CN114819413B - Recommendation system and method for customizing passenger transport route by network taxi appointment - Google Patents

Recommendation system and method for customizing passenger transport route by network taxi appointment Download PDF

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CN114819413B
CN114819413B CN202210720331.7A CN202210720331A CN114819413B CN 114819413 B CN114819413 B CN 114819413B CN 202210720331 A CN202210720331 A CN 202210720331A CN 114819413 B CN114819413 B CN 114819413B
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order
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power consumption
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CN114819413A (en
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张展航
王国田
张清枝
周耿城
刘静
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China Transport Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
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    • G06Q30/0635—Processing of requisition or of purchase orders
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Abstract

The invention discloses a recommendation system and a method for customizing a passenger transport route by network taxi appointment, which comprises a historical order data acquisition module, an average power consumption value estimation module, an optimal route set making module and a passenger transport route limiting module; a historical order data acquisition module acquires historical order data, an urban charging pile distribution circuit diagram and a hot site distribution circuit diagram; the average power consumption value estimation module is used for estimating the average power consumption value of the network appointment vehicle and setting a critical return power consumption residual threshold; the optimal route set formulating module formulates passenger transport routes which are not beyond the critical return journey power consumption residual threshold and are beyond the critical return journey power consumption residual threshold; the passenger transport route defining module is used for defining the time requirement and the distance requirement in the optimal route set; the invention solves the problem of how to move the net appointment vehicle under the condition that the order is not received or the mileage of the order is unreasonable, reduces the judgment cost of a driver, and improves the utilization rate of the electric quantity of the net appointment vehicle so as to greatly reduce the empty time.

Description

Recommendation system and method for customizing passenger transport route by network booking vehicle
Technical Field
The invention relates to the technical field of passenger transport route recommendation systems, in particular to a recommendation system and method for customizing a passenger transport route by network appointment.
Background
In recent years, with the gradual maturity of intelligent devices and internet platforms, the online taxi is attractive to users who use public transport to a certain extent by virtue of the advantages of convenience and comfort; in the using process of the network car booking, a network car booking driver serves as a main body of the network car booking, and how to maximally utilize the driving cost of the network car booking is a necessary road for each network car booking owner, but at present, due to randomness and uncertainty of orders, the network car booking driver can have the problem that no orders exist under some conditions or the orders are too far away to cause overhigh cost, the driver needs to determine the forward direction of the network car booking by self judgment to obtain the proper orders at the fastest speed, and waste of time cost and power consumption cost or wrong judgment is often caused;
meanwhile, the current network car booking is mainly carried out by the electric car, and the electric quantity of the network car booking and the distribution of the urban charging piles also need to be included in the planning of a reasonable route, so that the possibility that the electric quantity is exhausted before the charging piles are reached due to the problem of improper route planning which may exist at present is solved.
Disclosure of Invention
The invention aims to provide a recommendation system and method for customizing a passenger transport route by means of network booking, which are used for solving the problems in the background art.
In order to solve the technical problems, the invention provides the following technical scheme: a recommendation method for customizing a passenger transport route by a network appointment comprises the following specific steps:
acquiring historical order data, wherein the historical order data comprises time points of historical orders, positions and distances of starting and ending points of the historical orders, total mileage from the start of order taking to the end of order taking every day and total power consumption; the historical order data is stored in a passenger transport route recommendation system, and an urban charging pile distribution circuit diagram and a hot station distribution circuit diagram recorded in the passenger transport route recommendation system are obtained;
estimating average power consumption value of each order of network car booking based on historical order data in recommendation system
Figure 520840DEST_PATH_IMAGE001
Wherein
Figure 828193DEST_PATH_IMAGE002
Represents the total electricity consumption from the beginning to the end of the order taking of the 1 st, 2 nd, and k network appointment cars,
Figure 342351DEST_PATH_IMAGE003
representing the total order receiving quantity from the beginning to the end of the order receiving of the 1 st, 2 nd,. Setting critical return power consumption residual threshold
Figure 206402DEST_PATH_IMAGE004
The critical return power consumption remaining threshold value
Figure 942146DEST_PATH_IMAGE004
Greater than the average electricity consumption per order
Figure 30187DEST_PATH_IMAGE005
；
Optimal route set in passenger transport route recommendation system
Figure 766062DEST_PATH_IMAGE006
Said
Figure 433804DEST_PATH_IMAGE007
Representing a passenger traffic route before not below a critical return electricity consumption remaining threshold, said
Figure 24054DEST_PATH_IMAGE008
Representing the passenger transport route after being lower than the critical return electricity consumption residual threshold;
and recording the actual distance and the actual duration between the terminal point of the last passenger and the starting point of the next passenger in the average adjacent orders in historical order data of different online appointments as L1 and T1 respectively, and the optimal route set A
Figure 486260DEST_PATH_IMAGE007
And
Figure 709431DEST_PATH_IMAGE008
in the process of making, the estimated distance L2 between the last passenger's terminal and the next passenger's starting point is less than L1, and the estimated time length T2 is less than T1.
Further, in the above-mentioned case,
Figure 173341DEST_PATH_IMAGE007
the passenger transport route planning comprises the following steps:
recording the driving data of the first order of the taxi appointment in the day network, wherein the driving data of the first order comprises an order terminal pointLocation of and electricity consumption of this order
Figure 165567DEST_PATH_IMAGE009
；
Determining the power consumption of the order
Figure 64253DEST_PATH_IMAGE009
Average power consumption value of each order
Figure 774720DEST_PATH_IMAGE005
The relationship between the size of the order and the power consumption when the order is made
Figure 767953DEST_PATH_IMAGE009
Greater than the average electricity consumption per order
Figure 880265DEST_PATH_IMAGE005
And judging whether the position distance between the starting point of the next order and the end point of the first order meets the following conditions:
Figure 949853DEST_PATH_IMAGE010
and is
Figure 147616DEST_PATH_IMAGE011
(ii) a The power consumption of the order is analyzed so that the power can be reasonably and uniformly arranged in each time of the order of the network appointment vehicle, and the monitoring is carried out under the condition of abnormal power consumption;
if not satisfied with
Figure 944539DEST_PATH_IMAGE010
And is
Figure 911358DEST_PATH_IMAGE011
Or when L2=0 is not satisfied and T2=0 is not satisfied, the network appointment vehicle goes to a hot station within the ideal radius of the terminal point of the order when the order is carried out to receive the order; the precondition for going to the hot station is that the average driving time in the historical order data is predicted to be exceeded when the starting point of the next order is reached or no new order is generated after the order is finished, and the driver of the online taxi appointment is required to judge the driving sideTherefore, the system analysis is introduced to assist the judgment of the net car booking driver, because the invention aims to shorten the empty time of the user after finishing each order, improve the driving utilization rate of the net car booking, and if the empty time meets the requirement, the invention can reduce the empty time of the user as much as possible
Figure 355109DEST_PATH_IMAGE010
And is provided with
Figure 571327DEST_PATH_IMAGE011
The online taxi appointment driver receives the order and goes to the starting point position of the order;
when the order is made
Figure 375204DEST_PATH_IMAGE009
Less than or equal to the average power consumption value of each order
Figure 993267DEST_PATH_IMAGE005
When the order is started, selecting the order starting point position corresponding to the minimum value in the next order L2 for driving; and if no next order is available, selecting the hot station within the ideal radius of the end point of the order when the order is carried out according to the recommendation system.
