WO2018122587A1 - Dynamic pricing method for premium parking spaces with priority given to short-term parking - Google Patents

Abstract

A dynamic pricing method for premium parking spaces with priority given to short-term parking. Said method factors in the number of premium parking spaces, parking demand characteristics of an area, parking space occupancy rates, and so on. A progressively-increasing fee calculation method is used to calculate fee prices for premium parking spaces in a precise manner, and adjustments are made dynamically according to actual situations. This allows vehicles parking for short periods of time to be given priority to the limited supply of premium parking spaces, and thereby increases the turnover rate of premium parking spaces, which enables more drivers to enjoy a parking service that is comfortable and convenient, and that affords a shorter walking time, thus leading to an increase in overall societal efficiency.

Description

A high-quality berth dynamic pricing method with priority short stop

 A Pricing Method for High Quality Parking Lots with Priority to Short-parking Cars

Technical field

The invention relates to a high quality berth dynamic pricing method with priority short stop. When the driver drives to the parking area near the destination to prepare for parking, he prefers to choose a high-quality berth with convenient location and safe parking. He is not willing to have a remote location, a parking lot is difficult, and it is difficult to find a normal berth. The shortage of supply will result in congestion and increased emissions. The city manager can use the method proposed by the present invention to park the premium berth to realize the management and guidance of the parking demand. In particular, the present invention considers the number of high-quality parking berths, the characteristics of regional parking demand, the occupancy rate of parking spaces, etc., by means of incremental progressive charging, finely setting the charging price of high-quality berths and dynamically adjusting according to actual conditions to achieve The priority of providing limited quality berths to vehicles with shorter parking hours, improving the turnover rate of high-quality berths, enabling more drivers to get comfortable and convenient parking services and shorter walking time, improving the overall efficiency of society. Background technique

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

 (1) embody the principle of fairness of "user pays";

 (2) Improve the turnover rate of public parking berths and optimize the use of existing parking facilities;

 (3) Guarantee parking order and traffic safety through fee management;

 (4) Stimulating or suppressing certain modes of transportation by adjusting the parking rate;

 (5) The spatial difference, parking time difference and parking facility type difference have a significant effect on adjusting the supply and demand relationship of urban parking facilities. For example, the implementation of the land-level differential level and time-based progressive charging method in the central area is used as an economic lever. It can adjust and control the parking supply in the central area, and then regulate the dynamic and static traffic demand in the central area. At present, most of the roadside parking fee rates are formulated using the "cost pricing method." The basis for its consideration is service costs (including land cost, construction cost, operating cost, etc.), willingness to pay, characteristics of parking demand, and urban transport policy objectives. Prior art 1

A U.S. Patent Application Serial No. US20140122375 discloses a method for dynamically adjusting parking pricing based on real-time parking occupancy of a parking lot. This pricing method needs to detect the real-time occupancy rate of the parking space through the smart sensor. The comparison module compares the current occupancy rate with the target occupancy rate, and realizes the feedback control of the parking demand by adjusting the parking pricing in real time. Figure 1 shows a flow chart of the implementation of this dynamic pricing method. Figure 2 shows the change in parking demand, parking space occupancy, and set parking pricing for an implementation of this pricing method. It can be seen from Fig. 2 that this pricing method improves the pricing of parking charges when it detects that the occupancy rate of the parking space exceeds the set target value, that is, when the parking demand is large, and suppresses the demand, so as to reduce the occupancy rate of the parking space to Set below the 85% threshold. But In this pricing method, the system provides berth resources to the parking lot according to the principle of first-come first-served service, and does not consider the difference between the advantages and disadvantages of the berth resource conditions, and does not distinguish and select the parking time of the parking users. Therefore, the maximum utilization of high quality berth resources has not been realized. Prior art 2

 A US patent application, US20110213672, discloses a differential pricing method for berths under high demand conditions. This method divides the available berths in the parking lot into categories such as "ordinary berths", "one of the last reserved berths", and "the only last berths reserved". The concept of berth "contribution value" is used for reference, according to different categories. The berths have different contribution values and are priced differently in order to maximize the operator's profits. Figure 3 shows the division of the berth category using this method in a parking lot. The mark L is "large size berth", the mark S is "safe berth", and the unmarked is the ordinary parking space. The following table shows the classification of berths and pricing rules in one implementation of this method.

It can be seen that although this pricing method differentiates and differentiates the berth, it does not make a reasonable choice for the parking time of the parking lot. The purpose of this pricing method is to maximize the operator's profit rather than optimize the social efficiency. Therefore, it cannot guarantee that its high quality berth can serve more drivers to the greatest extent. Therefore, there is also a certain amount of waste of high quality berth resources. Summary of the invention

 The use of limited quality berths to maximize the parking demand of vehicles with shorter parking periods and improve the turnover rate of premium berths is the key to improving the overall efficiency of society. This idea can be illustrated with the following examples:

 Assume that there is a convenient high-quality berth, and the walking distance of the final destination that the traveler wants to reach after parking is 2 minutes. At the same time, there is a common parking space with a far distance, and the walking distance to the final destination is 5 minutes. Suppose that two drivers in the first and second time need to stop at the same time to reach this destination. The parking time of A is 6 hours, the parking time of B is 2 hours, and the driver is 2 hours later (:, After 4 hours, the driver D also needs to stop and arrive at the same destination, and the parking time is also 2 hours. Under the existing technical methods, the possible situation is:

Driver A parks the car in a premium parking space and walks for 2 minutes to reach the destination; at the same time, driver B parks the car in the regular parking space and walks for 5 minutes to reach the destination. After 2 hours, the B car leaves, and the C that arrives can only park the car in the ordinary parking space (because the high quality berth is still occupied by the A car), and it takes 5 minutes to walk to the destination after parking; In the sample plot, C will leave after 2 hours, and the D that arrives at this time can only park the car in the ordinary parking space (because the high quality berth is still occupied by the A car), and it takes 5 minutes to walk to the destination after parking. In this case, the total time spent by four drivers in the entire system is 2+5+5+5=17 minutes. However, if the idea of the present invention is adopted to prioritize the high quality berth to meet the short stop vehicle, the situation will become:

Driver A parked the car in the regular parking space and walked for 5 minutes after parking; at the same time, driver B parked the car in a premium parking space and walked for 2 minutes after parking. After 2 hours, when C arrives, the B on the premium parking space has already left, so C will park the car in the quality parking space. Similarly, when the arrival of 2 hours D, the C on the premium parking space has already left, so D will park the car in a premium parking space, so (:, D requires 2 minutes of walking time. In this case, the total walking time of the four drivers in the entire system is 5+2+2 +2=11 minutes. Figure 4 compares the two scenarios.

