WO2023138212A1 - 一种基于地铁拥挤度的站内路径规划方法及装置 - Google Patents

一种基于地铁拥挤度的站内路径规划方法及装置 Download PDF

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WO2023138212A1
WO2023138212A1 PCT/CN2022/134199 CN2022134199W WO2023138212A1 WO 2023138212 A1 WO2023138212 A1 WO 2023138212A1 CN 2022134199 W CN2022134199 W CN 2022134199W WO 2023138212 A1 WO2023138212 A1 WO 2023138212A1
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station
passenger flow
topological
path
congestion
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PCT/CN2022/134199
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English (en)
French (fr)
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夏晨
肖雄
肖中卿
贾建平
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广州新科佳都科技有限公司
广州华佳软件有限公司
佳都科技集团股份有限公司
广东华之源信息工程有限公司
广州佳都城轨智慧运维服务有限公司
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Publication of WO2023138212A1 publication Critical patent/WO2023138212A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/20—Instruments for performing navigational calculations
    • G01C21/206—Instruments for performing navigational calculations specially adapted for indoor navigation
    • 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
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A30/00—Adapting or protecting infrastructure or their operation
    • Y02A30/60—Planning or developing urban green infrastructure

Definitions

  • the embodiments of the present application relate to the technical field of public transportation, and in particular to a method and device for planning routes in stations based on subway congestion.
  • the route planning in the existing bus and subway stations usually considers a single element, usually only considering the shortest route, and does not consider the consideration of ride comfort, resulting in poor ride experience for passengers and affecting travel mood.
  • the embodiments of the present application provide a method and device for route planning in a station based on subway congestion, which can solve the problem of ride comfort and improve ride comfort and route planning practicability.
  • the embodiment of the present application provides a subway congestion-based route planning method in a station, including:
  • the demand information including travel attribute factors, starting point information and destination information;
  • the passenger flow congestion degree model in the station includes the distribution of the degree of congestion grade and the equivalent surface of the degree of congestion degree;
  • the spatial topology network in the station and the passenger flow congestion model in the station According to the user demand information, the spatial topology network in the station and the passenger flow congestion model in the station, the path planning is carried out, and the planned path is output.
  • topological nodes include common nodes and key nodes, wherein the key nodes have node factors;
  • the subway bus line network is abstracted to construct the spatial topological network in the station, and the topological nodes and topological arcs are obtained, specifically:
  • the two-dimensional space topology network in the station is constructed according to the three-dimensional graph of all paths, and the actual route vertices are used as the topological nodes of the topological network, and the topological nodes are connected through the topological arcs to form the spatial topological network in the station, in which the topological nodes correspond to the entrances and exits of stairs, escalators, vertical ladders, gates and station entrances.
  • the passenger flow data collected by the corresponding passenger flow data acquisition device is obtained according to the corresponding topology node, and the passenger flow congestion degree model in the station is obtained, specifically:
  • the passenger flow data collected by the cameras near the topological nodes are obtained;
  • the passenger flow congestion model in the station is obtained by combining the spatial topology network in the station with the passenger flow heat map in the station.
  • the method also includes:
  • the unit consumption corresponding to each congestion degree level is obtained, and the unit consumption includes the passage time of passengers per unit distance length.
  • the path planning is carried out according to the user demand information, the spatial topology network in the station and the passenger flow congestion model in the station, and the planned path is output, specifically:
  • the consumption is obtained according to the passenger flow congestion model in the station, and the second path is screened according to the consumption to obtain the third path;
  • the travel attribute factor includes an outbound factor or an inbound factor, and the travel attribute factor represents whether the user needs to go out or enter the station;
  • the node factors include two-way traffic, impassable, outbound traffic or inbound traffic, and different key nodes correspond to different node factors.
  • the consumption is obtained according to the passenger flow congestion degree model in the station, and the second path is screened according to the consumption to obtain the third path, specifically:
  • the path length corresponding to each congestion degree level is obtained
  • the consumption corresponding to each congestion level is obtained;
  • the embodiment of the present application provides a station route planning device based on subway congestion, including:
  • An information receiving unit configured to receive demand information input by the user, the demand information including travel attribute factors, starting point information and end point information;
  • the topological network construction unit is used to abstract the subway bus line network according to the demand information to construct the spatial topological network in the station, and obtain the topological nodes and topological arcs;
  • Congestion degree model construction unit for obtaining the passenger flow data collected by corresponding passenger flow data acquisition equipment according to corresponding topological nodes, obtain the passenger flow congestion degree model in the station, the passenger flow congestion degree model in the station includes the distribution of the degree of congestion level and the degree of congestion level isosurface;
  • the route planning unit is used for performing route planning according to the user demand information, the spatial topology network in the station and the passenger flow congestion degree model in the station, and outputting the planned route.
  • topological nodes include common nodes and key nodes, wherein the key nodes have node factors;
  • the topological network construction unit is also used to obtain the three-dimensional graphs of all paths from the starting point to the ending point according to the starting point information and the ending point information of the user;
  • the two-dimensional spatial topological network in the station is constructed according to the three-dimensional graphs of all paths, and the actual route vertices are used as the topological nodes of the topological network, and the topological nodes are connected by topological arcs to form the spatial topological network in the station.
  • congestion degree model construction unit is also used to obtain passenger flow data collected by cameras near the topological nodes according to the topological nodes in the spatial topological network in the station;
  • the passenger flow congestion model in the station is obtained by combining the spatial topology network in the station with the passenger flow heat map in the station.
  • the device further includes a unit consumption calculation unit, which is used to obtain the unit consumption corresponding to each congestion level according to the passenger flow congestion degree model in the station, and the unit consumption includes the travel time of passengers per unit distance.
  • the path planning unit is further configured to obtain all first paths from the starting point to the ending point according to the starting point and the ending point combined with the spatial topology network in the station, and the first path includes topological nodes and topological arcs;
  • the consumption is obtained, and the second path is screened according to the consumption to obtain the third path;
  • the travel attribute factor includes an outbound factor or an inbound factor, and the travel attribute factor represents whether the user needs to go out or enter the station;
  • the node factors include two-way traffic, impassable, outbound traffic or inbound traffic, and different key nodes correspond to different node factors.
  • the path planning unit is also used to obtain the path length corresponding to each congestion degree level according to the passenger flow congestion degree model in the station;
  • the consumption corresponding to each congestion level is obtained;
  • an electronic device including:
  • the memory is used to store one or more programs
  • the one or more processors are made to implement the subway congestion-based intra-station route planning method as described in the first aspect.
  • the embodiment of the present application provides a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute the subway congestion-based intra-station route planning method as described in the first aspect when executed by a computer processor.
  • the embodiment of the present application abstracts the bus line network by receiving user demand information to construct a spatial topological network in the station, obtains topological nodes and topological arcs, obtains passenger flow data collected by corresponding passenger flow data collection equipment according to the corresponding topological nodes, obtains a passenger flow congestion model in the station, performs path planning according to the user demand information, the spatial topology network in the station, and the passenger flow congestion model in the station, and obtains the planned route.
  • the complex bus line network can be simplified into corresponding topological nodes and topological arcs, which is convenient for subsequent data processing and route planning; in addition, by comprehensively considering the needs of users and the passenger flow congestion in the station for route planning, it can improve passenger comfort, improve passenger travel experience, and increase the competitiveness and attractiveness of public transport.
  • Fig. 1 is a flow chart of a method for planning routes in a station based on subway congestion provided by Embodiment 1 of the present application;
  • Fig. 2 is a schematic plan view of the bus line network in the station in Embodiment 1 of the present application;
  • FIG. 3 is a schematic diagram of some topological nodes in Embodiment 1 of the present application.
  • FIG. 4 is a schematic diagram of the spatial topology network in the station in Embodiment 1 of the present application.
  • Fig. 5 is a schematic diagram of a passenger flow congestion model in a station provided in Embodiment 1 of the present application;
  • FIG. 6 is a schematic diagram of path planning provided in Embodiment 1 of the present application.
  • FIG. 7 is a schematic diagram of route planning including travel attribute factors provided in Embodiment 1 of the present application.
