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WO2018122812A1 - Procédé de classement et de tarification dynamique de places de stationnement, dans lequel priorité est donnée à un stationnement à court terme - Google Patents

Procédé de classement et de tarification dynamique de places de stationnement, dans lequel priorité est donnée à un stationnement à court terme Download PDF

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Publication number
WO2018122812A1
WO2018122812A1 PCT/IB2017/058542 IB2017058542W WO2018122812A1 WO 2018122812 A1 WO2018122812 A1 WO 2018122812A1 IB 2017058542 W IB2017058542 W IB 2017058542W WO 2018122812 A1 WO2018122812 A1 WO 2018122812A1
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WO
WIPO (PCT)
Prior art keywords
parking
berth
time
vehicles
area
Prior art date
Application number
PCT/IB2017/058542
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English (en)
Chinese (zh)
Inventor
杜豫川
王晨薇
蒋盛川
Original Assignee
同济大学
许军
杜豫川
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 同济大学, 许军, 杜豫川 filed Critical 同济大学
Priority to CN201780036524.8A priority Critical patent/CN109416879B/zh
Priority to GBGB1909412.7A priority patent/GB201909412D0/en
Publication of WO2018122812A1 publication Critical patent/WO2018122812A1/fr

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Classifications

    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
    • G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
    • G07B15/02—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points taking into account a variable factor such as distance or time, e.g. for passenger transport, parking systems or car rental systems
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas

