13 results about "Travel cost" patented technology

This invention provides an optimization method and system for attraction-based tolling strategies under traffic demand management. The method includes establishing a two-level programming model. The upper-level model aims to maximize the profit of the attraction points, and the decision variable of the upper-level model is the attraction point toll. By changing the attraction point toll, the generalized travel cost of travelers in the lower-level model is altered, thereby influencing travelers' route choices. The lower-level model is a traveler route selection model considering both attraction points and travel costs under stochastic demand. The system includes an information acquisition module, a model building module, and a model solving module. This invention transfers congestion tolling functions to the attraction points. Attraction points in congested areas charge positive tolls to travelers arriving at them, while attraction points in areas with excess road supply charge negative tolls. Travelers choose their routes based on the attraction point's attractiveness, the attraction point toll, and road segment impedance, thereby alleviating road segment congestion and making the road network traffic distribution more balanced.

This invention belongs to the field of business travel expense management technology, and particularly relates to an intelligent dynamic business travel expense management method and system based on a microservice architecture. This invention utilizes an information parsing microservice, employing an improved BERT model to perform semantic parsing and entity extraction on travel booking requests, outputting structured itinerary information and user job level; it uses an expense benchmark calculation microservice to lock in a matching pool of benchmark users, splits itinerary units, and generates an initial expense range through cluster analysis; it uses a credit rating microservice to calculate personalized credit coefficients for users; and it uses a dynamic expense calibration microservice, combining credit coefficients to calibrate expense standards, generating compliant expense ranges constrained by compliance red line thresholds. This invention achieves dynamic and refined management of business travel expense standards, solving the pain points of poor adaptability and low efficiency of traditional static management models, and improving the intelligent level of enterprise travel cost management.

This application provides a method for recommending travel routes, an in-vehicle system, and a storage medium, relating to the field of in-vehicle tourism service technology. The method can obtain the route length, travel time, required travel cost, and average experience score of all attractions for each travel route. Then, for each travel route, it determines a first sub-rating corresponding to the route length, a second sub-rating corresponding to the travel time, a third sub-rating corresponding to the travel cost, and a fourth sub-rating corresponding to the average experience score. A weighted average of the first, second, third, and fourth sub-ratings for each travel route is taken to obtain a recommended rating for each travel route. Based on the top N% of travel routes ranked by their recommended ratings, recommended routes are output, which can balance short route length, short travel time, low travel cost, and high average experience score, achieving a balance between the user's itinerary, travel time, cost, and overall experience.

The application discloses a kind of walking network three-dimensional accessibility evaluation method, device, equipment, medium and product, the method includes the road facility data of target area in mountain city is preprocessed;According to the road facility data after processing, construct multilayer walking network;According to multilayer walking network and elevation constraint, construct composite impedance function that fuses time cost and physical cost;According to user group parameters and composite impedance function, the minimum cumulative travel cost of starting point to target node is obtained to obtain the optimal path planning result of different user groups;According to optimal path planning result and preset threshold, generate the three-dimensional accessible domain of different user groups.Based on multilayer walking network, composite impedance function and user group parameters, optimal path solving can be realized, and the real travel burden of different people under the constraint of mountainous elevation can be accurately quantified, so as to solve the problem that existing technology cannot adapt to the elevation, real walking burden and three-dimensional accessibility of mountain city.

We provide the system. [Solution] The information processing system provides a means for obtaining schedule information from the schedule management system, A means for automatically identifying the departure point and destination point based on the information of places to visit included in the aforementioned itinerary information, A means for searching for a route between the departure point and the destination point and calculating the travel cost, A means for automatically registering the calculated travel expenses in the expense settlement system, A means of automatically calculating transportation costs using planned route data, by searching for the optimal travel distance between the departure point and destination point using a route search service, A system that includes this.

The invention relates to the technical field of automobile travel service, discloses a travel comprehensive cost optimization method, system and equipment based on a multi-modal large model, and aims to solve the problems of poor travel experience and high comprehensive cost caused by difficulty in considering charging site selection, accommodation hotel screening and travel cost management and control during long-distance travel. The method comprises the steps of collecting travel associated data based on travel demand information; constructing a comprehensive cost function including charging cost, hotel cost and travel time cost, and defining a weight coefficient based on user preference learning; calculating charging cost, hotel cost and travel time cost in the comprehensive cost function according to travel association data; and based on a calculation result of the comprehensive cost function, screening, sorting and optimizing the multiple groups of charging-hotel-path combination schemes by adopting a decision inference engine, generating an optimal electric travel scheme, and outputting the optimal electric travel scheme to a vehicle-mounted terminal for a vehicle owner to select, so that the comprehensive cost optimization and travel experience improvement of the long-distance travel of the vehicle are realized.

