# Mitigating Urban Congestion: A Cooperative Reservation Framework for Automated Vehicles
## 1 Introduction
However, excessive haptic cues can disrupt the driver, leading to overcorrection and degraded driving performance [15]. Effective implementation requires human-machine interfaces capable of accurately predicting driver state. On the other hand, the introduction of traffic lights has significantly improved junction traffic performance by automatically controlling intersection entries. However, because they cannot dynamically adjust to the actual vehicle traffic, traffic lights appear to be less effective when there is a high demand over the network. The reason why this happens is primarily because the technology does not have the capabilities of adapting dynamically to the current traffic demand and acting in accordance with the context. To cope with this limitation, several approaches have been made, such as Virtual or optimized Traffic Signals [16; 17], multiagent coordination [18], and intelligent reservation control [19]. While the first option provides a fast solution to the problem, there is still the issue of agent coordination and distributed collaboration. In that sense, intersection management based on resource allocation has the potential of benefiting from the opportunities offered by Connected Cooperative Autonomous Mobility, possibly coping with current challenges in critical traffic emplacements [20] such as four-way intersections or roundabouts [21]. The allocation of resources for arbitration within traffic management is not a recent innovation and has been subject to considerable discourse regarding its efficacy relative to classical policies [22]. Previously related work, for instance, explored the same notion in common intersections, with the difference that the execution of the arbitration itself was assumed from a simulation instance, which has full control over its actors and lacks a reliable and realistic approach where the control operates instantaneously [23]. Hence, the proposed models operate over a simplified traffic network whose structure was extracted from real-world information but with a simulated demand of traffic managed by a constant ubiquitous omnipotent hypervisor that knows everything at any moment, globally. Therefore, despite ongoing optimizations implemented with these tools, as seen in [24; 25], there is insufficient effort dedicated to developing a framework for validating these advancements under more realistic scenarios. This work presents an approach to complex traffic emplacement arbitration based on behavior collaboration between traffic agents, together with a framework focused on cooperation implemented with ROS [26] and Carla [27] based on multi-agent simulation [28]. The proposed framework implements a distributed control architecture onboard each automated vehicle, enabling the centralized arbitration of resource reservation requests by evaluating individual vehicle intent and relative proximity. The notion of arbitration here is defined as the number of resources from the traffic emplacement that can be allocated in real time, providing a tool to select which vehicle is going to use that resource and which one should wait for it. The proposal is based on the presented idea of automated intersection management [29]. This solution assumes all vehicles are connected and automated, allowing them to provide collaboration capabilities but also automated behaviors for navigation and planning [30; 31; 32]. The main goal for these tools is to allocate the maximum slots of resources at a time state potentially improving the flow of traffic and allowing to select resources based on different parameters such as the priority, the number of vehicles waiting or a time limit for a specific resource. In this proposal, the basic foundation for the testing and validation of intersection management algorithms is presented. This solution provides a stack for behavior collaboration between distributed components that operate as standalone containers within the same network but with an independent software control architecture.