CN110458309B - Network about splicing station point location method based on actual road network environment - Google Patents
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Abstract
The invention discloses a network approximately spliced station point location method based on an actual road network environment, which comprises the following steps: (1) Grouping the passenger reservation demand points by using a K-means clustering method, and determining a clustering center of each grouping; (2) Each group determines a corresponding road network analysis area according to the space positions of the passenger demand points and the clustering center; (3) Taking any one road section according to the road network analysis area corresponding to any group, and calculating road section division points corresponding to all passenger demand points of the group; (4) Calculating the sum of the shortest distances from all passenger demand points in the road network analysis area to the spelling station points by taking the position of the spelling station points on the road section as a variable to determine the optimal station position aiming at the road section; (5) Repeating the operation on other road sections in the road network analysis area, and comparing the sum of the shortest distances of the road sections to determine the road section and the position of the optimal station. The method provides reference and selection basis for reasonable layout of carpooling stations in real life.
Description
Technical Field
The invention belongs to the field of public transportation in transportation planning and management, and particularly relates to a network pinch station point location method based on an actual road network environment.
Background
As a representative of the "internet+shared economy", the "carpool" is considered as an improved travel mode of public transportation service, and can play a role in replacement in urban public transportation service blind areas. The existing network car sharing adopts a free car sharing mode at any place, and when passengers are positioned more or a plurality of passengers need to be carried, the network car sharing has larger bypassing distance and longer waiting time of the passengers, so that the travel of the users cannot be guaranteed.
The station carpool is firstly issued by a drip company, and the main purpose is to reduce the detour mileage generated by the connection of the carpools in the existing network carpool service, and the establishment of the carpool station allows the vehicle to carry a plurality of passengers at the same place without increasing extra parking times. At present, the development of the station carpooling in China is still in a preliminary exploration stage, and the study on the problem of site selection of the carpooling station is relatively lacking. However, in real life, reasonable station point location has stronger realistic meaning to the aspects of improving the car matching rate, enhancing the user experience sense, promoting the sustainable development of the car sharing industry and the like. In addition, the actual road network environment is considered when the station is spliced for site selection, so that the site selection result is closer to the actual situation and is easy to implement.
Therefore, it is necessary to design a network about station sharing site selection method based on an actual road network environment to reasonably arrange the station sharing sites, and corresponding references are provided for the development of the current station sharing vehicles.
Disclosure of Invention
The invention provides a network approximately spliced station point site selection method based on an actual road environment, which can meet the requirements of passengers in an actual road network, minimize the walking distance of the passengers and has ingenious and reasonable conception.
In order to solve the technical problems, the network approximately spliced station site selection method based on the actual road network environment comprises the following steps:
(1) Grouping the passenger reservation demand points by using a K-means clustering method, and determining a clustering center of each grouping;
(2) Determining an actual road network analysis area corresponding to each group according to the space positions of the demand points of each group passenger and the clustering center;
(3) Road network analysis zone Z i Any road section [ v ] a ,v b ]Calculating the road section [ v ] corresponding to all the passenger demand points of the group a ,v b ]Dividing points;
(4) For road segments [ v ] possibly existing a ,v b ]The method comprises the steps of calculating the shortest path distance from all passenger demand points to a station x in an analysis area at a carpooling station x, and summing the distances to determine the optimal station position for the road section;
(5) Analysis zone Z of road network i Repeating the operations of the step (3) and the step (4) on other road sections, comparing the sum of the shortest distances of the road sections, and determining the road section and the position of the optimal station.
Further, in the present invention, in the step (1), the specific step of determining the number of the cluster center points is:
(11) Collecting the space position coordinate information of the passenger reservation demand point, comprising: longitude and latitude coordinates of the get-on point and the get-off point;
(12) Based on a K-means clustering algorithm, when the clustering center is K, calculating all passenger demand points in each clustering range and corresponding clustering centers K i Is the Euclidean distance of (1) taking the maximum value of the distance
(13) For each clustering center range, taking the spliced station point service radius R as a constraint, and judging the maximum distance value calculated in the step (12)
Whether or not it is greater than R. If not, the step (14) is skipped, and the corresponding K value is the number of the clustering center points.
(14) Taking k=k+1, and repeating the step (12) and the step (13).
