CN116108288A - Method and system for searching optimal get-on and get-off points in taxi taking service - Google Patents

Method and system for searching optimal get-on and get-off points in taxi taking service Download PDF

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Publication number
CN116108288A
CN116108288A CN202310068400.5A CN202310068400A CN116108288A CN 116108288 A CN116108288 A CN 116108288A CN 202310068400 A CN202310068400 A CN 202310068400A CN 116108288 A CN116108288 A CN 116108288A
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points
point
passenger
road network
driver
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张得天
金伦
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Suzhou University
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Suzhou University
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/901—Indexing; Data structures therefor; Storage structures
    • G06F16/9024—Graphs; Linked lists
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9538—Presentation of query results
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/10—Internal combustion engine [ICE] based vehicles
    • Y02T10/40—Engine management systems

Abstract

The invention relates to a method and a system for searching optimal getting-on and getting-off points in taxi taking service, which are characterized in that firstly, a current urban road network and all POIs are obtained, the POIs are mapped to the nearest side of the road network, then, the positions of passengers and drivers are mapped to the road network side, the intersection of the getting-on points in the maximum receiving time range of the drivers and the getting-on points in the maximum walking time range of the passengers is obtained, a virtual map is constructed through the intersection, all getting-off points around the terminal point of the passengers and real-time traffic conditions, and finally, the optimal getting-on and getting-off points are searched through establishing virtual points on the virtual map. The method for searching the optimal get-on and get-off points in the taxi taking service can effectively improve the accuracy and precision of searching the optimal get-on and get-off points, correctly select the optimal get-on and get-off points, effectively avoid detouring and avoid congestion areas, effectively reduce the travel time of passengers and drivers and improve the operation efficiency of a taxi taking service platform.

Description

Method and system for searching optimal get-on and get-off points in taxi taking service
Technical Field
The invention relates to the technical field of searching optimal points in space crowdsourcing service, in particular to a method and a system for searching optimal get-on and get-off points in taxi taking service.
Background
With the development of shared economic and geographic information systems, space crowdsourcing services increasingly take a significant role in our daily lives. Common space crowdsourcing services include taxi taking (e.g., drop and gorgeous travel), take-out (e.g., globus hystericus and hunger), city perception (gorgeous map, OSM), and the like. Among them, the taxi taking service (or the network taxi taking service) is a widely used space crowdsourcing service. The existing method mostly only uses Euclidean distance as the distance measurement in the space crowdsourcing task, and does not use travel time in the road network with more practical significance. In addition, the related work of the existing taxi taking system cannot determine the optimal get-on and get-off point on the road network. However, the selection of the optimal getting-on and getting-off points can effectively avoid detouring and congestion areas, greatly shorten the travel time of users and drivers and improve the running efficiency of the system.
Although some of the existing path planning methods in windward service consider the influence of getting on/off points, a related optimization algorithm is proposed. However, these algorithms are too time-complex to guarantee real-time requirements and their aim is more to reduce the driver pick-up time and the empty rate. The existing heuristic windmill following algorithm reduces the time complexity, but can not ensure that the optimal getting-on and getting-off points can be found, and the method is not suitable for driving services similar to fast driving, special driving and the like. The existing get-on point searching method of the get-on system is mainly based on historical data to recommend get-on and get-off points, and neglects the influence of traffic flow and get-off points on the total travel time, so that the optimal get-on and get-off point searching precision and accuracy are not high.
Disclosure of Invention
Therefore, the technical problem to be solved by the invention is to overcome the problems that in the prior art, historical data are used when the on-vehicle point search is carried out, and the influence of traffic flow is ignored, so that the accuracy of a final result is low; and the time complexity of the windward path planning algorithm considering the optimal get-on and get-off points is too high to meet the real-time requirement.
