This paper expands on previous work that used topic models to characterize transportation research as evidenced by TRB annual meeting papers. This paper advances the previous work by identifying trends over a longer period, exploring the papers in greater depth, and offering a more comprehensive analysis. Almost two decades (1998–2016) of papers were used in the topic model presented here, which identified the themes of the TRB papers and then sorted the documents by these themes. Because the number of accepted papers has increased, most areas of research have also increased in volume over the past 19 years. However, the topic model suggests that transportation research is becoming more holistic and more global. Research on energy and fuel; alternative transportation modes such as carsharing, bicycles, and buses; accessibility and health; and mobile technology is growing much faster than the increase in accepted papers. Additionally, TRB has accepted more papers from international sources, with many papers coming from China. Research on construction and infrastructure, particularly pavements, bridges, pipes, signs and markings, and barriers and guardrails, has increased but is now a smaller proportion of the body of papers accepted by TRB. This change may be attributable to the high cost of the research laboratories and facilities needed to carry out infrastructure research compared with costs for supporting research in some of the rapidly growing research fields that are more information intensive.


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    Titel :

    Trends Over Two Decades of Transportation Research


    Untertitel :

    A Machine Learning Approach


    Weitere Titelangaben:

    Transportation Research Record


    Beteiligte:


    Erscheinungsdatum :

    2017-01-01




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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