CN111047138A - Taxi waiting aid decision-making method and system based on passenger carrying benefit analysis - Google Patents

Taxi waiting aid decision-making method and system based on passenger carrying benefit analysis Download PDF

Info

Publication number
CN111047138A
CN111047138A CN201911103514.9A CN201911103514A CN111047138A CN 111047138 A CN111047138 A CN 111047138A CN 201911103514 A CN201911103514 A CN 201911103514A CN 111047138 A CN111047138 A CN 111047138A
Authority
CN
China
Prior art keywords
taxi
waiting
time
passengers
area
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
CN201911103514.9A
Other languages
Chinese (zh)
Inventor
栾悉道
郭焰摩
蒋子怡
谭亿君
黄志坚
李方敏
王卫威
谢毓湘
肖湘江
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hunan Chaonengrobot Technology Co ltd
Changsha University
Original Assignee
Hunan Chaonengrobot Technology Co ltd
Changsha University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hunan Chaonengrobot Technology Co ltd, Changsha University filed Critical Hunan Chaonengrobot Technology Co ltd
Priority to CN201911103514.9A priority Critical patent/CN111047138A/en
Publication of CN111047138A publication Critical patent/CN111047138A/en
Withdrawn legal-status Critical Current

Links

Images

Classifications

    • 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
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • 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
    • G06Q30/0645—Rental transactions; Leasing transactions
    • 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
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Human Resources & Organizations (AREA)
  • Theoretical Computer Science (AREA)
  • Strategic Management (AREA)
  • Economics (AREA)
  • General Business, Economics & Management (AREA)
  • Data Mining & Analysis (AREA)
  • Development Economics (AREA)
  • Marketing (AREA)
  • Accounting & Taxation (AREA)
  • Mathematical Analysis (AREA)
  • Educational Administration (AREA)
  • Mathematical Physics (AREA)
  • Finance (AREA)
  • Tourism & Hospitality (AREA)
  • Computational Mathematics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Operations Research (AREA)
  • Mathematical Optimization (AREA)
  • Game Theory and Decision Science (AREA)
  • Software Systems (AREA)
  • Probability & Statistics with Applications (AREA)
  • Algebra (AREA)
  • General Engineering & Computer Science (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Quality & Reliability (AREA)
  • Evolutionary Biology (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Databases & Information Systems (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention discloses a taxi waiting aid decision-making method based on passenger carrying benefit analysis, which comprises the following steps: the method comprises the steps of obtaining the number of trains or planes arriving at a traffic hub in a time period, the average passenger number of each time of traffic tools and the proportion of the number of passengers taking taxis to the total number of passengers arriving at the traffic hub, calculating the number of passengers in a queuing state in a taxi waiting area of the traffic hub at the current moment, judging whether the current situation of taxi running tension exists in the traffic hub or not according to the obtained number of passengers, if so, calculating the waiting time of taxis according to the duration time and the total number of taxis queued in front of the current taxi at the current moment, and obtaining the predicted profit of the taxi according to the waiting time. The invention can solve the technical problems that taxis in the existing traffic hub are mistakenly selected to be queued in a waiting area or return to an urban area in a no-load manner, so that traffic resources are wasted, the operation efficiency of the taxis is reduced, and the operation cost of the taxis is increased.