In order to solve the technical problems, the invention provides a method for searching for optimal getting-on and getting-off points in taxi taking service, which comprises the following steps:
s1, acquiring a current urban road network, and analyzing the urban road network into a pedestrian road network and a vehicular road network;
s2, acquiring all POIs of a current city, finding edges, closest to the POIs, in a pedestrian road network and a vehicular road network, mapping the POIs to the edges, acquiring current positions of a driver and a passenger, mapping the current positions of the driver and the passenger to the edges of the urban road network, and acquiring a boarding point in the maximum boarding time range of the driver and a boarding point and a alighting point in the maximum walking time range of the passenger according to the set maximum boarding time of the driver and the maximum walking time of the passenger;
s3, acquiring intersection of boarding points of the driver of the passenger according to boarding points in the maximum pickup time range of the driver, boarding points in the maximum walking time range of the passenger and real-time traffic conditions;
s4, constructing a virtual image through the intersection of the boarding points of the passenger driver and all the alighting points around the passenger terminal point;
s5, searching for the optimal get-on and get-off point by establishing a virtual point on the virtual graph.
In one embodiment of the present invention, the method for resolving the urban road network into the pedestrian road network and the vehicular road network in S1 includes:
acquiring a current city overall road network through an OSM Api interface of OSMnx, analyzing the edge attribute of the city road network, and separating the road network into a pedestrian road network and a vehicle road network.
In one embodiment of the present invention, the method of mapping the POI to the edge in S2 is as follows:
acquiring all POIs of the current city through OSM Api of OSMnx, judging whether the edge searching is needed to be accelerated, if not, finding the edge closest to the POI, mapping the POI to the edge, if so, finding a vertex set nearby the POI through KDTE, finding the edge closest to the POI in the edge associated with the point in the vertex set, and mapping the POI to the edge.
In one embodiment of the present invention, the method for obtaining the boarding point in the maximum pickup time range of the driver and the boarding point in the maximum walking time range of the passenger in S2 is as follows:
acquiring the current positions of a driver and a passenger through a GPS, converting the position information into longitude and latitude coordinates in a wsg format, finding the edge closest to the current position of the driver according to the current longitude and latitude and altitude information of the driver, and mapping the position of the driver to the edge;
BFS is made by taking the position of the driver on the edge as a starting point, and all boarding points in the maximum pickup time range of the driver are found;
finding the edge closest to the passenger starting point according to the longitude, latitude and altitude information of the passenger starting point, and mapping the passenger starting point to the edge;
and taking the position of the starting point of the passenger on the edge as a source point to serve as BFS, and finding all boarding points within the maximum walking time around the starting point of the passenger.
In one embodiment of the present invention, the method for acquiring all the get-off points around the passenger end point in S4 includes:
finding the side closest to the starting point of the passenger according to the longitude, latitude and altitude information of the passenger end point, and mapping the passenger end point to the side;
and taking the position of the passenger end point on the edge as a source point to serve as BFS, and finding all the getting-off points in the maximum walking time around the passenger end point.
In one embodiment of the present invention, the method for constructing the virtual map in S4 by the intersection of the boarding points of the passenger driver and all the alighting points around the passenger destination includes:
copying the top point of the vehicle road network as the top point of the virtual graph, the side of the vehicle road network as the side of the virtual graph, and constructing an initial virtual graph by taking the travel time of the current vehicle road network as the side weight;
taking the intersection of the boarding points of the passenger driver as a candidate boarding point set, adding all POIs in the candidate boarding point set into an initial virtual map, and adding the POIs in all the alighting points into the initial virtual map;
connecting a replication point p1 of an origin of an edge where the POI is located on an initial virtual graph with the POI point, wherein the travel time from the p1 to the POI is the travel time from the origin of the edge where the POI is located on a road network to the POI;
connecting a copy point p2 of an end point of an edge where the POI is located on an initial virtual graph with the POI point, wherein the travel time from the POI to the p2 is the travel time from the end point of the edge where the POI is located on a road network to the POI;
and deleting the copying of the edges of all POIs in the initial virtual graph to finish the virtual graph.