  • FIG. 8 is a schematic structural diagram of a subway congestion-based route planning device provided in Embodiment 2 of the present application.
  • FIG. 9 is a schematic structural diagram of an electronic device provided in Embodiment 3 of the present application.
  • the route planning method and device based on subway congestion provided by this application is aimed at planning public transport travel routes, usually only considering the shortest route for planning, resulting in ignoring passengers' riding comfort, making passengers feel poor, and affecting travel mood. Based on this, the method for planning an intra-station route based on subway congestion in an embodiment of the present application is provided to solve the existing problem of ride comfort.
  • Fig. 1 has provided the flow chart of a kind of in-station path planning method based on subway congestion degree that the present application embodiment one provides
  • the in-station path planning method based on subway congestion degree provided in the present embodiment can be carried out by the in-station path planning device based on subway congestion degree
  • this in-station path planning device based on subway congestion degree can be realized by the mode of software and/or hardware
  • this in-station path planning device based on subway congestion degree can be made of two or more physical entities, also can be made of a physical entity.
  • the in-station route planning device based on subway congestion can be a terminal device, such as a computer, tablet or mobile phone.
  • the mobile phone is used as an example to implement the subway congestion-based route planning method in a station for description.
  • the route planning method in the station based on subway congestion specifically includes:
  • S101 Receive demand information input by a user, where the demand information includes travel attribute factors, departure point information, and destination information.
  • the departure point information includes the name of the departure point and the departure time
  • the destination information includes the name of the destination point and the expected arrival time.
  • the travel attribute factors include outbound factors or inbound factors.
  • the user's starting point information and end point information obtain the three-dimensional map of all paths from the starting point to the end point; construct the two-dimensional space topology network in the station according to the three-dimensional map of all paths, use the actual route vertices as the topological nodes of the topological network, and connect the topological nodes through topological arcs to form the spatial topological network in the station, in which the topological nodes correspond to the entrances and exits of stairs, escalators, vertical ladders, gates and station entrances.
  • the topological nodes include ordinary nodes and key nodes.
  • the key nodes have node factors, and the node factors include two-way traffic, impassable, outbound traffic or inbound traffic.
  • Different key nodes correspond to different node factors; ordinary nodes do not have node factors and do not have directionality.
  • stairs and vertical ladders are not directional, and can be passed upwards and downwards, so stairs and vertical ladders are common nodes, while escalators are directional, and escalators installed in some locations can only pass upwards or downwards, so escalators are key nodes, and gates are also key nodes.
  • ordinary nodes do not have node factors and do not have directionality, and the directionality of ordinary nodes does not need to be considered in path planning.
  • Key nodes have node factors.
  • the node factors include two-way traffic, impassable, outbound traffic, or inbound traffic. That is, key nodes have directionality.
  • the directionality of key nodes needs to be considered, and comprehensive consideration should be given to the user's demand factors.
  • the three-dimensional map is split into the plan of the platform floor and the plan of the station hall floor, and the two-dimensional spatial topological network of the platform floor and the station hall floor are respectively constructed to obtain the two-dimensional spatial topological network of the platform layer and the two-dimensional spatial topological network of the station hall floor.
  • the two-dimensional space topological network of the hall level is logically connected, and then realizes the connection between the two-dimensional space topological network of the platform level and the two-dimensional space topological network of the station hall level.
  • the subway or bus station there are cameras and other image acquisition equipment all over the space, combined with video structural analysis technology, it can dynamically calculate the distribution of passenger flow in the subway station.
  • the passenger flow data collected by the camera near the topological nodes is obtained; the obtained passenger flow data is analyzed and processed by GIS space, and the thermal map of passenger flow in the station is constructed; the passenger flow congestion model in the station is obtained by combining the spatial topology network in the station with the thermal map of passenger flow in the station.
  • the passenger flow congestion degree model in the station includes the distribution of the congestion degree level and the iso-value surface of the congestion degree level.
  • the degree of congestion can be set according to the actual situation. For example, it is set as level 1, level 2 and level 3.
  • a certain degree of congestion range is set for each level of degree of congestion, and the degree of congestion obtained by actual statistics falls within the range of the preset degree of congestion and is within the range of the isosurface corresponding to the degree of congestion.
  • the passenger flow heat map in the station is obtained.
  • the heat map is essentially an isosurface
  • the data structure is the vector surface data in the GIS data
  • the station route is the vector line data in the GIS data.
  • the spatial analysis of the vector surface data and the vector line data is carried out, and the intersection of the passenger flow congestion model in the station is obtained.
  • the line color depths corresponding to different congestion levels are different, and thus the lengths of routes corresponding to different congestion levels can be obtained.
  • the unit consumption corresponding to each congestion degree level is obtained, and the unit consumption includes the passage time of passengers per unit distance length.
  • the preset unit length is 1 meter
  • the travel time for passengers on a road segment with a congestion level of 1 is 1 minute.
  • the unit consumption model constructed is a theoretical model.
  • the data source for constructing the unit consumption model can be the weighted average of the travel time consumption of passengers in different time periods within a certain period of time in a subway station to establish a mathematical model.
  • S104 Perform path planning according to the user demand information, the spatial topology network in the station, and the passenger flow congestion degree model in the station, and output the planned path.
  • the starting point and the ending point combined with the spatial topology network in the station, all first paths from the starting point to the ending point are obtained, and the first paths include topological nodes and topological arcs.
  • the travel attribute factors include outbound factors or inbound factors, and the travel attribute factors represent whether the user needs to leave the station or need to enter the station.
  • the node factors include two-way traffic, impassable, outbound traffic or inbound traffic, and different key nodes correspond to different node factors.
  • the consumption is obtained according to the passenger flow congestion degree model in the station, and the second path is screened according to the consumption to obtain the third path, and the third path is output.
  • the positioning node P1 is the starting point of path planning
  • node P4 is the end point of path planning.
  • the factor of congestion degree is not considered, and the path starting from point P1 to the node with endpoint is first screened out. From all paths, the path whose endpoint is node P4 is found, and the first path set L-n is obtained, where n represents the number of lines.
  • the path set L-n shown in Figure 6 is the ideal result. However, during the actual subway or bus operation, passenger flow control may occur in the morning and evening peak hours, equipment failures, emergency events, etc., resulting in some lines being blocked. In this case, it is necessary to comprehensively consider the influence of node factors and travel attribute factors.
  • node P5 is a key node, it has node factor A, which is used to indicate its control status. Passengers coming from P1 also carry travel attribute factor B, which is used to indicate whether the passenger is leaving or entering the station. Among them, the transfer attribute factor B is outbound, and when the recursive execution reaches the transfer layer, the travel attribute factor B is converted to inbound. Then you can make a judgment: when the factor A is 0, P5 is passable, and the line passing through P5 is valid. When factor A is 1, P5 is impassable, and the lines passing through P5 are invalid. When factor A is 2, when factor B is 0, the route via P5 is valid, otherwise it is invalid.
  • the route via P5 is valid, otherwise it is invalid. In this way, after another round of screening, part of routes will be eliminated from the first path set L-n again to obtain the second path set L-f.
  • the second path set L-f is all valid and passable paths. In the case of passability, the influence of congestion degree also needs to be considered. Therefore, on the basis of the second path set L-f, the consumption is obtained according to the passenger flow congestion degree model in the station, and the second path set L-f is screened according to the consumption to obtain the third path and output the third path.
  • the path length corresponding to each congestion level is obtained according to the passenger flow congestion degree model in the station; the corresponding consumption amount of each congestion degree level is obtained according to the path length corresponding to each congestion degree level combined with the unit consumption corresponding to each congestion degree level; the consumption amount corresponding to all congestion degree levels in each path in the second path is added to obtain the total consumption amount; the path with the smallest total consumption amount is selected as the third path.
  • TWeigh Cw1_TWeight+Cw2_TWeight+Cw3_TWeight...+CwN_TWeight.
  • the total consumption of each path in the second path set L-f is calculated, and the path with the smallest total consumption is selected as the third path, and the third path is the optimal path from the starting point to the destination in the station.
  • the first path is screened by considering the user demand factor and the node factor, and the impassable paths are eliminated to obtain all the corresponding second paths that can be passed, which improves the accuracy of path planning.
