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Evolving a Real-World Vehicle Warning System (2006)
Nate Kohl
,
Kenneth Stanley
,
Risto Miikkulainen
, Michael Samples, and
Rini Sherony
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. This paper describes three advances toward evolving neural networks with NEAT (NeuroEvolution of Augmenting Topologies) to warn about such crashes in real-world environments. First, NEAT was evaluated in a complex, dynamic simulation with other cars, where it outperformed three hand-coded strawman warning policies and generated warning levels comparable with those of an open-road warning system. Second, warning networks were trained using raw pixel data from a simulated camera. Surprisingly, NEAT was able to generate warning networks that performed similarly to those trained with higher-level input and still outperformed the baseline hand-coded warning policies. Third, the NEAT approach was evaluated in the real world using a robotic vehicle testbed. Despite noisy and ambiguous sensor data, NEAT successfully evolved warning networks using both laser rangefinders and visual sensors. The results in this paper set the stage for developing warning networks for real-world traffic, which may someday save lives in real vehicles.
View:
PDF
Citation:
In
Proceedings of the Genetic and Evolutionary Computation Conference
, 2006.
Bibtex:
@InProceedings{kohl:gecco06, title={Evolving a Real-World Vehicle Warning System}, author={Nate Kohl and Kenneth Stanley and Risto Miikkulainen and Michael Samples and Rini Sherony}, booktitle={Proceedings of the Genetic and Evolutionary Computation Conference}, url="http://nn.cs.utexas.edu/?kohl:gecco06", year={2006} }
People
Nate Kohl
Ph.D. Alumni
nate [at] natekohl net
Risto Miikkulainen
Faculty
risto [at] cs utexas edu
Rini Sherony
Former Collaborator
rini sherony [at] tema toyota com
Kenneth Stanley
Postdoctoral Alumni
kstanley [at] cs ucf edu
Projects
NEAT: Evolving Vehicle Warning Systems
2004 - 2006
Demos
Evolving Vehicle Warning Systems
Nate Kohl
2006
Software/Data
NEAT C++
The NEAT package contains source code implementing the NeuroEvolution of Augmenting Topologies method. The source code i...
2010
Areas of Interest
Neuroevolution