Method, system and product for measuring the accessibility of a charging station applied to a mountainous environment

Abstract

The present invention relates to a method, system and product for measuring the accessibility of charging stations applied to mountainous environments. The method for measuring the accessibility of charging stations applied to mountainous environments includes: S1. Construct a traffic topology of the mountainous environment and divide the traffic topology into I grid cells G 1 to G I ; the b th charging station is located in the j th grid cell G j ; S2. Collect the traffic road network information of the i th grid cell G i and G j , and calculate to obtain: slope information #imgabs0#, passability T ij , and the final cluster effect value C j . In view of the complex and changeable mountainous urban environment, the present invention comprehensively incorporates the slope factor into the accessibility calculation system, accurately considers the influence of different uphill and downhill on the accessibility calculation, and at the same time combines the cluster effect to comprehensively evaluate the multiple characteristics of charging stations in the region, providing a solid and powerful basis for the mountainous traffic planning department to formulate a scientific and reasonable traffic plan and for relevant enterprises to optimize the layout of charging stations.

Description

Technical Field

[0001] The present invention relates to the fields of transportation and geographic information technology, and in particular to a method for measuring the accessibility of charging stations in a mountainous environment, a system for measuring the accessibility of charging stations in a mountainous environment, and a computer program product. Background Art

[0002] In the fields of transportation and geographic information technology, spatial accessibility has always been a highly regarded research focus. With the advancement of urbanization, the transportation road network has been continuously expanded and densified, profoundly changing the spatio-temporal connections between different regions of the city. Reasonably measuring spatial accessibility is of great significance for optimizing the allocation of transportation resources and promoting regional balanced development. Especially in practical application scenarios such as transportation planning and commercial facility layout, accurate accessibility assessment can effectively guide the rational flow of resources and improve the operating efficiency of the city.

[0003] In traditional accessibility research, existing measurement methods mainly focus on the conventional road network. Currently, there is little or insufficient research on the accessibility of charging stations in mountainous cities, which may lead to difficulties for drivers in accurately judging the actual availability of target charging stations when planning trips in mountainous areas, greatly increasing the uncertainty of travel. Summary of the Invention

[0004] Based on this, in view of the problem that existing accessibility measurement methods do not study the charging stations in mountainous cities, it is necessary to provide a method, a system and a product for measuring the accessibility of charging stations in a mountainous environment.

[0005] In a first aspect, the present invention provides a method for measuring the accessibility of charging stations in a mountainous environment, which measures the accessibility of charging stations in a mountainous environment; it includes:

[0006] S1. Construct a traffic topological structure of the mountainous environment; wherein, the traffic topological structure includes: B charging stations;

[0007] Divide the traffic topological structure into I grid cells G 1 to G I ; the b th charging station is located in the j th grid cell G j ; b ∈ [1, B ; j ∈ [1, I ;

[0008] S2. Collect the i th grid cell G iand G j traffic road network information, and calculate to obtain: used to characterize G i to G j the slope information of the overall uphill and downhill distribution of the k th path between them 、used to characterize G i to G j the passability of the congestion degree between them T ij 、used to characterize G j the final cluster effect value of the cluster effect C j ; where i ∈[ 1, I ;

[0009] Then, according to 、 T ij 、 C j calculate G i to G j the reachability between them A ij ;

[0010] where A ij the calculation formula of is:

[0011]

[0012] In the formula, K is G i to G j the total number of paths between them, and k ∈[ 1, K ; is the weight coefficient; is the attenuation coefficient; is G i to G j the length of the k th path between them;

[0013] C j the calculation formula of is:

[0014]

[0015] In the formula, represents G i to G j the charging station cluster effect regarding available charging piles; represents G j the facility cluster effect regarding other surrounding facilities; x 1, x 2 respectively represent , the weight distribution of

[0016] The calculation formula of

[0017]