  • the consideration of the degree of congestion is added, and the path that consumes the least total transit time is selected as the final planned path for output, which improves the travel comfort of passengers and improves the travel experience of passengers.
  • the bus line network is abstracted to construct the spatial topology network in the station, and the topological nodes and topological arcs are obtained.
  • the passenger flow data collected by the corresponding passenger flow data acquisition equipment is obtained, and the passenger flow congestion model in the station is obtained.
  • Path planning is carried out according to the user demand information, the spatial topology network in the station, and the passenger flow congestion model in the station, and the planned route is obtained.
  • the complex bus line network can be simplified into corresponding topological nodes and topological arcs, which is convenient for subsequent data processing and route planning; in addition, by comprehensively considering the needs of users and the passenger flow congestion in the station for route planning, it can improve passenger comfort, improve passenger travel experience, and increase the competitiveness and attractiveness of public transport.
  • FIG. 8 is a schematic structural diagram of a subway congestion-based route planning device in a station provided in Embodiment 2 of the present application.
  • the subway congestion-based route planning device provided in this embodiment specifically includes: an information receiving unit 21 , a topology network construction unit 22 , a congestion model construction unit 23 and a route planning unit 24 .
  • the information receiving unit 21 is used to receive the demand information input by the user, and the demand information includes travel attribute factors, starting point information and destination information;
  • the topological network construction unit 22 is used to abstract the subway bus line network according to the demand information to construct the spatial topological network in the station, and obtain topological nodes and topological arcs;
  • Congestion degree model building unit 23 for obtaining the passenger flow data collected by corresponding passenger flow data acquisition equipment according to corresponding topological nodes, obtain passenger flow congestion degree model in station, described station passenger flow congestion degree model including the distribution of degree of congestion level and degree of congestion degree isosurface;
  • the path planning unit 24 is configured to perform path planning according to the user demand information, the spatial topology network in the station, and the passenger flow congestion degree model in the station, and output the planned path.
  • topological nodes include common nodes and key nodes, wherein the key nodes have node factors;
  • the topological network construction unit 22 is further configured to obtain three-dimensional maps of all paths from the starting point to the ending point according to the starting point information and the ending point information of the user;
  • the two-dimensional spatial topological network in the station is constructed according to the three-dimensional graphs of all paths, and the actual route vertices are used as the topological nodes of the topological network, and the topological nodes are connected by topological arcs to form the spatial topological network in the station.
  • congestion degree model construction unit 23 is also used to obtain passenger flow data collected by cameras near the topological nodes according to the topological nodes in the spatial topological network in the station;
  • the passenger flow congestion model in the station is obtained by combining the spatial topology network in the station with the passenger flow heat map in the station.
  • the device further includes a unit consumption calculation unit, which is used to obtain the unit consumption corresponding to each congestion level according to the passenger flow congestion degree model in the station, and the unit consumption includes the travel time of passengers per unit distance.
  • the path planning unit 24 is also used to obtain all first paths from the starting point to the ending point according to the starting point and the ending point combined with the spatial topology network in the station, and the first path includes topological nodes and topological arcs;
  • the consumption is obtained, and the second path is screened according to the consumption to obtain the third path;
  • the travel attribute factor includes an outbound factor or an inbound factor, and the travel attribute factor represents whether the user needs to go out or enter the station;
  • the node factors include two-way traffic, impassable, outbound traffic or inbound traffic, and different key nodes correspond to different node factors.
  • path planning unit 24 is also used to obtain the path length corresponding to each congestion degree level according to the passenger flow congestion degree model in the station;
  • the consumption corresponding to each congestion level is obtained;
  • the bus line network is abstracted to construct the spatial topology network in the station, and the topological nodes and topological arcs are obtained.
  • the passenger flow data collected by the corresponding passenger flow data acquisition equipment is obtained, and the passenger flow congestion model in the station is obtained.
  • Path planning is carried out according to the user demand information, the spatial topology network in the station, and the passenger flow congestion model in the station, and the planned route is obtained.
  • the complex bus line network can be simplified into corresponding topological nodes and topological arcs, which is convenient for subsequent data processing and route planning; in addition, by comprehensively considering the needs of users and the degree of passenger flow congestion in the station for route planning, passengers' comfort and travel experience can be improved, and the competitiveness and attractiveness of public transport can be improved.
  • the apparatus for route planning in a station based on subway congestion degree provided in Embodiment 2 of the present application can be used to execute the method for planning route in a station based on subway congestion degree provided in Embodiment 1 above, and has corresponding functions and beneficial effects.
  • Embodiment 3 of the present application provides an electronic device.
  • the electronic device includes: a processor 31 , a memory 32 , a communication module 33 , an input device 34 and an output device 35 .
  • the number of processors in the electronic device may be one or more, and the number of memories in the electronic device may be one or more.
  • the processor, memory, communication module, input device and output device of the electronic device can be connected through a bus or in other ways.
  • Memory 32 can be used to store software programs, computer-executable programs and modules, such as program instructions/modules corresponding to the method for planning routes in stations based on subway congestion as described in any embodiment of the present application (for example, information receiving units, topology network construction units, congestion model construction units and path planning units in station route planning devices based on subway congestion).
  • the memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required by a function; the data storage area may store data created according to the use of the device, and the like.
  • the memory may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage devices.
  • the memory may further include memory located remotely from the processor, which remote memory may be connected to the device via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.
  • the communication module 33 is used for data transmission.
  • the processor 31 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory, that is, realizes the above-mentioned subway congestion-based route planning method in the station.
  • the input device 34 can be used for receiving inputted numerical or character information, and generating key signal input related to user setting and function control of the device.
  • the output device 35 may include a display device such as a display screen.
  • the electronic device provided above can be used to implement the subway congestion-based route planning method in the station provided in the first embodiment, and has corresponding functions and beneficial effects.
  • the in-station route planning method based on subway congestion degree includes: receiving demand information input by a user, the demand information including travel attribute factors, starting point information, and destination information; abstracting the subway bus line network according to the demand information to construct a spatial topology network in the station to obtain topological nodes and topological arcs; flow data, obtain the passenger flow congestion degree model in the station, and the passenger flow congestion degree model in the station includes the distribution of the degree of congestion level and the equivalent surface of the degree of congestion degree; carry out path planning according to the user demand information and the spatial topology network in the station and the degree of passenger flow degree of congestion model in the station, and output the planned path.
  • storage medium any of various types of memory devices or storage devices.
  • storage medium is intended to include: installation media such as CD-ROMs, floppy disks, or magnetic tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g. hard disk or optical storage); registers or other similar types of memory elements, etc.
  • the storage medium may also include other types of memory or combinations thereof.
  • the storage medium may be located in a first computer system in which the program is executed, or may be located in a different second computer system connected to the first computer system through a network such as the Internet.
  • the second computer system may provide program instructions to the first computer for execution.
  • storage medium may include two or more storage media that reside in different locations, for example in different computer systems connected by a network.
  • the storage medium may store program instructions (eg embodied as computer programs) executable by one or more processors.
  • the computer-executable instructions are not limited to the above-mentioned subway congestion-based in-station route planning method, and can also perform related operations in the subway congestion-based in-station route planning method provided in any embodiment of the present application.
  • the in-station route planning device, storage medium and electronic equipment based on subway congestion provided in the above-mentioned embodiments can perform the in-station route planning method based on subway congestion provided by any embodiment of the present application, and the technical details not described in detail in the above-mentioned embodiments can refer to the in-station route planning method based on subway congestion provided in any embodiment of the application.

