Method and system for distributing departure time by comprehensively considering inter-city and intra-city multi-mode traffic

Abstract

The invention relates to the technical field of traffic transportation optimization and scheduling, and discloses a departure time distribution method and system comprehensively considering inter-city and intra-city multi-mode traffic, through constructing a super network, a traveler is allowed to departure from a starting point of one city and arrive at a destination of another city, and the traffic transportation optimization and scheduling efficiency is improved. Therefore, selection of travel modes, routes and time is comprehensively analyzed. A quasi-dynamic traffic distribution algorithm considering residual queues is researched and adopted to solve the problem of user balance in departure time. According to the method, the intercity traffic frequency can be improved, the comprehensive travel cost of travelers is effectively reduced, the use of intercity traffic is promoted, a new idea is provided for optimizing intercity and intra-city traffic connection, and the method has important application value and popularization prospects.

Description

Technical Field

[0001] The present invention belongs to the technical field of transportation optimization and scheduling, and relates to a departure time allocation method and system that comprehensively considers inter-city and intra-city multimodal transportation. Background Art

[0002] As cities continue to expand in size and social connections become increasingly close, demand for intercity travel is growing, along with emerging intercity travel groups such as cross-city commuters and day trips. Economic opportunities and educational resources in urban areas attract many people. However, rising housing prices and living costs in major cities often lead people to choose to live in more remote areas or nearby cities to reduce expenses. Well-developed transportation infrastructure improves travel convenience, increasing people's willingness to commute across cities.

[0003] Intercity travel differs significantly from intra-city travel, primarily in the longer distances involved. Unlike city roads, highways are closed systems, and vehicles are generally not subject to traffic lights. Furthermore, trains and planes operate on fixed schedules, and travelers must wait for their departures before a specified time. Therefore, when planning their trips, travelers must not only choose their mode of transportation and route but also consider travel time. Ideally, the closer travelers arrive at an intercity transportation hub (such as a train station) to the departure time of their train, the shorter their waiting time at the hub. Therefore, travelers' travel decision-making process must encompass both intra-city and inter-city travel, requiring comprehensive decisions on travel mode, route, and departure time.

[0004] Intercity travel decisions are influenced by intracity travel options. Intracity transportation includes buses, subways, and private cars. Buses and subways offer multiple routes connecting different parts of the city, while private cars provide convenient point-to-point travel in areas where public transportation is insufficient. Different modes of transportation require varying amounts of time to reach intercity hubs, so travelers must consider a comprehensive range of intracity transportation options.

[0005] Research on travelers' departure times and routes mainly falls into two methods: aggregated and non-aggregated. Early research used questionnaire-based aggregated models to analyze the characteristics of intercity travel demand from a macroscopic perspective. In recent years, scholars have utilized information such as mobile phone signals and mobile Internet data to identify travelers' travel times and routes. With the improvement of intercity transportation hub facilities, travelers' travel modes have shown obvious differential characteristics. Based on the aggregated method, accurately describing travelers' characteristics and their impact on the transportation system has become a problem. Therefore, scholars have adopted non-aggregated methods to reflect travelers' individual differences and travel behaviors. Travelers' travel choices are subject to the dual constraints of time and route costs, and many scholars have studied the impact of time and route cost utility on travelers' travel mode choices. The departure time affects the travel route cost because the costs at different times vary. Therefore, under a complex transportation network, how to determine the optimal departure time and route for each traveler has become a challenge. Summary of the Invention

[0006] The object of the present invention is to provide a departure time allocation method and system that comprehensively considers multi-modal transportation between cities and within cities, providing more accurate departure times and travel chains for intercity travelers, being able to increase intercity transportation frequencies, effectively reduce the comprehensive travel costs of travelers, and promote the use of intercity transportation.

[0007] To solve the above technical problems, the present invention is implemented by adopting the following technical solutions.

[0008] In a first aspect, the present invention proposes a departure time allocation method that comprehensively considers multi-modal transportation between cities and within cities, including:

[0009] Based on a pre-constructed intercity travel chain, identify the optimal intercity travel chain to obtain the route of the traveler from the starting point to the ending point;

[0010] Use an iterative algorithm to optimize the optimal intercity travel chain and its corresponding matching traveler departure time to obtain the optimal departure time, transportation mode selection, transfer information, and estimated arrival time.

[0011] In combination with the first aspect, further, the method for constructing the intercity travel chain is:

[0012] Construct a super network, where the super network includes an intra-city transportation network and an intercity transportation network. The intra-city transportation network includes a bus network, a subway network, and a road network; the intercity transportation network includes a railway network, an aviation network, and a highway network;

[0013] Based on the intra-city transportation network and the intercity transportation network, construct an intercity travel chain.

[0014] In combination with the first aspect, further, the method for constructing the super network is:

[0015] The construction method of the urban transportation network is as follows:

[0016] Collect data on bus, subway and road operating times, routes, station distribution and service areas;

[0017] Visualize and spatially analyze the collected data on bus, subway, and road operating times, routes, station distribution, and service coverage to determine the flow direction and demand area distribution of urban traffic;

[0018] Based on the determined flow direction and demand area distribution of urban traffic, an urban traffic network model is established, in which nodes represent traffic stations or intersections, and edges represent the connection relationship between different transportation modes and their traffic capacity;

[0019] It should be noted that visualization processing and spatial analysis are existing technologies.

[0020] Combined with the first aspect, in order to further improve the accuracy of the urban traffic network model, factors such as traffic flow, traveler transfer time and travel cost need to be considered to better reflect the actual situation of urban traffic.

