Multi-mode traffic fusion connection facility layout method and device

Abstract

The invention provides a multi-mode traffic fusion connection facility layout method and device, and the method comprises the steps: obtaining the travel data of a user, and the travel data comprises the predicted peak hour passenger flow of a to-be-planned hub region, and the time, cost and comfort required by various traffic modes; predicting the use probability of each traffic mode according to the peak hour passenger flow volume, the time required by each traffic mode, the cost and the comfort level; according to the peak hour passenger flow volume and the use probability of each traffic mode, the connection demand quantity of each traffic mode is predicted; calculating facility scales required by various traffic modes through the connection demand quantity; obtaining a transfer demand of a passenger, and determining arrangement positions of various traffic mode facilities and distances among the various facilities based on the transfer demand; and the facility scale, the facility position and the distance between the facilities required by various traffic modes are used as a layout scheme. According to the layout scheme designed by the method, the transfer efficiency among the connection facilities can be improved, and the traffic pressure is relieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of traffic planning, and in particular relates to a method and device for arranging docking facilities for multi-modal traffic integration. Background Art

[0002] With the acceleration of urbanization, multimodal transportation has become an important part of modern cities. As a transfer node for different modes of transportation, the rationality of the design of a comprehensive transportation hub directly affects the efficiency and smoothness of transportation. The traditional layout of transportation connection facilities often determines the location and area of ​​various connection facilities based on the population density of the planning area, without considering the actual traffic conditions. The unreasonable layout leads to low utilization efficiency of the connection facilities, and passengers experience congestion and delays during the transfer process. Summary of the invention

[0003] In order to solve the problem of low transfer efficiency caused by unreasonable facility layout in the prior art, the present invention provides a method and device for layout of docking facilities for multi-modal transportation integration.

[0004] In order to achieve the above object, the present invention provides the following technical solutions:

[0005] A method for layout of docking facilities for multi-modal transportation integration, comprising:

[0006] Obtain user travel data, including the predicted peak hour passenger flow in the hub area to be planned, the time, cost and comfort required by various modes of transportation; predict the probability of using various modes of transportation based on the peak hour passenger flow, the time, cost and comfort required by various modes of transportation;

[0007] Predict the connection demand of various modes of transportation based on peak hour passenger flow and the probability of use of various modes of transportation; calculate the scale of facilities required for various modes of transportation based on the connection demand;

[0008] Obtain the transfer needs of passengers, and determine the layout of various transportation facilities and the distances between various facilities based on the transfer needs;

[0009] The size of facilities required for various modes of transportation, the location of facilities and the distance between facilities are taken as the layout plan.

[0010] Optionally, a multimodal deep learning model is used to predict the probability of using various modes of transportation based on peak hour passenger flow, time required for each mode of transportation, cost, and comfort, including:

[0011] Obtain the weights corresponding to time, cost and comfort, and calculate the impedance values ​​of various modes of transportation according to their corresponding weights; the calculation formula for the impedance value is:

[0012] Ri =w T ·T i +w C C i +w U ·(1-U i );

[0013] R i represents the impedance value of the ith mode of transportation, w T 、w C 、w U are the weights of time, cost and comfort, respectively, T i , C i , U i are the travel time, cost and comfort of the i-th mode of transportation respectively;

[0014] The actual traffic network diagram is obtained, and the peak hour passenger flow, impedance values ​​of various transportation modes and the traffic network diagram are input into the pre-trained multimodal deep learning model to obtain the usage probability of various transportation modes, where the traffic network diagram includes transportation stations and transportation modes between transportation stations.

[0015] Optionally, calculate the size of facilities required for each mode of transportation based on the connection demand, including:

[0016] Obtain the single-trip passenger capacity of various modes of transportation, and determine the required number of vehicles based on the connection demand and single-trip passenger capacity of various modes of transportation;

[0017] The size of facilities required for various modes of transportation is determined based on the area occupied by each vehicle and the number of vehicles required.

[0018] Optionally, after considering the scale of facilities, location of facilities and distance between facilities required by various modes of transportation as the layout plan, it also includes:

[0019] Input the layout plan into the traffic simulation software, simulate the passenger flow during peak hours through the traffic simulation software, and identify the operating status of various transportation facilities;

[0020] The layout plan is optimized and adjusted according to the operating status of the facilities.

