<rss version="2.0" xmlns:atom="https://www.w3.org/2005/Atom">
  <channel>
    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
    <description></description>
    <language>en-us</language>
    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
    </image>
    <item>
      <title>Decision Optimization of Urban Rail Transit Equipment Maintenance Mode Based on Reliability</title>
      <link>https://trid.trb.org/View/2237664</link>
      <description><![CDATA[The paper proposes an urban rail transit equipment maintenance mode decision method (EMMDM). The framework takes the reliability-centered maintenance (RCM) into consideration to make up for the problem that over-maintenance and under-maintenance of urban rail transit equipment for the decision-making model. To improve the application process of the RCM, the analysis of the composition and critical equipment of urban rail transit equipment is of vital importance. Failure rate, failure detectability, and failure consequence are selected as the equipment risk evaluation indexes. The cycle of optimal maintenance mode is given by the maintenance mode choice model based on the failure risk. Taking automatic ticket gate machine (AGM) and environmental monitoring equipment as examples, the results show cost savings of 8% and 2%, respectively, supporting the optimization of maintenance mode decision.]]></description>
      <pubDate>Wed, 27 Sep 2023 13:12:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/2237664</guid>
    </item>
    <item>
      <title>Potential of Electronic Ticketing Machine Data in Public Transport Planning</title>
      <link>https://trid.trb.org/View/2113479</link>
      <description><![CDATA[Public transport planning is one of the most important criteria in the development strategy of any country. India is a developing country, and the smart card facilities are rare; hence, it is suitable to look upon easily available data sources which could be helpful for public transport planning. One such big data source is the electronic ticketing machine (ETM) data. This study focuses on the long-distance bus services operated under Kerala State Road Transport Corporation (KSRTC) in Thrissur district, Kerala. KSRTC has been identified as one of the major losses making public sector services according to the Shushil Khanna Panel report. In order to improve the situation, a study on the existing conditions was essential. This study explores the use of ETM data in the generation of origin destination matrix for the long-distance bus services. The ETM data of the long-distance routes maintained by KSRTC has been collected from all the five bus depots in Thrissur. An algorithm has been developed which defines the sequential procedure followed to get the desired matrix output. Based on the developed algorithm, a Python code has been framed so as to estimate the origin destination matrix. The network model was created in VISUM, and desire line and flow bundle analysis has been carried out based on the consolidated OD Matrix in VISUM. The analysis found out Thiruvananthapuram to Attingal as the OD pair with maximum demand and the route sections that are contributing to the loss in the sector has been identified.]]></description>
      <pubDate>Wed, 22 Feb 2023 09:53:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2113479</guid>
    </item>
    <item>
      <title>Recovering the Association Between Unlinked Fare Machines and Stations Using Automated Fare Collection Data in Metro Systems</title>
      <link>https://trid.trb.org/View/1760025</link>
      <description><![CDATA[Data quality is the foundation of data-driven applications in transportation. Data problems such as missing and invalid data could sharply reduce the performance of the methods used in these applications. Although there exist plenty of studies related to data quality issues, they only focus on missing or invalid data caused by infrastructure failures (e.g., loop detector malfunction). In general, there is a lack of attention to data quality issues from insufficient data management. This paper proposes a tensor decomposition based framework to tackle a specific missing data problem which occurs when the machine-station dictionary of an automated fare collection system database is incomplete. In such cases, there is a large amount of loss of origin/destination information as the affected machines are not linked to any station. Consequently, all associated transactions may miss the origin/destination information. The proposed framework recovers the dictionary by capturing features of the passenger flow passing through the unlinked fare machine. Evaluation results show that the proposed approach could recover the missing data with high accuracy even when several fare machines are not linked to a station. The framework could also support other beneficial applications.]]></description>
      <pubDate>Thu, 04 Feb 2021 11:00:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/1760025</guid>
    </item>
    <item>
      <title>Modeling Mobile Ticket Dispenser System with Impatient Clerk</title>
      <link>https://trid.trb.org/View/1440136</link>