[0021] The construction method of intercity transportation network is as follows:

[0022] Collect rail, air and road timetables, capacity, fares and service levels;

[0023] Based on the collected railway, aviation and highway timetables, capacity, ticket prices and service levels, and using network optimization algorithms, taking into account the travel demand and time cost between different cities, an intercity transportation network model is constructed with cities or transportation hubs as nodes and transportation routes as edges.

[0024] In combination with the first aspect, further, the intercity travel chain is constructed based on the urban transportation network and the intercity transportation network, including:

[0025] Determine the departure time from the intercity transportation hub of the destination city by working backward from the traveler's destination.

[0026] Based on the determined departure time from the intercity transportation hub of the destination city and the travel time between the two intercity transportation hubs, reverse deduction is performed to obtain the departure time from the intercity transportation hub of the origin city;

[0027] Based on the departure time from the intercity transportation hub of the departure city, reverse deduction is performed to obtain the departure time from the starting point to the intercity transportation hub of the departure city. At this point, at least one intercity travel chain including the traveler's departure time and travel path is obtained.

[0028] In combination with the first aspect, further, based on the pre-constructed intercity travel chain, identifying the optimal intercity travel chain to obtain the route of the traveler from the starting point to the ending point includes:

[0029] Based on the pre-constructed intercity travel chain, obtaining at least one travel chain, and evaluating the optimal intercity travel chain through the generalized travel cost, where the generalized travel cost includes time cost and economic cost, the time cost includes travel time, waiting time, and transfer time, and the economic cost includes intercity transportation fare, intracity transportation cost, and potential additional costs;

[0030] By setting the objective function to minimize the generalized travel cost of all travelers and setting the constraint conditions for time cost and economic cost to determine the optimal intercity travel chain; the expression of the objective function is:

[0031] (1)

[0032] The objective function aims to minimize the generalized travel cost of all travelers; where is the set of departure times of travelers; is the final output result, indicating the departure time of traveler ; is a known quantity, indicating the expected arrival time of traveler ; represents the generalized travel cost of traveler .

[0033] (2)

[0034] Among them, is an intermediate calculation variable, representing the generalized cost of the railway network; is a known quantity, representing the unit time cost of the railway network; is an intermediate calculation variable, representing the time spent by the traveler on the railway network; is a known quantity, representing the fare from city to city in the railway network; represents the railway network; represents the set of travel times, represents the time period in the set of travel times .

[0035] (3)

[0036] Among them, is an intermediate calculation variable, representing the generalized cost of the aviation network; is a known quantity, representing the unit - time cost of the aviation network; is an intermediate calculation variable, representing the time spent by travelers on the aviation network; is a known quantity, representing the aviation network from city to city ticket price, represents the aviation network.

[0037] (4)

[0038] (5)

[0039] Among them, is an intermediate calculation variable, representing the number of remaining queues on section section at time period;" is an intermediate calculation variable, representing the traffic volume on section section at time period; is an intermediate calculation variable, representing the number of remaining queues on section at time period section; and are both congestion - degree parameters, which are fixed values; is an intermediate calculation variable, representing the travel time on section section at time period; is a known quantity, representing the fastest travel time on section section; is a known quantity, representing the maximum traffic volume on section at time period on section and are both known quantities, representing the parameters of section impedance.

[0040] (6)

[0041] Among them, is an intermediate calculation variable, representing the generalized cost of the highway network; is a known quantity, representing the unit - time cost of the highway network; is an intermediate calculation variable, representing the time spent by travelers on the highway network.

[0042] (7)

[0043] Among them, is an intermediate calculation variable, representing the generalized cost of the subway network; is a known quantity representing the unit - time cost of the subway network; is an intermediate calculation variable representing the time spent by the traveler on the subway network; is a known quantity representing the subway network from station to station of the fare, represents the subway network.

[0044] (8)

[0045] Among them, is an intermediate calculation variable representing the generalized cost of the bus network; is a known quantity representing the unit - time cost of the bus network; is an intermediate calculation variable representing the time spent by the traveler on the bus network; is a known quantity representing the bus network from station to station of the fare, represents the bus network.

[0046] (9)

[0047] Among them, is an intermediate calculation variable representing the transfer cost between the bus network and the subway network; is a known quantity representing the unit - time cost of transferring between the bus network and the subway network; is an intermediate calculation variable representing the transfer time of the traveler between the bus network and the subway network.

[0048] (10)

[0049] Among them, is an intermediate calculation variable representing the generalized travel cost of the traveler departing at the departure time departing; of the generalized travel cost; is a known set of travel modes, including railway, aviation, highway, subway, bus, and car, represents the travel mode; is the generalized cost corresponding to each travel mode, including the generalized cost of the railway network the generalized cost of the aviation network the generalized cost of the highway network the generalized cost of the subway network the generalized cost of the bus network the transfer cost between the bus network and the subway network .

[0050] (11)

[0051] Among them, is an intermediate calculation variable, representing the general travel cost of the traveler departing at the departure time ; is the known set of travel modes, including railway, aviation, highway, subway, bus, and car, representing the travel mode; is the general cost corresponding to each travel mode, including the general cost of the railway network[[ID=!7]] , the general cost of the aviation network , the general cost of the highway network , the general cost of the subway network , the general cost of the bus network , the transfer cost between the bus network and the subway network .

