WO2018107510A1 - 公交系统服务质量的评估方法和装置 - Google Patents

公交系统服务质量的评估方法和装置 Download PDF

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WO2018107510A1
WO2018107510A1 PCT/CN2016/110860 CN2016110860W WO2018107510A1 WO 2018107510 A1 WO2018107510 A1 WO 2018107510A1 CN 2016110860 W CN2016110860 W CN 2016110860W WO 2018107510 A1 WO2018107510 A1 WO 2018107510A1
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evaluation
data
indicators
level
public transportation
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PCT/CN2016/110860
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English (en)
French (fr)
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关金平
须成忠
关志超
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深圳先进技术研究院
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395—Quality analysis or management

Definitions

  • the present invention relates to the field of data processing, and in particular to a method and apparatus for evaluating the quality of service of a public transportation system.
  • the track public transportation service index is usually a traditional way of releasing the rail transit service index by issuing a traffic travel questionnaire to the public and summarizing the statistical analysis.
  • problems such as the length of the questionnaire survey period, the scope of the questionnaire distribution and the sampling ratio are insufficient, the questions answered by the questionnaire are not very accurate, and the real-time dynamic evaluation of the bus service cannot be performed.
  • the present invention provides a method and apparatus for evaluating the quality of service of a public transportation system, with the aim of improving the above problems.
  • the invention provides a method for evaluating service quality of a public transportation system, the method comprising: acquiring basic data of a public transportation system, and obtaining an evaluation index corresponding to a plurality of service quality according to the basic data of the public transportation system and a preset indicator evaluation model.
  • the evaluation score wherein the evaluation score of each evaluation index is used to characterize the service level of the service quality corresponding thereto.
  • the invention provides an evaluation device for the service quality of a public transportation system
  • the evaluation device for the service quality of the public transportation system comprises: a basic data acquisition module, configured to acquire basic data of the public transportation system.
  • An evaluation score obtaining module configured to obtain an evaluation score of the evaluation index corresponding to the plurality of service qualities according to the basic data of the public transportation system and the preset indicator evaluation model, wherein the evaluation score of each evaluation indicator is used to represent the corresponding evaluation score Service level of service quality.
  • the evaluation result obtaining module is configured to obtain an evaluation result of the service quality of the public transportation system according to the evaluation score of each of the plurality of evaluation indicators and the weight of the evaluation indicator.
  • the method and device for evaluating the service quality of the public transportation system obtain basic data that can be acquired and updated in real time in the public transportation system, and substitute the obtained basic data into a pre-established evaluation model to obtain multiple service quality corresponding evaluations.
  • the evaluation score of the indicator The evaluation scores of the evaluation indicators calculated by the indicator evaluation model and the weights of the corresponding indicators are used to obtain the evaluation results of the service quality of the public transportation system required.
  • the calculation of the evaluation results of the public transportation system can be carried out through the data of the electronic system collected in real time and the pre-established indicator evaluation model, which greatly improves the efficiency, accuracy, convenience and penetration rate of the service quality assessment of the public transportation system.
  • FIG. 1 is an interaction diagram of an evaluation device for a service quality of a public transportation system, a user terminal, and a data terminal according to an embodiment of the present invention
  • FIG. 2 is a block diagram of an apparatus for evaluating a service quality of a public transportation system according to an embodiment of the present invention
  • FIG. 3 is a flow chart showing the steps of a method for evaluating a service quality of a public transportation system according to a first embodiment of the present invention
  • step S301 is a flowchart of a sub-step of step S301 of the method for evaluating the quality of service of the public transportation system according to the first embodiment of the present invention
  • FIG. 5 is a flow chart showing the steps of a method for evaluating the quality of service of a public transportation system according to a second embodiment of the present invention
  • step S302 is a flowchart of sub-steps of step S302 and step S303 of the method for evaluating the quality of service of the public transportation system according to the first embodiment of the present invention
  • FIG. 7 is a block diagram of a device for evaluating a service quality of a public transportation system according to a third embodiment of the present invention.
  • the urban rail transit service production system has a certain degree of closure, and is basically isolated from other modes of transportation and services in the city during the actual production process. Therefore, for transportation companies and consumers, different feelings will be formed.
  • the technical problems to be solved by the Urban Rail Transit Service Index mainly include the following four aspects:
  • the 3 urban rail transit service production system is also a place where all passengers “share”, and the passenger experience of the rail passengers occurs in the presence of other passengers. Therefore, passengers' own behavior can also affect the passenger service experience of rail transit.
  • the urban rail transit service index is an important basis for the optimization and comprehensive evaluation of the urban public transport system. It is a comprehensive study of the existing public transport system layout, analysis of its characteristics, evaluation of its rationality, summing up its experience for the public in the future. The adjustment and optimization of the transportation system provides a scientific and rational decision-making basis.
  • the rail transit service index in the urban transportation field is usually carried out by issuing a traffic travel questionnaire to the public, summarizing the statistical analysis and sorting out the questionnaire, and releasing the track service index.
  • There are problems such as long questionnaires, high labor costs, insufficient questionnaires and sampling ratios, inaccurate questions answered by questionnaires, and inability to conduct real-time dynamic evaluation of rail transit services.
  • Entering the era of the new generation of information technology it has become possible to release the rail transit service index in real time through traffic big data. After years of research accumulation and practice, it has taken the lead in proposing “the method and system for real-time release of the rail transit service index based on traffic big data”. It is used to evaluate the quality of rail transit service in real time for public travel.
  • a method and system for real-time publishing of an orbital bus service index based on traffic big data the main purpose of which is to:
  • Urban public transportation is a general term for various economic and convenient passenger transportation modes that are provided to the public in the city, mainly including rail transit, regular public transportation, taxis, and bicycles.
  • Urban public transport is specifically defined on a designated route, providing a system of short-distance passenger services at a public rate in accordance with a fixed schedule.
  • the invention provides The evaluation method and mode for the service quality of the public transport system, especially the urban rail transit system, aims to dynamically release the urban rail transit service index in real time, so that the public can know the running status of the rail transit system before and during the trip. It is of great significance for the public to adopt the priority mode of public transportation system, and it is also an important means to alleviate traffic congestion, improve travel safety and reduce traffic pollution.
  • the quality of urban rail transit service is the perceived quality of passengers (serceiced service quality). It is actually an evaluation of passengers on rail transit services. It mainly includes: the expected service level of passengers before the consumption of transport services and the actual perceived service during the consumption process. Level. The overdue service level of passengers before consuming transportation services is affected by the transportation company, service brand image and word of mouth, passengers' individual demand characteristics and past experience. The actual perceived service level in the consumption process is the passenger's experience in the reliability, responsiveness, guarantee, empathy and tangibility of the service. The difference between the expected service level of passengers and the actual perceived service level and the relationship between them will result in different evaluations of service quality by passengers.
  • the quality of urban rail transit service reflects the passengers' requirements for urban rail transit quality services, including: before the ride, the information consultation channel is smooth, the ticket purchase is convenient, the pit stop is convenient, the waiting is comfortable; in the ride process, mainly refers to the environment. Comfortable; after arriving at the station, it mainly includes the connection of different modes of transportation, and the guiding signs are clear.
  • the quality of service includes technical quality and functional quality.
  • the quality of technology is what the passenger actually gets through the consumer service. It is the quality of the service result, that is, whether the quality standard of the service itself, environmental conditions, service items, service time, service equipment, etc. are adapted and meet the needs of the passengers.
  • Urban rail transit services must first have a comfortable waiting environment. Secondly, it is necessary to have the necessary technical equipment, such as: automatic ticket checking system, electronic station display system, connection transfer guidance system. Once again, it is necessary to meet the highest demand for passengers to “safe” the quality of service.
  • Functional quality is how passengers consume services during transportation and make the quality of the service process.
  • the service process coincides with the passenger consumption process, emphasizing what the passengers pay for consumption, including time, physical, mental, psychological and other aspects of consumption costs.
  • the service attitude, service behavior and service skills of the staff have a great influence on the quality of the function.
  • the urban rail transit service quality index is not only the unification of the technology and function of the service, but also the unification of the service process and results.
  • Safety is the mental and physical harm of passengers in the process of consuming urban rail transit services.
  • Fast it is the track bus train maintains a high running speed, saving passengers travel time, and also includes convenient and efficient service process.
  • Reliable is the ability to accurately provide according to plans and commitments in various services, such as passengers getting on and off in time, accurately entering and leaving the station.
  • the economy is to provide passengers with quality services at an economical price.
  • the invention provides a method and a model for evaluating the service quality of a public transportation system, especially an urban rail transit system, and aims to evaluate and calculate the acquired public transportation big data, and dynamically publish the urban rail transit service index in real time. Determining the purpose of the index evaluation and the reference system of the evaluation, obtaining the evaluation information, and forming the value judgment are the general processes of the index evaluation problem.
  • the specific process of the evaluation of the rail transit service index mainly includes: establishing the index evaluation object and the evaluation structure model, determining the index evaluation target and evaluation purpose, and online detection association. Information and analysis processing, determination of evaluation index system and index weight, design index evaluation method and index quantification, single index evaluation, comprehensive index evaluation and evaluation results.
  • FIG. 1 it is a schematic diagram of an interaction device (hereinafter referred to as an evaluation device) of a bus system service quality provided by an embodiment of the present invention interacting with a user terminal and a data terminal.
  • the evaluation device 100 is in communication connection with one or more user terminals and data terminals over a network for data communication or interaction.
  • the evaluation device 100 may be a network server, a database server, etc., and the evaluation device 100 may also be an integrated server system that combines a network server and a database.
  • the evaluation device 100 applied to the method and apparatus for evaluating the quality of service of the public transportation system is preferably an integrated server system, including an access interface and a database module, and the database module is responsible for classifying storage and processing of system information, the access The interface is used to implement the call between the user and the database.
  • the user terminal is configured to send the query information, the evaluation parameter, and the like input by the received user (generally the user who receives the parameter of the public transportation system evaluation and the bus system evaluation result) to the evaluation device, so that the evaluation device performs data acquisition and The result of the feedback operation.
  • the user terminal may be a personal computer (PC), a tablet computer, a smart phone, a personal digital assistant (PDA), or the like.
  • the data terminal is configured to send public transportation big data collected by the public transportation system to the evaluation device, where the data terminal is generally disposed at an operation site of the public transportation system, and an image acquisition device, a data collection device, and an electronic device at the operation site of the public transportation system. Control systems and other connections to achieve real-time access and update of public transportation big data in the public transport system.
  • the data terminal may be connected to a video collection device such as a bus station, a track hub site, etc., to obtain video information of the corresponding bus system, and then perform filtering and extraction operations of the demand information.
  • the data terminal may further include an all-in-one device or the like in a public place, and display the evaluation result of the public transportation system fed back by the evaluation device to the user for viewing, querying, and the like.
  • the evaluation device 100 includes an evaluation device for the service quality of the public transportation system (hereinafter referred to as an evaluation device), a display unit 101, a memory 102, a storage controller 103, a processor 104, a peripheral interface 105, and an input and output unit 106.
  • an evaluation device for the service quality of the public transportation system
  • a display unit 101 for the service quality of the public transportation system
  • a memory 102 for the service quality of the public transportation system
  • a storage controller 103 for the service quality of the public transportation system
  • a processor 104 for the service quality of the public transportation system
  • peripheral interface 105 As shown in FIG. 2, it is a block schematic diagram of the evaluation device 100.
  • an input and output unit 106 input and output unit 106.
  • the memory 102, the memory controller 103, the processor 104, the peripheral interface 105, the input and output unit 106, and the display unit 101 are electrically connected directly or indirectly to each other to implement data transmission or interaction.
  • the components can be electrically connected to one another via one or more communication buses or signal lines.
  • the evaluation device comprises at least one software function module that can be stored in the memory or in an operating system (OS) of the evaluation device 100 in the form of software or firmware.
  • OS operating system
  • the processor 104 is configured to execute an executable module stored in the memory 102, such as a software function module or a computer program included in the evaluation device.
  • the memory 102 can be, but not limited to, a random access memory (RAM), a read only memory (Read). Only Memory, ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Erasable Readable Memory (Electric Erasable Programmable Read) -Only Memory, EEPROM), etc.
