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CN108764606B - Shared bicycle system scheduling method based on dynamic scheduling time domain - Google Patents

Shared bicycle system scheduling method based on dynamic scheduling time domain Download PDF

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CN108764606B
CN108764606B CN201810306284.5A CN201810306284A CN108764606B CN 108764606 B CN108764606 B CN 108764606B CN 201810306284 A CN201810306284 A CN 201810306284A CN 108764606 B CN108764606 B CN 108764606B
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刘冬旭
董红召
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ZHEJIANG RADIO AND TV UNIVERSITY
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Abstract

The shared bicycle system scheduling method based on the dynamic scheduling time domain comprises the following steps: step 1, determining basic parameters for BSS dynamic scheduling time domain judgment; step 2, a judgment acquisition method of a BSS dynamic scheduling time domain; and 3, using the dynamic scheduling time domain obtained in the step 2 for bicycle scheduling of the BSS service point.

Description

Shared bicycle system scheduling method based on dynamic scheduling time domain
Technical Field
The invention relates to a scheduling method of a bicycle sharing system, and belongs to the field of intelligent transportation.
Background
The shared Bicycle System (BSS) is currently divided into a lock-pile BSS (public Bicycle) and a lock-pile-free BSS (shared Bicycle), the lock-pile BSS provides a renting and returning service through a self-service renting point, and the shared Bicycle solves the problem of disordered parking through electronic fences and other modes. However, both of them have the limitation of bicycle parking capacity, and face the problem of unbalanced space-time distribution of the travel demand, and it is difficult to rent and return a bicycle to be a common phenomenon of two BSSs, so the BSS service point balance scheduling technology becomes the focus of research. When scheduling starts and how long it is done, which affects the scheduling efficiency, cost and service level of BSS, so it is very important to study the timing of BSS service point scheduling.
In order to solve the problems, reasonable scheduling time can be obtained through analysis of historical data of BSS operation, and therefore a BSS automatic flow model and a method for judging and obtaining a BSS dynamic scheduling time domain are provided. The scheduling time domain is a time interval when the BSS service point is continuously in a state of needing to call in or out bicycles, aims to help a manager select the optimal scheduling time, and reduces scheduling frequency as much as possible even if the BSS service point cannot rent or call out bicycles.
Disclosure of Invention
The invention provides a shared bicycle system scheduling method based on a dynamic scheduling time domain, aiming at overcoming the defects of the scheduling problem of the existing shared bicycle system.
The invention discloses a shared bicycle system scheduling method for dynamically scheduling a time domain, which comprises the following steps:
step 1, determining basic parameters for BSS dynamic scheduling time domain judgment.
The BSS self-flow model is used for obtaining the travel rule of the bicycle user, and the BSS self-flow model is also an important decision basis for the BSS manager to select the time and the service points to be scheduled. The basic parameters comprise bicycle turnover rate of a service point, difference of renting and returning amount and bicycle-to-volume ratio.
(1.1) calculating bicycle renting and returning amount of a service point;
bicycle renting and returning amount Z of service point i in certain time period taui(tau) is the number of vehicles returned in the period
Figure BDA0001621072250000021
And the number of borrowed vehicles
Figure BDA0001621072250000022
The calculation method of the sum of (a) is shown in formula (1):
Figure BDA0001621072250000023
(1.2) calculating the bicycle turnover rate of the service point;
cycle rate r of service point i at certain time period taui(τ) includes the cycle rate r of borrowingi in(τ) and Return turnover Rate ri in(τ) and the cycle rate of borrowing/returning is respectively defined as the bicycle renting/returning amount of the service point i in the time period τ and the parking capacity E of the service pointiThe calculation method of the ratio of (the number of the locking piles or the design capacity of the electronic fence) is shown as the formula (2):
Figure BDA0001621072250000024
(1.3) calculating a difference of the renting amount of the service points;
the bicycle renting amount and returning amount of the service point change along with time, the tide phenomenon is caused by imbalance, and therefore a renting and returning amount difference parameter L is introducedi(τ) to represent the bicycle renting amount difference of the service point i in the time period τ, the calculation method is shown as (3).
