212 results about "Transit line" patented technology

The present invention discloses a bus route optimization design method and system based on resident travel big data, the method comprising the steps of: obtaining mobile phone signaling data of residents in a target area; obtaining the stop points of residents' travel trajectories; dividing the target area into a number of traffic areas; obtaining an OD matrix based on the stop points of residents' travel trajectories and traffic areas; constructing a bus route planning model; generating a number of bus alternative routes based on a shortest path algorithm; obtaining a target bus route from the alternative routes based on a genetic algorithm and in combination with an objective function and an OD matrix. Compared with the prior art, the present invention not only innovatively combines spatiotemporal big data and genetic algorithms in technical means, improving the accuracy and efficiency of bus route planning, but also demonstrates strong advantages in system architecture and data processing capabilities, and can provide a more scientific, dynamic and sophisticated optimization solution for the urban public transportation system, contributing to the efficient operation of urban transportation and the construction of smart cities.

The invention discloses a dynamic estimation method and device for the carbon emission reduction effect of a bus lane and a medium, and the method comprises the steps: estimating the mileage of a bus line running on the bus lane and the mileage of a bus line running on a common lane; the types of the bus routes are divided, so that the bus routes are divided into a first bus route mainly running on the bus lane and a second bus route mainly running on the common lane; and according to the types of the bus lines, taking bus station level, bus link level and bus line level influence factors as covariables, taking each bus line as a sample, and adopting a dynamic emission reduction effect estimation model to estimate a condition emission reduction index and an average emission reduction index of the bus lane so as to quantify global and local emission reduction effects of carbon emission factors of unit passengers. In combination with cross-city bus data, a regional hierarchy random effect is introduced, and a multi-level dynamic emission reduction effect estimation model is constructed to reveal the difference of the emission reduction effects of bus lanes between different cities.

The invention discloses a trunk line intelligent network connection bus speed and signal timing collaborative optimization method, which comprises the following steps: acquiring basic information of bus lines, such as departure time interval, line length, station distribution and intersection signal phase; an intelligent networked bus speed control model is constructed, and dynamic speed guidance is implemented for different deviation types by calculating the deviation of the time headways of adjacent vehicles in real time; based on a vehicle speed control result, intersection signal lamp timing is optimized, and the negative influence of traffic signals on the driving speed of the public transport vehicle is reduced. By implementing accurate speed and signal lamp cooperative control at each bus station and intersection, the method can improve the overall operation efficiency of the trunk bus system to the maximum extent and reduce intersection delay while ensuring that the buses arrive on time, and compared with a traditional whole-line adjustment strategy, the method has the advantages that the overall operation efficiency of the trunk bus system is improved to the maximum extent, and the cost is reduced. According to the control strategy, the problem that the time headway deviation of a local road section is large can be solved more accurately.

The invention relates to the technical field of urban public transportation, and discloses an intelligent passenger flow perception and bus route adaptive adjustment system and device, and the adjustment system is composed of a data collection module, a data processing module, a passenger flow prediction and event detection module, a dynamic scheduling and route adjustment module, and an information release and user interaction module. According to the method, the characteristics of passenger flow density, flow direction, peak period and the like are extracted, the passenger flow change from a few minutes to a few hours in the future is predicted based on real-time data, and the passenger flow trend from a few days to a few weeks in the future is predicted in combination with historical data and special event information such as large-scale activities, traffic congestion and weather change. By automatically identifying the influence of the special event on the passenger flow, the passenger flow peak or the abnormal passenger flow condition can be predicted in advance, the module automatically adjusts the bus route and the departure time according to the passenger flow prediction result, and the beneficial effect of adjusting the bus route in real time according to the passenger flow distribution in the high stage or the special event period is achieved.

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 provides a public transport line passenger flow prediction method for optimizing a deep neural network based on a CPO algorithm, and belongs to the technical field of public transport. Comprising the following steps: data collection and arrangement; obtaining multi-source data and preprocessing the data; mining features in the public transportation system; features in the public transportation system are integrated into the passenger flow prediction model; the training set is used to train the obtained CNN-LSTM-Attention model; calculating a fitness function of a CPO optimization layer through the verification set, outputting a performance evaluation and passenger flow prediction result, and obtaining a verified CNN-LSTM-Attention model; and the verified CNN-LSTM-Attention model is used to predict the passenger flow of the bus route. According to the method, multi-factor comprehensive consideration is effectively realized, and various factors influencing the public transport passenger flow are effectively fused. And through the strong feature learning ability of the deep neural network, potential relationships between the factors and the passenger flow are mined, so that an internal driving mechanism of passenger flow change is comprehensively and meticulously reflected, and a prediction result is more suitable for an actual operation scene.

