Nonconvex, Fully Distributed Optimization based CAV Platooning Control under Nonlinear Vehicle Dynamics
Jinglai Shen, Eswar Kumar H. Kammara, Lili Du

TL;DR
This paper develops a fully distributed model predictive control scheme for CAV platooning considering nonlinear vehicle dynamics, addressing nonconvex optimization challenges and ensuring local input-to-state stability through advanced theoretical analysis.
Contribution
It introduces a novel sequential convex programming approach for distributed control of nonlinear CAV platoons, overcoming nonconvexity and coupling issues.
Findings
Effective real-time implementation demonstrated
Ensures local input-to-state stability
Works for heterogeneous vehicle platoons
Abstract
CAV platooning technology has received considerable attention in the past few years, driven by the next generation smart transportation systems. Unlike most of the existing platooning methods that focus on linear vehicle dynamics of CAVs, this paper considers nonlinear vehicle dynamics and develops fully distributed optimization based CAV platooning control schemes via the model predictive control (MPC) approach for a possibly heterogeneous CAV platoon. The nonlinear vehicle dynamics leads to several major difficulties in distributed algorithm development and control analysis and design. Specifically, the underlying MPC optimization problem is nonconvex and densely coupled. Further, the closed loop dynamics becomes a time-varying nonlinear system subject to external perturbations, making closed loop stability analysis rather complicated. To overcome these difficulties, we formulate the…
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Taxonomy
TopicsTraffic control and management · Vehicle Dynamics and Control Systems · Transportation Planning and Optimization