[0021] Optionally, after considering the scale of facilities, location of facilities and distance between facilities required by various modes of transportation as the layout plan, it also includes:

[0022] After the connecting facilities in the planned hub area are laid out according to the layout plan, the actual peak hour passenger flow and the connecting demand of various modes of transportation are obtained at preset intervals; the layout plan is optimized and adjusted based on the actual peak hour passenger flow and connecting demand; or,

[0023] Monitor the operating status of the docking facilities in real time, and optimize and adjust the layout plan based on the operating status of the facilities.

[0024] The present invention also provides a multi-modal transportation integration docking facility layout device, comprising:

[0025] The acquisition module is used to acquire user travel data, including the predicted peak hour passenger flow in the hub area to be planned, the time, cost and comfort required by various modes of transportation; and predict the use probability of various modes of transportation based on the peak hour passenger flow, the time, cost and comfort required by various modes of transportation;

[0026] The prediction module is used to predict the connection demand of various modes of transportation based on the peak hour passenger flow and the use probability of various modes of transportation; and calculate the size of facilities required for various modes of transportation based on the connection demand;

[0027] A determination module is used to obtain the transfer needs of passengers and determine the layout locations of various transportation facilities and the distances between various facilities based on the transfer needs;

[0028] The layout module is used to take the scale of facilities, location of facilities and distance between facilities required by various modes of transportation as layout plan.

[0029] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for layout of docking facilities for multi-modal transportation integration when executing the program.

[0030] The present invention also provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the method for layout of docking facilities for multi-modal transportation integration is implemented.

[0031] The method for layout of multi-modal transportation integration docking facilities provided by the present invention has the following beneficial effects:

[0032] In the present invention, since the scale of facilities affects the number of vehicles carried and thus the passenger flow carried, a reasonable planning of the scale of facilities required for various modes of transportation can effectively alleviate traffic pressure and improve transfer efficiency. Therefore, the present invention predicts the use probability of various modes of transportation according to the peak hour passenger flow, the time, cost and comfort required by various modes of transportation, and predicts the connection demand of various modes of transportation according to the peak hour passenger flow and the use probability of various modes of transportation; calculates the scale of facilities required for various modes of transportation according to the connection demand; can more accurately obtain the use probability of various modes of transportation and the connection demand of various modes of transportation based on traffic conditions and user experience, so as to calculate the connection demand of various modes of transportation at peak hours. The scale of facilities is reasonably allocated to ensure that each mode of transportation can carry the corresponding passenger flow during peak hours, avoiding traffic congestion caused by passengers being stranded due to the small scale; secondly, the transfer needs of passengers are obtained; the layout location of facilities of various modes of transportation and the distance between various facilities are determined based on the transfer needs; the transfer needs of passengers refer to the behavior and expectations of passengers in switching between different transportation routes or means of transportation when using the public transportation system. Generally, passengers hope to be able to transfer smoothly and seamlessly between different means of transportation or routes, and the time required is as short as possible. Therefore, the transfer needs of users are fully considered when arranging the location and the distance between facilities, so that users can achieve more convenient and quick transfers and improve transfer efficiency. Therefore, the present invention comprehensively considers various types of transportation, reasonably plans the scale of facilities of various modes of transportation, the location and the distance between facilities, improves the utilization efficiency of connecting facilities, and alleviates the traffic pressure of passengers transferring. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiment of the present invention and its design scheme, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 A schematic flow chart of a method for layout of docking facilities for multi-modal transportation integration provided by an embodiment of the present invention;

[0035] Figure 2 A schematic structural diagram of a docking facility layout device for multi-modal transportation integration provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] In order to enable those skilled in the art to better understand the technical solution of the present invention and implement it, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the scope of protection of the present invention.

[0037] In the description of the present invention, it is to be understood that the terms “center”, “longitudinal”, “lateral”, “length”, “width”, “thickness”, “up”, “down”, “front”, “back”, “left”, “right”, “vertical”, “horizontal”, “top”, “bottom”, “inside”, “outside”, “axial”, “radial”, “circumferential”, etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing the technical solutions of the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0038] In addition, the terms "first", "second", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance. In the description of the present invention, it should be noted that, unless otherwise clearly specified or limited, the terms "connected" and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances. In the description of the present invention, unless otherwise specified, "plurality" means two or more, which will not be described in detail here.

[0039] In view of the problems of low transfer efficiency and congestion caused by unreasonable layout of transportation connection facilities in the prior art, the present invention provides a connection facility layout method for multi-modal transportation integration, such as Figure 1 As shown, the method comprises the following steps:

[0040] S1, obtains user travel data and predicts the probability of using various transportation modes based on peak hour passenger flow, the time, cost and comfort required by various transportation modes.