  • the memory 102 is configured to store a program, and the processor 104 executes the program after receiving the execution instruction, and the method performed by the process-defined evaluation device 100 disclosed in any of the foregoing embodiments of the present invention may be applied to the processor. In 104, or implemented by processor 104.
  • Processor 104 may be an integrated circuit chip with signal processing capabilities.
  • the above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (Network Processor, NP for short), and the like; or a digital signal processor (DSP) or an application specific integrated circuit ( ASIC), off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component.
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • FPGA off-the-shelf programmable gate array
  • the general purpose processor 104 can be a microprocessor or the processor can be any conventional processor or the like.
  • the peripheral interface 105 couples various input/input devices to the processor 104 and the memory 102.
  • the peripheral interface, processor, and memory controller can be implemented in a single chip. In other instances, they can be implemented by separate chips.
  • the input and output unit 106 is configured to provide input data to the user to implement interaction between the user and the data collection terminal.
  • the input and output unit may be, but not limited to, a mouse, a keyboard, and the like.
  • the display unit 101 provides an interactive interface between the server and the user, such as a user interface, or for displaying image data for user reference.
  • the display unit may be a liquid crystal display or a touch display.
  • a touch display it can be a capacitive touch screen or a resistive touch screen that supports single-point and multi-touch operations. Supporting single-point and multi-touch operations means that the touch display can sense the simultaneous touch operation from one or more positions on the touch display, and the touch operation is performed by the processor. Calculation and processing.
  • FIG. 3 it is a flowchart of the steps of the evaluation method provided by the first embodiment of the present invention, and the evaluation method is applied to the above-mentioned evaluation device. The steps shown in Fig. 3 will be specifically described below.
  • Step S301 acquiring basic data of the public transportation system.
  • the evaluation process of the public transport system requires the acquisition of basic data for subsequent calculations.
  • the basic data of the public transportation system is data of a basic source obtained by filtering the collected public transportation big data and used for the index evaluation model to calculate the evaluation result.
  • the attribute content may include: a card number, a transaction date, a transaction time, a line/subway site name, an industry name (bus, subway, Rental, ferry, P+R parking lot), transaction amount, nature of the transaction (non-preferential, preferential, no discount).
  • the attribute content may include: equipment number, line code, site code, protocol No., entry and exit status, direction, vehicle reporting time, code correspondence table.
  • the attribute content may include: a device number, a line code, a station code, a protocol number, an entry and exit status, a direction, a vehicle reporting time, and a code correspondence table.
  • the attribute content may include: the track bus line network structure and the traffic geographic information data GIS-T, the first and last bus time (the city's 946 bus lines, the first and last bus times) Table, first and last bus, timetable, etc.
  • the attribute content may include: vehicle ID, GPS time, latitude and longitude, speed, number of satellites, operating state elevated state, braking state.
  • the attribute content may include: line, station, transfer station data, timetable data of each station of the first and last bus, running time data between stations, current limit station, sealing station Data, road network fare matrix, train real-time arrival time, line congestion and congestion data, exit/entry, toilet, disabled elevator data. Bus around the city track (all rail transit stations in Shenzhen, nearby bus stops, locations, names of each site).
  • the attribute content may include: traffic weather data, and its attributes include: date, time, monitoring point, weather type, temperature, wind speed, wind direction, and precipitation. The data types and attributes actually collected by the above-mentioned public transportation big data are automatically released, and the relevant features of the main data are extracted. Other data can be used for auxiliary teaching and evaluation.
  • Step S302 obtaining evaluation scores of the plurality of evaluation indicators according to the basic data of the public transportation system and the preset index evaluation model.
  • An indicator evaluation model for evaluating the bus system service quality index is preset in the evaluation device of the evaluation device.
  • the indicator evaluation model is mainly used to match the collected basic data to corresponding evaluation indicators, and obtain the evaluation scores of each evaluation index according to the numerical values of the basic data and the evaluation criteria.
  • Step S303 Acquire an evaluation result of the public transportation system according to an evaluation score of each of the plurality of evaluation indicators and a weight of the evaluation indicator.
  • the evaluation results of the required public transportation system are calculated according to the evaluation scores of each evaluation index and the weights of the evaluation indicators.
  • the evaluation indicators of the public transportation system include: comfort, convenience, economy, safety, and reliability, and the evaluation scores of the above five evaluation indicators are A1, A2, A3, A4, and A5.
  • the evaluation device After the evaluation device obtains the evaluation result of the public transportation system according to the above steps, it can be used for data result evaluation in different urban areas and different time periods. It is also possible to generate an evaluation report based on the obtained relevant evaluation results, and send the evaluation report to the user terminal where the demander is located, so as to facilitate the passengers to inquire, refer to and select, and facilitate the supervision of the public transportation situation by the government regulatory department. And control, as well as monitoring of the business conditions of the relevant public transport companies.
  • the evaluation methods provided by the embodiments of the present invention mainly include accessibility, service quality, travel time, and ride safety evaluation indicators of the rail transit network.
  • the accessibility of public transport network is the core.
  • the six-level feature extraction of passengers, vehicles, stations, lines, station groups and line networks of each bus line is dynamically released, and the urban rail transit network and single track are dynamically released in real time.
  • Bus lines, each rail transit station, the arrival time of rail transit, the speed of rail transit lines, the number of passengers in the bus, and the passenger flow information of the station evaluate the reliability and timeliness of the urban rail transit system.
  • the red, yellow and green colors of the passenger lines of the rail transit line network, the rail transit vehicles and the rail transit stations are changed in different colors.
  • Real-time dynamic rail passenger flow conditions, rail line congestion, estimated arrival time and other rail transit stations, single lines, and overall line rail transit operations improve the overall transport capacity and service quality of rail transit.
  • the evaluation method provided by the embodiment of the present invention obtains basic data that can be acquired and updated in real time in the public transportation system, and substitutes the acquired basic data into a pre-established indicator evaluation model to obtain evaluation scores of multiple evaluation indicators.
  • the evaluation scores of the evaluation indicators calculated by the indicator evaluation model and the weights of the corresponding indicators are used to obtain the evaluation results of the public transportation system required.
  • the calculation of the evaluation results of the public transportation system can be carried out through the data of the electronic system collected in real time and the pre-established indicator evaluation model, which greatly improves the efficiency, accuracy, convenience and penetration rate of the service quality assessment of the public transportation system.
  • step S301 is a flowchart of a sub-step of step S301 of the method for evaluating the quality of service of a public transportation system according to the first embodiment of the present invention, which mainly performs processing such as cleaning and screening, feature extraction, and the like by collecting public transportation big data.
  • the contents shown in FIG. 4 will be specifically described below.
  • step S401 the current public transportation big data is collected.
  • Bus transportation big data includes real-time data of public transportation systems such as rail transit IC card data, real-time data of rail transit vehicles, rail transit network data, and taxi driving data.
  • public transportation big data can be selected for clustering, and data collection is performed for different types of public transportation big data.
  • the public transportation big data After the public transportation big data is clustered, it can be mainly classified into: vehicle order data, facility supply data, and vehicle running status data. There are many ways to collect public transportation big data. For the above main types of data, it can be collected by corresponding data collection methods.
  • the riding order data included in the collected live video may be acquired by image processing. For example, through the live video collected by the image acquisition device of the bus stop, the track hub site, etc., the image processing is performed, the feature points included in the acquired video are extracted, and the bus stop is calculated according to the distribution and movement of the extracted feature points.
  • the riding order data may include: order of entering and leaving the station (channel, stairs, escalator), waiting list of the platform, order of loading and unloading, order of the car, order of entering and leaving, time of getting on and off, time of picking up, and compartment of the peak hour. Congestion and so on.
  • the facility supply data can be obtained by electronic identification sensing.
  • electronic identification sensing For example, through the electronic identification sensing system to collect security service facility signs and instructions for use, eye-catching, emergency evacuation identification clarity and accuracy, subway security facilities (quantity, speed), ticket vending machines (layout, quantity, speed), automatic ticket gates ( Layout, quantity, sensitivity), escalators (quantity, operation), transfer convenience between rail transit lines, rail transit and other bus transfer data.
  • the vehicle operating state data may also be acquired by running a control system data extraction method.
  • the operation management system may include: a navigation system, a reporting system, a driving system, etc.
  • the operation status data may include: accuracy of the navigation identification information, accuracy and timeliness of the reporting, punctuality of the train operation, and train operation. Speed, train departure interval reasonable first, last vehicle time, train running smoothly (starting, braking, acceleration), and so on.
  • ticketing data may also be obtained through a ticketing system, such as fare plausibility, ticket variety, and the like.
  • Step S402 performing feature extraction on the public transportation big data.
  • the feature extraction of the obtained public transportation big data is mainly performed on the acquired public transportation big data according to system requirements and processing algorithms.
  • FCD acquisition algorithm In the data processing process, it is mainly applied to: traffic information FCD acquisition algorithm, FCD data fusion analysis and processing, MVC-based FCD data acquisition and fusion, object-oriented design of event flow, and object-oriented collaborative diagram design of derived requirements.
  • the core algorithms involved in traffic information FCD acquisition include seven key algorithms such as raw data FCD anomaly rejection algorithm, vehicle speed calculation, fusion and prediction algorithms, and statistical algorithms for standard and historical data (flow and vehicle speed). These algorithms realize the conversion of raw data from the field to the data of the “Urban Integrated Traffic Information Platform”, which is the key to ensuring the reliability of the “information platform” and even the entire system.
  • FCD collection information according to the data collected by the external field, calculate the current section speed and comprehensively collect information to predict the speed of 5 minutes, 10 minutes, 30 minutes.
  • the vehicle speed fusion prediction process is divided into three processes: calculating the travel speed of the road segment based on the FCD data based on the FCD vehicle speed calculation model; calculating the current vehicle speed based on the data fusion model based on the flow rate, the location speed and the travel speed; predicting the vehicle speed based on the current vehicle speed based on the vehicle speed prediction model .
  • FCD data fusion The main task of FCD data fusion is to perform data level fusion on current traffic data, FCD calculation speed and location speed.
  • data fusion is mainly divided into two aspects: one is the fusion of real-time data and historical data, using linear transformation, fuzzy algorithm, calibrating different weights and membership degrees, and obtaining more accurate values; on the other hand, floating cars
  • the fusion of data and fixed-point detector data based on the respective characteristics of two different information sources, through the isomorphic data isomorphization process, the same parameters are fused, and the results with higher credibility are obtained.
  • the data is homogenized by the flow-closed relationship model.
  • FCD data collection of Shenzhen urban traffic simulation is the large-scale GPS taxi of the city's comprehensive traffic information center and the operating enterprises such as the Shenzhen Public Transport Group. It plans to provide real-time data collection of FCD dynamic traffic of more than 15,000 taxis inside and outside the SAR.
  • the interval is not less than 30 seconds, and the total number of vehicles is not less than 15,000.
  • step S403 the feature extracted data is used as the basic data.
  • the public transportation big data is collected, and after the feature extraction of the acquired public transportation big data is extracted, the finally obtained data is used as the basic data.
  • Applying the acquired basic data to the process of service quality assessment of the public transportation system greatly improves the efficiency and accuracy of basic data acquisition.
  • FIG. 5 it is a flow chart of steps of a method for evaluating service quality of a public transportation system according to a second embodiment of the present invention.
  • the embodiment of the present invention further adds an establishment process of the evaluation model. The process of establishing the evaluation model added in the embodiment of the present invention will be specifically explained below.
  • step S501 the data types of all the data of the basic data are used as the three-level evaluation index.
  • Step S502 classifying all the three-level evaluation indicators according to the categories of all the three-level evaluation indicators and the preset second-level evaluation indicators, so that each of the three-level evaluation indicators corresponds to a category-level second-level evaluation index. .
  • Step S503 obtaining a second-level evaluation index corresponding to each of the three-level evaluation indicators and a first weight of the three-level evaluation index.
  • the establishment of an evaluation model for the quality of the public transport system requires the identification of an evaluation indicator system.
