A vehicle dispatching system based on vehicle return reservation data

Abstract

The invention relates to the field of vehicle scheduling, and discloses a vehicle scheduling system based on vehicle return reservation data, comprising: a client, comprising a vehicle pick-up and return time selection module and a service point selection module; the vehicle pick-up and return time selection module pre-selects the vehicle pick-up and return time according to a default strategy according to the time when a user logs into the client; the service point selection module matches the service point according to the vehicle pick-up and return time; a vehicle status monitoring module, used for generating vehicle parameter data in real time; an analysis and planning module, used for receiving the user's scheduled vehicle pick-up and return time data and the vehicle pick-up and return quantity data of the scheduled service point, and judging whether the service point has inventory danger according to the scheduled vehicle pick-up and return time data and the vehicle pick-up and return quantity data of the scheduled service point, and generating a first scheduling task, judging and generating a second scheduling task by pre-selecting the vehicle pick-up and return quantity data and the real-time generated to-be-rented vehicle status data; and a scheduling module, receiving the first scheduling task and the second scheduling task and executing them.

Description

Technical Field

[0001] The invention relates to the field of vehicle dispatching, and in particular to a vehicle dispatching system based on vehicle return reservation data. Background Art

[0002] At present, with the rise of self-driving tourism, the online car rental industry has achieved tremendous development. Generally, online car rental platforms require users to manually select the time when entering the car rental platform, and the general method of manually selecting the pick-up and return time is used. Users can only enter the car selection interface after selecting, which will inevitably reduce the user's car selection efficiency and user experience.

[0003] At the same time, due to the different distribution of potential user groups in each service point, the frequency of renting and returning cars is high in some service points, while the frequency of renting cars is high and the frequency of returning cars is low in some service points, and the frequency of returning cars is high and the frequency of renting cars is low in some service points. This leads to an imbalance between the vehicle storage capacity and the rental demand of the service points, which requires frequent vehicle dispatch, increases operating costs and affects the user experience. Summary of the invention

[0004] The purpose of the present invention is to provide a vehicle dispatching system based on vehicle return reservation data to solve the above technical problems.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] A vehicle dispatching system based on vehicle return reservation data, comprising:

[0007] The client side includes a pick-up and return time selection module and a service point selection module;

[0008] The pick-up and return time selection module performs auxiliary selection of the pick-up and return time according to the default strategy based on the time when the user logs into the client, and generates the scheduled pick-up and return time data;

[0009] The service point selection module matches the service point according to the selected pick-up and return time, and generates the number of pick-up and return data at the scheduled service point;

[0010] The vehicle status monitoring module is used to detect various parameters of the vehicle in real time and generate vehicle parameter data;

[0011] The analysis and planning module is used to receive the user's scheduled pick-up and return time data and the number of cars picked up and returned at the scheduled service point, and determine whether the service point has inventory risks based on the scheduled pick-up and return time data and the number of cars picked up and returned at the scheduled service point, and generate a first scheduling task, and determine the inventory status when the user picks up the car based on the pre-picked and returned car number data and the real-time generated rental car status data, and generate a second scheduling task;

[0012] The scheduling module receives and executes the first scheduling task and the second scheduling task.

[0013] As a further technical solution, the working process of the pick-up and return time selection module is as follows:

[0014] Divide each day into the first time period, the second time period and the third time period according to the set time periods;

[0015] Matching the first time period with the first default return period, matching the second time period with the second default return period, and matching the third time period with the third default return period;

[0016] The first time period is from 0:00 to 08:00 on the same day; the first default pick-up and return time period is set from 10:00 on the same day to 10:00 two days later;

[0017] The second time period is from 08:00 to 16:00 on the same day. The second default pick-up and return time period is set to 2 hours later than the current time to two days later.

[0018] The third time period is from 16:00 on the current day to 00:00 on the next day, and the third default pick-up and return time is set from 10:00 on the next day to 10:00 three days later;

[0019] After the user logs in to the client, the judgment is made based on the login time and whether it is the first login;

[0020] If it is the first time, the client will set the pick-up and return time to the corresponding default pick-up and return time according to the time period of the login time;

[0021] If not, get the pick-up and return time selected by the user last time.

