CN114495552B - Navigation method and system for quickly parking and finding vehicle - Google Patents
Navigation method and system for quickly parking and finding vehicle Download PDFInfo
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- CN114495552B CN114495552B CN202210071606.9A CN202210071606A CN114495552B CN 114495552 B CN114495552 B CN 114495552B CN 202210071606 A CN202210071606 A CN 202210071606A CN 114495552 B CN114495552 B CN 114495552B
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- G08G1/144—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces on portable or mobile units, e.g. personal digital assistant [PDA]
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Abstract
The invention discloses a navigation method and a system for quickly parking and finding a vehicle, and belongs to the technical field of intelligent parking. Acquiring vacant parking spaces and parking lot inlets in a parking layer where the current vehicle is located; taking an elevator in a parking layer where a vehicle is located as a starting point, establishing a screening model, and screening a preset number of target parking spaces in the vacant parking space set to obtain a target parking space set; a hierarchical analysis algorithm is introduced, and the optimal parking space meeting the user requirements is obtained based on the target parking space set analysis; and recommending an optimal parking path from the entrance of the parking lot to the optimal parking space to the user by adopting a path algorithm. The invention selects the target parking spaces with the preset number from the current vacant parking spaces, so that the user can park in the fastest time and leave the parking lot in the fastest time while selecting the proper parking spaces according to the preference of the user. The position of the user is tracked in real time based on software, and the user can push a car-finding navigation route for the user when finding the car by combining the previously pushed optimal parking space, so that the user can conveniently find the car.
Description
Technical Field
The invention belongs to the technical field of intelligent parking, and particularly relates to a navigation method and a navigation system for fast parking and finding a vehicle.
Background
With the improvement of living standard and the rapid development of economy, although the increase of the number of the household cars brings convenience to life, the problem of 'difficult parking' also comes along. To solve the problem of "difficult parking", multi-storey parking lots are becoming popular. At present, most commercial and trade centers have multilayer underground or overground parking spaces for people to use, and due to the fact that the parking spaces are not familiar to the parking lot and lack of parking space information of the current parking lot, car owners cannot find the optimal parking spaces in a short time, so that vicious circle of parking difficulty is further aggravated, and the traveling efficiency of people is reduced.
Disclosure of Invention
The invention provides a navigation method and a system for quickly parking and finding a vehicle to solve the technical problems in the background technology.
The invention is realized by adopting the following technical scheme: a quick parking and vehicle finding navigation method comprises the following steps:
acquiring vacant parking spaces in a parking layer where a current vehicle is located and generating a vacant parking space set U by a parking lot entrance;
taking an elevator in a parking layer where a vehicle is located as a starting point, establishing a screening model, and screening a preset number of target parking spaces from the vacant parking space set U to obtain a target parking space set C;
a hierarchical analysis algorithm is introduced, and the optimal parking space meeting the user requirements is obtained based on the analysis of the target parking space set C;
and recommending an optimal parking path from the entrance of the parking lot to the optimal parking space to the user by adopting a path algorithm.
In a further embodiment, the method further comprises the following steps:
recommending an optimal walking path from an optimal parking space to an elevator to a user by adopting a path algorithm, generating parking information by the optimal parking path, the optimal walking path and a corresponding license plate, and sending the parking information to a mobile phone of the user;
when finding the car, the mobile phone is switched to the navigation mode to recommend a walking route from the current position to the optimal parking space to the user based on the parking information and the current position of the user.
Through adopting above-mentioned technical scheme, be convenient for the user with the shortest time from the elevator parking area, parking stall and license plate bind and send car owner's cell-phone APP through wireless mode, the later stage is when looking for the car, starts the navigation mode based on the position at parking information and user current place, makes things convenient for the car owner to look for the car.
In a further embodiment, the screening model is established as follows:
each element in the free parking space set at least comprises the following parameters: the distance from the vacant parking space node k to the starting point corresponds to the vacant parking space node k;
comparing the new path length obtained by calculation with a threshold value every time, and upgrading the corresponding node smaller than the threshold value into a target node;
and removing the target nodes and the corresponding path lengths from the vacant parking space set U, and updating the target nodes and the corresponding path lengths into a target set S until elements in the target set S meet the calculation stop conditions.
