CN109949604B - Large parking lot scheduling navigation method and system - Google Patents
Large parking lot scheduling navigation method and system Download PDFInfo
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Abstract
The invention discloses a large parking lot dispatching navigation method, which comprises the following steps: constructing an optimal parking place selection model: abstracting a parking lot scene into a grid shape, setting the initial empty state of all parking places in the parking lot, calculating the selection weight of each free parking place, and further obtaining the optimal parking place according to the selection weight of the free parking places; constructing a global optimal scheduling model: estimating the time from the entrance of the parking lot to the optimal parking place according to the corresponding weight of the left and right directions of the road in the parking lot, thereby estimating the congestion condition of the parking lot; path planning: and obtaining an evaluation matrix according to the global optimal scheduling model by combining a Floyd search algorithm, and updating the evaluation matrix in real time to realize path planning and scheduling of the parking lot. The optimal navigation path is provided by using the path planning model in the invention, and the parking efficiency and accuracy of the user are improved.
Description
Technical Field
The invention relates to the field of vehicle scheduling application, in particular to a large parking lot scheduling navigation method and system.
Background
Cars bring convenience to people's lives and a series of problems to cities. The parking problem becomes an important problem which troubles people every day when people go to work or entertain the weekend. At present, most of working units and shopping malls need the car owner to know the remaining conditions of the parking space after arriving, so that the car owner is often required to know that no parking space exists after arriving at the shopping mall due to the blocked parking space information, and the car owner has to search for the parking lot nearby again. When the parking lot has free parking spaces, the ideal parking spaces cannot be quickly found due to unreasonable management and planning design of the parking lot after the parking lot enters the parking lot. In a large parking lot, most car owners often face the situation that the car owners cannot remember the parking position after parking, and much time is wasted in finding the car. Under some special conditions, especially at the peak and eating time of going to work and going to work, the parking lot can be used for parking quickly and efficiently, so that the living efficiency of people can be effectively improved, and meanwhile, certain economic benefits can be brought to markets and units. Therefore, the parking efficiency in the parking lot needs to be effectively improved on the premise that the number of parking spaces in the urban parking lot is limited.
In a large parking lot in a city, a vehicle owner cannot know the congestion condition in the parking lot in detail, and the vehicle owner often determines which direction to drive to within an intuitive and visible range when entering the parking lot. However, congestion often occurs at the intersection of a corner, which cannot be predicted by the vehicle owner; after entering the parking lot, the vehicle owner firstly needs to go to the place near the destination and then searches for the parking space. However, in a complex parking lot scene, the owner often needs to find the nearest parking space for a long time around the destination; when the owner finds the vehicle and prepares to leave the parking lot, the external road jam condition at the exit is difficult to know. When the vehicle leaves the parking lot and drives to the highway, much time is wasted due to the congestion of the highway, but the congestion of the vehicle is also related to the planning of the number of vehicles at the exit of the parking lot. In the existing scheduling scheme, when the parking lot is in a peak use period, the scheduling accuracy is low.
Disclosure of Invention
The purpose of the invention is as follows: in order to overcome the defects of the prior art, the invention provides a large parking lot scheduling navigation method, which can solve the problem of low accuracy of a scheduling route when a parking lot is in a use peak period, and also provides a large parking lot scheduling navigation system and a use method of the system.
The technical scheme is as follows: the invention relates to a large parking lot dispatching navigation method, which comprises the following steps:
(1) constructing an optimal parking place selection model: abstracting parking lot scenes into grids, wherein each grid comprises a plurality of parking spaces, and setting the initial empty state of all the parking spaces in the parking lot; searching for an idle parking space by taking the set target position as a center; if no free parking space exists, enlarging the searched radius by one unit of grid until the free parking space is found, at the moment, calculating the selection weight of each free parking space, and further obtaining the optimal parking space according to the selection weight of the free parking space;
(2) constructing a global optimal scheduling model: estimating the time from the entrance of the parking lot to the optimal parking place according to the corresponding weight of the left and right directions of the road in the parking lot, thereby estimating the congestion condition of the parking lot;
(3) path planning: and obtaining an evaluation matrix according to the global optimal scheduling model by combining a Floyd search algorithm, and updating the evaluation matrix in real time to realize path planning and scheduling of the parking lot.
