CN114783200A - Dynamic and static linkage vehicle path guiding method and device and storage medium - Google Patents
Dynamic and static linkage vehicle path guiding method and device and storage medium Download PDFInfo
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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 directed weighted complex network of a road network; step S3: determining an alternative point set of the terminal point of the parked vehicle according to the destination of the parked vehicle, wherein alternative points in the alternative point set are nodes corresponding to each parking lot entrance; step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parked 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 route in all the routes as a destination of the parked vehicle, and guiding the parked vehicle to enter the parking lot for parking according to the route corresponding to the real route of the route. Compared with the prior art, the parking system 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 more particularly, to a dynamic and static linkage vehicle route guidance method, device, and storage medium.
Background
With the increasing demand for parking, the problem of difficulty in parking in cities is caused by limited parking space supply and unreasonable parking space distribution. The construction of an ultra-large parking lot is one of important means for solving the problem of difficulty in parking of a city complex, and the large parking lot is often provided with a plurality of entrances. In a peak period, a large number of parking vehicles often face an entrance selection problem when driving into a parking lot, long-time congestion and queuing can be caused by selecting the entrance of the parking lot nearby on the premise that the congestion state of a road network is unknown, the user experience is poor, dynamic traffic confusion is easily caused, and the traffic efficiency is low.
The past vehicle guidance method generally only provides an algorithm for navigating to a parking lot or an algorithm for navigating from an entrance to a parking space, the entrance of the parking lot is not optimized or selected as a variable, and the shortest path calculation is usually performed by taking off-line road speed information as a known condition, so that the efficiency cannot be improved by utilizing real-time data.
Disclosure of Invention
The invention aims to provide a dynamic and static linked vehicle path guiding method, a device and a storage medium aiming at the problem of selecting an entrance of a parking lot for parking vehicles to rapidly enter the parking lot under the road network congestion state.
The purpose of the invention can be realized 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 a 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 intersections, starting positions of parked vehicles and entrance and exit positions of a parking lot as nodes of a network, taking roads in the road network as directed edges of the network, setting the weight of each directed edge according to real-time data of the roads, and establishing a directed weighted complex network of the road network;
step S3: determining an alternative point set of the terminal point of the parked vehicle according to the destination of the parked vehicle, wherein alternative points in the alternative point set are nodes corresponding to each parking lot entrance;
step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parked vehicle to each alternative point in the complex network by using a shortest path algorithm to serve as a path corresponding to the alternative point;
step S5: and selecting the alternative point corresponding to the shortest route in all the routes as the destination of the parked vehicle, and guiding the measured parked vehicle to enter the parking lot for parking according to the route corresponding to the real route of the route.
The real-time data includes an average traveling speed of the vehicle on the road,
the weight of the directed edge is specifically:
wherein: w is aijAs a weight of a directed edge pointed to by node j, LijLength of road as directed edge pointed to by node j, vijThe average travel speed of the vehicle in the road that is the directed edge pointed to by node j by node i.
The target parking lot location is a single parking lot or a combination of parking lots, and the road includes a town road and a road in the parking lot.
In step S4, the distance of the directional edge sequence is the sum of the weights of the directional edges in the directional edge sequence.
The shortest distance is:
wherein: w is a group ofm(qmin) Min () is a small function, χ (s, t), as the shortest distance to the m-th alternate pointm) Is s as the starting point and t as the end pointmW (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 comprises a road which is bound to pass through a parking vehicle and is led to an entrance of the parking lot, a road where an exit of the parking lot is located, and all road networks in a set range in the area or the vicinity of the parking lot.
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.
A 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 executes the program to realize the method.
Which when executed performs the method as described above.
Compared with the prior art, the invention has the following beneficial effects:
1. the method comprises the steps of establishing a directional weighted road network by utilizing real-time data of a traffic state detection device of a road network around a parking lot and taking road running time as side weight, and selecting running routes of different parking lot entrances for parking vehicles in different congestion states of the road network by calculating and comparing shortest paths between different starting and ending points.
2. The average running speed and the road length are used as the basis for weight setting, so that on one hand, the running time of each vehicle on the road is used as the cost for evaluating the shortest path, and the condition of a real traffic scene is met; on the other hand, compared with the method that only the length of the road 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 of the road which is changed constantly is represented in a self-adaptive mode, and the optimal parking path selection can be provided for the parked vehicles on line.
