OAIDS: An Ontology-Based Framework for Building an Intelligent Urban Road Traffic Automatic Incident Detection System

Abstract

Handling interoperability of data exchange among road traffic sensor devices, connected vehicles, infrastructure components and heterogeneous traffic management center applications has become an important and basic requirement nowadays. To meet this requirement, this paper proposes an ontology based framework to capture the knowledge domain about traffic automatic incident detection system (AIDS) based on Connected Vehicles (CVs) technology. This ontology addresses the semantic data interoperability needed between different heterogeneous entities constituent this AIDS. This contribution aims at modeling and capturing the semantic of the anomaly information used in the incident detection process and describing the AIDS components, their observations, measurements and communications messages features. First, to achieve this goal, NeOn methodology was adopted. Then, we defined the basic concepts and observations of a traffic sensor and CVs that has been extended to define concepts related to the data sensing and gathering layer of this framework based on ontology concepts. In addition, to ensure data interoperability and identify ontology’s restrictions, we used the OWL (Web Ontology Language) language. Furthermore, to build this ontology, we used the OWL under Protégé tool. Finally, OAIDS consisted of 93 concepts and 33 object properties. OntoMetrics was used to confirm the effectiveness of this proposed ontology to carry out the interoperability of CV’s sensor data in the urban road AIDS domain.