# Mitigating Urban Congestion: A Cooperative Reservation Framework for Automated Vehicles
## 6 Resource Optimization  
The previous approach relied on complete isolation between control areas represented by _Clusters_. While this procedure is safe, it is also impractical in reality because vehicles can access these areas concurrently. If an incoming vehicle obtains a _Cluster_, this resource is locked, forcing other vehicles to wait until the first vehicle leaves, making this system no better than a traffic light and decreasing its capabilities to dynamically assign efficiently managed resources.  
To improve the described implementation, a conflict zone optimization based on estimated arrival times (ETAs) is introduced. Hence, instead of blocking entire _Clusters_, smaller conflict zones within them are defined. Compatibility is now checked based on the specific _Tracking Node_ connected, not the entire _Cluster_. This approach, inspired by related work on conflict zones and time-based optimization, lays the foundation for a more dynamic system [50; 51; 52] that does not force a one-to-one relation with clusters and incoming connected cooperative automated vehicles (CCAV). However, for this optimization to take place, several changes to the previous methodology have to be made. First, the tracking process of the vehicle needs to be extended to not only give information about the _Cluster_ in use but also to provide computation-based information about its trajectory and position inside the _Cluster_. For that to happen, the HD Map module is crucial, since the position of the _Tracking Node_ reported by the connected vehicle will be periodically checked and matched against the Map and the _Cluster Control Areas_. This will give the system a dynamic waypoint to localize the vehicle that can be expressed in local, global, and Frenet coordinates for planning and time estimation. This waypoint will be used to construct a set of predictions based on the speed and control commands reported by the connected vehicle.  
In Figure 7, this interaction is depicted with three CCAVs approaching a four-way intersection. As can be seen, from the current location of the vehicle, a trajectory is constructed. This trajectory can be computed in several manners. Since this work does not take trajectory predictors into account and the vehicle is automated, the system assumes that the vehicle is going to follow its road plan. Hence, from the local position in map coordinates, a trajectory is constructed following the current cluster lane in which the vehicle reports are to be located. From that lane, the _Control Area_ length is retrieved, and with the speed the vehicle is reporting, the estimated time of arrival (ETA) is computed. Then, in the callback to select the cluster, instead of comparing _Clusters_, the algorithm compares nodes in such a way that to define compatibility, if two vehicles want to share the same conflict zone, a wall time is generated. On the one hand, if the differences between the ETAs of both _Tracking Nodes_ are less than the assigned wall time, then they are incompatible and cannot be in the same compatibility set. On the other hand, if the system computes the ETAs for both nodes and detects that there is enough time for both to not converge in the same conflict area in the same time window, both nodes are compatible and the entrance is allowed.  
Including this methodology within the implementation of the arbitration system, a highly flexible, on demand resource allocation is provided with the real-time processing of current traffic information. Therefore, the final system will make use of more dynamic parameters and constraints to improve the overall flow of the directives provided with the Entry/Exit behaviors.