Ontology for human factor and its influence to support decision-making in route planning

Abstract

Autonomous vehicles (AVs) have become one of the most transformative innovations in modern transportation, generating widespread interest among researchers, industry stakeholders, and policymakers. Both automotive and non-automotive companies around the world have been investing substantial resources in advancing the research and development of autonomous driving systems (ADSs).

This thesis aims to develop an ontology that represents the relationship between human factors and their influence on route planning while considering various route attributes. The ontology is designed to support route planning in the context of Hybrid Intelligence-Autonomous Driving System (HI-ADS).

A thorough review of prior research and experiments related to human factors and decision-making in driving scenarios was conducted to provide a solid foundation for the ontology’s development. The ontology was constructed using the Design Science Research (DSR) methodology and the ontology is based on OWL and was developed using the Protégé tool.

A use-case scenario was presented to demonstrate that the ontology is applicable in real-world scenario. The ontology was evaluated based on logical consistency, clarity, extendibility and practicality. The result indicates that the developed ontology is thus logical and can support decision-making in route planning. However, further research is necessary to validate its real-world applicability and reasoning capabilities.