Further, in the present invention, in step (13), the splice station point service radius determining method is as follows:
the station service radius R is the maximum walking range of passengers, 500m is taken, and the station service range is a circular area range which takes the cluster center as the center and takes R as the radius to radiate outwards.
Further, in the step (2), the method for determining the actual road network analysis area corresponding to each packet is as follows:
setting UNIT as the minimum closed polygon which can be formed by the road network nodes and as the minimum road network UNIT;
the road network analysis area is the minimum actual road network area containing all passenger demand points in a clustering range;
(21) For a cluster range K i Judging the passenger demand point in the network UNIT, if it is in the network UNIT or at the boundary, recording the node n contained in the UNIT i (including vertex) and segment e i (including boundary) Road segments can also be represented by their endpoints, e.g. road segments v 1 ,v 2 ]；
(22) Obtaining the cluster containing range K i Node set N of all demand points in i ＝{n 1 ,n 2 ,n 3 … and road segment set E i ＝{e 1 ,e 2 ,e 3 …}；
(23) Road network analysis zone Z i Z can be represented by graph theory method i ＝(N i ，E i )。
Further, in the present invention, in the step (3), the road segment division point determining method corresponding to the passenger demand point is as follows:
description: the shortest distance adopts an actual network distance instead of the Euclidean distance;
v a and v b Representing two end points of a road section, the length of the road section can be [ v ] a ,v b ]A representation; p is p i And p j For shortest path between
A representation; if p i And p j The shortest path point v between a Sum point v b Then p i And p j The shortest path between them is available
A representation;
(31) From the above step (23), a road network analysis zone Z i Contains node number N i Road segment number E i The set of the passenger demand points is P i ＝{p 1 ,p 2 ,p 3 …}；
(32) For road section [ v a ,v b ]([v a ,v b ]∈E i ) At the passenger demand point p i (p i ∈P i ) Starting from the road segments [ v ] a ,v b ]Two end points v of (2) a And v b As the end point, the Dijkstra algorithm is used to calculate the shortest path distance respectively, which is recorded as
And
(33) At p i 、v a 、v b Is the vertex of triangle, to
[v a ,v b ]，/>
For triangle side, find road segment [ v ] using triangle inequality relation a ,v b ]Is defined by the dividing points of the pair.
Further, in the present invention, in step (33), the triangle inequality relationship is used to find the road section [ v ] a ,v b ]The specific steps are as follows:
(331) In triangle p i v a v b The following relationship holds:
then for the passenger demand point p i For the road section [ v ] a ,v b ]There is a dividing point es pi So that
(332) Dividing points es pi In road section [ v ] a ,v b ]Available segmentation points es for positions on pi And v a The distance of the road section [ v ] a ,v b ]Ratio of total length
(hereinafter referred to as a division point es) pi Road segment [ v ] a ,v b ]Duty cycle). Wherein->
Corresponding road segment origin v a ，/>
Corresponding road segment end v b 。
Let the road distance distribution function be
Representing the distance between point i and point j on the road segment;
dividing points es pi The position calculation formula of (2) is as follows:
dividing points es pi Distance segment origin v a The distance calculation formula of (2) is as follows:
[v a ,v b ]road section [ v ] a ,v b ]Is a length of (2);
(334) Set of demand points for passengers P i All the objects in the map can be found to correspond to the road segment v a ,v b ]The set of division points on the upper part is
Further, in the present invention, in the step (4), for the road section [ v ] which may exist a ,v b ]The shortest path distance from all passenger demand points to the station x in the analysis area is calculated, and the distances are summed to determine the optimal station position for the road section, and the specific steps are as follows:
initializing, shortest distance set
(41) Get the road section [ v ] a ,v b ]Any point x is taken as a spelling station point, and a road section v of the station x is set a ,v b ]The duty ratio is theta;
(42) As described in connection with step (32) and step (333), it is known that when
At this time, the passenger demand point p i Shortest to site x must go through start point v a The shortest length is denoted +.>
When (when)
At this time, the passenger demand point p i The shortest path to site x must be via endpoint v b The shortest path length is
From the passenger demand point p i The shortest path distance to site x can be expressed as a linear piecewise function,
(43) Road network analysis zone Z i Set of all passenger demand points P in i Repeating the operation of step (42) for the object to calculate P i The shortest path distance from each object to the site, the result is stored in the set D θ [v a ,v b ]In (a) is marked as
