156 results about "Transit line" patented technology

The invention relates to the field of urban public transport deployment, and provides a public transport network matching method and system based on an urban space structure, which divides urban areas by constructing a traffic model, identifies areas with dense demands on the basis of power consumption density, and provides a public transport network matching method and system based on the urban space structure. And the coverage condition of the existing public transport network on the areas with dense demands is evaluated, and uncovered areas are identified. For the uncovered areas, the information of stores and companies in the map data is used to subdivide the uncovered areas into a plurality of types of areas. A bus rapid transit system is additionally arranged in a commercial district to improve transportation efficiency, a peak period special line is additionally arranged in an office building area to meet commuting requirements, a customized bus special line is provided in an industrial district to meet requirements of specific periods and routes, and a conventional bus route is additionally arranged in a residential district to improve daily travel. Accurate matching between the urban space structure and the public transport demand is realized, and the coverage rate and efficiency of public transport service are improved.

The invention belongs to the technical field of public transport scheduling, and discloses a public transport capacity monitoring and scheduling method and system, and the method comprises the steps: collecting the real-time passenger flow volume, historical passenger flow volume and environmental factor data of a target bus line, and carrying out the standardization and abnormality detection; constructing a hybrid prediction model comprising a time sequence decomposition model and a random fluctuation model, and predicting the passenger flow in the future period; the vehicles are divided into fixed shifts, maneuvering shifts and standby shifts, and vehicle configuration is dynamically adjusted according to the predicted load factor; through multi-source data fusion and an intelligent prediction algorithm, accurate monitoring and dynamic scheduling of the public transport capacity are realized, the vehicle utilization rate and the service quality are improved, and the operation cost is reduced.

The invention relates to a modular bus jump and relocation scheduling method considering stop time, and belongs to the field of urban public transport operation scheduling. The method comprises the following steps: acquiring geographical location information of a certain conventional bus route and a station and travel data information of bus passengers, and determining the number of passengers getting on and off the bus at the station; the method comprises the following steps: defining a jump station and relocation coupling operation as a decision variable, and establishing a relational expression between the stop time of a modular bus at a stop and the number of passengers getting on and off according to a modular bus single-door design characteristic and a bus combination form; taking the minimum sum of the passenger travel time cost and the vehicle operation cost as an objective function, setting a modular bus flow constraint and an operation time constraint, and constructing a modular bus scheduling optimization model; and solving to obtain an optimal modularized bus jump station and relocation scheduling scheme under the passenger demand of the corresponding line. According to the invention, for a bus route scene where part of bus stations are relatively high in load, modular bus operation scheduling which efficiently utilizes bus transport capacity resources is realized.

The invention discloses a bus dynamic scheduling method and system based on vehicle management, and the method comprises the steps: building a scheduling environment simulation system through collecting the historical data and real-time data of the operation of an electric bus, automatically generating passenger travel information based on bus line data and historical passenger getting-on data, carrying out the modeling of the bus operation as a dynamic discrete process, and carrying out the real-time scheduling of the electric bus. Constraints such as vehicle availability and charging limitation are introduced, and a bus operation simulation environment close to reality is constructed; establishing a Markov decision process based on a scheduling simulation environment, and definitely defining vehicle availability management parameters in a state space and a reward function; a Rainbow DQN model is adopted for training, a scheduling strategy is continuously optimized according to environment feedback, a dynamic scheduling scheme is generated by utilizing the model obtained through training according to real-time data reasoning, the travel requirements of passengers and the operation benefits of a bus company are considered on the premise that the vehicle availability is met, and intelligent scheduling decision support is provided for management personnel.

The invention provides a bus route mining method and device, and relates to the technical field of artificial intelligence, in particular to the technical field of intelligent traffic and deep learning. A specific embodiment of the method comprises the steps of matching a user track of a user in a bus running period with a bus route to obtain a matched track point, an unmatched track point and a matched bus route; determining a maximum matching track segment based on the matching track points and the mismatching track points; performing space-time matching on the maximum matching track segment and the real-time bus track of the matched bus route to obtain a space-time matching degree; determining a confidence coefficient based on the real-time bus track with the highest space-time matching degree; and determining the bus route corresponding to the real-time bus track with the highest time-space matching degree when the user takes the bus in response to the condition that the confidence meets a preset condition.

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 provides a flexible bus route planning method based on user travel behavior prediction. The invention discloses a flexible bus route planning method based on user travel behavior prediction. The method comprises the following steps: S1, collecting and integrating multi-source travel data; s2, user behavior analysis and demand prediction; s3, dynamic service area division; s4, generating and optimizing a flexible line; s5, performing real-time dynamic scheduling and adjustment; s6, ticket price dynamic generation and feedback; and S7, service effect evaluation and iterative optimization. The flexible bus route planning method based on user travel behavior prediction provided by the invention has the advantages of being capable of obtaining balance between global optimum and calculation efficiency, reducing the vehicle empty driving rate, improving the route operation cost recovery rate, quickly responding to newly added demands and shortening the average waiting time of passengers.

