CN113380023B - Mixed land sharing parking demand prediction method based on berth selection behavior - Google Patents

Mixed land sharing parking demand prediction method based on berth selection behavior Download PDF

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CN113380023B
CN113380023B CN202110560705.9A CN202110560705A CN113380023B CN 113380023 B CN113380023 B CN 113380023B CN 202110560705 A CN202110560705 A CN 202110560705A CN 113380023 B CN113380023 B CN 113380023B
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周竹萍
梅亚岚
裘梦琪
刘博闻
唐旭
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Nanjing University of Science and Technology
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Abstract

The invention relates to a mixed land shared parking demand prediction method based on parking space selection behavior, which is characterized in that parking demands of all land types in mixed land are predicted, the parking demands are compared with parking capacity of the mixed land, and a part exceeding the parking capacity is defined as shared parking demand; establishing a generalized cost function according to the shared parking selection behavior of the parking persons, and selecting each shared parking lot by each parking demander with the minimum parking cost; and (4) counting the parking conditions before and after the selection of each parking demander to obtain the parking requirement conditions of all the places in the shared parking environment and the parking requirement transfer amount in the shared parking process. The invention provides a basis for the allocation, addition and arrangement of parking berths and a parking guidance scheme in a peak period aiming at the supersaturated parking demand.

Description

Mixed land sharing parking demand prediction method based on berth selection behavior
Technical Field
The invention relates to the technical field of static traffic and parking berth configuration, in particular to a mixed land shared parking demand prediction method based on berth selection behaviors.
Background
With the improvement of the level of motorization, the holding amount of motor vehicles continuously rises, parking resources cannot meet the existing parking requirements, and parking is gradually a difficult problem to be solved for traveling. In order to solve the problem of difficult parking, the existing stage mainly aims to build a parking lot and increase parking spaces, but the problem cannot be solved effectively for a long time, the existing parking resources are fully utilized, and the utilization rate of the parking spaces is improved.
Shared parking among parking lots with different land properties is a new idea to solve the problem of "difficulty in parking" because parking requirements can be complemented due to differences in parking characteristics among the parking lots with different land properties. Through a shared parking mode, supersaturated parking requirements are dispersed to peripheral idle parking positions, idle parking resources are used, and the parking position utilization rate is improved.
Some existing papers propose a related method for forecasting shared parking demand, for example, documents (xu xiao, ma jian xiao, parking space shared demand forecasting [ J ] based on behavior selection characteristics, logistics technology, 2019,42(07):27-32.) expand questionnaire survey on shared parking space selection behaviors, through analysis of survey data, shared parking space selection probabilities of three types of land parkers are obtained, and a parking generation rate method is corrected by using the selection probabilities, so that a shared parking demand forecasting result is obtained. The method is novel in the related research of sharing the prediction direction of the parking demand, but still has a plurality of problems:
(1) for parking people to share parking choices, the paper adopts a questionnaire survey mode, and due to the limitation of land types, the method needs to survey the parking choice behaviors of the parking people of each land type in the mixed land, the required data volume is large, and the post-processing is complex.
(2) For the shared parking demand prediction, the paper utilizes the parking selection probability shared by the parkers to correct the parking generation rate method, and the parking demands of various land types of mixed land under the shared parking environment are obtained. However, in an actual parking environment, the shared parking demand is often present in a case where the parking lot of the parking person destination has no empty parking space, and when the parking lot of the parking person destination has an empty parking space, the parking person normally parks the vehicle.
Disclosure of Invention
The invention aims to provide a mixed land shared parking demand prediction method based on parking space selection behaviors, so that parking demands of shared parking among different land properties can be predicted more accurately, parking spaces are configured reasonably, and the utilization rate of existing parking facilities is improved.
