TY - GEN
T1 - Approximating the Transition Probability Function Corresponding to the Solution of Stochastic Optimal Velocity Dynamical Model
AU - Matin, Hossein Nick Zinat
AU - Sowers, Richard B.
N1 - Funding Information:
*This material is based upon work partially supported by the National Science Foundation under Grant No. CMMI 1727785. **Authors acknowledge the funding support by University of Illinois Campus Research Board Under project No. RB20017.
Publisher Copyright:
© 2021 American Automatic Control Council.
PY - 2021/5/25
Y1 - 2021/5/25
N2 - In this paper a stochastic optimal velocity dynamical model in considered. The probabilistic behavior of the solution of such dynamics can be explained by its transition density function. We investigate an explicit approximation of this transition function through an iterative method.
AB - In this paper a stochastic optimal velocity dynamical model in considered. The probabilistic behavior of the solution of such dynamics can be explained by its transition density function. We investigate an explicit approximation of this transition function through an iterative method.
UR - http://www.scopus.com/inward/record.url?scp=85111930632&partnerID=8YFLogxK
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U2 - 10.23919/ACC50511.2021.9483012
DO - 10.23919/ACC50511.2021.9483012
M3 - Conference contribution
AN - SCOPUS:85111930632
T3 - Proceedings of the American Control Conference
SP - 3326
EP - 3332
BT - 2021 American Control Conference, ACC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 American Control Conference, ACC 2021
Y2 - 25 May 2021 through 28 May 2021
ER -