Order allocation method and system

Abstract

The invention provides an order allocation method and system. The method comprises the following steps: continuously monitoring a new mobile charging call order; order features of the mobile charging call order are analyzed; matching an optimal mobile charging calling vehicle from a mobile charging vehicle network based on order features; and distributing the mobile charging call order to the optimal mobile charging call vehicle. According to the order distribution method and system, the new first mobile charging call order is continuously monitored, the optimal mobile charging call vehicle is matched from the mobile charging vehicle network based on the order characteristics of the first mobile charging call order, the first mobile charging call order is distributed to the optimal mobile charging call vehicle, and order matching and distribution are rapidly performed. The method greatly improves the order distribution efficiency, and is especially suitable for unmanned mobile charging vehicles.

Description

Technical Field

[0001] The present invention relates to the technical field of mobile charging order distribution, and in particular to an order distribution method and system. Background Art

[0002] At present, the delivery of mobile charging call orders of mobile charging vehicles adopts the grab order mode, that is, when the user of the electric vehicle places an order for mobile charging call, multiple mobile charging vehicle drivers grab the order for the mobile charging call. However, due to the influence of factors such as the subjectivity of the drivers of the mobile charging vehicles, the order delivery efficiency of the grab order mode is low. In addition, the grab order mode cannot be applied to unmanned mobile charging vehicles.

[0003] Therefore, a solution is urgently needed. Summary of the invention

[0004] One of the purposes of the present invention is to provide an order distribution method, which continuously monitors new first mobile charging call orders, matches the best mobile charging call vehicle from the mobile charging vehicle network based on the order characteristics of the first mobile charging call order, and dispatches the first mobile charging call order to the best mobile charging call vehicle, so as to quickly match and dispatch the order, greatly improve the order dispatch efficiency, and is particularly suitable for unmanned mobile charging vehicles.

[0005] An order allocation method provided by an embodiment of the present invention includes:

[0006] Keep monitoring new First Mobile charging call orders;

[0007] parsing order features of the first mobile charging call order;

[0008] Based on the order characteristics, the best mobile charging call vehicle is matched from the mobile charging vehicle network;

[0009] The first mobile charging call order is dispatched to the best mobile charging call vehicle.

[0010] Preferably, the order allocation method further includes:

[0011] When the mobile charging vehicle actively inputs a dispatch request for a number of times exceeding a threshold number of times and has not been dispatched for a period exceeding a first time threshold, obtaining vehicle information of the mobile charging vehicle;

[0012] Analyze the information characteristics of vehicle information;

[0013] Based on information features, mobile charging induction is performed;

[0014] When the second mobile charging call order is induced, the second mobile charging call order is dispatched to the mobile charging vehicle.

[0015] Preferably, the mobile charging induction based on the information feature includes:

[0016] Extract the single position and charging capacity of the mobile charging vehicle such as parking among the information features;

[0017] Searching for a first target vehicle; the straight-line distance between the current position of the first target vehicle and the parking position is less than a distance threshold;

[0018] The first target vehicle whose future driving route has a local route that meets the local route condition is used as the second target vehicle;

[0019] Predict the success probability of induction of the second target vehicle;

[0020] Based on the batch division table, the second target vehicle is divided into induction batches of multiple batch levels according to the induction success probability;

[0021] Performing simultaneous mobile charging induction on the second target vehicles in the same induction batch from large to small according to the batch level; wherein, when the second target vehicles in an induction batch that is being induced have not confirmed to accept the induction for a period exceeding the second time threshold, performing simultaneous mobile charging induction on the second target vehicles in the induction batch of the next batch level;

[0022] Among them, local route conditions include:

[0023] The remaining power of the first target vehicle when arriving at the starting point of the local route is less than the power threshold;

[0024] and,

[0025] The local route is a congested section route or the route similarity between each stop route in the same historical stop route set of the first target vehicle is greater than the similarity threshold; the stop locations of each stop route in the same historical stop route set are the same, and the difference in stop time is less than the first difference threshold;

[0026] and,

[0027] The proportion of local routes falling within the target range is greater than the ratio threshold; the smallest encirclement on the city map includes a single location such as parking, the current location and the starting point of the route;

[0028] and,

[0029] The charging capacity meets the remaining power.