Through this example, it can be found that by preferentially assigning premium parking spaces to vehicles with short parking periods (hereinafter referred to as "short stop vehicles"), in this system, the overall walking time of the system is significantly reduced, and the efficiency is greatly improved. How to stop the short stop vehicle to stop at the high quality berth and stop the vehicle to the ordinary parking by reasonable pricing of the quality berth is the problem to be solved by the present invention. The invention provides a method for dynamic pricing of high quality berths based on priority berth quantity limitation and parking demand feature distribution, which can obtain parking parking behavior characteristics, calculate parking time control threshold and charging standard, and realize induced transfer length. Stop the vehicle to the ordinary berth, and dynamically adjust the price according to the actual demand status. Achieve the goal of improving the quality of berths and reducing the total cruise time and walking time of the system. The high quality berth described here refers to a parking space with higher convenience. The obvious feature is that the distance from the final destination to be reached by the driver in the parking area is relatively short, and the walking time required by the driver after parking is short. The ordinary berths described here refer to berths that are less convenient than high quality berths, and are characterized by relatively remote locations, and the walking time required for the driver to walk to the final destination in the parking area after parking is longer. When high quality berths and ordinary berths are present in a certain area, the high quality berths therein can be priced by the method of the present invention. The invention specifically includes the following steps:

 (1) Establish a parking area geometry information table. The information includes the number of car entrances in the parking area, the distance between the parking areas of the parking areas and the quality berths, the distance between the parking areas of the parking areas and the ordinary berths, and the quality berths. The walking distance Ad between the ordinary berths is obtained by field measurement. The established parking area geometric information is shown, for example, in FIG.

(2) Determine the unit billing duration ^. The unit billing time length i _Q may be any length of time shorter than the required price period. If the parking fee policy within 3 hours is to be established, it shall satisfy ^ ≤ 3 hours. The portion of the parking duration that is less than one ^ is calculated as an i _Q at the time of billing. In particular, it is proposed in the method that the value of i _Q should satisfy 1 minute ≤ i _Q ≤ 20 minutes. This is because the larger the parking fee increases with the increase of the parking time, the more obvious the stepwise mutation will make the user with the time near the sudden change threshold more sensitive to the change of the charge, thus increasing the user's time anxiety and reducing the parking user's parking. Service satisfaction. Figure 6 shows that in the case where a user is parked for 2 hours and the total cost of the final payment is the same, the parking fee is set in the case of setting the unit billing duration i _Q = 1 hour and i _Q = 10 minutes. Changes in time over time in 2 hours. It can be seen from Fig. 6 that in the case of t _Q = l hours, the charging increase has a significant step change, which makes the parking person have obvious psychological anxiety when parking for nearly 2 hours, because the worry time is more than 2 Hours, the cost will increase suddenly. In the case of i _Q = 10 minutes, the fee increase is more gradual, and the user does not have to worry about a large increase in the cost due to exceeding a certain time limit, thereby improving the user's parking experience. Determine the parking feature data in the parking area. The data includes the number of vehicles entering the parking area with the parking demand Q, the parking time of the vehicle having the parking demand, the ratio of the vehicles entering the parking area from the respective entrances β _η , and the parking users in the parking area. The time value α, the average speed i7 _d in the parking area, the average walking speed in the parking area, and the price sensitivity coefficient μ of the parking user in the parking area. The travel time value α of the parking user in the proportional parking area of the vehicle entering the parking area, the average speed i7 _d in the parking area, the average walking speed I7 _W of the parking user in the parking area, and the parking area The price sensitivity coefficient μ of the parking user can be obtained by field sampling survey in the parking area. In determining the two data of the number Q of vehicles in the parking area and the parking time t of the vehicle having the parking demand, it is necessary to utilize at least one of the following four related data: a) parking at the same time The number of parking vehicles in the area ρ j and the historical experience value of the parking time ί j. Through the data or manual records stored in the intelligent parking facilities, the number of arrivals of high-quality berths and parking vehicles at ordinary berths is obtained and summed, and the parking time of each vehicle is recorded, and the recorded values of multiple days are randomly selected and averaged. That is, the historical experience value of the number of parking vehicles in the parking area and the historical experience value of the parking time. In particular, when the historical data is extracted and counted, the selected date is divided into three categories: the working day, the weekend, and the special holiday. b) Real-time traffic flow ρ _{π of the} surrounding roads. Refers to real-time traffic flow data published by the traffic management department or related professional third parties around the road network around the parking area. c) on the mobile terminal berth ΑΡΡ reservation data _ρ ΠΙ, ί ΠΙ. Refers to the user who has the parking demand to make an appointment for the high quality berth in the parking area through the relevant mobile terminal application in advance, and informs the time period of the required parking. The number of premium berths reserved on the 和 and the appointment period can be obtained in real time from the application background. d) The induced parking demand ρ!ν, t _w of the temporary activity in the known parking area. Temporary activities that will occur in the parking area will increase the parking demand in the parking area, so it is necessary to know the number of people participating in the event and the time when the event is held. Using one or more of the above related data, the number of vehicles Q having parking demand and the parking time t of the vehicle having parking demand in the parking area are predicted by one of the following three methods: a) the parking Number of vehicles with parking demand in the area Q =

 The historical experience value of the number of parking vehicles in the parking area at the same time ρ! + The number of participants in temporary parking activities in the parking area ρ^χ The sharing ratio of car trips; the sharing ratio of car trips is greater than 0.1 and less than 0.3, obtained by field sampling survey; the parking time t in the parking area is The historical experience value of the parking time and the parking time distribution i!V superimposed by the temporary parking activity in the parking area are superimposed. b) Number of vehicles with parking demand in the parking area Q =

The number of reserved berths in the APP ρ _ΠΙ + The historical experience value of the number of parking vehicles in the parking area at the same time ρ j X (l - the ratio of APP reservation users to all parking users) + Temporary activities in the parking area

The sharing ratio of car travel; the ratio of APP reservation users to all users is obtained through sample survey. The share ratio of car travel is greater than 0.1 and less than 0.3, obtained through field sampling survey; parking in parking area The duration t is obtained by superimposing the historical experience value tj of the parking time period and the parking time length of the parking demand determined by the historical data, the APP reservation data, and the parking time length i!V of the parking demand induced by the temporary activity in the parking area. There are parking demand within c) the number of vehicles in the parking area of real-time traffic flow Q = _ρ ΤΙ χ roads around the same time the historical experience of the number of vehicles parking in the parking area segment

 -, total demand parking time t distribution and parking time history data historical average of real-time traffic flow of surrounding roads