(44) Summing the elements in the distance set, denoted as Σd θ [v a ,v b ]；
Further, in the present invention, in the step (5), the road network analysis zone Z i Repeating the operations of the step (3) and the step (4) on other road sections, comparing the sum of the shortest distances of the road sections, and determining the road section and the position of the optimal station, wherein the method comprises the following specific steps:
initializing, distance and collection
And minimum distance set->
(51) Analysis zone Z of road network i Road segment set E i Repeating the steps (3) and (4) for the road segment [ v ] a ,v b ]Respectively sum the distancesThe resulting value is stored in set D, then d= { Σd θ [e 1 ],∑D θ [e 2 ],∑D θ [e 3 ]…}
(52) Sd (e) 1 )＝min∑D θ [e 1 ]Calculating Sigma D θ [e 1 ]And record sd (e) 1 ) A value and a corresponding θ value;
(53) Likewise, similar to road segment e 1 Respectively, the minimum values of all elements in the set D are calculated, and the result is stored in the set sd, i.e., sd= { sd (e 1 ),sd(e 2 ),sd(e 3 ),sd(e 4 ) …, and recording the respective corresponding θ values;
(54) Comparing all elements in the set sd, wherein the road section and theta value corresponding to the minimum element value are the road network analysis zone Z i The optimal road section and the optimal position of the middle carpooling station x.
Compared with the prior art, the technical scheme of the invention has the following beneficial effects:
1. the invention can reasonably arrange the station sharing points based on the passenger reservation demand data, fills the blank of the network reservation station sharing point location method, and provides corresponding reference and method support for the station location layer in the current station car sharing service.
2. The spliced station point location method provided by the invention is based on a real road network environment, the defect of the traditional subjective setting and adjusting method of artificial experience is overcome, and the scientificity, accuracy, rationality and effectiveness of spliced station point layout are ensured.
3. According to the invention, the spliced station point positions of any road section are optimized based on the road section dividing points, and the final road section and the position of the optimal station are determined by comparing the results of all road sections, so that the method is reasonable and easy to calculate.
Drawings
Fig. 1 is a flow chart of the present invention.
Fig. 2 is a diagram of an actual road network structure according to the present invention.
FIG. 3 is a road network analysis zone Z according to the present invention 2 。
Detailed Description
The technical scheme of the invention is further described in detail below with reference to the attached drawings and examples.
Example 1: referring to fig. 1, a network about spelling station point location method based on actual road network environment comprises the following steps:
(1) Grouping the passenger reservation demand points by using a K-means clustering method, and determining a clustering center of each grouping;
(2) Determining an actual road network analysis area corresponding to each group according to the space positions of the demand points of each group passenger and the clustering center;
(3) Road network analysis zone Z i Any road section [ v ] a ,v b ]Calculating the road section [ v ] corresponding to all the passenger demand points of the group a ,v b ]Dividing points;
(4) For road segments [ v ] possibly existing a ,v b ]The method comprises the steps of calculating the shortest path distance from all passenger demand points to a station x in an analysis area at a carpooling station x, and summing the distances to determine the optimal station position for the road section;
(5) Analysis zone Z of road network i Repeating the operations of the step (3) and the step (4) on other road sections, comparing the sum of the shortest distances of the road sections, and determining the road section and the position of the optimal station.
Further, in the present invention, in the step (1), the specific step of determining the number of the cluster center points is:
(11) Collecting the space position coordinate information of the passenger reservation demand point, comprising: longitude and latitude coordinates of the get-on point and the get-off point;
(12) Based on a K-means clustering algorithm, when the clustering center is K, calculating all passenger demand points in each clustering range and corresponding clustering centers K i Is the Euclidean distance of (1) taking the maximum value of the distance
(13) For each clustering center range, taking the spliced station point service radius R as a constraint, and judging the maximum distance value calculated in the step (12)
Whether or not it is greater than R. If not, the step (14) is skipped, and the corresponding K value is the number of the clustering center points.
(14) Taking k=k+1, and repeating the step (12) and the step (13).