Further, the network appointment vehicle goes to a hot station within the ideal radius of the terminal point of the order when the distance is carried out to receive the order, and the method comprises the following steps:
connecting the boarding points in the historical order data according to the standard that the straight-line distance between the boarding points of each order is smaller than
Figure 607919DEST_PATH_IMAGE012
And will satisfy the distance less than
Figure 766892DEST_PATH_IMAGE012
Is formed by the upper vehicle point
Figure 656351DEST_PATH_IMAGE013
Is a circular area with a radius, the circular area comprises all the upper vehicle points of the connecting line, and
Figure 394500DEST_PATH_IMAGE013
is greater than
Figure 976791DEST_PATH_IMAGE012
；
The passenger transport route recommendation system obtains the number m of the formed circle areas and the number p of all boarding points in the historical order data, and calculates the average number of the boarding points in the circle areas in the historical order data as
Figure 370863DEST_PATH_IMAGE014
Recording the circle area with the number of the upper vehicle points in the actual circle area larger than the number of the upper vehicle points in the average circle area as the hot station;
recording the position of the hot station, and acquiring the actual distance set of the order end point when the hot station distance in the historical order data is carried out
Figure 47701DEST_PATH_IMAGE015
And set of actual durations
Figure 578039DEST_PATH_IMAGE016
(ii) a Aggregating actual routes
Figure 596811DEST_PATH_IMAGE015
Sorting according to the order from small to large, and selecting the sorted set
Figure 478179DEST_PATH_IMAGE015
The actual routes of the corresponding hot stations with the median value of more than or equal to L2 and less than L1 are taken as target route sets
Figure 958708DEST_PATH_IMAGE017
；
Obtaining a target range set
Figure 609132DEST_PATH_IMAGE017
Corresponding target duration set
Figure 267647DEST_PATH_IMAGE018
Set of target durations
Figure 636311DEST_PATH_IMAGE018
Expressed as the center of a circle with the end point of the order as the center of the progress in the historical order data,
Figure 920531DEST_PATH_IMAGE019
Setting the actual time length from the historical order end point to the hot site in the radius range as a target time length set;
determining a target duration set
Figure 487778DEST_PATH_IMAGE018
And analyzing the ideal radius priority of the hot station before the network taxi appointment according to the accuracy of the target duration set and the corresponding target distance set.
Further, a target duration set is judged
Figure 317194DEST_PATH_IMAGE018
According to the accuracy of the target duration set and the accuracy of the corresponding target distance set, the ideal radius priority of the hot station before the network taxi appointment is analyzed, and the method comprises the following steps of:
obtaining a target duration set
Figure 173155DEST_PATH_IMAGE018
Time length ordering n1 in (1), and target time length set
Figure 11798DEST_PATH_IMAGE018
Calculating a target time length set in a sequence n2 from small to large
Figure 617573DEST_PATH_IMAGE018
Is measured with respect to the accuracy of
Figure 883469DEST_PATH_IMAGE020
Similarity of the two
Figure 695567DEST_PATH_IMAGE021
；
When the accuracy is high
Figure 603480DEST_PATH_IMAGE022
Selecting the actual time length of the hot site corresponding to the time length less than T1 in the target time length set as an ideal time length set
Figure 66692DEST_PATH_IMAGE023
Then the priority order of the ideal radius is the ideal duration set
Figure 503489DEST_PATH_IMAGE023
Corresponding ideal course set
Figure 68463DEST_PATH_IMAGE024
The order of (a); the accuracy =1 indicates that the sequence in the target time length set is from large to small, that is, the distance from the hot station is in direct proportion to the travel time of the network appointment vehicle, so that the travel station with the length greater than the time length L1 can be directly removed, that is, the network appointment vehicle can be selected according to the situation in an ideal radius according to the priority sequence, and the time judged by a driver is saved;
when the accuracy is high
Figure 248908DEST_PATH_IMAGE025
Selecting the actual time length of the hot station corresponding to the sequence n2 and smaller than T1 in the target time length set as an ideal time length set
Figure 832205DEST_PATH_IMAGE026
And
Figure 439904DEST_PATH_IMAGE026
the hot site analysis data corresponding to the sequence number value which does not meet the time length from big to small in the middle comprises the distance from the hot site to the end point of the order when the order is carried out or the distance between the hot site and the end point of the order when the order is carried out as the circle center,
Figure 288911DEST_PATH_IMAGE027
The routes within the radius range correspond to the braking times in the total routes of the 1 st, 2 nd, and c th hot stop network appointment vehicles in the historical order data
Figure 7469DEST_PATH_IMAGE028
The hot station analysis data also comprises the taxi appointment travel time length of the 1 st, 2 nd, c th hot station network
Figure 461584DEST_PATH_IMAGE029
And calculating the braking frequency of the 1 st, 2 nd, and c th hot stations in the historical order data
Figure 489452DEST_PATH_IMAGE030
(ii) a The number of times of obtaining the brakes is to analyze whether the distance from the hot station is not in proportion to the driving time of the networked taxi appointment or not, and whether the distance is close but long time is easily consumed due to the congestion of road conditions, because the probability that some hot stations are congested relative to ordinary road sections is high.
Will be provided with
Figure 29017DEST_PATH_IMAGE031
The formed sets are sorted from small to large, if the sorted sets
Figure 551265DEST_PATH_IMAGE031
Corresponding time length sequence and ideal time length set
Figure 859887DEST_PATH_IMAGE032
If the ideal radius is the same, the priority order of the ideal radius is the ideal duration set
Figure 61586DEST_PATH_IMAGE032
Corresponding ideal course set
Figure 822868DEST_PATH_IMAGE033
The order of (a).
