CN114783200B - Dynamic and static linkage vehicle path guiding method, device and storage medium - Google Patents
Dynamic and static linkage vehicle path guiding method, device and storage medium Download PDFInfo
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- G—PHYSICS
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
- G08G1/145—Traffic control systems for road vehicles indicating individual free spaces in parking areas where the indication depends on the parking areas
- G08G1/148—Management of a network of parking areas
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Abstract
The invention relates to a dynamic and static linkage vehicle path guiding method, a device and a storage medium, wherein the method comprises the following steps: step S1: acquiring real-time data of each road; step S2: establishing a directionally weighted complex network of the road network; step S3: determining an alternative point set of the end point of the parked vehicle according to the destination of the parked vehicle, wherein the alternative points in the alternative point set are nodes corresponding to the inlets of the parking lots; step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parking vehicle to each alternative point in the complex network by using a shortest path algorithm as a path corresponding to the alternative point; step S5: and selecting an alternative point corresponding to the shortest path in all paths as a destination of the parking vehicle, and guiding the measured parking vehicle into a parking lot for parking according to the path corresponding to the actual route. Compared with the prior art, the invention has the advantages of improving parking efficiency and experience and the like.
Description
Technical Field
The present invention relates to a parking guidance method, and in particular, to a method, an apparatus, and a storage medium for guiding a vehicle path in dynamic and static linkage.
Background
With the continuous rising of parking demands, limited parking space supply and unreasonable parking space distribution cause urban parking difficulties. The construction of ultra-large parking lots is one of important means for solving the problem of difficult parking of urban complex, and the large parking lots often have a plurality of entrances. In peak time, a large amount of parking vehicles often face an entrance selection problem when driving into a parking lot, on the premise of unknown road network congestion state, the entrance of the parking lot is selected nearby, so that long-time congestion and queuing can be caused, the user experience is poor, the confusion of dynamic traffic is easily further caused, and the traffic efficiency is low.
In the conventional vehicle guidance method, only an algorithm for navigating to a parking lot or an algorithm for navigating from an entrance to a parking space is generally provided, the entrance of the parking lot is not optimized or selected as a variable, and the shortest path calculation is generally performed under the condition that off-line road speed information is taken as a known condition, so that the efficiency cannot be improved by using real-time data.
Disclosure of Invention
The invention aims to solve the problem of entrance selection of a parking vehicle in a parking lot rapidly entering the parking lot in a road network congestion state, and provides a vehicle path guiding method, device and storage medium for dynamic and static linkage.
The aim of the invention can be achieved by the following technical scheme:
a dynamic and static linkage vehicle path guiding method comprises the following steps:
step S1: acquiring a target range according to the current position of the parking vehicle and the characteristics of a target parking lot, and acquiring real-time data of each road in the target range;
step S2: taking the intersection, the starting point position of the parking vehicle and the entrance and exit position of the parking lot as nodes of a network, taking roads in the road network as directed edges of the network, setting weights of the directed edges by real-time data of the roads, and establishing a complex network with directed weights of the road network;
step S3: determining an alternative point set of the end point of the parked vehicle according to the destination of the parked vehicle, wherein the alternative points in the alternative point set are nodes corresponding to the inlets of the parking lots;
step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parking vehicle to each alternative point in the complex network by using a shortest path algorithm as a path corresponding to the alternative point;
step S5: and selecting an alternative point corresponding to the shortest path in all paths as a destination of the parking vehicle, and guiding the measured parking vehicle into a parking lot for parking according to the path corresponding to the actual route.
The real-time data includes an average travel speed of the vehicle in the road,
the weight of the directed edge is specifically as follows:
wherein: w (w) ij L is the weight of the directed edge directed from node i to node j ij V, the length of the road being the directed edge from node i to node j ij Is the average travel speed of the vehicle in the road from node i to the directed edge of node j.
The target parking lot is a single parking lot or a combination of multiple parking lots, and the roads include municipal roads and roads within the parking lot.
