45 results about "Passenger satisfaction" patented technology

The invention discloses an elevator control system based on artificial intelligence, which belongs to the technical field of elevator control, and comprises a plurality of layers of architectures such as data acquisition, transmission, processing, intelligent decision, execution control and the like. The data acquisition layer collects multi-source data through a car inside and outside and operation state sensor group; the data processing layer provides support for intelligent decision-making through preprocessing, analysis mining and model training optimization. An elevator dispatching module of the intelligent decision-making layer carries out peak dynamic zoning and flat peak energy-saving dispatching according to information such as passenger flow; the safety protection module monitors and processes hidden dangers in real time; the personalized service module provides customized services based on passenger behaviors and demands. And driving of the control layer, a door machine and a car environment control system are executed, and stable lifting of the car, safe operation of a door and intelligent environment adjustment are achieved correspondingly. Experiments show that the system can remarkably improve the elevator operation efficiency, safety and passenger satisfaction and reduce energy consumption, and has important application value.

The embodiment of the invention provides a multi-system rail transit junction streamline optimization method and device, and the method comprises the steps: carrying out the three-dimensional modeling of a multi-system rail transit junction, and obtaining a transportation junction model; dividing the transportation junction model into a plurality of digital blocks according to geographic information, facility layout information, passenger flow data and operation data of the multi-system rail transportation junction; according to passenger flow and logistics demands among different digital blocks, determining a connection relationship among the different digital blocks; according to the method, a streamline path is determined based on a connection relationship between different digital blocks, a streamline operation condition is simulated, a preset optimization target is taken as a target function, the streamline path is optimized, an optimized streamline is obtained, and the operation efficiency of the hub is effectively improved through division of the digital blocks in the hub and optimization of streamline organizations and stream nodes between the blocks; the travel time of passengers is shortened, and the passenger satisfaction is improved.

The invention provides a demand response bus intelligent scheduling method and system driven by real-time data. A demand response bus intelligent scheduling method driven by real-time data comprises the following steps: S1, collecting and fusing multi-source data in real time, and constructing a dynamic data set; s2, carrying out short-time demand prediction and clustering analysis based on LSTM and DBSCAN; s3, dynamic service area division and greedy algorithm line generation; s4, elastic vehicle scheduling based on combination of mixed integer programming and a simulated annealing algorithm; s5, dynamically adjusting the real-time ticket price driven by the supply and demand game model; s6, passenger personalized service matching is achieved through a collaborative filtering algorithm; s7, performing multi-target simulation verification on the digital twin platform; and S8, reinforcing a learning-driven dynamic feedback optimization mechanism. According to the real-time data-driven demand response bus intelligent scheduling method and system provided by the invention, the operation efficiency, the passenger satisfaction degree and the enterprise benefit of the demand response type customized bus can be remarkably improved, and the method and the system are suitable for construction of an urban intelligent bus system and have remarkable advantages.

The invention discloses a cruise ship theater temperature airflow organization evaluation system which comprises an adjusting module used for adjusting the air supply speed, the air supply amount and the air supply temperature in a cruise ship theater; the data acquisition module is used for acquiring air supply speed, air supply quantity and air supply temperature data of the passenger sightseeing area and performance area measuring point trees; the data recording module is used for recording the collected air supply speed, air supply quantity and air supply temperature data in real time to obtain the change process of the temperature and the air flow along with time; and the data evaluation module is used for obtaining an indoor temperature field and air flow organization distribution in a stable state according to the obtained change process of the temperature and the air flow along with the time. The invention further discloses a cruise ship theater temperature airflow organization evaluation method. According to the invention, the temperature and airflow field measurement precision of the cruise ship theater is improved, and data support is provided for subsequent air conditioner air port position adjustment, so that the environment comfort of the theater and the passenger satisfaction are improved.

The invention relates to the field of rail transit, and discloses a rail transit safety monitoring method and system based on the Internet of Things, and the method comprises the steps: carrying out the statistical analysis of passenger access related data, drawing a passenger flow change curve of each entrance, recognizing a passenger flow peak time period and a passenger flow trough time period, and extracting passenger flow features from the peak time period and the trough time period; according to the passenger travel information data and the number of passengers entering and exiting the entrances and exits, the crowdedness degree of the getting-on positions and the flow direction distribution of the passengers at the entrances and exits on the platform are analyzed, the crowdedness degree of each getting-on position in different time periods is comprehensively predicted, and the train operation plan is adjusted according to the prediction result. And getting-on safety risk analysis and detection are carried out according to prediction results of crowdedness degrees of all getting-on positions in different time periods, real-time passenger flow volume fluctuation and platform safety capacity, possible crowded getting-on positions and safety risks can be found in advance, the train running state can be flexibly adjusted according to the actual passenger flow condition, and the safety of the train is improved. And the train operation efficiency and the passenger satisfaction are improved.