The distribution of empirical values t _{T is} consistent. Method a) should be used when determining the premium berth price offered to the subscriber in the APP; method b) or method c) should be used when real-time dynamic adjustment of the premium berth price is made. But the price adjusted in real time only applies For non-reserved users who enter the berth after the price is released, the charging standard for the parking users who have made reservations on the APP is still executed according to the charging standard notified at the time of the reservation. Determine the parking duration control threshold t _m . Follow these steps:

From the data obtained in the step (3), the total number of vehicles Q having parking demand in the parking area is grouped according to the parking time length t, and the group distance is the unit charging time period t _Q . That is, the parking duration of the i-th data is ti = iXt _Q , the number of vehicles in the group is qi, and the range of i is i = 1, 2, 3 T/t _0; where T is the total pricing duration; vehicle group number _qi, calculation of the average length reaches an amount per t _Q i-th group vehicle q _Qi = ^ - by the average stop time _Q long reaches an amount q _Qi and the i-th group of vehicles each t i-th group vehicle length calculation i The number of parking space and time resources required for the group of vehicles = q _oi Xt _r , the number of parking space and time resources required by each group of vehicles Si, S ₂ Calculate the amount of parking space and space resources required for the former group i vehicles ∑8^ = 8 ₁ + 8 ₂ +- + 5^; Calculate the parking space and time resources S _p = 0.85xsxt _o provided by the berths of the high quality berths; and the parking space and time resources that can be provided by ∑Si, ∑S ₂ ∑Si and high quality berths 5 _!? compared to find a i ', such that Σ nearest to but not more than S _p, in its category i' ^ long length corresponding to the parking and a parking control when the threshold

Figure 7 shows the calculation flow of the parking duration control threshold t _m . This calculation process can be calculated using the parking demand statistics table. The following table is an example of a parking demand statistics table.

Average _waiting time for parking time q _Qi required parking resources Si Cumulative required parking space resources

 Number of cars

(10min) (cars/lOmin) (hours·hours) ∑s _; (one hour)

 1 6 0.333 0.056 0.056

 2 1 0.056 0.019 0.074

 3 1 0.056 0.028 0.102

 4 1 0.056 0.037 0.139

 5 3 0.167 0.139 0.278

 6 2 0.1 1 1 0.1 1 1 0.389

 7 3 0.167 0.194 0.583

 8 1 0.056 0.074 0.657

 9 3 0.167 0.250 0.907

10 0 0.000 0.000 0.907 Determine the price of premium berth parking. Follow these steps:

According to the known ordinary berth parking charging policy, when the parking time is the parking time control threshold, the parking levy price P _t ' of the ordinary berth _; the free parking time t _{f of} the high quality berth, that is, the parking time of the vehicle at the high quality berth If it does not exceed ^, no charge will be made; ^ can be valued as o, that is, the vehicle starts to charge from a high-quality berth; the cost price is used to determine the lower price limit of the premium berth in the duration, as the free berth free parking time ^ The charge price p ₁ in the first t _Q duration after the end _; by the parking time length t„^f, the parking charge price P _t ' of the ordinary berth and the data in the parking area geometric information table, according to the formula ( 1) Calculate the parking charge for vehicles parked at high quality berths when the parking time is t _m : pp _{+ a} (^ _{+ 2} .^ (1)

V v _d v _w

among them:

P _t ' represents the parking fee required to park the vehicle at the ordinary berth when the parking time is equal to the duration control threshold t _m ;

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

Ad means walking distance between high quality berth and ordinary berth;

d' denotes the distance between the ordinary berth and the entrance of the parking area. If there are multiple entrances in the parking area, a weighted average of the normal berths and the lanes between the vehicle entrances is used, and the weight is the ratio of the vehicles entering the parking area from each entrance by (2):

d' =∑^ ₌₁ β _η -ά _η ' (2) where:

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

β _η represents the proportion of the vehicle entering the area from the nth car line entrance in the parking area; d represents the road path between the nth car line entrance and the ordinary berth.

d represents the distance between the high quality berth and the parking area entrance of the parking area. If there are multiple car entrances in the area, the weighted average of the distance between the high quality berth and each of the car entrances is used, and the weight is the ratio of the vehicles entering the parking area from each entrance by (3):

d =∑^ ₌₁ β _η -ά _η (3) where:

d _n represents the distance between the nth car line entrance and the premium berth. The rest is the same as above.

v _c represents the average traveling speed of the vehicle in the parking area;

v _w represents the average walking speed of the traveler in the parking area. From the parking charge when the parking time is 1 ₎ „ when the vehicle is parked at the high quality berth, the price increase variance Δρ of the high quality berth is calculated according to formula (4), that is, the charging ratio of the nth unit billing time length of the high quality berth ^ Η-1) unit billing duration t _Q part of the increase in charges: 2(P _t -W- _Pl )

 Δρ = ( 4) W(W-l)

among them:

_ t _m — tf

N represents the length control threshold stop ₁₎ "long time units contained in the billing number, i.e., N _t f) t to time length t _Q after the end _f the first price charged p ₁ and high berth when free parking by the high berth The price increase variance Δρ, calculated according to formula (5), the high-quality berth free parking duration ^ the end of the η time after the charge price

Wherein, steps b), c), and d) can be performed simultaneously, and FIG. 7 shows a flow chart for calculating the price of the premium berth parking fee. In this step, one possible implementation manner is that for a parking user who makes a reservation for a premium berth using the mobile terminal application APP, the system provides a charging plan at the time of reservation, and at the time of final charging, the charging scheme Based on a certain degree of discount. In this step, one possible implementation is to consider the price sensitivity coefficient μ of the parking user in the parking area. That is, when the parking user in the parking area has a small response to the price change of the premium berth charge, the calculated parking charge price may be multiplied by a coefficient μ, 1 < μ ≤ 1.5 to achieve a certain expansion to achieve the purpose of effective splitting. . In this step, a possible implementation manner is that when the number of high quality berths is large, the high quality berths are classified according to the difference of conditions, facilities, sizes and the like between different high quality berths. When the location of the high quality berth is more convenient, the berth size is larger, and the difficulty of the vehicle entering and leaving the berth is smaller. The higher the level corresponding to the high quality berth, the larger the value of the grade factor I is. By multiplying the calculated parking fare price by a different grade factor ^, differentiated premium berths of different grades are realized, and finally a high quality berth charging matrix indicating premium berths at different times and different levels of conditions is obtained. Figure 9 shows a possible classification of multiple premium berths located in the same parking lot and the setting of the grading factor. Figure 10 shows an example of a premium berth charging matrix. Here, the derivation of formula (1) is explained: When the driver enters the area, the parking option is to go to the high quality berth or the ordinary berth with the principle of minimizing the travel cost. The travel costs incurred by the driver during the parking process include: parking fees paid at high quality berths or ordinary berths, driving time from the entrance of the area to the berth, and the time required to walk between the berth and the destination. . The parking cost consisting of these three parts can be expressed as:

C = Ρ + at _d + at _w ( 6 ) In equation (6 ):

 C indicates the parking cost incurred when the driver selects a premium berth;

 P represents the parking fee paid by the driver when selecting a premium berth;

t _d represents the travel time required for the driver to travel from the area entrance to the premium berth, equal to the driving distance divided by the average speed; t _w represents the walking time required for the driver to walk between the high quality berth and the destination, equal to twice the (round trip) walking distance divided by the average walking speed;

 The rest is the same as above.

