57 results about "Transit line" patented technology

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 discloses a subway interval interruption scene-oriented planned operation bus route fine adjustment method, which mainly comprises the following steps of: constructing a candidate bus route set and a rail station set capable of being conveniently transferred, and generating a multi-point connection path; on the premise of restraining the total demand of the detained passengers, the number of passengers getting on and off each bus station, the dynamic passenger capacity in the bus, the bus route arrival and departure time and the detour connection time are calculated, and the conventional operation service level is guaranteed; and constructing an optimization model aiming at minimizing the total delay of all system passengers, and solving the optimization model. By scientifically deploying existing operation bus resources, a multi-station dispersed transportation strategy is implemented, and travel requirements of passengers are accurately matched. The method effectively avoids the problem of congestion caused by centralized transportation of a single destination, and the constructed optimization model gives consideration to the operation efficiency of the public transportation system and the evacuation demands of detained passengers in a subway, remarkably reduces the overall delay cost, greatly improves the emergency response speed and the toughness of the public transportation system, and powerfully supports the safe and stable operation of an urban traffic system.

The embodiment of the invention discloses a bus scheduling method and device based on the battery health state, and the method comprises the steps: obtaining the battery health state parameter, the battery remaining capacity, the real-time position information and the line information of each bus in real time, carrying out the loss coefficient evaluation of each bus line based on the line information, and obtaining the loss coefficient of each bus line; matching each loss coefficient obtained by evaluation with the battery health state parameter of each bus, and determining a plurality of dispatchable vehicles on each bus route; classifying the plurality of dispatchable vehicles according to the battery remaining capacity and the battery health state parameter of each dispatchable vehicle and the route information of the corresponding bus route, determining running vehicles and alternative vehicles on each bus route, and when the battery remaining capacity of the running vehicles is smaller than a preset capacity threshold value, sending the alternative vehicles to the dispatchable vehicles; and scheduling the alternative vehicles based on the real-time position information of the running vehicles. The matching precision of each bus route and the schedulable vehicle is improved, and the rationality and timeliness of vehicle scheduling are fully guaranteed.

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 relates to a vehicle-road collaborative non-blind area sensing system for intelligent network connection buses, which belongs to the technical field of intelligent traffic and vehicle-road collaborative sensing, and is characterized in that based on multi-dimensional data of vehicle side and road side sensors, a vehicle sensor sensing range, a fixed bus route and real-time pose information are combined; a blind area target is sensed and predicted in real time, the potential risk of the blind area target to a bus is dynamically evaluated, high-risk information is transmitted back to a bus end, non-blind area global environment sensing and early warning are achieved, a reliable sensing basis is provided for follow-up functions such as intelligent scheduling, safety early warning and automatic driving, and the system is suitable for popularization and application. And the sensing safety and the risk early warning capability of the bus in the complex urban road section are obviously improved.

This invention relates to the field of public transportation technology, and particularly to a mobile electronic bus stop sign mounted on a bus. The sign includes a terminal device mounted on the right side of the bus. The terminal device is connected to a backend system via a network. The terminal device includes a housing structure with a display screen installed inside. The display screen is electrically connected to a control module installed inside the housing structure. The control module is connected to the backend system network via a communication module. A power module is installed inside the housing structure. The sign can display arrival prediction information for all routes passing through all stops; it can also display more basic information about bus routes, such as route name, direction of travel, first and last bus times, arrival reminders, and next stop reminders; and it can play media information, including videos, pictures, and text. Compared to traditional LED bus stop signs, this invention better meets the waiting needs of passengers and facilitates public transportation.

The application discloses a bus service gap identification method based on mobile phone signaling and bus data coupling and belongs to the technical field of traffic supply condition supervision. The method specifically comprises the following steps: S1, data collection; S2, data processing; S3, identification of job and residence locations; S4, construction of a commuting OD matrix; S5, construction of a commuting demand index; S6, construction of a bus supply level index; and S7, analysis of a demand-supply matching degree index. First, job and residence locations of residents are identified by using mobile phone signaling data, and a commuting OD matrix is established; then, commuting demand intensity and bus supply level are quantified; finally, a demand-supply matching degree index model is constructed, and a bus service gap area is identified by using GIS spatial coupling analysis.

The embodiment of the invention discloses a public transport scheduling method, device and equipment based on cloud side-end cooperation and a medium. One specific embodiment of the method comprises the following steps: sending a plurality of pieces of multi-source real-time state data corresponding to a bus route to a plurality of corresponding roadside edge computing nodes to generate a plurality of pieces of corresponding traffic state feature information; sending the plurality of pieces of traffic state feature information to a cloud platform, and fusing the plurality of pieces of traffic state feature information with pre-acquired historical data on the cloud platform; generating a dynamic scheduling instruction set; generating a dynamic signal timing scheme according to the dynamic scheduling instruction set and the real-time state of the related intersection signal lamp; generating a bus driving guide instruction set; and guiding the corresponding public transport vehicle to execute driving operation coordinated with the dynamic signal timing scheme. According to the embodiment of the invention, the dynamic coordination of the bus and the traffic signal can be realized, and the waiting time of passengers and the intersection waiting time of the bus are reduced.

