Optimizing a start-stop controller using policy search

Journal Article

Copyright © 2014, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. We applied a policy search algorithm to the problem of optimizing a start-stop controller-a controller used in a car to turn off the vehicle's engine, and thus save energy, when the vehicle comes to a temporary halt. We were able to improve the existing policy by approximately 12% using real driver trace data. We also experimented with using multiple policies, and found that doing so could lead to a further 8% improvement if we could determine which policy to apply at each stop. The driver's behaviors before stopping were found to be un- correlated with the policy that performed best; however, further experimentation showed that the driver's behavior during the stop may be more useful, suggesting a useful direction for adding complexity to the underlying start-stop policy.

Duke Authors

Cited Authors

  • Hollingsworth, N; Meyer, J; McGee, R; Doering, J; Konidaris, G; Kaelbling, L

Published Date

  • January 1, 2014

Published In

  • Proceedings of the National Conference on Artificial Intelligence

Volume / Issue

  • 4 /

Start / End Page

  • 2984 - 2989

Citation Source

  • Scopus