The invention relates to a gate control method and device for an airport security check channel, equipment and a medium. The method comprises the steps of obtaining a current passenger inflow rate, a current passenger outflow rate, a gate change factor, a personnel change factor and a passenger satisfaction degree of an airport security check channel gate, determining a gate admission rate and a gate exit rate according to the data, obtaining a time interval of successive gate opening of the gate, and controlling the gate to execute corresponding operation. By adopting the method, the opening and closing speed of the gate can be dynamically adjusted, so that the visitor flow in the airport security check channel is controlled, and the high-efficiency management of the security check channel is realized.

The invention relates to the technical field of passenger flow distribution, in particular to a quasi-dynamic random user balanced distribution method, electronic equipment and a storage medium, and the method comprises the steps: firstly obtaining a line physical network of urban rail transit, then building a travel transfer network based on the line physical network, and then building a travel transfer network based on the travel transfer network; and constructing a quasi-dynamic random user balanced distribution model, and then solving the quasi-dynamic random user balanced distribution model according to the line physical network to obtain a target passenger flow distribution result. By solving the quasi-dynamic random user equilibrium distribution model, the target passenger flow distribution result of the line interval in each time period can be quickly obtained, so that the problem of complexity in dynamic passenger flow distribution of urban rail transit is effectively solved, and the overall operation efficiency and passenger satisfaction of a traffic system are improved.

The invention relates to the technical field of intelligent fitness bus stations, and particularly discloses a sports equipment matching recommendation system for an intelligent fitness bus station. According to the method, the duration constraint influence factor is calculated according to the predicted waiting duration of the target passenger and the effective exercise duration of each to-be-analyzed sports apparatus, and the time limit of the passenger staying at the bus station is fully considered, so that the recommended apparatus can achieve a certain exercise effect within the time range acceptable by the passenger, and the user experience is improved. The recommendation feasibility and practicability are improved, the final matching recommendation degree is calculated according to the basic matching recommendation degree and the duration constraint influence factor, the recommendation result is further optimized on the basis of comprehensively considering the physiological features, the exercise preference and the time constraint, the finally recommended exercise equipment is made to better meet the actual requirements and conditions of passengers, and the user experience is improved. Sports equipment selection more conforming to the overall condition is provided for passengers, the satisfaction degree of the passengers on recommendation results is improved, and the willingness of the passengers to use the sports equipment of the intelligent fitness bus station is enhanced.

The invention provides a car-sharing boarding point recommendation method and system for inter-city online car hailing. The method comprises the following steps: acquiring inter-city traffic network data; projecting the three-dimensional road network to a two-dimensional topological plane; calculating the dynamic weight of each road based on the real-time traffic data; folding the secondary road according to the dynamic weight and the folding threshold to generate a backbone network; generating candidate recommendation results on the backbone network, wherein the candidate recommendation results comprise necessary points, selectable points and dynamic adjustment points; and carrying out optimization screening on the candidate recommendation results to obtain recommended boarding points. According to the invention, through dynamic weight calculation and backbone network generation, changes of traffic conditions can be reflected in real time, more accurate recommended boarding points can be generated, the ride-sharing efficiency can be improved, and through generation of diversified candidate recommendation points and optimization of candidate results, ride-sharing demands of different passengers can be satisfied, and the satisfaction degree of the passengers can be improved. The generation of the backbone network and the optimization of the candidate points effectively improve the calculation efficiency, so that the recommendation system can respond to the passenger request more quickly.