[0022] As a further technical solution, the working process of the analysis and planning module is as follows:

[0023] Get the inventory vehicle data of the current service point, as well as the scheduled vehicle pick-up data and scheduled vehicle return data for the day, analyze the scheduled vehicle pick-up data and scheduled vehicle return data, and obtain the dispatch status value F of the service point ij ;

[0024] Set the state scheduling value of the service point F ij and the preset first scheduling state threshold F ijmin and the second scheduling state threshold F ijmax Make comparisons;

[0025] If the scheduling state value F ij >Second scheduling state threshold F ijmax ;

[0026] If the scheduling state value Fij <First scheduling state threshold F ijmin ;

[0027] If one of the above conditions is met, the first scheduling task is generated;

[0028] If the second scheduling state threshold F ijmax ≤Scheduling status value F ij ≤ the first scheduling state threshold F ijmin , the vehicle parameter data is analyzed, and it is determined whether to generate a second scheduling task based on the analysis results.

[0029] As a further technical solution, the process of obtaining the scheduling state value is:

[0030] Merchants select service points on the map, and the area covered by the polygon formed by multiple service points is a service area;

[0031] Get the change curve of service point inventory vehicles over time Gradient division is carried out according to the service area to which the service point belongs;

[0032] By formula:

[0033]

[0034] Calculate the dispatch state value F of the jth service point ij ,

[0035] Where n is the number of service areas, i∈[1,j], is the standard change curve of the inventory vehicles of the jth service point in the i-th service area over time, R ij (t) is the change curve of the inventory vehicles of the jth service point in the i-th service area over time, δ ij is the reference coefficient of the inventory vehicle of the jth service point in the i-th service area, ΔR ij is the reference value of the inventory vehicles of the jth service point in the i-th service area, t i ~t i+1 is the selected time period.

[0036] As a further technical solution, the process of analyzing the vehicle parameter data is as follows:

[0037] Get the vehicle fuel information and maintenance information of each vehicle at the current service point, through the formula

[0038]

[0039] Calculate the status value M of the car to be rented n ;

[0040] Among them, θ1 and θ2 are proportional coefficients, Pn is the remaining fuel of each vehicle; K n To get the fuel volume of the vehicle; D n ΔD is the mileage of the vehicle in stock at the service point until the next maintenance; n0 The standard mileage of the next maintenance for the vehicles in stock at the service point;

[0041] Set the status value of the car to be rented to M n Compare with the preset threshold M0;

[0042] If M n ≤M0, it is predicted that the next user’s car rental driving requirements cannot be met, and a second scheduling task is generated for the vehicle.

[0043] As a further technical solution, the analysis and planning module is also used to calculate the rental status value M of the car to be rented. n Car pickup sequence allocation is performed, and the process of car pickup sequence allocation is as follows:

[0044] Get the number of vehicles to be picked up at the current service point N;

[0045] The inventory vehicles in the service point are sorted from high to low. n Sorting: select the top N people in the queue to be picked up;

[0046] Priority recommendations are made in order from high to low.

[0047] As a further technical solution, the process of the scheduling module executing the first scheduling task is:

[0048] The scheduling module receives a first scheduling task;

[0049] Get the dispatch status value F of each service point ij ;

[0050] Set the dispatch state value F of each service point ij and the preset first scheduling state threshold F ijmin and the second scheduling state threshold F ijmax Make comparisons and categorizes;

[0051] Class A is less than the first scheduling state threshold F ijmin Service point, Class B is greater than the second scheduling state threshold F ijmax ;

[0052] The A-type service point is judged as lacking vehicles, and the B-type service point is judged as having too many vehicles. The A-type service points and the B-type service points are sorted from large to small, and the dispatching state values ​​of the A-type and B-type service points and the preset first dispatching state threshold F are calculated respectively. ijmin Deviation value C A , C B ;

[0053] Match the A-type service points and the B-type service points according to the deviation value.

[0054] By formula:

[0055]

[0056] Calculate the matching degree W;

[0057] The matching degree W calculated between the current Class A service point and the qualified Class B service point is sorted from large to small, and the Class B service point ranked first is determined as the vehicle dispatch point for vehicle dispatch.

[0058] As a further technical solution, the process of the scheduling module executing the second scheduling task is:

[0059] The scheduling module receives the second scheduling task;

[0060] The vehicle generating the second dispatch task is marked, and then the vehicle is removed from the queue of vehicles to be picked up at the current service point;

[0061] The excluded vehicles will be refueled first;

[0062] Recalculate the rental vehicle status value M for the vehicle n , if M n >M0, then it will be re-listed in the waiting list;

[0063] Otherwise, the vehicle is maintained until the vehicle rental status value M n >M0, and then put it back into the queue for pickup.