[0052] (12)

[0053] Among them, is an intermediate calculation variable, representing the total time expenditure of the traveler departing at the departure time , that is, the travel time; is an intermediate calculation variable, representing the set of travel modes in which, the sum of the travel times of all travel modes ;

[0054] (13)

[0055] Constraint (13) indicates that the actual arrival time of the traveler is equal to the sum of the departure time and the total time expenditure of departing at the departure time ;

[0056] Equation (2) is the constraint for calculating the generalized cost of the railway network; Equation (3) is the constraint for calculating the generalized cost of the aviation network; Equation (4) is the constraint indicating the calculation method of the remaining queue; Equation (5) is the constraint for calculating the real-time road impedance; Equation (6) is the constraint for calculating the generalized cost of the highway network; Equations (7) and (8) are the constraints for calculating the generalized costs of the subway network and the bus network respectively; Equation (9) is the constraint for calculating the generalized cost of the in-city transfer network; Equation (10) is the constraint for calculating the sum of the generalized travel costs of travelers; Equation (11) is the constraint considering the penalty for the arrival time, where the greater the difference between the actual arrival time and the expected arrival time, the higher the penalty; Equations (12) and (13) indicate the constraint that the sum of the travel time and the departure time is the arrival time.

[0057] Combined with the first aspect, further, the optimization of the optimal occurrence chain and its corresponding matching traveler departure time by using the iterative algorithm includes:

[0058] Preset the number of iterations. If the number of iterations is reached, stop the iteration and output the result of the last iterative calculation, which is the optimal departure time, transportation mode selection, transfer information, and expected arrival time.

[0059] The specific iterative calculation method is as follows:

[0060] Initialize the generalized travel cost of the intercity travel chain and set the number of iterations to 1.

[0061] According to the expected arrival time of the traveler, reverse-derive the best path for the traveler from the origin to the destination to obtain the objective function and a number of discrete departure times.

[0062] Based on the obtained number of discrete departure times, calculate the set of departure times and the set of objective functions corresponding to each discrete departure time.

[0063] Select the traveler's departure time and travel path based on the minimum objective function value.

[0064] Update the generalized travel cost of the intercity travel chain according to the selected traveler's departure time and travel path, and increment the number of iterations by 1.

[0065] If the number of iterations has not reached the set upper limit, return to the step of calculating the set of departure times and the set of objective functions corresponding to each discrete departure time for the next iteration; if the number of iterations reaches the set upper limit, output the optimal departure time and travel path of the traveler.

[0066] In the second aspect, the present invention proposes a departure time allocation system that comprehensively considers multi-modal transportation between cities and within cities, including:

[0067] The optimal intercity travel chain construction module is configured to identify the optimal intercity travel chain based on the pre-constructed intercity travel chain, and obtain the route of the traveler from the starting point to the ending point;

[0068] The iteration module is configured to optimize the optimal intercity travel chain and its corresponding traveler departure time by using an iterative algorithm, and obtain the optimal departure time, transportation mode selection, transfer information, and estimated arrival time.

[0069] In a third aspect, the present invention proposes a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned departure time allocation method that comprehensively considers intercity and intracity multi-modal transportation are realized.

[0070] In a fourth aspect, the present invention proposes a computer device, including:

[0071] A memory for storing a computer program;

[0072] A processor for executing the computer program to realize the steps of the above-mentioned departure time allocation method that comprehensively considers intercity and intracity multi-modal transportation.

[0073] In a fifth aspect, the present invention proposes a computer program product, including a computer program. When the computer program is executed by a processor, the steps of the above-mentioned departure time allocation method that comprehensively considers intercity and intracity multi-modal transportation are realized.

[0074] Compared with the prior art, the beneficial effects achieved by the present invention:

[0075] (1) The present invention can optimize the travel decisions of travelers, improve the frequency of intercity transportation, effectively reduce the comprehensive travel costs of travelers, promote the use of intercity transportation, provide a new idea for optimizing the connection between intercity and intracity transportation, and has important application value and promotion prospects.

[0076] (2) The present invention considers the remaining queue and adopts a quasi-dynamic traffic assignment algorithm to solve the Departure Time User Equilibrium (DTUE) problem.

[0077] (3) The present invention not only considers the multi-modal travel needs of travelers, but also integrates real-time traffic data and historical travel patterns, aiming to optimize the travel experience of travelers in a complex traffic network, so as to ensure that they can complete cross-city travel efficiently and smoothly. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is a flowchart of the allocation method in this embodiment;

[0079] Figure 2 This is the flowchart of the iterative algorithm in this embodiment;

[0080] Figure 3 This is the schematic diagram of the super network in this embodiment;

[0081] Figure 4 This is the schematic example diagram of the super network in the verification example of the present invention;

[0082] Figure 5 This is the schematic diagram of urban traffic load in the verification example of the present invention, where Figure (a) is the schematic diagram of traffic load in City A and Figure (b) is the schematic diagram of traffic load in City B;

[0083] Figure 6 This is the sample diagram of bus + subway network data input in the verification example;

[0084] Figure 7 This is the sample diagram of road network data input in the verification example;

[0085] Figure 8 This is the sample diagram of train network input in the verification example;

[0086] Figure 9 This is the sample diagram of airplane network input in the verification example;

[0087] Figure 10 This is the sample diagram of highway network input in the verification example;

[0088] Figure 11 This is the sample diagram of travel demand data input in the verification example;

[0089] Figure 12 This is the sample diagram of travel demand data input in the verification example;

[0090] Figure 13 This is the sample diagram of a single intercity travel chain in the verification example;

