A method and system for generating a vehicle operation plan based on market expansion

Abstract

The present invention belongs to the field of data processing technology, and provides a method and system for generating a vehicle operation plan based on market expansion. Before urban and rural carpooling enters the market, the market positioning of each urban area in the urban agglomeration is determined, and the suburban market expansion is carried out in stages according to the market positioning. The key to the first stage is the selection of the initial suburban market. The second stage mainly focuses on the expansion of the suburban market. In the third stage, capital investment and operation management gradually shift to refined management. The refined management method is to optimize the vehicle's origin, fare, reservation time and departure time deviation, and detour time threshold through order big data analysis and travel mode selection behavior investigation. The present invention systematically describes the management strategies and key points of urban and rural carpooling in various periods, which can promote the success of its operation.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and in particular relates to a method and system for generating a vehicle operation plan based on market expansion. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] In the existing technology, foreign countries started research on rural public transportation earlier and there are many operating routes, mainly divided into two modes: variable route type and demand response type (usually using 7-seater vehicles, similar to carpooling). At present, the relevant theoretical research is also very sufficient and mature, and there is a set of public transportation operation and scheduling methods suitable for foreign environments. Domestic research on demand-responsive public transportation operation mode started late, mainly focusing on route optimization and scheduling research, but did not consider the impact of market changes on operations. Summary of the invention

[0004] In order to solve at least one technical problem existing in the above-mentioned background technology, the present invention provides a method and system for generating a vehicle operation plan based on market expansion, which first determines the market positioning of each urban area in the urban agglomeration, and then carries out market expansion in the suburbs in stages according to the market positioning, and can formulate corresponding operation strategies in a targeted manner to improve passenger satisfaction while reducing operation costs.

[0005] In order to achieve the above object, the present invention adopts the following technical solution:

[0006] A first aspect of the present invention provides a method for generating a vehicle operation plan based on market expansion, comprising the following steps:

[0007] Get travel hotspot information for each given area;

[0008] Obtain the concentration of hot spots based on the travel hot spot information, compare the concentration of hot spots with a set threshold, and determine the market type of a given area;

[0009] Generate different operation plans for different market types. Generate carpooling operation plans for major markets and charter operation plans for auxiliary markets.

[0010] The process of generating the carpooling operation plan is as follows:

[0011] Divide the suburbs of the city into traffic zones and select target sub-regional markets based on the attractiveness between the zones and sub-regions and the convenience of public transportation between the zones and sub-regions;

[0012] Obtain past order information, divide the target sub-regional market, determine the departure point of the vehicle, build an objective function with maximum revenue and maximum passenger satisfaction, optimize ticket prices, reservation time thresholds, and detour time thresholds based on constraints, and generate an operation plan based on the optimization results.

[0013] A second aspect of the present invention provides a system for generating a vehicle operation plan based on market expansion, comprising:

[0014] The travel hotspot acquisition module is configured to: acquire travel hotspot information of each given area;

[0015] The market type determination module is configured to: obtain the concentration of hot spots according to the travel hot spot information, compare the concentration of hot spots with a set threshold, and determine the market type of a given area;

[0016] The operation plan generation module is configured to: generate different operation plans for different market types, generate a carpooling operation plan for the main market, and generate a chartered car operation plan for the auxiliary market;

[0017] The process of generating the carpooling operation plan is as follows:

[0018] Divide the suburbs of the city into traffic zones and select target sub-regional markets based on the attractiveness between the zones and sub-regions and the convenience of public transportation between the zones and sub-regions;

[0019] Obtain past order information, divide the target sub-regional market, determine the departure point of the vehicle, build an objective function with maximum revenue and maximum passenger satisfaction, optimize ticket prices, reservation time thresholds, and detour time thresholds based on constraints, and generate a carpooling operation plan based on the optimization results.

[0020] A third aspect of the present invention provides a computer-readable storage medium.

[0021] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps in the method for generating a vehicle operation plan based on market expansion as described above.

[0022] A fourth aspect of the present invention provides a computer device.

[0023] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps in the method for generating a vehicle operation plan based on market expansion as described above are implemented.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] Before urban and rural carpooling enters the market, the present invention first determines the market positioning of each urban area in the urban agglomeration, and carries out market expansion in the suburbs in stages based on the market positioning. The key to the first stage is the selection of the initial suburban market, and the selection basis includes: the urban area and the suburbs are attractive, and the public transportation convenience between the two is low. The second stage focuses on the expansion of the suburban market. In the above two stages, capital investment mainly tends to market promotion, and operation management is simple and extensive. In the third stage, capital investment and operation management gradually shift to refined management. The refined management method is to optimize the vehicle origin, fare, reservation time and departure time deviation, and detour time threshold through order big data analysis and travel mode selection behavior investigation.