 According to the definition of high quality berth, that is, its distance from the driver's destination is very close, the walking cost can be neglected when considering the travel cost of selecting a premium berth. Then equation (7) can be written as

C = P + at _d = P + a— (7) Similarly, there are:

C' = P' + at' _d + at _w ' (8) In equation (8):

 C represents the parking cost incurred by the driver when selecting an ordinary berth;

 P' indicates the parking fee paid by the driver when selecting the ordinary berth;

t' _d represents the travel time required for the driver to travel from the regional entrance to the ordinary berth, equal to the driving distance divided by the average speed;

 t represents the walking time required for the driver to walk between the ordinary berth and the destination, equal to twice the (return) walking distance divided by the average walking speed;

 The rest is the same as above.

 Since the distance between the premium berth and the destination is negligible, the distance between the ordinary berth and the destination can be approximated by the distance Ad between the ordinary berth and the premium berth. Then equation (8) can be written as:

C = ?' + t' _d + t' = ?' + — + — (9) In order to achieve the purpose of inducing long-term vehicle transfer to ordinary berth, the price of the premium berth charge and the price of the ordinary berth should be met. :

C < C , when t<t _m

Second, when two! ^ (10) OC , when t>t _m

among them:

t indicates the length of time the driver is parked, and the rest is the same as above.

Figure 11 shows a comparison of parking charges between premium berths and regular berths.

Therefore, the formula (1) can be derived by deriving from the equations (7), (9) and (10), and then the charge price in the billing duration i _Q of each unit of the high quality berth is obtained.

(6) Determine the real-time detection interval duration ^, perform real-time statistics and detection of the actual number of vehicles parked at the high quality berth and the real-time occupancy rate of the high quality berth. Using intelligent gates, video parking detectors, infrared parking detectors, microwave parking detectors or geomagnetic coils, the actual number of vehicles parked at high quality berths and the quality at this time from the beginning of the pricing period to the current time. The real-time occupancy of the berth is 0, and the data is reported to the system.

(7) Compare the real-time detection data with the predicted data to determine the premium berth parking charge price for the subsequent period. The number Q of vehicles having parking demand in the parking area determined in step (3) is obtained from the beginning of the pricing period to the current Forecast demand at the moment = 诵 long,

The total time length τ of the pricing period is compared with the actual number of vehicles parked at the high quality berth. If 0.85ρ _ρ < Q _r < 1.15ρ _ρ and 0.7 < O _r < 0.9, the original charging plan is unchanged; if not, the required Re-execute steps (3) through (5), update the relevant parameters, and publish and release a new charging plan. The above symbols and their meanings are summarized in the following table:

 Symbol meaning

 m Total number of car entrances in the parking area

 Dn parking area between the nth car line entrance and the quality berth

 Άη' Parking area between the nth car line entrance and the ordinary berth

 Ad quality berth and regular berth walk

 To unit billing time

 Q Number of vehicles with parking demand in the parking area

 t Parking time of vehicles with parking demand in the parking area

 Historical experience of parking time in the parking area

Q i Historical experience of the number of vehicles parked in the parking area

Q ll Real-time traffic flow of surrounding roads Mobile terminal Stop time of reserved berths on APP

Number of berth reservations on the Qm mobile terminal APP The length of parking for the temporary parking activity in the parking area

Qw The amount of parking demand for temporary activities in the parking area βη The proportion of vehicles entering from the nth car entrance in the parking area

 a Travel time value of parking users in the parking area

v _d average speed of vehicles in the parking area

 Average walking speed of parking users in the parking area

 μ Price sensitivity coefficient of parking users in parking area

 Parking time control threshold

 Parking duration of the i-th vehicle in the parking demand statistics table

 Number of vehicles in the i-th group in the parking demand statistics table

The average amount of arrival of the i-th vehicle in the qoi parking demand statistics table per t _Q duration

 T total pricing duration

Number of parking time and space resources required for Group i vehicles in the Si Parking Demand Statistics Number of parking time and space resources required for the former i group of vehicles in the parking demand statistics table s Number of parking spaces for high quality berths

s _p quality berths can provide the amount of parking space resources

Group corresponding to the parking duration control threshold t _{m in} the V parking demand statistics table

Pt parking time is equal to t _m , the parking fee for parking the vehicle at the ordinary berth

Pt parking time is equal to 1 ₎ „When the vehicle is parked at a premium berth, the parking fee is required. tf High-quality berth free parking time

 Pi quality berth free parking time ^ the first time after the end of the price of the price d high-quality berth and parking area between the car line entrance between the weighted average d' ordinary berth and parking area between the car line entrance Weighted average

 Δρ high quality berth price increment variance

N When the parking time is t _m , the number of unit billing durations i _Q

 Pn premium berth free parking duration ^ nth ^ duration after the end of the charge price

 Yi rank factor of high quality berth with grade i

 c Total parking cost when parking users choose premium berths

 P Parking fee paid by parking users when selecting premium berths

 The travel time required for the parking user to travel from the entrance of the parking area to the quality berth. The required walking time between the parking user and the high quality berth and the destination. c The total parking cost when the parking user selects the ordinary berth.

 P' Parking fee paid by parking users when choosing a normal berth

 The travel time required for the parking user to travel from the entrance of the parking area to the normal berth t' The walking time required for the parking user to walk between the ordinary berth and the destination tr The real-time detection interval of the quality berth

 Qr The actual number of vehicles parked at high quality berths

 Real-time occupancy of Or premium berths

 Qp The predicted value of the number of vehicles with parking demand from the beginning of the pricing period to the detection time.

Long (1) unit when charging t _Q: refers parked in the quality berth vehicle at the end of free parking duration ^, each full of parked a t _Q long, its parking fee will increase once part of the increase is the recent i _Q period Pricing.

 (2) Price sensitivity coefficient μ: Reflects the degree of change of the parking user's choice of berth caused by the change of the premium berth parking price. The smaller the change of the parking user's choice, the larger the μ value.

(3) Parking duration control threshold t _{m :} refers to the maximum length of time that the parking manager wants to park the premium berth to the vehicle.

