An integrated obstacle detection framework for intelligent cruise control on motorways

This paper deals with the development and implementation of a purely visual obstacle detection framework for autonomous driving on motorways. Our activities are embedded in the SMART VEHICLE subproject of the ESPRIT project CLEOPATRA. The aim of SMART VEHICLE is the development of a visually controlled intelligent cruise control (ICC) for a prototype passenger car, the Mercedes-Benz research car VITA II. The vision modules are operating concurrently on a net of digital signal processors with multiple video inputs. Our obstacle detection framework bases on the application of highly adapted machine-vision elements such as robust symmetry measuring, neural net-based adaptive object recognition, real-time tracking of multiple vehicles, and inverse-perspective stereo image matching (IPM). We will show detailed results from extensive closed-loop autonomous driving on public motorways and we will present the final HPC hardware system which is part of the application computer of VITA II.