  • the evaluation index system of the service quality of the public transport system is a multi-indicator structure. Using the hierarchical structure to set the evaluation indicators, the connotation of the evaluation index system for passenger satisfaction can be expressed in a clear and in-depth manner. Each level of evaluation indicators is developed by the previous level of evaluation indicators, while the previous level of evaluation indicators are reflected by the evaluation results of the next level of evaluation indicators.
  • the establishment of passenger service quality assessment index system must follow the systemic principle, the principle that passengers are God, the principle of simplicity and simplification, the principle of operability, and the principle of timeliness of public transportation big data.
  • the SERVQUAL Service Quality
  • the pedestrian crossing method and the key event technology evaluation method are used to obtain the evaluation index system of the rail transit service quality.
  • the SERVQUAL The algorithm is the service quality evaluation system.
  • the theoretical core is the “service quality gap model”. The quality of service depends on the degree of difference between the service level perceived by the user and the service level expected by the user. Walking through the hair is a diagnostic tool used primarily to diagnose associations: personal-to-individual services; service delays; environmental variables; billing; promotional and suggestive sales.
  • Key event technology evaluation is a work analysis technical method used to identify key factors in job performance in various work environments.
  • the perceived quality is defined as the primary evaluation indicator to indicate the total service quality of the public transportation system.
  • Safety, reliability, economy, convenience, and comfort are defined as secondary evaluation indicators to characterize the quality assessment of the user's main perception direction of the public transportation system.
  • the evaluation index system will be formed and a number of three-level evaluation indicators will be established.
  • the three-level evaluation index includes a first measured indicator and a first theoretical indicator, and the first measured indicator is data that can be directly measured from an electronic system of a public transportation system by means of data acquisition or image acquisition.
  • the first theoretical indicator is an evaluation index that can be calculated by actually measuring the data and a theoretical calculation formula.
  • the secondary assessment indicator comprises at least one of safety, reliability, economy, convenience, and comfort.
  • the first measured index mainly corresponds to 10 parts: train passenger service; station train safety guarantee, rail transit information service, train car capacity, station time consumption, station waiting time, station train congestion, Station transfer service, station train facility support, passenger station train satisfaction evaluation.
  • the above 10 parts are classified into 32 more specific first measured indicators, including: order of entering and leaving the station, order waiting for the platform, order of getting on and off, order of the car, identification of the service facilities and instructions for use, eye-catching, emergency evacuation identification and accuracy. , subway security inspection facilities, automatic ticket vending machines, automatic ticket gates, escalators, guide sign information accuracy, station accuracy and timeliness, train operation punctuality rate, fare reasonableness, fare diversity, entry and exit time, Ticket purchase time, boarding time, train running speed, train departure interval reasonable first and last car time, transfer convenience between rail transit lines, convenience of transfer between rail transit and other buses, peak congestion, train operation At least one of smoothness, channel cleanliness, cabin environment cleanliness, station noise decibel, air temperature and humidity suitability, air circulation, staff response rate to passenger requirements, and convenience facility penetration rate.
  • the first measured indicators mentioned above can be directly obtained or extracted from the corresponding electronic system.
  • the first theoretical indicators of the three-level evaluation index include: a punctuality rate, a train running map redemption rate, a train congestion degree, a ticket vending machine reliability, a savings card recharge machine reliability, and a savings card refilling machine. Reliability, reliability of entrance and exit gates, reliability of escalators, reliability of vertical elevators, reliability of station passenger information systems, reliability of train passenger information systems, reliability of train passenger information, reliability of train services, complaints from valid passengers, and At least one of the effective passenger complaint recovery rates.
  • the first theoretical indicator mentioned above needs to calculate the theoretical value of the public transportation big data in the original state directly obtained. The specific calculation process of the above first theoretical index will be explained below.
  • the punctuality rate refers to the ratio of the number of on-time trains to the number of trains in total. It is used to indicate the degree of operation of the trains on time according to the specified time. Calculated as follows: According to the time specified in the operation chart, the trains that do not exceed the specified time limit in the morning and evening are the quasi-point trains.
  • the time limit of the punctual points refers to the trains with the key arrival time error of less than or equal to 2 minutes (except for the municipal rapid transit bus system);
  • the time limit of the on-track bus system on time is defined as the train whose terminal arrival time error is less than or equal to 3 minutes.
  • the train operation map redemption rate refers to the ratio of the actual number of trains running and the number of trains to be operated.
  • the actual number of trains does not include the number of trains temporarily opened. Its calculation method is as follows:
  • Train congestion degree refers to the ratio of the average hourly passenger traffic volume of the rail transit line to the actual transport capacity of the line.
  • the train is calculated according to the quota to indicate the congestion degree of the train. The calculation method is as follows:
  • the actual transportation capacity of the line the train capacity ⁇ the peak hour hour traffic volume.
  • Ticket machine reliability refers to the ratio of the actual service time of the ticket vending machine to the service time of the ticket vending machine.
  • the actual service time includes the normal ticketing and Canadian dollar time. The calculation method is as follows:
  • the reliability of the stored value card recharge machine refers to the ratio of the actual service time of the stored value card recharge machine to the service time.
  • the actual service time includes the normal ticketing and Canadian dollar time. Its calculation method is as follows:
  • the reliability of the entrance and exit gates refers to the ratio of the actual service time of the entry and exit gates to the service time.
  • the calculation method of the reliability of the entrance and exit gates is as follows:
  • Escalator reliability refers to the ratio of the actual service time of the escalator to the service time. The calculation method is as follows:
  • Vertical elevator reliability refers to the ratio of the actual service time of the vertical elevator to the service time. The calculation method is as follows:
  • Station passenger information system reliability refers to the ratio of the actual service time of the station passenger information system to the service time.
  • the calculation method of the station passenger information system reliability is as follows:
  • the reliability of the train passenger information system refers to the ratio of the actual service time of the train passenger information system to the service time.
  • the calculation method of the reliability of the train passenger information system is as follows:
  • Train service reliability refers to the train that runs between 5min and 15min within one year. The average number of kilometers traveled by the train, the larger the value, the higher the reliability.
  • the effective passenger complaint rate refers to the ratio of the number of valid passenger complaints to the city passenger traffic.
  • the calculation method is as follows:
  • Effective passenger complaint response rate refers to the ratio of the number of valid passenger complaints that have been replied to the number of valid passenger complaints.
  • the effective passenger complaint response rate is calculated as follows:
  • Step S404 obtaining a second weight of each of the secondary evaluation indicators.
  • Step S405 establishing, according to each of the three-level evaluation index and its first weight, each of the second-level evaluation indicators and the second weight thereof, and the corresponding relationship between the three-level evaluation index and the second-level evaluation index.
  • the indicator evaluation model establishing, according to each of the three-level evaluation index and its first weight, each of the second-level evaluation indicators and the second weight thereof, and the corresponding relationship between the three-level evaluation index and the second-level evaluation index.
  • a three-level evaluation index corresponding to each data in the basic data according to the impact degree of each three-level evaluation index under each of the second-level evaluation indicators according to the service quality evaluation of the public transportation system
  • the weight of each of the three-level evaluation indicators in the corresponding second-level evaluation indicators is determined, and is set as the first weight.
  • the weight of each of the secondary assessment indicators in the primary assessment indicators is determined according to the degree of influence of each secondary assessment indicator under the primary assessment indicator, and is set to the second weight.
  • each secondary assessment indicator and its second weight under the primary assessment indicator, and the primary assessment indicator category under each of the secondary assessment indicators, and each of the primary assessment indicators in its corresponding The first weight in the evaluation index is used to establish the indicator evaluation model.
  • each data in the obtained basic data can be directly matched to the corresponding three-level evaluation index, and according to the corresponding two-level evaluation index
  • the evaluation index corresponding to the first evaluation index and the first weight calculation level, and then the calculation of the final evaluation result based on the obtained evaluation score and the second weight of the secondary evaluation index greatly improving the public transportation system service.
  • the efficiency, accuracy and timeliness of quality assessments improve user experience.
  • FIG. 6 is a flowchart of sub-steps of step S301 and step S302 of the evaluation method according to the first embodiment of the present invention. Based on the indicator model established in the above embodiment, the acquisition operation of the evaluation result is performed. The steps shown in Fig. 6 will be specifically explained below.
  • Step S601 Acquire a target three-level evaluation index corresponding to a data type of each data of the collected basic data.
  • the obtained public transportation big data is filtered and used as the basic data for evaluation calculation. According to the data type of the currently obtained basic data, the target three-level evaluation index corresponding to the data is searched.
  • the target three-level evaluation index corresponding to the data is the cabin order.
  • Step S602 Acquire a first evaluation score according to the first weight of the target three-level evaluation index corresponding to the value of each of the data and the data type of the data.
  • the value of the acquired data and the first weight of the target three-level evaluation index corresponding to the data are calculated.
  • the evaluation score obtained from the data is the first evaluation score of the target three-level evaluation index.
  • Step S603 obtaining a second evaluation score according to the first evaluation score of each of the target three-level evaluation indicators and the second weight of the target secondary evaluation index corresponding to the target three-level evaluation index.
  • each of the secondary evaluation indicators is calculated. Firstly, according to the correspondence between the three-level evaluation index and the second-level evaluation index, the target secondary evaluation index corresponding to each target three-level evaluation index is obtained, and all three-level evaluation indicators under the target secondary evaluation index are obtained. First evaluation score. Calculating a second evaluation score of the second-level target evaluation index according to the second weight of each of the second-level evaluation indicators and the first evaluation score of each of the three-level evaluation indicators under the second-level evaluation index.
  • Step S604 obtaining an evaluation result of the public transportation system according to a second evaluation score of all the secondary evaluation indicators.
  • the evaluation method provided by the embodiment of the present invention when evaluating the service quality of the public transportation system, uses the public transportation big data that can be directly, real-time, and automatically obtained as the basic data of the result calculation, and substitutes the basic data into the preset indicator.
  • the matching of the evaluation indicators of each level and the calculation of the evaluation scores are automatically completed, and the evaluation of the service quality of the public transportation system is realized quickly and accurately.
  • FIG. 7 is a functional block diagram of an evaluation apparatus 700 according to a third embodiment of the present invention.
  • the evaluation device 700 includes a basic data acquisition module 701, an evaluation score acquisition module 702, and an evaluation result acquisition module 703.
  • the basic data obtaining module 701 is configured to acquire basic data of the public transportation system.
  • the evaluation score obtaining module 702 is configured to obtain the evaluation scores of the plurality of evaluation indicators according to the basic data of the public transportation system and the preset indicator evaluation model.
  • the evaluation result obtaining module 703 is configured to obtain an evaluation result of the public transportation system according to an evaluation score of each of the plurality of evaluation indicators and a weight of the evaluation indicator.
  • the evaluation apparatus 700 further includes an indicator evaluation model establishing module 704, and the indicator evaluation model establishing module 704 is configured to:
  • the data type of all the data of the basic data is used as a three-level evaluation index
  • All the three-level evaluation indicators are classified according to the categories of all the three-level evaluation indicators and the preset second-level evaluation indicators, so that each of the three-level evaluation indicators corresponds to a category of secondary evaluation indicators;
  • each of the second-level evaluation indicators and their second weights corresponds to each of the three-level evaluation indicators and their first weights.
  • the evaluation score obtaining module 702 is specifically configured to:
  • the first evaluation score is obtained according to the first weight of the target three-level evaluation index corresponding to the value of each of the data and the data type of the data.
  • the evaluation result obtaining module 703 is specifically configured to:
  • the evaluation result of the public transportation system is obtained according to the second evaluation score of all the secondary evaluation indicators.
  • the evaluation device provided by the embodiment of the present invention obtains the basic data that can be acquired and updated in real time in the public transportation system, and substitutes the acquired basic data into the pre-established index evaluation model to obtain the evaluation scores of the plurality of evaluation indicators.
  • the evaluation scores of the evaluation indicators calculated by the indicator evaluation model and the weights of the corresponding indicators are used to obtain the evaluation results of the public transportation system required.
  • the calculation of the evaluation results of the public transportation system can be carried out through the data of the electronic system collected in real time and the pre-established indicator evaluation model, which greatly improves the efficiency, accuracy, convenience and penetration rate of the service quality assessment of the public transportation system.
