CN113516263A - Vehicle scheduling method and device based on station image recognition - Google Patents

Vehicle scheduling method and device based on station image recognition Download PDF

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CN113516263A
CN113516263A CN202110432870.6A CN202110432870A CN113516263A CN 113516263 A CN113516263 A CN 113516263A CN 202110432870 A CN202110432870 A CN 202110432870A CN 113516263 A CN113516263 A CN 113516263A
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riding
reservation
passenger
station
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梁发祥
刘文婷
张建明
邢映彪
马廷铿
杨辛霖
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Guangzhou Tongbada Electric Technology Co ltd
Guangzhou Tongda Auto Electric Co Ltd
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Guangzhou Tongbada Electric Technology Co ltd
Guangzhou Tongda Auto Electric Co Ltd
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    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
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    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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    • G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
    • G08G1/202—Dispatching vehicles on the basis of a location, e.g. taxi dispatching

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Abstract

The embodiment of the application discloses a vehicle scheduling method and device based on station image recognition. According to the technical scheme provided by the embodiment of the application, the bus taking reservation instruction initiated by a passenger is received, the bus taking information is obtained based on the bus taking reservation instruction, the reserved passenger flow of different stations in different time periods is counted according to the bus taking information, the face characteristic information of the bus taking object on the stations is collected at the same time, the bus taking object is checked and screened again based on the comparison between the face characteristic information and the reserved object, the accurate counting of the passenger flow is realized, the passenger flow is determined according to the reserved passenger flow and the passenger taking object to be taken, the dispatching scheme of the corresponding train number is adjusted based on the passenger flow, and the vehicle waste caused by repeated counting is avoided.

Description

Vehicle scheduling method and device based on station image recognition
Technical Field
The embodiment of the application relates to the technical field of vehicle management, in particular to a vehicle scheduling method and device based on station image identification.
Background
As the volume of passenger in large cities increases, vehicle dispatch at urban transportation hubs faces greater challenges. The efficiency of vehicle dispatch needs to be improved to accommodate the increase in passenger traffic, otherwise it can cause a huge obstruction to urban traffic.
At present, traffic scheduling management of cities generally schedules vehicles in a storage area to one or more riding areas by using communication equipment and according to requirements of different riding areas through scheduling personnel. The manual scheduling mode has the problems of high labor cost, low scheduling efficiency, low speed and the like. In addition, some cities are convenient to manage vehicle scheduling, various traffic data in a past period of time are acquired by means of urban traffic observation, and traffic scheduling modes corresponding to different periods of time are obtained by means of processing and calculating the traffic data. Although the method overcomes the problems of high cost, low efficiency and the like caused by manual scheduling, the data of the trips can bring corresponding changes according to different weather, different festivals, road planning changes and the like, and the future vehicle scheduling is governed only according to the past data, which may cause the problems of uneven and inaccurate vehicle scheduling.
Disclosure of Invention
The embodiment of the application provides a vehicle scheduling method and device based on station image recognition, vehicle scheduling equipment and a storage medium, so that the passenger objects are screened for duplicate checking, and the accuracy and the reasonability of vehicle scheduling are improved.
In a first aspect, an embodiment of the present application provides a vehicle scheduling method based on station image identification, including:
acquiring the riding information of the reserved object in response to the riding reservation instruction; the riding information comprises riding times, riding time, getting-on sites, getting-off sites, destinations and reservation object information; the reservation object information comprises biological sign information, account information and identity information;
counting the reserved passenger flow of any train number in any time period and any station according to the riding information;
the method comprises the steps of obtaining face feature information of a riding object on a station, and comparing the face feature information of the riding object with reserved object information to obtain an object to be ridden;
and determining the passenger flow according to the reserved passenger flow and the object to be ridden, and adjusting the departure scheme of the corresponding train number based on the passenger flow.
Further, after obtaining the riding information of the riding object in response to the riding reservation instruction, the method further includes:
and feeding back a riding code to a riding object based on the riding information.
Further, the method also comprises the following steps:
responding to a riding command of a riding object, and acquiring a riding code of the riding object;
and determining whether the current riding object accords with the current riding sequence according to the riding code, and prompting the riding object when the current riding sequence is not accorded with the current riding sequence.