Further, in the above-mentioned case,
Figure 148808DEST_PATH_IMAGE034
the passenger transport route planning comprises the following steps:
recording network contractThe residual electric quantity of the vehicle reaches and equals to the critical return journey power consumption residual threshold value
Figure 311936DEST_PATH_IMAGE035
The position of a temporal order and the urban charging pile position in historical order data within a preset range from the end position of the order are obtained, and the distance between the end position of the order and the 1 st, 2 nd, so, s urban charging piles within the preset range is obtained
Figure 681606DEST_PATH_IMAGE036
；
Calculating the kilometer electricity consumption value of the network appointment car in the historical order data
Figure 930185DEST_PATH_IMAGE037
Wherein
Figure 59815DEST_PATH_IMAGE038
Representing the total mileage from the beginning to the end of the order taking of the 1 st, 2 nd, and k network appointment cars; acquiring actual electricity consumption values of charging pile positions of 1 st, 2 nd, so s cities in a preset range
Figure 77449DEST_PATH_IMAGE039
And corresponding ideal power consumption value
Figure 883600DEST_PATH_IMAGE040
；
Calculating the actual power consumption value
Figure 619475DEST_PATH_IMAGE039
Corresponding ideal power consumption value
Figure 287217DEST_PATH_IMAGE040
Deviation value therebetween
Figure 893779DEST_PATH_IMAGE041
Will deviate from the value
Figure 870831DEST_PATH_IMAGE042
Sorting from small to large is performed, then
Figure 94002DEST_PATH_IMAGE034
Is defined as deviation value
Figure 299855DEST_PATH_IMAGE042
The minimum corresponding to
Figure 292082DEST_PATH_IMAGE043
And (4) the driving route of the charging pile in the historical database of each city.
A recommendation system for customizing a passenger transport route by network taxi appointment comprises a historical order data acquisition module, an average power consumption value estimation module, an optimal route set making module and a passenger transport route limiting module;
the historical order data acquisition module is used for acquiring historical order data recorded in the passenger transport route recommendation system, wherein the historical order data comprises time points of historical orders, positions and distances of starting and ending points of the historical orders, and total mileage and total power consumption from starting to ending of taking orders every day; the method comprises the steps of obtaining an urban charging pile distribution circuit diagram and a hot station distribution circuit diagram recorded in a passenger transport route recommendation system;
the average power consumption value estimation module is used for estimating the average power consumption value of each order of the network appointment according to historical order data and setting a critical return power consumption residual threshold value, wherein the critical return power consumption residual threshold value is larger than the average power consumption value of each order;
the optimal route set making module is used for making a passenger transport route which does not fall below the critical return journey electricity consumption residual threshold value
Figure 261324DEST_PATH_IMAGE044
And the passenger transport route is lower than the critical return power consumption residual threshold
Figure 706212DEST_PATH_IMAGE034
The optimal route set is
Figure 715756DEST_PATH_IMAGE045
；
The passenger transport route definition module is used for defining time requirements and distance requirements in the optimal route set.
Further, the optimal route set formulation module comprises
Figure 828069DEST_PATH_IMAGE044
Passenger transport route planning module and
Figure 881344DEST_PATH_IMAGE034
a passenger transport route making module;
Figure 79108DEST_PATH_IMAGE044
the passenger transport route formulating module comprises a power consumption preliminary judging module, a route analyzing module and an ideal radius planning module;
the power consumption preliminary judgment module is used for judging the magnitude relation between the power consumption of the first order and the average power consumption value of each order; the route analysis module is used for analyzing and judging whether the estimated time length and the estimated distance between the position of the first order and the position of the next order are both smaller than the corresponding actual time length and actual distance in the historical order; the ideal radius planning module is used for planning hot stations with ideal radius when the conditions that the ideal radius is smaller than the preset radius are not met;
the ideal radius planning module comprises a circular domain establishing module, a hot site analyzing module, a target set establishing module and an accuracy judging module; the circle domain making module is used for connecting the boarding points in the historical order data and setting the boarding points meeting the distance requirement as a circle domain; the hot station analysis module is used for analyzing and obtaining the hot stations based on the number of the circular domains and the number of all boarding points in the historical order data; the target set formulation module is used for analyzing the positions of popular stations and correspondingly acquiring the actual duration and the actual distance in the historical order data for analysis; and the accuracy judging module is used for analyzing the ideal radius priority of the hot station before the network appointment according to the accuracy of the target duration set.
Furthermore, the accuracy judgment module comprises an accuracy calculation module and an accuracy analysis module; the accuracy analysis module comprises a brake data acquisition module and a brake frequency calculation module;
the accuracy calculation module is used for acquiring time length sequencing and sequencing from small to large of the target time length set, and comparing the similarity of the sequences of the time length sequencing and the sequencing from small to large to obtain an accuracy calculation value;
the accuracy analysis module analyzes the ideal radius priority sequence when the accuracy is equal to 1 and the ideal radius priority when the accuracy is not equal to 1 according to the calculated value of the accuracy;
the brake data acquisition module is used for acquiring the corresponding brake times of the network appointment car when the accuracy is not equal to 1; and the braking frequency calculation module is used for analyzing the relation between the braking frequency and the running time of the corresponding network appointment vehicle and formulating an ideal time priority sequence with the accuracy not equal to 1 according to the corresponding relation.
Further, in the above-mentioned case,
Figure 423501DEST_PATH_IMAGE034
the passenger transport route formulating module comprises a critical data acquiring module, a kilometer electricity consumption value calculating module and a deviation value analyzing module;
the critical data acquisition module is used for acquiring an order end point position when the remaining electric quantity of the network appointment vehicle is greater than or equal to a critical return journey power consumption remaining threshold value, and an urban charging pile position within a preset range from the order end point position in historical order data, and acquiring the distance between the order end point and the urban charging pile within the preset range;
the kilometer electricity consumption value calculating module is used for calculating a kilometer electricity consumption value according to the total mileage from the start of order receiving to the end of order receiving of the network appointment car and the total electricity consumption;
the deviation value analysis module is used for acquiring an actual power consumption value and a corresponding ideal power consumption value of a city charging pile position in a preset range, and calculating an absolute value of the difference between the actual power consumption value and the ideal power consumption value as a deviation value; sorting the deviation values from small to large, and then obtaining the deviation values
Figure 390320DEST_PATH_IMAGE046
The minimum corresponding city charging pile driving route in the historical database is
Figure 365229DEST_PATH_IMAGE034
Passenger transport route.
