CN112533140B - Shared bicycle distribution condition evaluation method based on index - Google Patents

Shared bicycle distribution condition evaluation method based on index Download PDF

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CN112533140B
CN112533140B CN202011332557.7A CN202011332557A CN112533140B CN 112533140 B CN112533140 B CN 112533140B CN 202011332557 A CN202011332557 A CN 202011332557A CN 112533140 B CN112533140 B CN 112533140B
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distribution
shared bicycle
shared
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road sections
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CN112533140A (en
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蒋寅
薛文
左文泽
贾国洋
郑倩
程锦
安睿
徐国山
杜鹏
李强强
徐磊
赵宁
李鑫
赵阳
和喆
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TIANJIN SAIYING ENGINEERING CONSTRUCTION CONSULTING MANAGEMENT Co.,Ltd.
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    • H04—ELECTRIC COMMUNICATION TECHNIQUE
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    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/30—Services specially adapted for particular environments, situations or purposes
    • H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]

Abstract

The invention discloses an index-based shared bicycle distribution condition evaluation method, which comprises the steps of collecting shared bicycle travel data in a selected evaluation area and cleaning the data; calculating real-time point positions of the shared bicycle; matching the shared bicycle point location with the road section location; calculating the distribution density of the shared single vehicles on the road sections based on the distribution number and the length of the road sections of the shared single vehicles; calculating the distribution index of the shared bicycle road sections and dividing the distribution grade of the shared bicycle road sections according to the functional relation between the distribution density and the distribution index of the shared bicycle road sections; and carrying out region division on the evaluation region, calculating the distribution index of the shared single-vehicle region in the divided region, and dividing the distribution grade of the shared single-vehicle region, thereby quantitatively evaluating the real-time distribution condition of the shared single-vehicle. The method has the characteristics of time and space universality, and can calculate in real time or by using historical data from the time perspective; and the method is suitable for calculation of an area with any space size from the traffic of the space.

Description

Shared bicycle distribution condition evaluation method based on index
Technical Field
The invention relates to shared bicycle evaluation, in particular to an index-based shared bicycle distribution condition evaluation method.
Background
With the continuous innovation and development of science and technology, the internet has penetrated all aspects of our lives, and the internet + also becomes an important form for the development and transformation of the traditional industry. In recent years, with the surge of the internet, the shared economy has been well developed, and a shared bicycle is released in 2016. The shared bicycle enriches the traveling modes, provides convenience for life production, is widely popular with the public, and brings a plurality of problems to city management.
However, the management of the shared bicycle still depends on traditional means such as patrol and the like at present, the obtained shared bicycle distribution information has poor timeliness and comprehensiveness, the requirements of an industry management department are difficult to meet, an accurate and real-time shared bicycle distribution condition evaluation system is lacked, and a basis is provided for the management of the urban shared bicycle.
Disclosure of Invention
Aiming at the prior art, the invention provides an index-based shared bicycle distribution condition evaluation method, which combines the big data of the shared bicycle of the Internet, provides the shared bicycle distribution index, can visually reflect the distribution condition of the shared bicycle at the road section and the region level, and can quantitatively evaluate the real-time distribution condition of the shared bicycle.
In order to solve the technical problem, the invention provides an index-based shared bicycle distribution condition evaluation method, which mainly comprises the following steps: 1) collecting shared bicycle travel data in the selected evaluation area, and cleaning the data; 2) calculating real-time point positions of the shared bicycle; 3) matching the shared bicycle point location with the road section location; 4) calculating the distribution density of the shared single vehicles on the road sections based on the distribution number and the length of the road sections of the shared single vehicles; 5) calculating the distribution index of the shared bicycle road sections and dividing the distribution grade of the shared bicycle road sections according to the functional relation between the distribution density and the distribution index of the shared bicycle road sections; 6) and carrying out area division on the evaluation area, calculating the distribution index of the shared bicycle area in the divided area, and dividing the distribution grade of the shared bicycle area to obtain the evaluation result of the distribution condition of the shared bicycle area in the divided area.