[0030] Preferably, the predicting the induction success probability of the second target vehicle includes:

[0031] Performing feature description on the multimodal prediction basis of the second target vehicle to obtain a feature description vector;

[0032] Determine the induction success probability corresponding to the feature description vector from the probability library.

[0033] Preferably, the order allocation method further includes:

[0034] When a third mobile charging call order from a third-party platform is monitored, respectively analyzing the first credibility of the third-party platform and the second credibility of the third mobile charging call order;

[0035] Based on the mobile charging vehicle network, determine the advance amount of the standby mobile charging vehicle and the successful charging docking time of the third mobile charging call order;

[0036] Assigning a first credibility preset first weight to obtain a first target value;

[0037] Assigning a second preset weight to the second credibility to obtain a second target value;

[0038] Determine the waiting time corresponding to the sum of the first target value and the second target value from the waiting time library;

[0039] When the waiting time is less than or equal to the advance amount or the difference between the waiting time and the advance amount is less than or equal to the second difference threshold, after waiting for the waiting time, the third mobile charging call order is dispatched to the standby mobile charging vehicle;

[0040] When the difference between the waiting time and the advance amount is greater than a second difference threshold, the third mobile charging call order is dispatched to the standby mobile charging vehicle after waiting for the average value of the waiting time and the advance amount.

[0041] An embodiment of the present invention provides an order distribution system, comprising:

[0042] An order monitoring module, used for continuously monitoring new first mobile charging call orders;

[0043] A feature analysis module, used for analyzing the order features of the first mobile charging call order;

[0044] A vehicle matching module is used to match the best mobile charging call vehicle from the mobile charging vehicle network based on order characteristics;

[0045] The order dispatching module is used to dispatch the first mobile charging call order to the best mobile charging call vehicle.

[0046] Preferably, the order distribution system further includes:

[0047] Charge induction module for:

[0048] When the mobile charging vehicle actively inputs a dispatch request for a number of times exceeding a threshold number of times and has not been dispatched for a period exceeding a first time threshold, obtaining vehicle information of the mobile charging vehicle;

[0049] Analyze the information characteristics of vehicle information;

[0050] Based on information features, mobile charging induction is performed;

[0051] When the second mobile charging call order is induced, the second mobile charging call order is dispatched to the mobile charging vehicle.

[0052] Preferably, the charging induction module performs mobile charging induction based on information features, including:

[0053] Extract the single position and charging capacity of the mobile charging vehicle such as parking among the information features;

[0054] Searching for a first target vehicle; the straight-line distance between the current position of the first target vehicle and the parking position is less than a distance threshold;

[0055] The first target vehicle whose future driving route has a local route that meets the local route condition is used as the second target vehicle;

[0056] Predict the success probability of induction of the second target vehicle;

[0057] Based on the batch division table, the second target vehicle is divided into induction batches of multiple batch levels according to the induction success probability;

[0058] Performing simultaneous mobile charging induction on the second target vehicles in the same induction batch from large to small according to the batch level; wherein, when the second target vehicles in an induction batch that is being induced have not confirmed to accept the induction for a period exceeding the second time threshold, performing simultaneous mobile charging induction on the second target vehicles in the induction batch of the next batch level;

[0059] Among them, local route conditions include:

[0060] The remaining power of the first target vehicle when arriving at the starting point of the local route is less than the power threshold;

[0061] and,

[0062] The local route is a congested section route or the route similarity between each stop route in the same historical stop route set of the first target vehicle is greater than the similarity threshold; the stop locations of each stop route in the same historical stop route set are the same, and the difference in stop time is less than the first difference threshold;

[0063] and,

[0064] The proportion of local routes falling within the target range is greater than the ratio threshold; the smallest encirclement on the city map includes a single location such as parking, the current location and the starting point of the route;

[0065] and,

[0066] The charging capacity meets the remaining power.