Compared with the prior art, the invention has the following beneficial effects: the method comprises the steps of planning a driving route of the online taxi appointment into two parts by taking the power consumption of an order in historical order data as a basis, and respectively carrying out time length limitation, route limitation and power quantity limitation on the two parts so as to plan an optimal route which accords with the actual condition of the online taxi appointment; the problem of how to move ahead under the circumstances that net car reservation driver does not receive the order or order mileage is unreasonable is solved, greatly reduced driver's judgement cost, improved the utilization of net car reservation electric quantity and made the time of empty wagon reduce greatly, when reaching the remaining threshold value of critical return journey power consumption simultaneously, the return journey route of selecting the minimum correspondence of deviation value net car reservation position this moment returns the journey, increased net car reservation and gone forward the feasibility and the security of filling electric pile distance.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic structural diagram of a recommendation system for ordering passenger transportation routes by network appointment according to the invention;
fig. 2 is a flow chart of steps of a method for recommending a customized passenger transport route by means of online booking.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides a technical solution: a recommendation method for customizing a passenger transport route by a network appointment comprises the following specific steps:
acquiring historical order data, wherein the historical order data comprises time points of historical orders, positions and distances of starting and ending points of the historical orders, total mileage from the start of order taking to the end of order taking every day and total power consumption; the historical order data is stored in a passenger transport route recommendation system, and an urban charging pile distribution circuit diagram and a hot station distribution circuit diagram recorded in the passenger transport route recommendation system are obtained;
estimating average power consumption value of each order of network car booking based on historical order data in recommendation system
Figure 299556DEST_PATH_IMAGE047
Wherein
Figure 650903DEST_PATH_IMAGE048
Represents the total electricity consumption from the beginning to the end of the order taking of the 1 st, 2 nd, and k network appointment cars,
Figure 472229DEST_PATH_IMAGE049
representing the total order receiving quantity from the beginning to the end of the order receiving of the 1 st, 2 nd,. Setting critical return power consumption residual threshold
Figure 618039DEST_PATH_IMAGE050
Said critical return power consumption residual threshold
Figure 774083DEST_PATH_IMAGE050
Greater than the average electricity consumption per order
Figure 663542DEST_PATH_IMAGE051
；
Optimal route set in passenger transport route recommendation system
Figure 604953DEST_PATH_IMAGE052
Said
Figure 921665DEST_PATH_IMAGE053
Representing a passenger traffic route before not below a critical return electricity consumption remaining threshold, said
Figure 567934DEST_PATH_IMAGE054
Representing the passenger transport route after being lower than the critical return trip electricity consumption residual threshold;
and recording the actual distance and the actual time length between the terminal of the last passenger and the starting point of the next passenger in the average adjacent orders in historical order data of different networked appointments as L1 and T1 respectively, and the optimal route set A
Figure 261084DEST_PATH_IMAGE053
And
Figure 57001DEST_PATH_IMAGE054
in the formulation process, it is required to satisfy that the predicted distance between the last passenger's terminal and the next passenger's starting point, L2, is less than L1, and the predicted time period, T2, is less than T1.
Figure 810194DEST_PATH_IMAGE053
The passenger transport route planning comprises the following steps:
recording the driving data of the first order of the taxi appointment in the day network, wherein the driving data of the first order comprises the position of an order terminal and the power consumption of the order
Figure 940830DEST_PATH_IMAGE055
；
Judging the power consumption of the order
Figure 968828DEST_PATH_IMAGE055
Average power consumption value of each order
Figure 619253DEST_PATH_IMAGE056
The power consumption when the order is made
Figure 543346DEST_PATH_IMAGE055
Greater than the average electricity consumption per order
Figure 912011DEST_PATH_IMAGE056
Then, the distance between the starting point of the next order and the end point of the first order is judgedWhether the separation satisfies:
Figure 196230DEST_PATH_IMAGE057
and is
Figure 701161DEST_PATH_IMAGE058
(ii) a The power consumption of the order is analyzed so that the power can be reasonably and uniformly arranged in each time of the order of the network appointment vehicle, and the monitoring is carried out under the condition of abnormal power consumption;
if not satisfied with
Figure 796156DEST_PATH_IMAGE057
And is
Figure 652117DEST_PATH_IMAGE058
Or when L2=0 is not satisfied and T2=0 is not satisfied, the network appointment vehicle goes to a hot station within the ideal radius of the terminal point of the order when the order is carried out to receive the order; the premise of going to the hot station is that the estimated arrival of the starting point of the next order exceeds the average driving time in the historical order data or no new order is generated after the order is finished, the network taxi appointment driver is required to judge the driving direction, and the system analysis is introduced to assist the judgment of the network taxi appointment driver
Figure 208869DEST_PATH_IMAGE057
And is
Figure 833885DEST_PATH_IMAGE058
The online taxi appointment driver receives the order and goes to the starting point position of the order;
when the order is made
Figure 99781DEST_PATH_IMAGE055
Less than or equal to the average power consumption value of each order
Figure 177459DEST_PATH_IMAGE056
Then, the next order is selectedDriving at the corresponding order starting point position at the minimum value in L2; and if no next order is available, selecting the hot station within the ideal radius of the end point of the order when the order is carried out according to the recommendation system.
The method for receiving the order by the hot station within the ideal radius of the terminal point of the order when the network appointment vehicle goes to the distance is carried out comprises the following steps:
connecting the boarding points in the historical order data according to the standard that the straight-line distance between the boarding points of each order is smaller than
Figure 66131DEST_PATH_IMAGE059
And will satisfy the distance less than
Figure 545654DEST_PATH_IMAGE059
Is formed by the upper vehicle point
Figure 982451DEST_PATH_IMAGE060
Is a circular area with a radius, the circular area comprises all the upper vehicle points of the connecting line, and
Figure 547425DEST_PATH_IMAGE060
is greater than
Figure 711559DEST_PATH_IMAGE059
；
Passenger transport route recommendation system obtains number of circle areas
Figure 311167DEST_PATH_IMAGE061
And the number of all boarding points in the historical order data
Figure 918866DEST_PATH_IMAGE062
Calculating the number of the vehicle points on the average circle in the historical order data as
Figure 971136DEST_PATH_IMAGE063
Recording the circle area with the number of the upper vehicle points in the actual circle area larger than the number of the upper vehicle points in the average circle area as the hot station;
recording the location of hot sites and obtaining historyActual course aggregation of order end points when portal site distance is in progress in order data
Figure 486431DEST_PATH_IMAGE064
And set of actual durations
Figure 189813DEST_PATH_IMAGE065
(ii) a Aggregating the actual routes
Figure 968413DEST_PATH_IMAGE064
Sorting according to the order from small to large, and selecting the sorted set
Figure 507979DEST_PATH_IMAGE064
The actual routes of the corresponding hot stations with the median value of more than or equal to L2 and less than L1 are taken as target route sets
Figure 30227DEST_PATH_IMAGE066
；
Obtaining a target range set
Figure 588117DEST_PATH_IMAGE066
Corresponding target duration set
Figure 272039DEST_PATH_IMAGE067
Set of target durations
Figure 33321DEST_PATH_IMAGE067
Expressed as the center of a circle with the end point of the order as the center of the circle in the historical order data,
Figure 359261DEST_PATH_IMAGE068
Setting the actual time from the historical order end point to the hot station existing in the radius range as a target time set;
determining a target duration set
Figure 774586DEST_PATH_IMAGE067
According to the accuracy of the target duration set and the accuracy of the corresponding target distance set, analyzing the advance hot door of the network taxi appointmentIdeal radius priority of a station.
