45 results about "Travel cost" patented technology

The invention provides a traffic mode prediction method considering parking lot charging and related equipment thereof. The method comprises the following steps: acquiring a grid map of a target area, parking lot data and resident trip chain data; calculating the grid parking fee of each grid unit in the grid map based on the parking lot data and the resident trip chain data; based on the resident trip chain data and the grid parking fee, constructing a private car generalized trip cost expression; constructing a multivariate utility selection model according to the private car generalized travel cost expression and a plurality of preset other travel cost expressions; generating a travel distribution matrix among the grid units according to the grid map and the resident travel chain data; and carrying out traffic mode prediction on the travel distribution matrix according to a multivariate utility selection model to obtain a refined travel distribution matrix considering traffic mode selection. According to the invention, by considering the influence of the parking fees on resident travel mode selection, the accuracy of urban traffic travel prediction is improved.

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.

The invention provides a method and device for carrying out cost optimization prediction through multi-dimensional business travel behavior analysis, and belongs to the technical field of enterprise business travel management.The method comprises the steps that business travel data are collected, cleaning, duplicate removal and entity alignment operation are carried out, and a business travel behavior data set is constructed; executing a preset query script on the business travel behavior data set, extracting characteristic indexes from preset dimensions, executing descriptive analysis, diagnostic analysis and clustering analysis, and generating a business travel behavior analysis report; and inputting the business travel behavior data set and the business travel behavior analysis report into a cost optimization prediction model to carry out business travel demand prediction, business travel price prediction and business travel travel optimization, generating an optimal travel travel scheme set, pushing the optimal travel travel scheme set to the employee user, collecting a feedback result of the employee user on the optimal travel travel scheme set, updating the business travel behavior data set, and obtaining a business travel result. And incremental training and iterative optimization are carried out on the cost optimization prediction model. Through multi-dimensional analysis and prediction, the travel cost is optimized, and the management efficiency is improved.

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 method for setting a transfer bus station and a line based on grid optimization, and comprises the following steps: 1, based on travel big data, respectively calculating travel demand distribution indexes of each unit grid in a region; 2, respectively calculating total travel demand and regional competitive advantage of each evaluation grid by using an evaluation grid optimization method; 3, searching and optimizing the evaluation grid of the site coverage range to respectively calculate and obtain quantitative evaluation values of the evaluation grid and the centroid longitude and latitude of the evaluation grid, thereby obtaining an evaluation grid quantitative evaluation value set in a certain range according to a certain step; 4, determining the optimal unit grid of the site selection of each evaluation grid as the optimal site selection position of the transfer station based on travel cost, and forming a bus driving route scheme; and 5, establishing a multi-objective optimization model to optimize the bus driving route to obtain a final bus driving route scheme, wherein the decision variables of the model optimization include the bus driving route and the number of vehicles equipped on the line. The application realizes scientific and accurate site selection for a city public transport stop.

[Problem] To enable a traveling vehicle to smoothly pass through a merging section without requiring complicated setting work. [Solution] A traveling vehicle system comprises: a storage unit that stores a traveling cost indicating the time required for traveling through each section of a track; a calculation unit that acquires, from the storage unit, traveling costs for sections through which the traveling vehicle travels before entering the merging section from the current position, and calculates the total value of the traveling costs for the traveling vehicle; and a determination unit that determines whether the total value of the traveling costs is lower than a threshold value. The traveling vehicle transmits, to a controller, a request for permission of passage through a merging section scheduled for passage, enters the merging section scheduled for passage upon reception of a passage permission from the controller, and stops at a stop position if no passage permission is received. The controller transmits the passage permission to the traveling vehicle for which the total value of the traveling costs is determined to be lower than the threshold value.

The application relates to the field of travel management and discloses a travel management system which comprises an employee login module, an employee identity verification module, a travel application module, a travel information analysis module, a traffic distribution module, a lodging distribution module, an information receiving module, a data auditing module, a general control module, an information sending module, an employee receiving end and a report generation module; the employee login module is used for guiding employee login information; the employee identity verification module is used for verifying the identity information guided by the employee, and after verification, verification pass information is sent to the travel application module; the travel application module is used for applying for travel by the employee who passes the verification and guiding travel information, wherein the travel information comprises a business trip duration and a business trip location; the travel information is sent to the travel information analysis module to analyze the travel information and obtain path information; the application can more reasonably arrange travel, reduce travel cost and reduce resource waste.

