3 research outputs found
ADVANCED PERSONALIZATION OF LOCATION BASED SERVICES
This article explores possible solutions for improving Location Based Services (LBS). For the purpose of this paper context, user profile, previous choices and the choice profiles of similar users are aspects taken into consideration. A possible implementation of an LBS system, in the form of a public transport route finding application based on genetic algorithms is also presented. The proposed application uses semantic tagging to integrate data from multiple sources and sensors into a single interpretation.Knowledge Management, Geographic Information Systems, Location-based Services, Semantic Web
Utilising Semantic Web Technologies for Improved Road Network Information Exchange
Road asset data harmonisation is a challenge for the Australian road and transport authorities considering their heterogeneous data standards, data formats and tools. Classic data harmonisation techniques require huge databases with many tables, a unified metadata definition and standardised tools to share data with others. In order to find a better way to harmonise heterogeneous road network data, this dissertation uses Semantic Web technologies to investigate fast and efficient road asset data harmonisation
Towards intelligent transport systems: geospatial ontological framework and agent simulation
In an Intelligent Transport System (ITS) environment, the communication component is of high
significance as it supports interactions between vehicles and the roadside infrastructure.
Existing studies focus on the physical capability and capacity of the communication
technologies, but the equally important development of suitable and efficient semantic content
for transmission has received notably less attention. Using an ontology is one promising
approach for context modelling in ubiquitous computing environments. In the transport domain,
an ontology can be used both for context modelling and semantic contents for vehicular
communications. This research explores the development of an ontological framework
implementing a geosemantic messaging model to support vehicle-to-vehicle communications.
To develop an ontology model, two scenarios (an ambulance situation and a breakdown on the
motorway) are constructed to describe specific situations using short-range communication in
an ITS environment. In the scenarios, spatiotemporal relations and semantic relations among
vehicles and road facilities are extracted and defined as classes, objects, and properties/relations
in the ontology model. For the ontology model, some functions and query templates are also
developed to update vehicles’ movements and to provide some logical procedures that vehicles
need to follow in emergency situations. To measure the effects of the vehicular communication
based on the ontology model, an agent-based approach is adopted to dynamically simulate the
moving vehicles and their communications following the scenarios.
The simulation results demonstrate that the ontology model can support vehicular
communications to update each vehicle’s context model and assist its decision-making process
to resolve the emergency situations. The results also show the effect of vehicular
communications on the efficiency trends of traffic in emergency situations, where some vehicles
have a communication device, and others do not. The efficiency trends, based on the percentage
of vehicles having a communication device, can be useful to set a transition period plan for
implanting communication devices onto vehicles and the infrastructure.
The geospatial ontological framework and agent simulation may contribute to increase the
intelligence of ITS by supporting data-level and application-level implementation of
autonomous vehicle agents to share knowledge in local contexts. This work can be easily
extended to support more complex interactions amongst vehicles and the infrastructure