6 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 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.

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 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.