[0026] Through the above scheme, corresponding operation strategies can be generated in a targeted manner to reduce operating costs and improve passenger satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0028] Figure 1 It is a flow chart of a method for generating a vehicle operation plan based on market expansion implemented in the present invention. DETAILED DESCRIPTION

[0029] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0030] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0031] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0032] Embodiment 1

[0033] like Figure 1 As shown, this embodiment provides a method for generating a vehicle operation plan based on market expansion, comprising the following steps:

[0034] Step 101: Obtain travel hotspot information of each given area;

[0035] Step 102: Obtain the concentration of the hotspots according to the travel hotspot information, compare the concentration of the hotspots with a set threshold, and determine the market type of the given area;

[0036] Step 103: Generate different operation plans for different market types. For the main market, generate a carpooling operation plan, and for the auxiliary market, generate a chartered car operation plan;

[0037] The process of generating the carpooling operation plan is as follows:

[0038] Divide the suburbs of the city into traffic zones and select target sub-regional markets based on the attractiveness between the zones and sub-regions and the convenience of public transportation between the zones and sub-regions;

[0039] Obtain past order information, divide the target sub-regional market, determine the departure point of the vehicle, build an objective function with maximum revenue and maximum passenger satisfaction, optimize ticket prices, reservation time thresholds, and detour time thresholds based on constraints, and generate a carpooling operation plan based on the optimization results.

[0040] Wherein, in step 101, the travel hotspot information of each given area includes: type (such as hospital, high-speed, hub, scenic spot and residential area, etc.), level (measured by travel frequency) and location.

[0041] In step 102, the concentration of the hot spots can be measured by kernel density, and the concentration of the hot spots is calculated by the formula:

[0042]

[0043] In the formula, O i represents the kernel density of region i, K j is the weight value of hotspot j, which is assigned according to the travel frequency, d ij is the distance between the center of region i and hotspot j, r is the bandwidth of region i, and n is the number of hotspots within the bandwidth r.

[0044] Compare the concentration of the hotspot with the threshold. If the concentration of the hotspot is greater than the threshold, the area is determined to be the main market for sub-regional travel and a carpooling operation mode is adopted. Otherwise, the area is an auxiliary market and a chartered car operation mode is carried out.

[0045] In step 103, the calculation formula of the attraction between the region and the sub-region is:

[0046]

[0047] Where Y ig represents the attraction value between region i and sub-region g, P i and Pg denote the population density of region i and sub-region g, E i and E g They represent the per capita GDP of region i and sub-region g respectively, and dig represents the spatial Euclidean distance between region i and sub-region g.

[0048] In order to facilitate understanding of the technical solution of the present invention, the technical solution of the present invention is further explained by taking the given area as an urban area and the sub-area as a suburban area as an example.

[0049] Among them, the attraction Y between urban area i and suburban area g ig Compared with the attraction threshold Y0, the suburb g whose attraction between urban area i (i=1,2…n) and suburb g is greater than the attraction threshold is selected to form a set J={1,2,…j}; at the same time, the suburb with worse public transportation convenience between urban area i and suburb g is more suitable as the initial suburban market.

[0050] The calculation formula for the convenience of public transportation between the urban area and the suburbs is:

[0051]

[0052] In the formula, n is the number of hotspots in region i; K j is the weight value of hotspot j; is the network accessibility between hotspot j in region i and the long-distance bus hub in region i; Q i-g is the network accessibility between the long-distance bus hubs in region i and sub-region g; Q g is the network accessibility between sub-region g and its adjacent long-distance bus hub.

[0053] The network accessibility calculation formula between the hotspot j in area i and the long-distance bus hub in area i is:

[0054]

[0055] In the formula, is the number of bus stops that can be reached by hotspot j in region i within a certain travel threshold; is the distance between hotspot j in area i and bus stop u in area i; is the network accessibility between bus station u in area i and the long-distance bus hub in area i. is the number of bus routes in area i that stop at bus station u and can reach the long-distance bus hub by direct or transfer; a s is the weight of the sth influencing factor; S is the number of factors considered (such as departure frequency, line non-linear coefficient, operating speed, etc.); is the value of the sth influencing factor of the mth bus line passing through bus stop u in area i.