In the step (13), the splice station point service radius determining method comprises the following steps:
the station service radius R is the maximum walking range of passengers, 500m is taken, and the station service range is a circular area range which takes the cluster center as the center and takes R as the radius to radiate outwards.
In the step (2), the method for determining the actual road network analysis area corresponding to each packet is as follows:
setting UNIT as the minimum closed polygon which can be formed by the road network nodes and as the minimum road network UNIT;
the road network analysis area is the minimum actual road network area containing all passenger demand points in a clustering range;
(21) For a cluster range K i Judging the passenger demand point in the network UNIT, if it is in the network UNIT or at the boundary, recording the node n contained in the UNIT i (including vertex) and segment e i (including boundaries), a road segment may also be represented by its end points, e.g., road segment v 1 ,v 2 ]；
(22) Obtaining the cluster containing range K i Node set N of all demand points in i ＝{n 1 ,n 2 ,n 3 … and road segment set E i ＝{e 1 ,e 2 ,e 3 …}；
(23) Road network analysis zone Z i Z can be represented by graph theory method i ＝(N i ，E i )。
In the step (3), the method for determining the road segment division point corresponding to the passenger demand point comprises the following steps:
description: the shortest distance adopts an actual network distance instead of the Euclidean distance;
v a and v b Representing two end points of a road section, the length of the road section can be [ v ] a ,v b ]A representation; p is p i And p j For shortest path between
A representation; if p i And p j The shortest path point v between a Sum point v b Then p i And p j The shortest path between them is available
A representation;
(31) From the above step (23), a road network analysis zone Z i Contains node number N i Road segment number E i The set of the passenger demand points is P i ＝{p 1 ,p 2 ,p 3 …}；
(32) For road section [ v a ,v b ]([v a ,v b ]∈E i ) At the passenger demand point p i (p i ∈P i ) Starting from the road segments [ v ] a ,v b ]Two end points v of (2) a And v b As the end point, the Dijkstra algorithm is used to calculate the shortest path distance respectively, which is recorded as
And
(33) At p i 、v a 、v b Is the vertex of triangle, to
[v a ,v b ]，/>
For triangle side, find road segment [ v ] using triangle inequality relation a ,v b ]Is defined by the dividing points of the pair.
In the present invention, in step (33), the triangle inequality relationship is used to find the road segment [ v ] a ,v b ]The specific steps are as follows:
(331) In triangle p i v a v b The following relationship holds:
then for the passenger demand point p i For the road section [ v ] a ,v b ]There is a dividing point es pi So that
(332) Dividing points es pi In road section [ v ] a ,v b ]Available segmentation points es for positions on pi And v a The distance of the road section [ v ] a ,v b ]Ratio of total length
(hereinafter referred to as a division point es) pi Road segment [ v ] a ,v b ]Duty cycle). Wherein->
Corresponding road segment origin v a ，/>
Corresponding road segment end v b 。
Let the road distance distribution function be
Representing the distance between point i and point j on the road segment;
dividing points es pi The position calculation formula of (2) is as follows:
dividing points es pi Distance segment origin v a The distance calculation formula of (2) is as follows:
[v a ,v b ]road section [ v ] a ,v b ]Is a length of (2);
(334) Set of demand points for passengers P i All the objects in the map can be found to correspond to the road segment v a ,v b ]The set of division points on the upper part is
In the present invention, in the step (4), for the road section [ v ] which may exist a ,v b ]The shortest path distance from all passenger demand points to the station x in the analysis area is calculated, and the distances are summed to determine the optimal station position for the road section, and the specific steps are as follows:
initializing, shortest distance set
(41) Get the road section [ v ] a ,v b ]Any point x is taken as a spelling station point, and a road section v of the station x is set a ,v b ]The duty ratio is theta;
(42) As described in connection with step (32) and step (333), it is known that when
At this time, the passenger demand point p i Shortest to site x must go through start point v a The shortest length is denoted +.>
When (when)
At this time, the passenger demand point p i The shortest path to site x must be via endpoint v b The shortest path length is
From the passenger demand point p i The shortest path distance to site x can be expressed as a linear piecewise function,