[0041] The user travel data includes the time, cost and comfort of various modes of transportation and the predicted peak hour passenger flow C in the hub area to be planned. h And other information.

[0042] Exemplarily, the average travel time, travel cost, passenger comfort score, accessibility of transportation tools, etc. of various modes of transportation including buses, taxis, private cars, etc. are obtained. For example, for buses, the travel time, fare, waiting time and other data from the starting point to the end point are obtained; for taxis, the average cost and time of passengers from boarding to the destination are obtained; for private cars, the travel time, fuel cost, toll and other data are obtained.

[0043] Among them, the peak hour passenger flow C can be obtained by investigating the traffic flow and passenger flow in the planned hub area or by using historical traffic data for speculation. h For example, obtain the historical peak hour passenger flow data of the transportation station, analyze the time distribution characteristics of the passenger volume based on the historical data, and identify the difference between peak days (such as holidays and large-scale event days) and ordinary days; then calculate the average daily passenger flow, and determine the peak factor based on the peak hour passenger flow data and the average daily passenger flow. The peak factor refers to the ratio of the peak hour passenger flow to the average daily passenger flow; further, the peak hour passenger flow can be predicted by the direct proportion method:

[0044] Peak hour passenger flow = average daily passenger flow × peak factor.

[0045] Alternatively, historical peak hour passenger flow data can be used to predict peak hour passenger flow through a time series (such as an ARIMA model).

[0046] In order to more accurately predict the usage probability of different modes of transportation, the present invention adopts a multimodal deep learning model to predict the usage probability of various modes of transportation.

[0047] The model architecture of the multimodal deep learning model includes an input layer, a graph neural network layer, and an output layer. The input layer is used to receive peak hour passenger flow and impedance values ​​of various transportation modes to form a feature vector; the graph neural network (GNN) layer is used to capture the structural characteristics of the transportation network. The input of the graph neural network layer is the graph data representing the transportation network graph, where nodes represent transportation stations and edges represent transportation modes between transportation stations. The graph neural network layer learns the characteristics of the transportation network through message passing between nodes; the output layer outputs the predicted usage probability of various transportation modes.

[0048] Before applying the multimodal deep learning model, the present invention uses historical peak hour passenger flow, impedance value and traffic network diagram as training data, uses the cross entropy loss function to evaluate the gap between the predicted usage probability and the actual selection probability, and updates the parameters of the model through the Adam optimizer. That is, the loss value between the model prediction probability and the actual selection probability is calculated through the cross entropy loss function, and the parameters of the model are updated through the Adam optimizer based on the loss value until the accuracy of the model reaches the preset requirements. Optionally, during the model training process, the prediction accuracy can be improved not only by updating the parameters of the model, but also by resetting the weights of time, cost and comfort or introducing new factors to improve the prediction accuracy of the model.

[0049] Before applying the multimodal deep learning model, the weights corresponding to the time, cost and comfort of various modes of transportation are first obtained, and the impedance values ​​of various modes of transportation are calculated based on the weights. It should be understood that the greater the impedance value of a mode of transportation, the less likely it is that passengers will choose this mode of transportation. When choosing a mode of transportation, passengers often consider various unfavorable factors (i.e., "impedance"), such as travel time, travel costs, etc. In order to quantify these factors, the present invention represents the impedance of each mode of transportation as part of its utility function. The impedance function can be composed of multiple variables, for example:

[0050] R i =w T ·T i +w C C i +w U ·(1-U i );

[0051] R i represents the impedance value of the ith mode of transportation, w T 、w C 、w U are the weights of time, cost and comfort, respectively, T i , C i , U i are the travel time, cost and comfort of the i-th mode of transportation, respectively. The weight coefficients of information such as time, cost and comfort can be determined according to actual conditions or through investigation and research.

[0052] The impedance function can reflect the perceived resistance of passengers to each mode of transportation. It should be understood that the impedance function can also include more influencing factors besides time, cost and comfort, such as the age of the passenger, etc., which is not specifically limited in this application.

[0053] Furthermore, the actual traffic network diagram is obtained, and then the peak hour passenger flow, impedance value and traffic network diagram are input into the trained multimodal deep learning model to obtain the usage probability P of various transportation modes. i ;

[0054] P i =softmax(z i );

[0055] Among them, z i is the output of the multimodal deep learning model. The softmax function converts the output into probabilities, ensuring that the sum of all used probabilities is 1.