Figure BDA0001621072250000025
(1.4) calculating a vehicle-to-volume ratio of a service point;
here defined as the number of bicycles q held by a certain service point i at time ti(t) parking capability E of the service PointiThe ratio of the two is in the range of [0,1 ]]This is an important concept for characterizing the time-varying characteristics of the service point, let t0As an initial time, qi(t0) The initial bicycle holding capacity of the service point i and the bicycle-to-volume ratio H of the service point i at the time ti(t) will be subject to a previous rental difference Li(t-t0) The direct influence of (2) is calculated as shown in equation (4).
Figure BDA0001621072250000031
And step 2, a judgment and acquisition method of a BSS dynamic scheduling time domain.
(2.1) obtaining the empty/full vehicle capacity ratio threshold value of the service point
The difference of renting amount and the change of the car-to-capacity ratio of the service point can cause the service point to enter an empty/full state when L is in a certain time intervali(τ)＞0，Hi(t) will continue to become smaller or even close to 0, the service point enters the vacant state and borrowing is difficult, and when LiWhen (τ) < 0, HiAnd (t) continuously increasing until the service point approaches 1, entering a full state, and difficult to return. Order to
Figure BDA0001621072250000032
Indicating full vehicle capacityThe value of the bit threshold is set in the bit-line,
Figure BDA0001621072250000034
indicating a vehicle-to-capacity vacancy threshold, a vehicle-to-capacity threshold
Figure BDA0001621072250000033
And the judgment rule of the service point i state is as follows:
Figure BDA0001621072250000035
and (4) a normal state.
Figure BDA0001621072250000036
The vacant state, requiring the bicycle to be recumbent, is called "positive dispatch".
Figure BDA0001621072250000037
In a full state, the bicycle needs to be called out, which is called as negative dispatching.
According to the BSS self-flow model, the time periods of the service points in the empty positions and the full positions, namely the dynamic time domain of the intervention scheduling can be calculated. The ideal service point vehicle-to-capacity ratio threshold value has the following value range: [0,1]In the actual operation process, when only a small amount of bicycles can be lent out at the service point or the empty lock pile can be returned, the empty/full state is defined, namely the vehicle volume is smaller than the threshold range. Meanwhile, service points with high turnover rate often have higher influence on resident travel and the whole BSS, so corresponding scheduling needs to be arranged in advance, namely, the range of the vehicle-to-capacity ratio threshold value is reduced. The empty/full car-to-capacity ratio threshold value is based on overall consideration of the dispatching response speed and the bicycle turnover rate of the service point
Figure BDA0001621072250000045
Obtained from the formulae (5) and (6).
Figure BDA0001621072250000041
Figure BDA0001621072250000042
Here, τ is a time period, and one day of a certain working day and holiday may be sampled.
[ωmin,ωmax]The dispatching demand dispatching vehicle is an empty and full bit judgment reference threshold value related to dispatching response speed, if the dispatching delay is not considered, namely the dispatching vehicle can arrive at the site immediately after the dispatching demand dispatching vehicle is sent out by the service point, the service point can wait until the state of the service point becomes completely empty (no bicycle) or full (no empty lock pile), then the dispatching request is sent out, the vehicle-to-volume ratio is 0 and 1, and therefore the reference threshold value is also taken as [0,1 ]]But in practice there is a delay in arrival of the dispatch vehicle at the site, so the reference threshold range should be less than [0,1 ]]Moreover, the faster the BSS response speed is, i.e., the shorter the time required for the dispatching vehicle to reach the site is, the closer the reference threshold value is to [0,1 ]]。
ri(τ) bicycle turnover at service Point i, riThe larger the value of (τ) is, the more important the service point is in the BSS, and the earlier the scheduling should be intervened. r ismax(τ) is the maximum value of all service points turnover rate, rmin(τ) is the minimum value for the value,
Figure BDA0001621072250000043
is the turnover number riNormalized value of (tau) over a range of [0,1 ]]. The bicycle turnover rate localization coefficient is used for representing the influence degree of the bicycle turnover rate of the service point on the bicycle capacity ratio threshold value, and if the value is larger, the influence of the bicycle turnover rate of different service points on the bicycle capacity ratio threshold value is larger. Desired vehicle-to-volume ratio (defined as
Figure BDA0001621072250000044
) Is a threshold value
Figure BDA0001621072250000046
The intermediate value of (c), in the case of a balanced and stable turnover,
Figure BDA0001621072250000051
bicycle inventory design for instant service pointHalf of the parking capacity.