3. The target parking lot is a single parking lot or a combination of a plurality of parking lots, the road comprises a municipal road and a road in the parking lot, 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 diagram of the present invention;
FIG. 2 is a schematic diagram of a complex network established for a road network in a research scope according to the present invention;
FIG. 3 is a schematic diagram of the starting and ending points of a parked vehicle according to the present invention;
FIG. 4 is a schematic diagram of an embodiment of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. The present embodiment is implemented on the premise of the technical solution of the present invention, and a detailed implementation manner and a specific operation process are given, but the scope of the present invention is not limited to the following embodiments.
A dynamic-static linked vehicle route guidance method, as shown in fig. 1, includes:
step S1: a target range is obtained according to the current position of the parked vehicle and the characteristics of the target parking lot, and real-time data of each road in the target range is obtained, wherein the target range is also used as a research range, as shown in fig. 3, the target range includes a road where the parked vehicle is led to the entrance of the parking lot, a road where the exit of the parking lot is located, and all road networks in a range of 2 kilometers near the area or the plot where the parking lot is located.
The real-time data of road is connected by the intellectual detection system who locates the road both sides, and the kind of intellectual detection system includes intelligent detection system that tests the speed, the flow measurement such as coil sensor, high definition digtal camera and millimeter wave radar, can output traffic status information such as speed, the flow of road in real time.
Step S2: taking the intersection, the starting position of the parked vehicle and the entrance and exit position of the parking lot as nodes of the network, taking the road in the road network as directed edges of the network, setting the weight of each directed edge according to the real-time data of the road, and establishing a complex network G (V, E) with directed weighting of the road network;
the nodes of the network are nodes in the complex network G, which are abstracted from the start point of a parked vehicle, the intersection on the road, and the exit of a parking lot (the end point of the parked vehicle), and the set of the nodes is represented by V. The directed edge is obtained by abstracting the urban traffic road connecting each node into a directed edge in the complex network G, the set of edges is represented by E, and the weight w (E) of the network directed edge is a real function with the domain defined as E and is called as the weight of the directed edge E in the complex network G. In this embodiment, the real-time data includes the average traveling speed of the vehicles on the road,
the weight of the directed edge is specifically:
wherein: w is aijAs a weight of a directed edge pointed to by node j, LijLength of road as directed edge pointed to by node j, vijThe average travel speed of the vehicle in the road that is the directed edge pointed to by node j by node i.
Step S3: determining an alternative point set of the terminal point of the parked vehicle according to the destination of the parked vehicle, wherein alternative points in the alternative point set are nodes corresponding to each parking lot entrance;
wherein the set of all entrances of the parking lot is T,T＝{t1,t2,…tm}
in this embodiment, a single parking lot or a combination of multiple parking lots in the target parking lot location, where the road includes a town road and a road in the parking lot, may implement joint deployment of the parking lots, thereby improving parking efficiency.
Step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parked 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 directional edge sequence is the sum of the weights of the directional edges in the directional edge sequence.
The shortest path algorithm refers to all algorithms capable of solving the shortest path problem of the directed weighting network. The shortest path algorithm is used for calculating the shortest path between the starting place s of the parked vehicles and any terminal point t in the candidate terminal point set of the parked vehiclesmFinding a weight and the minimum effective path from the effective paths in the form of E T
The calculation formula is as follows:
wherein: wm(qmin) Min () is a small function, χ (s, t), for the shortest distance to the mth candidate entrym) Is s as the starting point and t as the end pointmW (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 route in all the routes as a destination of the parked vehicle, and guiding the parked vehicle to enter the parking lot for parking according to the route corresponding to the real route of the route.
The calculation mode of the parking route with the shortest route is as follows:
R＝min{W1(qmin),W2(qmin),…Wm(qmin)}
wherein: and R is the parking route with the shortest path among the m alternative entrances.
As shown in fig. 4, 2 entrances M, N are arranged on different roads of a large parking lot, and holographic perception of the road network state is achieved by the aid of millimeter wave radars and high-definition cameras on surrounding roads. And firstly, when the vehicle in the parking lot runs to the road network O, the system platform starts to adopt a dynamic and static linkage vehicle path guiding algorithm to issue a guiding path instruction for the vehicle. The specific process is as follows:
step S1: and acquiring a target range according to the current position O of the parked vehicle and the characteristics of the target parking lot, as shown in the figure, and acquiring real-time data of each road in the target range.