In one embodiment of the present invention, the method for searching for the optimal get-on/off point by establishing a virtual point on the virtual graph in S5 is as follows:
inserting a virtual point vs in the virtual graph, connecting vs with all POIs which are taken as the boarding points and added into the virtual graph, and copying all candidate boarding points in the virtual graph, wherein the limit weight from vs to the side of the boarding points is the maximum value of the travel time from the passenger walking to the point and the travel time from the driver driving to the point;
inserting a virtual point vd in the virtual map, connecting the vd with all POIs which are taken as the get-off points and added into the virtual map, and copying all candidate get-off points in the virtual map, wherein the side weight from the candidate get-off points to the sides corresponding to the vd is the travel time from the get-off points to the terminal points of passengers;
finding the shortest path from vs to vd, wherein the second point on the shortest path is the optimal get-on point, and the penultimate point on the shortest path is the optimal get-off point.
The invention also provides a system for searching the optimal getting-on and getting-off points in the taxi taking service, which comprises:
the road network module is used for acquiring the current urban road network and analyzing the urban road network into a human driving network and a vehicle driving network;
the information acquisition module is used for acquiring all POIs of the current city, finding the edge closest to the POIs in the pedestrian road network and the vehicle road network, mapping the POIs to the edge, acquiring the current positions of a driver and a passenger, mapping the current positions of the driver and the passenger to the edge of the urban road network, and acquiring the boarding point in the maximum boarding time range of the driver and the boarding point and the alighting point in the maximum walking time range of the passenger according to the set maximum boarding time of the driver and the maximum walking time of the passenger;
the intersection module is used for acquiring intersection of boarding points of the driver of the passenger according to boarding points in the maximum pickup time range of the driver, boarding points in the maximum walking time range of the passenger and real-time traffic conditions;
the virtual image construction module is used for constructing a virtual image through the intersection of the boarding points of the passenger driver and all the alighting points around the passenger terminal;
and the calculation module is used for establishing virtual points on the virtual graph to search for optimal get-on and get-off points.
Correspondingly, the embodiment of the invention also provides a searching device, which comprises:
a memory for storing a computer program;
and the processor is used for realizing the method for searching the optimal get-on and get-off points in the taxi taking service when executing the computer program.
Correspondingly, the embodiment of the invention also provides a computer-readable nonvolatile storage medium, which comprises computer-readable instructions, and when the computer reads and executes the computer-readable instructions, the computer is enabled to execute the method for searching the optimal getting-on and getting-off point in the taxi taking service.
Compared with the prior art, the technical scheme of the invention has the following advantages:
the invention relates to a method and a system for searching optimal getting-on and getting-off points in taxi taking service, which are characterized in that firstly, a current urban road network and all POIs are obtained, the POIs are mapped to the nearest side of the road network, then, the positions of passengers and drivers are mapped to the road network side, the intersection of the getting-on points in the maximum receiving time range of the drivers and the getting-on points in the maximum walking time range of the passengers is obtained, a virtual map is constructed through the intersection, all getting-off points around the terminal point of the passengers and real-time traffic conditions, and finally, the optimal getting-on and getting-off points are searched through establishing virtual points on the virtual map. The method for searching the optimal get-on and get-off points in the taxi taking service can effectively improve the accuracy and precision of searching the optimal get-on and get-off points, correctly select the optimal get-on and get-off points, effectively avoid detouring and avoid congestion areas, effectively reduce the travel time of passengers and drivers and improve the operation efficiency of a taxi taking service platform.
Drawings
In order that the invention may be more readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof that are illustrated in the appended drawings, in which
FIG. 1 is a flow chart of a method for searching for optimal get-on and get-off points in a taxi service according to the present invention;
FIG. 2 is a flow chart of the present invention mapping POIs to edges;
FIG. 3 is a schematic diagram of a system for searching for optimal pick-up and drop-off points in the taxi taking service according to the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and specific examples, which are not intended to be limiting, so that those skilled in the art will better understand the invention and practice it.
