# BIM-Based Description of Intelligent Transportation Systems for Roads
## 2 Knowledge Sources for Semantic Modeling of ITS
### ITS Applications  
Different implementation strategies and design requirements have led to a plethora of ITS applications, the second category of knowledge sources relevant to the semantic model. Designing frameworks that focus on traffic information generation and urban mobility demands has been frequently addressed in the past decade [42; 43]. Therefore, ITS applications are often solely regarded as traffic-related applications, such as traffic lights monitoring systems and public transportation control systems [44]. However, with the advent of vehicular clouds, cloud-based services and applications have been introduced [45].  
As for the variety of existing applications, many application categories have been proposed with respect to different aspects of ITS architecture. For example, regarding ITS communication networks, the European Telecommunications Standards Institute (ETSI) groups ITS applications into the categories cooperative traffic efficiency, active road safety, cooperative local services, and global Internet services [46]. Cooperative traffic efficiency aims at improving the traffic flow and is further categorized into speed management and cooperative navigation applications. Active road safety comprises driving assistance applications and warning scenarios, aiming to increase cooperative awareness to prevent hazardous situations. Cooperative local services include applications for location-based services, such as point-of-interest notifications and media downloading. Last, but not least, global Internet services comprise applications for community services and life-cycle management of ITS infrastructure, such as insurance and financial services and infrastructure software provisioning and update. In this study, a categorization of ITS applications is defined as follows:  
* _Traffic management_, granting optimized commutes and efficient mobility by reducing travel duration and fuel consumption, offers alternative routes in case of emergency and traffic flow control. Urban mobility controls, such as traffic lights control systems and public transportation control systems, are also included in this category.
* _Maintenance management_ comprises continuous monitoring and assessment of intelligent road infrastructure and road conditions using real-time data exchange. In-time alerting for detours in case of disasters or accidents, road services such as winter road maintenance, and structural damage detection and reconstruction process management are typical examples of applications in this category.
* _Telematics_, combining telecommunications and informatics, represent on-board applications that monitor the performance of vehicle on-board functional processes (\"intra-vehicle monitoring\") and provide driving assistance services. Autonomous driving is one of the most important applications in this category.
* _Infotainment_, merging information and entertainment, offers Internet-based services (such as online media platforms and on-demand information) to passengers for increasing the en route comfort.  
Figure 2: Vehicular cloud formations in ITS for roads.  
While emphasis is put on traffic management and maintenance management scenarios, the semantic model presented in this study must be able to describe all the above-mentioned application categories. Traffic efficiency and safety messages are prioritized to be included in the ITS semantics for roads. In the following subsection, ITS intelligent infrastructure, representing a crucial element when implementing ITS applications, is discussed.