(2.2) obtaining a vehicle-to-volume ratio threshold value considering a difference in rental amount for the next period
In the actual operation process of the BBS, the turnover rate of a service point is often not in a balanced and stable state, and the expected vehicle-to-volume ratio
Figure BDA0001621072250000052
Also subject to a rental difference L for the next periodi(τ) if the next period lease amount is greater than the return amount, Li(τ) > 0, the desired vehicle-to-capacity ratio should be greater than 0.5, and the vehicle-to-capacity ratio threshold also shifts to the right; otherwise, the expected vehicle-to-volume ratio should be less than 0.5, and the threshold value is shifted left. Let TtRepresenting a time period with the time length T from the time T, and the expected vehicle-to-volume ratio of each time period
Figure BDA0001621072250000053
And vehicle-to-capacity threshold
Figure BDA00016210722500000511
The algorithm is further improved as in equations (7) - (9):
Figure BDA0001621072250000054
Figure BDA0001621072250000055
Figure BDA0001621072250000056
here, Tt+TRepresenting a period starting at time T + T and having a duration T, i.e. TtLi(Tt+T) Service point i is at TtThe rental amount for the next period is different,
Figure BDA0001621072250000057
value range of [ -1,1 [)]Mu is a localization coefficient of the difference of the rental quantity, representing the difference of the rental in the next period of the service point to the threshold value of the vehicle-to-capacity ratioThe greater the influence degree, the greater the influence of the rental difference at the next time period of the service point on the vehicle-to-capacity ratio threshold. In the formulae (7) to (9),
Figure BDA0001621072250000058
and a threshold value
Figure BDA00016210722500000512
Will be according to TtLease return difference L in next time periodi(Tt+T) And different, the method specifically comprises three cases:
S1)Li(Tt+T) When the value is 0, the equations (8) and (9) are equivalent to the equations (5) and (6),
Figure BDA0001621072250000059
S2)Li(Tt+T) Greater than 0, threshold range
Figure BDA00016210722500000513
The right-hand movement is carried out,
Figure BDA00016210722500000510
S3)Li(Tt+T) If < 0, the threshold value range
Figure BDA0001621072250000066
The left-hand movement is carried out,
Figure BDA0001621072250000061
after the threshold value of the vehicle-to-volume ratio of the service point is calculated, the unbalance degree of various service points under the influence of self-flow and the dynamic time domain needing intervention scheduling can be determined by analyzing the dynamic evolution rule and the distribution characteristic of the vehicle-to-volume ratio of the service point along the time axis.
(2.3) final calculation acquisition of dynamic scheduling time domain of BSS service point
WI for service point needing to transfer bicycle to positive transfer time domainlow,WIupp]Denotes, here WIlowAnd WIuppRespectively representing the start time of the time domainAnd an end time, provided with n positive scheduling dynamic time domains:
Figure BDA0001621072250000062
the calculation method is as shown in formula (10). In the same way, m negative dispatching time domains are set for dispatching bicycles
Figure BDA0001621072250000063
If so, the calculation method is as (11). Where σ represents the time interval over which the vehicle-to-capacity ratio takes value.
Figure BDA0001621072250000064
Figure BDA0001621072250000065
And 3, using the dynamic scheduling time domain obtained in the step 2 for bicycle scheduling of the BSS service point. According to the positive scheduling time domain [ WI ] of the BSS service point obtained in the step (2.3)low,WIupp]In a time period [ WIlow,WIupp]The bicycle is transferred from the service point, so that the phenomenon of difficulty in renting the bicycle is solved. Obtaining the negative scheduling time domain of the BSS service point according to the step (2.3) [ WO ]k low,WOk upp]In time period [ WO ]k low,WOk upp]The bicycles are called out from the service point, so that the problem that the bicycles are difficult to return from the service point is solved.