Step S2: the intersection (A, B … K), the starting point position O of the parked vehicle and the entrance/exit position M, N of the parking lot are used as nodes of the network, roads in the road network are used as directed edges of the network, the weight of each directed edge is set according to real-time data of the roads, and a directed weighted complex network of the road network is established;
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 M, N a set of alternative points for the endpoint of the parked vehicle based on the destination of the parked vehicle, the alternative points in the set of alternative points being nodes corresponding to each parking lot entry;
step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parked vehicle to each alternative point in the complex network by using a shortest path algorithm to serve as a path corresponding to the alternative point;
for the first entry M, the sequence of vehicle parking paths and their weights sum:
(1) the sum of the O-B-D-C-M weights W is 5+6+ 4-21
(2) The sum of the O-I-D-C-M weights W is 10+5+6+4 is 25
(3) The sum of the O-I-J-F-E-M weights W10 +5+6+4 30
(4) The sum of the weights W of O-B-A-C-M is 5+6+10+4 is 25
The shortest distance WM21, corresponding path is O-B-D-C-M, sum of weights WM＝5+6+6+4＝21
For the second entry N, the sequence of vehicle parking paths and their weights sum:
(1) the sum of the O-B-D-N weights W is 5+6+1 is 12
(2) The sum of the O-I-D-N weights W10 +5+1 16
(3) The sum of the O-I-J-F-N weights W is 10+5+5+ 25
Then the shortest distance WN12, corresponding to path O-B-D-N, sum of weights WN＝5+6+1＝12
Step S5: selecting the shortest path R ═ W in all pathsNThe corresponding alternative point N is used as the destination of the parked vehicle, and the parked vehicle is guided to enter the parking lot for parking according to the route guidance in reality corresponding to the path (O-B-D-N).
The above functions, if implemented in the form of software functional units and sold or used as a separate product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute 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), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Claims (10)
1. A dynamic and static linkage vehicle path guiding method is characterized by comprising the following steps:
step S1: acquiring a target range according to the current position of a parking vehicle and the characteristics of a target parking lot, and acquiring real-time data of each road in the target range;
step S2: the method comprises the steps that an intersection, a starting point position of a parked vehicle and an entrance and exit position of a parking lot are used as nodes of a network, roads in the road network are used as directed edges of the network, the weights of the directed edges are set according to real-time data of the roads, and a directed weighted complex network of the road network is established;
step S3: determining an alternative point set of the terminal point of the parked vehicle according to the destination of the parked vehicle, wherein alternative points in the alternative point set are nodes corresponding to each parking lot entrance;
step S4: solving a directed edge sequence with the minimum distance from a node corresponding to the starting point position of the parked 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 the alternative point corresponding to the shortest route in all the routes as the destination of the parked vehicle, and guiding the measured parked vehicle to enter the parking lot for parking according to the route corresponding to the real route of the route.
2. The dynamic-static linkage vehicle path guiding method according to claim 1, wherein the real-time data includes an average traveling speed of the vehicle in the road,
the weight of the directed edge is specifically:
wherein: w is aijIs the weight of a directed edge pointed to by node i at node j, LijLength of road as directed edge pointed to by node j, vijThe average travel speed of the vehicles in the road that are directed by node i to the directed edge of node j.
3. The dynamic and static linkage vehicle path guiding method as claimed in claim 1, wherein the target parking lot location is a single parking lot or a combination of a plurality of parking lots, and the road includes a town road and a road in the parking lot.
4. The dynamic-static linkage vehicle route guidance method according to claim 1, wherein in step S4, the distance of the directional edge sequence is the sum of the weights of the directional edges in the directional edge sequence.
5. The dynamic and static linkage vehicle path guiding method according to claim 4, characterized in that the shortest distance is:
wherein: w is a group ofm(qmin) Min () is a small function, χ (s, t), as the shortest distance to the mth candidate pointm) Is s as the starting point and t as the end pointmW (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.
6. The dynamic and static linked vehicle path guiding method as claimed in claim 1, wherein the target range includes a road where the parked vehicle is led to the entrance of the parking lot, a road where the exit of the parking lot is located, and all road networks in a set range in the area or the vicinity of the land where the parking lot is located.
7. The dynamic and static linkage vehicle path guiding method according to claim 1, wherein the real-time data of the road are connected by intelligent detection devices arranged on two sides of the road.
8. The dynamic and static linkage vehicle path guiding method as claimed in claim 7, wherein the types of the intelligent detection device include a coil sensor, a high definition camera and a millimeter wave radar.
9. A dynamic and static linked vehicle path guidance device comprising a memory, a processor, and a program stored in the memory, wherein the processor when executing the program implements the method of any of claims 1-8.
10. A storage medium having a program stored thereon, wherein the program, when executed, implements the method of any of claims 1-8.
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