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Abstract

一种基于地铁拥挤度的站内路径规划方法、装置、电子设备及存储介质，该方法包括：接收用户输入的需求信息，需求信息包括出行属性因子、出发点信息和终点信息（S101）；根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段（S102）；根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，站内客流拥挤度模型包括拥挤度等级和拥挤度等级等值面的分布（S103）；根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，输出规划路径（S104）。该方法能够解决乘车舒适度问题，提升乘车舒适度和路径规划实用性。

Description

一种基于地铁拥挤度的站内路径规划方法及装置 技术领域
本申请实施例涉及公共交通技术领域，尤其涉及一种基于地铁拥挤度的站内路径规划方法及装置。
背景技术
城市公共交通具有容量大、效率高、能耗低、污染小、道路资源占用低等优势，欧美、日本、新加坡等地经验表明，优先发展城市公共交通是缓解城市交通拥堵、保证人民群众便捷高效出行的根本保障，是实现城市绿色、低碳、可持续发展的必然选择。
随着社会经济的发展和群众生活水平逐步提高，出行乘客对城市公交服务质量提出了更高的要求，要求公交企业能够提供安全、快捷、舒适的出行环境，多元化、个性化公交出行的要求普遍提升。近年来，城市公共交通运力规模不断扩大，有力地支撑了城市社会经济的快速发展，但公交运能发挥不充分、运输效率不高、乘车舒适性较差等问题仍然存在，无法满足快速发展的社会经济速度和居民出行需求，要求公交企业转变发展方式，积极推进科技创新和管理创新，提升城市公交的服务品质。为提升城市公共交通***的资源利用效率，提高竞争力和吸引力，需要考虑多种服务品质影响因素，包括乘车舒适度、出行时间、出行费用以及步行距离等因素。
现有公交地铁站内路径规划通常考虑的要素较为单一，通常仅考虑路径最短，并不会考虑乘车舒适度的考量，导致乘客乘车体验感差，影响出行心情。
发明内容
本申请实施例提供一种基于地铁拥挤度的站内路径规划方法及装置，能够解决乘车舒适度问题，提升乘车舒适度和路径规划实用性。
在第一方面，本申请实施例提供了一种基于地铁拥挤度的站内路径规划方法，包括：
接收用户输入的需求信息，所述需求信息包括出行属性因子、出发点信息和终点信息；
根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段；
根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，所述站内客流拥挤度模型包括拥挤度等级和拥挤度等级等值面的分布；
根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，输出规划路径。
进一步的，所述拓扑节点包括普通节点和关键节点，其中关键节点拥有节点因子；
所述根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段，具体为：
根据用户的出发点信息和终点信息，获取从出发点到终点的所有路径的三维图；
根据所有路径的三维图构建站内二维空间拓扑网，将实际的路线折点作为拓扑网的拓扑节点，通过拓扑弧段将拓扑节点连接起来构成站内空间拓扑网，其中拓扑节点对应楼梯出入口、手扶梯出入口、垂梯出入口、闸机和进出站口。
进一步的，所述根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，具体为：
根据站内空间拓扑网中的拓扑节点，获取拓扑节点附近的摄像头采集到的客流量数据；
将获取到的客流量数据进行GIS空间分析处理，构建站内客流热力图；
将站内空间拓扑网结合站内客流热力图得到站内客流拥挤度模型。
进一步的，所述方法还包括：
根据站内客流拥挤度模型得到每一拥挤度等级对应的单位消耗，所述单位消耗包括单位路程长度乘客的通行时间。
进一步的，所述根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，输出规划路径，具体为：
根据出发点和终点结合站内空间拓扑网，获取所有从出发点到终点的第一路径，所述第一路径包括拓扑节点和拓扑弧段；
结合出行属性因子和节点因子对第一路径进行筛选，得到第二路径；
根据站内客流拥挤度模型得到消耗量，根据消耗量对第二路径进行筛选， 得到第三路径；
输出第三路径。
进一步的，所述出行属性因子包括出站因子或进站因子，所述出行属性因子代表用户需要出站还是需要进站；
所述节点因子包括双向通行、不可通行、出站通行或进站通行，不同的关键节点对应的节点因子不同。
进一步的，所述根据站内客流拥挤度模型得到消耗量，根据消耗量对第二路径进行筛选，得到第三路径，具体为：
根据站内客流拥挤度模型得到每一拥挤度等级对应的路径长度；
根据每一拥挤度等级对应的路径长度结合每一拥挤度等级对应的单位消耗，得到每一拥挤度等级对应的消耗量；
将第二路径中每一条路径中的所有拥挤度等级对应的消耗量相加，得到总的消耗量；
筛选出总消耗量最小的路径为第三路径。
在第二方面，本申请实施例提供了一种基于地铁拥挤度的站内路径规划装置，包括：
信息接收单元，用于接收用户输入的需求信息，所述需求信息包括出行属性因子、出发点信息和终点信息；
拓扑网构建单元，用于根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段；
拥挤度模型构建单元，用于根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，所述站内客流拥挤度模型包括拥挤度等级和拥挤度等级等值面的分布；
路径规划单元，用于根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，输出规划路径。
进一步的，所述拓扑节点包括普通节点和关键节点，其中关键节点拥有节点因子；
所述拓扑网构建单元，还用于根据用户的出发点信息和终点信息，获取从出发点到终点的所有路径的三维图；
根据所有路径的三维图构建站内二维空间拓扑网，将实际的路线折点作为拓扑网的拓扑节点，通过拓扑弧段将拓扑节点连接起来构成站内空间拓扑网， 其中拓扑节点对应楼梯出入口、手扶梯出入口、垂梯出入口、闸机和进出站口。
进一步的，所述拥挤度模型构建单元，还用于根据站内空间拓扑网中的拓扑节点，获取拓扑节点附近的摄像头采集到的客流量数据；
将获取到的客流量数据进行GIS空间分析处理，构建站内客流热力图；
将站内空间拓扑网结合站内客流热力图得到站内客流拥挤度模型。
进一步的，所述装置还包括单位消耗计算单元，用于根据站内客流拥挤度模型得到每一拥挤度等级对应的单位消耗，所述单位消耗包括单位路程长度乘客的通行时间。