  • the development process of the evaluation model and the physical system carried by the embodiment of the present invention mainly includes: data collection, cleaning, mining, summary rules and algorithms, overall realization of function and technical indicators, real-time release of rail transit service index development, Urban rail transit service index assessment application and other processes.
  • Data analysis includes: establishing data collection rules, data cleaning rules, data mining rules, and data aggregation rules.
  • the data analysis design includes: based on FCD, establishes the bus travel data analysis mining process and model algorithm supported by the road network.
  • the data analysis design includes: establishing a data analysis mining process and model algorithm for the transit bus IC card travel.
  • the data analysis design includes: establishing data analysis mining process and model algorithm for regular bus travel.
  • Data analysis design includes: establishing data analysis mining process and model algorithm for taxi trips.
  • Sixth establish database search engines such as tracks, buses, rentals, and IC cards. Data analysis design: build track, Database search engine and database development design for bus, rental, IC card, etc.
  • Seventh establish a database group analysis and mining environment interface, data analysis design: establish a database group analysis and mining environment interface.
  • the dimension design is: urban rail, bus, rental bus integrated service query platform - dimension design.
  • the functional design is the functional design of the urban rail transit service inquiry platform--functional design and rail transit system, and the rental bus integrated service inquiry platform.
  • the special analysis design is the urban rail, bus, and bus rental service inquiry platform--special analysis design, development of the rail transit system GIS-T query interface, and time-space modeling of the query results.
  • the process of passenger satisfaction evaluation of the public transportation system can also be added.
  • the specific process of passenger satisfaction assessment of the public transport system may include: the specific steps of the passenger satisfaction evaluation of the railway bus are as follows: determine the passenger satisfaction degree evaluation structure model, establish a satisfaction degree evaluation index system, determine the weight of the evaluation index, and quantify the evaluation index Public transportation big data correlation detection, generating public transportation big data detection results, and obtaining passenger satisfaction evaluation.
  • the process of passenger level assessment can be found in the above evaluation process of service quality, and will not be described again.
  • the public transportation big data releases the distribution of the rail transit service index in real time
  • the real-time release system of the rail transit service index based on the Rational Rose Real Time modeling environment is used as an integrated application structure of the urban “traffic simulation and traffic public information platform”.
  • the system mainly provides 8 functional components for 3 types of users (public citizens, government related departments, transportation technicians), realizes 60 function points, and can carry out more than 5,000 combined query rail transit service index real-time release system construction core projects.
  • Mainly by "one network, four platforms" (the one network refers to the traffic information communication and transmission network, the four platforms refer to: traffic information collection platform, traffic public information platform and traffic simulation platform and traffic information service platform ) constitutes.
  • the real-time release system of the rail transit service index mainly reflects the information of the actual use of the rail transit flow of the rail transit network supported by the urban rail network (for example, setting a period of 3 minutes), mainly including information on traffic flow and rail network work. Status information, information on traffic incidents, etc.
  • Traffic flow information includes traffic flow, orbital congestion, etc., where the congestion degree index can be quantified (traffic congestion index), and ten levels can be set to reflect the different degrees of smooth, crowded, and blocked urban rail transit, respectively, marked with green and yellow. , red three color expression.
  • the track network working status information mainly reflects the current congestion degree of the urban skeleton bus network, including congestion area, congestion status, congestion duration, congestion change trend, formation of congestion, congestion and so on.
  • the traffic incident information mainly reflects the current traffic behavior events in the urban rail network, including traffic accidents, traffic control, traffic monitoring, and traffic congestion.
  • the real-time release system data of the rail transit service index should be simple and practical, and it is as convenient as possible to update and query data, thus improving data efficiency.
  • the data items mainly include content: number, line name, date, time, direction, traffic flow, traffic speed, congestion, road status, traffic events, etc.
  • the real-time release system of the rail transit service index presents different characteristics from the traditional non-real-time dynamic system and requires good methods, tools and language support.
  • the real-time publishing system of the rail transit service index, the real-time dynamic unified unified modeling language, the unified development process of the real-time dynamic traffic information release system and the Rational Rose Real Time modeling environment are organically combined to carry out system requirements analysis and use case modeling. Interdisciplinary applications of advanced software technologies for static and dynamic modeling, implementation and deployment in traffic information engineering.
  • the rail transit public information platform is responsible for data fusion, data dictionary, data mining-based decision support, data services and data maintenance.
  • Traffic data statistics query is a sub-function of data services.
