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Review of Traffic Volume Prediction Based on Bibliometric Analysis |
PEI Yu-long, HE Qing-ling, HOU Lin, CAI Xiao-xi |
College of Traffic and Transportation, Northeast Forestry University, Harbin Heilongjiang 150040, China |
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Abstract In order to understand the current study status and development trend of traffic volume forecast, based on the VOSviewer bibliometric tool, taking the Web of Science core collection and the literatures related to traffic volume prediction studies in recent 29 years (1993—2021) in CNKI core database as the data sources, the study trends in the field of traffic volume forecasting are analyzed in terms of article age, country and region, journal source and technical topics. Taking the "traffic volume forecast and" "traffic volume forecasting" as the search topics, 592 valid literatures covering 6 438 keywords are searched. Based on the scientific knowledge mapping, the literatures in the field of traffic volume prediction are sorted out and analyzed. The result shows that (1) Traffic forecasting studies have been on the rise in the past 29 years, and the number of publications in China is the highest. (2) Transportation Research Part C: Emerging Technologies is not only the journal with the largest number of literatures, but also the journal with the largest number of citations, and Journal of Highway and Transportation Research and Development is the most cited journal among domestic journals. (3) The studies in the field of traffic volume forecasting are mainly conducted from the perspectives of highway traffic demand development prediction, traffic volume prediction method model, traffic events and real-time monitoring, focusing on the topics of highway traffic volume prediction, project construction feasibility study, short-time traffic volume prediction method modelling and accuracy improvement, traffic event monitoring and traffic spatial and temporal distribution characteristics. (4) The number of foreign study literatures on the relationship between highway traffic volume and construction investment, traffic volume prediction under atypical conditions and the studies on traffic volume prediction under adverse weather conditions such as rain and snows shown a significant increase in recent years. (5) Domestic studies on the improvement of the four-stage method, feasibility study of road traffic construction projects and road tourism traffic volume prediction are relatively abundant, but mainly from the macro perspective of economy, population and tourism industry, it is necessary to further increase the studies on the influence of seasonal changes, individual travel characteristics and travel preferences on road tourism traffic volume prediction.
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Received: 20 May 2021
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Fund:Supported by the National key R&D Program of China(No.2018YFB1600902) |
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