By adopting the technical scheme, the calculation stopping condition is introduced, namely, calculation analysis is not needed to be carried out on each vacant parking space node, the target parking space can be screened out when the calculation stopping condition is met, the calculation amount is greatly reduced, and the calculation time for generating the path is shortened.
In a further embodiment, the calculation stop condition is:
when the newly added elements in the target set S are more than the preset number, stopping the operation on the remaining elements in the vacant parking space set U;
or if the newly added elements in the target set S are less than the preset number and the parking lot entrance is transferred to the target set S as the newly added elements, the operation on the residual elements in the vacant parking space set U is stopped.
In a further embodiment, the hierarchical analysis algorithm specifically includes the following steps:
establishing a target layer Z, a criterion layer A and a scheme layer B; the scheme layer B comprises a target parking space set C = { C = { (C) } 1 ，c 2 ，c 3 ，…，c m M represents the number of target parking spaces;
the criterion layer A comprises n rules, which are recorded asG={ g 1 ，g 2 ，g 3 ，…，g n Where n denotes the number of rules, with
ij The j-th attribute value, which represents the i-th rule, is decided on to compare the matrix A = (= live in case of a positive decision)>
ij ） m×n Wherein i is more than or equal to 1 and less than or equal to n;
calculating a weight value for each rule in criterion layer A corresponding to a target layer
；
Respectively calculating the weight value of each target parking space in the scheme layer B corresponding to each rule in the criterion layer A
；
Based on weight value
And weight value->
Combining the weights ^ on the combination of each target parking space>
Selecting a combination weight->
The target parking space corresponding to the maximum value in the parking space is the optimal parking space.
In a further embodiment, the method further comprises the step of checking consistency of comparison matrixes in the criterion layer A and the scheme layer B, wherein the check criterion is as follows by taking the comparison matrix A as an example:
then a =: (
ij ） m×n =/>
；
A 
=/>
max />
Wherein is present>
max Is the maximum characteristic value of the matrix A, <' > is>
Is corresponding to>
max The feature vector of (2).
In further embodiments, at least the following rules are included: whether the parking space is close to the entrance of the parking lot, whether the parking space is close to the elevator, the type of the parking space, whether the two sides of the parking space occupy and the distance between the parking space and the exit of the parking lot.
By adopting the technical scheme, the optimal parking space with the elevator as the starting point is selected according to the user requirement and the parking preference of the user.
In a further embodiment, the path algorithm employs Dijkstra's algorithm.
A quick park and find vehicle navigation system comprising:
the mobile terminal comprises a mobile terminal, a first module, a second module, a third module and a fourth module, wherein the mobile terminal is arranged on the first module, the second module, the third module and the fourth module of the mobile terminal;
the first module is set to acquire vacant parking spaces in a parking layer where a current vehicle is located and a parking lot entrance to generate a vacant parking space set U;
the second module is set to establish a screening model by taking an elevator in a parking layer where a vehicle is located as a starting point, and a target parking space set C is obtained by screening a preset number of target parking spaces in the vacant parking space set U;
the third module is set to introduce a hierarchical analysis algorithm, and the optimal parking space meeting the user requirement is obtained based on the analysis of the target parking space set C;
the fourth module is configured to recommend an optimal parking path to the user from the parking lot entrance to the optimal parking space using a path algorithm.
In a further embodiment, further comprising: the fifth module is set to recommend an optimal walking path from an optimal parking space to an elevator to a user by adopting a path algorithm, and generates parking information from the optimal parking path, the optimal walking path and a corresponding license plate;
a sixth module configured to store the parking information;
and the seventh module is set to switch to a navigation mode to recommend a walking route from the current position to the optimal parking space to the user based on the parking information and the current position of the user.