Determining a target duration set
Figure 894989DEST_PATH_IMAGE067
According to the accuracy of the target duration set and the accuracy of the corresponding target distance set, the ideal radius priority of the hot station of the network taxi appointment advance is analyzed, and the method comprises the following steps:
obtaining a target duration set
Figure 409147DEST_PATH_IMAGE067
Time length ordering n1 in (1), and target time length set
Figure 273197DEST_PATH_IMAGE067
Calculating a target duration set in the order n2 from small to large
Figure 540100DEST_PATH_IMAGE067
Is measured with respect to the accuracy of
Figure 96983DEST_PATH_IMAGE069
Figure 98437DEST_PATH_IMAGE070
Figure 500599DEST_PATH_IMAGE071
；
When the accuracy is high
Figure 887587DEST_PATH_IMAGE072
Selecting the actual time length of the hot site corresponding to the time length less than T1 in the target time length set as an ideal time length set
Figure 615372DEST_PATH_IMAGE073
The priority order of the ideal radius is the ideal duration set
Figure 572964DEST_PATH_IMAGE073
Corresponding ideal course set
Figure 44396DEST_PATH_IMAGE074
The order of (a); the accuracy =1 indicates that the sequence in the target time length set is from large to small, that is, the distance from the hot station is in direct proportion to the travel time of the network appointment vehicle, so that the travel station with the length greater than the time length L1 can be directly removed, that is, the network appointment vehicle can be selected according to the situation in an ideal radius according to the priority sequence, and the time judged by a driver is saved;
for example: target duration set
Figure 20311DEST_PATH_IMAGE075
；
Then
Figure 653418DEST_PATH_IMAGE076
In the order of
Figure 363885DEST_PATH_IMAGE077
，
While
Figure 373429DEST_PATH_IMAGE078
In the order of
Figure 478219DEST_PATH_IMAGE079
；
And target duration set
Figure 547806DEST_PATH_IMAGE080
Corresponding target journey set
Figure 479990DEST_PATH_IMAGE081
；
Target duration set
Figure 293226DEST_PATH_IMAGE080
Is measured with respect to the accuracy of
Figure 774891DEST_PATH_IMAGE082
Degree of similarity
Figure 749801DEST_PATH_IMAGE083
=
Figure 434860DEST_PATH_IMAGE084
；
At this time
Figure 786207DEST_PATH_IMAGE085
If at all
Figure 856800DEST_PATH_IMAGE086
Then, then
Figure 2610DEST_PATH_IMAGE087
；
And is in
Figure 909386DEST_PATH_IMAGE088
Corresponding brake times {4, 10}, at the moment
Figure 64424DEST_PATH_IMAGE089
，
Figure 989524DEST_PATH_IMAGE090
，
Then
Figure 306236DEST_PATH_IMAGE091
The sequence from small to big is
Figure 700308DEST_PATH_IMAGE092
And
Figure 659037DEST_PATH_IMAGE093
the same;
the priority order of the ideal radius is the ideal duration set
Figure 441572DEST_PATH_IMAGE094
Corresponding ideal path gathers
Figure 194765DEST_PATH_IMAGE095
I.e., {3.5km, 2km }.
When the accuracy is high
Figure 810554DEST_PATH_IMAGE096
Selecting the actual time length of the hot station corresponding to the sequence n2 and smaller than T1 in the target time length set as an ideal time length set
Figure 307394DEST_PATH_IMAGE097
And
Figure 207086DEST_PATH_IMAGE097
the hot site analysis data corresponding to the sequence number value which does not meet the time length from big to small in the middle comprises the distance from the hot site to the end point of the order when the order is carried out or the distance between the hot site and the end point of the order when the order is carried out as the circle center,
Figure 131180DEST_PATH_IMAGE098
The routes within the radius range correspond to the braking times in the total routes of the 1 st, 2 nd, and c th hot stop network appointment vehicles in the historical order data
Figure 296582DEST_PATH_IMAGE099
The hot station analysis data also comprises the taxi appointment travel time length of the 1 st, 2 nd, c th hot station network
Figure 534796DEST_PATH_IMAGE100
And calculating the braking frequency of the 1 st, 2 nd, and c th hot stations in the historical order data
Figure 836465DEST_PATH_IMAGE101
(ii) a The number of times of obtaining the brake is to analyze whether the distance from the hot station is not in proportion to the driving time of the network taxi appointment or not, and whether the distance is close but long time is easily consumed due to congestion of road conditions, and the probability that congestion exists in some hot stations is higher than that of common road sections.
Will be provided with
Figure 180727DEST_PATH_IMAGE102
Structure of the organizationThe resultant sets are sorted from small to large, if the sorted sets are
Figure 771108DEST_PATH_IMAGE102
Corresponding time length sequence and ideal time length set
Figure 609751DEST_PATH_IMAGE103
If the ideal radius is the same, the priority order of the ideal radius is the ideal duration set
Figure 234768DEST_PATH_IMAGE103
Corresponding ideal path gathers
Figure 749932DEST_PATH_IMAGE104
The order of (a).
Figure 827609DEST_PATH_IMAGE105
The passenger transport route planning comprises the following steps:
recording the residual electric quantity of the network appointment vehicle to reach the threshold value equal to the critical return power consumption residual electric quantity
Figure 938785DEST_PATH_IMAGE106
The position of a temporal order and the urban charging pile position in historical order data within a preset range from the end position of the order are obtained, and the distance between the end position of the order and the 1 st, 2 nd, so, s urban charging piles within the preset range is obtained
Figure 418307DEST_PATH_IMAGE107
；
Calculating the kilometer electricity consumption value of the network appointment car in the historical order data
Figure 101443DEST_PATH_IMAGE108
Wherein
Figure 666416DEST_PATH_IMAGE109
Representing the total mileage from the start to the end of order taking of the 1 st, 2 nd, k-th online appointment cars; acquiring the 1 st, 2 nd, s th cities in a preset rangeActual power consumption value of charging pile position
Figure 846862DEST_PATH_IMAGE110
And corresponding ideal power consumption value
Figure 446471DEST_PATH_IMAGE111
；
Calculating the actual power consumption value
Figure 303437DEST_PATH_IMAGE110
Corresponding ideal power consumption value
Figure 90128DEST_PATH_IMAGE111
Deviation value therebetween
Figure 74264DEST_PATH_IMAGE112
Will deviate from the value
Figure 325117DEST_PATH_IMAGE113
Sorting from small to large, then
Figure 103717DEST_PATH_IMAGE114
The passenger traffic route is made into deviation value
Figure 626971DEST_PATH_IMAGE113
And (4) the driving route of the charging pile in the s-th city corresponding to the minimum time in the historical database.
