15 results about "Public transport network" patented technology

A system (100) for realizing an automated inspection of equipment (1) of a public transportation system, characterized in that it comprises at least: - a control system (10) comprising at least one electronic processing unit (12) configured to elaborate an inspection plan for an equipment (1) to be inspected; - at least one drone (30) which is configured to execute said inspection plan, wherein said at least one drone (30) is provided with at least one device (32, 34) adapted to collect data and / or one or more images / videos of said equipment (1) while executing said inspection plan; and wherein at least one of said at least one electronic processing unit (12) and a computer system (35) onboard of the at least one drone (30) is configured to allow identifying an abnormality in the equipment (1) inspected by comparing the collected data and / or one or more images / videos with respective data and / or one or more corresponding images indicative of a reference condition of said equipment (1).

This invention discloses a method for assessing the accessibility level of public transportation based on work-residence integration, belonging to the field of urban public transportation planning and assessment technology. The method includes: acquiring multi-source data on the public transportation system of the target area, including static geographic information, departure timetables, and historical operation data; dividing the area into spatial analysis units based on planning boundaries and linear geographic elements; calculating and standardizing three indicators—spatial coverage, service frequency intensity, and operational reliability—for each unit; employing an objective weighting method based on information entropy to automatically determine the weight of each indicator according to its dispersion across all units; weighting and aggregating the standardized indicator values ​​of each unit with their corresponding weights to generate a comprehensive public transportation network service capacity index; and finally generating and outputting a service capacity visualization map based on this index. This invention, through multi-dimensional quantification and objective weighting, achieves a scientific and comprehensive assessment of public transportation service capacity, providing intuitive decision support for planning and management.

The invention discloses a public transportation service gap identification method based on mobile phone signaling and public transportation data coupling. The method belongs to the technical field of traffic supply condition supervision. The technical problem that research for accurately optimizing the public transit network is still lacked is solved. The method specifically comprises the steps of S1, data collection, S2, data processing, S3, occupational and residential place identification, S4, commuting OD matrix construction, S5, commuting demand index construction, S6, bus supply level index construction and S7, demand-supply matching degree index analysis. The method comprises the following steps: firstly, identifying resident places and residences by using mobile phone signaling data and establishing a commuting OD matrix; respectively quantifying commuting demand intensity and bus supply level; and finally, constructing a demand-supply matching degree index model, and identifying a bus service gap area by utilizing GIS space coupling analysis.

The invention relates to the technical field of data analysis, and discloses a multi-dimensional feature-based connection passenger flow prediction method and device, and the method comprises the steps: obtaining user riding data corresponding to a public transport network and passenger flow influence data associated with the user riding data; preprocessing the user riding data to obtain target riding data; counting historical connection passenger flow data based on a connection passenger flow prediction formula and according to the target riding data; extracting features of the passenger flow influence data and the historical connection passenger flow data based on a multi-dimensional feature processing model to obtain multi-dimensional features associated with the historical connection passenger flow data; and on the basis of a dynamic generalized additive model, according to the multi-dimensional features, calculating the predicted connection passenger flow of any connection station. Therefore, the dynamic prediction of the bus and subway connection passenger flow can be realized on the basis of improving the analysis comprehensiveness of the multi-dimensional characteristics of the bus and subway connection, so that the prediction accuracy of the bus and subway connection passenger flow is improved.

The application relates to the technical field of urban bus line network and timetable integration optimization, and particularly discloses a bus line network and timetable integration optimization method and device based on graph reinforcement learning. The method is used for generating a bus line network structure and a timetable in a multi-mode public transport network containing BRT, subway and shared bicycles. Firstly, a multi-mode public transport road network is constructed, and passenger flow demand data is obtained; a bus line network design and a synchronous timetable compilation process are modeled as a Markov decision process; according to a current bus line network state, the road network is reconstructed into a heterogeneous graph containing time sequence evolution arcs and spatial topology arcs, and a double attention graph neural network is used to extract candidate node features; according to the node features, an action is selected through an action network, and the bus line network state is updated; the node feature extraction, the action selection are repeated until a termination condition is met, and the bus line network structure and the line timetable are output. The application can generate a bus line network and timetable which are more coordinated with other public transport modes, and reduce the operation cost of bus enterprises and the travel and transfer time of passengers.

This application relates to a bus route and stop registration method, system, storage medium, and intelligent terminal, belonging to the field of computer analysis of public transport networks. It includes acquiring bus route and road network data from different sources; identifying missing parts of the road network based on the bus route data to obtain complete road network data; using a preset spatial clustering algorithm to cluster and merge bus stops with the same station but different coordinates to obtain real bus stops; drawing perpendiculars from the real bus stops to the roads corresponding to the complete road network data to obtain the actual nodes of the bus stops in the road network; and obtaining the bus route nodes and stops located within the complete road network data based on the bus route data, and outputting them as registration points. This application has the effect of clustering and merging bus stops from different data, and then drawing perpendiculars to the real bus stops, so that the registered bus stops can restore the actual situation as much as possible, ensuring the accuracy of the data.