Description

Taxi waiting aid decision-making method and system based on passenger carrying benefit analysis
Technical Field
The invention belongs to the technical field of traffic management, and particularly relates to a taxi waiting aid decision-making method and system based on passenger carrying benefit analysis.
Background
At present, there is a great demand for taxis at transportation hubs (such as airports, high-speed rail stations, etc.) that need to be connected to urban areas by highways. Considering the safety factor and the effectiveness of taxi management, special waiting areas and transfer areas (as shown in fig. 1) are often set in the transportation hubs, taxis are sequentially arranged in the waiting areas according to the entering sequence for waiting, and passengers are carried to leave after entering the transfer areas.
However, because taxis at the existing transportation hub lack effective channels for acquiring related traffic information and cost accounting strategies, on one hand, taxi drivers may choose to queue up for one hour or even several hours in a waiting area of the transportation hub, which may cause the reduction of urban taxi operation efficiency and the increase of taxi operation cost; on the other hand, the taxi driver may choose to give up waiting and return to the urban area without load, thereby causing waste of traffic resources and increasing the operation cost of the taxi.
Disclosure of Invention
Aiming at the defects or the improvement requirements in the prior art, the invention provides a taxi waiting aid decision-making method and a taxi waiting aid decision-making system based on passenger carrying benefit analysis, and aims to obtain the profit waiting in a waiting area and the profit returning to the urban area in a no-load mode respectively based on profit factors and cost factors, and compare the profit waiting in the waiting area and the profit returning to the urban area in a no-load mode to obtain an optimal waiting strategy, so that the technical problems that the taxi in the existing traffic hub is mistakenly selected to be queued in the waiting area or returned to the urban area in a no-load mode due to the lack of an effective traffic related information obtaining channel and a cost accounting strategy, traffic resources are wasted, the taxi operation efficiency is reduced, and the taxi operation cost is increased are.
In order to achieve the above object, according to an aspect of the present invention, there is provided a taxi waiting aid decision method based on passenger-carrying benefit analysis, which is applied to taxis located in a waiting area of a transportation hub, and includes the following steps:
(1) obtaining a time period ti-1Number N of trains or planes arriving at the terminali-1Time period ti-1Average number of passengers per vehicle α, and time period ti-1The proportion r of the number of the passengers taking the taxi to the total number of the passengers arriving at the traffic hub, wherein the time period ti-1Is the current time TiPrevious time T ofi-1To the current time TiThe time interval in between;
(2) obtaining the time period t according to the step (1)i-1Number N of trains or planes arriving at the terminali-1The current time T is calculated from the average passenger number α per trip of the vehicle and the ratio r of the number of passengers arriving at the traffic hub who take the taxi to the total number of passengersiPassenger number P in queuing state in taxi waiting area of traffic hubi：
Figure BDA0002270550560000021
Wherein t' represents the duration of the process from the time a taxi drives into the transfer area of the transportation hub until the taxi-mounted passenger leaves the transfer area of the transportation hub;
(3) the number P of passengers acquired according to the step (2)iJudging whether the current situation of taxi transport capacity shortage exists in the transportation hub, if yes, turning to the step (4), and if not, turning to the step (5);
(4) according to the duration T' and the current time TiThe total number n of taxis queued in front of the current taxiiCalculating waiting time T ═ n of taxiiT', then go to step (6);
(5) according to the total number n of taxis queued in front of the current taxiiNumber of passengers P in queueiAnd t' calculating the waiting time of the taxi
Figure BDA0002270550560000022
Then, the step (6) is carried out, wherein KiIs shown at the current time TiThe taxi waiting area arrival rate;
(6) obtaining the predicted profit F of the taxi continuously waiting in the taxi waiting area until the arrival of the passenger according to the waiting time T of the taxiA(T), specifically adopting the following formula:
FA(T)＝(M0+Mk·s)-(T·c+T·GP·β+s·GH·E)
wherein M is0Indicating the starting price of the taxi, MkRepresenting the freight rate per kilometer after the taxi exceeds the starting rate, s representing the distance from the traffic hub to the edge of the urban area, c representing the average human cost per hour of the taxi driver, GpIndicating the average fuel consumption of a taxi when the taxi is turned on, β indicating the proportionality coefficient, GHThe average fuel consumption of the taxi at high speed is shown, and E represents the fuel price.