The application discloses a public transport composite network joint optimization method considering heterogeneous demand under low carbon orientation, comprising the following steps: S1, obtaining travel demand data of a target region; S2, constructing a total cost function based on the travel demand data; the total cost function at least includes passenger travel cost, system operation cost and carbon emission cost based on environmental sensitive coefficient for spatial dynamic mapping; S3, establishing a joint optimization model with the target of minimizing the total cost function; the decision variables of the joint optimization model at least include the line spacing, station spacing, departure interval of the subway and the line spacing, station spacing, departure interval of the regular bus; S4, solving the joint optimization model to obtain the optimized network structure parameters; S5, generating a public transport network planning scheme based on the optimized network structure parameters. The heterogeneous demand, multivariable joint optimization and spatial dynamic carbon emission cost are unified.

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.

The invention provides a travel reservation method, electronic equipment, a storage medium and a computer program product, and relates to the technical field of travel reservation. According to the travel reservation method disclosed by the invention, the space-time network about the reservation period is constructed according to the entity road network of the target area, the entity road network is used for describing the position information of each space node in the target area and the association relationship among the space nodes, and the space-time network is a set of space-time arcs. The space-time arc is a space-time resource which can be used for moving or staying; according to the space-time network and the reservation information set, a plurality of candidate travel schemes are iterated, and the candidate travel schemes are a set of candidate travel tables of travelers; and taking the candidate travel scheme corresponding to the minimum total travel cost as a target travel scheme, the total travel cost being used for measuring the comprehensive cost of the group time cost and the group time deviation cost of each traveler. The technical scheme disclosed by the invention can be suitable for a complex city scene with a large-scale road network.

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.

An embodiment of the present application provides a method, device, server, and storage medium for recommending boarding locations, wherein the method includes: obtaining a user location; if the user location is within an area of ​​interest (AOI), taking the grid in which the user location is located within the AOI as a first grid, wherein the AOI is pre-divided into multiple grids; determining a second grid located around the first grid within the AOI; obtaining a first set of candidate boarding locations corresponding to the area formed by the first and second grids; obtaining a second set of historical real boarding locations corresponding to historical user locations located in the first grid; and determining a recommended boarding location from the candidate boarding locations in the first set based on the distance between the candidate boarding locations in the first set and the historical real boarding locations in the second set. The embodiment of the present application can recommend reasonable boarding locations to users, thereby reducing the travel cost for users to reach the recommended boarding locations.

The invention discloses an intelligent exhibition hall guiding path guiding system and method, and relates to the technical field of intelligent exhibition halls. The method comprises the following steps: constructing a three-dimensional intelligent exhibition hall model according to an intelligent exhibition hall construction drawing and data acquired by unmanned aerial vehicle photography; internet-of-things data in the intelligent exhibition hall are acquired in real time; constructing a space-time weight matrix, and marking exhibit value weights and path passing costs; constructing a user interest dynamic model, and predicting user interest migration; a user selects a user interest exhibition stand recommended by the system through the mobile terminal; the system performs path planning according to the exhibition stand selected by the user, and selects a path recommendation user with the minimum passing cost; and the user watches the recommended path in the three-dimensional intelligent exhibition hall model through the mobile terminal. According to the method, the regional population density is calculated through the equipment in the exhibition hall, the time-space weight matrix is constructed to calculate the passage cost of the user visiting the path, and the lowest passage cost is recommended to the user, so that the interactivity of audiences and the guide efficiency are improved.

The present invention discloses a dynamic evolution analysis method for studying transportation mode selection in a ride-sharing system, comprising: obtaining a set of travel modes for travelers, wherein the travel mode set includes travel modes selectable by both car-based and non-car-based travelers; calculating travel costs for different travel modes based on the travel mode set; calculating generalized travel costs based on the travel costs, wherein the generalized travel costs take into account the constraint relationship between the number of passengers in a ride-sharing trip and the number of drivers in a ride-sharing trip; obtaining the probability of travelers selecting different transportation modes based on the generalized travel costs; and constructing a daily dynamic evolution model for ride-sharing travel. The method, based on the daily dynamic evolution model for ride-sharing travel, obtains the dynamic evolution of travelers' daily transportation mode selection behavior based on the selection probabilities. The present invention can simulate daily fluctuations in traffic flow for different travel modes, providing technical support for transportation planning and management departments in formulating management decisions related to ride-sharing travel.

This invention relates to a method for evaluating the accessibility of public transportation stations considering the travel environment, comprising: S1, obtaining a set of environmental indicators affecting walking impedance in the station area; S2, identifying key environmental factors; S3, determining the hierarchy of each key environmental factor; S4, obtaining travel route selection survey data based on a passenger travel intention survey; S5, establishing a binary logit model based on the travel route selection survey data to calculate the willingness to pay for each key environmental factor; S6, establishing a comprehensive walking cost model considering the walking environment; S7, using the number of points of interest reachable by walking under a certain travel cost as an indicator of walking accessibility to obtain a station area accessibility calculation model; S8, calculating the station area accessibility of each station based on the station area accessibility calculation model. Compared with existing technologies, this invention establishes a mapping relationship between the physical environment of travel and passengers' psychological perceived impedance, achieving an objective and reliable evaluation of station area accessibility.