Example 1
As shown in fig. 1, a method for searching for an optimal get-on/off point in a taxi taking service according to this embodiment specifically includes:
s1, acquiring a current urban road network, and analyzing the urban road network into a pedestrian road network and a vehicular road network; s2, acquiring all POIs (marked points on a Point Of Interest map) of a current city, finding edges, closest to the POIs, in a pedestrian road network and a vehicular road network, mapping the POIs to the edges, acquiring current positions of a driver and a passenger, mapping the current positions of the driver and the passenger to the edges of the urban road network respectively, and acquiring boarding points in the maximum cab receiving time range of the driver and boarding points and alighting points in the maximum cab receiving time range of the passenger according to the set maximum cab receiving time of the driver and the maximum cab receiving time of the passenger; s3, acquiring intersection of boarding points of the driver of the passenger according to boarding points in the maximum pickup time range of the driver, boarding points in the maximum walking time range of the passenger and real-time traffic conditions; s4, constructing a virtual image through the intersection of the boarding points of the passenger driver and all the alighting points around the passenger terminal point; s5, searching for the optimal get-on and get-off point by establishing a virtual point on the virtual graph.
According to the method for searching the optimal getting-on and getting-off points in the taxi taking service, the current urban road network and the current POI are obtained, the data can be updated in real time, the real-time traffic condition can be obtained, and the precision and the accuracy of searching the optimal getting-on and getting-off points can be improved; by establishing the virtual graph, the current traffic flow and road network topological structure, the driver position, the starting point and the destination of the passengers can be utilized, the optimal getting-on and getting-off points can be accurately searched from all the candidate getting-on and getting-off points in real time, the travel time of the passengers is minimized, the receiving and sending time of the drivers is reduced, and the real-time requirement is met.
The method for analyzing the urban road network into the pedestrian road network and the vehicular road network in the S1 comprises the following steps: acquiring a current city overall road network through an OSM Api interface of an OSMnx (Open Street Map block network analysis library), analyzing the edge attribute of the city road network, and separating the road network into a pedestrian road network and a vehicle road network.
Specifically, the road network is exported as a file in a pile format, edges on the road network are saved as csv files in the form of initial vertexes, end vertexes, side lengths and free flow travel time of roads, the vertexes on the road network are saved as csv files in the form of IDs, OSMIDs, longitudes, latitudes and altitudes, the csv files of the pedestrian road network and the vehicular road network are respectively read through csvUtil, and the csv files are saved in a memory in the form of a graph structure.
The current city whole road network is obtained through an OSM Api interface of the OSMnx, so that the side attribute information of the city road network can be obtained, and the complete establishment of a subsequent virtual graph is facilitated.
As shown in fig. 2, the method of mapping the POI to the edge in S2 is as follows: acquiring all POIs of a current city through an OSM Api of the OSMnx, judging whether the edge searching is required to be accelerated, if not, finding the edge closest to the POI through a sea-state formula and a trigonometric function, mapping the POI to the edge, if so, finding a vertex set nearby the POI through a KDTE, finding the edge closest to the POI in the edge associated with the point in the vertex set, and mapping the POI to the edge.
Specifically, the road network file stored in S1 is read, and its edges are stored in numpy format data and torch. Exporting the acquired POIs into a click file to be stored, and circularly traversing all the POIs to acquire the longitude, latitude and altitude of each POI; and storing the results of the POI mapping to the edges as csv files in the form of edge starting points, edge ending points and edge positions. The road network traffic flow updating interface is started, so that the system can receive traffic flow data input from the outside to update the travel time on the road network side in real time.
The method for obtaining the boarding point in the maximum pickup time range of the driver and the boarding point in the maximum walking time range of the passenger in the S2 comprises the following steps: acquiring the current positions of a driver and a passenger through a GPS, converting the position information into longitude and latitude coordinates in a wsg (geocentric coordinate system) format, finding the edge nearest to the current position of the driver according to the current longitude and latitude and altitude information of the driver, and mapping the position of the driver to the edge; BFS (breadth first search algorithm) is carried out by taking the position of the driver on the edge as a starting point, and all getting-on points (POIs and road points) within the maximum pickup time range of the driver are found; finding the edge closest to the passenger starting point according to the longitude, latitude and altitude information of the passenger starting point, and mapping the passenger starting point to the edge; and taking the position of the starting point of the passenger on the edge as a source point to serve as BFS, and finding all boarding points within the maximum walking time around the starting point of the passenger.