The invention has the advantages that: the method for acquiring the dynamic scheduling time domain of the shared bicycle system can more accurately acquire the scheduling time of the BSS, and can reduce the scheduling frequency and the service cost under the condition of meeting the scheduling service quality of the BSS.
Drawings
Fig. 1 is a flow structure diagram of a BSS self-flow model and a dynamic scheduling time domain acquisition method of the present invention.
Detailed Description
The process of the present invention is further described below with reference to the accompanying drawings.
The invention discloses a shared bicycle system scheduling method based on a dynamic scheduling time domain, which comprises the following steps:
step 1, determining basic parameters for BSS dynamic scheduling time domain judgment.
The BSS self-flow model is used for obtaining the travel rule of the bicycle user, and the BSS self-flow model is also an important decision basis for the BSS manager to select the time and the service points to be scheduled. The basic parameters comprise bicycle turnover rate of a service point, difference of renting and returning amount and bicycle-to-volume ratio.
(1.1) calculating bicycle renting and returning amount of a service point;
bicycle renting and returning amount Z of service point i in certain time period taui(tau) is the number of vehicles returned in the period
Figure BDA0001621072250000071
And the number of borrowed vehicles
Figure BDA0001621072250000072
The calculation method of the sum of (a) is shown in formula (1):
Figure BDA0001621072250000073
(1.2) calculating the bicycle turnover rate of the service point;
cycle rate r of service point i at certain time period taui(τ) includes the cycle rate r of borrowingi in(τ) and Return turnover Rate ri in(τ) and the cycle rate of borrowing/returning is respectively defined as the bicycle renting/returning amount of the service point i in the time period τ and the parking capacity E of the service pointiThe calculation method of the ratio of (the number of the locking piles or the design capacity of the electronic fence) is shown as the formula (2):
Figure BDA0001621072250000081
(1.3) calculating a difference of the renting amount of the service points;
the amount of bicycle rented and returned at the service point varies with time, often because of failureBalance to cause tidal phenomena, so a difference parameter L of rental quantity is introducedi(τ) to represent the bicycle renting amount difference of the service point i in the time period τ, the calculation method is shown as (3).
Figure BDA0001621072250000082
(1.4) calculating a vehicle-to-volume ratio of a service point;
here defined as the number of bicycles q held by a certain service point i at time ti(t) parking capability E of the service PointiThe ratio of the two is in the range of [0,1 ]]This is an important concept for characterizing the time-varying characteristics of the service point, let t0As an initial time, qi(t0) The initial bicycle holding capacity of the service point i and the bicycle-to-volume ratio H of the service point i at the time ti(t) will be subject to a previous rental difference Li(t-t0) The direct influence of (2) is calculated as shown in equation (4).
Figure BDA0001621072250000083
And step 2, a judgment and acquisition method of a BSS dynamic scheduling time domain.
(2.1) obtaining the empty/full vehicle capacity ratio threshold value of the service point
The difference of renting amount and the change of the car-to-capacity ratio of the service point can cause the service point to enter an empty/full state when L is in a certain time intervali(τ)＞0，Hi(t) will continue to become smaller or even close to 0, the service point enters the vacant state and borrowing is difficult, and when LiWhen (τ) < 0, HiAnd (t) continuously increasing until the service point approaches 1, entering a full state, and difficult to return. Order to
Figure BDA0001621072250000084
Indicating that the vehicle is more than the full threshold,
Figure BDA0001621072250000085
indicating a vehicle-to-capacity vacancy threshold, a vehicle-to-capacity threshold
Figure BDA0001621072250000086
And the judgment rule of the service point i state is as follows:
Figure BDA0001621072250000093
and (4) a normal state.
Figure BDA0001621072250000094
The vacant state, requiring the bicycle to be recumbent, is called "positive dispatch".
Figure BDA0001621072250000095
In a full state, the bicycle needs to be called out, which is called as negative dispatching.