[0067] Preferably, the charging induction module predicts the probability of successful induction of the second target vehicle, including:

[0068] Performing feature description on the multimodal prediction basis of the second target vehicle to obtain a feature description vector;

[0069] Determine the induction success probability corresponding to the feature description vector from the probability library.

[0070] Preferably, the order distribution system further includes:

[0071] Third-party service modules for:

[0072] When a third mobile charging call order from a third-party platform is monitored, respectively analyzing the first credibility of the third-party platform and the second credibility of the third mobile charging call order;

[0073] Based on the mobile charging vehicle network, determine the advance amount of the standby mobile charging vehicle and the successful charging docking time of the third mobile charging call order;

[0074] Assigning a first credibility preset first weight to obtain a first target value;

[0075] Assigning a second preset weight to the second credibility to obtain a second target value;

[0076] Determine the waiting time corresponding to the sum of the first target value and the second target value from the waiting time library;

[0077] When the waiting time is less than or equal to the advance amount or the difference between the waiting time and the advance amount is less than or equal to the second difference threshold, after waiting for the waiting time, the third mobile charging call order is dispatched to the standby mobile charging vehicle;

[0078] When the difference between the waiting time and the advance amount is greater than a second difference threshold, the third mobile charging call order is dispatched to the standby mobile charging vehicle after waiting for the average value of the waiting time and the advance amount.

[0079] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description, claims, and drawings.

[0080] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0082] Figure 1 A schematic diagram of an order allocation method in an embodiment of the present invention;

[0083] Figure 2 It is a schematic diagram of an order distribution system in an embodiment of the present invention. DETAILED DESCRIPTION

[0084] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0085] The embodiment of the present invention provides an order allocation method, such as Figure 1 As shown, including:

[0086] S1, continuously monitor new first mobile charging call orders;

[0087] S2. analyzing order features of the first mobile charging call order;

[0088] S3, based on the order characteristics, matching the best mobile charging call vehicle from the mobile charging vehicle network;

[0089] S4. Dispatching the first mobile charging call order to the best mobile charging call vehicle.

[0090] The first mobile charging call order is newly placed by the user of the electric vehicle; the order features include: charging appointment time, charging appointment location, required charging amount, etc.; there are a large number of mobile charging vehicles in the mobile charging vehicle network, and the vehicle status includes: vehicle location, rechargeable charging amount, etc.; based on the order features, the best mobile charging call vehicle is matched from the mobile charging vehicle network, and the matching mechanism considerations can be considered from the distance between the vehicle location of the mobile charging vehicle and the charging appointment location, whether the rechargeable charging amount of the mobile charging vehicle can meet the required charging amount, etc. The specific matching mechanism can be set in advance by technical personnel according to actual needs; when the best mobile charging call vehicle is matched, the first mobile charging call order is dispatched to the best mobile charging call vehicle.

[0091] This application continuously monitors new first mobile charging call orders, matches the best mobile charging call vehicle from the mobile charging vehicle network based on the order characteristics of the first mobile charging call order, and dispatches the first mobile charging call order to the best mobile charging call vehicle, quickly matching and dispatching orders, greatly improving the order dispatch efficiency, and is particularly suitable for unmanned mobile charging vehicles.

[0092] In one embodiment, the order allocation method further includes:

[0093] When the mobile charging vehicle actively inputs a dispatch request for a number of times exceeding the number threshold and has not been dispatched for a period exceeding the first time threshold, the vehicle information of the mobile charging vehicle is obtained; the number threshold can be 3; the first time threshold can be 10 minutes; when the mobile charging vehicle actively inputs a dispatch request, it indicates that the mobile charging vehicle wants to perform mobile charging operations; when the mobile charging vehicle actively inputs a dispatch request for a number of times exceeding the number threshold and has not been dispatched for a period exceeding the first time threshold, it indicates that the mobile charging vehicle is in urgent need of dispatch;