[0056] Q i-g and Q g The calculation principle is the same as that of , which will not be described here.

[0057] In step 103, the location of the departure point of the vehicle is selected based on the previous order information, and the target market is divided by applying the k-means clustering analysis method, and the cluster center is the departure point of the vehicle.

[0058] The objective function includes an operator revenue function, a penalty function for deviations between reservation time and departure time, and a penalty function for detour time;

[0059] The expression is:

[0060] max[α1·f1-α2·f2(T i ′)-α3·f3(T i ″)](5)

[0061] Among them, α1, α2 and α3 are the weights of the corresponding functions, f1 is the operator's profit function, f2 is the penalty function of the deviation between the appointment time and the departure time, and f3 is the penalty function of the detour time; T′ is the total deviation time between the appointment time and the departure time, and T″ is the total detour time of the fleet.

[0062] The calculation formula for the total deviation time T′ between the reservation time and the departure time is:

[0063]

[0064] Where, t ik is the boarding time of the passenger of order i taking vehicle k, represents the booking time of the passenger of order i;

[0065] The calculation formula for the total detour time T″ of the fleet is:

[0066]

[0067] In the formula, represents the arrival time of the passenger of order i taking vehicle k, Represents the direct travel time for passengers of order i.

[0068] The operator's profit function is:

[0069]

[0070] In the formula, J 0 is the carpooling fare, D 0 For carpool passengers, Fixed cost for the driver, is the total fuel cost of the fleet, is depreciation expense;

[0071] Carpooling passengers D 0 It is expressed as:

[0072]

[0073] Where D all represents the total travel demand of passengers, p 0 represents the probability of choosing carpooling, H represents the total number of travel modes for urban and rural travel (depending on the development of urban and rural transportation, travel modes may include private cars, ordinary buses, carpooling, etc.), J h represents the fare of the h-th mode of travel. When h=0, it is the carpooling fare. h It represents the total time of the h-th travel mode. When h=0, it is the total time of carpooling.

[0074] Total fuel costs for the fleet The calculation formula is:

[0075]

[0076] Where, d ijk represents the delivery distance between vehicle k and stop points i and j; x ijk Represents a variable. If vehicle k passes through arc (i, j), the variable is 1, otherwise the variable is 0.

[0077] The constraints include three categories: route constraints, passenger capacity constraints, and time constraints, as follows:

[0078] A. The route constraints include:

[0079] (1) Ensure that each customer of an order has only one vehicle path to serve him, which is the vehicle in-and-out balance constraint:

[0080]

[0081] (2) Ensure that when a vehicle is activated, there is only one service route, and its starting and ending points are both distribution centers:

[0082]

[0083] (3) Ensure that each customer is served by a specific vehicle:

[0084]

[0085] (4) Branch elimination constraints:

[0086]

[0087] B. The passenger capacity constraints include:

[0088] (1) Changes in vehicle load during delivery:

[0089]

[0090] (2) The capacity of the vehicle at any node cannot exceed the vehicle capacity limit:

[0091]

[0092] C. The time constraints include:

[0093] (1) The vehicle carries passengers within the specified time interval:

[0094]

[0095] (2) Time variation relationship between adjacent delivery points:

[0096]

[0097] (3) The detour time of vehicle k transporting passenger order i cannot exceed the prescribed upper limit:

[0098]

[0099] Embodiment 2

[0100] This embodiment provides a system for generating a vehicle operation plan based on market expansion, including:

[0101] The travel hotspot acquisition module is configured to: acquire travel hotspot information of each given area;

[0102] The market type determination module is configured to: obtain the concentration of hot spots according to the travel hot spot information, compare the concentration of hot spots with a set threshold, and determine the market type of a given area;

[0103] The operation plan generation module is configured to: generate different operation plans for different market types, generate a carpooling operation plan for the main market, and generate a chartered car operation plan for the auxiliary market;

[0104] The process of generating the carpooling operation plan is as follows:

[0105] Divide the suburbs of the city into traffic zones and select target sub-regional markets based on the attractiveness between the zones and sub-regions and the convenience of public transportation between the zones and sub-regions;

[0106] Obtain past order information, divide the target sub-regional market, determine the departure point of the vehicle, build an objective function with maximum revenue and maximum passenger satisfaction, optimize ticket prices, reservation time thresholds, and detour time thresholds based on constraints, and generate a carpooling operation plan based on the optimization results.

