A platoon-based cooperative optimal control for connected autonomous vehicles at highway on-ramps under heavy traffic
Artikel i vetenskaplig tidskrift, 2023

To improve traffic efficiency at highway on-ramps under heavy traffic, this study proposes a platoon-based cooperative optimal control algorithm for connected autonomous vehicles (CAVs). The proposed algorithm classifies CAVs on both mainline and on-ramp into multiple local platoons (LPs) according to their initial conditions (i.e., spacing and speed), which enables the algorithm to adapt to time-varying traffic volume. A distributed cooperative control for multiple LPs is designed which projects on-ramp LPs onto mainline to transform the complex 2-D multi-platoon cooperation problem into a 1-D platoon following control problem. An optimal control is applied to further consider the strict nonlinear safety spacing constraint and state limitations (e.g., maximum speed and acceleration), and an analytical solution to the optimal control is derived based on Pontryagin's maximum principle. The consensus of intra-platoon and inter-platoon are analyzed, and sufficient conditions of the consensus are mathematically deducted based on Lyapunov stability theorem. Numerical simulations are conducted for different traffic demand levels and demand splits to verify the effectiveness of the proposed algorithm. The sensitivity analysis of maximum platoon sizes for mainline and on-ramp LPs is performed. A comparison with a baseline virtual platooning merging strategy is conducted, and results show that the proposed algorithm could significantly improve the average travel speed and traffic efficiency, and reduce total travel time.

Connected autonomous vehicles

Merging control

Highway on-ramps

Virtual platooning


Yongjie Xue

Beihang University

Xiaokai Zhang

Dalian University of Technology

Zhiyong Cui

Beihang University

Bin Yu

Beihang University

Kun Gao

Chalmers, Arkitektur och samhällsbyggnadsteknik, Geologi och geoteknik

Transportation Research, Part C: Emerging Technologies

0968-090X (ISSN)

Vol. 150 104083







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