[0064] Beneficial effects of the present invention:

[0065] (1) The current solution process, after entering the platform, can reduce the process of users manually selecting the time, so that users can easily complete the process of picking up and returning the car, improving the efficiency of the car rental platform and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] The present invention will be further described below in conjunction with the accompanying drawings.

[0067] Figure 1 A flow chart of a vehicle pick-up and return time selection module of the present invention;

[0068] Figure 2 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0069] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0070] See also Figure 1-Figure 2 As shown, the present invention is a vehicle dispatching system based on vehicle return reservation data, comprising:

[0071] The client side includes a pick-up and return time selection module and a service point selection module;

[0072] The pick-up and return time selection module performs auxiliary selection of the pick-up and return time according to the default strategy based on the time when the user logs into the client, and generates the scheduled pick-up and return time data;

[0073] The service point selection module matches the service point according to the selected pick-up and return time, and generates the number of pick-up and return data at the scheduled service point;

[0074] The vehicle status monitoring module is used to detect various parameters of the vehicle in real time and generate vehicle parameter data;

[0075] The analysis and planning module is used to receive the user's scheduled pick-up and return time data and the number of cars picked up and returned at the scheduled service point, and determine whether the service point has inventory risks based on the scheduled pick-up and return time data and the number of cars picked up and returned at the scheduled service point, and generate a first scheduling task, and determine the inventory status when the user picks up the car based on the pre-picked and returned car number data and the real-time generated rental car status data, and generate a second scheduling task;

[0076] The scheduling module receives and executes the first scheduling task and the second scheduling task.

[0077] The working process of the pick-up and return time selection module is as follows:

[0078] Divide each day into the first time period, the second time period and the third time period according to the set time periods;

[0079] Matching the first time period with the first default return period, matching the second time period with the second default return period, and matching the third time period with the third default return period;

[0080] The first time period is from 0:00 to 08:00 on the same day; the first default pick-up and return time period is set from 10:00 on the same day to 10:00 two days later;

[0081] The second time period is from 08:00 to 16:00 on the same day. The second default pick-up and return time period is set to 2 hours later than the current time to two days later.

[0082] The third time period is from 16:00 on the current day to 00:00 on the next day, and the third default pick-up and return time is set from 10:00 on the next day to 10:00 three days later;

[0083] After the user logs in to the client, the judgment is made based on the login time and whether it is the first login;

[0084] If it is the first time, the client will set the pick-up and return time to the corresponding default pick-up and return time according to the time period of the login time;

[0085] If not, get the pick-up and return time selected by the user last time.

[0086] Through the above technical solution, the user's login status is monitored, and the user's pick-up and return time is pushed by default according to the time when the user logs in to the client, reducing the process of users manually selecting time, so that users can easily complete the pick-up and return process, and improve the efficiency and user experience of the car rental platform. Specifically, each day is divided into a first time period, a second time period and a third time period according to a set time period; the first time period is matched with the first default return time period, the second time period is matched with the second default return time period, and the third time period is matched with the third default return time period; after the user logs in to the client, it is first determined whether it is the first login; if it is the first time, then according to which time period the login time is in, the client defaults to set the pick-up and return time to the corresponding default pick-up and return time. time period; if not, then obtain the pick-up and return time selected by the user last time; after the user makes fine adjustments to the pick-up and return reservation time, determine the pick-up and return reservation time and the location of the service point that is still open during the time period, and determine the location of the pick-up service point and the return service point on the map. The analysis and planning module receives the user's scheduled pick-up and return time data and the number of cars picked up and returned at the scheduled service point, and dynamically analyzes and judges the number of cars to be picked up and the number of cars to be parked at the service point based on the scheduled pick-up and return time data and the number of cars picked up and returned at the scheduled service point, so as to comprehensively discover and judge the risks in the pick-up and return process, and avoid the situation in which there is no parking space at the service point to be returned and no vehicles to be picked up at the service point to be picked up due to misjudgment in the actual work process.