The invention has the beneficial effects that: according to the invention, a preset number of target parking spaces are selected from the current vacant parking spaces, a hierarchical analysis method is generated by combining the user requirements, the optimal parking spaces are screened out from the preset number of target parking spaces, then the Dijkstra algorithm is adopted again to guide the vehicle to enter the parking spaces, so that the user can park in the fastest time and can be ensured to leave the parking lot in the fastest time while selecting the proper parking spaces according to the preference of the user. Fully embodies people oriented, improves the parking efficiency, practices thrift user's time. Meanwhile, the position of the user is tracked in real time based on software, and when the user finds the vehicle, a vehicle finding navigation route is pushed for the user by combining the best parking space pushed before, so that the user can find the vehicle conveniently.
Drawings
Fig. 1 is a schematic view of parking lot roads and parking space distribution.
Fig. 2 is a flowchart of a navigation method for fast parking and finding a vehicle.
FIG. 3 is a diagram of a hierarchical analysis structure model.
Fig. 4 is a simulation diagram of an optimal parking space.
Detailed Description
The invention is further described in the following with reference to the examples and the drawings.
The large-scale complex underground parking garage has several layers, and the car owner drives to the underground parking garage generally to oneself and drives and look for the parking stall, because once parking usually, the car owner is unclear the map and the position in parking area, leads to the blind parking, and people and car are difficult to look for the parking stall of stopping after separating. Much time and effort is wasted.
Based on the above-described problems, the time and effort saving is fundamentally reflected in time, and in the present embodiment, the shortest time is a period of time from when a person enters the parking lot together with a vehicle to when the person leaves the parking lot. This period includes the time from the entrance of the car to the parking space and the parking time and the time from the exit of the person from the parking space to the exit location (here, the exit location refers to the elevator entrance of the underground parking lot). The time of the person in the whole parking lot is directly related to the distance time and the work efficiency of the car owner. 2 factors are used for determining the time, and firstly, the position of the vacant parking space is selected; the other is the time from the entrance of the parking lot to the parking space and parking of the vehicle. The time from a person to an elevator entrance depends on the walking time from an empty parking space to the elevator entrance, and the walking time is different according to the position of the parking space, so the time is generally invariable statically. By combining the above analysis, the shortest time path is the shortest time for selecting the vacant parking space and the parking guidance system.
Example 1
As shown in fig. 1, P1 to P8 in the drawing indicate free parking spaces, and there are parking spaces in different situations, such as those occupied at both sides or those occupied at one side, and those with different distances from the elevator. The embodiment discloses a navigation method for quickly parking and finding a vehicle, as shown in fig. 2, comprising the following steps:
acquiring vacant parking spaces in a parking layer where a current vehicle is located and generating a vacant parking space set U by a parking lot entrance; and abstracting each vacant parking space and each parking lot entrance into a vacant parking space node and a destination node respectively. Wherein, every element in vacant parking stall set U includes the following parameter at least: and the distance from the vacant parking space node k to the starting point is corresponding to the vacant parking space node. That is, each vacant parking space comprises the parameters: and the distance from the vacant parking space node k to the starting point corresponds to the vacant parking space node. k represents the number of the vacant parking spaces, and k is more than or equal to 1 and less than or equal to 8 in the embodiment.
Establishing a screening model by taking an elevator in a parking layer where a vehicle is located as a starting point, and screening a preset number of target parking spaces from the vacant parking space set U to obtain a target parking space set C = { C = 1 ，c 2 ，c 3 ，…，c m And f, wherein m represents the number of the target parking spaces. In the present embodiment, the predetermined number takes on a value of 3, i.e., m =3. In other words, 3 vacant parking spaces meeting the requirements are selected from the vacant parking space set U to serve as target parking spaces.
Based on the description, the user does not know much information of the parking lot, and information asymmetry exists between the subjective intention of the user and the vacant parking spaces in the parking lot. Often, the user finds that a better parking space meets the personal requirement of parking after the parking is finished. The user is very important to select the parking space according to the current requirement, so that the user can more remarkably enhance the humanization and the high efficiency of the parking by introducing the personal preference of the user into the selection of the vacant parking space.
Therefore, in this embodiment, a hierarchical analysis algorithm is introduced, and an optimal parking space meeting the user requirements is obtained based on the target parking space set C; and recommending an optimal parking path from the entrance of the parking lot to the optimal parking space to the user by adopting a path algorithm.