The position information is converted into longitude and latitude coordinates in a wsg format, so that unified standards are achieved, and the nearest edge can be calculated quickly; and the BFS is made by taking the position of the driver on the edge as a starting point, so that the getting-on points in the maximum receiving time range of all drivers can be searched, and the accuracy of searching the optimal getting-on and getting-off points is improved.
In the step S4, the method for constructing the virtual map through the intersection of the boarding points of the passenger driver and all the alighting points around the passenger terminal point is as follows: copying the top point of the vehicle road network as the top point of the virtual graph, the side of the vehicle road network as the side of the virtual graph, and constructing an initial virtual graph by taking the travel time of the current vehicle road network as the side weight; taking the intersection of the boarding points of the passenger driver as a candidate boarding point set, adding all POIs in the candidate boarding point set into an initial virtual map, and adding the POIs in all the alighting points into the initial virtual map; connecting a replication point p1 of an origin of an edge where the POI is located on an initial virtual graph with the POI point, wherein the travel time from the p1 to the POI is the travel time from the origin of the edge where the POI is located on a road network to the POI; connecting a copy point p2 of an end point of an edge where the POI is located on an initial virtual graph with the POI point, wherein the travel time from the POI to the p2 is the travel time from the end point of the edge where the POI is located on a road network to the POI; and deleting the copying of the edges of all POIs in the initial virtual graph to finish the virtual graph.
By constructing the virtual graph, the optimal getting-on and getting-off points on the road network can be searched efficiently, the topological structure and traffic flow of the road network are taken into consideration, the optimal getting-on and getting-off points are searched for all taxi taking services, the travel time of passengers is minimized, and the pick-up time of drivers is shortened.
The method for searching the optimal get-on/off points by establishing the virtual points on the virtual graph in the S5 comprises the following steps: inserting a virtual point vs in the virtual graph, connecting vs with all POIs which are taken as the boarding points and added into the virtual graph, and copying all candidate boarding points in the virtual graph, wherein the limit weight from vs to the side of the boarding points is the maximum value of the travel time from the passenger walking to the point and the travel time from the driver driving to the point; inserting a virtual point vd in the virtual map, connecting the vd with all POIs which are taken as the get-off points and added into the virtual map, and copying all candidate get-off points in the virtual map, wherein the corresponding get-off point to the vd becomes the journey time of the passenger from the get-off point to the terminal point; finding the shortest path from vs to vd, wherein the second point on the shortest path is the optimal get-on point, and the penultimate point on the shortest path is the optimal get-off point.
After the steps are completed, waiting for the inquiry requests of passengers and drivers, continuously updating the traffic flow information of the road network, if the inquiry requests of the passengers and the drivers are received, finding out the optimal getting-on and getting-off points through the virtual graph, returning to the optimal getting-on and getting-off point pairs, and continuously waiting for the inquiry requests and updating the traffic flow.
Example two
Based on the same inventive concept, the present embodiment provides a system for searching for an optimal get-on/off point in a taxi taking service, and the principle of solving the problem is similar to that of the method for searching for the optimal get-on/off point in the taxi taking service, and the repetition is not repeated.
As shown in fig. 3, a system for searching for an optimal get-on/off point in a taxi taking service provided by an embodiment of the present invention includes:
the road network module 11 is used for acquiring a current city road network and analyzing the city road network into a human driving network and a vehicle driving network;
the information obtaining module 12 is configured to obtain all POIs in a current city, find edges closest to the POIs in a pedestrian road network and a vehicular road network, map the POIs to the edges, obtain current positions of a driver and a passenger, map the current positions of the driver and the passenger to the edges of the urban road network, and obtain a get-on point in a maximum receiving time range of the driver and a get-on point and a get-off point in a maximum walking time range of the passenger according to a set maximum receiving time of the driver and a set maximum walking time of the passenger;
an intersection module 13, configured to obtain an intersection of boarding points of a passenger driver according to boarding points within the maximum pickup time range of the driver, boarding points within the maximum walking time range of the passenger, and real-time traffic conditions;
a virtual map construction module 14, configured to construct a virtual map through the intersection of the boarding points of the passenger driver and all the alighting points around the passenger destination;
and the calculating module 15 is used for establishing a virtual point on the virtual graph to search for the optimal get-on and get-off point.