[0018] is as follows: s represents G i to G j the number of grid cells passed by the straight-line distance; l ∈[1, s ; g ( l ) represents the information increment coefficient; represents G j the number of available charging piles of the b th charging station on represents the number of available charging piles of the l th charging station within range around the h th grid cell; H represents l the total number of charging stations within range around the represents the control parameter;

[0019] The calculation formula of

[0020]

[0021] is as follows: T represents G j the number of other facility types around; r t represents the number of locations of the t th other facility; t ∈[1, T ; represents thet The weight of other facilities; Indicating the influencing parameter; c Indicating the comprehensive cost of charging;

[0022] S3. Traverse B each charging station to obtain the accessibility A i,1 and A i,2 and so on; A i,B ;

[0023] After normalizing A i,1 and A i,2 and so on; A i,B and then taking the average to obtain G i the final accessibility of A i ;

[0024] Traverse G from 1 to G I to obtain I the number of final accessibilities A 1, A 2, and so on; A I .

[0025] In a second aspect, the present invention further provides a charging station accessibility measurement system applied to a mountainous environment, which uses the charging station accessibility measurement method applied to a mountainous environment in the first aspect; the charging station accessibility measurement system applied to a mountainous environment includes:

[0026] A generation module, which is used to construct the traffic topology of the mountainous environment and divide the traffic topology into I a number of grid cells G from 1 to G I ;

[0027] An acquisition module, which is used to acquire G i and G j traffic road network information to calculate and obtain , T ij , C j ; and according to , T ij , C jCalculation G i to G j reachability between A ij ;

[0028] A measurement module, which is used to traverse B charging stations to obtain reachable A i,1 , A i,2 ,…, A i,B ; Then normalize A i,1 , A i,2 ,…, A i,B and then calculate the average to obtain G i the final reachability A i ; And traverse G 1 to G I to obtain I reachable A 1, A 2,…, A I .

[0029] In a third aspect, the present invention also provides a computer program product, including computer programs / instructions, which, when executed by a processor, implement the steps of the method for measuring the reachability of charging stations applied to mountainous environments in the first aspect.

[0030] The beneficial effects of the present invention are as follows:

[0031] Aiming at the complex and changeable mountainous urban environment, the present invention comprehensively incorporates the slope factor into the reachability calculation system, accurately considers the impact of different uphill and downhill on reachability calculation, and at the same time combines the cluster effect to comprehensively evaluate the diverse characteristics of charging stations in the region, including the number of charging stations around the charging station node, the distribution data of catering and leisure, and the cost, etc., so as to calculate the reachability score of each charging station, thereby providing a reference for drivers to select charging stations at any node, and providing a solid and powerful basis for mountainous traffic planning departments to formulate scientific and reasonable traffic plans and relevant enterprises to optimize the layout of charging stations. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0033] Figure 1 It is a flowchart of the method for measuring the accessibility of charging stations applied to mountainous environments in Embodiment 1;

[0034] Figure 2 It is the current heat map of the accessibility of charging stations in the research area;

[0035] Figure 3 It is the heat map of the accessibility of charging stations after the layout optimization of charging stations in the research area. Detailed implementation manners

[0036] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs. The terms used in the description of the present invention herein are only for the purpose of describing specific embodiments, and are not intended to limit the present invention. The term "or / and" used herein includes any and all combinations of one or more of the related listed items.

[0038] Embodiment 1

[0039] The technical personnel in this case found that especially for mountainous cities, such as Chongqing, its terrain is complex, the slope changes frequently and significantly. During driving, for uphill, the new energy vehicle overcomes the resistance and rises, which will significantly increase the energy consumption and thus affect the cruising range. For downhill, although the new energy vehicle will reduce part of the energy consumption, the driver will be more cautious about driving on downhill sections and frequently brake, which will have a negative impact on the speed. For flat roads, it is a normal situation. At the same time, the diverse characteristics of charging stations in the region, such as the number of charging stations around the charging station nodes, the distribution data of catering and leisure, and the cost, etc., will also have a comprehensive impact on the accessibility of charging stations. However, the existing methods for measuring charging stations mainly focus on conventional factors such as distance, time, and selected paths, but ignore the influence of many complex real-world conditions.

