# Mitigating Urban Congestion: A Cooperative Reservation Framework for Automated Vehicles
## 2 Ecosystem Containers
### Vehicle Container  
The vehicle operates as an automated and connected platform with localization, control, navigation and decision-making capabilities. These skills are provided by a complete architecture of control in which different layers focus on assorted responsibilities [33]. These modules are implemented to supply most of the four capabilities needed for arbitration to happen during the collaboration:  
* **High-Definition Map module**: That is the _HD Map_ module, able to provide a stack for interaction with HD maps for automated driving [34, 35]. The module parses an ASAM Opendrive file [36] containing the complete road network for navigation and map localization. * **Planning module**: This is the _Waypoint Manager_, based on a tree structure search engine [37, 38, 39], and it is able to provide a high-level road plan to follow and localize the vehicle with respect to it. The module implements a search algorithm to localize the vehicle with respect to the plan, allowing the trajectory generation and path-following modules to work with sufficiently accurate information. * **Cooperative module**: This is the _Cooperation Manager_, which is able to process incoming and outgoing collaborative information. The module represents the basic layer of communication between connected containers, whether an intelligent infrastructure component or another connected vehicle. * **Mission module**: This is the _Mission Manager_[31], which is able to provide global and local behaviors based on contextual information, including requesting a connection to the infrastructure container. The _Mission Manager_ is responsible for managing the contextual awareness and the resulting behaviors, depending on the navigation profile. This is performed through the _Advanced Behavioral Point (ABP)_[31] concept, a strategic point distributed and integrated into the software architecture [33] of an automated vehicle control system using a mission system and a route plan. On the one hand, the contextual information mentioned above required by the _Mission Manager_ comes from the Traffic Scene notion described in the work [33], where all information related to the current traffic context is depicted. The representation of the context is based on the following components:  
* **Road Events**: Events generated by the vehicle navigation system to produce localization, planning, and map information for high-level movement commands. Used primarily for motion and path planning features. * **Perception Events**: Events generated from the perception system of the automated vehicle with perceptual information for cruise control, collision evasion and overtaking maneuvers. * **Cooperation Events**. Shared events with collaborative information, such as perceptual data coming from connected traffic agents' perceptual systems. * **Awareness Events**. Internal managed events with information about the system operating on the platform and its status. Primary source of anomaly detection. These items completely describe all dynamic and static elements for the vehicle to operate automatically on the road. On the other hand, the decision-making is implemented using behavior trees [40] deployed dynamically through the road plan with _Advanced_Behavioral Point (ABP)_[31]. These ABPs are a key component for the arbitration to work because they represent the information that is being interchanged between containers. These ABPs can be added, updated, and removed dynamically from the mission on demand, changing effectively the mission in real time depending on the context. There are three main components that define the ABP:  
* **ID**: An identifier that correlates the ABP with a behavior tree to load when chosen. This identifier is taken at runtime and used to find and load, from among those available in the database, the behavior tree that best fits the current situation. This database is designed to grow in complExity for more robust behaviors.