A Hierarchical System Integration Approach with Application to Visual Scene Exploration for Driver Assistance

Abstract

A scene exploration which is quick and complete according to current task is the foundation for most higher scene processing. Many specialized approaches exist in the driver assistance domain (e.g. car recognition or lane marking detection), but we aim at an integrated system, combining several such techniques to achieve sufficient performance. In this work we present a novel approach to this integration problem. Algorithms are contained in hierarchically arranged layers with the main principle that the ordering is induced by the requirement that each layer depends only on the layers below. Thus, higher layers can be added to a running system (incremental composition) and shutdown or failure of higher layers leaves the system in an operational state, albeit with reduced functionality (graceful degradation). Assumptions, challenges and benefits when applying this approach to practical systems are discussed. We demonstrate our approach on an integrated system performing visual scene exploration on real-world data from a prototype vehicle. System performance is evaluated on two scene exploration completeness measures and shown to gracefully degrade as several layers are removed and to fully recover as these layers are restarted while the system is running.