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Development of bus transit system control measures with open transit data

Treść / Zawartość
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The purpose of this study is to analyse the accuracy of the static schedule of bus transit network in Delhi using real-time data available from Delhi’s Open Transit Data (OTD) platform. To access and organise the data, an algorithm that can convert real-time data into a General Transit Feed Specification (GTFS) format, needs to be designed. Further, this study intends to develop a methodology, which can convert raw data of bus locations into link travel times, which consequently, helps in identifying problematic links. As researchers continue to make use of the data available via GTFS, they may well be aware of the fact that such data may differ systematically from actual transit operations. Continuous improvement of the accuracy of the GTFS static file would benefit its users.
Rocznik
Tom
Strony
169--180
Opis fizyczny
Bibliogr. 8 poz.
Twórcy
autor
  • M.Tech. Scholar, Indian Institute of Technology Delhi, New Delhi, 110016, India
  • Ph.D. Research Scholar, Indian Institute of Technology Delhi, New Delhi, 110016, India
  • Department of Civil Engineering and Transportation Research and Injury Prevention Programme (TRIPP), Indian Institute of Technology Delhi, New Delhi, 110016, India
Bibliografia
  • 1. Monzon Andres, Sara Hernandez, Rocio Cascajo. 2013. ,,Quality of bus services performance: Benefits of real time passenger information systems”. Transport and Telecommunication 14(2): 155-166. DOI: 10.2478/ttj-2013-0013.
  • 2. Lyons Glenn, Reg Harman. 2002. ,,The UK public transport industry and provision of multi-modal traveller information”. International Journal of Transport Management 1(1): 1-13.
  • 3. Lorkowski S., P. Mieth, K.U. Thiessenhusen, D. Chauhan, B. Passfeld, R.P. Schäfer. 2004. „Towards Area-wide Traffic Monitoring-applications derived from Probe Vehicle Data”. In: Eighth International Conference on Applications of Advanced Technologies in Transportation Engineering (AATTE): 1-6. ASCE. May 26-28, Beijing, China.
  • 4. Mazloumi Ehsan, Graham Currie, Goeffrey Rose. 2010. ,,Using GPS data to gain insight into public transport travel time variability”. Journal of Transportation Engineering 136: 623-631. DOI: 10.1061/(ASCE)TE.1943-5436.0000126.
  • 5. Syrjärinne Paula, Jyrki Nummenmaa, Peter Thanisch, Riitta Kerminen, Esa Hakulinen. 2015. ,,Analysing traffic fluency from bus data”. IET Intelligent Transport Systems 9(6): 566-572. DOI: 10.1049/iet-its.2014.0192. ISSN: 1751-956X.
  • 6. Lu Hui, Peter Burge, Chris Heywood, Rob Sheldon, Peter Lee, Kate Barber, Alex Phillips. 2018. „The impact of real-time information on passengers’ value of bus waiting time”. Transportation Research Procedia 31: 18-34. DOI: 10.1016/j.trpro.2018.09.043.
  • 7. Cats Oded, Gerasimos Loutos. 2016. „Real-Time Bus Arrival Information System : An Real-Time Bus Arrival Information System: An Empirical Evaluation”. Journal of Intelligent Transport Systems 20(2): 138-151. DOI: 10.1080/15472450.2015.1011638.
  • 8. Wessel Nate, Jeff Allen, Steven Farber. 2017. „Constructing a routable retrospective transit timetable from a real-time vehicle location feed and GTFS”. Journal of Transport Geography 62: 92-97. DOI: 10.1016/j.jtrangeo.2017.04.012.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-b4887393-7808-473c-b109-f86886f757fc
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