The invention provides an unmanned aerial vehicle terminal distribution method and system based on a public transport network, and belongs to the technical field of logistics distribution, and the method comprises the steps: obtaining customer information, public transport network information and unmanned aerial vehicle information; establishing a multi-target optimization model for cooperative distribution of the bus and the unmanned aerial vehicle by using the customer information, the public transportation network information and the unmanned aerial vehicle information; the target optimization module takes the minimum cost as a target function and considers time difference constraint, route constraint, load constraint and energy constraint; adopting a non-dominated transformer neighborhood search algorithm of a simulated annealing algorithm acceptance criterion to solve the multi-objective optimization model to obtain an approximate Pareto optimal solution set; the optimal solution set is an unmanned aerial vehicle tail end distribution scheme considering cost, time and risk. Based on the method, the invention further provides an unmanned aerial vehicle tail end distribution system based on the public transport network. According to the invention, through combination of unmanned aerial vehicle electric driving and public transportation network cooperation, multi-objective optimized logistics distribution is realized.

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 innovatively provides an urban and rural public transportation network optimization and intelligent scheduling method based on big data and an AI algorithm, and the method comprises the steps: generating a station demand degree; according to the method, the number of bus routes is preset, the station demand degree is obtained, the demand frequency is generated through a demand strategy, a bus route scheme group is randomly generated according to the demand frequency, the demand frequency reflects the occurrence frequency of stations in the bus route scheme group, and a plurality of bus route groups are arranged in the bus route scheme group. The bus departure time and the bus departure frequency of the bus route group are adjusted according to the station demand time and the number of passengers getting on and off each station; the method comprises the following steps: respectively calculating a waiting cost parameter, a substitutability parameter and an income parameter through a route prediction model in combination with historical riding travel data, calculating a recommendation index of a bus route scheme group through a route optimization algorithm, carrying out priority ranking from high to low according to the recommendation index of the bus route scheme group, and carrying out priority ranking according to the recommendation index of the bus route scheme group. And obtaining a recommended bus route scheme group.

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.

The invention discloses a bus route time control point determination method considering delay propagation influence, which belongs to the field of public traffic data mining application and mainly comprises the following steps of: calculating a delay value of each bus station based on bus arrival time data; determining the propagation range of delay generated by each bus number at each bus stop and the number of times of delay recovery at each bus stop; identifying a delay generation station based on a K-means algorithm; and determining a final time control point set based on the delay generation station. According to the method, on the basis of considering the fluctuation of the bus travel time, the delay generation intensity, the propagation range and the recovery capability of the station are measured by constructing three indexes including the delay reduction value, the delay propagation length and the recovery delay times from the angle of delay propagation, so that the accurate identification of the delay generation station is realized; by screening delay generation stations as time control points, delay generation can be reduced from the source, further propagation of delay is prevented, and reliability and operation efficiency are improved from the perspective of overall operation of bus lines.

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 invention relates to the field of bus management, and discloses a bus dispatching interval optimization system and method based on waiting negative emotion accumulation and sensing time expansion, and the system comprises a sensing waiting time quantification module, a data collection module, a parameter fitting module and a bus dispatching scheme optimization module. According to the invention, the subjective emotion experience of the passengers and the actual scheduling model are deeply fused for the first time, and the emotion experience target of the passengers is considered in parallel with the operation target in the mathematical level by quantifying the change of negative emotions in the waiting process of different passengers and sensing the expansion phenomenon of waiting time, so that the travel satisfaction degree of the passengers is improved, and the user experience is improved. And double balance is realized in cost and structure. Meanwhile, the method has extremely high adaptability and generalizability, can be suitable for different cities and different bus route types, and even can be popularized to operation optimization of other waiting scenes.

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 present invention discloses a method for analyzing the total travel distance of multiple modes of transportation based on traffic distribution, which belongs to the technical field of calculation, estimation or counting. The method includes the following steps: clarifying the research area and time period; dividing traffic areas; constructing a road network and a bus line network; calculating the line network density and average station spacing of buses in the traffic area; conducting a questionnaire survey on residents' transportation travel; constructing a traffic distribution matrix and performing traffic distribution; calculating the non-linear coefficient of residents' transportation travel within the traffic area; constructing a calculation model for the distance from passengers to bus stops; and calculating the total travel distance of various transportation modes. The present invention comprehensively analyzes all aspects of the integrated transportation system, organically combining travel on the road network, travel within the traffic area, and travel by passengers to bus stops. It can systematically analyze the entire process of residents' transportation travel and accurately calculate the total travel distance of multiple transportation modes.