The invention discloses a rail transit ticket price optimization method and system based on big data, and relates to the technical field of intelligent optimization, and the method comprises the following steps: carrying out the first matching according to operation data and a distance radiation condition, carrying out the second matching according to the operation data and a date radiation condition, and calculating overlapping passenger flow resources and inverse difference passenger flow resources; and performing first optimization, calculating the total profit after the first optimization, and performing second optimization on the ticket price of the station after the first optimization according to the profit expectation. According to the invention, the ticket price is optimized, the passenger flow is distributed more reasonably, the congestion in peak hours is reduced, the utilization rate of trains is improved, the ticket price is optimized, the ticket price income is improved, the satisfaction degree of passengers is improved, the ticket price is flexibly adjusted according to different dates, time and passenger flow changes, the market change and the passenger demand are better adapted, and the market competitiveness is improved. The ticket price optimization method based on the big data significantly improves the operation efficiency and economic benefits of rail transit in practical application, and can provide higher-quality services for passengers at the same time.

To provide a technique of increasing a passenger satisfaction degree in a service for distributing content to passengers of vehicles.SOLUTION: A control unit of an information processing device acquires a passage time at which a vehicle actually passes a prescribed halfway point of a scheduled travel route, and calculates a scheduled arrival time at which the vehicle is predicted to arrive at a destination of the scheduled travel route in accordance with the acquired passage time. The control unit of the information processing device calculates a surplus time length representing the difference between the scheduled arrival time and a scheduled content distribution end time if the scheduled content distribution end time is earlier than the calculated scheduled arrival time. The control unit of the information processing device outputs information about the calculated surplus time length and proposal information including information for encouraging a delay of the scheduled content distribution end time.SELECTED DRAWING: Figure 5

The present invention provides a global planning method for multi-passenger itineraries on a cruise ship, belonging to the technical field of cruise ship operation and maintenance. In the present invention, the global planning problem of multi-passenger itineraries on a cruise ship is modeled as a multi-agent orientation problem model considering venue capacity and time windows. The constraints of cruise passenger itinerary attributes, service venue attributes, and coupling constraints between passenger itineraries are transformed into constraints of state variables and control variables in the mathematical model. By using the optimal benefit density construction method, a high-quality initial solution is obtained. Furthermore, an adaptive large neighborhood search algorithm with an improved destruction-repair operator is used to solve the multi-agent orientation problem considering venue capacity and time windows, and a global itinerary plan for multi-passengers on a cruise ship that meets the complex environmental constraints of the cruise ship, has good usability, and strong rationality can be given, which is of great significance for improving the passenger satisfaction and on-board service quality of high-tech ocean liners represented by large cruise ships.

A kind of urban rail transit line transport capacity precision regulation and control method, comprising: S100. Obtain urban rail transit line transfer passenger data, according to the transfer passenger data, section passenger flow information is obtained;S200. Obtain car fixed number information, according to the section passenger flow information and car fixed number information, the section congestion degree of urban rail transit line is obtained, according to the section congestion degree, transfer passenger flow density information is obtained;S300. Establish periodic train diagram evaluation mechanism, according to the transfer passenger flow density information, optimize rail transit line train diagram;S400. Real-time update the transfer passenger flow density information, the train diagram iterative optimization is carried out, set the iteration number or other iteration termination condition, obtain the final rail transit line train diagram.The method disclosed in the application considers the distribution of transport capacity in transfer station with different transfer passenger flow density, can save passenger travel time, improve passenger satisfaction, and reasonably allocate transport capacity.

The application discloses an airport bus network optimization method and system integrating air traffic control information, and the method comprises the following steps: acquiring the geographical range of the airport bus operation area, passenger reservation demand and passenger online car-hailing order data generated by the influence of flight dynamic changes according to the air traffic control information; determining all airport bus station positions in the airport bus operation area; establishing a target function according to passenger travel time cost and airport bus operation cost, and establishing constraint conditions according to the maximum number of passengers served by the airport bus starting station, the service level of the airport bus service, the lower limit and the upper limit of the time window in which the passenger expects the airport bus to arrive; and solving a reservation response bus scheduling model to obtain an airport bus scheduling scheme. Under the condition of flight changes, the number of passengers taking the airport bus and their destinations can be known in advance, the operation strategy can be quickly adjusted, and the vehicle scheduling can be optimized, so that the waiting time and in-vehicle time of passengers can be effectively saved, and the passenger satisfaction under the condition of flight changes can be improved.