Preferably, the weight of the free parking space selection comprises:
W(Pi)＝αDi+βTi+η
α+β＝1
wherein, PiIs an empty parking space, the distance from the empty parking space to the destination is DiThe time from the entrance of the parking lot to the vacant parking space is TiI is the serial number of the idle parking space, α is the influence factor of the distance traveled after parking, β is the influence factor from the entrance of the parking lot to the target parking space, and η is the self-factor of the parking space, and is generally 3, 6 and 9 according to the parking space condition.
Preferably, the estimating the time from the entrance of the parking lot to the optimal parking space according to the corresponding weight of the left and right directions of the road in the parking lot specifically includes:
assuming that the roads of the parking lot are bidirectional lanes, the left side and the right side of each corresponding grid are provided with WLjAnd WRjA weight;
if the vehicle on the right side of the road continues to drive forward at the current position, WRj1, and when there is a vehicle running on the left side of the road, the weight WLjIs also 1;
when the vehicle needs to be parked and put in storage after reaching the optimal parking space, the W at the position needs to be checked because the vehicle needs to occupy the road beside the road when parking and putting in storagejIncrease by 1 and subtract by 1 the weight of the location after parking.
The vehicle finally drives to the optimal parking space P from the entrance of the parking lotiThe time used is TiExpressed as:
wherein R isjIs the position of the pathAnd setting the automobile to use one unit time for each unit parking space. Since roads are bidirectional, the road weight of each position needs to be selected according to actual conditions during route selection, and therefore the left side and the right side of each road are combined into a whole
And selecting corresponding weights according to actual conditions.
Preferably, the obtaining an evaluation matrix according to the global optimal scheduling model by combining with a Floyd search algorithm and updating the evaluation matrix in real time includes:
the evaluation matrix comprises a distance evaluation matrix and a time evaluation matrix, and the distance evaluation matrix and the time evaluation matrix are firstly calculated:
setting all intersections in the parking lot as a road intersection viAll the intersections are put into a weighted directed graph G (V, E, W), where V ═ V is set as the intersection set1,v2,...,vnUsing path set E { < v { [ v ]i,vj＞|vi≠vj,vi,vjE.g. V) to describe whether each two intersections are communicated, and the corresponding weight on the communicated path is W ═ Wij|wij>0}，vjIs any one intersection point in the weighted directed graph G (V, E, W);
generating a distance evaluation matrix W according to the weighted directed graphdAnd time evaluation matrix Wt：
Wherein d isijFor the distance between each intersection in the directed graph, tijThe travel time of the vehicle from the current position to the optimal parking space,
Tkfor the final driving of the vehicle from the entrance of the parking lot to the optimal parking space PkThe time taken;
updating the distance evaluation matrix WdAnd time evaluation matrix Wt：
Is provided with
Is v isiPoint to vjThe shortest length at which a point does not pass through any intermediate point,
is v isiPoint to vjThe shortest time for a point not to pass any intermediate point, then:
then
And
respectively, a directed graph G (V, E, W) takes into account Vi、vjAnd v1Shortest path and shortest time consumption of three nodes;
if v isiPoints v and vjPoint of no passing through v1Node, then dij 0＝dij 1，tij 0＝tij 1Otherwise, there is
Then
Order to
For the directed graph G (V, E, W), V needs to be consideredi,vj,v1,v2,...,vl-1Situation of a node, then
Based on the iterative relationship, the weight matrix W can be updateddAnd WtSuch iterative operations are implemented each time the vehicle travels to an intersection. The result of each update is maintained in the same evaluation matrix.
On the other hand, the invention also provides a large parking lot dispatching navigation system, which comprises:
the optimal parking place selection module is used for abstracting a parking place scene into grids, each grid comprises a plurality of parking places, and the initial empty state of all the parking places in the parking place is set; searching for an idle parking space by taking the set target position as a center; if no free parking space exists, enlarging the searched radius by one unit of grid until the free parking space is found, at the moment, calculating the selection weight of each free parking space, and further obtaining the optimal parking space according to the selection weight of the free parking space;
the global optimal scheduling module is used for estimating the time from an entrance of the parking lot to the optimal parking place according to the corresponding weight of the left direction and the right direction of the road in the parking lot, so that the congestion condition of the parking lot is estimated;
and the path planning module is used for obtaining an evaluation matrix according to the global optimal scheduling model by combining a Floyd search algorithm, and updating the evaluation matrix in real time to realize path planning and scheduling of the parking lot.
