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Open AccessArticle

Connected Traffic Data Ontology (CTDO) for Intelligent Urban Traffic Systems Focused on Connected (Semi) Autonomous Vehicles

Information Systems in the Built Environment (ISBE), Department of the Built Environment, Technical University of Eindhoven, 5612 AZ Eindhoven, The Netherlands
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Sensors 2020, 20(10), 2961; https://doi.org/10.3390/s20102961
Received: 29 April 2020 / Revised: 19 May 2020 / Accepted: 19 May 2020 / Published: 23 May 2020
For autonomous vehicles (AV), the ability to share information about their surroundings is crucial. With Level 4 and 5 autonomy in sight, solving the challenge of organization and efficient storing of data, coming from these connected platforms, becomes paramount. Research done up to now has been mostly focused on communication and network layers of V2X (Vehicle-to-Everything) data sharing. However, there is a gap when it comes to the data layer. Limited attention has been paid to the ontology development in the automotive domain. More specifically, the way to integrate sensor data and geospatial data efficiently is missing. Therefore, we proposed to develop a new Connected Traffic Data Ontology (CTDO) on the foundations of Sensor, Observation, Sample, and Actuator (SOSA) ontology, to provide a more suitable ontology for large volumes of time-sensitive data coming from multi-sensory platforms, like connected vehicles, as the first step in closing the existing research gap. Additionally, as this research aims to further extend the CTDO in the future, a possible way to map to the CTDO with ontologies that represent road infrastructure has been presented. Finally, new CTDO ontology was benchmarked against SOSA, and better memory performance and query execution speeds have been confirmed.
Keywords: CTDO; ontology; connected autonomous vehicles; linked data; semantic web; SOSA CTDO; ontology; connected autonomous vehicles; linked data; semantic web; SOSA
MDPI and ACS Style

Viktorović, M.; Yang, D.; Vries, B. Connected Traffic Data Ontology (CTDO) for Intelligent Urban Traffic Systems Focused on Connected (Semi) Autonomous Vehicles. Sensors 2020, 20, 2961.

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