CN205608812U - Public transport passenger flow measures detecting system based on face identification and position location - Google Patents
Public transport passenger flow measures detecting system based on face identification and position location Download PDFInfo
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- CN205608812U CN205608812U CN201620280696.2U CN201620280696U CN205608812U CN 205608812 U CN205608812 U CN 205608812U CN 201620280696 U CN201620280696 U CN 201620280696U CN 205608812 U CN205608812 U CN 205608812U
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Abstract
The utility model discloses a public transport passenger flow measures detecting system based on face identification and position location, its system is including image gathering module, bus position collection module, data mining center and the data analysis center connected in order, image gathering module is used for gathering the facial image that the bus was got on or off the bus, and bus position collection module is used for carrying out the record to the traveling track of bus, and the data mining center is used for carrying out analysis of people's face and position analysis to the image of gathering, and the data analysis center is used for the center analysis obtained according to data mining result to carry out flow statistical analysis, provides the decision -making foundation for bus line way planning, operation management, circuit conditioning etc.. The utility model discloses an use and not only improved the precision that the public transport passenger flow volume detected, improved the frequency that the public transport passenger flow volume detected moreover, saved flow investigation cost greatly.
Description
Technical field
This utility model relates to bus passenger flow amount detection systems based on recognition of face and location positioning.
Background technology
Due to Urban Residential Trip skewness weighing apparatus property over time and space, necessarily cause inside the bus of part website the most crowded, even occur that the load factor in website stayer, or the bus of part website is the highest.Above-mentioned phenomenon is relevant to the reasonability of public transport network and Management plan thereof, their data basis is bus passenger flow amount, including the getting on or off the bus of website, section flow (passenger inside the vehicle's number) and public transport OD (get on the bus from certain website and number that another one website is got off).In order to ensure the enforcement of public traffic in priority national development strategy, passenger flow evacuated in time by the limited transport power of rationalization, and bus passenger flow amount statistical analysis is increasingly by traffic control department, the attention of public transport company and concern.
At present, the acquisition mode of bus passenger flow amount is broadly divided into two kinds:
(1) manually gather, common artificial data investigation method has site surveys, with car investigation and survey on vehicle etc., put into and manually carry out questionnaire survey in a large number, being easily caused survey data quality cannot be control, analysis of statistical data is the most time-consuming, investigation cost is higher, and can not the temporal-spatial evolution problem of the continuous detecting volume of the flow of passengers.
(2) smart machine collection, in conjunction with wireless sensor networks, face recognition technology, human body signal detection technique, obtains the record of each passenger getting on/off in real time, utilizes getting on or off the bus and number of people in car of smart machine each website of statistical analysis.Common acquisition means includes public transport IC card, RFID technique, pressure transducer, infrared and recognition of face etc., and each intelligent acquisition mode cuts both ways.Although bus IC card can obtain passenger getting on/off information exactly from technology angle, but general passenger loading is swiped the card and is got off and do not swipe the card.RFID technology ignores the electronic tag of bus external environment condition to be affected it, and the requirement of its application places is the highest.The bus passenger flow analysis of the technology combined based on recognition of face and location positioning and location positioning is a kind of new technological means, it is possible not only to gather the number of getting on or off the bus of bus station, section flow, and public transport OD distribution situation can be analyzed according to positional information.
In sum, the detecting system carrying out bus passenger flow amount in conjunction with recognition of face and location positioning can provide decision-making foundation for public bus network planning, operational management, line adjustment etc. well with method.
Utility model content
Weak point for existing bus passenger flow amount detection systems Yu method, this utility model provides a kind of high accuracy, the novel bus volume of the flow of passengers detecting system of detection in real time, obtained get on or off the bus temporal information and the positional information of binding site location acquisition of information passenger getting on/off of passenger by the uniqueness of face characteristic, draw the data such as the number of getting on or off the bus of bus station, section flow and public transport OD by data mining and analysis.
The purpose of this utility model is achieved through the following technical solutions: bus passenger flow amount system based on recognition of face and location positioning, including the image capture module being sequentially connected with, position of bus acquisition module, data mining center and data analysis center；On the one hand the video information of the camera collection passenger getting on/off being arranged on bus is utilized, image pre-processing module carries out pretreatment and facial image is sent to the memory module at data mining center image information, and the driving trace information on the other hand utilizing station acquisition module to gather bus is sent to the memory module at data mining center.
Described image capture module is acquired for the facial image getting on or off the bus bus；Described position of bus acquisition module is for being acquired the driving trace of bus；Described data mining center includes memory module, image analysis module and location analysis module；Image analysis module, location analysis module are connected with the memory module of data analysis center；Described memory module is got on or off the bus the facial image of personnel, information of getting on or off the bus and bus driving trace for storing bus；Described image analysis module is for being analyzed the image collected, it is judged that the personnel that image is corresponding get on or off the bus information；Described location analysis module passes through image capturing time and bus travel track record time match, and analysis draws gets on or off the bus and position；Described data analysis center includes flow analysis module, is connected with the memory module at data mining center；Described flow analysis module is for statistical analysis public bus network, the single-point flow of website and OD distribution situation.
Application of the present utility model not only increases the precision of bus passenger flow amount detection, and improves the frequency of bus passenger flow amount detection, is greatly saved traffic investigation cost.
Accompanying drawing explanation
With detailed description of the invention, this utility model is described in further detail below in conjunction with the accompanying drawings.
Fig. 1 is the theory diagram of this utility model system.
Detailed description of the invention
The technical solution of the utility model is described in further detail below in conjunction with the accompanying drawings, but protection domain of the present utility model is not limited to the following stated.