Definitions

  • the invention relates to a berth hierarchical dynamic pricing method with priority short stop.
  • the driver prefers to choose a high-quality berth with convenient location and safe parking. He is not willing to be remote or park a difficult berth. Therefore, a large number of vehicles will cruise for high-quality berth resources, resulting in emissions. increase.
  • the prioritized short-stop berth grading dynamic pricing method proposed by the invention can realize the management and guidance of parking demand by time and space differential pricing of different parking resources.
  • the present invention considers the number of berths, the characteristics of the parking parking demand, the occupancy rate of the parking space, etc., and by means of incremental progressive charging, finely sets the charging price of the premium berth and dynamically adjusts according to the actual situation, so as to achieve limited
  • the high-quality berths are preferentially provided for the purpose of providing 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 times.
  • 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 the flow chart for 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.
  • 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, thereby reducing the occupancy rate of the parking space to Set below the 85% threshold.
  • 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.
  • Figure 3 shows the division of berth categories using this method in a parking lot.
  • the mark L is the "large size berth”
  • the mark S is the "safe berth”
  • the unmarked is the ordinary parking space.
  • the following table shows the classification of berths and pricing rules in one implementation of this method.
  • a Chinese patent application, CNid 00000063094751 discloses a method of regulating a parking guidance system that considers parking time.
  • the inductive system described in the method displays the parking condition of the area in the form of a road network diagram, and the inducing screen includes the berth information and the driving route of each parking lot in the area, and dynamically displays the road traffic condition of the road network and the parking lot of each parking lot.
  • Information on the difficulty level of parking This difficulty level information is given by different color identifications depending on the parking time range.
  • the control method of the parking guidance system is to calculate the parking time required by the driver in different parking lots in the current location selection area according to the parking time and select an appropriate manner for release, and the parking time of the parking lot considers the road section reaching the parking lot.
  • the driver's induction is determined only according to the current parking occupancy rate of different parking lots.
  • the convenience of parking resources is not distinguished, and the quality parking resources are not fully utilized.
  • Prior Art 4 A Chinese patent application, CN201510448131, discloses a parking dynamic pricing method based on demand characteristics and parking lot utilization.
  • a parking dynamic pricing method based on demand characteristics and parking lot utilization.
  • RP survey through the mobile APP to construct the parking lot probability equation of the parking lot or the parking lot area, to establish the relationship between parking utilization and parking lot attributes (including price), and then combined with the detector
  • the regional parking flow data can optimize the parking lot utilization rate of the parking lot by adjusting the parking price of the parking lot, and reach the previously set target, thereby realizing the reasonable dynamic pricing of the parking lot.
  • the prices of all berths within a particular parking lot are the same, ie, the convenience of different berths inside the parking lot is not differentiated.
  • a Chinese patent application, CNid00000071874281 discloses an intelligent parking space parking mechanism algorithm based on an optimal berth model.
  • the method includes the determination of the optimal berth model of the parking lot, the drawing of the weight map of the road network and the design and programming of the parking space induction algorithm.
  • the optimal berth is determined according to the driving distance of the vehicle entering the parking space, the walking distance from the parking lot and the personal safety.
  • a mathematical model is established with the shortest path method in which the sum of the three distances is the shortest, and the optimal berth is thus determined.
  • the parking lot road network can be abstracted into the weighted graph solution in the graph theory, so that the optimal berth problem can be solved.
  • the problem is calculated by converting to the shortest distance on the weighted graph.
  • the improved floyd algorithm with better performance is used, and finally verified by Matlab simulation. This method distinguishes different berths in the parking lot and determines the optimal berth, but only uses the algorithm for parking induction, does not involve parking pricing, and does not regulate parking demand through differentiated pricing.
  • 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 normal parking space with a far distance, and the walking distance to the final destination is 5 minutes.
  • two drivers, A and B need to stop at the same time and arrive at this destination.
  • the parking time of A is 6 hours
  • the parking time of B is 2 hours
  • the driver C is 2 hours later.
  • the driver D also needs to stop and arrive at the same destination.
  • the parking time is also 2 hours.
  • 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.
  • 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.
  • C will leave, 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.
  • the idea of the present invention is adopted to prioritize the high quality berth to meet the short stop vehicle, the situation will become:
  • short stop vehicles vehicles with short parking periods
  • 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 high quality berth is the problem to be solved by the present invention.
  • the invention provides a method for prioritizing short-stay berth grading dynamic pricing based on the berth number limitation and the parking demand feature distribution, which can obtain the parking behavior characteristics in the area, calculate the parking time control threshold and the charging standard, and realize the induced transfer long stop. Vehicles to ordinary berths, and can dynamically adjust prices according to actual demand status. Achieve the goal of improving the utilization of high quality berths and reducing the total cruise time and walking time of the system.
  • the invention specifically includes the following steps: (1) Establish a berth information table.
  • the established berth information is shown in the following table.
  • the statistical item is deleted in the berth information table; when the camera system for monitoring is not installed in the parking area under consideration, the berth information table is Delete the statistic.
  • ⁇ indicates the average distance of the berth from the entrances and exits of each parking lot in the parking area; indicates the average of the average vehicular distances of all berths in the parking area from the entrances and exits of the parking areas;
  • d w indicates the walking distance of the berth from the nearest elevator in the parking area
  • ⁇ indicates the distance of the berth from the nearest self-service payment machine
  • ⁇ indicates the average distance of all berths in the parking area from the nearest self-service payment machine
  • f) Calculate the gradation coefficient ⁇ of the berth, Equation (5) for calculation:
  • ⁇ represents the rank coefficient of the berth, and the larger the ⁇ , the better the comprehensive condition indicating the berth;
  • ⁇ characterizes the minimum standard for the set of high quality berth conditions, with a range of 12 .