(7) Obtaining the predicted profit F of the taxi returning to the edge of the urban area without load according to the waiting time T of the taxiB(T), specifically adopted isThe following formula:
FB(T)＝T·c-(s·GH·E+VL·T·GL·E)
wherein VLIndicating the average speed of the taxi in the urban area, GLThe average fuel consumption of the taxi in the urban area is shown.
(8) Calculating the predicted profit F obtained in the step (6)A(T) and predicted profit F from step (7)BDifference in profit between (T) W (T) FA(T)-FBAnd (T) judging whether the profit difference is greater than or equal to 0, if so, indicating that the taxi continues to wait in the taxi waiting area until the passenger arrives, and otherwise, indicating that the taxi returns to the edge of the city area in an unloaded manner.
Preferably, the time period t is acquired in step (1)i-1Number N of trains or planes arriving at the terminali-1Time period ti-1Average number of passengers per vehicle α, and time period ti-1The process of the proportion r of the number of the passengers taking the taxi to the total number of the passengers arriving at the traffic hub is obtained from a taxi dispatching center of the traffic hub in real time.
Preferably, the time period ti-1Is in the range of 15 to 30 minutes.
Preferably, the duration t' includes time taken for a taxi to enter a transfer area of the transportation hub, time taken for a passenger to walk to the rear of the taxi from a taxi waiting area, time taken for the passenger to open a taxi trunk to put in luggage and close the trunk, time taken for the passenger to walk to the taxi to open the door to sit in the taxi and close the door, time taken for a boarding area manager to confirm safety and allow the taxi to leave, and time taken for the taxi to take a passenger to leave the transfer area of the transportation hub.
Preferably, the number of passengers P obtained in step (3) according to step (2)iJudging whether the current situation of taxi transport capacity shortage exists in the traffic hub or not by judging whether P exists or noti+Ni·a·r≥niIf so, the situation that the taxi capacity is tense currently exists in the transportation hub is indicated, otherwise, the situation that the taxi capacity is not tense currently exists in the transportation hub is indicatedIn the situation of taxi transport capacity shortage.
Preferably, the current time TiTaxi waiting area passenger arrival rate KiEqual to:
Figure BDA0002270550560000041
according to another aspect of the present invention, there is provided a taxi waiting aid decision making system based on passenger-carrying benefit analysis, which is applied to taxis in a waiting area of a transportation hub, and includes:
a first module for obtaining a time period ti-1Number N of trains or planes arriving at the terminali-1Time period ti-1Average number of passengers per vehicle α, and time period ti-1The proportion r of the number of the passengers taking the taxi to the total number of the passengers arriving at the traffic hub, wherein the time period ti-1Is the current time TiPrevious time T ofi-1To the current time TiThe time interval in between;
a second module for obtaining the time period t according to the first modulei-1Number N of trains or planes arriving at the terminali-1The current time T is calculated from the average passenger number α per trip of the vehicle and the ratio r of the number of passengers arriving at the traffic hub who take the taxi to the total number of passengersiPassenger number P in queuing state in taxi waiting area of traffic hubi：
Figure BDA0002270550560000042
Wherein t' represents the duration of the process from the time a taxi drives into the transfer area of the transportation hub until the taxi-mounted passenger leaves the transfer area of the transportation hub;
a third module for obtaining the number P of passengers according to the second moduleiJudging whether the current situation of taxi transport capacity shortage exists in the transportation hub, if yes, switching to a fourth module, and otherwise, switching to a fifth module;
a fourth module for determining the duration T' and the current time TiThe total number n of taxis queued in front of the current taxiiCalculating waiting time T ═ n of taxiiT', then go to the sixth module;
a fifth module for counting n taxis queued in front of the current taxiiNumber of passengers P in queueiAnd t' calculating the waiting time of the taxi
Figure BDA0002270550560000051
Then go to the sixth module, where KiIs shown at the current time TiThe taxi waiting area arrival rate;
a sixth module for obtaining the predicted profit F of the taxi continuously waiting in the waiting area until the arrival of the passenger according to the waiting time T of the taxiA(T), specifically adopting the following formula:
FA(T)＝(M0+Mk·s)-(T·c+T·GP·β+s·GH·E)
wherein M is0Indicating the starting price of the taxi, MkRepresenting the freight rate per kilometer after the taxi exceeds the starting rate, s representing the distance from the traffic hub to the edge of the urban area, c representing the average human cost per hour of the taxi driver, GpIndicating the average fuel consumption of a taxi when the taxi is turned on, β indicating the proportionality coefficient, GHThe average fuel consumption of the taxi at high speed is shown, and E represents the fuel price.