The application discloses a kind of urban public transport network optimization method considering scheduling, comprising: processing bus card data, vehicle shift data, line site data, analyze the influencing factors in the process of passenger line;For the influence factor analysis of passenger riding habit, vehicle shift, analyze the influence relationship of the selection of each type of passenger line and riding habit, respectively with the same bus station OD inter-route selection proportion and Person correlation coefficient define its correlation degree, obtain the Pearson correlation coefficient of the selection of different types of passengers and shift;Through the actual-virtual bus network construction mode, construct line and scheduling synchronous optimization model, optimize the output optimization result by the line site layout and vehicle scheduling synchronous optimization by the constructed model.The application considers the influence of vehicle scheduling in the process of public transport network optimization, optimizes the layout of public transport network and vehicle scheduling simultaneously;It is convenient for passenger travel, reduces travel cost.

The application provides an AI-assisted travel itinerary creation system, belonging to the technical field of itinerary creation, which automatically completes demand recognition, itinerary generation and dynamic adjustment through an AI algorithm, without human intervention, and the planning efficiency is improved by more than 80% compared with the manual mode; at the same time, the visual itinerary display and one-key reservation function further shorten the cycle of itinerary confirmation and execution. Through implicit demand mining and multi-objective optimization, the matching degree of the itinerary scheme and the user's personalized demand and official activity demand is improved by more than 90%, and the frequency of itinerary modification caused by demand mismatch is reduced. Through precise regulation and control of the cost sensitivity weight and multi-objective optimization, the total travel cost is reduced by an average of 15%-25% compared with the prior art under the premise of meeting the travel demand; at the same time, the additional expenditure caused by unreasonable travel is reduced.

The invention discloses a power distribution network pricing method and device based on electric vehicle demand response and cooperative game, equipment and a medium. The method comprises the following steps: acquiring a charging price, a charging station state and a road network state every first preset time; calculating travel time and travel distance from the electric vehicle to the charging station based on the road network state; based on the charging price, the state of the charging station, the travel time and the travel distance, the attraction force of the charging station to the charging vehicle is calculated, and based on the attraction force, the distribution result of the electric vehicle distributed to the charging station is determined; and determining the power load of the charging station based on the distribution result, and updating the charging price based on the power load and the charging income of the first preset time. According to the method, the power distribution network node marginal electricity price (DLMP) is used for real conduction of the electric energy price, the operation service fee is optimized under the cooperative game framework, and the road network travel cost and the attraction function are combined to construct the user charging selection model; on the premise of satisfying operation constraints of the power distribution network, problems of voltage out-of-limit, branch overload, network loss rising and the like which are easy to occur in a rapid peak period are improved, and the electric energy quality of the power distribution network is improved.

The invention belongs to the field of artificial intelligence, and relates to a tourist route intelligent recommendation method and system based on scenic spot document travel fusion feature similarity. The method comprises the following steps: constructing a scenic spot resource knowledge base according to scenic spot culture and tourism information, and determining N historical scenic spots according to historical tourism attention information of a user; when the number of historical scenic spots is small, the similarity between the scenic spots and the destination scenic spots is directly calculated, and a scenic spot planning routes with the high similarity are selected; when the number of historical scenic spots is large, 3-5 core scenic spots with high user attention are screened out through an improved time decay weighting method, then the similarity between the core scenic spots and destination scenic spots is calculated, and a scenic spot planning routes are selected. And if the a scenic spots contain destination boundary scenic spots and the scenic spots with higher similarity exist in the adjacent boundaries, replacing the scenic spots with the lowest similarity with the scenic spots and rerecommending the scenic spots. The method can reduce the calculation amount of the server, considers the demands of adjacent scenic spots, is small in route change, saves the travel cost, and better accords with the willingness of the target user.

This invention discloses a method for modeling activity chain time allocation behavior that considers travel costs. The method includes acquiring vehicle travel trajectories, calculating the inherent utility of activities based on the influence of activity-related attributes and individual attributes on individual preferences, calculating the travel-related negative utility of activities based on the influence of necessary travel-related attributes on individual preferences, and constructing a utility function that comprehensively considers both the inherent utility and travel-related negative utility. Based on utility maximization theory and time conservation theory, a joint decision-making model for activity selection and time allocation is established. Statistical methods are used to solve the constructed model to obtain the optimal activity time allocated to each destination, thereby maximizing the overall activity utility. This method can more accurately characterize the time allocation process of individuals between different activity locations, improving the model's applicability and prediction accuracy to real-world travel behavior.

This invention discloses a method and system for generating community built environment regulation scenarios oriented towards multi-objective optimization. By constructing a spatial regression model at the community scale between the built environment and residents' travel carbon emissions, travel time, and travel costs, the method quantifies the regulatory relationship between built environment variables and multi-dimensional travel characteristics. A multi-objective optimization mathematical model of "carbon emission reduction - time reduction - cost reduction" is established, and an improved NSGA-II algorithm based on response priority is used to solve for the community, regulation variables, and regulation intensity of built environment regulation. This achieves efficient generation of refined community-scale built environment regulation scenarios and multi-objective decision support for coordinated carbon reduction and cost reduction in travel.