In the step S4, the distance of the directed edge sequence is the sum of the weights of the directed edges in the directed edge sequence.
The shortest distance is:
wherein: w (W) m (q min ) For the shortest distance to the mth candidate point, min () is a decreasing function, χ (s, t m ) Is s as the starting point and t as the end point m W (q) is the sum of the weights of all the directed edges, W (e) is the weight of the directed edge, e is the directed edge, and q is the set of all the directed edges in the directed edge sequence.
The target range contains the necessary road of the parking vehicle to the parking lot entrance and the road where the parking lot exit is located, and all road networks in the set range near the area where the parking lot is located or the land block.
The real-time data of the road are connected by intelligent detection devices arranged on two sides of the road.
The intelligent detection device comprises a coil sensor, a high-definition camera and a millimeter wave radar.
The dynamic and static linkage vehicle path guiding device comprises a memory, a processor and a program stored in the memory, and is characterized in that the processor realizes the method when executing the program.
The program when executed implements a method as described above.
Compared with the prior art, the invention has the following beneficial effects:
1. by using real-time data of traffic state detection devices of road networks around a parking lot, a directionally weighted road network is established by taking road running time as side weight, and running routes of different parking lot entrances are selected for parking vehicles under different congestion states of the road network by calculating and comparing and selecting shortest paths among different starting and ending points, so that an optimal method for guiding vehicle paths is provided for parking vehicles in the parking lot, parking efficiency and experience can be improved, congestion conditions of the road network can be further increased, and road network traffic efficiency is improved.
2. The average running speed and the road length are adopted as the basis for weight setting, on one hand, the running time of each vehicle on the road is used as the cost for evaluating the shortest path, and the situation of real traffic scenes is met; on the other hand, compared with the method that only the road length is used as the weight, the speed of each time interval is updated through real-time data, so that the weight can be changed in real time, the running time which is changed continuously in the road is represented in a self-adaptive mode, and the optimal parking path selection can be provided for the parking vehicle on line.
3. The target parking lot is a single parking lot or a combination of a plurality of parking lots, the roads comprise municipal roads and roads in the parking lots, and the joint allocation of the parking lots can be realized, so that the parking efficiency is improved.
Drawings
FIG. 1 is a schematic flow chart of the present invention;
FIG. 2 is a schematic diagram of a complex network established for a road network within the scope of the present invention;
FIG. 3 is a schematic illustration of a start and end point of a parked vehicle according to the present invention;
fig. 4 is a schematic diagram of a specific example in the embodiment.
Detailed Description
The invention will now be described in detail with reference to the drawings and specific examples. The present embodiment is implemented on the premise of the technical scheme of the present invention, and a detailed implementation manner and a specific operation process are given, but the protection scope of the present invention is not limited to the following examples.
A dynamic and static linkage vehicle path guiding method, as shown in figure 1, comprises the following steps:
step S1: and acquiring a target range according to the current position of the parking vehicle and the characteristics of a target parking lot, and acquiring real-time data of each road in the target range, wherein the target range is also used as a research range, and as shown in fig. 3, the target range comprises roads where the parking vehicle passes through the entrance of the parking lot and the exit of the parking lot, and all road networks in a range of 2 km near the area or the land block where the parking lot is located.
The real-time data of road is connected by the intelligent detection device who locates the road both sides, and intelligent detection device's kind includes the intelligent detector of speed measuring such as coil sensor, high definition digtal camera and millimeter wave radar, traffic state information such as the speed of road, flow can real-time output.