[0056] It should be understood that the actual traffic network diagram can intuitively display the connection relationship between various transportation modes, the route layout and the distribution of traffic nodes. By analyzing the traffic network diagram, we can understand the accessibility, convenience and comfort of different transportation modes, so as to more accurately predict passengers' travel preferences; therefore, by combining the traffic network diagram with passenger travel data such as peak hour passenger flow and impedance values ​​of various transportation modes, it is more accurate to predict the probability of use of various transportation modes.

[0057] For example, in practical applications, the multimodal deep learning model is used to predict the probability of using transportation modes during the peak hours in the planning year y1: bus a%, taxi b%, private car c%, and other modes d%.

[0058] S2, predict the connection demand of various modes of transportation based on the peak hour passenger flow and the usage probability of various modes of transportation; calculate the size of facilities required for various modes of transportation based on the connection demand.

[0059] The scale prediction of connecting facilities is a crucial step in the design of integrated transportation hubs. It ensures that the connecting facilities of various modes of transportation can meet the future passenger flow demand. In S2, the required scale of each type of connecting facility (such as bus terminals, taxi parking areas, social vehicle parking lots, etc.) is calculated to provide a basis for the planning and design of the facilities.

[0060] In order to ensure the accuracy of the prediction of the scale of the connecting facilities, the present invention adopts a facility demand prediction model based on peak hour passenger flow. First, the peak hour passenger flow of the planning year y1 is input, and then the demand scale of facilities such as bus terminals, taxi stations, and social vehicle parking lots are calculated based on the connecting demand of different modes of transportation and the turnover rate and capacity of transportation tools.

[0061] It should be understood that if the planned peak hour transmission volume in year y1 is C h People, then this C h Some of the passengers will use buses, some will use taxis, and some will choose private cars or other modes of transportation.

[0062] For example, the planned peak hour passenger flow in year y1 is C h The usage probability of various modes of transportation predicted by S1 is a%, b%, c%, and d%. From this, the connection demand of each mode of transportation can be calculated: the bus is expected to connect C h ×a%=aC h % of people, taxi transfer bC h % people, private car transfer cC h % of people, other ways to connect dC h% person-times.

[0063] Then, the size of facilities required for various modes of transportation is predicted based on the connection demand and the turnover rate and capacity of transportation vehicles.

[0064] The following is an introduction to the prediction of the scale of facilities using buses, taxis and private cars (social vehicles) as examples.

[0065] Prediction of the size of bus terminal: The demand for bus connections mainly affects the size design of bus terminal. If the passenger capacity of each bus is e people, then aC h % of passengers need to travel aC during peak hours h % / e buses. According to the "Design Specifications for Urban Road Public Transport Stations, Yards and Plants", the area required for each bus terminal is 100 square meters to 120 square meters. Therefore, the required area of ​​the bus terminal is (aC h % / e)×100 m2-(aC h % / e)×120 square meters.

[0066] In addition, the layout of the bus terminal must also consider the convenience of vehicle access, so the station needs to provide corresponding space for the number of routes. If the station has l bus routes, each route requires about k square meters, then an additional l*k square meters can be provided for scheduling space between routes.

[0067] Taxi parking area and passenger boarding and alighting berth size forecast: The size of taxi pick-up demand depends on the passenger capacity of each taxi and the vehicle turnover rate during peak hours. The turnover rate indicates the average number of pick-ups that each taxi can complete during peak hours.

[0068] For example, if the average passenger capacity of each taxi is f, and bC h % people, so bC is needed h % / f taxis; then use bC h % / f divided by the turnover rate T, we get the final number of taxis bC h % / fT. It should be understood that in order to ensure smooth taxi connection, some parking spaces need to be reserved in the parking area. Considering the uneven distribution of taxi arrival time, a correction factor of 1.3 can be multiplied to finally set (bC h % / fT)×1.3 taxi parking spaces. Each taxi parking space requires an area of ​​approximately 25 square meters, so the total area of ​​the taxi parking area is (bC h % / fT)×1.3×25=32.5(bC h % / fT) square meters.