The technical solution for realizing the purpose of the invention is as follows: a mixed land sharing parking demand prediction method based on parking space selection behaviors comprises the following steps:
step 1, determining land use indexes of land types in mixed land and land types;
step 2, forecasting the parking demand of the single land by using a parking generation rate method, and calculating the parking demand of each land type in each time period;
step 3, comparing the parking demand of each land type in each time period with the parking capacity of the land to determine the shared parking demand;
step 4, establishing a generalized cost function according to the parking person shared parking space selection behavior;
step 5, calculating the parking cost of each shared parking demander for selecting peripheral idle parking positions, and selecting the parking position according to the minimum parking cost;
and 6, counting the selection conditions of the shared parking demanders to obtain the parking demand amount of each type of the shared parking and the shared parking demand transfer amount.
Further, in step 1, determining the land utilization indexes of the mixed land use type and the land use types, specifically:
the land types are divided into residential land, public management and public service land, commercial service facility land, industrial land, green land and square land, public facility land, road and traffic facility land and logistics storage land;
the residential land is divided into a first type residential land, a second type residential land and a third type residential land;
the public management and public service land is divided into administrative and office land, cultural facility land, education and scientific research land, sports land, medical and health land, social welfare facility land, cultural relics and ancient sites, field application land and religious facility land;
the commercial service industry facility land is divided into a commercial facility land, an entertainment and fitness facility land, a public facility business network land and other service facility land;
the industrial land is divided into a first-class industrial land, a second-class industrial land and a third-class industrial land;
the greenbelts and the square lands are divided into park greenbelts, protection greenbelts and square lands;
the public facility land is divided into a supply facility land, an environment facility land, a safety facility land and other public facility lands;
the land for the road and the traffic facilities is divided into urban road land, urban rail transit land, traffic junction land, traffic station land and other traffic facility land;
the logistics storage land is divided into a first-class logistics storage land, a second-class logistics storage land and a third-class logistics storage land.
Further, in step 2, the single land parking demand is predicted by using a parking generation rate method, and the parking demand of each land type in each time period is calculated, specifically:
calculating the parking demand of each land according to the mixed land type and the land utilization index and the parking generation rate model, wherein the calculation formula is as follows:
Figure BDA0003078851060000031
wherein,
Figure BDA0003078851060000032
the parking demand of the land i in the time period t; siThe land utilization index of the land utilization i is used;
Figure BDA0003078851060000033
is the parking generation rate of the land i in the time period t.
Further, in step 3, comparing the parking demand of each land type in each time period with the parking capacity of the land to determine the shared parking demand, specifically as follows:
when the parking demand is less than or equal to the land parking capacity, the parking demand is not shared; when the parking demand is larger than the land parking capacity, the shared parking demand exists, and the shared parking demand is a part exceeding the land parking capacity, and the calculation formula is as follows:
Figure BDA0003078851060000034
wherein, ViIn order to park a large capacity with the ground i,
Figure BDA0003078851060000035
sharing parking demand for land i in a time period t;
sharing total parking demand:
Figure BDA0003078851060000036
further, in step 4, a generalized cost function is established according to the parking space sharing selection behavior of the parking lot, which is specifically as follows:
parking cost of a parking person in the process of sharing parking space selection is divided into four parts: parking cost; detour time cost for going to the shared parking lot; cruise time cost of free parking spaces in the parking lot; walking cost for going from the shared parking lot to the destination; the calculation formula is as follows:
Figure BDA0003078851060000037
wherein,
Figure BDA0003078851060000038
sharing the parking total cost for the nth shared parking lot; PC (personal computer)jParking fee for land j;
Figure BDA0003078851060000039
a detour time cost to park with ground j for the nth shared parker;
Figure BDA00030788510600000310
time cost of finding parking space for nth shared parker at destination j;
Figure BDA00030788510600000311
for the nth share stopThe cost of pedestrian time for the vehicle occupant to go from destination j;
Figure BDA00030788510600000312
wherein,
Figure BDA00030788510600000313
a detour distance for the nth shared parking lot to park with ground j; vdriveThe average speed of the vehicle around; VOT is a time value coefficient;
Figure BDA0003078851060000041
wherein, alpha is the minimum bit-searching time; vjParking capacity for Utility j;
Figure BDA0003078851060000042
the number of parked vehicles in the ground j is used for the nth shared parking person;
Figure BDA0003078851060000043
wherein,
Figure BDA0003078851060000044
a walking distance from destination j for the nth shared parking; vwalkIs the average walking speed of the parked person.
