Modeling Speed Profile on Freeway Exit Ramps Using Support Vector Regression
Document Type
Conference Proceeding
Publication Date
2012
Digital Object Identifier (DOI)
https://doi.org/10.1061/9780784412442.069
Abstract
A speed profile, which is defined as the speed spatial distribution along a roadway facility, is a very important factor for assessing the geometric design, operations, and safety of a roadway facility. Because of the complicated lane change and deceleration maneuvers within freeway exit sections, the speed profile along a freeway exit ramp is a typical nonlinear function of ramp configuration, geometric design, traffic volume, and other factors. This study developed speed profile models for freeway exit ramps using Support Vector Regression (SVR), a novel statistical learning algorithm based on the structural risk minimization theory. Two SVR models, ε-SVR and v-SVR, were developed and tested in this study. Compared to traditional regression models, the SVR models can improve the prediction accuracy in terms of Mean Absolute Percentage Error (MAPE) and Mean Square Error (MSE) for predicting the speed profile along a freeway exit ramp.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
CICTP 2012 : Multimodal Transportation Systems—Convenient, Safe, Cost-Effective, Efficient, p. 671-682
Scholar Commons Citation
Huang, Bing; Wang, Zhenyu; Lu, Jian J.; and Lu, Linjun, "Modeling Speed Profile on Freeway Exit Ramps Using Support Vector Regression" (2012). CUTR Faculty Journal Publications. 130.
https://digitalcommons.usf.edu/cutr_facpub/130