The invention discloses a trunk bus dynamic speed optimization method based on time headway equalization, and a dynamic optimization model is constructed by taking the minimum total deviation of the time headway on a bus line as a target. According to the method, factors such as departure time, driving speed and signalized intersection delay of intelligent networked buses are comprehensively considered, and the departure time of the buses at stations and the driving speed of the buses when the signalized intersection delay is not considered are optimized by establishing a calculation method for the bus delay at the signalized intersection. Meanwhile, according to a time headway balance principle, a calculation method based on the waiting time of passengers is provided so as to coordinate the operation efficiency of the motorcade and the experience of the passengers. According to the method, the fluctuation of the time headway is effectively reduced, the bunching effect is avoided, the overall operation efficiency and the service level of the bus route are remarkably improved, and theoretical support and technical guarantee are provided for design and implementation of an intelligent network connection bus system.

The invention discloses a passenger selection behavior-based connection bus line-sharing optimization method and equipment, belongs to the technical field of urban traffic, and is used for solving the problems that existing connection buses are unreasonable in line-sharing station design, the cost of passengers and bus enterprises is difficult to reduce, the service level of the connection buses is not favorably improved, and the service quality of the connection buses is influenced. And the travel time of passengers is difficult to optimize. The method comprises the following steps: determining generalized travel cost based on waiting time cost, in-transit time cost and bus company operation cost; according to the generalized travel cost, carrying out regression analysis on the travel selection behavior influence factors of the passengers, and determining a connection bus route selection probability; carrying out model condition constraint under a related cost objective function on the connection bus to obtain a connection bus common line segment station optimization constraint condition set; constructing a connection bus common line segment station optimization model; and carrying out output calculation on the connection bus line-sharing station optimization model to obtain a connection bus line-sharing station optimization scheme and a departure interval.

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 relates to a bus route scheduling management method and system based on weather big data. The method comprises the following steps: obtaining and accessing a real-time meteorological data source in a bus route scheduling area; acquiring and accessing historical operation data and real-time operation data of bus lines in the bus line scheduling area; determining whether the current weather type in the bus route scheduling area is severe weather or not based on the real-time rainfall data; when it is determined that the weather is severe weather, whether the current real-time passenger flow link is in an increasing trend compared with the historical average passenger flow under the condition of no severe weather in the historical same period is judged according to the real-time passenger flow data of the bus line, and when it is judged that the current real-time passenger flow link is in the increasing trend, it is determined that the shift interval time of the bus line needs to be shortened. According to the invention, through integrating meteorological data information, intelligent scheduling management can be comprehensively and effectively carried out on the bus route and the operation of the bus, so that the service efficiency and the passenger experience are improved, and the adaptability and the flexibility of the bus system are improved.

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 relates to the technical field of public transport planning, and discloses a calculation method for quantitative evaluation of a bus track connection relationship, and the method comprises the following steps: 1, collecting data: collecting travel time, travel cost data and track travel time data between any stations of a bus line; according to the calculation method for the quantitative evaluation of the bus track connection relationship, a comprehensive quantitative evaluation model is provided by comprehensively evaluating the travel time, the cost and the competition coefficient between the bus line and the track line; the comprehensive evaluation method can more accurately identify and quantify the advantages and disadvantages in the bus track connection relationship, thereby helping a planner to optimize the layout of bus lines and track lines, reducing resource waste, improving the overall transportation efficiency, and improving the transportation efficiency by optimizing connection points and adjusting operation strategies. The transfer time and waiting time of passengers can be reduced, the travel experience of the passengers is improved, and the operation cost is reduced.

The invention discloses an urban and rural passenger transport line network optimization system based on intelligent evaluation and scheduling, which relates to the technical field of urban and rural traffic and comprises a data acquisition module, a data processing module, a line network diagnosis module, a traffic supply and demand analysis module and a line network optimization module. The data acquisition module comprises a bus data acquisition unit, a road condition data acquisition unit and a travel data acquisition unit and is used for acquiring urban and rural bus operation data in real time; the data processing module is used for preprocessing the collected data. Technical research and development and product construction are carried out around an intelligent bus big data analysis system, Internet geographic information data and a big data analysis technology are fully utilized, the current situation of a bus network is evaluated, the bus travel demands of all county residents are actually mined and extracted, the travel demand change of people is analyzed, and the travel demand change of people is analyzed. The conditions of insufficient line coverage, unreasonable transport capacity configuration and inconvenience in resident trip are avoided, the resident trip time and cost are reduced, and convenience is provided.

