CN109661693B

CN109661693B - High-quality berth dynamic pricing method with priority short stop

Info

Publication number: CN109661693B
Application number: CN201680086693.8A
Authority: CN
Inventors: 杜豫川; 王晨薇; 赵聪; 邓富文; 岳劲松
Original assignee: Tongji University
Current assignee: Tongji University
Priority date: 2016-12-30
Filing date: 2016-12-30
Publication date: 2021-06-15
Anticipated expiration: 2036-12-30
Also published as: WO2018122812A1; CN109416879A; WO2018122587A1; WO2018122813A1; GB201909413D0; CN110337680A; CN109661693A; GB201711410D0; CN109416879B

Abstract

A high-quality parking space dynamic pricing method for priority short parking considers the number of high-quality parking spaces, regional parking demand characteristics, parking space occupancy and the like, finely sets the charging price of the high-quality parking spaces in an incremental progressive charging mode, and dynamically adjusts according to actual conditions, so that the limited high-quality parking spaces are limitedly supplied to vehicles with short parking time, the turnover rate of the high-quality parking spaces is improved, more drivers can obtain comfortable and convenient parking services and short walking time, and the overall social efficiency is improved.

Description

High-quality berth dynamic pricing method with priority short stop

Technical Field

The invention relates to a high-quality berth dynamic pricing method with priority short stop. When a driver drives a vehicle to a parking area near a destination to prepare for parking, the driver is biased to select a high-quality parking space with convenient and safe parking position, and is reluctant to find a common parking space with a remote position, high parking difficulty and difficulty, so that congestion and emission increase can be caused due to the fact that the number of the high-quality parking spaces is insufficient. The city manager can utilize the method provided by the invention to carry out parking pricing on the high-quality parking space, and realize the management and guidance of parking requirements. Particularly, the invention considers the quantity of high-quality parking positions, regional parking demand characteristics, parking space occupancy and the like, finely sets the charging price of the high-quality parking positions in an incremental and progressive charging mode, and dynamically adjusts according to actual conditions so as to achieve the purpose of preferentially supplying limited high-quality parking positions to vehicles with shorter parking time, improve the turnover rate of the high-quality parking positions, enable more drivers to obtain comfortable and convenient parking services and shorter walking time, and improve the overall social efficiency.

Background

At present, the contradiction between supply and demand of parking in many cities is prominent, and the parking problem becomes a serious urban traffic problem. Charging is one of the most direct and effective means for regulating market supply and demand, and thus parking charge pricing is an important content and key measure for parking management. The following aims can be achieved through reasonable parking charge:

(1) the fairness principle of 'user payment' is embodied;

(2) the turnover rate of the public parking berth is improved, and the optimal use of the existing parking facilities is realized;

(3) through charging management, the parking order and traffic safety are guaranteed;

(4) stimulating or inhibiting certain traffic modes by adjusting parking rates;

(5) the space difference, the time difference and the type difference of the parking rate have great effects on adjusting the supply and demand relationship of the urban parking facilities, for example, a charging method of grading according to the price difference of land and progressively timing is carried out in the central area, and the charging method is used as an economic lever and can play a role in adjusting and controlling the parking supply of the central area so as to adjust and control the dynamic and static traffic demands of the central area. At present, the rate of roadside parking charging is mostly established by adopting a 'cost pricing method'. The basis for consideration is mainly service cost (including land cost, construction cost, operation cost and the like), willingness to pay, parking demand characteristics, urban traffic policy objectives and the like.

Prior art 1

One united states patent application, US20140122375, discloses a method of dynamically adjusting parking pricing based on real-time occupancy of a parking lot. The pricing method needs to detect the real-time occupancy rate of the parking space through an intelligent sensor, compare the current occupancy rate with the target occupancy rate through a comparison module, and realize the feedback control of the parking requirement through real-time adjustment of parking pricing. Fig. 1 shows a flow chart of an implementation of such a dynamic pricing method. Fig. 2 shows the change of parking demand, occupancy and set parking pricing in one implementation of the pricing method.

As can be seen from fig. 2, when it is detected that the occupancy exceeds the set target value, that is, when the parking demand is large, the pricing method increases the pricing of parking charge, and plays a role in suppressing the demand, so as to reduce the occupancy below the set threshold of 85%. However, in the pricing method, the system provides parking space resources for the parking lot according to the first-come-first-serve principle, and neither the difference of the advantages and disadvantages of the parking space resource conditions nor the differentiation and selection of the parking time length for the parking lot are considered. Thus, maximum utilization of good quality berthage resources cannot be achieved.

Prior art 2

One US patent application, US20110213672, discloses a differential pricing method of berths in high demand situations. The method divides the available parking spaces in the parking lot into categories of 'common parking spaces', 'one of the last reserved parking spaces', 'only the last reserved parking spaces' and the like from the quantity, uses the concept of using the 'contribution value' of the parking spaces for reference, and carries out different pricing according to different types of the contribution values of the parking spaces so as to realize the maximization of the profit of operators.

Fig. 3 shows the classification of the parking classes in a parking lot using this method. The mark L is a large-size parking space, the mark S is a safe parking space, and the mark S is an ordinary parking space. The following table shows classification of berths and pricing rules in one example of implementation of this method.

Identification	Classification	Price ($)	Duration limit (h)
				O	General berth	1.00	2.5
L	Final parking position reservation	3.00	3.0
				NL	Finally reserving adjacent parking spaces of parking spaces	2.00	3.0
S	Safety berth	10.00	10.0

It can be seen that although the pricing method carries out differentiated pricing on the parking spaces, the reasonable selection is not carried out on the parking time length of the parking person. The purpose of this pricing method is to maximize the profit of the operator rather than to optimize the social efficiency, so it cannot guarantee that its premium parking will serve more drivers to the maximum extent, and there is also a waste of premium parking resources.

Disclosure of Invention

The limited high-quality berth is used for meeting the parking requirement of the vehicle with short parking time to the maximum extent, the turnover rate of the high-quality berth is improved, and the key for improving the overall efficiency of the society is realized. This concept can be illustrated by the following example:

assuming that a high-quality parking lot convenient and fast to use exists, the walking distance from a final destination to which a traveler wants to arrive after parking is 2 minutes; meanwhile, a common parking space with a far position is arranged, and the walking distance from the final destination is 5 minutes. Suppose that A, B drivers need to stop for a stop at the same time in a certain period of time to reach the destination, wherein a has a stop duration of 6 hours, B has a stop duration of 2 hours, 2 hours later has driver C, 4 hours later has driver D also needs to stop for the same destination, and the stop durations are all 2 hours.