[0094] Analyze the information characteristics of vehicle information;

[0095] Based on information features, mobile charging induction is performed;

[0096] When a second mobile charging call order is induced, the second mobile charging call order is dispatched to the mobile charging vehicle. The second mobile charging call order is an order placed by an induced user of an electric vehicle who needs to perform mobile charging;

[0097] The mobile charging induction based on the information feature includes:

[0098] Extract the parking and waiting positions and charging capacity of the mobile charging vehicle in the information features; when the mobile charging vehicle is not performing mobile charging operations, in order to save costs, it will stop and wait at a certain location, that is, a parking and waiting position is generated; charging capacity refers to the amount of charge that can be charged, etc.;

[0099] Searching for a first target vehicle; the straight-line distance between the current position of the first target vehicle and a single position such as a parking vehicle is less than a distance threshold; the distance threshold may be 1.5 kilometers; a mobile charging vehicle is more suitable for mobile charging of the first target vehicle;

[0100] The first target vehicle whose future driving route has a local route that meets the local route condition is used as the second target vehicle; based on the local route that meets the local route condition, the second target vehicle that is more suitable for mobile charging is selected as a mobile charging vehicle;

[0101] Predict the success probability of induction of the second target vehicle; the success probability of induction refers to the probability that the second target vehicle confirms acceptance of induction after the mobile charging induction is performed on the second target vehicle, that is, the induction is successful;

[0102] Based on the batch division table, the second target vehicle is divided into induced batches of multiple batch levels according to the probability of successful induction; the batch division table includes multiple groups of one-to-one corresponding batch levels and corresponding probability intervals, and the larger the left boundary value of the probability interval, the larger the corresponding batch level; the probability intervals corresponding to each batch level are adjacent to each other but do not overlap; when the second target vehicle is divided into batch levels according to the probability of successful induction, the probability interval where the probability of successful induction is located is determined, and the batch level corresponding to the probability interval where the second target vehicle is located is assigned, and the second target vehicles assigned the same batch level are combined into an induced batch;

[0103] The second target vehicles in the same induction batch are induced to move and charge simultaneously according to the batch level from large to small; wherein, when the second target vehicles in an induction batch that is induced do not confirm to accept the induction for a period exceeding the second time threshold, the second target vehicles in the induction batch of the next batch level are induced to move and charge simultaneously; the larger the batch level, the higher the priority of the induction, and the second target vehicles in the same induction batch are induced to move and charge simultaneously according to the batch level from large to small, so that the induction is successful as quickly as possible; the second time threshold may be 100 seconds;

[0104] Among them, local route conditions include:

[0105] The remaining power of the first target vehicle when it arrives at the starting point of the local route is less than the power threshold; the electric vehicle not only performs route planning, but also performs power usage prediction, so the remaining power of the first target vehicle when it arrives at the starting point of the local route can be determined, and the power threshold can be 30% (the power of the electric vehicle is expressed in the form of a percentage of usage); when this local route condition is met, it means that the first target vehicle needs to be recharged when it arrives at the starting point of the local route;

[0106] and,

[0107] The local route is a congested section route or a route similarity between each stop route in the same historical stop route set of the first target vehicle is greater than the similarity threshold; the stop locations of the stop routes in the same historical stop route set are the same and the difference in stop time is less than the first difference threshold; the stop route is a 300-meter continuous route generated before and after arriving at a stop location (for example, a vegetable market, a supermarket, an office building, etc.) after arriving at the stop location in history (for example, 3 hours); the similarity threshold can be 75%; the congested section route is a route where the vehicle is congested The route is congested and the estimated travel time is longer than, for example, 20 minutes; under the premise of needing to replenish energy, when the local route is a congested route, it means that the user of the electric vehicle can replenish energy instead of wasting it in the traffic jam. When the route similarity between each stop route in the same historical stop route set of the first target vehicle is greater than the similarity threshold, it means that the first target vehicle may stop again at this time, and the time can be used for replenishment; the first difference threshold can be half an hour; the stop time difference is the difference between the stop times of each stop route in the same historical stop route set;