A seventh module for obtaining the predicted profit F of the taxi returning to the edge of the urban area without load according to the waiting time T of the taxiB(T), specifically adopting the following formula:
FB(T)＝T·c-(s·GH·E+VL·T·GL·E)
wherein VLIndicating the average speed of the taxi in the urban area, GLThe average fuel consumption of the taxi in the urban area is shown.
An eighth module for calculating the predicted profit F obtained by the sixth moduleA(T) and a seventh Module toPredicted profit FBDifference in profit between (T) W (T) FA(T)-FBAnd (T) judging whether the profit difference is greater than or equal to 0, if so, indicating that the taxi continues to wait in the taxi waiting area until the passenger arrives, and otherwise, indicating that the taxi returns to the edge of the city area in an unloaded manner.
In general, compared with the prior art, the above technical solution contemplated by the present invention can achieve the following beneficial effects:
(1) according to the invention, various income factors and cost factors influencing the income of a taxi driver are comprehensively considered, the passenger carrying benefit is analyzed and calculated based on the income factors and the cost factors, and finally, a taxi passenger carrying selection scheme of a traffic hub is provided for the taxi driver according to the calculation result, so that the taxi driver does not blindly or mistakenly select to queue in a waiting area or return to an urban area without load, thereby avoiding traffic resource waste, improving the taxi operation efficiency and reducing the taxi operation cost;
(2) the parameters for reflecting the profit factors and the cost factors are obtained in real time, so that the timeliness and the accuracy of the obtained result can be ensured;
(3) the invention can be widely applied to various transportation hubs including high-speed railway stations, airports and the like, and has better applicability.
Drawings
Fig. 1 is a schematic view of a taxi transfer area and a waiting area provided in a transportation hub;
fig. 2 is a flow chart of the taxi waiting aid decision-making method based on passenger carrying benefit analysis.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other.
As shown in fig. 2, the invention provides a taxi waiting aid decision-making method based on passenger carrying benefit analysis, which is applied to taxis in a waiting area of a transportation hub, and comprises the following steps:
(1) obtaining a time period ti-1The number Ni-1 of trains or planes arriving at the traffic hub in the interior and the time period ti-1Average number of passengers per vehicle α, and time period ti-1The proportion r of the number of the passengers taking the taxi to the total number of the passengers arriving at the traffic hub, wherein the time period ti-1Is the current time TiPrevious time T ofi-1To the current time TiThe time interval in between;
specifically, the transportation hub in the present invention includes a train station, an airport, and the like.
In this step, the process of obtaining the four parameters is all obtained in real time from a taxi dispatching center of the transportation hub.
Specifically, the time period ti-1Is in the range of 15 to 30 minutes, preferably 20 minutes.
(2) Obtaining the time period t according to the step (1)i-1Number N of trains or planes arriving at the terminali-1The current time T is calculated from the average passenger number α per trip of the vehicle and the ratio r of the number of passengers arriving at the traffic hub who take the taxi to the total number of passengersiPassenger number P in queuing state in taxi waiting area of traffic hubi：
Figure BDA0002270550560000071
Wherein t' represents the duration of the process from the time a taxi enters a transfer area of a transportation hub (as shown in fig. 1) until the taxi-mounted passenger leaves the transfer area of the transportation hub;
the duration is analyzed to be composed of six parts, and the corresponding symbols and descriptions of the parts are shown in the following table 1:
TABLE 1 composition of duration
Figure BDA0002270550560000072
The duration t' can be expressed as:
Figure BDA0002270550560000073
empirically, values were taken for six portions of the duration and the sum was calculated as in table 2 below (it should be understood that this is for exemplary purposes only and is not intended to limit the invention specifically):
TABLE 2 values and sums of the various fractions of the duration (units: seconds)
Figure BDA0002270550560000074
(3) The number P of passengers acquired according to the step (2)iJudging whether the current situation of taxi capacity shortage (namely, few taxis but many passengers) exists in the traffic hub, if so, turning to the step (4), otherwise, turning to the step (5);