进一步的，所述路径规划单元，还用于根据出发点和终点结合站内空间拓扑网，获取所有从出发点到终点的第一路径，所述第一路径包括拓扑节点和拓扑弧段；
结合出行属性因子和节点因子对第一路径进行筛选，得到第二路径；
根据站内客流拥挤度模型得到消耗量，根据消耗量对第二路径进行筛选，得到第三路径；
输出第三路径。
进一步的，所述出行属性因子包括出站因子或进站因子，所述出行属性因子代表用户需要出站还是需要进站；
所述节点因子包括双向通行、不可通行、出站通行或进站通行，不同的关键节点对应的节点因子不同。
进一步的，所述路径规划单元，还用于根据站内客流拥挤度模型得到每一拥挤度等级对应的路径长度；
根据每一拥挤度等级对应的路径长度结合每一拥挤度等级对应的单位消耗，得到每一拥挤度等级对应的消耗量；
将第二路径中每一条路径中的所有拥挤度等级对应的消耗量相加，得到总的消耗量；
筛选出总消耗量最小的路径为第三路径。
在第三方面，本申请实施例提供了一种电子设备，包括：
存储器以及一个或多个处理器；
所述存储器，用于存储一个或多个程序；
当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现如第一方面所述的基于地铁拥挤度的站内路径规划方法。
在第四方面，本申请实施例提供了一种包含计算机可执行指令的存储介质，所述计算机可执行指令在由计算机处理器执行时用于执行如第一方面所述的基于地铁拥挤度的站内路径规划方法。
本申请实施例通过接收用户的需求信息对公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段，根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，得到规划路径。采用上述技术手段，通过将公交线路网络进行抽象化处理构建站内空间拓扑网，能够将复杂的公交线路网络简化成对应的拓扑节点和拓扑弧段，便于后续的数据处理和路径规划；此外，通过综合考量用户的需求及站内客流拥挤度进行路径规划，提升乘客的乘车舒适度，改善乘客出行体验，提高公共交通的竞争力和吸引力。
附图说明
图1是本申请实施例一提供的一种基于地铁拥挤度的站内路径规划方法的流程图；
图2是本申请实施例一中站内公交线路网络的平面示意图；
图3是本申请实施例一中的部分拓扑节点示意图；
图4是本申请实施例一中的站内空间拓扑网示意图；
图5是本申请实施例一中提供站内客流拥挤度模型示意图；
图6是本申请实施例一中提供的路径规划示意图；
图7是本申请实施例一中提供的包含出行属性因子的路径规划示意图；
图8是本申请实施例二提供的一种基于地铁拥挤度的站内路径规划装置的结构示意图；
图9是本申请实施例三提供的一种电子设备的结构示意图。
具体实施方式
为了使本申请的目的、技术方案和优点更加清楚，下面结合附图对本申请具体实施例作进一步的详细描述。可以理解的是，此处所描述的具体实施例仅仅用于解释本申请，而非对本申请的限定。另外还需要说明的是，为了便于描述，附图中仅示出了与本申请相关的部分而非全部内容。在更加详细地讨论示 例性实施例之前应当提到的是，一些示例性实施例被描述成作为流程图描绘的处理或方法。虽然流程图将各项操作(或步骤)描述成顺序的处理，但是其中的许多操作可以被并行地、并发地或者同时实施。此外，各项操作的顺序可以被重新安排。当其操作完成时所述处理可以被终止，但是还可以具有未包括在附图中的附加步骤。所述处理可以对应于方法、函数、规程、子例程、子程序等等。
本申请提供的基于地铁拥挤度的站内路径规划方法及装置，旨在公共交通出行路径规划时，通常仅考虑路径最短进行规划，导致忽视乘客的乘车舒适度感受，使得乘客体验感差，影响出行心情。基于此，提供本申请实施例的基于地铁拥挤度的站内路径规划方法，以解决现有乘车舒适度问题。
实施例一：
图1给出了本申请实施例一提供的一种基于地铁拥挤度的站内路径规划方法的流程图，本实施例中提供的基于地铁拥挤度的站内路径规划方法可以由基于地铁拥挤度的站内路径规划设备执行，该基于地铁拥挤度的站内路径规划设备可以通过软件和/或硬件的方式实现，该基于地铁拥挤度的站内路径规划设备可以是两个或多个物理实体构成，也可以是一个物理实体构成。一般而言，该基于地铁拥挤度的站内路径规划设备可以是终端设备，如电脑、平板或手机等。
下述以手机为执行基于地铁拥挤度的站内路径规划方法的主体为例，进行描述。参照图1，该基于地铁拥挤度的站内路径规划方法具体包括：
S101、接收用户输入的需求信息，所述需求信息包括出行属性因子、出发点信息和终点信息。
在乘客用户需要进行路径规划时，需要输入对应的出发点信息和终点信息，所述出发点信息包括出发点名称和出发时间，所述终点信息包括终点名称和预计想要到达的时间；除此之外，基于提高乘客的乘坐舒适度，还需要输入相关的出行属性因子，所述出行属性因子包括出站因子或进站因子，所述出行属性因子代表用户需要出站还是需要进站。根据用户输入的需求信息进行后续路径规划。
S102、根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段。
根据用户的出发点信息和终点信息，获取从出发点到终点的所有路径的三 维图；根据所有路径的三维图构建站内二维空间拓扑网，将实际的路线折点作为拓扑网的拓扑节点，通过拓扑弧段将拓扑节点连接起来构成站内空间拓扑网，其中拓扑节点对应楼梯出入口、手扶梯出入口、垂梯出入口、闸机和进出站口。
参照图2，根据用户的出发点信息和终点信息，获取从出发点到终点的所有路径的三维图，将三维图拆分为不同的二维平面图，如图2所示，将三维图拆分成站台层的平面图和站厅层的平面图，分别进行构建二维空间拓扑网，分别构建完成后根据共同节点将两个二维空间拓扑网进行连接，得到完整的二维空间拓扑网。其中将实际的路线折点作为拓扑网的拓扑节点，拓扑节点对应楼梯出入口、手扶梯出入口、垂梯出入口、闸机和进出站口，通过拓扑弧段将拓扑节点连接起来构成站内空间拓扑网。所述拓扑节点包括普通节点和关键节点，所述关键节点拥有节点因子，所述节点因子包括双向通行、不可通行、出站通行或进站通行，不同的关键节点对应的节点因子不同；普通节点不拥有节点因子，不具有方向性。例如楼梯和垂梯不具有方向性，向上向下都可以实现通行，因此楼梯和垂梯属于普通节点，而手扶梯具有方向性，部分位置设置的手扶梯仅能向上通行或者仅能向下通行，因此手扶梯属于关键节点，此外还有闸机同样属于关键节点。
参照图3，其中普通节点不拥有节点因子，不具备方向性，在路径规划中不用考虑普通节点的方向性。关键节点拥有节点因子，所述节点因子包括双向通行、不可通行、出站通行或进站通行，即关键节点具有方向性，在进行路径规划时需要考虑关键节点的方向性，并要与用户的需求因子进行综合考量。
参照图4，根据图2可知将三维图拆分成站台层的平面图和站厅层的平面图，将站台层平面图和站厅层平面图分别进行构建二维空间拓扑网，得到站台层二维空间拓扑网和站厅层二维空间拓扑网，两者是彼此独立的，为了让两个二维空间拓扑网也保持空间相关性，通过手扶梯、垂梯和楼梯这些拓扑节点建立站台层二维空间拓扑网和站厅层二维空间拓扑网的连接，使得站台层和站厅层的二维空间拓扑网逻辑上相连接，进而实现站台层二维空间拓扑网和站厅层二维空间拓扑网的连接。
