## 2 Related Works
### Modeling of Traffic Information  
Modeling refers to the process of creating a concise representation or abstraction of a complex system, phenomenon, or object in order to understand its behavior. Numerous objects (e.g., vehicles) existing in various traffic environments (e.g., road networks) generate a considerable amount of traffic data/information. By employing data/information modeling methods, traffic data/information are represented concisely so that users concerned with traffic sites can communicate with each other. Generally, conventional studies have primarily focused on traffic object modeling.  
Several studies have proposed traffic data/information models that can represent objects moving in road networks. [PERSON] et al. [33] suggested a semantic model to represent trajectories using the background geographic information and an algorithm to map vehicle positions onto a road network. Thus, trajectories were spatially modeled as networks comprising edges and nodes. [PERSON] and [PERSON] [34] designed a model that adopts a discrete view of the underlying space for moving objects. They partitioned the space into zones, each of them being uniquely identified by a label. Then, locations were represented by mapping them into zones. [PERSON] et al. [35] proposed a route-oriented model for moving objects in networks. In this technique, a road network is represented by using routes and junctions. Then, the represented road network, where a road's geometrical property is described by a line, integrates trajectories. Similar studies have been presented in the literature [36; 37].  
A traffic data/information model that focused on the objects moving in various environments (e.g., indoor and free space) has also been proposed. [PERSON] et al. [38] introduced a graph-based model employing radio frequency identification (RFID) for indoor tracking of moving objects. In this model, indoor space is separated into cells corresponding to graph vertices and movement of objects in cells is detected by RFID readers and is represented as edges in the graph. Notably, a trajectory consists of a sequence of RFID records, and a method for constructing and refining trajectories is developed. In a similar vein, the modeling structure for moving objects in a symbolic indoor space has been proposed in the literature [39]. The proposed model consists of records in a trajectory-based format (i.e., oid, symbolicID, and t), where oid represents the id of a moving object, symbolicID indicates a specific indoor space region, and t implies time. [PERSON] and [PERSON] [40] proposed a data model that can generally deal with the movement of objects in comprehensive traffic environments. In this model, generic moving objects, space, and infrastructure components are represented with the incorporation of precise/succinct transportation modes, such as cars, walks, and buses.  
Although these studies have contributed to the concise and effective modeling of various objects existing in traffic sites, these studies have only considered the information related to moving objects. As aforementioned, various challenges are expected because of the mixing of AVs and conventional vehicles. To facilitate the safety of vehicles and pedestrians, traffic control centers should collect and provide real-time and microscopic traffic information from moving objects (e.g., autonomous vehicles) and unmovable objects (e.g., traffic flow detectors and traffic lights) altogether. Thus, a data/information model that can represent various kinds of objects and attributes determined by the specific object, time and location should be designed that can be used by traffic control centers to ensure the safety of traffic sites. Table 1 presents a comparative overview of the proposed model with conventional models.