[0040] Based on the above findings, the technical personnel in this case provided a method for measuring the accessibility of charging stations applicable to mountainous environments. This method combines the complex environment of mountain cities and the clustering effect of charging stations, can describe the accessibility of charging stations in the complex and changeable mountain environment, provide a reference for drivers to select charging stations at any node, and provide a solid and powerful basis for traffic planning departments in mountain cities to formulate scientific and reasonable traffic plans and relevant enterprises to optimize the layout of charging stations.

[0041] Specifically, as Figure 1 shown, the method for measuring the accessibility of charging stations applicable to mountainous environments provided in this embodiment makes up for the deficiency of not considering slope information in the measurement of charging station accessibility. At the same time, considering the charging station clustering effect, the surrounding clustering effect of the charging station and the passability between nodes, the complex and qualitative charging station accessibility is calculated according to the following steps:

[0042] S1. Construct the traffic topological structure of the mountainous environment; where the traffic topological structure includes: B charging stations. Divide the traffic topological structure into I grid cells G 1 to G I ; the b th charging station is located on G j ; b ∈[1, B ; j ∈[1, I .

[0043] In this step, GIS software can be used to perform topological construction on traffic road network data by using spatial analysis tools. By accurately identifying the connection relationships and spatial positions of various elements in the road network, the complex traffic road network is transformed into a rigorous traffic topological structure. Subsequently, according to the set spatial scale, the traffic topological structure containing traffic road network data is divided into I identical-sized G 1 to G I . Using the data binding function of GIS software, each grid cell becomes an information carrier, and slope data, charging station information, other facility information, etc. are accurately entered to achieve the multi-dimensional data expression of the traffic road network. It should be noted that the corresponding relationship between the charging station location and the grid cell: According to the traffic road network data, the actual location of the charging station is known. During the process of dividing the grid cells, the charging station is mapped to one of the corresponding grid cells according to the actual location. If there are multiple charging stations, they are synchronously mapped to the corresponding grid cells.

[0044] S2. Based on the traffic topology structure constructed in S1 and the traffic road network information carried by the grid cells, it is necessary to calculate: to characterize G i to G j the slope information of the overall uphill and downhill distribution of the k th path , to characterize G i to G j the passability indicating the congestion level between T ij , to characterize G j the final cluster effect value indicating the cluster effect C j ; where i ∈[1, I .

[0045] Next, the calculation processes for , T ij , C j will be described one by one.

[0046] (1) Calculation process of slope information

[0047] According to the types of slopes of the G i to G j th path, different weights are assigned, and combined with the path length, after weighted averaging, k is obtained to reflect the overall slope situation of the th path, providing basic parameters for traffic network related analysis. Among them, the types of slopes include uphill, flat road, and downhill. k The calculation formula of is:

[0048] .

[0049] In the formula, p k represents an indicator variable. S k represents the average slope of the k th path. When S k is uphill, that is, S k > 0, p k = 1. When S kWhen it is downhill, i.e., S k <0, p k = -1. When S k it is flat road, i.e., S k = 0, p k = 0. represents G i from G j to k the length of the K th G i path between G j and k ∈ [1, K . The numerator in the formula is given different weights according to different slope types, so as to obtain an index comprehensively reflecting the uphill and downhill conditions of the k th path.

[0050] Among them, S k can be calculated by the following method:

[0051] First, divide the k th path into L segments at intervals of Δ N distance. Then calculate the height difference Δ n between the two ends of the H n th segment. Among them, n ∈ [1, N . Then, divide Δ H n by Δ L to represent the slope of the n th segment. Finally, average S 1, S 2,..., S N to get S k . Its S k calculation formula is:

[0052] .