That is, the manager wants all vehicles with a parking time less than or equal to t _m to park to a high quality berth, and the parking time is longer than t„^ The vehicle goes to the ordinary berth to stop.

(4) Parking demand statistics table: A table for calculating the parking time control threshold t _m by grouping the vehicles with parking demand in the parking area and the required parking time and space resources according to the parking time. (5) Parking time and space resources: The product of the number of parking spaces occupied by parking vehicles and their parking time, in units of one hour.

 (6) The price increase variance of high quality berths Δρ: the quality berth η unit billing time t. The price is higher than the price of the (η-1) unit billing period.

 (7) Grade factor of high quality berths It is used to characterize the difference between high quality berths of different grades due to differences in position and size. The better the condition of high quality berth, the larger the value of grade factor.

 (8) High quality berth charging matrix: A matrix used to indicate the price of premium berths at different times and levels.

 (9) Time interval for real-time detection of high-quality berths means that the system automatically detects and collects real-time data of high-quality berths every 0 hours during the pricing period, and compares them with predicted or target values. DRAWINGS

1 is a flow chart showing the implementation of the prior art 1.

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

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

Figure 4 is a comparison of the existing situation and the optimization situation.

Figure 5 is an example of a parking area geometry information table.

Figure 6 is a graph of the change in charging for different unit billing durations t _Q .

Figure 7 is a flow chart of the calculation of the parking time control threshold t„^.

Figure 8 is a flow chart for calculating the premium parking price for premium parking spaces.

Figure 9 is a possible classification of multiple high quality berths in a parking lot and the setting of its classification factor.

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

Figure 11 is a comparison of the premium berth fee P with the ordinary berth charge P'.

Figure 12 is a flow chart of the implementation of the high quality berth dynamic pricing method with priority short stop.

Figure 13 is a schematic view of a parking area in the embodiment.

Figure 14 is an internal plan view of the parking lot where the premium berth is located in the embodiment. detailed description

Specific embodiment 1

In this embodiment, a possible implementation manner of the above invention is provided. The overview of the parking area in this example is shown in FIG. 13 . There are two entrances E1 and E2 in the area, and the on-street parking space PI is a high-quality parking resource, and there are 100 Parking spaces; off-street parking lot P' is a general parking resource, and the charging study time is from 07:00 to 24:00 on a certain day. The user can reserve the premium berth in the parking area in advance through the relevant mobile terminal application APP. At the time of the reservation, the APP will inform the user of the premium price of the premium berth, and finally charge the user who made the reservation according to the price. The premium berth dynamic pricing method with priority short stop is used to price the premium parking spaces in the parking area for APP reservation users. The implementation process is as follows:

 Through the field measurement, the geometric information table of the parking area is established as follows:

 Parking area entrance Each car entrance and high quality berth between the car entrance and the ordinary berth

 Car travel distance ( km ) car travel distance ( km )

E1 0.5 1.2 E2 2 1.2 Walking distance between high quality berth and ordinary berth Ad ( km ) 1.4

 Set the unit billing time to 10 minutes, and the part that stops for less than 10 minutes will be charged for 10 minutes.

 According to the field sample survey, 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 per person in the parking area is 25 yuan/hour; The average speed of vehicles in the parking area is 10km/h, and the per capita walking speed is 5km/h.

 From the high-quality berth parking lot P and the intelligent berth data at the ordinary berth parking lot P', the historical experience value of the number of parking vehicles in the parking area is 500, and the parking time distribution is known. At the same time, the parking area is known to be in this day. An event is scheduled to be held. The number of participants is expected to be 300, and the event time is from 9:00 to 11:00. The proportion of people who participated in the event before driving was about 20%.

 Because it is the premium berth parking pricing for APP reservation users, follow the method in step (3) a) to predict the number of vehicles with parking demand in the parking area during the day.

 Number of vehicles with parking demand in the parking area Q

 = historical experience value of parking vehicle arrival rate

 +Number of participants in temporary parking activities in the parking area X Sharing ratio of car travel = 500 + 300x20% = 560 vehicles

The number of vehicles Q that have parking demand in the area is grouped according to their parking time t, and the parking demand statistics table is as follows: Average parking time of parking time q _Qi required parking resources to accumulate parking space resources required

 Number of cars

(10min) (vehicle / lOmin) (one 'hours' ∑s _; (one hour)

 1 10 0.1 190 0.0198 0.0198

 2 1 1 0.1310 0.0437 0.0635

 3 14 0.1667 0.0833 0.1468

 4 5 0.0595 0.0397 0.1865

 5 9 0.1071 0.0893 0.2758

 6 9 0.1071 0.1071 0.3829

 7 9 0.1071 0.1250 0.5079

 8 1 1 0.1310 0.1746 0.6825

 9 13 0.1548 0.2321 0.9147

 10 12 0.1429 0.2381 1.1528

 1 1 13 0.1548 0.2837 1.4365

 12 9 0.1071 0.2143 1.6508

 13 7 0.0833 0.1806 1.8313

 14 1 1 0.1310 0.3056 2.1369

 15 8 0.0952 0.2381 2.3750

 16 15 0.1786 0.4762 2.8512

 17 13 0.1548 0.4385 3.2897

 18 1 1 0.1310 0.3929 3.6825

 19 5 0.0595 0.1885 3.8710

 20 10 0.1 190 0.3968 4.2679

 21 12 0.1429 0.5000 4.7679

22 8 0.0952 0.3492 5.1 171

 η

Z.OT8SO/9lOZai/X3d 66 10 0.1 190 1.3095 29.5655

 67 4 0.0476 0.5317 30.0972

 68 7 0.0833 0.9444 31.0417

 69 5 0.0595 0.6845 31.7262

 70 3 0.0357 0.4167 32.1429

 71 4 0.0476 0.5635 32.7063

 72 6 0.0714 0.8571 33.5635

 73 2 0.0238 0.2897 33.8532

 74 3 0.0357 0.4405 34.2937

 75 5 0.0595 0.7440 35.0377

 76 4 0.0476 0.6032 35.6409

 77 1 0.01 19 0.1528 35.7937

 78 1 0.01 19 0.1548 35.9484

 79 1 0.01 19 0.1567 36.1052

 80 2 0.0238 0.3175 36.4226

 81 3 0.0357 0.4821 36.9048

 82 1 0.01 19 0.1627 37.0675

 83 2 0.0238 0.3294 37.3968

84 0 0.0000 0.0000 37.3968 At the same time, because the number of high quality berths is s=100, the parking space and time resources it can provide S _p = 0.85xsxt ₀ =

0.85X100X = 14.1667. Hours). By comparing with the accumulated parking space and time resources ∑Si of each group in the parking demand statistics table, it is found that in the 42nd group data, that is, when the parking time is ti = 42 xl0 = 420min, the accumulated parking space and time resources are required. Si = 13.7698 hours, which is the closest group that does not exceed S _p = 14.1667 - hour. Therefore, the parking time control threshold of the parking area is determined to be 1 ₎ „ = 420^^ _? 1.