Preferably, in the optimal parking space selection module, the weight of the selection of the free parking spaces includes:
W(Pi)＝αDi+βTi+η
α+β＝1
wherein, PiThe parking space is an idle parking space,the distance from the free parking space to the destination is DiThe time from the entrance of the parking lot to the vacant parking space is TiI is the serial number of the idle parking space, α is the influence factor of the distance traveled after parking, β is the influence factor from the entrance of the parking lot to the target parking space, and η is the self-factor of the parking space, and is generally 3, 6 and 9 according to the parking space condition.
Preferably, the global optimal scheduling module further includes:
a lane weight representation unit for firstly assuming that the road of the parking lot is a bidirectional lane, and the left and right sides of each corresponding grid are provided with WLjAnd WRjA weight;
if the vehicle on the right side of the road continues to drive forward at the current position, WRj1, and when there is a vehicle running on the left side of the road, the weight WLjIs also 1;
when the vehicle needs to be parked and put in storage after reaching the optimal parking space, the W at the position needs to be checked because the vehicle needs to occupy the road beside the road when parking and putting in storagejIncrease by 1 and subtract by 1 the weight of the location after parking.
The vehicle finally drives to the optimal parking space P from the entrance of the parking lotiThe time used is TiExpressed as:
wherein R isjAnd setting the use of one unit time for each unit parking space driven by the automobile for the position of the path. Since roads are bidirectional, the road weight of each position needs to be selected according to actual conditions during route selection, and therefore the left side and the right side of each road are combined into a whole
And selecting corresponding weights according to actual conditions.
The path planning module comprises:
an evaluation matrix calculation unit configured to calculate the distance evaluation matrix and the time evaluation matrix:
setting all intersections in the parking lot as a road intersection viAll the intersections are put into a weighted directed graph G (V, E, W), where V ═ V is set as the intersection set1,v2,...,vnUsing path set E { < v { [ v ]i,vj＞|vi≠vj,vi,vjE.g. V) to describe whether each two intersections are communicated, and the corresponding weight on the communicated path is W ═ Wij|wij>0}，vjIs any one intersection point in the weighted directed graph G (V, E, W);
generating a distance evaluation matrix W according to the weighted directed graphdAnd time evaluation matrix Wt：
Wherein d isijFor the distance between each intersection in the directed graph, tijThe travel time of the vehicle from the current position to the optimal parking space,
Tkfor the final driving of the vehicle from the entrance of the parking lot to the optimal parking space PkThe time taken;
an evaluation matrix updating unit for updating the distance evaluation matrix WdAnd time evaluation matrix Wt：
Is provided with
Is v isiPoint to vjThe shortest length at which a point does not pass through any intermediate point,
is v isiPoint to vjThe shortest time for a point not to pass any intermediate point, then:
then
And
respectively, a directed graph G (V, E, W) takes into account Vi、vjAnd v1Shortest path and shortest time consumption of three nodes;
if v isiPoints v and vjPoint of no passing through v1Node, then dij 0＝dij 1，tij 0＝tij 1Otherwise, there is
Then
Order to
For the directed graph G (V, E, W), V needs to be consideredi,vj,v1,v2,...,vl-1Situation of a node, then
Based on the iterative relationship, the weight matrix W can be updateddAnd WtSuch iterative operations are implemented each time the vehicle travels to an intersection. The result of each update is maintained in the same evaluation matrix.
On the other hand, the invention also provides a use method for realizing the large parking lot dispatching navigation system, which comprises the following steps:
s1, the user arrives at the entrance of the parking lot according to the requirement;
s2, after the user enters the entrance of the parking lot, the user gives a destination to which the user wants to go, and then the optimal parking space position is calculated by combining the parking space condition near the destination and the optimal parking space selection module in the invention;
s3, the intelligent terminal sends the current position of the user and the position of the optimal parking space as requests to the global optimal scheduling module to perform overall scheduling and monitoring on the congestion condition in the parking lot, and the path planning module calculates the optimal path to the optimal parking space according to the current position and returns the optimal path to the intelligent terminal used by the user;
s4 whether the user reaches the target parking position when the user drives the vehicle to reach the intersection position or stops moving, if yes, navigation is finished, and if not, the method returns to S3.
Has the advantages that: according to the invention, the optimal parking space is given out by using the optimal parking space selection model in the invention near the destination in the parking lot according to the requirements of the user, then the optimal navigation path is given out by using the path planning model in the invention, the parking efficiency and the accuracy of the user are improved, and the problem of congestion caused by unclear road conditions in the parking lot in the process of searching the parking space is avoided.
Drawings
Fig. 1 is a schematic model diagram of a parking lot according to an embodiment of the present invention;
FIG. 2 is a flow chart of a method for using the dispatch navigation system of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in detail with reference to the accompanying drawings and specific embodiments.