Under the prior art method, the situation that may occur is:

the driver A parks the vehicle in a high-quality parking space, walks for 2 minutes after parking and arrives at a destination; meanwhile, the driver B parks the vehicle in a common parking space, and walks for 5 minutes after parking to reach the destination. After 2 hours, the B car drives away, and the arriving C car can only park the car in a common parking space (because the high-quality parking space is still occupied by the A car), and the B car also walks for 5 minutes to arrive at the destination after parking; similarly, C drives away after 2 hours, and D arriving at the same time can only park the vehicle in a common parking space (because the good parking space is still occupied by the vehicle a), and the vehicle also walks for 5 minutes to arrive at the destination after parking. In this case, the walking time spent by four drivers in the entire system is 2+5+5+ 17 minutes in total.

If the idea of the invention is adopted to make the high-quality berth meet the requirement of short-stop vehicles in priority, the situation can be changed as follows:

the driver A parks the vehicle in a common parking space and walks for 5 minutes after parking; meanwhile, the driver B parks the vehicle in a good-quality parking space and walks for 2 minutes after parking. After 2 hours, when the vehicle C arrives, the vehicle B on the high-quality parking place is driven away, so that the vehicle C can park on the high-quality parking place; similarly, when the vehicle arrives in 2 hours, the vehicle C in the good-quality parking space drives away, so that the vehicle D can be parked in the good-quality parking space, and the walking time required by C, D is 2 minutes. In this case, the walking time spent by four drivers in the entire system is 5+2+2+ 11 minutes in total.

Fig. 4 illustrates these two cases in comparison.

By means of the example, it can be found that the walking time paid by the whole system is obviously reduced and the efficiency is greatly improved by preferentially allocating the good-quality parking spaces to the vehicles with shorter parking time (hereinafter referred to as short parking vehicles). The invention aims to solve the problem of guiding a short-stop vehicle to stop to a high-quality berth and guiding a long-stop vehicle to stop to a common berth by reasonably pricing the high-quality berth.

The invention provides a high-quality berth dynamic pricing method for preferential short stopping based on high-quality berth quantity limitation and parking demand characteristic distribution, which can obtain parking behavior characteristics in a region, calculate a parking duration control threshold and a charging standard, realize the induced transfer of long-stop vehicles to a common berth and dynamically regulate and control the price according to the actual demand state. The purposes of improving the utilization rate of the high-quality berth and reducing the total tour time and walking time of the system are achieved.

The high-quality parking space is a parking space with high convenience, and is obviously characterized in that the parking space is closer to the final destination to be reached by a driver in a parking area, and the walking time required by the driver after parking is shorter. The general parking space is a parking space which is inferior in convenience to a good-quality parking space, and is characterized in that the parking space is relatively far away, and a driver needs to walk to a final destination in a parking area for a long time after parking. When the excellent berth and the common berth exist simultaneously in a certain area, the method of the invention can be used for pricing the excellent berth.

The invention specifically comprises the following steps:

(1) and establishing a parking area geometric information table. The contained information includes the number m of the vehicle driving entrances of the parking areas, the vehicle driving distance d between the vehicle driving entrance and the high-quality parking place of each parking area_nAnd a vehicle traveling distance d 'between the vehicle traveling entrance and the ordinary parking place of each parking area'_nAnd the walking distance delta d between the high-quality berth and the ordinary berth, and the data are obtained through field measurement. The established parking area geometric information representation is shown, for example, in fig. 5.

(2) Determining a unit charging duration t₀. Unit meterTime-consuming period t₀May be any duration less than the length of the required pricing period, and if a parking charge policy is to be established within 3 hours, t should be satisfied₀Less than or equal to 3 hours. Less than one t in parking time₀Is charged by a t₀And (4) calculating.

In particular, t is proposed in the method₀The value of (a) should satisfy t being less than or equal to 1 minute₀Less than or equal to 20 minutes. This is because of t₀The larger the rate of change of parking charge, the more obvious the step change of parking charge with the increase of parking duration, the more sensitive the change of charge is to users whose duration is near the change threshold, thereby increasing the time anxiety of users and reducing the satisfaction of parking users to parking service.

FIG. 6 shows that a unit charging time t is set on the assumption that a user stops for 2 hours and the total fee to be finally paid is the same₀1 hour and t₀In both cases, 10 minutes, the parking cost changes over time in 2 hours. As can be seen from FIG. 6, t₀In the 1 hour case, the toll growth has a distinct step-wise jump, which causes the parker to experience a distinct psychological anxiety as the parking approaches 2 hours, because there is a fear that the cost will suddenly increase once the duration exceeds 2 hours. And at t₀In the case of 10 minutes, the increase in the charge is more gradual, and the user does not have to worry about a large increase in the charge due to exceeding a certain time limit, thereby improving the user's parking experience.

(3) And determining parking characteristic data in the parking area. These data include the number Q of vehicles entering the parking area with a parking demand, the parking time t of the vehicles with a parking demand, the proportion β of vehicles entering the parking area from the respective entry points_nTravel time value alpha of parking user in parking area and average vehicle speed v in parking area_dAverage speed v of travel in parking area_wAnd a price sensitivity factor mu of a parking user in the parking area.

Wherein a ratio β of vehicles entering from each driving entrance in the parking area_nParking user trip time value alpha in parking area and parkingAverage vehicle speed v in the region_dAverage walking speed v of parking users in parking area_wAnd the price sensitivity coefficient mu of the parking users in the parking area can be obtained by sampling and surveying in the parking area.