S103、根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，所述站内客流拥挤度模型包括拥挤度等级和拥挤度等级等值面的分布。
在地铁或者公交站内空间遍布摄像头等进行图像采集的设备，结合视频结 构化分析技术，可以动态计算出地铁站内客流的分布状况。根据站内空间拓扑网中的拓扑节点，获取拓扑节点附近的摄像头采集到的客流量数据；将获取到的客流量数据进行GIS空间分析处理，构建站内客流热力图；将站内空间拓扑网结合站内客流热力图得到站内客流拥挤度模型。所述站内客流拥挤度模型包括拥挤度等级和拥挤度等级等值面的分布。所述拥挤度等级可根据实际情况进行设定，例如说设定为1级、2级和3级，每一个拥挤度等级设置一定的拥挤度范围，实际统计得到的拥挤度落入预设拥挤度范围则处于该拥挤度等级对应的等值面范围内。
参照图5，根据将获取到的客流量数据进行GIS空间分析处理，得到站内的客流热力图，热力图本质是等值面，数据结构是GIS数据中的矢量面数据，而站内路线则是GIS数据中的矢量线数据，对矢量面数据和矢量线数据进行空间分析，求交得到站内客流拥挤度模型。在图5中构建好的站内客流拥挤度模型中不同拥挤度等级对应的线路颜色深度不相同，由此可以得到不同拥挤度等级对应的路线的长度。
根据站内客流拥挤度模型得到每一拥挤度等级对应的单位消耗，所述单位消耗包括单位路程长度乘客的通行时间。例如，预设单位长度1米，乘客在拥挤度等级为1级的路段乘客的通行时间为1分钟。构建的单位消耗模型为理论模型，实际上构建单位消耗模型的数据来源可以是对地铁站内一段时间内乘客在不同时间段的通行时间消耗，进行加权平均，建立一个数学模型。
S104、根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，输出规划路径。
根据出发点和终点结合站内空间拓扑网，获取所有从出发点到终点的第一路径，所述第一路径包括拓扑节点和拓扑弧段。结合出行属性因子和节点因子对第一路径进行筛选，得到第二路径，所述出行属性因子包括出站因子或进站因子，所述出行属性因子代表用户需要出站还是需要进站，所述节点因子包括双向通行、不可通行、出站通行或进站通行，不同的关键节点对应的节点因子不同。根据站内客流拥挤度模型得到消耗量，根据消耗量对第二路径进行筛选，得到第三路径，输出第三路径。
示例性的，参照图6，定位节点P1为路径规划的出发点，节点P4为路径规划的终点，进行路径规划初始阶段先不考虑拥挤度的因素，首先筛选出从P1点出发到有端点节点的路径，在从所有路径中找到端点为节点P4的路径，得到第 一路径集合L-n，其中n代表线路的数量。如图6所述的路径集合L-n是理想情况下的结果，但是，实际的地铁或公交运营的过程中，有可能出现早晚高峰、设备故障、应急事件等情况的客流管控，导致有些线路不通行，在这样子的情况下，需要综合考量节点因子和出行属性因子的影响。
参照图7，假设节点P5为关键节点，它具备节点因子A，用来指示它的管控情况，乘客从P1而来，同样携带了出行属性因子B，用来指示乘客是出站还是进站，其中换乘是出行属性因子B为出站，当递归执行到换乘层时出行属性因子B转为进站。则可以做一下判断：因子A为0时，P5可通行，途经P5的线路有效。因子A为1时，P5不可通行，途经P5的线路无效。因子A为2时，当因子B为0，途经P5的路线有效，否则无效。因子A为3时，当因子B为1，途经P5的路线有效，否则无效。这样，经过再一轮的筛选，第一路径集合L-n会再次剔除一部分路线，得到第二路径集合L-f。所述第二路径集合L-f为所有有效可通行的路径，在可通行的情况下，还需要考虑拥挤度的影响，因此在第二路径集合L-f基础上，根据站内客流拥挤度模型得到消耗量，根据消耗量对第二路径集合L-f进行筛选，得到第三路径，输出第三路径。
进一步的，根据站内客流拥挤度模型得到每一拥挤度等级对应的路径长度；根据每一拥挤度等级对应的路径长度结合每一拥挤度等级对应的单位消耗，得到每一拥挤度等级对应的消耗量；将第二路径中每一条路径中的所有拥挤度等级对应的消耗量相加，得到总的消耗量；筛选出总消耗量最小的路径为第三路径。
设置每一拥挤度等级对应的路径长度为Distance(N)，每一拥挤度等级对应的单位消耗为UC(N)，每一拥挤度等级对应的消耗量为CwN_TWeight，其中N为拥挤度等级，因此得到CwN_TWeight＝UC(N)*Distance(N)，从而得到总的消耗量为:
TWeigh＝Cw1_TWeight+Cw2_TWeight+Cw3_TWeight...+CwN_TWeight。对第二路径集合L-f中的每一条路径的总消耗量进行计算，并筛选出总消耗量最小的路径为第三路径，所述第三路径为站内从出发点到终点的最优路径。
本申请实施例通过用户需求因子和节点因子的考量对第一路径进行筛选，剔除掉不可以通行的路径，得到对应的所有可以通行的第二路径，提高了路径规划的准确性，此外，在所有可以通行的第二路径的基础上，增加对拥挤度的考量，选在通行时间总消耗最小的路径作为最终的规划路径进行输出，提高了 乘客的出行的舒适度，提升乘客出行体验。
上述，通过接收用户的需求信息对公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段，根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，得到规划路径。采用上述技术手段，通过将公交线路网络进行抽象化处理构建站内空间拓扑网，能够将复杂的公交线路网络简化成对应的拓扑节点和拓扑弧段，便于后续的数据处理和路径规划；此外，通过综合考量用户的需求及站内客流拥挤度进行路径规划，提升乘客的乘车舒适度，改善乘客出行体验，提高公共交通的竞争力和吸引力。
实施例二：
在上述实施例的基础上，图8为本申请实施例二提供的一种基于地铁拥挤度的站内路径规划装置的结构示意图。参考图8，本实施例提供的基于地铁拥挤度的站内路径规划装置具体包括：信息接收单元21、拓扑网构建单元22、拥挤度模型构建单元23和路径规划单元24。
其中，信息接收单元21，用于接收用户输入的需求信息，所述需求信息包括出行属性因子、出发点信息和终点信息；
拓扑网构建单元22，用于根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段；
拥挤度模型构建单元23，用于根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，所述站内客流拥挤度模型包括拥挤度等级和拥挤度等级等值面的分布；
路径规划单元24，用于根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，输出规划路径。
进一步的，所述拓扑节点包括普通节点和关键节点，其中关键节点拥有节点因子；