The present invention discloses an intelligent bus stop guidance system. The intelligent bus stop guidance system of the present invention integrates highly automated technical components. The system ensures that passengers get on and off the bus in an orderly manner through automatic telescopic doors or fences. At the same time, the projection device adjusts the projection area according to the real-time passenger flow, and clearly indicates the appropriate boarding area. It not only optimizes the passenger flow and reduces congestion, but also significantly improves the efficiency and safety of riding. In particular, when the alarm module of the system detects that a passenger cuts in line or fails to enter a non-designated boarding area as instructed, it will automatically activate the blocking device and issue visual and sound warnings to force the passengers to return to the designated area, thereby directly reducing disputes and confusion caused by disorderly riding and significantly improving the riding experience. In addition, the credit point mechanism records the behavior of each passenger, punishes violations, and further regulates the behavior of passengers, thereby improving the overall operating efficiency and passenger satisfaction of the public transportation system in the long term.

The invention discloses an intelligent passenger satisfaction prediction method and system and a storage medium, and belongs to the technical field of data processing. The method comprises the following steps: collecting multi-source data of a target passenger and an associated group thereof; based on the multi-source data, respectively generating a substantial experience feature representation of the target passenger and a psychological expectation feature representation of multiple dimensions; performing dynamic fusion on the essential experience feature representation and the psychological expectation feature representation of the multiple dimensions through a difference perception fusion mechanism to generate a comprehensive feature representation; and based on the comprehensive feature representation, outputting a satisfaction prediction value through a machine learning model. According to the method, accurate prediction of the passenger satisfaction is realized by fusing the multi-source data and dynamically quantifying the expected difference.

The invention discloses a dynamic aircraft stand redistribution method based on a passenger gathering degree and an electronic terminal, and the method comprises the steps: obtaining aircraft stand information and initial flight plan information of an airport, and obtaining flight delay information; according to the flight initial plan information, according to a flight first-arrival first-service rule, carrying out machine position distribution, and generating a machine position pre-distribution scheme; calculating a single-flight passenger gathering probability at a boarding gate; and setting parameters of a taboo search algorithm, taking the minimum passenger adjustment loss time after the aircraft position changes as a target function, inputting the aircraft position pre-distribution scheme and the flight delay information into the taboo search algorithm for solving, and generating an aircraft position redistribution scheme. According to the invention, extra adjustment time of passengers caused by change of the boarding gate can be reduced to ensure the satisfaction of the passengers; the tabu length is adjusted to be a variable which changes along with the frequency of a tabu object, and a neighborhood moving method is finely divided, so that the solving speed is improved, and rapid optimization is realized.

A system and method for individualized airline passenger disembarkment integrates with Passenger Service Systems (PSS) and Airport Operational Databases (AODB) using IATA New Distribution Capability (NDC) standards for real-time data exchange. Passengers book priority disembarkment options during reservations, with availability determined via priority queues in distributed software modules interacting with cloud-based hardware to allocate limited slots efficiently. Upon detecting delays, the system identifies at-risk passengers for missed connections by computing gate-to-gate travel times using graph data structures, assigns priority disembarkment passes (physical or virtual) with verification elements such as QR codes, NFC, or RFID, and deactivates passes post-disembarkment via geo-fencing or hash-based structures. This reduces airline costs, enhances operational efficiency by minimizing latency and optimizing resources, and complies with aviation regulations across multiple jurisdictions while improving passenger satisfaction.

The present invention provides a method, device, electronic device and storage medium for adjusting the scale of a train operation diagram, the method comprising: determining the scale information of a train operation diagram to be adjusted; adjusting the scale information based on optimal scale information to obtain an adjusted train operation diagram; wherein the optimal scale information includes first scale information corresponding to the minimum average passenger waiting time determined in multiple historical scale information, and the multiple historical scale information and the scale information correspond to the same time period. The method, device, electronic device and storage medium provided by the present invention evaluate different historical scale schemes by taking the average passenger waiting time as a universal evaluation standard, and adjust the scale information of the train operation diagram based on the optimal scale information determined thereby, thereby improving the adjustment efficiency of the operation diagram scale and passenger satisfaction, ensuring the safe and efficient operation of the train, and reducing operating costs.