The present application relates to the technical field of bus charging, in particular to a bus fast charging station orderly charging method based on a data-driven energy efficiency model; first, the power demand meeting the operation of a bus line is determined, and then a relationship between charging energy conversion efficiency and the actual charging power of a vehicle-mounted energy storage system is established; taking the minimum actual power consumption of the charging station in a day or the minimum actual electricity cost of the charging station in a day as an objective function, wherein the charging energy conversion efficiency is considered, a nonlinear optimization objective function model is established with the power demand of the electric bus line operation, the continuity of the electric bus charging time as constraint conditions, then the nonlinear optimization objective function model is converted into a mixed integer convex programming problem using piecewise linearization, and the optimal charging plan is obtained by solving the mixed integer convex programming problem; the present scheme can further improve the energy conversion efficiency of charging on the basis of traditional orderly charging, reduce the power consumption cost of the charging station operator and the charging cost of the electric bus, and improve the economy.

The invention discloses an improved NSGA-II algorithm-based high-speed rail bus receiving and transporting timetable optimization method, and relates to the technical field of traffic transportation, and the method comprises the following steps: determining basic parameters and precondition assumption of a high-speed rail bus receiving and transporting system; constructing a multi-objective optimization model which aims at minimizing the waiting time of passengers and the operation cost of public transport enterprises and meets the constraints of departure intervals, route lengths and departure train numbers; an improved NSGA-II algorithm fusing championade selection of mixed linear ranking and a uniform multi-parent crossover strategy is adopted, a population is initialized through Gray coding, and a Pareto optimal solution set is obtained through iterative solution of operations such as fitness calculation, selection, crossover, variation, population merging and elite retention; extracting an optimal scheme from the obtained Pareto optimal solution set; according to the optimal scheme, generating a departure time table of each receiving and transporting bus route; the overall coordination and adaptability of the public transportation system are enhanced by constructing a multi-objective optimization model with the goal of minimizing the passenger waiting time and the public transportation enterprise operation cost.

This invention discloses a MaaS dynamic bus route and station planning method and a trip optimization method based on spatiotemporal clustering. The MaaS algorithm based on spatiotemporal clustering, within a defined boundary area of ​​no more than 25 square kilometers, determines bus routes and stops based on existing public transport demand where both origin and destination are within this area, according to established spatiotemporal clustering rules. It then returns the determined bus routes, stops, and estimated arrival times to passengers using the planned bus routes and stops. The application of this invention maximizes the convenience of public transport, reduces unnecessary waiting time and connection distances, increases bus occupancy rates, reduces the probability of empty bus runs, and minimizes stops at unnecessary stops, thereby improving operational efficiency.

The application provides a bus fast-charging station orderly charging method considering battery dynamic charging loss, comprising: determining the power demand meeting bus line operation according to the operation time of the charging station, equipment power limit, quantity limit and bus departure plan; establishing a battery heat loss model and the relationship between charging energy conversion efficiency and the actual charging power of the vehicle-mounted energy storage system based on a first-order RC circuit model; taking the minimum actual power consumption of the charging station in a day or the minimum actual electricity cost of the charging station in a day as an objective function, wherein the battery heat loss is considered, and an optimization model is established with the charging station operation time, charging pile number, charging pile maximum power, power distribution capacity, electric bus travel power demand, electric bus charging time continuity as constraint conditions; using piecewise linearization to convert the nonlinear optimization objective function model into a mixed integer convex programming problem, and solving the mixed integer convex programming problem to obtain the optimal charging plan, including the optimal charging time and corresponding charging power of each vehicle. The method improves the charging energy conversion efficiency, reduces the battery heat loss and prolongs the service life of the battery, reduces the charging cost of the bus while improving the charging energy conversion efficiency, and improves the economy.

1. The name of the design product: dynamic graphical user interface of touch screen of electronic device. 2. The use of the design product: for running programs, displaying information. 3. The design points of the design product: in the graphical interface design. 4. The picture or photo that best indicates the design points: design 1 front view. 5. The design for which protection is sought contains colors. 6. The electronic station display screen is a conventional design, and other views are omitted. 7. The use of the graphical user interface: for displaying the graphical interface of the electronic station touch screen, design 1 is used to represent the running state of the electronic station in the daytime, design 2 is used to represent the running state of the electronic station in the night, and design 1 front view and design 2 front view are presented in a cycle during the running process of the electronic station; and design 1 front view is presented in the daytime, and design 2 front view is presented at night. 8. The area of the graphical user interface in the product: the upper part of the interface is for playing video advertisements, and this area contains a touch function menu bar in the middle of the video playing; the bottom of the interface is for bus line station information, including line name and station name. 9. Design 1 is designated as the base design.