It is known that the parking fee for the ordinary berth in the parking area is 5 yuan/h, and the portion for less than 1 hour is calculated as 1 hour. When the parking time is the parking time control threshold t _m = 420min, the parking fee for parking in the off-street parking lot is '=7hx5 yuan/h=35 yuan. The weighted average of the quality berths and the distance between the lanes of the parking lot in the parking area d = ∑^ ₌₁ β _η ■ d _n =

■ 0.5 + -^- χ2 = 1 km ;

400+200 400+200 The weighted average d^ Z!^/ d!^ ^ x + ^ x : km of the distance between the ordinary berth and the parking lot entrance of the parking area. According to the formula " ), the parking charge for parking the vehicle at the high quality berth when the parking time is t _m is calculated:

 Id' - d M (1.2 - 1 1.4\ ―

 P, = P/ + α + 2 = 35 + 25Χ + 2x— = 49.5兀

v _d v _w ) \ 10 5 /

The free parking time for setting high quality berths is ^ = 30min, that is, there is no charge when parking in the road is no more than 30min. Then, when the parking duration is the parking duration control threshold t _m = 420 min, the number of unit billing durations t _Q = lOmin included therein is N = ^ = 1^2 = 39.

t ₀ 10

At the same time, according to the cost pricing method, the lower limit of the on-street parking space at P1 is 2 yuan/h, that is, during the free parking time. After t ₀ = 30min, the first unit billing time of the on-street parking space is t _Q = lOmin, the charge is _Pl = 0.5 yuan.

Therefore, according to (4), _{Δρ =} 3⁄4^2 = ^ ^2 _{= 0} . ₀₄₀ yuan. Therefore, the parking fee for the P1 premium berth is free for the first 30 minutes, and the first lOmin fee is 0.5 yuan. After that, the price per lOmin is 0.040 yuan higher than the previous lOmin, that is, the second lOmin charge is 0.540 yuan. The lOmin charge is 0.580 yuan, the fourth lOmin charge is 0.620 yuan... and so on, as shown in the following table:

 At the same time, in order to encourage parking users to make reservations for high-quality berths through APP, the final parking charge for users who come to high-quality berth parking after APP reservations is calculated at 90% of the above calculated price, that is, 10% discount. On the day of parking, if the price of the premium berth is adjusted in real time, the fee for the reserved user does not change, and it is still executed according to the charging standard notified by the system at the time of the reservation. Specific embodiment 2

In this embodiment, a possible implementation manner of the above invention is provided. Also in the parking area described in the first embodiment, it is now known that the number of high quality berths reserved by the APP is used for the quality berth in the parking area. The same day applies to the parking fee standard for unreserved vehicles, and is dynamically adjusted according to the actual parking situation. The implementation process is as follows:

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

 2. Set the unit billing duration to 10 minutes, and the parking period of less than 10 minutes will be charged for 10 minutes.

 3. According to the field sampling survey, 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 per-person travel time value in the parking area is 25 yuan/hour. The average speed of vehicles in the parking area is 10km/h, and the per capita walking speed is 5km/h.

 It is known that in the relevant mobile terminal APP, the number of high-quality berths in the parking area is 60, and the number of parking users who use the APP to reserve high-quality parking spaces here accounts for about the parking users here. 10% of the total number of people, the length of their parking is filled in at the time of booking; the historical experience value of the number of parking vehicles in the parking area is 500 by the intelligent gate data at the parking lot P, and the parking length is known. It is known that there will be an event on this day in the parking area. It is expected that the number of participants will be 300, and the event time will be from 9:00 to 11:00. The proportion of people who participate in the event is about 20%.

 Follow the method in step (3) b) predict the number of vehicles with parking demand in the parking area during the day.

 Number of vehicles with parking demand in the parking area Q

 = Number of reserved berths in ΑΡΡ

 + historical experience value of parking vehicle arrival rate

 x(l - 比例 the ratio of reserved users to all users)

 +Number of participants in temporary parking activities in the parking area X Sharing ratio of car travel = 60 + 500x (l - 10%) + 300x20% = 570 (units)

4. The number of vehicles with parking demand in the area is grouped according to their parking time t, and the parking demand statistics table is as follows: Average parking time of parking time q _Qi required parking resources to accumulate parking space resources required

 Number of cars

(10min) (vehicle / lOmin) (one 'hours' ∑s _; (one hour)

1 7 0.0833 0.0139 0.0139

 LI

Z.OT8SO/9lOZai/X3d

At the same time, because the number of high quality berths is s=100, the parking space and time resources that it can provide are S _p = 0.85 xsxt ₀ =

0.85X 100X = 14.1667. Hours). By comparing the accumulated required parking space and time resources ∑Si in the parking demand statistics table, it is found that in the 41st group of data, that is, when the parking time is ti = 41 x l0 = 410 min, it accumulates the required parking space and time resources. ∑ Si = 14.0357 hours, which is the group closest to and not exceeding S _p = 14.1667 - hour. Therefore, the parking time control threshold of the parking area is determined to be 1 ₎ „ = 410^^ _? 1.

It is known that the parking fee for the ordinary berth in the parking area is 5 yuan/h, and the portion for less than 1 hour is calculated as 1 hour. When the parking time is the parking time control threshold t _m = 410min, the parking fee for parking in the off-street parking lot is '=7h x5 yuan/h=35 yuan. The weighted average of the quality berths and the distance between the lanes of the parking lot in the parking area d = ∑^ ₌₁ β _η ■ d _n =

■X0.5 + - _T ^ _rr x2 = 1 km ;

 400+200 400+200 equal weighting of the common berth and the distance between the parking lanes of the parking areas

For a length of t _m , parking fees for vehicles parked at high quality berths:

= 49.5 yuan

The free parking time for setting high quality berths is ^ = 30min, that is, there is no charge when parking in the road is no more than 30min. Then, when the parking duration is the parking duration control threshold t _m = 410 min, the number of unit billing durations t _Q = Wmin included therein is 1^ ₌ ^ = 112^ _{= 38} .

 To 10

At the same time, according to the cost pricing method, the price limit of the on-street parking space at P1 is 2 yuan/h, that is, the charge for the first unit billing time t _Q = lOmin after the end of the free parking time t ₀ = 30min. _Pl = 0.5 yuan.

