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The main goal when operating a vehicle is to safely participate in road-traffic while minimising the adverse effects on our environment. This goal is pursued by road safety measures ranging from safety-oriented road design to driver assistance systems. The latter require exteroceptive sensors to acquire information about the vehicle‘s current environment. In this thesis an efficient resource allocation algorithm for automotive vision systems is proposed. The novel system architecture is shown to efficiently allocate both high-resolution sensor resources and computational expensive processes…mehr

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Produktbeschreibung
The main goal when operating a vehicle is to safely participate in road-traffic while minimising the adverse effects on our environment. This goal is pursued by road safety measures ranging from safety-oriented road design to driver assistance systems. The latter require exteroceptive sensors to acquire information about the vehicle‘s current environment. In this thesis an efficient resource allocation algorithm for automotive vision systems is proposed. The novel system architecture is shown to efficiently allocate both high-resolution sensor resources and computational expensive processes based upon low-resolution sensor data. The Pareto efficient decision making process used for resource allocation is formalised, implemented, and evaluated using road traffic test sequences acquired by a multi-modal sensor system on a test vehicle provided by AUDI AG.

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