CN112533140B

CN112533140B - An index-based method for evaluating the distribution of shared bicycles

Info

Publication number: CN112533140B
Application number: CN202011332557.7A
Authority: CN
Inventors: 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
Original assignee: TIANJIN SAIYING ENGINEERING CONSTRUCTION CONSULTING MANAGEMENT CO LTD
Current assignee: Tianjin Municipal Engineering Design and Research Institute
Priority date: 2020-11-24
Filing date: 2020-11-24
Publication date: 2021-10-12
Anticipated expiration: 2040-11-24
Also published as: CN112533140A

Abstract

The invention discloses an index-based evaluation method for the distribution of shared bicycles, which collects travel data of shared bicycles in a selected evaluation area, and cleans the data; calculates the real-time position of shared bicycles; Matching; based on the number of shared bicycle sections and the length of the section, calculate the shared bicycle distribution density of the section; according to the functional relationship between the shared bicycle section distribution density and the distribution index, calculate the shared bicycle section distribution index and divide the shared bicycle section distribution level; The area is divided into regions, the regional distribution index of shared bicycles in the divided area is calculated, and the regional distribution level of shared bicycles is divided, so as to quantitatively evaluate the real-time distribution of shared bicycles. The invention has the characteristics of temporal and spatial universality, from the perspective of time, it can be calculated in real time or by using historical data; from the traffic in space, it is suitable for calculation in areas of any size of 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:

wherein i is a road section number; rho_iSharing the real-time distribution density of the single vehicle for the road section i; n is a radical of_iThe total number of the shared single-vehicle points on the road section i; l is_iIs 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:

wherein, Index _ LDFB_iThe shared bicycle distribution index of the road section i; rho_iThe 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:

wherein, Index _ QYFB_jIs the shared bicycle distribution index for region j; p_jSharing 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

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 section_iAnd a link length L_iWherein the total number N of the shared bicycle points_iThe 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 L_iIs 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:

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:

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 P_jThe 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:

wherein, Index _ QYFB_jIs the shared bicycle distribution index for region j; p_jAnd 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

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:

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:

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:

wherein, Index _ QYFB_jIs the shared bicycle distribution index for region j; p_jIs 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.