UCT CS Research Document Archive

Autonomous Intersection Driving with Neuro-Evolution

Parker, Aashiq and Geoff Nitschke (2017) Autonomous Intersection Driving with Neuro-Evolution. In Proceedings Genetic and Evolutionary Computation Conference (GECCO 2017), pages 133-134, Berlin, Germany.

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Neuro-Evolution (NE) has been used to evolve controllers in land-based vehicles that accomplish various tasks. However, there has been little work on evolving coordinated movement for maximizing traffic flow through intersections. This study used NE to synthesize collective driving behaviors for given road networks (interconnected intersections), where there were no traffic signals to assist with vehicle coordination and navigation. Rather, NE automates controller design where collective driving behavior emerges in response to the task of maximizing traffic throughput and minimizing delays at intersections.

EPrint Type:Conference Poster
Subjects:I Computing Methodologies: I.2 ARTIFICIAL INTELLIGENCE
ID Code:1183
Deposited By:Nitschke, Geoff
Deposited On:23 November 2017