Further, in step 5, the parking cost of each shared parking demander selecting the peripheral idle parking spaces is calculated, and the parking space is selected according to the minimum parking cost, which specifically comprises the following steps:
(1) judging the parking conditions of the parking lots in each land, and inputting the shared parking demand: when the parking demand is greater than or equal to the parking capacity, the parking lot is a destination parking lot, and the parking quantity in the parking lot is equal to the parking capacity; if the parking demand is smaller than the parking capacity, the parking lot is shared, and the parking quantity in the parking lot is equal to the parking demand;
(2) judging whether a shared parking demand exists, if the total shared parking demand N is more than 0, making N equal to 1, and starting shared parking position selection by a shared parking person; if the total shared parking demand N is 0, ending the process and outputting parking lot data;
(3) calculating the parking cost of the shared parking demanders and each shared parking lot;
(4) comparing the parking cost of each parking lot, and sharing the selection of the parking person according to the minimum parking cost;
(5) judging whether the selected parking lot is full, if so, comparing the parking costs of the rest parking lots, selecting the parking lot with the minimum parking cost for parking, and if not, selecting the parking lot for parking;
(6) updating the parking quantity of the parking lot;
(7) judging whether a termination condition is reached, if N is more than or equal to N or all parking spaces are fully stopped, finishing the calculation, and outputting related data; otherwise, n is n +1, and the procedure returns to (3).
Compared with the prior art, the invention has the following remarkable advantages: (1) forecasting the shared parking demand by a method of selecting peripheral idle parking spaces according to the parking space selection behavior by using the supersaturated parking demand, so as to obtain a more complete forecasting method of the shared parking demand; (2) and aiming at the parking demand part exceeding the parking capacity, the shared parking demand and the transferred parking demand are clear, and the shared parking actual condition in a mixed mode is better met.
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Fig. 1 is a flowchart of a hybrid land-based shared parking demand prediction method based on a parking space selection behavior according to the present invention.
Fig. 2 is a classification diagram of urban construction land.
FIG. 3 is a flow chart of the present invention for a parking selection shared by parking lots.
Detailed Description
The invention relates to a mixed land sharing parking demand prediction method based on parking space selection behavior, which comprises the following steps of:
step 1, determining land use indexes of land types in mixed land and land types;
step 2, forecasting the parking demand of the single land by using a parking generation rate method, and calculating the parking demand of each land type in each time period;
step 3, comparing the parking demand of each land type in each time period with the parking capacity of the land to determine the shared parking demand;
step 4, establishing a generalized cost function according to the parking person shared parking space selection behavior;
step 5, calculating the parking cost of each shared parking demander for selecting peripheral idle parking positions, and selecting the parking position according to the minimum parking cost;
and 6, counting the selection conditions of the shared parking demanders to obtain the parking demand amount of each type of the shared parking and the shared parking demand transfer amount.
Further, in step 1, determining the land utilization indexes of the mixed land use type and the land use types, specifically:
the land types are divided into residential land, public management and public service land, commercial service facility land, industrial land, green land and square land, public facility land, road and traffic facility land and logistics storage land;
the living land is divided into a first type living land, a second type living land and a third type living land;
the public management and public service land is divided into administrative and office land, cultural facility land, education and scientific research land, sports land, medical and health land, social welfare facility land, cultural relics and ancient sites, field application land and religious facility land;
the commercial service industry facility land is divided into a commercial facility land, an entertainment and fitness facility land, a public facility business network land and other service facility land;
the industrial land is divided into a first-class industrial land, a second-class industrial land and a third-class industrial land;
the greenbelts and the square lands are divided into park greenbelts, protection greenbelts and square lands;
the public facility land is divided into a supply facility land, an environment facility land, a safety facility land and other public facility lands;
the land for the road and the traffic facilities is divided into urban road land, urban rail transit land, traffic junction land, traffic station land and other traffic facility land;
the logistics storage land is divided into a first-class logistics storage land, a second-class logistics storage land and a third-class logistics storage land.