Therefore, according to (4), ₌ 3⁄43⁄42 ₌ 3⁄4 ^ _{= 0. 043} yuan. Therefore, the P1 premium berth is applicable to unreserved users. The parking charge price is free for the first 30 minutes, and the first lOmin charge is 0.5 yuan. After that, each lOmin charge price is 0.043 yuan higher than the previous lOmin, that is, the second lOmin. The charge is 0.543 yuan, the third lOmin charge is 0.586 yuan, the fourth lOmin charge is 0.629 yuan... and so on, as shown in the following table:

Set the system real-time detection interval length = 1/ι, that is, every 1 hour, the actual number of vehicles parking at the high-quality berth and the real-time occupancy rate of the high-quality berth at this time are automatically detected by the intelligent gate and video parking detector. And reported to the system, compared with the forecast data and target values. Now take the test result of this time at 09:00 as an example to explain the comparison process.

 The system detects the data from the gate detection at 09:00 in the morning. During the period from 07:00 to 09:00, the total number of actual vehicles parked at the high quality berth is = 120, and the video parking detector at 09:00 The test data shows that there are a total of 79 high quality berths at this time, that is, the real-time occupancy rate of high quality berths at this time is 0.79.

From the quality berth from 07:00 to the end of 09:00, forecast demand Q _P = _ρχ | | Μ ^ = _560x I. = ₈₀ , then ₁₂₀ 〉 _1Λ5χ80 = ₉₂ , ie ο.85ρ _ρ ≤ ≤ ι.ΐ5ρ _ρ is not satisfied. Therefore, it is necessary to re-predict the number Q of vehicles having parking demand in the parking area for the remaining time of the day, that is, repeat steps (3) to (5), recalculate the premium price of the premium berth according to the new parameters, and issue the updated parking. Charged price. For non-reserved users who come to the high quality berth from 09:00 to the next update, the parking charges will be charged according to the updated charging standard. However, the parking price of the parking users who have entered the market is still subject to the charging standards announced at the time of entry; the subscribers are still charged according to the charging standard notified in the APP at the time of their appointment. Embodiment 3

 In the present embodiment, a possible embodiment of the above invention is provided, and the parking area and known conditions are as described in the second embodiment. Further, the high quality berths in the high quality berth parking lot P are graded according to the location, size and other conditions, and differentiated pricing is implemented for different grades of high quality berths. 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. The changes in the price and the parking time with the high quality berth under the non-grading condition are as follows:

The quality berths are now graded. The interior of the parking lot P where the premium berth is located is shown in Figure 14. The berth of the sign 1 in the figure is a first-class high-quality berth located close to the entrance and exit, the elevator or the paying machine and larger than the remaining berths. The berth of the sign 2 is the same size as the majority berth but close to the entrance and exit, the elevator or the paying machine. High quality berths, unmarked berths are three quality berths. The grade factor of different grades of premium berths! ^Set as shown in Figure 9. According to the grade factor and the high-quality berth charge price calculated in the second embodiment, the parking charge matrix of the high-quality berth in the parking area can be obtained as follows:

In the real-time detection of the actual number of vehicles parked at high quality berths and the real-time occupancy rate of high quality berths on the same day, both indicators met 0.85ρ _ρ < Q _r < 1.15ρ _ρ and 0.7 < O _r < 0.9 . Therefore, the charging standard for high-quality berths for unsubscribed users on the same day has been executed at the above prices, and no changes have been made.

Claims

Claim

1. A high-quality berth dynamic pricing method with priority short stop, the steps of which include:

 1) Establish a parking area geometry information table;

 2) Determine the unit billing duration ί. ;

 3) Determine the parking feature data in the parking area;

4) Determine the parking duration control threshold t _m ;

 5) Determine the price of premium berth parking fees;

 6) Determine the real-time detection interval duration ^, and perform real-time statistics and detection on the actual number of vehicles parked at the high quality berth and the real-time occupancy rate c of the high quality berth every ^ duration;

 7) Compare the real-time detection data with the forecast data to determine the premium berth parking charge price for the subsequent period.

2. The high-quality berth dynamic pricing method for priority short stop according to claim 1, wherein the parking area geometric information table comprises the following data: a number of vehicle entrances in the parking area, and a parking area in each parking area. The distance between the entrance and the quality berth is d„, the distance between the parking area of the parking area and the ordinary berth, and the walking distance between the high quality berth and the ordinary berth. These data are obtained by field measurement.

3. The method of claim 1, wherein the unit charging duration i _{Q is} equal to 1 minute ≤ i _Q ≤ 20 minutes.

The high-quality berth dynamic pricing method for priority short stop according to claim 1, wherein the parking area parking characteristic data includes a number Q of vehicles having parking demand in the parking area, and a parking demand The average speed of the vehicle in the parking area, the average walking speed I7 _W in the parking area, and the price sensitivity coefficient μ of the parking user in the parking area.

5. The high quality berth dynamic pricing method for priority short stop according to claim 4, wherein: the vehicle speed in the parking area, the average walking speed of the parking user in the parking area, and the price of the parking user in the parking area. The sensitivity coefficient μ is obtained by field sampling survey in the parking area.

6. The high quality berth dynamic pricing method for priority short stop according to claim 4, wherein at least two of the following four related data are obtained first:

Q) The number of parking vehicles in the parking area at the same time (historical experience value of the work and parking time): refers to the data stored by the intelligent parking facilities or manual recording, respectively, the high quality berth and the ordinary berth at the same time parking Number of vehicles, summing the two to obtain the number of parking vehicles in the parking area; simultaneously recording the parking time of each vehicle; randomly extracting the recorded values of multiple days and taking an average value, that is, the number of parking vehicles in the parking area The empirical value of the experience value and the length of the parking period; in particular, when the historical data is extracted and counted, the selected three periods of the work period, the weekend, and the special holiday should be separately counted; b The real-time traffic flow of the surrounding roads ρ _π : refers to the traffic management department or related professional third party, surrounded by Real-time traffic flow data of the road network around the parking area; c) berth reservation data ρ _ω , t _ra on the mobile terminal App means that the premium berth in the parking area is reserved on the relevant mobile terminal application APP Quantity and time period; d) The estimated parking demand for temporary activities in the known parking area ρ„, t _w : refers to the number of participants in the temporary activities that will occur in the parking area and the time of the event, induced The parking duration of the parking demand is the same as the duration of the event. Using the acquired data, the number of vehicles Q with parking demand in the parking area and the parking time of the vehicle with parking demand are calculated in one of the following three ways: The number of vehicles with parking demand in the parking area Q =