Further, the acquiring the face feature information of the riding object on the station, and comparing the face feature information of the riding object with the riding object information to obtain a new object to be ridden, includes:
acquiring image information, and confirming the face information in the image information based on preset face key point characteristics;
detecting the number of riding objects based on the face information, and when the number of the riding objects is larger than 1, respectively amplifying a face area corresponding to each riding object in the face information to obtain face feature information of the face area;
acquiring passenger account information corresponding to the face feature information based on the face feature information;
comparing the passenger account information with account information in the reservation object information, and ignoring the riding object on the site when the passenger account information is consistent with the account information in the reservation object information; and when the passenger account information is inconsistent with the account information in the reservation object information, taking the riding object as the object to be ridden.
Further, the obtaining of the face feature information of the riding object on the station and comparing the face feature information of the riding object with the riding object information to obtain a new object to be ridden includes:
acquiring face feature information of a riding object on a station, and acquiring passenger identity information corresponding to the face feature information based on the face feature information;
comparing the passenger identity user information with identity information in the reservation object information, and ignoring the riding object on the station when the passenger identity information is consistent with the identity information in the reservation object information; and when the passenger identity information is inconsistent with the identity information in the reservation object information, taking the riding object as the object to be ridden.
Further, the obtaining of the face feature information of the riding object on the station and comparing the face feature information of the riding object with the riding object information to obtain a new object to be ridden includes:
collecting the face characteristic information of a riding object on a station, and calculating the similarity between the face characteristic information of the riding object and the face characteristic information of the reserved object information;
and when the similarity is greater than a similarity threshold value, taking the riding object as the object to be ridden, and when the similarity is less than or equal to the similarity threshold value, ignoring the riding object on the station.
Further, the determining the passenger flow volume according to the reserved passenger flow volume and the object to be taken by the car and adjusting the departure scheme of the corresponding car number based on the passenger flow volume includes:
calculating the sum of the reserved passenger flow and the object to be ridden to obtain the passenger flow;
updating the demand of the corresponding train number counted last time based on the passenger flow, and acquiring the idle quantity in the departure scheme of the corresponding train number;
and calculating the residual quantity of the corresponding train number based on the required quantity and the idle quantity of the corresponding train number, and increasing the number of vehicles of the corresponding train number when the residual quantity is smaller than a residual threshold value.
In a second aspect, an embodiment of the present application provides a vehicle scheduling apparatus based on station image recognition, including:
a reservation response module: the system comprises a bus taking reservation command acquisition unit, a bus taking reservation unit and a bus taking management unit, wherein the bus taking reservation command acquisition unit is used for acquiring bus taking information of a reserved object in response to the bus taking reservation command; the riding information comprises riding times, riding time, getting-on sites, getting-off sites, destinations and reservation object information; the reservation object information comprises biological sign information, account information and identity information;
a passenger volume statistics module: the system is used for counting the reserved passenger flow of any train number in any time period and any station according to the riding information;
a feature comparison module: the system comprises a bus stop, a bus reservation module, a bus stop control module and a bus transfer module, wherein the bus stop is used for acquiring the face characteristic information of a bus object on the bus stop and comparing the face characteristic information of the bus object with the reservation object information to acquire an object to be bus;
a scheme adjusting module: and the dispatching scheme is used for determining the passenger flow according to the reserved passenger flow and the new object to be ridden and adjusting the corresponding train number based on the passenger flow.
Further, the system also comprises an information feedback module: and the system is used for feeding back the riding code of the riding object based on the riding information after the reservation response module.
Further, the method also comprises the following steps:
a code acquisition module: the system comprises a riding code acquisition unit, a riding code acquisition unit and a control unit, wherein the riding code acquisition unit is used for acquiring a riding code of a riding object in response to a riding command of the riding object;
an order arrangement module: and the riding device is used for determining whether the current riding object accords with the current riding sequence according to the riding code and prompting the riding object when the current riding sequence is not accorded with.
Further, the obtaining of the face feature information of the riding object on the station and comparing the face feature information of the riding object with the riding object information to obtain a new object to be ridden includes:
the method comprises the steps of obtaining face feature information of a riding object on a station, and obtaining passenger account information corresponding to the face feature information based on the face feature information;
comparing the passenger account information with account information in the reservation object information, and ignoring the riding object on the site when the passenger account information is consistent with the account information in the reservation object information; and when the passenger account information is inconsistent with the account information in the reservation object information, taking the riding object as the object to be ridden.