[0069] Calculation of the size of private car parking lot: The size of the parking lot depends on the composition of the passenger flow and the vehicle stay time. Social vehicle parking lots need to distinguish between temporary parking and long-term parking. The drop-off vehicle may only stay for about 20 minutes, while the pick-up vehicle may need longer. Since the number of vehicles picking up passengers at general transportation stations can be larger than the number of vehicles dropping off passengers, the pick-up vehicles and the drop-off vehicles can be divided according to a preset ratio, for example, 6:4. If the average number of private cars carrying g passengers each time, the average stay time of the drop-off vehicle is t1, and the average stay time of the pick-up vehicle is t2 (t2>t1), then the demand for the drop-off vehicle is: cC h % / g×0.6×t1, the demand for passenger vehicles is: cC h % / g×0.4×t2, the total demand for vehicles is: cC h % / g×0.6×t1+cC h % / g×0.4×t2.

[0070] Assuming that the area of ​​each parking space is 30 square meters, (cC h % / g×0.6×t1+cC h % / g×0.4×t2)×30 square meters of parking lot. In addition, in order to cope with the future growth of vehicles, a certain number of reserved parking spaces can be set up, usually 20% of the number of parking spaces.

[0071] It should be understood that the scale of the access facility is not static. After the facility planning is completed, it is still necessary to consider the changes in future passenger flow and optimize the layout and scale of the facility through dynamic adjustments. The predicted demand for various modes of transportation will fluctuate over time and with changes in traffic patterns. For example, the predicted demand for private car parking in y1 is m vehicles, but with the increase in passenger flow in y2, the demand for private car parking lots may increase by h vehicles. At this time, the parking lot needs to be expanded by h×30=30h square meters. Therefore, a certain amount of expansion space needs to be reserved when designing the facility for future adjustments.

[0072] Through the above calculations, the present invention obtains the demand scale of various docking facilities, and these data will be used for subsequent facility layout and optimization design to ensure that the docking facilities can operate efficiently and meet future passenger flow needs.

[0073] S3, obtaining the transfer demand of passengers, and determining the layout locations of various transportation facilities and the distances between various facilities based on the transfer demand.

[0074] Reasonable facility layout design can effectively improve the transfer efficiency of transportation hubs and reduce conflicts in traffic flow lines. In order to achieve this goal, before optimizing the layout of connecting facilities, the overall layout principles should be determined according to the overall design goals of the comprehensive transportation hub. The goals mainly include three aspects: first, to ensure convenient transfers between connecting facilities for different modes of transportation, second, to optimize the traffic flow lines within the hub, and third, to ensure the uniform distribution of various facilities to avoid reduced operational efficiency due to excessive concentration or dispersion of facilities. To this end, the principles of "public transport priority", "pedestrian-friendly" and "reducing traffic intersection" should be followed in layout optimization.

[0075] When making the layout, first determine the location of various connecting facilities, then design the transfer lines, and finally design the distance between facilities so that passengers can quickly and conveniently transfer between different modes of transportation.

[0076] The specific process is as follows:

[0077] Step 1: First, you can collect information such as passengers' travel habits, transfer preferences, travel time, etc. through questionnaires, interviews, smart card data, etc.; use geographic information systems and transportation planning software to analyze the layout, route directions, and station settings of the existing transportation network; based on passenger travel surveys and transportation network analysis, identify passengers' transfer needs between different modes of transportation, including transfer volume, transfer time, transfer routes, etc.

[0078] In order to reduce costs and improve efficiency, simulation software can also be used to simulate the transfer behavior of passengers and obtain their transfer needs. The process is as follows:

[0079] First, define the characteristics of the agent. Each agent represents a passenger and has attributes such as departure point, destination, departure time, preferences (such as cost, time, and comfort). Define the agent's behavior rules, such as giving priority to transfer methods that are time-saving or cost-effective, to ensure that the flow of the agent between transfer nodes meets actual needs.

[0080] Secondly, a transportation network model is established. The transportation network model includes different transportation modes and transfer nodes to simulate the real traffic environment; each transfer point and transportation mode is used as a node and edge in the network, and the characteristics of each edge (such as travel time and fee) are set; and transfer rules between nodes are defined. For example, passengers can transfer between bus stops and subway stations.

[0081] Then, the agent path selection is simulated. Each agent selects a travel path based on its preferences (time, cost, etc.) and transfers on the path. The agent's transfer data, such as transfer location, time, and number, are recorded at each transfer.

[0082] Set up traffic flow and travel demand in the simulation environment, execute transfer behavior in multi-agent simulation, analyze passengers' transfer behavior, and obtain passengers' transfer demand.

[0083] Furthermore, docking facilities are set up at locations that are easy for passengers to reach and convenient for transfers based on transfer needs, reducing transfer time and walking distance.