By adopting the technical scheme, the preference of the user considers the information release in the path planning, so that the user can select the proper parking space according to the preference of the user.
In order to enable the user to use the shortest time to walk from the optimal parking space to the elevator, a Dijkstra path algorithm (the Dijkstra path algorithm is a common algorithm in the prior art, and is not described herein) is adopted to recommend the optimal walking path from the optimal parking space to the elevator to the user. And meanwhile, in order to provide convenience for the user to find the vehicle when the user leaves, the optimal parking path, the optimal walking path and the corresponding license plate are used for generating parking information, and the parking information is sent to the mobile phone of the user.
When the user finishes the work or needs to find the car, the mobile phone is switched to the navigation mode to recommend a walking route from the current position to the optimal parking space to the user based on the parking information and the current position of the user. In the embodiment, the walking route, the optimal parking path and the optimal walking path are displayed to the user in the form of a map, so that the user can more intuitively acquire information. The parking space where the vehicle is located is found through the fastest path to find the vehicle, the possibility of getting lost due to unfamiliarity of the parking lot is reduced, and the vehicle finding efficiency is improved.
The shortest path research method in the existing parking lot guidance system mainly comprises a Dijkstra algorithm, an ant colony algorithm, a particle swarm algorithm, a heuristic search algorithm and the like, wherein the Dijkstra algorithm has high practical value in finding the shortest path in a weighted directed graph, and in the path planning of the parking lot, the entrance and the exit of the parking lot and the position of an elevator are determined position points and meet the algorithm solving requirement. When the traditional Dijkstra algorithm is used for calculation, shortest paths from a starting node to any node are added into a shortest path tree one by one according to the ascending weight of the shortest paths from the starting node to other nodes, and the shortest path from the starting point to the arbitrary node is solved. In a parking guidance system, if a conventional Dijdktra searches for a shortest path to park in a parking lot with a large number of nodes with an entrance of the parking lot as a starting point and an exit as an end point, the calculation amount is large, and the efficiency is very low.
This parking solution has two problems: firstly, all parking spaces are the same for the user, and the user can park the vehicle by taking the entrance as the shortest path without considering the actual requirement of the user. In addition, the traditional Dijkstra algorithm is used for traversing and sequencing all the idle parking spaces from the entrance to the exit, the waste of time and resources is serious, and the found parking spaces with the shortest paths do not necessarily meet the requirements of users. Therefore, the following improvements are made in the embodiment:
the establishment process of the screening model is as follows: each element in the set of vacant parking spaces at least comprises the following parameters: the distance from the vacant parking space node k to the starting point corresponds to the vacant parking space node k;
and comparing the new path length obtained by calculation with the threshold value every time, and upgrading the corresponding node smaller than the threshold value into a target node.
And removing the target nodes and the corresponding path lengths from the vacant parking space set U, and updating the target nodes and the corresponding path lengths into a target set S until elements in the target set S meet the calculation stop conditions. By introducing the calculation stop condition, the number of nodes is reduced, the calculation amount is small, and the guidance efficiency is improved.
In a further embodiment, the calculation stop condition is: when the newly added elements in the target set S are more than the preset number, stopping the operation on the remaining elements in the vacant parking space set U; or if the newly added elements in the target set S are less than the preset number and the parking lot entrance is transferred to the target set S as the newly added elements, the operation on the residual elements in the vacant parking space set U is stopped.
By way of example: and if a certain vacant parking space node v in the vacant parking space set U is not adjacent to the starting point S, the distance from v to the starting point S is infinity, and the initial value i =0 of the number of elements in the target set S is recorded.
When a certain vacant parking space node v in the vacant parking space set U is adjacent to the starting point s and the calculated distance length is smaller than a threshold (the threshold is set in advance according to the actual situation of the parking lot in the embodiment), upgrading the vacant parking space node v to be a target node; and removing the target nodes and the corresponding path lengths from the vacant parking space set U, updating the target nodes and the corresponding path lengths into a target set S, and recording the initial value i +1 of the number of elements in the target set S. This is repeated until i =3 or the target set S already has a parking lot entrance.