[0053] (2) Passability T ij calculation process

[0054] To avoid large-scale congestion caused by everyone using the shortest path, rendering the reachability calculation worthless, it is necessary to consider G i to G j the probability of selecting the k th path , and then calculate and to calculate T ij . Among them, the process of calculating includes: first adding the reciprocals of , , after weighting to obtain G i to G j the comprehensive weight parameter of selecting the k th path , and then calculate to obtain , and its calculation formula is:

[0055] .

[0056] .

[0057] In the formula, w 1,[[]]END]] w 2 and w 3 are the weights of , and respectively, and ([[]]END]] w 1 + w 2 + w 3 = 1). represents G i to G j the traffic flow information of the k th path represents the adjustment parameter, which is a very small positive number to avoid the denominator being 0. exp represents the natural exponential function represents the constant parameter

[0058] Combining and to calculate T ij , and its calculation formula is:

[0059] .

[0060] In the formula, Indicates the influence coefficient on path selection, and its value > 0.

[0061] (3)Calculation process of the final cluster effect value C j

[0062] The cluster effect of the target charging station is considered. In this embodiment, the cluster effect is further divided into the charging station cluster effect regarding the charging situation of the charging station , and the facility cluster effect regarding the distribution of other facilities . Other facilities include places such as restaurants, entertainment venues, and hospitals. Subsequently, , are comprehensively considered to calculate C j .

[0063] Specifically, related to the charging stations within the range between G i and G j , and its calculation formula is:

[0064] .

[0065] In the formula, s represents G i to G j the number of grid cells passed by the straight-line distance. l ∈[1, s . G represents b j the number of available charging piles of the th charging station on l . represents the number of available charging piles of the h th charging station within the range around the H th grid cell. l represents the total number of charging stations within the range around the th grid cell. g ( l ) represents the information increment coefficient; represents the control parameter, and it is a positive number. By controls the influence of distance on , and it means that the closer to G j , the greater the reference value of the charging station cluster effect obtained at the l th grid cell.​​​

[0066] Suppose G j There are T types of other facilities within the set range. For the t th type of other facility, the number of locations is r t . Then The calculation formula of

[0067] .

[0068] In the formula, represents the weight of the t th type of other facility and satisfies . c represents the comprehensive cost of charging. Among them, c 1 represents the electricity price of the charging station, c 2 represents the parking fee during queuing for charging. represents the influence parameter and is a positive number used to adjust c the influence degree of on

[0069] Finally, considering the comprehensive influence of and , we get C j , and its calculation formula is:

[0070] .

[0071] In the formula, x 1 and x 2 respectively represent and 's weight distribution.

[0072] Based on the above analysis, according to the obtained and T ij and C j Calculate the accessibility between G i and G j . Its calculation formula is: A ij . The formula is:

[0073]

[0074] In the formula, is the weight coefficient and is a positive number used to adjust 's influence degree on A ij . is the attenuation coefficient, and it is between 0 and 1, used to reflect the A ij influence degree.

[0075] S3. After calculating A ij , it is also necessary to calculate I grid cells G 1 to G I final accessibility A i , so as to facilitate the driver to obtain the optimal accessible charging station location at any position in the research area and provide a basis for optimizing the charging station layout.

[0076] Specifically, following the process of S2, with G i unchanged, traverse B charging stations to obtain the accessibility A i,1 , A i,2 , …, A i,B . Then perform normalization to obtain G i to the b normalized value of the th charging station

[0077] .

[0078] In the formula, A i,max represents A i,1 , A i,2 , …, A i,B the maximum value in A i,min represents A i,1 , A i,2 , …, A i,B the minimum value in

[0079] The B normalized values are averaged to obtain G i final accessibility A i . Finally, traverse G 1 toG I , obtain I the final accessibility A 1. A 2. …, A I , that is, each grid cell corresponds to a numerical value of the final accessibility.