[0084] For example, taking the high-speed rail station as the transportation hub area to be planned, analyze the movement paths of passengers from getting off the high-speed rail station to various docking facilities, and determine whether passengers will give priority to buses, taxis, or private cars after leaving the station. According to the user's transfer needs, the user's preferred means of transportation is set in the docking area closest to the transportation hub exit to ensure that passengers can reach it by walking a short distance. For example, in general, passengers will give priority to convenient and economical transportation methods, so the transfer path between buses and taxis can be guaranteed to be the shortest and the walking environment can be good.

[0085] In addition, the entrance and exit of the bus station should avoid crossing the entrance of taxis and private cars to reduce traffic conflicts. Taxi parking areas can be set up next to the bus station to facilitate passengers to choose taxis for pick-up and avoid traffic congestion when taxis pick up and drop off passengers.

[0086] In the layout design of some examples, the bus terminal is set on the south side of the station square, the taxi station is on the north side, and the private vehicle parking lot is located underground, so as to maximize the transfer efficiency.

[0087] Step 2: To ensure the comfort of passengers during transfers, spacious walkways and clear transfer signs should be designed. For example, in the square in front of the station, a dedicated pedestrian passage should be set up to prevent passengers from crossing the lanes. At the same time, awnings, seats and other facilities should be laid out in the hub to provide passengers with a comfortable transfer environment.

[0088] Step 3: Since the distance between connecting facilities directly affects the transfer efficiency, the distance between different facilities needs to be considered in the layout optimization. For example, the walking distance between the bus terminal and the high-speed rail station exit should be controlled within 100 meters to ensure that passengers can reach it quickly. The taxi parking area can be set a little further away, but the walking distance should also be guaranteed not to exceed 150 meters.

[0089] S4, the scale of facilities required for various modes of transportation, the location of facilities and the distance between facilities are taken as the layout plan.

[0090] Through the process in the above embodiment, a preliminary layout plan can be obtained. Furthermore, to ensure the effectiveness of the layout plan, the MATSim (Multi-Agent Transport Simulation) traffic simulation software can be used to verify and optimize the plan. Specifically, the layout plan is input into the traffic simulation software, and the passenger flow during peak hours is simulated by the traffic simulation software to identify the operating status of various transportation facilities; the layout plan is optimized and adjusted according to the operating status of the facilities.

[0091] For example, specific design parameters are input into the traffic simulation software, including road width, facility location, and traffic volume; then, passenger flow during peak hours is simulated and the operating status of various transfer facilities is observed. Through simulation, potential traffic bottlenecks or congestion points can be identified, and the location of facilities or additional evacuation channels can be adjusted through the replanning module of the traffic simulation software to improve traffic flow. For example, in the simulation, if it is found that the speed of taxi pick-up and drop-off areas is too slow, more taxi pick-up and drop-off berths can be added or the layout of taxi entrances can be adjusted, or transfer facilities can be re-arranged to areas where passengers travel more frequently.

[0092] It should be understood that since the passenger flow and traffic demand of transportation hubs are dynamically changing, the layout plan should not only consider current demand, but also reserve space for future development. For example, with the rise of electric vehicles and shared travel modes, parking lots in the future need to reserve space for these emerging modes of transportation. When designing private car parking lots, some parking spaces can be reserved for the installation of electric vehicle charging piles. In addition, with the popularity of shared travel, the demand for shared car parking areas may increase, so the layout and setting of shared car parking spaces need to be considered in advance during planning.

[0093] Optionally, after obtaining the layout plan, the connecting facilities in the planned hub area are laid out according to the layout plan, and after the layout plan is implemented, continuous optimization and adjustment are made to adapt to the complex changes in traffic. Specifically, first, a dynamic monitoring system is established to continuously obtain the latest traffic data, and analyze and identify potential problems based on these traffic data to predict future trends. The dynamic monitoring system can monitor the use of different modes of transportation in real time through smart cameras, sensors and data acquisition equipment, including passenger transfer behavior, vehicle in and out flow and dwell time. For example, data such as the number of bus arrivals, the frequency of taxi boarding and alighting, and the time it takes for private cars to enter and exit the garage can all be automatically collected by the monitoring system.

