This article presents a multiagent approach to managing autonomous vehicles at intersections. The authors argue that current traffic control methods, such as traffic lights and stop signs, are outdated and inefficient for autonomous vehicles. Instead, they propose a new mechanism where vehicles and intersections are treated as autonomous agents in a multiagent system. This system uses a reservation-based approach with a detailed communication protocol to coordinate vehicle movements through intersections. The mechanism can emulate traffic lights and stop signs, and it includes extensions to control human-driven vehicles and prioritize emergency vehicles. The system is implemented and tested in simulation, showing significant improvements in efficiency and safety compared to current methods. The authors also describe a failure mode analysis and discuss related work. The article concludes with future research directions. The proposed mechanism satisfies several desiderata, including autonomy, low communication complexity, sensor model realism, protocol standardization, deadlock/ starvation avoidance, incremental deployability, safety, and efficiency. The system uses a reservation idea where vehicles "call ahead" to reserve space-time in the intersection. The intersection manager decides whether to grant or reject reservations based on an intersection control policy. The system is implemented with a custom simulator and a communication protocol. The FCFS policy is introduced as a core contribution, enabling fine-grained coordination of vehicles at intersections and reducing delays. The policy uses an internal simulation to determine whether a reservation can be granted. The policy also includes modifications to handle acceleration in the intersection and reservation distance. The system is designed to be scalable, safe, and efficient, with the ability to handle both autonomous and human-driven vehicles. The authors conclude that this approach has the potential to significantly improve the safety and efficiency of roadways.This article presents a multiagent approach to managing autonomous vehicles at intersections. The authors argue that current traffic control methods, such as traffic lights and stop signs, are outdated and inefficient for autonomous vehicles. Instead, they propose a new mechanism where vehicles and intersections are treated as autonomous agents in a multiagent system. This system uses a reservation-based approach with a detailed communication protocol to coordinate vehicle movements through intersections. The mechanism can emulate traffic lights and stop signs, and it includes extensions to control human-driven vehicles and prioritize emergency vehicles. The system is implemented and tested in simulation, showing significant improvements in efficiency and safety compared to current methods. The authors also describe a failure mode analysis and discuss related work. The article concludes with future research directions. The proposed mechanism satisfies several desiderata, including autonomy, low communication complexity, sensor model realism, protocol standardization, deadlock/ starvation avoidance, incremental deployability, safety, and efficiency. The system uses a reservation idea where vehicles "call ahead" to reserve space-time in the intersection. The intersection manager decides whether to grant or reject reservations based on an intersection control policy. The system is implemented with a custom simulator and a communication protocol. The FCFS policy is introduced as a core contribution, enabling fine-grained coordination of vehicles at intersections and reducing delays. The policy uses an internal simulation to determine whether a reservation can be granted. The policy also includes modifications to handle acceleration in the intersection and reservation distance. The system is designed to be scalable, safe, and efficient, with the ability to handle both autonomous and human-driven vehicles. The authors conclude that this approach has the potential to significantly improve the safety and efficiency of roadways.