When determining two items of data, namely the number Q of vehicles with parking demands and the parking time t of the vehicles with parking demands in the parking area, at least one of the following four relevant data is required to be utilized:

a) the number Q of the parked vehicles in the parking area at the same time period_ⅠAnd historical empirical value t of parking duration_Ⅰ. The arrival number of the parking vehicles at the high-quality parking space and the ordinary parking space is obtained through data or manual records stored in an intelligent parking facility and summed, the parking time of each vehicle is recorded, the recorded values of multiple days are randomly extracted and averaged, and the historical experience value of the number of the parking vehicles in the parking area and the historical experience value of the parking time are obtained. Particularly, when the historical data is extracted and counted, the selected dates are respectively counted under the condition that the difference of the demands is large, namely working days, double holidays and special holidays.

b) Real-time traffic flow Q of surrounding roads_Ⅱ. Means real-time traffic flow data of a road network surrounding the parking area, published by traffic authorities or related professional third parties.

c) Berth reservation data Q on mobile terminal APP_Ⅲ、t_Ⅲ. And the user with the parking requirement makes an appointment for the high-quality berth in the parking area through the APP of the related mobile terminal in advance, and informs the time period of parking. The number of reserved premium berths and the reservation period on the APP can be obtained in real time from the application background.

d) Known inducement of temporary activity in parking area parking demand Q_Ⅳ、t_Ⅳ. The temporary event to be generated in the parking area increases the parking demand in the parking area, and thus the number of people participating in the event and the time for holding the event need to be grasped.

Using one or more of the above related data, predicting the number Q of vehicles with parking demand and the parking time t of the vehicles with parking demand in the parking area by one of the following three methods:

a) the number Q of vehicles with parking demands in the parking area is equal to the historical experience value Q of the number of the vehicles parked in the parking area at the same time_Ⅰ+ number of persons participating in temporary activities in parking area Q_ⅣThe sharing ratio of the trip of the car is multiplied; wherein the value of the sharing ratio of the car traveling is more than 0.1 and less than 0.3, and the sharing ratio is obtained by sampling and surveying on the spot; the parking time t in the parking area is determined by the historical empirical value t of the parking time_ⅠAnd parking duration distribution t of temporary activity induced parking demand in parking area_ⅣAnd (4) superposing to obtain the product.

b) The number Q of vehicles with parking requirements in the parking area is equal to the number Q of reserved parking positions in APP_Ⅲ+ historical experience value Q of number of parked vehicles in the parking area in the same time period_ⅠX (1-APP reservation user to all parking users) + number of participants for temporary activities in parking area Q_ⅣThe sharing ratio of the trip of the car is multiplied; the proportion of APP reservation users to all users is obtained through sampling investigation, the value of the sharing ratio of car traveling is more than 0.1 and less than 0.3, and the APP reservation users are obtained through sampling investigation on the spot; the parking time t in the parking area is determined by the historical empirical value t of the parking time_ⅠAnd the parking time length t of the parking demand determined by the historical data and the APP reservation data_ⅢAnd a parking duration t of a parking demand induced by temporary activity in the parking area_ⅣAnd three terms are superposed.

c) Number of vehicles in the parking area having parking demand

Distribution of parking time t of total demand and distribution t of historical data experience value of parking time_ⅠAnd (5) the consistency is achieved.

Method a) should be used when determining the premium parking price offered to the subscribing user in APP; method b) or method c) should be used when performing real-time dynamic adjustment of premium berth prices. However, the price adjusted in real time is only applied to non-reservation users who enter the parking space after the price is released, and for parking users who have reserved on the APP, the charging standard is still executed according to the charging standard informed when the parking users make a reservation.

(4) Determining a parking duration control threshold t_m. The method comprises the following steps:

a) grouping the total quantity Q of the vehicles with parking demands in the parking area according to the parking time t by the data obtained in the step (3), wherein the group distance is the unit charging time t₀. I.e. the parking time of the ith group of data is t_i＝i×t₀The number of vehicles of the group is q_iThe value range of i is 1,2,3, …, T/T₀Where T is the total pricing duration;

b) number q of vehicles from group i_iCalculating the average per t of the ith group of vehicles₀Amount of arrival of duration

c) Averaged every t by i-th group of vehicles₀Time length arrival q_0iAnd a parking time period t of the ith group of vehicles_iCalculating the amount S of parking space-time resources required by the ith group of vehicles_i＝q_0i×t_i；

d) The number S of parking space-time resources required by each group of vehicles₁,S₂,…,S_iCalculating the accumulated parking space-time resource quantity sigma S of the front i groups of vehicles_i＝S₁+S₂+…+S_i；

e) Calculating the parking space-time resource S provided by the high-quality berth according to the berth number S of the high-quality berth_p＝0.85×s×t₀；

f) Will sigma S₁，∑S₂,…,∑S_iParking space-time resource S provided by high-quality berth_pComparing to find an i' to make S_i′Closest to but not exceeding S_pThe parking duration t corresponding to the group i_i′Is thatParking duration control threshold t_m。

FIG. 7 shows the parking duration control threshold t_mThe calculation procedure of (1). This calculation may be performed using a parking demand statistical table. The following table is an example of a parking demand statistics table.

(5) And determining the price of the high-quality parking charge. The method comprises the following steps:

a) calculating the parking time as the parking time control threshold t according to the known ordinary parking charging policy_mTime, parking charge price P 'of ordinary parking space'_t；

b) Setting free parking time t of high-quality berth_fI.e. the vehicle is parked at a premium parking space for a period of time not exceeding t_fWhen the charge is not made, the charge is not made; t is t_fThe value of (1) can be 0, namely, the vehicle starts to charge as soon as the vehicle stops at a high-quality parking space;

c) determining high-quality berth at t according to cost pricing method₀The lower price limit in the time length is used as the free parking time length t of the high-quality berth_fFirst t after the end₀Price charged in duration p₁；

d) When the parking time is t_mTime, parking charge price P 'of ordinary parking space'_tAnd the data in the parking area geometric information table, and calculating the parking time length t according to the formula (1)_mParking charge P for parking vehicles at high-quality berths_t:

Wherein:

P′_tindicating that a vehicle is parkedLength equals duration control threshold t_mMeanwhile, the vehicle is parked at a common parking position for paying the parking fee;

a represents the travel time value of the parking user in the parking area;

Δ d represents a walking distance between the premium berth and the ordinary berth;

d' represents the vehicle travel between a normal parking space and the entrance of the parking area. If the parking area has a plurality of entrances, adopting a weighted average value of the common berth and the vehicle traveling distance between the vehicle traveling entrances, wherein the weight is the proportion beta of the vehicles in the parking area entering from each entrance_n. Expressed by the formula (2):

wherein:

m represents the total number of vehicle entrances in the area;

β_nindicating a proportion of vehicles in the parking area entering the area from the nth vehicle entrance;

d′_nindicating the driving distance between the nth driving entrance and the common parking place.