At the same time, the historical experience value of the number of parking vehicles in the parking area is Q! + Number of participants in temporary parking activities in the parking area ρ _w X Sharing ratio of car trips; where the sharing ratio of car trips is greater than 0.1 and less than 0.3, obtained by field sampling survey; parking time in parking area is t by parking The historical experience value of the duration and the parking time distribution of the parking demand induced by the temporary activity in the parking area are superimposed; ii) the number of vehicles with parking demand in the parking area Q =

The number of reserved parking spaces in the APP Q _m + the historical experience value of the number of parking vehicles in the parking area at the same time Q z X —

The ratio of APP reservation users to all parking users) + The number of participants in temporary parking activities in the parking area Q _w X The sharing ratio of car travel; The ratio of APP reservation users to all users is obtained through sample survey, the contribution ratio of car travel values greater than 0.1 less than 0.3, obtained by the field sampling; length ί _m and a parking area parking duration t a long parking historical experience and from the historical data, the APP reservation data is determined when the parking in the parking area of the parking demand The length of the parking period for the temporary parking activity induced by the temporary activity ^ three superimposed;

Iii) the number of vehicles with parking demand in the parking area Q = real-time traffic flow of surrounding roads ρ _π历史 historical experience value of the number of parking vehicles in the parking area at the same time

 Total demand of parking time t distribution and parking time history data experience Historical average of real-time traffic flow of surrounding roads

The distribution of values t _{T is} consistent.

7. The high quality berth dynamic pricing method of priority short stop according to claim 6, wherein when determining the premium berth price provided to the reserved user, the method i) as claimed in claim 6 should be used; Carry out high quality berth prices When dynamically adjusting, the method ii) or method iii) as claimed in claim 6 should be used; the price adjusted in real time is only applicable to non-reserved users entering the berth after the price is released, and the parking user who has made the reservation is charged. The price is still executed in accordance with the charging standard that was notified at the time of the appointment.

8. The high-quality berth dynamic pricing method for priority short stop according to claim 1, wherein said parking time control threshold value 1 ₎ is determined according to the following steps:

(1) The number of vehicles Q having a parking demand in the parking area determined by one of the methods i), ii), iii) of claim 6, and the parking time t of the vehicle having the parking demand, the parking The total number of vehicles with parking demand in the area is counted according to the parking time t of the vehicles with parking demand. The group distance is the unit charging time t _Q , and the parking time of the i-th data is ti = ixt _Q , and the number of vehicles is _The range of _qi and i is i = 1, 2, 3 T/t ₀ , where T is the total pricing duration;

(2) the number of vehicles _qi group i, the calculated average length _Q reaches the amount of each vehicle group i t q _Qi = ^;

(3) Calculate the number of parking space-time resources required for the i-th group of vehicles from the i-group vehicle's average arrival amount q _Qi per t ₀ duration and the parking duration of the i-th group vehicle = q _oi Xt _{i ;}

(4) The amount of parking space and time resources required by each group of vehicles Si, S ₂ S _{i ;} Calculate the number of parking space and space resources required for the accumulation of vehicles in the former group i Si = Si + S ₂ +

(5) Calculate the parking space and time resources that can be provided by the number of berths of high quality berths 5 _!? = 0.85xsxt ₀ ;

(6) Compare ∑S _{1 ;} ∑S ₂ ∑Si with the parking space and time resources 5 _!? provided by the high quality berth, and find an i' so that ∑S is closest but not exceeding S _p The parking time corresponding to the i' is the parking time control threshold t _m .

9. The high quality berth dynamic pricing method for priority short stop according to claim 1, wherein the premium berth parking fee price is determined according to the following steps:

(α) From the known ordinary berth parking charge policy, calculate the parking charge price P _t ' of the ordinary berth when the parking time is the parking time control threshold t _m ;

(b) Set the free parking time for quality berths t _{/ ;}

(c) Determine the first t after the end of the free parking time t _f for the premium berth by cost pricing. The price of the price within the length of time pi;

(d) When the parking time is t _m , the parking charge price P _t ' of the ordinary berth and the data in the parking area geometric information table are calculated according to formula (1). When the parking time is t _m , the car quality berth Parking charge P _t:

Where d' is calculated using equation ( ² ) and d is calculated using equation ( ³ ): d' =∑^ ₌₁ β _η - ά _η ' (2)

ά =∑^ ₌₁ β _η - ά _η ( 3) where the meaning of each symbol is as shown in the table in the manual; by the parking time when the parking time is 1 ₎ „ when the vehicle is parked at the high quality berth, according to the formula (4) Calculate the price increase variance Δρ of the high quality berth:

 = 2(^) (4) where N = " , the meaning of each symbol is as shown in the table in the manual;

(f) The first t after the end of the free parking time t _f by the premium berth. The time-to-price price ₁ and the price increase variance Δρ of the high-quality berth are calculated according to formula (5) to obtain the high-quality berth free parking time ^ the ηth t after the end. Duration of the price

Vn -

10. The high-quality berth dynamic pricing method for priority short-stop according to claim 1, wherein the high-quality berth parking charge price is multiplied by the calculated parking charge price by the parking user in the parking area. The price sensitivity coefficient μ, which should satisfy 1 < μ ≤ 1.5.

11. The high-quality berth dynamic pricing method for priority short-stop according to claim 1, wherein the premium berth parking fee is discounted to a parking user who has reserved in advance.

12. The high-quality berth dynamic pricing method for priority short stop according to claim 1, wherein the high-quality berth parking charge is based on the location, facilities, size, etc. of different high-quality berths when the number of high-quality berths is large. Differences in conditions, grading of high quality berths; by multiplying the calculated parking charge price by different high quality berth grade coefficients, a high quality berth charging matrix is obtained.

13. The method of claim 1, wherein the actual number of vehicles parked at the high quality berth and the real-time occupancy rate of the high quality berth are smart gates and video parking spaces. Real-time information gathered by at least one of the detector, infrared parking detector, microwave parking detector or geomagnetic coil, which is collected once every time; the actual number of vehicles parked at the high quality berth ρ ^ refers to the actual number of vehicles parked at the high quality berth from the beginning of the pricing period to the current moment of real-time detection; the real-time occupancy rate of the high quality berth refers to the ratio of the number of high quality berths occupied at the current time to the total number of premium berths. .

14. The high-quality berth dynamic pricing method for priority short-stop according to claim 1, wherein the comparing the real-time detection data with the predicted data to determine the quality berth parking fee price for the subsequent period is: 0.85Q _p ≤ Q _r ≤ 1.15ρ _ρ and 0.7 ≤ O _r ≤ 0.9 , where the predicted demand from the start of the pricing period to the current time

_{QP = the} duration of _QX from the pricing _; if this criterion is met, the original charging plan will remain unchanged; if not, the steps (3) to (5) described in claim 1 will be re-executed, and the relevant parameters will be updated. , develop and publish new charging plans.