198 results about "Bus transit" patented technology

The invention discloses a bus passenger getting-on station estimation method based on multi-source data fusion, and relates to the field of public traffic operation planning and management, and the method comprises the steps: obtaining multi-source sample data, and carrying out the integration processing, and obtaining database storage information; processing and extracting by using the public transport data preprocessing terminal to obtain a public transport operation time parameter; segmenting and constructing a fixed threshold time window; matching the intelligent card data to obtain an intelligent card data set of the candidate site; performing first data screening, constructing a candidate site group, and calculating by using a maximum likelihood estimation model to obtain a first data set of a determined site; performing second data screening and division to obtain a time sequence subset, and performing prediction by using a prediction neighbor information algorithm to obtain site information of the second data; and carrying out unified site numbering to obtain a site matching data set, and carrying out verification by using a multi-dimensional data terminal to obtain an evaluation result of the multi-dimensional data. According to the method, key field dependence is broken through, and data adaptability is improved.

The invention discloses an intelligent bus scheduling system and method based on an AI large model, and the system comprises a data collection unit which is used for collecting multi-source urban traffic data; the data preprocessing unit is used for performing cleaning, standardization and feature extraction on the acquired multi-source urban traffic data; the knowledge graph construction unit is used for constructing the processed data into a knowledge graph containing entities, relationships and attributes; the AI reasoning unit is used for generating a natural language scheduling suggestion based on the knowledge graph state; the strategy optimization unit is used for optimizing a scheduling strategy based on a reinforcement learning algorithm; and the execution feedback unit is used for executing the scheduling instruction and collecting execution effect feedback. The problems that an existing bus dispatching system is insufficient in data utilization and lacks deep understanding and reasoning ability for a complex traffic environment are solved.

The invention provides a parallel main cabinet type direct current charging pile system, which comprises a main control unit, at least one power distribution matrix unit, at least one main cabinet and a plurality of charging terminals, and is characterized in that each main cabinet is internally provided with a plurality of pluggable power supply modules, and each charging terminal is provided with at least one charging gun; the switching control logic of the power distribution matrix unit supports any power scheduling across a main cabinet, across a charging terminal and across a charging gun; each power distribution matrix unit is constructed as an M * N full-connection switch matrix, and the power distribution matrix unit dynamically switches the output power of any one power supply module to any one charging gun. The main control unit dynamically dispatches the output ports of the SCU to be connected in parallel according to the number of the charging gun, automatic superposition of power of multiple main cabinets is achieved, the megawatt charging requirements of electric heavy trucks, buses and the like are met, any power module is supported to be correspondingly connected with the charging gun of any number, and the physical boundary among the main cabinets, the charging terminals and the charging gun is broken.

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 an artificial intelligence-driven bus real-time scheduling and path optimization method. The artificial intelligence-driven bus real-time scheduling and path optimization method comprises the following steps: S1, multi-source data acquisition; s2, data preprocessing; s3, constructing an artificial intelligence scheduling optimization model; s4, generating a real-time scheduling decision; s5, vehicle execution and data feedback; and S6, path dynamic optimization. Through deep fusion of an artificial intelligence technology and public transportation services, the precision, dynamic and intelligent scheduling decision is realized, and finally the operation efficiency and service quality of a public transportation system are improved.

The invention discloses an electric bus station optimization scheduling method and system based on light storage and charging cooperation. The method comprises the following steps: acquiring parameters; according to the obtained parameters, an electric bus charging and discharging behavior model, a photovoltaic output model, an energy storage system operation model and a charging pile operation model considering a one-pile multi-gun sharing mode are established; by taking the minimization of the total operation cost of the station as a target and taking the established unit models as constraints, constructing an optical storage and charging integrated electric bus station optimization scheduling model, and solving to obtain a scheduling plan in the station; and issuing the solved scheduling plan to a station operation control system to generate a scheduling instruction and a charging and discharging instruction of the electric bus so as to realize cooperative scheduling of the station optical storage and charging resources. According to the method, the physical matching relation of the vehicle pile gun is depicted finely, the problem of symmetric solution space explosion caused by neglecting equipment homogenization in a traditional model is solved, and the solving efficiency and feasibility of a large-scale scheduling problem are remarkably improved.

