Traffic system improves flow of large vehicles in narrow industrial spaces
A traffic management system for large and heterogeneous vehicles in narrow industrial environments
RoboticsMultiagent Systems
Summary
Managing the movement of automated vehicles in busy and tight industrial areas is tricky because traditional methods slow things down. The authors created a new system that plans paths more efficiently using smart algorithms and smooth map curves, which works better even when vehicles are different sizes and share narrow roads. Their system can predict and avoid traffic jams and conflicts earlier than before, helping vehicles move safely without stopping for long. Tests showed this approach improved overall traffic flow by up to 11%, compared to older methods.
What this means in practice
- •For industrial automation teams: Coordinate large diverse automated vehicles in tight industrial layouts to prevent collisions and improve transport efficiency using adaptive conflict resolution.
- •For warehouse operations managers: Increase throughput in busy warehouses with narrow aisles by implementing a traffic system that manages mixed vehicle sizes safely and continuously.
Authors
Alessandro Bonetti, Silvia Proia, Simone Guidetti, Lorenzo Sabattini
Abstract
The coordination of Automated Guided Vehicles (AGVs) in high-density industrial environments represents a critical challenge within Logistics 4.0, as traditional traffic management methods often lead to inefficiencies caused by negotiation-based priority assignment. To overcome the resulting limitations, this paper presents an innovative AGV traffic management system based on a Lifelong Multi-Agent Path Finding (L-MAPF) algorithm operating on roadmaps generated with Non-Uniform Rational B-Splines (NURBS) curves. The approach guarantees locally optimal coordination and ensures safe operation of large and heterogeneous AGVs. Building on this concept, the proposed framework integrates a modified version of the Bounded Horizon Conflict Based Search (CBS) technique within a Rolling Horizon Conflict Resolution strategy, utilizing an extended time horizon for each agent to enable effective conflict resolution in corridors identified by a topological map. In contrast to state-of-the-art methods for AGV fleet traffic management, the proposed solution is designed for real-world, non-standardized (i.e., non-grid-like) industrial settings characterized by narrow bidirectional corridors and high-traffic density, where AGVs of various sizes and capabilities operate simultaneously. Key contributions include an anytime conflict resolution strategy with adaptive time horizon regulation, an execution layer for safe and standard-compliant interaction with real AGVs, and an advanced mechanism for deadlock detection and resolution. Experimental results obtained in realistic industrial environments demonstrate higher throughput, with improvements of up to 11% over a conventional rule-based traffic management system, a state-of-the-art industrial method, and a priority-based L-MAPF variant, while maintaining continuous operation and improved efficiency.