  • the ⁇ can be set by the parking facility operator, and can take values of 1, 1.2, 1.25, 1.4, 1.5, 1.75; the rest of the symbols have the same meaning as before.
  • g) Determine the number s of premium berths.
  • the berth convenience line c e , pedestrian convenience c w , payment convenience C / , berth size convenience and safety degree ⁇ one of the five items is greater than or equal to 1.5, or the berth grade coefficient ⁇ is greater than
  • the berth is a high quality berth and the remaining berths are ordinary berths.
  • the calculation results of all berths in the parking area are counted, and the number s of high quality berths in the parking area is obtained.
  • the unit billing time length t Q can be any length of time longer than the required price period, if The parking charge policy within 3 hours should be met for ⁇ ⁇ 3 hours.
  • the portion of the parking duration that is less than one t Q is calculated by pressing a ⁇ during billing.
  • the values proposed in the method should satisfy 1 minute ⁇ to ⁇ 20 minutes. This is because the larger the to, the more obvious the step-by-step mutation of the parking charge with the increase of the parking time, and the user whose time is near the sudden change threshold is more sensitive to the change of the charge, thereby increasing the user's time anxiety and reducing the parking user's Satisfaction with parking services.
  • the parking fee is 2 hours. Changes in internal growth over time.
  • the selected date is divided into three categories: the working day, the weekend, and the special holiday.
  • Real-time traffic flow Q n of 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.
  • berth reservation data ⁇ ⁇ , t m on the mobile terminal APP. Refers to users with parking needs in advance through relevant mobile terminal applications
  • the APP makes an appointment for the premium berth in the parking area, and informs the time period of the required parking.
  • the number of premium berths reserved for the APP and the appointment period can be obtained in real time from the application background.
  • the induced parking demand for temporary activities in known parking areas is t ni . 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.
  • 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.
  • the price adjusted in real time is only applied to non-reserved users who enter the berth after the price is released.
  • the charging standard is still executed according to the charging standard notified at the time of the reservation.
  • Step (3) From the data obtained in step (3), group the total number of vehicles Q with parking demand in the parking area according to the parking time t, and the group distance is the unit charging time t Q .
  • T is the total pricing duration
  • b) by the i number of vehicle group, the i-th group of vehicles calculated average to the duration amount reaches q Qi ⁇ -; c) t to the average stop each to the length of the arrival quantity q Qi and the i-th group of the vehicle group i of the vehicle, is calculated
  • the amount of parking space and time resources required for the i-th vehicle i ⁇ Xt i ;
  • Step c) and step d) can be performed simultaneously.
  • n Pi + ( ⁇ - 1) ⁇ ⁇ ( 8 )
  • steps b), c), d) can be performed simultaneously
  • Figure 7 shows the flow chart for calculating the premium parking price.
  • the price sensitivity coefficient ⁇ can be set to take into account user loyalty and user coupon usage. Among them, user loyalty is measured by the user's repurchase rate, that is, the number of repeated parkings in a month. The higher the user loyalty, the less sensitive the price is, and the corresponding price sensitivity coefficient ⁇ is larger. The higher the user coupon usage rate, the more sensitive the user is to the price and the smaller the price sensitive factor ⁇ .
  • the parking charge price charging rule for a calculated premium berth can be represented by a charging matrix.
  • An example of a high quality berth charging matrix is as follows:
  • step (4) Compare the real-time detection data with the predicted data to determine the premium berth parking charge price for the subsequent period.
  • d w berth is the distance from the nearest elevator.
  • Historical experience value of parking time in parking area Historical experience value of number of parking vehicles in parking area Real-time traffic flow of surrounding road tIII Mobile terminal Parking time of reserved berth on APP
  • Qui Number of berth reservations on the mobile terminal APP Temporary parking in the parking area, the demand for parking, the parking time, the temporary parking activity in the parking area, the amount of parking demand ⁇ , the price sensitivity coefficient of the parking user in the parking area, tm, the parking time control threshold
  • the number of parking space-time resources required for the i-th vehicle in the Si parking demand statistics table The number of parking space-time resources required for the first group of vehicles in the parking demand statistics table s The number of parking space-time resources that the high-quality berth can provide
  • the parking time control threshold 1 ⁇ corresponds to the group
  • Parking Pt length equal to t m
  • the vehicle is parked in the general parking is required to pay parking fees parking duration equal to p t t m
  • the vehicle is parked in high-berth required to pay parking fees Free Parking quality long time tf berth
  • QP Predicted value of the number of vehicles with parking demand from the beginning of the pricing period to the detection time.
  • 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 a graph of the change in charging for different unit billing durations t Q .
  • Figure 6 is a flow chart for calculating the parking duration control threshold 1 ⁇ .
  • Figure 7 is a flow chart for calculating the premium berth parking charge price.
  • Figure 8 is a possible classification of multiple high quality berths in a parking lot.
  • Figure 9 is a flow chart of the implementation of the high-quality berth dynamic pricing method with priority short stop.
  • Figure 10 is a schematic view showing the distribution of parking spaces in the parking area of the embodiment.
  • the parking area parking map in this example is shown in FIG.
  • the fee study time is from 07:00 to 24:00 on a certain day.
  • the berth grading dynamic pricing method based on the priority short stop is used to dynamically priced the berth rating for the APP reservation users in the parking area.
  • the implementation process is as follows: Establish the parking area berth information table as follows: The berth is from the car line. The berth is the nearest berth.
  • the berth convenience line c e When the berth convenience line c e , pedestrian convenience c w , payment convenience C / , berth size convenience ⁇ and safety degree ⁇ one of the five items is greater than or equal to 1.5, or the berth grade coefficient ⁇ When it is greater than 1, the berth is a high quality berth and the remaining berths are ordinary berths.
  • the calculation results of all the berths in the parking area are counted, and the number of the high quality berths in the parking area is shown in the gray part of the above table.
  • the berth grade coefficient ⁇ 1.21, according to formula (5), when the parking time is t m , the parking fee of the vehicle parked at the high quality berth 02
  • the parking charge price for the premium berth numbered 02 is 1 yuan for the first 20min, and then the price for each 20min is 0.10 yuan higher than the previous 20min, which is the second lOmin charges 1.10 yuan, the third 20min charges 1.20 yuan, the fourth 20min charges 1.30 yuan... and so on, as shown in the following table:
  • the final parking charge for users who come to the premium berth parking after the advance reservation through the APP is calculated at 90% of the above calculated price, that is, enjoy a 10% discount.
  • 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.