[0087] As one implementation method, the working process of the analysis and planning module is as follows:

[0088] Get the inventory vehicle data of the current service point, as well as the scheduled vehicle pick-up data and scheduled vehicle return data for the day, analyze the scheduled vehicle pick-up data and scheduled vehicle return data, and obtain the dispatch status value F of the service point ij ;

[0089] Set the state scheduling value of the service point F ij and the preset first scheduling state threshold Fijmin and the second scheduling state threshold F ijmax Make comparisons;

[0090] If the scheduling state value F ij >Second scheduling state threshold F ijmax ;

[0091] If the scheduling state value F ij <First scheduling state threshold F ijmin ;

[0092] If one of the above conditions is met, the first scheduling task is generated;

[0093] If the second scheduling state threshold F ijmax ≤Scheduling status value F ij ≤ the first scheduling state threshold F ijmin , the vehicle parameter data is analyzed, and it is determined whether to generate a second scheduling task based on the analysis results.

[0094] The process of obtaining the scheduling status value is as follows:

[0095] Merchants select service points on the map, and the area covered by the polygon formed by multiple service points is a service area;

[0096] Get the change curve of service point inventory vehicles over time Gradient division is carried out according to the service area to which the service point belongs;

[0097] By formula:

[0098]

[0099] Calculate the dispatch state value F of the jth service point ij ,

[0100] Where n is the number of service areas, i∈[1,j], is the standard change curve of the inventory vehicles of the jth service point in the i-th service area over time, R ij (t) is the change curve of the inventory vehicles of the jth service point in the i-th service area over time, δ ij is the reference coefficient of the inventory vehicle of the jth service point in the i-th service area, which is obtained by selecting historical experimental data, ΔR ij is the reference value of the inventory vehicles of the jth service point in the i-th service area, t i ~t i+1 is the selected time period.

[0101] The above technical solution provides a working method of the analysis and planning module. Specifically, firstly, the reservation pick-up and return data and the inventory quantity of the service point are obtained based on the client, and the status scheduling value F of the service point is obtained after analyzing it. ij , and then the state scheduling value F of the service point ij and the preset first scheduling state threshold F ijmin and the second scheduling state threshold F ijmax The comparison is performed, where the second scheduling state threshold F ijmax The first scheduling state threshold F is set according to the inventory quantity upper limit of the service point. ijmin According to the inventory quantity of the service point, the first state is set, so when the scheduling state value F ij >Second scheduling state threshold F ijmax ; Scheduling status value F ij <First scheduling state threshold F ijmin In the case of , it means that the inventory vehicles in the service point are more or less in an abnormal state, so the first scheduling task is generated, and when the second scheduling state threshold F ijmax ≤Scheduling status value F ij ≤ the first scheduling state threshold F ijmin , it means that the inventory vehicles meet the basic requirements, but the status of the inventory vehicles needs further judgment;

[0102] Specifically, through the formula Calculate the dispatch status value F of the service point ij , where n is the number of service areas, i∈[1,j], is the standard change curve of the inventory vehicles of the jth service point in the i-th service area over time, R ij (t) is the change curve of the inventory vehicles of the jth service point in the i-th service area over time, δ ij is the reference coefficient of the inventory vehicle of the jth service point in the i-th service area, which is selected based on historical experimental data and empirical data, ΔR ij is the reference value of the inventory vehicles of the jth service point in the i-th service area, t i ~t i+1 is the selected time period. Obviously, by scheduling the state value F ij To judge the dispatching status of the service point, it can directly reflect the overall situation of the current service point and the entire service area. Then, it is compared with the first dispatching status threshold F ijmin and the second scheduling state threshold F ijmaxBy comparing, it is possible to accurately determine whether the current service point can undertake normal pick-up or return services, and to dispatch emergency vehicles through the dispatch module to meet the needs of each service point for appointment pick-up and return services, and to reflect the balance of pick-up and return services in each service area according to the dispatch status value in the service area. For example, when more than half of the service points in a service area are in the dispatch status value F ij Greater than the second scheduling state threshold F ijmax When , it means that the demand for returning cars in the service area is greater than the demand for picking up cars. On the contrary, when more than half of the service points in a service area are in a dispatching state value less than the first dispatching state threshold F ijmin , it means that the demand for picking up vehicles in this service area is greater than that for returning vehicles. Therefore, based on the above situation, the number of inventory vehicles in service areas with large demand for returning vehicles can be reduced, and the number of inventory vehicles in service areas with large demand for picking up vehicles can be increased, so as to meet the needs of users in different service areas while reducing vehicle dispatch costs.