Step S2: setting weights of the directional edges by taking the intersection, the starting point position of the parking vehicle and the entrance and exit position of the parking lot as nodes of a network, taking roads in the road network as the directional edges of the network, and setting the weights of the directional edges by real-time data of the roads to establish a directionally weighted complex network G= (V, E) of the road network;
the nodes of the network abstract the starting point of the parked vehicle, the intersection in the road and the parking lot exit (the end point of the parked vehicle) into the nodes in the complex network G, and the set of the nodes is denoted by V. The directed edge abstracts the urban traffic road connected between the nodes into the directed edge in the complex network G, the set of edges is represented by E, and the weight w=w (E) of the directed edge of the network is a real function with a definition domain of E, which is called the weight of the directed edge E in the complex network G. In this embodiment, the real-time data includes an average running speed of the vehicle in the road,
the weights of the directed edges are specifically:
wherein: w (w) ij L is the weight of the directed edge directed from node i to node j ij V, the length of the road being the directed edge from node i to node j ij Is the average travel speed of the vehicle in the road from node i to the directed edge of node j.
Step S3: determining an alternative point set of the end point of the parked vehicle according to the destination of the parked vehicle, wherein the alternative points in the alternative point set are nodes corresponding to the inlets of the parking lots;
wherein, the set of all entrances of the parking lot is T, and T= { T 1 ,t 2 ,…t m }
In this embodiment, the target parking lot is a single parking lot or a combination of a plurality of parking lots, and the road includes the municipal road and the road in the parking lot, so that the joint allocation of the parking lots can be realized, thereby improving the parking efficiency.
Step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parking vehicle to each alternative point in the complex network by using a shortest path algorithm as a path corresponding to the alternative point;
in step S4, the distance of the directed edge sequence is the sum of the weights of the directed edges in the directed edge sequence.
The shortest path algorithm refers to all algorithms capable of solving the shortest path problem of the directional weighted network. The shortest path algorithm is that from the departure place s of the parking vehicle to any destination t in the candidate destination set of the parking vehicle m E, respectively solving the effective paths of TA weighted and minimum effective pathThe calculation formula is as follows:
wherein: w (W) m (q min ) For the shortest distance to the mth alternative entry, min () is a decreasing function, χ (s, t m ) Is s as the starting point and t as the end point m W (q) is the sum of the weights of all the directed edges, W (e) is the weight of the directed edge, e is the directed edge, and q is the set of all the directed edges in the directed edge sequence.
Step S5: and selecting an alternative point corresponding to the shortest path in all paths as a destination of the parking vehicle, and guiding the measured parking vehicle into a parking lot for parking according to the path corresponding to the actual route.
The parking route with the shortest path is calculated as follows:
R＝min{W 1 (q min ),W 2 (q min ),…W m (q min )}
wherein: r is the parking route with the shortest path in m alternative entrances.
As shown in fig. 4, a certain large parking lot is provided with 2 entrances M, N on different roads, and surrounding roads are subjected to holographic sensing of road network states through millimeter wave radar-high-definition cameras. And a vehicle with a destination of the parking lot runs to the road network O, and the system platform starts to adopt a dynamic and static linkage vehicle path guiding algorithm to issue guiding path instructions for the vehicle. The specific process is as follows:
step S1: and acquiring a target range according to the current position O of the parking vehicle and the characteristics of the target parking lot, and acquiring real-time data of each road in the target range as shown in the figure.
