Evolving Vehicle Warning Systems (2006)
Author: Nate Kohl
Many serious automobile accidents could be avoided if drivers were warned of impending crashes before they occur. Creating such warning systems by hand, however, is a difficult and time-consuming task. The goal of this project is to evolve neural networks with NEAT (NeuroEvolution of Augmenting Topologies) to warn about such crashes in real-world environments.

Demo Page
Nate Kohl Ph.D. Alumni nate [at] natekohl net
Kenneth Stanley Postdoctoral Alumni kstanley [at] cs ucf edu
Risto Miikkulainen Faculty risto [at] cs utexas edu
Rini Sherony Former Collaborator rini sherony [at] tema toyota com
Evolving a Real-World Vehicle Warning System Nate Kohl, Kenneth Stanley, Risto Miikkulainen, Michael Samples, and Rini Sherony In Proceedings of the Genetic and Evolutionary Computation Conference, 2006. 2006

Neuroevolution of an Automobile Crash Warning System Kenneth Stanley, Nate Kohl, Rini Sherony, and Risto Miikkulainen In Proceedings of the Genetic and Evolutionary Computation Conference, 2005. 2005

IJCNN-2013 Tutorial on Evolution of Neural Networks Risto Miikkulainen To Appear In 2013. Tutorial slides.. 2013

Neuroevolution: Harnessing Creativity in AI Model Design Sebastian Risi, David Ha, Yujin Tang, Risto Miikkulainen To Appear In , Cambridge, MA, 2025. MIT Press. 2025

NEAT C++ The NEAT package contains source code implementing the NeuroEvolution of Augmenting Topologies method. The source code i... 2010