Further, the shared bicycle distribution condition evaluation method based on the index of the invention comprises the following steps:
step 1) comprises collecting shared bicycle travel data in a selected evaluation area; and invalid orders are removed through data cleaning, and the data of real-time position calculation of the shared bicycle are guaranteed to be valid data. The invalid order is travel data with the riding time of less than 1min and the riding distance of less than 300 m.
The step 2) comprises the following steps: 2-1) firstly, acquiring shared bicycle travel data and static position data of one month to form a shared bicycle initial position library; 2-2) updating the position of the shared bicycle according to the real-time travel data of the shared bicycle; and 2-3) correcting the real-time position of the shared bicycle according to the real-time static position data of the shared bicycle to form a real-time position library of the shared bicycle.
The step 3) comprises the following steps: establishing a matching rule of the shared bicycle point location and the road section position, namely matching the shared bicycle to the road section with the shortest vertical distance; and matching the positions of the shared bicycle sections according to the calculation result of the real-time point positions of the shared bicycles.
The step 4) comprises the following steps: firstly, counting the total number of the shared bicycle points distributed on each road section and the road section length, and then determining the real-time distribution density of the shared bicycle on each road section according to the following formula:
Figure BDA0002796232800000021
wherein i is a road section number; rhoiSharing the real-time distribution density of the single vehicle for the road section i; n is a radical ofiThe total number of the shared single-vehicle points on the road section i; l isiIs the length of the section i.
In step 5), the functional relationship between the distribution density and the distribution index of the shared bicycle section is as follows:
Figure BDA0002796232800000022
wherein, Index _ LDFBiThe shared bicycle distribution index of the road section i; rhoiThe real-time distribution density of the individual cars is shared for road section i.
In step 5), the division standard of the distribution grade of the shared single-vehicle road sections is shown in table 1:
TABLE 1 shared bicycle section distribution index grade division table
Road section distribution density [0,0.2) [0.2,0.4) [0.4,0.6) [0.6,0.8) [0.8,∞]
Road section distribution index [0,2) [2,4) [4,6) [6,8) [8,10]
Degree of distribution density Distributed sporadically Sparse distribution Mild dense Moderately dense Excessive densification
Step 6) comprises the following steps:
6-1) carrying out region division on the evaluation region; 6-2) calculating the mileage proportion of the shared single-vehicle excessively and densely distributed road sections in the divided areas; 6-2) standardizing the distribution index of the shared bicycle in the divided area according to the proportion of the mileage of the shared bicycle in the divided area, wherein the standardized formula is as follows:
Figure BDA0002796232800000023
wherein, Index _ QYFBjIs the shared bicycle distribution index for region j; pjSharing the mileage proportion of the over-densely distributed road sections of the single vehicle for the area j; 6-3) according to the classification standard of the distribution indexes of the shared bicycles in the region, the distribution indexes of the shared bicycles in the region are classified as shown in the table 2:
table 2 shared bicycle regional distribution index grading table
Figure BDA0002796232800000024
Compared with the prior art, the invention has the beneficial effects that:
the shared bicycle distribution condition evaluation method based on the index has the characteristics of time and space universality, and can be used for calculating in real time or by using historical data from the time perspective; and the method is suitable for calculation of an area with any space size from the traffic of the space. The method can macroscopically measure the development and distribution conditions of the shared bicycle in the whole city and each administrative district, and monitor the change of the distribution conditions of the shared bicycle in real time, so that on one hand, data support is provided for the future development policy formulation of the shared bicycle, and on the other hand, the implementation effect of the relevant policy can be analyzed through the change of the distribution conditions before and after policy implementation; microscopically, the shared single-vehicle distribution dense area can be quickly positioned by monitoring the shared single-vehicle distribution conditions of the traffic districts and the road sections in real time, the quick and accurate dispatching of the power-assisted shared single-vehicle is realized, the management level of the urban shared single-vehicle is improved, and the power-assisted shared single-vehicle disorder treatment is realized.
