Short-term Forecast for Average Speed of Road Section based on Floating Car Data with Support Vector Regression

Abstract

The recent intelligent transportation system has yielded remarkable progress on traffic data collection, resource allocation and intelligent programming. However, development on traffic real-time data processing and prediction still remains limited. In pursuit of real-time prediction on road section average speed, we introduced a prediction method, which mines GIS floating car data with support vector regression algorithm. The result indicated our proposed method was superior in comparison with other commonly used algorithms including linear regression, artificial neural network, Bayesian regression and ridge regression. Besides, the quick convergence and well fitting confirmed the plausibility of our method in this domain.