Receding Horizon Stochastic Optimal Control Strategy for ACC and CACC under Uncertainty
This paper presents a receding horizon stochastic optimal control strategy for both Adaptive Cruise Control and Cooperative Adaptive Cruise Control under uncertainty based on the constant time headway policy. Specifically, uncertainties that can arise in vehicle control systems and vehicle sensor measurements are represented as normally-distributed disturbances to state and measurement equations in a state-space formulation. Then, acceleration sequence of a controlled vehicle is determined by optimizing an objective function that captures control efficiency and driving comfort over a predictive horizon, constrained by bounded acceleration/deceleration and collision protection. The optimization problem is formulated as a linearly constrained linear quadratic Gaussian problem and solved using a separation principle, Lagrangian relaxation, and Kalman filter. A sensitivity analysis and a scenario-based analysis via simulations demonstrate that the proposed control strategy can generate smoother vehicle control and perform better than a deterministic feedback controller, particularly under small system disturbances and large measurement disturbances.
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Supplemental Notes:
- This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics. Alternate title: Stochastic Optimal Control Strategy for ACC and CACC under Uncertainty.
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Corporate Authors:
500 Fifth Street, NW
Washington, DC United States 20001 -
Authors:
- Zhou, Yang
- Ahn, Soyoung
- Chitturi, Madhav
- Noyce, David A
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Conference:
- Transportation Research Board 96th Annual Meeting
- Location: Washington DC, United States
- Date: 2017-1-8 to 2017-1-12
- Date: 2017
Language
- English
Media Info
- Media Type: Digital/other
- Features: References;
- Pagination: 19p
- Monograph Title: TRB 96th Annual Meeting Compendium of Papers
Subject/Index Terms
- TRT Terms: Autonomous intelligent cruise control; Intelligent vehicles; Mobile communication systems; Optimization; Sensitivity analysis; Uncertainty
- Subject Areas: Highways; Operations and Traffic Management;
Filing Info
- Accession Number: 01627550
- Record Type: Publication
- Report/Paper Numbers: 17-02005
- Files: TRIS, TRB, ATRI
- Created Date: Feb 27 2017 5:12PM