      <description><![CDATA[The mobile ticket dispenser system (MTDS) allows customers to remotely draw tickets for service orders anywhere through a mobile handset. In our previous work, the MTDS was applied to a restaurant scenario in which both clerks and customers are patient, i.e., once a mobile ticketing (MT) customer remotely draws the ticket, his request can be served by the clerk when the clerk is available, regardless of when the customer arrives at the restaurant. In this paper, the MTDS is applied to a post office scenario in which the customers are patient, but the clerk is impatient since the original ticket drawn by the MT customer may be invalid if he/she does not arrive at the post office before his/her turn. In this case, the behavior of the MT customer is the same as the so-called in-person ticketing customer who needs to draw a ticket in person when he/she arrives at the service counter. The authors propose an analytical model to derive the probability that an MT customer misses his/her turn when he/she arrives at the post office. A discrete-event simulation model is developed to investigate the performance of the predicted time adjustment mechanism for the MTDS. The authors also use real data collected at a post office to observe the queuing behavior. The authors' study provides guidelines for arranging the time for an MT customer to arrive at the MTDS server.]]></description>
      <pubDate>Thu, 22 Dec 2016 16:47:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/1440136</guid>
    </item>
    <item>
      <title>Design and Calculation Methodology for Air Conditioning Systems of Railway Buildings</title>
      <link>https://trid.trb.org/View/1417090</link>
      <description><![CDATA[The capacity of air conditioning systems for railway buildings is decided by calculating the quantity of heating or cooling load. Heat pump air conditioners work at their best energy efficiency under specific conditions, and to conserve energy used for those air conditioners, it is important to choose air conditioners of optimum capacity. In choosing air conditioners of optimum capacity, it is necessary to accurately calculate the loads. There are general design and calculation methodologies for the loads of ordinary buildings; however, those methodologies do not fit special loads in railway buildings, such as ticket vending machine rooms, train draft load, and train heat emission. This paper will cover the special loads in railway buildings]]></description>
      <pubDate>Thu, 28 Jul 2016 10:03:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/1417090</guid>
    </item>
    <item>
      <title>Involving the Public in the Design of the Ticket Vending Machine User Interface</title>
      <link>https://trid.trb.org/View/1394482</link>
      <description><![CDATA[This paper examines the process and benefits of user centered design as a research methodology and the key takeaways and findings from using the methodology to redesign a public transit ticket vending machine interface. By observing riders interacting with progressively more refined prototypes of the interface, listening to their feedback, and understanding their pain points, the researchers identified insightful ways to facilitate successful transactions on the ticket vending machine and ensure positive outcomes for the redesign project, the region’s transit agencies, and the public.]]></description>
      <pubDate>Mon, 29 Feb 2016 09:20:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/1394482</guid>
    </item>
    <item>
      <title>The OPUS Card: Yesterday, Today &amp; Tomorrow</title>
      <link>https://trid.trb.org/View/1378434</link>
      <description><![CDATA[This brief paper describes the OPUS smart card, used for Societie de Transport de Montreal (STM) transit fares. OPUS is also accepted by a community of Transit Authorities throughout the Greater Montréal and Québec City areas in Canada.  Transit users appreciate the integration of OPUS with other transit networks of neighboring cities of Montreal. They also appreciate the speed at which users can buy or validate fares. Transit authorities appreciate many aspects of the OPUS e-ticketing system (including avoidance of fraud). OPUS is a lot more than a card and a 200 M$ project! The presentation will introduce the objectives of the OPUS e-ticketing system, its governance principles, its step by step implementation, main key performance indicators (KPIs) and an overview of its strategic planning.]]></description>
      <pubDate>Mon, 28 Dec 2015 15:00:04 GMT</pubDate>
      <guid>https://trid.trb.org/View/1378434</guid>
    </item>
    <item>
      <title>Free Riders and Ticket Fraud in Public Transport: a Delphi Analysis</title>
      <link>https://trid.trb.org/View/1325244</link>