Further, in step 2, the single land parking demand is predicted by using a parking generation rate method, and the parking demand of each land type in each time period is calculated, specifically:
calculating the parking demand of each land according to the mixed land type and the land utilization index and the parking generation rate model, wherein the calculation formula is as follows:
Figure BDA0003078851060000061
wherein,
Figure BDA0003078851060000062
the parking demand of the land i in the time period t; siThe land utilization index of the land utilization i is used;
Figure BDA0003078851060000063
is the parking generation rate of the land i in the time period t.
Further, in step 3, comparing the parking demand of each land type in each time period with the parking capacity of the land to determine the shared parking demand, specifically as follows:
when the parking demand is less than or equal to the land parking capacity, the parking demand is not shared; when the parking demand is larger than the land parking capacity, the shared parking demand exists, and the shared parking demand is a part exceeding the land parking capacity, and the calculation formula is as follows:
Figure BDA0003078851060000064
wherein, ViIn order to park a large capacity with the ground i,
Figure BDA0003078851060000065
sharing parking demand for land i in a time period t;
sharing total parking demand:
Figure BDA0003078851060000066
further, in step 4, a generalized cost function is established according to the parking space sharing selection behavior of the parking lot, which is specifically as follows:
parking cost of a parking person in the process of sharing parking space selection is divided into four parts: parking cost; detour time cost for going to the shared parking lot; cruise time cost of free parking spaces in the parking lot; the walking cost for going to the destination from the shared parking lot; the calculation formula is as follows:
Figure BDA0003078851060000067
wherein,
Figure BDA0003078851060000068
sharing the parking total cost for the nth shared parking lot; PC (personal computer)jParking fee for land j;
Figure BDA0003078851060000069
a detour time cost to park with ground j for the nth shared parker;
Figure BDA00030788510600000610
time cost of finding parking space for nth shared parker at destination j;
Figure BDA00030788510600000611
a walk time cost for the nth shared parking lot to go from destination with lot j;
Figure BDA00030788510600000612
wherein,
Figure BDA00030788510600000613
a detour distance for the nth shared parking lot to park with ground j;
Figure BDA00030788510600000614
the average speed of the vehicle around; VOT is a time value coefficient;
Figure BDA0003078851060000071
wherein, alpha is the minimum bit-searching time; vjParking capacity for ground j;
Figure BDA0003078851060000072
the number of parked vehicles in the ground j is used for the nth shared parking person;
Figure BDA0003078851060000073
wherein,
Figure BDA0003078851060000074
a walking distance from destination j for the nth shared parking; vwalkIs the average walking speed of the parked person.
Further, in step 5, the parking cost of each shared parking demander selecting the peripheral idle parking spaces is calculated, and the parking space is selected according to the minimum parking cost, which specifically comprises the following steps:
(1) judging the parking conditions of the parking lots in each land, and inputting the shared parking demand: when the parking demand is greater than or equal to the parking capacity, the parking lot is a destination parking lot, and the parking quantity in the parking lot is equal to the parking capacity; if the parking demand is smaller than the parking capacity, the parking lot is shared, and the parking quantity in the parking lot is equal to the parking demand;
(2) judging whether a shared parking demand exists, if the total shared parking demand N is more than 0, making N equal to 1, and starting shared parking position selection by a shared parking person; if the total shared parking demand N is 0, ending the process and outputting parking lot data;
(3) calculating the parking cost of the shared parking demanders and each shared parking lot;
(4) comparing the parking cost of each parking lot, and sharing the selection of the parking person according to the minimum parking cost;
(5) judging whether the selected parking lot is full, if so, comparing the parking costs of the rest parking lots, selecting the parking lot with the minimum parking cost for parking, and if not, selecting the parking lot for parking;
(6) updating the parking quantity of the parking lot;
(7) judging whether a termination condition is reached, if N is more than or equal to N or all parking spaces are fully stopped, finishing the calculation, and outputting related data; otherwise, n is n +1, and return to (3).
The invention is described in further detail below with reference to the figures and the embodiments.