specifically, the number of passengers P obtained in the step (2) in this stepiJudging whether the current situation of taxi transport capacity shortage exists in the traffic hub or not by judging whether P exists or noti+Ni·a·r≥niIf so, indicating that the current taxi capacity tension condition exists in the traffic hub, otherwise indicating that the current taxi capacity tension condition does not exist in the traffic hub, wherein niIndicates the current time TiThe total number of taxis queued ahead of the current taxi.
(4) According to the current time TiThe total number n of taxis queued in front of the current taxiiAnd T' calculating the waiting time T ═ n of the taxiiT', then go to step (6);
(5) according to the total number n of taxis queued in front of the current taxiiNumber of passengers P in queueiAnd t' calculating the waiting time of the taxi
Figure BDA0002270550560000081
Then, the step (6) is carried out, wherein KiIs shown at the current time TiThe taxi waiting area has the following arrival rate:
Figure BDA0002270550560000082
(6) obtaining the predicted profit F of the taxi continuously waiting in the taxi waiting area until the arrival of the passenger according to the waiting time T of the taxiA(T), specifically adopting the following formula:
FA(T)＝(M0+Mk·s)-(T·c+T·GP·β+s·GH·E)
wherein M is0Indicating the starting price of the taxi, MkRepresenting the freight rate per kilometer after the taxi exceeds the starting rate, s representing the distance from the traffic hub to the edge of the urban area, c representing the average human cost per hour of the taxi driver, GpRepresenting the average fuel consumption when the taxi is on air-conditioned, β representing the proportionality coefficient (when the taxi is on air-conditioned, its value is 1, when the taxi is not on air-conditioned, its value is 0), GHIndicating the average fuel consumption of the taxi at high speed and E indicating the fuel price (unit is yuan/liter).
(7) Obtaining the predicted profit F of the taxi returning to the edge of the urban area without load according to the waiting time T of the taxiB(T), specifically adopting the following formula:
FB(T)＝T·c-(s·GH·E+VL·T·GL·E)
wherein VLIndicating the average speed of the taxi in the urban area, GLThe average fuel consumption of the taxi in the urban area is shown.
(8) Calculating the predicted profit F obtained in the step (6)A(T) and predicted profit F from step (7)BDifference in profit between (T) W (T) FA(T)-FB(T) and judging whether the profit difference is more than or equal to 0, if so, indicating that the taxi continues to wait in the taxi waiting area until the passenger arrives, otherwise, indicating that the taxi rentsThe vehicle returns to the edge of the urban area in an empty state.
Test results
(1) Selection of parameter values
Taking Changsha city as an example, the values of the parameters of the airport and the high-speed rail station in the city are obtained by looking up at hundred degrees, and the following table 3:
TABLE 3 values of the parameters for the long sand airport and high-speed rail
Figure BDA0002270550560000091
(2) Selection of a scheme
The parameter values in table 3 are respectively substituted into the predicted profit expressions of the scheme a (i.e. taxis continue to wait in the taxi waiting area until passengers arrive) and the scheme B (i.e. taxis return to the edge of the urban area without load), i.e. the formulas in steps (6) and (7), so as to obtain the selection schemes in spring, autumn and summer and winter of Changsha, which are determined by the number of taxis waiting in line and the number of train/plane flights arriving at the transportation hub, as shown in table 4 below:
TABLE 4 selection schemes in spring and autumn for south station (high-speed rail) of Changsha city
Figure BDA0002270550560000092
As can be seen from table 4, if taxi drivers are in line at the southern station of the hsha high-speed railway, if taxi drivers are found to have more than 45 cars in line waiting for passengers, the taxi drivers can leave the high-speed railway directly without the taxi, and the profit is even greater.
TABLE 5 selection scheme of Changsha Huanghua airport in summer and winter
Figure BDA0002270550560000101
As can be seen from table 5, if taxi drivers are queued up in the daylily airport in summer and winter, and if more than 100 taxis are found in front to wait for passengers in queue, the taxi drivers can leave the airport directly without leaving the airport and return to the urban area to carry passengers, which is more beneficial.
TABLE 6 selection scheme of Changsha Huanghua airport in spring and autumn
Figure BDA0002270550560000102
Table 6 is an auxiliary decision table for car renters in spring and autumn at the daylily airport, and comparing the table with table 5, it can be found that the difference between the spring and autumn and the summer and winter is not large, and the difference varies from 101 to 103 vehicles. That is, the driver can choose to wait in line no matter what season, no matter how many flights arrive, as long as the number of passengers is sufficient and the number of passengers is less than 101-103. And the number of the devices exceeds 101-103, so that no queuing is needed.
It will be understood by those skilled in the art that the foregoing is only a preferred embodiment of the present invention, and is not intended to limit the invention, and that any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (7)