Example 1
The invention is mainly used for solving the problems that a user in a large parking lot is difficult to find a parking space and the parking is difficult due to the fact that the jam condition in the parking lot is not clear in the peak period of using the parking lot. The optimal parking space selection model is used for giving the optimal parking space position near the destination according to the requirements of users, then the optimal path reaching the target parking space is given according to the optimal global scheduling model, and the latest navigation path is given according to the latest road congestion condition in the parking lot before the target parking space is reached.
Firstly, the invention provides a scheduling navigation method for a large parking lot, which comprises the following steps:
(1) constructing an optimal parking place selection model: abstracting parking lot scenes into grids, wherein each grid comprises a plurality of parking spaces, and setting the initial empty state of all the parking spaces in the parking lot; searching for an idle parking space by taking the set target position as a center; if no free parking space exists, enlarging the searched radius by one unit of grid until the free parking space is found, at the moment, calculating the selection weight of each free parking space, and further obtaining the optimal parking space according to the selection weight of the free parking space;
firstly, a parking lot scene is abstracted into a grid shape for modeling, as shown in fig. 1, the parking lot comprises buildings 1-8, roads are bidirectional lanes, each grid can contain 3 or 6 parking spaces according to the planning, and the initial empty state of all the parking spaces in the parking lot is set. And searching for free parking spaces in one week by taking the target position set by the user as the center. When no free parking space exists, the searched radius is enlarged by one unit of grid, and the process is repeated until the free parking space is found, and at the moment, P is setiIs an empty parking space, the distance from the empty parking space to the destination is DiThe time from the entrance of the parking lot to the vacant parking space is TiAnd i is the serial number of the idle parking space. Then the weight index of the selection of the free parking space is as follows:
in the formula, alpha is a distance influence factor of walking after parking; beta is an influence factor from the entrance of the parking lot to the target parking space; eta is the self factor of the parking space, and is generally 3, 6 and 9 according to the parking space condition.
The parameter alpha and the parameter beta represent the selection proportion of the vehicle time and the walking time of the user, and in the selection model of the optimal parking space, the parameter alpha and the parameter beta represent that the user is willing to select more paths to walk or find a closer parking space after parking. According to the optimal parking space model, the optimal parking space can be selected near the destination according to the intention of the owner.
(2) Constructing a global optimal scheduling model: estimating the time from the entrance of the parking lot to the optimal parking place according to the corresponding weight of the left and right directions of the road in the parking lot, thereby estimating the congestion condition of the parking lot;
when a large number of vehicles enter the parking lot at the same time, the beta factor in the optimal parking space selection model is not determined by subjective factors of users, and the congestion condition in the parking lot gives the time T from the entrance of the parking lot to the vacant parking spaceiWith a greater impact. In the parking lot scene, the situation that appears blocking up on the parking lot route is divided into two kinds: one is that the front vehicle is parking and entering the garage, and at this time, the rear vehicle has to stop to wait, and the front vehicle continues to move forward after stopping. In another case, when other vehicles need to pass through at the intersection, the vehicle has to stop to wait for the other vehicles to pass through before continuing to pass through. If special situations such as lane snatching occur, more time is needed to wait. Therefore, under the application background, the parking lot scene is divided in a gridding mode, and the length of one parking space is one unit length. Because roads are generally bidirectional lanes, each grid on a path has a WLjAnd WRjWeight, if the vehicle on the right side of the road continues to drive forward at the current position, then W at this timeRj1, and when there is a vehicle traveling on the left side of the road, the weight W is set toLjAlso 1. When the vehicle needs to be parked and put in storage after reaching the target parking space, W at the positionRjCorresponding weight increases need to be made.
Since the weight of each position on the route needs to be determined according to the traveling direction of the vehicle, the weight is determined according to the traveling direction of the vehicleThis unification sets the weight of that location to WjWherein, in the step (A),
the weights on the path and the required time relationship are then as follows:
in the formula, RjFor the position of the route, the model is set to use one unit time for each unit parking space driven by the vehicle. P of the vehicle owner finally travelingiThe time of parking space is Ti. Therefore, when the overall scheduling is carried out, a path selection algorithm needs to be optimized from the perspective of the path weight, and a path with low congestion degree can be selected to avoid the congestion condition.
The parking lot scheduling model can be used for integrally scheduling and monitoring the congestion condition in the parking lot, and the blindness of a user in selecting a route can be solved. Meanwhile, the system can provide real-time congestion conditions for the parking lot, and manage and control vehicles entering the parking lot.
