Sequencing-enabled Hierarchical Cooperative CAV On-ramp Merging Control with Enhanced Stability and Feasibility
Sixu Li, Yang Zhou, Xinyue Ye, Jiwan Jiang, Meng Wang

TL;DR
This paper presents a hierarchical control framework for connected automated vehicle (CAV) on-ramp merging that improves traffic stability, safety, and efficiency through sequencing, mixed-integer programming, and distributed model predictive control.
Contribution
It introduces a novel two-layer hierarchical control framework with enhanced stability and feasibility, including a new distributed MPC and auxiliary lateral control for smooth merging.
Findings
Outperforms distance-based sequencing in simulations
Ensures asymptotic local stability and string stability
Achieves smooth acceleration and safe merging
Abstract
This paper develops a sequencing-enabled hierarchical connected automated vehicle (CAV) cooperative on-ramp merging control framework. The proposed framework consists of a two-layer design: the upper level control sequences the vehicles to harmonize the traffic density across mainline and on-ramp segments while enhancing lower-level control efficiency through a mixed-integer linear programming formulation. Subsequently, the lower-level control employs a longitudinal distributed model predictive control (MPC) supplemented by a virtual car-following (CF) concept to ensure asymptotic local stability, l_2 norm string stability, and safety. Proofs of asymptotic local stability and l_2 norm string stability are mathematically derived. Compared to other prevalent asymptotic local-stable MPC controllers, the proposed distributed MPC controller greatly expands the initial feasible set.…
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Taxonomy
TopicsTraffic control and management · Vehicle Dynamics and Control Systems · Vehicle emissions and performance