  • the functions of the rail transit public information platform are organized in a data fusion use case package, a data mining based decision support use case package, a traffic data statistical query use case package, and a data maintenance use case package.
  • the traffic simulation platform performs strategic level simulation analysis and project level simulation analysis through intelligent simulation components. Since the intelligent simulation component has its environment configuration data, it is necessary to calibrate the relevant parameters. In addition, for a software integration product, maintenance functions are essential, and the maintenance function of the platform needs to be added. Therefore, the functions can be divided into four parts: strategic level simulation analysis, project level simulation analysis, intelligent simulation component maintenance and simulation platform maintenance. Based on the above analysis, the traffic simulation function is corresponding to the needs of the traffic simulation platform, and organized into a strategic level simulation analysis use case package, a project-level simulation analysis use case package, an intelligent simulation component maintenance use case package, and a simulation platform maintenance use case package.
  • the traffic information service platform will transmit and process the traffic operation status data and simulation calculation results in real time to the user in an appropriate form with accuracy and timelyness, and realize dynamic and static traffic information release in all weather, multi-mode and multi-layer.
  • maintenance functions are essential, and the maintenance function of the platform needs to be added. Therefore, the functions can be divided into two parts: information publishing service and information management service. Based on the above analysis, the information service functions are organized in the information release service use case package and the information management service use case package.
  • interaction diagrams The sequence diagram and collaboration diagram published by the real-time release system of the Orbital Bus Service Index are collectively called interaction diagrams, which are used to analyze the dynamic interaction and message transfer between objects in the system use case realization, help identify classes, responsibilities, and assign responsibilities among collaborators. Also used to identify interfaces and abstract classes.
  • the real-time release system software of the rail transit service index needs to be deployed on the corresponding hardware, and must also provide the corresponding operating environment to operate normally.
  • the system involves more software and hardware environments, which can be divided into five deployment areas: data collection area, external User area, DMZ isolation area, internal service area, internal user area.
  • the interconnection between the various areas is through the wireless network, the Internet and the local area network; the Internet interconnection between the Internet and the local area network is implemented by using a router; to ensure the security and efficiency of the entire system network, the firewall is used to isolate the Internet and the local area network, and the switch is used between the firewall and the local area network. Connection, use the gatekeeper to achieve physical isolation between the internal user area and the internal service area, and use the network management to manage the network equipment of the entire system.

Abstract

一种公交系统服务质量的评估方法和装置，应用于数据处理领域。所述评估方法中，通过获取公交系统内可实时获取和更新的基础数据，将所获取的基础数据代入到预先建立的指标评估模型，获取多个评估指标的评价分数。将指标评估模型计算所得的评估指标的评价分数和相应评估指标的权重获取所述公交系统的服务质量的评估结果。所述评估方法可以通过实时采集的电子系统的数据和预先建立的指标评估模型进行公交系统的评估结果的计算，极大程度地提高了公交系统服务质量评估的效率、准确度、便捷度和普及率。

Description

公交系统服务质量的评估方法和装置 技术领域
本发明涉及数据处理领域，具体而言，涉及公交系统服务质量的评估方法和装置。
背景技术
当前，城市交通拥堵、安全、污染是全世界城市发展的重点、难点问题，需要我们高度关注并予以解决。缓解城市交通拥堵、保障交通出行安全、减少交通污染排放等问题，必须优先发展公交出行方式。2005年，中国颁布了《国务院办公厅转发建设部等部门关于优先发展城市公共交通意见的通知》，把优先发展公共交通定为交通发展的战略方针。
当前城市交通领域中轨道公共交通服务指数通常是通过向市民发放交通出行问卷、归纳统计分析整理问卷后，来发布轨道交通服务指数方式进行的传统方式。上述方式存在发放问卷调查周期长、问卷发放范围与取样比例不足、问卷回答的问题不十分准确度、不能进行实时动态对公交服务进行评价等问题。
发明内容
本发明提供公交系统服务质量的评估方法和装置，旨在改善上述问题。
本发明提供的一种公交系统服务质量的评估方法，所述方法包括：获取公交系统的基础数据，根据所述公交系统的基础数据和预设的指标评估模型获取多项服务质量对应的评估指标的评价分数，其中，每个评估指标的评价分数用于表征与其对应的服务质量的服务水平。根据所述多个评估指标中的每个评估指标的评价分数和该评估指标的权重获取所述公交系统服务质量的评估结果。
本发明提供的一种公交系统服务质量的评估装置，所述公交系统服务质量的评估装置包括：基础数据获取模块，用于获取公交系统的基础数据。评价分数获取模块，用于根据所述公交系统的基础数据和预设的指标评估模型获取多项服务质量对应的评估指标的评价分数，其中，每个评估指标的评价分数用于表征与其对应的服务质量的服务水平。评估结果获取模块，用于根据所述多个评估指标中的每个评估指标的评价分数和该评估指标的权重获取所述公交系统服务质量的评估结果。
上述本发明提供的公交系统服务质量的评估方法和装置，获取公交系统内可实时获取和更新的基础数据，将所获取的基础数据代入到预先建立的指标评估模型获取多项服务质量对应的评估指标的评价分数。将指标评估模型计算所得的评估指标的评价分数和相应指标的权重获取所需要的公交系统服务质量的评估结果。可以通过实时采集的电子系统的数据和预先建立的指标评估模型进行公交系统的评估结果的计算，极大程度地提高了公交系统服务质量评估的效率、准确度和便捷度和普及率。
附图说明
为了更清楚地说明本发明实施例的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，应当理解，以下附图仅示出了本发明的某些实施例，因此不应被看作是对范围的限定，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他相关的附图。
图1是本发明实施例提供的公交系统服务质量的评估设备与用户终端和数据终端的交互图；
图2是本发明实施例提供的公交系统服务质量的评估设备的方框图；
图3是本发明第一实施例提供的公交系统服务质量的评估方法的步骤流程图；
图4是本发明第一实施例提供的公交系统服务质量的评估方法的步骤S301的子步骤流程图；
图5是本发明第二实施例提供的公交系统服务质量的评估方法的步骤流程图；
图6是本发明第一实施例提供的公交系统服务质量的评估方法的步骤S302和步骤S303的子步骤流程图；
图7是本发明第三实施例提供的公交系统服务质量的评估装置的模块框图。
具体实施方式
进入新型城镇化建设发展时期，随着城市化进程的不断加快和城市机动化出行的迅猛发展，城市道路需求迅速增长，交通拥堵、安全、污染问题日益突出，并成为社会经济发展的瓶颈问题。从供给侧实现结构性改革，轨道交通作为城市公共交通的骨架，是保证城市公交生产、生活正常运转的出行核心大动脉，是提高城市综合功能的重要基础设施，它对城市产业的影响，经济、社会、文化事业的繁荣、城际与城乡间联系起着重要纽带和促进作用。通过城市轨道交通系统的服务质量评价，可以清楚地认识到轨道公交服务现状和社会需求的差距，以便调整公交体系产业结构，进一步提高新型城镇化建设与发展的品质。
城市轨道交通服务生产系统具有一定的封闭性，在实际生产过程中基本与城市内其他交通方式和服务相对隔离。因此，对于运输企业和消费者来讲会形成不同的感觉，城市轨道公交服务指数要解决的技术问题主要包括以下四个方面：
①从运输企业的角度来看，城市轨道交通服务生产系统具有涉及部门多、生产环节多、技术性强等特征，以及生产环节的连续性和流畅性要求。
②从消费者的角度来看，乘客在进入轨道交通运输服务生产系统、参与消费的过程中，直接影响其服务感受的有可见因素和不可见因素内容；可见因素是展示在乘客面前的，包括轨道周围环境、服务人员，以及其他乘客；不可见因素是由于轨道交通不可见的组织和系统组成的。
③城市轨道交通服务生产系统也是所有乘客“共享”的场所，轨道乘客对服务的感受是在其他乘客在场情况下发生的。因此，乘客自身的行为表现也可以影响轨道交通的其他乘客服务感受。
④城市轨道交通服务不可见因素是乘客看不见的运输组织过程和相关的系统，这些组织过程和系统反映了轨道交通服务的规则、规范、运输组织的流程等，尽管它们对乘客来说输不可见的，但其运作和执行的效果对乘客的服务感受具有深远的影响。
总之，城市轨道公交服务指数是城市公共交通系统骨架优化与综合评价的重要依据，是对现有公共交通系统布局进行综合研究、分析其特点、评价其布局合理性，总结其经验，为今后公共交通系统的调整优化提供科学合理的决策依据。
长期以来，城市交通领域中轨道交通服务指数通常是通过向市民发放交通出行问卷、归纳统计分析整理问卷后，来发布轨道服务指数方式进行的。存在着发放问卷调查周期长、耗费人力成本大、问卷发放范围与取样比例不足、问卷回答的问题不够准确、不能进行实时动态对轨道公交服务进行评价等问题。进入新一代信息技术时代，通过交通大数据实时发布轨道公交服务指数成为了可能，经过多年的研究积累与实践，在国内外率先提出“基于交通大数据实时发布轨道公交服务指数方法与系统”，用以面向公众出行实时动态对轨道公交服务质量进行评价。
构建基于交通大数据实时发布轨道公交服务指数的方法与系统，其主要目的在于：
①面向城市，构建较完善的、时效性强的城市轨道公交服务水平的评价指标体系，成为编制城市公交规划的重要依据，成为展示城市公交运输血脉的高品质服务窗口；