A recommendation system for customizing a passenger transport route by network taxi appointment comprises a historical order data acquisition module, an average power consumption value estimation module, an optimal route set making module and a passenger transport route limiting module;
the historical order data acquisition module is used for acquiring historical order data recorded in the passenger transport route recommendation system, wherein the historical order data comprises time points of historical orders, positions and distances of starting points and ending points of the historical orders, total mileage from the start of order taking to the end of order taking every day and total electricity consumption; acquiring an urban charging pile distribution circuit diagram and a hot station distribution circuit diagram recorded in a passenger transport route recommendation system;
the average power consumption value estimation module is used for estimating the average power consumption value of each order of the network appointment according to historical order data and setting a critical return power consumption residual threshold value, wherein the critical return power consumption residual threshold value is larger than the average power consumption value of each order;
the optimal route set making module is used for making a passenger transport route which does not fall below the critical return journey electricity consumption residual threshold value
Figure 149219DEST_PATH_IMAGE115
And the passenger transport route is lower than the critical return power consumption residual threshold
Figure 457841DEST_PATH_IMAGE116
The optimal route set is
Figure 141763DEST_PATH_IMAGE117
；
The passenger transport route definition module is used for defining time duration requirements and distance requirements in the optimal route set.
The optimal route set making module comprises
Figure 683472DEST_PATH_IMAGE115
Passenger transport route planning module and
Figure 478252DEST_PATH_IMAGE116
a passenger transport route making module;
Figure 906960DEST_PATH_IMAGE115
the passenger transport route formulating module comprises a power consumption preliminary judging module, a route analyzing module and an ideal radius planning module;
the power consumption preliminary judgment module is used for judging the magnitude relation between the power consumption of the first order and the average power consumption value of each order; the route analysis module is used for analyzing and judging whether the estimated time length and the estimated distance of the position of the first order and the position of the next order are both smaller than the corresponding actual time length and actual distance in the historical order; the ideal radius planning module is used for planning hot stations with ideal radius when the conditions that the ideal radius is smaller than the preset ideal radius are not met;
the ideal radius planning module comprises a circle domain formulation module, a hot site analysis module, a target set formulation module and an accuracy judgment module; the circle domain making module is used for connecting the boarding points in the historical order data and setting the boarding points meeting the distance requirement as a circle domain; the hot station analysis module is used for analyzing and obtaining the hot stations based on the number of the circular domains and the number of all boarding points in the historical order data; the target set formulation module is used for analyzing the positions of popular stations and correspondingly acquiring the actual duration and the actual distance in the historical order data for analysis; and the accuracy judging module is used for analyzing the ideal radius priority of the hot station before the network appointment according to the accuracy of the target duration set.
The accuracy judging module comprises an accuracy calculating module and an accuracy analyzing module; the accuracy analysis module comprises a brake data acquisition module and a brake frequency calculation module;
the accuracy calculation module is used for acquiring time length sequencing and sequencing from small to large of the target time length set, and comparing the similarity of the sequences of the time length sequencing and the sequencing from small to large to obtain a calculation value of accuracy;
the accuracy analysis module analyzes the ideal radius priority sequence when the accuracy is equal to 1 and the ideal radius priority when the accuracy is not equal to 1 according to the calculated value of the accuracy;
the brake data acquisition module is used for acquiring the corresponding brake times of the network appointment car when the accuracy is not equal to 1; and the brake frequency calculation module is used for analyzing the relation between the brake frequency and the running time of the corresponding network appointment vehicle and formulating an ideal time priority sequence with the accuracy not equal to 1 according to the corresponding relation.
Figure 27362DEST_PATH_IMAGE116
The passenger transport route formulating module comprises a critical data acquiring module, a kilometer electricity consumption value calculating module and a deviation value analyzing module;
the critical data acquisition module is used for acquiring an order end point position when the remaining electric quantity of the network appointment vehicle is greater than or equal to a critical return journey power consumption remaining threshold value, and an urban charging pile position within a preset range from the order end point position in historical order data, and acquiring the distance between the order end point and the urban charging pile within the preset range;
the kilometer electricity consumption value calculating module is used for calculating a kilometer electricity consumption value according to the total mileage from the start of order receiving to the end of order receiving of the network appointment car and the total electricity consumption;
the deviation value analysis module is used for acquiring an actual power consumption value and a corresponding ideal power consumption value of a city charging pile position in a preset range, and calculating an absolute value of the difference between the actual power consumption value and the ideal power consumption value as a deviation value; sorting the deviation values from small to large, and then obtaining the deviation values
Figure 528138DEST_PATH_IMAGE113
The minimum corresponding city charging pile driving route in the historical database is
Figure 392189DEST_PATH_IMAGE116
Passenger transport route.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (9)

1. A recommendation method for customizing a passenger line by a network appointment car is characterized by comprising the following specific steps:
acquiring historical order data, wherein the historical order data comprises time points of historical orders, positions and distances of starting and ending points of the historical orders, total mileage from the start of order taking to the end of order taking every day and total power consumption; the historical order data is stored in a passenger transport route recommendation system, and an urban charging pile distribution circuit diagram and a hot station distribution circuit diagram recorded in the passenger transport route recommendation system are obtained;
estimating average power consumption value of each order of network car booking based on historical order data in recommendation system
Figure DEST_PATH_IMAGE001
Wherein
Figure 481200DEST_PATH_IMAGE002
Represents the total electricity consumption from the beginning to the end of the order taking of the 1 st, 2 nd, and k network appointment cars,
Figure DEST_PATH_IMAGE003
representing the total order receiving quantity from the beginning to the end of the order receiving of the 1 st, 2 nd,. Setting critical return power consumption residual threshold
Figure 735595DEST_PATH_IMAGE004
The critical return power consumption remaining threshold value
Figure 395247DEST_PATH_IMAGE004
Greater than the average electricity consumption per order
Figure DEST_PATH_IMAGE005
；
Optimal route set in passenger transport route recommendation system
Figure 760500DEST_PATH_IMAGE006
The above-mentioned
Figure DEST_PATH_IMAGE007
Representing a passenger traffic route before not being below a critical return power consumption remaining threshold, said
Figure 759680DEST_PATH_IMAGE008
Representing the passenger transport route after being lower than the critical return electricity consumption residual threshold;
and recording the actual distance and the actual time length between the terminal of the last passenger and the starting point of the next passenger in the average adjacent orders in the historical order data of different networked appointments as L1 and T1 respectively, and the optimal route set
Figure DEST_PATH_IMAGE009
In
Figure 247293DEST_PATH_IMAGE007
And
Figure 331924DEST_PATH_IMAGE008
in the formulation process, it is required to satisfy that the predicted distance between the last passenger's terminal and the next passenger's starting point, L2, is less than L1, and the predicted time period, T2, is less than T1.