[0080] Based on the numerical value of the final accessibility, when a driver plans a journey in a mountainous city, he can more accurately select a charging station according to the charging station accessibility measurement result of the present invention, reducing travel uncertainty. The mountain traffic planning department can also formulate a more scientific and reasonable traffic plan based on this. When relevant enterprises optimize the layout of charging stations, they have a solid basis, thereby improving the efficiency of resource allocation and promoting the healthy development of the new energy vehicle industry and transportation facilities construction in mountainous areas.

[0081] Embodiment 2

[0082] Based on the solution of Embodiment 1, this embodiment provides a visualization method for the accessibility of charging stations applied to mountainous environments, which includes:

[0083] First, obtain the final accessibility according to the charging station accessibility measurement method applied to mountainous environments in Embodiment 1 A 1. A 2. …, A I . Then, use visualization software according to A 1. A 2. …, A I Generate a heat map of the accessibility of charging stations. Among them, the heat map of the accessibility of charging stations is marked with the positions of charging station nodes (i.e., the grid cells occupied by charging stations), and the numerical value of the final accessibility is reflected by the depth of color or the size of the charging station nodes.

[0084] Verify the method in Embodiment 1 through the generated heat map of the accessibility of charging stations. As Figure 2 shown, the research area is Jiulongpo District, Chongqing. Based on the actual geographical space as the basic framework, the grid cells occupied by charging stations are marked according to the actual geographical positions, and the numerical value of the final accessibility is reflected by the color change of the grid cells. It can be seen from Figure 2 that the final accessibility of some areas is relatively low, only between 0 and 0.2. Accordingly, the problem of low accessibility of charging stations can be solved by optimizing the layout of charging stations and increasing the number of charging stations in areas with low accessibility. As Figure 3 shown, the three added charging stations are represented by red icons. It can be found that after optimizing the layout of charging stations, the overall final accessibility in the research area has increased, which is beneficial for drivers to select charging stations.

[0085] Example 3

[0086] Based on Example 1, this example also provides a charging station accessibility measurement system applied to mountainous environments, which adopts the charging station accessibility measurement method applied to mountainous environments in Example 1. The charging station accessibility measurement system applied to mountainous environments includes: a generation module, a collection module, and a measurement module.

[0087] Among them, the generation module is used to construct the traffic topology of the mountainous environment and divide the traffic topology into I grid cells G 1 to G I . The collection module is used to collect G i and G j traffic road network information to calculate , T ij , C j , and calculate the accessibility between , T ij , C j according to G i to G j . The measurement module is used to traverse A ij charging stations to obtain the accessibility B , A i,1 , A i,2 , …, A i,B , and then normalize A i,1 , A i,2 , …, A i,B and then average to obtain the final accessibility G i , and traverse A i 1 to G 1 to G I to obtain I final accessibilities A 1, A 2, …, A I .

[0088] Example 4

[0089] This embodiment also provides a computer program product, including computer programs / instructions. When the computer programs / instructions are executed by a processor, the steps of the method for measuring the accessibility of charging stations applied to mountainous environments in Embodiment 1 are implemented.

[0090] The technical features of the above-described embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0091] The above-described embodiments only represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the invention patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention patent shall be subject to the appended claims.