The present invention discloses a terminal security intelligent monitoring system and method based on the Internet of Things, relating to the technical field of terminal security intelligent monitoring, and comprising the following steps: during the operation of the frequency converter, converting data that the rectified direct current enters the inverter and is converted into alternating current of the required frequency through an insulated gate bipolar transistor is acquired in real time; features are extracted from the conversion data, and abnormal analysis is performed on the extracted features. The present invention uses a deep learning model to extract features and perform abnormal analysis on the conversion data, accurately identify potential abnormalities in the frequency conversion process of the frequency converter, ensure timely processing, prevent the fan from affecting the train ventilation and air conditioning systems. By comparing the actual and expected frequency curves, an expected deviation index is generated to provide a maintenance guide, reduce faults and downtime, improve the efficiency and lifespan of the frequency converter, ensure the normal operation of the train system, and improve the operation efficiency and passenger satisfaction.

The invention discloses a rail transit management method, system and device and a medium, and belongs to the technical field of rail transit, and the method comprises the steps: obtaining the current activity information, and preliminarily predicting the passenger flow during the activity through a first passenger flow prediction model built based on historical activity information; designing a target function by taking maximization of the rail transit income as a target, and generating an initial rail transit strategy during an activity period; based on the preliminarily predicted passenger flow volume and historical data of roads around the area where the activity is located, the congestion degree of self-driving routes of the roads around the activity area during the activity is predicted, and a detouring suggested route is generated based on the predicted congestion degree; and based on the actual activity data during the activity period, accurately predicting the passenger flow volume through the constructed second passenger flow volume prediction model, and adjusting and publishing the initial rail transit strategy based on the accurately predicted passenger flow volume. When large-scale activities are held, sharp increase of passenger flow volume can be effectively coped with, and the transportation efficiency and the passenger satisfaction degree are guaranteed.

In order to improve passenger satisfaction with a transportation service and to provide an operation plan creation means capable of reducing operating costs for a transportation service provider, an operation plan creation device comprises: a transportation leg network generation unit that generates transportation leg network information that defines each transportation leg of the transportation service; a cancellation determination unit that generates transportation leg cancellation possibility information that indicates whether or not cancellation of each transportation leg of the transportation service is possible; a travel route candidate determination unit that generates travel route candidate information that indicates a travel route candidate for each travel plan in passenger travel plan information; a people flow prediction unit that generates people flow prediction information that indicates a predicted people flow in the transportation service; and an operation plan generation unit that generates new operation plan information in which certain transportation legs of the transportation service are eliminated.

The invention discloses an aviation service recommendation method. The method comprises the steps of obtaining user behavior data of a to-be-tripped passenger and preprocessing the user behavior data; wherein the user behavior data comprises personal attribute data, flight travel data and service purchase records; inputting the preprocessed user behavior data into a pre-trained service recommendation model, and outputting a passenger feature tag of the to-be-tripped passenger; generating a service recommendation strategy based on the passenger feature tag; according to the service recommendation strategy, carrying out aviation service recommendation on the to-be-tripped passenger; according to the method, the requirements and preferences of the passengers can be more accurately captured, and the accuracy of aviation service recommendation is improved, so that the service quality and the satisfaction degree of the passengers are improved.

The embodiment of the invention provides a bullet train-based along-the-way wind and light video playing method and related equipment, a bullet train comprises a plurality of bullet train carriages, each bullet train carriage is provided with at least one public display screen and a plurality of passenger seats and passenger interaction terminals, and the method comprises the following steps: acquiring real-time geographic position information of the bullet train in the running process, the real-time geographical location information is matched with a plurality of sceneries along the way; when the real-time geographical location information is matched with the target scenery along the way, controlling a public display screen and a passenger interaction terminal to play a scenery introduction video; in response to a reading request of the target passenger interaction terminal for the target interest point, playing detailed introduction data of the target interest point in the target passenger interaction terminal; and determining the remaining time along the way based on the playing end time, further obtaining the compressed introduction video, and playing the compressed introduction video on the target passenger interaction terminal after the detailed introduction data is played on the target passenger interaction terminal, thereby remarkably improving the riding satisfaction of the passenger.

The invention discloses a pick-up and drop-off reservation recommendation method and system, a medium and equipment. The method comprises the following steps: acquiring journey data and flight dynamic data of a user in real time; according to the journey data and the flight dynamic data of the user, determining a recommendation scene of the pick-up and drop-off service; and according to the recommendation scene of the pick-up service, preset pick-up arrival information in the recommendation scene is pushed to the user. According to the invention, the most suitable pick-up service scene can be intelligently recommended to the user according to the journey data and the flight dynamic data of the user, the reservation accuracy is improved, the waiting time is reduced, the satisfaction and experience of passengers are improved, the resource allocation is optimized, and the operation cost is reduced.