Examples
With reference to fig. 1 to 2, a method for forecasting a mixed land shared parking demand based on a parking space selection behavior comprises the following steps:
the method comprises the following steps: determining the land types in the mixed land and land utilization indexes of all land types;
step two: forecasting the parking demand of the single land by using a parking generation rate method, and calculating the parking demand of each land type in each time period;
the parking generation rate method considers the difference of different land properties on parking characteristics and requirements, establishes the relationship between land utilization and parking demand by analyzing the parking demands generated by land utilization of each land property unit, and has the following calculation formula:
Figure BDA0003078851060000081
wherein,
Figure BDA0003078851060000082
the parking demand of the land i in the time period t; riGenerating the parking rate of the land i in the time period t; s. theiThe land utilization index of the land used for the land i.
Step three: comparing the parking demand of each land type in each time period with the parking capacity of the land to determine the shared parking demand;
when the parking demand is less than or equal to the land parking capacity, the parking demand is not shared; when the parking demand is larger than the land parking capacity, the shared parking demand exists, and the shared parking demand is a part exceeding the land parking capacity, and the calculation formula is as follows:
Figure BDA0003078851060000083
wherein, ViIn order to park a large capacity with the ground i,
Figure BDA0003078851060000084
the shared parking demand for land i in the time period t.
Sharing total parking demand:
Figure BDA0003078851060000085
step four: establishing a generalized cost function according to the parking space sharing selection behavior of the parking persons;
parking cost of a parking person in the process of sharing parking space selection is mainly divided into four parts: parking cost; detour time cost for going to the shared parking lot; cruise time cost of free parking spaces in the parking lot; and fourthly, the walking cost for going to the destination from the shared parking lot. The calculation formula is as follows:
Figure BDA0003078851060000086
wherein,
Figure BDA0003078851060000087
sharing the parking total cost for the nth shared parking lot; PC (personal computer)jParking fee for land j;
Figure BDA0003078851060000088
a detour time cost to park with ground j for the nth shared parker;
Figure BDA0003078851060000089
time cost of finding parking space for nth shared parker at destination j;
Figure BDA00030788510600000810
the cost of walking time from destination j for the nth shared parker.
Figure BDA00030788510600000811
Wherein,
Figure BDA00030788510600000812
a detour distance for the nth shared parking lot to park with ground j; vdriveThe average speed of the vehicle around; VOT is the time value coefficient.
Figure BDA0003078851060000091
Wherein, alpha is the minimum bit-searching time; vjParking capacity for Utility j;
Figure BDA0003078851060000092
the number of the parked vehicles in the right ground j when the parking person is parked is shared for the nth shared parking person.
Figure BDA0003078851060000093
Wherein,
Figure BDA0003078851060000094
a walking distance from destination j for the nth shared parking; vwalkIs the average walking speed of the parked person.
Step five: calculating the parking cost of each shared parking demander for selecting peripheral idle parking spaces, and selecting the parking space according to the minimum parking cost, wherein the specific steps are as follows by combining the step shown in the figure 3:
(1) and judging the parking conditions of the parking lots of each land, and inputting the shared parking demand. When the parking demand is greater than or equal to the parking capacity, the parking lot is a destination parking lot, and the parking quantity in the parking lot is equal to the parking capacity; and secondly, if the parking demand is smaller than the parking capacity, the parking lot is shared, and the parking quantity in the parking lot is equal to the parking demand.
(2) Judging whether a shared parking demand exists, if the total shared parking demand N is more than 0, making N equal to 1, and starting shared parking position selection by a shared parking person; if the total shared parking demand N is 0, the process ends and parking lot data is output.
(3) And calculating the parking cost of the shared parking demanders and each shared parking lot.
(4) Comparing the parking cost of each parking lot, and sharing the selection of the parking person according to the minimum parking cost.
(5) And judging whether the selected parking lot is full, if so, comparing the parking costs of the rest parking lots, selecting the parking lot with the minimum parking cost for parking, and if not, selecting the parking lot for parking.
(6) And updating the parking quantity of the parking lot.
(7) And judging whether a termination condition is reached, if N is more than or equal to N or all parking spaces are fully stopped, finishing the calculation, and outputting related data. Otherwise, n is n +1, and the procedure returns to (3).
Step six: and counting the selection conditions of the shared parking demanders to obtain the parking demand of each type of the shared parking and the shared parking demand transfer amount.