Claims

1. A method for measuring the accessibility of a charging station applied to a mountainous environment, characterized in that, It measures the accessibility of charging stations in mountainous environments; It includes: S1. Construct the traffic topology of the mountainous environment; among them, the traffic topology includes: B charging stations; Divide the traffic topology into I grid cells G 1 to G I ; The b th charging station is located in the j th grid cell G j ; b ∈ [1, B ; j ∈ [1, I ; S2. Collect the i th grid cell G i and G j traffic road network information, and calculate to obtain: used to characterize G i to G j the slope information of the overall uphill and downhill distribution of the k th path, used to characterize G i to G j the passability indicating the congestion degree, T ij used to characterize G j the final cluster effect value indicating the cluster effect; C j wherein, i ∈ [1, I ; Then, according to , T ij , C j calculate G i the reachability between G j ; A ij ​ Among them, A ij The calculation formula is: ， In the formula, K is G i to G j the total number of paths between them, and k ∈ [1, K ; is the weight coefficient; is the attenuation coefficient; is G i to G j the length of the k th path between them; C j The calculation formula is as follows: ， In the formula, represents G i to G j the charging station cluster effect regarding available charging piles; represents regarding G j the facility cluster effect of other surrounding facilities; x 1, x 2 respectively represent , the weight distributions of The calculation formula is as follows: ， In the formula, s represents G i to G j the number of grid cells on the straight-line distance path; l ∈[1, s ; g () represents the information volume increment coefficient; l represents G j the number of available charging piles at the b th charging station; represents the number of available charging piles at the l th charging station within the range around the h th grid cell; H represents the total number of charging stations within the l th grid cell within the range; represents the control parameter;​ The calculation formula is as follows: ， In the formula, T represents G j the quantity of other types of facilities around; r t represents the number of places of the t th other type of facility; t ∈ [1, T ; represents the weight of the t th other type of facility; represents the influence parameter; c represents the comprehensive cost spent on charging; S3. Traverse B charging stations to obtain reachability A i,1 , A i,2 , …, A i,B ; After A i,1 , A i,2 , …, A i,B are normalized and then averaged, the final reachability of G i is obtained A i ; Traverse G 1 to G I , obtain I final reachabilities A 1. A 2, …, A I .

2. The method for measuring the accessibility of a charging station applied to a mountainous environment according to claim 1, wherein In S2, The calculation formula is: ， In the formula, p k represents an indication variable; S k represents the average slope of the k th path; when S k is an uphill, p k = 1; when S k is a downhill, p k = -1; when S k is a flat road, p k = 0.

3. The method for measuring the accessibility of a charging station applied to a mountainous environment according to claim 2, wherein, S k The calculation formula is as follows: ， In the formula, N represents the total number of segments after equally dividing the k th path; n ∈[1, N ; Δ H n represents the height difference between the two ends of the n th segment path; Δ L represents the length of the n th segment path.

4. The method for measuring the accessibility of a charging station applied to a mountainous environment according to claim 1, wherein In S2, T ij The calculation formula is: ， Wherein, represents G i to G j the probability of selecting the k th path; exp represents the natural exponential function; represents a constant parameter; represents G i to G j the comprehensive weight parameter of selecting the k th path; represents the influence coefficient.

5. The method for measuring the accessibility of a charging station applied to a mountainous environment according to claim 4, characterized in that The calculation method is as follows: ， Wherein, w 1, w 2, and w 3 are respectively , , and 's weights; represents G i to G j the traffic flow information of the k th path; represents the adjustment parameter.

6. The method for measuring the accessibility of a charging station applied to a mountainous environment according to claim 1, wherein In S3, A 1, A 2, …, A I are visually processed to obtain the heat map of the accessibility of charging stations.

7. A charging station accessibility measurement system applied to mountainous environments, characterized in that, It uses the method for measuring the accessibility of charging stations in mountainous environments as described in any one of claims 1 to 6; It includes: A generation module, which is used to construct a traffic topology structure of a mountainous environment and divide the traffic topology structure into I grid cells G 1 to G I ; A collection module, which is used to collect G i and G j traffic road network information to calculate 、 T ij 、 C j ; and calculate the reachability between 、 T ij 、 C j according to G i to G j ; A ij ; A measurement module for traversing B charging stations to obtain reachability A i,1 , A i,2 …, A i,B ; Then A i,1 , A i,2 …, A i,B after normalization, and then calculate the average to obtain G i the final reachability A i ; And traverse G 1 to G I to obtain I the number of final reachabilities A 1, A 2, …, A I .

8. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by a processor, the steps of the method for measuring the accessibility of charging stations in mountainous environments as described in any one of claims 1 to 6 are implemented.

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