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Business, Economics & Management (AREA)
  • Finance (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • Traffic Control Systems (AREA)

Abstract

L'invention concerne un procédé de classement et de tarification dynamique de places de stationnement, dans lequel priorité est donnée à un stationnement à court terme. Selon l'invention, des places de stationnement dans une zone de stationnement sont classées et des places de stationnement prioritaires dans la zone sont tarifées. Le procédé comprend les étapes consistant à : (1) établir une table d'informations de places de stationnement; (2) classer des places de stationnement, et déterminer un nombre de places de stationnement prioritaires; (3) déterminer une durée de mesure d'unité de tarification de stationnement; (4) déterminer un prix de tarification de stationnement de places de stationnement prioritaires, et ajuster ledit prix; (5) déterminer une durée d'intervalle de détection en temps réel, et exécuter un comptage et une détection en temps réel sur un nombre réel de véhicules stationnés sur les places de stationnement prioritaires et un taux d'occupation de places de stationnement prioritaires à chaque intervalle; (6) comparer des données de détection en temps réel et des données de prévision, et déterminer un prix de tarification de stationnement de places de stationnement prioritaires pour une période de temps suivante. Le procédé gère et oriente des demandes de stationnement en exécutant une tarification différenciée en termes de temps et d'espace pour différentes ressources de stationnement. Un moyen de mesure augmentant progressivement est utilisé pour définir des prix de tarification concernant des places de stationnement prioritaires d'une manière précise, et des ajustements dynamiques sont effectués selon des circonstances réelles, ce qui permet d'atteindre l'objectif de fournir de préférence des places de stationnement prioritaires limitées à des véhicules stationnant durant des périodes courtes.
PCT/IB2017/058542 2016-12-30 2017-12-30 Procédé de classement et de tarification dynamique de places de stationnement, dans lequel priorité est donnée à un stationnement à court terme WO2018122812A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201780036524.8A CN109416879B (zh) 2016-12-30 2017-12-30 一种优先短停的泊位分级动态定价方法
GBGB1909412.7A GB201909412D0 (en) 2016-12-30 2017-12-30 Comfort-based self-driving vehicle speed control method

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
PCT/IB2016/058107 WO2018122587A1 (fr) 2016-12-30 2016-12-30 Procédé de tarification dynamique pour des places de stationnement privilégiées ayant une priorité donnée au stationnement à court terme
IBPCT/IB2016/058107 2016-12-30

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WO2018122812A1 true WO2018122812A1 (fr) 2018-07-05

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PCT/IB2016/058107 WO2018122587A1 (fr) 2016-12-30 2016-12-30 Procédé de tarification dynamique pour des places de stationnement privilégiées ayant une priorité donnée au stationnement à court terme
PCT/IB2017/058542 WO2018122812A1 (fr) 2016-12-30 2017-12-30 Procédé de classement et de tarification dynamique de places de stationnement, dans lequel priorité est donnée à un stationnement à court terme
PCT/IB2017/058543 WO2018122813A1 (fr) 2016-12-30 2017-12-30 Procédé permettant la réservation de place de stationnement « premium » en accordant la priorité aux stationnements de courte durée et la fixation dynamique de tarifs

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CN (3) CN109661693B (fr)
GB (2) GB201711410D0 (fr)
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CN111785069B (zh) * 2020-07-01 2021-11-05 宁波工程学院 一种停车诱导方法、系统、智能终端和储存介质
JP7596768B2 (ja) * 2020-12-11 2024-12-10 トヨタ自動車株式会社 制御装置及び料金決定方法
CN112820134B (zh) * 2020-12-30 2022-08-23 深圳市前海亿车科技有限公司 一种局部区域预约停车的方法、系统及介质
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CN113554276B (zh) * 2021-06-25 2023-11-07 桂林电子科技大学 基于泊位供给可用性感知冲突规避泊位分配系统
CN113936347B (zh) * 2021-09-30 2023-12-19 深圳市科漫达智能管理科技有限公司 一种停车计费方法、停车计费装置以及终端设备
CN114360078A (zh) * 2021-12-31 2022-04-15 浙江树人学院（浙江树人大学） 一种基于车位物联系统的车位计费方法
CN115223389B (zh) * 2022-07-15 2023-11-21 西南交通大学 一种基于动态路段代价的停车引导路径规划方法
CN115798196B (zh) * 2022-11-02 2024-12-27 智慧互通科技股份有限公司 视频设备路侧泊车流量预测方法以及系统
CN117409492A (zh) * 2023-12-14 2024-01-16 杭州万物互联智慧产业有限公司 路内智慧停车无人化运营管理方法及系统

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