A Survey on the Coordination of Connected and Automated Vehicles at Intersections and Merging at Highway On-Ramps

Rios-Torres, Jackeline; Malikopoulos, Andreas A. · 2016 · OpenAlex-citations

DOI: 10.1109/tits.2016.2600504

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Summary

This 2016 survey paper by Rios-Torres and Malikopoulos reviews the state of research regarding the coordination of Connected and Automated Vehicles (CAVs) at intersections and highway on-ramps. The study is motivated by the significant economic and environmental costs of traffic congestion, which resulted in billions of hours of delay and increased fuel consumption, alongside safety concerns including millions of injuries and fatalities annually. The authors aim to summarize existing literature on how CAVs, utilizing vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, can optimize traffic flow, reduce emissions, and improve safety by coordinating maneuvers without traditional traffic lights or stop signs. The paper categorizes existing coordination strategies into two primary frameworks: centralized and decentralized approaches. In centralized systems, a single controller makes global decisions for all vehicles, whereas decentralized systems treat vehicles as autonomous agents that optimize their own performance through strategic interaction. The authors formulate the general problem for both intersections and merging zones, defining a control zone where vehicles communicate and a merging zone where collisions must be avoided. The review organizes the literature chronologically and by control scheme, detailing specific methodologies such as heuristic rules, optimization techniques, and control theories. Regarding centralized approaches, the survey highlights reservation schemes where vehicles request time-space cells to cross intersections, a method pioneered by Dresner and Stone and later extended to include priority assignments and environmental metrics. Other heuristics include two-level control systems that manage traffic density and platoon-based controls that coordinate groups of vehicles. Optimization approaches focus on minimizing travel time, reducing vehicle overlap within the intersection, or employing multi-objective functions that balance speed tracking, acceleration smoothness, and collision risk. Techniques such as Dynamic Programming, Model Predictive Control, and queuing theory are discussed as methods to solve these optimization problems. For merging scenarios, the paper reviews linear optimal regulators and sliding mode control strategies designed to minimize speed errors and ensure safe headways. The significance of this work lies in its comprehensive synthesis of the theoretical foundations for CAV coordination, identifying key challenges such as communication requirements, deadlock prevention, and computational complexity. By reviewing these diverse approaches, the paper establishes a baseline for understanding how automated coordination can alleviate congestion and improve transportation efficiency. It also highlights gaps in current research, suggesting future directions for addressing unanswered questions in the field of cooperative driving and sustainable transportation technologies.

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• v2x connected vehicle