      <description><![CDATA[Public transport companies are the backbone of urban transport networks and provide important mobility services for the general public. As these services are of particular importance to a vast majority of people, municipal, provincial and state governments take responsibility for financing infrastructure networks and – at least in part – also the maintenance of the services. However, the use of public transport services is usually not free of charge for passengers. Although tariffs are frequently subsidised, revenues generated by ticket sales are an important source of income for the transport companies in order to keep the system financially balanced. The problem of free riding (= fare evasion, fare dodging or toll fraud; i.e. people using a transport service without paying for it) and ticket fraud (= ticket forgery, ticket falsification; i.e. the production of an illegal ticket facsimile) is, of course, not new to transport industries. Due to technological changes (on the suppliers‟ as well as on the passengers‟ side) the problem seems to change. Different approaches to ticket control, electronic ticketing, a rise in propensity to violence, broadening of poverty or better copying machines are but a few impact factors to take into consideration rendering the problem more and more serious. Thus, transport companies need to react to recent developments if they want to avoid substantial loss of income at present and in the future. This article gives an actual overview on experts‟ perspectives in the German-speaking part of Europe (Germany, Austria and the German-speaking part of Switzerland) and discusses different aspects of both free riding and ticket fraud. It is organised as follows: At the beginning free-riding and ticket-fraud are discussed in the actual context. Then the method employed to analyse the phenomena are explained. The subsequent chapter depicts the results in detail before the paper eventually concludes by presenting some implications with practical relevance as well as an outlook on further steps in research.]]></description>
      <pubDate>Wed, 29 Oct 2014 11:27:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/1325244</guid>
    </item>
    <item>
      <title>Optimization Scheduling of Subway Ticket Vending Machines Based on Passenger Behavior</title>
      <link>https://trid.trb.org/View/1326608</link>
      <description><![CDATA[While subways are being accepted and selected by more and more people, they are also facing an urgent need for improvement in service quality and competitiveness. The ticket vending machine (TVM) is an important tool for communicating with passengers and plays an important and highlighted role. Based on behavioral characteristics of different passengers, effectively regulating the number of TVMs and types of passenger queues has practical significance. Firstly, use a triple α / β / γ to describe the problem. An optimization scheduling problem regards minimizing manufacturing as the goal, with machine usage restrictions and the "first in-first out" principle. Then, establish a mathematical model. Secondly, using plant growth simulation algorithm design an algorithm. Finally, the case study demonstrates the algorithm's feasibility and efficiency.]]></description>
      <pubDate>Wed, 15 Oct 2014 12:01:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/1326608</guid>
    </item>
    <item>
      <title>A Vehicle Management System of Community Based on Radio Frequency Identification Technology</title>
      <link>https://trid.trb.org/View/1271218</link>
      <description><![CDATA[With the development of economy and the improvement of living standards, the vehicles in public places are increasing. In today's world, the traditional technology of parking management can not satisfy the needs. This paper aims to improve the efficiency of vehicles management and guarantee the safety of vehicles. The research paper presents an intelligent vehicle management expert system with radio frequency identification (RFID) technology. The system provides practically important user data collection, guidance information, control information and can trace criminal or illegal vehicles such as stolen cars or vehicles that evade tickets, tolls or vehicle taxes. The system architecture consists of an RFID reader, a passive tag, a terminal computer, a pair of magnetic induction coils and a high-speed server with a database system. The system collects user information and allocates parking spaces on a community of a district area in a city based on RFID technology. Moreover, it can identify cars that do not have a tag and then provide a temporary card through Automatic Vending Machine.]]></description>
      <pubDate>Wed, 28 May 2014 15:21:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/1271218</guid>
    </item>
    <item>
      <title>Effects of Perceived Benefits and Perceived Costs on Passenger’s Intention to Use Self-ticketing Kiosk of Taiwan High Speed Rail Corporation</title>
      <link>https://trid.trb.org/View/1284118</link>
      <description><![CDATA[Firms are incorporating self-service technologies into their operations, which results in cost savings. But the cost savings cannot be accomplished unless customers embrace and use these new services. Taiwan High Speed Rail Corporation (THSRC) collaborated with 7-Eleven for the self-ticketing system-ibon. But the utilization was not as expected. Thus, this study was exploring the factors which influence THSR passenger’s acceptance toward ibon ticketing system. The authors apply and extend the technology acceptance model (TAM) to determine the external variables of intention to use the self-ticketing system. The authors added four key constructs (two related to perceived benefits and two related to perceived costs) as external variables to the TAM. Further, when applying structural equation modeling to test the predictions, the research results showed that the perceived benefits (monetary benefits and non-monetary benefits) and perceived costs (monetary costs and non-monetary costs) had influence on the intention to use ibon. This study also proposed some managerial implications and suggestions for future research.]]></description>