Determining parking requirements of the time period mixed places in the shared parking environment according to the final parking lot selected by each shared parking person; determining a parking demand transfer amount in the shared parking environment based on each of the shared parking lot destination parking lots and the finally selected shared parking lot.
The invention provides a hybrid land-based shared parking demand prediction method based on parking space selection behaviors, and a plurality of methods and ways for realizing the technical scheme are provided, the above description is only a preferred embodiment of the invention, and it should be noted that a person skilled in the art can make a plurality of improvements and embellishments without departing from the principle of the invention, and the improvements and embellishments should be regarded as the protection scope of the invention, and all components which are not clear in the embodiment can be realized by the prior art.

Claims (4)

1. A mixed land shared parking demand prediction method based on parking space selection behaviors is characterized by comprising the following steps:
step 1, determining land use indexes of land types in mixed land and land types;
step 2, forecasting the single land parking demand by using a parking generation rate method, and calculating the parking demand of each land type in each time period, wherein the method specifically comprises the following steps:
calculating the parking demand of each land according to the mixed land type and the land utilization index and the parking generation rate model, wherein the calculation formula is as follows:
Figure FDA0003582642410000011
wherein, Pi tThe parking demand of the land i in the time period t; siThe land utilization index of the land utilization i is used;
Figure FDA0003582642410000012
generating the parking rate of the land i in the time period t;
step 3, comparing the parking demand of each land type in each time period with the parking capacity of the land to determine the shared parking demand;
step 4, establishing a generalized cost function according to the parking space sharing selection behavior of the parking persons, which is concretely as follows:
parking cost of a parking person in the process of sharing parking space selection is divided into four parts: parking cost; detour time cost for going to the shared parking lot; cruise time cost of free parking spaces in the parking lot; the walking cost for going to the destination from the shared parking lot; the calculation formula is as follows:
Figure FDA0003582642410000013
wherein,
Figure FDA0003582642410000014
sharing the parking total cost for the nth shared parking lot; PC (personal computer)jParking fee for land j;
Figure FDA0003582642410000015
a detour time cost to park with ground j for the nth shared parker;
Figure FDA0003582642410000016
time cost of finding parking space for nth shared parker at destination j;
Figure FDA0003582642410000017
a walk time cost from destination j for the nth shared parker;
Figure FDA0003582642410000018
wherein,
Figure FDA0003582642410000019
a detour distance for the nth shared parking lot to park with ground j; vdriveThe average speed of the vehicle around; VOT is a time value coefficient;
Figure FDA00035826424100000110
wherein, alpha is the minimum bit-searching time; vjParking capacity for Utility j;
Figure FDA00035826424100000111
the number of parked vehicles in the ground j is used for the nth shared parking person;
Figure FDA0003582642410000021
wherein,
Figure FDA0003582642410000022
a walking distance from destination j for the nth shared parking; vwalkAverage walking speed for the parked person;
step 5, calculating the parking cost of each shared parking demander for selecting peripheral idle parking positions, and selecting the parking position according to the minimum parking cost;
and 6, counting the selection conditions of the shared parking demanders to obtain the parking demand amount of each type of the shared parking and the shared parking demand transfer amount.
2. The method for forecasting the demand for parking in mixed land based on the berth selection behavior as claimed in claim 1, wherein: in the step 1, the land utilization indexes of the mixed land inner land type and the land types are determined, and the method specifically comprises the following steps:
the land types are divided into residential land, public management and public service land, commercial service facility land, industrial land, green land and square land, public facility land, road and traffic facility land and logistics storage land;
the living land is divided into a first type living land, a second type living land and a third type living land;
the public management and public service land is divided into administrative and office land, cultural facility land, education and scientific research land, sports land, medical and health land, social welfare facility land, cultural relics and ancient sites, field application land and religious facility land;
the commercial service industry facility land is divided into a commercial facility land, an entertainment and fitness facility land, a public facility business network land and other service facility land;
the industrial land is divided into a first-class industrial land, a second-class industrial land and a third-class industrial land;
the greenbelt and the square land are divided into a park greenbelt, a protection greenbelt and a square land;
the public utility land is divided into a supply facility land, an environmental facility land, a safety facility land and other public facility lands;
the road and traffic facility land is divided into urban road land, urban rail transit land, traffic junction land, traffic station land and other traffic facility land;
the logistics storage land is divided into a first-class logistics storage land, a second-class logistics storage land and a third-class logistics storage land.