[0108] and,

[0109] The proportion of local routes falling within the target range is greater than the ratio threshold; the minimum encirclement on the city map includes a single location such as parking, the current location and the starting point of the route; the proportion of local routes falling within the target range is the ratio of the route length of the local routes falling within the target range to the total route length of the local routes; the ratio threshold can be 1 / 8; the greater the route proportion, the lower the cost of electric vehicles choosing to connect with mobile charging vehicles for energy replenishment and the cost of mobile charging vehicles for mobile charging and energy replenishment for electric vehicles;

[0110] and,

[0111] Charging capacity meets the remaining power. Secondly, the charging capacity of the mobile charging vehicle needs to meet the remaining power.

[0112] Generally, there may be a situation in a city where a mobile charging vehicle has not performed mobile charging operations for a long time. At this time, if the mobile charging vehicle is not dispatched in time, it may lead to a waste of mobile charging resources and increase the cost of mobile charging. When solving this problem, the embodiment of the present invention performs mobile charging induction based on the information characteristics of the vehicle information of the mobile charging vehicle. When the second mobile charging call order is induced, the second mobile charging call order is dispatched to the mobile charging vehicle.

[0113] Secondly, when conducting mobile charging induction, the first target vehicle is searched first and preliminarily screened. Then the second target vehicle is determined and further screened, and local route conditions are introduced to ensure the suitability of the screened second target vehicle. Finally, the second target vehicles in the same induction batch are simultaneously induced to perform mobile charging according to the batch level from large to small, which greatly improves the rationality, accuracy and comprehensiveness of mobile charging induction.

[0114] In one embodiment, the predicting the probability of successful induction of the second target vehicle includes:

[0115] Performing feature description on the multimodal prediction basis of the second target vehicle to obtain a feature description vector; the multimodal prediction basis includes: the number of times of receiving mobile charging induction in history, etc.;

[0116] The induction success probability corresponding to the feature description vector is determined from the probability library. The probability library is preset with the induction success probabilities corresponding to different feature description vectors.

[0117] In one embodiment, the order allocation method further includes:

[0118] When a third mobile charging call order from a third-party platform is monitored, the first credibility of the third-party platform and the second credibility of the third mobile charging call order are analyzed respectively; the third-party platform refers to a platform that outsources mobile charging call orders; the third mobile charging call order is a mobile charging call order outsourced by the third-party platform; the first credibility of the third-party platform represents the credibility of the third-party platform, and the first credibility is related to the number and frequency of real mobile charging call orders provided by the third-party platform in history; the second credibility represents the credibility of the third mobile charging call order, and the second credibility is related to the completeness of the information of the third mobile charging call order;

[0119] Based on the mobile charging vehicle network, determine the advance amount of the standby mobile charging vehicle and the successful charging docking time of the third mobile charging call order; first, match the standby mobile charging vehicle for the third mobile charging call order based on the mobile charging vehicle network, and determine the advance amount of the time when the standby mobile charging vehicle goes to the charging reservation location in the third mobile charging call order compared to the charging reservation time in the third mobile charging call order;

[0120] Assigning a first credibility preset first weight to obtain a first target value; the preset first weight and the preset second weight are preset weight values, and the first weight is greater than the second weight; when assigning, multiplying the credibility and the weight to obtain the target value;

[0121] Assigning a second preset weight to the second credibility to obtain a second target value;

[0122] Determine the waiting time corresponding to the sum of the first target value and the second target value from the waiting time library; the larger the sum of the first target value and the second target value, the higher the comprehensive credibility, and the longer the waiting time for the third mobile charging call order to be stable (to prevent malicious cancellation);

[0123] When the waiting time is less than or equal to the advance amount or the difference between the waiting time and the advance amount is less than or equal to the second difference threshold, after waiting for the waiting time, the third mobile charging call order is dispatched to the standby mobile charging vehicle; the second difference threshold can be 200 seconds; when the waiting time is less than or equal to the advance amount or the difference between the waiting time and the advance amount is less than or equal to the second difference threshold, it means that you can wait, and after waiting for the waiting time, the third mobile charging call order is dispatched to the standby mobile charging vehicle;

[0124] When the difference between the waiting time and the advance time is greater than the second difference threshold, the third mobile charging call order is dispatched to the standby mobile charging vehicle after the average value of the waiting time and the advance time is obtained. When the difference between the waiting time and the advance time is greater than the second difference threshold, the third mobile charging call order is dispatched after the average value of the waiting time and the advance time is obtained.