Step S2: taking an intersection (A, B … K), a starting point position O of a parking vehicle and an entrance and exit position M, N of a parking lot as nodes of a network, taking a road in a road network as a directed edge of the network, setting weights of the directed edges by real-time data of the road, and establishing a complex network with directed weights of the road network;
and obtaining the length and the average running speed of each known road in the previous 1min according to the millimeter wave radar-high-definition camera device at the road side. The length, average speed and edge weight of the road are shown in the following table:
step S3: determining a set of candidate points M, N of the end points of the parked vehicle according to the destination of the parked vehicle, wherein the candidate points in the set of candidate points are nodes corresponding to the entrances of the parking lots;
step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parking vehicle to each alternative point in the complex network by using a shortest path algorithm as a path corresponding to the alternative point;
for the first entry M, the sequence of vehicle parking paths and their weights sum to:
(1) The sum of the weights of O-B-D-C-M w=5+6+6+4=21
(2) The sum of the weights of O-I-D-C-M w=10+5+6+4=25
(3) The sum of the weights of O-I-J-F-E-M w=10+5+5+6+4=30
(4) The sum of the weights of O-B-ase:Sub>A-C-M w=5+6+10+4=25
Shortest distance W M =21, the corresponding path is O-B-D-C-M, the sum of weights W M ＝5+6+6+4＝21
For the second portal N, the sequence of vehicle parking paths and their weights are summed as:
(1) The sum of the weights of O-B-D-N w=5+6+1=12
(2) The sum of the O-I-D-N weights w=10+5+1=16
(3) The sum of the weights of O-I-J-F-N w=10+5+5+5=25
Shortest distance W N =12, the corresponding path is O-B-D-N, the sum of weights W N ＝5+6+1＝12
Step S5: selecting the shortest path r=w among all paths N The corresponding alternative point N is used as a destination of the parking vehicle, and the parking vehicle is guided to enter the parking lot for parking according to the path (O-B-D-N) corresponding to the actual route.
The above functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
Claims (6)
1. A dynamic-static linkage vehicle path guiding method, characterized by comprising:
step S1: acquiring a target range according to the current position of the parking vehicle and the characteristics of a target parking lot, and acquiring real-time data of each road in the target range;
step S2: taking the intersection, the starting point position of the parking vehicle and the entrance and exit position of the parking lot as nodes of a network, taking roads in the road network as directed edges of the network, setting weights of the directed edges by real-time data of the roads, and establishing a complex network with directed weights of the road network;
step S3: determining an alternative point set of the end point of the parked vehicle according to the destination of the parked vehicle, wherein the alternative points in the alternative point set are nodes corresponding to the inlets of the parking lots;
step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parking vehicle to each alternative point in the complex network by using a shortest path algorithm as a path corresponding to the alternative point;
step S5: selecting an alternative point corresponding to the shortest path in all paths as a destination of the parking vehicle, and guiding the measured parking vehicle to enter a parking lot for parking according to the path corresponding to the actual route;
the real-time data includes an average travel speed of the vehicle in the road,
the weight of the directed edge is specifically as follows:
wherein: w (w) ij L is the weight of the directed edge directed from node i to node j ij V, the length of the road being the directed edge from node i to node j ij The average travel speed of the vehicle in the road from node i to the directed edge of node j;
the target parking lot is a single parking lot or a combination of a plurality of parking lots, and the roads comprise municipal roads and roads in the parking lots;
in the step S4, the distance of the directed edge sequence is the sum of the weights of the directed edges in the directed edge sequence;
the shortest distance is:
wherein: w (W) m (q min ) For the shortest distance to the mth candidate point, min () is a decreasing function, χ (s, t m ) Is s as the starting point and t as the end point m W (q) is the sum of the weights of all the directed edges, W (e) is the weight of the directed edge, e is the directed edge, and q is the set of all the directed edges in the directed edge sequence.
2. The method according to claim 1, wherein the target range includes a road where a parked vehicle is located on a necessary road leading to an entrance of a parking lot and an exit of the parking lot, and all road networks within a set range in a region where the parking lot is located or in the vicinity of a land block.
3. The method for guiding a vehicle path in dynamic and static linkage according to claim 1, wherein the real-time data of the road is connected by intelligent detection devices arranged on both sides of the road.
4. The dynamic and static linkage vehicle path guiding method according to claim 3, wherein the types of the intelligent detection device comprise coil sensors, high-definition cameras and millimeter wave radars.
5. A vehicle path guiding device with dynamic and static linkage, comprising a memory, a processor and a program stored in the memory, wherein the processor implements the method of any one of claims 1-4 when executing the program.
6. A storage medium having a program stored thereon, wherein the program, when executed, implements the method of any of claims 1-4.
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