[0091] Figure 14 This is the sample diagram of the generalized travel cost of all travelers in the verification example;

[0092] Figure 15 This is the sample diagram of the travel time required by all travelers on the intercity travel chain with the lowest generalized travel cost in the verification example;

[0093] Figure 16 This is the sample diagram of the updated road network data input in the verification example;

[0094] Figure 17 This is the sample diagram of the updated highway network data input in the verification example;

[0095] Figure 18Sample diagram of updated trip chain data input in the verification example;

[0096] Figure 19 Sample diagram of the lowest generalized travel cost for travelers in the verification example;

[0097] Figure 20 Sample diagram of the best departure time for travelers in the verification example. Detailed implementation manners

[0098] The technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present invention and the specific features in the embodiments are detailed descriptions of the technical solution of the present invention, rather than limitations on the technical solution of the present invention. Without conflict, the embodiments of the present invention and the technical features in the embodiments may be combined with each other.

[0099] The term "and / or" is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " generally represents an "or" relationship between the associated objects before and after.

[0100] Embodiment 1

[0101] As Figure 1 shown, the departure time allocation method for comprehensively considering intercity and intracity multimodal transportation in this embodiment includes the following steps:

[0102] Step 1: In this step, first, a comprehensive intracity transportation network model needs to be established. The network model includes a bus network, a subway network (as shown in Table 1, where INT represents integer data, FLOAT represents floating-point data, and LIST represents a list for storing any type of data), and a road network (as shown in Table 2). By analyzing in detail the running times, line layouts, station settings, and their interconnection relationships of the above various transportation modes, a complete intracity transportation network diagram is formed. At the same time, the location and functions of intercity transportation hubs (as shown in Table 3) also need to be considered to ensure seamless connection between intracity transportation and intercity transportation. Through data collection and existing network analysis techniques, the main traffic flow nodes and their connectivity are identified, thereby providing basic data support for subsequent departure time allocation.

[0103]

[0104]

[0105]

[0106] Step 2: In this step, an intercity transportation network needs to be established, including a railway network, an aviation network (as shown in Table 4), and a highway network (as shown in Table 5). By analyzing the operating characteristics, schedules, and service scopes of various intercity transportation modes, a comprehensive intercity transportation network is constructed. Meanwhile, the settings and functions of intercity transportation hubs are considered to facilitate the effective transfer between different transportation modes. The construction of this network aims to provide diverse travel options for travelers and offer the necessary network structure support for departure time matching.

[0107]

[0108]

[0109] Step 3: The core of this step is to construct an intercity travel chain (as shown in Table 6). When travelers choose travel modes, they need to comprehensively consider the connection between urban transportation and intercity transportation. Through the demand analysis of travelers' departure and destination locations (as shown in Table 7), the optimal intercity travel chain is identified to ensure that travelers can complete their journeys smoothly from the starting point to the end point. This process involves the combination of different transportation modes, the selection of transfer nodes, and the evaluation of time costs to ensure the efficiency and feasibility of the intercity travel chain.

[0110]

[0111]

[0112] Step 4: In this stage, an iterative algorithm is used to match the departure times of travelers. In N iterations, the allocation system of the present invention will return to Step 3 to continuously optimize the matching of the intercity travel chain and the departure time. Each iteration is based on the results of the previous iteration, combined with real-time traffic data and changes in travelers' demands, to adjust the departure time to maximize travel efficiency. Through this dynamic adjustment mechanism, it can better adapt to the changing traffic environment and travelers' demands.

[0113] Step 5: According to the analysis results of the previous steps, the optimal departure time and the specific travel route are output. This output not only includes the best departure time of travelers but also provides details such as the selection of transportation modes, transfer information, and estimated arrival time. The provision of this information can help travelers better plan their trips and improve the convenience and comfort of travel. At the same time, this method also provides data support for traffic management departments to optimize the operating efficiency of urban and intercity transportation.

[0114] Example 2

[0115] The following is a detailed description of the departure time allocation method that comprehensively considers multi-modal transportation between intercity and urban areas:

[0116] (1)Construct a super network: In this step, it is first necessary to construct a comprehensive super network, including the intra-city network and the inter-city network. The intra-city network includes various transportation modes such as the bus network, the subway network, and the road network, ensuring that travelers can flexibly choose travel modes within the city. At the same time, the inter-city network connects transportation hubs between different cities, including the railway network, the aviation network, and the highway network, etc. By deeply analyzing the operation times, route plans, and station settings of various transportation modes, a complete super network is formed. This super network provides travelers with diverse travel options and provides the necessary network structure support for subsequent departure time allocation.

[0117] (2)Construct an inter-city travel chain: The core of this step is to construct the travel chain of travelers. Travelers start from one city, pass through the inter-city transportation hub, and finally reach the destination in another city. By analyzing the departure and destination of travelers, the best travel path is identified to ensure a smooth transfer to other transportation modes at the inter-city transportation hub. The construction of the travel chain not only considers the combination of different transportation modes but also includes transfer time, waiting time, and the accessibility of various transportation tools to ensure that travelers can complete the journey from the starting point to the end point in the shortest time.

[0118] (3)Whether the iteration number is reached: In this stage, the system of the present invention will check whether the preset iteration number has been reached. If not, it will enter step 4 for further calculation; if so, the algorithm will be stopped and the final departure time and travel path will be output. At this time, the final departure time and travel path are the optimal departure time and travel path. The design of this step aims to ensure the effectiveness and accuracy of the algorithm. By iterating multiple times to optimize the matching of the departure time and the travel chain, the travel experience of travelers is improved.