This invention provides a method for optimizing the shared use of dedicated bus lanes, relating to the field of transportation technology. The method includes: identifying congested road sections and obtaining vehicle speeds in each lane of the congested sections; comparing the congestion levels of dedicated bus lanes and regular lanes by calculating travel indices, and identifying routes where regular lanes are congested while dedicated bus lanes are unobstructed; establishing a multi-objective integer optimization model with the objectives of maximizing the number of shared vehicles available for reservation and minimizing overall road delays; solving for the maximum number of vehicles that can use the dedicated bus lane during a given time period; conducting simulations to verify the multi-objective integer optimization model and evaluating the impact of the shared reservation scheme on dedicated bus lanes and regular lanes; and, considering user acceptance, constructing a mechanism for regular vehicles to reserve bus lanes using carbon credits. This invention addresses the shortcomings of dynamic schemes and the one-size-fits-all approach to existing dedicated bus lane management models.

The invention discloses a transportation hub transport capacity scheduling system based on big data, and particularly relates to the technical field of traffic scheduling, which comprises a data aggregation and sensing module, an early warning and triggering module, a scheduling scheme simulation and decision module and an instruction distribution and execution monitoring module. The system collects subway, bus, taxi, online car-hailing and passenger flow data in real time through a multi-source interface and a sensor, and a unified transport capacity diagram is generated after cleaning and anomaly detection; carrying out transport capacity gap identification and early warning based on a multi-index coupling risk analysis model; a plurality of scheduling schemes are generated and evaluated through a microscopic simulation model integrated with passenger behavior prediction, and an optimal scheme is recommended; finally, the scheme is converted into a specific instruction to be distributed and executed, and real-time monitoring and feedback are performed to form closed-loop management. According to the invention, the transformation from passive response to active intervention and from experience decision to scientific scheduling is realized, and the transport capacity cooperation efficiency and passenger evacuation capability of the transportation hub are significantly improved.

The invention discloses a public transport passenger flow prediction method based on IC card data, which relates to the technical field of intelligent transportation, and comprises the following steps: respectively carrying out feature inspection on a week time sequence, a day time sequence, a time interval sequence and a holiday effect sequence, selecting an adaptive model, carrying out parameter and noise variance feature analysis on the adaptive model by using an RLS algorithm, and carrying out prediction on the public transport passenger flow. Outputting four groups of prediction result sequences; models corresponding to the four groups of prediction result sequences are converted into a state space form, a noise variance estimation value is estimated online through an RLS algorithm, and four groups of time-varying fusion weights are generated; and constructing an observation noise covariance matrix based on the four groups of time-varying fusion weights, performing recursive optimization through a Kalman filter, and outputting a hybrid prediction result by weighting and fusing observation prediction values of the four groups of sequences. According to the method, accurate fitting of passenger flow periodicity, seasonality and heterovariance is realized, and the single-model prediction precision is improved.

The invention discloses a multi-mode collaborative passenger flow acquisition and guidance method and system for a honeycomb bus port in a peak period, and the method comprises the steps: obtaining the real-time passenger flow video data, collected by hardware equipment, of a target region, and calculating the risk score of the target region according to the real-time passenger flow video data; generating a corresponding passenger flow guiding strategy based on the risk score; the passenger flow guiding strategy comprises an unmanned aerial vehicle guiding strategy and a ground guiding strategy; controlling the unmanned aerial vehicle and the ground personnel to guide the passenger flow according to the passenger flow guide strategy; according to the invention, the accuracy, high efficiency and intelligentization of passenger flow guidance are realized, the guidance efficiency and emergency response speed are effectively improved, and the system toughness and safety in a large passenger flow scene are significantly enhanced.

The invention discloses a bus dedicated path planning method and system for coping with multi-dimensional consideration, and relates to the technical field of path planning, and the method comprises the steps: synchronously collecting the multi-dimensional data of a target road section, and calculating a real-time traffic entropy value based on an information entropy theory; determining participants, performing auditing to generate an effective bidding list, regarding road use right distribution as a cooperative game problem, calculating marginal contribution of each game subject by adopting a Shapley value algorithm, and screening an optimal bidding combination; dividing traffic state intervals, combining the optimal bidding combination, the real-time traffic entropy and the exclusive lane occupancy rate, deciding the right to use according to an interval allocation rule, and generating a standardized allocation scheme; and converting the distribution scheme into a V2X broadcast instruction to be pushed, completing dynamic lane mark switching and passing guidance, collecting feedback data in real time to judge whether deviation occurs, and if the deviation is judged, dynamically adjusting the scheme and re-executing the scheme, thereby realizing dynamic optimal configuration of bus lane resources and system stability.

