Abstract
AbstractA short-term traffic prediction model VHSSA (prediction model based on vertical and horizontal sequence similarity algorithm) is proposed for accurate traffic prediction and dynamic route planning. The model is based on the similarity of vertical and horizontal sequences and analyzes historical traffic time series data and cyclic similarity characteristics of traffic volume in urban roads. The model can overcome the deficiency of the traditional model VSSA (prediction model based on vertical sequence similarity algorithm), which focuses only on vertical cyclic sequence similarity. Complete data are transformed into basic sequences that reflect basic characteristics and fluctuant sequences as well as variation characteristics by utilizing the wavelet transformation function. This transformation can achieve both basic and complete sequence prediction. For complete sequence prediction, the paper corrected the fluctuant sequence based on confidence interval and overlapped it with the basic sequence. V...
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Highway and Transportation Research and Development (English Edition)
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
