<p>This thesis project was carried out at Volvo Car Corporation. It is based on an EU project called Locust in which a bio-inspired visual sensor system (the Locust sensor system) for automotive collision avoidance was developed. The Locust sensor system is designed to emulate the collision avoidance functionality of the Locust grasshopper, which is well-known for its extraordinary vision based collision avoidance ability, in particular with regard to its fast reaction times to perceived threats. Volvo Car Corporation is interested in the possibility of using the bio-inspired technology developed in the Locust project to improve its already existing collision avoidance systems. Pedestrian collision avoidance is of high interest, for which the properties of the Locust grasshopper are desirable.</p><p>The purpose of this thesis project is to develop two demonstrator vehicles to test the performance of the Locust sensor system, carry out the testing, and evaluate its usability for Volvo Car Corporation. The first vehicle is a scale 1:5 model car that was originally developed in a thesis project at KTH, and the second a full scale Volvo XC90.</p><p>It was found in the testing that the Locust sensor system is promising for pedestrian collision avoidance applications. The results for detecting other vehicles were also acceptable, but Volvo Car Corporation already has other collision avoidance systems with better performance in this regard. In general the test results were very good for speeds up to about 40 km/h. This indicates that the Locust sensor system would be most usable in a city driving environment, parking lot situations, and for driving in residential areas.</p>
| Identifer | oai:union.ndltd.org:UPSALLA/oai:DiVA.org:liu-8252 |
| Date | January 2007 |
| Creators | wei, Jonny, Palmebäck, Pär |
| Publisher | Linköping University, Department of Electrical Engineering, Linköping University, Department of Electrical Engineering, Institutionen för systemteknik |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, text |
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