The invention belongs to the technical field of urban planning, and particularly relates to a traffic station region land utilization efficiency evaluation method, which comprises the following steps of: acquiring and preprocessing point-of-interest data and a traffic station region in an analysis region; extracting land utilization layout features based on the null data set; constructing a multi-mode traffic network including walking, bicycles, buses and rail transit based on the layout features; establishing a land coupling simulation model of traffic based on the regional reachability index; causal inference and model calibration are carried out based on historical traffic intervention events of dynamic evolution; adopting a multi-objective optimization algorithm to generate traffic and land utilization configuration schemes meeting different planning objectives; according to the method, the evaluation result is subjected to visual display and decision output, unified modeling of traffic and social economic data is achieved through multi-source heterogeneous data fusion and standardization processing, and the effect of improving data space-time matching precision and calculation reliability is achieved.

1. Name of the product in this design: Platform screen door (semi-enclosed lifting type). 2. Application of this design: It is used in rail transit, installed on the safety line of high-speed railway platforms; it can also be used in other fields such as subways and buses. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: a 3D model.

The utility model relates to a trolley technology field discloses a bus trolley battery mounting anti -loose fixed knot structure, including the frame, the one side of frame is provided with a plurality of connecting bolts, the one side of frame is provided with the battery protection board, the one side of battery protection board away from frame is provided with a plurality of anti -loose gasket, the one side of anti -loose gasket away from battery protection board is provided with locking nut subassembly, the outer wall of connecting bolt is connected in the inner wall of locking nut subassembly, the outer wall of connecting bolt is provided with anti -loose subassembly. In the utility model, through frame and battery protection board provide support for battery, through the thread connection of connecting bolt and locking nut subassembly, through the function of anti -loose gasket and locking nut subassembly self -locking anti -loose, and through the cooperation of anti -loose subassembly, thereby solved the situation that traditional torque control assembly process exists clamping force attenuation, and then make long -time frequent vibration can lead to the problem of nut loosening.

The invention discloses a bus passenger getting-off station prediction method and system based on rank learning, and the method comprises the steps: obtaining bus card swiping data and weather data, carrying out the data preprocessing and data normalization processing, and constructing a normalized to-be-predicted line feature matrix; constructing a sorting learning model according to the normalized feature matrix of the to-be-predicted line; and through a LambdaMART algorithm, carrying out feature prediction, index screening and parameter adjustment processing on documents in the sorting learning model to obtain a bus passenger getting-off station prediction result. According to the method, the spatial relationship between the stations can be utilized more effectively, so that the prediction precision and stability are improved. The bus passenger getting-off station prediction method and system based on sorting learning can be widely applied to the technical field of machine learning.

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 utility model discloses a bus station advertisement panel convenient to replace advertisements, which comprises an advertisement panel shell arranged on a bus station stand column, first glass panels are arranged at openings on two sides of the advertisement panel shell, the advertisement panel shell comprises mounting outer frames which are symmetrically distributed, and first glass panels are arranged on the mounting outer frames. The symmetrically-distributed outer mounting frames are located in the advertising panel shell, connecting plates are arranged on the side edges of the outer mounting frames, and the upper side and the lower side of each connecting plate are connected with the upper side and the lower side of the inner wall of the advertising panel shell through sliding assemblies correspondingly; a second glass panel is arranged in the mounting outer frame, and locking assemblies are arranged on the periphery of the edge of the outer side of the mounting outer frame; the sides, away from the connecting plate, of the outer mounting frames on the two sides are connected with a handle through side edge plates. According to the utility model, the problem that the operation space is limited when advertisements are replaced is solved, the operation space of workers is increased, and the advertisements are convenient to replace.