Further, the obtaining of the face feature information of the riding object on the station and comparing the face feature information of the riding object with the riding object information to obtain a new object to be ridden includes:
the method comprises the steps of obtaining face feature information of a riding object on a station, and obtaining passenger identity information corresponding to the face feature information based on the face feature information;
comparing the passenger identity user information with identity information in the reservation object information, and ignoring the riding object on the station when the passenger identity information is consistent with the identity information in the reservation object information; and when the passenger identity information is inconsistent with the identity information in the reservation object information, taking the riding object as the object to be ridden.
Further, the obtaining of the face feature information of the riding object on the station and comparing the face feature information of the riding object with the riding object information to obtain a new object to be ridden includes:
acquiring the face characteristic information of a riding object on a station, and calculating the similarity between the face characteristic information of the riding object and the face characteristic information of the reserved object information;
and when the similarity is greater than a similarity threshold value, taking the riding object as the object to be ridden, and when the similarity is less than or equal to the similarity threshold value, ignoring the riding object on the station.
Further, the determining the passenger flow volume according to the reserved passenger flow volume and the object to be taken by the car and adjusting the departure scheme of the corresponding car number based on the passenger flow volume includes:
calculating the sum of the reserved passenger flow and the object to be ridden to obtain the passenger flow;
updating the demand of the corresponding train number counted last time based on the passenger flow, and acquiring the idle quantity in the departure scheme of the corresponding train number;
and calculating the residual quantity of the corresponding train number based on the required quantity and the idle quantity of the corresponding train number, and increasing the number of vehicles of the corresponding train number when the residual quantity is smaller than a residual threshold value.
In a third aspect, an embodiment of the present application provides a computer device, including: a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method for vehicle dispatch based on site image recognition as described in the first aspect.
In a fourth aspect, embodiments of the present application provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the method for vehicle dispatch based on station image recognition as described in the first aspect.
According to the method and the device, the riding information is obtained based on the riding reservation instruction by receiving the riding reservation instruction initiated by the passenger, the reserved passenger flow of different stations in different time periods is counted according to the riding information, meanwhile, the face characteristic information of riding objects on the stations is collected, the riding objects are checked for duplicate and screened based on the comparison between the face characteristic information and the reserved objects, the passenger flow is accurately counted, the passenger flow is determined according to the reserved passenger flow and the objects to be ridden, the departure scheme of the corresponding number of vehicles is adjusted based on the passenger flow, and the vehicle waste caused by repeated counting is avoided.
Drawings
Fig. 1 is a flowchart of a vehicle scheduling method based on station image identification according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a vehicle scheduling device based on station image identification according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a vehicle dispatching device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, specific embodiments of the present application will be described in detail with reference to the accompanying drawings. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some but not all of the relevant portions of the present application are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
The embodiment of the application provides a vehicle scheduling method and device based on station image identification, vehicle scheduling equipment and a storage medium. The embodiment of the application is as follows. Receiving a riding reservation instruction initiated by a passenger, acquiring riding information based on the riding reservation instruction, counting reserved passenger flow of different stations in different time periods according to the riding information, simultaneously acquiring face characteristic information of riding objects on the stations, comparing the face characteristic information with the reserved objects to check for repeated screening of the riding objects, realizing accurate counting of the passenger flow, determining the passenger flow according to the reserved passenger flow and the objects to be ridden, adjusting a departure scheme of a corresponding number of cars based on the passenger flow, and avoiding vehicle waste caused by repeated counting.
The following are detailed below.
Fig. 1 is a flowchart of a vehicle scheduling method based on station image recognition according to an embodiment of the present disclosure, where the vehicle scheduling method based on station image recognition according to an embodiment of the present disclosure may be executed by a vehicle scheduling apparatus based on station image recognition, and the vehicle scheduling method based on station image recognition may be implemented in hardware and/or software and integrated in a computer device.
The following description will be given taking as an example a vehicle scheduling method in which a vehicle scheduling apparatus based on station image recognition performs vehicle scheduling based on station image recognition. Referring to fig. 1, the vehicle scheduling method based on station image recognition includes:
101: and acquiring the riding information of the reserved object in response to the riding reservation instruction.