②面向政府，形成政府部门为轨道公交企业制订运营任务和目标的工具，有效地实现政府对公交运输行业监管的重要手段；
③面向行业、企业，开展公众选择公交方式出行行为决策研究，进行交通行为离散选择等分析研判，特别是新型城镇化建设和发展时期，完善涉及到行业、企业服务水平指标等级的划分与确定，为加速公交都市建设和城市轨道公交系统的健康发展服务，提高公众出行对轨道主体公交服务需求得到有效的监督和满足；
④面向公众，为公众市民出行对城市轨道公交系统服务进行监督和评价的标准，建立健全公众市民参与的公交运输服务量化、实时监督评价新模式。
城市公共交通是城市中提供给公众使用的经济型、方便型的各种客运交通方式的总称，主要包括轨道交通、常规公交、出租车、自行车慢行等。城市公共交通具体定义在指定的路线上，按照固定的时刻表，以公开的费率为城市公众提供短途客运服务的系统。
在进行城市大交通发展模式构建时，选择以轨道交通为骨架、以常规公交为主体、以出租车为辅助、以自行车为延伸的优先发展公共交通的战略方针。本发明提 供的针对公交系统，尤其是城市轨道交通系统的服务质量的评估方法和模式，旨在实时动态发布城市轨道公交服务指数，能够让公众出行前、出行途中随时了解轨道公交系统运行状态，对于引导公众采用公交系统优先出行方式具有重要意义，也是缓解交通拥堵、提高出行安全、降低交通污染的重要手段。
城市轨道公交服务质量是乘客感知的质量(serceiced service quality)，实际上也是乘客对轨道公交服务的一种评价，主要包括：乘客在消费运输服务前的预期服务水平和消费过程中的实际感知服务水平。乘客在消费运输服务前的逾期服务水平受运输企业、服务品牌形象和口碑、乘客个人需求特征和过去经历的影响。消费过程中的实际感知服务水平是乘客在服务的可靠性、响应性、保证性、移情性和有形性等方面的感受。乘客的预期服务水平和实际感知服务水平的高低及相互关系的不同，会导致乘客对服务质量评价程度不同。
城市轨道公交服务质量内容反映乘客对城市轨道公交优质服务的要求，主要包括：在乘车前，信息咨询渠道畅通，购票便捷、进站方便、候车舒适；在乘车过程中，主要指环境舒适；到站后，主要包括不同交通方式的衔接、导向指引标志明确等。通常服务质量包括技术质量和功能质量。
技术质量是乘客通过消费服务实际得到了什么，是服务结果的质量，即服务本身的质量标准、环境条件、服务项目、服务时间、服务设备等是否适应和满足乘客的需要。城市轨道公交服务，首先要有舒适的候车环境。其次，要有必要的技术装备，如：自动售票检票系统、电子站牌显示系统、接驳换乘出入口指引系统等。再次，要满足乘客对服务质量“安全”的最高需求。
功能质量，是乘客如何在运输过程中消费服务，使服务过程的质量。服务过程与乘客消费过程同时发生，强调乘客为消费付出了什么，包括时间、体力、精神、心理等各方面的消费成本。工作人员的服务态度、服务行为、服务技巧等对功能质量影响较大。城市轨道公交服务质量指数既是服务的技术和功能的统一，也是服务的过程和结果的统一。
基于上述公交服务分析，轨道公交服务的技术质量主要体现在安全、快速、可靠、经济四个方面。安全，是乘客在消费城市轨道公交服务过程中，自身的精神和身体不受到伤害。快速，是轨道公交列车保持较高的运行速度，为乘客节省出行时间，同时也包括便捷高效的服务过程。可靠，是在各项服务中按计划和承诺准确提供的能力，如乘客及时上、下车，准确进、出站。经济，是以经济的价格，使乘客获得优质的服务。
本发明提供的针对公交系统，尤其是城市轨道交通系统的服务质量的评估方法和模式，旨在将所获取的公共交通大数据，进行评估计算，以实时动态发布城市轨道公交服务指数。确定指数评价的目的和评价的参考系统、获取评价信息、形成价值判断，是指数评价问题的一般过程。轨道公交服务指数评价的具体流程主要包括：确立指数评价对象与评价结构模型、确定指数评价目标与评价目的、在线检测关联 信息与分析处理、确定评价指标体系与指标权重、设计指数评价方法与指标量化、单项指数评价、综合指数评价和评估结果研判。下面将对本发明所提供的公交系统服务质量的评估方法和装置进行具体描述。
如图1所示，是本发明实施例提供的公交系统服务质量的评估设备(以下简称评估设备)与用户终端和数据终端进行交互的示意图。所述评估设备100通过网络与一个或多个用户终端和数据终端进行通信连接，以进行数据通信或交互。所述评估设备100可以是网络服务器、数据库服务器等，所述评估设备100也可以是结合了网络服务器和数据库的集成式服务器系统。本实施例提供的公交系统服务质量的评估方法和装置所应用的评估设备100优选为集成式服务器系统，包括访问接口和数据库模块，所述数据库模块负责系统信息的分类存储和处理，所述访问接口用于实现用户与数据库之间的调用。
所述用户终端用于将所接收的用户(一般是参数公交系统评估和公交系统评估结果接收的用户)输入的查询信息和评价参数等发送至评估设备，以使所述评估设备进行数据获取和结果反馈的操作。所述用户终端可以是个人电脑(personal computer，PC)、平板电脑、智能手机、个人数字助理(personal digital assistant，PDA)等。
所述数据终端用于将公交系统采集的公共交通大数据发送至所述评估设备，所述数据终端一般设置于公交系统的运行现场，与公交系统运行现场的图像采集装置、数据采集装置和电子管控系统等连接，实现公交系统的公共交通大数据的实时获取和更新等。例如，所述数据终端可以为与公交车站点、轨道枢纽站点等的视频采集装置连接，获取相应公交系统的视频信息，进而进行需求信息的过滤和提取操作。所述数据终端还可以包括公共场合的一体机设备等，用于将所述评估设备反馈的公交系统的评估结果显示给用户查看和查询等。
如图2所示，是所述评估设备100的方框示意图。所述评估设备100包括公交系统服务质量的评估装置(以下简称评估装置)、显示单元101、存储器102、存储控制器103、处理器104、外设接口105、输入输出单元106。
所述存储器102、存储控制器103、处理器104、外设接口105、输入输出单元106、显示单元101，各元件相互之间直接或间接地电性连接，以实现数据的传输或交互。例如，这些元件相互之间可通过一条或多条通讯总线或信号线实现电性连接。所述评估装置包括至少一个可以软件或固件(firmware)的形式存储于所述存储器中或固化在所述评估设备100的操作系统(operating system，OS)中的软件功能模块。
所述处理器104用于执行存储器102中存储的可执行模块，例如所述评估装置包括的软件功能模块或计算机程序。其中，存储器102可以是，但不限于，随机存取存储器(Random Access Memory，RAM)，只读存储器(Read  Only Memory，ROM)，可编程只读存储器(Programmable Read-Only Memory，PROM)，可擦除只读存储器(Erasable Programmable Read-Only Memory，EPROM)，电可擦除只读存储器(Electric Erasable Programmable Read-Only Memory，EEPROM)等。其中，存储器102用于存储程序，所述处理器104在接收到执行指令后，执行所述程序，前述本发明任一实施例揭示的过程定义的评估设备100所执行的方法可以应用于处理器104中，或者由处理器104实现。
处理器104可能是一种集成电路芯片，具有信号的处理能力。上述的处理器可以是通用处理器，包括中央处理器(Central Processing Unit，简称CPU)、网络处理器(Network Processor，简称NP)等；还可以是数字信号处理器(DSP)、专用集成电路(ASIC)、现成可编程门阵列(FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件。可以实现或者执行本发明实施例中的公开的各方法、步骤及逻辑框图。通用处理器104可以是微处理器或者该处理器也可以是任何常规的处理器等。
所述外设接口105将各种输入/输入装置耦合至处理器104以及存储器102。在一些实施例中，外设接口，处理器以及存储控制器可以在单个芯片中实现。在其他一些实例中，他们可以分别由独立的芯片实现。
输入输出单元106用于提供给用户输入数据实现用户与数据采集终端的交互。所述输入输出单元可以是，但不限于，鼠标和键盘等。
显示单元101在所述服务器与用户之间提供一个交互界面，例如用户操作界面，或用于显示图像数据给用户参考。在本实施例中，所述显示单元可以是液晶显示器或触控显示器。若为触控显示器，其可为支持单点和多点触控操作的电容式触控屏或电阻式触控屏等。支持单点和多点触控操作是指触控显示器能感应到来自该触控显示器上一个或多个位置处同时产生的触控操作，并将该感应到的触控操作交由处理器进行计算和处理。
请参见图3，是本发明第一实施例提供的评估方法的步骤流程图，所述评估方法应用于上述的评估设备。下面将对图3所示的步骤进行具体描述。
步骤S301，获取公交系统的基础数据。
公交系统的评估过程需要先获取基础数据，以进行后续的计算。所述公交系统的基础数据，为所采集的公共交通大数据进行过滤处理后所获取的用于指标评估模型进行评估结果计算的基础来源的数据。
在一种实施方式中，如果所述公共交通大数据是指轨道公交IC卡数据，则其属性内容可以包含：卡号、交易日期、交易时间、线路/地铁站点名称、行业名称(公交、地铁、出租、轮渡、P+R停车场)、交易金额、交易性质(非优惠、优惠、无优惠)。如果所述公共交通大数据是指轨道公交车辆实时数据，则其属性内容可以包含：设备号码，线路编码，站点编码，协议编 号，进出站状态，方向，车载上报时间、编码对应表。如果所述公共交通大数据是指轨道公交车辆实时数据，则其属性内容可以包含：设备号码，线路编码，站点编码，协议编号，进出站状态，方向，车载上报时间、编码对应表。如果所述公共交通大数据是指轨道公交线网数据，则其属性内容可以包含：轨道公交线路网络结构与交通地理信息数据GIS-T，首末班车时间(全市946条公交线路、上行首末班车时刻表、下行首末班车、时刻表)等。如果所述公共交通大数据是指出租车行车数据，则其属性内容可以包含：车辆ID、GPS时间、经纬度、速度、卫星颗数、营运状态高架状态、制动状态。如果所述公共交通大数据是指轨道交通运行数据，则其属性内容可以包含：线路、车站、换乘站数据、首末班车各站时刻表数据、站间运行时间数据、限流车站、封站数据、路网票价矩阵、列车实时到发站台时刻、线路拥挤及阻塞数据、出/入口、厕所、残疾电梯数据。城市轨道周边公交(深圳市所有轨道交通站点、附近的公交车站、位置、各站点的名称)。如果所述公共交通大数据是指交通气象数据，则其属性内容可以包含：交通气象数据，其属性包含：日期、时间、监测点、天气类型、温度、风速、风向、降水量。采集上述公共交通大数据实时发布轨道公交服务指数实际采集的数据类型与属性，建立主要数据的相关特征提取，其它数据可以进行辅助教研与评估。
步骤S302，根据所述公交系统的基础数据和预设的指标评估模型获取多个评估指标的评价分数。
所述评估设备的评估装置内预先设置用于评估公交系统服务质量指数的指标评估模型。所述指标评估模型主要用于，将所采集的基础数据对应到相应的评估指标下，根据基础数据的数值和评估标准获取每个评估指标的评价分数。
步骤S303，根据所述多个评估指标中的每个评估指标的评价分数和该评估指标的权重获取所述公交系统的评估结果。
在针对所述公交系统的服务质量评估的所述指标评估模型中，不同评估指标对服务质量的影响不同，则不同评估指标的权重也不相同，每个评估指标均对应各自的权重。
依据上述步骤获取所述指标评估模型中的各个评估指标的评价分数后，根据每个评估指标的评价分数和该评估指标的权重计算所需要的公交系统的评估结果。
在一种实施方式中，所述公交系统的评估指标包括:舒适性、便捷性、经济性、安全性和可靠性，上述五个评估指标的评价分数依次为A1、A2、A3、A4和A5，相应地，五个评估指标的权重依次为：B1、B2、B3、B4和B5。则所述评估结果S的计算可以简述为：S＝A1*B1+A2*B2+A3*B3+A4*B4+A5*B5。
所述评估装置依据上述步骤获取公交系统的评估结果之后，可以用于不同城市地区、不同时段的数据结果评比。还可以根据所获得的相关的评估结果生成评估报告，将所述评估报告发送至需求者所在的用户终端，以方便乘客进行查询、参阅和选择，也方便了政府监管部门对公共交通状况的监察和掌控，以及对相关公共交通工具承载企业的经营状况等的监察等。
本发明实施例提供的评估方法中，主要包括轨道公交线网可达性、服务质量、出行时间、乘车安全评价指标。其中，公交线网可达性是核心。用一卡通乘客刷卡数据与视频图像数据等数据融合处理，对每条轨道公交线路乘客、车辆、场站、线路、站组、线网六级特征提取，实时动态发布城市轨道公交线网、单条轨道公交线路、每个轨道公交站点、轨道公交到达时刻、轨道公交线路车速、车内乘客数量、场站候车客流信息，评价城市轨道公交系统可靠性与时效性服务。
对于轨道公交系统总体线路网络、城市轨道公交单线线路、城市轨道公交各站点客流等类别，通过轨道公交线路网络、轨道公交车辆、轨道公交各站点客流的红、黄、绿不同颜色形式变化，提供实时动态的轨道公交客流状况、轨道线路拥挤程度、预计到达时间等轨道公交站点、单条线路、总体线路轨道公交运行状况，提高轨道公交的总体运输能力与服务质量。
上述本发明实施例提供的评估方法，获取公交系统内可实时获取和更新的基础数据，将所获取的基础数据代入到预先建立的指标评估模型获取多个评估指标的评价分数。将指标评估模型计算所得的评估指标的评价分数和相应指标的权重获取所需要的公交系统的评估结果。可以通过实时采集的电子系统的数据和预先建立的指标评估模型进行公交系统的评估结果的计算，极大程度地提高了公交系统服务质量评估的效率、准确度和便捷度和普及率。
请参见图4，为本发明第一实施例提供的公交系统服务质量的评估方法的步骤S301的子步骤流程图，主要是通过采集的公共交通大数据进行清洗筛选、特征提取等处理，获取可以作为公交系统服务质量评估的基础数据的过程。下面将对图4所示的内容进行具体描述。
步骤S401，采集当前的公共交通大数据。
公交交通大数据包括：轨道公交IC卡数据、轨道公交车辆实时数据、轨道公交线网数据、出租车行车数据等公共交通系统的实时数据。公共交通大数据来源众多，数据类型不同，其所述评估指标也不同，因此可以选择将公共交通大数据进行聚类，针对不同类别的公共交通大数据采取对应的方式进行数据采集。
所述公共交通大数据进行聚类后，可以主要归类为：乘车秩序数据、设施供应数据和车辆运行状态数据。采集公共交通大数据的方式有多种，针对上述主要类型的数据，可以通过对应的数据采集方式进行采集。
在一种实施方式中，可以通过图像处理方式获取所采集的现场视频中包含的乘车秩序数据。例如，通过公交站点、轨道枢纽站点等的图像采集装置采集的现场视频，进行图像处理，提取所获取的视频中包含的人物特征点，根据所提取的人物特征点的分布和移动计算该公交场所的乘车秩序数据。所述乘车秩序数据可以包括：进、出站台秩序(通道、楼梯、扶梯)、站台候车秩序、上、下车秩序、车厢秩序、进、出站时间、上、下车时间、高峰时段车厢拥挤度等。