The invention discloses a typhoon pre-disaster and post-disaster interconnected power distribution network recovery method based on a reconfigurable soft switch, and the method comprises the steps: considering the power support function of an electric bus in a pre-disaster stage, combining the reconfigurable soft switch with the port topology cooperative change of the interconnected power distribution network, building a pre-disaster deployment model of the electric bus, and carrying out the power support function of the electric bus; therefore, the parking position of the electric bus before the fault occurs is determined; in the post-disaster stage, the uncertainty of renewable energy sources and loads in continuous faults and recovery of the interconnected power distribution network is considered, an event-driven recovery model is constructed by defining fault events and predicting error events through an event-driven mechanism, and therefore an interconnected power distribution network fault recovery strategy is obtained to promote fault recovery of the interconnected power distribution network. According to the invention, fault deduction can be carried out before disasters, potential power-losing loads are reduced, and power supply recovery after disasters is accelerated; in the post-disaster continuous fault state, strategy updating can be triggered in real time, and the method adapts to fault evolution and uncertainty of renewable energy sources and loads.

This invention relates to the field of public transportation technology, specifically to a temporary charging method suitable for temporary charging of driverless buses, comprising a temporary battery vehicle and a driverless bus; the temporary battery vehicle includes a battery body, a drive chassis mounted on the lower end of the battery body, a control body mounted on the upper end of the battery body, and an identification mechanism mounted on the upper end of the control body; the driverless bus includes a vehicle body and a receiving cavity mounted at the rear of the vehicle body suitable for housing the temporary battery vehicle; this invention addresses the technical problems of ensuring the continuity of driverless bus operation, preventing insufficient battery power during operation, and avoiding excessively long charging waiting times for driverless buses at depots.

This invention provides a Bus Rapid Transit (BRT) system and method based on onboard ticketing and inspection, comprising at least one BRT vehicle and at least one BRT station matching the operating route of the BRT vehicle; wherein, the BRT vehicle is equipped with at least one contactless payment terminal inside the vehicle for passengers to pay for their tickets after boarding; and, the BRT station does not include an enclosed concourse level for ticketing or inspection, allowing passengers to directly access the waiting platform level via an open passageway. This invention significantly reduces construction and operating costs, improves passenger experience, and enhances system flexibility.

The invention discloses an automatic bus stop reporting system based on single-chip microcomputer control. The automatic bus stop reporting system comprises a single-chip microcomputer control unit, a wireless transceiver module, a voice module, a display module, a temperature sensor and a clock module. The single chip microcomputer control unit is used for processing and controlling the whole station reporting system; the wireless receiving and transmitting module is used for receiving and transmitting wireless signals and identifying station names; the voice module is used for converting the station name information into voice broadcast; the display module is provided with a liquid crystal display screen, and the liquid crystal display screen is connected with a P0 port of the single chip microcomputer; the temperature sensor is connected with a P3.3 port of the single chip microcomputer; and the clock module is connected with P1.0 to P1.2 ports of the single chip microcomputer through a serial interface.

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

The application discloses a bus riding route planning method based on human-vehicle-road cooperation and belongs to the cross-application field of intelligent networked public transport system design. The method comprises the following steps: collecting passenger external origin-destination point demand data, real-time road condition data, bus station GIS data and road network GIS data; associating the external origin-destination point with the nearby bus station according to the passenger external origin-destination point demand data and the bus station GIS data; estimating the walking transfer time between the external origin-destination point and the corresponding bus station; sequentially connecting the bus stations associated with the external origin-destination point based on the shortest path principle to obtain the bus driving path; constructing an optimization model, with the target being the minimum total passenger travel time and the constraint condition being that the passengers only board from the bus stations associated with the external origin-destination point; and solving the optimization model to obtain the time and position information of the boarding and alighting bus stations.

This invention relates to the field of smart city technology, and in particular to a method and system for accurately pushing dynamic information from smart city bus stop signs. The method involves constructing a query semantic representation structure by collecting query requests and scene state information, obtaining a joint understanding representation through multi-level semantic association modeling with scene state information, performing scene-constrained multi-hop reasoning in a public transport knowledge association network, filtering and generating candidate answer sequences, calculating scene suitability scores, selecting the optimal answer to generate push content, and collecting interactive feedback to adaptively adjust feature fusion weights to form a closed-loop optimization. This achieves accurate dynamic push of public transport information and improves user experience.