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 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 method and system for triggering alarm clock reminding based on a geographic position, and relates to the technical field of geographic information. According to the method and system for triggering alarm clock reminding based on the geographic position, the current position information of a user is obtained in real time through a terminal, the time for arriving at a destination is calculated in combination with a movement route and a movement speed, and when the detected time is within a preset reminding range, a reminding function is activated. The core of the method is that positioning data provided by a GPS, Beidou, Galileo, Glonass and the like are obtained, a motion path is calculated, time prediction is carried out, a multi-sequence priority system is set as a trunk by taking a previous driving route and driving time data as a benchmark, and time prediction is carried out. A double verification process, a priority level increasing system and a priority level adjusting system are formed in combination with a geofence, and a more accurate and diversified reminding function is given; the system supports cross-equipment linkage synchronous reminding, and is suitable for anti-sitting and station-crossing early warning in travel scenes such as public transportation, online car hailing, factory and enterprise regular buses and self-driving navigation.

The invention discloses a vehicle-mounted passenger flow distribution method based on a bus operation timetable, and relates to the field of public transport network computing. According to the method, firstly, a space-time expansion network is constructed in combination with a bus timetable and spatial information, and a Markov decision process-based user equalization strategy including a state space, an action space, a transfer matrix and a value function is established; and then a random user balanced distribution model considering a perception cost error is constructed, a single-node and full-network flow loading algorithm is designed under capacity limitation, and arc flow and available probability distribution are obtained. And forming a calculation process of a dynamic update value function based on the arc flow and the arc available probability distribution result. And iteratively executing network flow loading, value function dynamic updating and convergence judgment by adopting a continuous average method, solving a passenger flow space-time distribution equilibrium solution in a Markov decision process, and obtaining waiting passenger flow of a station in each time period and passenger flow distribution of a train number level.

The invention discloses an urban unmanned logistics transportation method and system by means of an urban public transportation network. The method comprises the following steps: creating an urban unmanned logistics transportation mode by means of the urban public transportation network; according to the urban unmanned logistics transportation mode, constructing an urban unmanned logistics transportation feature data set by means of an urban public transit network; according to the collected urban unmanned logistics transportation feature data set, determining a transportation scheme of cargo cross-regional unmanned consignment by means of an urban public transit network; according to the collected urban area unmanned logistics transportation feature data set, distribution stations distributed to all bus downlink stop stations are determined, the number of buses needed for goods distribution in all distribution sections is calculated, and a transportation scheme of goods cross-area unmanned distribution by means of an urban public transportation network is determined. According to the method, efficient transportation of urban logistics is realized by means of the urban public transportation network, so that the public transportation use efficiency is improved, and the logistics transportation cost is reduced.

The invention discloses a subway network key station identification method and system considering bus substitution, and the method comprises the steps: respectively constructing a subway weighted network and a bus weighted network with the travel time as the weight based on subway and bus station and line data in a research range; the method comprises the following steps of: screening bus stations in a walking range of a subway station through a spatial connection method, constructing an initial bus alternative network, and optimizing to obtain a final weighted bus alternative network by combining walking time, a passenger walking perception coefficient and an acceptable travel time threshold value; and calculating the betweenness centrality, the proximity centrality and the weighting centrality of each subway station, establishing a comprehensive importance calculation model, and identifying the key stations in the subway network based on the comprehensive importance. The method is used for accurately capturing the trade-off relationship between the importance of the subway station in the network structure and the availability of the bus replacement service, and can provide decision support for emergency plan making of a subway system and connection bus network planning.

The invention relates to the technical field of intelligent transportation, and discloses a method for acquiring a public transportation network, which comprises the following steps: acquiring the number of people getting on and getting off a bus in a plurality of grid areas in a first preset time period; obtaining a first candidate bus stop corresponding to the first preset time period according to the number of passengers getting on the bus and the number of passengers getting off the bus in each grid region in the first preset time period; acquiring first driving time and first travel demand quantity between the first candidate bus stops; according to each first candidate bus stop, each first driving time and each first travel demand, constructing a first traffic model diagram; and inputting the first traffic model diagram into a preset public transportation network acquisition model to obtain a target public transportation network of the preset area. According to the method, the efficiency and practicability of obtaining the public transportation network can be improved. The invention further discloses a device for acquiring the public transportation network, electronic equipment and a storage medium.

The application discloses a kind of city intelligent public transport scheduling method and system based on Internet of Things, including the traffic influence coefficient of gathering city multi-source traffic information calculation, construct city public transport network time-varying diagram carries out flow propagation prediction each future state feature of public transport station, calculates the dynamic adjustment vehicle station time of vehicle head time interval, calculates the support demand index to determine the station to be supported, the support weighted demand index of corresponding neighborhood station of the station to be supported is selected to support vehicle.The method not only can improve the efficiency and accuracy of city public transport scheduling, but also has good interpretability, can be directly applied in city intelligent public transport scheduling system.

The invention discloses a rail transit key station identification method considering toughness of a composite public transport network. The method comprises the following steps: firstly, constructing a weighted rail transit-conventional bus composite network model based on the number of lines, departure intervals, running time consumption and rated passenger capacity; on the basis, three toughness indexes including a network average efficiency change value, a passenger travel time change value and an average interlayer degree change value are calculated respectively, and a comprehensive toughness performance response function is constructed; thirdly, comprehensively evaluating each rail transit station by adopting a TOPSIS method, and identifying key stations in the composite network; and finally, verifying the method through actual cases. According to the method, network topology, passenger travel and interlayer coupling relations are comprehensively considered, dynamic identification and toughness evaluation of key stations are realized, a basis can be provided for cooperative protection and emergency scheduling of an urban public transport system, and network toughness and sustainable operation capability can be improved.