According to the BSS self-flow model, the time periods of the service points in the empty positions and the full positions, namely the dynamic time domain of the intervention scheduling can be calculated. The ideal service point vehicle-to-capacity ratio threshold value has the following value range: [0,1]In the actual operation process, when only a small amount of bicycles can be lent out at the service point or the empty lock pile can be returned, the empty/full state is defined, namely the vehicle volume is smaller than the threshold range. Meanwhile, service points with high turnover rate often have higher influence on resident travel and the whole BSS, so corresponding scheduling needs to be arranged in advance, namely, the range of the vehicle-to-capacity ratio threshold value is reduced. The empty/full car-to-capacity ratio threshold value is based on overall consideration of the dispatching response speed and the bicycle turnover rate of the service point
Figure BDA0001621072250000096
Obtained from the formulae (5) and (6).
Figure BDA0001621072250000091
Figure BDA0001621072250000092
Here, τ is a time period, and one day of a certain working day and holiday may be sampled.
[ωmin,ωmax]The dispatching demand dispatching vehicle is an empty and full bit judgment reference threshold value related to dispatching response speed, if the dispatching delay is not considered, namely the dispatching vehicle can arrive at the site immediately after the dispatching demand dispatching vehicle is sent out by the service point, the service point can wait until the state of the service point becomes completely empty (no bicycle) or full (no empty lock pile), then the dispatching request is sent out, the vehicle-to-volume ratio is 0 and 1, and therefore the reference threshold value is also taken as [0,1 ]]But in practice there is a delay in arrival of the dispatch vehicle at the site, so the reference threshold range should be less than [0,1 ]]Moreover, the faster the BSS response speed is, i.e., the shorter the time required for the dispatching vehicle to reach the site is, the closer the reference threshold value is to [0,1 ]]。
ri(τ) bicycle turnover at service Point i, riThe larger the value of (τ) is, the more important the service point is in the BSS, and the earlier the scheduling should be intervened. r ismax(τ) is the maximum value of all service points turnover rate, rmin(τ) is the minimum value for the value,
Figure BDA0001621072250000101
is the turnover number riNormalized value of (tau) over a range of [0,1 ]]. The bicycle turnover rate localization coefficient is used for representing the influence degree of the bicycle turnover rate of the service point on the bicycle capacity ratio threshold value, and if the value is larger, the influence of the bicycle turnover rate of different service points on the bicycle capacity ratio threshold value is larger. Desired vehicle-to-volume ratio (defined as
Figure BDA0001621072250000102
) Is a threshold value
Figure BDA0001621072250000109
The intermediate value of (c), in the case of a balanced and stable turnover,
Figure BDA0001621072250000103
i.e., the service point bicycle holds half the designed parking capacity.
(2.2) obtaining a vehicle-to-volume ratio threshold value considering a difference in rental amount for the next period
In the actual operation process of the BBS, the turnover rate of the service point is often not in a balanced and stable state,desired vehicle to capacity ratio
Figure BDA0001621072250000104
Also subject to a rental difference L for the next periodi(τ) if the next period lease amount is greater than the return amount, Li(τ) > 0, the desired vehicle-to-capacity ratio should be greater than 0.5, and the vehicle-to-capacity ratio threshold also shifts to the right; otherwise, the expected vehicle-to-volume ratio should be less than 0.5, and the threshold value is shifted left. Let TtRepresenting a time period with the time length T from the time T, and the expected vehicle-to-volume ratio of each time period
Figure BDA0001621072250000105
And vehicle-to-capacity threshold
Figure BDA00016210722500001010
The algorithm is further improved as in equations (7) - (9):
Figure BDA0001621072250000106
Figure BDA0001621072250000107
Figure BDA0001621072250000108
here, Tt+TRepresenting a period starting at time T + T and having a duration T, i.e. TtLi(Tt+T) Service point i is at TtThe rental amount for the next period is different,
Figure BDA0001621072250000111
value range of [ -1,1 [)]And μ is a localization coefficient of the difference of the renting amount, and represents the degree of influence of the renting difference of the next period of the service point on the threshold value of the vehicle-to-capacity ratio of the service point, and if the value of μ is larger, the influence of the renting difference of the next period of the service point on the threshold value of the vehicle-to-capacity ratio is larger. In the formulae (7) to (9),
Figure BDA0001621072250000112
and a threshold value
Figure BDA00016210722500001110
Will be according to TtLease return difference L in next time periodi(Tt+T) And different, the method specifically comprises three cases:
S1)Li(Tt+T) When the value is 0, the equations (8) and (9) are equivalent to the equations (5) and (6),
Figure BDA0001621072250000113
S2)Li(Tt+T) Greater than 0, threshold range
Figure BDA00016210722500001111
The right-hand movement is carried out,
Figure BDA0001621072250000114
S3)Li(Tt+T) If < 0, the threshold value range
Figure BDA00016210722500001112
The left-hand movement is carried out,
Figure BDA0001621072250000115
after the threshold value of the vehicle-to-volume ratio of the service point is calculated, the unbalance degree of various service points under the influence of self-flow and the dynamic time domain needing intervention scheduling can be determined by analyzing the dynamic evolution rule and the distribution characteristic of the vehicle-to-volume ratio of the service point along the time axis.
