Real-time Vehicle Detection for Highway Driving

B. Southall, M. Bansal, J. Eledath

Abstract

We present a new multi-stage algorithm for car and truck detection from a moving vehicle. The algorithm performs a search for pertinent features in three dimensions, guided by a ground plane and lane boundary estimation sub-system, and assembles these features into vehicle hypotheses. A number of classifiers are applied to the hypotheses in order to remove false detections. Quantitative analysis on real- world test data show a detection rate of 99.4% and a false positive rate of 1.77%; a result that compares favourably with other systems in the literature.