(43) Road network analysis zone Z i Set of all passenger demand points P in i Repeating the operation of step (42) for the object to calculate P i The shortest path distance from each object to the site, the result is stored in the set D θ [v a ,v b ]In (a) is marked as
(44) Summing the elements in the distance set, denoted as Σd θ [v a ,v b ]；
Further, in the present invention, in the step (5), the road network analysis zone Z i Repeating the operations of the step (3) and the step (4) on other road sections, comparing the sum of the shortest distances of the road sections, and determining the road section and the position of the optimal station, wherein the method comprises the following specific steps:
initializing, distance and collection
And minimum distance set->
(51) Analysis zone Z of road network i Road segment set E i Repeating the steps (3) and (4) for the road segment [ v ] a ,v b ]Respectively, the values obtained by summing the distances are stored in the set D, then d= { Σd θ [e 1 ],∑D θ [e 2 ],∑D θ [e 3 ]…}
(52) Sd (e) 1 )＝min∑D θ [e 1 ]Calculating Sigma D θ [e 1 ]And record sd (e) 1 ) A value and a corresponding θ value;
(53) Likewise, similar to road segment e 1 Respectively, the minimum values of all elements in the set D are calculated, and the result is stored in the set sd, i.e., sd= { sd (e 1 ),sd(e 2 ),sd(e 3 ),sd(e 4 ) …, and recording the respective corresponding θ values;
(54) Comparing all elements in the set sd, wherein the road section and theta value corresponding to the minimum element value are the road network analysis zone Z i The optimal road section and the optimal position of the middle carpooling station x.
Application example 1: referring to fig. 1-3, a network about spelling station point location method based on actual road network environment comprises the following steps:
(1) And grouping the passenger reservation demand points by using a K-means clustering method, and determining a clustering center of each grouping. In this embodiment, a part of the real road network is selected, and as shown in fig. 2, the road network includes 11 nodes and 19 road segments. And randomly generating a passenger carpooling reservation demand point on the road network. The number of clustering centers can be 3 and the numbers are respectively K through the constraint of the maximum walking distance range of the passengers by adopting a K-means clustering method 1 、K 2 、K 3 。
(2) And determining an actual road network analysis area corresponding to each group according to the space positions of the demand points of each group passenger and the clustering center. Here and the following are all in a cluster center K 2 For purposes of illustration, other cluster regions operate similarly. By aligning cluster centers K 2 The demand point within the range (numbered p 1 、p 2 、p 3 ) Judging the range of the existing road network, and determining the corresponding road network analysis zone as Z 2 As shown in fig. 3. Road network analysis zone Z 2 The node set N is included 2 And road segment set E 2 Respectively N 2 ＝{V5,V4,V6,V7]，E 2 ＝{[V5,V4],[V4,V6],[V6,V7],[V5,V6],[V5,V7]}。
(3) Road network analysis zone Z 2 Any one of the road segments [ V5, V6]]And calculating the road section [ V5, V6 division points corresponding to all the passenger demand points of the group. Analysis zone Z 2 The weights of the road sections are [ V5, V4 ]]＝6，[V4,V6]＝7，[V6,V7]＝4，[V5,V6]＝7，[V5,V7]=5. Passenger demand point p 1 、p 2 、p 3 The positions on the road are [ V5, p1 ]]＝4,[V4,p2]＝3,[V5,p3]＝2。
Passenger demand point p 1 Corresponding road segments [ V5, V6]The segmentation points are calculated as follows:
similarly, the passenger demand point p can be calculated 2 And p 3 Corresponding road section[V5,V6]The dividing point is
(4) For a carpool station x that may exist on a road segment V5, V6, the shortest distance from all passenger demand points to station x in the analysis zone is calculated and the distances are summed to determine the optimal station location for that road segment. The shortest distance from each passenger demand point to station x can be expressed as
Summing the distances to obtain Σd θ [V5,V6]Is that
(5) Analysis zone Z of road network 2 Repeating the operations of the step (3) and the step (4) on other road sections, comparing the sum of the shortest distances of the road sections, and determining the road section and the position of the optimal station. For the piecewise function Sigma D θ [V5,V6]For the reason of sd ([ V5, V6)])＝min∑D θ [V5,V6]When θ=4/7, sd ([ V5, V6) can be obtained])＝13；
Similarly, sd ([ V5, V7 ])=19, sd ([ V4, V5 ])=15, sd ([ V4, V6 ])=18, sd ([ V6, V7 ])=18; thus, the set sd= {13,19,15,18}, the smallest element is 13, i.e. sd ([ V5, V6 ]);
in road network analysis zone Z 2 In the building, the most preferred site for the existence of the station point x is the road section [ V5, V6]]At a distance of 4/7 of the road length from the point V5.