(2.3) final calculation acquisition of dynamic scheduling time domain of BSS service point
WI for service point needing to transfer bicycle to positive transfer time domainlow,WIupp]Denotes, here WIlowAnd WIuppRespectively representing the start time and the end time of a time domain, and n positive scheduling dynamic time domains are set:
Figure BDA0001621072250000116
the calculation method is as shown in formula (10). In the same way, m negative tones are providedFor taking out the bicycle in time domain
Figure BDA0001621072250000117
If so, the calculation method is as (11). Where σ represents the time interval over which the vehicle-to-capacity ratio takes value.
Figure BDA0001621072250000118
Figure BDA0001621072250000119
Figure BDA0001621072250000121
And 3, using the dynamic scheduling time domain obtained in the step 2 for bicycle scheduling of the BSS service point. According to the positive scheduling time domain [ WI ] of the BSS service point obtained in the step (2.3)low,WIupp]In a time period [ WIlow,WIupp]The bicycle is transferred from the service point, so that the phenomenon of difficulty in renting the bicycle is solved. Obtaining the negative scheduling time domain of the BSS service point according to the step (2.3) [ WO ]k low,WOk upp]In time period [ WO ]k low,WOk upp]The bicycles are called out from the service point, so that the problem that the bicycles are difficult to return from the service point is solved.
The embodiments described in this specification are merely illustrative of implementations of the inventive concept and the scope of the present invention should not be considered limited to the specific forms set forth in the embodiments but rather by the equivalents thereof as may occur to those skilled in the art upon consideration of the present inventive concept.

Claims (1)

1. The shared bicycle system scheduling method based on the dynamic scheduling time domain comprises the following steps:
step 1, determining basic parameters for BSS dynamic scheduling time domain judgment;
the method is obtained by a BSS self-flowing model, reflects the travel rule of a bicycle user, and is also an important decision basis for a BSS manager to select which time and service points need to be scheduled; the basic parameters comprise bicycle turnover rate, difference of renting and returning amount and bicycle-to-volume ratio of a service point;
(1.1) calculating bicycle renting and returning amount of a service point;
bicycle renting and returning amount Z of service point i in certain time period taui(tau) is the number of vehicles returned in the period
Figure FDA0002500260620000011
And the number of borrowed vehicles
Figure FDA0002500260620000012
The calculation method of the sum of (a) is shown in formula (1):
Figure FDA0002500260620000013
(1.2) calculating the bicycle turnover rate of the service point;
cycle rate r of service point i at certain time period taui(τ) cycle rate including borrowing
Figure FDA0002500260620000014
Turnover rate of return car
Figure FDA0002500260620000015
The cycle rate of borrowing/returning is respectively defined as the bicycle renting/returning amount of the service point i in the time period tau and the parking capacity E of the service pointiRatio of (D), parking capacity EiI.e. the number of the locking piles or the design capacity of the electronic fence, the turnover rate r of the vehicleiThe calculation method of (τ) is shown in formula (2):
Figure FDA0002500260620000016
(1.3) calculating a difference of the renting amount of the service points;
bicycle rental and return amounts at service points over timeVariation, often due to imbalance, leads to tidal phenomena, thus introducing a rental difference parameter Li(τ) to represent the bicycle renting amount difference of the service point i in the time period τ, the calculation method is as shown in equation (3):
Figure FDA0002500260620000017
(1.4) calculating a vehicle-to-volume ratio of a service point;
here defined as the number of bicycles q held by a certain service point i at time ti(t) parking capability E of the service PointiThe ratio of the two is in the range of [0,1 ]]This is an important concept for characterizing the time-varying characteristics of the service point, let t0As an initial time, qi(t0) The initial bicycle holding capacity of the service point i and the bicycle-to-volume ratio H of the service point i at the time ti(t) will be subject to a previous rental difference Li(t-t0) The direct influence of (2) is calculated as shown in equation (4):