[0125] Generally, the system will also receive a third-party mobile charging call order transmitted by a third-party platform. However, since the malicious cost of maliciously placing and canceling orders on the third-party platform is relatively low, such malicious behavior is very likely to occur. Therefore, the embodiment of the present invention introduces the first credibility and the second credibility, and assigns weights to determine the target value respectively. The waiting time corresponding to the sum of the first target value and the second target value is introduced, and the specific waiting operation is determined according to the relationship between the waiting time and the advance amount, which greatly improves the security of accepting orders from the third-party platform and is particularly applicable.

[0126] The embodiment of the present invention provides an order distribution system, such as Figure 2 As shown, including:

[0127] An order monitoring module 1, used for continuously monitoring a new first mobile charging call order;

[0128] Feature parsing module 2, used for parsing order features of the first mobile charging call order;

[0129] The vehicle matching module 3 is used to match the best mobile charging call vehicle from the mobile charging vehicle network based on the order characteristics;

[0130] The order dispatching module 4 is used to dispatch the first mobile charging call order to the best mobile charging call vehicle.

[0131] The order distribution system also includes:

[0132] Charge induction module for:

[0133] When the mobile charging vehicle actively inputs a dispatch request for a number of times exceeding a threshold number of times and has not been dispatched for a period exceeding a first time threshold, obtaining vehicle information of the mobile charging vehicle;

[0134] Analyze the information characteristics of vehicle information;

[0135] Based on information features, mobile charging induction is performed;

[0136] When the second mobile charging call order is induced, the second mobile charging call order is dispatched to the mobile charging vehicle.

[0137] The charging induction module performs mobile charging induction based on the information features, including:

[0138] Extract the single position and charging capacity of the mobile charging vehicle such as parking among the information features;

[0139] Searching for a first target vehicle; the straight-line distance between the current position of the first target vehicle and the parking position is less than a distance threshold;

[0140] The first target vehicle whose future driving route has a local route that meets the local route condition is used as the second target vehicle;

[0141] Predict the success probability of induction of the second target vehicle;

[0142] Based on the batch division table, the second target vehicle is divided into induction batches of multiple batch levels according to the induction success probability;

[0143] Performing simultaneous mobile charging induction on the second target vehicles in the same induction batch from large to small according to the batch level; wherein, when the second target vehicles in an induction batch that is being induced have not confirmed to accept the induction for a period exceeding the second time threshold, performing simultaneous mobile charging induction on the second target vehicles in the induction batch of the next batch level;

[0144] Among them, local route conditions include:

[0145] The remaining power of the first target vehicle when arriving at the starting point of the local route is less than the power threshold;

[0146] and,

[0147] The local route is a congested section route or the route similarity between each stop route in the same historical stop route set of the first target vehicle is greater than the similarity threshold; the stop locations of each stop route in the same historical stop route set are the same, and the difference in stop time is less than the first difference threshold;

[0148] and,

[0149] The proportion of local routes falling within the target range is greater than the ratio threshold; the smallest encirclement on the city map includes a single location such as parking, the current location and the starting point of the route;

[0150] and,

[0151] The charging capacity meets the remaining power.

[0152] The charging induction module predicts the probability of successful induction of the second target vehicle, including:

[0153] Performing feature description on the multimodal prediction basis of the second target vehicle to obtain a feature description vector;

[0154] Determine the induction success probability corresponding to the feature description vector from the probability library.

