Pavement boundary detection via circular shape models

Abstract

Automated detection of pavement boundaries is an important enabling technology in intelligent vehicle applications. This paper describes a circular shape model for detecting pavement boundaries and shows that the circular shape models enjoy several critical advantages over the polynomial models without any additional increase in model complexity including: the model parameters are all of the same units, even a small change to any one parameter results in a uniformly different shape appearance; and as a result the associated shape matching problem is considerably better conditioned than the corresponding problem with polynomial shape models. Our application domain is one of road/pavement boundary estimation based on image data from a high-resolution multibeam 77 GHz millimeter-wave radar. A successful solution to this problem has impact on a number of driver assistance systems, such as road departure warning, forward collision warning, etc.