1. A taxi waiting aid decision-making method based on passenger carrying benefit analysis is applied to taxis in waiting areas of traffic hubs, and is characterized by comprising the following steps:
(1) obtaining a time period ti-1Number N of trains or planes arriving at the terminali-1Time period ti-1Average number of passengers per vehicle α, and time period ti-1The proportion r of the number of the passengers taking the taxi to the total number of the passengers arriving at the traffic hub, wherein the time period ti-1Is the current time TiPrevious time T ofi-1To the current time TiThe time interval in between;
(2) obtaining the time period t according to the step (1)i-1Number N of trains or planes arriving at the terminali-1The current time T is calculated from the average passenger number α per trip of the vehicle and the ratio r of the number of passengers arriving at the traffic hub who take the taxi to the total number of passengersiTraffic pivotNumber P of passengers in queuing state in taxi waiting area of Newmani：
Figure FDA0002270550550000011
Wherein t' represents the duration of the process from the time a taxi drives into the transfer area of the transportation hub until the taxi-mounted passenger leaves the transfer area of the transportation hub;
(3) the number P of passengers acquired according to the step (2)iJudging whether the current situation of taxi transport capacity shortage exists in the transportation hub, if yes, turning to the step (4), and if not, turning to the step (5);
(4) according to the duration T' and the current time TiThe total number n of taxis queued in front of the current taxiiCalculating waiting time T ═ n of taxiiT', then go to step (6);
(5) according to the total number n of taxis queued in front of the current taxiiNumber of passengers P in queueiAnd t' calculating the waiting time of the taxi
Figure FDA0002270550550000012
Then, the step (6) is carried out, wherein KiIs shown at the current time TiThe taxi waiting area arrival rate;
(6) obtaining the predicted profit F of the taxi continuously waiting in the taxi waiting area until the arrival of the passenger according to the waiting time T of the taxiA(T), specifically adopting the following formula:
FA(T)＝(M0+Mk·s)-(T·c+T·GP·β+s·GH·E)
wherein M is0Indicating the starting price of the taxi, MkRepresenting the freight rate per kilometer after the taxi exceeds the starting rate, s representing the distance from the traffic hub to the edge of the urban area, c representing the average human cost per hour of the taxi driver, GpIndicating the average fuel consumption of a taxi when the taxi is turned on, β indicating the proportionality coefficient, GHIndicating average fuel consumption of taxi at high speedAnd E represents oil price.
(7) Obtaining the predicted profit F of the taxi returning to the edge of the urban area without load according to the waiting time T of the taxiB(T), specifically adopting the following formula:
FB(T)＝T·c-(s·GH·E+VL·T·GL·E)
wherein VLIndicating the average speed of the taxi in the urban area, GLThe average fuel consumption of the taxi in the urban area is shown.
(8) Calculating the predicted profit F obtained in the step (6)A(T) and predicted profit F from step (7)BDifference in profit between (T) W (T) FA(T)-FBAnd (T) judging whether the profit difference is greater than or equal to 0, if so, indicating that the taxi continues to wait in the taxi waiting area until the passenger arrives, and otherwise, indicating that the taxi returns to the edge of the city area in an unloaded manner.
2. The taxi waiting aid decision making method according to claim 1, wherein the time period t is obtained in the step (1)i-1Number N of trains or planes arriving at the terminali-1Time period ti-1Average number of passengers per vehicle α, and time period ti-1The process of the proportion r of the number of the passengers taking the taxi to the total number of the passengers arriving at the traffic hub is obtained from a taxi dispatching center of the traffic hub in real time.
3. The taxi waiting aid decision making method according to claim 1 or 2, wherein the time period t isi-1Is in the range of 15 to 30 minutes.
4. The taxi waiting aid decision making method according to any one of claims 1 to 3, wherein the duration t' comprises the time taken for a taxi to enter a transfer area of a transportation hub, the time taken for a passenger to walk from the taxi waiting area to the tail of the taxi, the time taken for the passenger to open a taxi trunk to put luggage in and close the trunk, the time taken for the passenger to walk to the taxi to open the door to sit in the taxi and close the door, the time taken for a boarding area manager to confirm safety and allow the taxi to leave, and the time taken for the taxi to carry passengers to leave the transfer area of the transportation hub.
