Control Concepts for Facilitating Motorway On-ramp Merging Using Intelligent Vehicles

Scarinci, Riccardo; Heydecker, Benjamin · 2014 · OpenAlex-citations

DOI: 10.1080/01441647.2014.983210

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Summary

This paper addresses the persistent problem of congestion at motorway on-ramps, a phenomenon that degrades infrastructure operation and reduces traffic capacity. While traditional solutions focused on physical infrastructure improvements or ramp metering, recent advancements in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication have enabled Cooperative Intelligent Transport Systems (CITS). The authors aim to review control strategies that utilize intelligent vehicles to facilitate the merging process, a specific area lacking comprehensive prior review. The study excludes systems aimed solely at preventing congestion (like ramp metering) or increasing string stability, focusing instead on algorithms that actively assist the merging maneuver. The methodology involves a chronological review of control strategies categorized by the type of intelligent vehicle employed: completely automated vehicles, vehicles equipped with Cooperative Adaptive Cruise Control (CACC), and vehicles with on-board displays. The authors establish a common terminology for the merging process, defining components such as the near-side lane, merging section, and vehicle formations (strings, platoons, and groups). They further classify algorithms by their control scope (longitudinal vs. lateral), target (individual, string, or group), and architecture (centralized vs. decentralized). The review synthesizes concepts from numerous studies, identifying similarities, dissimilarities, and trends in both control strategies and the evaluation methods used, such as microscopic simulation and test track experiments. The findings reveal distinct approaches based on vehicle technology. For completely automated vehicles, early studies linked to automated guideway transit evolved into strategies for mixed traffic, often using centralized control to manage longitudinal and lateral movements. CACC-equipped vehicles typically utilize decentralized algorithms where vehicles exchange information within their communication range to coordinate merging, often forming platoons to create gaps. Vehicles with on-board displays rely on infrastructure-provided advice to drivers, representing a less intrusive form of control. The review highlights that while many algorithms exist, there is no single dominant approach; rather, strategies vary significantly in how they handle mixed traffic penetration rates and whether they prioritize main carriageway flow or on-ramp efficiency. The significance of this work lies in its systematic classification of merging control strategies, providing a clear framework for understanding the evolution of CITS applications in traffic management. By identifying common structures and evaluation methods, the paper highlights critical aspects for future research, such as the need for standardized evaluation metrics and the challenges of integrating intelligent vehicles into mixed traffic environments. The authors conclude that while V2V and V2I technologies offer promising solutions for mitigating merge-related congestion, further research is required to optimize these strategies for real-world deployment and to determine the most effective control architectures for varying traffic conditions.

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• traffic density