The stop condition is a condition whether the target node reaches 3 or does not reach 3 and the parking lot entry node has entered the shortest path as the operation stop. The amount of calculation is greatly reduced.
In a further embodiment, as shown in fig. 3, the hierarchical analysis algorithm specifically includes the following steps:
establishing a target layer Z, a criterion layer A and a scheme layer B; the scheme layer B comprises a target parking space set C = { C = { (C) } 1 ，c 2 ，c 3 ，…，c m M represents the number of target parking spaces;
the rule layer A comprises n rules, and the rules are marked as G = { G = { (G) 1 ，g 2 ，g 3 ，…，g n Where n denotes the number of rules, with
ij The j-th attribute value, which represents the i-th rule, is decided on to compare the matrix A = (= live in case of a positive decision)>
ij ） m×n Wherein i is more than or equal to 1 and less than or equal to n; the rules further include whether a parking space is near an entrance of the parking lot, whether a parking space is near an elevator, a type of the parking space, whether both sides of the parking space are occupied, and a distance between the parking space and an exit of the parking lot.
Calculating a weight value for each rule in criterion layer A corresponding to a target layer
；
Respectively calculating the weight value of each target parking space in the scheme layer B corresponding to each rule in the criterion layer A
；
Based on weight value
And a weight value>
Combining to obtain a combination weight &' for each target parking space>
Selecting a combination weight->
The target parking space corresponding to the maximum value in the parking space is the optimal parking space. The optimal parking space is not only optimal in position and time, but also meets the requirements of users and increases the comfort of parking.
The method also comprises the consistency check of comparison matrixes in the criterion layer A and the scheme layer B, taking the comparison matrix A as an example, the check criterion is as follows:
then a =: (
ij ） m×n =/>
；
A 
=/>
max />
Wherein is present>
max Is the maximum characteristic value of the matrix A, <' > is>
Is corresponding to>
max The feature vector of (2).
By way of example: according to the parking lot model established in fig. 1, considering the requirements of the user, the determination matrix is:
A= 
screening out three target parking spaces P8, P5 and P6 by adopting a screening model, and calculating the weight value (corresponding to the target layer) of each rule in the criterion layer A by adopting a normalization method based on the formula>
0.1263, 0.5495, 0.2476 and 0.0736, respectively.
Similarly, the weight value of each target parking space in the scheme layer B corresponding to each rule in the criterion layer A is calculated
As shown in expression 1:
TABLE 1
| A1 | A2 | A3 | A4 | |
| B1 | 0.6370 | 0.5816 | 0.1396 | 0.1095 |
| B2 | 0.2583 | 0.3090 | 0.5278 | 0.3090 |
| B3 | 0.1047 | 0.1095 | 0.3325 | 0.5816 |
And finally, calculating the combined weight of the three parking schemes as follows: 0.445, 0.3567 and 0.199, corresponding to the weights of P8, P5 and P6, respectively. And calculating P8 as the optimal parking space of the user according to an analytic hierarchy process. As can be seen from fig. 4, the optimal parking space is P8. The simulation result is consistent with the actual situation.
The embodiment combines the requirement decision of the user on the parking space with the shortest condition search path of the existing parking space, on one hand, the requirements of different users are facilitated, on the other hand, the guiding of parking is facilitated, the shortest parking path and the shortest path reaching the elevator of the user are fully considered, and the parking efficiency of the user and the parking space utilization rate of the underground parking lot are improved.
Example 2
The embodiment discloses a navigation system for fast parking and finding a vehicle, which is used for realizing the method in the embodiment 1. The method comprises the following steps: the mobile terminal comprises a mobile terminal, a first module, a second module, a third module and a fourth module, wherein the mobile terminal is arranged on the first module, the second module, the third module and the fourth module of the mobile terminal;
the first module is set to acquire vacant parking spaces in a parking layer where a current vehicle is located and a parking lot entrance to generate a vacant parking space set U;
the second module is set to establish a screening model by taking an elevator in a parking layer where a vehicle is located as a starting point, and a target parking space set C is obtained by screening a preset number of target parking spaces in the vacant parking space set U;
the third module is set to introduce a hierarchical analysis algorithm, and the optimal parking space meeting the user requirement is obtained based on the target parking space set C;
the fourth module is configured to recommend an optimal parking path to the user from the parking lot entrance to the optimal parking space using a path algorithm.