[0119] (4)Calculate the objective function: In this stage, the system of the present invention will calculate the best path for travelers from the starting point to the end point in reverse according to the expected arrival time of travelers to obtain the objective function. The calculation of the objective function includes the time cost and economic cost of each path to determine the optimal travel plan. By this method, the system of the present invention can provide travelers with the departure time and travel path that best meet their needs, ensuring that travelers can reach the destination smoothly within the specified time.

[0120] (5)Match the optimal departure time: In this step, the system of the present invention will calculate a set of departure times and generate a set of objective functions corresponding to each departure time. Through the analysis of this data, the system of the present invention can identify discrete optimal departure times, ensuring that travelers can choose the travel time and mode with the lowest comprehensive travel cost when selecting a departure time. This matching process not only considers the individual needs of travelers but also synthesizes the global traffic conditions and network operation efficiency, providing more accurate departure time suggestions for travelers.

[0121] (6)Update the path cost: In this stage, the system of the present invention will update the passing cost (time) of the path based on the traveler's travel chain. As traffic conditions change and the traveler's needs are dynamically adjusted, the path cost may change.

[0122] (7)Update the intercity travel chain: The system of the present invention will recalculate the traveler's intercity travel chain to ensure that the intercity travel chain matches the latest path cost. By updating the intercity travel chain, the system can optimize the traveler's travel path and improve the overall travel efficiency. This step will also consider the traveler's preferences and actual needs to ensure the flexibility and adaptability of the intercity travel chain. Return to step (3).

[0123] Through these steps, the algorithm can optimize the traveler's travel decision-making, evenly distribute the departure time, thereby reducing the traveler's comprehensive travel cost and optimizing the operation efficiency of urban and intercity transportation.

[0124] When solving the dynamic time-dependent traffic assignment problem, the assignment method of the present invention first needs to initialize the cost of the link and set the number of iterations to 1. This step provides a basis for subsequent calculations. Next, the algorithm reversely derives the optimal path from the starting point to the ending point according to the traveler's expected arrival time. This process involves evaluating each path in the super network to determine which paths can reach the destination in the shortest time within the given time limit. Through this reverse path search, the objective function and several discrete sets of departure times are obtained, laying a foundation for subsequent travel time and path selection.

[0125] The assignment method of the present invention will calculate a set of departure times and its corresponding set of objective functions. Each departure time is associated with a specific objective function value, which usually represents the time or cost required to travel from the starting point to the ending point. By analyzing the objective functions of different departure times, the optimal travel time period can be identified, thereby providing more targeted suggestions for travelers. This process not only considers the current traffic conditions but also reflects the possible changes in traffic flow that travelers may encounter at different time periods, thus more accurately predicting the travel time.

[0126] The distribution method of the present invention selects the travel route and departure time based on the minimum objective function value. This selection process is dynamic, meaning that each iteration will be adjusted according to the latest traffic data and the traveler's needs. The selection of the route and departure time not only depends on the current link cost but also takes into account possible future traffic condition changes. Subsequently, the algorithm updates the link cost according to the traveler's departure time and the selected route, and this update process will affect the results of subsequent iterations. As the number of iterations increases, the algorithm continuously optimizes the traveler's departure time and route selection until the set iteration limit is reached. Finally, the algorithm outputs the traveler's optimal departure time and travel route, ensuring the maximization of travel efficiency in a complex traffic environment.

[0127] Verification Example 1

[0128] In order to verify that the time distribution method of the present invention can improve the intercity traffic frequency and effectively reduce the comprehensive travel cost of travelers, a verification example is listed for verification and explanation.

[0129] The following takes the example of a traveler departing from a certain traffic zone in City A to a certain location in City B. Using the departure time distribution method of the present invention, the optimal departure time, transportation mode selection, transfer information, and estimated arrival time are obtained as follows:

[0130] Intercity travel in the urban agglomeration means that in order to achieve specific living or production goals, travelers travel from a certain location in one city to a specific location in another city through urban roads and intercity traffic lines, and the entire travel process is one-way. As an important part of intercity travel, the travel of travelers cannot exist in isolation and must be connected to the urban travel in the origin city and the destination city to complete the entire journey. Therefore, the study of intercity travel in the urban agglomeration should focus on the whole process of travelers' travel and grasp the laws of travel as a whole. The entire intercity passenger travel process can be divided into three stages: First is the urban travel in the origin city, where the traveler departs from a certain traffic zone in City A and reaches the intercity transportation hub through the urban traffic network; then is the intercity travel between City A and City B, where the traveler arrives at the intercity transportation hub in City B from the intercity transportation hub in City A through the lines on the intercity traffic network; finally is the urban travel in the destination city B, where the traveler reaches the destination from the intercity transportation hub in City B through the urban traffic network.

[0131] Based on the travel process of intercity travelers in the urban agglomeration, a super network model of the intercity multimodal transport system in the urban agglomeration is constructed. To evaluate the mathematical model and algorithm for selecting the traveler's departure time, an integrated intercity and intra-city network is used. The super network is as Figure 4As shown, it consists of two identical Sioux-Falls networks, with a total of 24 nodes, 76 links, and 528 trips. Two bus lines and one subway line are established, where node 1 and node 21 serve as the entrance and exit of the highway respectively. Travelers can transfer from any starting city entrance to the destination city exit, with the same highway toll. Node 16 represents the railway station, facilitating intercity commuting for travelers, while node 12 serves as the airport, providing intercity flight connections. At the same time, private cars can enter and exit the highway through nodes 1 and 21 to reach other cities.