Determining the optimal spelling station point position operation for other clustering center ranges is the same as the K 2 Similarly.
The above examples are only preferred embodiments of the present invention, it being noted that: it will be apparent to those skilled in the art that several modifications and equivalents can be made without departing from the principles of the invention, and such modifications and equivalents fall within the scope of the invention.
Claims (8)
1. The network about splicing station site selection method based on the actual road network environment is characterized by comprising the following steps of:
(1) Grouping the passenger reservation demand points by using a K-means clustering method, and determining a clustering center of each grouping;
(2) Determining an actual road network analysis area corresponding to each group according to the space positions of the demand points of each group passenger and the clustering center;
(3) Road network analysis zone Z i Any road section [ v ] a ,v b ]Calculating the road section [ v ] corresponding to all the passenger demand points of the group a ,v b ]Dividing points;
(4) For existing in road section v a ,v b ]The method comprises the steps of calculating the shortest path distance from all passenger demand points to a station x in an analysis area at a carpooling station x, and summing the distances to determine the optimal station position for the road section;
(5) Analysis zone Z of road network i Repeating the operations of the step (3) and the step (4) on other road sections, comparing the sum of the shortest distances of the road sections, and determining the road section and the position of the optimal station.
2. The method for selecting the site of the network approximately splicing station based on the actual road network environment according to claim 1, wherein the specific steps in the step (1) are as follows:
(11) Collecting the space position coordinate information of the passenger reservation demand point, comprising: longitude and latitude coordinates of the get-on point and the get-off point;
(12) Based on a K-means clustering algorithm, when the clustering center is K, calculating all passenger demand points in each clustering range and corresponding clustering centers K i Is the Euclidean distance of (1) taking the maximum value of the distance
(13) For each clustering center range, taking the spliced station point service radius R as a constraint, and judging the maximum distance value calculated in the step (12)
If not, skipping step (14), wherein the corresponding K value is the number of clustering center points;
(14) Taking k=k+1, and repeating the step (12) and the step (13).
3. The method for selecting the network approximately spliced station points based on the actual road network environment according to claim 2, wherein the step (13) uses the spliced station point service range as a constraint, and comprises the following steps:
the station service radius R is the maximum walking range of passengers, 500m is taken, and the station service range is a circular area range which takes the cluster center as the center and takes R as the radius to radiate outwards.
4. The network approximately splicing station location method based on the actual road network environment according to claim 1, wherein in the step (2), the determination method of the actual road network analysis area corresponding to each packet is as follows:
setting UNIT as the minimum closed polygon which can be formed by the road network nodes and as the minimum road network UNIT; the road network analysis area is the minimum actual road network area containing all passenger demand points in a clustering range;
(21) For a cluster range K i Judging the passenger demand point in the network UNIT, if it is in the network UNIT or at the boundary, recording the node n contained in the UNIT i And road segment e i ；
(22) Obtaining the cluster containing range K i Section of all demand points inPoint set N i ＝{n 1 ,n 2 ,n 3 … and road segment set E i ＝{e 1 ,e 2 ,e 3 …}；
(23) Road network analysis zone Z i The Z can be represented by a graph representation method i ＝(N i ,E i )。
5. The method for selecting the network pinch points based on the actual road network environment according to claim 4, wherein in the step (3), the method for determining the road segment division points corresponding to the passenger demand points is as follows:
wherein the shortest distance adopts the actual road network distance,
v a and v b Representing two end points of a road section, the length of the road section can be [ v ] a ,v b ]A representation; passenger demand point p i And p j For shortest path between
A representation; if p i And p j The shortest path point v between a Sum point v b Then p i And p j The shortest possible between +.>
A representation;
(31) From the above step (23), a road network analysis zone Z i Contains node number N i Road segment number E i The set of the included passenger demand points is P i ＝{p 1 ,p 2 ,p 3 …}；
(32) For road section [ v a ,v b ]Wherein [ v ] a ,v b ]∈E i At the passenger demand point p i ，p i ∈P i Starting from the road segments [ v ] a ,v b ]Two end points v of (2) a And v b As the end point, the Dijkstra algorithm is used to calculate the shortest path distance respectively, which is recorded as
And
(33) At p i 、v a 、v b Is the vertex of triangle, to
[v a ,v b ]，/>
For triangle side, find road segment [ v ] using triangle inequality relation a ,v b ]Is defined by the dividing points of the pair.