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 relates to the field of bus scheduling and path optimization, and provides a passenger bus connection method, device and equipment under subway operation interruption, and the method comprises the steps: building a passenger transfer demand distribution randomness model based on historical data, the historical data being passenger transfer demand data; determining a passenger evacuation strategy according to the fault station and the passenger transfer demand distribution randomness model; determining a candidate bus route set based on a passenger evacuation strategy; constructing a bus connection model based on the candidate bus route set, and determining an optimization target taking minimization of total delay as the bus connection model; the total delay is determined according to the delay of common passengers, the delay of passengers who do not get on the bus successfully and the delay of detained passengers; and solving the optimization target based on a genetic algorithm, and outputting an optimal solution. According to the invention, the defect of low scheduling efficiency of a traditional single line connection method in the prior art is overcome, the evacuation efficiency is improved, and passenger delay is reduced.

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 discloses a bus route passenger flow prediction method, system and terminal considering spatial-temporal characteristics, and the method comprises the steps: carrying out the preprocessing of bus card swiping data, carrying out the statistics of route passenger flow data, and determining the time granularity; performing qualitative analysis on the line passenger flow data from a time dimension and a space dimension to obtain bus line passenger flow characteristics in the time dimension and bus line passenger flow characteristics in the space dimension; quantifying a passenger flow similarity relationship between lines and a passenger flow circulation relationship between line stations, and screening out high-correlation spatial-temporal characteristics; a bus route passenger flow prediction combination model is constructed, and the bus route passenger flow prediction combination model is trained, tested and optimized; and inputting to-be-predicted bus route data into the trained bus route passenger flow prediction combination model, and outputting a bus route passenger flow prediction result. According to the invention, more accurate and effective line passenger flow prediction data is provided, a system is helped to formulate a daily operation scheduling scheme which is more practical, resource waste is reduced, and transportation efficiency is improved.

The invention discloses an intelligent network connection bus operation optimization control method based on a heterogeneous line scene, and relates to an intelligent network connection bus operation optimization control method. The invention aims to solve the technical problems of non-uniformity of bus time intervals and congestion of stations and intersections of intelligent networked buses running on bus lanes due to coexistence of a manual driving bus route and an intelligent networked bus route at present. According to the intelligent network connection bus operation hierarchical optimization control model established by the invention, the optimal speed control scheme and the signal priority scheme are output under the condition of considering the uncertainty of manual driving bus operation, the uniformity of the time headway is improved, and the number of times of entering a node for queuing is reduced. The method provides a new thought for efficient operation of an intelligent network connection bus company, and is of great significance in promoting large-scale operation of the intelligent network connection bus from a specific simple road to a complex road.

The invention discloses a bus stop board content generation method combined with people flow analysis, and relates to the technical field of information processing, and the method comprises the steps: obtaining the bus operation line data of a target bus stop, monitoring and analyzing the station flow data of a certain line and the in-vehicle flow of a target vehicle, and predicting the in-vehicle flow when the vehicle arrives at the station; in combination with the route prediction flow of the platform, if the total flow exceeds a vehicle bearing threshold, activating a hitchhiking linkage platform, and generating and optimizing a hitchhiking route sequence; and mapping the optimized hitchhiking route information to each bus route according to a predetermined layout scheme, and dynamically displaying the optimized hitchhiking route information on a platform display screen. The technical problem that in an existing bus stop board content updating mode, passenger flow fluctuation is difficult to respond in time is solved, and the technical effects that the real-time performance and accuracy of bus stop board content updating are improved, so that passenger flow fluctuation is responded in time, and passenger distribution and traffic resource utilization are optimized are achieved.

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.

Method for operating a first slave (104 ae) in a ring-shaped closed bus line (100) which is connected to a master (102) and at least one further slave (104 ae), wherein the master (102) sends at least one forward telegram in a forward direction and at least one reverse telegram in a reverse direction via the bus line to the slaves (104 ae), wherein the method comprises the following step: Deactivating (200) a buffer memory (400, 402) of the first slave (104 ae) to suspend forwarding of forward and reverse telegrams until a reactivation time when the forward and reverse telegrams are received within a predetermined time window.