Drawings
FIG. 1 is a flow chart of a method of calculating a real-time distribution index of a shared bicycle in accordance with the present invention;
FIG. 2 is a spatial distribution diagram of the distribution index of the shared bicycles in each section of the central city of Tianjin City according to the embodiment of the present invention;
FIG. 3 is a spatial distribution diagram of the distribution index of the shared single vehicles in each traffic district of the central city of Tianjin City according to the embodiment of the present invention;
FIG. 4 is a histogram of the distribution index of shared bicycles in each administrative district of the central city of Tianjin City, according to an embodiment of the present invention;
FIG. 5 is a distribution index chart of shared cars in the urban area of Tianjin City in the embodiment of the present invention.
Detailed Description
The following describes the implementation of the method for estimating the distribution of shared bicycles in detail with tianjin city as a selected area in conjunction with a chart, but the following embodiments are by no means limiting the invention.
From 2017 and 2 months, the Internet bicycle leasing enterprises continuously enter Tianjin City for operation. Through the development of three years, the market of Internet rented bicycles in Tianjin city gradually becomes stable, and three main operation enterprises are respectively a Mei Tuo bicycle, a Hao Luo bicycle and a Qing Ju bicycle. The main operation areas comprise six urban areas (including Heping, Hexi, Hedong, Hebei, Hongqiao and Nankai), four surrounding areas (including Xiqing, Jinnan, Dongli and Beichen), new coastal areas, Wuqing and Jizhou areas.
Data base of embodiments
The shared bicycle data used in the embodiment mainly include shared bicycle travel data and shared bicycle real-time static position data in an urban area of the Tianjin city. The data mainly comes from a transportation big data platform in Tianjin city. The time period of the data is from 9 months 1 day to 11 months 18 days in 2020.
The shared bicycle journey data is mainly data generated by riding a shared bicycle running in Tianjin city in the whole city range, the daily data volume is about 208 ten thousand, and the fields mainly comprise a journey number, an enterprise number, a vehicle number, a starting point longitude, a starting point latitude, a journey starting time, a terminal point longitude, a terminal point latitude, a journey ending time, a riding journey distance, a journey duration and the like. Specifically, as shown in table 3:
TABLE 3 shared bicycle journey data schematic
Journey numbering Enterprise number Vehicle number Longitude of origin Starting point latitude Starting time of journey
115xxxx 13 17139909 117.14924 39.104008 1605570837000
mbk864xxxx 10 8641883676 117.21474 39.11495 1605570925000
115xxxx 13 14812163 117.23635 39.09787 1605570230000
115xxxx 13 15066083 117.13096 39.09048 1605570870000
115xxxx 13 14809857 117.25653 39.09795 1605570430000
…… …… …… …… …… ……
TABLE 3
Journey numbering End point longitude Terminal latitude End of travel time Travel distance of riding Duration of travel
115xxxx 117.15247 39.10747 1605571200000 480 363
mbk864xxxx 117.21482 39.11504 1605571200000 12 240
115xxxx 117.22849 39.10156 1605571200000 800 970
115xxxx 117.12899 39.08778 1605571200000 470 330
115xxxx 117.24258 39.09972 1605571201000 3160 771
…… …… …… …… …… ……
The real-time static position data of the shared bicycle is mainly data generated by the shared bicycle running in Tianjin city, the daily data volume is about 470 ten thousand, and the fields mainly comprise enterprise number, vehicle number, longitude, latitude, positioning time and the like. Specifically, as shown in table 4:
TABLE 4 shared bicycle real-time static position data schematic
Enterprise number Vehicle number Longitude (G) Latitude Positioning time
12 3110646092 117.27427 39.10605 1605571200000
12 9510142592 117.21044 39.13522 1605571200000
12 9190783857 117.15169 39.14306 1605571200000
12 9150101306 117.14962 39.13480 1605571200000
12 5920639057 117.15978 39.18760 1605571200000
…… …… …… …… ……
Second, specific evaluation process for shared bicycle distribution situation in city center of Tianjin city
As shown in fig. 1, the method comprises the following steps:
1) cleaning shared bicycle travel data
In the embodiment, shared bicycle data of 9 month, 1 day and 11 month, 18 days in 2020 are collected through a big traffic data platform in Tianjin, invalid orders are removed through data cleaning, and the data of real-time position calculation of the shared bicycles are guaranteed to be valid data. Through comprehensive consideration, the removed data comprises riding order data with riding time less than 1min and riding distance less than 300 m. After cleaning, the stroke data is changed from 161.25 ten thousand to 151.76 ten thousand, and the specific cleaning data is shown in table 5:
table 5 cleaning data schematic
Journey numbering Enterprise number Vehicle number Longitude of origin Starting point latitude Starting time of journey
mbk864xxxx
10 8641883676 117.21474 39.11495 1605570925000
mbk864xxxx 10 8641783269 117.07382 39.14825 1605570490000
115xxxx 13 14836841 117.18607 39.12377 1605571136000
115xxxx 13 14786791 117.15830 39.14499 1605571196000
115xxxx 13 14223145 117.26404 39.10181 1605571184000
…… …… …… …… …… ……
TABLE 5 continuation
Journey numbering End point longitude Terminal latitude End of travel time Travel distance of riding Duration of travel
mbk864xxxx 117.21482 39.11504 1605571200000 12 240
mbk864xxxx 117.07383 39.14826 1605571200000 33 60
115xxxx 117.18640 39.12385 1605571202000 60 66
115xxxx 117.15832 39.14500 1605571202000 0 6
115xxxx 117.26390 39.10172 1605571202000 0 18
…… …… …… …… …… ……
2) Calculating real-time point positions of the shared bicycle;
in the embodiment, shared bicycle journey data and static position data of 9 months in 2020 are acquired through a big traffic data platform in Tianjin, the journey data are divided into two groups according to time, and the data periods are respectively 1-15 days in 9 months in 2020 and 16-30 days in 9 months in 2020. Calculating the real-time position database of the shared bicycle at 0:00 on 16 days at 9 months and 16 months in 2020 according to the two sets of travel data respectively, forming an initial position database of the shared bicycle through comparison, and then correcting the initial position database of the shared bicycle according to the static position data of the shared bicycle at 0:00 on 16 days at 9 months and 16 months in 2020 to finally form the initial position database of the shared bicycle. Specifically, as shown in table 6:
TABLE 6 initial position library schematic for shared bicycle
Enterprise number Vehicle number Longitude (G) Latitude Positioning time
12 9190446830 117.22634 39.10506 1600185600
12 2800191992 117.24772 39.13660 1600185600
12 9510066295 117.65311 39.04024 1600185600
12 9190572976 117.25022 39.06737 1600185600
12 3510167449 117.19687 39.12017 1600185600
…… …… …… …… ……
And calculating the position of the shared bicycle by using the shared bicycle travel data from 9 month, 16 days to 11 month and 18 days in 2020, correcting the real-time position of the shared bicycle according to the real-time static position data of the shared bicycle, and finally forming a shared bicycle real-time position library.
