Distributed Platoon Control for Safe and Smooth Crossing at an Unsignalized Intersection-Part I: Stability Analysis

Bin-Bin Hu; Shuwei Pei; Saeed Ahmed; Bayu Jayawardhana

eess.SYOct 20, 2026

Distributed Platoon Control for Safe and Smooth Crossing at an Unsignalized Intersection-Part I: Stability Analysis

Authors: Bin-Bin Hu, Shuwei Pei, Saeed Ahmed, Bayu Jayawardhana

Organizations: Engineering and Technology Institute Groningen, University of Groningen, 9747 AG Groningen, The Netherlands

Abstract

We propose a distributed platoon controller that guarantees safe and smooth crossing of multi-vehicle systems at an unsignalized intersection. To support the stability analysis, we consider a multi-vehicle platoon maneuvering along a closed path with a single unsignalized intersection. Unlike traditional bi-level decoupled designs on open paths, which primarily focus on intersection control while neglecting its coupling with platoon convergence, and thus hindering rigorous convergence analysis, the closed-path setting allows us to analyze the asymptotic behavior of the platoon. The local exponential convergence analysis of the switched closed-loop system, induced by repeated vehicle switching at the intersection, is presented. Under some mild conditions on the controller gains, we show that safe intersection crossing is ensured during the transient phase and smooth crossing is achieved in steady state, where all vehicles travel at a common constant speed while avoiding collisions at the intersection. Finally, the effectiveness of the proposed distributed controller is demonstrated in a high-fidelity CARLA simulator using multiple commercial vehicle models.

Figures & tables

Fig. 1: Different types of single-intersection closed paths under the interpretation of ( 1 ) and ( 2 ). (a) The eight-shape path with a single intersection at the center point in 2D. (b) The path with a single intersection at the center point in 3D. (c) Random urban path with a single intersection.

Fig. 2: (a) Illustration of the vehicle platoon on a figure-eight road with an intersection in Fig. 1 . (b) The corresponding displacements in the phase space. The brown and blue vehicles in (a) represent vehicles that are ready to enter the intersection. The red point denotes the intersection.

Fig. 3: Illustration of the periodic switching sequences in ( 22 ), where vehicles from the two sides of the intersection pass through alternately.

Fig. 4: Safe- and smooth-crossing platoon on figure-eight path in CARLA. (a) Initial states. (b) Safe- and smooth-crossing platoon. (c) Error $e_{i}$ and phase velocity $\dot{\theta}_{i}$ . (d) Adjacent phase error $\theta_{i+1}-\theta_{i}$ and switching distance $|d_{j,k}|$ at the intersection.

Fig. 5: Validation on random urban paths with an intersection in CARLA. (a) Initial states. (b) Safe- and smooth-crossing platoon.

Distributed Control

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Jul 23, 2026Gil Lifshits, Igal Bilik, Gilad KatzMulti-Agent Coordination Hierarchical RL
Ben-Gurion University of the Negev

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Decentralized Opinion-Integrated Decision making at Unsignalized Intersections via Signed Networks

Bhaskar Varma, Ying Shuai Quan, Karl D. von Ellenrieder, Paolo Falcone

Faculty of Engineering, Free University of Bozen-Bolzano, Italy · Mechatronics Group, Department of Electrical Engineering, Chalmers University of Technology, Gothenburg, Sweden

Multi-Agent Coordination Intelligent Transportation Systems Autonomous Driving Opinion Dynamics

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In this letter, we consider the problem of decentralized decision making among connected autonomous vehicles at unsignalized intersections, where existing centralized approaches do not scale gracefully under mixed maneuver intentions and coordinator failure. We propose a closed-loop opinion-dynamic decision model for intersection coordination, where vehicles exchange intent through dual signed networks: a conflict topology based communication network and a commitment-driven belief network that enable cooperation without a centralized coordinator. Continuous opinion states modulate velocity optimizer weights prior to commitment; a closed-form predictive feasibility gate then freezes each vehicle's decision into a GO or YIELD commitment, which propagates back through the belief network to pre-condition neighbor behavior ahead of physical conflicts. Crossing order emerges from geometric feasibility and arrival priority without the use of joint optimization or a solver. The approach is validated across three scenarios spanning fully competitive, merge, and mixed conflict topologies. The results demonstrate collision-free coordination and lower last-vehicle exit times compared to first come first served (FCFS) in all conflict non-trivial configurations.

Abstract

Distributed Control

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