[0107] Embodiment 3

[0108] This embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the method for generating a vehicle operation plan based on market expansion as described above.

[0109] Embodiment 4

[0110] This embodiment provides a computer device, including 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 steps in the method for generating a vehicle operation plan based on market expansion as described above are implemented.

[0111] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, 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 and optical storage, etc.) containing computer-usable program code.

[0112] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (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 the 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.

[0113] 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 1A function specified in one or more boxes.

[0114] 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.

[0115] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0116] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for generating a vehicle operation plan based on market expansion, characterized in that: The steps include: Get travel hotspot information for each given area; Obtain the concentration of hot spots based on the travel hot spot information, compare the concentration of hot spots with a set threshold, and determine the market type of a given area; Generate different operation plans for different market types. Generate carpooling operation plans for major markets and charter operation plans for auxiliary markets. The generation process of the carpooling operation plan is as follows: Divide the sub-regions of a given area into traffic zones, and select the target sub-regional markets based on the attractiveness between the given area and the sub-regions and the convenience of public transportation between the given area and the sub-regions; Among them, the given area is the urban area and the sub-area is the suburban area; Obtain past order information, divide the target sub-regional market, determine the origin of the vehicle, build an objective function with maximum revenue and maximum passenger satisfaction, optimize the fare, reservation time threshold, and detour time threshold based on constraints, and generate an operation plan based on the optimization results; The calculation formula for the hotspot concentration is: In the formula, O i represents the kernel density of a given region i, K j is the weight value of hotspot j, which is assigned according to the travel frequency, d ij is the distance between the center of the given region i and the hotspot j, r is the bandwidth of the given region i, and n is the number of hotspots within the bandwidth r; The calculation formula of the attraction between the given area and the sub-area is: Where Y ig represents the attraction value between a given region i and a subregion g, P i and P g Represent the population density of a given region i and a sub-region g, E i and E g They represent the per capita GDP of a given region i and a sub-region g, respectively, and dig represents the spatial Euclidean distance between a given region i and a sub-region g; The calculation formula for the convenience of public transportation in the given area and sub-areas is: Where n is the number of hotspots in a given area i; K j is the weight value of hotspot j; is the network accessibility between hotspot j in a given region i and the long-distance bus hub in a given region i; Q i-g is the network accessibility between the long-distance bus hubs in a given area i and sub-area g; Q g is the network accessibility between sub-region g and its adjacent long-distance bus hub.

2. The method for generating a vehicle operation plan based on market expansion according to claim 1, characterized in that: The location of the departure point of the vehicle is selected based on past order information and the target market is divided using the k-means clustering analysis method, and the cluster center is the departure point of the vehicle.

3. The method for generating a vehicle operation plan based on market expansion according to claim 1, characterized in that: The objective function includes an operator's revenue function, a penalty function for deviations between reservation time and departure time, and a penalty function for detour time.

4. The method for generating a vehicle operation plan based on market expansion according to claim 1, characterized in that: The constraints include route constraints, passenger capacity constraints and time constraints.

5. A system for generating a vehicle operation plan based on market expansion, using a method for generating a vehicle operation plan based on market expansion as described in any one of claims 1 to 3, characterized in that: include: The travel hotspot acquisition module is configured to: acquire travel hotspot information of each given area; The market type determination module is configured to: obtain the concentration of hot spots according to the travel hot spot information, compare the concentration of hot spots with a set threshold, and determine the market type of a given area; The operation plan generation module is configured to: generate different operation plans for different market types, generate a carpooling operation plan for the main market, and generate a chartered car operation plan for the auxiliary market; The process of generating the carpooling operation plan is as follows: Divide the given sub-region into traffic zones, and select the target sub-region market according to the attractiveness between the given region and the sub-region and the convenience of public transportation between the given region and the sub-region; wherein the given region is the urban area and the sub-region is the suburb; Obtain past order information, divide the target sub-regional market, determine the departure point of the vehicle, build an objective function with maximum revenue and maximum passenger satisfaction, optimize ticket prices, reservation time thresholds, and detour time thresholds based on constraints, and generate a carpooling operation plan based on the optimization results.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in a method for generating a vehicle operation plan based on market expansion as described in any one of claims 1 to 4 are implemented.

7. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the method for generating a vehicle operation plan based on market expansion as described in any one of claims 1-4 are implemented.

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