[0155] The order distribution system also includes:

[0156] Third-party service modules for:

[0157] When a third mobile charging call order from a third-party platform is monitored, respectively analyzing the first credibility of the third-party platform and the second credibility of the third mobile charging call order;

[0158] Based on the mobile charging vehicle network, determine the advance amount of the standby mobile charging vehicle and the successful charging docking time of the third mobile charging call order;

[0159] Assigning a first credibility preset first weight to obtain a first target value;

[0160] Assigning a second preset weight to the second credibility to obtain a second target value;

[0161] Determine the waiting time corresponding to the sum of the first target value and the second target value from the waiting time library;

[0162] When the waiting time is less than or equal to the advance amount or the difference between the waiting time and the advance amount is less than or equal to the second difference threshold, after waiting for the waiting time, the third mobile charging call order is dispatched to the standby mobile charging vehicle;

[0163] When the difference between the waiting time and the advance amount is greater than a second difference threshold, the third mobile charging call order is dispatched to the standby mobile charging vehicle after the average value of the waiting time and the advance amount is calculated.

[0164] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An order allocation method, characterized in that: include: Keep monitoring new First Mobile charging call orders; parsing order features of the first mobile charging call order; Based on the order characteristics, the best mobile charging call vehicle is matched from the mobile charging vehicle network; The first mobile charging call order is dispatched to the best mobile charging call vehicle.

2. The order allocation method according to claim 1, characterized in that: Also includes: When the mobile charging vehicle actively inputs a dispatch request for a number of times exceeding a threshold number of times and has not been dispatched for a period exceeding a first time threshold, obtaining vehicle information of the mobile charging vehicle; Analyze the information characteristics of vehicle information; Based on information features, mobile charging induction is performed; When the second mobile charging call order is induced, the second mobile charging call order is dispatched to the mobile charging vehicle.

3. The order distribution method according to claim 2, characterized in that: The mobile charging induction based on the information feature includes: Extract the single position and charging capacity of the mobile charging vehicle such as parking among the information features; Searching for a first target vehicle; the straight-line distance between the current position of the first target vehicle and the parking position is less than a distance threshold; The first target vehicle whose future driving route has a local route that meets the local route condition is used as the second target vehicle; Predict the success probability of induction of the second target vehicle; Based on the batch division table, the second target vehicle is divided into induction batches of multiple batch levels according to the induction success probability; Performing simultaneous mobile charging induction on the second target vehicles in the same induction batch from large to small according to the batch level; wherein, when the second target vehicles in an induction batch that is being induced have not confirmed to accept the induction for a period exceeding the second time threshold, performing simultaneous mobile charging induction on the second target vehicles in the induction batch of the next batch level; Among them, local route conditions include: The remaining power of the first target vehicle when arriving at the starting point of the local route is less than the power threshold; and, The local route is a congested section route or the route similarity between each stop route in the same historical stop route set of the first target vehicle is greater than the similarity threshold; the stop locations of each stop route in the same historical stop route set are the same, and the difference in stop time is less than the first difference threshold; and, The proportion of local routes falling within the target range is greater than the ratio threshold; the smallest encirclement on the city map includes a single location such as parking, the current location and the starting point of the route; and, The charging capacity meets the remaining power.

4. The order allocation method according to claim 3, characterized in that: The predicting of the induction success probability of the second target vehicle includes: Performing feature description on the multimodal prediction basis of the second target vehicle to obtain a feature description vector; Determine the induction success probability corresponding to the feature description vector from the probability library.

5. The order distribution method according to claim 1, characterized in that: Also includes: When a third mobile charging call order from a third-party platform is monitored, respectively analyzing the first credibility of the third-party platform and the second credibility of the third mobile charging call order; Based on the mobile charging vehicle network, determine the advance amount of the standby mobile charging vehicle and the successful charging docking time of the third mobile charging call order; Assigning a first credibility preset first weight to obtain a first target value; Assigning a second preset weight to the second credibility to obtain a second target value; Determine the waiting time corresponding to the sum of the first target value and the second target value from the waiting time library; When the waiting time is less than or equal to the advance amount or the difference between the waiting time and the advance amount is less than or equal to the second difference threshold, after the waiting time, the third mobile charging call order is dispatched to the standby mobile charging vehicle; When the difference between the waiting time and the advance amount is greater than a second difference threshold, the third mobile charging call order is dispatched to the standby mobile charging vehicle after the average value of the waiting time and the advance amount is calculated.