5. The taxi waiting aid decision making method according to any one of claims 1 to 4, wherein the number P of passengers obtained in step (3) according to step (2)iJudging whether the current situation of taxi transport capacity shortage exists in the traffic hub or not by judging whether P exists or noti+Ni·a·r≥niIf so, the situation that the taxi capacity is tense currently exists in the traffic hub is indicated, otherwise, the situation that the taxi capacity is tense currently does not exist in the traffic hub is indicated.
6. The taxi waiting aid decision making method according to any one of claims 1 to 5, wherein the current time T isiTaxi waiting area passenger arrival rate KiEqual to:
Figure FDA0002270550550000031
7. a taxi waiting aid decision-making system based on passenger carrying benefit analysis is applied to taxis in waiting areas of traffic hubs, and is characterized by comprising the following steps:
a first module for obtaining a time period ti-1Number N of trains or planes arriving at the terminali-1Time period ti-1Average number of passengers per vehicle α, and time period ti-1The proportion r of the number of the passengers taking the taxi to the total number of the passengers arriving at the traffic hub, wherein the time period ti-1Is the current time TiPrevious time T ofi-1To the current time TiThe time interval in between;
a second module for obtaining the time period t according to the first modulei-1Of trains or aircraft arriving at traffic junctions internallyNumber Ni-1The current time T is calculated from the average passenger number α per trip of the vehicle and the ratio r of the number of passengers arriving at the traffic hub who take the taxi to the total number of passengersiPassenger number P in queuing state in taxi waiting area of traffic hubi：
Figure FDA0002270550550000032
Wherein t' represents the duration of the process from the time a taxi drives into the transfer area of the transportation hub until the taxi-mounted passenger leaves the transfer area of the transportation hub;
a third module for obtaining the number P of passengers according to the second moduleiJudging whether the current situation of taxi transport capacity shortage exists in the transportation hub, if yes, switching to a fourth module, and otherwise, switching to a fifth module;
a fourth module for determining the duration T' and the current time TiThe total number n of taxis queued in front of the current taxiiCalculating waiting time T ═ n of taxiiT', then go to the sixth module;
a fifth module for counting n taxis queued in front of the current taxiiNumber of passengers P in queueiAnd t' calculating the waiting time of the taxi
Figure FDA0002270550550000041
Then go to the sixth module, where KiIs shown at the current time TiThe taxi waiting area arrival rate;
a sixth module for obtaining the predicted profit F of the taxi continuously waiting in the waiting area until the arrival of the passenger according to the waiting time T of the taxiA(T), specifically adopting the following formula:
FA(T)＝(M0+Mk·s)-(T·c+T·GP·β+s·GH·E)
wherein M is0Indicating the starting price of the taxi, MkIndicating taxiFreight per kilometer after exceeding starting price, s represents distance from traffic hub to urban edge, c represents average hourly human cost for taxi drivers, GpIndicating the average fuel consumption of a taxi when the taxi is turned on, β indicating the proportionality coefficient, GHThe average fuel consumption of the taxi at high speed is shown, and E represents the fuel price.
A seventh module for obtaining the predicted profit F of the taxi returning to the edge of the urban area without load according to the waiting time T of the taxiB(T), specifically adopting the following formula:
FB(T)＝T·c-(s·GH·E+VL·T·GL·E)
wherein VLIndicating the average speed of the taxi in the urban area, GLThe average fuel consumption of the taxi in the urban area is shown.
An eighth module for calculating the predicted profit F obtained by the sixth moduleA(T) and predicted profit F from the seventh ModuleBDifference in profit between (T) W (T) FA(T)-FBAnd (T) judging whether the profit difference is greater than or equal to 0, if so, indicating that the taxi continues to wait in the taxi waiting area until the passenger arrives, and otherwise, indicating that the taxi returns to the edge of the city area in an unloaded manner.
CN201911103514.9A 2019-11-13 2019-11-13 Taxi waiting aid decision-making method and system based on passenger carrying benefit analysis Withdrawn CN111047138A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911103514.9A CN111047138A (en) 2019-11-13 2019-11-13 Taxi waiting aid decision-making method and system based on passenger carrying benefit analysis

