Developing an Ontology-Based Rollover Monitoring and Decision Support System for Engineering Vehicles

The increasing number of rollover accidents of engineering vehicles has attracted close attention; however, most researchers focus on the analysis and monitoring of rollover stability indexes and seldom the assessment and decision support for the rollover risk of engineering vehicles. In this context, an ontology-based rollover monitoring and decision support system for engineering vehicles is proposed. The ontology model is built for representing monitored rollover stability data with semantic properties and for constructing semantic relevance among the various concepts involved in the rollover domain. On the basis of this, ontology querying and reasoning methods based on the Simple Protocol and RDF Query Language (SPARQL) and Semantic Web Rule Language (SWRL) rules are utilized to realize the rollover risk assessment and to obtain suggested measures. PC and mobile applications (APPs) have also been developed to implement the above methods. In addition, five sets of rollover stability data for an articulated off-road engineering vehicle under different working conditions were analyzed to verify the accuracy and effectiveness of the proposed system.