A system is provided.SOLUTION: A system comprising: means for receiving an image input by a user; means for analyzing the image to determine a specific place or landmark; means for acquiring tourist spot information based on the determined place or landmark; means for automatically generating a travel schedule based on the tourist spot information; means for estimating a travel cost based on the travel schedule; means for generating a travel bookmark including the travel schedule and the cost estimate; and means for presenting the travel bookmark to the user.SELECTED DRAWING: Figure 1

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 discloses a kind of vehicle scheduling and travel path optimization methods of coordinating trunk line and branch line public transport service, comprising: obtaining the demand information of passenger in preset time period;Based on the contact between each passenger and the selected boarding point and the selected transfer point, a virtual space-time information is constructed;Objective function is constructed;Randomly select virtual transfer point and virtual boarding point, generate current sequence;The current sequence is input into the first algorithm, and the first function value is obtained;By changing the current sequence, the optimal objective function value is found using the annealing algorithm, and the branch line vehicle scheduling and passenger travel path are planned based on the optimal objective function value.The application improves the passenger-carrying rate and operating efficiency of branch line vehicles, enhances the overall travel experience of passengers, and reduces operating costs and passenger travel costs.

This application proposes a method for predicting traffic modes that takes parking fees into account, and related equipment. The method includes: obtaining a grid map, parking data, and resident travel chain data for a target area; calculating the grid parking fee for each grid cell in the grid map based on the parking data and resident travel chain data; constructing a generalized travel cost expression for private cars based on the resident travel chain data and the grid parking fee; constructing a multivariate utility choice model based on the generalized travel cost expression for private cars and multiple other preset travel cost expressions; generating a travel distribution matrix between grid cells based on the grid map and resident travel chain data; and performing traffic mode prediction on the travel distribution matrix based on the multivariate utility choice model to obtain a refined travel distribution matrix that takes traffic mode selection into account. This application improves the accuracy of urban traffic travel prediction by considering the impact of parking fees on resident travel mode choices.

The application discloses a real-time online collaborative deduction system and method of an urban multi-mode traffic system, and belongs to the technical field of intelligent traffic. In order to solve the problem of real-time online collaborative evolution simulation, the application determines the initial travel demand of the whole network through a multi-mode network model; a multi-mode travel demand distribution module distributes the multi-mode travel proportion based on generalized travel cost, and distributes road travel demand and rail travel demand; a road simulation deduction module outputs the road traffic operation situation; a rail simulation deduction module outputs the rail traffic operation situation; a multi-mode interactive fusion module performs coupling deviation calculation; a dynamic calibration module dynamically checks the calculation results of the road simulation deduction module, the rail simulation deduction module and the multi-mode interactive fusion module, and obtains the whole-network multi-mode operation situation which is qualified in checking. A global optimization and output module is used for receiving the whole-network multi-mode operation situation which is qualified in checking, and outputting the accurate restoration and prediction results of the multi-mode whole-network state.

The invention discloses a bus departure time optimization method based on a particle swarm and plant rhizome optimization, and the method comprises the steps: building a multi-objective optimization model, and achieving the optimization of the bus departure time by taking the minimization of the operation cost of a bus company and the comprehensive travel cost of passengers as well as the maximization of the net income of an enterprise and the direct passenger flow volume as objectives; in combination with dynamic conditions such as departure interval constraint, load factor limitation and adjacent period smoothness, global fast search is performed by adopting a particle swarm algorithm, and a plant rhizome optimization algorithm is introduced to perform refined iterative solution; initializing a departure interval scheme through a particle swarm algorithm, and generating a potential solution set; based on a rhizome nutrient distribution mechanism, a root growth process is simulated to dynamically adjust a departure strategy, complex constraints are restored, and a multi-target competition relationship is balanced; and finally, outputting a Pareto frontier solution set, and outputting an optimal scheduling scheme. According to the invention, the direct passenger flow of the bus line can be effectively improved, the problems of passenger retention and social vehicle interference in peak periods are relieved, and the efficiency and service level of an urban public transport system are remarkably enhanced.

The invention discloses a method for quantifying the influence of congestion charging on a travel mode in an automatic driving environment in the field of smart traffic, and relates to the technical field of smart traffic, and the method comprises the steps: inputting a road network and travel demand information; calculating the generalized travel cost of the parking mode AV-P and the no-load return mode AV-R of the public transport PT and the autonomous vehicles AVs; estimating a mode selection probability by using a discrete selection model; establishing a dynamic congestion charging strategy based on the road section LTS, the distance DTS and the travel time TTS; evaluation indexes are designed from the four dimensions of travel efficiency, mode proportion, greenhouse gas emission and charge income. Through AVs dual-mode cost distinguishing, multi-strategy dynamic charging and full-process quantitative analysis, travelers are guided to turn to public transportation, AVs no-load driving is inhibited, congestion mileage and delay are reduced, energy consumption and emission are reduced, and meanwhile, accurate congestion treatment and multi-target optimization in an automatic driving scene are achieved through a charging income back to a traffic system.