In this embodiment, the vehicle dispatching system may be implemented, and the vehicle dispatching system includes a user terminal, a dispatching center, and a stop board interaction device. The user terminal and the stop board interaction device can be communicated with the dispatching center. The communication between the user terminal and the dispatch center is typically wireless transmission, while the communication between the stop sign interaction device and the dispatch center may include wireless and wired. The user terminal is an intelligent electronic product held by a user, and includes but is not limited to a smart phone, a smart bracelet, a smart watch, a notebook computer and a tablet computer. The user can input a riding reservation instruction through a corresponding application program in the user terminal, and riding information of the user is synchronously formed when the riding reservation instruction is generated, and at the moment, the user is used as a riding reservation object because the user has riding requirements. The dispatching center is used for obtaining information of the user terminal and the stop board interaction device to allocate vehicles, and the dispatching center is used as an intelligent device in the embodiment, such as an entity server or a cloud service center, and has a data operation processing function. The stop board interaction device is an intelligent device arranged at a stop, for example, the stop board interaction device is installed at a bus stop, wherein the stop board interaction device comprises an image acquisition device, automatically carries out face recognition on passengers passing through the image acquisition device to obtain face characteristic information, and sends the face characteristic information to a dispatching center.
The riding information comprises riding times, riding time, getting-on sites, getting-off sites, destinations and reservation object information; the reservation object information comprises biological sign information, account information and identity information.
Preferably, the riding information of the riding object is acquired in response to the riding reservation instruction, and then is fed back to the riding code of the riding object based on the riding information. Illustratively, the ride code may be in the form of a two-dimensional code or a bar code. Further, responding to a riding command of the riding object, and acquiring a riding code of the riding object; and determining whether the current riding object accords with the current riding sequence according to the riding code, and prompting the riding object when the current riding sequence is not accorded with the current riding sequence.
In this embodiment, the vehicle dispatching system may further include vehicle terminals installed in the vehicle and corresponding to the vehicles one to one. The vehicle terminal has the function of code scanning riding codes, the user terminal held by a user receives the riding codes and carries out code scanning recognition on the riding codes through the vehicle terminal when the user enters the vehicle to ride, so as to judge whether the riding objects accord with the current riding sequence, and the vehicle terminal can effectively prevent queue insertion and enable the riding objects to ride the vehicle in order.
102: and counting the reserved passenger flow of any train number in any time period and any station according to the riding information.
The scheduling center can simultaneously receive the riding reservation commands sent by the plurality of user terminals, and the riding reservation commands comprise riding information, so that the reserved passenger flow volume can be counted based on riding times and the like in the riding information. The user can reserve the riding information of one or more riding objects through the user terminal, and when the riding reservation command comprises a plurality of riding objects, the included reservation object information is in one-to-one correspondence with the riding objects.
103: the method comprises the steps of obtaining the face feature information of a riding object on a station, and comparing the face feature information of the riding object with the reserved object information to obtain an object to be ridden.
The image acquisition equipment is used for acquiring the face image information of the riding objects on the station, and usually, the face image information is uniquely corresponding to each riding object, so that the corresponding riding object can be obtained through the face image information.
The method comprises the steps of acquiring face feature information of a riding object on a station, and acquiring passenger account information corresponding to the face feature information based on the face feature information; comparing the passenger account information with account information in the reservation object information, and ignoring the riding object on the site when the passenger account information is consistent with the account information in the reservation object information; and when the passenger account information is inconsistent with the account information in the reservation object information, taking the riding object as the object to be ridden. In the exemplary embodiment, a face recognition algorithm for acquiring the face feature information of the riding objects on the station is to acquire image information, confirm the face information in the image information based on preset face key point features, detect the number of the riding objects based on the face information, and respectively amplify a face area corresponding to each riding object in the face information when the number of the riding objects is greater than 1, so as to acquire the face feature information of the face area. Wherein, the collected image information can be obtained by a high-definition camera. The preset human face key point features are any one or more of lips, eyes, ears and noses, a human face key point feature recognition model can be constructed by training a human face key feature point training set in advance, and when image information is subsequently input, the human face key point features can be rapidly detected so as to determine the human face information. Since a plurality of riding objects may be photographed at the same time at the station, separate information matching is required for each riding object information.