d represents the vehicle traveling distance between the high-quality berth and the vehicle traveling entrance of the parking area. If there are multiple vehicle entrance in the area, the weight is represented by the weighted average value of the distance between the high-quality berth and each vehicle entrance, and the weight is the proportion beta of the vehicles entering from each entrance in the parking area_n. Expressed by the formula (3):

wherein:

d_nindicating the driving distance between the nth driving entrance and the high-quality parking place. The other meanings are the same as above.

v_dRepresenting an average traveling speed of the vehicle in the parking area;

v_windicating said parkingAverage walking speed of travelers in the area.

e) When the parking time is t_mParking charge P for parking vehicles at high-quality berths_tCalculating the price incremental variance delta p of the high-quality berth according to the formula (4), namely the nth unit charging time t of the high-quality berth₀Charging time t of (n-1) th unit charging time₀Part of the rising charge:

wherein:

n represents a parking duration control threshold t_mUnit charging time length t contained in₀Is a number of

f) Free parking time t from high-quality berth_fFirst t after the end₀Charge price p of duration₁And the price increasing variance delta p of the high-quality berth, and the free parking time t of the high-quality berth is calculated according to the formula (5)_fAfter the end of the nth t₀Charge price p of duration_n：

p_n＝p₁+(n-1)·Δp (5)

Wherein steps b), c), d) can be performed simultaneously, and fig. 8 shows a flowchart for calculating the premium parking charge price.

In this step, one possible implementation is that for the parking user who uses the mobile terminal APP to make a reservation for a good parking space, the system provides a charging scheme for the parking user at the time of reservation, and a discount is given to the parking user on the basis of the charging scheme at the time of final charging.

In this step, one possible implementation is to take into account the price sensitivity factor μ of the parking users in the parking area. Namely, when the response of the parking user to the change of the high-quality parking charge price in the parking area is small, the calculated parking charge price can be multiplied by a coefficient mu, wherein mu is more than 1 and less than or equal to 1.5, and certain expansion can be carried out, so that the aim of effectively shunting is fulfilled.

In this step, a possible implementation is to grade the premium berths according to the difference of the conditions of position, facilities, size, etc. between different premium berths when the number of premium berths is large. When the position of the high-quality berth is more convenient and faster, the larger the berth size is, the smaller the difficulty of the vehicle entering and exiting the berth is, the higher the grade corresponding to the high-quality berth is, and the larger the value of the grade coefficient l is. By multiplying the calculated parking charge price by different ranking factors gamma_iAnd the differentiated charging of the high-quality berths of different grades is realized, and finally the high-quality berth charging matrix which represents the charging price of the high-quality berths under the conditions of different time and different grades is obtained. Fig. 9 shows a possible grading pattern and the setting of the grading factor for a plurality of premium berths located in the same parking lot. Fig. 10 shows an example of a premium berth charging matrix.

The derivation of equation (1) is explained here: when a driver enters a region, the driver selects whether to go to a high-quality parking place or a common parking place by using the principle of minimizing the travel cost. The trip cost of the driver during parking includes:

parking fee paid at high-quality berth or ordinary berth, driving time required for driving to the berth from an area entrance, and time required for walking between the berth and a destination. The parking cost made up of these three parts can be expressed as:

C＝P+αt_d+αt_w (6)

in formula (6):

c represents the parking cost generated when the driver selects a high-quality parking space;

p represents the parking fee paid by the driver when selecting a high-quality parking space;

t_drepresenting the driving time required by a driver to drive from the region entrance to a high-quality berth, which is equal to the driving distance divided by the average vehicle speed;

t_wrepresenting a walking time, equal to twice (to and from) the walking time required for the driver to walk to and from the premium berth and the destinationReturn) walking distance divided by average walking speed;

the other meanings are the same as above.

According to the definition of the good berth, namely, the distance between the good berth and the destination of the driver is very close, the walking cost can be ignored when considering the travel cost paid by selecting the good berth. Equation (7) can be written as

In a similar way, the method comprises the following steps:

C‘＝P’+αt′_d+αt′_w (8)

in formula (8):

c' represents the parking cost generated when the driver selects a common berth;

p' represents the parking fee paid by the driver when selecting the common parking space;

t′_drepresenting the driving time required by a driver to drive from the region entrance to the ordinary berth, which is equal to the driving distance divided by the average vehicle speed;

t′_wrepresenting the walk time required for the driver to walk to and from the ordinary berth and the destination, equal to twice the (round trip) walk distance divided by the average walk speed;

the other meanings are the same as above.

Since the distance of the premium berth from the destination is negligible, the distance between the ordinary berth and the destination can be approximately replaced by the distance Δ d between the ordinary berth and the premium berth. Equation (8) can be written as:

in order to achieve the purpose of inducing long-stop vehicles to transfer to ordinary berths, the established premium berth charging price and the ordinary berth charging price should meet the following requirements:

wherein:

t represents the parking time of the driver, and the rest is the same as above.

Fig. 11 shows a comparison of parking charges between premium and ordinary berths.

Therefore, the formula (1) can be obtained by deriving the formulas (7), (9) and (10), and then the charging time t of each unit of the high-quality berth can be obtained₀The price charged in.

(6) Determining a real-time detection interval duration t_rNumber of actual vehicles parked at a good parking lot Q_rAnd real-time occupancy rate of premium berths O_rAnd carrying out timing real-time statistics and detection. By using an intelligent barrier gate, a video parking space detector, an infrared parking space detector, a microwave parking space detector or a geomagnetic coil every t_rCounting the actual number Q of vehicles parked at a good-quality berth from the beginning of a pricing period to the current moment in time_rAnd real-time occupancy rate O of the premium berths at that time_RAnd reporting the data to the system.

(7) And comparing the real-time detection data with the prediction data, and determining the high-quality parking charge price in the later time period. Obtaining the predicted demand amount from the pricing period to the current time according to the number Q of the vehicles with the parking demands in the parking area determined in the step (3)

And the actual number Q of vehicles parked at the good-quality parking space_RBy comparison, if 0.85Q_p≤Q_r≤1.15Q_pAnd 0.7 or more of O_rIf the charging rate is less than or equal to 0.9, the original charging scheme is not changed; if not, the step (3) to the step (5) are executed again, the relevant parameters are updated, and a new charging scheme is determined and issued.

The above symbols and their significances are summarized in the following table:

noun interpretation

(1) Duration per unit charge t₀: the time length t of a vehicle parked at a high-quality berth in free parking_fAfter finishing, stopping for every t₀The time length is increased once the parking cost is increased, and the increased part is the latest t₀Pricing of the time period.