(3) Path planning: and obtaining an evaluation matrix according to the global optimal scheduling model by combining a Floyd search algorithm, and updating the evaluation matrix in real time to realize path planning and scheduling of the parking lot.
The invention provides an overall optimal path planning mechanism aiming at the path planning characteristics of a parking lot, which is used for solving the congestion condition caused by the entrance or exit of a large number of users in the parking lot or similar environment. The system is planned and scheduled from a global perspective mainly by using the idea of a Floyd global optimization algorithm, so that the global effect on time and throughput is optimal. A series of evaluation indexes are added on the basis of the Floyd search algorithm, so that the system is integrally optimal. The method mainly comprises two parts of model establishment in the early stage and updating in planning.
In the model building stage, corresponding node and path weight models are required to be built according to actual environments, and the stage mainly requires a parking lot to be builtThe scene is abstracted into a grid form, as shown in figure 1, all intersections in the grid are set as a road intersection viAll the intersections are abstracted into a weighted directed graph G (V, E, W), where V ═ V is set as the intersection set1,v2,...,vnGreat face with path set E ═<vi，vj>|vi≠vj，vi，vjE.g., V) to describe whether each two intersections are connected, wherein the corresponding weight on the connected path is W ═ { W ═ij|wij>0}。
The invention uses the actual parking lot plane as a research prototype, and the intersection points of the paths can be abstracted into a directed graph model according to the plane graph. From the crossing paths in the planar graph, the crossing nodes in the graph generate a directed graph G (V, E, W), and initial weights are given according to the lengths of the edges. After the optimal destination parking space is selected according to the global optimal scheduling model introduced in the previous section, a distance evaluation matrix W is generated according to the weighted directed graphdTime evaluation matrix Wt。
Wherein d isijFor the distance between each intersection in the directed graph, tijThe travel time of the vehicle from the current position to the target parking space is determined. This travel time needs to be calculated using the weight model above, e.g. when i and j are connected intersections,
wherein, TkThe time from the entrance of the parking lot to the optimal parking space is described above.
Suppose viAnd vjIs any two points in the directed graph G (V, E, W) in the model.
Is provided with
Is v isiPoint to vjThe point does not pass through anyThe shortest length of the intermediate point is
Is v isiPoint to vjThe shortest time a point does not pass any intermediate point.
Then
And
respectively, a directed graph G (V, E, W) takes into account Vi、vjAnd v1Shortest path of three nodes and shortest time consumption.
Then viPoint to vjThere are two cases where the first is not going through v1Node, then dij 0＝dij 1(ii) a In another case, v passes1Node, then
Then
In the same way
Order to
For the directed graph G (V, E, W), V needs to be consideredi,vj,v1,v2,...,vl-1Situation of a node, then
Based on the iterative relationship, the weight matrix W can be updateddAnd WtSuch iterative operations are implemented each time the vehicle travels to an intersection. The result of each update is maintained in the same evaluation matrix.
In the path searching stage, the Floyd algorithm is adopted for global searching, and in the searching process, the distance evaluation matrix W of the optimal parking space selection model to the path weight is adopteddAnd time evaluation matrix WtAnd (6) updating. And the global optimal search and planning of the parking lot are ensured on the premise of ensuring the parking willingness of the car owner.
Example 2
On the other hand, the invention also provides a large parking lot dispatching navigation system, which comprises:
the optimal parking place selection module is used for abstracting a parking place scene into grids, each grid comprises a plurality of parking places, and the initial empty state of all the parking places in the parking place is set; searching for an idle parking space by taking the set target position as a center; if no free parking space exists, enlarging the searched radius by one unit of grid until the free parking space is found, at the moment, calculating the selection weight of each free parking space, and further obtaining the optimal parking space according to the selection weight of the free parking space;
firstly, a parking lot scene is abstracted into grids for modeling, as shown in fig. 1, each grid can contain 3 or 6 parking spaces according to a plan, and all the parking spaces in the parking lot are set to be in an empty state initially. And searching for free parking spaces in one week by taking the target position set by the user as the center. When no free parking space exists, the searched radius is enlarged by one unit of grid, and the process is repeated until the free parking space is found, and at the moment, P is setiIs an empty parking space, the distance from the empty parking space to the destination is DiThe time from the entrance of the parking lot to the vacant parking space is TiAnd i is the serial number of the idle parking space. Then the weight index of the selection of the free parking space is as follows:
in the formula, alpha is a distance influence factor of walking after parking; beta is an influence factor from the entrance of the parking lot to the target parking space; eta is the self factor of the parking space, and is generally 3, 6 and 9 according to the parking space condition.