6. The method for selecting a station point for a network about splicing based on an actual road network environment according to claim 5, wherein in said step (33), a triangle inequality relation is used to find a road section [ v ] a ,v b ]The specific steps are as follows:
(331) In triangle p i v a v b The following relationship holds:
then for the passenger demand point p i For the road section [ v ] a ,v b ]There is a dividing point es pi So that
(332) Dividing points es pi In road section [ v ] a ,v b ]Available segmentation points es for positions on pi And v a The distance of the road section [ v ] a ,v b ]Ratio of total length
Is hereinafter referred to as a division point es pi Road segment [ v ] a ,v b ]Duty ratio of->
Corresponding road segment origin v a ，/>
Corresponding road segment end v b ；
Let the road distance distribution function be
Representing the distance between point i and point j on the road segment;
dividing points es pi The position calculation formula of (2) is as follows:
dividing points es pi Distance segment origin v a The distance calculation formula of (2) is as follows:
[v a ,v b ]road section [ v ] a ,v b ]Is a length of (2);
(334) Set of demand points for passengers P i All the objects in the map can be found to correspond to the road segment v a ,v b ]The division point duty ratio set is
7. The method for network pinch point location based on actual road network environment according to claim 6, wherein in the step (4), for the road segment [ v ] a ,v b ]The shortest path distance from all passenger demand points to the station x in the analysis area is calculated, and the distances are summed to determine the optimal station position for the road section, and the method specifically comprises the following steps:
initializing, shortest distance set
(41) Get the road section [ v ] a ,v b ]Any point x is taken as a spelling station point, and a road section v of the station x is set a ,v b ]The duty ratio is theta;
(42) As described in connection with step (32) and step (333), it is known that when
At this time, the passenger demand point p i Shortest to site x must go through start point v a The shortest length is denoted +.>
When->
At this time, the passenger demand point p i The shortest path to site x must be via endpoint v b The shortest length is denoted +.>
From the passenger demand point p i The shortest path distance to site x can be expressed as a linear piecewise function,
(43) Road network analysis zone Z i Set of all passenger demand points P in i Repeating the operation of step (42) for the object to calculate P i The shortest path distance from each object to the site, the result is stored in the set D θ [v a ,v b ]In (a) is marked as
(44) Will shortest distance set D θ [v a ,v b ]The sum of the elements in (a) is denoted as Sigma D θ [v a ,v b ]。
8. The method for selecting a station point for network splicing based on actual road network environment according to claim 1, wherein in the step (5), the road network analysis zone Z is i Repeating the operations of the step (3) and the step (4) on other road sections, comparing the sum of the shortest distances of the road sections, and determining the road section and the position of the optimal station, wherein the method comprises the following specific steps:
initializing, distance and collection
And minimum distance set->
(51) Analysis zone Z of road network i Road segment set E i Repeating the steps (3) and (4) for the road segment [ v ] a ,v b ]Respectively, the values obtained by summing the distances are stored in the set D, then d= { Σd θ [e 1 ],∑D θ [e 2 ],∑D θ [e 3 ]…}
(52) Sd (e) 1 )＝min∑D θ [e 1 ]Calculating Sigma D θ [e 1 ]And record sd (e) 1 ) A value and a corresponding θ value;
(53) Likewise, similar to road segment e 1 Respectively, the minimum values of all elements in the set D are calculated, and the result is stored in the set sd, i.e., sd= { sd (e 1 ),sd(e 2 ),sd(e 3 ),sd(e 4 ) …, and recording the respective corresponding θ values;
(54) Comparing all elements in the set sd, wherein the road section and theta value corresponding to the minimum element value are the road network analysis zone Z i The optimal road section and the optimal position of the middle carpooling station x.
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