(2) Price sensitivity coefficient μ: reflecting the degree of change of the parking user to the parking space selection caused by the change of the parking price of the high-quality parking space, wherein the smaller the degree of change of the parking user selection is, the larger the mu value is.

(3) Parking duration control threshold t_m: refers to the maximum amount of time that the parking manager wants to give the vehicle a premium parking space. I.e. the manager wishes all parking periods to be less than or equal to t_mThe vehicle is parked to a good parking space for a time period longer than t_mThe vehicle goes to a normal parking space for parking.

(4) Parking requirement statistical table: grouping and counting vehicles with parking requirements and required parking space-time resources in a parking area according to parking time length to calculate a parking time length control threshold value t_mTable (2).

(5) Parking space-time resources: the product of the number of parking positions occupied by the parked vehicle and the parking time is expressed in units of hours.

(6) Price incremental variance Δ p of premium berths: nth unit charging time t of high-quality berth₀The price of (b) is longer than the (n-1) th unit charging time t₀The portion of the price rise.

(7) Class coefficient gamma of premium berth_i: representing difference of merits caused by difference of conditions such as position, size and the like among high-quality berths with different grades, wherein the better the condition of the high-quality berth is, the grade coefficient gamma is_iThe larger the value of (c).

(8) Premium berth charging matrix: a matrix representing the price charged by premium berths at different times and different levels.

(9) High-quality berth real-time detection interval duration T_r: means within the pricing period, every t_rAnd (4) the duration, the system automatically detects and collects the real-time data of the high-quality berth once, and compares the real-time data with a predicted value or a target value.

Drawings

Fig. 1 is a flow chart of an implementation of the prior art 1.

Fig. 2 is an illustration of an embodiment of prior art 1.

Fig. 3 is an example of berthage classification in prior art 2.

FIG. 4 is a diagram comparing a prior art scenario and an optimized scenario.

Fig. 5 is an example of a parking area geometric information table.

FIG. 6 shows the charging duration t per unit₀Lower charging change pair chart.

FIG. 7 is a parking duration control threshold t_mThe calculation of (1).

Fig. 8 is a flowchart of the calculation of the premium parking charge price.

Fig. 9 shows a possible classification scheme and setting of classification coefficients for a plurality of premium berths in a parking lot.

Fig. 10 is an example of a premium berth charging matrix.

Fig. 11 is a graph comparing premium parking charge P with normal parking charge P'.

FIG. 12 is a flow chart of an embodiment of a method for dynamically pricing premium berths with priority short stops.

Fig. 13 is an overview of a parking area in the embodiment.

Fig. 14 is an internal plan view of a parking lot in which a premium berth is located in the embodiment.

Detailed Description

Detailed description of the invention

In this embodiment, a possible implementation of the above invention is provided, in this example, an overview of the parking area is shown in fig. 13, the area has two entrances E1 and E2, and the on-road parking space P1 is a high-quality parking resource and has 100 parking spaces; the off-road parking lot P' is a common parking resource, and the charging research time is 07: 00-24: 00 in a certain day. The user can reserve the high-quality parking space in the parking area in advance through the related mobile terminal application APP, the APP informs the user of the charge price of the high-quality parking space during reservation, and finally the user before reservation is charged according to the price. Parking pricing aiming at APP reservation users is carried out on the high-quality parking positions in the parking area by utilizing a high-quality parking position dynamic pricing method with priority for short parking. The implementation process is as follows:

1. through field measurement, the parking area geometric information table is established as follows:

2. setting a unit charging duration t₀The 10 minutes, the 10 minutes portion of the parking time less than 10 minutes is charged for 10 minutes.

3. The number of vehicles entering the parking area from E1 every day in the parking area is 400, and the number of vehicles entering the parking area from E2 is 200; the travel time value of all people in the parking area is 25 yuan/hour; the average running speed of the vehicles in the parking area is 10km/h, and the average walking speed of people is 5 km/h.

Obtaining the historical experience value of the number of the parked vehicles in the parking area by the intelligent barrier data of the high-quality parking lot P and the common parking lot P', wherein the parking duration distribution is known; meanwhile, the number of people who are expected to participate in the parking area is 300, the activity time is 9: 00-11: 00, and the proportion of the number of people who are expected to participate in the activity before starting is about 20%.

Because the pricing is good parking space pricing for the APP reservation user, the number Q of vehicles with parking requirements in the parking area in the day is predicted according to the method a) in the step (3):

the number of vehicles Q with parking demand in the parking area is the historical experience value of the arrival rate of the parking vehicles + the sharing ratio of the number of temporarily active participants in the parking area multiplied by the trip of the car is 500+300 × 20%: 560

The number Q of vehicles with parking demands in the area is grouped according to the parking time t, and a parking demand statistical table is obtained as follows:

meanwhile, as the number s of the high-quality berths is 100, the parking space-time resource can be provided

By integrating the required parking space-time resources S in the parking demand statistics with the groups_iBy comparison, it is found in group 42 data, i.e. when parking time t_iWhen 42 × 10 is 420min, it accumulates the required parking space time resource ∑ S_i13.7698 · hr, is the closest and does not exceed S_pGroup 14.1667 · hr. Therefore, the parking duration control threshold t of the parking area is determined_m＝420min。

4. It is known that parking charges for ordinary parking in the parking area are 5 yuan/h, and less than 1 hour is counted by 1 hour. When the parking time is the parking time control threshold t_mParking in off-road parking lot when 420minThe parking cost of is P'_t7 hx 5 yuan/h 35 yuan. The weighted average value of the driving distance between the high-quality parking space and each driving entrance of the parking area

Weighted average value of vehicle traveling distance between each vehicle traveling entrance of common parking space and parking area

Calculating the time length when the vehicle is stopped as t according to the formula (1)_mParking charge P for parking vehicles at high-quality berths_t:

Setting free parking time t of high-quality berth₀And (4) no charge is paid when the vehicle is parked in the in-road parking space for not more than 30 min.

When the parking time is the parking time control threshold t_m420min, including the unit charging duration t₀Number of 10min

Meanwhile, according to the cost pricing method, the price lower limit of the road parking space at P1 is 2 Yuan/h, namely the time t for free parking₀30min later, the first unit charging duration t of the parking space in the road₀Charging p of 10min₁0.5 yuan.