[0094] For example, the collected traffic data is summarized and analyzed at regular intervals (such as every year or every quarter) to obtain the actual peak hour passenger flow and the connection demand of various transportation modes, and the layout plan is optimized and adjusted based on the actual peak hour passenger flow and connection demand. For example, the analysis results show that the predicted demand for private car connection in y1 is cC h % of the total number of people, but by y2, due to the popularity of new energy vehicles and shared travel modes, the utilization rate of private cars has declined, and the demand for parking has decreased. Therefore, the originally planned parking lot size may appear too large, and facilities such as shared car parking spaces and charging piles need to be expanded. At this stage, the scale of facilities needs to be adjusted according to the new needs, unnecessary parking areas need to be reduced, and shared travel facilities and new energy vehicle charging piles need to be added. At the same time, in the layout optimization, it is necessary to ensure that the adjusted facilities are reasonably distributed. For example, the routes of bus terminals may need to be increased or adjusted, the parking spaces in taxi parking areas need to be expanded to meet new needs, and part of the space in private car parking lots can be converted into shared car parking spaces.

[0095] Secondly, based on the actual peak hour passenger flow and the demand for connections to various modes of transportation, the multimodal deep learning model and facility demand forecasting model can also be adjusted and updated to ensure that the model can accurately reflect the new traffic conditions for subsequent predictions. The update of the model involves not only the adjustment of model parameters, but also the adjustment of impedance factors of different modes of transportation, such as changes in bus service levels, taxi accessibility, or the introduction of emerging modes of transportation (such as shared bicycles, shared cars, etc.).

[0096] To ensure that the adjusted plan is effective, simulation and verification are essential steps. Before implementing the scale and layout adjustments, traffic simulation software can be used to simulate the adjusted plan. For example, simulate the new bus and taxi traffic during peak hours to observe whether the facility's capacity can cope with the new demand. At the same time, the congestion of pedestrian transfer channels can also be evaluated to ensure that passengers can smoothly transfer between different modes of transportation. If the simulation results show that a facility has potential congestion problems, it is necessary to further adjust the location of the facility or add channels to evacuate the flow of people.

[0097] After the adjustment of the scale and layout of the facilities is completed, the use of the new facilities needs to be continuously monitored and further optimized according to the actual operation results. Through the dynamic feedback mechanism, problems can be quickly identified and solved in a timely manner after the adjustment is implemented. For example, in the adjusted taxi parking area, if it is found that there are still insufficient parking spaces or the waiting time is too long, the pressure can be relieved by adding parking spaces or optimizing scheduling. At the same time, through the survey of passenger satisfaction, the effect of the facility adjustment is evaluated, the passengers' evaluation of the new facility distribution and transfer flow lines is understood, and the design is further optimized based on these feedbacks.

[0098] Based on the same inventive concept, the embodiment of the present invention also provides a multi-modal transportation integration docking facility layout device, such as Figure 2 As shown, including:

[0099] The acquisition module 21 is used to obtain user travel data, which includes the predicted peak hour passenger flow in the hub area to be planned, the time, cost and comfort required by various modes of transportation; and predicts the probability of use of various modes of transportation based on the peak hour passenger flow, the time, cost and comfort required by various modes of transportation.

[0100] The prediction module 22 is used to predict the connection demand of various modes of transportation according to the peak hour passenger flow and the use probability of various modes of transportation; and calculate the scale of facilities required for various modes of transportation according to the connection demand.

[0101] The determination module 23 is used to obtain the transfer demand of passengers and determine the layout locations of various transportation facilities and the distances between various facilities based on the transfer demand.

[0102] The layout module 24 is used to take the scale of facilities required by various modes of transportation, the location of facilities and the distance between facilities as a layout plan.

[0103] Each module in the above-mentioned multi-modal transportation integration docking facility layout device can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0104] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps in the embodiment of the method for layout of docking facilities for multi-modal transportation integration. The specific implementation method can be found in the method embodiment, which will not be repeated here.

[0105] Furthermore, the present invention also provides a non-temporary computer-readable storage medium containing instructions, and a computer program is stored on the storage medium. For example, a memory containing instructions, the above instructions can be executed by a processor of a computer device to complete the above method. For example, a non-temporary computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device. When the computer program is executed by the processor, the steps in the embodiment of the method for layout of docking facilities for multi-modal transportation integration can be implemented. The specific implementation method can be found in the method embodiment, which will not be repeated here.

[0106] It will be appreciated by those skilled in the art that embodiments of the present invention may provide methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0107] The present invention is described with reference to flowcharts and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as a combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0108] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0109] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0110] It should be pointed out that the specific implementation methods described above can enable those skilled in the art to understand the invention more comprehensively, but do not limit the invention in any way. Therefore, although the invention has been described in detail in this specification and embodiments, those skilled in the art should understand that the invention can still be modified or replaced by equivalents; and all technical solutions and improvements that do not deviate from the spirit and scope of the invention are included in the protection scope of the invention. Any figure mark in the claims should not be regarded as limiting the claims involved. Any simple change or equivalent replacement of the technical solution that can be obviously obtained by any technician familiar with the field within the technical scope disclosed in the present invention belongs to the protection scope of the present invention.