The invention discloses a traffic distribution method based on public transportation super network construction, which relates to the technical field of road traffic, and comprises the following steps: acquiring all bus station information, bus lines and traffic zone centroid point information in a target distribution area; generating real nodes and virtual nodes according to the bus station information and the bus route information; constructing a driving arc according to the virtual nodes; constructing a co-station transfer arc according to the real nodes and the virtual nodes; constructing a different-station transfer arc according to the real nodes; constructing an upper / lower network arc according to the real node and the centroid point of the traffic zone; according to the real node, the virtual node, the driving arc, the same-station transfer arc, the different-station transfer arc and the upper / lower network arc, constructing a bus super network; according to the method, the traffic flow is distributed to each arc section of the bus super network by adopting a multi-path-capacity limiting method, so that the bus distribution can comprehensively consider the influence of the transfer behavior, the distribution result of the traffic flow is closer to the reality, and the reasonability of the bus distribution is improved.

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.

The invention relates to an intelligent station scheduling method and system based on a bus reservation function and a medium, and the method comprises the steps: R1, sorting out bus route congestion data according to a platform navigation map and obtained vehicle position information and bus route data, the cloud platform issues the acquired vehicle operation data and bus route congestion data to a station terminal platform; and R2, the intelligent station terminal platform decodes and decomposes the data in real time according to the received bus operation real-time data and the factors of the station positions of the stations and the number of the bus routes of the stations, and transmits the data to the corresponding intelligent stations through Ethernet data. According to the invention, real-time updating and display of the vehicle position, the vehicle end passenger flow and the line traffic flow information on the intelligent station bus line are realized, and citizens can timely know the bus real-time information and carry out reasonable travel selection.

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 discloses a kind of bus line network optimization method and system, the method includes: step 1: obtaining city traffic road network data, bus station data, station data, passenger flow OD, line needing adjustment;Step 2: bus station is mapped to city traffic road network;Step 3: update city traffic road network data;Step 4: connect adjacent bus station and form bus traffic network;Step 5: find out the target OD that planning route needs to cover;Step 6: generate candidate line pool;Step 7: calculate the covering relationship of line in candidate line pool and target OD, then through finding out the line set that can cover all target OD and the shortest mileage, realize bus line network optimization.The application can solve the line network optimization adjustment problem of common asymmetric traffic network, greatly improve the applicability of line network optimization method.Especially in the case of current bus operation cost pressure, realize the reduction of operation cost while not reducing service level.

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.

The present invention provides a bus coordination evaluation device and system based on travel data and GIS clustering. The system consists of a bus data system, a coordination analysis system, a GIS cluster analysis system, a display system, an information transmission device, input and output equipment, and an intelligent mobile terminal. The system is based on big data fusion mining and processing technology, can perform quantitative evaluation of urban bus lines, realize rapid evaluation and analysis of public transportation networks, and provide participatory decision-making for the optimization of urban public transportation networks.

The present invention discloses a method and system for calculating cross-sectional distances for bus routes. The method comprises: Step 1: collecting route linear data and station data; Step 2: standardizing the linear data for each route; Step 3: preliminarily calculating the station bearing angles for each station on each route; and Step 4: calculating the cross-sectional distance for each route. The present invention significantly improves the adaptability of calculating cross-sectional distances for bus routes using route linear data and route station data. The present invention provides excellent calculation results for complex situations such as loop-like routes, routes that pass through stations twice, and individual station location data with significant deviations. The present invention can accurately obtain cross-sectional distances, further optimizing network layout and improving operational efficiency.

The present invention discloses a multi-path signal coordination control method for bus priority, comprising the following steps: S1, collecting relevant information about trunk intersections and bus routes in the trunk; S2, dividing the multi-path bus signal control sub-areas based on the stop locations of each bus route and combining dummy variables; S3, establishing a multi-path signal coordination control optimization model for bus priority with the optimization goal of maximizing the weighted green wave bandwidth of each bus route, and then establishing intra-control sub-area group constraints, inter-control sub-area group constraints, and travel time constraints for each path; S4, solving the optimization model, obtaining the green wave bandwidth of each bus route, and outputting the optimized signal control parameters for each intersection in the trunk route. When applied to the bus signal coordination control of urban trunk routes, the present invention can provide green wave bandwidth for multiple bus routes, significantly improve the traffic efficiency of buses on urban trunk roads, and alleviate traffic congestion.

The invention relates to the technical field of public transport passenger flow distribution, and relates to a public transport passenger flow distribution method and system, and the method comprises the steps: obtaining first information which comprises a public transport line set, a station set and a public transport travel set; constructing a public transport network according to the first information; an event-activity expansion network is constructed according to the public transport network, the event-activity expansion network comprises space-time nodes, time-independent nodes and arcs for connecting the nodes, and the arcs have different priorities; based on the event-activity expansion network, establishing a balance condition of user balance priority; the passenger flow distribution model is established according to the balance condition of the user balance priority, the passenger flow distribution model is used for calculating the passenger flow distribution result, the passenger flow distribution model is solved, so that the path selection and the flow distribution of passengers reach a stable balance state, and the reasonable distribution of the public transport passenger flow is realized.