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Synthesizing voluntary lane-change policy using control improvisation

Ge, Jin I. and Murray, Richard M. (2019) Synthesizing voluntary lane-change policy using control improvisation. IFAC-PapersOnLine, 51 (34). pp. 396-399. ISSN 2405-8963.

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In this work, we propose control improvisation to synthesize voluntary lane-change policy that meets human preferences under given traffic environments. We first train Markov models to describe the lane-change environment for an automated vehicle under assumed traffic patterns. Parameters in the environment model are trained using traffic data and calibrated using control improvisation. Then, based on human lane-change behavior, we train a voluntary lane-change policy using explicit-duration Markov decision process. Parameters in the lane-change policy are calibrated through control improvisation to allow an automated car to voluntarily change lanes while avoiding overly frequent lane-change maneuvers under various traffic environments.

Item Type:Article
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Murray, Richard M.0000-0002-5785-7481
Additional Information:© 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. Available online 8 February 2019. This work is supported by NSF VeHiCal project 1545126.
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Subject Keywords:voluntary lane-changing, control improvisation, human car-following behavior
Record Number:CaltechAUTHORS:20190228-112317657
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Official Citation:Jin I. Ge, Richard M. Murray, Synthesizing voluntary lane-change policy using control improvisation⁎⁎This work is supported by NSF VeHiCal project 1545126., IFAC-PapersOnLine, Volume 51, Issue 34, 2019, Pages 396-399, ISSN 2405-8963, (
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:93339
Deposited By: Tony Diaz
Deposited On:28 Feb 2019 19:45
Last Modified:28 Feb 2019 19:45

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