Figure FDA0002500260620000018
step 2, a judgment acquisition method of a BSS dynamic scheduling time domain;
(2.1) acquiring an empty/full vehicle capacity ratio threshold value of a service point;
the difference of renting amount and the change of the car-to-capacity ratio of the service point can cause the service point to enter an empty/full state when L is in a certain time intervali(τ)>0，Hi(t) will continue to become smaller or even close to 0, the service point enters the vacant state and borrowing is difficult, and when Li(τ)<At 0, Hi(t) continuously increasing until the size is close to 1, and making the service point enter a full state and difficult to return to the vehicle; order to
Figure FDA0002500260620000021
Indicating that the vehicle is more than the full threshold,
Figure FDA0002500260620000022
indicating a vehicle-to-capacity vacancy threshold, a vehicle-to-capacity thresholdValue of
Figure FDA0002500260620000023
And the judgment rule of the service point i state is as follows:
Figure FDA0002500260620000024
a normal state;
Figure FDA0002500260620000025
a vacant state, called "positive dispatch", requiring the bicycle to be dispatched;
Figure FDA0002500260620000026
a full state, namely a state that bicycles need to be called out, is called as 'negative dispatching';
according to the BSS self-flow model, the time periods of the service points in the vacant positions and the full positions, namely the dynamic time domain of intervention scheduling can be calculated; the ideal service point vehicle-to-capacity ratio threshold value has the following value range: [0,1]In the actual operation process, when only a small amount of bicycles can be lent out at a service point or when the empty lock pile can be returned, the empty/full state is defined, namely the range of the bicycle capacity ratio threshold value is reduced; meanwhile, service points with high turnover rate often have higher influence degree on resident trip and the whole BSS, so that corresponding scheduling needs to be arranged in advance, namely, the range of the vehicle-to-capacity ratio threshold value is reduced; the empty/full car-to-capacity ratio threshold value is based on overall consideration of the dispatching response speed and the bicycle turnover rate of the service point
Figure FDA0002500260620000027
Obtained from formulae (5), (6):
Figure FDA0002500260620000028
Figure FDA0002500260620000029
here, τ is a time period, and a day of a certain working day and a holiday can be sampled respectively;
[ωmin,ωmax]the dispatching demand dispatching vehicle is an empty and full bit judgment reference threshold value related to dispatching response speed, if the dispatching delay is not considered, namely once the dispatching vehicle sending the dispatching demand is sent by the service point, the service point can immediately arrive at the site, the service point can wait until the state of the service point becomes completely empty or full, then the dispatching request is sent, the vehicle-to-capacity ratio is 0 and 1, therefore, the reference threshold value is also taken as [0,1 ]]But in practice there is a delay in arrival of the dispatch vehicle at the site, so the reference threshold range should be less than [0,1 ]]Moreover, the faster the BSS response speed is, i.e., the shorter the time required for the dispatching vehicle to reach the site is, the closer the reference threshold value is to [0,1 ]]；
ri(τ) bicycle turnover at service Point i, riThe larger the value of (tau) is, the more important the service point is in the BSS, and the earlier the scheduling should be intervened; r ismax(τ) is the maximum value of all service points turnover rate, rmin(τ) is the minimum value for the value,
Figure FDA00025002606200000210
is the turnover number riNormalized value of (tau) over a range of [0,1 ]](ii) a The bicycle turnover rate is a localization coefficient of the turnover rate, and represents the influence degree of the bicycle turnover rate of the service point on the bicycle capacity ratio threshold, if the value is larger, the influence of the bicycle turnover rates of different service points on the bicycle capacity ratio threshold is larger; desired vehicle-to-volume ratio of service Point i
Figure FDA00025002606200000211
Is a threshold value
Figure FDA00025002606200000212