所述拓扑网构建单元22，还用于根据用户的出发点信息和终点信息，获取从出发点到终点的所有路径的三维图；
根据所有路径的三维图构建站内二维空间拓扑网，将实际的路线折点作为拓扑网的拓扑节点，通过拓扑弧段将拓扑节点连接起来构成站内空间拓扑网， 其中拓扑节点对应楼梯出入口、手扶梯出入口、垂梯出入口、闸机和进出站口。
进一步的，所述拥挤度模型构建单元23，还用于根据站内空间拓扑网中的拓扑节点，获取拓扑节点附近的摄像头采集到的客流量数据；
将获取到的客流量数据进行GIS空间分析处理，构建站内客流热力图；
将站内空间拓扑网结合站内客流热力图得到站内客流拥挤度模型。
进一步的，所述装置还包括单位消耗计算单元，用于根据站内客流拥挤度模型得到每一拥挤度等级对应的单位消耗，所述单位消耗包括单位路程长度乘客的通行时间。
进一步的，所述路径规划单元24，还用于根据出发点和终点结合站内空间拓扑网，获取所有从出发点到终点的第一路径，所述第一路径包括拓扑节点和拓扑弧段；
结合出行属性因子和节点因子对第一路径进行筛选，得到第二路径；
根据站内客流拥挤度模型得到消耗量，根据消耗量对第二路径进行筛选，得到第三路径；
输出第三路径。
进一步的，所述出行属性因子包括出站因子或进站因子，所述出行属性因子代表用户需要出站还是需要进站；
所述节点因子包括双向通行、不可通行、出站通行或进站通行，不同的关键节点对应的节点因子不同。
进一步的，所述路径规划单元24，还用于根据站内客流拥挤度模型得到每一拥挤度等级对应的路径长度；
根据每一拥挤度等级对应的路径长度结合每一拥挤度等级对应的单位消耗，得到每一拥挤度等级对应的消耗量；
将第二路径中每一条路径中的所有拥挤度等级对应的消耗量相加，得到总的消耗量；
筛选出总消耗量最小的路径为第三路径。
上述，通过接收用户的需求信息对公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段，根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，得到规划路径。采用上述技术手段，通过将公交线路网络进行抽象化处理构建站内空间拓 扑网，能够将复杂的公交线路网络简化成对应的拓扑节点和拓扑弧段，便于后续的数据处理和路径规划；此外，通过综合考量用户的需求及站内客流拥挤度进行路径规划，提升乘客的乘车舒适度，改善乘客出行体验，提高公共交通的竞争力和吸引力。
本申请实施例二提供的基于地铁拥挤度的站内路径规划装置可以用于执行上述实施例一提供的基于地铁拥挤度的站内路径规划方法，具备相应的功能和有益效果。
实施例三：
本申请实施例三提供了一种电子设备，参照图9，该电子设备包括：处理器31、存储器32、通信模块33、输入装置34及输出装置35。该电子设备中处理器的数量可以是一个或者多个，该电子设备中的存储器的数量可以是一个或者多个。该电子设备的处理器、存储器、通信模块、输入装置及输出装置可以通过总线或者其他方式连接。
存储器32作为一种计算机可读存储介质，可用于存储软件程序、计算机可执行程序以及模块，如本申请任意实施例所述的基于地铁拥挤度的站内路径规划方法对应的程序指令/模块(例如，基于地铁拥挤度的站内路径规划装置中的信息接收单元、拓扑网构建单元、拥挤度模型构建单元和路径规划单元)。存储器可主要包括存储程序区和存储数据区，其中，存储程序区可存储操作***、至少一个功能所需的应用程序；存储数据区可存储根据设备的使用所创建的数据等。此外，存储器可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。在一些实例中，存储器可进一步包括相对于处理器远程设置的存储器，这些远程存储器可以通过网络连接至设备。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。
通信模块33用于进行数据传输。
处理器31通过运行存储在存储器中的软件程序、指令以及模块，从而执行设备的各种功能应用以及数据处理，即实现上述的基于地铁拥挤度的站内路径规划方法。
输入装置34可用于接收输入的数字或字符信息，以及产生与设备的用户设置以及功能控制有关的键信号输入。输出装置35可包括显示屏等显示设备。
上述提供的电子设备可用于执行上述实施例一提供的基于地铁拥挤度的站内路径规划方法，具备相应的功能和有益效果。
实施例四：
本申请实施例还提供一种包含计算机可执行指令的存储介质，所述计算机可执行指令在由计算机处理器执行时用于执行一种基于地铁拥挤度的站内路径规划方法，该基于地铁拥挤度的站内路径规划方法包括：接收用户输入的需求信息，所述需求信息包括出行属性因子、出发点信息和终点信息；根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段；根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，所述站内客流拥挤度模型包括拥挤度等级和拥挤度等级等值面的分布；根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，输出规划路径。
存储介质——任何的各种类型的存储器设备或存储设备。术语“存储介质”旨在包括：安装介质，例如CD-ROM、软盘或磁带装置；计算机***存储器或随机存取存储器，诸如DRAM、DDR RAM、SRAM、EDO RAM，兰巴斯(Rambus)RAM等；非易失性存储器，诸如闪存、磁介质(例如硬盘或光存储)；寄存器或其它相似类型的存储器元件等。存储介质可以还包括其它类型的存储器或其组合。另外，存储介质可以位于程序在其中被执行的第一计算机***中，或者可以位于不同的第二计算机***中，第二计算机***通过网络(诸如因特网)连接到第一计算机***。第二计算机***可以提供程序指令给第一计算机用于执行。术语“存储介质”可以包括驻留在不同位置中(例如在通过网络连接的不同计算机***中)的两个或更多存储介质。存储介质可以存储可由一个或多个处理器执行的程序指令(例如具体实现为计算机程序)。
当然，本申请实施例所提供的一种包含计算机可执行指令的存储介质，其计算机可执行指令不限于如上所述的基于地铁拥挤度的站内路径规划方法，还可以执行本申请任意实施例所提供的基于地铁拥挤度的站内路径规划方法中的相关操作。
上述实施例中提供的基于地铁拥挤度的站内路径规划装置、存储介质及电子设备可执行本申请任意实施例所提供的基于地铁拥挤度的站内路径规划方法，未在上述实施例中详尽描述的技术细节，可参见本申请任意实施例所提供 的基于地铁拥挤度的站内路径规划方法。
上述仅为本申请的较佳实施例及所运用的技术原理。本申请不限于这里所述的特定实施例，对本领域技术人员来说能够进行的各种明显变化、重新调整及替代均不会脱离本申请的保护范围。因此，虽然通过以上实施例对本申请进行了较为详细的说明，但是本申请不仅仅限于以上实施例，在不脱离本申请构思的情况下，还可以包括更多其他等效实施例，而本申请的范围由权利要求的范围决定。