      <pubDate>Tue, 11 Feb 2014 10:12:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/1284118</guid>
    </item>
    <item>
      <title>Simulation and Optimization of the Ticket Vending Machine Configuration in Metro Stations Based on Anylogic Software</title>
      <link>https://trid.trb.org/View/1276388</link>
      <description><![CDATA[Taking Chengdu metro as an example, first, this paper uses survey data to fit out the random distribution of passenger arrival and the service time of the TVM (ticket vending machine). Then, based on introducing a state correlation theory, a queuing model with obvious service desks  is built up. The simulation and parameter passing function of the AnyLogic software is then applied to verify and optimize the above model. Finally, the simulation result has proved the strong feasibility of the model and simulation optimization is able to relieve the passenger queue status resulted from the TVM, and thus it has significance for guiding the configuration of the TVM.]]></description>
      <pubDate>Thu, 30 Jan 2014 09:26:20 GMT</pubDate>
      <guid>https://trid.trb.org/View/1276388</guid>
    </item>
    <item>
      <title>The human factor</title>
      <link>https://trid.trb.org/View/1266458</link>
      <description><![CDATA[This article describes the reconstruction and development taking place at London Bridge station, scheduled for completion in 2018. Upon completion, the station will have the largest concourse in the UK and feature new retail shops and station facilities. The project aims to make London Bridge the most user-friendly station in the UK, moving passengers through bottlenecks and overcrowding even during service disruptions. Consideration of people has, therefore, been a core value of the project.  The author highlights a control room that will be critical to ensuring the station's smooth operation, new ticket-buying machines for efficient purchasing, and a station wayfinding system that is being developed using human factors thinking.]]></description>
      <pubDate>Thu, 21 Nov 2013 09:12:40 GMT</pubDate>
      <guid>https://trid.trb.org/View/1266458</guid>
    </item>
    <item>
      <title>Leveraging Electronic Ticketing to Provide Personalized Navigation in a Public Transport Network</title>
      <link>https://trid.trb.org/View/1217894</link>
      <description><![CDATA[Public transport networks (PTNs) are difficult to use when the user is unfamiliar with the area she is traveling to, as shown by a user survey that we present in this paper. This is true for both infrequent users (including visitors) and regular users who need to travel to areas with which they are not acquainted. In these situations, adequate on-trip navigation information can substantially ease the use of public transportation and be the driving factor in motivating travelers to prefer it over other modes of transportation. However, estimating the localization of a user is not trivial, although it is critical for providing relevant information. In this paper, we propose the use of an electronic ticketing infrastructure of a PTN operator for positioning within the context of the PTN to give on-trip personalized navigation cues. To our knowledge, this is an innovative contribution that has not been described or deployed, to date, elsewhere. We assess relevant design issues for a modular cost-efficient user-friendly on-trip navigation service that uses position sensors and present the details of a proof-of-concept prototype running in our laboratory. We also present and analyze the results of a user survey on the usefulness of the service and its acceptance by users.]]></description>
      <pubDate>Thu, 11 Jul 2013 09:37:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/1217894</guid>
    </item>
    <item>
      <title>Automating Resolution of Ticketing Issues — The Self-Service Point</title>
      <link>https://trid.trb.org/View/1114680</link>
      <description><![CDATA[Two Self-Service Points have been put on trial in the Hong Kong Station by the MTR Corporation in July 2007. This paper describes the design principles, difficulties encountered and lessons learnt in the development of the machine. The Self-Service Point is among the Corporation’s new initiatives to provide better customer service. Through enabling passengers to resolve certain ticketing issues on their own instead of approaching station staff, it offers an extra service channel for passengers to handle their ticking needs. The design of the man-machine interface, adaptation of business rules and data and co-ordination with station operations were among the critical issues from the design to commissioning phase. It is envisioned that more Self-Service Points with enhanced functions will be installed in the MTR stations where suitable.]]></description>
      <pubDate>Fri, 21 Oct 2011 07:38:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/1114680</guid>
    </item>
  </channel>
</rss>