3) Matching the shared bicycle point location with the road section location;
the matching algorithm of the shared bicycle point location and the road section is designed in the scheme, and the specific matching rule is that the shared bicycle is matched to the road section with the shortest vertical distance. And matching the positions of the shared bicycle sections according to the real-time position calculation result of the shared bicycle. The matching results are shown in table 7:
TABLE 7 shared bicycle position matching result schematic
Enterprise number Vehicle number Longitude (G) Latitude Positioning time Home road segment id
12 9190446830 117.22634 39.10506 1600185600 15624
12 2800191992 117.24772 39.13660 1600185600 14219
12 9510066295 117.65311 39.04024 1600185600 16524
12 9190572976 117.25022 39.06737 1600185600 11568
12 3510167449 117.19687 39.12017 1600185600 21167
…… …… …… …… …… ……
4) Calculating the distribution density of the road sections;
for carrying out shared cyclesAnd calculating the distribution density of the road sections after real-time position calculation and road section matching. Firstly, counting the total number N of shared bicycle points distributed in each road sectioniAnd a link length LiWherein the total number N of the shared bicycle pointsiThe matching times of the shared bicycle position are obtained by counting the occurrence times of the same road section id in the matching result; road section length LiIs an inherent attribute of a link in a map.
After the data statistics is finished, determining the distribution density of the shared single vehicles of each road section according to the following formula:
Figure BDA0002796232800000071
wherein i is a road section number; rhoiSharing the real-time distribution density of the single vehicle for the road section i; n is a radical ofiThe total number of the shared single-vehicle points on the road section i; l isiIs the length of the section i.
5) Determining the corresponding relation between the road section distribution density and the index, and realizing the calculation and the grade division of the road section distribution index;
calculating a road section distribution index according to the calculation result of the road section distribution density, and realizing the evaluation of the road section distribution density, wherein the road section distribution density and the index have the following functional relation:
Figure BDA0002796232800000072
wherein, Index _ LDFBiThe shared bicycle distribution index of the road section i; rhoiThe real-time distribution density of the individual cars is shared for road section i.
After the distribution index of each road section is calculated by the above formula, the shared single-vehicle distribution condition of each road section is evaluated according to the grading standard, and the specific grading standard of the road section distribution is shown in table 8:
table 8 shared bicycle section distribution index grade division table
Road section distribution index [0,2) [2,4) [4,6) [6,8) [8,10]
Degree of distribution density Distributed sporadically Sparse distribution Mild dense Moderately dense Excessive densification
The evaluation result of the distribution situation of each road section in the central city area of Tianjin City is shown in fig. 2, and it can be seen from fig. 2 that the distribution situation of the shared bicycle of different road sections in the central city area of Tianjin City is that the darker the color of the road section is, the denser the distribution of the shared bicycle is, and the lighter the color is, the more sparse the distribution of the shared bicycle is.
6) Carrying out region division on the evaluation region, calculating a distribution index of the shared bicycle region, and carrying out grade division;
after the evaluation of the road section distribution condition is finished, the area distribution condition can be evaluated according to the evaluation result, the evaluation area can be divided into areas according to the requirements, and in the example, the central urban area is divided into a plurality of traffic districts by taking railways, rivers and the like as partition boundaries.
Then calculating the mileage of the road sections which share the excessive and intensive distribution of the single vehicles in each traffic districtRatio PjThe distribution mileage proportion of the over-dense road sections is the ratio of the sum of the lengths of the road sections in the over-dense level in the traffic cell to the sum of the lengths of all the road sections in the traffic cell.
And finally, converting the over-densely distributed mileage proportion into a shared bicycle area distribution index, wherein the conversion function relationship is as follows:
Figure BDA0002796232800000073
wherein, Index _ QYFBjIs the shared bicycle distribution index for region j; pjAnd sharing the mileage proportion of the over-densely distributed road sections of the single vehicle for the area j.
The area distribution ranking criteria are shown in table 9:
TABLE 9 shared bicycle regional distribution index grading table
Index of area distribution [0,2) [2,4) [4,6) [6,8) [8,10]
Degree of distribution density Distributed sporadically Sparse distribution Mild dense Moderately dense Excessive densification
The evaluation results of the traffic districts in the central city of Tianjin City are shown in fig. 3, and it can be seen from fig. 3 that the distribution density of the shared vehicles in Tianjin City is gradually decreased from the center to the periphery, the more the traffic districts closer to the center are distributed with the shared vehicles, the more the traffic districts closer to the outer ring are distributed with the shared vehicles.