在另一种实施方式中，可以通过电子标识感应方式获取设施供应数据。例如，通过电子标识感应系统采集安全服务设施标示及使用说明醒目、紧急疏散标识清晰度和准确度、地铁安检设施(数量、速度)、自动售票机(布局、数量、速度)、自动检票机(布局、数量、灵敏度)、自动扶梯(数量、运转情况)、轨道公交线路间换乘便捷度、轨道交通与其他公交间换乘等数据。
在其它实施方式中，还可以通过运行管控系统数据提取方式获取车辆运行状态数据。所述运行管控系统可以包括：导乘系统、报站系统、驾驶系统等，所述运行状态数据可以包括：导乘标识信息准确度、报站准确度和及时度、列车运行准点率、列车运行速度、列车发车间隔合理度首、末车时间、列车运行平稳(起动、制动、加速)、等。
在其它实施方式中，还可以通过票务系统获取票务数据，例如票价合理性、票种多样性等。
步骤S402，对所述公共交通大数据进行特征提取。
依据上述步骤采集到当前的公共交通大数据后，对所获取的所述公共交通大数据进行特征提取，主要是根据系统需求和处理算法对获取的公共交通大数据进行处理。
在数据处理过程中，主要应用到：交通信息FCD采集算法、FCD数据融合分析与处理、基于MVC的FCD数据采集与融合、事件流的面向对象设计、派生需求的面向对象协作图设计。
交通信息FCD采集中所涉及的核心算法包括原始数据FCD异常剔除算法，车速计算、融合和预测算法，标准和历史数据(流量和车速)的统计算法等七个关键算法。这些算法实现了从外场原始数据到“城市综合交通信息平台”使用数据的转换，是保证“信息平台”乃至整个系统基础数据可靠性的关键。在FCD采集信息中，根据外场采集的数据信息，计算当前路段车速并综合采集信息预测5分钟、10分钟、30分钟车速。车速融合预测过程分为三个过程：根据FCD数据基于FCD车速计算模型计算路段行程车速；根据流量、地点车速和行程车速基于数据融合模型计算当前车速；根据当前车速基于车速预测模型对车速进行预测。
FCD数据融合的主要任务是对当前流量数据，FCD计算车速和地点车速进行数据级的融合。这里数据融合主要分为两个方面：一方面是实时数据和历史数据的融合，采用线性变换，模糊算法，标定不同的权值和隶属度，得出较为精确的数值；另一方面是浮动车数据和定点检测器数据的融合，根据两种不同信息源的各自特点，通过异构数据同构化处理，对同一参数进行融合，得出可信度较高的结果。在交通流理论中的流密速关系模型，通过流密速关系模型对数据进行同构化处理。实时动态发布轨道公交服务指数与系统，采用自动或人工触发方式建立出租车、公交车公司与系统之间的连接，出租车、公交车公司能够全天连续提供FCD数据。深圳市城市交通仿真的FCD数据采集，就是城市综合交通信息中心的大规模GPS出租车及深圳公交集团等运营企业，计划在特区内外将提供超过15000辆出租车的FCD动态交通实时采集数据，采集间隔不小于30秒，车总量不少于15000辆。
步骤S403，将经特征提取后的数据作为基础数据。
依据上述步骤完成公共交通大数据的采集，以及对所获取的公共交通大数据的特征提取之后，将最终获取的数据作为基础数据。将所获取的基础数据应用到公交系统服务质量评估的过程中，极大程度地提高了基础数据获取效率和准确率。
请参见图5，为本发明第二实施例提供的公交系统服务质量的评估方法的步骤流程图。在上述实施例的基础上，本发明实施例还增设评估模型的建立过程。下面将对本发明实施例增设的评估模型的建立过程进行具体解释。
步骤S501，将所述基础数据的全部数据的数据类型均作为三级评估指标。
步骤S502，根据全部所述三级评估指标和预设的二级评估指标的类别对全部所述三级评估指标进行分类，以使每个所述三级评估指标对应一个类别的二级评估指标。
步骤S503，获取每个所述三级评估指标所对应的二级评估指标及该三级评估指标的第一权重。
公交系统服务质量的评估模型的建立，需要确定评估指标体系。公交系统服务质量的评估指标体系是一个多指标结构，运用层次化结构设定评估指标，能够由表及里、深入清晰地表述乘客满意的评估指标体系内涵。每一个层次的评估指标都是由上一个层次评估指标展开的，而上一个层次的评估指标则通过下一个层次的评估指标的评估结果反映出来。建立乘客服务质量评估指标体系必须遵循系统性原则、乘客是上帝的原则、繁简得当的原则、可操作性原则、公共交通大数据时效性关联原则等。
依据上述评估指标的选取原则和设置功能，在交通大环境数据下，利用SERVQUAL(Service Quality，服务质量)算法、步行穿越法、关键事件技术评测法，得到轨道公交服务质量的评估指标体系。其中，所述SERVQUAL 算法，是服务质量评价体系，其理论核心是“服务质量差距模型”，服务质量取决于用户所感知的服务水平与用户所期望的服务水平之间的差别程度。步行穿越发，是一种诊断工具，主要用于诊断关联：个人对个人的服务；服务延迟；环境变量；帐单提供；促销和暗示性销售等的问题。关键事件技术评测发，是用以识别各种工作环境下工作绩效的关键性因素的一种工作分析技术方法。
在评估指标体系中，将感知质量定义为一级评估指标，用以表示公交系统的总的服务质量。将安全性、可靠性、经济性、便捷性、舒适性定义为二级评估指标，表征用户对所述公交系统的主要感知方向的质量评估。根据二级评估指标展开形成评估指标体系，建立多项三级评估指标。在轨道公交系统服务质量的评价指标体系中，只有三级评估指标是可以直接关联公共交通大数据直接检测的，它直接转化为乘客对服务质量内涵。所述三级评估指标包括第一实测指标和第一理论指标，所述第一实测指标为可以通过数据采集或者图像采集等的方式直接从公交系统的电子系统中测得的数据。所述第一理论指标为可以实际测得数据和理论计算公式计算获得的评估指标。
在一种实施方式中，所述二级评估指标包括：安全性、可靠性、经济性、便捷性和舒适性中的至少一种。
所述第一实测指标主要对应10部分：列车司乘服务；场站列车安全保障、轨道公交信息服务、列车车容车况、场站乘车时耗、场站等候时间、场站列车拥挤程度、场站换乘服务、场站列车设施保障、乘客场站列车满意测评。
上述10部分内容分类为32项较为具体的第一实测指标，包括：进出站台秩序、站台候车秩序、上下车秩序、车厢秩序、安全服务设施标识及使用说明醒目、紧急疏散标识清晰度和准确度、地铁安检设施、自动售票机、自动检票机、自动扶梯、导乘标识信息准确度、报站准确度和及时度、列车运行准点率、票价合理度、票价多样性、进出站时间、购票时间、上下车时间、列车运行速度、列车发车间隔合理度首末车时间、轨道公交线路间换乘便捷度、轨道交通与其它公交间换乘便捷度、高峰时段车厢拥挤度、列车运行平稳度、通道整洁程度、车厢环境整洁度、站车噪声分贝、空气温湿度适宜程度、空气流通性、工作人员对乘客要求的响应率和便民设施普及率中的至少一种。上述的第一实测指标都可以从相应电子系统中直接获取或者提取。
所述公交系统的评估指标体系的具体结构请参见表(1)。
Figure PCTCN2016110860-appb-000001
Figure PCTCN2016110860-appb-000002
Figure PCTCN2016110860-appb-000003
表(1)
在其它实施方式中，所述三级评估指标的所述第一理论指标包括：准点率、列车运行图兑现率、列车拥挤度、售票机可靠度、储蓄卡充值机可靠度、储蓄卡充值机可靠度、进出站闸机可靠度、自动扶梯可靠度、垂直电梯可靠度、车站乘客信息系统可靠度、列车乘客信息系统可靠度、列车乘客信息可靠度、列车服务可靠度、有效乘客投诉了和有效乘客投诉恢复率中的至少一种。上述的第一理论指标需要将直接获取的原始状态的公共交通大数据进行理论值计算。下面将对上述第一理论指标的具体计算过程进行解释。
1.准点率，是指准点列车次数与全部开行列车次数之比，通过相关系统感知监测，用以表示运营列车按规定时间准点运行的程度。计算公式如下：
Figure PCTCN2016110860-appb-000004
按照运行图图定的时间运行，早、晚不超过规定时间界限的为准点列车，准点的时间界限指重点准点到站时间误差小于或等于2min的列车(市域快速轨道公交系统除外)；市域快速轨道公交系统准点的时间界定指终点到站时间误差小于或等于3min的列车。
2.列车运行图兑现率，是指实际开行列车数与运行图图定开行列车数之比，实际开行列车数中不包括临时加开的列车数。其计算方法如下：
Figure PCTCN2016110860-appb-000005
3.列车拥挤度，是指轨道公交线路高峰小时平均断面客运量与线路实际运输能力之比，列车按定员计算，用以表示列车的拥挤程度。计算方法如下：
Figure PCTCN2016110860-appb-000006
上式中，线路实际运输能力＝列车定员×线路高峰小时发车量。
4.售票机可靠度，是指售票机实际服务时间与售票机应服务时间之比。实际服务时间包括正常的加票和加币时间，计算方法如下：
Figure PCTCN2016110860-appb-000007
5.储值卡充值机可靠度，是指储值卡充值机实际服务时间与应服务时间之比，实际服务时间包括正常的加票和加币时间。其计算方法如下：
Figure PCTCN2016110860-appb-000008
6.进、出站闸机可靠度，是指进、出站闸机实际服务时间与应服务时间之比，所述进、出站闸机可靠度的计算方法如下：
Figure PCTCN2016110860-appb-000009
7.自动扶梯可靠度，是指自动扶梯实际服务时间与应服务时间之比。计算方法如下：
Figure PCTCN2016110860-appb-000010
8.垂直电梯可靠度，是指垂直电梯实际服务时间与应服务时间之比，计算方法如下：
Figure PCTCN2016110860-appb-000011
9.车站乘客信息系统可靠度，是指车站乘客信息系统实际服务时间与应服务时间之比。所述车站乘客信息系统可靠度的计算方法如下：
Figure PCTCN2016110860-appb-000012
10.列车乘客信息系统可靠度，是指列车乘客信息系统实际服务时间与应服务时间之比。所述列车乘客信息系统可靠度的计算方法如下：
Figure PCTCN2016110860-appb-000013
11.列车服务可靠度，是指一年内发生5min至15min延误之间的列车，其平均行驶的车公里数，数值越大，表明可靠度性越高。
12.有效乘客投诉率，是指有效乘客投诉率次数与城客运量之比，计算方法如下：
Figure PCTCN2016110860-appb-000014
13.有效乘客投诉回复率，是指已经回复的有效乘客投诉次数与有效乘客投诉次数之比。所述有效乘客投诉回复率的计算方法如下：
Figure PCTCN2016110860-appb-000015
上式中，有效乘客投诉应在接到投诉之日起，7个工作日内回复，超过7个工作日按未回复处理。
步骤S404，获取每个所述二级评估指标的第二权重。
步骤S405，根据每个所述三级评估指标及其第一权重、每个所述二级评估指标及其第二权重以及所述三级评估指标和所述二级评估指标的对应关系建立所述指标评估模型。
依据上述步骤获取所述基础数据中的每个数据对应的三级评估指标，根据在公交系统的服务质量评估时，每个所述二级评估指标下的每个三级评估指标的影响度的不同，确定每个所述三级评估指标在其所对应的二级评估指标中所占的权重，设为第一权重。在根据一级评估指标下的每个二级评估指标的影响度的不同，确定每个所述二级评估指标在一级评估指标中所占的权重，设为第二权重。
获取一级评估指标下的每个二级评估指标及其第二权重，以及每个所述二级评估指标下的一级评估指标类别，以及每个所述一级评估指标在其对应的二级评估指标中的第一权重，建立所述指标评估模型。
依据所建立的指标评估模型，在获取公交系统的基础数据后，可以直接将所获取的基础数据中的每个数据匹配到对应的三级评估指标，并根据该三级评估指标所对应的二级评估指标以及其第一权重计算二级评估指标对应的评价分数，再依据所获取的评价分数和二级评估指标的第二权重获取最终评估结果的计算，极大程度地提高了公交系统服务质量评估的效率、准确率和时效性，提高了用户体验度。
请参见图6，为本发明第一实施例提供的评估方法的步骤S301和步骤S302的子步骤流程图。在上述实施例建立的指标模型的基础上，进行评估结果的获取操作。下面将对图6所示的步骤进行具体解释。
步骤S601，获取所采集的基础数据的每个数据的数据类型对应的目标三级评估指标。
获取公交系统提供的原始状态的基础大数据后，将所获取的公共交通大数据进行筛选后作为评估计算的基础数据。根据当前获取的基础数据的数据类型，查找该数据对应的目标三级评估指标。
例如，在获取公交车厢内的视频数据后，由于该公交车厢的视频数据可以获取该公交的车厢内的秩序数据。因此该数据所对应的目标三级评估指标为车厢秩序。
步骤S602，根据每个所述数据的数值和该数据的数据类型对应的所述目标三级评估指标的第一权重获取第一评价分数。
依据上述步骤获取的基础数据中的每个数据的数值和其所对应的目标三级评估指标后，将所获取的数据的数值与该数据对应的目标三级评估指标的第一权重后，计算该数据所得出的评价分数，作为该目标三级评估指标的所述第一评价分数。
步骤S603，根据每个所述目标三级评估指标的第一评价分数和该目标三级评估指标对应的目标二级评估指标的第二权重获取第二评价分数。
依据上述步骤获取所述基础数据的每个数据对应的目标三级评估指标的第一评价分数后，计算每个所述二级评估指标。首先，根据所述三级评估指标和二级评估指标的对应关系，获取每个目标三级评估指标对应的目标二级评估指标，并获取该目标二级评估指标下的所有三级评估指标的第一评价分数。依据每个所述二级评估指标的第二权重和该二级评估指标下的各个三级评估指标的第一评价分数计算该二级目标评估指数的第二评价分数。
步骤S604，根据全部所述二级评估指标的第二评价分数获得所述公交系统的评估结果。
依据上述步骤计算所述三级评估指标的第一评价分数和二级评估指标的第二评价分数后，计算一级评估指标的评价分数，所述以及评估指标的评价分数直接关联所述公交系统的服务质量的评估结果。
上述本发明实施例提供的评估方法，在针对公交系统的服务质量进行评估时，以可以直接、实时、自动获取的公共交通大数据作为结果计算的基础数据，将基础数据代入到预先设置的指标评估模型中，自动完成各个级别评估指标的匹配和评价分数的计算，较为快速准确的实现了公交系统的服务质量的评估，
请参见图7，是本发明第三实施例提供的评估装置700的功能模块图。所述评估装置700包括：基础数据获取模块701、评价分数获取模块702和评估结果获取模块703。
基础数据获取模块701，用于获取公交系统的基础数据。
评价分数获取模块702，用于根据所述公交系统的基础数据和预设的指标评估模型获取多个评估指标的评价分数。
评估结果获取模块703，用于根据所述多个评估指标中的每个评估指标的评价分数和该评估指标的权重获取所述公交系统的评估结果。
在上述实施例的基础上，所述评估装置700还包括指标评估模型建立模块704，所述指标评估模型建立模块704用于：
将所述基础数据的全部数据的数据类型均作为三级评估指标；