The intermediate value of (c), in the case of a balanced and stable turnover,
Figure FDA00025002606200000213
namely, the bicycle holding capacity of the service point is half of the designed parking capacity;
(2.2) acquiring a vehicle-to-volume ratio threshold value considering a difference in rental quantity in a next period;
in the actual operation process of the BBS, the turnover rate of a service point is often not in a balanced and stable state, and the expected vehicle-to-volume ratio
Figure FDA0002500260620000031
Also subject to a rental difference L for the next periodi(τ) if the next period lease amount is greater than the return amount, Li(τ)>0, the desired vehicle-to-capacity ratio should be greater than 0.5, the vehicle-to-capacity ratio threshold also shifts to the right; otherwise, the expected vehicle-to-volume ratio is less than 0.5, and the threshold value is shifted left; let TtRepresenting a time period with the time length T from the time T, and the expected vehicle-to-volume ratio of each time period
Figure FDA0002500260620000032
And vehicle-to-capacity threshold
Figure FDA0002500260620000033
The algorithm is further improved as in equations (7) - (9):
Figure FDA0002500260620000034
Figure FDA0002500260620000035
Figure FDA0002500260620000036
here, Tt+TRepresenting a period starting at time T + T and having a duration T, i.e. TtLi(Tt+T) Service point i is at TtThe rental amount for the next period is different,
Figure FDA0002500260620000037
value range of [ -1,1 [)]Mu is a localization coefficient of the difference of the rental quantity, which represents the degree of influence of the rental difference of the next period of the service point on the vehicle-to-capacity ratio threshold thereof, such asThe larger the value of mu is, the larger the influence of the renting difference of the next period of the service point on the vehicle-to-volume ratio threshold value is; in the formulae (7) to (9),
Figure FDA0002500260620000038
and a threshold value
Figure FDA0002500260620000039
Will be according to TtLease return difference L in next time periodi(Tt+T) And different, the method specifically comprises three cases:
S1)Li(Tt+T) When the value is 0, the equations (8) and (9) are equivalent to the equations (5) and (6),
Figure FDA00025002606200000310
S2)Li(Tt+T)>0, then threshold range
Figure FDA00025002606200000311
The right-hand movement is carried out,
Figure FDA00025002606200000312
S3)Li(Tt+T)<0, then threshold range
Figure FDA00025002606200000313
The left-hand movement is carried out,
Figure FDA00025002606200000314
after the threshold value of the vehicle-to-volume ratio of the service point is calculated, the unbalance degree of various service points under the influence of self-flow and the dynamic time domain needing intervention scheduling can be determined by analyzing the dynamic evolution rule and the distribution characteristic of the vehicle-to-volume ratio of the service point along the time axis;
(2.3) the BSS service point dynamically schedules the final calculation of the time domain to obtain;
WI for service point needing to transfer bicycle to positive transfer time domainlow,WIupp]Denotes, here WIlowAnd WIuppRespectively representing the start time and the end time of a time domain, and n positive scheduling dynamic time domains are set:
Figure FDA00025002606200000315
the calculation method is as formula (10); in the same way, m negative dispatching time domains are set for dispatching bicycles
Figure FDA00025002606200000316
If the result is shown, the calculation method is as (11); wherein σ represents a time interval of the vehicle-to-capacity ratio value;
Figure FDA00025002606200000317
Figure FDA00025002606200000318
step 3, using the dynamic scheduling time domain obtained in the step 2 for bicycle scheduling of the BSS service point; according to the positive scheduling time domain [ WI ] of the BSS service point obtained in the step (2.3)low,WIupp]In a time period [ WIlow,WIupp]The bicycle is called from the service point, so that the phenomenon of difficulty in renting the bicycle is solved; obtaining the negative scheduling time domain of the BSS service point according to the step (2.3) [ WO ]k low,WOk upp]In time period [ WO ]k low,WOk upp]The bicycles are called out from the service point, so that the problem that the bicycles are difficult to return from the service point is solved.
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