Thus, it is obtained according to the formula (4)

Therefore, the parking charge price of P1 premium berth is free for the first 30min, charge 0.5 yuan for the first 10min later, and then the charge price of each 10min is 0.040 yuan higher than the previous 10min, namely, the charge price for the second 10min is 0.540 yuan, the charge price for the third 10min is 0.580 yuan, the charge price for the fourth 10min is 0.620 yuan … …, and so on, as shown in the following table:

time period (min)	0-30	30-40	40-50	50-60	…	(30+n×10)-[30+(n+1)×10]
							Charging (Yuan)	0	0.5	0.540	0.580	…	0.5+n×0.040

Meanwhile, in order to encourage the parking user to reserve and use the high-quality parking space through the APP, the final parking charge of the user who parks the high-quality parking space before the advance reservation through the APP is calculated to be 90% of the calculated price, namely, the user enjoys the 9-fold discount. On the day of parking, if the charging price of the high-quality berth is adjusted in real time, the charging of the reservation user is not changed, and the reservation user still executes according to the charging standard informed by the system when the reservation user makes a reservation.

Detailed description of the invention

In this embodiment, a possible implementation of the above invention is provided, which is also the parking area described in the first embodiment, and when the number of the reserved good-quality parking spaces through APP is known, the parking charging standard applicable to the unreserved vehicle on the same day is established for the good-quality parking spaces in the parking area, and the parking charging standard is dynamically adjusted according to the actual parking situation. The implementation process is as follows:

1. through the field measurement, the parking area geometry information table is established as follows, and the result is the same as in the first embodiment.

It is known that in a related mobile terminal APP, the number of reserved high-quality parking spaces in a parking area is 60, and meanwhile, the number of parking users who reserve high-quality parking spaces by using the APP at the position is about 10% of the total number of the parking users at the position, which is obtained through field sampling investigation, and the parking time is filled in when reservation is carried out; obtaining the historical experience value of the number of the parked vehicles in the parking area from the intelligent barrier gate data at the parking lot P, wherein the parking time distribution is known; meanwhile, the number of people who are expected to participate in the parking area is 300, the activity time is 9: 00-11: 00, and the proportion of the number of people who are expected to participate in the activity before starting is about 20%.

Predicting the number Q of vehicles with parking demands in the parking area in the day according to the method b) in the step (3):

the number Q of vehicles in the parking area with parking demand

The number of reserved parking spots in APP + historical experience value of arrival rate of the parked vehicle x (1-proportion of reserved users to all users of APP) + number of temporarily active participants in parking area x sharing ratio of car traveling

60+500 × (1-10%) +300 × 20% ═ 570 (vehicle)

4. The number Q of vehicles with parking demands in the area is grouped according to the parking time t, and a parking demand statistical table is obtained as follows:

By integrating the required parking space-time resources S in the parking demand statistics with the groups_iBy comparison, found in group 41 data, i.e. when parking for a period of time t_iWhen 41 × 10min, it accumulates the required parking space-time resource ∑ S_i14.0357 · hr, is the closest and does not exceed S_pGroup 14.1667 · hr. Therefore, the parking duration control threshold t of the parking area is determined_m＝410min。

5. It is known that parking charges for ordinary parking in the parking area are 5 yuan/h, and less than 1 hour is counted by 1 hour. When the parking time is the parking timeControl threshold t_mWhen the time is 410min, the parking fee for parking in the off-road parking lot is P_t' -7 hx 5-membered/h-35-membered. The weighted average value of the driving distance between the high-quality parking space and each driving entrance of the parking area

According to formula (1), when parking

Length of t_mParking charge P for parking vehicles at high-quality berths_t:

When the parking time is the parking time control threshold t_m410min, including a unit charging duration t₀Number of 10min

Thus, it is obtained according to the formula (4)

Therefore, the parking charge price of the P1 premium berth suitable for the un-reserved user is free in the first 30min, the first 10min is charged for 0.5 yuan, then the charge price of each 10min is increased by 0.043 yuan compared with the first 10min, namely, the second 10min is charged for 0.543 yuan, the third 10min is charged for 0.586 yuan, the fourth 10min is charged for 0.629 yuan … …, and so on, as shown in the following table:

time period (min)	0-30	30-40	40-50	50-60	…	(30+n×10)-[30+(n+1)×10]
							Charging (Yuan)	0	0.5	0.543	0.586	…	0.5+n×0.043

6. Setting the real-time detection interval duration t of the system _r1h, namely every 1 hour, automatically detecting the actual vehicle number Q parked at a high-quality parking position by an intelligent barrier gate and a video parking space detector_rAnd real-time occupancy rate O of the premium berths at that time_rAnd report toAnd comparing the data with the predicted data and the target value. Now, the comparison process will be described by taking the result of the current measurement at 09:00 as an example.

The system detects the total number of the actual vehicles parked at the high-quality berth in the time period of 07:00-09:00 by detecting the data by the barrier gate in the morning of 09:00_rThe detection data of the video parking space detector at 09:00 shows that 79 vehicles are totally selected from 100 high-quality berths at the moment, namely the real-time occupancy rate O of the high-quality berths at the moment_r＝0.79。

Forecasting the demand by 09:00 from the operation of the optimal berth from 07:00

Then 120 > 1.15 × 80 ═ 92, that is, 0.85Q is not satisfied_p≤Q_r≤1.15Q_p. Therefore, the number Q of vehicles having parking demands in the parking area in the remaining time period of the day needs to be predicted again, that is, the steps (3) to (5) are performed again, the charge price of the premium parking space is recalculated according to the new parameters, and the updated parking charge price is issued. And the parking fee of the non-reserved users who come to park at the high-quality berth from 09:00 to the next time of updating is executed according to the updated charging standard. But the parking user who has entered the parking lot still executes the charging price according to the charging standard published when the parking user enters the parking lot; the subscriber is still charged according to the charging standard informed in the APP at the time of his subscription.

Detailed description of the invention

In this embodiment, a possible implementation of the above invention is provided, and the parking area and known conditions are the same as those described in example two. And classifying the high-quality berths in the high-quality berth parking lot P according to the conditions of position, size and the like, and implementing differentiated pricing on the high-quality berths in different grades. The specific implementation process is as follows:

since the parking area and the implementation conditions are the same as those in the second embodiment, the previous steps and results are the same as those in the second embodiment, and the price of the high-quality parking space and the change of the parking time under the condition of no grading are shown in the following table:

The premium berths are now ranked. An internal plan view of a parking lot P in which a premium parking space is located is shown in fig. 14. In the figure, the berth marked I is a first-grade high-quality berth which is close to the entrance and the exit, the elevator or the payment machine in position and is larger than other berths, the berth marked II is a second-grade high-quality berth which is the same as most berths in size but close to the entrance and the exit, the elevator or the payment machine in position, and the berth which is not marked is a third-grade high-quality berth. Grade coefficient gamma of different grades of premium berths_iThe setting is shown in fig. 9.