[0132] Step S1: Construction of the urban transportation network

[0133] In this step, a comprehensive urban transportation network will be established, which covers the bus network, subway network, and road network. As Figure 6 and Figure 7 shown Figure 6 and Figure 7 show some data of the bus network and subway network as well as some input data of the road network.

[0134] Step S2: Construction of the intercity transportation network

[0135] In this step, a comprehensive intercity transportation network will be established, which includes the aviation network, train network, and highway network. As Figures 8 to 10 shown, Figures 8 to 10 shows some data of the train network and aviation network as well as some input data of the highway network.

[0136] Step S3: Calculation of the optimal intercity travel chain

[0137] The key in this step is to construct the intercity travel chain. When choosing the travel mode, travelers need to comprehensively evaluate the connection between urban transportation and intercity transportation. As Figure 11 shown, Figure 11 is a sample data input for travel demand. By analyzing the departure and destination demands of travelers, the best travel chain is identified to ensure that travelers can smoothly reach the destination from the starting point. Examples of all intercity travel chains of travelers are shown as Figure 12 shown, and each traveler may have multiple intercity travel chains.

[0138] An example of a certain intercity travel chain is shown as Figure 13As shown in the figure. The intercity travel chain consists of three parts, and each part includes two elements. Counting from top to bottom, the first part is the trip in the destination city. The first element of the first part is the sum of the generalized cost of the traveler in the destination city and the intercity travel cost. The second element of the first part is the travel chain of the traveler in the destination city. Counting from top to bottom, the second part is the trip in the origin city. The first element of the second part is the sum of the generalized costs of the traveler. The second element of the second part is the travel chain of the traveler in the origin city. Counting from top to bottom, the third part is the travel situation of the intercity network. In this verification example, it refers to highway travel.

[0139] The generalized travel costs of all travelers are as Figure 14 shown. The traveler will select the travel chain with the lowest generalized travel cost.

[0140] The travel time required by all travelers on the travel chain with the lowest generalized travel cost is as Figure 15 shown.

[0141] Step S4: Iteratively adjust the travel costs of the road network and the travel chain

[0142] An iterative algorithm is used to match the departure times of travelers. During the N iterations, return to step three and continuously optimize the matching of the intercity travel chain and the departure time.

[0143] The input example of the updated road network data is as Figure 16 shown; the input example of the updated highway network data is as Figure 17 shown; the input example of the updated travel chain data is as Figure 18 shown.

[0144] Step five: According to the analysis results above, output the optimal departure time and the specific travel route. This output not only includes the best departure time of the traveler, but also provides detailed information such as the choice of transportation mode, transfer information, and estimated arrival time.

[0145] An example of the lowest generalized travel cost of a traveler is as Figure 19 shown; an example of the best travel time of a traveler is as Figure 20 shown.

[0146] As Figure 5 shown, Figure 5 is a schematic diagram of urban traffic load. From the heat maps of City A and City B in the figure, the impact of intercity traffic can be clearly shown. Figure 5Shows the number of travelers at each node during different time periods. The gradient from purple to yellow indicates the number of travelers increasing from low to high. City A is the departure city and City B is the destination city. Therefore, the travel peak in City A occurs before that in City B because travelers are going from City A to City B. Nodes 12 and 16 are the airports and railway stations of the two cities respectively. The travel peak at Node 16 shows obvious periodic changes, with a peak occurring every 120 minutes. However, the train departure frequency is 60 minutes, which is different from the peak frequency. Since the flight departure frequency is 120 minutes, when both trains and planes can depart, trains, planes, and roads jointly bear the intercity travel demand, so the heat maps of Nodes 12 and 16 are both blue. However, when there are no planes and only trains depart, trains and roads will bear the travel demand of the city, which leads to an increase in the passenger flow at the railway station.

[0147] By establishing a time-varying super network model, the present invention can dynamically reflect the changes in traffic demand, thus effectively solving the problem that the travel decisions of travelers in different time intervals affect each other.

[0148] In the present invention, the determination of the departure time is derived backward based on the expected arrival time of the traveler to ensure that the traveler can reach the destination within a reasonable time.

[0149] The present invention allows travelers to choose different departure time intervals, and then calculates the minimum generalized travel cost corresponding to each departure time, helping travelers make the optimal choice among various transportation modes.

[0150] Considering the diversity of intercity transportation hubs and the flexibility of transportation modes, when choosing a travel route, travelers can comprehensively evaluate the time and economic costs of different transportation tools, and finally achieve efficient and economical travel.

[0151] Embodiment 3

[0152] Based on the same inventive concept as Embodiment 1, this embodiment introduces a departure time allocation system that comprehensively considers intercity and intracity multi-modal transportation, including:

[0153] An optimal intercity travel chain construction module, configured to identify the optimal intercity travel chain based on the pre-constructed intercity travel chain, and obtain the route of the traveler from the starting point to the ending point;

[0154] An iteration module, configured to optimize the optimal intercity travel chain and its corresponding matching traveler departure time by using an iterative algorithm to obtain the optimal departure time, transportation mode selection, transfer information, and expected arrival time.

[0155] Embodiment 4

[0156] Based on the same inventive concept as other embodiments, this embodiment introduces a computer-readable storage medium with a computer program stored thereon. When the computer program is executed by a processor, the steps of the above-described departure time allocation method that comprehensively considers intercity and intracity multimodal transportation are implemented.

