity, bus speed, and bus size; calculating the energy consumption factor, fuel consumption factor, carbon emission factor of fuel combustion, cold start carbon emission factor, and / or lubricant carbon emission factor of a bus vehicle, so as to estimate the direct carbon emissions of the bus vehicle; calculating the total carbon emissions in the well-to-tank stage corresponding to the bus vehicle, the carbon emission factor in the well-to-tank stage corresponding to the electric bus vehicle, the carbon emission factor of the bus vehicle throughout its life cycle, and / or the infrastructure carbon emission factor of the bus vehicle, so as to estimate the indirect carbon emissions of the bus vehicle; and deriving the bus carbon emission factors at the individual level, grid level, regional level, link level, and line level according to the estimated direct and indirect carbon emissions of the bus vehicle.

The invention discloses an optimization method and system of an urban area public transport network, and relates to the field of public transport planning, and the method comprises the steps: constructing a three-index system based on a road segment dynamic interaction index, a passenger flow space-time demand index and a subway collaborative transfer index; according to the public transit network data, using a three-index system to obtain a backbone line; constructing a target function by taking the bus route operation cost, the daily average load factor of the network, the transfer subway passenger flow and the energy efficiency index of the bus network as variables; and randomly selecting a preset number of bus lines and the backbone lines to form a bus network, taking a plurality of bus networks as a population, taking the target function value of each bus network as a fitness value, and obtaining an individual with the optimal fitness value in the population by using a genetic algorithm to serve as an optimized bus network. The circuit operation efficiency can be improved.

The invention belongs to the technical field of public transportation network optimization, and discloses a built public transportation network suitability optimization method based on deep reinforcement learning. Comprising the steps of 1, setting an optimization target; step 2, constructing an optimization objective function according to the optimization objective; and step 3, solving by adopting a DQN-based method. Aiming at the aging development trend of the current society, in the public transit network optimization problem, consideration of aging suitability is added, and reachability, convenience and the like concerned by the elderly are taken as optimization objectives; the invention provides a DQN-based solving method aiming at the problems that a current mainstream search method is weak in result stability and difficult to adapt to an established public transportation network. The invention further provides a DQN-based solving method for solving the problems that the current mainstream search method is weak in result stability and difficult to adapt to the established public transportation network. The full load rate of the supersaturation interval can be effectively reduced, and the average walking distance of old people and the transfer passenger flow ratio can be reduced.

According to the public transit network optimization method and system based on the reinforcement learning technology, the electronic equipment and the storage medium provided by the invention, the method comprises the following steps: constructing a local optimal public transit route based on the passenger flow intensity, obtaining the first passenger flow intensity, constructing a Monte Carlo tree search model, and constructing an optimal public transit network for a public transit route set; the first passenger flow intensity and the second passenger flow intensity are compared and judged to obtain a final public transport line network; the public transport line is planned based on the passenger flow intensity; the passenger flow can be accurately matched; resources are reasonably allocated to hot spot areas according to the passenger flow intensity of different areas and time periods; the Monte Carlo tree search model is adopted to quickly generate a scheme, the search weight is calculated by utilizing multiple attributes of the line, the line is comprehensively analyzed, line selection and line network construction are more scientific, decision is made based on data and an algorithm, and human experience deviation is reduced.

A method and system for preprocessing and query stages for a trip-based public transit routing algorithm, which is used for multimodal routing computations, clusters the public transit network and computes relevant network parts when transiting between different clusters in order to prune the search at query time. The processing phase is modified to use only a subset of the network, depending on the clusters associated to the origin and destination locations.

The application discloses a subway-bus network cascade fault prediction method and related device, including the following steps: constructing a subway-bus double-layer network model with transfer points; determining the importance of each node in the subway-bus double-layer network model with transfer points; obtaining the load of each node, and calculating the capacity of each node according to the load of each node; according to the capacity and importance of each node, judging whether the node with importance greater than a preset threshold value has an accident type overload, and when the node with importance greater than the preset threshold value has the accident type overload, the node is taken as an overload node; and according to the type of the overload node, the method and related device can associate different node states with load abandonment and load transfer of node passenger flow, and realize load adjustment of the node.

The application discloses a kind of urban public transport network optimization method considering scheduling, comprising: processing bus card data, vehicle shift data, line site data, analyze the influencing factors in the process of passenger line;For the influence factor analysis of passenger riding habit, vehicle shift, analyze the influence relationship of the selection of each type of passenger line and riding habit, respectively with the same bus station OD inter-route selection proportion and Person correlation coefficient define its correlation degree, obtain the Pearson correlation coefficient of the selection of different types of passengers and shift;Through the actual-virtual bus network construction mode, construct line and scheduling synchronous optimization model, optimize the output optimization result by the line site layout and vehicle scheduling synchronous optimization by the constructed model.The application considers the influence of vehicle scheduling in the process of public transport network optimization, optimizes the layout of public transport network and vehicle scheduling simultaneously;It is convenient for passenger travel, reduces travel cost.

The invention discloses a bus distribution method under complete congestion. The method comprises the following steps: introducing a super-path structure into a bus network to express a travel route selection strategy of passengers; reconstructing an over-path traffic loading problem into a monotonic VI sequence along an over-path topological node sequence to obtain an over-path traffic loading scheme; and constructing an over-path traffic loading algorithm based on gradient projection, and executing over-path traffic loading so as to obtain arc traffic distribution, arc use probability and node use probability corresponding to each node of each over-path. Therefore, aiming at the problem of no capacity constraint, a column generation algorithm is introduced based on a super-path framework, and local adjustment and rapid equalization of super-path traffic are realized in a super-path set of each OD pair. And for the problem with capacity constraint, a high-precision feasible solution is obtained under the condition that the capacity constraint condition is met by combining a super-path framework and an augmented Lagrange method.

An additional PDU (in the form of a private breadcrumb PDU) traverses a Network Address Translator, NAT, and address translation correlation is performed by placing source information in fields immune