VRU Safety at Road Intersections: An Ontology-Driven Digital Twin

Although the role of optimization in transportation systems is widely recognized as key to future sustainable development, alarming statistics related to accidents and deaths continue to be overlooked. Among the various components of road networks, road intersections pose the greatest safety challenges for smart and human cities. Digital twins (DT) have emerged as a promising alternative to assist intelligent transportation system (ITS) decision-makers in recent years. However, a critical component is still lacking in developing DTs for ITS: a robust information modeling framework that effectively integrates the physical world with cyberspace in these intricate and dynamic environments. Furthermore, the current emphasis on the efficiency of ITS solutions often overshadows pressing safety concerns for vulnerable road users (VRUs). This paper tackles the challenge of modeling transportation scenarios to enhance VRU safety, focusing on a crucial element: a road intersection, in particular, the semantic issues of such elements when addressing VRU safety. For the first time, we propose an ontology-based information modeling method for road intersections using recent advancements from market-driven, regulatory, and standardization bodies. It specifies the information classification, content to be modeled, and modeling methodology. Nevertheless, inexpensive, swift, and friendly prototyping remains a bottleneck for innovation in this area. Practitioners currently require more means and methods to realize ontology-based DTs for ITS. Another contribution is to provide information model instantiation, visualization, and simulation, as well as fully based open-source tools, as a case study.