[0103] The process of analyzing vehicle parameter data is as follows:

[0104] Get the vehicle fuel information and maintenance information of each vehicle at the current service point, through the formula

[0105]

[0106] Calculate the status value M of the car to be rented n ;

[0107] Among them, θ1 and θ2 are proportional coefficients, P n is the remaining fuel of each vehicle; K n To get the fuel volume of the vehicle; D n ΔD is the mileage of the vehicle in stock at the service point until the next maintenance; n0 The standard mileage of the next maintenance for the vehicles in stock at the service point;

[0108] Set the status value of the car to be rented to M n Compare with the preset threshold M0;

[0109] If M n ≤M0, it is predicted that the next user’s car rental driving requirements cannot be met, and a second scheduling task is generated for the vehicle.

[0110] The above technical solution provides a method for analyzing vehicle parameters. Specifically, the vehicle fuel quantity information and maintenance information of each vehicle are obtained through the on-board computer, and then the formula is used to calculate the vehicle fuel quantity information and maintenance information of each vehicle. Calculate the rental status value M of each vehicle n , where θ1 and θ2 are proportional coefficients, which are selected based on historical experimental data and empirical data, P n is the remaining fuel of each vehicle; Kn To get the fuel volume of the vehicle; D n ΔD is the mileage of the vehicle in stock at the service point until the next maintenance; n0 is the standard mileage of the next maintenance of the vehicle in the service point; it is obvious that the closer the mileage to the next maintenance and the less the remaining fuel in the vehicle, the worse the condition of the vehicle for the next rental task. Therefore, when the interval between pick-up and return is short, the status of the vehicles waiting to be rented in the service point can be accurately analyzed and judged, and the status value M of the vehicles waiting to be rented is set. n Compare with the preset threshold M0. If M n ≤M0, it is predicted that the next user's car rental driving requirements cannot be met, and a second scheduling task is generated for the vehicle, thereby avoiding potential crises in the process of car rental. At the same time, vehicles that cannot perform car rental tasks can also be eliminated, ensuring that the number of inventory vehicles is more accurate and effective.

[0111] The analysis and planning module is also used to calculate the state value M of the car to be rented. n Car pickup sequence allocation is performed, and the process of car pickup sequence allocation is as follows:

[0112] Get the number of vehicles to be picked up at the current service point N;

[0113] The inventory vehicles in the service point are sorted from high to low. n Sorting: select the top N people in the queue to be picked up;

[0114] Priority recommendations are made in order from high to low.

[0115] Through the above technical solution, according to the state value M of the car to be rented n To achieve intelligent allocation of vehicle pickup tasks, first obtain the number of vehicles to be picked up, and sort the inventory vehicles in the service point from high to low. n Sorting, select the top N people in the queue to be picked up; prioritize and recommend them in order from high to low. Obviously, vehicles in good condition can be recommended in a limited manner, thereby buying time for the remaining vehicles that do not meet the requirements to perform the second scheduling task, effectively ensuring the reasonable scheduling of vehicles within the service point and reducing the cost of remote scheduling of vehicles from other service points or service areas.

[0116] The process of the scheduling module executing the first scheduling task is:

[0117] The scheduling module receives a first scheduling task;

[0118] Get the dispatch status value F of each service point ij ;

[0119] Set the dispatch state value F of each service point ij and the preset first scheduling state threshold Fijmin and the second scheduling state threshold F ijmax Make comparisons and categorizes;

[0120] Class A is less than the first scheduling state threshold F ijmin Service point, Class B is greater than the second scheduling state threshold F ijmax ;

[0121] The A-type service point is judged as lacking vehicles, and the B-type service point is judged as having too many vehicles. The A-type service points and the B-type service points are sorted from large to small, and the dispatching state values ​​of the A-type and B-type service points and the preset first dispatching state threshold F are calculated respectively. ijmin Deviation value C A , C B ;

[0122] Match the A-type service points and the B-type service points according to the deviation value.

[0123] By formula:

[0124]

[0125] Calculate the matching degree W;

[0126] The matching degree W calculated between the current Class A service point and the qualified Class B service point is sorted from large to small, and the Class B service point ranked first is determined as the vehicle dispatch point for vehicle dispatch.