[0157] Embodiment 5

[0158] Based on the same inventive concept as other embodiments, this embodiment introduces a computer device, including: a memory for storing a computer program; a processor for executing the computer program to implement the steps of the above-described departure time allocation method that comprehensively considers intercity and intracity multimodal transportation.

[0159] Embodiment 6

[0160] Based on the same inventive concept as other embodiments, this embodiment introduces a computer program product, including a computer program that, when executed by a processor, implements the steps of the above-described departure time allocation method that comprehensively considers intercity and intracity multimodal transportation.

[0161] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can 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.

[0162] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one or more flows and / or blocks Figure 1 one or more blocks.

[0163] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device that implements the functions in Figure 1 one or more flows and / or blocksFigure 1 The functions specified in one or more boxes.

[0164] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing in the process Figure 1 One process or more processes and / or boxes Figure 1 The steps of the functions specified in one or more boxes.

[0165] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms, and these all fall within the protection scope of the present invention.

Claims

1. A departure time allocation method that comprehensively considers multi-modal transportation in intercity and intra-city areas, characterized in that, include: Based on the pre-built inter-city travel chain, the optimal inter-city travel chain is identified to obtain the traveler's route from the starting point to the destination; An iterative algorithm is used to optimize the optimal intercity travel chain and its corresponding matching traveler departure time to obtain the optimal departure time, transportation mode selection, transfer information and estimated arrival time.

2. The departure time allocation method for comprehensively considering multi-modal transportation in intercity and intracity areas according to claim 1, wherein The method for constructing the intercity travel chain is as follows: Building a super network, wherein the super network includes an urban transportation network and an inter-city transportation network, wherein the urban transportation network includes a bus network, a subway network, and a road network; and the inter-city transportation network includes a railway network, an aviation network, and a highway network; An intercity travel chain is constructed based on the urban transportation network and the intercity transportation network.

3. The departure time allocation method for comprehensively considering multi-modal transportation in intercity and intracity according to claim 2, characterized in that The method for constructing the super network is as follows: The construction method of the urban transportation network is as follows: Collect data on bus, subway and road operating times, routes, station distribution and service areas; Visualize and spatially analyze the collected data on bus, subway, and road operating times, routes, station distribution, and service coverage to determine the flow direction and demand area distribution of urban traffic; Based on the determined flow direction and demand area distribution of urban traffic, an urban traffic network model is established, in which nodes represent traffic stations or intersections, and edges represent the connection relationship between different transportation modes and their traffic capacity; The construction method of intercity transportation network is as follows: Collect rail, air and road timetables, capacity, fares and service levels; Based on the collected railway, aviation and highway timetables, capacity, ticket prices and service levels, and using network optimization algorithms, taking into account the travel demand and time cost between different cities, an intercity transportation network model is constructed with cities or transportation hubs as nodes and transportation routes as edges.

4. The departure time allocation method for comprehensively considering multi-modal transportation in intercity and intracity as claimed in claim 2, wherein The intercity travel chain is constructed based on the urban transportation network and the intercity transportation network, including: Work backward from the traveler's destination to the destination city's intercity transportation hub to determine the departure time from the destination city's intercity transportation hub; Based on the determined departure time from the intercity transportation hub of the destination city and the travel time between the two intercity transportation hubs, reverse deduction is performed to obtain the departure time from the intercity transportation hub of the origin city; Based on the departure time from the intercity transportation hub of the departure city, reverse deduction is performed to obtain the departure time from the starting point to the intercity transportation hub of the departure city. At this point, at least one intercity travel chain including the traveler's departure time and travel path is obtained.