Example III
The present embodiment also provides a search apparatus including:
a memory for storing a computer program;
and the processor is used for realizing the step of searching the optimal getting-on and getting-off point in the taxi taking service according to the embodiment when executing the computer program.
Example IV
The present embodiment also provides a computer-readable nonvolatile storage medium including:
computer readable instructions, when read and executed by a computer, cause the computer to perform the method for searching for an optimal pick-up and pick-up point in the taxi service described in embodiment one.
It will be appreciated by those skilled in the art that 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 flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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.
It is apparent that the above examples are given by way of illustration only and are not limiting of the embodiments. Other variations and modifications of the present invention will be apparent to those of ordinary skill in the art in light of the foregoing description. It is not necessary here nor is it exhaustive of all embodiments. And obvious variations or modifications thereof are contemplated as falling within the scope of the present invention.

Claims (10)

1. A method for searching for optimal pick-up and pick-up points in a taxi taking service, comprising:
s1, acquiring a current urban road network, and analyzing the urban road network into a pedestrian road network and a vehicular road network;
s2, acquiring all POIs of a current city, finding edges, closest to the POIs, in a pedestrian road network and a vehicular road network, mapping the POIs to the edges, acquiring current positions of a driver and a passenger, mapping the current positions of the driver and the passenger to the edges of the urban road network, and acquiring a boarding point in the maximum boarding time range of the driver and a boarding point and a alighting point in the maximum walking time range of the passenger according to the set maximum boarding time of the driver and the maximum walking time of the passenger;
s3, acquiring intersection of boarding points of the driver of the passenger according to boarding points in the maximum pickup time range of the driver, boarding points in the maximum walking time range of the passenger and real-time traffic conditions;
s4, constructing a virtual image through the intersection of the boarding points of the passenger driver and all the alighting points around the passenger terminal point;
s5, searching for the optimal get-on and get-off point by establishing a virtual point on the virtual graph.
2. The method for searching for optimal getting-on/off points in the taxi taking service according to claim 1, wherein the method for analyzing the urban road network into a pedestrian road network and a vehicular road network in S1 is as follows:
acquiring a current city overall road network through an OSM Api interface of OSMnx, analyzing the edge attribute of the city road network, and separating the road network into a pedestrian road network and a vehicle road network.
3. The method for searching for optimal get-on/off points in a taxi service according to claim 1, wherein the method for mapping the POI to the edge in S2 is as follows:
acquiring all POIs of the current city through OSM Api of OSMnx, judging whether the edge searching is needed to be accelerated, if not, finding the edge closest to the POI, mapping the POI to the edge, if so, finding a vertex set nearby the POI through KDTE, finding the edge closest to the POI in the edge associated with the point in the vertex set, and mapping the POI to the edge.
4. The method for searching for optimal getting-on/off points in the taxi taking service according to claim 1, wherein the method for obtaining the getting-on point in the maximum pickup time range of the driver and the getting-on point in the maximum walking time range of the passenger in S2 is as follows:
acquiring the current positions of a driver and a passenger through a GPS, converting the position information into longitude and latitude coordinates in a wsg format, finding the edge closest to the current position of the driver according to the current longitude and latitude and altitude information of the driver, and mapping the position of the driver to the edge;
BFS is made by taking the position of the driver on the edge as a starting point, and all boarding points in the maximum pickup time range of the driver are found;
finding the edge closest to the passenger starting point according to the longitude, latitude and altitude information of the passenger starting point, and mapping the passenger starting point to the edge;
and taking the position of the starting point of the passenger on the edge as a source point to serve as BFS, and finding all boarding points within the maximum walking time around the starting point of the passenger.