Claims (10)

  1. 一种基于地铁拥挤度的站内路径规划方法，其特征在于，包括：
    接收用户输入的需求信息，所述需求信息包括出行属性因子、出发点信息和终点信息；
    根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段；
    根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，所述站内客流拥挤度模型包括拥挤度等级和拥挤度等级等值面的分布；
    根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，输出规划路径。
  2. 根据权利要求1所述的基于地铁拥挤度的站内路径规划方法，其特征在于，所述拓扑节点包括普通节点和关键节点，其中关键节点拥有节点因子；
    所述根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段，具体为：
    根据用户的出发点信息和终点信息，获取从出发点到终点的所有路径的三维图；
    根据所有路径的三维图构建站内二维空间拓扑网，将实际的路线折点作为拓扑网的拓扑节点，通过拓扑弧段将拓扑节点连接起来构成站内空间拓扑网，其中拓扑节点对应楼梯出入口、手扶梯出入口、垂梯出入口、闸机和进出站口。
  3. 根据权利要求1所述的基于地铁拥挤度的站内路径规划方法，其特征在于，所述根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，具体为：
    根据站内空间拓扑网中的拓扑节点，获取拓扑节点附近的摄像头采集到的客流量数据；
    将获取到的客流量数据进行GIS空间分析处理，构建站内客流热力图；
    将站内空间拓扑网结合站内客流热力图得到站内客流拥挤度模型。
  4. 根据权利要求3所述的基于地铁拥挤度的站内路径规划方法，其特征在于，所述方法还包括：
    根据站内客流拥挤度模型得到每一拥挤度等级对应的单位消耗，所述单位消耗包括单位路程长度乘客的通行时间。
  5. 根据权利要求4所述的基于地铁拥挤度的站内路径规划方法，其特征在 于，所述根据用户需求信息和站内空间拓扑网以及站内客流拥挤度模型进行路径规划，输出规划路径，具体为：
    根据出发点和终点结合站内空间拓扑网，获取所有从出发点到终点的第一路径，所述第一路径包括拓扑节点和拓扑弧段；
    结合出行属性因子和节点因子对第一路径进行筛选，得到第二路径；
    根据站内客流拥挤度模型得到消耗量，根据消耗量对第二路径进行筛选，得到第三路径；
    输出第三路径。
  6. 根据权利要求2所述的基于地铁拥挤度的站内路径规划方法，其特征在于，所述出行属性因子包括出站因子或进站因子，所述出行属性因子代表用户需要出站还是需要进站；
    所述节点因子包括双向通行、不可通行、出站通行或进站通行，不同的关键节点对应的节点因子不同。
  7. 根据权利要求5所述的基于地铁拥挤度的站内路径规划方法，其特征在于，所述根据站内客流拥挤度模型得到消耗量，根据消耗量对第二路径进行筛选，得到第三路径，具体为：
    根据站内客流拥挤度模型得到每一拥挤度等级对应的路径长度；
    根据每一拥挤度等级对应的路径长度结合每一拥挤度等级对应的单位消耗，得到每一拥挤度等级对应的消耗量；
    将第二路径中每一条路径中的所有拥挤度等级对应的消耗量相加，得到总的消耗量；
    筛选出总消耗量最小的路径为第三路径。
  8. 一种基于地铁拥挤度的站内路径规划装置，其特征在于，包括：
    信息接收单元，用于接收用户输入的需求信息，所述需求信息包括出行属性因子、出发点信息和终点信息；
    拓扑网构建单元，用于根据需求信息对地铁公交线路网络进行抽象化处理构建站内空间拓扑网，得到拓扑节点和拓扑弧段；
    拥挤度模型构建单元，用于根据对应的拓扑节点获取对应的客流量数据采集设备采集到的客流量数据，得到站内客流拥挤度模型，所述站内客流拥挤度模型包括拥挤度等级和拥挤度等级等值面的分布；
    路径规划单元，用于根据用户需求信息和站内空间拓扑网以及站内客流拥 挤度模型进行路径规划，输出规划路径。
  9. 一种电子设备，其特征在于，包括：
    存储器以及一个或多个处理器；
    所述存储器，用于存储一个或多个程序；
    当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现如权利要求1-7任一所述的方法。
  10. 一种包含计算机可执行指令的存储介质，其特征在于，所述计算机可执行指令在由计算机处理器执行时用于执行如权利要求1-7任一所述的方法。
PCT/CN2022/134199 2022-01-19 2022-11-24 一种基于地铁拥挤度的站内路径规划方法及装置 WO2023138212A1 (zh)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118195102A (zh) * 2024-05-15 2024-06-14 北京建筑大学 一种基于交通大数据的客流拥挤事件传播检测方法及***

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114593734B (zh) * 2022-01-19 2023-06-06 广州新科佳都科技有限公司 一种基于地铁拥挤度的站内路径规划方法及装置
CN115619048A (zh) * 2022-12-19 2023-01-17 成都智元汇信息技术股份有限公司 一种自动规划快速进出地铁站的方法和装置
CN116659515B (zh) * 2023-07-28 2024-01-23 北京城建智控科技股份有限公司 地铁站内线路的导航方法及装置、电子设备及存储介质
CN117252323B (zh) * 2023-11-17 2024-01-30 西华大学 一种基于用户偏好的多模式出行路径规划方法

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170059341A1 (en) * 2015-08-31 2017-03-02 Sap Se Diversified route planning for public transportation network
CN109819038A (zh) * 2019-01-30 2019-05-28 成都智元汇信息技术股份有限公司 一种基于客流信息实时上传的地铁综合管控***及方法
CN110857856A (zh) * 2018-08-22 2020-03-03 阿里巴巴集团控股有限公司 路线规划方法及***
CN112163701A (zh) * 2020-09-23 2021-01-01 佳都新太科技股份有限公司 一种车站枢纽换乘管理方法及装置
CN113807026A (zh) * 2021-10-08 2021-12-17 青岛理工大学 地铁站内客流流线优化及动态引导指示牌***及设计方法
CN113919582A (zh) * 2021-10-20 2022-01-11 广州新科佳都科技有限公司 一种站内路况的分析方法、装置、设备和存储介质
CN114593734A (zh) * 2022-01-19 2022-06-07 广州新科佳都科技有限公司 一种基于地铁拥挤度的站内路径规划方法及装置

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4652848B2 (ja) * 2005-03-02 2011-03-16 株式会社日立ソリューションズ 駅構内における最適経路探索装置および方法
JP2018002037A (ja) * 2016-07-06 2018-01-11 株式会社日立製作所 混雑率予想システム及び方法
CN110059861A (zh) * 2019-03-22 2019-07-26 江苏大学 一种考虑拥挤度的公交线路选择方法及***
CN111256724A (zh) * 2020-03-25 2020-06-09 交通运输部科学研究院 一种根据地铁拥挤度的公交地铁换乘路径规划方法

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170059341A1 (en) * 2015-08-31 2017-03-02 Sap Se Diversified route planning for public transportation network
CN110857856A (zh) * 2018-08-22 2020-03-03 阿里巴巴集团控股有限公司 路线规划方法及***
CN109819038A (zh) * 2019-01-30 2019-05-28 成都智元汇信息技术股份有限公司 一种基于客流信息实时上传的地铁综合管控***及方法
CN112163701A (zh) * 2020-09-23 2021-01-01 佳都新太科技股份有限公司 一种车站枢纽换乘管理方法及装置
CN113807026A (zh) * 2021-10-08 2021-12-17 青岛理工大学 地铁站内客流流线优化及动态引导指示牌***及设计方法
CN113919582A (zh) * 2021-10-20 2022-01-11 广州新科佳都科技有限公司 一种站内路况的分析方法、装置、设备和存储介质
CN114593734A (zh) * 2022-01-19 2022-06-07 广州新科佳都科技有限公司 一种基于地铁拥挤度的站内路径规划方法及装置

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN118195102A (zh) * 2024-05-15 2024-06-14 北京建筑大学 一种基于交通大数据的客流拥挤事件传播检测方法及***

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