Further comprising: the fifth module is set to recommend an optimal walking path from an optimal parking space to an elevator to a user by adopting a path algorithm, and generates parking information from the optimal parking path, the optimal walking path and a corresponding license plate;
a sixth module configured to store the parking information;
and the seventh module is set to switch to the navigation mode to recommend a walking route from the current position to the optimal parking space to the user based on the parking information and the current position of the user.
Claims (6)
1. A quick parking and vehicle finding navigation method is characterized by comprising the following steps:
acquiring vacant parking spaces in a parking layer where a current vehicle is located and generating a vacant parking space set U by a parking lot entrance;
taking an elevator in a parking layer where a vehicle is located as a starting point, establishing a screening model, and screening a preset number of target parking spaces from the vacant parking space set U to obtain a target parking space set C;
a hierarchical analysis algorithm is introduced, and the optimal parking space meeting the user requirements is obtained based on the target parking space set C;
recommending an optimal parking path from the entrance of the parking lot to the optimal parking space to the user by adopting a path algorithm;
the establishment process of the screening model is as follows:
each element in the set of vacant parking spaces at least comprises the following parameters: the distance from the vacant parking space node k to the starting point corresponds to the vacant parking space node k;
comparing the new path length obtained by calculation with a threshold value every time, and upgrading the corresponding node smaller than the threshold value into a target node;
removing the target nodes and the corresponding path lengths from the vacant parking space set U, and updating the target nodes and the corresponding path lengths into a target set S until elements in the target set S meet the calculation stop conditions; the calculation stop conditions are as follows:
when the number of the newly added elements in the target set S is larger than the preset number, stopping the operation on the remaining elements in the vacant parking space set U; or when the number of the newly added elements in the target set S is smaller than the preset number and the parking lot entrance is transferred to the target set S as the newly added element, stopping the operation on the residual elements in the vacant parking lot set U;
the hierarchical analysis algorithm specifically comprises the following steps:
establishing a target layer Z, a criterion layer A and a scheme layer B; the scheme layer B comprises a target parking space set C = { C = { (C) } 1 ，c 2 ，c 3 ，…，c m M represents the number of target parking spaces;
the rule layer A comprises n rules, and the rules are marked as G = { G = { (G) 1 ，g 2 ，g 3 ，…，g n Where n denotes the number of rules, by α ij J attribute value representing i rule, and deciding a pair comparison matrix A = (alpha) ij ) m×n Wherein i is more than or equal to 1 and less than or equal to n;
calculating a weight value δ for each rule in the criterion layer A corresponding to the target layer n ；
Respectively calculating the weight value delta of each target parking space in the scheme layer B corresponding to each rule in the criterion layer A mn ；
Based on weight value delta n Sum weight value delta mn Combining to obtain a combined weight for each target parking space
Selected combination weights>
The target parking space corresponding to the maximum value in the parking space is the optimal parking space; also comprises a consistency check of comparison matrix in the criterion layer A and the scheme layer B, and comparisonThe matrix a test criteria are as follows:
then
A∨＝λ max V. wherein, λ max Is the maximum characteristic value of the matrix A, V is corresponding to λ max The feature vector of (2).
2. The quick parking and vehicle finding navigation method according to claim 1, further comprising the steps of:
recommending an optimal walking path from an optimal parking space to an elevator to a user by adopting a path algorithm, generating parking information by the optimal parking path, the optimal walking path and a corresponding license plate, and sending the parking information to a mobile phone of the user;
when finding the car, the mobile phone is switched to the navigation mode to recommend a walking route from the current position to the optimal parking space to the user based on the parking information and the current position of the user.
3. The quick parking and vehicle finding navigation method according to claim 1, characterized by comprising at least the following rules: whether the parking space is close to the entrance of the parking lot, whether the parking space is close to the elevator, the type of the parking space, whether the two sides of the parking space are occupied and the distance between the parking space and the exit of the parking lot.
