Semantic Web Based Multi-agent Framework for Real-time Freeway Traffic Incident Management System

Recurring traffic congestion is attributable to steadily increasing travel demand coupled with constrained space and financial resources for infrastructure expansion. Another major source of congestion is non-recurrent incidents that disrupt the normal operation of the infrastructure. Aiming to optimize the utilization of the transportation infrastructure, innovative infrastructure management techniques that incorporate on edge technological equipment and information systems need to be adopted to manage recurrent and non-recurrent congestion and reduce their adverse externalities. The framework presented in this thesis lays the foundation for multi-disciplinary semantic web based incident management. During traffic incident response, involved stakeholders will share their knowledge and resources, forming an ad-hoc framework within which each party will focus on its core competencies and cooperate to achieve a coherent incident management process. Negotiation between various response agencies operators is performed using intelligent software agents, alleviating the coordination and synchronization burden of the massive information flow during the incident response. The software agents provide a decision support to human operators based on the reasoning provided from the underlying system knowledge models. Ontological engineering is used to lay the foundation of the knowledge models, which are coded in a web based ontology language, allowing a decentralized access to various elements of the system. The whole system communication infrastructure is based on the Semantic Web technologies. The semantic web facilitates the use of, in an enhanced manner, the already existing web technologies as the communication infrastructure of the proposed system. Its semantic capabilities help to resolve the information and data interoperability issues among various parties. The web services concepts combined with the semantic web allow the direct exploration and access of knowledge models, resources, and data repertories held by various parties. The developed ontology along with the developed software system were tested and evaluated by domain experts and targeted system users. Based on the conducted evaluation, both the ontology and the software system were found to be promising tools in developing pervasive, collaborative and multi-disciplinary traffic incident management systemsPh