According to the ranking coefficient and the calculated premium parking charge price under the non-ranking condition in the second embodiment, the parking charge matrix of the premium parking space in the parking area can be obtained as follows:

actual number of vehicles Q parked at a premium parking lot 13 times on the day_rAnd real-time occupancy rate of premium berths O_rIn the real-time detection, both indexes meet 0.85Q_p≤Q_r≤1.15Q_pAnd 0.7 or more of O_rLess than or equal to 0.9. Therefore, the charging standard of the high-quality berth suitable for the non-reservation user is executed according to the price on the day and is not changed.

Claims

1. A high-quality berth dynamic pricing method for priority short stop comprises the following steps:

1) establishing a parking area geometric information table; the geometric information of the parking areas comprises the number m of vehicle driving entrances of the parking areas and the vehicle driving distance d between the vehicle driving entrance and the high-quality parking place of each parking area_nAnd a vehicle traveling distance d 'between the vehicle traveling entrance and the ordinary parking place of each parking area'_nAnd the walking distance delta d between the high-quality berth and the common berth, and the data are obtained by field measurement;

2) determining a unit charging duration t₀；

3) Determining parking characteristic data in a parking area; the parking characteristic data in the parking area comprises the number Q of vehicles with parking requirements entering the parking area, the parking time t of the vehicles with parking requirements, and the proportion beta of the vehicles entering from each driving entrance in the parking area_nTravel time value alpha of parking user in parking area and average vehicle speed v in parking area_dAverage speed v of travel in parking area_wAnd a price sensitivity coefficient mu of a parking user in the parking area;

4) determining a parking duration control threshold t_m(ii) a The parking time control threshold t_mRefers to the length of time that a parking manager wants to give a good quality parking space to a vehicle for parkingMaximum value of (d); i.e. the manager wishes all parking periods to be less than or equal to t_mThe vehicle is parked to a good parking space for a time period longer than t_mThe vehicle goes to a common parking space for parking;

5) controlling a threshold t according to the parking duration_mDetermining the price of high-quality parking charge; the high-quality parking charge price is determined according to the following steps:

(a) calculating a control threshold t when the parking time is the parking time according to a known ordinary parking charging policy_mTime, parking charge price P 'of ordinary parking space'_t；

(b) Setting free parking time t of high-quality berth_f；

(c) Method for determining free parking time t of high-quality berth according to cost pricing method_fFirst t after the end₀Price charged in duration p₁；

(d) When the parking time is t_mTime, parking charge price P 'of ordinary parking space'_tAnd the data in the parking area geometric information table, and calculating the parking time length t according to the formula (1)_mParking charge P for parking vehicles at high-quality berths_t:

Wherein d' is calculated by equation (2) and d is calculated by equation (3):

d' is the weighted average of the vehicle traveling distance between the ordinary parking space and each vehicle traveling entrance of the parking area; delta d is the walking distance between the high-quality berth and the common berth; v. of_dIs the level of the vehicle in the parking areaThe average running speed; v. of_wIs the average walking speed of the parking user within the parking area; d_nThe driving distance between the nth driving entrance of the parking area and the high-quality parking place; d'_nThe driving distance between the nth driving entrance of the parking area and the high-quality parking place; beta is a_nThe proportion of vehicles entering from the nth driving entrance in the parking area is shown; d is the weighted average of the vehicle traveling distance between the high-quality berth and each vehicle traveling entrance of the parking area; alpha is the travel time value of the parking user in the parking area;

(e) when the parking time is t_mParking charge P for parking vehicles at high-quality berths_tAnd calculating the price increment variance delta p of the high-quality berth according to the formula (4):

wherein

(f) Free parking time t from high-quality berth_fFirst t after the end₀Charge price p of duration₁And the price increasing variance delta p of the high-quality berth, and the free parking time t of the high-quality berth is calculated according to the formula (5)_fAfter the end of the nth t₀Charge price p of duration_n：

p_n＝p₁+(n-1)·Δp (5)；

6) Determining a real-time detection interval duration t_rEvery t, every_rDuration versus actual number of vehicles parked at premium parking lot Q_rAnd real-time occupancy rate of premium berths O_rCarrying out real-time statistics and detection;

7) comparing the real-time detection data with the prediction data, and determining the high-quality parking charge price in the following time period; the real-time detection data refers to the actual number O of vehicles parked at a high-quality parking space_rAnd real-time occupancy rate of premium berths O_r(ii) a The number of vehicles with parking requirements in the parking area determined in the step 3)Q, obtaining the predicted demand from the initial pricing period to the current time

2. The method for dynamically pricing premium berths with priority short stops according to claim 1, wherein the unit charging duration t is₀The value should satisfy t is less than or equal to 1 minute₀Less than or equal to 20 minutes.

3. A method for dynamic pricing of premium berths with priority short stops according to claim 2, characterized in that the ratio β of vehicles entering from each entrance of vehicles in the parking area_nTravel time value alpha of parking user in parking area and average vehicle speed v in parking area_dAverage walking speed v of parking users in parking area_wAnd the price sensitivity coefficient mu of the parking users in the parking area is obtained by sampling and surveying in the parking area.