The passenger account information and the corresponding face feature information can be bound and stored in advance, and when the station interaction device collects the face feature information and sends the face feature information to the dispatching center, the dispatching center can quickly match the corresponding passenger account information according to the face feature information. When the account information of the passenger is consistent with the account information in the reservation object information, the two objects are the same person, and at the moment, one repeated information needs to be deleted, so that the waste of the vehicle caused by repeated statistics is avoided.
In another example, the method comprises the steps of acquiring the face feature information of a riding object on a station, and acquiring the passenger identity information corresponding to the face feature information based on the face feature information; comparing the passenger identity user information with identity information in the reservation object information, and ignoring the riding object on the station when the passenger identity information is consistent with the identity information in the reservation object information; and when the passenger identity information is inconsistent with the identity information in the reservation object information, taking the riding object as the object to be ridden.
Correspondingly, in this example, the passenger identity information and the corresponding face feature information may also be bound and stored first, and when the station interaction device collects the face feature information, the face feature information is sent to the scheduling center, so that when the scheduling center can quickly match the corresponding passenger identity information according to the face feature information.
Another example is that the face feature information of the riding object on the station is obtained, and the similarity between the face feature information of the riding object and the face feature information of the reservation object information is calculated; and when the similarity is greater than a similarity threshold value, taking the riding object as the object to be ridden, and when the similarity is less than or equal to the similarity threshold value, ignoring the riding object on the station.
104: and determining the passenger flow according to the reserved passenger flow and the object to be ridden, and adjusting the departure scheme of the corresponding train number based on the passenger flow.
Illustratively, calculating the sum of the reserved passenger flow and the object to be taken to obtain the passenger flow; updating the demand of the corresponding train number counted last time based on the passenger flow, and acquiring the idle quantity in the departure scheme of the corresponding train number; and calculating the residual quantity of the corresponding train number based on the required quantity and the idle quantity of the corresponding train number, and increasing the number of vehicles of the corresponding train number when the residual quantity is smaller than a residual threshold value. Specifically, the number of the specific increased vehicle numbers may be determined according to the difference between the residual amount and the residual threshold. For example, the required quantity of the ride number of the vehicle is 50, and the required quantity of the ride number a is 50, which indicates that 50 ride objects are currently intended to ride on the corresponding station. And when the idle quantity of the train number A is currently 1, the residual quantity is-49, namely 49 additional empty spaces are needed to meet the requirement, and the number of the vehicles is set according to the empty quantity of one train number until all the requirements are met.
As shown in fig. 2, the present embodiment further provides a vehicle dispatching device based on station image recognition, which includes a reservation response module 201, a passenger volume statistics module 202, a feature comparison module 203, and a plan adjustment module 204. The reservation response module 201 is configured to obtain the riding information of the reserved object in response to the riding reservation instruction; the riding information comprises riding times, riding time, getting-on sites, getting-off sites, destinations and reservation object information; the reservation object information comprises biological sign information, account information and identity information; the passenger volume counting module 202 is used for counting the reserved passenger volume of any train number in any time period and any station according to the riding information; the characteristic comparison module 203 is used for acquiring the face characteristic information of the riding object on the station, and comparing the face characteristic information of the riding object with the reserved object information to acquire the object to be ridden; and the plan adjusting module 204 is configured to determine passenger flow volumes according to the reserved passenger flow volumes and the new objects to be ridden, and adjust a departure plan of a corresponding train number based on the passenger flow volumes.
Further, the embodiment further includes an information feedback module 205: and the system is used for feeding back the riding code of the riding object based on the riding information after the reservation response module.
More preferably, the method further comprises the following steps: the code acquisition module 206: the system comprises a riding code acquisition unit, a riding code acquisition unit and a control unit, wherein the riding code acquisition unit is used for acquiring a riding code of a riding object in response to a riding command of the riding object; the ordering module 207: and the riding device is used for determining whether the current riding object accords with the current riding sequence according to the riding code and prompting the riding object when the current riding sequence is not accorded with.