[0127] The above technical solution provides a method for executing a first scheduling task. Specifically, after receiving the first scheduling task, the scheduling module first obtains the scheduling state value F of each service point. ij ; Then the dispatch status value F of each service point ij and the preset first scheduling state threshold F ijmin and the second scheduling state threshold F ijmax Compare and classify; among them, Class A is less than the first scheduling state threshold F ijmin Service point, Class B is greater than the second scheduling state threshold F ijmax According to the above analysis and comparison results, it can be determined that the A-type service point is judged to be short of vehicles, and the B-type service point is judged to be too many vehicles. The A-type service points and the B-type service points are sorted from large to small, and the dispatching state values ​​of the A-type and B-type service points and the preset first dispatching state threshold F are calculated respectively. ijmin Deviation value C A , C B ; Then match the A-type service points and the B-type service points according to the deviation value, through the formula: The matching degree W is calculated; wherein d is the distance between the redundant vehicle service point and the current vehicle shortage service point. The matching degrees W calculated for the current Class A service point and the eligible Class B service points are sorted from large to small, and the Class B service point ranked first is determined as the vehicle dispatch point for vehicle dispatch. Obviously, through the above process, when a service point is short of vehicles, the service point that is closest and can meet the demand for the number of missing vehicles at one time can be selected, thereby minimizing the cost and efficiency when vehicle dispatch is required.

[0128] The process of the scheduling module executing the second scheduling task is:

[0129] The scheduling module receives the second scheduling task;

[0130] The vehicle generating the second dispatch task is marked, and then the vehicle is removed from the queue of vehicles to be picked up at the current service point;

[0131] The excluded vehicles will be refueled first;

[0132] Recalculate the rental vehicle status value M for the vehicle n , if M n >M0, then it will be re-listed in the waiting list;

[0133] Otherwise, the vehicle is maintained until the vehicle rental status value M n >M0, and then put it back into the queue for pickup.

[0134] Through the above technical solution, a method for executing the second scheduling task is provided. Specifically, the scheduling module first receives the second scheduling task; marks the vehicle generating the second scheduling task, and then removes the vehicle from the waiting-for-pickup sequence of the current service point; refuels the removed vehicle; recalculates the waiting-for-rental vehicle state value M for the vehicle; n , if M n >M0, then the vehicle will be re-listed in the waiting list; otherwise, the vehicle will be maintained until the waiting state value of the vehicle is M n >M0, and then re-include it in the waiting-for-pickup sequence; obviously, the above method can ensure that the vehicles in the waiting-for-pickup sequence are all effective vehicles that can meet the next pick-up demand, and can accurately sort the vehicles in the waiting-for-pickup sequence to ensure that the vehicle status is in the best state when picking up the vehicle, thereby improving user satisfaction and usage experience.

[0135] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A vehicle dispatching system based on vehicle return reservation data, characterized in that: include: The client side includes a pick-up and return time selection module and a service point selection module; The pick-up and return time selection module performs auxiliary selection of the pick-up and return time according to the default strategy based on the time when the user logs into the client, and generates the scheduled pick-up and return time data; The service point selection module matches the service point according to the selected pick-up and return time, and generates the number of pick-up and return data at the scheduled service point; The vehicle status monitoring module is used to detect various parameters of the vehicle in real time and generate vehicle parameter data; The analysis and planning module is used to receive the user's scheduled pick-up and return time data and the number of cars picked up and returned at the scheduled service point, and determine whether the service point has inventory risks based on the scheduled pick-up and return time data and the number of cars picked up and returned at the scheduled service point, and generate a first scheduling task, and determine the inventory status when the user picks up the car based on the pre-picked and returned car number data and the real-time generated rental car status data, and generate a second scheduling task; A scheduling module receives and executes the first scheduling task and the second scheduling task; The working process of the analysis and planning module is as follows: Get the inventory vehicle data of the current service point, as well as the scheduled vehicle pick-up data and scheduled vehicle return data for the day, analyze the scheduled vehicle pick-up data and scheduled vehicle return data, and obtain the dispatch status value F of the service point ij ; Set the state scheduling value of the service point F ij and the preset first scheduling state threshold F ijmin and the second scheduling state threshold F ijmax Make comparisons; If the scheduling state value F ij >Second scheduling state threshold F ijmax ; If the scheduling state value F ij <First scheduling state threshold F ijmin ; If one of the above conditions is met, the first scheduling task is generated; If the second scheduling state threshold F ijmax ≤Scheduling status value F ij ≤ the first scheduling state threshold F ijmin , the vehicle parameter data is analyzed, and it is determined whether to generate a second scheduling task according to the analysis result; The process of obtaining the scheduling status value is as follows: Merchants select service points on the map, and the area covered by the polygon formed by multiple service points is a service area; Get the change curve of service point inventory vehicles over time Gradient division is carried out according to the service area to which the service point belongs; By formula: Calculate the dispatch state value F of the jth service point ij , Where n is the number of service areas, i∈[1,j], is the standard change curve of the inventory vehicles of the jth service point in the i-th service area over time, R ij (t) is the change curve of the inventory vehicles of the jth service point in the i-th service area over time, δ ij is the reference coefficient of the inventory vehicle of the jth service point in the i-th service area, ΔR ij is the reference value of the inventory vehicles of the jth service point in the i-th service area, t i ~t i+1 is the selected time period.