As shown in Fig. 1, bus passenger flow amount detection systems based on recognition of face and location positioning, including the image capture module being sequentially connected with, position of bus acquisition module, data mining center and data analysis center；
Described image capture module is acquired for the facial image getting on or off the bus bus；Described position of bus acquisition module is for being acquired the driving trace of bus；
Described data mining center includes memory module, image analysis module and location analysis module；Image analysis module, location analysis module are connected with the memory module of data analysis center；
Described memory module is got on or off the bus the facial image of personnel, information of getting on or off the bus and bus driving trace for storing bus；
Described image analysis module is for being analyzed the image collected, it is judged that the personnel that image is corresponding get on or off the bus information；
Described location analysis module passes through image capturing time and bus travel track record time match, and analysis draws gets on or off the bus and position；
Described data analysis center includes flow analysis module, is connected with the memory module at data mining center；
Described flow analysis module is for statistical analysis public bus network, the single-point flow of website and OD distribution situation.
It is obvious to a person skilled in the art that this utility model is not limited to the details of above-mentioned one exemplary embodiment, and in the case of without departing substantially from spirit or essential attributes of the present utility model, it is possible to realize this utility model in other specific forms.Therefore, no matter from the point of view of which point, embodiment all should be regarded as exemplary, and be nonrestrictive, scope of the present utility model is limited by claims rather than described above, it is intended that all changes fallen in the implication of equivalency and scope of claim included in this utility model.Should not be considered as limiting involved claim by any reference in claim.
Claims (2)
1. bus passenger flow amount detection systems based on recognition of face and location positioning, it is characterised in that: include image capture module, position of bus acquisition module, data mining center and the data analysis center being sequentially connected with；Image capture module is acquired for the facial image getting on or off the bus bus, position of bus acquisition module is for being acquired the driving trace of bus, data mining center is for carrying out human face analysis and position analysis to the image collected and positional information, data analysis center carries out flow analysis for the result obtained according to data mining center analysis, provides decision-making foundation for public bus network planning, operational management, line adjustment etc.；Described image capture module is acquired for the facial image getting on or off the bus bus；Described position of bus acquisition module is for being acquired the driving trace of bus；Described data mining center includes memory module, image analysis module and location analysis module；Image analysis module, location analysis module are connected with the memory module of data analysis center；Described memory module is got on or off the bus the facial image of personnel, information of getting on or off the bus and bus driving trace for storing bus；Described image analysis module is for being analyzed the image collected, it is judged that the personnel that image is corresponding get on or off the bus information；Described location analysis module passes through image capturing time and bus travel track record time match, and analysis draws gets on or off the bus and position；Described data analysis center includes flow analysis module, is connected with the memory module at data mining center；Described flow analysis module is for statistical analysis public bus network, the single-point flow of website and OD distribution situation.
Bus passenger flow amount detection systems based on recognition of face and location positioning the most according to claim 1, it is characterized in that: described image capture module includes two photographic head of image pre-processing module and bus front/rear door, described image pre-processing module for camera collection to image carry out pretreatment, obtain facial image of the same size with image in memorizer.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105913367A (en) * | 2016-04-07 | 2016-08-31 | 北京晶众智慧交通科技股份有限公司 | Public bus passenger flow volume detection system and method based on face identification and position positioning |
| CN107240289A (en) * | 2017-07-24 | 2017-10-10 | 济南博图信息技术有限公司 | A kind of bus routes optimum management method and system |
| CN110147784A (en) * | 2019-06-26 | 2019-08-20 | 苏州金螳螂怡和科技有限公司 | A kind of passenger flow recognition of face flow system |
| CN112001232A (en) * | 2020-07-09 | 2020-11-27 | 北京北大千方科技有限公司 | Airport passenger flow travel chain accurate sensing device with individual characteristics |
| CN114973680A (en) * | 2022-07-01 | 2022-08-30 | 哈尔滨工业大学 | Bus passenger flow obtaining system and method based on video processing |
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2016
- 2016-04-07 CN CN201620280696.2U patent/CN205608812U/en active Active
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105913367A (en) * | 2016-04-07 | 2016-08-31 | 北京晶众智慧交通科技股份有限公司 | Public bus passenger flow volume detection system and method based on face identification and position positioning |
| CN107240289A (en) * | 2017-07-24 | 2017-10-10 | 济南博图信息技术有限公司 | A kind of bus routes optimum management method and system |
| CN110147784A (en) * | 2019-06-26 | 2019-08-20 | 苏州金螳螂怡和科技有限公司 | A kind of passenger flow recognition of face flow system |
| CN110147784B (en) * | 2019-06-26 | 2024-03-26 | 苏州朗捷通智能科技有限公司 | Passenger flow face identification flow system |
| CN112001232A (en) * | 2020-07-09 | 2020-11-27 | 北京北大千方科技有限公司 | Airport passenger flow travel chain accurate sensing device with individual characteristics |
| CN112001232B (en) * | 2020-07-09 | 2023-10-13 | 北京北大千方科技有限公司 | Airport passenger flow travel chain accurate sensing device containing individual characteristics |
| CN114973680A (en) * | 2022-07-01 | 2022-08-30 | 哈尔滨工业大学 | Bus passenger flow obtaining system and method based on video processing |
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| C14 | Grant of patent or utility model | ||
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| TR01 | Transfer of patent right |
Effective date of registration: 20181225 Address after: Room J145, Room 108, 1st Floor, Building 6988, Jiasong North Road, Anting Town, Jiading District, Shanghai, 201800 Patentee after: Shanghai Jingzhong Information Technology Co., Ltd. Address before: 100000 Floor 901-B905, B911, B912, No. 11 Shuguang Garden Middle Road, Haidian District, Beijing Patentee before: Beijing TrafficData Technology Co., Ltd. |
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| TR01 | Transfer of patent right |