In the feature comparison module 203, for example, face feature information of a riding object on a station is obtained, and passenger account information corresponding to the face feature information is obtained based on the face feature information; comparing the passenger account information with account information in the reservation object information, and ignoring the riding object on the site when the passenger account information is consistent with the account information in the reservation object information; and when the passenger account information is inconsistent with the account information in the reservation object information, taking the riding object as the object to be ridden.
In another example, the method comprises the steps of acquiring the face feature information of a riding object on a station, and acquiring the passenger identity information corresponding to the face feature information based on the face feature information;
comparing the passenger identity user information with identity information in the reservation object information, and ignoring the riding object on the station when the passenger identity information is consistent with the identity information in the reservation object information; and when the passenger identity information is inconsistent with the identity information in the reservation object information, taking the riding object as the object to be ridden.
Another example is that the face feature information of the riding object on the station is obtained, and the similarity between the face feature information of the riding object and the face feature information of the reservation object information is calculated;
and when the similarity is greater than a similarity threshold value, taking the riding object as the object to be ridden, and when the similarity is less than or equal to the similarity threshold value, ignoring the riding object on the station.
In the scheme adjusting module 204, the sum of the reserved passenger flow and the object to be taken by the bus is calculated to obtain the passenger flow;
updating the demand of the corresponding train number counted last time based on the passenger flow, and acquiring the idle quantity in the departure scheme of the corresponding train number; and calculating the residual quantity of the corresponding train number based on the required quantity and the idle quantity of the corresponding train number, and increasing the number of vehicles of the corresponding train number when the residual quantity is smaller than a residual threshold value.
As shown in fig. 3, an embodiment of the present application further provides a computer device, including: a memory 401 and one or more processors 302; the memory 301 is used for storing one or more programs; when executed by the one or more processors 32, cause the one or more processors to implement a method for vehicle dispatch based on site image recognition as described herein.
Embodiments of the present application further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the vehicle scheduling method based on station image identification provided in the foregoing embodiments, where the vehicle scheduling method based on station image identification includes: acquiring the riding information of the reserved object in response to the riding reservation instruction; the riding information comprises riding times, riding time, getting-on sites, getting-off sites, destinations and reservation object information; the reservation object information comprises biological sign information, account information and identity information; counting the reserved passenger flow of any train number in any time period and any station according to the riding information; the method comprises the steps of obtaining face feature information of a riding object on a station, and comparing the face feature information of the riding object with reserved object information to obtain an object to be ridden; and determining the passenger flow according to the reserved passenger flow and the object to be ridden, and adjusting the departure scheme of the corresponding train number based on the passenger flow.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (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. In addition, 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. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium provided in the embodiments of the present application contains computer-executable instructions, and the computer-executable instructions are not limited to the vehicle scheduling method based on station image identification as described above, and may also perform related operations in the vehicle scheduling method based on station image identification as provided in any embodiment of the present application.
The vehicle scheduling device, the apparatus and the storage medium based on the station image recognition provided in the foregoing embodiments may execute the vehicle scheduling method based on the station image recognition provided in any embodiment of the present application, and reference may be made to the vehicle scheduling method based on the station image recognition provided in any embodiment of the present application without detailed technical details described in the foregoing embodiments.
The foregoing is considered as illustrative of the preferred embodiments of the invention and the technical principles employed. The present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the claims.

Claims (10)

1. A vehicle scheduling method based on station image recognition is characterized by comprising the following steps:
acquiring the riding information of the reserved object in response to the riding reservation instruction; the riding information comprises riding times, riding time, getting-on sites, getting-off sites, destinations and reservation object information; the reservation object information comprises biological sign information, account information and identity information;
counting the reserved passenger flow of any train number in any time period and any station according to the riding information;
the method comprises the steps of obtaining face feature information of a riding object on a station, and comparing the face feature information of the riding object with reserved object information to obtain an object to be ridden;
and determining the passenger flow according to the reserved passenger flow and the object to be ridden, and adjusting the departure scheme of the corresponding train number based on the passenger flow.
2. The vehicle scheduling method according to claim 1, wherein after obtaining the riding information of the riding object in response to the riding reservation instruction, the method further comprises:
and feeding back a riding code to a riding object based on the riding information.
