6
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Impact of a New Metro Line: Analysis of Metro Passenger Flow and Travel Time Based on Smart Card Data

      1 , 2
      Journal of Advanced Transportation
      Hindawi Limited

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Over the past few decades, massive volumes of smart card data from metro systems have been used to investigate passengers’ mobility patterns and assess the performance of metro network. With the rapid development of urban rail transit in densely populated areas, new metro lines are constantly designed and operated in recent years. The appearance of new metro lines may significantly affect passenger flow and travel time in the metro network. In this study, smart card data of metro system from Nanjing, China, are used to study the changes of metro passenger flow and travel time due to the operation of a new metro line (i.e., Line 4, opened on 18 January 2017). The impact of the new metro line on passenger flow distribution and travel time in the metro network is first analysed. As commuting is one of the major purposes of metro trips, the impact of the new metro line on commuters’ trips is then explicitly investigated. The results show that the new metro line influences passenger flow, travel time, and travel time reliability in the metro network and has different impacts on different categories of commuters.

          Related collections

          Most cited references33

          • Record: found
          • Abstract: not found
          • Article: not found

          Beyond Space (As We Knew It): Toward Temporally Integrated Geographies of Segregation, Health, and Accessibility

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Mining smart card data for transit riders’ travel patterns

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              The promises of big data and small data for travel behavior (aka human mobility) analysis

              The last decade has witnessed very active development in two broad, but separate fields, both involving understanding and modeling of how individuals move in time and space (hereafter called “travel behavior analysis” or “human mobility analysis”). One field comprises transportation researchers who have been working in the field for decades and the other involves new comers from a wide range of disciplines, but primarily computer scientists and physicists. Researchers in these two fields work with different datasets, apply different methodologies, and answer different but overlapping questions. It is our view that there is much, hidden synergy between the two fields that needs to be brought out. It is thus the purpose of this paper to introduce datasets, concepts, knowledge and methods used in these two fields, and most importantly raise cross-discipline ideas for conversations and collaborations between the two. It is our hope that this paper will stimulate many future cross-cutting studies that involve researchers from both fields.
                Bookmark

                Author and article information

                Journal
                Journal of Advanced Transportation
                Journal of Advanced Transportation
                Hindawi Limited
                0197-6729
                2042-3195
                August 19 2018
                August 19 2018
                : 2018
                : 1-13
                Affiliations
                [1 ]School of Transportation, Southeast University, Nanjing 210096, China
                [2 ]Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Centre of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing 210096, China
                Article
                10.1155/2018/9247102
                8fe81dc6-bb38-418e-97f7-78ffd6ec063e
                © 2018

                http://creativecommons.org/licenses/by/4.0/

                History

                Comments

                Comment on this article