The parameter alpha and the parameter beta represent the selection proportion of the vehicle time and the walking time of the user, and in the selection model of the optimal parking space, the parameter alpha and the parameter beta represent that the user is willing to select more paths to walk or find a closer parking space after parking. According to the optimal parking space model, the optimal parking space can be selected near the destination according to the intention of the owner.
The global optimal scheduling module is used for estimating the time from an entrance of the parking lot to the optimal parking place according to the corresponding weight of the left direction and the right direction of the road in the parking lot, so that the congestion condition of the parking lot is estimated;
the global optimal scheduling module further comprises:
a lane weight representation unit for firstly assuming that the road of the parking lot is a bidirectional lane, and the left and right sides of each corresponding grid are provided with WLjAnd WRjA weight;
if the vehicle on the right side of the road continues to drive forward at the current position, WRj1, and when there is a vehicle running on the left side of the road, the weight WLjIs also 1;
when the vehicle needs to be parked and put in storage after reaching the optimal parking space, the W at the position needs to be checked because the vehicle needs to occupy the road beside the road when parking and putting in storagejIncrease by 1 and subtract by 1 the weight of the location after parking.
The vehicle finally drives to the optimal parking space P from the entrance of the parking lotiThe time used is TiExpressed as:
wherein R isjAnd setting the use of one unit time for each unit parking space driven by the automobile for the position of the path. Since roads are bidirectional, the road weight of each position needs to be selected according to actual conditions during route selection, and therefore the left side and the right side of each road are combined into a whole
If there are different routes from the starting point to the end point, the corresponding weight needs to be selected according to the actual situation.
And the path planning module is used for obtaining an evaluation matrix according to the global optimal scheduling model by combining a Floyd search algorithm, and updating the evaluation matrix in real time to realize path planning and scheduling of the parking lot.
The path planning module comprises:
an evaluation matrix calculation unit configured to calculate the distance evaluation matrix and the time evaluation matrix:
setting all intersections in the parking lot as a road intersection viAll the intersections are put into a weighted directed graph G (V, E, W), where V ═ V is set as the intersection set1,v2,...,vnGreat face with path set E ═<vi，vj>|vi≠vj，vi，vjE.g. V) to describe whether each two intersections are communicated, and the corresponding weight on the communicated path is W ═ Wij|wij>0}，vjIs any one intersection point in the weighted directed graph G (V, E, W);
generating a distance evaluation matrix W according to the weighted directed graphdAnd time evaluation matrix Wt：
Wherein d isijFor the distance between each intersection in the directed graph, tijThe travel time of the vehicle from the current position to the optimal parking space,
Tkfor the final driving of the vehicle from the entrance of the parking lot to the optimal parking space PkThe time taken;
an evaluation matrix updating unit for updating the distance evaluation matrix WdAnd time evaluation matrix Wt：
Is provided with
Is v isiPoint to vjThe shortest length at which a point does not pass through any intermediate point,
is v isiPoint to vjThe shortest time for a point not to pass any intermediate point, then:
then
And
respectively, a directed graph G (V, E, W) takes into account Vi、vjAnd v1Shortest path and shortest time consumption of three nodes;
if v isiPoints v and vjPoint of no passing through v1Node, then dij 0＝dij 1，tij 0＝tij 1Otherwise, there is
Then
Order to
For the directed graph G (V, E, W), V needs to be consideredi,vj,v1,v2,...,vl-1Situation of a node, then
Based on the iterative relationship, the weight matrix W can be updateddAnd WtSuch iterative operations are implemented each time the vehicle travels to an intersection. The result of each update is maintained in the same evaluation matrix.
On the other hand, the present invention further provides a use method implemented by the large parking lot dispatching navigation system, as shown in fig. 2, including:
s1, the user arrives at the entrance of the parking lot according to the requirement;
s2, after the user enters the entrance of the parking lot, the user gives a destination to which the user wants to go, and then the optimal parking space position is calculated by combining the parking space condition near the destination and the optimal parking space selection module in the invention;
s3, the intelligent terminal sends the current position of the user and the position of the optimal parking space as requests to the global optimal scheduling module to perform overall scheduling and monitoring on the congestion condition in the parking lot, and the path planning module calculates the optimal path to the optimal parking space according to the current position and returns the optimal path to the intelligent terminal used by the user;
s4 whether the user reaches the target parking position when the user drives the vehicle to reach the intersection position or stops moving, if yes, navigation is finished, and if not, the method returns to S3.