3. The vehicle scheduling method of claim 2, further comprising:
responding to a riding command of a riding object, and acquiring a riding code of the riding object;
and determining whether the current riding object accords with the current riding sequence according to the riding code, and prompting the riding object when the current riding sequence is not accorded with the current riding sequence.
4. The vehicle scheduling method according to claim 1, wherein the obtaining of the face feature information of the riding object on the station and comparing the face feature information of the riding object with the riding object information to obtain a new object to be ridden comprises:
acquiring image information, and confirming the face information in the image information based on preset face key point characteristics;
detecting the number of riding objects based on the face information, and when the number of the riding objects is larger than 1, respectively amplifying a face area corresponding to each riding object in the face information to obtain face feature information of the face area;
acquiring passenger account information corresponding to the face feature information based on the face feature information;
comparing the passenger account information with account information in the reservation object information, and ignoring the riding object on the site when the passenger account information is consistent with the account information in the reservation object information; and when the passenger account information is inconsistent with the account information in the reservation object information, taking the riding object as the object to be ridden.
5. The vehicle scheduling method according to claim 1, wherein the obtaining of the face feature information of the riding object on the station and comparing the face feature information of the riding object with the riding object information to obtain a new object to be ridden comprises:
the method comprises the steps of obtaining face feature information of a riding object on a station, and obtaining passenger identity information corresponding to the face feature information based on the face feature information;
comparing the passenger identity user information with identity information in the reservation object information, and ignoring the riding object on the station when the passenger identity information is consistent with the identity information in the reservation object information; and when the passenger identity information is inconsistent with the identity information in the reservation object information, taking the riding object as the object to be ridden.
6. The vehicle scheduling method according to claim 1, wherein the obtaining of the face feature information of the riding object on the station and comparing the face feature information of the riding object with the riding object information to obtain a new object to be ridden comprises:
acquiring the face characteristic information of a riding object on a station, and calculating the similarity between the face characteristic information of the riding object and the face characteristic information of the reserved object information;
and when the similarity is greater than a similarity threshold value, taking the riding object as the object to be ridden, and when the similarity is less than or equal to the similarity threshold value, ignoring the riding object on the station.
7. The vehicle scheduling method according to claim 1, wherein the determining a passenger flow volume according to the reserved passenger flow volume and the object to be ridden and adjusting a departure scheme of a corresponding train number based on the passenger flow volume comprises:
calculating the sum of the reserved passenger flow and the object to be ridden to obtain the passenger flow;
updating the demand of the corresponding train number counted last time based on the passenger flow, and acquiring the idle quantity in the departure scheme of the corresponding train number;
and calculating the residual quantity of the corresponding train number based on the required quantity and the idle quantity of the corresponding train number, and increasing the number of vehicles of the corresponding train number when the residual quantity is smaller than a residual threshold value.
8. A vehicle scheduling device based on station image recognition is characterized by comprising:
a reservation response module: the system comprises a bus taking reservation command acquisition unit, a bus taking reservation unit and a bus taking management unit, wherein the bus taking reservation command acquisition unit is used for acquiring bus taking information of a reserved object in response to the bus taking reservation command; the riding information comprises riding times, riding time, getting-on sites, getting-off sites, destinations and reservation object information; the reservation object information comprises biological sign information, account information and identity information;
a passenger volume statistics module: the system is used for counting the reserved passenger flow of any train number in any time period and any station according to the riding information;
a feature comparison module: the system comprises a bus stop, a bus reservation module, a bus stop control module and a bus transfer module, wherein the bus stop is used for acquiring the face characteristic information of a bus object on the bus stop and comparing the face characteristic information of the bus object with the reservation object information to acquire an object to be bus;
a scheme adjusting module: and the dispatching scheme is used for determining the passenger flow according to the reserved passenger flow and the new object to be ridden and adjusting the corresponding train number based on the passenger flow.
9. A computer device, comprising: a memory and one or more processors;
the memory for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the method for vehicle dispatch based on image recognition of a station as claimed in any of claims 1-7.
10. A storage medium containing computer-executable instructions for performing the method for vehicle dispatch based on image identification of a station according to any one of claims 1 to 7 when executed by a computer processor.
CN202110432870.6A 2021-04-21 2021-04-21 Vehicle scheduling method and device based on station image recognition Pending CN113516263A (en)

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