IDEAS home Printed from https://ideas.repec.org/p/zbw/itsb12/72485.html
   My bibliography  Save this paper

An approach to design a real-time transportation information application with enabling technologies

Author

Listed:
  • Huang, KuangChiu
  • Pai, Shu-hsuan

Abstract

Real-time transportation information (RTTI) brings convenience by immediate traffic information for drivers and minimizes uncertainty of waiting time for bus passengers. Information about heavy rains suddenly flood underground passages and traffic accidents cause road blocking can be accessed immediately through an application service via smartphones. Bus passengers can check bus waiting time from Internet before moving to bus stations by RTTI. With the development of information communication technology (ICT), benefits of real-time transportation information can be realized by an integration of location based service (LBS), smartphone, applications, 3G network and cloud computing service. In order to gain insight of RTTI service, we carry out this research with two steps. The first, the study collects existing transportation related applications from both Apple iOS platform and Google Android platform to analyze their features. Next, we analyze enabling ICT technologies to design a RTTI service model and the issue on energy saving and CO2 emission reduction. The outcome of this research can provide a clear model to assist transportation regulators, municipalities and application developers to evaluate benefits and costs of RTTI service.

Suggested Citation

  • Huang, KuangChiu & Pai, Shu-hsuan, 2012. "An approach to design a real-time transportation information application with enabling technologies," 19th ITS Biennial Conference, Bangkok 2012: Moving Forward with Future Technologies - Opening a Platform for All 72485, International Telecommunications Society (ITS).
  • Handle: RePEc:zbw:itsb12:72485
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/72485/1/742707393.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Watkins, Kari Edison & Ferris, Brian & Borning, Alan & Rutherford, G. Scott & Layton, David, 2011. "Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(8), pages 839-848, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Stanis£Aw Brzeziñski & Piotr Stefañczyk, 2013. "Use Of Smartphone’S Possibilities In Construction Of Logistics System Of Vending Machines," Advanced Logistic systems, University of Miskolc, Department of Material Handling and Logistics, vol. 7(1), pages 21-30, December.
    2. Ma. Janice J. Gumasing & Frances Jeann Charlize S. Bermejo & Keisha Taranee C. Elpedes & Lady Fatima E. Gonzales & Aaron Chastine V. Villajin, 2023. "Antecedents of Waze Mobile Application Usage as a Solution for Sustainable Traffic Management among Gen Z," Sustainability, MDPI, vol. 15(13), pages 1-18, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marina Lagune-Reutler & Andrew Guthrie & Yingling Fan & David Levinson, 2015. "Transit Riders' Perception of Waiting Time and Stops' Surrounding Environments," Working Papers 000142, University of Minnesota: Nexus Research Group.
    2. Sarker, Rumana Islam & Kaplan, Sigal & Mailer, Markus & Timmermans, Harry J.P., 2019. "Applying affective event theory to explain transit users’ reactions to service disruptions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 593-605.
    3. Allard, Ryan F. & Moura, Filipe, 2018. "Effect of transport transfer quality on intercity passenger mode choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 109(C), pages 89-107.
    4. Matsumoto, Takayuki & Hidaka, Kazuyoshi, 2015. "Evaluation the effect of mobile information services for public transportation through the empirical research on commuter trains," Technology in Society, Elsevier, vol. 43(C), pages 144-158.
    5. Kelly, J. Andrew & Fu, Miao, 2014. "Sustainable school commuting – understanding choices and identifying opportunities," Journal of Transport Geography, Elsevier, vol. 34(C), pages 221-230.
    6. Zack Aemmer & Andisheh Ranjbari & Don MacKenzie, 2022. "Measurement and classification of transit delays using GTFS-RT data," Public Transport, Springer, vol. 14(2), pages 263-285, June.
    7. Bounie, Nathan & Adoue, François & Koning, Martin & L'Hostis, Alain, 2019. "What value do travelers put on connectivity to mobile phone and Internet networks in public transport? Empirical evidence from the Paris region," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 158-177.
    8. Yang Chen & Arturo Ardila-Gomez & Gladys Frame, 2016. "Achieving Energy Savings by Intelligent Transportation Systems Investments in the Context of Smart Cities," World Bank Publications - Reports 24740, The World Bank Group.
    9. Liu, Luyu & Miller, Harvey J., 2020. "Does real-time transit information reduce waiting time? An empirical analysis," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 167-179.
    10. Mulley, Corinne & Clifton, Geoffrey Tilden & Balbontin, Camila & Ma, Liang, 2017. "Information for travelling: Awareness and usage of the various sources of information available to public transport users in NSW," Transportation Research Part A: Policy and Practice, Elsevier, vol. 101(C), pages 111-132.
    11. Cats, Oded & Loutos, Gerasimos, 2013. "Real-time bus arrival information system: an empirical evaluation," Working papers in Transport Economics 2013:25, CTS - Centre for Transport Studies Stockholm (KTH and VTI).
    12. Monika Bąk & Przemyslaw Borkowski, 2019. "Young Transport Users’ Perception of ICT Solutions Change," Social Sciences, MDPI, vol. 8(8), pages 1-17, July.
    13. Moran, Marcel E, 2022. "Are shelters in place? Mapping the distribution of transit amenities via a bus-stop census of San Francisco," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3gj1t495, Institute of Transportation Studies, UC Berkeley.
    14. Kari Watkins & Alan Borning & G. Rutherford & Brian Ferris & Brian Gill, 2013. "Attitudes of bus operators towards real-time transit information tools," Transportation, Springer, vol. 40(5), pages 961-980, September.
    15. Meng, Meng & Rau, Andreas & Mahardhika, Hita, 2018. "Public transport travel time perception: Effects of socioeconomic characteristics, trip characteristics and facility usage," Transportation Research Part A: Policy and Practice, Elsevier, vol. 114(PA), pages 24-37.
    16. Justyna Patalas-Maliszewska & Hanna Łosyk & Jacek Newelski, 2021. "Modeling the Effectiveness of Intelligent Systems in Public Transport That Uses Low-Carbon Energy: A Case Study," Energies, MDPI, vol. 14(9), pages 1-13, May.
    17. Anne Brown & Whitney LaValle, 2021. "Hailing a change: comparing taxi and ridehail service quality in Los Angeles," Transportation, Springer, vol. 48(2), pages 1007-1031, April.
    18. Giacomo Lozzi & Valerio Gatta & Edoardo Marcucci, 2018. "European urban freight transport policies and research funding: are priorities and H2020 calls aligned?," REGION, European Regional Science Association, vol. 5, pages 53-71.
    19. Wen Hua & Ghim Ping Ong, 2018. "Effect of information contagion during train service disruption for an integrated rail-bus transit system," Public Transport, Springer, vol. 10(3), pages 571-594, December.
    20. Frei, Charlotte & Mahmassani, Hani S. & Frei, Andreas, 2015. "Making time count: Traveler activity engagement on urban transit," Transportation Research Part A: Policy and Practice, Elsevier, vol. 76(C), pages 58-70.

    More about this item

    Keywords

    real time transportation information; ICT; energy saving; CO2 emission;
    All these keywords.

    JEL classification:

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:itsb12:72485. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: http://www.itsworld.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.