The route planning module, the optimal parking space selection module and the global optimal scheduling module are implemented in the server.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (4)
1. A large parking lot scheduling navigation method is characterized by comprising the following steps:
(1) constructing an optimal parking place selection model: abstracting parking lot scenes into grids, wherein each grid comprises a plurality of parking spaces, and setting the initial empty state of all the parking spaces in the parking lot; searching for an idle parking space by taking the set target position as a center; if no free parking space exists, enlarging the searched radius by one unit of grid until the free parking space is found, at the moment, calculating the selection weight of each free parking space, and further obtaining the optimal parking space according to the selection weight of the free parking space;
(2) constructing a global optimal scheduling model: estimating the time from the entrance of the parking lot to the optimal parking place according to the corresponding weight of the left and right directions of the road in the parking lot, thereby estimating the congestion condition of the parking lot;
(3) path planning: obtaining an evaluation matrix according to the global optimal scheduling model by combining a Floyd search algorithm, and updating the evaluation matrix in real time to realize path planning and scheduling of the parking lot;
estimating the time from the entrance of the parking lot to the optimal parking space according to the corresponding weight of the left and right directions of the road in the parking lot, specifically comprising:
assuming that the roads of the parking lot are bidirectional lanes, the left side and the right side of each corresponding grid are provided with WLjAnd WRjA weight;
if the vehicle on the right side of the road continues to drive forward at the current position, WRj1, and when there is a vehicle running on the left side of the road, the weight WLjIs also 1;
when the vehicle needs to be parked and put in storage after reaching the optimal parking space, the W at the position needs to be checked because the vehicle needs to occupy the road beside the road when parking and putting in storagejIncreasing 1, and performing 1 reduction operation on the weight of the position after parking;
the vehicle finally drives to the optimal parking space P from the entrance of the parking lotiThe time used is TiExpressed as:
wherein R isjSetting a unit time for each unit parking space driven by the automobile as the position of the path; since roads are bidirectional, the road weight of each position needs to be selected according to the actual route when selecting a route, so that the left side and the right side of each road are combined into a whole
Obtaining an evaluation matrix according to the global optimal scheduling model by combining a Floyd search algorithm, and updating the evaluation matrix in real time, wherein the method comprises the following steps:
the evaluation matrix comprises a distance evaluation matrix and a time evaluation matrix, and the distance evaluation matrix and the time evaluation matrix are firstly calculated:
setting all intersections in the parking lot as a road intersection viAll the intersections are put into a weighted directed graph G (V, E, W), where V ═ V is set as the intersection set1,v2,...,vnGreat face with path set E ═<vi，vj>|vi≠vj，vi，vjE.g. V) to describe whether each two intersections are communicated, and the corresponding weight on the communicated path is W ═ Wij|wij>0}，vjIs any one intersection point in the weighted directed graph G (V, E, W);
generating a distance evaluation matrix W according to the weighted directed graphdAnd time evaluation matrix Wt：
Wherein d isijFor the distance between each intersection in the directed graph, tijThe travel time of the vehicle from the current position to the optimal parking space,
Tkfor the final driving of the vehicle from the entrance of the parking lot to the optimal parking space PkThe time taken;
updating the distance evaluation matrix WdAnd time evaluation matrix Wt：
Is provided with
Is v isiPoint to vjThe shortest length at which a point does not pass through any intermediate point,
is v isiPoint to vjThe shortest time for a point not to pass any intermediate point, then:
then
And
respectively, a directed graph G (V, E, W) takes into account Vi、vjAnd v1Shortest path and shortest time consumption of three nodes;
if v isiPoints v and vjPoint of no passing through v1Node, then dij 0＝dij 1，tij 0＝tij 1Otherwise, there is
Then
Order to
For the directed graph G (V, E, W), V needs to be consideredi,vj,v1,v2,...,vl-1Situation of a node, then
Based on the iterative relationship, the weight matrix W can be updateddAnd WtSuch iterative operation is realized every time the vehicle travels to an intersection, and the result of each update is maintained in the same evaluation matrix.
2. The large parking lot scheduling navigation method according to claim 1, wherein the weight of the free parking space selection comprises:
W(Pi)＝αDi+βTi+η
α+β＝1
wherein, PiIs an empty parking space, the distance from the empty parking space to the destination is DiAt the entrance of the parking lotThe time of the idle parking space is TiI is the serial number of the idle parking space, alpha is the influence factor of the walking distance after parking, beta is the influence factor from the entrance of the parking lot to the target parking space, eta is the self factor of the parking space, and the values are 3, 6 and 9 according to the parking space condition.