5. The method for searching for optimal getting-on/off points in the taxi taking service according to claim 1, wherein the method for acquiring all getting-off points around the passenger end point in S4 is as follows:
finding the side closest to the starting point of the passenger according to the longitude, latitude and altitude information of the passenger end point, and mapping the passenger end point to the side;
and taking the position of the passenger end point on the edge as a source point to serve as BFS, and finding all the getting-off points in the maximum walking time around the passenger end point.
6. The method for searching for optimal getting-on/off points in the taxi taking service according to claim 1 or 5, wherein the method for constructing a virtual map in S4 by the intersection of the getting-on points of the passenger driver and all getting-off points around the passenger end point is as follows:
copying the top point of the vehicle road network as the top point of the virtual graph, the side of the vehicle road network as the side of the virtual graph, and constructing an initial virtual graph by taking the travel time of the current vehicle road network as the side weight;
taking the intersection of the boarding points of the passenger driver as a candidate boarding point set, adding all POIs in the candidate boarding point set into an initial virtual map, and adding the POIs in all the alighting points into the initial virtual map;
connecting a replication point p1 of an origin of an edge where the POI is located on an initial virtual graph with the POI point, wherein the travel time from the p1 to the POI is the travel time from the origin of the edge where the POI is located on a road network to the POI;
connecting a copy point p2 of an end point of an edge where the POI is located on an initial virtual graph with the POI point, wherein the travel time from the POI to the p2 is the travel time from the end point of the edge where the POI is located on a road network to the POI;
and deleting the copying of the edges of all POIs in the initial virtual graph to finish the virtual graph.
7. The method for searching for the optimal get-on/off point in the taxi taking service according to claim 1, wherein the method for searching for the optimal get-on/off point by establishing the virtual point on the virtual map in S5 is as follows:
inserting a virtual point vs in the virtual graph, connecting vs with all POIs which are taken as the boarding points and added into the virtual graph, and copying all candidate boarding points in the virtual graph, wherein the limit weight from vs to the side of the boarding points is the maximum value of the travel time from the passenger walking to the point and the travel time from the driver driving to the point;
inserting a virtual point vd in the virtual map, connecting the vd with all POIs which are taken as the get-off points and added into the virtual map, and copying all candidate get-off points in the virtual map, wherein the side weight from the candidate get-off points to the sides corresponding to the vd is the travel time from the get-off points to the terminal points of passengers;
finding the shortest path from vs to vd, wherein the second point on the shortest path is the optimal get-on point, and the penultimate point on the shortest path is the optimal get-off point.
8. A system for searching for optimal pick-up and pick-up points in a taxi service, comprising:
the road network module is used for acquiring the current urban road network and analyzing the urban road network into a human driving network and a vehicle driving network;
the information acquisition module is used for acquiring all POIs of the current city, finding the edge closest to the POIs in the pedestrian road network and the vehicle road network, mapping the POIs to the edge, acquiring the current positions of a driver and a passenger, mapping the current positions of the driver and the passenger to the edge of the urban road network, and acquiring the boarding point in the maximum boarding time range of the driver and the boarding point and the alighting point in the maximum walking time range of the passenger according to the set maximum boarding time of the driver and the maximum walking time of the passenger;
the intersection module is used for acquiring intersection of boarding points of the driver of the passenger according to boarding points in the maximum pickup time range of the driver, boarding points in the maximum walking time range of the passenger and real-time traffic conditions;
the virtual image construction module is used for constructing a virtual image through the intersection of the boarding points of the passenger driver and all the alighting points around the passenger terminal;
and the calculation module is used for establishing virtual points on the virtual graph to search for optimal get-on and get-off points.
9. A search apparatus, comprising:
a memory for storing a computer program;
processor for implementing the steps of the method of searching for an optimal pick-up and pick-up point in a taxi service according to any of claims 1-7 when executing said computer program.
10. A computer-readable non-volatile storage medium, comprising:
computer readable instructions which, when read and executed by a computer, cause the computer to perform the method of searching for an optimal pick-up and pick-up point in a taxi service according to any of the preceding claims 1-7.
CN202310068400.5A 2023-02-06 2023-02-06 Method and system for searching optimal get-on and get-off points in taxi taking service Pending CN116108288A (en)

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