根据全部所述三级评估指标和预设的二级评估指标的类别对全部所述三级评估指标进行分类，以使每个所述三级评估指标对应一个类别的二级评估指标；
获取每个所述三级评估指标所对应的二级评估指标及该三级评估指标的第一权重；
获取每个所述二级评估指标的第二权重；
根据每个所述三级评估指标及其第一权重、每个所述二级评估指标及其第二权重、所述三级评估指标和所述二级评估指标的对应关系以及所述一级评估指标建立所述指标评估模型。
在上述实施例的基础上，所述评价分数获取模块702具体用于：
获取所采集的基础数据的每个数据的数据类型对应的目标三级评估指标；
根据每个所述数据的数值和该数据的数据类型对应的所述目标三级评估指标的第一权重获取第一评价分数。
在上述实施例的基础上，所述评估结果获取模块703具体用于：
根据每个所述目标三级评估指标的第一评价分数和该目标三级评估指标对应的目标二级评估指标的第二权重获取第二评价分数；
根据全部所述二级评估指标的第二评价分数获得所述公交系统的评估结果。
上述本发明实施例提供的评估装置，通过获取公交系统内可实时获取和更新的基础数据，将所获取的基础数据代入到预先建立的指标评估模型获取多个评估指标的评价分数。将指标评估模型计算所得的评估指标的评价分数和相应指标的权重获取所需要的公交系统的评估结果。可以通过实时采集的电子系统的数据和预先建立的指标评估模型进行公交系统的评估结果的计算，极大程度地提高了公交系统服务质量评估的效率、准确度和便捷度和普及率。本发明实施例提供的评估装置的具体实施过程请参见上述方法实施例，在此不再一一赘述。
上述本发明实施例提供的评估模型和其所运载的实体系统的开发过程主要包括：数据采集、清洗、挖掘、汇总规则与算法、实现功能与技术指标总体设计、实时发布轨道公交服务指数开发、城市轨道公交服务指数测评应用等过程。
在数据采集、清洗、挖掘、汇总规则与算法的开发过程中，主要完成7个任务。其一，建立数据处理规则。数据分析包括：建立数据采集规则、数据清洗规则、数据挖掘规则和数据汇总规则。其二，建立道路网络支撑的数据分析挖掘流程与模型算法。数据分析设计包括：基于FCD，建立道路网络支撑的公交出行数据分析挖掘流程与模型算法。其三，建立轨道公交IC卡的数据分析挖掘流程与模型算法。数据分析设计包括：建立轨道公交IC卡出行的数据分析挖掘流程与模型算法。其四，建立常规公交出行的数据分析挖掘流程与模型算法。数据分析设计包括：建立常规公交出行的数据分析挖掘流程与模型算法。其五，建立出租车出行的数据分析挖掘流程与模型算法。数据分析设计包括：建立出租车出行的数据分析挖掘流程与模型算法。其六，建立轨道、巴士、出租、IC卡等数据库搜索引擎。数据分析设计：建立轨道、 巴士、出租、IC卡等数据库搜索引擎与数据库开发设计。其七，建立数据库群的分析与挖掘环境界面，数据分析设计：建立数据库群的分析与挖掘环境界面。
在实现功能与技术指标总体设计时，主要完成维度设计、功能设计和专项分析设计。所述维度设计即为：城市轨道、巴士、出租公交一体化服务查询平台--维度设计。所述功能设计，即为城市轨道交通服务查询平台--功能设计和轨道公交系统、出租公交一体化服务查询平台--功能设计。所述专项分析设计即为，城市轨道、巴士、出租公交一体化服务查询平台--专项分析设计，开发轨道公交系统GIS-T查询界面，对查询结果进行时空建模。
在上述实施例的基础上，还可以增设公交系统的乘客满意程度测评的过程。公交系统的乘客满意程度测评的具体过程可以包括：轨道公交乘客满意程度测评的具体步骤如下所示：确定乘客满意程度测评结构模型，建立满意程度测评指标体系，确定测评指标的权重，测评指标量化，公共交通大数据关联性检测，生成公共交通大数据检测结果，得出乘客满意程度测评。乘客程度测评的过程可参见上述服务质量的评估过程，不再赘述。
上述本发明实施例提供的公交系统服务质量的评估方法和装置所实现的公共交通大数据实时发布轨道公交服务指数模式主要包括：
1.公共交通大数据实时发布城市公交系统服务指数；
2.公共交通大数据实时发布轨道公交服务指数分布；
3.公共交通大数据实时发布轨道公交服务指数指标分布；
4.公共交通大数据实时发布轨道公交服务指数指标--拥挤程度排名分布；
5.公共交通大数据实时发布轨道公交服务指数指标--乘车拥挤站点分布；
6.公共交通大数据实时发布轨道公交服务指数指标--早高峰运量分布；
7.公共交通大数据实时发布轨道公交服务指数指标—晚高峰运量分布；
8.公共交通大数据实时发布轨道公交服务指数--线网、线路、拥挤实时动态监测平台指数发布；
9.公共交通大数据实时发布轨道公交服务指数--车辆、乘客、场站位置/时间/客流实时动态监测发布；
10.公共交通大数据实时发布轨道公交服务指数--载客流量实时动态发布；
11.公共交通大数据实时发布轨道公交服务指数--乘客候车场站位置分布；
12.公共交通大数据实时发布轨道公交服务指数--运行网络拥挤状态分布。
在实际应用中，基于Rational Rose Real Time建模环境轨道公交服务指数实时发布系统，作为城市“交通仿真与交通公用信息平台”一体化应用结构。 该系统主要面向3类用户(公众市民用户、政府相关部门、交通技术人员)提供8大功能组件，实现60个功能点，可进行5000多种组合查询轨道公交服务指数实时发布系统建设核心工程。主要由“一个网络、四个平台”(所述一个网络是指交通信息通信与传输网络，所述四个平台是指：交通信息采集平台、交通公用信息平台和交通仿真平台与交通信息服务平台)构成。
轨道公交服务指数实时发布系统主要反映城市轨道网络支撑的每时每刻(例如，设定3分钟为一个周期)实际使用轨道公交客流分布情况的信息，主要包括交通流方面的信息、轨道网络工作状况信息、交通事件方面的信息等。交通流信息包括车流量、轨道拥挤程度等，其中拥挤程度指标可进行量化(交通拥挤指数)，可以设置十个级别来反映城市轨道公交畅通、拥挤、阻塞的不同程度，分别标以绿、黄、红三种颜色表达。轨道网络工作状况信息主要反映城市骨架公交网络目前拥挤程度，包括拥挤区域、拥挤状态、拥挤持续时间、拥挤变化趋势、形成拥挤的成因、拥挤状况等。交通事件方面信息主要反映城市轨道网络中当前时刻发生的交通行为事件，主要包括交通事故、交通管制、交通监控、交通疏解等。轨道公交服务指数实时发布系统数据应该设计简单、实用，尽可能方便数据更新与查询，从而提高数据使用效率。其数据项主要包括内容：编号、线路名称、日期、时刻、方向、车流量、车流速度、拥挤度、路况状态、交通事件等。
轨道公交服务指数实时发布系统在设计与实践过程中，与传统的非实时动态系统呈现不同的特性，需要良好的方法、工具、语言的支持。将轨道公交服务指数实时发布系统、实时动态统一建模语言、实时动态交通信息发布系统的统一开发过程和Rational Rose Real Time建模环境有机地结合起来，进行了系统的需求分析与用例建模、静态与动态建模、实现与部署的先进软件技术在交通信息工程中的跨学科应用。
轨道交通公用信息平台负责数据融合、数据字典、基于数据挖掘的决策支持、数据服务和数据维护，交通数据统计查询是数据服务的一个子功能。基于上述分析，将轨道交通公用信息平台的功能组织在数据融合用例包、基于数据挖掘的决策支持用例包、交通数据统计查询用例包和数据维护用例包中。
交通仿真平台通过智能仿真组件进行战略级仿真分析和项目级仿真分析。由于智能仿真组件有其环境配置数据，所以需要标定相关参数。另外，对于一个软件集成产品来说，维护功能必不可少，还需要增加平台的维护功能。因此，功能可以分成战略级仿真分析、项目级仿真分析、智能仿真组件维护和仿真平台维护四块。基于上述分析，将交通仿真功能对应于交通仿真平台的需要，将其组织为战略级仿真分析用例包、项目级仿真分析用例包、智能仿真组件维护用例包和仿真平台维护用例包。
交通信息服务平台将实时检测、处理后的交通运行状态数据以及仿真计算结果，以适当的形式准确度、及时地传达至用户，实现全天候、多方式、多层面的动态、静态交通信息发布。另外，对于一个软件集成产品来说，维护功能必不可少，还需要增加平台的维护功能。因此，功能可以分成信息发布服务、信息管理服务两块。基于上述分析，将信息服务功能组织在信息发布服务用例包和信息管理服务用例包中。
轨道公交服务指数实时发布系统发布的顺序图和协作图统称交互图，它们用于分析刻画系统用例实现中对象间的动态交互和消息传递，帮助识别类、职责，并在协作者之间分配职责，还用于识别接口和抽象类。
轨道公交服务指数实时发布系统软件需要部署在相应硬件上，而且还必须提供相应的运行环境才能正常运行，系统所涉及的软硬件环境比较多，可以划分成五个部署区域:数据采集区，外部用户区，DMZ隔离区，内部服务区，内部用户区。各个区域之间通过无线网络、互联网和局域网实现连接；互联网和局域网之间的网际互连使用路由器实现；为保障整个系统网络安全和高效，使用防火墙隔离互联网和局域网，防火墙和局域网之间使用交换机连接，使用网闸实现内部用户区和内部服务区之间物理隔离，使用网管负责整个系统网络设备的管理。
以上所述仅为本发明的优选实施例而已，并不用于限制本发明，对于本领域的技术人员来说，本发明可以有各种更改和变化。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。

Claims (10)

  1. 一种公交系统服务质量的评估方法，其特征在于，所述方法包括：
    获取公交系统的基础数据；
    根据所述公交系统的基础数据和预设的指标评估模型获取多项服务质量对应的评估指标的评价分数，其中，每个评估指标的评价分数用于表征与其对应的服务质量的服务水平；
    根据多个评估指标中的每个评估指标的评价分数和该评估指标的权重获取所述公交系统服务质量的评估结果。
  2. 根据权利要求1所述的方法，其特征在于，获取公交系统的基础数据的步骤包括：
    采集当前的公共交通大数据；
    对所述公共交通大数据进行特征提取，将经过所述特征提取后的公共交通大数据作为所述公交系统的基础数据。
  3. 根据权利要求2所述的方法，其特征在于，所述公共交通大数据包括通过图像处理方式获取的所采集的现场视频中包含的乘车秩序数据、通过电子标识感应方式获取的设施供应数据和通过运行管控系统数据提取方式获取的车辆运行状态数据中的至少一个。
  4. 根据权利要求1所述的方法，其特征在于，获取所述公交系统的评估结果之后，所述方法还包括：
    将所述评估结果发送至用户终端。
  5. 根据权利要求2所述的方法，其特征在于，所述评估结果对应一级评估指标，获取公交系统的基础数据的步骤之前，所述方法还包括：
    将所述基础数据的全部数据的数据类型均作为三级评估指标；
    根据全部所述三级评估指标和预设的二级评估指标的类别对全部所述三级评估指标进行分类，以使每个所述三级评估指标对应一个类别的二级评估指标；
    获取每个所述三级评估指标所对应的二级评估指标及该三级评估指标的第一权重；
    获取每个所述二级评估指标的第二权重；
    根据每个所述三级评估指标及其第一权重、每个所述二级评估指标及其第二权重、所述三级评估指标和所述二级评估指标的对应关系以及所述一级评估指标建立所述指标评估模型。
  6. 根据权利要求5所述的方法，其特征在于，根据所述公交系统的基础数据和预设的指标评估模型获取多个评估指标的评价分数，根据所述多个评估指标中的每个评估指标的评价分数和该评估指标的权重获取所述公交系统的评估结果的步骤包括：
    获取所采集的基础数据的每个数据的数据类型对应的目标三级评估指标；
    根据每个所述数据的数值和该数据的数据类型对应的所述目标三级评估指标的第一权重获取第一评价分数；
    根据每个所述目标三级评估指标的第一评价分数和该目标三级评估指标对应的目标二级评估指标的第二权重获取第二评价分数；
    根据全部所述二级评估指标的第二评价分数获得所述公交系统的评估结果。
  7. 根据权利要求5所述的方法，其特征在于，所述三级评估指标包括第一实测指标和第一理论指标，所述第一实测指标包括：进出站台秩序、站台候车秩序、上下车秩序、车厢秩序、安全服务设施标识及使用说明醒目程度、紧急疏散标识清晰度和准确度、地铁安检设施、自动售票机、自动检票机、自动扶梯、导乘标识信息准确度、报站准确度和及时度、列车运行准点率、票价合理度、票价多样性、进出站时间、购票时间、上下车时间、列车运行速度、列车发车间隔合理度首末车时间、轨道公交线路间换乘便捷度、轨道交通与其它公交间换乘便捷度、高峰时段车厢拥挤度、列车运行平稳度、通道整洁程度、车厢环境整洁度、站车噪声分贝、空气温湿度适宜程度、空气流通性、工作人员对乘客要求的响应率和便民设施普及率中的至少一种；
    所述第一理论指标包括：准点率、列车运行图兑现率、列车拥挤度、售票机可靠度、储蓄卡充值机可靠度、储蓄卡充值机可靠度、进出站闸机可靠度、自动扶梯可靠度、垂直电梯可靠度、车站乘客信息系统可靠度、列车乘客信息系统可靠度、列车乘客信息可靠度、列车服务可靠度、有效乘客投诉了和有效乘客投诉恢复率中的至少一种；
    所述二级评估指标包括：安全性、可靠性、经济性、便捷性和舒适性中的至少一种。
  8. 一种公交系统服务质量的评估装置，其特征在于，所述公交系统服务质量的评估装置包括：
    基础数据获取模块，用于获取公交系统的基础数据；
    评价分数获取模块，用于根据所述公交系统的基础数据和预设的指标评估模型获取多项服务质量对应的评估指标的评价分数，其中，每个评估指标的评价分数用于表征与其对应的服务质量的服务水平；
    评估结果获取模块，用于根据多个评估指标中的每个评估指标的评价分数和该评估指标的权重获取所述公交系统的评估结果。
  9. 根据权利要求8所述的装置，其特征在于，所述评估结果对应一级评估指标，所述装置还包括指标评估模型建立模块，所述指标评估模型建立模块用于：
    将所述基础数据的全部数据的数据类型均作为三级评估指标；
    根据全部所述三级评估指标和预设的二级评估指标的类别对全部所述三级评估指标进行分类，以使每个所述三级评估指标对应一个类别的二级评估指标；
    获取每个所述三级评估指标所对应的二级评估指标及该三级评估指标的第一权重；
    获取每个所述二级评估指标的第二权重；
    根据每个所述三级评估指标及其第一权重、每个所述二级评估指标及其第二权重、所述三级评估指标和所述二级评估指标的对应关系以及所述一级评估指标建立所述指标评估模型。
  10. 根据权利要求9所述的装置，其特征在于，所述评价分数获取模块具体用于：
    获取所采集的基础数据的每个数据的数据类型对应的目标三级评估指标；
    根据每个所述数据的数值和该数据的数据类型对应的所述目标三级评估指标的第一权重获取第一评价分数；
    所述评估结果获取模块具体用于：
    根据每个所述目标三级评估指标的第一评价分数和该目标三级评估指标对应的目标二级评估指标的第二权重获取第二评价分数；
    根据全部所述二级评估指标的第二评价分数获得所述公交系统的评估结果。
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