The present application relates to a kind of wisdom public transport combined scheduling method, device and storage medium, it is related to scheduling optimization field, call bus card record establishes card site feature set, establishes navigation site trigger and carries out navigation record matching analysis, establishes space-time heat forecast graph;Multi-source traffic flow data set is constructed to carry out road congestion state prediction and construct regional level road congestion state graph;According to space-time heat forecast graph, regional level road congestion state graph, establish site passenger flow demand, line travel time and congestion state;Configure multi-objective scheduling channel, and site passenger flow demand, line travel time and congestion state are used as input data, by passenger waiting time target, scheduling cost target, vehicle utilization rate target, congestion influence target, line bus scheduling optimization is carried out, the technical problem that the present application solves is that there is data utilization insufficient, prediction precision is limited and scheduling strategy lacks flexibility in bus scheduling.

This invention relates to a method, device, and medium for optimizing the matching of flexibility resources for electric buses. It constructs a single-vehicle energy consumption prediction model for electric buses that includes a quadratic temperature term, and establishes a battery capacity correction model that considers low-temperature degradation and limited regenerative braking to obtain the physical boundary of flexibility resources. The method uses kernel density estimation to fit the probability distribution of bus return time and dwell time, and combines this with the energy consumption prediction model to establish state-of-charge (SOC) opportunity constraints. Under the physical boundary of flexibility resources and SOC opportunity constraints, a hierarchical response mechanism with dead-zone control is used to implement vehicle-grid flexibility supply and demand matching, and to formulate an optimal vehicle-grid coordinated flexibility resource allocation scheme. Compared with existing technologies, this invention can correct the energy consumption prediction bias of traditional linear models under extreme temperatures, alleviate the scheduling mismatch problem caused by the randomness of return time, and improve the response capability of electric bus clusters to participate in grid peak load reduction while considering battery life.

The invention discloses a bus intelligent scheduling optimization method and system based on a multi-source data fusion model, relates to the technical field of intelligent traffic and public traffic operation management, is suitable for an intelligent bus use scenario, and comprises the following steps: a terminal collects continuous sampling operation data and active safety alarm to form a local data stream; and segmenting operation segments according to bus event semantics, generating versioned evidences, and reporting segment abstracts. The terminal receives and analyzes a scheduling instruction generated by the cloud platform based on the abstract, wherein the instruction carries evidence consistency and observation freezing control, candidate action and intensity gears and effective windows, two-stage instructions, instruction serial numbers and evidence version binding fields; the preparation state is low disturbance and can be revoked, and the submission state is strong action and is executed after conditions are met. And the terminal carries out idempotent processing and staged execution according to the serial number and the version number. According to the method, repeated issuing is effectively reduced, rebounding and gating overturning are cancelled, and execution consistency and recoverability are improved.

The utility model relates to the technical field of sunshade equipment, in particular to a sunshade. According to the technical scheme, the greenhouse comprises a greenhouse roof and further comprises a supporting cover fixedly connected to the lower surface of the greenhouse roof, and a pair of roller shutter mechanisms for sun shading are arranged in the supporting cover; and a pair of switching mechanisms. Through the cooperation of the shed roof, the supporting cover, the roller shutter mechanism, the switch mechanism and other structures, the sunshade is provided with an intelligent system, and the roller shutter mechanism can be automatically started according to the sun irradiation angle and the temperature change. At the high temperature of the burning sun, the sunshade roll film is accurately unfolded, sunlight is effectively blocked, and the heatstroke risk of passengers is reduced; when sun shading is not needed in daily life, the rolling film is folded, so that the sunshade is compact in structure, space is saved, and the bus station is more flexible and attractive in design. Besides, the system can intelligently control a sunshade roll film switch according to illumination characteristics of different seasons and time periods, so that the passengers can be shaded, clear identification of bus numbers is not affected, and the waiting experience is optimized in an omnibearing manner.

Embodiments of the present application provide a segmented bus fare calculation method and device, electronic equipment and storage medium, belonging to the technical field of public transportation fare calculation. The method comprises: performing vehicle-mounted machine state monitoring on a target segmented bus to obtain a vehicle-mounted machine running state, wherein the vehicle-mounted machine running state comprises a vehicle-mounted machine fault state; based on the vehicle-mounted machine fault state, generating a fault code for the target segmented bus to obtain a fault registration code; receiving journey registration data uploaded by a ride registration client based on the fault registration code; based on a preset journey data pool, performing matching query on the journey registration data to obtain a journey matching result, wherein the journey matching result comprises journey matching success information; and based on the journey matching success information and the journey registration data, performing ride fare calculation. Embodiments of the present application can improve the accuracy of segmented bus fare calculation in the case of vehicle-mounted machine failure.