2. The method for recommending a customized passenger transport route by online booking, according to claim 1, wherein: the above-mentioned
Figure 828764DEST_PATH_IMAGE007
The passenger transport route planning comprises the following steps:
recording the driving data of a first order of the taxi appointment in the network of the day, wherein the driving data of the first order comprises the position of an order terminal and the power consumption of the order
Figure 479188DEST_PATH_IMAGE010
；
Determining the power consumption of the order
Figure 400352DEST_PATH_IMAGE010
Average electricity consumption value of each order
Figure DEST_PATH_IMAGE011
The relationship between the size of the order and the power consumption when the order is made
Figure 441121DEST_PATH_IMAGE010
Greater than the average electricity consumption per order
Figure 476073DEST_PATH_IMAGE011
And judging whether the position distance between the starting point of the next order and the end point of the first order meets the following requirements:
Figure 512162DEST_PATH_IMAGE012
and is
Figure 341578DEST_PATH_IMAGE014
；
If not satisfied
Figure 197538DEST_PATH_IMAGE012
And is
Figure 239444DEST_PATH_IMAGE014
Or when the distance does not satisfy L2=0 and T2=0, the network appointment is carried out to the hot station within the ideal radius of the terminal point of the order when the distance is carried out to receive the order; if it satisfies
Figure 598881DEST_PATH_IMAGE012
And is
Figure 130356DEST_PATH_IMAGE014
The online taxi appointment driver receives the order and goes to the starting point position of the order;
when the order is made
Figure 208034DEST_PATH_IMAGE010
Less than or equal to the average power consumption value of each order
Figure 850368DEST_PATH_IMAGE011
Then, selecting the corresponding order starting point position in the next order L2 when the order starting point position is the minimum value to drive; and if no next order is available, selecting the hot station within the ideal radius of the end point of the order when the distance is increased according to the recommendation system.
3. The method for recommending a customized passenger transport route by online booking, according to claim 2, wherein: the network appointment vehicle goes to a hot station within the ideal radius of the terminal point of the order for order taking when the distance is carried out, and the method comprises the following steps:
connecting the boarding points in the historical order data, wherein the connection standard is that the straight line distance between the boarding points of each order is smaller than a, and the boarding points meeting the requirement that the distance is smaller than a form a circular domain with the radius of b, the circular domain comprises all the boarding points of the connection, and b is larger than a;
the passenger transport route recommendation system obtains the number m of the formed circle areas and the number p of all boarding points in the historical order data, and calculates the average number of the boarding points in the circle areas in the historical order data as
Figure DEST_PATH_IMAGE015
Recording the circle area with the number of the upper vehicle points in the actual circle area larger than the number of the upper vehicle points in the average circle area as the hot station;
recording the position of the hot station, and acquiring the actual distance set of the order end point when the hot station distance in the historical order data is carried out
Figure 999065DEST_PATH_IMAGE016
And set of actual durations
Figure DEST_PATH_IMAGE017
(ii) a Aggregating the actual routes
Figure 170283DEST_PATH_IMAGE016
Sorting according to the order from small to large, and selecting the sorted set
Figure 735256DEST_PATH_IMAGE016
The actual routes corresponding to the hot stops with the median value of L2 being greater than or equal to L1 are taken as target route sets
Figure 118964DEST_PATH_IMAGE018
；
Obtaining a target range set
Figure 452994DEST_PATH_IMAGE018
Corresponding target duration set
Figure DEST_PATH_IMAGE019
The target duration set
Figure 795113DEST_PATH_IMAGE019
Expressed as the center of a circle with the end point of the order as the center of the circle in the historical order data,
Figure 847383DEST_PATH_IMAGE020
Setting the actual time length from the historical order end point to the hot site in the radius range as a target time length set;
determining a target duration set
Figure 769203DEST_PATH_IMAGE019
And analyzing the ideal radius priority of the hot station of the network taxi appointment according to the accuracy of the target duration set and the corresponding target distance set.
4. The method for recommending customized passenger transport routes by network appointment as claimed in claim 3, wherein: the set of judgment target durations
Figure 223318DEST_PATH_IMAGE019
According to the accuracy of the target duration set and the accuracy of the corresponding target distance set, the ideal radius priority of the hot station of the network taxi appointment advance is analyzed, and the method comprises the following steps:
obtaining a target duration set
Figure 470760DEST_PATH_IMAGE019
Time length ordering n1 in (1), and target time length set
Figure 275904DEST_PATH_IMAGE019
Calculating a target time length set in a sequence n2 from small to large
Figure 998485DEST_PATH_IMAGE019
Is measured to
Figure DEST_PATH_IMAGE021
Degree of similarity
Figure 41528DEST_PATH_IMAGE022
；
When the accuracy is high
Figure DEST_PATH_IMAGE023
Then, selecting the actual time length of the hot site corresponding to the time length less than T1 in the target time length set as an ideal time length set
Figure 397554DEST_PATH_IMAGE024
The priority order of the ideal radius is the ideal duration set
Figure 627678DEST_PATH_IMAGE024
Corresponding ideal course set
Figure 422459DEST_PATH_IMAGE025
The order of (a);
when the accuracy is high
Figure 992111DEST_PATH_IMAGE026
Selecting the actual time length of the hot station corresponding to the sequence n2 and smaller than T1 in the target time length set as an ideal time length set
Figure 352047DEST_PATH_IMAGE027
And
Figure 538308DEST_PATH_IMAGE028
and hot site analysis data corresponding to the sequence number value which does not meet the requirement from large to small in the middle length comprises the distance from the hot site to the end point of the order in the process, or the distance takes the end point of the order in the process as the circle center,
Figure 605622DEST_PATH_IMAGE029
The routes within the radius range correspond to the braking times in the total routes of the 1 st, 2 nd, and c th hot stop network appointment vehicles in the historical order data
Figure 560939DEST_PATH_IMAGE030
The hot station analysis data further comprises the length of the car appointment journey when the car is driven to the 1 st, 2 nd, e
Figure 55506DEST_PATH_IMAGE031
And calculating the braking frequency of the 1 st, 2 nd, and c th hot stations in the historical order data
Figure 460555DEST_PATH_IMAGE032
；
Will be provided with
Figure 331559DEST_PATH_IMAGE033
The formed sets are sorted from small to large, if the sorted sets
Figure 610224DEST_PATH_IMAGE033
Corresponding time length sequence and ideal time length set
Figure 85812DEST_PATH_IMAGE034
If the ideal radius is the same, the priority order of the ideal radius is the ideal duration set
Figure 918770DEST_PATH_IMAGE034
Corresponding ideal course set
Figure 859044DEST_PATH_IMAGE035
The order of (a).