6. An order distribution system, characterized in that: include: An order monitoring module, used for continuously monitoring new first mobile charging call orders; A feature analysis module, used for analyzing the order features of the first mobile charging call order; A vehicle matching module is used to match the best mobile charging call vehicle from the mobile charging vehicle network based on order characteristics; The order dispatching module is used to dispatch the first mobile charging call order to the best mobile charging call vehicle.

7. The order distribution system according to claim 6, characterized in that: Also includes: Charge induction module for: When the mobile charging vehicle actively inputs a dispatch request for a number of times exceeding a threshold number of times and has not been dispatched for a period exceeding a first time threshold, obtaining vehicle information of the mobile charging vehicle; Analyze the information characteristics of vehicle information; Based on information features, mobile charging induction is performed; When the second mobile charging call order is induced, the second mobile charging call order is dispatched to the mobile charging vehicle.

8. The order distribution system according to claim 7, characterized in that: The charging induction module performs mobile charging induction based on the information characteristics, including: Extract the single position and charging capacity of the mobile charging vehicle such as parking among the information features; Searching for a first target vehicle; the straight-line distance between the current position of the first target vehicle and the parking position is less than a distance threshold; The first target vehicle whose future driving route has a local route that meets the local route condition is used as the second target vehicle; Predict the success probability of induction of the second target vehicle; Based on the batch division table, the second target vehicle is divided into induction batches of multiple batch levels according to the induction success probability; Performing simultaneous mobile charging induction on the second target vehicles in the same induction batch from large to small according to the batch level; wherein, when the second target vehicles in an induction batch that is being induced have not confirmed to accept the induction for a period exceeding the second time threshold, performing simultaneous mobile charging induction on the second target vehicles in the induction batch of the next batch level; Among them, local route conditions include: The remaining power of the first target vehicle when arriving at the starting point of the local route is less than the power threshold; and, The local route is a congested section route or the route similarity between each stop route in the same historical stop route set of the first target vehicle is greater than the similarity threshold; the stop locations of each stop route in the same historical stop route set are the same, and the difference in stop time is less than the first difference threshold; and, The proportion of local routes falling within the target range is greater than the ratio threshold; the smallest encirclement on the city map includes a single location such as parking, the current location and the starting point of the route; and, The charging capacity meets the remaining power.

9. The order distribution system according to claim 8, characterized in that: The charging induction module predicts the probability of successful induction of the second target vehicle, including: Performing feature description on the multimodal prediction basis of the second target vehicle to obtain a feature description vector; Determine the induction success probability corresponding to the feature description vector from the probability library.

10. The order distribution system according to claim 6, characterized in that: Also includes: Third-party service modules for: When a third mobile charging call order from a third-party platform is monitored, respectively analyzing the first credibility of the third-party platform and the second credibility of the third mobile charging call order; Based on the mobile charging vehicle network, determine the advance amount of the standby mobile charging vehicle and the successful charging docking time of the third mobile charging call order; Assigning a first credibility preset first weight to obtain a first target value; Assigning a second preset weight to the second credibility to obtain a second target value; Determine the waiting time corresponding to the sum of the first target value and the second target value from the waiting time library; When the waiting time is less than or equal to the advance amount or the difference between the waiting time and the advance amount is less than or equal to the second difference threshold, after the waiting time, the third mobile charging call order is dispatched to the standby mobile charging vehicle; When the difference between the waiting time and the advance amount is greater than a second difference threshold, the third mobile charging call order is dispatched to the standby mobile charging vehicle after the average value of the waiting time and the advance amount is calculated.

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