Short-term forecasting of bicycle traffic using structural time series models
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|Title:||Short-term forecasting of bicycle traffic using structural time series models||Authors:||Doorley, Ronan
|Permanent link:||http://hdl.handle.net/10197/10420||Date:||20-Nov-2014||Online since:||2019-05-13T11:46:20Z||Abstract:||Short term forecasting algorithms are widely used for prediction of vehicular traffic flows for adaptive traffic management. However, despite the increasing interest in the promotion of cycling in cities, little research has been carried out into the use of traffic forecasting algorithms for bicycle traffic. Structural time series models allow the various components of a time series such as level, seasonal and regression effects to be modelled separately to allow analysis of previous trends and forecasting. In this paper, a case study at a segregated bicycle lane in Dublin, Ireland was performed to test the forecasting accuracy of structural time series models applied to continuous observations of cyclist traffic volumes. It has been shown that the proposed models can produce accurate peak period forecasts of cyclist traffic volumes at both 1 hour and fifteen minute resolution and that the percentage errors are lower for hourly forecasts. The inclusion of weather metrics as explanatory variables had varying effects on the forecasting accuracies of the models. These results directly aid the design of traffic signal control systems accommodating cyclists.||Funding Details:||Environmental Protection Agency||Type of material:||Conference Publication||Publisher:||IEEE||Copyright (published version):||2014 IEEE||Keywords:||Forecasting; Time series analysis; Predictive models; Temperature measurement; Computational modeling; Load modeling; Cities and towns||DOI:||10.1109/ITSC.2014.6957948||Language:||en||Status of Item:||Peer reviewed||Is part of:||17th International IEEE Conference on Intelligent Transportation Systems (ITSC)||Conference Details:||2014 17th IEEE International Conference on Intelligent Transportation Systems, ITSC 2014, Qingdao, China, 8-11 October 2014||ISBN:||978-1-4799-6078-1|
|Appears in Collections:||Mechanical & Materials Engineering Research Collection|
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