3. The method for predicting the mixed land-based shared parking demand based on the berth selection behavior as claimed in claim 1, wherein in the step 3, the parking demand of each land type in each time period is compared with the land parking capacity to determine the shared parking demand, and the specific steps are as follows:
when the parking demand is less than or equal to the land parking capacity, the parking demand is not shared; when the parking demand is greater than the land parking capacity, the shared parking demand exists, and the shared parking demand is a part exceeding the land parking capacity, and the calculation formula is as follows:
Figure FDA0003582642410000031
wherein, ViIn order to park a large capacity with the ground i,
Figure FDA0003582642410000032
sharing parking demand for land i in a time period t;
sharing total parking demand:
Figure FDA0003582642410000033
4. the method for predicting the demand for shared parking in mixed land based on the parking space selection behavior as claimed in claim 1, wherein in the step 5, the parking cost for each shared parking demander to select the peripheral idle parking spaces is calculated, and the parking space is selected according to the minimum parking cost, and the specific steps are as follows:
(1) judging the parking conditions of the parking lots in each land, and inputting the shared parking demand: when the parking demand is greater than or equal to the parking capacity, the parking lot is a destination parking lot, and the parking quantity in the parking lot is equal to the parking capacity; if the parking demand is smaller than the parking capacity, the parking lot is shared, and the parking quantity in the parking lot is equal to the parking demand;
(2) judging whether a shared parking demand exists, if the total shared parking demand N is more than 0, making N equal to 1, and starting shared parking position selection by a shared parking person; if the total shared parking demand N is 0, ending the process and outputting parking lot data;
(3) calculating the parking cost of the shared parking demanders and each shared parking lot;
(4) comparing the parking cost of each parking lot, and sharing the selection of the parking person according to the minimum parking cost;
(5) judging whether the selected parking lot is full, if so, comparing the parking costs of the rest parking lots, selecting the parking lot with the minimum parking cost for parking, and if not, selecting the parking lot for parking;
(6) updating the parking quantity of the parking lot;
(7) judging whether a termination condition is reached, if N is more than or equal to N or all parking spaces are fully stopped, finishing the calculation, and outputting related data; otherwise, n is n +1, and the procedure returns to (3).
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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104157166A (en) * 2014-08-21 2014-11-19 孙之光 Parking place management system and parking place reservation method
CN107845288A (en) * 2017-11-27 2018-03-27 东南大学 Matched somebody with somebody based on climate resourcee polymorphic type land used and build parking position shared resource matching process
CN107958610A (en) * 2017-11-21 2018-04-24 同济大学 A kind of function area of mixed usage parking stall predictor method shared based on berth
CN108292474A (en) * 2015-11-04 2018-07-17 祖克斯有限公司 Send and safeguard the coordination of the fleet of autonomous vehicle
CN110175718A (en) * 2019-05-29 2019-08-27 清华大学深圳研究生院 A kind of berth allocation method and terminal device

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104157166A (en) * 2014-08-21 2014-11-19 孙之光 Parking place management system and parking place reservation method
CN108292474A (en) * 2015-11-04 2018-07-17 祖克斯有限公司 Send and safeguard the coordination of the fleet of autonomous vehicle
CN107958610A (en) * 2017-11-21 2018-04-24 同济大学 A kind of function area of mixed usage parking stall predictor method shared based on berth
CN107845288A (en) * 2017-11-27 2018-03-27 东南大学 Matched somebody with somebody based on climate resourcee polymorphic type land used and build parking position shared resource matching process
CN110175718A (en) * 2019-05-29 2019-08-27 清华大学深圳研究生院 A kind of berth allocation method and terminal device

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
中心城区高校泊车位共享的动态分配模型及效果评价;陈峻 等;《中国公路学报》;20151115;全文 *

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