In this embodiment, besides the evaluation of the distribution of the shared vehicles in the traffic districts, the evaluation of the distribution of the shared vehicles in each administrative district in the central urban area of Tianjin city is also performed, and the evaluation results are shown in fig. 4 and 5. From fig. 4, it can be seen that the density of the shared bicycles in six urban areas (including the peace area, the western area, the eastern area, the northern area, the red bridge area and the southern open area) is obviously higher than that in the four areas around the city (including the west green area, the jin south area, the east li area and the north chen area), and the distribution situation is not changed greatly with time. Fig. 5 shows the distribution index of the shared vehicles in the entire central city of tianjin city, at the level of "moderately dense", and it can be seen that the distribution of the shared vehicles in tianjin city is more than normal.
According to the shared bicycle distribution condition evaluation result obtained by the invention, the development distribution conditions of the shared bicycles in the whole city and each administrative district can be macroscopically measured, and the change of the distribution conditions of the shared bicycles can be monitored in real time, so that on one hand, data support is provided for the future development policy establishment of the shared bicycles, and on the other hand, the implementation effect of the relevant policy can be analyzed through the change of the distribution conditions before and after the policy implementation. Microscopically, the shared single-vehicle distribution dense area can be quickly positioned by monitoring the shared single-vehicle distribution conditions of the traffic districts and the road sections in real time, the quick and accurate dispatching of the power-assisted shared single-vehicle is realized, the management level of the urban shared single-vehicle is improved, and the power-assisted shared single-vehicle disorder treatment is realized. Meanwhile, the evaluation of the distribution condition of the shared bicycle is beneficial to the improvement of the service level of the shared bicycle, so that the attraction of the shared bicycle is improved, the green trip proportion in Tianjin city is further improved, and the method has important significance for saving resources, reducing energy consumption, reducing pollution and promoting the sustainable development of economy and society.
Although the present invention has been described in connection with the drawings, it is not intended to be limited to the specific embodiments described above, which are intended as illustrative rather than restrictive, and that many modifications may be made by one of ordinary skill in the art without departing from the spirit and scope of the present invention as defined by the appended claims.

Claims (7)

1. An index-based shared bicycle distribution condition evaluation method is characterized by comprising the following steps of:
1) collecting shared bicycle travel data in the selected evaluation area, and cleaning the data;
2) calculating real-time point positions of the shared bicycle, comprising the following steps:
2-1) firstly, acquiring shared bicycle travel data and static position data of one month to form a shared bicycle initial position library;
2-2) updating the position of the shared bicycle according to the real-time travel data of the shared bicycle;
2-3) correcting the real-time position of the shared bicycle according to the real-time static position data of the shared bicycle to form a real-time position library of the shared bicycle;
3) matching the shared bicycle point location with the road section location, comprising: establishing a matching rule of the shared bicycle point location and the road section position, namely matching the shared bicycle to the road section with the shortest vertical distance; matching the positions of the shared bicycle sections according to the calculation result of the real-time point positions of the shared bicycles;
4) calculating the distribution density of the shared single vehicles on the road sections based on the distribution number and the length of the road sections of the shared single vehicles;
5) calculating the distribution index of the shared bicycle road sections and dividing the distribution grade of the shared bicycle road sections according to the functional relation between the distribution density and the distribution index of the shared bicycle road sections;
6) and carrying out area division on the evaluation area, calculating the distribution index of the shared bicycle area in the divided area, and dividing the distribution grade of the shared bicycle area to obtain the evaluation result of the distribution condition of the shared bicycle area in the divided area.
2. The shared bicycle index-based distribution assessment method according to claim 1, wherein step 1) comprises collecting shared bicycle trip data within a selected assessment area; and invalid orders are removed through data cleaning, and the data of real-time position calculation of the shared bicycle are guaranteed to be valid data.