The invention discloses a terminal safety intelligent monitoring system and method based on the Internet of Things, and relates to the technical field of terminal safety intelligent monitoring, and the method comprises the following steps: in the operation process of a frequency converter, obtaining the conversion data of a rectified direct current which enters an inverter and is converted into an alternating current with a required frequency through an insulated gate bipolar transistor in real time; and performing feature extraction on the converted data, and performing anomaly analysis on the extracted features. The deep learning model is used for carrying out feature extraction and anomaly analysis on the conversion data, potential anomaly in the frequency conversion process of the frequency converter is accurately recognized, timely processing is ensured, and a draught fan is prevented from influencing a train ventilation and air conditioning system. Through comparing actual and expected frequency curves, an expected deviation index is generated, maintenance guidance is provided, fault and downtime is reduced, efficiency and service life of a frequency converter are improved, normal operation of a train system is guaranteed, and operation efficiency and passenger satisfaction are improved.

The invention discloses a continuous ticket refunding method influenced by the arrival delay of a front train, and the method comprises the steps: collecting the current train delay data in real time through the position information of a vehicle-mounted station train interaction device in the train operation process; establishing an analysis model of transfer time required by internal transfer of each station and transfer between stations in the same city, and analyzing and acquiring reference time required by passengers to complete transfer through the transfer time analysis model; based on the reference time and the delay data, after a passenger ticket refunding application is received, all continuous train tickets of the passenger and travel characteristics of the passenger are inquired according to a current ticket, and a continuous train arrival delay analysis result of the current ticket refunding application is automatically analyzed; and according to the subsequent train arrival delay analysis result, passenger ticket refunding operation is executed. According to the method, the handling efficiency of each ticket refunding channel and the ticket refunding passenger satisfaction of each channel are improved, and the customer service complaint rate is reduced.

Techniques are described for adaptive control of media channel interfaces for delivery of media content over communications systems to transport craft passengers. Embodiments monitor viewership of various media channel offerings provided to transport craft passengers to compute aggregated viewership scores. Based on the scores, respective prominence parameters associated with the various media channel offerings can be automatically updated. Interface control signals can be communicated to cause media channel interfaces being displayed on passenger devices to dynamically and automatically update the graphical listings of the media channel offerings in accordance with the updates to their respective prominence parameters. Dynamically updating the graphical prominence of different media channel offerings can tend to make passengers more likely to view a smaller subset of the media channel offerings, thereby helping to maintain high passenger satisfaction with less network capacity demand.

The present invention discloses a taxi dispatching method, system, computer device and storage medium for a passenger station. In order to improve the taxi dispatching efficiency of a passenger station and effectively analyze and predict the taxi capacity of the passenger station, the present invention obtains the historical taxi dispatching volume and the historical train arrival frequency, and predicts the demand capacity of the passenger station based on the relationship between the historical taxi dispatching volume and the historical train arrival frequency, and obtains the demand capacity of the passenger station. According to the demand capacity of the passenger station, the taxis around the passenger station are reasonably allocated and dispatched. The taxi dispatching method for a passenger station proposed by the present invention can analyze and predict the taxi demand of the passenger station, deploy the capacity dispatching work, enhance the operational efficiency, improve the service reliability, and improve the passenger satisfaction. The present invention relates to the field of traffic dispatching.

An elevator group control optimization scheduling method based on evolutionary scheduling domain and nonlinear coupled objectives includes the following steps: S1: Operation status perception and basic data construction; S2: Evolutionary scheduling domain construction; S3: Risk perception nonlinear scheduling objective construction; S4: AI large model parameter generation and interpretation; S5: Group control elevator dispatch decision and execution; S6: Iterative execution. This invention suppresses the tail of waiting time distribution through nonlinear coupled objectives and CVaR long-tail penalty, significantly reducing waiting time and improving passenger satisfaction and comfort; it balances efficiency, energy consumption, and fairness through nonlinear coupled objectives, and constrains adaptive adjustment to ensure safety and stability; it uses a large language model to parse natural language rules, emergency instructions, and passenger preferences, quickly integrating manager intentions into scheduling decisions to achieve interpretable and flexible strategy adjustments; the evolutionary scheduling domain enables smooth transitions between different traffic modes, avoiding the performance drop caused by traditional hard switching between "up" and "down".