3. A large parking lot dispatching navigation system is characterized by comprising:
the optimal parking place selection module is used for abstracting a parking place scene into grids, each grid comprises a plurality of parking places, and the initial empty state of all the parking places in the parking place is set; searching for an idle parking space by taking the set target position as a center; if no free parking space exists, enlarging the searched radius by one unit of grid until the free parking space is found, at the moment, calculating the selection weight of each free parking space, and further obtaining the optimal parking space according to the selection weight of the free parking space;
the global optimal scheduling module is used for estimating the time from an entrance of the parking lot to the optimal parking place according to the corresponding weight of the left direction and the right direction of the road in the parking lot, so that the congestion condition of the parking lot is estimated;
the path planning module is used for obtaining an evaluation matrix according to the global optimal scheduling model by combining a Floyd search algorithm, updating the evaluation matrix in real time and realizing path planning and scheduling of the parking lot;
the global optimal scheduling module further comprises:
a lane weight representation unit for firstly assuming that the road of the parking lot is a bidirectional lane, and the left and right sides of each corresponding grid are provided with WLjAnd WRjA weight;
if the vehicle on the right side of the road continues to drive forward at the current position, WRj1, and when there is a vehicle running on the left side of the road, the weight WLjIs also 1;
when the vehicle needs to be parked and put in storage after reaching the optimal parking space, the W at the position needs to be checked because the vehicle needs to occupy the road beside the road when parking and putting in storagejIncrease 1 for the position after parkingThe weight of (1) is subtracted from the weight of (1);
the vehicle finally drives to the optimal parking space P from the entrance of the parking lotiThe time used is TiExpressed as:
wherein R isjSetting a unit time for each unit parking space driven by the automobile as the position of the path; since roads are bidirectional, the road weight of each position needs to be selected according to actual conditions during route selection, and therefore the left side and the right side of each road are combined into a whole
A path planning module, comprising:
an evaluation matrix calculation unit configured to calculate the distance evaluation matrix and the time evaluation matrix:
setting all intersections in the parking lot as a road intersection viAll the intersections are put into a weighted directed graph G (V, E, W), where V ═ V is set as the intersection set1,v2,...,vnGreat face with path set E ═<vi，vj>|vi≠vj，vi，vjE.g. V) to describe whether each two intersections are communicated, and the corresponding weight on the communicated path is W ═ Wij|wij>0}，vjIs any one intersection point in the weighted directed graph G (V, E, W);
generating a distance evaluation matrix W according to the weighted directed graphdAnd time evaluation matrix Wt：
Wherein d isijFor the distance between each intersection in the directed graph, tijThen it is the current vehicleThe travel time of the location to the optimal parking space,
Tkfor the final driving of the vehicle from the entrance of the parking lot to the optimal parking space PkThe time taken;
an evaluation matrix updating unit for updating the distance evaluation matrix WdAnd time evaluation matrix Wt：
Is provided with
Is v isiPoint to vjThe shortest length at which a point does not pass through any intermediate point,
is v isiPoint to vjThe shortest time for a point not to pass any intermediate point, then:
then
And
respectively, a directed graph G (V, E, W) takes into account Vi、vjAnd v1Shortest path and shortest time consumption of three nodes;
if v isiPoints v and vjPoint of no passing through v1Node, then dij 0＝dij 1，tij 0＝tij 1Otherwise, there is
Then
Order to
For the directed graph G (V, E, W), V needs to be consideredi,vj,v1,v2,...,vl-1Situation of a node, then
Based on the iterative relationship, the weight matrix W can be updateddAnd WtSuch iterative operation is realized every time the vehicle travels to an intersection, and the result of each update is maintained in the same evaluation matrix.
4. The large parking lot dispatching navigation system according to claim 3, wherein in the optimal parking space selection module, the weight of the selection of the free parking spaces comprises:
W(Pi)＝αDi+βTi+η
α+β＝1
wherein, PiIs an empty parking space, the distance from the empty parking space to the destination is DiThe time from the entrance of the parking lot to the vacant parking space is TiI is the serial number of the idle parking space, alpha is the influence factor of the walking distance after parking, beta is the influence factor from the entrance of the parking lot to the target parking space, eta is the self factor of the parking space, and the values are 3, 6 and 9 according to the parking space condition.
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