4. The quick parking and vehicle finding navigation method according to any one of claims 1 or 2, characterized in that the path algorithm adopts Dijkstra algorithm.
5. A quick parking and car finding navigation system is characterized by comprising:
the mobile terminal comprises a mobile terminal, a first module, a second module, a third module and a fourth module, wherein the mobile terminal is arranged on the first module, the second module, the third module and the fourth module of the mobile terminal;
the first module is set to acquire vacant parking spaces in a parking layer where a current vehicle is located and a parking lot entrance to generate a vacant parking space set U;
the second module is set to establish a screening model by taking an elevator in a parking layer where a vehicle is located as a starting point, and a target parking space set C is obtained by screening a preset number of target parking spaces in the vacant parking space set U;
the third module is set to introduce a hierarchical analysis algorithm, and the optimal parking space meeting the user requirement is obtained based on the analysis of the target parking space set C;
the fourth module is configured to recommend an optimal parking path from the parking lot entrance to the optimal parking space to the user using a path algorithm;
the establishment process of the screening model comprises the following steps:
each element in the set of vacant parking spaces at least comprises the following parameters: the distance from the vacant parking space node k to the starting point corresponds to the vacant parking space node k;
comparing the new path length obtained by calculation with a threshold value every time, and upgrading the corresponding node smaller than the threshold value into a target node;
removing the target nodes and the corresponding path lengths from the vacant parking space set U, and updating the target nodes and the corresponding path lengths into a target set S until elements in the target set S meet the calculation stop conditions; the calculation stop conditions are as follows:
when the newly added elements in the target set S are more than the preset number, stopping the operation on the remaining elements in the vacant parking space set U; or if the newly added elements in the target set S are less than the preset number and the parking lot entrance is transferred to the target set S as the newly added elements, stopping the operation on the residual elements in the vacant parking space set U;
the hierarchical analysis algorithm specifically comprises the following steps:
establishing a target layer Z, a criterion layer A and a scheme layer B; the scheme layer B comprises target parking space set C = { C 1 ，c 2 ，c 3 ，…，c m M represents the number of target parking spaces;
the rule layer A comprises n rules, and the rules are marked as G = { G = { (G) 1 ，g 2 ，g 3 ，…，g n Where n denotes the number of rules, with α ij Denotes the ith rulej attribute values, and deciding a pair comparison matrix A = (alpha) ij ) m×n Wherein i is more than or equal to 1 and less than or equal to n;
calculating a weight value delta of each rule in the criterion layer A corresponding to the target layer n ；
Respectively calculating the weight value delta of each target parking space in the scheme layer B corresponding to each rule in the criterion layer A mn ；
Based on weight value delta n Sum weight value delta mn Combining to obtain a combined weight for each target parking space
Selected combination weight->
The target parking space corresponding to the maximum value in the parking space is the optimal parking space; the method also comprises the consistency check of comparison matrixes in the criterion layer A and the scheme layer B, wherein the criterion of the comparison matrix A is as follows:
then
A∨＝λ max V. V.A max Is the maximum characteristic value of the matrix A, V is corresponding to lambda max The feature vector of (2).
6. The quick parking and car finding navigation system as claimed in claim 5, further comprising:
the fifth module is set to recommend an optimal walking path from an optimal parking space to an elevator to a user by adopting a path algorithm, and generates parking information from the optimal parking path, the optimal walking path and a corresponding license plate;
a sixth module configured to store the parking information;
and the seventh module is set to switch to the navigation mode to recommend a walking route from the current position to the optimal parking space to the user based on the parking information and the current position of the user.
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| CN115273526A (en) * | 2022-06-20 | 2022-11-01 | 广州小鹏汽车科技有限公司 | Method, vehicle and mobile terminal for providing route guidance |
| CN115209504B (en) * | 2022-07-19 | 2024-05-28 | 东南大学成贤学院 | Mobile social network routing method based on preference communities and energy consumption factors |
| CN116167536B (en) * | 2022-12-07 | 2023-08-04 | 江苏巨楷科技发展有限公司 | Intelligent parking management method based on time period learning optimization |
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