5. The method for recommending a customized passenger transport route by online booking, according to claim 2, wherein: the above-mentioned
Figure 523374DEST_PATH_IMAGE036
The passenger transport route planning comprises the following steps:
recording the residual electric quantity of the network appointment car to reach the threshold value equal to the critical return journey power consumption residual electric quantity
Figure DEST_PATH_IMAGE037
The position of a current order and the position of the urban charging pile within a preset range from the end position of the order in historical order data are obtained, and the distance between the end position of the order and the distance between the charging pile of the 1 st, 2 nd, so, s th urban charging pile within the preset range and the distance between the end position of the order and the charging pile of the s th urban charging pile within the preset range are obtained
Figure 294497DEST_PATH_IMAGE038
；
Calculating the kilometer electricity consumption value of the network appointment car in the historical order data
Figure DEST_PATH_IMAGE039
Wherein
Figure 83592DEST_PATH_IMAGE040
Representing the total mileage from the beginning to the end of the order taking of the 1 st, 2 nd, and k network appointment cars; acquiring actual electricity of charging pile positions of 1 st, 2 nd, s cities in a preset rangeConsumption value
Figure DEST_PATH_IMAGE041
And corresponding ideal power consumption value
Figure 968503DEST_PATH_IMAGE042
；
Calculating the actual power consumption value
Figure 18499DEST_PATH_IMAGE041
Corresponding ideal power consumption value
Figure 85156DEST_PATH_IMAGE042
Deviation value therebetween
Figure DEST_PATH_IMAGE043
The deviation value
Figure 627127DEST_PATH_IMAGE044
Sorting from small to large, then
Figure 581308DEST_PATH_IMAGE045
The passenger traffic route is made into deviation value
Figure 689072DEST_PATH_IMAGE044
And (4) the driving route of the charging pile in the s-th city corresponding to the minimum time in the historical database.
6. A recommendation system for customizing a passenger transportation route by a networked car appointment applied to the method of any one of claims 1 to 5 is characterized by comprising a historical order data acquisition module, an average electricity consumption value estimation module, an optimal route set making module and a passenger transportation route limiting module;
the historical order data acquisition module is used for acquiring historical order data recorded in the passenger transport route recommendation system, wherein the historical order data comprises time points of historical orders, positions and distances of starting and ending points of the historical orders, and total mileage and total power consumption from starting to ending of receiving the orders every day; acquiring an urban charging pile distribution circuit diagram and a hot station distribution circuit diagram recorded in a passenger transport route recommendation system;
the average power consumption value estimation module is used for estimating the average power consumption value of each order of the network appointment according to historical order data and setting a critical return power consumption residual threshold value, wherein the critical return power consumption residual threshold value is larger than the average power consumption value of each order;
the optimal route set making module is used for making a passenger transport route which does not fall below a critical return journey electricity consumption residual threshold value
Figure 864314DEST_PATH_IMAGE046
And the passenger transport route is lower than the critical return power consumption residual threshold
Figure 221477DEST_PATH_IMAGE045
The optimal route set is
Figure 776086DEST_PATH_IMAGE047
；
The passenger transport route defining module is used for defining time duration requirements and distance requirements in the optimal route set.
7. The system of claim 6, wherein the vehicle-ordering passenger route recommendation system comprises: the optimal route set formulation module comprises
Figure 269516DEST_PATH_IMAGE046
Passenger transport route planning module and
Figure 618589DEST_PATH_IMAGE045
a passenger transport route making module; the above-mentioned
Figure 259785DEST_PATH_IMAGE046
The passenger transport route formulating module comprises a power consumption preliminary judging module, a route analyzing module and an ideal radius planning module;
the power consumption preliminary judgment module is used for judging the magnitude relation between the power consumption of the first order and the average power consumption value of each order; the route analysis module is used for analyzing and judging whether the estimated time length and the estimated distance between the position of the first order and the position of the next order are both smaller than the corresponding actual time length and actual distance in the historical order; the ideal radius planning module is used for planning hot stations with ideal radius when the conditions that the ideal radius is smaller than the preset radius are not met;
the ideal radius planning module comprises a circle domain formulation module, a hot site analysis module, a target set formulation module and an accuracy judgment module; the circle domain making module is used for connecting the boarding points in the historical order data and setting the boarding points meeting the distance requirement as a circle domain; the hot station analysis module is used for analyzing and obtaining the hot stations based on the number of the circular domains and the number of all boarding points in the historical order data; the target set formulation module is used for analyzing the positions of popular stations and correspondingly acquiring the actual duration and the actual distance in the historical order data for analysis; the accuracy judging module is used for analyzing the ideal radius priority of the hot station before the network appointment according to the accuracy of the target time length set.
8. The system of claim 7, wherein the vehicle-ordering passenger route recommendation system comprises: the accuracy judging module comprises an accuracy calculating module and an accuracy analyzing module; the accuracy analysis module comprises a brake data acquisition module and a brake frequency calculation module;
the accuracy calculation module is used for acquiring time length sequencing and sequencing from small to large of the target time length set, and comparing the similarity of the sequences of the time length sequencing and the sequencing from small to large to obtain an accuracy calculation value;
the accuracy analysis module analyzes the ideal radius priority sequence when the accuracy is equal to 1 and the ideal radius priority when the accuracy is not equal to 1 according to the calculated value of the accuracy;
the brake data acquisition module is used for acquiring the corresponding brake times of the network appointment car when the accuracy is not equal to 1; and the braking frequency calculation module is used for analyzing the relation between the braking frequency and the running time of the corresponding network appointment vehicle and formulating an ideal time priority sequence with the accuracy not equal to 1 according to the corresponding relation.
9. The system of claim 8, wherein the vehicle appointment system comprises: the described
Figure 83997DEST_PATH_IMAGE045
The passenger transport route formulating module comprises a critical data acquiring module, a kilometer electricity consumption value calculating module and a deviation value analyzing module;
the critical data acquisition module is used for acquiring an order end point position when the remaining electric quantity of the network appointment vehicle is greater than or equal to a critical return journey power consumption remaining threshold value, and an urban charging pile position within a preset range from the order end point position in historical order data, and acquiring the distance between the order end point and the urban charging pile within the preset range;
the kilometer electricity consumption value calculating module is used for calculating a kilometer electricity consumption value according to the total mileage from the start of order receiving to the end of order receiving of the network appointment car and the total electricity consumption;
the deviation value analysis module is used for acquiring an actual power consumption value and a corresponding ideal power consumption value of a city charging pile position in a preset range, and calculating an absolute value of the difference between the actual power consumption value and the ideal power consumption value as a deviation value; sorting the deviation values from small to large, and then obtaining the deviation values
Figure 104037DEST_PATH_IMAGE044
The minimum corresponding city charging pile driving route in the historical database is
Figure 561695DEST_PATH_IMAGE045
Passenger transport route.
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