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http://dx.doi.org/10.22680/kasa2022.14.4.035

Stochastic Model Predictive Control for Stop Maneuver of Autonomous Vehicles under Perception Uncertainty  

Sangyoon, Kim (서울대학교 기계항공공학부)
Ara, Jo (서울대학교 기계항공공학부)
Kyongsu, Yi (서울대학교 기계항공공학부)
Publication Information
Journal of Auto-vehicle Safety Association / v.14, no.4, 2022 , pp. 35-42 More about this Journal
Abstract
This paper presents a stochastic model predictive control (SMPC) for stop maneuver of autonomous vehicles considering perception uncertainty of stopped vehicle. The vehicle longitudinal motion should achieve both driving comfortability and safety. The comfortable stop maneuver can be performed by mimicking acceleration profile of human driving pattern. In order to implement human-like stop motion, we propose a reference safe inter-distance and velocity model for the longitudinal control system. The SMPC is used to track the reference model which contains the position uncertainty of preceding vehicle as a chance constraint. We conduct simulation studies of deceleration scenarios against stopped vehicle in urban environment. The test results show that proposed SMPC can execute comfortable stop maneuver and guarantee safety simultaneously.
Keywords
Stochastic Model Predictive Control; Stop Maneuver; Perception Uncertainty;
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