Decentralized On-Ramp Merging Control of Connected and Automated Vehicles in the Mixed Traffic Using Control Barrier Functions
Haoji Liu, Weichao Zhuang, Guodong Yin, Rongcan Li, Chang Liu,, Shanxing Zhou

TL;DR
This paper introduces a decentralized control framework using control barrier and Lyapunov functions for CAVs to safely and efficiently merge at highway on-ramps amidst mixed traffic, accounting for human-driven vehicle uncertainties.
Contribution
It develops a novel recursive control method that treats human-driven vehicles as disturbances and reformulates the merging problem into a real-time quadratic programming approach.
Findings
Robust merging control under HDV disturbances.
Improved traffic efficiency and energy savings.
Real-time applicability demonstrated through simulations.
Abstract
The cooperative control of the connected and automated vehicle (CAV) is recognized as an effective approach to alleviate traffic congestion and improve traffic safety, especially for on-ramp bottlenecks. However, in the mixed traffic, the uncertainty of human-driven vehicles (HDVs) makes the on-ramp merging control for CAVs more challenging. This paper proposes a decentralized optimal control method to address the merging control problem of CAVs at highway on-ramps in the mixed traffic. We first formulate the optimal merging control problem, which includes the constraints of safety and vehicle dynamics, with the objectives of minimizing travel time and energy consumption. Then, a control framework, combining control barrier functions (CBFs) and control Lyapunov functions (CLFs) is proposed. CBFs render the system subject to safety-critical constraints, while CLFs stabilize the system to…
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Taxonomy
TopicsTraffic control and management · Transportation Planning and Optimization · Autonomous Vehicle Technology and Safety
MethodsEmirates Airlines Office in Dubai