2. The vehicle dispatching system based on vehicle return reservation data according to claim 1, characterized in that: The working process of the pick-up and return time selection module is as follows: Divide each day into the first time period, the second time period and the third time period according to the set time periods; Matching the first time period with the first default return period, matching the second time period with the second default return period, and matching the third time period with the third default return period; The first time period is from 0:00 to 08:00 on the same day; the first default pick-up and return time period is set from 10:00 on the same day to 10:00 two days later; The second time period is from 08:00 to 16:00 on the same day. The second default pick-up and return time period is set to 2 hours later than the current time to two days later. The third time period is from 16:00 on the current day to 00:00 on the next day, and the third default pick-up and return time is set from 10:00 on the next day to 10:00 three days later; After the user logs in to the client, the judgment is made based on the login time and whether it is the first login; If it is the first time, the client will set the pick-up and return time to the corresponding default pick-up and return time according to the time period of the login time; If not, get the pick-up and return time selected by the user last time.

3. The vehicle dispatching system based on vehicle return reservation data according to claim 1, characterized in that: The process of analyzing vehicle parameter data is as follows: Get the vehicle fuel and maintenance information of each vehicle at the current service point, and use the formula Calculate the status value M of the car to be rented n ; Among them, θ1 and θ2 are proportional coefficients, P n is the remaining fuel volume of each vehicle; K n To get the fuel volume of the vehicle; D n ΔD is the mileage of the vehicle in stock at the service point until the next maintenance; n0 The standard mileage of the next maintenance for the vehicles in stock at the service point; Set the status value of the car to be rented to M n Compare with the preset threshold M0; If M n ≤M0, it is predicted that the next user’s car rental driving requirements cannot be met, and a second scheduling task is generated for the vehicle.

4. The vehicle dispatching system based on vehicle return reservation data according to claim 3, characterized in that: The analysis and planning module is also used to calculate the state value M of the car to be rented. n Car pickup sequence allocation is performed, and the process of car pickup sequence allocation is as follows: Get the number of vehicles to be picked up at the current service point N; The inventory vehicles in the service point are sorted from high to low. n Sorting: select the top N people in the queue to be picked up; Priority recommendations are made in order from high to low.

5. The vehicle dispatching system based on vehicle return reservation data according to claim 1, characterized in that: The process of the scheduling module executing the first scheduling task is: The scheduling module receives a first scheduling task; Get the dispatch status value F of each service point ij ; Set the dispatch state value F of each service point ij and the preset first scheduling state threshold F ijmin and the second scheduling state threshold F ijmax Make comparisons and categorizes; Class A is less than the first scheduling state threshold F ijmin Service point, Class B is greater than the second scheduling state threshold F ijmax ; The A-type service point is judged as lacking vehicles, and the B-type service point is judged as having too many vehicles. The A-type service points and the B-type service points are sorted from large to small, and the dispatching state values ​​of the A-type and B-type service points and the preset first dispatching state threshold F are calculated respectively. ijmin Deviation value C A , C B ; Match the A-type service points and the B-type service points according to the deviation value. By formula: Calculate the matching degree W; The matching degree W calculated between the current Class A service point and the qualified Class B service point is sorted from large to small, and the Class B service point ranked first is determined as the vehicle dispatch point for vehicle dispatch.

6. The vehicle dispatching system based on vehicle return reservation data according to claim 3, characterized in that: The process of the scheduling module executing the second scheduling task is: The scheduling module receives the second scheduling task; The vehicle generating the second dispatch task is marked, and then the vehicle is removed from the queue of vehicles to be picked up at the current service point; The excluded vehicles will be refueled first; Recalculate the rental vehicle status value M for the vehicle n , if M n >M0, then it will be re-listed in the waiting list; Otherwise, the vehicle is maintained until the vehicle rental status value M n >M0, and then put it back into the queue for pickup.

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