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 present application relates to the field of bus scheduling and path optimization, and provides a passenger bus transfer method, device and equipment under subway operation interruption, which comprises the following steps: constructing a passenger transfer demand distribution randomness model based on historical data, wherein the historical data is passenger transfer demand data; determining a passenger evacuation strategy according to the fault site and the passenger transfer demand distribution randomness model; determining a candidate bus line set based on the passenger evacuation strategy; constructing a bus transfer model based on the candidate bus line set, and determining the minimization of total delay as the optimization target of the bus transfer model; the total delay is determined according to the delay of ordinary passengers, the delay of passengers who fail to successfully board and the delay of stranded passengers; solving the optimization target based on a genetic algorithm, and outputting an optimal solution. The present application solves the defect of low scheduling efficiency of the traditional single-line transfer method in the prior art, improves the evacuation efficiency, and reduces passenger delay.

The invention discloses a bus OD derivation and road network flow matching method based on multi-source data and electronic equipment, and the method comprises the steps: obtaining and preprocessing bus multi-source data in a target area, and building a station-line-vehicle three-dimensional mapping relation with direction information; the bus multi-source data comprises bus GPS (Global Positioning System) data, station GIS (Geographic Information System) data and IC (Integrated Circuit) card swiping data; determining passenger types and historical travel laws according to the IC card swiping data, analyzing travel chain features according to the historical travel laws, and then deducing getting-off stations and time of passengers in combination with POI types of stations; according to the deduced get-off station of the passenger and the corresponding route, determining a station sequence interval of the travel path of the passenger on the bus route; then, according to the corresponding relation between the line station and the road section number in the road network, the passenger travel path is mapped to the actual bus road network, the total passenger flow of each road section is counted, and flow statistical data with the road section as the unit is generated.

The application relates to the field of bus management and discloses a bus departure interval optimization system and method based on waiting negative emotion accumulation and perceived time expansion, wherein the system comprises a perceived waiting time quantization module, a data acquisition module, a parameter fitting module and a bus departure plan optimization module. The subjective emotional experience of passengers is deeply fused with an actual scheduling model for the first time, the change of negative emotions of different passengers in the waiting process and the expansion phenomenon of perceived waiting time are quantized, the emotional experience target of passengers can be considered on the mathematical level and the operation target at the same time, the travel satisfaction of passengers is improved, and double balance is realized on the cost structure. Meanwhile, the method has strong adaptability and generalizability and can be applied to different cities, different bus line types and even other operation optimization existing waiting scenes.

1. The name of the design product: the graphical user interface of bus route navigation of electronic equipment. 2. The use of the design product: for an electronic device. 3. The design points of the design product: the content of the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: the present graphical user interface is used for the touchable bus driver terminal scheduling screen, which can be used to display the map route and provide navigation function.

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.

A circuit that features the following: an output stage (T H , T L ), which is connected to a first bus line (CANH) and a second bus line (CANL); a driver circuit (11) designed to drive the output stage (T H , T L ) depending on a first logic signal (DOUT) such that a corresponding bus voltage (V BUS ) is generated between the first bus line (CANH) and the second bus line (CANL); a slew rate control (16) coupled to the driver circuit (11) and configured to set a slew rate of the driver circuit (11) depending on an input signal (SR); and a monitoring circuit (15) configured to generate the input signal (SR) for the slew rate control (16), wherein the input signal (SR) indicates a higher slew rate during an arbitration phase of a data frame contained in the first logic signal (DOUT) than during a data transmission phase of the data frame.

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 invention relates to the technical field of station passenger flow analysis, and discloses a bus station classification method based on payment data, which comprises the following steps: acquiring payment data, route data and departure time table data of buses; extracting a transaction time sequence of each vehicle in each bus route according to the payment data; calculating the predicted arrival time of each station in each bus route according to the route data and the departure timetable data; performing passenger flow station matching according to the transaction time sequence of each vehicle and the predicted arrival time of each station to obtain a matching result of the passenger flow station and the transaction time in each bus route; and performing clustering analysis based on time sequence features according to the matching result of the passenger flow stations and the transaction time in each bus route to obtain a bus station classification result. According to the method, the problem of station matching errors caused by data missing and line dynamic adjustment in a traditional method is solved, and the bus station classification accuracy is improved.