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911103514.9A CN111047138A (en) 2019-11-13 2019-11-13 Taxi waiting aid decision-making method and system based on passenger carrying benefit analysis

Publications (1)

Publication Number Publication Date
CN111047138A true CN111047138A (en) 2020-04-21

Family

ID=70232664

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911103514.9A Withdrawn CN111047138A (en) 2019-11-13 2019-11-13 Taxi waiting aid decision-making method and system based on passenger carrying benefit analysis

Country Status (1)

Country Link
CN (1) CN111047138A (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111626479A (en) * 2020-04-30 2020-09-04 南京邮电大学 Taxi passenger flow distribution point passenger carrying decision method and system based on real-time data
CN113158462A (en) * 2021-04-21 2021-07-23 电子科技大学成都学院 Method for selecting taxi dispatching mode
CN113192354A (en) * 2021-04-02 2021-07-30 浙江浙大中控信息技术有限公司 Large-scale station waiting duration prediction method based on time pane state probability
CN114372688A (en) * 2021-12-29 2022-04-19 广州交信投科技股份有限公司 Passenger station taxi capacity scheduling method, system, computer device and storage medium
CN115619133A (en) * 2022-09-29 2023-01-17 北京交通大学 Airport terminal taxi transportation capacity allocation method considering driver decision

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111626479A (en) * 2020-04-30 2020-09-04 南京邮电大学 Taxi passenger flow distribution point passenger carrying decision method and system based on real-time data
CN113192354A (en) * 2021-04-02 2021-07-30 浙江浙大中控信息技术有限公司 Large-scale station waiting duration prediction method based on time pane state probability
CN113192354B (en) * 2021-04-02 2022-06-17 浙江中控信息产业股份有限公司 Large-scale station waiting duration prediction method based on time pane state probability
CN113158462A (en) * 2021-04-21 2021-07-23 电子科技大学成都学院 Method for selecting taxi dispatching mode
CN114372688A (en) * 2021-12-29 2022-04-19 广州交信投科技股份有限公司 Passenger station taxi capacity scheduling method, system, computer device and storage medium
CN115619133A (en) * 2022-09-29 2023-01-17 北京交通大学 Airport terminal taxi transportation capacity allocation method considering driver decision

Similar Documents

Publication Publication Date Title
CN111047138A (en) Taxi waiting aid decision-making method and system based on passenger carrying benefit analysis
CN107563683A (en) Passenger and goods collaboration transportation resources and system in a kind of city
CN110751366A (en) Method for calculating running capacity matching degree of main railway and urban rail transit
CN110020745A (en) Real-time large aerospace hinge parking lot scale forecast method based on flight schedule
Justin et al. Demand modeling and operations optimization for advanced regional air mobility
CN110889591A (en) Decision method for passenger carrying problem of airport taxi
Čulík et al. Alternative taxi services and their cost analysis
CN111445091B (en) Intelligent decision-making method for taxi driver in passenger transport center
CN111369065B (en) Method for determining minimum marshalling number of goods train based on time window constraint
CN111325649B (en) Urban rail transit combined station stopping method
Bogumil et al. Analysis of the main risks in the development and implementation of unmanned vehicles of urban passenger transport
CN111047159B (en) Airport taxi passenger carrying distribution method
CN110400025A (en) It is a kind of to alleviate congested in traffic method, system and utilization
Baron Air transport efficiency and its measures
Pollard et al. Summary of opportunities to conserve transportation energy
CN116704763B (en) Intelligent bus team dynamic formation method considering bus operation scheme
CN117649761A (en) Bus intermediate station line bearing capacity calculation method considering characteristics of stations and road sections
De Beer Strategic assessment of the impact of the priority infrastructure on the perfomance of minibus-taxi services in the context of south africa
Liu et al. Research of emergency feeder bus scheme for urban rail transit under unexpected incident
Rote et al. The US market for high-speed maglev vehicles
Turvey et al. Optimal bus fares
Lukasiewicz Public policy and technology: Passenger rail in Canada as an issue in modernization
Janić et al. Modelling Performances of the Airport Access Modes and Their Systems
Fu et al. The Impact of Changsha Maglev Line on Land-Side Transportation of Changsha Huanghua International Airport
Pickrell Urban rail in America: A review of procedures and recommendations from the regional plan association study

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WW01 Invention patent application withdrawn after publication
WW01 Invention patent application withdrawn after publication

Application publication date: 20200421