The application provides an information induction method and system considering passenger dynamic behavior under an emergency, belonging to the technical field of rail transit operation management, considering passenger waiting process, dynamically updating personalized heterogeneous induction information, constructing a multi-stage dynamic behavior model to observe Markov decision changes of passengers, defining different affected passenger flows under the emergency and constructing an alternative travel scheme set for the passenger flows, estimating dynamic passenger flow demand under an induction time unit, constructing a dynamic passenger flow induction information release scheme optimization model based on double-layer planning, outputting an optimal recommended scheme of time-sharing passenger flow induction information, realizing line network section passenger flow equilibrium and passenger generalized travel cost minimization. The application discloses a dynamic behavior mechanism of passengers under an urban rail operation emergency, analyzes dynamic evolution characteristics of demand in a line network over time in combination with an alternative travel scheme set, takes into account operation efficiency and safety concepts, realizes accurate optimization of an induction information release scheme effect and develops a corresponding system.

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 carbon transaction management method based on a bilevel programming model, and aims to optimize carbon emission management in the traffic field. According to the method, through the benefit game of the government, the transportation enterprises (buses and online car-hailing enterprises) and travelers, a carbon trading market is established, and a reasonable carbon point distribution scheme is formulated, so that social welfare is maximized. Firstly, the government allocates carbon quotas to enterprises, and the enterprises can trade carbon points in the market; the traveler selects the optimal traffic mode according to the generalized travel cost (including time, economy and comfort cost). Then, based on the usage amount of each trip mode, the total amount of carbon emission is calculated. Through a bilevel planning model, the upper layer maximizes social welfare and considers enterprise profits, traveler utility and environmental benefits, and the lower layer depicts competitive games of enterprises and travelers and optimizes operation decisions of transportation enterprises and traveler selection. Finally, an optimal carbon integral distribution scheme is determined, and the goals of green travel, low-carbon technology investment and traffic carbon emission reduction are achieved. According to the invention, a basis is provided for the government to make a low-carbon traffic policy, and green traffic development is effectively promoted.

The invention discloses an activity chain time allocation behavior modeling method considering travel cost, which comprises the steps of acquiring a travel track of a vehicle, calculating inherent effectiveness of an activity according to influence of activity related attributes and individual attributes on individual preferences, and calculating inherent effectiveness of the activity on the basis of influence of travel related attributes necessary for arriving at an activity place on the individual preferences. Calculating the travel negative utility of the activity, and constructing a utility function which comprehensively considers the inherent utility of the activity and the travel negative utility; based on a utility maximization theory and a time conservation theory, establishing a joint decision model of activity selection and time distribution; and solving the constructed model by adopting a statistical method to obtain the optimal activity time distributed at each destination, so that the overall activity effectiveness is maximized. According to the method, the time distribution process of individuals among different activity places can be described more accurately, and the applicability and prediction precision of the model to real travel behaviors are improved.

The present invention relates to a method for planning safe travel routes for elderly drivers that takes travel costs into account, belonging to the field of road traffic safety technology. The method primarily comprises: Step 1: Collecting relevant data about elderly drivers; Step 2: Constructing a cost function for elderly drivers' safety and reliability; Step 3: Constructing a cost function for elderly drivers' driving confidence; Step 4: Constructing a cost function for elderly drivers' driving ability; Step 5: Constructing a cost function for road impedance; and Step 6: Planning safe travel routes for elderly drivers. The present invention can provide route solutions for elderly drivers' driving trips, helping them achieve safe travel.

The invention discloses an optimal carbon quota pricing method suitable for mixed traffic flow, and particularly relates to the technical field of traffic planning and low-carbon management. The method comprises the following steps: constructing a mixed traffic circulation service behavior model through a bottleneck model, and designing a travel cost function and a carbon transaction cost function in combination with the loss avoidance psychology of a commuter; secondly, according to a government carbon quota distribution scene, typical travel modes are divided, and an optimization model taking the total carbon emission cost and the total carbon transaction cost as targets is constructed; and finally, through algorithm iteration, optimal carbon quota prices under different weights are determined. The method gives consideration to the traffic system operation efficiency and the carbon emission reduction target, has good adaptability and accuracy, and has an important application prospect in a traffic environment in which multiple travel and a carbon transaction mechanism are fused and developed in the future.