5. The departure time allocation method for comprehensively considering multi-modal transportation in intercity and intracity as claimed in claim 1, wherein The method of identifying the optimal intercity travel chain based on the pre-built intercity travel chain and obtaining the traveler's route from the starting point to the end point includes: Based on the pre-built inter-city travel chain, at least one travel chain is obtained, and the optimal inter-city travel chain is evaluated by generalized travel cost, where the generalized travel cost includes time cost and economic cost; The objective function aims to minimize the generalized travel costs of all travelers, and sets time cost and economic cost constraints to determine the optimal intercity travel chain; the expression of the objective function is: （1）； The objective function aims to minimize the generalized travel cost of all travelers; among which is the set of departure times of travelers; is the final output result, indicating the departure time of traveler ; is a known quantity, indicating the expected arrival time of traveler ; represents the generalized travel cost of traveler ; The constraints are: （2）； Among them, is an intermediate calculation variable representing the generalized cost of the railway network; is a known quantity representing the cost per unit time of the railway network; is an intermediate calculation variable representing the time spent by travelers on the railway network; is a known quantity representing the railway network from city to city fare; represents the railway network; represents the set of travel times, represents the time period in the set of travel times ; （3）； Among them, is an intermediate calculation variable representing the generalized cost of the air network; is a known quantity representing the cost per unit time of the air network; is an intermediate calculation variable representing the time spent by travelers on the air network; is a known quantity representing the airfare from city to city in the air network, represents the air network; （4）； （5）； Among them, is an intermediate calculation variable, representing the number of remaining queues on section section during the time period; is an intermediate calculation variable, representing the traffic volume on section section during the time period; is an intermediate calculation variable, representing the number of remaining queues on section at time section and are both congestion degree parameters and are fixed values; is an intermediate calculation variable, representing the travel time on section section during the time period; is a known quantity, representing the fastest travel time on section ; is a known quantity, representing the maximum traffic volume on section at time section and are both known quantities, representing parameters of section impedance; （6）； Among them, is an intermediate calculation variable representing the generalized cost of the highway network; is a known quantity representing the cost per unit time of the highway network; is an intermediate calculation variable representing the time spent by travelers on the highway network; （7）； Among them, is an intermediate calculation variable representing the generalized cost of the subway network; is a known quantity representing the cost per unit time of the subway network; is an intermediate calculation variable representing the time spent by travelers on the subway network; is a known quantity representing the subway network from station to station the fare, represents the subway network; （8）； Among them, is an intermediate calculation variable representing the generalized cost of the bus network; is a known quantity representing the cost per unit time of the bus network; is an intermediate calculation variable representing the time spent by travelers on the bus network; is a known quantity representing the fare from station to station in the bus network, represents the bus network; （9）； Among them, is an intermediate calculation variable representing the transfer cost between the bus network and the subway network; is a known quantity representing the unit time cost of transferring between the bus network and the subway network; is an intermediate calculation variable representing the time for a traveler to transfer between the bus network and the subway network; （10）； Among them, is an intermediate calculation variable, representing the traveler departing at the departure time 's generalized travel cost; is the known set of travel modes, including railways, aviation, highways, subways, buses, and cars, representing the travel mode; is the generalized cost corresponding to each travel mode, including the generalized cost of the railway network , the generalized cost of the aviation network , the generalized cost of the highway network , the generalized cost of the subway network , the generalized cost of the bus network , the transfer cost between the bus network and the subway network ; （11）； Among them, is an intermediate calculation variable, representing the generalized travel cost considering the arrival time penalty; is a known quantity, representing the weight of the generalized travel cost; is an intermediate calculation variable, representing the sum of the generalized travel costs of all travelers, represents the set of travelers; and are known quantities, representing the weights of arriving at the destination early and arriving at the destination late respectively; is an intermediate calculation variable, representing the time of arriving at the destination early, which is a non - negative value; is an intermediate calculation variable, representing the time of arriving at the destination late, which is also a non - negative value; （12）； Among them, is an intermediate calculation variable, representing the traveler at the departure time the total time cost of departure, that is, the travel time; is an intermediate calculation variable, representing the set of travel modes in which the sum of the travel times of all travel modes; （13）； Constraint (13) indicates that the actual arrival time of the traveler is equal to the departure time plus the total time cost starting from the departure time ; Formula (2) is the constraint for calculating the generalized cost of the railway network; Formula (3) is the constraint for calculating the generalized cost of the aviation network; Formula (4) is the constraint indicating the calculation method of the remaining queue; Formula (5) is the constraint for calculating the real-time road impedance; Formula (6) is the constraint for calculating the generalized cost of the highway network; Formulas (7) and (8) are the constraints for calculating the generalized costs of the subway network and the bus network respectively; Formula (9) is the constraint for calculating the generalized cost of the in-city transfer network; Formula (10) is the constraint for calculating the sum of the generalized travel costs of travelers; Formula (11) is the constraint considering the penalty for the arrival time, and the greater the difference between the actual arrival time and the expected arrival time, the higher the penalty; Formulas (12) and (13) indicate the constraint that the sum of the travel time and the departure time is the arrival time.

6. The departure time allocation method for comprehensively considering multi-modal transportation between cities and within cities according to claim 1, wherein The optimization of the optimal occurrence chain and the corresponding matching traveler departure time by using the iterative algorithm includes: Presetting the number of iterations. If the number of iterations is reached, stop the iteration and output the result of the last iterative calculation, which is the optimal departure time, transportation mode selection, transfer information, and expected arrival time. The specific iterative calculation method is as follows: Initialize the generalized travel cost of the intercity travel chain and set the number of iterations to 1. According to the expected arrival time of the traveler, reverse-deduce the best path for the traveler from the starting point to the end point, and obtain the objective function and several discrete departure times. Based on the obtained several discrete departure times, calculate the set of departure times and the set of objective functions corresponding to each discrete departure time. Select the traveler's departure time and travel path based on the minimum objective function value. Update the generalized travel cost of the intercity travel chain according to the selected traveler's departure time and travel path, and increment the number of iterations by 1. If the number of iterations does not reach the set upper limit, return to the step of calculating the set of departure times and the set of objective functions corresponding to each discrete departure time for the next iteration; if the number of iterations reaches the set upper limit, output the optimal departure time and travel path of the traveler.

7. A departure time allocation system that comprehensively considers multi-modal transportation in intercity and intra-city areas, characterized in that, It includes: An optimal intercity travel chain construction module configured to identify the optimal intercity travel chain based on the pre-constructed intercity travel chain, and obtain the route of the traveler from the starting point to the end point. An iteration module configured to optimize the optimal intercity travel chain and the corresponding matching traveler departure time by using the iterative algorithm to obtain the optimal departure time, transportation mode selection, transfer information, and expected arrival time.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, it implements the steps of the departure time allocation method for comprehensively considering intercity and intra-city multi-modal transportation according to any one of claims 1 to 6.

9. A computer device, characterized in that, It includes: A memory for storing a computer program. A processor for executing the computer program to implement the steps of the departure time allocation method for comprehensively considering intercity and intra-city multi-modal transportation according to any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that: When the computer program is executed by a processor, it implements the steps of the departure time allocation method for comprehensively considering intercity and intra-city multi-modal transportation according to any one of claims 1 to 6.

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