4. A method for dynamic pricing of premium berths with priority short stops according to claim 2, characterized by first acquiring at least two of the following four relevant data:

a) the number Q of the parked vehicles in the parking area at the same time period_ⅠAnd historical empirical value t of parking duration_Ⅰ: the method comprises the steps that the number of vehicles parked in the parking area is obtained by summing the number of vehicles parked in the high-quality parking space and the number of vehicles parked in the same parking space at the common parking space respectively through data or manual records stored in an intelligent parking facility; simultaneously recording the parking time of each vehicle; randomly extracting recorded values of a plurality of days and averaging the recorded values to obtain historical experience values of the number of the parked vehicles and the historical experience values of the parking duration in the parking area; when historical data is extracted and counted, the selected dates are respectively counted under the three conditions of large demand difference, namely working days, weekends and special festivals and holidays;

b) real-time traffic flow Q of surrounding roads_Ⅱ: is defined by traffic control department orReal-time traffic flow data of a road network surrounding the parking area, which is published by a professional third party;

c) berth reservation data Q on mobile terminal APP_Ⅲ、t_Ⅲ: the number and the time period of reserved high-quality berths in the parking area on the related mobile terminal application APP are indicated;

d) known inducement of temporary activity in parking area parking demand Q_Ⅳ、t_Ⅳ: the number of the participants of the temporary event and the event holding time in the parking area are referred to, and the parking time length of the lured parking requirement is consistent with the event holding time length;

and calculating the number Q of vehicles with parking requirements and the parking time t of the vehicles with parking requirements in the parking area according to one of the following three methods by using the acquired data:

i) the number Q of vehicles with parking demands in the parking area is equal to the historical experience value Q of the number of the vehicles parked in the parking area at the same time_Ⅰ+ number of persons participating in temporary activities in parking area Q_ⅣThe sharing ratio of the trip of the car is multiplied; wherein the value of the sharing ratio of the car traveling is more than 0.1 and less than 0.3, and the sharing ratio is obtained by sampling and surveying on the spot; the parking time t in the parking area is determined by the historical empirical value t of the parking time_ⅠAnd parking duration distribution t of temporary activity induced parking demand in parking area_ⅣStacking to obtain the product;

ii) number of vehicles with parking demand Q in the parking area APP reserved parking space number Q_Ⅲ+ historical experience value Q of number of parked vehicles in the parking area in the same time period_ⅠX (1-APP reservation user to all parking users) + number of participants for temporary activities in parking area Q_ⅣThe sharing ratio of the trip of the car is multiplied; the proportion of APP reservation users to all users is obtained through sampling investigation, the value of the sharing ratio of car traveling is more than 0.1 and less than 0.3, and the APP reservation users are obtained through sampling investigation on the spot; the parking time t in the parking area is determined by the historical empirical value t of the parking time_ⅠAnd the parking time length t of the parking demand determined by the historical data and the APP reservation data_ⅢAnd from parking areasParking duration t of parking demand induced by internal temporary activities_ⅣThree terms are obtained by superposition;

iii) number of vehicles with parking demand in the parking area

5. The method for dynamic pricing of premium berth with priority short stops according to claim 4, characterized in that method ii) as defined in claim 4 should be used when determining the premium berth price offered to the booking user; when performing real-time dynamic adjustment of premium berth prices, method i) or method iii) as claimed in claim 4 should be used; the price adjusted in real time is only suitable for non-reservation users who enter the parking space after the price is released, and for the parking users who have made reservations, the charging price is still executed according to the charging standard informed when the parking users make reservations.

6. A method for dynamic pricing of premium berths with priority short stops according to claim 4, characterized in that said parking duration control threshold t_mThe determination is carried out according to the following steps:

(1) the number Q of vehicles with parking requirements and the parking time t of the vehicles with parking requirements determined by one of the methods i), ii) and iii) according to claim 4, the total number Q of vehicles with parking requirements in the parking area is grouped and counted according to the parking time t of the vehicles with parking requirements, and the group distance is the unit charging time t₀And obtaining the parking time of the ith group of data as t_i＝i×t₀The number of vehicles is q_iI has a value range of i ═ 1,2,3₀Where T is the total pricing duration;

(2) number q of vehicles from group i_iAnd calculating to obtain the ith group of vehiclesAverage per t₀Amount of arrival of duration

(3) Averaged every t by i-th group of vehicles₀Time length arrival q_0iAnd a parking time period t of the ith group of vehicles_iAnd calculating to obtain the number S of the parking space-time resources required by the ith group of vehicles_i＝q_0i×t_i；

(4) The number S of parking space-time resources required by each group of vehicles₁，S₂，...，S_iAnd calculating to obtain the accumulated parking space-time resource quantity sigma S of the front i groups of vehicles_i＝S₁+S₂+…+S_i；

(5) Calculating the parking space-time resource S provided by the high-quality berth according to the berth number S of the high-quality berth_p＝0.85×s×t₀；

(6) Will sigma S₁,∑S₂,...,∑S_iParking space-time resource S provided by high-quality berth_pComparing to find an i' to make S_i' nearest but not exceeding S_pThe parking duration t corresponding to the group i_i′I.e. the parking time control threshold t_m。

7. A method for dynamically pricing premium parking lots with priority over short stops according to claim 1, wherein the premium parking lot parking charge price is obtained by multiplying the calculated parking charge price by a price sensitivity factor μ of parking users in the parking area, wherein the value of μ is 1 < μ ≦ 1.5.

8. The method for dynamic pricing of premium berths with priority short stops according to claim 1, characterized in that the premium berth parking charge is discounted to parking subscribers who reserve ahead.

9. The method for dynamic pricing of premium berths with priority short stops according to claim 1, characterized in that said premium berths are obtained by a single-stage pricingWhen the parking charge is carried out on the parking lot, when the number of high-quality parking lots is large, the high-quality parking lots are classified according to the difference of position, facility and size conditions among different high-quality parking lots; by multiplying the calculated parking charge price by a different premium parking level factor gamma_iAnd obtaining a high-quality berth charging matrix.

10. A method for dynamic pricing of premium berths with priority short stops according to claim 1, characterized in that the number Q of actual vehicles parked at the premium berths is the number of actual vehicles_rAnd real-time occupancy rate of premium berths O_rIs real-time information acquired by at least one intelligent parking facility in an intelligent barrier gate, a video parking space detector, an infrared parking space detector, a microwave parking space detector or a geomagnetic coil, and the information is acquired at intervals of t_rThe duration is collected once; the number Q of the actual vehicles parked at the high-quality parking space_rThe actual number of vehicles stopping at a high-quality berth from the initial time of a pricing period to the current time detected in real time; real-time occupancy rate of premium berths O_rThe ratio of the number of the occupied high-quality berths to the total number of the high-quality berths at the current moment is referred to.

11. The method for dynamically pricing premium berth with priority short stop according to claim 1, wherein the real-time detection data is compared with the prediction data, and the judgment criteria for determining the premium berth parking charge price for the following time period are: 0.85Q_p≤Q_r≤1.15Q_pAnd 0.7 or more of O_r≦ 0.9, where the predicted demand is from the start of the pricing period to the current time

If the standard is met, the original charging scheme is unchanged; if not, the steps 3) to 5) described in claim 1 are executed again, the relevant parameters are updated, and a new charging scheme is formulated and issued.