Claims

1. A method for layout of docking facilities for multi-modal transportation integration, characterized in that: include: Obtain user travel data, including the predicted peak hour passenger flow in the hub area to be planned, the time, cost and comfort required by various modes of transportation; predict the probability of using various modes of transportation based on the peak hour passenger flow, the time, cost and comfort required by various modes of transportation; Predict the connection demand of various modes of transportation based on peak hour passenger flow and the probability of use of various modes of transportation; calculate the scale of facilities required for various modes of transportation based on the connection demand; Obtain the transfer needs of passengers, and determine the layout of various transportation facilities and the distances between various facilities based on the transfer needs; The size of facilities required for various modes of transportation, the location of facilities and the distance between facilities are taken as the layout plan.

2. The method for layout of docking facilities for multi-modal transportation integration according to claim 1, characterized in that: The multimodal deep learning model predicts the probability of using various modes of transportation based on peak hour passenger flow, time required for each mode of transportation, cost and comfort, including: Obtain the weights corresponding to time, cost and comfort, and calculate the impedance values ​​of various modes of transportation according to their corresponding weights; the calculation formula for the impedance value is: R i =w T ·T i +w C C i +w U ·(1-U i ); R i represents the impedance value of the ith mode of transportation, w T 、w C 、w U are the weights of time, cost and comfort, T i , C i , U i are the travel time, cost and comfort of the i-th mode of transportation respectively; The actual traffic network diagram is obtained, and the peak hour passenger flow, impedance values ​​of various transportation modes and the traffic network diagram are input into the pre-trained multimodal deep learning model to obtain the usage probability of various transportation modes, where the traffic network diagram includes transportation stations and transportation modes between transportation stations.

3. The method for layout of docking facilities for multi-modal transportation integration according to claim 1 or 2, characterized in that: The required facility size for each mode of transportation is calculated based on the connection demand, including: Obtain the single-trip passenger capacity of various modes of transportation, and determine the required number of vehicles based on the connection demand and single-trip passenger capacity of various modes of transportation; The size of facilities required for various modes of transportation is determined based on the area occupied by each vehicle and the number of vehicles required.

4. The method for layout of docking facilities for multi-modal transportation integration according to claim 1 or 2, characterized in that: After considering the size of facilities, location of facilities and distance between facilities required by various modes of transportation as the layout plan, it also includes: Input the layout plan into the traffic simulation software, simulate the passenger flow during peak hours through the traffic simulation software, and identify the operating status of various transportation facilities; The layout plan is optimized and adjusted according to the operating status of the facilities.

5. The method for layout of docking facilities for multi-modal transportation integration according to claim 1 or 2, characterized in that: After considering the size of facilities, location of facilities and distance between facilities required by various modes of transportation as the layout plan, it also includes: After the connecting facilities in the planned hub area are laid out according to the layout plan, the actual peak hour passenger flow and the connecting demand of various modes of transportation are obtained at preset intervals; the layout plan is optimized and adjusted based on the actual peak hour passenger flow and connecting demand; or, Monitor the operating status of the docking facilities in real time, and optimize and adjust the layout plan based on the operating status of the facilities.

6. A multi-modal transportation integration docking facility layout device, characterized in that: include: The acquisition module is used to acquire user travel data, including the predicted peak hour passenger flow in the hub area to be planned, the time, cost and comfort required by various modes of transportation; and predict the use probability of various modes of transportation based on the peak hour passenger flow, the time, cost and comfort required by various modes of transportation; The prediction module is used to predict the connection demand of various modes of transportation based on the peak hour passenger flow and the use probability of various modes of transportation; and calculate the size of facilities required for various modes of transportation based on the connection demand; A determination module is used to obtain the transfer needs of passengers and determine the layout locations of various transportation facilities and the distances between various facilities based on the transfer needs; The layout module is used to take the scale of facilities, location of facilities and distance between facilities required by various modes of transportation as layout plan.

7. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for layout of docking facilities for multi-modal transportation integration as described in any one of claims 1 to 5 is implemented.

8. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method for layout of docking facilities for multi-modal transportation integration described in any one of claims 1-5 is implemented.

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