3. The method of claim 2, wherein the invalid order is trip data with a ride time of less than 1min and a ride distance of less than 300 m.
4. The shared bicycle distribution evaluation method based on index as claimed in claim 1, wherein the step 4) comprises: firstly, counting the total number of the shared bicycle points distributed on each road section and the road section length, and then determining the real-time distribution density of the shared bicycle on each road section according to the following formula:
Figure FDA0003197478990000011
wherein i is a road section number; rhoiSharing the real-time distribution density of the single vehicle for the road section i; n is a radical ofiThe total number of the shared single-vehicle points on the road section i; l isiIs the length of the section i.
5. The method as claimed in claim 4, wherein the distribution density of the shared bicycle section as a function of the distribution index in step 5) is as follows:
Figure FDA0003197478990000021
wherein, Index _ LDFBiThe shared bicycle distribution index of the road section i; rhoiThe real-time distribution density of the individual cars is shared for road section i.
6. The shared bicycle distribution situation evaluation method based on the index as claimed in claim 1, wherein the division criteria of the shared bicycle section distribution grades in step 5) are as follows:
the distribution density of the shared bicycle road sections is [0,0.2 ], the distribution index of the shared bicycle road sections is [0,2), and the distribution grade of the shared bicycle road sections is sporadic distribution;
the distribution density of the shared bicycle road sections is [0.2,0.4 ], the distribution index of the shared bicycle road sections is [2,4 ], and the distribution grade of the shared bicycle road sections is sparse;
the distribution density of the shared bicycle road sections is [0.4,0.6 ], the distribution index of the shared bicycle road sections is [4,6 ], and the distribution grade of the shared bicycle road sections is slightly dense;
the distribution density of the shared bicycle road sections is [0.6,0.8 ], the distribution index of the shared bicycle road sections is [6,8 ], and the distribution grade of the shared bicycle road sections is moderately dense;
the distribution density of the shared bicycle road sections is [0.8, ∞ ], the distribution index of the shared bicycle road sections is [8,10], and the distribution grade of the shared bicycle road sections is excessively dense.
7. The shared bicycle distribution evaluation method based on index as claimed in claim 1, wherein step 6) comprises:
6-1) carrying out region division on the evaluation region;
6-2) calculating the mileage proportion of the shared single-vehicle excessively and densely distributed road sections in the divided areas;
6-3) standardizing the distribution index of the shared bicycle according to the proportion of the mileage of the shared bicycle in the divided area, wherein the standardized formula is as follows:
Figure FDA0003197478990000022
wherein, Index _ QYFBjIs the shared bicycle distribution index for region j; pjIs a regionj sharing the mileage proportion of the over-dense distribution road section of the single vehicle;
6-3) grading the area sharing single vehicle distribution indexes according to the area sharing single vehicle distribution index grading standard as follows:
the mileage proportion of the excessively dense road sections is [ 0%, 3%), the distribution index of the shared single-vehicle area is [0, 2%), and the distribution density degree of the shared single-vehicle area is sporadic distribution;
the mileage proportion of the excessively dense road sections is [ 3%, 6%), the distribution index of the shared single-vehicle area is [2, 4%), and the distribution density degree of the shared single-vehicle area is sparse distribution;
the mileage proportion of the excessively dense road sections is [ 6%, 9%), the distribution index of the shared single-vehicle area is [4, 6%), and the distribution density degree of the shared single-vehicle area is slightly dense;
the mileage proportion of the excessively dense road sections is [ 9%, 12%), the distribution index of the shared single-vehicle area is [6, 8%), and the distribution density degree of the shared single-vehicle area is moderately dense;
the mileage proportion of the excessively dense road section is 12 percent and infinity, the distribution index of the shared bicycle area is 8 and 10, and the distribution density degree of the shared bicycle area is excessively dense.
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