The application discloses a kind of based on improved hidden Markov model line network matching method, device and medium, by obtaining bus line network data and road network data, and the bus line network data and road network data are preprocessed, obtain the point set to be matched of bus line network and the section set of road network, the point set to be matched of bus line network and the section set of road network are input into the fitting hidden Markov model of pre-set, the emission probability and transition probability of all candidate points corresponding to all points to be matched of the bus line network are calculated, the shortest path between all candidate points of any adjacent point to be matched of the bus line network is calculated using Viterbi algorithm tracing source, obtain the matching result of bus line network and road network.Therefore, the application embodiment can improve the matching accuracy of bus line network and road network.

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 invention discloses a public transit network supply and demand matching strategy determination method, device and equipment, and relates to the technical field of public transit network planning and optimization. The method comprises the steps of performing label construction on user travel demand data according to a preset travel label rule to obtain a travel demand data set with a label; determining a high-demand travel data group by combining grid regions obtained by dividing the region to be optimized, and further determining a public transit network supply and demand matching result; in the case of mismatching, determining travel demand path data in combination with third-party path planning data; and in combination with current public transit network data, the travel demand coincidence degree is determined, and finally a public transit network supply and demand matching strategy is determined. According to the scheme, the travel demand coincidence degree is determined under the condition that the user travel demand is not matched with the current public transit network, and then the public transit network supply and demand matching strategy is determined for network optimization, so that the matching degree of the public transit network and the user travel demand is improved, and the demand of the user for the public transit travel efficiency is met.

This disclosure provides a method, electronic device, and program product for processing bus stop data. The method includes acquiring bus stop data, which includes the location of the bus stop and at least one of the following: bus stop name and bus route information on the bus stop; aggregating the bus stop data to obtain bus stop data, which includes at least one of the following: bus stop platform area and bus stop data within the bus stop, with the platform platform area covering the locations of the bus stops within the bus stop; and sending the target bus stop data to the client according to a request for target bus stop data sent by the client, so that the client can display the target bus stop data. This technical solution can fundamentally reduce the problem of wasted capacity, improve the accuracy of production data, and the increased bus stop platform data enhances user awareness of the bus stop area. The increased bus stop data within the bus stop refines the granularity of the bus stop display down to the bus stop itself, making bus stop navigation more accurate for users.

The application discloses a bus passenger alighting station inference method based on a travel chain and an integrated learning, and comprises the following steps: collecting bus multi-source data; performing data cleaning and preprocessing on the multi-source data; fusing the multi-source data and judging a passenger boarding station according to a station arrival time window; performing preliminary inference on the alighting station based on a deterministic algorithm; establishing a deterministic algorithm to infer the passenger alighting station according to a travel chain assumption and passenger travel history; performing supplementary inference on the alighting station based on the integrated learning; introducing built environment and bus line external information for a journey that cannot be inferred by the deterministic algorithm; and establishing a multi-classification model based on an integrated learning two-layer stacking framework to further infer the passenger alighting station. The application realizes non-aggregated, station-level single-ticket bus passenger alighting station inference based on bus multi-source big data, can obtain accurate bus passenger flow space-time distribution characteristics, and provides a reference for bus operation organization optimization.

The application discloses a kind of public transport route planning method based on crowd sensing, belong to public transport route planning technical field.The application adopts each wiring, the mode of optimizing network, facing all bus stops, after determining the starting point and end point of bus stop, any pairing between starting point and end point is carried out again, and the direct passenger number between each starting point and end point is recorded, the pair of starting point and end point with maximum direct passenger number is selected, and the shortest public transport route is set along the pair of starting point and end point.Through new building, merging and other ways to bus stop, further optimization of public transport route planning is realized, and the next optimal route is continuously searched, and unreasonable route or bus stop can also be selected and deleted from the built public transport route network by combining with other methods.The application not only fully considers the convenience of urban residents when planning public transport route, but also takes into account the interests of public transport company and the whole city public transport operation.

The application discloses a bus line network intelligent scheduling method based on a machine learning model, belongs to the technical field of data processing, and comprises the following steps: receiving line network sensing data; when it is detected that the line network sensing data has an abnormal evolution trend, generating a line network operation situation snapshot and conveying the line network operation situation snapshot to a scheduling information coordination processing unit to generate each scheduling information entry; calling each scheduling information entry to perform overlap detection, outputting an overlap relationship matrix, and dividing to obtain a normal scheduling information set and each conflict scheduling information set; obtaining machine learning model training parameters of each conflict scheduling information entry, analyzing to obtain a model history stability index and a model generalization confidence index of the machine learning model, and screening each conflict scheduling execution instruction according to the model history stability index and the model generalization confidence index to execute the bus line network intelligent scheduling, so that the technical problem that different scheduling information has deviation and inconsistency in the state cognition level in the prior art is solved.

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.